Magnitude of income-related disparities in adverse perinatal outcomes

In Nova Scotia, Canada, despite all families having access to essential health services through a publicly funded insurance program, lower-income mothers have worse perinatal outcomes than mothers with higher income [1]. Socioeconomic position (SEP) is a multi-dimensional characteristic with an indirect, complex relationship to perinatal health [1‐5], and past studies indicate that multiple indicators should be considered when measuring inequalities [6, 7].

Effects associated with SEP may reflect unique and inter-related mechanisms at multiple levels. This includes maternal and family characteristics associated with low income that mediate effects on adverse perinatal outcomes (e.g., whether or not a mother uses tobacco products during pregnancy), as well as macrosocial factors (i.e., economic, political and social) that are better measured at the group or environmental level (e.g., in relation to the availability of prenatal care) [8‐18]. These mechanisms may also vary by other contextual factors. In particular, lower SEP can mean different things for families living in urban and rural settings [19]; for example, in Nova Scotia there is poorer access to specialized health services in rural setting [20]. Family composition may also change the implications of lower SEP since female-headed lone parent families are often young [21] and have low income [22, 23], so it is likely harder to manage stressors than comparable two-parent families [24‐29]. Identifying what dimensions of SEP mean at different levels and in different contexts can facilitate interventions [30]; yet, few studies have compared the consistency in associations across measures of SEP for perinatal outcomes, and across various contexts.

Most investigations into income disparities and perinatal outcomes have assumed that the effects of income on health are direct. As a result, these analyses often control for risk factors as potential confounders that may actually lie on the causal pathways that relate income level to adverse perinatal outcomes. By controlling for a partly or fully mediating factor, this approach leads to underestimates of the magnitude of income-related disparities. For example, mothers of lower SEP are more likely to smoke tobacco products than higher SEP mothers in Nova Scotia [31], and some findings suggest that lower SEP mothers may also be more likely to continue smoking during pregnancy due to the the stressfulness of their context for several reasons (e.g., , partly as a maladaptive coping habit [32]. Similarly, property values in Nova Scotia drive lower SEP families in Nova Scotia to live in more polluted environments in [33, 34], so the deprivation level of a neighbourhood could reflect how likely individual are to be exposed to unhealthy environmental conditions [33, 34]. In these examples, family and neighbourhood SEP may increase risk for adverse perinatal outcomes through pathways involving differential exposure to tobacco smoke and air pollution; thus, we argue that such risk factors should correctly be considered mediators of health effects related to income, rather than confounders.

This analysis asks: 1) “On which disease processes, in which subpopulations, and at what geographic levels can socioeconomic inequalities in perinatal health be demonstrated in Nova Scotia?”; and 2) “Do different indicators of SEP demonstrate varying magnitudes of inequalities?” We examined the relationship between several indicators of SEP at the household and neighborhood levels and adverse perinatal outcomes among singleton births in Nova Scotia between 1988 and 2003 using a population-based observational study of the SEP in the year of delivery and birth outcomes up to one year of life. Lastly, we examined whether income disparities varied across families in urban and rural settings, and in female-headed lone-parent families versus two-parent families. This analysis treats family income-related variables as proxies for SEP and assumes that other maternal risk factors for perinatal health may plausibly lie downstream of income on common causal pathways that shape the development and constraint of maternal health behaviours and exposures to environmental toxins.

We sought to explore the relationship between SEP, measured using different indicators at the family and neighborhood levels, and perinatal outcomes in this population-based sample that was linked to a rich set of indicators on income and census data. Our findings suggest that the income-related indicators did not always have consistent patterns of association with the perinatal outcomes, and in some instances, such as for spontaneous preterm birth, had contradictory findings. Both individual level income and neighborhood level deprivation, when considered together, were significant predictors for most of the perinatal outcomes we examined.

For all outcomes examined in this study, there were consistent, nearly identical patterns for total family income after tax and before tax with all perinatal outcomes. The other individual-level SEP variables did not always have relationships to the outcomes that mirrored that of the total family income variables. For example, having a medium proportion of income from government transfers was risk-protective for spontaneous preterm birth and for postneonatal death; whereas lower income based on other variables conferred higher risk for these outcomes. While most income variables likely reflect the resources available to the families, a variable like proportion of income from government transfers did not take into account the absolute family income levels which may, in part, be contributing to the different patterns for SGA, spontaneous preterm and postneonatal death.

While the addition of neighborhood deprivation to the regression model did not substantively change the gradient for total family income (after tax) for any outcomes, the patterns of association were not always consistent across the individual and neighborhood level variables. For example, risk for perinatal death and iatrogenic preterm birth was substantially lower for those with lower total family income compared to those in the highest income category, while higher levels of neighborhood deprivation were associated with elevated risk for these outcomes. Such findings suggest that the two indicators of SEP may be operating through different pathways, at least for those outcomes. Neighborhood deprivation likely measured a wide range of social variables that went beyond income levels of neighborhood residents (e.g., see [30, 42]). Further research is needed to delineate the relevant pathways and mechanisms involved in these discordant findings.

Our findings also illustrated how family composition and level of urbanicity modify the associations between SEP and the some of the outcomes. The patterns of association between SEP and LGA, spontaneous preterm birth and perinatal death varied depending on family composition or urbanicity. This too suggests that the importance of certain pathways and mechanisms may vary by context.

These findings are from a Canadian setting with single payer universal health coverage for all essential healthcare services, so we expect there to be some generalizability for other settings with universal coverage like the United Kingdom. Whereas in other settings like the United States, where the quality of antenatal care may be commensurate with the level of family income, we might expect income to be a stronger determinant of perinatal outcomes, and so we might expect inequalities to be of a larger magnitude than we report.

There were limitations of our data and approach. First, not all birth records were linked to data on the income variables; linkage was successful in 81.3% of records [43]. Thus, the extent to which the failure to link may have contributed to an over or underestimate of the associations is not known. Also, some families were missing data on SGA (2%), LGA (2%) and preterm birth outcomes (iatrogenic, 5%; spontaneous 4%). Families excluded from the analysis here were less likely to be of higher SEP or to reside in lower deprivation neighbourhoods. For all outcomes, the difference in income and deprivation composition within strata was less than 7%, and usually less than 4% (data not shown). It is not possible to predict the direction of bias; however, given the small size of these differences, any impact on the magnitudes reported here are likely to be minimal.

Second, the use of cross sectional data meant that data on total family income (after tax) were for the same year as the year of birth, raising questions about the direction of the association; however, for studies of pregnancy it is unlikely that the outcome influenced the levels of income for the family. Finally, while SEP may reflect a range of causal mechanisms at the group level in health research, including the level of material deprivation, income inequality, social capital and racial segregation (e.g., [42]), we only assessed the magnitude of inequalities relative to a measure of material deprivation in the neighbourhood in this study.

Our main conclusions are that the choice of income indicator may influence the magnitude and pattern of inequality observed. In some instances, such as for iatrogenic and spontaneous preterm birth, some of the indicators of individual level SEP may contradict each other in terms of whether higher income is risk inducing or protective for the outcome. Thus, choosing indicators of SEP that are consistent with the purpose of the investigation is critical for the examination of inequities in perinatal health. Also, because the patterns of inequities may vary by context--family composition or urbanicity--examination of effect modification should be a priority in future studies. As with all analyses that demonstrate gaps and inequalities, a critical next step is to investigate why these inequalities exist and what factors, with intervention potential, can be identified so that effective programs and policies can be designed and implemented. This is but a first step in that larger research agenda to uncover strategies to address to continue the trend of reducing the gap in in perinatal health in Canada [44].