RESUMO
PURPOSE: This study evaluated the impact of obesity on cardiometabolic risk factors (CRF) interrelationships and predictive efficiency of CVD development in older African (AA) and European Americans (EA). DESIGN: A comparative research design evaluated CRF risk profile differences between participant groups. SETTING: Seven neighborhoods in a southern US city. SUBJECTS: A sample of 179 older AA (n = 128) and EA (n = 51) adults. MEASURES: Non-fasting blood samples were evaluated for lipids and lipoproteins, glycosylated hemoglobin, systolic -(SBP) and diastolic blood pressure (DBP), body mass index (BMI), body fat percentage (BF%) and physical function. ANALYSIS: Data were analysis with descriptive statistics, t-tests, and correlations. RESULTS: AA were heavier than EA although all had above average age-appropriate fitness. Means and relationships between CRF and other variables were different (P < .05) based on race. Both AA (41.3 + 5.8) and EA (38.6 + 6.4) BF% were CRF risks. Holding BMI constant, CRF were generally not related, and the relationships were different for AA and EA. AA had a range of 13.0 to 27.2% more favorable values for cholesterol, HDL-C, and triglyceride. EA had favorable A1c (EA 5.8 vs AA 6.2%) values. CONCLUSIONS: A limitation of this report is the small sample size. Although further research is warranted, these findings suggest population specific CRF selections would improve CVD prediction in AA.
RESUMO
Cardiometabolic (CMO) risks factors do not provide similar cardiovascular disease (CVD) predictions in young African (AA) and European Americans (EA) adults. Whether CMO risk predictions contribute to this disparity in older adults is unclear. We hypothesize that older AA CMO clustering pattern will be different from EA clustering patterns when determine with non-fasting lipid and lipoproteins. The participants were 106 older adults (66 AA and 40 EA) from a working/middle class neighborhood (income $46,364 - $80,904) in an urban North Carolina community. The participants were evaluated for CMO risk factors (total cholesterol, high- (HDL) and low-density lipoproteins (LDL), triglyceride (TG), glycosylated hemoglobin (HbA1c), systolic -SBP- and diastolic blood pressures -DBP), body mass index (BMI), body fat % (BF%) and timed up and go test (assessed falls risk and physical function). The AA participants were heavier, had higher BMI, BF%, and timed up and go values (p < 0.01). The data were evaluated for differences (t-test) and Pearson correlations for relationships. If data differ by p < 0.05 the data were significantly different. The AA had a 17.6 % higher HDL (64.7 vs 55.1 mg/dL - p < 0.05) and 7.6 % higher HbA1c (5.8 vs 5.4 % - p < 0.01) than EA. Higher HDL values in EA indicate lower CVD risks. The HDL paradox for AA (AA had higher HDL values, but greater CVD risks) was observed and the HbA1c difference may be misleading, as similar glucose values in AA tend to have higher HbA1c values. Lipid, lipoprotein, and blood pressure was not different between the races. AA had higher body composition and HDL values. Although future research on this topic with larger samples, dietary data and detailed descriptions of participations medications is warranted to validate findings from this study. These data suggest older AA and EA adults with similar environmental conditions have similar CMO risks when measures with none fasting blood samples. Since AA have a greater prevalence of CVD, these finding suggests that population specific CMO risk factor clustering may be more effective predictors of CVD for AA.
