Skip to main content

Advertisement

SpringerLink
Log in

Subjective life expectancy and associated factors among cancer survivors over 45 years old: evidence from the CHARLS

  • Published:
Quality of Life Research Aims and scope Submit manuscript

Abstract

Purpose

Associations between subjective life expectancy (SLE) and a variety of factors are well documented, but the relationship regarding cancer is limited. The purpose of this study was to disclose this potential relationship and identify the covariates that might influence this relationship.

Methods

Data were extracted from the China Health and Retirement Longitudinal Study (CHARLS), and a sample of 448 cancer survivors and 43,795 individuals without cancer were analyzed. Multilevel mixed-effects logistic regression was performed to examine the SLE associated with cancer survivors and participants without cancer after controlling for demographic, socioeconomic, health-related, and psychosocial factors.

Results

The findings revealed that cancer survivors had a 39% reduction in longer life expectancy compared to respondents without cancer. Disparities in SLE existed based on diverse individual characteristics. The rate of high SLE in urban citizens was 75% higher compared to that of rural residents, while the rate of high SLE in participants with disability fell by 55%. The rate of high SLE decreased by 22% and 35% in respondents with high blood pressure and diabetes, respectively. The proportion of respondents with high SLE was reduced by 70% when depression was present. Furthermore, the out-of-pocket expenditures of participants with and without cancer showed a significant difference, but discrepancies with respect to SLE among different cancer treatment options were not found.

Conclusion

The more challenging one’s socioeconomic status is and the unhealthier one’s physical and mental conditions are, the lower one’s prospect of subjective life expectancy is. Further work is warranted to confirm the causal association between subjective life expectancy and certain characteristics in cancer survivors.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

Data availability

The data and other items supporting the results in the paper will be made available upon reasonable request to the corresponding author.

Code availability

The corresponding author can be contacted to request a copy of the scripts used to generate the results included in this manuscript.

References

  1. Siegel, M., Bradley, E. H., & Kasl, S. V. (2003). Self-rated life expectancy as a predictor of mortality: Evidence from the HRS and AHEAD surveys. Gerontology, 49(4), 265–271. https://doi.org/10.1159/000070409.

    Article  PubMed  Google Scholar 

  2. Sonnega, A., Faul, J. D., Ofstedal, M. B., Langa, K. M., Phillips, J. W., & Weir, D. R. (2014). Cohort profile: The health and retirement study (HRS). International Journal of Epidemiology, 43(2), 576–585. https://doi.org/10.1093/ije/dyu067.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Steptoe, A., Breeze, E., Banks, J., & Nazroo, J. (2013). Cohort profile: The English longitudinal study of ageing. International Journal of Epidemiology, 42(6), 1640–1648. https://doi.org/10.1093/ije/dys168.

    Article  PubMed  Google Scholar 

  4. Bosch-Farré, C., Garre-Olmo, J., Bonmatí-Tomàs, A., Malagón-Aguilera, M. C., Gelabert-Vilella, S., Fuentes-Pumarola, C., et al. (2018). Prevalence and related factors of Active and Healthy Ageing in Europe according to two models: Results from the Survey of Health, Ageing and Retirement in Europe (SHARE). PLoS ONE, 13(10), e0206353. https://doi.org/10.1371/journal.pone.0206353.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. 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 

  6. Choi, Y., Lee, K. S., Shin, J., Kwon, J. A., & Park, E. C. (2017). Effects of a change in social activity on quality of life among middle-aged and elderly Koreans: Analysis of the Korean longitudinal study of aging (2006–2012). Geriatrics & Gerontology International, 17(1), 132–141. https://doi.org/10.1111/ggi.12685.

    Article  Google Scholar 

  7. Lee, S., & Smith, J. (2016). Methodological aspects of subjective life expectancy: Effects of culture-specific reporting heterogeneity among older adults in the United States. Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 71(3), 558–568. https://doi.org/10.1093/geronb/gbv048.

    Article  Google Scholar 

  8. 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), P195-201. https://doi.org/10.1093/geronb/61.4.p195.

    Article  Google Scholar 

  9. Bodner, E., & Bergman, Y. S. (2016). Loneliness and depressive symptoms among older adults: The moderating role of subjective life expectancy. Psychiatry Research, 237, 78–82. https://doi.org/10.1016/j.psychres.2016.01.074.

