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Longitudinal associations between perception of future time and subjective well-being among middle-aged and older people in China: the moderating roles of individual health and socioeconomic status

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Abstract

Purpose

This study examined the longitudinal association between perception of future time (PFT) and subjective well-being among middle- and old-aged people in China, and investigated the moderating roles of individual health resources and socioeconomic status (SES) in the association between PFT and subjective well-being.

Methods

Data for this study drew from a final sample of 10,644 respondents aged 45 years and above from four waves (2011–2018) of the China Health and Retirement Longitudinal Study (CHARLS). Subjective well-being was measured by depressive symptoms and life satisfaction. Multilevel linear modelling (MLM) was applied to analyse the main effects of PFT on depressive symptoms and life satisfaction over time and the moderating effects of individual health resources and SES.

Results

After controlling for the covariates, perceived future time as extended was associated with fewer depressive symptoms (β = − 0.85, p < 0.001) and higher levels of life satisfaction (β = 0.07, p < 0.001). Significant moderating effects of individual health resources (self-rated health, functional limitations and chronic diseases) and SES (urban–rural hukou) were found in associations between PFT and depressive symptoms.

Conclusion

Perceived future time as extended was associated with better subjective well-being. These associations differed in relation to different individual health resources and SES. This study extends understanding of Socioemotional Selectivity Theory and helps identify vulnerable people when they feel near to death.

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References

  1. Diener, E. (2009). Subjective well-being. In E. Diener (Ed.), The science of well-being: The collected works of diener (pp. 11–58). Springer.

    Chapter  Google Scholar 

  2. Ryan, R. M., & Deci, E. L. (2001). On happiness and human potentials: A review of research on hedonic and eudaimonic well-being. Annual Review of Psychology, 52, 141–166. https://doi.org/10.1146/annurev.psych.52.1.141

    Article  CAS  PubMed  Google Scholar 

  3. Chui, H., Gestorf, D., Hoppmann, C. A., & Luszcz, M. A. (2015). Trajectories of depressive symptoms in old age: Integrating age-, pathology-, and mortality-related changes. Psychology and Aging, 30(4), 940–951. https://doi.org/10.1037/pag0000054

    Article  PubMed  Google Scholar 

  4. Formanek, T., Csajbók, Z., Wolfová, K., Kučera, M., Tom, S., Aarsland, D., & Cermakova, P. (2020). Trajectories of depressive symptoms and associated patterns of cognitive decline. Scientific Reports. https://doi.org/10.1038/s41598-020-77866-6

    Article  PubMed  PubMed Central  Google Scholar 

  5. Burr, D. A., Castrellon, J. J., Zald, D. H., & Samanez-Larkin, G. R. (2021). Emotion dynamics across adulthood in everyday life: Older adults are more emotionally stable and better at regulating desires. Emotion, 21(3), 453–464. https://doi.org/10.1037/emo0000734

    Article  PubMed  Google Scholar 

  6. Carstensen, L. L. (2021). Socioemotional selectivity theory: The role of perceived endings in human motivation. The Gerontologist, 61(8), 1188–1196. https://doi.org/10.1093/geront/gnab116

    Article  PubMed  Google Scholar 

  7. Husman, J., & Shell, D. F. (2008). Beliefs and perceptions about the future: A measurement of future time perspective. Learning and Individual Differences, 18(2), 166–175. https://doi.org/10.1016/j.lindif.2007.08.001

    Article  Google Scholar 

  8. Carstensen, L. L. (1992). Social and emotional patterns in adulthood - Support for socioemotional selectivity theory. Psychology and Aging, 7(3), 331–338. https://doi.org/10.1037//0882-7974.7.3.331

    Article  CAS  PubMed  Google Scholar 

  9. Carstensen, L. L. (1993). Motivation for social contact across the life-span - A theory of socioemotional selectivity. Developmental Perspectives on Motivation, 40, 209–254.

