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Preplanned Studies: Prevalence of Metabolic Syndrome and Risk Factors Among Chinese Adults: Results from a Population-Based Study — Beijing, China, 2017–2018

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  • Summary

    What is already known about this topic?

    Metabolic syndrome (MetS) is one of the most easily available health indicative markers for cardiovascular diseases, and it has become a major public health problem worldwide due to increasing urbanization and aging populations. The prevalence of MetS increased dramatically in China, however, there are no records of MetS defined by the 2017 Chinese Diabetes Society for Beijing by far.

    What is added by this report?

    In this study, the data of 24,412 participants aged 18–74 years from a large population-based study in Beijing was collected. The overall prevalence of MetS among Beijing residents was 24.5%. The prevalence was 35.2% in males and 15.4% in females.

    What are the implications for public health practice?

    Effective public health strategies should target males, people with older age, lower education, higher body mass index, smokers, those who drink alcohol, those who are unemployed or retired, and those who live in rural areas on MetS prevention and control.

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  • Funding: Research Special Fund for Municipal Medical Public Welfare Institute (2017-BJYJ-15); National Natural Science Foundation of China (81373014); CNS-ZD Tizhi and Health Fund (CNS-ZD2020-115)
  • [1] Li CH, Lumey LH. Exposure to the Chinese famine of 1959-61 in early life and long-term health conditions: a systematic review and meta-analysis. Int J Epidemiol 2017;46(4):1157 − 70. http://dx.doi.org/10.1093/ije/dyx013CrossRef
    [2] Li R, Li WC, Lun ZJ, Zhang HP, Sun Z, Kanu JS, et al. Prevalence of metabolic syndrome in Mainland China: a meta-analysis of published studies. BMC Public Health 2016;16:296. http://dx.doi.org/10.1186/s12889-016-2870-yCrossRef
    [3] Cameron AJ, Shaw JE, Zimmet PZ. The metabolic syndrome: prevalence in worldwide populations. Endocrinol Metab Clin North Am 2004;33(2):351 − 75. http://dx.doi.org/10.1016/j.ecl.2004.03.005CrossRef
    [4] Zhang WCB, Du J, Li H, Yang Y, Cai C, Gao Q, et al. Multiple-element exposure and metabolic syndrome in Chinese adults: a case-control study based on the Beijing population health cohort. Environ Int 2020;143:105959. http://dx.doi.org/10.1016/j.envint.2020.105959CrossRef
    [5] Chinese Diabetes Society. The guideline of type 2 diabetes prevention and treatment (2017 Edition). Chin J Diabetes Mellitus 2018;10(1):4 − 67. http://dx.doi.org/10.3760/cma.j.issn.1674-5809.2018.01.003 (In Chinese). CrossRef
    [6] Ma AJ, Fang K, Dong J, Dong Z. Prevalence and related factors of metabolic syndrome in Beijing, China (Year 2017). Obes Facts 2020;13(6):538 − 47. http://dx.doi.org/10.1159/000508842CrossRef
    [7] Wang ZW, Wang X, Li X, Chen Z, Zhao LC, Li Y, et al. Prevalence and trend of metabolic syndrome in middle-aged Chinese population. Chin J Epidemiol 2009;30(6):596 − 600. http://dx.doi.org/10.3760/cma.j.issn.0254-6450.2009.06.015 (In Chinese). CrossRef
    [8] Su YX, Lu YQ, Li WL, Xue MY, Chen C, Haireti M, et al. Prevalence and correlation of metabolic syndrome: a cross-sectional study of nearly 10 million multi-ethnic chinese adults. Diabetes Metab Syndr Obes 2020;13:4869 − 83. http://dx.doi.org/10.2147/dmso.S278346CrossRef
    [9] Ning F, Ren J, Song X, Zhang D, Liu L, Zhang L, et al. Famine exposure in early life and risk of metabolic syndrome in adulthood: comparisons of different metabolic syndrome definitions. J Diabetes Res 2019;2019:7954856. http://dx.doi.org/10.1155/2019/7954856CrossRef
    [10] He YN, Zhao WH, Zhao LY, Yu DM, Zhang J, Yang XG, et al. Prevalence of metabolic syndrome in Chinese adults in 2010-2012. Chin J Epidemiol 2017;38(2):212 − 5. http://dx.doi.org/10.3760/cma.j.issn.0254-6450.2017.02.015 (In Chinese). CrossRef
    [11] Yi Y, An J. Sex differences in risk factors for metabolic syndrome in the Korean population. Int J Environ Res Public Health 2020;17(24):9513. http://dx.doi.org/10.3390/ijerph17249513CrossRef
    [12] Hailili G, Chen Z, Tian T, Fu WH, Pei HL, Mahan Y, et al. Dietary patterns and their associations with the metabolic syndrome and predicted 10-year risk of CVD in Northwest Chinese adults. Br J Nutr 2021;126(6):913 − 22. http://dx.doi.org/10.1017/s000711452000478xCrossRef
  • TABLE 1.  Prevalence of MetS by demographic characteristics, Beijing, China, 2017–2018.

