Obesity, Medication Use and Expenditures among Obesity, Medication Use and Expenditures among Nonelderly Adults with AsthmaNonelderly Adults with Asthma

Eric M. SarpongEric M. Sarpong

AHRQ Conference AHRQ Conference September 10, 2012September 10, 2012

IntroductionIntroduction

Prevalence of asthma in adults – chronic and complex Prevalence of asthma in adults – chronic and complex health condition increased over the past decade health condition increased over the past decade (Zahran et (Zahran et al., 2011)al., 2011)

Prevalence of obesity, an important risk factor for asthma Prevalence of obesity, an important risk factor for asthma remains high remains high (Ogden et al., 2012)(Ogden et al., 2012)

Asthma more difficult to control in obese asthma patients Asthma more difficult to control in obese asthma patients (Lavoie et al., 2006 Saint-Pierre et al., 2006 Dixon et al., 2006)(Lavoie et al., 2006 Saint-Pierre et al., 2006 Dixon et al., 2006)

Both conditions result in increased resource use and costsBoth conditions result in increased resource use and costs– Estimated healthcare costs of asthma in the U.S. - $18 Estimated healthcare costs of asthma in the U.S. - $18

billion billion (Sullivan et al., 2011)(Sullivan et al., 2011)

– 2008 estimated healthcare costs of obesity in the U.S. - 2008 estimated healthcare costs of obesity in the U.S. - $147 billion $147 billion (Finkelstein et al., 2009)(Finkelstein et al., 2009)

The presence of obesity in asthma patients may The presence of obesity in asthma patients may exacerbate medication use and expendituresexacerbate medication use and expenditures

Research ObjectiveResearch Objective

Provide insights on the role of obesity in Provide insights on the role of obesity in generating health resource use and costs for generating health resource use and costs for asthma treatmentasthma treatment

Study used nationally representative data on Study used nationally representative data on nonelderly adults with treatment for asthma to nonelderly adults with treatment for asthma to examine the relationship between obesity and;examine the relationship between obesity and;– Medication useMedication use

Asthma medication and all prescribed medicationsAsthma medication and all prescribed medications

– ExpendituresExpenditures Asthma medication, all prescribed medications and total Asthma medication, all prescribed medications and total

health carehealth care

Previous LiteraturePrevious Literature

Relationship between asthma and obesity well Relationship between asthma and obesity well documented documented (Ford, 2005; Shore and Johnston, 2006; Shore, 2006, (Ford, 2005; Shore and Johnston, 2006; Shore, 2006, 2007, 2008; Dixon et al., 2010)2007, 2008; Dixon et al., 2010)

Few studies in the U.S., however, have examined the Few studies in the U.S., however, have examined the contribution of obesity to increased medication use contribution of obesity to increased medication use and expenditures in adult asthma patientsand expenditures in adult asthma patients– Taylor et al (2008): obese asthma patients had Taylor et al (2008): obese asthma patients had

increased medication use compared to non-overweight increased medication use compared to non-overweight asthma patients asthma patients

– Mosen et al (2008): obese individuals more likely to Mosen et al (2008): obese individuals more likely to report use of oral corticosteroids report use of oral corticosteroids

– Suh et al (2011) estimated medical costs attributable to Suh et al (2011) estimated medical costs attributable to obesity in asthma patients - $1,087obesity in asthma patients - $1,087

ContributionsContributions

Previous literature limited Previous literature limited – Uses administrative claims data, key variables unavailable Uses administrative claims data, key variables unavailable

or uses regional samples or uses regional samples

– Analyses do not examine the use of all prescribed Analyses do not examine the use of all prescribed medications in addition to asthma medications medications in addition to asthma medications

– Previous studies differ from this study on a number of Previous studies differ from this study on a number of dimensionsdimensions

Time periods and population (e.g., ≥ 18 years, ≥ 35 years, Time periods and population (e.g., ≥ 18 years, ≥ 35 years, patients with diagnosed asthma)patients with diagnosed asthma)

Degree to which confounding variables are controlled for Degree to which confounding variables are controlled for across bodyweight categoriesacross bodyweight categories

