OBJECTIVE: Many studies show the average health status in deprived areas to be poorer and the use of health care to be higher, but there is hardly any information on the impact of the geographical classification on the size of these differences. This study examines the impact of the geographical classification on the clustering of poor health per area and on the size of the differences in health by area deprivation. DESIGN: Data on self reported health regarding 5121 people were analysed using three classifications: neighbourhoods, postcode sectors and boroughs. Multilevel logistic models were used to determine the clustering of poor health per area and the size of the differences in health by area deprivation, without and subsequently with adjustment for individual socioeconomic status. SETTING: General population aged 16 years and over of Amsterdam, The Netherlands. MAIN OUTCOME MEASURES: Self rated health, mental symptoms (General Health Questionnaire, 12-item version), physical symptoms and long term functional limitations. MAIN RESULTS: The clustering of poor health is largest in neighbourhoods and smallest in postcode sectors. Health differences by area deprivation differ only slightly for the three geographical classifications, both with and without adjustment for individual socioeconomic status. CONCLUSIONS: In this study, the choice of the geographical classification affects the degree of clustering of poor health by area but it has hardly any impact on the size of health differences by area deprivation.
OBJECTIVE: Many studies show the average health status in deprived areas to be poorer and the use of health care to be higher, but there is hardly any information on the impact of the geographical classification on the size of these differences. This study examines the impact of the geographical classification on the clustering of poor health per area and on the size of the differences in health by area deprivation. DESIGN: Data on self reported health regarding 5121 people were analysed using three classifications: neighbourhoods, postcode sectors and boroughs. Multilevel logistic models were used to determine the clustering of poor health per area and the size of the differences in health by area deprivation, without and subsequently with adjustment for individual socioeconomic status. SETTING: General population aged 16 years and over of Amsterdam, The Netherlands. MAIN OUTCOME MEASURES: Self rated health, mental symptoms (General Health Questionnaire, 12-item version), physical symptoms and long term functional limitations. MAIN RESULTS: The clustering of poor health is largest in neighbourhoods and smallest in postcode sectors. Health differences by area deprivation differ only slightly for the three geographical classifications, both with and without adjustment for individual socioeconomic status. CONCLUSIONS: In this study, the choice of the geographical classification affects the degree of clustering of poor health by area but it has hardly any impact on the size of health differences by area deprivation.
Authors: Dawn Kleindorfer; Christopher Lindsell; Kathleen A Alwell; Charles J Moomaw; Daniel Woo; Matthew L Flaherty; Pooja Khatri; Opeolu Adeoye; Simona Ferioli; Brett M Kissela Journal: Stroke Date: 2012-07-05 Impact factor: 7.914
Authors: Gina S Lovasi; Anne Vernez Moudon; Nicholas L Smith; Thomas Lumley; Eric B Larson; Dong W Sohn; David S Siscovick; Bruce M Psaty Journal: Health Place Date: 2007-09-21 Impact factor: 4.078
Authors: Susan E Stockdale; Kenneth B Wells; Lingqi Tang; Thomas R Belin; Lily Zhang; Cathy D Sherbourne Journal: Soc Sci Med Date: 2007-07-05 Impact factor: 4.634
Authors: Martina Behanova; Iveta Nagyova; Zuzana Katreniakova; Erik J C van Ameijden; Jitse P van Dijk; Sijmen A Reijneveld Journal: Int J Public Health Date: 2013-12-21 Impact factor: 3.380