To what extent do disparities in economic development and healthcare availability explain between‐province health inequalities among older people in China?

Sol Richardson; Zhihui Li

doi:10.1002/hcs2.32

Health Care Science 2023, 2(2): 94-111 https://doi.org/10.1002/hcs2.32

Original Article |

Open Access | Issue | Published: 09 March 2023

To what extent do disparities in economic development and healthcare availability explain between‐province health inequalities among older people in China?

Show Author's Information Hide Author's Information Sol Richardson

(

), Zhihui Li

Vanke School of Public Health, Tsinghua University, Beijing, China

Keywords:

depression, China, overweight, inequalities, multilevel modelling, wellbeing, disability, lung function

Cite this article:

Richardson S, Li Z. To what extent do disparities in economic development and healthcare availability explain between‐province health inequalities among older people in China?. Health Care Science, 2023, 2(2): 94-111. https://doi.org/10.1002/hcs2.32

Download citation

EndNote(RIS)

BibTeX

309

Views

Downloads

Citations

Crossref

N/A

WoS

Scopus

N/A

CSCD

Abstract Full text About this article

Abstract

Background

Uneven economic development has led to substantial health inequalities between Chinese provinces. The extent of, and factors underlying, between‐province health inequalities have received little attention.

Methods

Data from 15,278 respondents in Wave 2 (2013) of the China Health and Retirement Longitudinal Study (CHARLS) were used to investigate inequalities among people aged ≥50 years in five health outcomes between 27 Chinese province‐level administrative units. After characterizing the between‐province differences and the relevance of province effects, proportional change in variance between unadjusted and adjusted models was calculated to determine the percentage of between‐province variance in health outcomes explained by province‐level variables including measures of economic development and healthcare availability.

Results

Although province effects explained <10% of overall variance in health outcomes, they underpinned large between‐province inequalities among people aged ≥50 years. Gross Regional Product per capita was more important than doctor density in explaining between‐province variance in health outcomes, particularly depression symptoms and instrumental activities of daily living impairment.

Conclusion

Policy efforts, including more equal distribution of healthcare personnel, may be warranted to reduce between‐province health inequalities.

Full text

Abstract

Full text

Outline

About this article

To what extent do disparities in economic development and healthcare availability explain between‐province health inequalities among older people in China?

Show Author's information Hide Author's Information Sol Richardson

(

), Zhihui Li

Vanke School of Public Health, Tsinghua University, Beijing, China

Abstract

Background

Methods

Results

Conclusion

Policy efforts, including more equal distribution of healthcare personnel, may be warranted to reduce between‐province health inequalities.

Keywords: depression, China, overweight, inequalities, multilevel modelling, wellbeing, disability, lung function

References(38)

Lin JY. China's growth miracle in the context of Asian transformation. Helsinki: World Institute for Development Economics Research (UNU‐WIDER); 2018. https://doi.org/10.35188/UNU-WIDER/2018/534-3

DOI

Li S, Xu Z. The trend of regional income disparity in the People's Republic of China. Tokyo: Asian Development Bank Institute; 2008.

Jain‐Chandra S, Khor H, Mano R, Schauer J, Wingender W, Zhuang J. Inequality in China‐trends, drivers and policy remedies. Washington, DC: International Monetary Fund; 2018.

DOI

Yang G, Kong L, Zhao W, Wan X, Zhai Y, Chen LC, et al. Emergence of chronic non‐communicable diseases in China. Lancet. 2008;372(9650):1697–705. https://doi.org/10.1016/S0140-6736(08)61366-5

DOI Google Scholar

Campbell TC, Junshi C, Brun T, Parpia B, Yinsheng Q, Chumming C, et al. China: from diseases of poverty to diseases of affluence. policy implications of the epidemiological transition. Ecol Food Nutr. 1992;27(2):133–44. https://doi.org/10.1080/03670244.1992.9991235

DOI Google Scholar

Zhou M, Wang H, Zhu J, Chen W, Wang L, Liu S, et al. Cause‐specific mortality for 240 causes in China during 1990–2013: a systematic subnational analysis for the global burden of disease study 2013. Lancet. 2016;387(10015):251–72. https://doi.org/10.1016/S0140-6736(15)00551-6

DOI Google Scholar

Fan S, Kanbur R, Zhang X. China's regional disparities: experience and policy. Rev Dev Finance. 2011;1(1):47–56. https://doi.org/10.1016/j.rdf.2010.10.001