    Google Scholar 

  10. Gabrian, M., Dutt, A. J., & Wahl, H. W. (2017). Subjective time perceptions and aging well: A review of concepts and empirical research—A mini-review. Gerontology, 63(4), 350–358. https://doi.org/10.1159/000470906

    Article  PubMed  Google Scholar 

  11. Dutt, A. J., & Wahl, H. W. (2018). Future time perspective and general self-efficacy mediate the association between awareness of age-related losses and depressive symptoms. European Journal of Ageing, 16(2), 227–236. https://doi.org/10.1007/s10433-018-0482-3

    Article  PubMed  PubMed Central  Google Scholar 

  12. Hoppmann, C. A., Infurna, F. J., Ram, N., & Gerstorf, D. (2017). Associations among individuals’ perceptions of future time, individual resources, and subjective well-being in old age. Journals of Gerontology Series B—Psychological Science and Social Science, 72(3), 388–399. https://doi.org/10.1093/geronb/gbv063

    Article  Google Scholar 

  13. Sakakibara, R., & Ishii, Y. (2020). Examination on how emotion regulation mediates the relationship between future time perspective and well-being: A counter-evidence to the socioemotional selectivity theory. European Journal of Ageing, 17(1), 21–30. https://doi.org/10.1007/s10433-019-00522-0

    Article  PubMed  Google Scholar 

  14. Ziegelmann, J. P., Lippke, S., & Schwarzer, R. (2006). Subjective residual life expectancy in health self-regulation. Journals of Gerontology Series B—Psychological Sciences and Social Sciences, 61(4), 195–201. https://doi.org/10.1093/geronb/61.4.p195

    Article  Google Scholar 

  15. Baltes, B. B., Wynne, K., Sirabian, M., Krenn, D., & de Lange, A. (2014). Future time perspective, regulatory focus, and selection, optimization, and compensation: Testing a longitudinal model. Journal of Organizational Behavior, 35(8), 1120–1133. https://doi.org/10.1002/job.1970

    Article  Google Scholar 

  16. Lowsky, D. J., Olshansky, S. J., Bhattacharya, J., & Goldman, D. P. (2014). Heterogeneity in healthy aging. The Journals of Gerontology. Series A. Biological Sciences and Medical Sciences, 69(6), 640–649. https://doi.org/10.1093/gerona/glt162

    Article  PubMed  Google Scholar 

  17. Charles, S. T. (2010). Strength and vulnerability integration: A model of emotional well-being across adulthood. Psychological Bulletin, 136(6), 1068–1091. https://doi.org/10.1037/a0021232

    Article  PubMed  PubMed Central  Google Scholar 

  18. Baltes, M. M., & Carstensen, L. L. (1966). The process of successful ageing. Ageing and Society, 16(4), 397–422. https://doi.org/10.1017/S0144686X00003603

    Article  Google Scholar 

  19. Freund, A. M. (2008). Successful aging as management of resources: The role of selection, optimization, and compensation. Research in Human Development, 5(2), 94–106. https://doi.org/10.1080/15427600802034827

    Article  Google Scholar 

  20. Kahana, E., Kahana, B., & Lee, J. E. (2014). Proactive approaches to successful aging: One clear path through the forest. Gerontology, 60(5), 466–474. https://doi.org/10.1159/000360222

    Article  PubMed  Google Scholar 

  21. Hur, M. H. (2018). Demographic and socioeconomic determinants of self-efficacy: An empirical study of Korean older adults. International Journal of Aging and Human Development, 87(3), 289–308. https://doi.org/10.1177/0091415017738081

    Article  PubMed  Google Scholar 

  22. Xu, Y., Yang, J., Gao, J., Zhou, Z., Zhang, T., Ren, J., Li, Y., Qian, Y., Lai, S., & Chen, G. (2016). Decomposing socioeconomic inequalities in depressive symptoms among the elderly in China. B MC Public Health, 16(1), 1214. https://doi.org/10.1186/s12889-016-3876-1

    Article  Google Scholar 

  23. Barrett, A. E. (2003). Socioeconomic status and age identity: The role of dimensions of health in the subjective construction of age. Journals of Gerontology: Series B - Psychological Sciences and Social Sciences, 58(2), S101–S109. https://doi.org/10.1093/geronb/58.2.s101

    Article  Google Scholar 

  24. Muhammad, T., Srivastava, S., & Sekher, T. V. (2021). Association of self-perceived income status with psychological distress and subjective well-being: A cross-sectional study among older adults in India. BMC Psychology, 9(1), 82. https://doi.org/10.1186/s40359-021-00588-5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Han, Y., He, Y., Lyu, J., Yu, C., Bian, M., & Lee, L. (2020). Aging in China: Perspectives on public health. Global Health Journal, 4(1), 11–17. https://doi.org/10.1016/j.glohj.2020.01.002

    Article  Google Scholar 

  26. Yan, C., Liao, H., Ma, Y., Xiang, Q., & Wang, J. (2021). Association among multimorbidity, physical disability and depression trajectories: A study of urban-rural differences in China. Quality of Life Research, 30(8), 2149–2160. https://doi.org/10.1007/s11136-021-02807-3

