Andrew Stokes1, Samuel H Preston2. 1. Department of Global Health, Center for Global Health and Development, Boston University School of Public Health, Boston, MA, USA. Electronic address: acstokes@bu.edu. 2. Department of Sociology, Population Studies Center, University of Pennsylvania, Philadelphia, PA, USA.
Abstract
OBJECTIVE: We assessed the contribution of increasing adiposity to the rising prevalence of diabetes in the United States over the period 1988-2014. RESEARCH DESIGN AND METHODS: Data from NHANES III (1988-1994) and continuous waves (1999-2014) were pooled for the current study. Diabetes status was assessed using data on Hemoglobin A1c. We estimated a multivariable logistic regression model that predicted the odds of having diabetes as a function of age, sex, racial/ethnic group, educational attainment, and period of observation. At a second stage, we introduced measures of general and abdominal adiposity into the model. Changes in coefficients pertaining to period of observation between the first and second models were interpreted as indicating the extent to which adiposity can account for trends in the prevalence of diabetes. Sensitivity analyses were conducted to investigate how alternative definitions of adiposity and diabetes status would affect results. RESULTS: The predicted prevalence of diabetes rose by 2.59%/yr between 1988 and 2014 after adjusting for changes in population composition. Increasing adiposity explained 72% of the rise in diabetes. Results were consistent for men and women. CONCLUSIONS: Rising levels of adiposity explained the large majority of the rise in diabetes prevalence between 1988 and 2014.
OBJECTIVE: We assessed the contribution of increasing adiposity to the rising prevalence of diabetes in the United States over the period 1988-2014. RESEARCH DESIGN AND METHODS: Data from NHANES III (1988-1994) and continuous waves (1999-2014) were pooled for the current study. Diabetes status was assessed using data on Hemoglobin A1c. We estimated a multivariable logistic regression model that predicted the odds of having diabetes as a function of age, sex, racial/ethnic group, educational attainment, and period of observation. At a second stage, we introduced measures of general and abdominal adiposity into the model. Changes in coefficients pertaining to period of observation between the first and second models were interpreted as indicating the extent to which adiposity can account for trends in the prevalence of diabetes. Sensitivity analyses were conducted to investigate how alternative definitions of adiposity and diabetes status would affect results. RESULTS: The predicted prevalence of diabetes rose by 2.59%/yr between 1988 and 2014 after adjusting for changes in population composition. Increasing adiposity explained 72% of the rise in diabetes. Results were consistent for men and women. CONCLUSIONS: Rising levels of adiposity explained the large majority of the rise in diabetes prevalence between 1988 and 2014.
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