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Sociodemographic Effects on the Dynamics of Task-specific ADL Functioning at the Oldest-old Ages: The Case of China

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Abstract

Studies that systematically examine the dynamics of task-specific ADL functioning and its associates are very rare. Using the first three waves of the Chinese Longitudinal Healthy Longevity Survey, this study examines the dynamics of each of the six ADL tasks (bathing, dressing, toileting, indoor transferring, eating, and continence) and their sociodemographic correlates among the oldest-old by including the ADL information both at the follow-up wave for survivors and at the time prior to death for those who died during survey intervals. Effects of age, gender, urban/rural residence, ethnicity, education, primary lifetime occupation, primary source of daily expenses, living alone, and marital status are examined in both the absence and presence of other various confounders. Our results show that each sociodemographic factor still plays some limited role in the dynamics of ADL functioning across tasks.

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Notes

  1. As indicated in “Introduction” section, snapshot assessments in longitudinal surveys could result in substantial underestimation of disability of onset and recovery, especially when the survey interval exceeds 2 years. Therefore, we have tried to include disability information before dying for persons who died during survey interval to minimize underestimation based on the data available.

  2. Each of six ADL items has three categories in the CLHLS questionnaire representing “needing no help,” “needing partial help,” and “needing full help” although wordings might be slightly different for some tasks. The primary reason that we simply dichotomize each ADL task into “not disabled” (needing no help”) and disabled (needing partial or full help) is to match the concept of onset. Another reason is to avoid problems of complications and small sub-sample sizes in model estimation for few covariates. In the current dichotomized classification, the number of observations in recovery models for each of six ADL items among male ethnic minorities is around 20–60 and the number of events is around 10–20. The odds ratios would tend to be very larger or very small for the covariate of ethnicity and other few covariates in recovery models if we used three categories. Furthermore, the definition of recovery may get complicated in three categories, which is not the primary purpose of the study. Therefore, in our final analyses, we used dichotomized classification for each of six tasks of ADL functioning.

  3. The ordering of four tasks in the high level and two tasks in the low level of hierarchy is not very important since we do not focus on the ordering of six tasks in this study.

  4. Like studies focusing on aging in western societies that use different measurements to capture socioeconomic status, studies based on data in China lack a consensus in measuring socioeconomic status. For example, some studies use urban/rural residence and education as socioeconomic factors (e.g., Liang, Liu, & Gu, 2001); some use education and family income as proxy measurements of socioeconomic factors (e.g., Beydoun & Popkin, 2005); and others use education, household income, eligibility of pension, bank saving, and household amenities (e.g., Zimmer & Kwong, 2004). Zimmer and Kwong contended that primary lifetime occupation of the elderly should be a major indicator of socioeconomic status. Given that occupation data were unavailable in their dataset, Zimmer and Kwong used pension eligibility as a proxy of primary lifetime occupation. China is characterized by sharp disparities in socioeconomic development, healthcare, and welfare systems between urban and rural areas. Under this differential system, urban residents enjoy much better benefits in terms of public free medical services, employment, pension system, and other public goods. Eligibility of receiving benefits is symbolized by a household registration system. People belong to either a rural or urban household, and it is inherited from one generation to the next (Liang, Liu, & Gu, 2001). It is extremely difficult for rural households to convert to be urban households. Thus, it is acceptable to use urban/rural residence as a socioeconomic indicator of an individual or family for the data before 1978 when China started to undertake economic reform. However, since then, especially since the 1990s, rural residents could migrate to urban areas for employment or other opportunities, although they still would not have the same or similar benefits as urban residents. Urbanization has converted some rural households into urban households. Furthermore, the household registration system has been under reform in a few provinces since 2002. These events suggest it may be inappropriate to take urban/rural residence as an indicator of socioeconomic status in contemporary China. Some research in western countries argues that housing tenure should be included as a socioeconomic factor (e.g., Ebrahim, Papacosta, Wannamethee, & Adamson, 2004; Grundy & Holt, 2001); such data are not available in the first two waves of the CLHLS, however.

  5. Some studies focusing on the US find that racial/ethnical groups have significant disparity in ADL functioning at old ages with Black being disadvantaged (e.g., Crimmins et al., 1996; Land et al., 1994; Rogers et al., 1992). Other research shows that the racial gap converges and even crosses over at the oldest-old ages (e.g., Johnson, 2000). Zimmer and his colleagues find that Mainlanders and native Taiwanese have a significant difference in the onset of disability (Zimmer et al., 2002). In Mainland China, there is no study to explore the functional difference between ethnicities. Therefore, it is worthy to compare the difference of disability dynamics between ethnicities in China. Given that all minorities account for very small shares in the sample, we combine them into a single category.

  6. In the CLHLS questionnaire, primary lifetime occupation is grouped into seven categories: (1) agriculture/forestry/animal husbandry worker/fishery worker; (2) housekeeper; (3) professional and technical personnel/doctors/teachers; (4) governmental/institutional/managerial personnel; (5) industrial laborer/commercial/sales worker; (6) military personnel; and (7) others. For females, all non-agricultural occupations (i.e., category 3 to category 6) account for less than 15% share, which makes us unable to separate these categories in the analyses. For males, we have tested different categories of non-agricultural occupations on the onset and recovery of ADL. The results show that there is no significant difference across different non-agricultural categories. Therefore, we combined four non-agricultural categories together with other category (i.e., category 7) into a single non-agricultural category. This is also consistent with females’ non-agriculture category.

  7. The detailed coding system is not presented here but is available upon request.

  8. We have also imputed ADL status at Time 2 for those lost to follow-up. We have compared these results with the results excluding those respondents lost to follow-up and found that these two sets of results are very close. Given that the imputed data have more observations, we present results based on the imputed data.

  9. The weighted results are slightly different from unweighted ones. But their patterns and conclusions are the same. The weighted results are available from the authors upon request.

  10. See Footnote 1.

  11. The infant and child mortality of minorities in the 2000 census was 160% higher than the Han. The ethnic gap in mortality rate then tended to narrow to around 10% in the ages 70–79. In the oldest-old ages, minorities had a slightly lower mortality rate (National Bureau of Statistics of China, 2003).

  12. Bathing is considered the most difficult task among these six ADL tasks in previous studies (e.g., Katz et al., 1963; Jagger et al., 2001).

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Acknowledgement

Authors thank invaluable comments from two anonymous reviewers and constructive suggestions and edit work by Dr. Matthew E. Dupre at University of North Carolina at Chapel Hill, Dr. Denese Ashbaugh Vlosky at Duke University, and Dr. Haiyan Zhu at University of Michigan.

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  1. Center for Study of Aging and Human Development, Medical Center, Duke University, 200 Trent Dr. Busse BLDG RM 1506, Durham, NC, 27710, USA

    Danan Gu

  2. China National Research Center on Aging, Beijing, China

    Qin Xu

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Gu, D., Xu, Q. Sociodemographic Effects on the Dynamics of Task-specific ADL Functioning at the Oldest-old Ages: The Case of China. J Cross Cult Gerontol 22, 61–81 (2007). https://doi.org/10.1007/s10823-006-9024-0

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