State Example: Translating Infant Mortality Toolkit Content• This slide set, provided by Elizabeth J Conrey, PhD, RD, is an example of

how the content from the Infant Mortality Toolkit can be translated for training public health practitioners

• The slides are a subset from the course titled: The Epidemiology of Maternal and Infant Health for State and Local Practitioners, given at the Ohio State University Summer Program in Population Health

• Examples provided are from the Ohio Department of Health

State Example: Translating Infant Mortality Toolkit Content

Content from Day 1 - Toolkit Chapters Addressed: • Why Focus on Infant Mortality

• Using U.S. data, the slides outline trends, racial/ethnic disparities, and geographic disparities in infant mortality

• For Those Just Starting - Standing on Common Ground: Data Sources, Definitions, Basic Calculations• Using U.S. and Ohio examples, the slides describe key sources of

data to examine infant mortality, definitions integral to feto-infant mortality, measures of occurrence, measures of association, and methods of determining statistical significance

The Epidemiology of Maternal and Infant Health for State and Local PractitionersElizabeth J Conrey, PhD, RD

June 22-26, 2015

The Ohio State University, 2015 Summer Program in Population Health

Why Focus on Infant Mortality?

Measure of population health and health care

Recognized as crude indicator of: Community Health Status

Poverty and SES in a community

Availability and quality of health services and medical technology

Wide acceptance of measure

Easily calculated

Common use in needs assessments and evaluation

ODH Priorities for Improved Health

VISIONOptimal health for all Ohioans

MISSIONProtect and improve the health

of all Ohioans by preventing disease, promoting good health,

and assuring access to quality care

U.S. Trends in Infant Mortality,

1915-1997

US Trends in Infant Mortality, 1997-2013

199719981999200020012002200320042005200620072008200920102011201220130

2

4

6

87.2 7.2 7.0 6.9 6.8 7.0 6.8 6.8 6.9 6.7 6.8 6.6 6.4 6.2 6.1 6.0 6.0

199719981999200020012002200320042005200620072008200920102011201220130

2

4

6

87.2 7.2 7.0 6.9 6.8 7.0 6.8 6.8 6.9 6.7 6.8 6.6 6.4 6.2 6.1 6.0 6.0

Remember to see the faces behind the numbers…

--William Foege

US Trends in Infant Mortality, 1997-2012

Low & Very Low Birth Weight, US, 1990-2012

Racial & Ethnic Disparities in US IM

Geographic Disparities in Infant Mortality, by State– US, 2010

Standing on Common Ground: Data Sources, Definitions, Basic Calculations

Maternal & Infant Data Sources & Systems

NS-Childrens Health FIMR NS-

CSHCNBirth

Defects

PRAMS BRFSS Maternal Mortality

Vital Records

Medicaid

Oral Health WIC Newborn

Screening

Hospital Discharge

Child Fatality Review STD OMAS

Ohio

Maternal & Infant Data Sources & Systems

NS-Childrens Health FIMR NS-

CSHCNBirth

Defects

PRAMS BRFSS Maternal Mortality

Vital Records

Medicaid

Oral Health WIC Newborn

Screening

Hospital Discharge

Child Fatality Review STD OMAS

Ohio

Data Sources: National Data Only

Ohio

National Hospital Care Survey (NHCS)

National Health and Nutrition Examination Survey (NHANES

Data Sources: National and all States/Regions

Ohio

National Vital Statistics (NCHS) Live Births

Infant Deaths

Fetal Deaths

Linked Birth/Death files

National Immunization Survey (NIS)

National Survey of Children’s Health (NSCH)

National Survey of Children with Special Health Care Needs

Data Sources: National & Regions

Ohio

National Survey of Family Growth (NSFG)

National Health Interview Survey – Child (NHIS)

Data Sources: State Specific (all states)

Ohio

State Department of Health Vital Statistics Live Births

Infant Deaths

Fetal Deaths

Linked Birth/Death files

Behavioral Risk Factor Surveillance System

Hospital Discharge

Medicaid Claims

WIC Participant Characteristics (USDA)

Data Sources: State Specific (select)

Ohio

Health Care Utilization Project (HCUP), AHRQ

Youth Risk Behavioral Surveillance System (YRBSS)

PRAMS

School Health Profile Surveys

Birth Defects Registry Ohio Connections for Children with Special Needs (OCCSN)

Child Fatality Review

Perinatal Quality Care Collaboratives Vermont Oxford Network (VON)

Maternal Mortality Review Pregnancy Associated Mortality Review (PAMR)

Emergency Medical Services (EMS)

