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利用数据了解两个中等收入国家抑郁症的社会决定因素:3-D 委员会。

Use of Data to Understand the Social Determinants of Depression in Two Middle-Income Countries: the 3-D Commission.

机构信息

Department of Health Services, Policy and Practice, Brown University, Providence, USA.

Rockefeller Foundation-Boston University 3-D Commission on Determinants, Data, and Decision-making, Boston, USA.

出版信息

J Urban Health. 2021 Aug;98(Suppl 1):41-50. doi: 10.1007/s11524-021-00559-6. Epub 2021 Aug 18.

Abstract

Depression accounts for a large share of the global disease burden, with an estimated 264 million people globally suffering from depression. Despite being one of the most common kinds of mental health (MH) disorders, much about depression remains unknown. There are limited data about depression, in terms of its occurrence, distribution, and wider social determinants. This work examined the use of novel data sources for assessing the scope and social determinants of depression, with a view to informing the reduction of the global burden of depression.This study focused on new and traditional sources of data on depression and its social determinants in two middle-income countries (LMICs), namely, Brazil and India. We identified data sources using a combination of a targeted PubMed search, Google search, expert consultations, and snowball sampling of the relevant literature published between October 2010 and September 2020. Our search focused on data sources on the following HEALTHY subset of determinants: healthcare (H), education (E), access to healthy choices (A), labor/employment (L), transportation (T), housing (H), and income (Y).Despite the emergence of a variety of data sources, their use in the study of depression and its HEALTHY determinants in India and Brazil are still limited. Survey-based data are still the most widely used source. In instances where new data sources are used, the most commonly used data sources include social media (twitter data in particular), geographic information systems/global positioning systems (GIS/GPS), mobile phone, and satellite imagery. Often, the new data sources are used in conjunction with traditional sources of data. In Brazil, the limited use of new data sources to study depression and its HEALTHY determinants may be linked to (a) the government's outsized role in coordinating healthcare delivery and controlling the data system, thus limiting innovation that may be expected from the private sector; (b) the government routinely collecting data on depression and other MH disorders (and therefore, does not see the need for other data sources); and (c) insufficient prioritization of MH as a whole. In India, the limited use of new data sources to study depression and its HEALTHY determinants could be a function of (a) the lack of appropriate regulation and incentives to encourage data sharing by and within the private sector, (b) absence of purposeful data collection at subnational levels, and (c) inadequate prioritization of MH. There is a continuing gap in the collection and analysis of data on depression, possibly reflecting the limited priority accorded to mental health as a whole. The relatively limited use of data to inform our understanding of the HEALTHY determinants of depression suggests a substantial need for support of independent research using new data sources. Finally, there is a need to revisit the universal health coverage (UHC) frameworks, as these frameworks currently do not include depression and other mental health-related indicators so as to enable tracking of progress (or lack thereof) on such indicators.

摘要

抑郁症占全球疾病负担的很大一部分,全球估计有 2.64 亿人患有抑郁症。尽管抑郁症是最常见的精神健康(MH)障碍之一,但对其仍知之甚少。关于抑郁症的发生、分布和更广泛的社会决定因素的数据有限。这项工作检查了使用新的数据来源来评估抑郁症的范围和社会决定因素,以期减轻全球抑郁症负担。

本研究重点关注两个中等收入国家(LMICs),即巴西和印度的抑郁症及其社会决定因素的新的和传统的数据来源。我们使用有针对性的 PubMed 搜索、谷歌搜索、专家咨询以及 2010 年 10 月至 2020 年 9 月期间发表的相关文献的滚雪球抽样相结合的方法来确定数据源。我们的搜索重点是以下健康决定因素的数据源:医疗保健(H)、教育(E)、获得健康选择的机会(A)、劳动/就业(L)、交通(T)、住房(H)和收入(Y)。

尽管出现了各种数据源,但它们在印度和巴西的抑郁症及其健康决定因素研究中的使用仍然有限。基于调查的数据源仍然是最广泛使用的来源。在使用新数据源的情况下,最常用的数据来源包括社交媒体(特别是推特数据)、地理信息系统/全球定位系统(GIS/GPS)、移动电话和卫星图像。通常,新数据源与传统数据源结合使用。在巴西,新数据源在研究抑郁症及其健康决定因素方面的使用有限,可能与以下因素有关:(a)政府在协调医疗保健提供和控制数据系统方面的作用过大,从而限制了私营部门可能预期的创新;(b)政府定期收集抑郁症和其他 MH 障碍的数据(因此,不需要其他数据源);(c)对整体 MH 重视程度不够。在印度,新数据源在研究抑郁症及其健康决定因素方面的使用有限,可能是由于:(a)缺乏适当的监管和激励措施,以鼓励私营部门内部和之间的数据共享;(b)缺乏在国家以下各级有目的的数据收集;(c)对 MH 的重视程度不够。

抑郁症数据的收集和分析仍然存在差距,这可能反映出对整体心理健康的重视程度有限。利用数据来更好地了解抑郁症的健康决定因素的工作相对较少,这表明需要支持使用新数据源进行独立研究。最后,需要重新审视全民健康覆盖(UHC)框架,因为这些框架目前不包括抑郁症和其他与心理健康相关的指标,以便能够跟踪这些指标的进展情况(或缺乏进展情况)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/433c/8440785/ef2a6f61fbc9/11524_2021_559_Fig1_HTML.jpg

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