Skip to main content

Advertisement

SpringerLink
Log in

Area Social Deprivation and Public Health: Analyzing the Spatial Non-stationary Associations Using Geographically Weighed Regression

  • Published:
Social Indicators Research Aims and scope Submit manuscript

Abstract

The prevalence of non-communicable chronic diseases (NCDs) worldwide poses an alarming threat to public health. Recent literature has embraced the opinion that incorporating the social factors should advance the understanding of NCDs prevalence. In this context, examining the NCDs prevalence in association with area social deprivation should provide critical implications for coping with public health risks. However, few empirical studies have examined this specific issue, especially in the developing countries. Using the principal component analysis, an area social deprivation index (ASDI) is established for the Shenzhen city (China) by integrating ten indicators from four dimensions: education, housing, socially disadvantaged population, and economically disadvantaged population. The geographically weighted regression (GWR) is employed to analyze the associations between ASDI and the incidence rate of three prevalent NCDs at district scale. Spatial non-stationary relationships are identified for the three diseases. More specifically, prevalence of the three diseases is all positively correlated with the ASDI. Strength of the associations presents the geography that it generally decreases from the central city to the suburb. These findings suggest that greater possibility of NCDs prevalence would be expected in districts with higher social deprivation. Besides, the impact of social deprivation on NCDs prevalence is much stronger in the central city. The spatial stationarity can facilitate the formulation of location-specific preventive measurements. This paper is believed to provide an innovative insight for social indicators research.

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.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Atkinson, J., Salmond, C., & Crampton, P. (2014). NZDep2013 Index of Deprivation. Wellington: The Department of Public Health, University of Otago.

    Google Scholar 

  • Aubé-Maurice, J., Rochette, L., & Blais, C. (2012). Divergent associations between incident hypertension and deprivation based on different sources of case identification. Chronic Diseases & Injuries in Canada, 32(3), 121–130.

    Google Scholar 

  • Baumann, M., Spitz, E., Guillemin, F., Ravaud, J. F., Choquet, M., Falissard, B., et al. (2007). Associations of social and material deprivation with tobacco, alcohol, and psychotropic drug use, and gender: A population-based study. International Journal of Health Geographics, 6(25), 1–12.

    Google Scholar 

  • Bereitschaft, B., & Cammack, R. (2015). Neighborhood diversity and the creative class in Chicago. Applied Geography, 63, 166–183.

    Article  Google Scholar 

  • Berry, A., Bellisario, V., Capoccia, S., Tirassa, P., Calza, A., Alleva, E., et al. (2012). Social deprivation stress is a triggering factor for the emergence of anxiety- and depression-like behaviours and leads to reduced brain BDNF levels in C57BL/6J mice. Psychoneuroendocrinology, 37(6), 762–772.

    Article  Google Scholar 

  • Brennan-Olsen, S. L., Williams, L. J., Holloway, K. L., Hosking, S. M., Stuart, A. L., Dobbins, A. G., & Pasco, J. A. (2015). Small area-level socioeconomic status and all-cause mortality within 10 years in a population-based cohort of women: Data from the Geelong Osteoporosis Study. Preventive Medicine Reports, 2, 505–511.

    Article  Google Scholar 

  • Burrows, S., Auger, N., Gamache, P., St-Laurent, D., & Hamel, D. (2011). Influence of social and material individual and area deprivation on suicide mortality among 2.7 million Canadians: A prospective study. BMC Public Health, 11(16), 2040–2055.

    Google Scholar 

  • Chaix, B., Rosvall, M., & Merlo, J. (2007). Assessment of the magnitude of geographical variations and socioeconomic contextual effects on ischaemic heart disease mortality: A multilevel survival analysis of a large Swedish cohort. Journal of Epidemiology and Community Health, 61(4), 349–355.

    Article  Google Scholar 

  • Chalkias, A., Nitsotolis, T., Papalexandrou, A., Mikros, S., Iacovidou, N., & Xanthos, T. (2013). Sagittal abdominal diameter may effectively predict future complications and increased mortality in intensive care unit patients with severe sepsis. Journal of Critical Care, 28(6), 964–969.

    Article  Google Scholar 

  • Chen, D. R., Truong, K. D., & Tsai, M. J. (2013). Prevalence of poor sleep quality and its relationship with body mass index among teenagers: Evidence from Taiwan. Journal of School Health, 83(8), 582–588.

    Article  Google Scholar 

  • Chen, V. Y., Wu, P., Yang, T., & Su, H. (2010). Examining non-stationary effects of social determinants on cardiovascular mortality after cold surges in Taiwan. Science of the Total Environment, 408(9), 2042–2049.

    Article  Google Scholar 

  • Coggon, D., Rose, G., & Barker, D. J. P. (1997). Quantifying diseases in populations. Epidemiology for the uninitiated (4th ed.). BMJ. ISBN: 0-7279-1102-3.