This study uses regression-based modeling This study uses regression-based modeling approaches to help inform policymakers about how approaches to help inform policymakers about how obesity exacerbates medication use and expenditures obesity exacerbates medication use and expenditures

Data Data

2005-2009 Medical Expenditure Panel Survey (MEPS)2005-2009 Medical Expenditure Panel Survey (MEPS)– Nationally representative data on U.S. civilian non-Nationally representative data on U.S. civilian non-

institutionalized populationinstitutionalized population– Detailed information on drug therapeutic Detailed information on drug therapeutic

classifications, quantities purchased, and sources of classifications, quantities purchased, and sources of payment (OOP payments and private and public payment (OOP payments and private and public insurance payments)insurance payments)

Detailed information on health conditions, economic Detailed information on health conditions, economic and socio-demographic variablesand socio-demographic variables

Analytical sample of adults (ages 18-64) with reported Analytical sample of adults (ages 18-64) with reported treatment for asthmatreatment for asthma– Reported treatment implies health service use Reported treatment implies health service use

associated with asthma associated with asthma – Sample of 3,580 (964 = normal weight: 18.5 kg/mSample of 3,580 (964 = normal weight: 18.5 kg/m22 > >

BMI ≤ 25 kg/mBMI ≤ 25 kg/m22; 985 overweight: 25 kg/m; 985 overweight: 25 kg/m22 < BMI < 30 < BMI < 30 kg/mkg/m22, and 1,631 obese: 30 kg/m, and 1,631 obese: 30 kg/m22 ≥ BMI ≤ 100 kg/m ≥ BMI ≤ 100 kg/m22

Analytic ApproachAnalytic Approach

Describe differences in treated prevalence of asthma, Describe differences in treated prevalence of asthma, medication use and expenditures by BMI categoriesmedication use and expenditures by BMI categories

Use generalized linear models (GLM) to estimate the Use generalized linear models (GLM) to estimate the effects of BMI categories on: effects of BMI categories on: – Number of asthma and all prescribed medications used Number of asthma and all prescribed medications used

(Poisson family and log link function)(Poisson family and log link function)– Asthma and all prescribed medications expenditures Asthma and all prescribed medications expenditures

(gamma family and power link function) (gamma family and power link function) – Total health care expenditures (gamma family and log link Total health care expenditures (gamma family and log link

function)function) All GLM estimates control for age, sex, race-ethnicity, All GLM estimates control for age, sex, race-ethnicity,

health insurance, family income, employment status, health insurance, family income, employment status, marital status, family size, health status, marital status, family size, health status, comorbidities, medication beliefscomorbidities, medication beliefs– Effects of BMI presented as differences in observed and Effects of BMI presented as differences in observed and

predicted changepredicted change– Effects of Characteristics presented as marginal effectsEffects of Characteristics presented as marginal effects

Nonelderly Adults with Treatment for Nonelderly Adults with Treatment for Asthma by BMI CategoriesAsthma by BMI Categories

Source: MEPS, 2005–2009. BMI = Body mass index (normal weight: 18.5 kg/m2 > BMI ≤ 25 kg/m2; overweight: 25 kg/m2 < BMI < 30 kg/m2, and obese: 30 kg/m2 ≥ BMI ≤ 100 kg/m2). Estimate is significantly different from normal weight category at: ** p<0.05, *p<0.10. Estimate is significantly different from overweight category at: †† p<0.05, †p<0.10.

Medication Use Among Adults With Medication Use Among Adults With Treatment for Asthma by BMI CategoriesTreatment for Asthma by BMI Categories

Source: MEPS, 2005–2009. BMI = Body mass index (normal weight: 18.5 kg/m2 > BMI ≤ 25 kg/m2; overweight: 25 kg/m2 < BMI < 30 kg/m2, and obese:30 kg/m2 ≥ BMI ≤ 100 kg/m2). Estimate is significantly different from normal weight category at: ** p<0.05, *p<0.10.

