Cited by 400Obesity, Physical Activity, DietObesity and Health PracticesHealthcare Policy and Management

Direct medical costs of obesity in the United States and the most populous states

Open access
Cawley, John, Biener, Adam, Meyerhoefer, Chad, Ding, Yuchen, Zvenyach, Tracy, Smolarz, B Gabriel, Ramasamy, Abhilasha·2021·Journal of Managed Care & Specialty Pharmacy

Abstract

BACKGROUND: After a dramatic increase in prevalence over several decades, obesity has become a major public health crisis in the United States. Research to date has consistently demonstrated a correlation between obesity and higher medical costs for a variety of U.S. subpopulations and specific categories of care. However, by examining associations rather than causal effects, previous studies likely underestimated the effect of obesity on medical expenditures. OBJECTIVE: To estimate the causal effect of obesity on direct medical care costs at the national and state levels. METHODS: This study is a pooled cross-sectional analysis of retrospective data from the 2001-2016 Medical Expenditure Panel Surveys. Adults aged 20-65 years with a biological child living in the household were included in the study sample. Primary outcomes were individual-level medical expenditures due to obesity, overall, as well as separately by type of payer and category of medical care. Results were reported at the national level and separately for the 20 most populous states. The expenditure estimates were obtained from 2-part models of instrumental variables in which the respondent’s body mass index (BMI) was instrumented using the BMI of their biological child. RESULTS: Adults with obesity in the United States compared with those with normal weight experienced higher annual medical care costs by $2,505 or 100%, with costs increasing significantly with class of obesity, from 68.4% for class 1 to 233.6% for class 3. The effects of obesity raised costs in every category of care: inpatient, outpatient, and prescription drugs. Increases in medical expenditures due to obesity were higher for adults covered by public health insurance programs ($2,868) than for those having private health insurance ($2,058). In 2016, the aggregate medical cost due to obesity among adults in the United States was $260.6 billion. The increase in individual-level expenditures due to obesity varied considerably by state (e.g., 24.0% in Florida, 66.4% in New York, and 104.9% in Texas). CONCLUSIONS: The 2-part models of instrumental variables, which estimate the causal effects of obesity on direct medical costs, showed that the effect of obesity is greater than suggested by previous studies, which estimated only correlations. Much of the aggregate national cost of obesity—$260.6 billion—represents external costs, providing a rationale for interventions to prevent and reduce obesity. DISCLOSURES: Novo Nordisk financed the development of the study design, analysis, and interpretation of data, as well as writing support of the manuscript. Cawley, Biener, and Meyerhoefer received financial support from Novo Nordisk to conduct the research study on which this manuscript is based. Smolarz and Ramasamy are employees of Novo Nordisk. Ding and Zvenyach have no conflicts to declare. Our research has been presented as a poster at the 2020 Academy Health Annual Research Meeting (Virtual), July 28-August 6, 2020.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.18553/jmcp.2021.20410

Cites

43 of 43 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 1

  1. Judkins DR. Fay's method for variance estimation. J Off Stat. 1990;6(3):223-39.

Cited by

Sorted by citations

Authors
Cawley, J., Biener, A., Meyerhoefer, C., Ding, Y., Zvenyach, T., Smolarz, B. G., & Ramasamy, A.
Affiliations
  • Cornell University (US)
  • Lafayette College (US)
  • Lehigh University (US)
  • Bluebird Bio (United States) (US)
  • Independent Advisor, Healthcare and Obesity Public Policy, Madison, WI.
  • Novo Nordisk, Plainsboro, NJ.
Venue
Journal of Managed Care & Specialty Pharmacy
Published
2021-03
Volume
27
Issue
3
Pages
354-366
ISSN
  • 2376-0540 (ISSN-L)
  • 2376-1032
OpenAlex
W3125193263
Cited by
400
References
43
Citations by year
2026: 46 · 2025: 103 · 2024: 101 · 2023: 91 · 2022: 49 · 2021: 9 · 2020: 1
FWCI
54.17
Type
journal article
Language
en
Open access
Locations
  • Journal of Managed Care & Specialty Pharmacy (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
  • Health Sciences › Health Professions › Pharmacy › Obesity and Health Practices
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Healthcare Policy and Management
Keywords
obesity, direct medical costs, health care expenditure, body mass index, public health insurance, private health insurance, inpatient care, outpatient care, prescription drug costs, state-level variation, obesity prevention, United States, Medical Expenditure Panel Survey
MeSH terms
Adult, Aged, Cross-Sectional Studies, Female, Florida, Humans, Male, Middle Aged, New York, Obesity, Population Density, Texas, United States, Health Care Costs, Young Adult

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review