Does gender inequity increase men's mortality risk in the United States? A multilevel analysis of data from the National Longitudinal Mortality Study.
Does gender inequity increase men's mortality risk in the United States? A multilevel analysis of data from the National Longitudinal Mortality Study.
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DOI：
10.1016/j.ssmph.2017.03.003
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发表时间：
2017-12
期刊：
影响因子：
--
通讯作者：
Stevenson C
中科院分区：
文献类型：
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作者：
Kavanagh SA;Shelley JM;Stevenson C
一些理论方法表明，性别不平等可能给男子带来健康风险。这项研究进行了多层次的分析，以确定如果国家一级的措施，性别不平等的男性死亡率在美国的预测。分析数据主要来自国家纵向死亡率研究，该研究基于非机构化人口的随机样本。完整的数据集包括50个州内的174，703人，并对死亡率进行了6年的随访。性别不平等是通过九个变量来衡量的：高等教育、生殖权利、堕胎服务提供者的机会、民选职位、管理、企业所有权、劳动力参与、收入和相对贫困。个体水平的协变量为年龄、收入、教育、人种/种族、婚姻状况和就业状况。州一级的协变量是收入不平等和人均国内生产总值。逻辑多层次模型的结果显示，一些国家一级的性别不平等的措施显着相关的男性死亡率。在所有这些情况下，更大的性别不平等与死亡风险增加有关。在针对所有年龄段成年男子的完全调整模型中，（OR 1.05 95% CI 1.01 - 1.09），企业所有权（OR 1.04 95% CI 1.01 - 1.08），盈利（OR 1.04 95% CI 1.01 - 1.08）和相对贫困（OR 1.07 95% CI 1.03 - 1.10）测量结果均显示，性别不平等z评分每增加1个标准差，就会产生统计学显著性影响。在工作年龄的男性中也看到了类似的效果。在老年男子（65岁以上）中，只有收入和相对贫困的衡量标准具有统计意义。这项研究提供的证据表明，性别不平等可能会增加男性的健康风险。效应量虽然很小，但在确定的性别不平等范围内足够大，对人口健康具有重要影响。理论方法将性别不平等与男子健康风险增加联系起来。多层次分析可以调查性别不平等的背景影响。这项研究模拟了州一级性别不平等对男性死亡率的影响。性别不平等的各个方面预示着男性的死亡风险会增加。
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 z-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. Theoretical approaches link gender inequity to increased health risks for men. Multilevel analysis allows investigation of a contextual effect of gender inequity. The study modelled the effect of state-level gender inequity on men's mortality. Aspects of gender inequity predicted an increased mortality risk for men.