|Title||Validating a summary measure of weight history for modeling the health consequences of obesity.|
|Publication Type||Journal Article|
|Year of Publication||2016|
|Authors||Stokes, AC, Ni, Y|
|Date Published||2016 12|
|Keywords||Aged, Aged, 80 and over, Body Mass Index, Body Weight, Chronic disease, Female, Health Surveys, Humans, Logistic Models, Longitudinal Studies, Male, Middle Aged, Obesity, Self Report, United States|
PURPOSE: Data on weight history may enhance the predictive validity of epidemiologic models of the health risks of obesity, but collecting such data is often not feasible. In this study, we investigate the validity of a summary measure of weight history.
METHODS: We evaluated the quality of reporting of maximum weight in a sample of adults aged 50-84 years using data from the Health and Retirement Study. Recalled max body mass index (BMI, measured in kilogram per square meter) based on recalled weight in 2004 was compared with calculated max BMI based on self-reported weight collected biennially between 1992 and 2004. Logistic regression was used to assess similarity between the measures in predicting prevalent conditions.
RESULTS: The correlation coefficient between recalled and calculated max weight in the overall sample was 0.95. Recalled max BMI value was within three BMI units of the calculated value 91.4% of the time. The proportions of individuals with obese I (BMI: 30.0-34.9), obese II (BMI: 35.0-39.9), and obese III (BMI: 40.0 and above) were 28.8%, 12.7%, and 6.6% using recalled values compared with 27.1%, 10.5%, and 4.9% using calculated values. In multivariate analyses, the two BMI measures similarly predicted disease prevalence across a number of chronic conditions.
CONCLUSIONS: Recalled max BMI was strongly correlated with max BMI calculated over the 12-year period before recall, suggesting that this measure can serve as a reliable summary measure of recent weight status.
|User Guide Notes|
|Short Title||Annals of Epidemiology|
|Alternate Journal||Ann Epidemiol|
|PubMed Central ID||PMC5142761|
|Grant List||R01 AG040212 / AG / NIA NIH HHS / United States |
R03 SH000037 / SH / NCHS CDC HHS / United States