Kavanagh Shane A, Shelley Julia M, Stevenson Christopher
School of Health & Social Development, Faculty of Health, Deakin University, Locked Bag 20000, Geelong, VIC 3220, Australia.
SSM Popul Health. 2017 Mar 24;3:358-365. doi: 10.1016/j.ssmph.2017.03.003. eCollection 2017 Dec.
A number of theoretical approaches suggest that gender inequity may give rise to health risks for men. This study undertook a multilevel analysis to ascertain if state-level measures of gender inequity are predictors of men's mortality in the United States. Data for the analysis were taken primarily from the National Longitudinal Mortality Study, which is based on a random sample of the non-institutionalised population. The full data set included 174,703 individuals nested within 50 states and had a six-year follow-up for mortality. Gender inequity was measured by nine variables: higher education, 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 per capita gross domestic product. The results of logistic multilevel modelling showed a number of measures of state-level gender inequity were significantly associated with men's mortality. In all of these cases greater gender inequity was associated with an increased mortality risk. In fully adjusted models for all-age adult men the elected office (OR 1.05 95% CI 1.01-1.09), business ownership (OR 1.04 95% CI 1.01-1.08), earnings (OR 1.04 95% CI 1.01-1.08) and relative poverty (OR 1.07 95% CI 1.03-1.10) measures all showed statistically significant effects for each 1 standard deviation increase in the gender inequity -score. Similar effects were seen for working-age men. In older men (65+ years) only the earnings and relative poverty measures were statistically significant. This study provides evidence that gender inequity may increase men's health risks. The effect sizes while small are large enough across the range of gender inequity identified to have important population health implications.
一些理论方法表明,性别不平等可能会给男性带来健康风险。本研究进行了多层次分析,以确定州层面的性别不平等衡量指标是否可预测美国男性的死亡率。分析数据主要取自全国纵向死亡率研究,该研究基于非机构化人口的随机样本。完整数据集包括嵌套在50个州内的174,703个人,并对死亡率进行了为期六年的随访。性别不平等通过九个变量衡量:高等教育、生殖权利、堕胎服务提供者可及性、当选公职、管理、企业所有权、劳动力参与、收入和相对贫困。个体层面的协变量包括年龄、收入、教育、种族/族裔、婚姻状况和就业状况。州层面的协变量包括收入不平等和人均国内生产总值。逻辑多层次建模结果显示,一些州层面的性别不平等衡量指标与男性死亡率显著相关。在所有这些情况下,更大程度的性别不平等与更高的死亡风险相关。在针对所有年龄段成年男性的完全调整模型中,当选公职(比值比1.05,95%置信区间1.01 - 1.09)、企业所有权(比值比1.04,95%置信区间1.01 - 1.08)、收入(比值比1.04,95%置信区间1.01 - 1.08)和相对贫困(比值比1.07,95%置信区间1.03 - 1.10)指标在性别不平等得分每增加1个标准差时均显示出统计学上的显著影响。在职年龄男性也有类似影响。在老年男性(65岁及以上)中,只有收入和相对贫困指标具有统计学显著性。本研究提供了证据表明性别不平等可能会增加男性的健康风险。虽然效应量较小,但在已确定的性别不平等范围内足够大,对人群健康具有重要影响。