Obesity, Medication Use and Expenditures among Nonelderly Adults with Asthma

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Slide 1

Obesity, Medication Use and Expenditures among Nonelderly Adults with Asthma

Eric M. Sarpong

AHRQ Conference
September 10, 2012

Slide 2

Introduction

• Prevalence of asthma in adults—chronic and complex health condition increased over the past decade (Zahran et al., 2011).
• Prevalence of obesity, an important risk factor for asthma remains high (Ogden et al., 2012).
• Asthma more difficult to control in obese asthma patients (Lavoie et al., 2006 Saint-Pierre et al., 2006 Dixon et al., 2006).
• Both conditions result in increased resource use and costs:
  • Estimated healthcare costs of asthma in the U.S.—$18 billion (Sullivan et al., 2011).
  • 2008 estimated healthcare costs of obesity in the U.S.—$147 billion (Finkelstein et al., 2009).
• The presence of obesity in asthma patients may exacerbate medication use and expenditures.

Slide 3

Research Objective

• Provide insights on the role of obesity in generating health resource use and costs for asthma treatment.
• Study used nationally representative data on nonelderly adults with treatment for asthma to examine the relationship between obesity and:
  • Medication use:
    • Asthma medication and all prescribed medications.
  • Expenditures:
    • Asthma medication, all prescribed medications and total health care.

Slide 4

Previous Literature

• Relationship between asthma and obesity well documented (Ford, 2005; Shore and Johnston, 2006; Shore, 2006, 2007, 2008; Dixon et al., 2010).
• Few studies in the U.S., however, have examined the contribution of obesity to increased medication use and expenditures in adult asthma patients:
  • Taylor et al (2008): obese asthma patients had increased medication use compared to non-overweight asthma patients.
  • Mosen et al (2008): obese individuals more likely to report use of oral corticosteroids.
  • Suh et al (2011) estimated medical costs attributable to obesity in asthma patients—$1,087.

Slide 5

Contributions

• Previous literature limited:
  • Uses administrative claims data, key variables unavailable or uses regional samples.
  • Analyses do not examine the use of all prescribed medications in addition to asthma medications.
  • Previous studies differ from this study on a number of dimensions:
    • Time periods and population (e.g., ≥18 years, ≥35 years, patients with diagnosed asthma).
    • Degree to which confounding variables are controlled for across bodyweight categories.
• This study uses regression-based modeling approaches to help inform policymakers about how obesity exacerbates medication use and expenditures.

Slide 6

Data

• 2005-2009 Medical Expenditure Panel Survey (MEPS):
  • Nationally representative data on U.S. civilian non-institutionalized population.
  • Detailed information on drug therapeutic classifications, quantities purchased, and sources of payment (OOP payments and private and public insurance payments).
• Detailed information on health conditions, economic and socio-demographic variables.
• Analytical sample of adults (ages 18-64) with reported treatment for asthma:
  • Reported treatment implies health service use associated with asthma.
  • Sample of 3,580 (964 = normal weight: 18.5 kg/m² > BMI ≤ 25 kg/m²; 985 overweight: 25 kg/m² < BMI < 30 kg/m², and 1,631 obese: 30 kg/m² ≥ BMI ≤ 100 kg/m².

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Analytic Approach

• Describe differences in treated prevalence of asthma, medication use and expenditures by BMI categories.
• Use generalized linear models (GLM) to estimate the effects of BMI categories on:
  • Number of asthma and all prescribed medications used (Poisson family and log link function).
  • Asthma and all prescribed medications expenditures (gamma family and power link function).
  • Total health care expenditures (gamma family and log link function).
• All GLM estimates control for age, sex, race-ethnicity, health insurance, family income, employment status, marital status, family size, health status, comorbidities, medication beliefs:
  • Effects of BMI presented as differences in observed and predicted change.
  • Effects of Characteristics presented as marginal effects.

Slide 8

Nonelderly Adults with Treatment for Asthma by BMI Categories

Image: A bar graph presents the following data:

• Normal weight: 29.9%.
• Overweight: 27.7%.
• Obese: 42.5%^**††.

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.

Slide 9

Medication Use Among Adults With Treatment for Asthma by BMI Categories

Image: A bar graph presents the following data:

Normal weight:

• Asthma medications: 1.7.
• All medications: 23.7.

