Administrative health data that link individuals to their parents provide a valuable resource for population-based familial health research. Such data have been used to investigate the intergenerational transfer of health conditions and social risks, and the influence of exposures across generations, and to develop risk prediction models [1–14]. Linkages to parents in administrative data rely on personal identifiers, address or household identifiers, birth and marriage registry information, or health claims such as hospital records [15, 16]. Unlike maternal linkages, which can be derived from birth information recorded in the mother’s hospital record, paternal linkages cannot be determined from the father’s hospital records because paternal identifiers are not systematically captured in birth-related administrative records. Therefore, most existing familial health research focused on maternal and child health and did not consider fathers [7, 17–25]. Fathers play an important role in shaping offspring health through shared genetic risk, environmental exposures, and social factors that may differ from those of mothers. Paternal health is associated with a wide range of offspring health outcomes across the life course, including mental disorders and cardiovascular disease [1, 26, 27]. Consequently, complete and accurate paternal linkage is increasingly important for studies investigating familial disease risk, intergenerational health, and family-based risk prediction using population-based administrative data. In many data sources, paternal linkages are therefore derived using indirect information, such as address or household identifiers [16, 28–30]. This can result in incomplete paternal linkages and varying completeness over time, which presents challenges for using administrative health data in familial research [29, 31]. For example, 10% of births registered in Western Australia between 1980 and 2005 had incomplete paternal information [31]. Similarly, while administrative health data in Manitoba, Canada, contain virtually complete linkages to mothers (over 98%), linkages to fathers, which rely on household information reflecting registered family units, have decreased significantly from 86% in 1974 births to 36% in 2019 births [32].

Methods for addressing missing paternal information should be considered when incorporating fathers into population-based familial health research. Most previous familial research relied on complete-case analysis to address missing parental linkages [2, 10, 11, 14, 26, 33, 34]. This approach excludes offspring who cannot be linked to their parents. As this approach is simple to implement despite complex mechanisms underlying missing paternal linkages, and does not require advanced technical expertise or computational resources, it is commonly used in familial research. However, when paternal linkage is not missing completely at random, it could introduce selection bias and compromise the validity of estimated associations, in addition to reducing sample size and statistical precision [35, 36]. Using an indicator category by assigning an additional category to denote missing information about the variable is an alternative approach that has been previously used to address missing data [1, 37]. This approach is straightforward to apply and has the advantage of retaining cohort size; however, it can also result in biased estimates [36, 38–40].

Given the challenges posed by incomplete paternal linkages in administrative data and the limitations of existing approaches to handling missing paternal information, an approach that could probabilistically impute the missing relationships is needed. We hypothesised that geographic proximity and demographic plausibility, specifically, shared 6-digit postal code and a likely parental age gap, could be used to identify plausible candidate fathers. Because parents generally live together or in proximity at the time of birth and have age differences within a typical range, these characteristics provide reasonable criteria for identifying candidate fathers. Therefore, we aimed to develop and evaluate a novel approach to identify candidate fathers for offspring with missing paternal linkage. To evaluate whether the candidate father approach could preserve father–offspring associations in epidemiologic analyses, we adopted it in two use cases. These use cases tested the association between: (a) a paternal history of mental disorders and offspring mental disorders, and (b) a paternal history of ischaemic heart disease (IHD) and offspring IHD. Mental disorder and IHD were selected as test cases because they have different administrative data accuracy, aetiology and prevalence, and therefore can demonstrate the approach’s utility across diverse research scenarios. This novel approach provides a practical method for incorporating otherwise missing fathers by assigning plausible proxy fathers, thereby improving the completeness of paternal information for analysis, reducing bias, and facilitating more robust familial health research.

This large population-based cohort study developed a novel candidate father approach to address missing paternal linkages in administrative health data and applied it to investigate the paternal transfer of mental disorders and IHD. Although the candidate father approach had limited accuracy in identifying true fathers, it produced risk estimates that were close to the true estimates, particularly at lower missingness levels. Across outcomes, estimates produced using the candidate father approach showed progressive attenuation toward the null as the missingness level increased. In contrast, indicator category and complete-case approaches produced estimates closely aligned with the true estimate for mental disorders but increasingly deviated away from the null for IHD at higher missingness levels, with wider confidence intervals reflecting increased imprecision. In the full cohort, all three approaches resulted in comparable inferences about the paternal transfer of mental disorders and IHD, despite a modest attenuation of effects using the candidate father approach.

The attenuation in risk estimates using the candidate father approach is consistent with exposure misclassification arising from the use of plausible rather than true fathers. As missingness levels increased, the cohort included a greater proportion of plausible fathers, which may have diluted the measured association between paternal history and offspring outcomes, resulting in smaller effect estimates. This pattern was observed for both mental disorders and IHD outcomes, but the attenuation was stronger for IHD, likely reflecting a lower outcome prevalence and greater imprecision. In contrast, indicator category and complete-case approaches rely on observed linkages and therefore do not introduce exposure misclassification as with the candidate father approach, but they may increase statistical uncertainty and, in the case of complete-case approach, reduce precision due to smaller sample sizes. For mental disorders, these two approaches produced estimates closely aligned with the true estimates, likely due to the high prevalence of the outcome. However, for IHD, a rarer outcome, these approaches showed greater deviation from the null with increased missingness, suggesting their sensitivity to selection bias. In the full cohort with true paternal linkage missingness, all the approaches led to comparable risk estimates, demonstrating the practical utility of the candidate father approach. The consistent attenuation of effects with this approach highlights the trade-off between reducing selection bias by retaining offspring with missing paternal linkage and introducing exposure misclassification. By assigning plausible fathers rather than excluding offspring or classifying paternal history as missing, the candidate father approach preserves cohort size while providing a structured strategy for approximating paternal exposure under incomplete paternal linkage.

