Trends in Metabolically Unhealthy Obesity by Age, Sex, Race/Ethnicity, and Income among United States Adults, 1999 to 2018
- Author:
Wen ZENG
1
;
Weijiao ZHOU
;
Junlan PU
;
Juan LI
;
Xiao HU
;
Yuanrong YAO
;
Shaomei SHANG
Author Information
- Publication Type:Original Article
- From:Diabetes & Metabolism Journal 2025;49(3):475-484
- CountryRepublic of Korea
- Language:English
-
Abstract:
Background:This study aimed to estimate temporal trends in metabolically unhealthy obesity (MUO) among United States (US) adults by age, sex, race/ethnicity, and income from 1999 to 2018.
Methods:We included 17,230 non-pregnant adults from a nationally representative cross-sectional study, the National Health and Nutrition Examination Survey (NHANES). MUO was defined as body mass index ≥30 kg/m2 with any metabolic disorders in blood pressure, blood glucose, and blood lipids. The age-adjusted percentage of MUO was calculated, and linear regression models estimated trends in MUO.
Results:The weighted mean age of adults was 47.28 years; 51.02% were male, 74.64% were non-Hispanic White. The age-adjusted percentage of MUO continuously increased in adults across all subgroups during 1999–2018, although with different magnitudes (all P<0.05 for linear trend). Adults aged 45 to 64 years consistently had higher percentages of MUO from 1999–2000 (34.25%; 95% confidence interval [CI], 25.85% to 42.66%) to 2017–2018 (42.03%; 95% CI, 35.09% to 48.97%) than the other two age subgroups (P<0.05 for group differences). The age-adjusted percentage of MUO was the highest among non-Hispanic Blacks while the lowest among non-Hispanic Whites in most cycles. Adults with high-income levels generally had lower MUO percentages from 1999–2000 (22.63%; 95% CI, 17.00% to 28.26%) to 2017–2018 (32.36%; 95% CI, 23.87% to 40.85%) compared with the other two subgroups.
Conclusion:This study detected a continuous linear increasing trend in MUO among US adults from 1999 to 2018. The persistence of disparities by age, race/ethnicity, and income is a cause for concern. This calls for implementing evidence-based, structural, and effective MUO prevention programs.
