the lifetime impacts and costs of part 1: … · dr. benedetta contoli, dr. maria masocco, mr....

25 AUG 2017: LIFETIME IMPACT AND COST OF CHILDHOOD OBESITY IN GREECE, REPUBLIC OF IRELAND, ROMANIS AND SOLOVENIA 1

THE LIFETIME IMPACTS AND COSTS OF CHILDHOOD OBESITY/OVERWEIGHT IN EUROPE. PART 1:

MODELLING METHODOLOGY

DATA REQUIREMENTS

RESULTS FOR THE REPUBLIC OF IRELAND AND NORTHERN IRELAND

Deliverable D4.6

Work Package WP 4: Evidence (the economic rationale for action on childhood obesity)

Responsible Partner: IPH-IRL

Participating Member States: HZZO & HZJZ (Croatia), ATEITH & AHEPA (Greece), UCC-CHDR (IRL & NIR), ISS (Italy), MS (Portugal), NIMCP (Romania), NIJZ (Slovenia)

JANPA – Joint Action on Nutrition and Physical Activity (Grant agreement n° 677063) has received funding from the European Union’s Health Programme (2014 – 2020)

LIFETIME IMPACT AND COST OF CHILDHOOD OBESITY IN EUROPE (PART 1) 2

The content of this Deliverable represents the views of the author only and is his/her sole

responsibility; it cannot be considered to reflect the views of the European Commission

and/or the Consumers, Health, Agriculture and Food Executive Agency or any other body of

the European Union.

The European Commission and the Agency do not accept any responsibility for use that may

be made of the information it contains.


GENERAL INFORMATION

Joint Action full title Joint Action on Nutrition and Physical Activity

Joint Action acronym JANPA

Funding This Joint Action has received funding from the European

Union’s Health Programme (2014-2020)

Grant Agreement Grant agreement n°677063

Starting Date 01 September 2015

Duration 27 Months

DOCUMENT MANAGEMENT

Deliverable D4.6

WP and Task WP4 and Task 4.4

Author IPH-IRL

Due month of the deliverable M27

Actual submission month End of JANPA

Type

R: Document, report

DEC: Websites, patent fillings,

videos, etc.

OTHER

R

Dissemination level

PU: Public

PU


ROLES

COUNTRY ORGANISATION ROLE

Croatia HZZO

Zlatko Boni

HZIZ

Sanja Music

Country liaison, Data collation

Croatian Team Co-Leader


Croatian Team Co-Leader

Greece

ATEITH

Maria Hassapidou

AHEPA

Konstantinos Bouas

Country liaison , Data collation

Greek Team Co-Leader

Greek Team Co-Leader

Ireland

(Republic of Ireland)

IPH-IRL

Kevin Balanda

WP4 Lead Team

WP4 Leader, D4.6 Author

UK HEALTH FORUM

Laura Webber

Sub-contractor (to IPH-IRL)

Pre-modelling data processing

Simulation modelling and cost

estimation

Ireland

(Republic of Ireland &

Northern Ireland)

UCC CHDR

Ivan J Perry

IPH-IRL

Kevin Balanda

Country liaison

Irish Team Co-Leader


WP4 Team Leader

Irish Team Co-Leader

Italy ISS

Angela Spinelli

Laura Lauria


Italian Team Co-Leader

Italian team Co-Leader

Portugal MS

Pedro Graça

Andrea Costa

Gisele Camara

Country liaison

Portuguese Team Co-Leader

Portuguese Team Co-Leader

Data collation


Romania

NIMCH

Michaela Iuliana Nanu, National

Institute for Mother and Child

Health, Bucharest

Ioana Nanu, National Institute for

Mother and Child Health,

Bucharest


Romanian Team Co-Leader

Romanian Team Co-Leader

Slovenia

National Institute of Public Health

- NIJZ

Mojca Gabrijelcic Blenkus,

National Institute of Public Health

(NIJZ), Ljubljana

Aleš Korošec, National Institute of

Public Health (NIJZ), Ljubljana NIJZ


Slovenian Team Co-Leader

Slovenian Team Co-Leader


ACKNOWLEDGEMENTS

International Scientific

Advisory Group

Associate Prof Jennifer Baker, Institute of Preventive Medicine in

Denmark and the University of Copenhagen. Denmark

Dr Margherita Caroli, Nutrition Unit, Department of Prevention,

Azienda Sanitaria Locale Brindisi. Italy

Dr Anne Dee, Health Service Executive. Republic of Ireland

Dr Tony Fitzgerald, Department of Statistics and & Department of

Epidemiology & Public Health. University College Cork. Republic of

Ireland

Prof David Madden, School Of Economics, University College Dublin.

Republic of Ireland

Dr Martin O’Flaherty, University of Liverpool. England

Dr Pepijn Vemer, Department of Pharmacoepidemiology &

Pharmacoeconomy, University of Groningen. Netherlands

Italy Dr. Roberto Da Cas, Dr. Giuseppe Traversa National Centre for Drug Research and Evaluation, Istituto Superiore di Sanità Dr. Luigi Palmieri, Dr. Chiara Donfrancesco, Dr. Simona Giampaoli Department of Cardiovascular, Dismetabolic and Ageing-associated diseases, Istituto Superiore di Sanità; Dr. Daniela Pierannunzio, Dr. Valentina Minardi, Dr. Gianluigi Ferrante, Dr. Benedetta Contoli, Dr. Maria Masocco, Mr. Massimiliano Caldora National Center for Disease Prevention and Health Promotion, Istituto Superiore di Sanita Dr. Claudio Cricelli, Dr. Francesco Lapi, Dr. Serena Pecchioli Italian College of General Practitioners and Primary Care

Greece e-GOVERNMENT CENTER FOR SOCIAL SECURITY SERVICES (IDIKA S.A.)

Mathioudakis Kostas, Department of Electronic Prescriptions

HELLENIC STATISTICAL AUTHORITY

Eleni Katsorhi, Department for Statistical Information Provision


CANCER REGISTRY OF CRETE (CRC)

Dimitra Sifaki-Pistolla, School of Medicine, University of Crete

MINISTRY OF HEALTH

Ioanna Kontele, Dpt. of Public Health

Irene Grimani, Dpt. of Health Data Processing and Analysis

Portugal We would like to thank:

Carla Lopes, The National Food, Nutrition and Physical Activity Survey (IAN AF), Faculdade de Medicina da Universidade do Porto

Carla Rêgo e Margarida Nazareth, EPACI study

Carlos Dias, The National Health Examination Survey 2013-2016 (INSEF), Instituto Nacional de Saúde Doutor Ricardo Jorge, I.P.

Joana Sousa, Escola Superior de Tecnologia da Saúde de Lisboa (ESTeSL)

Julian Perelman, Universidade Nova de Lisboa / Escola Nacional de Saúde Pública

Margarida Gaspar de Matos, HBSC Portugal study

Rita Horgan, trainee nutritionist at Directorate-General of Health

Vanessa Silva, Administração Central do Sistema de Saúde, I.P.

Pedro Barras, Administração Central do Sistema de Saúde, I.P.

Slovenia We would like to thank : National Institute of Public Health – NIJZ, Health Data Unit Blaženka Jeren, Miloš Kravanja, Mojca Simončič, PoldkaButinar, Metka Zaletel, Ana Zgaga, Irena Zupanc

National Institute of Public Health – NIJZ, Health Survey and Health Promotion Unit Sonja Paulin, Tatjana Kofol Bric National Institute of Public Health – NIJZ, Prevention and Promotion Programes Unit Rade Pribakovič Brinovec National Institute of Public Health – NIJZ, Health Care System Unit Sabina Sedlak, Nevenka Kelšin Faculty of Sport, University of Ljubljana, Gregor Starc, for providing SLOfit data

Collaborating Partners

Ursula O’Dwyer, Department of Health, Republic of Ireland

Cliodha Foly-Nolan, safefood, Republic of Ireland

EU Joint Research Centre (EU JRC)


WHO Europe

CONVENTIONS AND DEFINITIONS

Adult 18 or more years

Adult Healthy Weight (HW) 18.5 ≤ BMI < 25.0

Adult obesity (OB)1 Defined by WHO cut-off point (30.0 ≤ BMI)

Adult Overweight (OW) 25.0 ≤ BMI < 30.0

Advanced study A more involved participation in WP4

Adult Underweight (UW) BMI < 18.52

Basic study A less involved participation in WP4

Body Mass Index (BMI)

Two BMI categories will be used throughout the life course:

Healthy weight (HW)

Obese/Overweight (OB/OW)

Bottom-up methods Methods used to estimate impact-related and cost-related model

inputs and outputs that are based on analysis of disease and

healthcare data in cross-sectional studies or longitudinal studies

that also include BMI data

Child 0-17 years

Childhood age categories for

reporting

Age categories for children that are used in the tables of model

outputs:

Younger children: 0 – 6 years

Older children: 7 -11 years

Adolescents: 12 – 17 years

Childhood obesity Based on an individual’s BMI at age 18 years as they exit childhood

(using IOTF cut-off points).

1 WHO defines three sub-categories of obesity: these are not considered in this study because of lack of data.

Obesity category I (OB-I): 30.0 ≤BMI < 35.0)

Obesity category II (OB-II): 35.0 ≤ BMI < 40.0)

Obesity category III (OB-III): 40.) ≤ BMI

2 Underweight individuals are included in the Healthy Weight (HW) category


Closed Cohort Simulation

Model (CCSM)

A simulation model that takes an initial cohort (representative of

the population at the time), ages them and simulates their

experiences throughout their lives. No additional entries into or

exits from the cohort (except by death of existing cohort members)

are allowed. A broad approach to burden of disease and cost of

illness studies; their primary interest is in the current and future

experiences of the initial cohort and not the whole population

living in any future year.

Current year 2015

Current value Cost expressed in 2016 euros

Direct healthcare costs Costs that result from outpatient and inpatient health services

(including surgery), laboratory and radiological tests, and drug

therapy.

Discounting

Discounting of future disease and disability and costs (because

people tend to devalue future disease and disability and costs

compared to present) is considered to be best practice.

Effect metric

Describes the effect of a reduction in mean childhood BMI

Excess metric

Describes an excess in some impact-cost indicator (e.g. direct

healthcare costs) that can be associated with current childhood

obesity/overweight.

Friction-cost approach An alternative approach for estimating value of productivity losses

(see Human-capital l approach)

Human-capital approach The approach used while estimating value of losses (see Friction-

Loss approach)

Impact-cost indicators Indicators that capture the impacts and costs that are incur as a

result of childhood obesity and overweight

Indirect healthcare costs Healthcare costs that are borne by the patient, their family and

community. They are not included in the JANPA costing model.

IOTF cut-off points

IOTF (now called World Obesity Federation) cut-off points used to

categorise childhood BMI. They apply to 2–17 year olds and map to

WHO’s adult BMI cut-off points

Lifetime BMI trajectory Lifetime trajectory of an individual’s annual BMI values throughout

their life

Life Expectancy at birth (LE) Measured in the year of birth

Obesity or overweight

(OW/OB)

A generic term used for a group of individuals who are either

overweight or obese (Jonoula et al)

Obesity-related impacts

Two types of consequences of childhood obesity and overweight

are considered:

Health impacts (diseases, disability and death)

Societal impacts (adult productivity losses and lifetime

income loss)

per case

Based on the number of cases of a disease and not the underlying

population size


Population Attributable

Fraction (PAF)

The proportion of an impact that would be avoided if a particular

risk factor was eliminated

Open Cohort Simulation

Model (OCSM)

A simulation model that takes an initial cohort (representative of

the population at the time), ages its members and simulates their

experiences throughout their lives. Additional entries (births and

immigration) and exits (emigration) are allowed to join as the

cohort ages so that the boosted cohort remains representative of

the whole population living in any future years. A broad approach

to burden of disease and cost of illness studies; the primary

interest here is in the current and future experiences of the whole

population in a particular year

Presenteeism Not covered in the JANPA costing model. It is reduced productivity

while attending work that is associated with obesity-related

disease or disability.

Private costs Costs incurred privately by patients, their families and

communities and not by the health and social care system

Relative Risk (RR) Also Odds Ratio (OR)

Sensitivity analysis

To represent the uncertainties inherent in data and modelling

assumptions

Societal costs These are the other resources that society and its citizens and

communities forego as a result of a health condition

Societal economic perspective

Includes impacts experienced and cost incurred by society and its

communities

Start-year First year of the simulation (2015)

Stochastic models Statistical models that operate probabilistically with random model

parameters having known distributions. For example:

The virtual children in the initial cohort are sampled from a

theoretical population that has a pre-specified population

distribution. At least asymptotically, the sample and the

population of interest have the same distribution

Transition probabilities and other model inputs are

random variables unknown and sampled from pre-

assigned distributions

Top-down methods Methods used to estimate impact-related and cost-related model

inputs and outputs that are based on the application of Population

Attributable Fractions (PAFs) to national disease and healthcare

data

Years of Life Lost (YLL) Years of life lost up to an individual’s national life expectancy in

their birth year

zBMI scores Because cut-off points for overweight and obesity vary with age,

gender-specific standardised z-score cut-off points will be used to

define BMI status at different ages.


TABLE OF CONTENTS

ROLES .............................................................................................................................. 4

ACKNOWLEDGEMENTS .................................................................................................... 6

CONVENTIONS AND DEFINITIONS .................................................................................... 8

TABLE OF CONTENTS ....................................................................................................... 11

SUMMARY ...................................................................................................................... 14

MODELLING METHODOLOGY ................................................................................................. 14

DATA REQUIREMENTS ............................................................................................................ 15

IMPACTS AND COSTS IN THE REPUBLIC OF IRELAND AND NORTHERN IRELAND ........................ 15

RECOMMENDATIONS ...................................................................................................... 21

1. INTRODUCTION ........................................................................................................... 23

1.1 INTERNATIONAL CONTEXT ................................................................................................ 23

1.2 INTERNATIONAL EVIDENCE ............................................................................................ 24

1.3 JANPA WP4 ................................................................................................................... 26

1.3.1 Aims ........................................................................................................................................ 26

1.3.2 Modelling Principles ............................................................................................................... 26

1.3.3 “Basic” and “advanced” studies ............................................................................................. 27

1.3.4 Deliverables ............................................................................................................................ 27

1.4 OUTLINE OF THE DOCUMENT ............................................................................................ 28

2. MODELLING METHODOLOGY ....................................................................................... 29

2.1 CONCEPTUAL FRAMEWORK .............................................................................................. 29

2.2 CLOSED COHORT SIMULATION MODELS ............................................................................ 30

2.2.1 Simulation Milestones ............................................................................................................ 31

2.3 SOME DEFINTIONS AND CONVENTIONS ............................................................................ 32

2.3.1 Obese/overweight child .......................................................................................................... 32

2.3.2 Reductions in childhood obesity/overweight ......................................................................... 33

2.3.3 Working ages and benefits eligibility ...................................................................................... 33

2.4 EXCESS AND EFFECT METRICS ........................................................................................... 45

2.4.1 Impacts and costs indicators .................................................................................................. 45

2.4.2 Excess metrics ......................................................................................................................... 47


2.4.3. Effect metrics ......................................................................................................................... 47

2.5 OBESITY-RELATED DISEASES ............................................................................................. 48

2.5.1 Global Disease List from the Evidence Reviews...................................................................... 48

2.5.2 Data requirements to be included in a country’s costing model ........................................... 50

2.6 SOFTWARE IMPLEMENTATION ......................................................................................... 50

2.6.1 Existing UKHF software ........................................................................................................... 50

2.6.2 Modification of existing UKHF software ................................................................................. 51

2.7 SOME STATISTICAL AND COSTING ISSUES .......................................................................... 53

2.7.1 Uncertainty intervals .............................................................................................................. 53

2.7.2 Other statistical issues ............................................................................................................ 54

2.7.3 Discounting future costs ......................................................................................................... 54

2.7.4 Approach to estimating productivity losses ........................................................................... 55

2.7.5 Valuing post-retirement productivity ..................................................................................... 55

2.7.6 Other costing issues ................................................................................................................ 55

3. WORKFLOW ................................................................................................................ 56

3.1 PHASE 1: DATA COLLATION .............................................................................................. 57

3.1.1 Identifying data sources .......................................................................................................... 57

3.1.2 Calculating per case treatment costs...................................................................................... 58

3.1.3 Data handling issues ............................................................................................................... 59

3.2 PHASE 2: PRE-SIMULATION DATA PROCESSING ................................................................. 59

3.2.1 Modelling lifetime BMI trajectories ........................................................................................ 60

3.2.2 Estimating disease parameters ............................................................................................... 60

3.3 PHASE 3: DISEASE MODELLING.......................................................................................... 60

3.3.1 Details of the simulations ....................................................................................................... 60

3.3.2 Simulating disease processes ................................................................................................. 61

3.4 PHASE 4: COST ESTIMATION ............................................................................................. 63

3.4.1 Model Outputs ........................................................................................................................ 64

3.5 PHASE 5: POST-SIMULATION REVIEW ............................................................................... 65

3.6 PHASE 6: REPORTING ........................................................................................................ 65

3.6.1 Data documentation ............................................................................................................... 66

3.7 JANPA COSTING MODEL TOOLBOX .................................................................................... 66

4. DATA REQUIREMENTS ................................................................................................. 68

4.1 DATA DOMAINS .............................................................................................................. 68

5. LIFETIME IMPACTS & COSTS OF CHILDHOOD OBESITY IN REPUBLIC OF IRELAND .......... 71


5.1 LOCAL CONTEXT ............................................................................................................... 71

5.2 LOCAL EVIDENCE .............................................................................................................. 74

5.2.1 Childhood Obesity / Overweight ........................................................................................... 74

5.2.2 Childhood and adulthood Impacts ......................................................................................... 75

5.2.3 Inequalities ............................................................................................................................. 75

5.3 COHORT DETAILS .............................................................................................................. 76

5.3.1 Profile of Irish Children ........................................................................................................... 76

5.3.2 Details of follow-up ................................................................................................................. 77

5.4 LIFETIME IMPACTS & COSTS IN REPUBLIC OF IRELAND ...................................................... 78

5.4.1 Adult Obesity / Overweight .................................................................................................... 78

5.4 .2. Morbidity .............................................................................................................................. 79

5.4.3 Mortality ................................................................................................................................. 83

5.4.4 Republic of Ireland summary .................................................................................................. 89

IRISH AND NORTHERN IRISH REFERENCES ............................................................................... 90

6. LIFETIME IMPACTS AND COSTS OF CHILDHOOD OBESITY IN NORTHERN IRELAND (NIR)93

6.1 COHORT DETAILS .............................................................................................................. 93

6.1.1 Profile of Northern Irish children ............................................................................................ 93

6.1.2 Details of follow-up ................................................................................................................. 94

6.2 LIFETIME IMPACTS & COSTS IN NORTHERN IRELAND ......................................................... 95

6.2.1. Adult Obesity / Overweight ................................................................................................... 95

6.2.2. Morbidity ............................................................................................................................... 96

6.2.3 Mortality ............................................................................................................................... 100

6.2.4 Northern Ireland summary ................................................................................................... 105

6.2.5 Comparison between the Republic of Ireland and Northern Ireland ................................... 106

7. LIMITATIONS AND RECOMMENDATIONS ................................................................ 109

7.1 LIMITATIONS ...................................................................................................................109

7.2 RECOMMENDATIONS ......................................................................................................112

7.2.1 Modelling Methodology ....................................................................................................... 112

7.2.2 Data and Research Gaps ....................................................................................................... 112


SUMMARY

JANPA WP4 was a very ambitious project. It is the first lifetime costing study of childhood

obesity/overweight that developed and applied standard modelling methodology in more than one

country (eight European countries).