DOI Google Scholar

Chou WL, Wang Z. Regional inequality in China's health care expenditures. Health Econ. 2009;18(suppl 2):S137–46. https://doi.org/10.1002/hec.1511

DOI Google Scholar

Zhou K, Zhang X, Ding Y, Wang D, Lu Z, Yu M. Inequality trends of health workforce in different stages of medical system reform (1985–2011) in China. Hum Resour Health. 2015;13:94. https://doi.org/10.1186/s12960-015-0089-0

DOI Google Scholar

Qin X, Wang S, Hsieh CR. The prevalence of depression and depressive symptoms among adults in China: estimation based on a national household survey. China Econ Rev. 2018;51:271–82. https://doi.org/10.1016/j.chieco.2016.04.001

DOI Google Scholar

Easterlin RA, Morgan R, Switek M, Wang F. China's life satisfaction, 1990‐2010. Proc Natl Acad Sci. 2012;109(25):9775–80. https://doi.org/10.1016/j.chieco.2016.04.001

DOI Google Scholar

Liang Y, Welmer A‐K, Möller J, Qiu C. Trends in disability of instrumental activities of daily living among older Chinese adults, 1997‐2006: population based study. BMJ Open. 2017;7(8):e016996. https://doi.org/10.1136/bmjopen-2017-016996

DOI Google Scholar

He Y, Pan A, Wang Y, Yang Y, Xu J, Zhang Y, et al. Prevalence of overweight and obesity in 15.8 million men aged 15–49 years in rural China from 2010 to 2014. Sci Rep. 2017;7(1):5012. https://doi.org/10.1038/s41598-017-04135-4

DOI Google Scholar

Fang L, Gao P, Bao H, Tang X, Wang B, Feng Y, et al. Chronic obstructive pulmonary disease in China: a nationwide prevalence study. Lancet Res Med. 2018;6(6):421–30. https://doi.org/10.1016/S2213-2600(18)30103-6

DOI Google Scholar

Evandrou M, Falkingham J, Feng Z, Vlachantoni A. Individual and province inequalities in health among older peoplein China: evidence and policy implications. Health Place. 2014;30:134–44. https://doi.org/10.1016/j.healthplace.2014.08.009

DOI Google Scholar

Feng Z, Wang WW, Jones K. A multilevel analysis of the role of the family and the state in self‐rated health of elderly Chinese. Health Place. 2013;30:148–56. https://doi.org/10.1016/j.healthplace.2013.07.001

DOI Google Scholar

Richardson S, Carr E, Netuveli G, Sacker A. Country‐level welfare‐state measures and change in wellbeing following work exit in early old age: evidence from 16 European countries. Int J Epidemiol. 48(2):389–401. https://doi.org/10.1093/ije/dyy205

DOI Google Scholar

Zhao Y, Hu Y, Smith JP, Strauss J, Yang G. Cohort profile: the China Health and Retirement Longitudinal Study (CHARLS). Int J Epidemiol. 2014;43(1):61–8. https://doi.org/10.1093/ije/dys203

DOI Google Scholar

Chen H, Mui AC. Factorial validity of the Center for Epidemiologic Studies Depression Scale short form in older population in China. Int Psychogeriatr. 2014;26(1):49–57. https://doi.org/10.1017/S1041610213001701

DOI Google Scholar

Andresen EM, Malmgren JA, Carter WB, Patrick DL. Screening for depression in well older adults: evaluation of a short form of the CES‐D. Am J Prev Med. 1994;10(2):77–84. https://doi.org/10.1016/S0749-3797(18)30622-6

DOI Google Scholar

Zhang W, O'Brien N, Forrest JI, Salters KA, Patterson TL, Montaner JSG, et al. Validating a shortened depression scale (10 item CES‐D) among HIV‐positive people in British Columbia, Canada. PLoS One. 2012;7(7):e40793. https://doi.org/10.1371/journal.pone.0040793

DOI Google Scholar

Tobias DK, Hu FB. Commentary: obesity and mortality in China: the shape of things to come. Int J Epidemiol. 2012;41(2):481–3. https://doi.org/10.1093/ije/dys031

DOI Google Scholar

Nunn AJ, Gregg I. New regression equations for predicting peak expiratory flow in adults. BMJ. 1989;298(6680):1068–70. https://doi.org/10.1136/bmj.298.6680.1068

DOI Google Scholar

Perez‐Padilla R, Vollmer WM, Vázquez‐García JC, et al. Can a normal peak expiratory flow exclude severe chronic obstructive pulmonary disease? Int J Tuberc Lung Dis. 2009;13(3):387393.

