Error bars indicate 95% CIs. Hispanic race/ethnicity includes Mexican American or other Hispanic race. Other race/ethnicity includes other non-Hispanic races, including non-Hispanic multiracial. Comparisons of prevalence estimates between age groups among the specified demographic subgroups were performed using χ2 tests. All comparisons yielded P <.001.
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Hirode G, Wong RJ. Trends in the Prevalence of Metabolic Syndrome in the United States, 2011-2016. JAMA. 2020;323(24):2526–2528. doi:10.1001/jama.2020.4501
Metabolic syndrome is associated with increased risk for cardiovascular disease and all-cause mortality.1,2 A previous study reported a prevalence of 33% in adults, which remained stable from 2007 to 2012.3 Understanding current trends in metabolic syndrome prevalence may help identify patients who would benefit from improved screening and optimization of cardiovascular risk profiles. We provide an updated analysis of metabolic syndrome prevalence through 2016.
Using National Health and Nutrition Examination Survey (NHANES) data from 2011 to 2016, a cross-sectional, stratified, multistage probability sample of the US population, we evaluated trends in metabolic syndrome prevalence among adults (aged ≥20 years). NHANES was approved by the institutional review board at the National Center for Health Statistics and written consent was obtained from participants. From 2011 to 2016, unweighted response rates ranged from 58.7% to 69.5%. Self-reported race/ethnicity was evaluated to determine race-specific differences. Metabolic syndrome was defined based on the National Cholesterol Education Program’s Adult Treatment Panel III as having at least 3 of the following: waist circumference greater than 102 cm in men or 88 cm in women, triglyceride level greater than 150 mg/dL, high-density lipoprotein cholesterol less than 40 mg/dL in men or less than 50 mg/dL in women, systolic blood pressure at least 130 mm Hg or diastolic blood pressure at least 85 mm Hg or taking hypertension medications, or fasting plasma glucose level at least 100 mg/dL or taking diabetes medications. Weighted data were used to estimate the unadjusted prevalence of metabolic syndrome, stratified by age group (20-39, 40-59, and ≥60 years), sex, and race/ethnicity. Tests for trends were assessed, overall and among subgroups, using logistic regression after regressing metabolic syndrome on year (modeled as a continuous predictor). Between-group comparisons used χ2 tests. Statistical significance was met with 2-tailed P <.05. Statistical analyses were performed with Stata, version 15 (StataCorp).
Among 17 048 participants, the weighted metabolic syndrome prevalence was 34.7% (95% CI, 33.1%-36.3% [n = 5885]). Metabolic syndrome prevalence was not significantly different among men and women (35.1% vs 34.3%; P = .47) and was highest among “other” race/ethnicity (39.0%), followed by Hispanic (36.3%) and non-Hispanic white (36.0%) participants (Table). The increase in the overall crude metabolic syndrome prevalence from 2011-2012 to 2015-2016 did not meet statistical significance (from 32.5% [95% CI, 29.0%-36.2%] in 2011-2012 to 36.9% [95% CI, 33.9%-39.9%] in 2015-2016; P = .07 for trend). Over the study period, metabolic syndrome prevalence increased significantly among those aged 20 to 39 years (from 16.2% to 21.3%; P = .02 for trend), women (from 31.7% to 36.6%; P = .04 for trend), Asian participants (from 19.9% to 26.2%; P = .008 for trend), and Hispanic participants (from 32.9% to 40.4%; P = .01 for trend) (Table).
The prevalence of metabolic syndrome significantly increased with increasing age among all subgroups (Figure). Prevalence was 19.5% among those aged 20 to 39 years and increased to 48.6% among those aged at least 60 years. Among each age group, there were no significant differences in metabolic syndrome prevalence between men and women. There were significant differences in prevalence between races/ethnicities among each age group, with the highest prevalence among participants who indicated “other” race/ethnicity who were aged at least 60 years (64.0%), followed by Hispanic participants aged at least 60 years (57.3%).
Although the overall increase in metabolic syndrome prevalence among US adults from 2011-2012 to 2015-2016 did not meet statistical significance, there was a significant increase observed among young adults. Prevalence among those aged 60 years or older remained high.3 The fast-growing prevalence in young adults and Hispanic and Asian individuals is important to note given their increasing population in the US.
With an aging US population and concurrent increases in other chronic conditions and comorbidities,4 increases in the prevalence of metabolic syndrome are concerning. Efforts to implement prevention strategies, including lifestyle modification and use of medications targeted at subgroups at highest risk, may assist in lowering the risk of developing cardiovascular disease.5,6
Limitations inherent in the use of NHANES data, such as nonresponse bias and potential misclassification based on medication use, should be acknowledged. Causal inference could not be drawn due to the cross-sectional nature of the study. No information was available on severity or control of each metabolic syndrome component. Lack of the use of race-specific abdominal obesity cut points may have affected the accuracy of the estimates, particularly for Asian participants. There exists the possibility of insufficient power to detect significant differences between groups or over the study period.
Corresponding Author: Robert J. Wong, MD, MS, Division of Gastroenterology and Hepatology, Veterans Affairs Palo Alto Health Care System, 3801 Miranda Ave, GI Endoscopy Unit, Palo Alto, CA 94304 (email@example.com).
Accepted for Publication: March 16, 2020.
Author Contributions: Dr Wong had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: All authors.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: Hirode.
Critical revision of the manuscript for important intellectual content: Wong.
Statistical analysis: Hirode.
Administrative, technical, or material support: Wong.
Conflict of Interest Disclosures: Dr Wong reported receiving research grants from Gilead Sciences and Abbvie and being part of the advisory board and speaker’s bureau for Gilead Sciences. No other disclosures were reported.
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