The modelling methodology for the JANPA costing model is applicable to other childhood risk factors,

like childhood obesity/overweight, that have significant short term and long term consequences that

are, in part, mediated through a similar adult risk factor, like adult obesity/overweight.

In this document we outline the modelling methodology; describe the data and research

requirements; and present the final results for the Republic of Ireland (IRL) and Northern Ireland (NIR).


The evidence reviews on childhood obesity/overweight that were published in the Deliverable D4.1

“Evidence Paper and Study Protocols” were used to develop the JANPA (childhood obesity) costing

model that can be used to estimate the lifetime impacts and costs attributable to childhood

obesity/overweight as well as the effects of 1% and 5% reductions in mean childhood Body Mass Index

(BMI) in participating countries.

Multiple logistic regression was used to forecast BMI distributions and generate lifetime BMI

trajectories. These were incorporated into Semi-Markov processes that were used to model

independent disease processes. The project proceeded in six inter-connected phases: Data Collation,

Pre-modelling Data Processing, Simulation Modelling, Cost Estimation, Post-Modelling Review and

Reporting that were undertaken by WP4 Lead Team, participating countries and UK Health Forum

(UKHF) (sub-contractor to IPH-IRL).

Eight countries (Croatia, Greece, Republic of Ireland, Italy, Northern Ireland, Portugal, Romania and

Slovenia) participated in either “advanced” or “basic” studies. Advanced studies included societal costs

(lifetime income loss (the “income penalty”) and productivity losses due to premature death and

absenteeism) as well as direct healthcare costs, whereas basic studies included only direct healthcare

costs.

Materials relating to the Data Collation, Pre-modelling Data Processing, Simulation, Modelling, Cost

Estimation, Post-Modelling Review and Reporting phases that can be used by other countries wanting

to deploy the JANPA costing model will be available in the Modelling ToolBox on the JANPA website

(www.janpa.eu) in early 2018.

http://www.janpa.eu/


DATA REQUIREMENTS

Data was required across six domains: Population, BMI, Disease (prevalence, incidence, survival,

mortality), Direct Healthcare Costs (hospital, primary care, pharmaceuticals), Income, Work absences.

All data are required to be broken down by sex, age and disease (where relevant).

Except for Portugal, complete country data files are described in Deliverable D4.7.

IMPACTS AND COSTS IN THE REPUBLIC OF IRELAND AND NORTHERN IRELAND

The problem

The JANPA costing model quantified the large burden of childhood obesity/overweight:

The total lifetime financial costs (in 2015 values) are €4,518m (€16,036 per person) in Republic

of Ireland and €2,533.7m (€22,647 per person) in Northern Ireland. In Republic of Ireland this

accounts for 1.6% of GDP.

In Republic of Ireland, it is estimated that just over 55,000 of today’s children will die

prematurely as a result of childhood obesity/overweight (around 1 in 10 of all premature

deaths). In Northern Ireland it is 30,513 premature deaths.

Costs in the report are discounted to 2015 values using an annual discount rate of 5% (for most

countries). The “per person lifetime cost of childhood obesity” in the Republic of Republic of

Ireland is estimated to be €16,036 in 2015 values. These costs are incurred over each individual’s

lifetime. To cover those costs for one obese/overweight child; in 2015 you would have to lodge

€16,036 into a bank account that earns 5% per annum compound interest, and leave it in that

account for the lifetime of the child. If you only made withdrawals to cover costs when they occur;

at the end of their lifetime the account would be empty and the lifetime costs would have been

paid.


Table A: Lifetime impacts and costs attributable to childhood obesity/overweight (2015 values)

SEX

DIRECT

HEALTH

CARE

COSTS

(€m)

LIFETIME

INCOME

LOSS

(€m)

PRODUCTIVITY

LOSS

(PREMATURE

MORTALITY)

(€m)

PRODUCTIVI

TY LOSS

(ABSENTEEIS

M

(€m)

TOTAL

COST

(€m)

COST PER

PERSON

COST

(€)

TOTAL

NUMBER OF

PREMATURE

DEATHS

REPUBLIC OF IRELAND

MALES €422.0m €151.7m €2,105.3m €223.5m €2,902.4m € 21,115 26,202

FEMALES €527.0m €104.3m €756.4m €299.6m €1,687.3m € 11,694 28,854

PERSONS €944.7m €256.1m €2,795.4m €521.9m €4,518.1m € 16,036 55,056

NORTHERN IRELAND

MALES €334.8m €69.8m €1,248.7m €59.2m €1,712.6m € 33,487 15,279

FEMALES €337.0m €46.4m €415.1m €68.4m €867.0m € 14,275

15,234

PERSONS €679.6m €116.3m €1,607.3m €130.6m €2,533.7m € 22,647

30,513

Total lifetime direct healthcare costs account for 4.8% of total public health expenditure in Republic of

Ireland.


Childhood obesity/overweight affects citizens, the health and social care systems and (most

significantly) the economics of EU member states.

Towards a solution

The JANPA costing model confirmed that substantial savings could be achieved if mean childhood BMI

was reduced by 1% and 5%. With a 5% reduction, total lifetime savings were estimated to be over a

billion euros in Republic of Ireland and almost early €400m in Northern Ireland.

Lifetime healthcare costs were expected to fall by €245.7m in Republic of Ireland and €100.1m in

Northern Ireland. The savings resulting from a 5% reduction in mean childhood BMI mean were

approximately 4 – 5 times those for 1% reductions.


Table B: Reductions in lifetime impacts and costs associated with 1% and 5% reductions in

population mean childhood BMI (2015 values)

REPUBLIC OF IRELAND

SEX

PERCENT

REDUCTION

IN MEAN

CHILDHOOD

BMI

DIRECT

HEALTH

CARE

(€m)

LIFETIME

INCOME

LOSS

(€m)

PRODUCTIVITY

LOSS

(PREMATURE

MORTALITY)

(€m)

PRODUCTIVIT

Y LOSS

(ABSENTEEIS

M)

(€m)

TOTAL COST

REDUCTION

(€m)

TOTAL COST

REDUCTION

PER PERSON

(€)

TOTAL

REDUCTION

IN NUMBER

OF

PREMATURE

DEATHS

MALES

1% €26.4m €8.6m €125.5m €16.1m €176.5m €1,284 1,272

5% €123.7m €38.8m €516.7m €70.4m €749.5m €5,453 5,948

FEMALES

1% €27.5m €5.0m €43.5m €17.4m €93.5m €648 683

5% €122.0m €22.7m €154.3m €78.6m €377.6m €2,617 3,321

PERSONS

1% €53.9m €13.5m €169.0m €33.5m €270.0m €958 1,955

5% €245.7m €61.4m €671.0m €149.0m €1,127.1m €4,000 9,269

NORTHERN IRELAND

MALES

1% €11.2m €2.6m €52.7m €2.1m €68.6m €1,341 269

5% €51.7m €12.7m €199.8m €10.4m €274.6m €5,369 1,267

FEMALES

1% €11.0m €1.5m €12.6m €2.2m €27.2m €448 295

5% €48.4m €7.4m €56.1m €10.3m €122.2m €2,012 1,252

PERSONS

1% €22.2m €4.0m €65.2m €4.4m €95.8m €856 563

5% €100.1m €20.1m €255.9m €20.7m €396.8m €3,546 2,519


As we have already noted, there are similarities in the broad features of the excess burden of

childhood obesity/overweight in the Republic of Ireland and Northern Ireland:

Lifetime total societal costs accounted for the majority of the total lifetime costs; accounting

for 79.1% of the total costs in Republic of Ireland and 73.2% in Northern Ireland.

Lifetime productivity losses due to premature mortality were the greatest single cost item

accounting for 61.9% and 63.4%, respectively, of total lifetime costs in Republic of Ireland

and Northern Ireland.

The total lifetime cost (and per person costs) attributed to childhood obesity/overweight is

much higher for males than it is for females.

Males incur higher total lifetime income losses and productivity losses due to premature

mortality while females incur higher lifetime healthcare costs and productivity losses due to

absenteeism.

These differences may be explained in part by higher risk of premature mortality and higher average

incomes amongst males and the greater tendency to seek care and respond to care amongst

females.

Table 6(o): Percentage of total morbidity-related and mortality-related burden attributable to

childhood obesity / overweight (PAFs)

PAFs

IRL NIR

M F P M F P

Direct Healthcare Cost 11.6% 15.9% 13.6% 15.0% 14.5% 14.9%

Productivity Losses (Absenteeism)

29.8% 29.0% 24.8% 15.6% 15.3% 15.8%

Premature Deaths 9.3% 11.2% 20.8% 19.9%

Productivity Losses (Premature Death)

20.0% 17.0% 18.9% 31.3% 25.9% 28.8%

However; the comparison of the Republic of Ireland and Northern Ireland also revealed that the

excess burden of childhood obesity/overweight is experienced differently by males and females in

the two countries:

In the Republic of Ireland, childhood obesity/overweight accounted for relatively more of

the morbidity-related burden amongst males than amongst females. In Northern Ireland, no

such gender difference was observed.


In the Republic of Ireland, but not Northern Ireland, childhood obesity / overweight

accounted for relatively more premature mortality amongst females than males.

In both the Republic of Ireland and Northern Ireland, however, childhood

obesity/overweight accounted for relatively more of the productivity losses due to

premature death amongst males than amongst females

Moreover; the comparison of the Republic of Ireland and Northern Ireland also emphasised the

importance of local context:

Direct health care costs are relatively higher in Northern Ireland

Indirect (societal) costs are relatively higher in the Republic of Ireland

These differences may be explained in part by the fact that Northern Ireland operates a universal

health care system (NHS in the UK) while a two-tiered public – private health care system operates

in the Republic of Ireland.

Discussion

Given the large human impact and the financial cost of today’s childhood obesity/overweight, the

need for urgent action is clear. Specific recommendations are:

• Obesity strategies and action plans in the Republic of Ireland and Northern Ireland should be

implemented, supported with adequate resources,

• A population and life-course approach is necessary with a strong emphasis on the

obesogenic environment balanced with supports for parents and carers.

• There should be increased investment in data collection to provide accurate and reliable

data for cost-of-illness studies and related health economic analysis. Data collected must

include utilisation of health services and illness-related productivity loss and absenteeism

from school.

• Research into the psychosocial impacts of overweight and obesity on the island is warranted

given the information gap identified.

RECOMMENDATIONS

The following recommendations relate to the modelling methodology; data and research gaps.

Recommendations about future project development are included in Deliverable D4.7


We recommend that:


An independent scientific review of the JANPA costing model and how it was developed

should be undertaken

The detailed suggestions for enhancements of the modelling methodology that are outlined

in Chapter 7 should be incorporated into the future development of the model.

Stand-alone dedicated software, provided as open source code, to fully implement the

JANPA costing model should be developed and available to other researchers for

independent scrutiny and audit

Detailed sensitivity audit and validation of the JANPA costing model should be undertaken

once the open source code is available. This should include calculation of uncertainty

intervals and the validity of critical assumptions and inputs

DATA AND RESEARCH GAPS

The validity and reliability of final results depend on the data inputs. The availability and quality of

data across the countries varied greatly. We recommend that work continues to improve the co-

ordination, and quality of the national and pan-European health information systems, particularly:

Obesity surveillance (particularly early years, later years and adolescence)

Surveillance of obesity-related diseases (particularly incidence and survival)

Healthcare costs (particularly primary care and pharmaceutical)

Analytical methods for using data

The biggest gap in the impacts and costs included in the JANPA costing model relates to the

psychosocial consequences of childhood obesity and the inability to undertake a sensitivity analysis

of the model. We recommend that the JANPA costing model be refined by incorporating research

into the psychosocial impacts of childhood obesity and their implications for human capital and the

economy (effects on school attendance, educational performance and subsequent employability,

position in the labour market and productivity).

In addition we recommend that:

A comprehensive review of multi-morbidities and their effects on the JANPA costing

model’s excess and effect metrics should be undertaken and a work programme to

incorporate its finding into the model should be developed

Support continues for longitudinal studies with long term follow-up


1. INTRODUCTION

This chapter contains a brief overview of the international context and international

evidence of childhood obesity and overweight. This is supplemented by local materials

from each participating country described in Deliverable D4.1 “Evidence Paper and Study

Protocols” and the local context and local evidence in each participating country in

Deliverable D4.7 “The Lifetime Impacts And Costs Of Childhood Obesity/Overweight In

Europe. Part 2” .

1.1 INTERNATIONAL CONTEXT

The primary international bodies working to address the global obesity epidemic are the WHO and

the European Commission. There is some policy collaboration between these agencies and a

recognition of the complexity of the solution required to intervene in any affective way. Their

policies recognize the contributing roles of social and environmental factors, such as; community

norms shaped by a market-driven economy, marketing campaigns promoting high-calorie low-

nutrition foods, sedentary behaviour, passive leisure activities, and lack of physical activity.

The WHO classifies obesity as a non-communicable disease (NCD), alongside cardiovascular disease,

cancer, chronic obstructive pulmonary diseases, and diabetes with primary efforts aimed at reducing

exposure to risk factors and strengthening health care. Between 2010 and 2012, WHO investigated

the underlying social causes of obesity and other NCD and their common risk factors in the EU’s 53

Member States in order to develop an implementation plan for the European Strategy for the

Prevention and Control of Noncommunicable Diseases 2012−2016 (WHO, 2012). This strategy is

WHO’s primary plan for addressing obesity and other NCD in Europe and includes: the WHO

European Food and Nutrition Action Plan 2015-2020 that encourages action in a range of policy

areas through a whole-of-government, health-in-all-policies approach to improve food system

governance and overall quality of the population’s diet and nutrition to ultimately promote health

and well-being; and the Global Strategy on Diet, Physical Activity and Health that addresses physical

activity and diet, while complementing ongoing work on other nutrition-related risk factors for

noncommunicable diseases, including undernutrition, micronutrient deficiencies and infant- and

young-child feeding. WHO has developed similar Action Plans for its non-EU members, the Global

Action Plan for the Prevention and Control of NCDs 2013-2020.

The European Commission advocates an integrated approach, involving stakeholders at local,

regional, national, and European levels. This has been the approach since 2007 when the

Commission established a Community Strategy based upon the Strategy on Nutrition, Overweight,

and Obesity-related Health Issues white paper (Commission of the European Communities, 2007).

The strategy encompassed a range of Commission policies to facilitate improved nutrition and

prevent overweight and obesity in policy areas, including: health and food safety, agriculture,

information society, education and culture, research, transport, and regional policy. These actions

were advanced by the Commission’s governmental representatives on the issue with the 2014

adoption of the EU Action Plan on Childhood Obesity 2014-2020 aimed at stopping the rise of


childhood obesity by 2020 (European Commission, 2014), and by the European Council’s Joint Action

policy designed to promote actions contributing to the implementation of the EU Action Plan on

Childhood Obesity (European Council, 2014), for example, the Joint Action on Nutrition and Physical

Activity (2015) that involves 25 Member States. In addition to setting policy, the EC provides funding

for projects that implement the EU health strategy, develops funding opportunities, organises

conferences, and identifies best practices. All the EC actions form the EC platform that was designed

to serve as an example of coordinated action by different parts of society to encourage national,

regional, and local initiatives across Europe.

1.2 INTERNATIONAL EVIDENCE

It is estimated that nearly 30% of the world population is overweight (Ng et al., 2014), resulting in a

burdensome public health issue that may prove to be among the most challenging for any nation to

address. Over the past three decades, the prevalence of overweight and obesity has increased

markedly worldwide and is described by the World Health Organization as a “global epidemic”

(WHO, 2017). Globally, adult obesity prevalence forecasts (2010–2030) that 32% of men and 30% of

women will be obese by 2020. By 2030, the model predicts that 44% of men and 40% of women will

be obese (WHO, 2013). The recent international prevalence of overweight and obesity in

adolescents is 41% of boys and 24% of girls aged 11 years (Currie et al., 2012) with European

childhood prevalence rates at 38.1% for boys and 39.9% for girls aged 7 years and at 45.1% for boys

and 42.3% for girls aged 9 years (Wijnhoven et al., 2014).

Overall, prevalence of childhood excess weight is a growing problem in most European countries and

the countries that is the focus of this investigation. In the Republic of Ireland, it is currently

estimated that 60% of adults and 25% of children are overweight or obese. Among children in

Northern Ireland aged 4-13, the prevalence of overweight and obesity is estimated at 22% for boys

and 27% for girls. Collectively, the findings of our updated review indicate that the prevalence of

childhood overweight and obesity is plateauing in the Republic of Ireland, and may be decreasing in

primary school-aged children, with the greatest reduction in prevalence observed among 5-year-

olds. Among children in Greece aged 1-12, it was estimated that 10.2% were obese, 23.7% were

overweight, and the combined prevalence of overweight and obesity was approximately 34%

(Kotanidou et al., 2013). Trends in the prevalence of child overweight and obesity in Greece show

rapid increases in both children and adolescents during the 1990s and early 2000s, followed by a

slowing down of increases in prevalence with some evidence of stabilisation in young children but

not in adolescents since around 2004. A Romanian survey reported that 20% of children aged 6-7

years were overweight or obese and that 18% of children aged 13-14 were overweight or obese

(Ardeleanu et al., 2015). Romanian trend investigations have reported a slight increase in the

prevalence of increased weight for height in children 0-24 months old in 2010 compared with 2004

(Nanu, Stativa, Moldovanu, Stoicescu, et al., 2011). In contrast to other JANPA participants, this

research has also highlighted the relatively high prevalence of underweight children, noting

relatively stable trends in underweight over time. A 2014 Slovenian study found 26.4% of boys and

22.2% of girls aged 7 to 18 were classified as overweight or obese, with trends suggesting that rates

of overweight and obesity have remained quite stable in recent years with some evidence of a

decline in overweight and obesity since around 2010.


Childhood obesity is strongly linked to mortality and morbidity in adulthood. Since obesity often

begins in childhood, many obese children grow up to become obese adults. Childhood obesity has

been linked to a number of serious health conditions in adulthood, including: asthma, hypertension,

type 2 diabetes, sleep apnoea, non-alcoholic fatty liver disease, cancer, and depressive disorders. A

review by Park, Falconer, Viner, et al. (2012) reported that the risk of all-cause mortality in

adulthood increased by 40-60% in people who had a high BMI between the ages of 2 and 19. Our

review of relevant research suggests childhood obesity is a strong predictor of adult obesity with

obese children in the 7-11 age group and the 12-18 age group, 5 times more likely than their non-

obese counterparts to be obese adults. Prospective research suggests that approximately 55% of

obese children will remain obese into adolescence and approximately 80% of obese adolescents will

remain obese into adulthood. Seventy per cent of obese adolescents will remain obese over the age

of 30 (Datar, Sturm, & Magnabosco, 2004; Canning & Mayer, 1967). However, when obese children

become normal weight by adulthood, the risks of developing many outcomes are similar to the risks

for children who were never obese. It should also be noted that the majority of cases of obesity-

related disease in adult life arise in individuals who were of healthy weight during childhood, which

is the majority of children and not the smaller group who were overweight or obese in childhood.

