Analysis of data from a national micronutrient survey with a linear mixed model: estimates, predictions and lessons for future surveys.

IF 1.6 Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Journal of Public Health Research Pub Date : 2024-10-22 eCollection Date: 2024-10-01 DOI:10.1177/22799036241274962
Hakunawadi Alexander Pswarayi, Edward J M Joy, Dawd Gashu, Fanny Sandalinas, Adamu Belay, R Murray Lark
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引用次数: 0

Abstract

Background: Because micronutrient deficiencies affect public health, countries monitor population status by national-scale, multi-stage, micronutrient surveys (MNS). In design-based surveys, inclusion probabilities are specified for sample units and the corresponding sample weights allow design-unbiased estimates to be made of population parameters. Corrections may be possible on departures from the design; an alternative is to use linear mixed models (LMM), with an estimated covariance structure reflecting the sampling design, to obtain model-based estimates.

Design: The Ethiopia National Micronutrient Survey (2016) specified inclusion probabilities at enumeration area (EA) and household (HH) levels, and sample weights are provided. However, the design was not followed as it would have resulted in insufficient sampling from women of reproductive age.

Results: Having found no evidence that sample weights were informative for target serum micronutrient concentrations (Zn), we estimated LMM parameters, with Regions as fixed effects, and the variation of individuals nested within households, households within EA, and EA within regions, random effects. We obtained LMM standard errors, Best Linear Unbiased Estimates (BLUEs) of regional means, and empirical Best Linear Unbiased Predictions for sampled/unsampled EA and HH. The probability that each true regional mean exceeded the sufficiency threshold ( 65 μ g dL - 1 ) was evaluated. The variances of BLUEs of regional means, under alternative sampling designs, were bootstrapped from LMM variance components.

Conclusions: We demonstrate use of LMM to obtain model-unbiased estimates and predictions when surveys deviate from the original design; and the use of LMM variance components to evaluate alternative designs for further sampling, or for sampling comparable populations.

用线性混合模型分析全国微量营养素调查数据:估计、预测和对未来调查的启示。
背景:由于微量营养素缺乏会影响公众健康,各国通过全国范围、多阶段的微量营养素调查(MNS)来监测人口状况。在基于设计的调查中,规定了样本单位的纳入概率和相应的样本权重,从而可以对人口参数进行无设计偏差的估计。可以对偏离设计的情况进行校正;另一种方法是使用线性混合模型 (LMM),用反映抽样设计的估计协方差结构来获得基于模型的估计值:埃塞俄比亚全国微量营养素调查(2016 年)规定了辖区(EA)和家庭(HH)层面的纳入概率,并提供了样本权重。然而,由于会导致育龄妇女抽样不足,因此没有遵循该设计:由于没有证据表明样本权重对目标血清微量营养素浓度(锌)具有参考价值,我们估算了 LMM 参数,并将地区作为固定效应,将家庭内的个人、EA 内的家庭和地区内的 EA 的变化作为随机效应。我们获得了 LMM 标准误差、区域均值的最佳线性无偏估计值 (BLUE) 以及对采样/未采样 EA 和 HH 的经验最佳线性无偏预测值。评估了每个真实区域均值超过充足阈值(65 μ g dL - 1)的概率。根据 LMM 方差分量,对其他采样设计下区域均值 BLUE 的方差进行了引导:我们展示了在调查偏离原始设计时,如何利用 LMM 获得无模型偏差的估计值和预测值;以及如何利用 LMM 方差分量评估进一步采样或可比种群采样的替代设计。
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来源期刊
Journal of Public Health Research
Journal of Public Health Research PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
3.70
自引率
4.30%
发文量
116
审稿时长
10 weeks
期刊介绍: The Journal of Public Health Research (JPHR) is an online Open Access, peer-reviewed journal in the field of public health science. The aim of the journal is to stimulate debate and dissemination of knowledge in the public health field in order to improve efficacy, effectiveness and efficiency of public health interventions to improve health outcomes of populations. This aim can only be achieved by adopting a global and multidisciplinary approach. The Journal of Public Health Research publishes contributions from both the “traditional'' disciplines of public health, including hygiene, epidemiology, health education, environmental health, occupational health, health policy, hospital management, health economics, law and ethics as well as from the area of new health care fields including social science, communication science, eHealth and mHealth philosophy, health technology assessment, genetics research implications, population-mental health, gender and disparity issues, global and migration-related themes. In support of this approach, JPHR strongly encourages the use of real multidisciplinary approaches and analyses in the manuscripts submitted to the journal. In addition to Original research, Systematic Review, Meta-analysis, Meta-synthesis and Perspectives and Debate articles, JPHR publishes newsworthy Brief Reports, Letters and Study Protocols related to public health and public health management activities.
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