    CharacteristicsMetSControlPPrevalence of MetS
    n%n%%
    Age, years Mean (SD)52.1 (12.9)43.8 (14.4)<0.001
    BMI, kg/m2 Mean (SD) 27.8 (3.7)24.2 (3.8)<0.001
    Han ethnic4,82896.21,486195.80.19924.5
    Sex<0.001
    Male3,30165.86,06539.1 35.2
    Female1,71934.29,45460.9 15.4
    Age group (years)<0.001
    ≤24651.31,1237.25.5
    25–3463612.74,23327.3 13.1
    35–4466213.22,77117.9 19.3
    45–541,05521.02,98119.2 26.1
    55–641,76435.13,04819.6 36.6
    ≥6583816.71,3638.8 38.1
    BMI group<0.001
    Normal1,05721.19,73262.7 9.8
    Overweight2,80655.94,85731.3 36.6
    Obese1,15723.09306.0 55.4
    Education<0.001
    Primary school or lower61712.31,1437.4 35.0
    Junior high school1,44228.72,87818.5 33.4
    Senior high school1,14222.72,94919.0 27.9
    College80816.13,17420.5 20.3
    Undergraduate and above1,01120.15,37534.6 15.8
    Marital status<0.001
    Married4,60191.712,78782.4 26.5
    Divorced/separated1022.03001.9 25.4
    Widowed1192.42421.6 33.0
    Single1983.92,19014.1 8.3
    Occupation<0.001
    Farmer, worker, and business1,07221.42,98519.226.4
    Leader, clerk, and technical1,99439.78,12352.319.7
    Others4569.11,4599.423.8
    Unemployment, student, retirement1,49829.82,95219.033.7
    Residence<0.001
    Urban1,36827.35,46135.2 20.0
    Suburban2,21144.06,47141.7 25.5
    Outer suburbs1,44128.73,58723.1 28.6
    Smoke<0.001
    Smoke2,22544.33,73024.0 37.4
    Do not smoke2,79955.711,82776.0 19.1
    Alcohol use<0.001
    Drink1,00219.92,21214.2 31.2
    Do not drink4,02280.113,34585.8 23.2
    Note: Values for some characteristics may not be equal to total numbers in each group because of missing values.
    Abbreviations: SD=standard deciation; MetS=metabolic syndrome; BMI=body mass index.
    Download: CSV

    TABLE 2.  Characteristics of components of MetS among adults in Beijing, China, 2017–2018.

    CharacteristicsMale (N=11,418)Female (N=12,994)P
    MeanSDMeanSD
    Waist circumference (cm)90.0510.89881.1710.872<0.001
    SBP (mmHg)130.1617.937123.0619.582<0.001
    DBP (mmHg)83.1111.06277.9012.550<0.001
    FPG (mmol/L)5.851.7695.531.515<0.001
    Triglycerides (mmol/L)2.022.0791.441.126<0.001
    HDL-C (mmol/L)1.310.3251.490.335<0.001
    Note: Data were presented as mean and standard deviation for continuous variables or percentage for categorical variables. P value in t-test for means or χ2 test for proportion differences between males and females.
    Abbreviations: DBP=diastolic blood pressure; FPG=fasting plasma glucose; HDL-C=high-density lipoprotein cholesterol; SBP=systolic blood pressure; MetS=metabolic syndrome; SD=standard deciation.
    Download: CSV

    TABLE 3.  Factors associated with MetS by sex in Beijing, China, 2017–2018.

