Advertisement

Income distribution and health: can polarization explain health outcomes better than inequality?

Abstract

Utilizing data from the China Health and Nutrition Survey (CHNS) from 1991 to 2011, we aim to analyze the effects of income distribution on two risks for chronic diseases: body mass index (BMI) and blood pressure. Unlike the previous studies, we consider two different kinds of indicators of income distribution: inequality and polarization. Different from relative inequality indicators such as the Gini index, which measure income gaps only, the recently developed polarization indicator captures group clustering and social alienation, in addition to income gaps. Our empirical results demonstrate that both BMI and blood pressure are positively correlated with income polarization, while inequality is a weaker predictor of these health outcomes. Thus, polarization, rather than inequality, should be used when analyzing the relationship between health outcomes and income distribution. We also examine the polarization-to-health transmission mechanism using mediation and moderation analytic frameworks. The results suggest that social networks mediate the effect of polarization on BMI and neutralize the effect on blood pressure.

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

Access options

Buy single article

Instant unlimited access to the full article PDF.

US$ 39.95

Price includes VAT for USA

Subscribe to journal

Immediate online access to all issues from 2019. Subscription will auto renew annually.

US$ 99

This is the net price. Taxes to be calculated in checkout.

Fig. 1

Source:Authors’ construction

Fig. 2

Source: Authors’ calculation of the CHNS data collected in 1991, 1993, 1997, 2000, 2004, 2006, 2009, and 2011

Fig. 3

Source: Authors’ calculation of the CHNS data collected in 1991, 1993, 1997, 2000, 2004, 2006, 2009, and 2011

Fig. 4

Source: Authors’ estimation of the CHNS data collected in 1991, 1993, 1997, 2000, 2004, 2006, 2009, and 2011. The figure is based on the estimates of Table 6 in the Appendix. Ranges indicate 95% confidence intervals

Notes

  1. 1.

    Data source: National Bureau of Statistics of China (2011), http://data.stats.gov.cn/english/easyquery.htm?cn=E0103.

  2. 2.

    The sample size of each wave is different. For details, see Table 5 in the Appendix.

  3. 3.

    We reported the median value, since the income variable had quite large dispersion and is skewed.

References

  1. 1.

    Aiken, L., West, S., Reno, R.: Multiple regression: Testing and interpreting interactions. SAGE Publications, Thousand oaks (1991)

  2. 2.

    Baron, R., Kenny, D.: The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. J. Pers. Soc. Psychol. 51, 1173–1182 (1986)

  3. 3.

    Bollen, K.A., Pearl, J.: Eight myths about causality and structural equation models, pp. 301–328. Springer, Dordrecht (2013)

  4. 4.

    Breslow, R.A., Smothers, B.A.: Drinking patterns and body mass index in never smokers national health interview survey, 1997–2001. Am. J. Epidemiol. 161(4), 368–376 (2005)

  5. 5.

    Chen, Z., Meltzer, D.: Beefing up with the chans: evidence for the effects of relative income and income inequality on health from the China Health and Nutrition Survey. Soc. Sci. Med. 66(11), 2206–2217 (2008)

  6. 6.

    Chou, SY., Grossman, M., Saffer, H.: An economic analysis of adult obesity: Results from the behavioral risk factor surveillance system. National Bureau of Economic Research Working Paper Series No. 9247 (2002)

  7. 7.

    Chou, S.Y., Grossman, M., Saffer, H.: An economic analysis of adult obesity: Results from the behavioral risk factor surveillance system. J. Health Econ. 23(3), 565–587 (2004)

  8. 8.

    Cutler, DM., Glaeser, EL., Rosen, AB.: Is the U.S. population behaving healthier? National Bureau of Economic Research Working Paper Series No. 13013 (2007)

  9. 9.

    Cutler, D.M., Glaeser, E.L., Rosen, A.B.: Is the U.S. population behaving healthier? vol. 12, pp. 423–442. University of Chicago Press, Chicago (2009) (Book section)

  10. 10.

    Duclos, J.Y., Esteban, J., Ray, D.: Polarization: Concepts, measurement, estimation. Econometrica 72(6), 1737–1772 (2004)

  11. 11.

    Esteban, J., Schneider, G.: Polarization and conflict: Theoretical and empirical issues. J. Peace Res. 45(2), 131–141 (2008)

  12. 12.

