Sandra S Albrecht1,2, Elizabeth Mayer-Davis1,3, Barry M Popkin1,2. 1. Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA. 2. Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA. 3. Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA.
Abstract
BACKGROUND: For the same body mass index (BMI) level, waist circumference (WC) is higher in more recent years. How this impacts diabetes and prediabetes prevalence in the United States and for different race/ethnic groups is unknown. We examined prevalence differences in diabetes and prediabetes by BMI over time, investigated whether estimates were attenuated after adjusting for waist circumference, and evaluated implications of these patterns on race/ethnic disparities in glycemic outcomes. METHODS: Data came from 12 614 participants aged 20 to 74 years from the National Health and Nutrition Examination Surveys (1988-1994 and 2007-2012). We estimated prevalence differences in diabetes and prediabetes by BMI over time in multivariable models. Relevant interactions evaluated race/ethnic differences. RESULTS: Among normal, overweight, and class I obese individuals, there were no significant differences in diabetes prevalence over time. However, among individuals with class II/III obesity, diabetes prevalence rose 7.6 percentage points in 2007-2012 vs 1988-1994. This estimate was partly attenuated after adjustment for mean waist circumference but not mean BMI. For prediabetes, prevalence was 10 to 13 percentage points higher over time at lower BMI values, with minimal attenuation after adjustment for WC. All patterns held within race/ethnic groups. Diabetes disparities among blacks and Mexican Americans relative to whites remained in both periods, regardless of BMI, and persisted after adjustment for WC. CONCLUSIONS: Diabetes prevalence rose over time among individuals with class II/III obesity and may be partly due to increasing waist circumference. Anthropometric measures did not appear to account for temporal increases in prediabetes, nor did they attenuate race/ethnic disparities in diabetes. Reasons underlying these trends require further investigation.
BACKGROUND: For the same body mass index (BMI) level, waist circumference (WC) is higher in more recent years. How this impacts diabetes and prediabetes prevalence in the United States and for different race/ethnic groups is unknown. We examined prevalence differences in diabetes and prediabetes by BMI over time, investigated whether estimates were attenuated after adjusting for waist circumference, and evaluated implications of these patterns on race/ethnic disparities in glycemic outcomes. METHODS: Data came from 12 614 participants aged 20 to 74 years from the National Health and Nutrition Examination Surveys (1988-1994 and 2007-2012). We estimated prevalence differences in diabetes and prediabetes by BMI over time in multivariable models. Relevant interactions evaluated race/ethnic differences. RESULTS: Among normal, overweight, and class I obese individuals, there were no significant differences in diabetes prevalence over time. However, among individuals with class II/III obesity, diabetes prevalence rose 7.6 percentage points in 2007-2012 vs 1988-1994. This estimate was partly attenuated after adjustment for mean waist circumference but not mean BMI. For prediabetes, prevalence was 10 to 13 percentage points higher over time at lower BMI values, with minimal attenuation after adjustment for WC. All patterns held within race/ethnic groups. Diabetes disparities among blacks and Mexican Americans relative to whites remained in both periods, regardless of BMI, and persisted after adjustment for WC. CONCLUSIONS:Diabetes prevalence rose over time among individuals with class II/III obesity and may be partly due to increasing waist circumference. Anthropometric measures did not appear to account for temporal increases in prediabetes, nor did they attenuate race/ethnic disparities in diabetes. Reasons underlying these trends require further investigation.
Authors: Kexin Li; Tianyu Feng; Lijuan Wang; Yang Chen; Pingping Zheng; Pan Pan; Min Wang; Isaac T S Binnay; Yingshuang Wang; Ruiyu Chai; Siyu Liu; Bo Li; Yan Yao Journal: Mol Genet Genomics Date: 2021-02-25 Impact factor: 3.291
Authors: Tomi Akinyemiju; Justin Xavier Moore; Suzanne Judd; Susan Lakoski; Michael Goodman; Monika M Safford; Maria Pisu Journal: BMC Cancer Date: 2017-12-15 Impact factor: 4.430