Li Qingfeng, Tsui Amy O
Population, Family and Reproductive Health Department, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe Street, W4033, Baltimore, MD, 21205-2179, USA.
Demography. 2016 Jun;53(3):835-63. doi: 10.1007/s13524-016-0472-z.
This study analyzes the relationships between maternal risk factors present at the time of daughters' births-namely, young mother, high parity, and short preceding birth interval-and their subsequent adult developmental, reproductive, and socioeconomic outcomes. Pseudo-cohorts are constructed using female respondent data from 189 cross-sectional rounds of Demographic and Health Surveys conducted in 50 developing countries between 1986 and 2013. Generalized linear models are estimated to test the relationships and calculate cohort-level outcome proportions with the systematic elimination of the three maternal risk factors. The simulation exercise for the full sample of 2,546 pseudo-cohorts shows that the combined elimination of risk exposures is associated with lower mean proportions of adult daughters experiencing child mortality, having a small infant at birth, and having a low body mass index. Among sub-Saharan African cohorts, the estimated changes are larger, particularly for years of schooling. The pseudo-cohort approach can enable longitudinal testing of life course hypotheses using large-scale, standardized, repeated cross-sectional data and with considerable resource efficiency.
本研究分析了女儿出生时存在的母亲风险因素之间的关系，即年轻母亲、多胎次和较短的上次生育间隔，以及她们随后的成年发育、生殖和社会经济结果。利用1986年至2013年期间在50个发展中国家进行的189轮人口与健康调查中的女性受访者数据构建了虚拟队列。估计广义线性模型以检验这些关系，并通过系统消除这三个母亲风险因素来计算队列水平的结果比例。对2546个虚拟队列的全样本进行的模拟分析表明，风险暴露的综合消除与成年女儿经历儿童死亡、出生时婴儿体重小和体重指数低的平均比例较低有关。在撒哈拉以南非洲队列中，估计的变化更大，特别是在受教育年限方面。虚拟队列方法能够利用大规模、标准化、重复的横断面数据，并以相当高的资源效率对生命历程假设进行纵向检验。
