Heterogeneity in familial clustering of metabolic syndrome components in the multiethnic GENNID study

• Published in: Obesity (Silver Spring, Md.) Vol. 32; no. 1; pp. 176 - 186
• Main Authors: Wan, Jia Y., Goodman, Deborah, Makhnoon, Sukh, Norden‐Krichmar, Trina M., Wu, Baolin, Edwards, Karen L.
• Format: Journal Article
• Language: English
• Published: United States 01.01.2024
• Subjects: Cholesterol; Cluster Analysis; Humans; Hypertension - epidemiology; Lipoproteins, HDL; Metabolic Syndrome - epidemiology; Metabolic Syndrome - genetics; Obesity; Obesity, Abdominal - epidemiology; Risk Factors; Triglycerides
• ISSN: 1930-7381; 1930-739X
• DOI: 10.1002/oby.23914

Objective Metabolic syndrome (MetS) is defined by clustering of cardiometabolic components, which may be present in different combinations. The authors evaluated clustering in individuals and extended families within and across ancestry groups. Methods The prevalence of different combinations of MetS components (high fasting glucose, low high‐density lipoprotein cholesterol, high triglycerides, high blood pressure, and abdominal obesity) was estimated in 1651 individuals (340 families) self‐reporting as European American (EA), Hispanic/Mexican American (MA), African American (AA), and Japanese American (JA). Odds ratios were estimated using logistic regression with generalized estimating equations comparing individual MetS components, number, and combinations of components for each ancestry group versus EA. Results Clustering of all five components (Combination #16) was more prevalent in EA (29.9%) and MA (25.2%) individuals than in AA (18.7%) and JA (15.5%) individuals. Compared with EA individuals, AA individuals were 64% and 66% less likely to have high triglycerides and low high‐density lipoprotein cholesterol, whereas JA individuals were 85% and 56% less likely to have abdominal obesity and high blood pressure, respectively. Compared with EA individuals, the odds of having two, four, or five components were at least 77% lower in JA individuals, whereas the odds of having three, four, or five components were at least 3.79 times greater in MA individuals. Conclusions Understanding heterogeneity in MetS clustering may identify factors important in reducing health disparities.