The lifetime costs of childhood overweight and obesity are high. Cost-of-illness studies have

repeatedly shown that obesity during adulthood causes substantial direct and indirect costs (Tsai,

Williamson, & Glick, 2011). A review of the global literature since 2000 estimated an average lifetime

cost (direct healthcare cost and indirect productivity loss) of €54,663 (range, €45,014 to €74,244)

for males and €36,053 (range, €24,433 to €61,700) for females (Safefood, 2017). Medical costs alone

have been estimated at over €16,000 for an obese child who becomes an obese adult and at

€11,000 for a healthy weight child who becomes overweight or obese in adulthood (Finkelstein,

Graham, & Malhotra, 2014). It remains a challenge to understand the risk factors predisposing a

child to become overweight or obese and further challenging to evaluate the increased risk of

mortality and obesity-related diseases associated with childhood obesity.

Due to the challenges of research on this topic, data quality, reliability, and generalizability has been

lacking. The quality of the available evidence on obesity related co-morbidity in childhood is poor

due to inconsistencies across studies in the definitions and thresholds for overweight and obesity,

and the preponderance of cross-sectional studies which limit assessment of temporal relations, for

example, whether obesity is a cause or consequence of asthma. A challenge to the call for

prospective studies is the length of time between a child’s diagnosis as overweight or obese and the

appearance of co-morbidities, with some conditions not diagnosed until later adulthood. Also

challenging is the age at which a child becomes overweight or obese and when the condition begins

to influence the child’s future. Complications with investigation and unreliable evidence have been

noted by others (Department of Health, 2005).


1.3 JANPA WP4

An expert International Scientific Advisory Group (ISAG) guided the scientific aspects of JANPA WP4.

The ISAG:

Gave scientific advice to WP4 Lead Team.

Reviewed background materials and draft reports

Attended face-to-face meetings

1.3.1 Aims

Effective and sustainable political decision-making is an essential prerequisite for the

implementation of actions to achieve the objective. Estimating short- and long-term health and

social costs and determining the avoidable costs are essential to the prioritisation process for

governmental decisions. Apart from long term longitudinal studies, simulation modelling is the best

way to comprehensively estimating the lifetime impacts and costs of childhood obesity/overweight.

The modelling objectives of JANPA WP4 were to:

1. Estimate the lifetime impacts and costs of childhood obesity/overweight in eight European

countries

2. Describe how these impacts and costs are expected to occur over time.

3. Assess the effect of reducing the mean population childhood BMI by 1% and 5%.

The incorporation of inequalities into costing studies of obesity was taken up in the EU

commissioned “Health Equity Pilot Project” (HEPP) .

Four evidence reviews of the international literature on the prevalence, childhood and adult

consequences, and lifetime costs of childhood obesity/overweight were conducted by the Irish Team

with additional funding from safefood (www.safefood.eu). These were supplemented by local

research and data collected in a survey of partners from the participating countries (Croatia, Greece,

Republic of Ireland, Italy, Northern Ireland, Portugal, Romania and Slovenia) and summarised in

Deliverable D4.1 ”Evidence Paper and Study Protocols” (www.janpa.eu).

These evidence reviews guided the development of the JANPA costing model.

1.3.2 Modelling Principles

The following Principles guided the direction and conduct of JANPA WP4:

Relevance to each country and EU

A societal economic perspective that includes societal (non-health) impacts and costs as well

as direct healthcare costs

Transparency for interpretability and generalisability


Making best use of available research and data

Identifying gaps and stimulating further research

Building capacity – data, research and modelling

1.3.3 “Basic” and “advanced” studies

Participating countries could choose to participate in JANPA WP4 in one of two types of costing

studies: “basic” and “advanced”. Differences between basic and advanced studies are described in

the table below:

Table 1(a): Summary of basic and advanced studies.

BASIC STUDIES ADVANCED STUDIES

Direct healthcare costs only Also include societal impacts and costs

Major clinical conditions only Wider range of clinical conditions

Focus on core pan-European data Also include country-specific data

Focus on “Top down” approaches

using international inputs (and

possibly) local inputs

Focus on “Bottom up” approaches

using local inputs

Basic studies were conducted in Croatia, Italy and Portugal. Advanced studies were conducted in

Greece, Republic of Ireland, Northern Ireland, Romania and Slovenia.

1.3.4 Deliverables

This report, Deliverable D4.6 “The Lifetime Impacts and Costs Of Childhood Obesity Overweight In

Europe. Part 1”, describes

Modelling methodology

Data and research requirements

Final results for Republic of Ireland and Northern Ireland

Deliverable D4.7 “The Lifetime Impacts And Costs Of Childhood Obesity Overweight In

Europe. Part 2” describes

Collated Data

Challenges and lessons

Future projects


1.4 OUTLINE OF THE DOCUMENT

Following an overview of the international context for JANPA WP4 regarding childhood

obesity/overweight in Chapter 1;

The modelling methodology for the JANPA (childhood obesity/.overweight) costing model is

given in Chapter 2

The workflow followed during the work package is described in Chapter 3.

Chapter 4 specifies the data and research required to deploy the JANPA costing model in a

country.

Chapter 5 and Chapter 6 present the final modelling results for the Republic of Ireland and

Northern Ireland.

Chapter 7 which reflects on the limitations of the modelling methodology and

recommendations regarding improvements of the methodology.


2. MODELLING METHODOLOGY

The evidence reviews in Deliverable D4.1 were used to develop the JANPA (childhood obesity)

costing model that estimates the lifetime impacts and costs (direct healthcare costs and societal

costs) attributable to childhood obesity/overweight as well as the effects of 1% and 5% reductions in

mean childhood BMI in each participating country.

2.1 CONCEPTUAL FRAMEWORK

The conceptual framework for the JANPA costing model extends that used by Fernandes (2010) to

model the direct healthcare costs by incorporating three societal costs:

Lifetime income loss (also called the “income penalty”) experienced by all individuals who

were obese/overweight as children

Productivity losses due to premature death

Productivity losses due to absenteeism

Figure 2 (a): Conceptual Framework (adapted from Fernandes (2010))


The Janpa WP4 evidence reviews summarised in Deliverable D4.1 confirmed Fernandes (2010)

description of the evidence-base given in the figure above.

The modelling methodology for the JANPA costing model is applicable to other childhood risk

factors, like childhood obesity/overweight, that have significant short term and long term

consequences that are, in part, mediated through a similar adult risk factor, like adult

obesity/overweight.

2.2 CLOSED COHORT SIMULATION MODELS

At the core of operationalising the conceptual framework are microsimulations.

Figure 2 (b): Cohort simulations underpinning the JANPA costing model

In such cohort simulations, an initial cohort of virtual children representative of the childhood

population living in a country in 2015 is created; their lifetime BMI trajectories are modelled using

historical BMI data; they are allowed to age and the morbidity and mortality, (direct) healthcare

costs and societal costs they experience over their lifetimes as a result of their modelled BMI

trajectories are recorded.


These cohort simulations can be used to describe either:

1. The experiences of a population alive in some future year (we call such models “Open

Cohort Simulation Models (OCSM)”); or

2. The lifetime experiences of a particular population as they age (we call such models “Closed

Cohort Simulation Models (CCSM)”).

The cohort simulations underpinning these purposes are implemented differently;

• They are conducted differently: OCSMs allow into the cohort new entries (through births

and immigration) and additional exits (through emigration) in order to ensure that, in any

future year, the surviving cohort members are representative of the population living in that

year. The surviving members of a cohort in a CCSM, on the other hand, become less

representative of the resident population from which they were originally drawn.

They require different data: OCSMs, for example, require forecasts of population, disease

occurrence and mortality to ensure that the experiences of the cohort in any future year

matches the experiences of the resident population in those years. These data are not

required for CCSMs.

• Are reported differently: For example, in a CCSM the focus is on the cohort’s experiences

accumulated up to a future calendar year of interest while the focus of an OCSM will be their

experience in that calendar year. Thus the base population used as the denominator for

risks, etc. in a CCSM is the original population while for an OCSM it is the resident population

future calendar year of interest.

Many of us would be familiar with Open Cohort Simulation Models designed to provide population-

level obesity forecasts or the burden of obesity-related disease in a population in some future year.

The JANPA costing model looks at the lifetime experiences of a closed cohort of children as they age

and is a Closed Cohort Simulation Model.

2.2.1 Simulation Milestones

Table 2: Simulation milestones

0-5 year olds 6-11 year olds 12-17 year olds

Reach adulthood At start of: 2028 (5 yo) – 2033 (0 yo)

At start of: 2022 (11 yo) – 2027 (6 yo)

At start of : 2016 (17 yo) – 2021 (12 yo)

First year no children left in cohort

2033

Period 1: all children

2015


Period 2: children plus adults

2016 - 2032

Period 3: all adults 2033 - 2105

Life expectancies at birth (females)

2010 (5 yo) - 2015 (0 yo) 82.6 - 83.6

2004 (11 yo) - 2009 (6 yo) 81.0 - 82.3

1998 (17 yo) – 2003 (12 yo) 79.1 - 80.6

Life expectancies at birth (males)

2010 (5 yo) - 2015 (0 yo) 78.1 - 79.6

2004 (11 yo) - 2009 (6 yo) 76.0 - 77.8

1998 (17 yo) – 2003 (12 yo) 73.7 - 75.5

Last year all deaths are premature deaths

2078 (females) 2072 (males)

First year all deaths are mature deaths

2099 (females) 2095 (males)

Period 1: all premature deaths

2015-2078 (females) 2015-2072 (males)

Period 2: mix of premature and mature deaths

2079-2098 (females) 2073 – 2095 (males)

Period 3: all mature deaths

2099-2105 (females) 2095-2105 (males)

In the adapted UKHF model, individuals die automatically when they turn 110 years

2120 - 2125 2114 - 2119 2108 - 2113

Period 1: all natural deaths

2015 – 2106 (useable data)

2015 - 2119 2015 - 2113 2015 - 2107

Period 2: mix of natural and unnatural deaths

2107 - 2124 2120 - 2124 2114 - 2118 2108 - 2112

Period 3: all unnatural deaths

2125 2125 (0 yo turn 110)

2119 (6 yo turn 110)

2113 (12 yo turn 110)

2.3 SOME DEFINTIONS AND CONVENTIONS

2.3.1 Obese/overweight child

For the JANPA costing model, a child is an individual aged 0 – 17 years.

Because of the lack of the required details in available data and research, we combine “obese” and “overweight” and use the term “obese/overweight” to refer to BMI ≥ 25.0 according to IOTF definition.


.

To address JANPA WP4’s modelling objectives, we first classify individuals as either

“obese/overweight as a child” or “healthy weight as a child”. There are many ways of doing this.

Because of the greater association with later life adult health consequences, an individual’s

modelled BMI on their 18th birthday is used to classify them as having been either an

“obese/overweight child” or a “healthy weight child”. During their childhood years, their

classification is updated if they die in childhood or develop a childhood obesity-related disease. In

the first calendar year in which either of these occurs, their classification was revised using their

modelled BMI in that calendar year. Thereafter, their classification does not change.

2.3.2 Reductions in childhood obesity/overweight

The second part of JANPA WP4’s objectives concerns the effect of reductions in mean childhood

BMI in a participating country. We consider two scenarios:

A one percent reduction in mean childhood BMI in which the means of the sex-age specific

childhood BMI distributions in 2015 (taken from the current BMI distributions in the

country) are reduced by 1% before the initial virtual children are selected.

A 5% percent reduction in mean childhood BMI in which the means of the sex-age specific

childhood BMI distributions in 2015 (taken from the current BMI distributions in the

country) are reduced by 5% before the initial virtual children are selected

In each scenario, the standard deviations are not changed.

2.3.3 Working ages and benefits eligibility

CROATIA

Minimum age for admission to employent

15 http://r2e.gn.apc.org/country-node/327/country-minimum

VI. Old-age Conditions Legal retirement age Standard pension Source http://www.missoc.org/MISSOC/INFORMATIONBASE/COMPARATIVETABLES/MISSOCDATABA

The pensionable age is currently: Men: 65 years Women: 61 years and 6 months Men and women long-insured persons with 41 years of insurance or more: 60 years. The pensionable age for women is being gradually increased by 3


SE/comparativeTableSearch.jsp

months per calendar year from 1 November 2010 onwards, to reach 65 in 2030. The pensionable age for both women and men will be gradually increased by 3 months per calendar year from 2031 onwards, to reach 67 in 2038.

VI. Old-age Conditions Legal retirement age Early pension Source http://www.missoc.org/MISSOC/INFORMATIONBASE/COMPARATIVETABLES/MISSOCDATABASE/comparativeTableSearch.jsp

Men: age of 60 years and qualifying period of 35 years. Women: age of 56 years and 6 months, and qualifying period of 31 years and 6 months. Age and qualifying period for women are being gradually increased by 3 months per calendar year from 1 November 2010 onwards, to reach 60 and 35 in 2030 respectively. The age limit for early pension (women and men) will be gradually increased by 3 months per calendar year from 2031 onwards, to reach 62 in 2038. The same conditions apply to persons unemployed for at least 2 years before fulfilling the early pension requirements due to enterprise bankruptcy.

Any laws which impose a mandatory retirement age? Reference: http://ec.europa.eu/justice/discrimination/files/age_and_employment_en.pdf Section 7.3

65 but can be extended by agreement

during what ages can a person apply for sickness benefit for work absences

employed persons http://ec.europa.eu/social/main.jsp?catId=1104&langId=en&intPageId=4459

III. Sickness - cash benefits Basic principles Source http://www.missoc.org/MISSOC/INFORMATIONBASE/COMPARATIVETABLES/MISSOCDATABASE/comparativeTableSearch.jsp

Compulsory social insurance scheme covering the active population and providing earnings-related benefits. Continued payment by the employer.

III. Sickness - cash benefits Conditions 2. Qualifying period Source http://www.missoc.org/MISSOC/INFORMATIONBASE/COMPARATIVETABLES/MISSOCDATABASE/comparativeTableSearch.jsp

Minimum period of insurance required: 9 months of consecutive insurance or 12 with interruptions during the last two years. If this condition is not fulfilled, the insured person is entitled to the minimum sickness benefit, see below "Benefits, 2. Benefits of social protection, Amount of the benefit".

included in the income files Mean equivalised net income


sent to UKHF

GREECE


15 http://r2e.gn.apc.org/country-node/348/country-minimum (article 2 of Law 1837/89)

VI. Old-age Conditions Legal retirement age Standard pension Source http://www.missoc.org/MISSOC/INFORMATIONBASE/COMPARATIVETABLES/MISSOCDATABASE/comparativeTableSearch.jsp

67 years (if 15 years of insurance). 62 years (if 40 years of insurance).


Persons insured before 1/1/1993: Full amount: For men and women, from the age of 62, if they have completed 10,500 insurance days (of which 7,500 must have been spent doing arduous and unhealthy work). Reduced amount: from 62 years for men and women if 15 insurance years or 4,500 insurance days (of which 100 days have been worked during the last 5 years), from 62 years of age and 10,000 insurance days for men (60 years and 12,000 insurance days for women, increasing by 6 months every year until the age of 62 is reached in 2017) of which 100 per year during the last five years, from 60 years for men and women if 35 working years or 10,500 insurance days (of which 7,500 days must have been worked under arduous or unhealthy conditions), from 62 years for mothers and widowed fathers with a minor or disabled child if 18 insurance years or 5,500 working days. Persons insured since 1/1/1993: Reduced amount: from 62 years for mothers with a minor or disabled child if 20 years of insurance or 6,000 working days.

Any laws which impose a mandatory retirement age? Reference:

None


http://ec.europa.eu/justice/discrimination/files/age_and_employment_en.pdf Section 7.3


employed persons If you are too sick or ill to do your job and if you are under 66, you may be entitled to Illness Benefit. http://ec.europa.eu/social/main.jsp?catId=1112&langId=en&intPageId=4563


Compulsory social insurance scheme for employees with earnings-related benefits. No continuation of payment by the employer.


* 120 days of work subject to contributions during the previous year or the 12 first months of the 15 months preceding the illness (100 for those employed in construction). Duration of benefit: 182 days for one or more illnesses within one year. * 300 days subject to contributions during the 2 years, or 27 months of the 30, preceding the illness (duration of benefit: 360 days for the same illness, within one year). * 1,500 days of insurance, 600 of which during the last 5 years preceding the incapacity for work due to the same illness (duration of benefit: 720 days). * 4,500 days of insurance before the declaration of the illness (duration of benefit: 720 days). * Depending on the patient’s age and insurance record, a 720 days’ benefit can be paid in case the requirement of the 1,500 or the 4,500 days is not fulfilled.

included in the income files sent to UKHF

Mean equivalised net income

IRELAND


15 http://r2e.gn.apc.org/country-node/348/country-minimum (article 2 of Law 1837/89)

VI. Old-age Conditions

67 years (if 15 years of insurance). 62 years (if 40 years of insurance).


Legal retirement age Standard pension Source http://www.missoc.org/MISSOC/INFORMATIONBASE/COMPARATIVETABLES/MISSOCDATABASE/comparativeTableSearch.jsp


Persons insured before 1/1/1993: Full amount: For men and women, from the age of 62, if they have completed 10,500 insurance days (of which 7,500 must have been spent doing arduous and unhealthy work). Reduced amount: from 62 years for men and women if 15 insurance years or 4,500 insurance days (of which 100 days have been worked during the last 5 years), from 62 years of age and 10,000 insurance days for men (60 years and 12,000 insurance days for women, increasing by 6 months every year until the age of 62 is reached in 2017) of which 100 per year during the last five years, from 60 years for men and women if 35 working years or 10,500 insurance days (of which 7,500 days must have been worked under arduous or unhealthy conditions), from 62 years for mothers and widowed fathers with a minor or disabled child if 18 insurance years or 5,500 working days. Persons insured since 1/1/1993: Reduced amount: from 62 years for mothers with a minor or disabled child if 20 years of insurance or 6,000 working days.


None


employed persons If you are too sick or ill to do your job and if you are under 66, you may be entitled to Illness Benefit. http://ec.europa.eu/social/main.jsp?catId=1112&langId=en&intPageId=4563

III. Sickness - cash benefits Compulsory social insurance scheme for employees with earnings-


Basic principles Source http://www.missoc.org/MISSOC/INFORMATIONBASE/COMPARATIVETABLES/MISSOCDATABASE/comparativeTableSearch.jsp

related benefits. No continuation of payment by the employer.


* 120 days of work subject to contributions during the previous year or the 12 first months of the 15 months preceding the illness (100 for those employed in construction). Duration of benefit: 182 days for one or more illnesses within one year. * 300 days subject to contributions during the 2 years, or 27 months of the 30, preceding the illness (duration of benefit: 360 days for the same illness, within one year). * 1,500 days of insurance, 600 of which during the last 5 years preceding the incapacity for work due to the same illness (duration of benefit: 720 days). * 4,500 days of insurance before the declaration of the illness (duration of benefit: 720 days). * Depending on the patient’s age and insurance record, a 720 days’ benefit can be paid in case the requirement of the 1,500 or the 4,500 days is not fulfilled.


Average disposable income

ITALY


varies between 14 and 18 depending on job type http://r2e.gn.apc.org/country-node/443/country-minimum


Male employees of the private sector, self-employed and para-subordinate workers: 66 years and 7 months; Male and female civil servants: 66 years and 7 months; Female employees of the private sector: 65 years and 7 months; Female self-employed and para-subordinate workers: 66 years and 1 month (see Annex on the social protection of the self-employed). The retirement age is being gradually increased according to the increase in life expectancy. As of January 2021, the retirement age cannot be lower than 67 (it will reach 69 and 9 months by the year 2050). The pension payment deferment scheme no longer applies except for certain duly certified categories of hard jobs to which the


previous “Quota system” still applies. Such categories include: miners, workers engaged in asbestos removal, night-shift workers, public transport heavy-vehicles’ drivers, etc.