    Ettner, S.L.: New evidence on the relationship between income and health. J. Health Econ. 15(1), 67–85 (1996)

  13. 13.

    Frijters, P., Haisken-DeNew, J.P., Shields, M.A.: The causal effect of income on health: Evidence from German reunification. J. Health Econ. 24(5), 997–1017 (2005)

  14. 14.

    Gao, C., Lv, X., Yin, Y., Song, Y., Zhang, P., Wang, R., Jiang, L., Wang, Y., Yu, Y., Li, B.: Perceptions and behaviours towards high body weight among adults in northeast China. Public Health Nutr. 20(9), 1557–1563 (2017)

  15. 15.

    Gravelle, H.: How much of the relation between population mortality and unequal distribution of income is a statistical artefact? BMJ 316(7128), 382 (1998)

  16. 16.

    Gravelle, H., Sutton, M.: Income, relative income, and self-reported health in Britain 1979–2000. Health Econ. 18(2), 125–145 (2009)

  17. 17.

    Gruber, J., Frakes, M.: Does falling smoking lead to rising obesity? J. Health Econ. 25(2), 183–197 (2006)

  18. 18.

    Hou, F., Myles, J.: Neighbourhood inequality, neighbourhood affluence and population health. Soc. Sci. Med. 60(7), 1557–1569 (2005)

  19. 19.

    Ichida, Y., Kondo, K., Hirai, H., Hanibuchi, T., Yoshikawa, G., Murata, C.: Social capital, income inequality and self-rated health in Chita peninsula, Japan: a multilevel analysis of older people in 25 communities. Soc. Sci. Med. 69(4), 489–499 (2009)

  20. 20.

    Institute for Health Metrics and Evaluation (2017) GBD compare data visualization. Seattle, WA: Institute for Health Metrics and Evaluation. https://vizhub.healthdata.org/gbd-compare/. Accessed 1 Mar 2018

  21. 21.

    Johnston, D.W., Propper, C., Shields, M.A.: Comparing subjective and objective measures of health: Evidence from hypertension for the income/health gradient. J. Health Econ. 28(3), 540–552 (2009)

  22. 22.

    Judd, C.M., Kenny, D.A.: Process analysis: Estimating mediation in treatment evaluations. Eval. Rev. 5(5), 602–619 (1981)

  23. 23.

    Kawachi, I., Kennedy, B.P., Lochner, K., Prothrow-Stith, D.: Social capital, income inequality, and mortality. Am. J. Public Health 87(9), 1491–1498 (1997)

  24. 24.

    Kawachi, I., Subramanian, S., Kim, D.: Social capital and health. Springer, New York (2008)

  25. 25.

    Kleibergen, F., Paap, R.: Generalized reduced rank tests using the singular value decomposition. J. Econom. 133(1), 97–126 (2006)

  26. 26.

    Lee, Y., Shin, D.: Measuring social tension from income class segregation. J. Bus. Econ. Stat. 34(3), 457–471 (2016)

  27. 27.

    Lim, S.S., Vos, T., Flaxman, A.D.: A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: A systematic analysis for the global burden of disease study 2010. Lancet 380(9859), 2224–2260 (2012)

  28. 28.

    Lynch, J., Smith, G.D., Harper, S., Hillemeier, M., Ross, N., Kaplan, G.A., Wolfson, M.: Is income inequality a determinant of population health? Part 1. A systematic review. Milbank Quart. 82(1), 5–99 (2004)

  29. 29.

    Macinko, J., Starfield, B.: The utility of social capital in research on health determinants. Milbank Quart. 79(3), 387–427 (2003)

  30. 30.

    Meer, J., Miller, D.L., Rosen, H.S.: Exploring the health–wealth nexus. J. Health Econ. 22(5), 713–730 (2003)

  31. 31.

    Miller, D.L., Paxson, C.: Relative income, race, and mortality. J. Health Econ. 25(5), 979–1003 (2006)

  32. 32.

    Montalvo, J.G., Reynal-Querol, M.: Ethnic polarization, potential conflict, and civil wars. Am. Econ. Rev. 95(3), 796–816 (2005)

  33. 33.