    CharacteristicsAdjusted odds ratio and 95% CIs
    MaleFemale
    Age group (years)  
    ≤241.0001.000
    25–342.453 (1.737−3.463)1.469 (0.692−3.119)
    35–443.754 (2.600−5.418)2.854 (1.310−6.219)
    45–545.445 (3.773−7.857)4.229 (1.952−9.162)
    55–646.154 (4.238−8.934)11.438 (5.248−24.933)
    ≥656.120 (4.127−9.077)14.502 (6.588−31.921)
    BMI group
    Normal1.0001.000
    Overweight3.554 (3.200−3.946)4.564 (3.979−5.237)
    Obese8.547 (7.357−9.930)12.545 (10.441−15.073)
    Education
    Primary school or lower0.967 (0.764−1.224)1.187 (0.887−1.588)
    Junior high school1.154 (0.975−1.366)1.377 (1.065−1.781)
    Senior high school1.290 (1.104−1.506)1.202 (0.936−1.543)
    College1.318 (1.142−1.520)1.338 (1.066−1.680)
    Undergraduate and above1.0001.000
    Marital status  
    Married1.0001.000
    Divorced/separated1.209 (0.868−1.686)0.908 (0.589−1.402)
    Widowed1.006 (0.622−1.627)1.031 (0.767−1.386)
    Single0.777 (0.620−0.973)0.777 (0.471−1.282)
    Occupation
    Farmer, worker, and business1.0001.000
    Leader, clerk, and technical1.237 (1.070−1.430)0.989 (0.782−1.251)
    Others0.979 (0.818−1.171)0.782 (0.610−1.002)
    Unemployment, student, retirement1.155 (0.984−1.356)1.074 (0.906−1.273)
    Residence  
    Urban1.0001.000
    Suburban1.081 (0.963−1.214)1.380 (1.195−1.593)
    Outer suburbs1.186 (1.037−1.357)1.825 (1.535−2.170)
    Smoke
    Never smoke1.0001.000
    Smoke1.270 (1.150−1.402)1.283 (0.935−1.761)
    Alcohol use
    Never drink1.0001.000
    Drink1.124 (1.009−1.252)0.951 (0.687−1.317)
    Abbreviations: MetS=Metabolic syndrome; CIs=confidence intervals, BMI=body mass index.
    *Adjusted for age, study cohort, residential area, sex, education levels, income levels, smoking, and drinking.
    Download: CSV

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Prevalence of Metabolic Syndrome and Risk Factors Among Chinese Adults: Results from a Population-Based Study — Beijing, China, 2017–2018

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Summary

What is already known about this topic?

Metabolic syndrome (MetS) is one of the most easily available health indicative markers for cardiovascular diseases, and it has become a major public health problem worldwide due to increasing urbanization and aging populations. The prevalence of MetS increased dramatically in China, however, there are no records of MetS defined by the 2017 Chinese Diabetes Society for Beijing by far.

What is added by this report?

In this study, the data of 24,412 participants aged 18–74 years from a large population-based study in Beijing was collected. The overall prevalence of MetS among Beijing residents was 24.5%. The prevalence was 35.2% in males and 15.4% in females.

What are the implications for public health practice?

Effective public health strategies should target males, people with older age, lower education, higher body mass index, smokers, those who drink alcohol, those who are unemployed or retired, and those who live in rural areas on MetS prevention and control.

  • 1. Institute of Reproductive and Child Health / Key Laboratory of Reproductive Health, National Health Commission of the People’s Republic of China, Peking University, Beijing, China
  • 2. Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
  • 3. Department of Information and Statistics, Beijing Center for Disease Prevention and Control, Beijing, China
  • 4. Beijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning, Beijing Center for Disease Prevention and Control, Beijing, China
  • Corresponding authors:

    Gang Li, ligang@bjcdc.org

    Bing Shao, shaobingch@sina.com

    Le Zhang, zhangle@bjmu.edu.cn

  • Funding: Research Special Fund for Municipal Medical Public Welfare Institute (2017-BJYJ-15); National Natural Science Foundation of China (81373014); CNS-ZD Tizhi and Health Fund (CNS-ZD2020-115)
  • Online Date: July 22 2022
    Issue Date: July 22 2022
    doi: 10.46234/ccdcw2022.138
  • Metabolic syndrome (MetS) is characterized as insulin resistance, obesity, hypertension, glucose intolerance, and dyslipidemia. MetS is associated with elevated cardiovascular diseases and chronic diseases. With increasing urbanization and aging populations, the prevalence of MetS increased dramatically in China and became a major public health challenge (1). Meta-analysis revealed that pooled prevalence in the mainland of China was 24.5% during 2005–2015 (2). Genetics, environmental influence, physical activity, diet, and behavior all influence the prevalence of both MetS and its components (3). Beijing, a metropolitan city with an aging population, had no record of the prevalence of MetS defined by the new criteria for Chinese adults. The current study estimated the prevalence of MetS and its risk factors in Beijing based on a recent large sample study conducted in 2017–2018. The total prevalence of MetS was estimated to be 24.5% among Beijing residents. Males, especially those who lived in the outer suburbs, smokers, and those of older age were associated with an increased risk for MetS.