From January 2012 the former seniority pension (pensione di anzianità) has been replaced by the Early retirement pension (pensione anticipata). If the person has accrued the conditions for drawing full pension: 42 years + 10 months for men and 41 years + 10 months for women, as from January 2016, the benefit shall not be subject to a permanent reduction in amount even though the pension is claimed before the age of 62, until 31st December 2017. Persons first insured after 1/1/1996 who have accrued a work insurance of at least 20 years, may retire at the age of 63 years and 7 months upon condition that the amount of the pension they would be entitled to is at least equal to 2.8 times the monthly amount of the welfare-based social allowance (assegno sociale) equal to €448.07 in 2016 (see also Table XI, “Guaranteed Minimum Resources”). Since January 2012, the pension payment deferment schemes (the so-called “windows”) and the “quota system” (based on the sum of contributions and age) no longer apply except for certain categories of hard jobs.


women can ask to postpone retirement to 65




Compulsory social insurance scheme for employees and assimilated groups with earnings-related benefits generally provided by the employer at the expense of the National Institute for Social Security (Istituto Nazionale della previdenza sociale, INPS).

III. Sickness - cash benefits Conditions 2. Qualifying period Source http://www.missoc.org/MISSOC/INFORMATIONBASE/COMPARATIVETABLES/MISSOCDATABA

Generally, no qualifying period. Exceptions: farming industry employees on fixed-term contracts must have been in their occupation for at least 51 days prior to the onset of the illness in the current or preceding year; show-business employees must have accrued at least 100 days of contributions as of 1 January of the year prior to the onset of the



illness.



PORTUGAL




66 years and 2 months for men and women in 2016 (after 2015, the normal age for access to a pension varies depending on the average life expectancy at the age of 65. 65 years for beneficiaries legally prevented from working beyond that age (e.g., pilots, drivers of heavy vehicles). When the beneficiary reaches the age of 65, the normal pensionable age is reduced by four months for each calendar year after the contribution period of 40 years, with a 65-year threshold.


Insured persons aged at least 60 who have completed a contribution period of 40 calendar years or more with registered earnings may claim an early pension. In this case the pension amount is reduced. Beneficiaries aged between 55 and 60 years that have contributed over a career of 30 or more years with registered earnings may also claim an early pension on condition that they have submitted a request by 9 March 2016. Unemployed: Early pension from the age of 62, provided that they were aged 57 at the beginning of their unemployment and have completed the qualifying period. For those who have contributed for 22 calendar years and are aged 52 or more when becoming unemployed, it is also possible from the age of 57. In this case the pension amount is reduced. For heavy or unhealthy work, as a general rule, from 55 years of age (only for the professions legally provided for). From 55 years in case of specific measures to protect economic activities or companies.


None





Compulsory social insurance scheme financed by contributions covering employees and self-employed, with benefits depending on the registered earnings and on the duration of incapacity. No continuation of payment of wage by the employer.


6 months affiliation with registered remuneration of which 12 days of actual work during the 4 months prior to the one preceding the day of incapacity.



ROMANIA




Old-Age Pension (pensie pentru limita de varsta): Men: 65 years. Women: 60 years and 4 months on 1 July 2016, gradually increasing to 63 years by 1 January 2030. The pace of increase varies: the rule is one month increase at every three or five or eleven months.

VI. Old-age Conditions Legal retirement age Early pension Source http://www.missoc.org/MISSOC/INFORMATIONBASE/COMPA

Old-Age Pension with Reduced Standard Retirement Age (pensie pentru limita de varsta cu reducerea varstelor standard de pensionare): There is an assortment of Standard Retirement Age reductions for: * persons who contributed under special, difficult or other specific working conditions,


RATIVETABLES/MISSOCDATABASE/comparativeTableSearch.jsp

* persons who have had a disability prior to obtaining the insured person status, * persons persecuted for political reasons by the regime in power after 6 March 1945, deported abroad or taken prisoners of war, * blind persons, * other categories of persons, defined by other legal acts. Early Retirement Pension (pensie anticipata): Granted up to 5 years before the Standard Retirement Age to a person who exceeds the Full Contribution Period by at least 8 years. Partial Early Retirement Pension (pensie anticipata partiala): Granted up to 5 years before the Standard Retirement Age to a person who exceeds the Full Contribution Period by up to 8 years.


None




Compulsory social insurance scheme for employees and self-employed providing an earnings-related benefit. Payment of a Benefit for incapacity to work (Beneficiu pentru incapacitate de munca) by the employer.


At least 1 month of contribution.


Gross achieved income


SLOVENIA

Minimum age for admission to employment



Legal full retirement age is 65 years for both women and men.


An insured person is entitled to early pension (predčasna pokojnina) at 60 years of age, if he or she has completed 40 years of qualifying period (pokojninska doba). More stringent early pension entitlement conditions are being introduced gradually, with the transitional period ending in 2018.


None



III. Sickness - cash benefits Basic principles Source http://www.missoc.org/MISSOC/INFORMATIONBASE/COMPARATIVETABLES/MISSOCDATABA

Compulsory social insurance scheme financed by contributions for employees and self-employed with earnings-related benefits. Continuation of payment of wages and salaries paid by the employer.




No qualifying period required.


Average yearly disposable income

NORTHERN IRELAND (UK)


age 13 and the minimum school leaving age (16) may work http://r2e.gn.apc.org/country-node/570/country-minimum


State Pension and New State Pension age: Men: 65 years Women: 60 years (up until 5 April 2010). From 6 April 2010 women’s State Pension age is gradually rising until it reaches age 65 in November 2018. From December 2018 the State Pension age for both men and women will start to increase to reach 66 by October 2020. The government is planning further increases, which will raise the state pension age from 66 to 67 between 2026 and 2028. They will then review it every five years in line with life expectancy.


No early State Pension or New State Pension.

Any laws which impose a mandatory retirement age? Reference: http://ec.europa.eu/justice/dis

None


crimination/files/age_and_employment_en.pdf Section 7.3




* Statutory Sick Pay (SSP) paid by the employer for up to 28 weeks; * Employment and Support Allowance: Provides financial help to people who are unable to work because of illness or disability.


Statutory Sick Pay: Employees' earnings before sickness must have reached the Lower Earnings Limit (LEL) for National Insurance contribution purposes. Employees must satisfy the contribution conditions where they claim Employment and Support Allowance on cessation of Statutory Sick Pay. Employment and Support Allowance (ESA): payable to claimants who either meet National Insurance-related contribution conditions, meet income and capital tests or meet both.


Average annual gross pay

2.4 EXCESS AND EFFECT METRICS

2.4.1 Impacts and costs indicators

The human impacts and financial costs included in the JANPA costing model are listed below.

Table 2 (a) : Obesity-related impacts and costs indicators

HUMAN IMPACTS

FINANCIAL COSTS

ADULT OBESITY /OVERWEIGHT Prevalence

Lifetime Income Losses

MORBIDITY Incidence

Prevalence

Years Lost due to Disability (YLD)

Quality Adjusted Life Years (QALY )

Direct healthcare costs

Productivity losses due to

absenteeism

MORTALITY Premature death Productivity losses due to


Years of Life Lost (YLL)

premature mortality

Adult productivity losses due to absenteeism are assumed to commence when a person develops an

obesity-related disease and last until after national retirement age. Lifetime income losses (the

“income penalty”) is assumed to commence on the 18th birthday for individuals who are classified as

“obese/overweight at age 18 years”.

Table below describes how these impact and cost indicators are handled in the JANPA costing

model.

Table 2(b): Handling of impact – cost indicators

Impact and cost indicators Distribution of impact-cost Discounted

Adult Obesity / Overweight No No

Mortality

Death To Year of Occurrence (YoO) No

Premature death To YoO No

Potential Years of Life Lost (PYLL) To YoO (to the year of premature death)

Years of Life Lost (YLL) To each Year to Life Lost (starting from year to premature death to year of life expectancy (at birth)) (YoLL)

Yes

Morbidity

Incidence To YoO

Prevalence To YoO

Years Lost due to Disability (YLD) To each Year to Life Lost (starting from year to premature death to year of life expectancy (at birth)) (YoLL)

Yes

Quality Adjusted Life Years (QALY)

Direct healthcare costs To YoLL (starting year that disease to year of death)

Yes

Societal costs


To YoLL (from year that disease developed to “retirement”)

Yes

Productivity losses due to premature mortality

To YoO (to the year of premature death) Yes

Lifetime income losses (applies only to those who are obese / overweight at 18 years)

To YoO (to the 18 years birth year) Yes


2.4.2 Excess metrics

To estimate the excess burden attributable to childhood obesity/overweight we compare the value

of an impact/cost indicator amongst individuals who were “obese/overweight as a child” to its value

amongst individuals who were “healthy weight as a child”:

An example of an excess metric is the number of diabetes cases that are attributable to childhood

obesity/overweight.

2.4.3. Effect metrics

To assess the effect of a 1% (or 5% ) reduction in (sex-age specific) mean childhood BMIs, the BMI

distributions of the initial cohort of children is changed appropriately and the modelling software

rerun. The effect of a 1% (or 5%) reduction in mean BMIs is then estimated by taking the difference

between total impacts/costs in the original model and impacts/costs in the changed model.

The current value of an excess metric thus serves as the base case for the assessment of the effect of

a reduction in mean childhood BMI. Increases in all impacts and costs (except QALYs) represent

greater burden. Therefore, for all impacts and costs except QALYs, a positive effect represents an

improvement (i.e. a reduction in a burden attributable to childhood obesity/overweight).

An example of an effect metric is the effect of a 1% reduction in the mean childhood BMI on the

excess number of diabetes cases that are attributable to childhood obesity/overweight. Another

Excess costs attributable to childhood obesity/overweight

Impact/Cost (Obese/Overweight as child) – Impact/Cost (Healthy weight as child)

Effect of reductions in mean childhood BMI

Total impact/cost (current BMI) – Total impact/cost (reduced BMI)


would be the effect that a 5% reduction in mean childhood BMI on the lifetime excess direct

healthcare costs that are attributable to childhood obesity/overweight.

2.5 OBESITY-RELATED DISEASES

To be incorporated into a country’s JANPA costing model, a disease or a societal impact must satisfy

two criteria:

It must be significantly related to childhood obesity in the evidence review; and

The necessary data must be available in the country

The global list of diseases and societal impacts that are significantly related to obesity and

overweight is identified from the evidence reviews of the international literature and local materials.

Diseases and societal impacts for which there is inadequate local data or acceptable proxy data are

removed from the country’s model.

2.5.1 Global Disease List from the Evidence Reviews

The evidence reviews confirmed Fernandes (2010) summary of the strength of the evidence

regarding the consequences of childhood obesity. The reviews revealed a substantial evidence base

on the link between childhood obesity/overweight and childhood diseases. However, studies of the

link between childhood obesity/overweight and adult diseases are more difficult and costly and the

evidence base regarding adult diseases is much weaker.

The sources from the evidence review of childhood consequences was combined with an updated

international literature review of adult consequences that was used in the safefood “Economic Cost

of Adult Obesity in Republic of Ireland” conducted in 2012 (ref). Relative risks of developing diseases

that were associated with childhood and adult obesity/overweight and childhood and adult diseases

were then extracted from these combined sources. The childhood obesity-related diseases were

used in the childhood years of the disease modelling and the adult obesity-related diseases were

used in the adult years.

Table 2 (c): Global Disease List (Diseases known to be associated with obesity and overweight)

Childhood (only) diseases Chronic pain, Wheezing disorders

Diseases in childhood and adulthood Asthma, Colorectal cancer, Deep Vein Thrombosis (DVT),

Depression, (Type 2) Diabetes, Hypertension, Kidney

Cancer, Liver Cancer, Multiple Sclerosis (MS), Non-

alcoholic Fatty Liver Disease (NAFLD), Obstructive sleep

apnoea, Oesophageal cancer, Psoriasis, Pulmonary

embolism, Stroke, Thyroid cancer.

Adult (only) diseases Chronic Back Pain, Endometrial cancer (females),

Gallbladder cancer, Gallbladder disease, Gout,

Hypertension in pregnancy, Ischaemic Heart Disease,

Osteoarthritic knee, Ovarian cancer (females),

Pancreatic cancer, Polycystic Ovarian Syndrome


(females), Breast cancer (females aged 50+ years),

Prostate cancer (males), Urothelial Cancer (males)

The characteristics of these diseases and the way they were handled in the disease modelling are

given in the table below.

Table 2 (d): Disease characteristics and their use in the disease modelling

DISEASE ICD-10 AM, 6th edition ADULT CHILD TERMINAL ACUTE GENDER

Asthma J45.1, J45.8, J45.9, J46 Yes Yes No No Both

Bladder cancer

(or Urothelial Cancer) C67 Yes No Yes No Males

Breast cancer C50 Yes No Yes No Females

CHD

(or Ischaemic Heart Disease) I20, I21, I22, I23, I24, I25, I46, I50 Yes No Yes No Both

Chronic back pain M54.3, M54.4, M54.5 Yes No No No Females

Chronic pain

No Yes No No Both

Colorectal cancer C18, C19, C20 Yes No Yes No Both

Depression

No Yes No No Both

Diabetes E11 Yes Yes No No Both

DVT I80.1, I80.2, I80.3 Yes No No Yes Both

Endometrial cancer C54, C55 Yes No Yes No Both

Gallbladder cancer C23 Yes No Yes No Both

Gallbladder disease K80, K81, K85.1 Yes No No Yes Both

Gout M10.0, M10.9 Yes No No No Both

Hypertension I10, I11, I12, I13 Yes Yes No No Both

Kidney cancer C64 Yes No Yes No Both

Knee osteoarthritis M17.0, M17.1, M17.9 Yes No No No Females

Liver cancer C22.0 Yes No Yes No Both

Multiple sclerosis G35 Yes No No No Males

NAFLD K76.0 No Yes No No Both


Oesophageal cancer C15 Yes No Yes No Both

Ovarian cancer C56 Yes No Yes No Both

Pancreatic cancer C25 Yes No Yes No Both

Prostate cancer C61 Yes No Yes No Both

Psoriasis L40 Yes No No No Both

Pulmonary embolism I26 Yes No No Yes Both

Sleep Apnoea

No Yes No No Both

Stroke G45, G46, I63,I64 Yes No Yes No Both

Thyroid cancer C73 Yes No Yes No Both

2.5.2 Data requirements to be included in a country’s costing model

A disease associated with obesity/overweight could be included in a country’s CCSM only if the

required detailed data was available. No country model included all diseases in the Table above.

2.6 SOFTWARE IMPLEMENTATION

2.6.1 Existing UKHF software

Disease modelling and cost estimation were undertaken by the UKHF (sub-contractor to IPH-IRL)

through its Public Health Modelling Unit that uses closed source software.

The UKHF has developed extensive software which has been used by WHO for their population

obesity forecasts and population-level burden of disease reports.


UKHF software is modularised; the modules are described in the figure below.

Figure 2 (c): Modules of UKHF’s software

Construction of individual lifetime BMI trajectories is undertaken in the Risk Module; disease

modelling of disease occurrence is undertaken in the Disease Modules and cost estimation was

undertaken in the Economic Module.

2.6.2 Modification of existing UKHF software

To implement the CCSMs required for the JANPA costing model, the WP4 Lead Team worked with

the UKHF to modify their OCSM-oriented software. This involved:

Adapting the Risk Module, Disease Module and Economic Module

Introducing a number of innovations into these modules

Integrating these modules in order to produce to the necessary Model Outputs Workbook

This presentation is part of the Joint Action JANPA (Grant agreement n°677063) which has received funding from the European Union’s Health Programme (2014-2020)

Example3:ForesightObesityModel


The table below lists the main modifications that were needed to existing UKHF software:

Table 2 (e): Modifications made to existing UKHF software

MODIFICATION COMMENTS

Incorporating children

Extending age ranges

Incorporating childhood impacts and costs that are

associated with childhood obesity/overweight

Excluding adults from initial cohort

“Closing the cohort”

Excluding new entries by births and immigration

Excluding exits by emigration

Incorporating the definition of an

overweight/obese child

Comparisons based on BMIs on 18th

birthday rather BMI

in a particular future year

Complications associated with the occurrence of

childhood diseases and deaths

Incorporating a number of other chronic obesity-related diseases

Incorporating acute conditions into a chronic

disease model

Acute conditions and costs are assumed to last one year

Incorporating three types of societal costs Lifetime income losses (associated with being

obese/overweight at 18 years of age)

Productivity losses due to premature death (associated

with an early death)

Productivity losses due to absenteeism (associated with

developing an obesity-related disease)

Incorporating post-retirement productivity into

productivity loss metrics

Introducing new metrics

Impact and cost indicators for the possible

consequences of burdens attributable to childhood

obesity/overweight

Excess metrics for the impacts and costs attributable to

childhood obesity/overweight

Effect metrics for the effects of 1% and 5% reductions in

mean childhood BMI


2.7 SOME STATISTICAL AND COSTING ISSUES

2.7.1 Uncertainty intervals

The uncertainty intervals that accompany the Model Outputs incorporate variation associated from

the simulation (stochastic or aleatoric uncertainty) and are derived from the various probabilistic

distributions that are used in the software.

Example equations for calculating the Monte Carlo errors

Annual incidence outputs

The annual incidence (I) per 100,000 is calculated with the following formula:

per 100,000 *100,000population

nI

N (0.1)

Where n refers to the number of new cases of a disease in a given year and Npopulation is the total

number of people alive in the simulation at a given year.

Calculating 95% confidence intervals

95% CI for epidemiological outputs

(1 )

95% CI per 100,000 1.96 *100,000population

p p

N

(0.2)

Where Npopulation relates to the number of individuals alive in the year (population size) and p (per 1)

is the rate of an event an occurring in the population (p=n/NP).

Direct costs

The annual costs for each disease (CTotal) per 100,000 are calculated in each year by multiplying the

cost per case (Ccase) by the prevalence of the disease (PD) (0.3).

*P

per 100,000 *100,000case DTotal

trials

CC

N (0.3)

95% CI for direct and absenteeism costs

(1 )

95% CI per 100,000 costs 1.96 * *100,000case

trials

p pC

N

(0.4)

The rate p corresponds to the prevalence rate per individual.

These only apply to the random processes incorporated into the microsimulation and ignore lots of

sources of variation:


BMI trajectories

Sampling of initial cohort

Prevalence, incidence, survival inputs

Proxy data

Cost estimation procedures

etc

The example equations do not attach meaningful uncertainty intervals to final Model Outputs. These

can only be derived from large scale sensitivity analyses.

2.7.2 Other statistical issues

In the Model Output Workbooks, a “premature” death is defined as one that occurs before their life

expectancy at birth. However, because life expectancy at birth is greater for females than it is for

males, female deaths are classified as “premature” for a greater number of calendar years.

Therefore, risk of “premature” deaths can appear higher amongst females. Therefore in the RE ADJ

Model Output Workbooks, the female premature mortality calculations are adjusted to take this into

account. In the RE ADJ Model Output Workbooks, a “premature” death in one that occurs before life

expectancy of the appropriate male.

2.7.3 Discounting future costs

All impacts and costs (except number of premature deaths) are discounted to 2015 euro values. The

annual discount used in each country to convert future values to current 2015 values are shown in

the table below.

