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本文引用的文献

1
Neighbourhood influences on health.邻里环境对健康的影响。
J Epidemiol Community Health. 2007 Jan;61(1):3-4. doi: 10.1136/jech.2005.045203.
2
HIV-1 infection prevalence and incidence trends in areas of contrasting levels of infection in the Kagera region, Tanzania, 1987-2000.1987 - 2000年坦桑尼亚卡盖拉地区不同感染水平区域的HIV - 1感染流行率和发病率趋势
J Acquir Immune Defic Syndr. 2005 Dec 15;40(5):585-91. doi: 10.1097/01.qai.0000168183.22147.c4.
3
A typology of groups at risk of HIV/STI in a gold mining town in north-western Tanzania.坦桑尼亚西北部一个金矿城镇中面临艾滋病毒/性传播感染风险的人群类型学。
Soc Sci Med. 2005 Apr;60(8):1739-49. doi: 10.1016/j.socscimed.2004.08.027.
4
Communities, opportunities, and adolescents' sexual behavior in KwaZulu-Natal, South Africa.南非夸祖鲁-纳塔尔省的社区、机遇与青少年性行为
Stud Fam Plann. 2004 Dec;35(4):261-74. doi: 10.1111/j.0039-3665.2004.00030.x.
5
Commentary: Reconciling the three accounts of social capital.评论:调和社会资本的三种解释。
Int J Epidemiol. 2004 Aug;33(4):682-90; discussion 700-4. doi: 10.1093/ije/dyh177. Epub 2004 Jul 28.
6
The relevance of multilevel statistical methods for identifying causal neighborhood effects.多级统计方法在识别因果邻里效应方面的相关性。
Soc Sci Med. 2004 May;58(10):1961-7. doi: 10.1016/S0277-9536(03)00415-5.
7
The neighborhood context of well-being.幸福的邻里环境。
Perspect Biol Med. 2003 Summer;46(3 Suppl):S53-64.
8
Variations of HIV and STI prevalences within communities neighbouring new goldmines in Tanzania: importance for intervention design.坦桑尼亚新金矿周边社区内艾滋病毒和性传播感染患病率的差异:对干预设计的重要性。
Sex Transm Infect. 2003 Aug;79(4):307-12. doi: 10.1136/sti.79.4.307.
9
Invited commentary: Advancing theory and methods for multilevel models of residential neighborhoods and health.特邀评论:推进居住社区与健康多层次模型的理论与方法
Am J Epidemiol. 2003 Jan 1;157(1):9-13. doi: 10.1093/aje/kwf171.
10
Community effects on the risk of HIV infection in rural Tanzania.坦桑尼亚农村地区社区对艾滋病毒感染风险的影响。
Sex Transm Infect. 2002 Aug;78(4):261-6. doi: 10.1136/sti.78.4.261.

地点很重要:坦桑尼亚艾滋病毒分布的多层次调查。

Place matters: multilevel investigation of HIV distribution in Tanzania.

作者信息

Msisha Wezi M, Kapiga Saidi H, Earls Felton J, Subramanian S V

机构信息

Europe and Central Asia Human Development Sector, The World Bank, Washington, DC, USA.

出版信息

AIDS. 2008 Mar 30;22(6):741-8. doi: 10.1097/QAD.0b013e3282f3947f.

DOI:10.1097/QAD.0b013e3282f3947f
PMID:18356604
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2789284/
Abstract

OBJECTIVE

To examine the extent to which the regional and neighborhood distribution of HIV in Tanzania is caused by the differential distribution of individual correlates and risk factors.

METHODS

Nationally representative, cross-sectional data on 12,522 women and men aged 15-49 years from the 2003-2004 Tanzanian AIDS Indicator Survey. Three-level multilevel binary logistic regression models were specified to estimate the relative contribution of regions and neighborhoods to the variation in HIV seroprevalence.

RESULTS

Spatial distribution of individual correlates (and risk factors) of HIV do not explain the neighborhood and regional variation in HIV seroprevalence. Neighborhoods and regions accounted for approximately 14 and 6% of the total variation in HIV. HIV prevalence ranged from 1.8% (Kigoma) to 6.7% (Iringa) even after adjusting for the compositional make-up of these regions. An inverse association was observed between log odds of being HIV positive and neighborhood poverty [odds ratio (OR) 0.24, 95% confidence interval (CI) 0.09-0.61] and regional poverty (OR 0.97, 95% CI 0.95-0.99).

CONCLUSION

Our study provides evidence for independent contextual variations in HIV, above and beyond that which can be ascribed to geographical variations in individual-level correlates and risk factors. We emphasize the need to adopt both a group-based and a place-based approach, as opposed to the dominant high-risk group approach, for understanding the epidemiology of HIV as well as for developing HIV intervention activities.

摘要

目的

研究坦桑尼亚艾滋病病毒(HIV)的地区和邻里分布在多大程度上是由个体相关因素和风险因素的差异分布所导致的。

方法

采用2003 - 2004年坦桑尼亚艾滋病指标调查中具有全国代表性的12522名15 - 49岁男女的横断面数据。使用三级多水平二元逻辑回归模型来估计地区和邻里对HIV血清阳性率变异的相对贡献。

结果

HIV个体相关因素(及风险因素)的空间分布并不能解释邻里和地区间HIV血清阳性率的差异。邻里和地区分别占HIV总变异的约14%和6%。即使对这些地区的构成进行调整后,HIV患病率仍在1.8%(基戈马)至6.7%(伊林加)之间。在HIV阳性的对数比值与邻里贫困[比值比(OR)0.24,95%置信区间(CI)0.09 - 0.61]以及地区贫困(OR 0.97,95% CI 0.95 - 0.99)之间观察到负相关。

结论

我们的研究为HIV存在独立的背景变异提供了证据,这种变异超出了个体层面相关因素和风险因素的地理变异所能解释的范围。我们强调,与占主导地位的高危人群方法不同,需要采用基于群体和基于地点的方法来理解HIV的流行病学以及开展HIV干预活动。