  • Cramm, J. M., & Nieboer, A. P. (2011). The influence of social capital and socio-economic conditions on self-rated health among residents of an economically and health-deprived South African township. International Journal for Equity in Health, 10(1), 51–57.

    Article  Google Scholar 

  • Cumming, S., & Vernier, P. (2002). Statistical models of landscape pattern metrics, with applications to regional scale dynamic forest simulation. Landscape Ecology, 17(5), 433–444.

    Article  Google Scholar 

  • D’Ambrosio, C., & Rodrigues, R. I. (2008). Deprivation in the São Paulo districts: Evidence from 2000. World Development, 36, 1094–1112.

    Article  Google Scholar 

  • Daniela, D., Maria, K., Georg, H., Teo, K. K., Annika, R., Janice, P., et al. (2015). Modifiable lifestyle and social factors affect chronic kidney disease in high-risk individuals with type 2 diabetes mellitus. Kidney International, 87(4), 784–791.

    Article  Google Scholar 

  • Fano, V., Pezzotti, P., Gnavi, R., Bontempi, K., Miceli, M., Pagnozzi, E., et al. (2013). The role of socio-economic factors on prevalence and health outcomes of persons with diabetes in Rome, Italy. European Journal of Public Health, 23(6), 991–997.

    Article  Google Scholar 

  • Feng, X., Girosi, F., & Mcrae, I. S. (2014). People with multiple unhealthy lifestyles are less likely to consult primary healthcare. BMC Family Practice, 15(1), 1–7.

    Article  Google Scholar 

  • Few, R., Lake, I., Hunter, P. R., Tran, P. G., & Thien, V. T. (2009). Seasonal hazards and health risks in lower-income countries: Field testing a multi-disciplinary approach. Environmental Health A Global Access Science Source, 8, 239–243.

    Google Scholar 

  • Foody, G. M., Boyd, D. S., & Cutler, M. E. J. (2003). Predictive relations of tropical forest biomass from Landsat TM data and their transferability between regions. Remote Sensing of Environment, 85(4), 463–474.

    Article  Google Scholar 

  • Fotheringham, A. S., & Brunsdon, C. (1999). Local forms of spatial analysis. Geographical Analysis, 31(4), 340–358.

    Article  Google Scholar 

  • Fotheringham, A. S., Brunsdon, C., & Charlton, M. E. (2002). Geographically weighted regression: The analysis of spatially varying relationships. New York: Wiley.

    Google Scholar 

  • Gong, P., Liang, S., Carlton, E. J., Jiang, Q., Wu, J., Wang, L., et al. (2012). Urbanisation and health in China. Lancet, 379, 843–852.

    Article  Google Scholar 

  • Goovaerts, P., Xiao, H., Adunlin, G., Ali, A., Tan, F., Gwede, C. K., et al. (2015). Geographically-weighted regression analysis of percentage of late-stage prostate cancer diagnosis in Florida. Applied Geography, 62, 191–200.

    Article  Google Scholar 

  • Griffith, J. A., Mantinko, E. A., & Price, K. P. (2000). Landscape structure analysis of Kansas at three scales. Landscape and Urban Planning, 52, 45–61.

    Article  Google Scholar 

  • Grintsova, O., Maier, W., & Mielck, A. (2014). Inequalities in health care among patients with type 2 diabetes by individual socio-economic status (SES) and regional deprivation: A systematic literature review. International Journal for Equity in Health, 13(1), 43–56.

    Article  Google Scholar 

  • Günther, I., & Schipper, Y. (2013). Pumps, germs and storage: The impact of improved water containers on water quality and health. Health Economics, 22(7), 757–774.

    Article  Google Scholar 

  • Guo, L., Ma, Z., & Zhang, L. (2008). Comparison of bandwidth selection in application of geographically weighted regression: A case study. Canadian Journal of Forest Research, 38, 2526–2534.

    Article  Google Scholar 

  • Havard, S., Deguen, S. J., Louis, K., Laurent, O., & Bard, D. (2008). A small-area index of socioeconomic deprivation to capture health inequalities in France. Social Science and Medicine, 67(12), 2007–2016.

    Article  Google Scholar 

  • Henke, J. M., & Petropoulos, G. P. (2013). A GIS-based exploration of the relationships between human health, social deprivation and ecosystem services: The case of wales. UK. Applied Geography, 45(5), 77–88.

    Article  Google Scholar 

  • Jacob, V., Vellappally, S., Smejkalova, J., Rajkumar, K., Cermakova, E., Fiala, Z., et al. (2008). Tabacco use in smokeless and smoking forms and its effect on periodontal health in India. Central European Journal of Medicine, 3(1), 97–104.