Although the unrestricted candidate pool contained the true father for approximately two-thirds of offspring, a substantial proportion of true fathers were not identified because they did not meet the candidate selection criteria. This finding reflects both deliberate design choices to prioritise plausible candidates and maintain computational feasibility, and inherent limitations of the administrative data. For example, some true fathers may not have shared the same postal code around the time of birth or may not have met the age-based eligibility criteria. Future refinements could incorporate additional information on familial relationships, where available, to improve candidate identification. However, the performance of any candidate father approach will ultimately remain constrained by the completeness and accuracy of familial information captured in administrative data. An additional validation analysis showed that the association between paternal and offspring mental disorders was preserved only when the selected candidate father matched the true father, indicating that the observed associations were driven by correct identification of the paternal linkage.

Missing paternal linkages in administrative health data primarily reflect administrative and social processes, rather than true absence of a biological father. In Manitoba, paternal linkage depends on the reporting of marital or common-law relationships for the fathers to share the same FRNs as the mother and children; such reporting is not mandatory. As a result, paternal linkages may be missing in cases of relationship instability, younger maternal age, or failure to report parental relationships, and are influenced by changes in family structure over time [29]. While other scenarios, such as same-sex parenting and assisted reproduction, may contribute to missing paternal information, these are expected to represent a minority of cases and cannot explain the magnitude of missingness observed in this study cohort. Although missing paternal linkage was more common among offspring of younger mothers and those from lower socioeconomic backgrounds, the candidate father approach was designed to improve the handling of missing paternal linkage rather than to characterise specific family structures. Because our study did not directly evaluate performance according to family structure, we cannot determine whether the approach performs differently in more or less stable family contexts. However, it identified at least one plausible candidate father for nearly 80% of offspring with missing paternal linkage, substantially reducing the number of offspring for whom paternal information could not be approximated.

Consistent with previous work, paternal linkage was systematically associated with sociodemographic and familial characteristics, indicating that missingness does not satisfy the assumption of missing completely at random [31]. In the validation analyses with simulated missing paternal linkage, approaches for handling missing paternal linkage performed differently based on the outcome characteristics and missingness level, with indicator category and complete-case approaches showing deviations from the true father estimate for IHD but not for mental disorders. In contrast, in the full cohort with true missing paternal linkage, all approaches resulted in comparable risk estimates for both outcomes, with the candidate father approach producing more conservative effect estimates. These findings highlight the importance of using multiple analytic approaches to assess robustness in familial studies using administrative data with incomplete parental linkage. In addition to analytic approaches for handling missing paternal linkage, there is also potential to improve paternal linkage by integrating administrative health data with complementary data sources. These may include social service or income assistance records that capture familial relationships, prospective cohorts with family information, or surveys that collect self-reported family structure information. Such data sources could enrich administrative datasets by providing additional information on paternal relationships that are not routinely captured. However, these sources are typically available only for selected subpopulations and lack the population-based coverage of administrative health data, potentially introducing selection bias. As a result, analytic approaches that can accommodate missing paternal information within population-based administrative data remain essential for familial health research.

A major strength of this study is the large, population-based cohort representative of the Manitoba population, enabled by the universal coverage of the healthcare system. Additional strengths include the use of objective administrative data case definitions of mental disorders and IHD in offspring and their parents, as well as the application of a novel validation design using a historical cohort with high paternal linkage completeness to compare multiple approaches against a true father benchmark. However, there are a few limitations to note. First, the approaches were compared in the context of the paternal transfer of mental disorders and IHD; findings may not generalise to other outcomes, exposure definitions or study designs. Second, although a reference standard was available in the validation analyses, no such benchmark existed in the full cohort with true missing paternal linkage, preventing definitive conclusions about which approach produces the least biased risk estimates in applied settings. Additionally, our validation analyses used the father identified through the FRN recorded at birth as the reference standard, which is expected to represent the biological father in most families, as adoptions at birth and other alternative family arrangements are uncommon. However, biological paternity cannot be independently verified using administrative data. The father–offspring associations evaluated in this study should be interpreted in the context of the Registry-defined paternal linkage, which likely reflects a combination of shared genetic susceptibility and familial environmental and social influences rather than biological inheritance alone. The candidate father approach is intended to recover the paternal relationship represented in the administrative data. Finally, the mechanisms and patterns of paternal linkage missingness in the Manitoba Repository may differ from those in other jurisdictions, potentially limiting generalizability of our candidate father approach to settings with different administrative or social contexts. The performance of the approach is likely influenced by the availability and quality of family identifiers, residential address information, and the administrative processes used to establish parent–child linkages. In addition, social and demographic factors, including family structure, partnership reporting practices, migration, and cultural differences in how familial relationships are recorded, may affect both the completeness of paternal linkage and the suitability of the candidate selection criteria. Replication in other jurisdictions with differing administrative practices would help establish the generalizability of these findings.

This newly developed approach used residence and demographic information to identify plausible fathers for offspring with missing paternal linkage. Although this approach identified only a subset of true fathers, it produced estimates of the association between paternal history and offspring mental disorder and IHD risks that were close to those obtained using the true fathers, particularly at lower missingness levels. These findings indicate that the candidate father approach can support population-based familial research using administrative data where incomplete paternal linkage limits the inclusion of paternal information. Across approaches, performance varied by outcome and level of missingness, and no single approach was uniformly superior, highlighting the value of applying multiple strategies to assess the robustness in studies with incomplete parental linkage.