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      Race/Ethnicity Disparities in Dysglycemia Among U.S. Women of Childbearing Age Found Mainly in the Nonoverweight/Nonobese

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          Abstract

          OBJECTIVE

          To describe the burden of dysglycemia—abnormal glucose metabolism indicative of diabetes or high risk for diabetes—among U.S. women of childbearing age, focusing on differences by race/ethnicity.

          RESEARCH DESIGN AND METHODS

          Using U.S. National Health and Nutrition Examination Survey data (1999–2008), we calculated the burden of dysglycemia (i.e., prediabetes or diabetes from measures of fasting glucose, A1C, and self-report) in nonpregnant women of childbearing age (15–49 years) by race/ethnicity status. We estimated prevalence risk ratios (PRRs) for dysglycemia in subpopulations stratified by BMI (measured as kilograms divided by the square of height in meters), using predicted marginal estimates and adjusting for age, waist circumference, C-reactive protein, and socioeconomic factors.

          RESULTS

          Based on data from 7,162 nonpregnant women, representing >59,000,000 women nationwide, 19% (95% CI 17.2–20.9) had some level of dysglycemia, with higher crude prevalence among non-Hispanic blacks and Mexican Americans vs. non-Hispanic whites (26.3% [95% CI 22.3–30.8] and 23.8% [19.5–28.7] vs. 16.8% [14.4–19.6], respectively). In women with BMI <25 kg/m 2, dysglycemia prevalence was roughly twice as high in both non-Hispanic blacks and Mexican Americans vs. non-Hispanic whites. This relative increase persisted in adjusted models (PRR adj 1.86 [1.16–2.98] and 2.23 [1.38–3.60] for non-Hispanic blacks and Mexican Americans, respectively). For women with BMI 25–29.99 kg/m 2, only non-Hispanic blacks showed increased prevalence vs. non-Hispanic whites (PRR adj 1.55 [1.03–2.34] and 1.28 [0.73–2.26] for non-Hispanic blacks and Mexican Americans, respectively). In women with BMI >30 kg/m 2, there was no significant increase in prevalence of dysglycemia by race/ethnicity category.

          CONCLUSIONS

          Our findings show that dysglycemia affects a significant portion of U.S. women of childbearing age and that disparities by race/ethnicity are most prominent in the nonoverweight/nonobese.

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          Most cited references27

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          Prevalence of diabetes and impaired fasting glucose in adults in the U.S. population: National Health And Nutrition Examination Survey 1999-2002.

          The purpose of this study was to examine the prevalences of diagnosed and undiagnosed diabetes, and impaired fasting glucose (IFG) in U.S. adults during 1999-2002, and compare prevalences to those in 1988-1994. The National Health and Nutrition Examination Survey (NHANES) contains a probability sample of adults aged > or =20 years. In the NHANES 1999-2002, 4,761 adults were classified on glycemic status using standard criteria, based on an interview for diagnosed diabetes and fasting plasma glucose measured in a subsample. The crude prevalence of total diabetes in 1999-2002 was 9.3% (19.3 million, 2002 U.S. population), consisting of 6.5% diagnosed and 2.8% undiagnosed. An additional 26.0% had IFG, totaling 35.3% (73.3 million) with either diabetes or IFG. The prevalence of total diabetes rose with age, reaching 21.6% for those aged > or =65 years. The prevalence of diagnosed diabetes was twice as high in non-Hispanic blacks and Mexican Americans compared with non-Hispanic whites (both P < 0.00001), whereas the prevalence of undiagnosed diabetes was similar by race/ethnicity, adjusted for age and sex. The prevalence of diagnosed diabetes was similar by sex, but prevalences of undiagnosed diabetes and IFG were significantly higher in men. The crude prevalence of diagnosed diabetes rose significantly from 5.1% in 1988-1994 to 6.5% in 1999-2002, but the crude prevalences were stable for undiagnosed diabetes (from 2.7 to 2.8%) and IFG (from 24.7 to 26.0%). Results were similar after adjustment for age and sex. Although the prevalence of diagnosed diabetes has increased significantly over the last decade, the prevalences of undiagnosed diabetes and IFG have remained relatively stable. Minority groups remain disproportionately affected.
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            Normal weight obesity: a risk factor for cardiometabolic dysregulation and cardiovascular mortality.

