Mexican immigrant health advantage in metabolic syndrome? Examining the contributions of demographic, socioeconomic, and health behavior characteristics

Ethnic differences in metabolic syndrome in high-income countries: A systematic review and meta-analysis

This review aimed to systematically quantify the differences in Metabolic Syndrome (MetS) prevalence across various ethnic groups in high-income countries by sex, and to evaluate the overall prevalence trends from 1996 to 2022. We conducted a systematic literature review using MEDLINE, Web of Science Core Collection, CINAHL, and the Cochrane Library, focusing on studies about MetS prevalence among ethnic groups in high-income countries. We pooled 23 studies that used NCEP-ATP III criteria and included 147,756 healthy participants aged 18 and above. We calculated pooled prevalence estimates and 95% confidence intervals (CI) using both fixed-effect and random-effect intercept logistic regression models. Data were analysed for 3 periods: 1996-2005, 2006-2009, and 2010-2021. The pooled prevalence of MetS in high-income countries, based on the NCEP-ATP III criteria, was 27.4% over the studied period, showing an increase from 24.2% in 1996-2005 to 31.9% in 2010-2021, with men and women having similar rates. When stratified by ethnicity and sex, ethnic minority women experienced the highest prevalence at 31.7%, while ethnic majority women had the lowest at 22.7%. Notably, MetS was more prevalent in ethnic minority women than men. Among ethnic minorities, women had a higher prevalence of MetS than men, and the difference was highest in Asians (about 15 percentage points). Among women, the prevalence of MetS was highest in Asians (41.2%) and lowest in Blacks/Africans (26.7%). Among men, it was highest in indigenous minority groups (34.3%) and lowest among in Blacks/Africans (19.8%). MetS is increasing at an alarming rate in high-income countries, particularly among ethnic minority women. The burden of MetS could be effectively reduced by tailoring interventions according to ethnic variations and risk profiles.

Social and Psychosocial Determinants of Racial and Ethnic Differences in Cardiovascular Health in the United States Population

BACKGROUND

Social and psychosocial factors are associated with cardiovascular health (CVH). Our objective was to examine the contributions of individual-level social and psychosocial factors to racial and ethnic differences in population CVH in the NHANES (National Health and Nutrition Examination Surveys) 2011 to 2018, to inform strategies to mitigate CVH inequities.

METHODS

In NHANES participants ages ≥20 years, Kitagawa-Blinder-Oaxaca decomposition estimated the statistical contribution of individual-level factors (education, income, food security, marital status, health insurance, place of birth, depression) to racial and ethnic differences in population mean CVH score (range, 0-14, accounting for diet, smoking, physical activity, body mass index, blood pressure, cholesterol, blood glucose) among Hispanic, non-Hispanic Asian, or non-Hispanic Black adults compared with non-Hispanic White adults.

RESULTS

Among 16 172 participants (representing 255 million US adults), 24% were Hispanic, 12% non-Hispanic Asian, 23% non-Hispanic Black, and 41% non-Hispanic White. Among men, mean (SE) CVH score was 7.45 (2.3) in Hispanic, 8.71 (2.2) in non-Hispanic Asian, 7.48 (2.4) in non-Hispanic Black, and 7.58 (2.3) in non-Hispanic White adults. In Kitagawa-Blinder-Oaxaca decomposition, education explained the largest component of CVH differences among men (if distribution of education were similar to non-Hispanic White participants, CVH score would be 0.36 [0.04] points higher in Hispanic, 0.24 [0.04] points lower in non-Hispanic Asian, and 0.23 [0.03] points higher in non-Hispanic Black participants; P<0.05). Among women, mean (SE) CVH score was 8.03 (2.4) in Hispanic, 9.34 (2.1) in non-Hispanic Asian, 7.43 (2.3) in non-Hispanic Black, and 8.00 (2.5) in non-Hispanic White adults. Education explained the largest component of CVH difference in non-Hispanic Black women (if distribution of education were similar to non-Hispanic White participants, CVH score would be 0.17 [0.03] points higher in non-Hispanic Black participants; P<0.05). Place of birth (born in the United States versus born outside the United States) explained the largest component of CVH difference in Hispanic and non-Hispanic Asian women (if distribution of place of birth were similar to non-Hispanic White participants, CVH score would be 0.36 [0.07] points lower and 0.49 [0.16] points lower, respectively; P<0.05).

CONCLUSIONS

Education and place of birth confer the largest statistical contributions to the racial and ethnic differences in mean CVH score among US adults.