Table 2(f): Annual Discount Rates

Country Annual discount rate

Croatia (HRV) 5%

Greece (GRC) 5%

Republic of Ireland (IRL) 5%

Italy (ITA) 3.5%

Northern Ireland (NIR) 3.5%

Portugal (PTG) not applicable

Romania (ROM) 5%

Slovenia (SVN) 5%

Discounting is a technique used to reflect people's time preferences to receive benefits now and pay

costs later. Discounting at the annual rate of 5% per annum is almost the opposite of compounding

interest at 5% per annum. So, for example, in the Republic of Ireland the JANPA costing model

estimates that the total lifetime costs of childhood obesity/overweight is €4,518.1 M in 2015 values.


These costs are incurred over the lifetimes of today’s children. To pay for these costs; in 2015 you

would have to lodge €4,4518.1 M into a bank account that earns 5% compound interest per annum

and leave it in that account only making withdrawals as those costs are incurred. At the end of the

children’s lifetimes the account would be empty (principal plus interest) and the lifetime costs would

have been paid.

2.7.4 Approach to estimating productivity losses

In each JANPA WP4 country, an estimate of the (per case) annual costs of adult productivity losses is

required. For this type of calculation, economists use either a Human-Capital approach or a Friction-

Cost approach although it is unclear which is the most appropriate application of the Friction-Cost

approach when an accumulation over many years is used. Therefore, like the majority of cost

studies, we will use the Human-Capital approach.

2.7.5 Valuing post-retirement productivity

To incorporate a value for productivity losses associated with the post-retirement age, their

calculation continues until 10 year after the national retirement age along with a scaling factor listed

below:

By 100% if death occurs before national retirement age.

By 30% if death occurs after but within 10 years of national retirement age

By 0% if death occurs thereafter

2.7.6 Other costing issues

Indirect healthcare costs that are incurred by patients, their families and communities are

omitted from the modelling because of the lack of data and research.

Acute diseases are modelled as lasting one year and use annual per case treatment costs

although their duration may be considerably shorter. This probably leads to overestimation

of healthcare costs.

The evidence reviews found that the cost of treatment for diseases that are not related to

obesity/overweight can be higher amongst obese/overweight patients than amongst

patients with healthy weight. This means that cost–related excess metrics will be

underestimated

Adult productivity losses due to absenteeism are assumed to commence when an individual

develops an obesity-related disease and last until retirement or death. They may be

overestimated.

No adjustments have been made for different purchasing powers in the different countries.


3. WORKFLOW

Six broad phases are involved in the deployment of the JANPA costing model in a country: Data

Collation, Pre-modelling Data Processing, Disease modelling, Cost estimation, Post-Modelling Review

and Reporting. These inter-related phases and the feedback loops between them are described in

the Figure blow:

Figure 3(a): JANPA costing model workflow3

3 UKHF were principally subcontracted for Phases 1 and 2.

1. Data

collation

2. Pre-

simulation

data

processing

3.

Simulation

modelling

5. Post-

simulation

review

6.

Reporting

4. Cost

estimation


3.1 PHASE 1: DATA COLLATION

Data collation was conducted by the JANPA WP4 Teams in the participating countries and overseen

by the WP4 lead Team in IPH-IRL. Standardised Excel workbooks were used to identify possible data

sources and collate the data required for the modelling (see Section 3.7).

A systematic approach was developed to collate the required data.

Figure 3(b): Data collation workflow

3.1.1 Identifying data sources

Identification of potential data sources, collation of data from these sources and final decisions

about data sources to use were undertaken jointly by the participating country and the WP4 lead

Team.

The availability and quality of data varied greatly across the countries. In all countries, multiple data

sources had to be used.

In the case of disease parameters (prevalence, incidence, survival, mortality), a modification of the

DISMOD software (ref) is used by UKHF to “regularise” these parameters and estimate the value of

missing parameters.


In all participating countries, data imputation may be necessary because:

Required data are not available and it is necessary to impute data from other sources

Some required data are available but not at the optimal level of detail and it is necessary to

collapse BMI, age, etc. categories.

When the required data, from any domain, is unavailable in a participating country, the most

appropriate proxy data was used. Decisions about data imputation were made by participating

countries in consultation with the WP4 Lead Team and the UKHF; and appropriately documented.

The table below describes the types of data sources used, the ranking given to in the decision

making, and who was responsible for collating the data:

Table 3(a): Potential data sources for participating country

RANKING TYPE RESPONSIBLE PERSON

1a

National source Participating country

1b

International source (national data) WP4 Lead Team

2 Regional source (extrapolation to national level)

Participating country

3

National source for another country (proxy data) WP4 lead team

4 International source (regional proxy data)

WP4 lead team

5 Regional source for another country

(extrapolated to national level)

WP4 lead team

3.1.2 Calculating per case treatment costs

We aimed to gather direct health care costs (costs to the state) covering hospital costs, primary care

costs and pharmaceutical cost. Indirect costs borne by a patient, their family or community are not

included. Specialist services for morbidly obese children or adults is not included.

Treatment costs for a particular disease in any year are obtained by multiplying the (sex-age)

number of prevalent cases at the beginning of that year by the (sex-age specific) annual per case

treatment costs.


A mixture of two approaches are used to calculate the annual cost per case for the management and

treatment of obesity-related diseases that are included in the Collated Data Workbook :

• “Top down” approach based on estimation of Population Attributable Fractions (PAFs) and

their application to national healthcare data

• “Bottom up” approaches based on analysis of healthcare utilisation in cross-sectional studies

or longitudinal studies that also include BMI data

The approach varies from one country to another and from one disease to another. Details are given

in the data documentation.

Ideally, all model inputs and outputs for a participating country would be calculated using a bottom-

up approach based to local research and/or data. Failing this, a top-down method applied to local

research and/or data is the next preferred approach. The least preferred approach is the use of a

top-down method with international inputs.

3.1.3 Data handling issues

Significant methodological challenges are associated with combining data from the different global,

international and regional sources used in the Data Collation and Pre-simulation Data Processing

phases. These include:

Significant data imputation involving sex-age extrapolation and interpolation of collated data

into early childhood years, adolescence and later adult years

Calculation of annual disease parameters from those relating to other periods (ten-year

incidence rates, five-year relative risks)

Appropriate data handling protocols with such complex collections of data gathered across a

large number of data domains

Challenges of estimating missing disease parameters

Mismatch between disease definitions used in the evidence reviews and those used in data

available.

3.2 PHASE 2: PRE-SIMULATION DATA PROCESSING

A country’s Collated Data Workbook was then sent to the UKHF (sub-contractor to IPH-IRL) who, in

collaboration with the WP4 Lead Team and the participating country, prepared it for inputting into

the modified simulation software. A description of these data processes is provided in the Model

Toolbox although the final data input file (“Input Data File”) is not provided by UKHF.

This stage involved several important procedures:

Obesity forecasting and the modelling of virtual individual lifetime BMI trajectories


“Regularising” and estimating values of missing disease parameters (prevalence, incidence,

survival and mortality)

3.2.1 Modelling lifetime BMI trajectories

Implementation software currently uses (sex, age, year) regression-based forecasts of

obesity/overweight prevalence plus a constant lifetime BMI percentile assumption to model

individual lifetime BMI trajectories .

3.2.2 Estimating disease parameters

A consistent set of disease parameters (prevalence, incidence, survival, mortality) is required.

Using the relationships that exist between these four disease parameters, a modified version of

DISMOD is used to estimate missing parameters and produce a consistent set of all parameters for

use in the simulation modelling.

3.3 PHASE 3: DISEASE MODELLING

3.3.1 Details of the simulations

A range of impacts and costs are recorded over a period of 90 years of follow-up from 2015 to 2105.

The initial cohort in a participating country’s simulation model consists of a random sample of 20

million virtual children selected to have the same sex-age-BMI distribution as the children living in

that country in 2015. In the Model Output Workbooks for a participating country include the counts

and totals for the 20 million initial cohort members as well as the counts and totals that have been

scaled to the childhood population size living in the country in 2015.

The virtual lives of the initial cohort of virtual children are simulated for 110 years: all cohort

members who survive until their 110th birthday automatically experience death at the end of their

110th year. In any calendar year in which there is at least one such individual, the simulation of

disease and mortality experience of the survivors in that year is biased and excluded from the Model

Outputs. Theoretically, this bias begins in 2108 when individuals who are 17 years old in 2015 turn

110 years of age. For this reason, follow-up is stopped in 2105 when there are individuals as young

as 93 years of age. At the beginning of 2106, surviving individuals will be aged 90-107 years

(estimated to be up to 5% of the initial cohort members) and their subsequent living experiences


are excluded from the Model Outputs. They are predominantly females who were healthy weight as

a child so this will probably underestimate the lifetime disease, mortality and healthcare costs of

female healthy weight children.

3.3.2 Simulating disease processes

Independent disease process

Each obesity-related disease that is included in a participating country’s model is modelled

independently. These independent disease process will probably underestimate disease incidence

and prevalence by ignoring multi-morbidities and overestimate healthcare cost estimates by

ignoring savings that might accrue from managed care. Checks are put in place to ensure that an

individual cannot develop a disease more than once and cannot continue to develop further diseases

after death. The order that the diseases are modelled is the order on which they appear in the

Collated Data Workbook.

Annual disease modelling

For each obesity-related disease in a country’s costing model, the disease experience of the virtual

individuals are modelled year-by-year using a semi-Markov process that has four states defined by

whether or not the individual has the disease and whether or not the individual is alive.

Figure 3(b): State transition probability matrix

END OF A YEAR

START OF A YEAR

ALIVE DEAD

WITHOUT DISEASE

WITH DISEASE

WITHOUT DISEASE

WITH DISEASE

ALIVE

WITHOUT DISEASE P 11 P12 P13 P14

WITH DISEASE P21 P22 P23 P24

DEAD

WITHOUT DISEASE P31 P32 P33 P34

WITH DISEASE P41 P42 P43 P44

In this table, PIJ = Probability {end of year state = J | start of year state = I} for I,J = 1,2,3,4.

This figure relates to chronic diseases which are assumed to last until death.

Acute diseases are assumed to last for one year.


Table 3(c): Calculation

of state transition

probabilities

Separate state

transition probability

matrices are used for

individuals who are

obese/overweight at

the start of the year

and those who are of

healthy weight.

The transition

probability matrix that

is applied to a

particular individual at

the beginning of a year is the one that matches their sex, age and BMI at the beginning of that year.

Some notes on the transition probability matrix used in the semi-Markov disease process:

1. The probabilities do not change over time. For example:#

They do not account for any possible changes in survival due to new medications

and treatments

2. The probabilities do not take into account how long a person who is obese/overweight at

the beginning of a year has been obese/overweight (duration of risk exposure)

3. Deaths from other causes are driven by underlying sex-age specific mortality rates. No

breakdown into finer (not obesity-related) causes of death categories is used.

In these calculations; diseases are developed towards the beginning of a calendar year and deaths

occur towards the end of a calendar year.

TRANSITION PROBABILITY

DATA REQUIREMENT

P11 Annual incidence

P12 Annual incidence

P13 All causes mortality

P14 0 (develop disease and die in one year)

P21 0

P22 Annual survival

P23 0

P24 Annual survival

P31 0

P32 0

P33 1

P34 0

P41 0

P42 0

P43 0

P44 1


Figure 3(c): Timing of process in Disease Module

The figure above shows the main model processes which take place for each individual in a given

year in the disease modelling. The outputs summarise at which time points the outputs are

generated.

3.4 PHASE 4: COST ESTIMATION

Cost estimation is done in the Economics Module of the implementation software using the disease

trajectories produced by the Disease Module and annual per case treatment cost estimates. The

calculations could thus also have been performed using the cost data supplied in the Data Collation

Workbooks and the counts and totals in Model Output Workbooks.

Three types of costs are calculated in each year of the simulation:

For each obesity-related disease; annual per case treatment costs are applied to the number

of prevalent cases in a year to obtain the direct healthcare cost estimates for that disease in

that year.

For each obesity-related disease, the annual per case cost of work absences (number of days

per year) associated with the disease and the absenteeism and the per case treatment costs

for each obesity-related disease are applied to the number of prevalent cases in that year.

Income losses are calculated by applying annual average incomes (adjusted for the income

penalty) to the number of individuals at the beginning of the year who are classified as

obese/overweight children

The assumption that the different disease processes are modelled independently probably means

that total direct healthcare costs and productivity losses due to absenteeism may be overestimated.

Discounted and undiscounted costs are included in the Model Output Workbooks.


3.4.1 Model Outputs

In order to contain sub-contracting costs, the Reporting phase was undertaken by the WP4 Lead

Team in IPH-IRL. For this, WP4 Lead Team and UKHF agreed a standard format for the Model

Outputs Workbook that consisted of annual counts and costs for a country.

The variables included in the Model Outputs Workbook for a country are listed in the table below:

Table 3(d): Counts and costs in the Models Outputs Workbook

Disease-related outputs

Model output Description

1. Population counts Number of individuals alive at the beginning of the year

2. Incidence counts Number of new cases of each disease to appear in the year

3. Prevalence counts Number of cases of each disease existing in the individuals alive at the

end of the year

4. Death counts Number of deaths that occur in each year

5. Premature death

counts

Number of people who die before their Life expectancy (LE) (at birth)

during the year

6. Years of Life Lost

(YLL) counts

The number of years of life lost during the year (due to premature

death) associated with individuals who died in the year or a previous

year This is the same as the number of people who died prematurely

during the year plus the number of people who died prematurely in a

previous year but would not have reached their LE (at birth) in the

year (had they lived)

7. Years Lost due to

Disability (YLD) counts

The number of years of life lived with disability during the year by all

individuals alive at the end of the year

8. QALY counts The number of quality adjusted years of life lived during the year

QALY by all individuals alive at the end of the year


Cost outputs

Model output Description

Direct healthcare costs Total direct healthcare costs in the year

Total Productivity Losses

due to Absenteeism

Total productivity losses due to absenteeism incurred in the year

Total Productivity Losses

due to premature

mortality

Total productivity losses due to premature mortality incurred in the

year

Total Life income losses

Total life income losses incurred in the year

3.5 PHASE 5: POST-SIMULATION REVIEW

Model outputs were provided to the WP4 Lead Team in a standardised Model Outputs Workbook

(see Model Toolbox). The WP4 Lead Team then restructured the Model Outputs Workbook into a

classical data analytical format. These are referred to as RE ADJ Model Output Workbooks.

Data and modelling issues needed to be treated sequentially because of their inter-relationship and

lack of access to software code.

The review considered:

survival at the end of 2105 after 91 years of follow up

3.6 PHASE 6: REPORTING

The WP4 Lead Team at IPH-IRL developed Excel macros and SAS programmes to calculate each

impact and cost indicator as well as the corresponding excess metric and effect metric from the total

counts and total costs provided in the Model Outputs Workbook. Standardised templates were then

produced to present the core tables and graphs need for reporting (see Model Toolbox).

Two versions of the core tables and graphs are available:

Accumulating impacts and costs using 2015 population as denominators for rates and

percentages.

Annual impacts and costs using current populations as denominators for rates and

percentages.


Core tables are broken down by sex, childhood age group (0-5 years, 6 -11 years and 12 -17 years)

and calendar year.

3.6.1 Data documentation

To document the availability and quality of data available across the required domains, and to help

identify data gaps in each country, a number of data quality scales were developed and used the

describe the data collated. These included a Disease data Quality Score for prevalence, incidence,

survival and mortality data.

Disease Data Quality Score

1. No acceptable data

2. Must be estimated from other data (for disease parameters: prevalence, incidence, survival

mortality).

3. International proxy

4. "Approximate" data only:

5. Not applicable (non-fatal disease)

6. Acceptable data

1 2 3 4 5 6

“Approximate” data included cases where theoretical ICD codes mismatched those actually used;

hospital data was used for prevalence or incidence , self-reported BMI or regional (sub-national)

data was used.

3.7 JANPA COSTING MODEL TOOLBOX

Materials relating to each of the phases of the JANPA Costing Model workflow (Data Collation, Pre-

modelling Data Processing, Disease Modelling, Cost Estimation, Post-Modelling Review and

Reporting) that could be used by other countries wanting to deploy the JANPA costing model will be

available in the Modelling ToolBox on the JANPA website (www.janpa.eu) in early 2018.

http://www.janpa.eu/


These resources include the following guidance documents and questionnaires and are described in

the table below:

Table 3(e): JANPA Costing Model Toolbox

WORKFLOW PHASE

RESOURCE

1. DATA COLLATION Local Materials Survey used to identify local reports and research to supplement the international literature Data Sources Survey to identify local and international data sources not captured by initial data scoping exercise Data Request Workbook to collate the required data for a country Collated Data workbook

2. PRE-SIMULATION DATA PROCESSING

Guide to Pre-modelling Data Processing and model inputs

3. SIMULATION MODELLING Model Outputs Workbook

4. COST ESTIMATION

5. POST – SIMULATION REVIEW Guide to Post-modelling Review

6. REPORTING SAS data file and codebook Core Table and Graph Workbook

OTHER RESOURCES Global list of child diseases significantly related to childhood obesity/overweight Global list of adult diseases significantly related to childhood obesity/overweight and/or adult obesity/overweight


4. DATA REQUIREMENTS

4.1 DATA DOMAINS

The data required for a model depends on the impact and costs that are included in the costing

study. Data requirements are described in the tables below.

Table 4(a): Data Requirements

1. Population

Current childhood population size estimates Broken down by sex-age.

(single year age groups preferred)

2. BMI

Current distribution and historical trends in BMI Broken down by year sex-age.

All ages required (single year age groups preferred)

Sample sizes required

3. Disease parameters

Current annual incidence rates for

Each obesity-related diseases

Broken down by sex-age (single year age groups

preferred)

Current annual prevalence rates for

Each obesity-related disease


preferred)

Current annual mortality rates for


All causes


preferable)

Current one-year survival probabilities for



preferable)

4. Direct healthcare costs

Current annual direct healthcare costs for case of:


Hospital costs, primary care costs, pharmaceutical

costs.

Either national annual total costs (if number of current

prevalent cases is known) or current annual per case

costs.


preferred)

5. Lifetime income losses and Productivity losses due to premature mortality

Current annual average income Broken down by sex-age (single year age groups

preferred)

Gross income perhaps better

6. Productivity losses due to absenteeism

Absenteeism rates (average number of days absent Broken down by sex-age (single year age groups


per year) or each obesity-related disease preferred)

Current social welfare payments for work

absences

Either national total annual costs (if current number of

prevalent cases is known) or current annual per case

costs.


preferred).

Table 4(b): Other parameter requirements

National BMI cut off-points and reference curves (if

they exist and are different than IOTF cut-off

points).

For classifying childhood BMI status

Disease risks for each obesity-related diseases Relative risks / odds ratios

Risks in healthy weight individuals


preferred)

National utility weights used in national studies (if

relevant) for:


EuroQOL’s EQ5D weights used by default in calculation

of QALYs.


preferred)

National disability weights used in national studies

(if relevant) for


GBD weights used by default in calculation of YLDs.


preferred)

Annual discounting rate used in national studies (if

relevant)

OECD recommendations used by default

Life expectancy at birth For each single-year from ages 0 to 17 at their year of

birth. Broken down by sex.

Minimum legal working age and retirement age


The figure below explains how data from these domains are used in the modules of the simulation

software.

Figure 4(a): Data use in software modules

Population Module

Risk Module

Disease Module

Economic Module

Model Outputs

Workbook

Initial childhood cohort

Virtual BMI trajectories

Virtual Diseases trajectories

Counts and totals

Current childhood

disease prevalence

Current childhood

sex-age distribution

Current childhood BMI

distribution

Current and historical

trends in BMI

RRs/ORs of disease

Disease one year survival

probabilities

All-cause mortality rates

Income penalties

Average annual income

Average work absences

Social services costs

Annual per case treatment

costs


5. LIFETIME IMPACTS & COSTS OF CHILDHOOD OBESITY IN REPUBLIC

OF IRELAND

5.1 LOCAL CONTEXT

This section should be read in conjunction with the international context outlined in Chapter 1.