            We hypothesized that subjects with a normal body mass index (BMI), but high body fat (BF) content [normal weight obesity (NWO)], have a higher prevalence of cardiometabolic dysregulation and are at higher risk for cardiovascular (CV) mortality. We analysed 6171 subjects >20 years of age from the Third National Health and Nutrition Examination Survey (NHANES III) and the NHANES III mortality study, whose BMI was within the normal range (18.5-24.9 kg/m(2)), and who underwent a complete evaluation that included body composition assessment, blood measurements, and assessment of CV risk factors. Survival information was available for >99% of the subjects after a median follow-up of 8.8 years. We divided our sample using sex-specific tertiles of BF%. The highest tertile of BF (>23.1% in men and >33.3% in women) was labelled as NWO. When compared with the low BF group, the prevalence of metabolic syndrome in subjects with NWO was four-fold higher (16.6 vs. 4.8%, P < 0.0001). Subjects with NWO also had higher prevalence of dyslipidaemia, hypertension (men), and CV disease (women). After adjustment, women with NWO showed a significant 2.2-fold increased risk for CV mortality (HR = 2.2; 95% CI, 1.03-4.67) in comparison to the low BF group. Normal weight obesity, defined as the combination of normal BMI and high BF content, is associated with a high prevalence of cardiometabolic dysregulation, metabolic syndrome, and CV risk factors. In women, NWO is independently associated with increased risk for CV mortality.
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              Estimating model-adjusted risks, risk differences, and risk ratios from complex survey data.

              There is increasing interest in estimating and drawing inferences about risk or prevalence ratios and differences instead of odds ratios in the regression setting. Recent publications have shown how the GENMOD procedure in SAS (SAS Institute Inc., Cary, North Carolina) can be used to estimate these parameters in non-population-based studies. In this paper, the authors show how model-adjusted risks, risk differences, and risk ratio estimates can be obtained directly from logistic regression models in the complex sample survey setting to yield population-based inferences. Complex sample survey designs typically involve some combination of weighting, stratification, multistage sampling, clustering, and perhaps finite population adjustments. Point estimates of model-adjusted risks, risk differences, and risk ratios are obtained from average marginal predictions in the fitted logistic regression model. The model can contain both continuous and categorical covariates, as well as interaction terms. The authors use the SUDAAN software package (Research Triangle Institute, Research Triangle Park, North Carolina) to obtain point estimates, standard errors (via linearization or a replication method), confidence intervals, and P values for the parameters and contrasts of interest. Data from the 2006 National Health Interview Survey are used to illustrate these concepts.
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                Author and article information

                Journal
                Diabetes Care
                Diabetes Care
                diacare
                dcare
                Diabetes Care
                Diabetes Care
                American Diabetes Association
                0149-5992
                1935-5548
                October 2013
                14 September 2013
                : 36
                : 10
                : 3033-3039
                Affiliations
                [1] 1National Center on Birth Defects and Developmental Disabilities, Division of Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention, Atlanta, Georgia
                [2] 2Oak Ridge Institute for Science and Education, Oak Ridge Associated Universities, Oak Ridge, Tennessee
                [3] 3Program in Nutrition and Health Sciences, Graduate Division of Biological and Biomedical Sciences, Laney Graduate School, Emory University, Atlanta, Georgia
                [4] 4Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, Georgia
                [5] 5D-Tree International, Weston, Massachusetts
                [6] 6Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi.
                Author notes
                Corresponding author: Jessica A. Marcinkevage, jmarcinkevage@ 123456cdc.gov .
                Article
                2312
                10.2337/dc12-2312
                3781530
                23780951
                afd9506a-5bfc-48f9-b686-680704ea4cc2
                © 2013 by the American Diabetes Association.

                Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details.

                History
                : 7 November 2012
                : 5 April 2013
                Page count
                Pages: 7
                Categories
                Original Research
                Epidemiology/Health Services Research

                Endocrinology & Diabetes
                Endocrinology & Diabetes

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