Google Scholar

Seidel D, Brayne C, Jagger C. Limitations in physical functioning among older people as a predictor of subsequent disability in instrumental activities of daily living. Age Ageing. 2011;40(4):463–9. https://doi.org/10.1093/ageing/afr054

DOI Google Scholar

Gale CR, Cooper C, Sayer AA. Prevalence of frailty and disability: findings from the English Longitudinal Study of Ageing. Age Ageing. 2015;44(1):162–5. https://doi.org/10.1093/ageing/afu148

DOI Google Scholar

Bloomberg M, Dugravot A, Landré B, et al. Sex differences in functional limitations and the role of socioeconomic factors: a multi‐cohort analysis. Lancet Healthy Longev. 2021;2(12): E780–90. https://doi.org/10.1016/S2666-7568(21)00249-X

DOI Google Scholar

National Bureau of Statistics. China 2014 Statistical Yearbook. Beijing: NBS; 2014.

OECD. PPPs and exchange rates. OECD National Accounts Statistics. Paris: Organisation for Economic Co‐operation and Development; 2015.

StataCorp. Stata Statistical Software: Release 14. College Station, TX: StataCorp LP; 2015.

Goldstein H, Browne W, Rasbash J. Partitioning variation in multilevel models. Understand Statist. 2002;1:223–31. https://doi.org/10.1207/S15328031US0104_02

DOI Google Scholar

Hox JJ. Multilevel analysis: techniques and applications. Mawah, NJ: Earlbaum; 2002.

DOI

Merlo J, Chaix B, Ohlsson H, et al. A brief conceptual tutorial of multilevel analysis in social epidemiology: using measures of clustering in multilevel logistic regression to investigate contextual phenomena. J Epidemiol Commun Health. 2006;60(4):290–7. https://doi.org/10.1136/jech.2004.029454

DOI Google Scholar

Merlo J, Chaix B, Yang M, Lynch J, Rastam L. A brief conceptual tutorial on multilevel analysis in social epidemiology: investigating contextual phenomena in different groups of people. J Epidemiol Commun Health. 2005;59(9):729–36. https://doi.org/10.1136/jech.2004.023473

DOI Google Scholar

Enzmann D, Kohler U. MERESC: Stata module to rescale the results of mixed nonlinear probability models. Statistical Software Components, Boston College Department of Economics; 2012.

Google Scholar

Wang T, Zeng R. Addressing inequalities in China's health service. Lancet. 2015;386(10002):1441. https://doi.org/10.1016/S0140-6736(15)00402-X

DOI Google Scholar

Anand S, Fan VY, Zhang J, Zhang L, Ke Y, Dong Z, et al. China's human resources for health: quantity, quality, and distribution. Lancet. 2008;372(9651):1774–81. https://doi.org/10.1016/S0140-6736(08)61363-X

DOI Google Scholar

Chan KW, Wang M. Remapping China's regional inequalities, 1990‐2006: a new assessment ofde factoandde JurePopulation data. Eurasian Geogr Econ. 2008;49(1):21–55. https://doi.org/10.2747/1539-7216.49.1.21

DOI Google Scholar

About this article

Publication history

Acknowledgements

Rights and permissions

Publication history

Received: 24 July 2022

Accepted: 28 December 2022

Published: 09 March 2023

Issue date: April 2023

Copyright

Acknowledgements

ACKNOWLEDGMENTS

The authors would like to thank Shaoru Chen, Vanke School of Public Health, Tsinghua University, for her assistance in preparing the manuscript for publication. The authors received no specific funding for this work. CHARLS was supported by the Behavioral and Social Research division of the National Institute on Aging (grant numbers 1‐R21‐AG031372‐01, 1‐R01‐AG037031‐01, and 3‐R01AG037031‐03S1); the Natural Science Foundation of China (grant numbers 70910107022, 71130002 and 71273237); the World Bank (contract numbers 7145915 and 7159234); the China Medical Board, and Peking University.

Rights and permissions

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.