The pictures of obesity-- its prevalence, causes, and human outcomes—are similar across the

Republic of Ireland and Northern Ireland, although their financial costs and losses differ. Each

government has responded to the epidemic with a similar multi-departmental, multi-sector strategy

policy that is aimed at prevention across the lifetime.

The government of the Republic of Ireland has very actively promoted partnership among

government bodies and across sectors. It has developed and funded internal programs and outside

agencies with a remit to address the obesity epidemic and has initiated and funded internal and

external: investigations into the scale of the problem in Republic of Ireland, into the best

interventions to address and prevent obesity, and into the financial and lifetime costs of overweight

and obesity to the person and society. The Government’s current range of initiatives rely on the

multi-sectorial approach outlined in Healthy Republic of Ireland (HI) – A Framework for Improved

Health and Well-Being 2013-2025 (Department of Health, 2013). The approach was adopted by the

Irish Government to serve as a tool to frame multi-sector action in response to not only the obesity

epidemic, but to Republic of Ireland’s changing health and wellbeing profile of increased life

expectancy, rising morbidity trends, and increasing associated costs. The framework includes

arrangements that promote cooperation among the health sector and other areas of Government

and public services. The framework also focuses on research and evidence to ensure goals,

programmes, policy, and programming decisions are based on robust evidence, best practice

approaches, and integrated with service delivery to maximise impact. The Healthy Republic of

Ireland team evaluated Republic of Ireland’s health status in the Healthy Republic of Ireland Survey

2015 and specifically evaluated Weight Management and found the same profound and rising

weight epidemic (Department of Health, 2015) that existed in 2013 when the program started.

The HSE has incorporated Healthy Republic of Ireland into the health services strategy. Healthy

Republic of Ireland in the Health Services – National Implementation Plan 2015-2017 describes a 3-

pronged strategy aimed at health service reform, reducing the burden of chronic disease, and

improving staff and well-being. Reducing overweight and obesity are listed among the plan’s

strategic priorities (HSE, 2015). The Government has continued its ideal of agency collaboration with

the 2016 Program for a Partnership Government that sets out the agreed government program

between Fine Gael, the Independent Alliance, and some Independent TDs. It lists the

implementation of a national obesity plan among the key public health interventions it will make.

The program will include a focus on child health and targeted investment in the early years that will

include a Prevention and Early Intervention Unit in the Department of Public Expenditure and

Reform/Finance focused on early intervention policies to improve life outcomes. The Government


developed the Obesity Policy and Action Plan 2016-2025 called A Healthy Weight for Republic of

Ireland aimed at assisting people to achieve better health and specifically reduce levels of

overweight and obesity. This approach is also based on the Government’s 2013 framework for

improved health and well-being, Healthy Republic of Ireland. A Healthy Weight for Republic of

Ireland covers a 10-year period (2016-2025) setting targets and actions to produce results and

includes: a sugar levy; a whole school approach; food establishments posting calorie content of

dishes; food industry reducing sugar, fat, and salt; and a code of practice for food and drink

marketing. (Department of Health, 2016) The critical point in the success of the plan relies on the

meaningful application of the Ten Steps Forward by government and non-government bodies. The

Ten Steps Forward:

1. Embed multi-sectoral actions on obesity prevention with the support of government

departments and public sector agencies.

2. Regulate for a healthier environment.

3. Secure appropriate support from the commercial sector to play its part in obesity

prevention.

4. Inform and empower change through a clear communications strategy.

5. The Department of Health will provide leadership.

6. Mobilise the health services with a focus on prevention.

7. Develop a service model for specialist care for children and adults.

8. Acknowledge the key role of physical activity in the prevention of overweight and obesity.

9. Allocate resources according to need, in particular children and disadvantaged groups.

10. Monitor research and review

The Government has partnered with non-government and external agencies across sectors to

actualize its policies and plans, to continue evaluation of the epidemic, and to advise on policy, and

regularly works with Republic of Ireland Department of Public Health (IPH) who assisted the

Government with policy development and implementation of A Healthy Weight for Republic of

Ireland. IPH contributed to the evidence base on a sugar sweetened drinks tax in 2012, when

commissioned by the Department of Health in the Republic of Republic of Ireland to undertake

a Health Impact Assessment. With the support of the EC, IPH is currently evaluating the lifetime

impact of childhood overweight and obesity as measured by body mass index (BMI), on the

individual and the society in terms of financial and human costs.

SafeFood has collaborated with IDPH, University College Cork, the European Commission and other

agencies to provide the first estimate of the financial costs of overweight and obesity to Republic of

Ireland in 2012, and are continuing to advance these investigations with a report of the Lifetime Cost

of Childhood Obesity (2017). In 2013, SafeFood worked with the Special Advisory Group on Obesity

(SAGO) and with the Regional Obesity Prevention Implementation Group (ROPIG) in Northern Ireland

on an obesity awareness public health campaign.

http://www.publichealth.ie/sites/default/files/documents/files/HIA%20Proposed%20Sugar%20Sweetened%20Drinks%20Tax%20Report.pdf


Children and Young People's Services Committees (CYPSC) operate on a county level to secure better

outcomes for children and young people in their area through more effective integration of existing

services and interventions. The Government identified them as a key to plan and co-ordinate

services for children and young people in every country in Republic of Ireland. One of CYPSC’s

priorities is obesity prevention and is developing initiatives to raise awareness of the issue of

childhood obesity. (CYPSE, 2017)

The European Union designed the Action Plan on Childhood Obesity 2014-2020 that aims halting the

rise in people’s ages 0-18 by 2020, requiring the involvement of many stakeholders within each

member state to develop relevant policy.

The Irish Government’s understanding of the complexity of the causes and contributors to the

obesity epidemic has culminated into the multi-sector solution strategy and an active collaboration

stance with internal and external agencies. This has provided a welcoming environment to support

and nurture results-oriented investigations, policy, and programs to bring results.

Northern Ireland Context: The government of Northern Ireland has very actively developed and

implemented programs to address the obesity and overweight epidemic and regularly evaluates

program effectiveness and modifies programs based on program outcomes and new evidence. The

Government’s acknowledgement of the complex solution required to address overweight and

obesity, due to the obesogenic environment, resulted in the current evidence-based, integrated,

cross-sector, life course policy approach.

Leading up to the current approach, the Government had addressed obesity with Fit Futures, a

nutrition and exercise approach. The 2007 UK-wide Foresight Report, Tackling Obesities: Future

Choices, suggested policy ineffectiveness due to the obesogenic environment requiring

comprehensive interventions. The report also evaluated how to address obesity over the next 40

years. The Department of Health, Social Services and Public Safety (DHSSPS) established the cross-

sectoral Obesity Prevention Steering Group (OPSG) in 2008 to promote Fit Futures and develop a life

course framework to tackle obesity that would replace Fit Futures. A whole system approach to

health became the foundation for A Fitter Future for All - Framework for Preventing and Addressing

Overweight and Obesity in Northern Ireland 2012-2022 and for Making Life Better - A Whole System

Strategic Framework for Public Health 2013 -2023, which is aimed at overall health and wellbeing

and includes tackling obesity as one of its aims. Both programs involve steering committees to

oversee progress and the Public Health Agency to facilitate implementation and delivery. (DHSSPS

2012; 2013) In 2012, various efforts had accomplished: the development of public information

campaigns and supporting materials; delivery of relevant training and support; development of

nutritional guidelines in key settings, particularly schools; community based initiatives on food and

physical activity; the introduction of the curriculum sports programme for primary schools, which

enables pupils to develop their physical literacy skills working with coaches from the GAA and IFA;

support, advice and guidance for professionals; improved support in health care settings, including

physical activity referrals; strengthened code of conduct for advertising high fat, sugar, or salt foods

to children; improved evidence and research base; and work with industry, including progress on

reformulation and improved labelling (DHSSPS).


Additional action include: Healthy Child, Healthy Future (DHSSPS, 2010), a framework for the

Universal Child Health Promotion Programme that involves the family in adopting health-enhancing

behaviours for children age 0-19; Healthy Foods for Health Outcomes (DHSSPS & DE, 2013) that

advocates a whole school approach to all food provided in schools; and the Public Health Agency’s

Obesity Awareness Week. The government also partners with regional government and external

agencies to actualize and extend its policies, including: district councils; schools; leisure centres and

healthy living centres; Regional Obesity Prevention Implementation Group (ROPIG) who developed

an obesity awareness public health campaign; Republic of Ireland Department of Public Health, who

is currently evaluating the lifetime impact of childhood overweight and obesity as measured by body

mass index (BMI), on the individual and the society in terms of financial and human costs; the Food

Standards Agency (FSA); Safefoods, who investigated the financial and healthcare costs to the local

economy as a result of obesity (2011), collaborated with IDPH, UCC, the EC, and other agencies to

provide the first estimate of the financial costs of overweight and obesity to Republic of Ireland

(2012), and the Lifetime Cost of Childhood Obesity (2017); and the Chartered Institute of

Environmental Health (CIEH) to develop a healthier eating award for catering establishments across

Northern Ireland; and The European Union, who designed the Action Plan on Childhood Obesity

2014-2020 that aims halting the rise in peoples ages 0-18 by 2020, requiring the involvement of

many stakeholders within each member state to develop relevant policy.

The Government’s policies aimed at the obesity epidemic are many and varied to address the

multiple causal factors through interventions delivered from multiple sectors of most government

organizations. The integrated environment is hospitable to actualizing these programs.

5.2 LOCAL EVIDENCE

This section should be read in conjunction with the international evidence outlined in Chapter 1.

5.2.1 Childhood Obesity / Overweight

The literature from Republic of Ireland provided 18 sets of estimates of the prevalence of

overweight and obesity. Five are considered here. They come from four sources. The first is the

Growing Up in Republic of Ireland (GUI) study, a national longitudinal survey of representative

samples of children in two cohorts, and followed every 2-3 years. The Infant Cohort of about 11,150

children was first surveyed at age 9 months in 2008-2009, while the Child Cohort of about 8,550

children was first surveyed at age 9 years in 2007-2008. The second is the third round of COSI (2012).

Estimates for adolescents come from a study on second-level students’ participation in sport (Fahey

et al. 2005), while the most recent estimates, based on data collected in 2013-2014, come from the

Fluoride and Caring for Children’s Teeth (FACCT) study (McCarthy et al., 2016a)37.

Among infants aged 9 months who took part in GUI, on the basis of the UK-WHO growth charts,

24.8% of all children were classified as overweight and 15.7% as obese (Mangan & Zgaga, 2014). Also

based on GUI, at age 9, it was reported that 22% of boys and 30% of girls were overweight or obese

(Layte & McCrory, 2011). The FACCT study indicated that 21% of children aged 4-7 years (18% of


boys and 25% of girls), and 26% of adolescents (aged 11-14 years; 23% of boys and 28% of girls)

were overweight and obese.

The COSI results for Republic of Ireland for round 3, conducted in 2012 (Heinen et al., 2014)

indicated that among children aged 7, the prevalence of overweight and obesity was higher in girls

(22%) than in boys (17%). These estimates are lower than those from the FACCT study for children

aged 4-7 years but the gender difference is consistent. At age 9, COSI estimates indicated that

prevalence was similar for girls (22%) and boys (20%).

Fahey et al. (2005) surveyed a representative sample of adolescents aged 13 to 18 in 2004 and

estimated that about one in five (19.9% of boys and 20.4% of girls) was overweight or obese. The

pattern of prevalence followed a U-shape with age, being lowest among adolescents aged 15 and 16.

5.2.2 Childhood and adulthood Impacts

Three papers from Republic of Ireland examined aspects of cardio-metabolic health. Finucane et al.

(2008a) reported that 51% of boys and 49% of girls had systolic BP in hypertensive range (> 95th

percentile for age, sex and height). Results also showed a clear and continuous increase in systolic BP

with increasing BMI, particularly in boys. This is of significance, since 93% of this sample (aged 2-18

years) was obese. Finucane et al. (2008b) reported significant associations between degree of

obesity, insulin sensitivity and markers of liver steatosis among a sample of obese children and

adolescents (mean age 15.5 years). Carolan et al. (2013) reported that obese children showed

changes in immune cell frequency, inflammatory environment, and regulation of metabolic gene

expression compared to children of healthy weight. These changes have been causally linked to

adult onset of metabolic disease and suggest a future trajectory for the development of type 2

diabetes and premature cardiovascular disease.

Three further papers examined associations between overweight/obesity and muscular-

skeletal/motor function (O’Malley et al., 2012, 2015a, 2015b). For example, in a sample of obese

children and adolescents (mean age 12.2 years), O’Malley et al. (2012) reported moderate negative

correlations were found between body composition and range of motion, flexibility, and strength.

Genu valgum deformity was moderately positively correlated to body mass index.

One source from Republic of Ireland examined psychological/emotional impacts. On the basis of a

representative sample of 9 year-olds, Layte & McCrory (2011) reported that self-perceptions relating

to popularity and physical appearance were significantly negatively related to self-perceptions of

weight. The perception of overweight was also significantly associated higher levels of emotional

and behavioural problems.

5.2.3 Inequalities

Nine studies from Republic of Ireland that examined inequalities in prevalence were retrieved. One

(Williams et al., 2013) confirmed the presence of a socio-economic gradient at age 3 years, while

another study examining weight gain from birth to three years showed that lower SES was

associated with lower birth weights and highest gains in weight; higher gains in weight were

associated with higher maternal weight gain during pregnancy and no breastfeeding (Layte &

Biesma-Blanco, 2014). Multivariate analyses of children’s BMI at age 9 (Layte & McCrory, 2011;


Keane et al., 2012; Perry et al., 2015) indicated higher prevalence of overweight and obesity among

girls, one parent families, lower occupational class, lower parental education, lower rates of physical

activity, poorer dietary quality, and, in particular, among children with overweight or obese parents.

Walsh and Cullinan (2015) conducted an analysis of the relative contributions of a range of child and

parent characteristics to the socio-economic gradient at age 9 and found that parental

characteristics accounted for a large majority of this gradient, while child-related measures were not

statistically significant. Other studies confirmed an association between socio-economic deprivation

and child overweight/obesity (Heinen et al., 2014; O’Shea et al., 2014). One study (Fahey et al.,

2005) did not find a significant association between SES and rates of overweight or obesity among

adolescents. However, Fahey et al.’s (2005) analysis was bivariate and used a rather broad measure

of SES (parental occupation, split into 9 groups by sector).

5.3 COHORT DETAILS

5.3.1 Profile of Irish Children

The table below gives the profile of children (age 0-17 years), living in Republic of Ireland in 2015.

Most (76.5%) children are healthy weight with 23.5% either obese or overweight. Percent who are

obese/overweight increases with age. In the 0-5 age group, slightly higher percent of males are

obese/overweight than females. However, this changes in 6-11 year old group and persists in the

12-17 year old group with relatively more obese/overweight females than males.

Table 5(a): Profile of Irish Children (2015)

REPUBLIC OF IRELAND

AGE SEX BMI AT AGE 18 NUMBER PERCENTAGE

0-17 YEARS PERSONS OBESE/OVERWEIGHT 281,751 23.5%

HEALTHY WEIGHT 917,569 76.5%

ALL 1,199,320 100.0%

FEMALES OBESE/OVERWEIGHT 144,292 24.6%


ALL 586,526 100.0%

MALES OBESE/OVERWEIGHT 137,459 22.4%


ALL 612,794 100.0%



ALL 431,592 100.0%



ALL 211,159 100.0%



ALL 220,433 100.0%




ALL 408,206 100.0%



ALL 200,426 100.0%



ALL 207,780 100.0%



ALL 359,522 100.0%



ALL 174,941 100.0%



ALL 184,581 100.0%

5.3.2 Details of follow-up

At the end of 2105 after 90 years of follow-up, 4.9% of the initial cohort will be alive.

Table 5(b): Details of the follow-up of Irish children (2015 – 2105)

REPUBLIC OF IRELAND

SEX BMI AT AGE 18 NUMBER ALIVE AT

BEGINNING 2015

NUMBER ALIVE AT

END 2015

PERCENTAGE ALIVE

AT END 2015

PERSONS OBESE/OVERWEIGHT 281,751 12,522 4.4%

HEALTHY WEIGHT 917,569 45,812 5.0%

TOTAL 1,199,320 58,334 4.9%

FEMALES OBESE/OVERWEIGHT 144,292 9,552 6.6%

HEALTHY WEIGHT 442,234 31,456 7.1%

TOTAL 586,526 41,008 7.0%

MALES OBESE/OVERWEIGHT 137,459 2,970 2.2%

HEALTHY WEIGHT 475,335 14,356 3.0%

TOTAL 612,794 17,326 2.8%


5.4 LIFETIME IMPACTS & COSTS IN REPUBLIC OF IRELAND

5.4.1 Adult Obesity / Overweight

Lifetime income loss

The problem

The total lifetime income loss attributable to childhood obesity/overweight is €256.1m; per person

losses males losing 50% more than females.

Table 5(c): Lifetime income losses attributable to childhood obesity/overweight in Republic of

Ireland (2015 values)

REPUBLIC OF IRELAND

SEX NUMBER OF OBESE /

OVERWEIGHT CHILDREN

IN 2015

TOTAL LIFETIME INCOME

LOSS (€m)

PER PERSON LIFETIME

INCOME LOSS (€)

MALES 137,459 €151.7m €1,104

FEMALES 144,292 €104.3m €723

PERSONS 281,751 €256.1m €909

Towards a solution

If mean childhood BMI is reduced by 1% and 5% then it is expected that lifetime income losses will

be reduced by €13.5m and €61.4m, respectively. Male savings greatly exceed female savings.

Table 5(d): Reductions in lifetime income losses associated with 1% and 5% reductions in

population mean childhood BMI in Republic of Ireland (2015 values)

REPUBLIC OF IRELAND

SEX PERCENT

REDUCTION IN

MEAN CHILDHOOD

BMI

NUMBER OF

OBESE /

OVERWEIGHT

CHILDREN IN 2015

TOTAL LIFETIME

INCOME LOSS

(€m)

REDUCTION IN

LIFETIME INCOME

LOSS

(€m)

MALES

Base (2015) 137,459 €151.7m

1% 131,372 €143.2m €8.6m

5% 112,840 €113.0m €38.8m

FEMALES Base (2015) 144,292 €104.3m


1% 138,344 €99.4m €5.0m

5% 119,588 €81.7m €22.7

PERSONS Base (2015) 281,751 €256.1m

1% 269,717 €242.5m €13.5m

5% 232,429 €194.6m €61.4m

5.4 .2. Morbidity

(Direct) Healthcare Costs

The problem

In the Republic of Ireland, the excess lifetime direct healthcare costs attributable to childhood

obesity/overweight is estimated to be €944.7m (2015 values) or € 3,353 per person; accounting for

13.6% of all lifetime healthcare costs. Whether referring to total lifetime costs or per person cost,

female costs attributable to childhood obesity/overweight were higher than male costs.

