Szwarcwald C L, Bastos F I, Barcellos C, Pina M F, Esteves M A
Department of Information on Health, Fundação Oswaldo Cruz Av Brasil 4365, 21045-900 Rio de Janeiro, RJ, Brazil.
J Epidemiol Community Health. 2000 Jul;54(7):530-6. doi: 10.1136/jech.54.7.530.
To establish the geographical relation of health conditions to socioeconomic status in the city of Rio de Janeiro, Brazil.
All reported deaths in the municipality of Rio de Janeiro, from 1987 to 1995, obtained from the Mortality Information System, were considered in the study. The 24 "administrative regions" that compose the city were used as the geographical units. A geographical information system (GIS) was used to link mortality data and population census data, and allowed the authors to establish the geographical pattern of the health indicators considered in this study: "infant mortality rate"; "standardised mortality rate"; "life expectancy" and "homicide rate". Information on location of low income communities (slums) was also provided by the GIS. A varimax rotation principal component analysis combined information on socioeconomic conditions and provided a two dimension basis to assess contextual variation.
The 24 administrative regions were aggregated into three different clusters, identified as relevant to reflect the socioeconomic variation. Almost all health indicator thematic maps showed the same socioeconomic stratification pattern. The worst health situation was found in the cluster composed of the harbour area and northern vicinity, precisely in the sector where the highest concentration of slum residents are present. This sector of the city exhibited an extremely high homicide rate and a seven year lower life expectancy than the remainder of the city. The sector that concentrates affluence, composed of the geographical units located along the coast, showed the best health situation. Intermediate health conditions were found in the west area, which also has poor living standards but low concentration of slums.
The findings suggest that social and organisation characteristics of low income communities may have a relevant role in understanding health variations. Local health and other social programmes specifically targeting these communities are recommended.
确定巴西里约热内卢市健康状况与社会经济地位之间的地理关系。
本研究纳入了1987年至1995年里约热内卢市从死亡信息系统获取的所有报告死亡病例。构成该市的24个“行政区”被用作地理单位。使用地理信息系统(GIS)将死亡率数据与人口普查数据相联系,使作者能够确定本研究中所考虑的健康指标的地理模式:“婴儿死亡率”;“标准化死亡率”;“预期寿命”和“凶杀率”。GIS还提供了关于低收入社区(贫民窟)位置的信息。通过最大方差旋转主成分分析整合社会经济状况信息,并提供一个二维基础来评估背景差异。
24个行政区被聚合为三个不同的聚类,确定这些聚类与反映社会经济差异相关。几乎所有健康指标专题地图都显示出相同的社会经济分层模式。在由港口区域及其北部附近地区组成的聚类中发现了最差的健康状况,确切地说是在贫民窟居民最集中的区域。该市的这个区域凶杀率极高,预期寿命比城市其他地区低七年。由沿海地理单位组成的集中富裕人群的区域健康状况最佳。在西部地区发现了中等健康状况,该地区生活水平也较低,但贫民窟集中度较低。
研究结果表明,低收入社区的社会和组织特征可能在理解健康差异方面具有重要作用。建议针对这些社区制定专门的地方健康和其他社会项目。