Summary: Differences in Treated Summary: Differences in Treated Prevalence and Medication Use by BMI Prevalence and Medication Use by BMI CategoriesCategories

Among nonelderly adults with reported Among nonelderly adults with reported treatment for asthma treatment for asthma – 42.5% percent were obese, 27.7% were 42.5% percent were obese, 27.7% were

overweight, and 29.9% were normal weight overweight, and 29.9% were normal weight

– Obese patients were prescribed 1.8 asthma Obese patients were prescribed 1.8 asthma medicines on average compared with 1.7 for medicines on average compared with 1.7 for normal weight patientsnormal weight patients

– Obese patients filled 40.4 prescribed Obese patients filled 40.4 prescribed medications on average compared with 26.1 medications on average compared with 26.1 for overweight patients and 23.7 for normal for overweight patients and 23.7 for normal weight patients weight patients

Expenditures for Adults with Treatment for Expenditures for Adults with Treatment for Asthma by BMI CategoriesAsthma by BMI Categories

Source: MEPS, 2005–2009. BMI = Body mass index (normal weight: 18.5 kg/m2 > BMI ≤ 25 kg/m2; overweight: 25 kg/m2 < BMI < 30 kg/m2, and obese:30 kg/m2 ≥ BMI ≤ 100 kg/m2). All expenditures for all years are CPI-U adjusted to 2009 U.S. dollars. Estimate is significantly different from normal weight category at: ** p<0.05, *p<0.10. Estimate is significantly different from overweight category at: †† p<0.05, †p<0.10.

Summary: Differences in Medications and Summary: Differences in Medications and Total Health Care Expenditures by BMI Total Health Care Expenditures by BMI CategoriesCategories

Among nonelderly adults with reported Among nonelderly adults with reported treatment for asthmatreatment for asthma– Asthma medications expenditures were 19.3 percent Asthma medications expenditures were 19.3 percent

higher for obese patients ($867) compared with higher for obese patients ($867) compared with those for normal weight patients ($726) those for normal weight patients ($726)

– All prescribed medication expenditures were more All prescribed medication expenditures were more than 40 percent higher for obese patients ($3,251) than 40 percent higher for obese patients ($3,251) than those for overweight patients ($2,243) and than those for overweight patients ($2,243) and normal weight patients ($2,019) normal weight patients ($2,019)

– Total health care expenditures were about 30 Total health care expenditures were about 30 percent higher for obese patients ($9,750) than percent higher for obese patients ($9,750) than those for overweight patients ($7,468) and normal those for overweight patients ($7,468) and normal weight patients ($7,486)weight patients ($7,486)

Selected Characteristics of Nonelderly Adults with Selected Characteristics of Nonelderly Adults with Reported Treatment for Asthma by BMI CategoriesReported Treatment for Asthma by BMI Categories

Source: MEPS, 2005–2009. BMI = Body mass index (normal weight: 18.5 kg/m2 > BMI ≤ 25 kg/m2; overweight: 25 kg/m2 < BMI < 30 kg/m2, and obese: 30 kg/m2 ≥ BMI ≤ 100 kg/m2). ). NH = non-Hispanic; FPL = Federal poverty line. Estimate is significantly different from normal weight category at: ** p<0.05, *p<0.10.

 Variables Categories Normal weight   Overweight   Obese

Age in years: 18 to 44 62.78   46.77**   42.62**   45 to 64 37.22   53.23**   57.38**

Race-ethnicity: NH White 81.15   78.09   72.03**   NH Black 9.62   12   15.23**   Hispanic 9.24   9.9   12.74**

Health insurance status: Any private 74.7   75.59   64.17**   Public only 17.7   15.07   27.00**   Uninsured 7.6   9.33   8.82

Family income (% of FPL): Middle/high income 72.65   70.8   62.58**   Low income 9.81   12.05   13.30**   Poor/near poor 17.54   17.15   24.12**

Marital status: Not married 57.9   45.63**   51.10**   Married 42.1   54.37**   48.90**

Perceived health status:Excellent/very good/good 69.41   64.39   43.98**

  Fair/poor 30.59   35.61   56.02** Comorbidity: No comorbid condition 57.17   49.67**   34.23**