Table 5(e): Lifetime direct healthcare costs for Republic of Ireland's childhood population (2015

values)

REPUBLIC OF IRELAND

SEX BMI AT 18 YEARS NUMBER OF

CHILDREN IN 2015

LIFETIME COST PER

PERSON

(€)

TOTAL LIFETIME

COST

(€m)

MALES OBESE/OVERWEIGHT

137,459 €8,335 €1,145.8m

HEALTHY WEIGHT 475,335 €5,265 €2,502.9m

ALL 612,794 €5,954 €3,648.6m

Lifetime cost attributable to childhood

obesity/overweight

€ 3,070 €422.0m

(PAF = 11.6%)

FEMALES OBESE/OVERWEIGHT 144,292 €8,420 €1,214.9m

HEALTHY WEIGHT 442,234 €4,768 €2,108.4m

ALL 586,526 €5,666 €3,323.3m


obesity/overweight

€ 3,652 €527.0m

(PAF = 15.9%)

PERSONS OBESE/OVERWEIGHT 281,751 € 8,379 €2,360.7m

HEALTHY WEIGHT 917,569 € 5,025 €4,611.2m

ALL 1,199,320 € 5,813 €6,971.9m


obesity/overweight

€ 3,353 €944.7m

(PAF = 13.6%)


Towards a solution

Lifetime healthcare costs were greatly reduced with a 1% and 5% reduction in BMI, with €53.9m

and €245.7m reduction in costs respectively. Cost reductions were substantially greater at 5%

childhood BMI reduction.

Table 5(f): Reduction in lifetime direct healthcare costs that are associated with 1% and 5%

reductions in mean childhood BMI in Republic of Ireland (2015 values)

REPUBLIC OF IRELAND

SEX PERCENT

REDUCTION IN

MEAN

CHILDHOOD BMI

NUMBER OF OBESE /

OVERWEIGHT

CHILDREN IN 2015

TOTAL LIFETIME

HEALTH CARE

COSTS (€m)

REDUCTION IN TOTAL

LIFETIME HEALTH CARE

COSTS (€m)

MALES Base (2015) 137,459 €3,649m

1% 131,372 €3,622m €26.4m

5% 112,840 €3,525m €123.7m

FEMALES Base (2015) 144,292 €3,323m

1% 138,344 €3,296m €27.5m

5% 119,588 €3,201m €122.0m

PERSONS Base (2015) 281,751 €6,972m

1% 269,717 €6,918m €53.9m

5% 232,429 €6,726m €245.7m



The problem

Over a lifetime, the excess productivity losses due to absenteeism attributed to childhood

obesity/overweight is estimated to be €521.9m. Female productivity losses (€299.6m) were larger

than male losses (€223.5m).

Table 5(g): Lifetime productivity losses due to absenteeism for Republic of Ireland's childhood

population (2015 values)

REPUBLIC OF IRELAND

SEX BMI AT 18 YEARS NUMBER OF CHILDREN IN

2015

PER PERSON

LOSS (€)

TOTAL LIFETIME

LOSSES (€m)

MALES OBESE/OVERWEIGHT 137,459 €3,011 €413.9m

HEALTHY WEIGHT 475,335 €1,386 €658.6m

ALL 612,794 €1,750 €1,072.5m

Lifetime loss attributable to childhood

obesity/overweight

€1,626 €223.5m

(PAF = 20.8%)

FEMALES OBESE/OVERWEIGHT

144,292 €3,326 €479.9m

HEALTHY WEIGHT 442,234 €1,250 €552.6m

ALL 586,526 €1,760 €1,032.5m


obesity/overweight

€2,076 €299.6m

(PAF = 29.0%)

PERSONS OBESE/OVERWEIGHT

281,751 €3,172 €893.8m

HEALTHY WEIGHT 917,569 €1,320 €1,211.2m

ALL 1,199,320 €1,755 €2,105.0m


obesity/overweight

€1,852 €521.9m

(PAF = 24.8%)


Towards a solution

As mean childhood BMI is reduced by 1% and 5%, there is expected to be a €33.5m and a €149.0m

reduction in lifetime productivity losses due to absenteeism, respectively. Reductions in productivity

losses were similar for males and females.

Table 5(h): Reductions in lifetime productivity losses due to absenteeism that are associated with

1% and 5% reductions in mean childhood BMI in Republic of Ireland (2015 values)

REPUBLIC OF IRELAND

SEX PERCENT

REDUCTION IN

MEAN CHILDHOOD

BMI

NUMBER OF OBESE /

OVERWEIGHT

CHILDREN IN 2015

TOTAL LIFETIME

PRODUCTIVITY

LOSSES

(ABSENTEEISM) (€m)

REDUCTION IN

LIFETIME

PRODUCTIVITY

LOSSES

(ABSENTEEISM)

(€m)

MALES Base (2015) 137,459 €1,073m

1% 131,372 €1,056m €16.1m

5% 112,840 €1,002m €70.4m

FEMALES Base (2015) 144,292 €1,032m

1% 138,344 €1,015m €17.4m

5% 119,588 €954m €78.6m

PERSONS Base (2015) 281,751 €2,105m

1% 269,717 €2,072m €33.5m

5% 232,429 €1,956m €149.0m


5.4.3 Mortality

Premature mortality

The problem

The excess risk of premature death that is attributed to childhood obesity/overweight in the

Republic of Ireland is 19.1% in males and 22.7% in females. This equate to an excess of 26,202

premature male deaths and 32,796 excess premature female deaths attributable to childhood

obesity/overweight.

Table 5(i): Premature deaths amongst Republic of Ireland’s childhood population

REPUBLIC OF IRELAND

SEX BMI AT 18 YEARS

NUMBER OF

CHILDREN IN

2015

TOTAL NUMBER OF

PREMATURE DEATHS

LIFETIME RISK OF

PREMATURE DEATH (%)

MALES

OBESE/OVERWEIGHT

137,459 83,587 60.8%

HEALTHY WEIGHT 475,335 198,438 41.7%

ALL 612,794 282,026 46.0%

Risk attributable to childhood obesity/overweight 19.1%

Number attributable to childhood

obesity/overweight

26,202

(PAF = 9.3%)

FEMALES

OBESE/OVERWEIGHT

144,292 85,128 59.0%

HEALTHY WEIGHT 442,234 172,471 39.0%

ALL 586,526 257,599 43.9%


Number attributable to childhood 28,854


obesity/overweight (PAF = 11.2%)

For males and females, amongst those who were healthy weight and obese/overweight as children,

the risk of premature death increases with age. At all ages, the risk is higher amongst males. In both

males and females, and at all ages the risk is higher amongst individuals who were obese/overweight

as a child.

For calculation purposes, all children in the 0-5 years age group in 2015 are assumed to be aged 2 ½

years in 2015

Towards a solution

Table 5(j): Reductions in premature death that are associated with 1% and 5% reductions in mean

childhood BMIs in Republic of Ireland


SEX

PERCENT REDUCTIONS

IN MEAN CHILDHOOD

BMI

TOTAL NUMBER OF

CHILDREN IN 2015

TOTAL NUMBER

OF PREMATURE

DEATHS

REDUCTION IN NUMBER

OF PREMATURE DEATHS

MALES

Base (2015) 612,794 282,026

1% 612,839 280,754 1,272

5% 612,721 276,078 5,948

FEMALES

Base (2015) 586,526 257,599

1% 586,481 256,916 683

5% 586,599 254,278 3,321

PERSONS

Base (2015) 1,199,320 539,625

1% 1,199,320 537,669 1,955

5% 1,199,320 530,356 9,269


The problem

An excess of 46,737 years of life lost (YLL) are attributable to childhood obesity/overweight;


26,379.1 in males and 21,170.1 in females

Table 5(k): Years of Life Lost (YLL) over the lifetime of Republic of Ireland’s childhood population4

REPUBLIC OF IRELAND


CHILDREN IN 2015 YLL PER PERSON

TOTAL NUMBER OF

YLL

MALES

OBESE/OVERWEIGHT 137,459 0.57 78,881.6

HEALTHY WEIGHT 475,335 0.38 181,554.1

ALL 612,794 0.42 260,435.7

YLL per person attributable to childhood obesity/overweight

0.2

Total YLL years attributable to childhood

obesity/overweight

26,379.1

(PAF = 10.1%)

FEMALES


HEALTHY WEIGHT 442,234 0.29 126,662.0

ALL 586,526 0.32 189,159.4

YLL per person attributable to childhood obesity/overweight 0.1


obesity/overweight

21,170.1

(PAF = 11.2%)

PERSONS


HEALTHY WEIGHT 917,569 0.34 308,216.1

ALL 1,199,320 0.37 449,595.1

YLL per person attributable to childhood obesity/overweight

0.2


obesity/overweight

46,737.3

(PAF = 10.4%)

Towards a solution

A 1% and 5% reduction in childhood BMI reduces the total number of premature deaths by 1,875

and 7,180. There are larger reductions in premature deaths for males than for females.

4 Discounting has been applied to these figures


Table 5(l): Reduction in Years of Life Lost (YLL) associated with 1% and 5% reductions in mean

childhood BMI in Republic of Ireland

REPUBLIC OF IRELAND

SEX PERCENT REDUCTION IN

MEAN CHILDHOOD BMI

TOTAL NUMBER OF

OBESE / OVERWEIGHT

CHILDREN IN 2015

TOTAL NUMBER OF

YEARS OF LIFE LOST

TOTAL REDUCTION

IN YEARS OF LIFE

LOST

MALES

Base (2015) 137,459 260,455

1% 131,372 259,446 1,010

5% 112,840 256,050 4,406

FEMALES

Base (2015) 144,292 189,159

1% 138,344 188,294 866

5% 119,588 186,385 2,775

PERSONS

Base (2015) 281,751 449,615

1% 269,717 447,739 1,875

5% 232,429 442,434 7,180


The problem

Total excess lifetime productivity loss attributable to childhood obesity/overweight is estimated to

be €2,975.4m, with excess male losses more than double female losses.


Table 5(m): Lifetime productivity losses due to premature mortality amongst Republic of Ireland’s

childhood population (2015 values)

REPUBLIC OF IRELAND


CHILDREN IN

2015

LIFETIME LOSS

PER PERSON (€)

TOTAL LIFETIME COST

(€m)

MALES OBESE/OVERWEIGHT

137,459 € 29,098 €4,000m

HEALTHY WEIGHT 475,335 € 13,783 €6,551m

ALL 612,794 € 17,218 €10,551m

Lifetime loss per person attributable

to childhood obesity/overweight

€15,316

Total lifetime loss attributable


€2,105.3m

(PAF = 20.0%)

FEMALES OBESE/OVERWEIGHT 144,292 € 11,225 €1,620m

HEALTHY WEIGHT 442,234 € 5,984 €2,646m

ALL 586,526 € 7,273 €4,266m



€5,242



€756.4m

(PAF = 17.7%)

PERSONS OBESE/OVERWEIGHT 281,751 € 19,945 €5,620m

HEALTHY WEIGHT 917,569 € 10,024 €9,198m

ALL 1,199,320 € 12,355 €14,817m



€9,921



€2,795.4m

(PAF = 18.9%)

Towards a solution

With a 1% and 5% reduction in mean childhood BMI, reductions in excess productivity losses due to

premature mortality are estimated to be €169.0m and €1671.0m respectively. Male reductions in

productivity losses are estimated to be about three times greater than those for females.


Table 5(n): Reductions in lifetime productivity losses due to premature death that are associated

with 1% and 5% reductions in mean childhood BMIs in Republic of Ireland (2015 values)

REPUBLIC OF IRELAND

SEX PERCENT REDUCTION

IN MEAN CHILDHOOD

BMI

TOTAL NUMBER OF

OBESE / OVERWEIGHT

CHILDREN IN 2015

TOTAL

PRODUCTIVITY

LOSSES (€m)

TOTAL REDUCTION

IN PRODUCTIVITY

LOSSES (€m)

MALES Base (2015) 137,459 €10,551.3m

1% 131,372 €10,425.8m €125.5m

5% 112,840 €10,034.6m €516.7m

FEMALES Base (2015) 144,292 €4,265.9m

1% 138,344 €4,222.3m €43.5m

5% 119,588 €4,111.6m €154.3m

PERSONS Base (2015) 281,751 €14,817.2m

1% 269,717 €14,648.2m €169.0m

5% 232,429 €14,146.2m €671.0m

5.4.4 Republic of Ireland summary

Childhood obesity/overweight affects citizens, the health and social care systems and (most

significantly) the economics of EU member states. These estimates are likely to be underestimates

because data limitations restricted what impacts and costs could be included.

All monies are in 2015 values. And future costs are discounted by an annual discount rate of 5% per

annum.

Impacts and costs (2015 values) attributable to childhood obesity/overweight in

the Republic of Ireland Total financial costs (€4,518.1M) account for 1.6% of GDP in 2015 Lifetime financial cost is €16,036 per person


Direct healthcare costs (€944.7M) account for 4.8% of public health expenditure in 2015. Premature deaths (55,056) account for 1 in 10 of all premature deaths Societal costs are larger than direct healthcare costs Premature death is a larger cause of productivity loss than absenteeism (€2,795.4M vs €521.9M) Gender differences:

Male productivity losses due to premature mortality and lifetime income losses are higher

Female direct healthcare costs and productivity losses due to absenteeism are higher

Large savings (€1,127M) with modest changes in mean childhood BMI

Figure 5(c): Lifetime impacts and costs attributable to childhood obesity/overweight in the

Republic of Ireland

IRISH AND NORTHERN IRISH REFERENCES

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A., Hayes, C., O’Dwyer, U., Eldin, N., & Kelleher, C. (2014). The Childhood Obesity Surveillance Initiative (COSI)

in the Republic of Republic of Ireland: Findings from 2008, 2010 and 2012. Dublin: Health Service Executive and

Department of Health.

Keane, E., Layte, R., Harrington, J., Kearney, P.M., & Perry, I.J. (2012). "Measured parental weight status and

familial socio-economic status correlates with childhood overweight and obesity at age 9." PloS One 7(8):

e43503.

Layte, R., & Biesma-Blanco, R. (2014). “Social class differences in weight gain from birth to three years.” Paper

presented at the Growing Up in Republic of Ireland Research Conference 2014: Dublin, November.

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literature. Report commissioned by safefood Republic of Ireland. Cork: safefood.

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in infants.” Paper presented at the Growing Up in Republic of Ireland Research Conference 2014: Dublin,

November.

O'Malley, G., Hussey, J., & Roche, E. (2012). "A pilot study to profile the lower limb musculoskeletal health in

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6. LIFETIME IMPACTS AND COSTS OF CHILDHOOD OBESITY IN

NORTHERN IRELAND (NIR)

6.1 COHORT DETAILS

6.1.1 Profile of Northern Irish children

The table below gives the profile of children (age 0-17 years), living in Northern Ireland in 2015.

Most (74.2%) children are healthy weight with 25.8% either obese or overweight. Percent who are

obese/overweight increases with age. In the 0-5 years age group, 6-11 years age group 12-17 years

age group, there are higher percentages of females who are obese/overweight than males.

However, this difference reduces with age.

Table 6(a): Profile of Northern Irish Children

NORTHEN IRELAND

AGE SEX BMI AT AGE 18 NUMBER PERCENTAGE

ALL PERSONS OBESE/OVERWEIGHT 111,875 25.8%


TOTAL 432,791 100.0%



TOTAL 210,716 100.0%



TOTAL 222,075 100.0%



TOTAL 150,187 100.0%



TOTAL 73,429 100.0%



TOTAL 76,758 100.0%



TOTAL 142,145 100.0%




TOTAL 69,071 100.0%



TOTAL 73,074 100.0%



TOTAL 140,459 100.0%



TOTAL 68,217 100.0%



TOTAL 72,243 100.0%

6.1.2 Details of follow-up

At the end of 2105 after 90 years of follow-up, 6.1% of the initial cohort will be alive.

Table 6(b): Details of the follow-up of Northern Irish children (2015 – 2105)

NORTHERN IRELAND

SEX BMI AT AGE 18 NUMBER ALIVE AT

BEGINNING 2015

NUMBER ALIVE AT

END 2015

PERCENTAGE ALIVE

AT END 2015

Persons Obese/Overweight 111,875 9,298 8.3%

Healthy weight 320,916 16,986 5.3%

Total 432,791 26,283 6.1%

Females Obese/Overweight 60,735 6,033 9.9%

Healthy weight 149,981 10,229 6.8%

Total 210,716 16,262 7.7%

Males Obese/Overweight 51,140 3,265 6.4%

Healthy weight 170,935 6,756 4.0%

Total 222,075 10,021 4.5%


6.2 LIFETIME IMPACTS & COSTS IN NORTHERN IRELAND

6.2.1. Adult Obesity / Overweight

Lifetime income loss

The problem

In Northern Ireland the total lifetime income losses attributable to childhood obesity/overweight is

estimated to be €116.3m, with total male losses being about 50% higher than total female losses.

Table 6(c): Lifetime income losses attributable to childhood obesity/ overweight in Northern

Ireland (2015 values)

NORTHERN IRELAND

SEX NUMBER OF OBESE / OVERWEIGHT

CHILDREN IN 2015

TOTAL LIFETIME INCOME

LOSS (€m)

PER PERSON LIFETIME

INCOME LOSS (€)

MALES 51,140 €69.8m €1,365

FEMALES 60,735 €46.4m €764

TOTAL 111,875 €116.3m €1,039

Towards a solution

If mean childhood BMI is reduced by 1% and 5% in Northern Ireland, it is estimated that total

lifetime income loss attributable to childhood obesity would be reduced by €4.0m and a €20.1m,

respectively. Total reductions for males are expected to be about 50% higher than reductions for

females.

Table 6(d): Reductions in lifetime income losses that is associated with 1% and 5% reductions in

population mean childhood BMI in Northern Ireland (2015 values)

NORTHERN IRELAND

SEX PERCENT REDUCTION IN

MEAN CHILDHOOD BMI

NUMBER OF OBESE /

OVERWEIGHT

CHILDREN IN 2015

TOTAL LIFETIME

INCOME LOSS (€m)

REDUCTION IN

LIFETIME INCOME

LOSS (€m)

MALES

Base (2015) 51,140 €69.8m

1% 49,218 €67.3m €2.6m

5% 43,168 €57.2m €12.7m

FEMALES Base (2015) 60,735 €46.4m


1% 58,789 €45.0m €1.5m

5% 51,842 €39.1m €7.4m

PERSONS

Base (2015) 111,875 €116.3m

1% 108,007 €112.3m €4.0m

5% 95,010 €96.2m €20.1m

6.2.2. Morbidity

(Direct) Healthcare costs

The problem

The total excess lifetime direct healthcare costs attributable to childhood obesity/overweight in

Northern Ireland is estimated to be €679.6m. The excesses for males and females were similar.

Table 6(e): Lifetime direct healthcare costs for Northern Ireland's childhood population (2015

values)

NORTHERN IRELAND


CHILDREN IN 2015

COST PER

PERSON TOTAL COST

(€) (€m)

MALES

OBESE/OVERWEIGHT 51,140 €15,084 €771.4m

HEALTHY WEIGHT 170,935 €8,537 €1,459.2m

ALL 222,075 €10,044 €2,230.6m


obesity/overweight € 6,547

€334.8m

(PAF = 15.0%)

FEMALES


HEALTHY WEIGHT 149,981 €9,452 €1,417.6m

ALL 210,716 €11,051 €2,328.7m



€337.0m

(PAF = 14.5%)

PERSONS

OBESE/OVERWEIGHT 111,875 € 15,039 €1,682.5m

HEALTHY WEIGHT 320,916 € 8,964 €2,876.8m

ALL 432,791 € 10,535 €4,559.3m



€679.6m

(PAF = 14.9%)


Towards a solution

Total excess lifetime healthcare costs in Northern Ireland are expected to be reduced by €22.2m

and €100.1m with 1% and 5% reductions in mean childhood BMI, respectively. Male and female

reductions are similar and total direct healthcare cost reductions were substantially greater at 5%

childhood BMI reduction.