    The data used in the current study came from the baseline dataset of Beijing Population Health Cohort study, which was designed to measure air pollution and health outcomes. Details of the study have been described in a previous publication (4). A stratified, random cluster sampling method was used to select participants from a general population in Beijing in 2017–2018. To ensure the sample size, the survey was conducted with an estimated sample, and if the respondent was not available, another candidate in the list would be surveyed then. Our study included 24,990 individuals from 16 districts, which included urban areas, suburban areas, and outer suburbs to represent a general population of Beijing. Participants were permanent residents living in Beijing for more than 2 years and aged 18–74 years. Among them, 578 individuals without identification number (ID) or repetitive ID were excluded; 24,412 individuals were included in the study. MetS was diagnosed according to the China Diabetes Society (CDS) criteria, which was newly released in 2017 according to Chinese guidelines, where a person has MetS if he or she meets 3 or more of the following criteria: 1) a waist circumference of ≥90 cm for men and ≥85 cm for women; 2) a fasting plasma glucose (FPG) of ≥6.1 mmol/L or previously diagnosed diabetes; 3) a systolic blood pressure (SBP) of ≥130 mmHg, a diastolic blood pressure (DBP) of ≥85 mmHg, or previously diagnosed hypertension; 4) a fasting triglyceride level of ≥1.7 mmol/L; and 5) a high-density lipoprotein cholesterol (HDL-C) of <1.04 mmol/L (5).

    The prevalence was calculated according to demographic and lifestyle factors and compared means using t-tests and distributions of categories using chi-squared tests. Logistic regression was used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for the main potential confounding variables, including age, body mass index (BMI), education, occupation, smoking habits, alcohol use, and other factors. All data were analysed using SPSS Statistics for Windows (version 20.0, IBM Corp., Armonk, NY, US). Two-tailed P values <0.05 were considered statistically significant.

    Of the total 24,412 participants in the study, 11,418 males and 12,994 females were surveyed. The total prevalence of MetS was 24.5% among Beijing residents. The prevalence of MetS was 35.2% in male participants and 15.4% in female participants. Subjects with MetS were more likely to be 55 years old and above, male, unemployed/student/retired, less educated, smoker, and drinker. (Table 1)

    CharacteristicsMetSControlPPrevalence of MetS
    n%n%%
    Age, years Mean (SD)52.1 (12.9)43.8 (14.4)<0.001
    BMI, kg/m2 Mean (SD) 27.8 (3.7)24.2 (3.8)<0.001
    Han ethnic4,82896.21,486195.80.19924.5
    Sex<0.001
    Male3,30165.86,06539.1 35.2
    Female1,71934.29,45460.9 15.4
    Age group (years)<0.001
    ≤24651.31,1237.25.5
    25–3463612.74,23327.3 13.1
    35–4466213.22,77117.9 19.3
    45–541,05521.02,98119.2 26.1
    55–641,76435.13,04819.6 36.6
    ≥6583816.71,3638.8 38.1
    BMI group<0.001
    Normal1,05721.19,73262.7 9.8
    Overweight2,80655.94,85731.3 36.6
    Obese1,15723.09306.0 55.4
    Education<0.001
    Primary school or lower61712.31,1437.4 35.0
    Junior high school1,44228.72,87818.5 33.4
    Senior high school1,14222.72,94919.0 27.9
    College80816.13,17420.5 20.3
    Undergraduate and above1,01120.15,37534.6 15.8
    Marital status<0.001
    Married4,60191.712,78782.4 26.5
    Divorced/separated1022.03001.9 25.4
    Widowed1192.42421.6 33.0
    Single1983.92,19014.1 8.3
    Occupation<0.001
    Farmer, worker, and business1,07221.42,98519.226.4
    Leader, clerk, and technical1,99439.78,12352.319.7
    Others4569.11,4599.423.8
    Unemployment, student, retirement1,49829.82,95219.033.7
    Residence<0.001
    Urban1,36827.35,46135.2 20.0
    Suburban2,21144.06,47141.7 25.5
    Outer suburbs1,44128.73,58723.1 28.6
    Smoke<0.001
    Smoke2,22544.33,73024.0 37.4
    Do not smoke2,79955.711,82776.0 19.1
    Alcohol use<0.001
    Drink1,00219.92,21214.2 31.2
    Do not drink4,02280.113,34585.8 23.2
    Note: Values for some characteristics may not be equal to total numbers in each group because of missing values.
    Abbreviations: SD=standard deciation; MetS=metabolic syndrome; BMI=body mass index.

