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. 2024 Nov 27;9(2):2402.
doi: 10.23889/ijpds.v9i2.2402. eCollection 2024.

A maternal and child health administrative cohort in Scotland: the utility of linked administrative data for understanding early years' outcomes and inequalities

Affiliations

A maternal and child health administrative cohort in Scotland: the utility of linked administrative data for understanding early years' outcomes and inequalities

Paul Henery et al. Int J Popul Data Sci. .

Abstract

Introduction: The early years are considered one of the most impactful points in the life course to intervene to improve population health and reduce health inequalities because, for example, both ill health and social disadvantage can track into adulthood. Scotland's outstanding systems for data linkage offer untapped potential to further our understanding of when and why inequalities in child health, development and wellbeing emerge. This understanding is vital for the consideration of policy options for their reduction.

Methods: Birth registrations, hospital episodes, dispensed community prescriptions, child health reviews and immunisation records were linked for 198,483 mother-child pairs for babies born in Scotland from October 2009 to the end of March 2013, followed up until April 2018 (average age 6 years).

Results: Outcomes include birthweight and newborn health, dispensed prescriptions for mental health medications, tobacco smoke exposure, infant feeding, immunisations, hospitalisation for unintentional injuries, socio-emotional, cognitive and motor development, and overweight and obesity. Several measures are repeated throughout childhood allowing examination of timing, change and persistence. Socio-economic circumstances (SECs) include neighbourhood deprivation, relationship status of the parents, and occupational status. Descriptive analyses highlight large inequalities across all outcomes. Inequalities are greater when measured by family-level as opposed to area-level, aspects of socio-economic circumstances and for persistent or more severe outcomes. For example, 41.4% of the most disadvantaged children (living with a lone, economically inactive mother in the most deprived fifth of areas) were exposed to tobacco smoke in utero and in infancy/toddlerhood compared to <1% in the least disadvantaged children (living with a married, managerial/professional mother in the least deprived quintile of areas).

Conclusion: This novel linkage provides a longitudinal picture of health throughout the early years and how this varies according to family- and area-level measures of SECs. Future linkages could include other family members (e.g. siblings, grandmothers) and other sectors (e.g. education, social care). The creation of additional cohorts would allow for long-term and efficient evaluation of policies as natural experiments.

Keywords: admin data; child health; cohort; inequalities; maternal health.

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Conflict of interest statement

Conflicts of interest: The authors have no conflicts of interest to declare except for the funding noted above.

Figures

Figure 1: Overview of datasets, topics and study period
Figure 1: Overview of datasets, topics and study period
Figure 2: Flow diagram to demonstrate how the four analytic samples were created from the original Eligible Cohort
Figure 2: Flow diagram to demonstrate how the four analytic samples were created from the original Eligible Cohort
Figure 3: Inequalities in selected outcomes according to three measures of socio-economic circumstances
Figure 3: Inequalities in selected outcomes according to three measures of socio-economic circumstances
Figure 4: Relative risk ratios (RRRs) for selected longitudinal health-related outcomes, according to a combined socio-economic score (comparing the notionally most to the notionally least deprived, using the relative index of inequality). (sample sizes correspond to Table 4, shown on the log scale)
Figure 4: Relative risk ratios (RRRs) for selected longitudinal health-related outcomes, according to a combined socio-economic score (comparing the notionally most to the notionally least deprived, using the relative index of inequality). (sample sizes correspond to Table 4, shown on the log scale)

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