 Comorbid condition 42.83   50.33**   65.77**

Summary: Selected Characteristics of Summary: Selected Characteristics of Nonelderly Adults with Reported Treatment Nonelderly Adults with Reported Treatment for Asthma for Asthma

Among nonelderly adults with Among nonelderly adults with reported treatment for asthma reported treatment for asthma – Obese adults were more likely than normal Obese adults were more likely than normal

weight adults:weight adults: To be older (ages 45-64), NH Black and To be older (ages 45-64), NH Black and

Hispanic, covered by public insurance, poor Hispanic, covered by public insurance, poor and low income, married, in fair or poor healthand low income, married, in fair or poor health

To have comorbiditiesTo have comorbidities

Effects of BMI on Medication Use and Effects of BMI on Medication Use and Expenditures. Expenditures.

Source: MEPS, 2005–2009. ‡ Differences in observed and predicted changes in BMI categories on outcomes. (a) GLM with Poisson family and log link; (b) GLM with gamma family and power link; (c) GLM with gamma family and log link. BMI = Body mass index (normal weight: 18.5 kg/m2 > BMI ≤ 25 kg/m2; overweight: 25 kg/m2 < BMI < 30 kg/m2, and obese: 30 kg/m2 ≥ BMI ≤ 100 kg/m2). NH = non-Hispanic; FPL = Federal poverty line. All expenditures for all years are CPI-U adjusted to 2009 U.S. dollars. GLM Models are estimated with controls for age, sex, race-ethnicity, health insurance, family income, employment status, marital status, family size, health status, comorbidities, medication beliefs and year dummies. Significance level: *** p<0.01, ** p<0.05, *p<0.10.

  Medication Use   Expenditures 

 Counterfactual BMI categories ‡Asthma

Medications a .All

Medications a .Asthma

Medications b .All

Medications b .Health Care c

Overweight as normal weight -0.03   -1.68   -137   -157   -372

 

Obese as normal weight -0.07**   -12.09**   -93*   -992**   -2433**

 

Obese as overweight -0.03   -10.20**   -89**   -829**   -2073**

 

Interpretation of Effects of BMI on Interpretation of Effects of BMI on Outcome Variables Outcome Variables

The study finds that, controlling for other The study finds that, controlling for other socio-demographic, economic and health socio-demographic, economic and health characteristics characteristics

If obese nonelderly adults were If obese nonelderly adults were counterfactually switched to normal weight or counterfactually switched to normal weight or overweight overweight – Mean number of all prescribed medication would Mean number of all prescribed medication would

decrease by 12.1 and 10.2 fillsdecrease by 12.1 and 10.2 fills– Expenditures on Expenditures on

Asthma medications would decrease by $93 and Asthma medications would decrease by $93 and $89 $89

All prescribed medications would decrease by All prescribed medications would decrease by $992 and $829$992 and $829

Total health care would decrease by $2,433 and Total health care would decrease by $2,433 and $2,073$2,073

Effects of Selected Characteristic on Effects of Selected Characteristic on Medication Use and Expenditures. Medication Use and Expenditures.

Source: MEPS, 2005–2009. ‡Marginal effects of characteristics on outcomes: (a) GLM with Poisson family and log link; (b) GLM with gamma family and power link; (c) GLM with gamma family and log link. BMI = Body mass index (normal weight: 18.5 kg/m 2 > BMI ≤ 25 kg/m2; overweight: 25 kg/m2 < BMI < 30 kg/m2, and obese: 30 kg/m2 ≥ BMI ≤ 100 kg/m2). NH = non-Hispanic; FPL = Federal poverty line. All expenditures for all years are CPI-U adjusted to 2009 U.S. dollars. GLM Models are estimated with controls for age, sex, race-ethnicity, health insurance, family income, employment status, marital status, family size, health status, comorbidities, medication beliefs and year dummies. Significance level: *** p<0.01, ** p<0.05, *p<0.10.

  Medication Use   Expenditures 

 Variables Asthma Medications a.

All Medications a.

Asthma Medications b.

All Medications b.

