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1.
J Gerontol B Psychol Sci Soc Sci ; 77(2): 365-377, 2022 02 03.
Article in English | MEDLINE | ID: mdl-33837409

ABSTRACT

OBJECTIVES: Determinants of mortality may depend on the time and place where they are examined. China provides an important context in which to study the determinants of mortality at older ages because of its unique social, economic, and epidemiological circumstances. This study uses a nationally representative sample of persons in China to determine how socioeconomic characteristics, early-life conditions, biological and physical functioning, and disease burden predict 4-year mortality after age 60. METHODS: We used data from the China Health and Retirement Longitudinal Study. We employed a series of Cox proportional hazard models based on exact survival time to predict 4-year all-cause mortality between the 2011 baseline interview and the 2015 interview. RESULTS: We found that rural residence, poor physical functioning ability, uncontrolled hypertension, diabetes, cancer, a high level of systemic inflammation, and poor kidney functioning are strong predictors of mortality among older Chinese. DISCUSSION: The results show that the objectively measured indicators of physical functioning and biomarkers are independent and strong predictors of mortality risk after accounting for several additional self-reported health measures, confirming the value of incorporating biological and performance measurements in population health surveys to help understand health changes and aging processes that lead to mortality. This study also highlights the importance of social and historical context in the study of old-age mortality.


Subject(s)
Aging , Chronic Disease , Cost of Illness , Mortality , Physical Functional Performance , Aged , Aging/ethnology , Aging/physiology , Aging/psychology , China/epidemiology , Chronic Disease/classification , Chronic Disease/epidemiology , Chronic Disease/mortality , Female , Health Status Disparities , Humans , Longitudinal Studies , Male , Proportional Hazards Models , Risk Factors , Socioeconomic Factors
2.
Glob Health Action ; 13(1): 1768502, 2020 12 31.
Article in English | MEDLINE | ID: mdl-32544003

ABSTRACT

BACKGROUND: Verbal autopsy is designed to ascertain causes of death that are not registered or certified. Verbal autopsy has been validated in multiple settings but has not been as widely evaluated for older populations as for younger age groups. OBJECTIVE: This study aims to provide empirical evidence of the value of verbal autopsy interviews in the context of population-based surveys of older adults by comparing the cause-of-death assignments derived from two methods of interpreting verbal autopsy data. METHODS: Data used in this study come from the China Health and Retirement Longitudinal Study, a nationally representative longitudinal survey of older Chinese. We compared 407 causes of death determined using InterVA, which is a computer-coded method, and causes of death as assigned by experts; then evaluated factors that affect the results of the two approaches. RESULTS: Among the 407 deaths, neoplasms, cardiac disease, and stroke are the leading causes of death according to both approaches. The consistency of the two approaches is about 45% at the individual level. The primary reason for the mismatch is that no cause of death could be assigned for more than 25% of the sample based on expert review. A higher likelihood of mismatch is associated with advanced age and a long period between death and verbal autopsy interview. CONCLUSION: Both approaches identify the same leading causes of death at the aggregate level, but consistency is relatively low at the individual level. InterVA works well when causes of death are characterized by distinctive signs and symptoms. Grouping the various causes of death with shared etiology or common risk factors may help improve the quality of the ascertainment of causes of death. Open-ended narratives are helpful because they provide information about the circumstances surrounding the death that are not available in the structured verbal autopsy interviews.


Subject(s)
Autopsy/methods , Cause of Death , Aged , Aged, 80 and over , Algorithms , China/epidemiology , Diagnosis, Computer-Assisted/mortality , Expert Testimony , Female , Humans , Longitudinal Studies , Male , Middle Aged , Mortality
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