Gender Disparities of Heart Disease and the Association with Smoking and Drinking Behavior among Middle-Aged and Older Adults, a Cross-Sectional Study of Data from the US Health and Retirement Study and the China Health and Retirement Longitudinal Study.
Yifei LiYuanan LuEric L HurwitzYan Yan WuPublished in: International journal of environmental research and public health (2022)
Heart disease remains the leading cause of death globally by gender and region. Smoking and alcohol drinking are known modifiable health behaviors of heart disease. Utilizing data from the US Health and Retirement Study and the China Health and Retirement Longitudinal Study, this study examines heart disease disparities and the association with smoking and drinking behavior among men and women in the US and China. Smoking and drinking behavior were combined to neither, smoke-only, drink-only, and both. In the US, the prevalence was higher in men (24.5%, 95% CI: 22.5-26.6%) than in women (20.6%, 95% CI: 19.3-22.1%) and a higher prevalence was found in the smoke-only group for both genders. In contrast, women in China had higher prevalence (22.9%, 95% CI: 21.7-24.1%) than men (16.1%, 95% CI: 15.1-17.2%), and the prevalence for women who smoked or engaged in both behaviors were ~1.5 times (95% CI: 1.3-1.8, p < 0.001) those who did not smoke or drink, but no statistical difference were found in men. The findings might be due to differences in smoking and drinking patterns and cultures by gender in the two countries and gender inequality among older adults in China. Culturally tailored health promotion strategies will help reduce the burden of heart disease.
Keyphrases
- health promotion
- mental health
- public health
- healthcare
- risk factors
- smoking cessation
- pulmonary hypertension
- health information
- alcohol consumption
- polycystic ovary syndrome
- physical activity
- magnetic resonance
- magnetic resonance imaging
- computed tomography
- machine learning
- pregnancy outcomes
- middle aged
- human health
- adipose tissue
- skeletal muscle
- deep learning
- affordable care act
- health insurance
- breast cancer risk