Is gender inequity a risk factor for men reporting poorer self-rated health in the United States?

• Published in: PloS one 2018-07, Vol.13 (7), p.e0200332-e0200332
• Main Authors: Kavanagh, Shane A, Shelley, Julia M, Stevenson, Christopher
• Format: Article
• Language: English
• Subjects: Abortion; Adolescent; Adult; Age; Age Factors; Aged; Aged, 80 and over; Behavioral Risk Factor Surveillance System; Biology and Life Sciences; Cardiovascular disease; Cross-Sectional Studies; Demographic aspects; Disease control; Disease prevention; Education; Gender; Gender equality; Health aspects; Health behavior; Health care; Health risks; Health Status; Health surveillance; Humans; Income; Income inequality; Internet; Male; Masculinity; Medicine and Health Sciences; Men; Men's health; Middle Aged; Minority & ethnic groups; Mortality; People and Places; Poverty; Profits; Public health; Reproductive rights; Risk Factors; Risk taking; Self Report; Sex Factors; Sexism - statistics & numerical data; Social change; Social Sciences; Socioeconomic Factors; Socioeconomics; Studies; Theory; United States - epidemiology; Womens health; Womens rights; Young Adult
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0200332

Theoretical approaches suggest that gender inequity increases men's health risks. Previous findings from the United States support this contention, however only a small number of health outcomes have been explored. This study extends the range of health outcomes examined by using a cross-sectional, multilevel analysis to investigate whether measures of state-level gender inequity are predictors of men's self-rated health. Data were derived primarily from the Behavioral Risk Factor Surveillance System and the full-case data set included 116,594 individuals nested within 50 states. Gender inequity was measured with nine variables: higher education, women's reproductive rights, abortion provider access, elected office, management, business ownership, labour force participation, earnings and relative poverty. Covariates at the individual level were age, income, education, race/ethnicity, marital status and employment status. Covariates at the state level were income inequality and gross domestic product per capita. In fully adjusted models for all-age men the reproductive rights (OR 1.06 95% CI 1.01-1.11), abortion provider access (OR 1.11 95% CI 1.05-1.16) and earnings (OR 1.06 95% CI 1.02-1.12) measures all predicted an increased risk of men reporting poorer self-rated health for each 1 standard deviation increase in the gender inequity z-score. The most consistent effect was seen for the 65+ age group where the reproductive rights (OR 1.09 95% CI 1.03-1.16), abortion provider access (OR 1.15 95% CI 1.09-1.21), elected office (OR 1.06 95% CI 1.01-1.11) and earnings (OR 1.10 95% CI 1.04-1.16) measures all showed a significant effect. These findings provide evidence that some aspects of gender inequity increase the risk of poorer self-rated health in men. The study contributes to a growing body of literature implicating gender inequity in men's health patterns.