Data Sources: State/Local Health Social Service Programs

Ohio

WIC

Family Planning

Home Visiting Programs

Hospital and Insurance Records

Ohio Medicaid Assessment Survey (OMAS)

Data Sources: Local Review Programs

Ohio

FIMR Age at death

Cause of Death

Maternal & Infant Data Sources & Systems

Ohio

Vital Records

Jurisdiction Responsibility for Vital Event Registration

ALL vital events that occur within each of the 57 jurisdictions (50 states, NYC, DC, 5 territories):• Live births

• Deaths

• Fetal deaths (based on length of gestation/birth weight)

• Induced Terminations of Pregnancy (ITOP)

• Marriages and Divorces

Early Vital Statistics Registration

Registration within parishes, ensured legal rights (≤ 1632 in Virginia)

Need for registration not in the Constitution Shifted from

church recording of traditional events: christenings, marriages, burials

Shifted to government recording of vital events: births, deaths,

marriages To collect and preserve records not for statistical purposes, but

legal evidence (e.g., property inheritance)

Early US Registration Systems

Cities were first: Boston, NYC, Philadelphia, Baltimore, New Orleans (1833)

Massachusetts first state system (1842) US government started to develop and maintain

a uniform system of registration after the 1900 census (last state was Texas, added in 1933)

Welfare and old age legislation of 1930s and World War II resulted in birth certificates becoming much more important for legal documentation

Early Ohio Death Registration

1867 Cincinnati

1870s Cleveland, Dayton

1880s Chillicothe, Nelsonville, Salem, Warren

1890s 16 cities, including Mansfield, Youngstown, Marietta, Springfield

1900s 22 cities, including Columbus, Akron, Canton, Toledo

Ohio VS Registration: 1908 Ohio passed Vital Statistics Registration Act

Considered model legislation , based on APHA VS section work

1,150 registration districts! (down to 118 in 2011)

Estimated 100% complete death reports, 80% complete birth reports in 1909

Ohio VS Registration: 1908

1908 Ohio passed the Vital Statistics Registration Act

Considered the model legislation of the time, based on APHA VS section work

1,150 registration districts! (down to 118 in 2011)

Estimated 100% complete death reports, 80% complete birth reports in 1909

From Records to Statistics

Use of birth and death records for control of epidemics and to improve sanitary conditions

Cholera in Europe and America (1830’s) Chadwick and Farr (Europe) and Shattuck

(Massachusetts) Comparative infant mortality statistics to

prove life-saving value of milk pasteurization 1898: first disease classification system for

deaths

Two Purposes of Vital Records

Legal/administrative uses (civil registration)

• Proof of citizenship, age, parentage

• Used to obtain identity documents, settle estates, obtain benefits

Public health/statistical uses

• Measure outcomes

• Identify risk factors

• Conduct research

National Center For Health Statistics (NCHS)

Established by law, NCHS is federal government’s principle health statistics agency

Through shared relationships and contracts with 57 jurisdictions (50 states, 2 cities, and 5 territories), NCHS responsible for disseminating nation’s official vital statistics

Jurisdictions are responsible for maintaining registries of vital events and issuing copies of birth, marriage, divorce, and death certificates.

www.cdc.gov/nchs/nvss.htm

Ohio VS receives from NCHS…

NCHS also collects, analyzes, and disseminates health statistics that provide national & state comparisons for Ohio

Limited monetary support Guidance and technical assistance on data:

- collection, storage, standards, & procedures

- processing methodologies

- coding, editing

- transmissions to NCHS

Process for Registering Vital Events and Preparing Data for Release

• Many steps

• Many actors

• Complex systems

• Differs by type of event

• Multiple data quality reviews

• National data depend on slowest jurisdiction

Vital Records Data

Natality data: From the birth certificate.

Mortality data: From the death certificate. Date of birth distinguishes infant deaths.

Linked birth-infant death records: Linkage and merging of birth certificate and death certificate data.

Induced Abortions

Fetal Deaths

Ohio Vital Statistics: Live Birth Variables

Ohio

Infant Variables

Maternal Variables

Paternal Variables

Data Warehouse Functionality Available

http://www.odh.ohio.gov/healthstats/dataandstats.aspx • Downloads• Charts• Reports• Maps• Data View (with Query)• Secure and Public Versions• Population-based rates (Cancer module only)

Vital Statistics Warehouse Dataset Status

COMPLETED• Resident Live Births • Occurrence Live Births• Deaths• “Added Value” Modules

DEFINING REQUIREMENTS / BUILDING• Fetal Deaths• “Added Value” Modules

Maternal & Infant Data Sources & Systems

PRAMS

Guest Presenter: Missy Vonderbrink, MPHMCH EpidemiologistOhio Department of Health

