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创建和使用新数据源来分析社会政策与全球健康之间的关系:以产假为例。

Creating and using new data sources to analyze the relationship between social policy and global health: the case of maternal leave.

机构信息

McGill University, Institute for Health and Social Policy, Montreal, QC, Canada.

出版信息

Public Health Rep. 2011 Sep-Oct;126 Suppl 3(Suppl 3):127-34. doi: 10.1177/00333549111260S317.

DOI:10.1177/00333549111260S317
PMID:21836745
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3150137/
Abstract

OBJECTIVES

Operating at a societal level, public policy is often one of our best approaches to addressing social determinants of health (SDH). Yet, limited data availability has constrained past research on how national social policy choices affect health outcomes. We developed a new data infrastructure to illustrate how globally comparative data on labor policy might be used to examine the impact of social policy on health.

METHODS

We used multivariate ordinary least squares regression models to examine the relationship between the duration of paid maternal leave and neonatal, infant, and child mortality rates in 141 countries when controlling for overall resources available to meet basic needs measured by per capita gross domestic product, total and government health expenditures, female literacy, and basic health care and public health provision.

RESULTS

An increase of 10 full-time-equivalent weeks of paid maternal leave was associated with a 10% lower neonatal and infant mortality rate (p ≤ 0.001) and a 9% lower rate of mortality in children younger than 5 years of age (p ≤ 0.001). Paid maternal leave is associated with significantly lower neonatal, infant, and child mortality in non-Organisation for Economic Co-operation and Development (OECD) countries and OECD countries.

CONCLUSIONS

This preliminary study, using newly available worldwide policy data, demonstrates the potential strength of using globally comparative data to examine SDH. Further data development to make multilevel modeling of the impact of labor conditions possible and to broaden which social policies can be examined is a critical next step.

摘要

目的

从社会层面入手,公共政策往往是解决健康社会决定因素(SDH)的最佳方法之一。然而,由于数据的局限性,过去的研究受到了限制,无法了解国家社会政策选择如何影响健康结果。我们开发了一种新的数据基础设施,以说明如何利用全球劳动力政策数据来研究社会政策对健康的影响。

方法

我们使用多元线性回归模型,在控制了由人均国内生产总值、总卫生支出和政府卫生支出、女性识字率以及基本医疗和公共卫生服务衡量的基本需求资源总量后,检验了 141 个国家中带薪产假与新生儿和婴儿死亡率以及 5 岁以下儿童死亡率之间的关系。

结果

带薪产假增加 10 个全职等效周与新生儿和婴儿死亡率降低 10%(p≤0.001)以及 5 岁以下儿童死亡率降低 9%(p≤0.001)显著相关。带薪产假与非经济合作与发展组织(OECD)国家和 OECD 国家的新生儿、婴儿和儿童死亡率显著降低相关。

结论

本初步研究利用新获得的全球政策数据,展示了使用全球可比数据研究 SDH 的潜在优势。进一步开发数据以实现劳动力条件影响的多层次建模,并扩大可研究的社会政策是至关重要的下一步。

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