Health Care c

Age in years (18 to 44) --   --   --   --   -- 45 to 64 0.19***   8.27***   355.83***   758.79***   2427.08*** Race-ethnicity (NH White) --   --   --   --   -- NH Black -0.18**   -3.56   -362.61***   -284.71   -1560.63**

Hispanic -0.24***   -8.08***   -537.94***   -729.56***   -1971.89***Health insurance status (Any private) --

 --

 --

 --

  -- Public only -0.09 11.84*** 215.19 711.58*** -1335.72

Uninsured -0.28***   -7.23***   -332.37***   -1031.39***   -6363.33*** Family income (% of FPL) (Middle/high income) --

 --

 --

 --

  -- Poor/near poor -0.07   -4.81***   -151.12*   -468.25**   -2192.58** Perceived health status (Excellent/very good/ good) --

 --

 --

 --

  -- Fair/poor 0.20***   13.08***   323.27***   1145.48***   4957.14*** Comorbidity (No comorbid condition) --

 --

 --

 --

  -- Comorbid condition -0.01   19.95***   126.03   1785.90***   3450.94***

Interpretation of Marginal Effects of Interpretation of Marginal Effects of Characteristics on Outcome VariablesCharacteristics on Outcome Variables

Several characteristics were significantly related to the Several characteristics were significantly related to the outcome variables.outcome variables.

Age 45-64 and fair or poor health status increaseAge 45-64 and fair or poor health status increase– Expected number of asthma medications and all prescribed Expected number of asthma medications and all prescribed

medication fillsmedication fills– Expenditures for asthma medication, all prescribed Expenditures for asthma medication, all prescribed

medications and total health caremedications and total health care Both NH Black and Hispanic race-ethnicity decreaseBoth NH Black and Hispanic race-ethnicity decrease

– Expected number of all prescribed medication fillsExpected number of all prescribed medication fills– Expenditures for asthma medication, all prescribed Expenditures for asthma medication, all prescribed

medications and total health caremedications and total health care Both public insurance and low income increaseBoth public insurance and low income increase

– Expected number of all prescribed medication fills and Expected number of all prescribed medication fills and corresponding expenditurescorresponding expenditures

Comorbid conditions increase Comorbid conditions increase – expected number of all prescribed medication fills, and expected number of all prescribed medication fills, and

expenditures for all prescribed medications and total health expenditures for all prescribed medications and total health carecare

LimitationsLimitations

BMI calculated using self-reported measures of BMI calculated using self-reported measures of height and weight height and weight – May result in underestimate of the true effects of BMI May result in underestimate of the true effects of BMI

on medication use and expenditures on medication use and expenditures Omitted variables and residual confounding Omitted variables and residual confounding

effects cannot be excludedeffects cannot be excluded– E.g., asthma severity may play a critical role in the E.g., asthma severity may play a critical role in the

effects of BMI on medication use and expenditureseffects of BMI on medication use and expenditures– Results may change if severity differs across BMI Results may change if severity differs across BMI

groupsgroups Inclusion of comorbidities – an intermediate Inclusion of comorbidities – an intermediate

pathway through which BMI affects health pathway through which BMI affects health services use and expenditures may affect services use and expenditures may affect resultsresults

Non-causal regression modelsNon-causal regression models

ConclusionsConclusions

Study demonstrates that obesity is associated with Study demonstrates that obesity is associated with increased medication use and expenditures in increased medication use and expenditures in nonelderly adults with asthma nonelderly adults with asthma

Multivariate analysis showed that counterfactually Multivariate analysis showed that counterfactually switching obese nonelderly adults to normal weight switching obese nonelderly adults to normal weight would decrease medication use and expenditureswould decrease medication use and expenditures

Implications: Implications: – There appears to be an association between obesity There appears to be an association between obesity

and high costs of care for the treatment of asthmaand high costs of care for the treatment of asthma

– The study suggest maintaining a normal weight could The study suggest maintaining a normal weight could reduce both asthma related and overall health care reduce both asthma related and overall health care costs for nonelderly adults with asthmacosts for nonelderly adults with asthma