    Article  PubMed  Google Scholar 

  10. Prochaska, J. D., Jupiter, D. C., Horel, S., Vardeman, J., & Burdine, J. N. (2020). Rural-urban differences in estimated life expectancy associated with neighborhood-level cumulative social and environmental determinants. Preventive Medicine, 139, 106214. https://doi.org/10.1016/j.ypmed.2020.106214.

    Article  PubMed  Google Scholar 

  11. Perozek, M. (2008). Using subjective expectations to forecast longevity: Do survey respondents know something we don’t know? Demography, 45(1), 95–113. https://doi.org/10.1353/dem.2008.0010.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Kim, J. H., & Kim, J. M. (2017). Subjective life expectancy is a risk factor for perceived health status and mortality. Health and Quality of Life Outcomes, 15(1), 190. https://doi.org/10.1186/s12955-017-0763-0.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Palloni, A., & Novak, B. (2016). Subjective survival expectations and observed survival: How consistent are they? Vienna Yearbook of Population Research, 14, 187–227. https://doi.org/10.1553/populationyearbook2016s187.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Philipov, D., & Scherbov, S. (2020). Subjective length of life of European individuals at older ages: Temporal and gender distinctions. PLoS ONE, 15(3), e0229975. https://doi.org/10.1371/journal.pone.0229975.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Wu, H. (2020). How do co- and non-residential children impact your subjective life expectancy: An empirical study on CHARLS Data? International Journal of Health and Planning Management, 35(2), 532–544. https://doi.org/10.1002/hpm.2946.

    Article  Google Scholar 

  16. Péntek, M., Brodszky, V., Gulácsi, Á. L., Hajdú, O., van Exel, J., Brouwer, W., et al. (2014). Subjective expectations regarding length and health-related quality of life in Hungary: Results from an empirical investigation. Health Expectations, 17(5), 696–709. https://doi.org/10.1111/j.1369-7625.2012.00797.x.

    Article  PubMed  Google Scholar 

  17. Griffin, B., Loh, V., & Hesketh, B. (2013). A mental model of factors associated with subjective life expectancy. Social Science and Medicine, 82, 79–86. https://doi.org/10.1016/j.socscimed.2013.01.026.

    Article  PubMed  Google Scholar 

  18. Feng, R. M., Zong, Y. N., Cao, S. M., & Xu, R. H. (2019). Current cancer situation in China: Good or bad news from the 2018 Global Cancer Statistics? Cancer Communication (London), 39(1), 22. https://doi.org/10.1186/s40880-019-0368-6.

    Article  Google Scholar 

  19. Zhou, M., Wang, H., Zeng, X., Yin, P., Zhu, J., Chen, W., et al. (2019). Mortality, morbidity, and risk factors in China and its provinces, 1990–2017: A systematic analysis for the Global Burden of Disease Study 2017. The Lancet, 394(10204), 1145–1158. https://doi.org/10.1016/S0140-6736(19)30427-1.

    Article  Google Scholar 

  20. Huang, H.-Y., Shi, J.-F., Guo, L.-W., Zhu, X.-Y., Wang, L., Liao, X.-Z., et al. (2016). Expenditure and financial burden for common cancers in China: A hospital-based multicentre cross-sectional study. The Lancet, 388, S10. https://doi.org/10.1016/S0140-6736(16)31937-7.

    Article  Google Scholar 

  21. Zeng, H., Chen, W., Zheng, R., Zhang, S., Ji, J. S., Zou, X., et al. (2018). Changing cancer survival in China during 2003–15: A pooled analysis of 17 population-based cancer registries. Lancet Global Health, 6(5), e555–e567. https://doi.org/10.1016/s2214-109x(18)30127-x.

    Article  PubMed  Google Scholar 

  22. Pak, T. Y., Kim, H., & Kim, K. T. (2020). The long-term effects of cancer survivorship on household assets. Health Economy Review, 10(1), 2. https://doi.org/10.1186/s13561-019-0253-7.

    Article  Google Scholar 

  23. Ekenga, C. C., Kwon, E., Kim, B., & Park, S. (2020). Long-term employment outcomes among female cancer survivors. International Journal of Environmental Research and Public Health. https://doi.org/10.3390/ijerph17082751.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Lunet, N., Pereira, S., Dias, T., Fontes, F., Araújo, N., Lopes-Conceição, L., et al. (2019). Changes in employment status up to 5 years after breast cancer diagnosis: A Prospective Cohort Study (Vol. 48, Vol. 12): The Breast.