Maternal & Infant Data Sources & Systems

Ohio

FIMRChild

Fatality Review

Ohio Child Fatality Review

Ohio

FIMR Age at death

Cause of Death

Ohio Fetal Infant Mortality Review

Ohio

Overarching Goal provide community leaders with recommendations from case reviews

Ohio FIMRs Cincinnati since 2008

7 New beginning 2014/15

Columbus/Franklin

Cuyahoga

Cleveland (expanding)

Butler

Lucas/Toledo

Stark/Canton

Summit

DEFINITIONS

Conception Live Birth 1 Year

Gestation Infancy20 wks 28 days

Fetal Death Infant Death

Neonatal Death

Reported Vital Events

Postneonatal Death

Feto-Infant Death

28 wks

Perinatal Death #1

7 days

Perinatal Death #2

1

2

Conception Live Birth 1st Birthday

Gestation Infancy20 wks 28 days

Fetal Death Infant Death

Neonatal Death

Definitions: Reported Vital Events

Perinatal Death

Postneonatal Death

Feto-Infant Death

12

4

5

3

6

Annual Infant Mortality Rate

Deaths in year= --------------

Births in yearX 1,000

SAMPLE PROBLEMIn 2012, 138,284 babies were born alive in Ohio and in the same time period, 1047 infants died before reaching their first birthday. What was the infant mortality rate for Ohio?

Deaths--------------

BirthsX 1,000 =

1047

-------------- 138,284

7.57

Infant Mortality Has 2 Main “Subcomponents”

# infant deaths between 0-27 days of life for a defined time period

= -------------- Births in same time

period

X 1,000

Neonatal Postneontal

# infant deaths between 28 and 365 days of life for a defined time

period

= -------------- Births in same time period

X 1,000

Infant Deaths by Age at Death, Ohio, 2012

Postneonatal 31%

Neonatal 69%

Neonatal Postneonatal Total0

2

4

6

8

5.21

2.36

7.57

Rate

per

10

00

liv

e b

irth

s

HP2020

Gestational Age and Preterm Birth Measures

Very preterm

Gestational age The age of the fetus or newborn infant in weeks

Estimates of a newborn’s gestational age based on birth certificate data are used to monitor trends in birth health

Late Preterm

image credit Wikipedia

Gestational Age and Preterm Birth Measures

Term birth: live births between 37 and 41 completed weeks gestation between 37 and 38 weeks referred to as Early Term

Preterm birth: live births less than 37 completed weeks (<259 days)

Very Preterm birth: live births less than 32 completed weeks Late Preterm birth: live births between 34 and 36 completed

weeks

Preterm Birth Rates, Ohio & US, 2001-2013

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 20148

9

10

11

12

13

14

*

//

Ohio

US

*preliminary

Percentage of Infants Born Late Preterm, by State, US 2012

NCHS

Birth Weight Measures

# live births weighing <2,500 g

= ---------------- # live births in same time

period

Low Birth Weight (LBW) RateVery LBW

<1,500 g

Moderately LBW 1,500 – 2,499 g

Low Birth Weight

Highly correlated with gestational age

Lower the birth weight the greater the risk for poor outcomes

LBW babies 25x more likely to die in 1st year of life

VLBW babies 100x more likely to die in 1st year

Low Birth Weight Rates Ohio & US, 2001-2013

19901992

19941996

19982000

20022004

20062008

20102012

0

2

4

6

8

10

Ohio

United States

Low Birth Weight (<2500g) Singleton Births, by Race/Ethnicity, Ohio, 2010-2012

Hispanic Black White0

2

4

6

8

10

12

14

16

Percent of Low Birth Weight Births by State and County– US, 2011 & Ohio, 2010-2012

Fetal Death Measures

“Death prior to the complete expulsion or extraction from its mother of a product of human conception, irrespective of the duration of pregnancy and which is not an induced termination of pregnancy”

Reporting Requirements (Ohio and most states) 20 weeks gestation or greater

“Death is indicated by the fact that after such expulsion or extraction, the fetus does not breathe or show any other evidence of life, such as beating of the heart, pulsation of the umbilical cord, or definite movement of voluntary muscles. Heartbeats are to be distinguished from transient cardiac contractions; respirations are to be distinguished from fleeting respiratory efforts or gasps.”

Fetal Death Measures

Early fetal death: A fetal death between 20 and 27 weeks of gestation.

Late fetal death: A fetal death at or after 28 weeks of gestation.

