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Kidney and cardiovascular disease are widespread among populations with high prevalence of diabetes, such as American Indians participating in the Strong Heart Study (SHS). Studying these conditions simultaneously in longitudinal studies is challenging, because the morbidity and mortality associated with these diseases result in missing data, and these data are likely not missing at random. When such data are merely excluded, study findings may be compromised. In this article, a subset of 2264 participants with complete renal function data from Strong Heart Exams 1 (1989–1991), 2 (1993–1995), and 3 (1998–1999) was used to examine the performance of five methods used to impute missing data: listwise deletion, mean of serial measures, adjacent value, multiple imputation, and pattern-mixture. Three missing at random models and one non-missing at random model were used to compare the performance of the imputation techniques on randomly and non-randomly missing data. The pattern-mixture method was found to perform best for imputing renal function data that were not missing at random. Determining whether data are missing at random or not can help in choosing the imputation method that will provide the most accurate results. [ABSTRACT FROM AUTHOR]

This study evaluated the association of arsenic exposure, as measured in urine, with diabetes prevalence, glycated hemoglobin, and insulin resistance in American Indian adults from Arizona, Oklahoma, and North and South Dakota (1989–1991). We studied 3,925 men and women 45–74 years of age with available urine arsenic measures. Diabetes was defined as a fasting glucose level of 126 mg/dL or higher, a 2-hour glucose level of 200 mg/dL or higher, a hemoglobin A1c (HbA1c) of 6.5% or higher, or diabetes treatment. Median urine arsenic concentration was 14.1 µg/L (interquartile range, 7.9–24.2). Diabetes prevalence was 49.4%. After adjustment for sociodemographic factors, diabetes risk factors, and urine creatinine, the prevalence ratio of diabetes comparing the 75th versus 25th percentiles of total arsenic concentrations was 1.14 (95% confidence interval: 1.08, 1.21). The association between arsenic and diabetes was restricted to participants with poor diabetes control (HbA1c ≥8%). Arsenic was positively associated with HbA1c levels in participants with diabetes. Arsenic was not associated with HbA1c or with insulin resistance (assessed by homeostatic model assessment to quantify insulin resistance) in participants without diabetes. Urine arsenic was associated with diabetes control in a population from rural communities in the United States with a high burden of diabetes. Prospective studies that evaluate the direction of the relation between poor diabetes control and arsenic exposure are needed. [ABSTRACT FROM PUBLISHER]

Improved accuracy in predicting coronary heart disease (CHD) risk in patients with diabetes and kidney disease is needed. The addition of albuminuria to established methods of CHD risk calculation was reported in the Strong Heart Study (SHS) cohort. In this study, the addition of estimated glomerular filtration rate (eGFR) was evaluated using data from 4,549 American Indian SHS participants aged 45 to 74 years. After adjustment for Framingham CHD risk factors, hazard ratios for eGFR as a predictor of CHD were 1.69 (95% confidence interval 1.34 to 2.13) in women and 1.41 (95% confidence interval 0.94 to 2.13) in men. Models including albuminuria, eGFR, or both scored higher in discriminatory power than models using conventional risk factors alone in women; in men, the improvement was seen only for albuminuria and the combination of albuminuria and eGFR. Hosmer-Lemeshow assessments showed good calibration for the models using eGFR alone in both genders, followed by models including albuminuria alone in both genders. Adding eGFR improved the net reclassification improvement (NRI) in women (0.085, p = 0.0004) but not in men (0.010, p = 0.1967). NRI and integrated discrimination improvement (IDI) were improved in both genders using albuminuria and eGFR (NRI 0.135, p <0.0001, and IDI 0.027, p <0.0001 in women; NRI 0.035, p <0.0196, and IDI 0.008, p <0.0156 in men). Therefore, a risk calculator including albuminuria enhances CHD prediction compared to a calculator using only standard risk factors in men and women. Including eGFR alone improves risk prediction in women, but for men, it is preferable to include eGFR and albuminuria. In conclusion, this enhanced calculator should be useful in estimating CHD risk in populations with high prevalence of diabetes and renal disease. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to examine the association between sugar-sweetened beverage (SSB) consumption and dental caries prevalence among underserved Black adolescents. Methods: This was a cross-sectional study of 545 Black adolescents, ages 12 to 17 years, who participated in the Howard Meharry Adolescent Caries Study (HMACS). The outcome was dental caries prevalence, measured using the decayed, missing, and filled permanent tooth surfaces (DMFS) index. Participants were recruited from middle and high schools in Washington, D.C., USA, and Nashville, Tenn., USA. Questionnaires were used to assess beverage intake, demographic, and health-related behavioral characteristics. The multivariable analysis used marginalized zero-inflated Poisson regression (MZIP) stratified by toothbrushing frequency to estimate adjusted mean caries ratios (MRs), adjusted odds ratios (ORs), and 95 percent confidence intervals (95 percent CIs). Results: The mean age of the participants was 14.1 years. Participants in the highest quartile for SSB consumption had a higher caries ratio than those in the lowest quartile [MR equals (=) 1.59, 95 percent CI equals 1.15 to 2.20] and a lower odds of not being at risk for caries (OR = 0.24, 95 percent CI = 0.09 to 0.61). These findings were only observed among those brushing once a day or less (n=202). Conclusions: Among Black adolescents in this study who brushed once a day or less, high levels of sugar-sweetened beverage consumption were associated with greater caries prevalence and a reduced likelihood of remaining caries-free than those with lower levels of SSB consumption. Future studies will focus on interventions to reduce SSB consumption. [ABSTRACT FROM AUTHOR]