Ming-Cheng Chang

The role of clinical risk factors in understanding self-rated health

PURPOSE This study examines the importance of clinical risk factors for predicting self-ratings of general health status, with and without controls for a broad range of self-reported indicators of physical and psychological well-being. METHODS Ordered probit models, estimated on 928 respondents aged 54 years and older who participated in an ongoing national survey in Taiwan, are used to examine the correlates of self-rated health. The model is estimated in two stages, first testing the association between clinical risk factors and self-rated health and second, examining whether those clinical measures remain significant after controlling for a large number of other factors hypothesized to affect self-ratings. RESULTS Most of the clinical variables are significantly associated with self-rated health, even in the presence of control variables. The largest effects pertain to the BMI, ratio of total to HDL cholesterol (among men) and presence of the epsilon4 allele of the APOE gene (among women). CONCLUSIONS The results suggest a variety of pathways linking clinical measures to the self-ratings. The findings also suggest that the clinical measures are less powerful predictors than self-reports about diverse aspects of well-being.

Social Ties and Perceived Support: Two Dimensions of Social Relationships and Health Among the Elderly in Taiwan

Objectives: Assess the effects of social relationships on physical and mental health among the elderly in Taiwan. Methods: Using 4 waves of a survey of the elderly, we examine the relationship between social ties and perceived support and four health outcomes—mortality, functional status, self-assessed health, and depression. Results:Perceived support and social ties are related to health, but many of the apparent effects are attenuated in the presence of controls for prior health. However, positive perceptions about support are protective of mental (but not physical) health. Discussion: If baseline health is ignored, estimates of the effects of social relationships on health at a given stage of life are likely to be inflated by reverse causality or by effects occurring prior to baseline. Inclusion of controls for initial health reveals that, in general, the relationship between social support and health at the older ages in Taiwan is relatively modest.

Sex differentials in biological risk factors for chronic disease: estimates from population-based surveys.

BACKGROUND In light of substantial sex differences in health outcomes, researchers need to focus on disentangling the underlying biological and social determinants. The objective of this study is to determine whether two populations that differ in many cultural and social dimensions--Taiwan and the United States--also vary with regard to sex differentials in biological markers of chronic disease. METHODS The analysis is based on three population-based surveys that include interviews, urine and blood specimens, and physical examinations: the Social Environment and Biomarkers of Aging Study (SEBAS) in Taiwan, the Wisconsin Longitudinal Survey (WLS), and the MacArthur studies of successful aging. The outcomes comprise six indicators of cardiovascular risk (total/high-density lipoprotein [HDL] cholesterol, HDL cholesterol, systolic and diastolic blood pressure, glycosylated hemoglobin, and waist/hip ratio) and four markers of sympathetic nervous system (SNS) and hypothalamic-pituitary-adrenal (HPA) axis functioning (epinephrine, norepinephrine, cortisol, and dehydroepiandrosterone sulfate [DHEA-S]). RESULTS U.S. males have significantly higher risk than females for all indicators of cardiovascular risk except glycosylated hemoglobin (p < 0.05). Sex differences are less consistent and smaller in Taiwan. Indicators of SNS and HPA axis functioning reveal a significant female disadvantage in both countries. CONCLUSIONS The analysis identifies important sex differences between Taiwan and the United States in biomarkers of cardiovascular risk that are consistent with cause of death data and may emanate from cultural and social differences between the two societies. The similarity of sex differences in SNS and HPA axis functioning across studies may reflect either stable sex differences in biological aging of these axes or commonalities in the social construction of gender-based responses to life experiences.

A Multistate Model of Fecundability and Sterility

This paper develops a multistate hazards model for estimating fecundability and sterility from data on waiting times to conception. Important features of the model include separate sterile and nonsterile states, a distinction between preexisting sterility and sterility that begins after initiation of exposure, and log-normally distributed fecundability among nonsterile couples. Application of the model to data on first birth intervals from Taiwan, Sri Lanka, and the Amish shows that heterogeneity in fecundability is statistically significant at most ages, but that preexisting sterility and new sterility are unimportant before age 40. These results suggest that sterility may not be an important determinant of natural fertility until later reproductive ages.

Cohort Profile: The Social Environment and Biomarkers of Aging Study (SEBAS) in Taiwan

The Social Environment and Biomarkers of Aging Study (SEBAS) is a nationally representative longitudinal survey of Taiwanese middle-aged and older adults. It adds the collection of biomarkers and performance assessments to the Taiwan Longitudinal Study of Aging (TLSA), a nationally representative study of adults aged 60 and over, including the institutionalized population. The TLSA began in 1989, with follow-ups approximately every 3 years; younger refresher cohorts were added in 1996 and 2003. The first wave of SEBAS, based on a sub-sample of respondents from the 1999 TLSA, was conducted in 2000. A total of 1023 respondents completed both a face-to-face home interview and, several weeks later, a hospital-based physical examination. In addition to a 12-h (7 pm-7 am) urine specimen collected the night before and a fasting blood specimen collected during the examination, trained staff measured blood pressure, height, weight and waist and hip circumferences. A second wave of SEBAS was conducted in 2006 using a similar protocol to SEBAS 2000, but with the addition of performance assessments conducted by the interviewers at the end of the home interview. Both waves of SEBAS also included measures of health status (physical, emotional, cognitive), health behaviours, social relationships and exposure to stressors. The SEBAS data, which are publicly available at [http://www.icpsr.umich.edu/icpsrweb/NACDA/studies/3792/version/5], allow researchers to explore the relationships among life challenges, the social environment and health and to examine the antecedents, correlates and consequences of change in biological measures and health.