Table 6(f): Reduction in direct lifetime healthcare costs that are associated with 1% and 5%

reductions in mean childhood BMI in Northern Ireland (2015 values)

NORTHEN REPUBLIC OF IRELAND

SEX

PERCENT

REDUCTION IN

MEAN CHILDHOOD

BMI

NUMBER OF OBESE /

OVERWEIGHT

CHILDREN IN 2015

TOTAL LIFETIME

HEALTH CARE

COSTS (€m)

REDUCTION IN

TOTAL LIFETIME

HEALTH CARE

COSTS (€m)

MALES

Base (2015) 51,140 €2,231m

1% 49,218 €2,219m €11.2m

5% 43,168 €2,179m €51.7m

FEMALES

Base (2015) 60,735 €2,329m

1% 58,789 €2,318m €11.0m

5% 51,842 €2,280m €48.4m

TOTAL

Base (2015) 111,875 €4,559m

1% 108,007 €4,537m €22.2m

5% 95,010 €4,459m €100.1m



The problem

The lifetime excess productivity losses due to absenteeism that are attributed to childhood

obesity/overweight was €130.6m. Male excess productivity losses were slightly less than those for

females.

Table 6(g): Lifetime productivity losses due to absenteeism amongst Northern Ireland's childhood

population (2015 values)

NORTHERN IRELAND


CHILDREN IN 2015

PER PERSON LOSS

(€)

TOTAL LIFETIME LOSSES

(€m)

MALES


HEALTHY WEIGHT 170,935 €1,443 €246.7m

ALL 222,075 €1,710 €379.7m


obesity/overweight €1,157

€59.2m

(PAF = 15.6%)

FEMALES


HEALTHY WEIGHT 149,981 €1,794 €269.1m

ALL 210,716 €2,119 €446.4m



€68.4m

(PAF = 15.3%)

PERSONS


HEALTHY WEIGHT 320,916 €1,607 €515.8m

ALL 432,791 €1,909 €826.2m



€130.6m

(PAF = 15.8%)


Towards a solution

If mean childhood BMI in Northern Ireland is reduced by 1% and 5%, it is estimated that lifetime

productivity losses attributable to childhood obesity will be reduced by €4.4m and €20.7m

respectively. Reductions in losses were similar for males and females.

Table 6(h): Reductions in lifetime productivity losses due to absenteeism that are associated with

1% and 5% reductions in mean childhood BMI in Northern Ireland (2015 values)

NORTHERN IRELAND

SEX

PERCENT

REDUCTION IN

MEAN

CHILDHOOD BMI

NUMBER OF OBESE /

OVERWEIGHT

CHILDREN IN 2015

TOTAL LIFETIME

PRODUCTIVITY LOSSES


REDUCTION IN LIFETIME

PRODUCTIVITY LOSSES


MALES

Base (2015) 51,140 €380m

1% 49,218 €378m €2.1m

5% 43,168 €369m €10.4m

FEMALES

Base (2015) 60,735 €446m

1% 58,789 €444m €2.2m

5% 51,842 €436m €10.3m

TOTAL

Base (2015) 111,875 €826m

1% 108,007 €822m €4.4m

5% 95,010 €805m €20.7m


6.2.3 Mortality

Premature mortality

The problem

The excess risk of premature death that is attributed to childhood obesity/overweight in Northern

Ireland is 29.9% in males and 25.1% in females. This equates to an excess of 15,279 premature male

deaths and 15,234 excess premature female deaths.

Table 6(i): Premature deaths amongst Northern Ireland’s childhood population

NORTHEN REPUBLIC OF IRELAND


CHILDREN IN 2015

TOTAL NUMBER OF

PREMATURE

DEATHS

LIFETIME RISK OF

PREMATURE DEATH (%)

MALES

OBESE/OVERWEIGHT 51,140 28,701 56.1%

HEALTHY WEIGHT 170,935 44,864 26.2%

ALL 222,075 73,565 33.1%

Risk attributable to childhood

obesity/overweight 29.9%


obesity/overweight

15,279

(PAF = 20.8%)

FEMALES

OBESE/OVERWEIGHT 60,735 32,942 54.2%

HEALTHY WEIGHT 149,981 43,727 29.2%

ALL 210,716 76,669 36.4%



obesity/overweight

15,234

(PAF = 19.9%)


For males and females, amongst those who were healthy weight and obese/overweight as children,

the risk of premature death increases with age. At all ages, the risk is higher amongst males. In both

males and females, and at all ages the risk is higher amongst individuals who were obese/overweight

as a child.

The risk of premature death amongst Northern Ireland’s 0-5 year old children as they age

Towards a solution

A 1% and 5% reduction in mean childhood BMI in Northern Ireland is estimated to reduce the total

number of premature deaths by 563 and 2,519 respectively, with substantially less deaths due to a

5% reduction in BMI.

Table 6(j): Reductions in premature death that are associated with 1% and 5% reductions in mean

childhood BMIs in Northern Ireland

NORTHERN IRELAND

SEX

PERCENT

REDUCTIONS IN

MEAN BMI

TOTAL NUMBER OF

CHILDREN IN 2015

TOTAL NUMBER OF

PREMATURE DEATHS

REDUCTION IN

NUMBER OF

PREMATURE DEATHS

MALES

Base (2015) 222,075 73,565

1% 222,006 73,296 269

5% 222,040 72,297 1,267

FEMALES Base (2015) 210,716 76,669


1% 210,785 76,375 295

5% 210,751 75,418 1,252

PERSONS

Base (2015) 432,791 150,234

1% 432,791 149,671 563

5% 432,791 147,715 2,519


The problem

An excess of 59,618.5 years of Life Lost (YLL) were attributable to childhood obesity/overweight .The

total excess is greater amongst males than it is amongst females.

Table 6(k): Years of life lost (YLL) over the lifetime of Northern Ireland’s childhood population

NORTHERN IRELAND

SEX BMI AT 18 YEARS

NUMBER OF

CHILDREN IN

2015

YLL PER PERSON TOTAL NUMBER OF

YLL

MALES


HEALTHY WEIGHT 170,935 0.59 101,169.8

ALL 222,075 0.74 165,165.5

YLL per person attributable to childhood obesity/overweight 0.7

Total YLL attributable to childhood

obesity/overweight

33,727.5

(PAF = 20.4%)

FEMALES


HEALTHY WEIGHT 149,981 0.54 80,417.5

ALL 210,716 0.66 139,344.1

YLL per person years attributable to childhood obesity/overweight 0.4


obesity/overweight

26,361.4

(PAF = 18.9%)

PERSONS


HEALTHY WEIGHT 320,916 0.57 181,587.4

ALL 432,791 0.70 304,509.6

YLL per person years attributable to childhood obesity/overweight 0.5



obesity/overweight

59,618.5

(PAF = 19.6%)

Towards a solution

A 1% and 5% reduction in mean childhood BMI is expected to reduce total excess YLL by 963 years

and 3,869 years respectively, with many more lives saved with a 5% BMI reduction.

Table 6(l): Reduction in years of life lost (YLL) due to premature mortality that is associated with

1% and 5% reductions in mean childhood BMIs in Northern Ireland

SEX

PERCENT

REDUCTIONS IN

MEAN CHILDHOOD

BMI

TOTAL NUMBER OF

OBESE / OVERWEIGHT

CHILDREN IN 2015

TOTAL NUMBER OF

YEARS OF LIFE

LOST

TOTAL REDUCTION

IN YEARS OF LIFE

LOST

MALES

Base (2015) 51,140 165,172

1% 49,218 164,552 620

5% 43,168 163,123 2,049

FEMALES

Base (2015) 60,735 139,344

1% 58,789 139,001 343

5% 51,842 137,524 1,820

PERSONS

Base (2015) 111,875 304,516

1% 108,007 303,553 963

5% 95,010 300,647 3,869


The problem

Total lifetime productivity loss due to premature death that is attributable to childhood

obesity/overweight is estimated to be €1,607.3m in Northern Ireland. The total losses amongst

males (€1,248.7m) is almost treble the total losses amongst females (€415.1m)


Table: 6(m) Lifetime productivity losses due to premature mortality amongst Northern Ireland’s

childhood population (2015 values)

NORTHERN IRELAND


CHILDREN IN 2015

LIFETIME LOSS PER

PERSON (€)

TOTAL LIFETIME

LOSS (€m)

MALES

OBESE/OVERWEIGHT 51,140 € 36,736 €1,879m

HEALTHY WEIGHT 170,935 € 12,319 €2,106m

ALL 222,075 € 17,942 €3,984m

Lifetime loss per person cost attributable to childhood


Total lifetime loss attributable to childhood

obesity/overweight

€1,248.7m

(PAF = 31.3%)

FEMALES

OBESE/OVERWEIGHT 60,735 € 12,461 €757m

HEALTHY WEIGHT 149,981 € 5,625 €844m

ALL 210,716 € 7,595 €1,600m




obesity/overweight

€415.1m

(PAF = 25.9%)

PERSONS

OBESE/OVERWEIGHT 111,875 € 23,557 €2,636m

HEALTHY WEIGHT 320,916 € 9,191 €2,949m

ALL 432,791 € 12,904 €5,585m


obesity/overweight €14,367m


obesity/overweight

€1,607.3m

(PAF = 28.8%)

Towards a solution

With a 1% and 5% reduction in mean childhood BMI, excess productivity losses due to premature

mortality are expected to reduce were substantially by €65.2m and €255.9m respectively. Male

reductions in total losses were around four times the reduction in total losses amongst females.

Table 6(n): Reduced productivity losses due to premature mortality that are associated with 1%

and 5% reductions in mean childhood BMIs in Northern Ireland (2015 values)


NORTHERN IRELAND

SEX PERCENT

REDUCTIONS IN

MEAN CHILDHOOD

BMI

TOTAL NUMBER OF

OBESE / OVERWEIGHT

CHILDREN

TOTAL

PRODUCTIVITY

LOSSES (€m)

TOTAL REDUCTION

IN PRODUCTIVITY

LOSSES (€)

MALES

Base (2015) 51,140 €3,984.4m

1% 49,218 €3,931.8m €52.7m

5% 43,168 €3,784.6m €199.8m

FEMALES

Base (2015) 60,735 €1,600.5m

1% 58,789 €1,587.9m €12.6m

5% 51,842 €1,544.4m €56.1m

PERSONS

Base (2015) 111,875 €5,584.9m

1% 108,007 €5,519.7m €65.2m

5% 95,010 €5,329.0m €255.9m

6.2.4 Northern Ireland summary

All monies are in 2015 values. Future costs are discounted by an annual discount rate of 5% per

annum.

Impacts and costs (2015 values) attributable to childhood obesity/overweight in

Northern Ireland Premature deaths (30,513) Lifetime financial costs (€2,533.7M) Lifetime financial costs are €22,647 per person Lifetime direct healthcare costs (€679.6M) Societal costs (€1,854.2M) are much larger than direct healthcare costs Premature death is a larger cause of productivity loss than absenteeism (€1,607.3M vs €130.6M) Gender differences:

Productivity losses due to premature mortality and lifetime income losses are higher amongst males

Direct healthcare costs and productivity losses due to absenteeism are higher amongst females


Large savings (€396.2M) with modest changes (5%) in mean childhood BMI5

Figure 6(c): Lifetime impacts & costs attributable to childhood obesity/overweight in Northern

Ireland

6.2.5 Comparison between the Republic of Ireland and Northern Ireland

As we have already noted, there are similarities in the broad features of the excess burden of

childhood obesity/overweight in the Republic of Ireland and Northern Ireland:

Lifetime total societal costs accounted for the majority of the lifetime total costs; accounting

for 79.1% of the total costs in Republic of Ireland and 73.2% in Northern Ireland.

Lifetime productivity losses due to premature mortality were the greatest single cost item

accounting for 61.9% and 63.4%, respectively, of total lifetime costs in Republic of Ireland

and Northern Ireland.

The total lifetime cost (and per person costs) attributed to childhood obesity/overweight is

much higher for males than it is for females.

Males incur higher total lifetime income losses and productivity losses due to premature

mortality while females incur higher lifetime healthcare costs and productivity losses due to

absenteeism.

5 All monies in 2015 values. Future costs discounted by annual discount rate of 5% per annum.

€0

€500

€1 000

€1 500

€2 000

€2 500

€3 000

Male Female Persons

Mill

ion

s

PRODUCTIVITY LOSS (ABSENTEEISM

PRODUCTIVITY LOSS (PREMATUREMORTALITY)

LIFETIME INCOME LOSS

DIRECT HEALTH CARE


These differences may be explained in part by higher risk of premature mortality and higher average

incomes amongst males and the greater tendency to seek care and respond to care amongst

females.

Table 6(o): Percentage of total morbidity-related and mortality-related burden attributable to

childhood obesity / overweight (PAFs)

PAFs

IRL NIR

M F P M F P

Direct Healthcare Cost 11.6% 15.9% 13.6% 15.0% 14.5% 14.9%

Productivity Losses (Absenteeism)

29.8% 29.0% 24.8% 15.6% 15.3% 15.8%

Premature Deaths 9.3% 11.2% 20.8% 19.9%

Productivity Losses (Premature Death)

20.0% 17.0% 18.9% 31.3% 25.9% 28.8%

However; the comparison of the Republic of Ireland and Northern Ireland revealed that the excess

burden of childhood obesity/overweight is experienced differently by males and females in the two

countries:

In the Republic of Ireland, childhood obesity/overweight accounted for relatively more of

the morbidity-related burden amongst males than amongst females. In Northern Ireland, no

such gender difference was observed.

In the Republic of Ireland, but not Northern Ireland, childhood obesity/overweight

accounted for relatively more premature mortality amongst females than amongst males.

In both the Republic of Ireland and Northern Ireland, childhood obesity/overweight

accounted for relatively more of the productivity losses due to premature mortality amongst

males than amongst females.

Moreover; the comparison of the Republic of Ireland and Northern Ireland also emphasised the

importance of local context:

Direct health care costs are relatively higher in Northern Ireland

Indirect (societal) costs are relatively higher in the Republic of Ireland


These differences may be explained in part by the fact that Northern Ireland operates a universal

health care system (NHS in the UK) while a two-tiered public – private health care system operates

in the Republic of Ireland.


7. LIMITATIONS AND RECOMMENDATIONS

7.1 LIMITATIONS

This section lists the limitations of the JANPA costing model and enhancements. Many of these

limitations arise out of the availability and quality of data and are shared by all costing models

LIMITATIONS REMEDIES

Population

The burden of childhood obesity is

unequally shared across our community.

Work programme to incorporate racial, ethnicity

and migrant /asylum seeker status into the

costing model.

Work programme to incorporate differences

between individuals in care and those not in care

into the costing model.

Linking with the EU commissioned “Health Equity

Pilot Project” (HEPP) to incorporate an equity

dimension to the costing model

BMI

Future age-sex specific BMI distributions of

today’s children may not follow historical

trends

Improvement in obesity surveillance (particularly

early childhood years, adolescence and later

adult years) across all sex, age and BMI groups

Strong population trends in some countries

towards increased prevalence of morbid and

severe obesity with their more severe

consequences

Incorporate sub-division of obese category into

morbidly obese and severely obese sub-

categories

Obesity and overweight are not

distinguished in many studies because of

lack of requisite data

Incorporate separation of obese and overweight

categories

The measurement of overweight and

obesity in epidemiological studies of RRs

may not match the BMI categorisations used

in the JANPA costing model. For example,

measure of central adiposity or the use of


different reference curves for BMI

Different BMI percentile cut-offs are used

for individual children in clinical settings (for

example, >98th percentile with UK90) and in

population studies (for example, >95th

centile with UK90).

Disease data

Improvements in surveillance of obesity-related

diseases (particularly incidence and survival)

across sex, age and BMI groups

Healthcare Costs

Improvements in collection of healthcare costs

data (particularly primary care and drug

prescription costs) across sex, age and BMI

groups

The international literature shows that the

cost of treatment for conditions not related

to obesity/overweight can be higher

amongst obese/overweight patients than

amongst patients with healthy weight

(Hamilton et al (2016) – in preparation).

This means that excess (direct) healthcare

cost may be underestimated.

No other specific diseases unrelated to

overweight and obesity are considered

Most studies only consider direct healthcare

costs making comparisons across countries

with different healthcare and social care

model difficult

Incorporate indirect healthcare costs (out of

pocket costs incurred by patients, their families

or communities) into the model

Specialist services for morbidly obese

children or adults is not included.

Incorporate specialist services for morbidly obese

children or adults into the model (ECOG and

EASO clinical networks)

Societal Costs

Carers of morbidly obese individuals and

carers of individuals who develop obesity-

related diseases experience reduced lifetime

earnings

Incorporate these associated secondary costs

Pension costs are not included in the

modelling. Ignoring socio-economic

differences, these will tend to higher

amongst individuals who are of healthy


weight than amongst individuals who are

obese or overweight because of premature

mortality in the latter.

Incorporate adult productivity losses due to:

Reduced productivity at work

(presenteeism)

Short term absences

Early retirement

Statistical issues

The uncertainty limits that accompany the

Model Outputs incorporate variation

associated from the simulation (stochastic

or aleatoric uncertainty) and is derived from

the various probabilistic distributions that

guide the simulations. However, variation

associated with the Collated Data is not

included. Because this source of variation is

expected to be very much larger than that

associated with the simulations, it is

impossible to attach meaningful uncertainty

intervals to the final Model Outputs. These

can probably only be derived from large

scale sensitivity analyses.

Sensitivity analyses

In-depth assessment of validity was not

possible

Incorporate comprehensive sensitivity audit

addressing:

Method of constructing lifetime BMI

trajectories

Definitions of childhood obesity - being

“obese/overweight” as a child

Bottom-up approaches that may use

different measures of adiposity

(measurement vs self-reports)

Incorporate comparison of model-based lifetime

risk of obesity-related diseases and research-

based risks


7.2 RECOMMENDATIONS

7.2.1 Modelling Methodology

We recommend that:

An independent scientific review of the JANPA costing model and how it was developed

should be undertaken

The detailed suggestions for enhancements of the modelling methodology that are outlined

in Chapter 7 should be incorporated into the future development of the model.

Stand-alone dedicated software, provided as open source code, to fully implement the

JANPA costing model should be developed and available to other researchers for

independent scrutiny and audit

Detailed sensitivity audit and validation of the JANPA costing model should be undertaken

once the open source code is available . This should include calculation of uncertainty

intervals and the validity of critical assumptions and inputs

7.2.2 Data and Research Gaps

The validity and reliability of final results depend on the data inputs. The availability and quality of

data across the countries varied greatly. We recommend that work continues to improve the co-

ordination, and quality of the national and pan-European health information systems, particularly:

Obesity surveillance (particularly early years, later years and adolescence)

Surveillance of obesity-related diseases (particularly incidence and survival)

Healthcare costs (particularly primary care and pharmaceutical)

Analytical methods for using data

The biggest gap in the impacts and costs included in the JANPA costing model relates to the

psychosocial consequences of childhood obesity and the inability to undertake a sensitivity analysis

of the model. We recommend that the JANPA costing model be refined by incorporating research

into the psychosocial impacts of childhood obesity and their implications for human capital and the

economy (effects on school attendance, educational performance and subsequent employability,

position in the labour market and productivity).

In addition we recommend that:

A comprehensive review of multi-morbidities and their effects on the JANPA costing

model’s excess and effect metrics should be undertaken and a work programme to

incorporate its finding into the model should be developed

Support continues for longitudinal studies with long term follow-up


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