Literature DB >> 17187909

Exceptions to the rule: healthy deprived areas and unhealthy wealthy areas.

Carolien van Hooijdonk1, Mariël Droomers, Jeanne A M van Loon, Fons van der Lucht, Anton E Kunst.   

Abstract

In general, inhabitants of low socio-economic areas are unhealthier than inhabitants of high socio-economic areas, but some areas are an exception to this rule. These exceptions imply that other factors besides the socio-economic level of an area contribute to the health of the inhabitants of an area, e.g. environmental factors. In our study we concentrate on areas within the Netherlands that are healthier or unhealthier than could be expected based on their socio-economic level. This study first identifies these areas and secondly determines which area characteristics distinguish these areas from those areas where the level of health is in agreement with their socio-economic level. We used nation-wide data on neighbourhood differences in population composition (gender, age, marital status and ethnicity), urbanisation and two health indicators: mortality and hospitalisation rates. In the Netherlands, many areas are healthier or unhealthier than could be expected based on their income level alone. Areas with higher mortality rates than expected are mainly urban areas with high percentages of elderly people and persons living alone. Similar but opposite associations are observed for areas with lower mortality rates than expected, which are further characterised by a low percentage of non-western immigrants. Areas with lower hospitalisation rates than expected are mainly rural areas with few non-western immigrants. From these results, we conclude that urbanisation and residential segregation based on age, ethnicity and marital status might be important contributors to geographical health inequalities.

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Year:  2006        PMID: 17187909     DOI: 10.1016/j.socscimed.2006.10.041

Source DB:  PubMed          Journal:  Soc Sci Med        ISSN: 0277-9536            Impact factor:   4.634


  6 in total

1.  Is demography destiny? Application of machine learning techniques to accurately predict population health outcomes from a minimal demographic dataset.

Authors:  Wei Luo; Thin Nguyen; Melanie Nichols; Truyen Tran; Santu Rana; Sunil Gupta; Dinh Phung; Svetha Venkatesh; Steve Allender
Journal:  PLoS One       Date:  2015-05-04       Impact factor: 3.240

2.  Identification of Resilient and At-Risk Neighborhoods for Cardiovascular Disease Among Black Residents: the Morehouse-Emory Cardiovascular (MECA) Center for Health Equity Study.

Authors:  Jeong Hwan Kim; Tené T Lewis; Matthew L Topel; Mohamed Mubasher; Chaohua Li; Viola Vaccarino; Mahasin S Mujahid; Mario Sims; Arshed A Quyyumi; Herman A Taylor; Peter T Baltrus
Journal:  Prev Chronic Dis       Date:  2019-05-09       Impact factor: 2.830

3.  Ethnic differences in the effect of environmental stressors on blood pressure and hypertension in the Netherlands.

Authors:  Charles Agyemang; Carolien van Hooijdonk; Wanda Wendel-Vos; Joanne K Ujcic-Voortman; Ellen Lindeman; Karien Stronks; Mariel Droomers
Journal:  BMC Public Health       Date:  2007-06-23       Impact factor: 3.295

4.  Features of home and neighbourhood and the liveability of older South Africans.

Authors:  Suzan van der Pas; Serela Ramklass; Brian O'Leary; Sharon Anderson; Norah Keating; Bilkish Cassim
Journal:  Eur J Ageing       Date:  2015

5.  Community Resilience throughout the Lifespan--The Potential Contribution of Healthy Elders.

Authors:  Odeya Cohen; Diklah Geva; Mooli Lahad; Arkady Bolotin; Dima Leykin; Avishay Goldberg; Limor Aharonson-Daniel
Journal:  PLoS One       Date:  2016-02-04       Impact factor: 3.240

6.  Immigrant and ethnic neighbourhood concentration and reduced child developmental vulnerability: A Canadian cohort study.

Authors:  D N McRae; N Muhajarine; M Janus; E Duku; M Brownell; B Forer; M Guhn
Journal:  Int J Popul Data Sci       Date:  2020-02-26
  6 in total

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