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利用新西兰综合数据基础设施构建全人群队列进行健康和社会研究。

Constructing whole of population cohorts for health and social research using the New Zealand Integrated Data Infrastructure.

机构信息

Section of Epidemiology & Biostatistics, School of Population Health, The University of Auckland, New Zealand.

Centre of Methods and Policy Application in the Social Sciences, The University of Auckland, New Zealand.

出版信息

Aust N Z J Public Health. 2018 Aug;42(4):382-388. doi: 10.1111/1753-6405.12781. Epub 2018 Apr 12.

Abstract

OBJECTIVES

To construct and compare a 2013 New Zealand population derived from Statistics New Zealand's Integrated Data Infrastructure (IDI) with the 2013 census population and a 2013 Health Service Utilisation population, and to ascertain the differences in cardiovascular disease prevalence estimates derived from the three cohorts.

METHODS

We constructed three national populations through multiple linked administrative data sources in the IDI and compared the three cohorts by age, gender, ethnicity, area-level deprivation and District Health Board. We also estimated cardiovascular disease prevalence based on hospitalisations using each of the populations as denominators.

RESULTS

The IDI population was the largest and most informative cohort. The percentage differences between the IDI and the other two populations were largest for males and for those aged 15-34 years. The percentage differences between the IDI and Census cohorts were largest for people living in the most deprived areas. The ethnic distribution varied across the three cohorts. Using the IDI population as a reference, the Health Service Utilisation population generally overestimated cardiovascular disease prevalence, while the Census population generally underestimated it.

CONCLUSIONS AND IMPLICATIONS

The New Zealand IDI population is the most comprehensive and appropriate national cohort for use in health and social research.

摘要

目的

构建并比较新西兰 2013 年的人口数据,其中包括来自新西兰统计局综合数据基础设施(IDI)的人口数据、2013 年人口普查数据和 2013 年卫生服务利用数据,并确定这三个队列的心血管疾病患病率估计值的差异。

方法

我们通过 IDI 中的多个链接行政数据源构建了三个全国性的人口数据集,并通过年龄、性别、种族、地区贫困程度和地区卫生局对这三个队列进行了比较。我们还根据每个队列的住院情况估算了心血管疾病的患病率。

结果

IDI 人口是最大和最具信息性的队列。IDI 与其他两个队列之间的百分比差异在男性和 15-34 岁年龄组中最大。IDI 与人口普查队列之间的百分比差异在最贫困地区的人群中最大。三个队列的种族分布存在差异。以 IDI 人群为参照,卫生服务利用人群普遍高估了心血管疾病的患病率,而人口普查人群则普遍低估了这一患病率。

结论和意义

新西兰 IDI 人口是健康和社会研究中最全面和最合适的全国性队列。

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