    Table 1.  Prevalence of MetS by demographic characteristics, Beijing, China, 2017–2018.

    There was a significant difference between male and female subjects. The mean values for BMI, waist circumference, FPG, and serum triglycerides were higher in males than those in females, while HDL-C was higher in females than in males (P<0.001 for all comparisons). (Table 2)

    CharacteristicsMale (N=11,418)Female (N=12,994)P
    MeanSDMeanSD
    Waist circumference (cm)90.0510.89881.1710.872<0.001
    SBP (mmHg)130.1617.937123.0619.582<0.001
    DBP (mmHg)83.1111.06277.9012.550<0.001
    FPG (mmol/L)5.851.7695.531.515<0.001
    Triglycerides (mmol/L)2.022.0791.441.126<0.001
    HDL-C (mmol/L)1.310.3251.490.335<0.001
    Note: Data were presented as mean and standard deviation for continuous variables or percentage for categorical variables. P value in t-test for means or χ2 test for proportion differences between males and females.
    Abbreviations: DBP=diastolic blood pressure; FPG=fasting plasma glucose; HDL-C=high-density lipoprotein cholesterol; SBP=systolic blood pressure; MetS=metabolic syndrome; SD=standard deciation.

    Table 2.  Characteristics of components of MetS among adults in Beijing, China, 2017–2018.

    Multiple logistic regression showed that males, especially those with older age, lower education, higher BMI, smoking, alcohol use, and living in rural areas were associated with MetS. (Table 3)

    CharacteristicsAdjusted odds ratio and 95% CIs
    MaleFemale
    Age group (years)  
    ≤241.0001.000
    25–342.453 (1.737−3.463)1.469 (0.692−3.119)
    35–443.754 (2.600−5.418)2.854 (1.310−6.219)
    45–545.445 (3.773−7.857)4.229 (1.952−9.162)
    55–646.154 (4.238−8.934)11.438 (5.248−24.933)
    ≥656.120 (4.127−9.077)14.502 (6.588−31.921)
    BMI group
    Normal1.0001.000
    Overweight3.554 (3.200−3.946)4.564 (3.979−5.237)
    Obese8.547 (7.357−9.930)12.545 (10.441−15.073)
    Education
    Primary school or lower0.967 (0.764−1.224)1.187 (0.887−1.588)
    Junior high school1.154 (0.975−1.366)1.377 (1.065−1.781)
    Senior high school1.290 (1.104−1.506)1.202 (0.936−1.543)
    College1.318 (1.142−1.520)1.338 (1.066−1.680)
    Undergraduate and above1.0001.000
    Marital status  
    Married1.0001.000
    Divorced/separated1.209 (0.868−1.686)0.908 (0.589−1.402)
    Widowed1.006 (0.622−1.627)1.031 (0.767−1.386)
    Single0.777 (0.620−0.973)0.777 (0.471−1.282)
    Occupation
    Farmer, worker, and business1.0001.000
    Leader, clerk, and technical1.237 (1.070−1.430)0.989 (0.782−1.251)
    Others0.979 (0.818−1.171)0.782 (0.610−1.002)
    Unemployment, student, retirement1.155 (0.984−1.356)1.074 (0.906−1.273)
    Residence  
    Urban1.0001.000
    Suburban1.081 (0.963−1.214)1.380 (1.195−1.593)
    Outer suburbs1.186 (1.037−1.357)1.825 (1.535−2.170)
    Smoke
    Never smoke1.0001.000
    Smoke1.270 (1.150−1.402)1.283 (0.935−1.761)
    Alcohol use
    Never drink1.0001.000
    Drink1.124 (1.009−1.252)0.951 (0.687−1.317)
    Abbreviations: MetS=Metabolic syndrome; CIs=confidence intervals, BMI=body mass index.
    *Adjusted for age, study cohort, residential area, sex, education levels, income levels, smoking, and drinking.

