Addressing Missing Paternal Linkage in Administrative Data - A Candidate Father Approach.

IF 2.2 Q3 HEALTH CARE SCIENCES & SERVICES
International Journal of Population Data Science Pub Date : 2026-07-06 eCollection Date: 2026-01-01 DOI:10.23889/ijpds.v11i5.3651
Amani Hamad, Lin Yan, Barret Monchka, Oleguer Plana-Ripoll, Olawale Ayilara, Lisa Lix
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引用次数: 0

Abstract

Objective: Paternal linkages are often missing in administrative data. We propose and evaluate a method to identify candidate fathers using residence and demographic information.

Approach: We conducted a population-based cohort study of Manitoba adults born 1977-2017 with maternal linkages. We modelled the probability of missing paternal linkage using key covariates for births post-1980, when missingness was highest. We applied this model to births pre-1980, when missingness was lowest, to exclude those with the highest predicted probability of missing linkage, at missingness levels of 10-50%. We identified candidate fathers in the same postal code area; up to three candidates were randomly selected using parental age-gap weights. We measured the percentage of candidate father sets containing the true father and estimated hazard ratios (HR) and 95% confidence intervals for paternal transfer of mental disorder and ischemic heart disease (IHD) for true versus candidate fathers.

Results: The cohort included 140,001 births; 25.8% lacked paternal linkages, and 26.8% were born before 1980. Only 27-28% of candidate sets included the true father across missingness levels. For mental disorders, the true-father HR was 1.27 (1.23-1.31); candidate-father HRs ranged from 1.17 (1.13-1.22) at 50% to 1.24 (1.20-1.29) at 10% missingness. For IHD, the true-father HR was 1.94 (1.35-2.79); candidate-father HRs ranged from 1.64 (0.92-2.89) to 1.91 (1.32-2.75).

Conclusions: Our method had low accuracy in identifying true fathers but produced similar risk estimates for true and candidate fathers, especially at lower missingness levels, suggesting utility for intergenerational research with incomplete paternal linkage.

解决行政数据中缺失的父系联系——一个候选父亲方法。
目的:父系联系在行政数据中经常缺失。我们提出并评估了一种利用居住和人口统计信息来识别候选父亲的方法。方法:我们对1977-2017年出生的曼尼托巴成年人进行了一项基于人群的队列研究,并与母亲有联系。我们使用1980年后出生的关键协变量对缺失父系联系的概率进行建模,当时缺失程度最高。我们将这个模型应用于1980年以前出生的婴儿,当时缺失率最低,排除了那些缺失率在10-50%的预测缺失联系概率最高的婴儿。我们在相同的邮政编码地区找到了候选父亲;使用父母年龄差距权重随机选择最多三名候选人。我们测量了包含真父亲的候选父亲组的百分比,并估计了真父亲与候选父亲之间精神障碍和缺血性心脏病(IHD)父亲遗传的风险比(HR)和95%置信区间。结果:该队列包括140,001名新生儿;25.8%的人缺乏父系关系,26.8%的人在1980年之前出生。只有27-28%的候选集在缺失程度上包含了真正的父亲。对于精神障碍,真父HR为1.27 (1.23-1.31);候选父亲的hr从1.17(1.13-1.22)(50%)到1.24(1.20-1.29)(10%)不等。IHD的亲本比为1.94 (1.35 ~ 2.79);候选者-父亲hr为1.64(0.92-2.89)~ 1.91(1.32-2.75)。结论:我们的方法在识别真父亲方面准确性较低,但对真父亲和候选父亲产生了相似的风险估计,特别是在缺失水平较低的情况下,这表明在不完全父系联系的代际研究中具有实用价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.50
自引率
0.00%
发文量
386
审稿时长
20 weeks
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