Perinatal Measures

Perinatal I

Refers to around (peri) the time of birth (natal) The entire or parts of the period beginning before conception and through the

first year of life

# fetal deaths >20 weeks gestation + infant deaths <28 days of life

= -------------- births plus fetal deaths

in same time period

X 1,000

Perinatal II

# fetal deaths >28 weeks gestation + infant

deaths <7 days of life

= -------------- births plus fetal deaths

in same time period

*NCHS definitions

X 1,000

Perinatal Mortality*, Ohio 2003-2012

2003 2004 2005 2006 2007 2008 2009 2010 2011 20120

1

2

3

4

5

6

7

8

9

10

7.27 6.94 7.04 6.97 7.01 6.996.56

6.977.39 7.33

Year

Rate

per

1,0

00

Liv

e B

irth

s

an

d F

eta

l D

eath

s

* NCHS Perinatal definition I: Fetal deaths of 28 weeks gestation or more and infant deaths of less than seven days of age.

BASIC CALCULATIONS

BASIC CALCULATIONS: Measures of Occurrence

Infant Mortality Rate

Cause-Specific Infant Mortality Rate

Proportionate Mortality Rates

Cause Specific Infant Mortality Rate

number of deaths from cause

(born in [birth year/s])= --------------------

births in yearX 100,000

Cause Specific Mortality: Ohio, 1990-2011

199519961997199819992000200120022003200420052006200720082009201020110

50

100

150

200

250Preterm Related Obstetric Complications

Maternal complications of pregnancy Congenital Anomalies

SIDS

Rat

e pe

r 10

0,00

0 B

irth

s

Proportionate Mortality Rate

number of deaths from cause

(born in [birth year/s])= ------------------------------- total number of deaths from all causes (in [birth

year/s])

X 100

BASIC CALCULATIONS: Measures of Occurrence – Standardized Rates

Direct Method

Indirect Method

Standardized Rates: Direct Method

Direct Adjusted Rate (DAR) Formula

m

Σ ci * ri i

m = number of strata

i = stratum

c = proportion of standard population in stratum i

r = rate in study population in stratum i

EXAMPLEStandardized Rates: Direct Method

Age (in years)Strata

(i)

US Birth Population

(c)

“STATE” Birth Population

US Infant Mortality

Rate/ 1,000 Live Births

“STATE” Infant

Mortality Rate / 1,000 Live Births

<18

18-20

21-34

35-44

TOTAL 100% 100%

Standardized Rates: Indirect Method

Used when insufficient data to directly calculate observed number

of infant deaths = --------------------- expected number

of infant deaths

X 100

Standardized Mortality Ratio (SMR)

EXAMPLE: Indirect Method

Birth WeightStrata

(i)

Live Births Ohio(c)

US Infant Mortality

Rate(r)

Expected Deaths

Observed Deaths

500-999 g

1,000-1,499 g

1,500-1,999 g

2,000-2,499 g

TOTAL

CASE STUDY Florida analyzed vital records data to identify geographic areas

where low birth weight and infant mortality rates were statistically higher than expected after adjusting for race, marital status and education level. Florida used an indirect method to calculate adjusted rates. This analysis informed further analysis and helped the Department of Health to focus efforts in counties that had significantly higher than expected infant deaths and low birth weight births.

For further detail, see information provided in the link:

www.doh.state.fl.us/Family/mch/docs/infant_mortality_docs/ExpectedRatesByCounty09.pdf

BASIC CALCULATIONS: Measures of Association (comparing rates)

Relative Risk of Infant Death

Absolute Risk Difference of Infant Death (Excess Death Rate)

Relative Risk of Cause-Specific Infant Death

Absolute Risk Difference of Cause-Specific Infant Death (Excess Cause-Specific Death Rate)

Measures of Association: Relative Risk of Infant Death

preferred for etiological studies of association

controls for baseline differences in mortality rates when comparing a risk factor across groups, time periods or outcomes

number of live

births among infants (group a)

number of live births among

infants (group b)

number of deaths among

infants (group a)

number of deaths among infants

(group b)

Measures of Association: Absolute Risk Difference of Infant Death

Excess rate

preferred for identifying potential to prevent a poor outcome or disease and quantifying the actual numbers in the population affected

number of

deaths among infants (group b)

X 1,000

number of live-born infants

(group b)

number of deaths among

infants (group a)x 1,000

number of live-born infants

(group a)