  25. Cagle, J. G., Lee, J., Ornstein, K. A., & Guralnik, J. M. (2020). Hospice utilization in the United States: A prospective cohort study comparing cancer and noncancer deaths. Journal of the American Geriatrics Society, 68(4), 783–793. https://doi.org/10.1111/jgs.16294.

    Article  PubMed  Google Scholar 

  26. Ellis, L., Canchola, A. J., Spiegel, D., Ladabaum, U., Haile, R., & Gomez, S. L. (2018). Racial and ethnic disparities in cancer survival: The contribution of tumor, sociodemographic, institutional, and neighborhood characteristics. Journal of Clinical Oncology, 36(1), 25–33. https://doi.org/10.1200/jco.2017.74.2049.

    Article  CAS  PubMed  Google Scholar 

  27. Elder, T. E. (2013). The predictive validity of subjective mortality expectations: Evidence from the Health and Retirement Study. Demography, 50(2), 569–589. https://doi.org/10.1007/s13524-012-0164-2.

    Article  PubMed  Google Scholar 

  28. Keyes, C. L. M., & Westerhof, G. J. (2012). Chronological and subjective age differences in flourishing mental health and major depressive episode. Aging Mental Health, 16(1), 67–74. https://doi.org/10.1080/13607863.2011.596811.

    Article  PubMed  Google Scholar 

  29. Lee, S., McClain, C., Webster, N., & Han, S. (2016). Question order sensitivity of subjective well-being measures: Focus on life satisfaction, self-rated health, and subjective life expectancy in survey instruments. Quality of Life Research, 25(10), 2497–2510. https://doi.org/10.1007/s11136-016-1304-8.

    Article  PubMed  Google Scholar 

  30. Kobayashi, L. C., von Wagner, C., & Wardle, J. (2017). Perceived life expectancy is associated with colorectal cancer screening in England. Annals of Behavioral Medicine, 51(3), 327–336. https://doi.org/10.1007/s12160-016-9855-z.

    Article  PubMed  Google Scholar 

  31. van Solinge, H., & Henkens, K. (2010). Living longer, working longer? The impact of subjective life expectancy on retirement intentions and behaviour. European Journal of Public Health, 20(1), 47–51. https://doi.org/10.1093/eurpub/ckp118.

    Article  PubMed  Google Scholar 

  32. Liu, J., Rozelle, S., Xu, Q., Yu, N., & Zhou, T. (2019). Social engagement and elderly health in China: Evidence from the China Health and Retirement Longitudinal Survey (CHARLS). International Journal of Environmental Research and Public Health. https://doi.org/10.3390/ijerph16020278.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Milić, S., Lulić, D., & Štimac, D. (2014). Non-alcoholic fatty liver disease and obesity: Biochemical, metabolic and clinical presentations. World Journal of Gastroenterology, 20(28), 9330–9337. https://doi.org/10.3748/wjg.v20.i28.9330.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Zaninotto, P., & Steptoe, A. (2019). Association Between Subjective Well-being and Living Longer Without Disability or Illness. JAMA Netw Open, 2(7), e196870. https://doi.org/10.1001/jamanetworkopen.2019.6870.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Jin, Y., Zhu, D., & He, P. (2020). Social causation or social selection? The longitudinal interrelationship between poverty and depressive symptoms in China. Social Science and Medicine, 249, 112848. https://doi.org/10.1016/j.socscimed.2020.112848.

    Article  PubMed  Google Scholar 

  36. Austin, P. C. (2010). Estimating multilevel logistic regression models when the number of clusters is low: A comparison of different statistical software procedures. International Journal of Biostatistics, 6(1), Article 16. https://doi.org/10.2202/1557-4679.1195.

  37. Shinan-Altman, S., & Werner, P. (2019). Subjective age and its correlates among middle-aged and older adults. The International Journal of Aging and Human Development, 88(1), 3–21. https://doi.org/10.1177/0091415017752941.

    Article  PubMed  Google Scholar 

  38. Freedman, R. A., Keating, N. L., Pace, L. E., Lii, J., McCarthy, E. P., & Schonberg, M. A. (2017). Use of surveillance mammography among older breast cancer survivors by life expectancy. Journal of Clinical Oncology, 35(27), 3123–3130. https://doi.org/10.1200/jco.2016.72.1209.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Schapmire, T. J., & Faul, A. C. (2017). Depression symptoms in older adults with cancer: A multilevel longitudinal study. Journal of Psychosocial Oncology, 35(3), 260–277. https://doi.org/10.1080/07347332.2017.1286698.

