Department of Psychiatry, University of Michigan, 4250 Plymouth Road, SPC 5763, Ann Arbor, MI, 48109-2700, USA.
Center for Research on Ethnicity, Culture and Health, University of Michigan, Ann Arbor, MI, USA.
J Racial Ethn Health Disparities. 2018 Apr;5(2):375-386. doi: 10.1007/s40615-017-0381-x. Epub 2017 Jun 20.
Despite the well-established health effects of socioeconomic status (SES), SES resources such as employment may differently influence health outcomes across sub-populations. This study used a national sample of US adults to test if the effect of baseline employment (in 1986) on all-cause mortality over a 25-year period depends on race, gender, education level, and their intersections.
Data came from the Americans' Changing Lives (ACL) study, which followed 2025 Whites and 1156 Blacks for 25 years from 1986 to 2011. The focal predictor of interest was baseline employment (1986), operationalized as a dichotomous variable. The main outcome of interest was time to all-cause mortality from 1986 to 2011. Covariates included baseline age, health behaviors (smoking, drinking, and exercise), physical health (obesity, chronic disease, function, and self-rated health), and mental health (depressive symptoms). A series of Cox proportional hazard models were used to test the association between employment and mortality risk in the pooled sample and based on race, gender, education, and their intersections.
Baseline employment in 1986 was associated with a lower risk of mortality over a 25-year period, net of covariates. In the pooled sample, baseline employment interacted with race (HR = .69, 95% CI = .49-.96), gender (HR = .73, 95% CI = .53-1.01), and education (HR = .64, 95% CI = .46-.88) on mortality, suggesting diminished protective effects for Blacks, women, and individuals with lower education, compared to Whites, men, and those with higher education. In stratified models, the association was significant for Whites (HR = .71, 95%CI = .59-.90), men (HR = .60, 95%CI = .43-.83), and individuals with high education (HR = .66, 95%CI = .50-.86) but not for Blacks (HR = .77, 95%CI = .56-1.01), women (HR = .88, 95%CI = .69-1.12), and those with low education (HR = .92, 95%CI = .67-1.26). The largest effects of employment on life expectancy were seen for highly educated men (HR = .50, 95%CI = .32-.78), White men (HR = .55, 95%CI = .38-.79), and highly educated Whites (HR = .63, 95%CI = .46-.84). The effects were non-significant for Black men (HR = 1.10, 95%CI = .68-1.78), Whites with low education (HR = 1.01, 95%CI = .67-1.51), and women with low education (HR = 1.06, 95%CI = .71-1.57).
In the USA, the health gain associated with employment is conditional on one's race, gender, and education level, along with their intersections. Blacks, women, and individuals with lower education gain less from employment than do Whites, men, and highly educated people. More research is needed to understand how the intersections of race, gender, and education alter health gains associated with socioeconomic resources.
尽管社会经济地位(SES)的健康影响已得到充分证实,但就业等 SES 资源可能会根据亚人群的不同而对健康结果产生不同的影响。本研究使用美国成年人的全国样本,检验基线就业(1986 年)对 25 年内全因死亡率的影响是否取决于种族、性别、教育水平及其交叉情况。
数据来自美国人生活变化(ACL)研究,该研究从 1986 年到 2011 年对 2025 名白人男性和 1156 名黑人男性进行了 25 年的随访。感兴趣的焦点预测因子是基线就业(1986 年),用二分变量表示。主要结果是 1986 年至 2011 年期间的全因死亡率。协变量包括基线年龄、健康行为(吸烟、饮酒和锻炼)、身体健康(肥胖、慢性疾病、功能和自我报告健康)和心理健康(抑郁症状)。使用一系列 Cox 比例风险模型来检验就业与死亡率风险之间的关联,同时基于种族、性别、教育和它们的交叉情况进行检验。
1986 年的基线就业与 25 年内的死亡率风险降低有关,在考虑了协变量后。在总样本中,基线就业与种族(HR=0.69,95%CI=0.49-0.96)、性别(HR=0.73,95%CI=0.53-1.01)和教育(HR=0.64,95%CI=0.46-0.88)交互作用,表明与白人、男性和教育程度较高的人相比,黑人、女性和教育程度较低的人保护作用减弱。在分层模型中,这种关联在白人(HR=0.71,95%CI=0.59-0.90)、男性(HR=0.60,95%CI=0.43-0.83)和教育程度较高的人(HR=0.66,95%CI=0.50-0.86)中是显著的,但在黑人(HR=0.77,95%CI=0.56-1.01)、女性(HR=0.88,95%CI=0.69-1.12)和教育程度较低的人(HR=0.92,95%CI=0.67-1.26)中则不显著。就业对预期寿命的最大影响见于教育程度较高的男性(HR=0.50,95%CI=0.32-0.78)、白人男性(HR=0.55,95%CI=0.38-0.79)和教育程度较高的白人(HR=0.63,95%CI=0.46-0.84)。黑人和男性(HR=1.10,95%CI=0.68-1.78)、教育程度较低的白人(HR=1.01,95%CI=0.67-1.51)和教育程度较低的女性(HR=1.06,95%CI=0.71-1.57)的影响则不显著。
在美国,与就业相关的健康收益取决于一个人的种族、性别和教育水平,以及它们的交叉情况。与白人、男性和教育程度较高的人相比,黑人、女性和教育程度较低的人从就业中获得的收益较少。需要进一步研究种族、性别和教育的交叉如何改变与社会经济资源相关的健康收益。