Deparment of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam UMC - location VU University Medical Center, Amsterdam, The Netherlands
Deparment of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam UMC - location VU University Medical Center, Amsterdam, The Netherlands.
BMJ Open. 2022 Mar 8;12(3):e052204. doi: 10.1136/bmjopen-2021-052204.
To investigate the contribution of behavioural, social and psychological factors to inequalities in mortality by educational level between birth cohorts.
Cohort-sequential design.
Two population-based studies in the Netherlands: the Longitudinal Aging Study Amsterdam (LASA) and the Doetinchem Cohort Study (DCS).
Data from the LASA included 1990 individuals with birth years 1928-1937 (cohort 1) and 1938-1947 (cohort 2) and, for replication, data from the DCS included 2732 individuals with birth years 1929-1941 (cohort 1) and 1939-1951 (cohort 2).
Years of education, 15-year mortality, lifestyle factors, social factors and psychological factors were modelled using multiple-group accelerated failure time models based on structural equation modelling to compare indirect effects between cohorts.
Both studies showed similar educational inequalities, with higher mortality among those with lower education. The indirect effects of education via smoking (LASA: difference in survival time ratio (TR)=1.0018, 95% CI 1.0000 to 1.0155, DCS: TR=1.0051, 95% CI 1.0000 to 1.0183), physical activity (LASA: TR=1.0056, 95% CI 1.00009 to 1.0132) and alcohol use (LASA: TR=1.0275, 95% CI 1.0033 to 1.0194) on mortality were stronger in cohort 2 than in cohort 1. In contrast to the other effects, alcohol use was the only factor that was associated positively with education and survival time, which effect increased in the most recent cohort. Emotional support, network size and cognitive functioning showed no difference between cohorts.
Smoking, physical activity and alcohol use contributed more to educational inequalities in mortality in recent cohorts. Hence, in addition to tackling fundamental social causes of inequality, policies focusing on intermediary mechanisms such as lifestyle need to adapt their targets to those that prove to be most important within a given time frame.
研究行为、社会和心理因素对不同教育程度出生队列之间死亡率差异的贡献。
队列序贯设计。
荷兰的两项基于人群的研究:阿姆斯特丹纵向老龄化研究(LASA)和多滕汉姆队列研究(DCS)。
LASA 中的数据包括 1990 名出生年份为 1928-1937 年的个体(队列 1)和 1938-1947 年的个体(队列 2),为了复制,DCS 中的数据包括 2732 名出生年份为 1929-1941 年的个体(队列 1)和 1939-1951 年的个体(队列 2)。
采用基于结构方程建模的多群组加速失效时间模型对教育年限、15 年死亡率、生活方式因素、社会因素和心理因素进行建模,以比较队列之间的间接效应。
两项研究均显示出类似的教育不平等现象,受教育程度较低的人群死亡率更高。教育通过吸烟(LASA:生存时间比(TR)差异=1.0018,95%CI 1.0000 至 1.0155,DCS:TR=1.0051,95%CI 1.0000 至 1.0183)、体育活动(LASA:TR=1.0056,95%CI 1.00009 至 1.0132)和饮酒(LASA:TR=1.0275,95%CI 1.0033 至 1.0194)对死亡率的间接影响在队列 2中强于队列 1。与其他影响因素不同,饮酒是唯一与教育和生存时间呈正相关的因素,而且这种效应在最近的队列中增加。情感支持、网络规模和认知功能在队列之间没有差异。
吸烟、体育活动和饮酒对最近队列中死亡率的教育不平等贡献更大。因此,除了解决不平等的根本社会原因外,侧重于生活方式等中介机制的政策还需要根据在给定时间框架内证明最重要的目标来调整其目标。