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《青年 19 岁 Rangatahi 智能调查:调查校准方法》全国估计数。

National estimates from the Youth '19 Rangatahi smart survey: A survey calibration approach.

机构信息

Department of Statistics, The University of Auckland, Auckland, New Zealand.

Department of Nursing, University of Auckland, Auckland, New Zealand.

出版信息

PLoS One. 2021 May 14;16(5):e0251177. doi: 10.1371/journal.pone.0251177. eCollection 2021.

DOI:10.1371/journal.pone.0251177
PMID:33989300
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8121344/
Abstract

BACKGROUND

Significant progress has been made addressing adolescent health needs in New Zealand, but some areas, such as mental health issues remain, particularly for rangatahi Māori (indigenous Māori young people). Little is known about how contemporary Māori whānau (families) and communities influence health outcomes, health literacy and access to services. Previous nationally representative secondary school surveys were conducted in New Zealand in 2001, 2007 and 2012, as part of the Youth2000 survey series. This paper focuses on a fourth survey conducted in 2019 (https://www.youth19.ac.nz/). In 2019, the survey also included kura kaupapa Māori schools (Māori language immersion schools), and questions exploring the role of family connections in health and wellbeing. This paper presents the overall study methodology, and a weighting and calibration framework in order to provide estimates that reflect the national student population, and enable comparisons with the previous surveys to monitor trends.

METHODS

Youth19 was a cross sectional, self-administered health and wellbeing survey of New Zealand high school students. The target population was the adolescent population of New Zealand (school years 9-13). The study population was drawn from three education regions: Auckland, Tai Tokerau (Northland) and Waikato. These are the most ethnically diverse regions in New Zealand. The sampling design was two-stage clustered stratified, where schools were the clusters, and strata were defined by kura schools and educational regions. There were four strata, formed as follows: kura schools (Tai Tokerau, Auckland and Waikato regions combined), mainstream-Auckland, mainstream-Tai Tokerau and mainstream-Waikato. From each stratum, 50% of the schools were randomly sampled and then 30% of students from the selected schools were invited to participate. All students in the kura kaupapa schools were invited to participate. In order to make more precise estimates and adjust for differential non-response, as well as to make nationally relevant estimates and allow comparisons with the previous national surveys, we calibrated the sampling weights to reflect the national secondary school student population.

RESULTS

There were 45 mainstream and 4 kura schools included in the final sample, and 7,374 mainstream and 347 kura students participated in the survey. There were differences between the sampled population and the national secondary school student population, particularly in terms of sex and ethnicity, with a higher proportion of females and Asian students in the study sample than in the national student population. We calculated estimates of the totals and proportions for key variables that describe risk and protective factors or health and wellbeing factors. Rates of risk-taking behaviours were lower in the sampled population than what would be expected nationally, based on the demographic profile of the national student population. For the regional estimates, calibrated weights yield standard errors lower than those obtained with the unadjusted sampling weights. This leads to significantly narrower confidence intervals for all the variables in the analysis. The calibrated estimates of national quantities provide similar results. Additionally, the national estimates for 2019 serve as a tool to compare to previous surveys, where the sampling population was national.

CONCLUSIONS

One of the main goals of this paper is to improve the estimates at the regional level using calibrated weights to adjust for oversampling of some groups, or non-response bias. Additionally, we also recommend the use of calibrated estimators as they provide nationally adjusted estimates, which allow inferences about the whole adolescent population of New Zealand. They also yield confidence intervals that are significantly narrower than those obtained using the original sampling weights.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7aee/8121344/bf51a582bb63/pone.0251177.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7aee/8121344/2d5a2723e283/pone.0251177.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7aee/8121344/bf51a582bb63/pone.0251177.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7aee/8121344/2d5a2723e283/pone.0251177.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7aee/8121344/bf51a582bb63/pone.0251177.g002.jpg
摘要

背景

新西兰在解决青少年健康需求方面取得了重大进展,但一些领域,如心理健康问题仍然存在,特别是对毛利青少年而言。人们对当代毛利家庭和社区如何影响健康结果、健康素养和获得服务知之甚少。之前在 2001 年、2007 年和 2012 年,新西兰进行了三次全国性的中学生调查,作为 Youth2000 调查系列的一部分。本文重点介绍了 2019 年进行的第四次调查(https://www.youth19.ac.nz/)。2019 年的调查还包括毛利语强化学校(毛利语沉浸式学校),并探讨了家庭联系在健康和幸福方面的作用。本文介绍了总体研究方法以及加权和校准框架,以便提供反映全国学生群体的估计值,并能够与之前的调查进行比较,以监测趋势。

方法

Youth19 是一项针对新西兰高中生的横断面、自我管理的健康和幸福感调查。目标人群是新西兰的青少年人口(9-13 年级)。研究人群来自三个教育地区:奥克兰、北地(泰托科鲁阿)和怀卡托。这些地区是新西兰种族最多样化的地区。抽样设计为两阶段聚类分层,学校为聚类,分层由 kura 学校和教育地区定义。有四个层次,形成如下:kura 学校(泰托科鲁阿、奥克兰和怀卡托地区合并)、主流奥克兰、主流泰托科鲁阿和主流怀卡托。从每个层次中,随机抽取 50%的学校,然后从选定的学校中邀请 30%的学生参加。所有 kura kaupapa 学校的学生都被邀请参加。为了做出更精确的估计值并调整差异非响应,以及做出全国相关的估计值并允许与之前的全国调查进行比较,我们对抽样权重进行了校准,以反映全国中学学生群体。

结果

最终样本包括 45 所主流学校和 4 所 kura 学校,7374 名主流学生和 347 名 kura 学生参加了调查。抽样人群与全国中学生人口存在差异,特别是在性别和族裔方面,研究样本中的女性和亚洲学生比例高于全国学生人口。我们计算了描述风险和保护因素或健康和幸福感因素的关键变量的总数和比例的估计值。根据全国学生人口的人口统计学特征,抽样人群中的冒险行为率低于全国预期水平。对于区域估计值,校准权重产生的标准误差低于未经调整的抽样权重。这导致分析中所有变量的置信区间明显变窄。经过校准的全国数量估计值提供了类似的结果。此外,2019 年的全国估计值可作为与之前调查的比较工具,之前的调查抽样人群是全国性的。

结论

本文的主要目标之一是使用校准权重来调整某些群体的过抽样或非响应偏差,从而提高区域水平的估计值。此外,我们还建议使用校准估计器,因为它们提供了全国调整后的估计值,允许对新西兰整个青少年人口进行推断。它们还产生了比使用原始抽样权重获得的置信区间明显更窄的置信区间。

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