    Moore, M., Gould, P., Keary, B.S.: Global urbanization and impact on health. Int. J. Hyg. Environ. Health 206(4), 269–278 (2003)

  34. 34.

    Oishi, S., Kesebir, S., Diener, E.: Income inequality and happiness. Psychol. Sci. 22(9), 1095–1100 (2011)

  35. 35.

    Pérez, C.B., Ramos, X.: Polarization and health. Rev. Income Wealth 56(1), 171–185 (2010)

  36. 36.

    Van de Poel, E., O’Donnell, O., Van Doorslaer, E.: Urbanization and the spread of diseases of affluence in china. Econ. Human Biol. 7(2), 200–216 (2009)

  37. 37.

    Popkin, B.M., Du, S., Zhai, F., Zhang, B.: Cohort profile: The China Health and Nutrition Survey–monitoring and understanding socio-economic and health change in China, 1989–2011. Int. J. Epidemiol. 39(6), 1435–1440 (2010)

  38. 38.

    Popkin, B.M., Adair, L.S., Ng, S.W.: Global nutrition transition and the pandemic of obesity in developing countries. Nutr. Rev. 70(1), 3–21 (2012)

  39. 39.

    Preston, S.H.: The changing relation between mortality and level of economic development. Popul. Stud. 29(2), 231–248 (1975)

  40. 40.

    Qin, X., Pan, J.: The medical cost attributable to obesity and overweight in China: Estimation based on longitudinal surveys. Health Econ. 25, 1291–1311 (2015)

  41. 41.

    Rohner, D.: Reputation, group structure and social tensions. J. Dev. Econ. 96(2), 188–199 (2011)

  42. 42.

    Sever, P.: Is systolic blood pressure all that matters? Yes. BMJ 339 (2009)

  43. 43.

    Vincens, N., Emmelin, M., Stafström, M.: Social capital, income inequality and the social gradient in self-rated health in Latin America: A fixed effects analysis. Soc. Sci. Med. 196, 115–122 (2018)

  44. 44.

    Wang, C., Wan, G.: Income polarization in China: Trends and changes. China Econ. Rev. 36, 58–72 (2015)

  45. 45.

    Wilkinson, R.G.: Commentary: Income inequality summarises the health burden of individual relative deprivation. BMJ 314(7096), 1727 (1997)

  46. 46.

    Winter, J.E., MacInnis, R.J., Wattanapenpaiboon, N., Nowson, C.A.: BMI and all-cause mortality in older adults: A meta-analysis. Am. J. Clin. Nutr. 99(4), 875–890 (2014)

  47. 47.

    World Bank: World development indicators. The World Bank, Washington, DC (2016)

  48. 48.

    World Health Organization: Global status report on noncommunicable diseases 2010. World Health Organization, Geneva (2011)

  49. 49.

    World Health Organization: Global status report on noncommunicable diseases 2014. World Health Organization, Geneva (2015)

  50. 50.

    Yang, Y., Hu, XM., Chen, TJ., Bai, MJ.: Rural-urban differences of dietary patterns, overweight, and bone mineral status in Chinese students. Nutrients 8(9) (2016)

  51. 51.

    Zhang, X., Kanbur, R.: What difference do polarisation measures make? An application to China. J. Dev. Stud. 37(3), 85–98 (2001)

Download references

Acknowledgements

This research was supported by the National Natural Science Foundation of China (71833003). The authors would like to thank the two anonymous reviewers for their constructive suggestions and comments.

Author information

Correspondence to Dongfang Meng.

Appendix

Appendix

See Tables 5, 6 and Fig. 5

Table 5 Sample size in each wave of the survey.
Table 6 Polarization and health.
Fig. 5
figure5

Source: authors’ analyses of the CHNS data collected in 1991, 1993, 1997, 2000, 2004, 2006, 2009, and 2011

Scatter plots: polarization and outcomes. a BMI. b Blood pressure.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Yao, Y., Wan, G. & Meng, D. Income distribution and health: can polarization explain health outcomes better than inequality?. Eur J Health Econ 20, 543–557 (2019) doi:10.1007/s10198-018-1016-9

Download citation

Keywords

  • Income distribution
  • Polarization
  • Inequality
  • BMI
  • Blood pressure
  • China

JEL Classification

  • I14
  • I15
  • D31