    Table 3.  Factors associated with MetS by sex in Beijing, China, 2017–2018.

    • Based on the baseline dataset of this large population-based study, a quarter of participants had MetS. With the disease burden increasing, especially for chronic diseases, understanding the epidemiology of MetS and exploring risk factors of MetS would be an effective approach for disease prevention and health promotion. This study added evidence that nearly one-fourth of the Beijing residents in our study had MetS and implied that special attention should be paid among males, people with older age, lower education, higher BMI, smoker, and those lived in rural areas, for the prevention of MetS.

      Few country-wide studies were conducted to describe the epidemiology of MetS in adults for all age groups; a previous study focused on older adults (≥60 years) or middle-aged people (35–59 years) as they were more susceptible to chronic cardiovascular disease (6). Using the updated CDS criterion (2017), the current study revealed the prevalence in a general population aged 18–74 years. The prevalence of MetS among Beijing residents (24.5%, 95% CI: 24.0%–25.5%) was generally consistent with a 2017 study of MetS in Beijing residents aged from 18 to 79 years (25.6%), which used the International Diabetes Federation criteria (7). The prevalence of MetS in this study was higher than general Xinjiang residents (20.9%) (8) and Qingdao residents (17.8%) (9). Current study showed that the prevalence of MetS increased compared to 2010 (24.5% and 11.0%, respectively) (10).

      Prevalence of MetS varied significantly by gender. Males had a higher prevalence than females, which was different from the previous study. The prevalence was 27.0% among females and 19.2% among males in a recent Chinese study (2). The main reason was survivor bias, as young males who survived the disparities of resources period were more likely to receive sufficient nutrition than young females in their early life. Malnutrition during the critical growth stages may lead to early adaptations in body structure and function, such as the establishment of a thrifty phenotype. Another reason may be biological differences in sex hormones, body composition, and glucose metabolism. The gender disparity in the risk for MetS requires further investigation. In addition, the pattern of risk factors is sex-specific. Alcohol drinking was identified as the main risk factor for MetS among males, while low household income and less education increased the risk for MetS among females (11).

      A significant increasing trend was observed in different age groups, as metabolic syndrome increased significantly with age (2). Developmental origins of health and disease well explained the origins of MetS in later life. Early-life malnutrition and later-life overnutrition were shown to be critical for metabolic disorders in adult life. Low birth weight, low socioeconomic status in early life increased the likelihood of adulthood metabolic disorders and chronic diseases.

      Studies observed an association between a lower socioeconomic status and MetS prevalence; the ORs for MetS prevalence for residents in outer suburbs were higher than residents in urban. Dietary and lifestyle factors may contribute to the difference. Although it's reported that the prevalence of MetS was higher in urban residents than in rural areas, the study was conducted on northwest Chinese adults who had different diets and lifestyles form Beijing adults (12). Smoking and drinking were related to higher risks of MetS, and the correlation between unhealthy lifestyle factors and lower socioeconomic status was also verified (8).

      The study had several strengths. First, our study included a random representative and large sample of adults in Beijing. Second, all interviews were conducted face to face by trained health workers, and the anthropometric parameters were measured on-site, which allowed for rigorous quality control. Third, the sample constituted of both urban, suburban, and outer suburbs residents, which was representative of the diversity of environments in China. Fourth, this study used the new version of MetS criteria for Chinese adults, 2017 CDS, which would be more suitable since a previous study revealed that CDS definition was superior to The Adult Treatment Panel III of the National Cholesterol Education Program criteria and International Diabetes Federation when predicting factors and MetS among Chinese (9).

      This study was subject to some limitations. First, this was a cross-sectional study, so the causal relation between factors and MetS risk could not be inferred. Second, lack of environmental exposure prevented us from exploring its effect on MetS.

      In conclusion, MetS was prevalent among residents in Beijing. The findings suggested males, especially those living in the rural areas, who smoked, had lower education, higher BMI and were of older age were associated with an increased risk of MetS.

    • No conflicts of interest.

    • The local research teams from 16 districts of Beijing Center for Disease Prevention and Control, and the participants of the study.

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