    Article  PubMed  PubMed Central  Google Scholar 

  27. Li, C., Chi, I., Zhang, X., Chrng, Z., Zhang, L., & Chen, G. (2015). Urban and rural factors associated with life satisfaction among older Chinese adults. Aging and Mental Health, 19(10), 947–954. https://doi.org/10.1080/13607863.2014.977767

    Article  PubMed  Google Scholar 

  28. Song, Q., & Smith, J. P. (2019). Hukou system, mechanisms, and health stratification across the life course in rural and urban China. Health & Place, 58, 102150. https://doi.org/10.1016/j.healthplace.2019.102150

    Article  Google Scholar 

  29. Liu, D., Xi, J., Hall, B. J., Fu, M., Zhang, B., Guo, J., & Feng, X. (2020). Attitudes toward aging, social support and depression among older adults: Difference by urban and rural areas in China. Journal of Affective Disorders, 274, 85–92. https://doi.org/10.1016/j.jad.2020.05.052

    Article  PubMed  Google Scholar 

  30. Zhao, Y., Hu, Y., Smith, J. P., Strauss, J., & Yang, G. (2014). Cohort profile: The China health and retirement longitudinal study (CHARLS). International Journal of Epidemiology, 43(1), 61–68. https://doi.org/10.1093/ije/dys203

    Article  PubMed  Google Scholar 

  31. Lewinsohn, P. M., Seeley, J. R., Roberts, R. E., & Allen, N. B. (1997). Center for Epidemiologic Studies Depression Scale (CES-D) as a screening instrument for depression among community-residing older adults. Psychology and Aging, 12(2), 277–87. https://doi.org/10.1037//0882-7974.12.2.277

    Article  CAS  PubMed  Google Scholar 

  32. Li, C. (2013). Little’s test of missing completely at random. Stata Journal, 13(4), 795–809. https://doi.org/10.1177/1536867X1301300407

    Article  Google Scholar 

  33. Kwok, O.-M., Underhill, A. T., Berry, J. W., Luo, W., Elliott, T. R., & Yoon, M. (2008). Analyzing longitudinal data with multilevel models: An example with individuals living with lower extremity intra-articular fractures. Rehabilitation Psychology, 53(3), 370–386. https://doi.org/10.1037/a0012765

    Article  PubMed  PubMed Central  Google Scholar 

  34. Luo, W., Li, H., Baek, E., Chen, S., Lam, K. H., & Semma, B. (2021). Reporting practice in multilevel modeling: A revisit after 10 years. Review of Educational Research, 91(3), 311–355. https://doi.org/10.3102/0034654321991229

    Article  Google Scholar 

  35. Snijders, T. (1996). Analysis of longitudinal data using the hierarchical linear model. Quality and Quantity, 30(4), 405–426. https://doi.org/10.1007/BF00170145

    Article  Google Scholar 

  36. Hofmann, D. A., Griffin, M. A., & Gavin, M. B. (2000). The application of hierarchical linear modeling to organizational research. In K. J. Klein & S. W. J. Kozlowski (Eds.), Multilevel theory, research, and methods in organizations: Foundations, extensions, and new directions (pp. 467–511). Jossey-Bass.

    Google Scholar 

  37. Simons, M., Peeters, S., Janssens, M., Lataster, J., & Jacobs, N. (2018). Does age make a difference? Age as moderator in the association between time perspective and happiness. Journal of Happiness Studies, 19(1), 57–67. https://doi.org/10.1007/s10902-016-9806-1

    Article  Google Scholar 

  38. Kim, Y., & Radoias, V. (2021). Subjective socioeconomic status, health, and early-life conditions. Journal of Health Psychology, 26(4), 595–604. https://doi.org/10.1177/1359105319828137

    Article  CAS  PubMed  Google Scholar 

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Correspondence to Shiyu Lu.

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The China Health and Retirement Longitudinal Study was ethically approved by the institutional review board of Peking University. All respondents provided written informed consent, and all data were deidentified.

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All respondents provided written informed consent in The China Health and Retirement Longitudinal Study.

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Lu, S. Longitudinal associations between perception of future time and subjective well-being among middle-aged and older people in China: the moderating roles of individual health and socioeconomic status. Qual Life Res 31, 3009–3018 (2022). https://doi.org/10.1007/s11136-022-03163-6

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