    Google Scholar 

  • Jaimes, N. B. P., Sendra, J. B., Delgado, M. G., & Plata, R. F. (2010). Exploring the driving forces behind deforestation in the state of Mexico (Mexico) using geographically weighted regression. Applied Geography, 30, 576–591.

    Article  Google Scholar 

  • Julie, K., Coupland, V. H., Kocher, H. M., William, A., Grocock, M. J., & Jack, R. H. (2014). Time and deprivation trends in incidence of primary liver cancer subtypes in England. Journal of Evaluation in Clinical Practice, 20(4), 498–504.

    Article  Google Scholar 

  • Laraia, B. A., Karter, A. J., Warton, E. M., Schillinger, D., Moffet, H. H., & Adler, N. (2012). Place matters: Neighborhood deprivation and cardiometabolic risk factors in the Diabetes Study of Northern California (DISTANCE). Social Science and Medicine, 74, 1082–1090.

    Article  Google Scholar 

  • LeSage, J. P. (2001). A family of geographically weighted regression models. Advances in spatial Econometrics (pp. 240–264). Berlin: Springer.

    Google Scholar 

  • Lian, M., Schootman, M., Doubeni, C. A., et al. (2011). Geographic variation in colorectal cancer survival and the role of small-area socioeconomic deprivation: A multilevel survival analysis of the NIH-AARP Diet and Health Study Cohort. American Journal of Epidemiology, 174, 828–838.

    Article  Google Scholar 

  • Mandal, R., St-Hilaire, S., Kie, J. G., & Derryberry, D. W. (2009). Spatial trends of breast and prostate cancers in the united states between 2000 and 2005. International Journal of Health Geographics, 8(22), 2817–2832.

    Google Scholar 

  • Mullins, C. D., Blatt, L., Gbarayor, C. M., Yang, H. W., & Baquet, C. (2005). Health disparities: A barrier to high-quality care. American Journal of Health-System Pharmacy, 62(18), 1873–1882.

    Article  Google Scholar 

  • Noble, M., Barnes, H., Wright, G., & Roberts, B. (2010). Small area indices of multiple deprivation in south Africa. Social Indicators Research, 95(2), 281–297.

    Article  Google Scholar 

  • Ogneva-Himmelberger, Y., Pearsall, H., & Rakshit, R. (2009). Concrete evidence & geographically weighted regression: A regional analysis of wealth and the land cover in Massachusetts. Applied Geography, 29, 478–487.

    Article  Google Scholar 

  • Pearce, J., Witten, K., Hiscock, R., & Blakely, T. (2007). Are socially disadvantaged neighborhoods deprived of health-related community resources? International Journal of Epidemiology, 36(2), 348–355.

    Article  Google Scholar 

  • Powell-Wiley, T. M., Ayers, C., Agyemang, P., Leonard, T., Berrigan, D., Ballard-Barbash, R., et al. (2014). Neighborhood-level socioeconomic deprivation predicts weight gain in a multi-ethnic population: Longitudinal data from the Dallas Heart Study. Preventive Medicine, 66, 22–27.

    Article  Google Scholar 

  • Richter, N. L., Gorey, K. M., Haji-Jama, S., & Luginaah, I. N. (2015). Care and survival of Mexican American women with node negative breast cancer: Historical cohort evidence of health insurance and barrio advantages. Journal of Immigrant and Minority Health, 17(3), 1–8.

    Article  Google Scholar 

  • Robert, P., Denis, H., Philippe, G., Philibert, M. D., Guy, R., & André, S. (2012). An area-based material and social deprivation index for public health in Québec and Canada. Canadian Journal of Public Health, 103, eS17–eS22.

    Google Scholar 

  • Ross, Z., Ito, K., Johnson, S., Yee, M., Pezeshki, G., Clougherty, J. E., et al. (2013). Spatial and temporal estimation of air pollutants in New York City: Exposure assignment for use in a birth outcomes study. Environmental Health, 12(25), 1–13.

    Google Scholar 

  • Santana, P., Costa, C., Marí-Dell’Olmo, M., Gotsens, M., & Borrell, C. (2015). Mortality, material deprivation and urbanization: Exploring the social patterns of a metropolitan area. International Journal for Equity in Health, 14(1), 1–13.

    Article  Google Scholar 

  • Shenzhen Health Statistical Yearbook, (2013). Health and Family Planning Commission of Shenzhen Municipality, Shenzhen.

  • Shenzhen Statistical Yearbook, (2014). China Statistic Press, Beijing.

  • Su, S., Li, D., Hu, Y., Xiao, R., & Zhang, Y. (2014). Spatially non-stationary response of ecosystem service value changes to urbanization in shanghai, China. Ecological Indicators, 45(5), 332–339.