    Article  PubMed  Google Scholar 

  40. Péntek, M., Brodszky, V., Biró, Z., Kölkedi, Z., Dunai, Á., Németh, J., et al. (2017). Subjective health expectations of patients with age-related macular degeneration treated with antiVEGF drugs. BMC Geriatrics, 17(1), 233–233. https://doi.org/10.1186/s12877-017-0619-9.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Zhang, X., Dupre, M. E., Qiu, L., Zhou, W., Zhao, Y., & Gu, D. (2017). Urban-rural differences in the association between access to healthcare and health outcomes among older adults in China. BMC Geriatrics, 17(1), 151. https://doi.org/10.1186/s12877-017-0538-9.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Hendi, A. S. (2017). Trends in education-specific life expectancy, data quality, and shifting education distributions: A note on recent research. Demography, 54(3), 1203–1213. https://doi.org/10.1007/s13524-017-0574-2.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Han, X., Yabroff, K. R., Ward, E., Brawley, O. W., & Jemal, A. (2018). Comparison of insurance status and diagnosis stage among patients with newly diagnosed cancer before vs after implementation of the Patient Protection and Affordable Care Act. JAMA Oncology, 4(12), 1713–1720. https://doi.org/10.1001/jamaoncol.2018.3467.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Kontis, V., Bennett, J. E., Mathers, C. D., Li, G., Foreman, K., & Ezzati, M. (2017). Future life expectancy in 35 industrialised countries: Projections with a Bayesian model ensemble. Lancet, 389(10076), 1323–1335. https://doi.org/10.1016/s0140-6736(16)32381-9.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Moussa, R. K., & Diaby, V. (2020). Self-assessed life expectancy among older adults in Côte d’Ivoire. BMC Public Health, 20(1), 932. https://doi.org/10.1186/s12889-020-09034-4.

    Article  PubMed  PubMed Central  Google Scholar 

  46. van Solinge, H., & Henkens, K. (2018). Subjective life expectancy and actual mortality: Results of a 10-year panel study among older workers. European Journal of Ageing, 15(2), 155–164. https://doi.org/10.1007/s10433-017-0442-3.

    Article  PubMed  Google Scholar 

  47. Arpino, B., Bordone, V., & Scherbov, S. (2018). Smoking, education and the ability to predict own survival probabilities. Advances in Life Course Research, 37, 23–30. https://doi.org/10.1016/j.alcr.2018.06.001.

    Article  Google Scholar 

  48. Zuniga, K., & Bishop, N. (2018). Recent cancer treatment and memory decline in older adults: An analysis of the 2002–2012 Health and Retirement Study (Vol. 9, Vol. 3): J Geriatr Oncol.

  49. Guimarães, R. M., & Andrade, F. C. D. (2020). Healthy life-expectancy and multimorbidity among older adults: Do inequality and poverty matter? Archives of Gerontology and Geriatrics, 90, 104157. https://doi.org/10.1016/j.archger.2020.104157.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

We thank the CHARLS field team and the research team for their contributions to data collection and management.

Author information

Authors and Affiliations

  1. Department of Medical Insurance, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, Beijing, China

    Zhishui Chen

  2. Center for Health Development Studies, Peking University, Beijing, China

    Dawei Zhu

  3. School of Public Health, Capital Medical University, Beijing, China

    Xingyu Hu & Guangying Gao

Authors
  1. Zhishui Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dawei Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xingyu Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Guangying Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

ZC and GG planned and designed the study. DZ and ZC acquired and analyzed the data. DZ, ZC and XH developed the analyses. All authors contributed to the advanced draft of the manuscript and approved the final version of the paper.

Corresponding author

Correspondence to Guangying Gao.

Ethics declarations

Conflict of interest

The authors have declared no conflicts of interest.

Ethical approval

The CHARLS study was approved by the ethics committee of Peking University Health Science Center, Beijing, China. The requirement for informed consent was waived since the collected data were already anonymous.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, Z., Zhu, D., Hu, X. et al. Subjective life expectancy and associated factors among cancer survivors over 45 years old: evidence from the CHARLS. Qual Life Res 30, 1571–1582 (2021). https://doi.org/10.1007/s11136-020-02751-8

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11136-020-02751-8

Keywords

Search

Navigation