Association of gender-specific risk factors in metabolic and cardiovascular diseases: an NHANES-based cross-sectional study

J Investig Med. 2018 Jan;66(1):22-31. doi: 10.1136/jim-2017-000434. Epub 2017 Sep 2.

Abstract

In the present cross-sectional study, based on National Health and Nutrition Examination Survey (NHANES, 2007-2010) cohorts, various risk factors for metabolic syndrome (MetS) and cardiovascular diseases (CVDs) were analyzed (n=12,153). The variables analyzed include, demographics, comorbidities associated with MetS or CVD, behavioral and dietary factors, while the primary endpoints were the prevalence of MetS and CVD. The prevalence of MetS and CVD was slightly higher in males as compared with females (42.50% and 7.65% vs 41.29% and 4.13%, respectively). After controlling for confounding factors, advanced age, family history of diabetes mellitus (DM), overweight, and obesity were significantly associated with the likelihood of MetS, irrespective of gender differences. In males, the diagnosis of prostate cancer and regular smoking were additional risk factors of MetS, whereas, advanced age, family history of heart attack or angina, health insurance coverage, diagnosis of rheumatoid arthritis or depression, obesity and low calorie intake were identified as risk factors for CVD. In addition to the above risk factors, higher physical activity and vitamin D insufficiency were also found to increase the risk of CVD in females. Furthermore, obesity was a higher risk factor for MetS than CVD. Emerging risk factors for CVD identified in this study has major clinical implications. Of interest is the correlation of higher physical activity and the risk of CVD in women and the role of depression and lower calorie intake in general population.

Keywords: National Health and Nutrition Examination Survey (NHANES); behavior; cardiovascular disease; diet; metabolic syndrome; risk factors.

MeSH terms

  • Behavior
  • Cardiovascular Diseases / epidemiology*
  • Cross-Sectional Studies
  • Demography
  • Diet
  • Female
  • Humans
  • Logistic Models
  • Male
  • Metabolic Syndrome / epidemiology*
  • Multivariate Analysis
  • Nutrition Surveys*
  • Risk Factors
  • Sex Factors