Saunders P, Mathers J, Parry J, Stevens A
Department of Public Health and Epidemiology, University of Birmingham, Edgbaston.
J Public Health Med. 2001 Jun;23(2):103-8. doi: 10.1093/pubmed/23.2.103.
The aim of the study was to identify 'non-medical' datasets holding routinely collected information that might be used to measure and monitor the wider determinants of community health and well-being.
An expert panel discussion, involving public health and environmental health academics and professionals with expertise in a variety of backgrounds (including environmental health, housing, transport, community safety, public health, primary and secondary care), and interrogation of the Office for National Statistics database were carried out for the West Midlands region. The aim was to identify routinely collected 'non-medical' datasets containing information on the following factors: physical environment, crime, housing and homelessness, social services, socio-economic environment including employment, lifestyles, education, leisure and culture, transport and accidents.
Fifty-six datasets were identified. Although 43 (77 per cent) were collected at least annually, few (17; 30 per cent) held data that were disaggregated and routinely available at the sub-local authority level.
This study has identified a number of datasets that hold information relevant to health. However, no single dataset is likely to provide information on all dimensions of health and the determinants of health, and local agencies should consider carefully the strengths and weaknesses of each. Through the development of inter-sectoral working and multi-agency involvement at the local level there is now considerable scope to improve the quality of many of these datasets and to promote their use in the measurement and monitoring of community health.
本研究旨在识别包含常规收集信息的“非医学”数据集,这些数据集可用于衡量和监测社区健康与福祉的更广泛决定因素。
针对西米德兰兹地区开展了一次专家小组讨论,参与讨论的有公共卫生和环境卫生领域的学者以及来自各种背景(包括环境卫生、住房、交通、社区安全、公共卫生、初级和二级医疗保健)的专业人员,并对国家统计局数据库进行了查询。目的是识别包含以下因素信息的常规收集的“非医学”数据集:物理环境、犯罪、住房与无家可归、社会服务、社会经济环境(包括就业、生活方式、教育、休闲和文化)、交通和事故。
识别出了56个数据集。虽然其中43个(77%)至少每年收集一次,但只有少数(17个;30%)拥有在地方当局以下层面进行了分类且可常规获取的数据。
本研究识别出了一些与健康相关的数据集。然而,没有一个数据集可能提供关于健康的所有方面以及健康决定因素的信息,地方机构应仔细考虑每个数据集的优缺点。通过在地方层面发展跨部门合作和多机构参与,现在有很大的空间来提高许多这些数据集的质量,并促进它们在社区健康的衡量和监测中的应用。