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日本全因死亡率的地理不平等:构成性还是情境性?

Geographic inequalities in all-cause mortality in Japan: compositional or contextual?

机构信息

Department of Epidemiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan.

出版信息

PLoS One. 2012;7(6):e39876. doi: 10.1371/journal.pone.0039876. Epub 2012 Jun 27.

DOI:10.1371/journal.pone.0039876
PMID:22761918
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3384616/
Abstract

BACKGROUND

A recent study from Japan suggested that geographic inequalities in all-cause premature adult mortality have increased since 1995 in both sexes even after adjusting for individual age and occupation in 47 prefectures. Such variations can arise from compositional effects as well as contextual effects. In this study, we sought to further examine the emerging geographic inequalities in all-cause mortality, by exploring the relative contribution of composition and context in each prefecture.

METHODS

We used the 2005 vital statistics and census data among those aged 25 or older. The total number of decedents was 524,785 men and 455,863 women. We estimated gender-specific two-level logistic regression to model mortality risk as a function of age, occupation, and residence in 47 prefectures. Prefecture-level variance was used as an estimate of geographic inequalities in mortality, and prefectures were ranked by odds ratios (ORs), with the reference being the grand mean of all prefectures (value = 1).

RESULTS

Overall, the degree of geographic inequalities was more pronounced when we did not account for the composition (i.e., age and occupation) in each prefecture. Even after adjusting for the composition, however, substantial differences remained in mortality risk across prefectures with ORs ranging from 0.870 (Okinawa) to 1.190 (Aomori) for men and from 0.864 (Shimane) to 1.132 (Aichi) for women. In some prefectures (e.g., Aomori), adjustment for composition showed little change in ORs, while we observed substantial attenuation in ORs in other prefectures (e.g., Akita). We also observed qualitative changes in some prefectures (e.g., Tokyo). No clear associations were observed between prefecture-level socioeconomic status variables and the risk of mortality in either sex.

CONCLUSIONS

Geographic disparities in mortality across prefectures are quite substantial and cannot be fully explained by differences in population composition. The relative contribution of composition and context to health inequalities considerably vary across prefectures.

摘要

背景

日本的一项最新研究表明,即使在调整了 47 个县中个体年龄和职业因素后,自 1995 年以来,两性全因过早成年死亡率的地域不平等现象仍有所增加。这种差异可能源于构成因素和环境因素。在这项研究中,我们试图通过探索每个县构成和环境对全因死亡率的相对贡献,进一步研究全因死亡率的新出现的地域不平等现象。

方法

我们使用了 2005 年年龄在 25 岁及以上人群的生命统计和人口普查数据。死亡总数为男性 524785 人,女性 455863 人。我们使用性别特异性两水平逻辑回归模型来模拟死亡率风险,其函数为年龄、职业和在 47 个县的居住情况。以死亡率的地域不平等程度作为县一级方差的估计值,用各地区的比值比(OR)来进行县一级的排名,参考值为所有县的平均值(值=1)。

结果

总体而言,当我们不考虑每个县的构成(即年龄和职业)时,地域不平等的程度更为明显。然而,即使在调整了构成因素后,各地区之间的死亡率风险仍存在显著差异,男性的 OR 值范围为 0.870(冲绳)至 1.190(青森),女性的 OR 值范围为 0.864(岛根)至 1.132(爱知)。在一些县(如青森),调整构成因素对 OR 值的影响不大,但在其他县(如秋田),OR 值明显减弱。我们还观察到一些县(如东京)的情况发生了质的变化。在两性中,都没有观察到县一级社会经济地位变量与死亡率风险之间存在明显的关联。

结论

各地区之间的死亡率地域差异相当大,不能完全用人口构成的差异来解释。构成因素和环境因素对健康不平等的相对贡献在各县之间差异很大。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b974/3384616/20a2273cc944/pone.0039876.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b974/3384616/bc348c15754a/pone.0039876.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b974/3384616/a3e5e0f2dfd3/pone.0039876.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b974/3384616/559b21a574ae/pone.0039876.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b974/3384616/3fd175a7ea5a/pone.0039876.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b974/3384616/20a2273cc944/pone.0039876.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b974/3384616/bc348c15754a/pone.0039876.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b974/3384616/a3e5e0f2dfd3/pone.0039876.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b974/3384616/559b21a574ae/pone.0039876.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b974/3384616/3fd175a7ea5a/pone.0039876.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b974/3384616/20a2273cc944/pone.0039876.g005.jpg

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