    Article  Google Scholar 

  • Su, S., Xiao, R., & Zhang, Y. (2012). Multi-scale analysis of spatially varying relationships between agricultural landscape patterns and urbanization using geographically weighted regression. Applied Geography, 32(2), 360–375.

    Article  Google Scholar 

  • Taylor-Robinson, D. C., Smyth, R., Diggle, P. J., & Whitehead, M. (2013). A longitudinal study of the impact of social deprivation and disease severity on employment status in the UK cystic fibrosis population. PLoS one, 8(8), e73322.

    Article  Google Scholar 

  • UNDP. (2013). Addressing the social determinants of non-communicable diseases. New York: UNDP.

    Google Scholar 

  • Verhaeghe, P. P., & Tampubolon, G. (2012). Individual social capital, neighbourhood deprivation, and self-rated health in England. Social Science and Medicine, 75(2), 349–357.

    Article  Google Scholar 

  • Walker, A. E., & Becker, N. G. (2005). Health inequalities across socio-economic groups: Comparing geographic-area-based and individual-based indicators. Public Health, 119(12), 1097–1104.

    Article  Google Scholar 

  • Weng, M., Pi, J., Tan, B., & Su, S. (2016). Area deprivation and liver cancer prevalence in Shenzhen, China: A spatial approach based on social indicators. Social Indicators Research. doi:10.1007/s11205-016-1358-6.

    Google Scholar 

  • Wheeler, D. C., & Calder, C. A. (2007). An assessment of coefficient accuracy in linear regression models with spatially varying coefficients. Journal of Geographical Systems, 9(2), 145–166.

    Article  Google Scholar 

  • Wheeler, D., & Páez, A. (2010). Geographically weighted regression. In M. M. Fischer & A. Getis (Eds.), Handbook of applied spatial analysis: Software tools, methods and applications (pp. 461–4866). Heidelberg: Springer.

    Chapter  Google Scholar 

  • WHO. (2006). Commission on the social determinants of health. In: Organisation GWH (Ed.), Fifth meeting of the commission on the social determinants of health, June 26–30, 2006, Nairobi Kenya.

  • WHO. (2010). Global status report on non-communicable diseases. Geneva: WHO.

    Google Scholar 

  • Winkleby, M., Sundquist, K., & Cubbin, C. (2007). Inequities in CHD incidence and case fatality by neighborhood deprivation. American Journal of Preventive Medicine, 32(2), 97–106.

    Article  Google Scholar 

  • World Bank. (2011). The growing danger of non-communicable diseases: Acting now to reverse course. Washington, DC: World Bank.

    Google Scholar 

  • Wu, D. S., Feng, X., & Wen, Q. (2011). The research of evaluation for growth suitability of carya cathayensis sarg. Based on PCA and AHP. Procedia Engineering, 15, 1879–1883.

    Article  Google Scholar 

  • Zhang, X., Cook, P. A., Lisboa, P. J., Jarman, I. H., & Bellis, M. A. (2013). The effects of deprivation and relative deprivation on self-reported morbidity in England: An area-level ecological study. International Journal of Health Geographics, 12(2), 1–11.

    Google Scholar 

  • Zhang, D., Mou, J., Cheng, J., & Griffiths, S. M. (2011). Public health services in Shenzhen: A case study. Public Health, 125(1), 15–19.

    Article  Google Scholar 

Download references

Acknowledgments

This paper is supported by the Fundamental Research Funds for the Central Universities (No. 2042014kf0282) and the Research Training Program of Geographical Science Base of Wuhan University (No. J0105).

Author information

Authors and Affiliations

  1. School of Resource and Environmental Sciences, Wuhan University, Wuhan, China

    Shiliang Su, Yue Gong, Bingqing Tan, Jianhua Pi, Min Weng & Zhongliang Cai

  2. Key Laboratory of Geographical Information Systems, Ministry of Education, Wuhan University, Wuhan, China

    Shiliang Su, Min Weng & Zhongliang Cai

  3. Collaborative Innovation Center of Geospatial Technology, Wuhan University, No.129 Luoyu Rd, Wuhan, Hubei Province, China

    Shiliang Su

  4. Key Laboratory of Digital Mapping and Land Information Application Engineering, National Administration of Surveying, Mapping and Geoinformation, Wuhan University, Wuhan, China

    Zhongliang Cai

Authors
  1. Shiliang Su
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yue Gong
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bingqing Tan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jianhua Pi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Min Weng
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Zhongliang Cai
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shiliang Su.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Su, S., Gong, Y., Tan, B. et al. Area Social Deprivation and Public Health: Analyzing the Spatial Non-stationary Associations Using Geographically Weighed Regression. Soc Indic Res 133, 819–832 (2017). https://doi.org/10.1007/s11205-016-1390-6

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11205-016-1390-6

Keywords

Search

Navigation