Overweight:

• Asthma medications: 1.8.
• All medications: 26.1.

Obese:

• Asthma medications: 1.8^*.
• All medications: 40.4^**††.

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.

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

• Among nonelderly adults with reported treatment for asthma:
  • 42.5% percent were obese, 27.7% were overweight, and 29.9% were normal weight.
  • Obese patients were prescribed 1.8 asthma medicines on average compared with 1.7 for normal weight patients.
  • Obese patients filled 40.4 prescribed medications on average compared with 26.1 for overweight patients and 23.7 for normal weight patients.

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Expenditures for Adults with Treatment for Asthma by BMI Categories

Image: A bar graph presents the following data:

Normal weight:

• Asthma medications: $726.
• All medications: $2,019.
• Total health care: $7,486.

Overweight:

• Asthma medications: $769.
• All medications: $2,243.
• Total health care: $7,468.

Obese:

• Asthma medications: $867^*.
• All medications: $3,251^**††.
• Total health care: $9,750^*††.

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 ≤ 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.

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

• Among nonelderly adults with reported treatment for asthma:
  • Asthma medications expenditures were 19.3 percent higher for obese patients ($867) compared with those for normal weight patients ($726).
  • All prescribed medication expenditures were more than 40 percent higher for obese patients ($3,251) than those for overweight patients ($2,243) and normal weight patients ($2,019).
  • Total health care expenditures were about 30 percent higher for obese patients ($9,750) than those for overweight patients ($7,468) and normal weight patients ($7,486).

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Selected Characteristics of Nonelderly Adults with Reported 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 ≤ kg/m²). NH = non-Hispanic; FPL = Federal poverty line. Estimate is significantly different from normal weight category at: ** p<0.05, *p<0.10.

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

• Among nonelderly adults with reported treatment for asthma:
  • Obese adults were more likely than normal weight adults:
    • To be older (ages 45-64), NH Black and Hispanic, covered by public insurance, poor and low income, married, in fair or poor health.
    • To have comorbidities.

Slide 15

Effects of BMI on Medication Use and 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 ≤ 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.

Slide 16

Interpretation of Effects of BMI on Outcome Variables

• The study finds that, controlling for other socio-demographic, economic and health characteristics.
• If obese nonelderly adults were counterfactually switched to normal weight or overweight:
  • Mean number of all prescribed medication would decrease by 12.1 and 10.2 fills.
  • Expenditures on:
    • Asthma medications would decrease by $93 and $89.
    • All prescribed medications would decrease by $992 and $829.
    • Total health care would decrease by $2,433 and $2,073.

Slide 17

Effects of Selected Characteristic on Medication Use and 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 ≤ 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.

Slide 18

Interpretation of Marginal Effects of Characteristics on Outcome Variables

• Several characteristics were significantly related to the outcome variables.
• Age 45-64 and fair or poor health status increase:
  • Expected number of asthma medications and all prescribed medication fills.
  • Expenditures for asthma medication, all prescribed medications and total health care.
• Both NH Black and Hispanic race-ethnicity decrease:
  • Expected number of all prescribed medication fills.
  • Expenditures for asthma medication, all prescribed medications and total health care.
• Both public insurance and low income increase:
  • Expected number of all prescribed medication fills and corresponding expenditures.
• Comorbid conditions increase:
  • Expected number of all prescribed medication fills, and expenditures for all prescribed medications and total health care.

Slide 19

Limitations

• BMI calculated using self-reported measures of height and weight:
  • May result in underestimate of the true effects of BMI on medication use and expenditures.
• Omitted variables and residual confounding effects cannot be excluded:
  • e.g., asthma severity may play a critical role in the effects of BMI on medication use and expenditures.
  • Results may change if severity differs across BMI groups.
• Inclusion of comorbidities—an intermediate pathway through which BMI affects health services use and expenditures may affect results.
• Non-causal regression models.

Slide 20

Conclusions

• Study demonstrates that obesity is associated with increased medication use and expenditures in nonelderly adults with asthma.
• Multivariate analysis showed that counterfactually switching obese nonelderly adults to normal weight would decrease medication use and expenditures.
• Implications:
  • There appears to be an association between obesity and high costs of care for the treatment of asthma.
  • The study suggest maintaining a normal weight could reduce both asthma related and overall health care costs for nonelderly adults with asthma.