Measures of Association: Relative Risk of Cause-Specific Infant Death

For example, to compare deaths due to SIDS in one time period to another, or among one racial group to another

number of live

births among infants (group a)

number of live births among

infants (group b)

number of deaths from cause A

among infants (group a) x 1,000

number of deaths from cause A

among infants (group b) X 1,000

Measures of Association: Relative Risk of Cause-Specific Infant Death

Ohio 2011 preterm-related deaths among black (a) and white (b) births

= 3.89

3.785

0.972

Measures of Association: Absolute Risk Difference of Cause-Specific Infant Death

Excess Cause-Specific Death Rate number of

deaths from Cause B among infants (group b)

X 1,000

number of live-born infants

(group b)

number of deaths from

cause A among infants (group a)

x 1,000

number of live-born infants

(group a)

Measures of Association: Absolute Risk Difference of Cause-Specific Infant Death

Ohio 2011 preterm-related deaths among black (a) and white (b) births

= 2.812 0.9723.785

If black infants had the same mortality rate as white infants, 65 more black infants would have lived in 2013

EXAMPLE: Cause-Specific Attributable Risks2008-10

NHB2008-10

NHW

Excess Cause-Specific Death Rate

Cause-Specific Proportion of Excess Deaths

Cause-Specific Infant Mortality Rate (per 1,000) (Ai-Bi) (Ai-Bi) / (Σ Ai-Σ Bi)

Preterm or LBW -related 3.2 1.3 1.9 23.8%

Congenital anomalies and chromosomal

abormal.1.5 1.2 0.3 3.7%

SIDS 2.3 0.6 0.7 8.8%

Maternal complications of pregnancy 0.9 0.5 0.4 5.0%

Complications of placenta, cord and

membranes0.8 0.4 0.4 5.0%

Other 5.6 2.3 3.3 41.3%

TOTAL 14.3 6.3 8.0 100%Franklin County Health Indicator Brief: Trends 1990-2010 Infant Mortality

100

BASIC CALCULATIONS: Testing the significance of differences

Differentiate

statistically significant

~versus~

clinically or programmatically meaningful

EXAMPLE: statistically significant vs. meaningful differences

1. U.S.- Very Low Birth Weight (VLBW) Deliveries

n %

1996 53,425 1.4

2008 61,773 1.5

P<0.05

2. County A - Very Low Birth Weight (VLBW) Deliveries

n %

1996 44 1.1

2008 110 2.2

P>0.05

BASIC CALCULATIONS: Methods for determining statistical significance

Using Confidence Intervals to Determine Statistical Significance

Using the Standard Error for Determining Statistically Significant Differences Between Two Rates

Confidence Intervals to Determine Statistical Significance

Quick and easy way to interpret differences in rates or ratios

A 95 percent confidence interval would mean that if you were to repeat the analysis 100 times, you would expect the real value to be contained within the confidence interval 95 times.

Confidence Intervals to Determine Statistical Significance: RATIOS

ASK: Does the confidence interval include the number “1” ?

If “yes”, ratio not statistically significant (rates not statistically significant from each other)

How wide is the confidence interval?

Confidence intervals (CI) often used to interpret a ratio comparing two groups. For EXAMPLE, if the infant mortality rate is 20.0 per 1,000 in county A and 10.0 per 1,000 in County B, the ratio = 2. How would you interpret the ratio of 2 if the 95% CI around the ratio was 0.8 – 2.6 ?

Standard Error for Determining Statistically Significant Differences Between Two Rates

Used to directly compare two rates

Significant (at 95% confidence level) if Difference exceeds 1.96 standard

errors The probability that the observed

difference was due to random variation is less that 5% (0.05)

p1q1 p2q2

n1 n2√p1 = infant mortality rate in 1991-1993 p2 = infant mortality rate in 2001-2003 qn = 1-p1 q2=1-p2 n = number of live births

EXAMPLE: Interpreting Differences Between Two Rates

In 1991-1993, there were 3,132 infant deaths (d1) out of 307,567 live births (n1) and in 2001-2003 there were 2,892 infant deaths (d2) out of 353,711 live births (n2).

HINTS

First Step: Calculate p1 and p2: p1 = d1/ n1

p2 = d2/ n2

p1q1 p2q2

n1 n2√

p1 = infant mortality rate in 1991-1993 p2 = infant mortality rate in 2001-2003 qn = 1-p1 q2=1-p2 n = number of live births

Second Step: Apply SE formula

EXAMPLE: Interpreting Differences Between Two Rates

First Step:

Calculate p1 & p2: p1 = 3,132 / 307,567

p2 = 2,892 / 353,7110.01018 x 0.98982 0.01018 x

0.99182

307567 353711√p1 = infant mortality rate in 1991-1993 p2 = infant mortality rate in 2001-2003 qn = 1-p1 q2=1-p2 n = number of live births

Second Step: Apply SE formula

= 0.000236