Ko Yi-An, Williams Anne M, Peerson Janet M, Luo Hanqi, Flores-Ayala Rafael, Wirth James P, Engle-Stone Reina, Young Melissa F, Suchdev Parminder S
Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America.
Department of Human Nutrition, University of Otago, Dunedin, Otago, New Zealand.
PLOS Glob Public Health. 2022 Oct 13;2(10):e0001071. doi: 10.1371/journal.pgph.0001071. eCollection 2022.
BACKGROUND: Attributable fractions (AF) of anemia are often used to understand the multifactorial etiologies of anemia, despite challenges interpreting them in cross-sectional studies. We aimed to compare different statistical approaches for estimating AF for anemia due to inflammation, malaria, and micronutrient deficiencies including iron, vitamin A, vitamin B12, and folate. METHODS: AF were calculated using nationally representative survey data among preschool children (10 countries, total N = 7,973) and nonpregnant women of reproductive age (11 countries, total N = 15,141) from the Biomarkers Reflecting Inflammation and Nutrition Determinants of Anemia (BRINDA) project. We used the following strategies to calculate AF: 1) Levin's formula with prevalence ratio (PR) in place of relative risk (RR), 2) Levin's formula with odds ratio (OR) in place of RR, and 3) average (sequential) AF considering all possible removal sequences of risk factors. PR was obtained by 1) modified Poisson regression with robust variance estimation, 2) Kleinman-Norton's approach, and 3) estimation from OR using Zhang-Yu's approach. Survey weighted country-specific analysis was performed with and without adjustment for age, sex, socioeconomic status, and other risk factors. RESULTS: About 20-70% of children and 20-50% of women suffered from anemia, depending on the survey. Using OR yielded the highest and potentially biased AF, in some cases double those using PR. Adjusted AF using different PR estimations (Poisson regression, Kleinman-Norton, Zhang-Yu) were nearly identical. Average AF estimates were similar to those using Levin's formula with PR. Estimated anemia AF for children and women were 2-36% and 3-46% for iron deficiency, <24% and <12% for inflammation, and 2-36% and 1-16% for malaria. Unadjusted AF substantially differed from adjusted AF in most countries. CONCLUSION: AF of anemia can be estimated from survey data using Levin's formula or average AF. While different approaches exist to estimate adjusted PR, Poisson regression is likely the easiest to implement. AF are a useful metric to prioritize interventions to reduce anemia prevalence, and the similarity across methods provides researchers flexibility in selecting AF approaches.
背景：尽管在横断面研究中解释贫血归因分数（AF）存在挑战，但贫血归因分数常被用于了解贫血的多因素病因。我们旨在比较估算因炎症、疟疾以及包括铁、维生素A、维生素B12和叶酸在内的微量营养素缺乏导致的贫血归因分数的不同统计方法。 方法：利用反映贫血炎症和营养决定因素（BRINDA）项目中来自10个国家的学龄前儿童（共N = 7973）和11个国家的育龄非孕妇女（共N = 15141）的具有全国代表性的调查数据计算归因分数。我们采用以下策略计算归因分数：1）用患病率比（PR）代替相对危险度（RR）的莱文公式；2）用比值比（OR）代替RR的莱文公式；3）考虑所有可能的危险因素去除顺序的平均（顺序）归因分数。患病率比通过以下方法获得：1）采用稳健方差估计的修正泊松回归；2）克莱曼 - 诺顿方法；3）使用张 - 于方法从比值比进行估计。在有和没有对年龄、性别、社会经济地位及其他危险因素进行调整的情况下，进行了调查加权的国家特异性分析。 结果：根据调查，约20% - 70%的儿童和20% - 50%的妇女患有贫血。使用比值比得出的归因分数最高且可能存在偏差，在某些情况下是使用患病率比得出的归因分数的两倍。使用不同患病率比估计方法（泊松回归、克莱曼 - 诺顿、张 - 于）得出的调整后归因分数几乎相同。平均归因分数估计值与使用患病率比的莱文公式得出的结果相似。儿童和妇女因缺铁导致的贫血归因分数估计分别为2% - 36%和3% - 46%，因炎症导致的分别<24%和<12%，因疟疾导致的分别为2% - 36%和1% - 16%。在大多数国家，未调整的归因分数与调整后的归因分数有很大差异。 结论：贫血归因分数可通过莱文公式或平均归因分数从调查数据中估算得出。虽然存在不同方法来估计调整后的患病率比，但泊松回归可能是最易于实施的。归因分数是确定降低贫血患病率干预措施优先级的有用指标，并且不同方法之间的相似性为研究人员在选择归因分数方法时提供了灵活性。
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