Medical Science Center, University of Wisconsin–Madison, 1300 University Avenue, Madison, WI 53706, USA.
J Aging Health. 2010 Apr;22(3):307-31. doi: 10.1177/0898264309358617. Epub 2010 Jan 26.
This article uses data from MIDUS (Midlife in the United States), a national study of Americans (N = 7,108), to investigate factors that predict longitudinal retention. With its extensive age range (25-75 at Time 1) and long-term design (9- to 10-year survey interval), MIDUS is useful for investigating common sociodemographic and health predictors of continuing participation.
The authors conducted logistic regression analyses of baseline sociodemographic and health variables predicting retention. Select interaction terms examined the interplay between targeted variables.
Consistent with prior research, higher retention rates were found among Whites, females, and married individuals as well as those with better health and more education. Interaction analyses further clarified that (a) health status better predicted retention among older compared to younger respondents and among women compared to men, (b) marital status better predicted retention among Whites compared to non-Whites and among women compared to men, and (c) economic status better predicted retention among those with poorer functional health status.
The authors' analyses clarify that longitudinal retention varied depending on respondents' sociodemographic characteristics and their health status. The unique contribution of this article is that factors predicting nonparticipation can be offset by, or compensated for, other factors.
本文利用美国中期生活研究(MIDUS)的数据(N=7108),调查了预测纵向保留率的因素。MIDUS 的年龄范围广泛(在第 1 次调查时为 25-75 岁)且设计长期(调查间隔为 9-10 年),因此非常适合调查常见的社会人口学和健康预测因素对持续参与的影响。
作者对基线社会人口学和健康变量进行了逻辑回归分析,以预测保留率。选择的交互项检验了目标变量之间的相互作用。
与先前的研究一致,发现白人、女性和已婚人士以及健康状况较好和受教育程度较高的人保留率较高。交互分析进一步阐明:(a)与年轻受访者相比,健康状况更好地预测了年长受访者的保留率,与男性相比,健康状况更好地预测了女性受访者的保留率;(b)与非白人相比,婚姻状况更好地预测了白人受访者的保留率,与男性相比,婚姻状况更好地预测了女性受访者的保留率;(c)与健康状况较差的人相比,经济状况更好地预测了健康功能较差的人的保留率。
作者的分析表明,纵向保留率因受访者的社会人口学特征及其健康状况而异。本文的独特贡献在于,非参与的预测因素可以被其他因素抵消或补偿。