Introduction
Adverse childhood experiences (ACEs), which include forms of abuse, neglect, and household dysfunction (Felitti et al.
1998), have been shown to influence academic achievement, health behaviours (e.g. smoking, alcohol, and drug use), and various health conditions (e.g. diabetes, depression, heart disease) throughout the life course (Cambois and Jusot
2011; Nandi et al.
2012). Setting the stage for lifelong health and social outcomes, (Nurius et al.
2015) ACEs merit attention both from the moral perspectives of child welfare and health justice (Venkatapuram
2013), and from perspectives of life course health promotion and societal prosperity (Schady
2015).
On average, children living in low-income households tend to experience a greater number of ACEs than their higher-income peers (Wade et al.
2014). In Scotland, where ACE prevalence is high [i.e. 65% of children experience one or more ACEs by the age of 8 years (Marryat and Frank
2019)], 53% of children in the highest income households are ACE-free by age eight, compared to 8% in the lowest income households (Marryat and Frank
2019). These inequities beg the question of whether the relationship between low-income and ACE incidence can be mitigated. A growing body of theoretical and empirical work suggests that the experience of low-income, and its association with health outcomes, can vary according to the relative generosity of state investment in benefits, social policies, and resources. For example, the generosity of unemployment benefits is known to influence psychological distress (O’Campo et al.
2015) and self-reported health (Bambra and Eikemo
2009) among the unemployed. It is possible, therefore, that the association between low-income and child adversity could be mitigated by protective social, economic, or infrastructural resources.
The assumed modifiability of poverty experience—in terms of its impact on childhood adversity—underpins many of the UK and Scotland’s policy recommendations for investment in early childhood development, as a means of reducing health inequities across the life course. Reports published between 1980 and 2014 (Acheson
1988; Black et al.
1980; Marmot et al.
2010; Scottish Government
2014) all discuss promoting access to adequate and affordable housing, transportation, childcare services, and recreational opportunities to ensure children are assured the “best start in life” (Scottish Government
2014). These features of local environments have been identified as upstream causes of health inequalities, and interventions on the latter domains are believed to be among the most effective at reducing life course health inequities (Smith and Kandlik Eltanani
2015).
The objectives of this study were therefore to assess whether certain community resources (namely, self-reported access to housing, local public parks or play parks, childcare services, transportation services, or formal, in-person pre- or perinatal counselling—specifically for breastfeeding) are associated with lower ACE incidence in households above and below the poverty line and to assess the extent to which income inequalities in 8-year cumulative ACE incidence could be eliminated if all had access to these community resources.
Discussion
In a population-based sample of Scottish children, we found that access to housing, transportation, and breastfeeding education were associated with lower ACE incidence among households above the poverty line. Below the poverty line, only transportation access was associated with lower ACE incidence. We estimated that if access to transportation was held fixed across the entire population, approximately 21% of the income-based inequality in cumulative incidence of 3 or more ACEs could be eliminated.
Our finding of the protective role of transportation is in line with those of previous studies. Transportation resources can mitigate the association between distance to health or social services and service utilization (Whetten et al.
2006) and enable families in accessing employment, food, and leisure facilities (Markovich and Lucas
2011). That access to housing and breastfeeding counselling was also associated with lower ACE incidence—at least among higher-income households—is also consistent with observations in the extant literature. Housing is known to influence general family well-being by shaping residents’ mental health, sense of self-worth, and offering a stable environment from which to pursue training, employment, and parenting responsibilities (Bratt
2002). Breastfeeding resources may represent a proxy for the density of other protective health resources, such as access to nurses. Perinatal nurse visits are known to be beneficial for mothers’ health and well-being (Olds et al.
2002).
Several theories may explain the observed association between transportation and lower ACE incidence. Transportation may help parents’ to gain a sense of control over their lives—offering opportunities for decisional latitude regarding work and daily activities (Syme
1996). A second theory is that inadequate transportation is itself a stressor for low-income families. Walking as a compulsory mode of transport in disadvantaged areas is often accompanied by physical fatigue and psychosocial stress (Bostock
2001), which may lead to greater household dysfunction. Third, transportation resources allow families to access a wealth of protective resources beyond their local area (Bostock
2001). Lastly, it may be that transportation resources enable parents—specifically mothers—to remove themselves and their children from adverse situations, thus protecting their children from ACEs (Bambra
2007). These theorized mechanisms merit attention in future work.
In contrast, there are several potential explanations why statistically significant associations between parks, childcare, and ACE incidence were not observed. First, it may be that park proximity does not guarantee park use or quality (i.e. aesthetics, safety, vegetation, and equipment availability). Parks in low-income areas in the UK tend to be of lesser quality than those in higher-income areas (Fairburn et al.
2005). Similarly, childcare may not be protective if its quality is low [a well-documented issue for poor Scottish families (Siraj and Kingston
2015)] or if the parents cannot afford a critical “dose” of childcare [i.e. several half-days weekly from ages 2–4 years (Geddes et al.
2011)]. Second, it may be that these two factors play a more important protective role later in the child’s life than at the time at which they were measured (i.e. within the first year of life). Future studies on these more nuanced elements are recommended.
This study requires replication in other settings before strong recommendations can be made. If other studies confirm protective effects of similar service features, specifically for ACE prevention, intervening on community-level resource availability could represent a valuable interim measure to mitigate the association between childhood poverty on ACEs. While obviously second best to the complete elimination of poverty, local measures to promote resources for families may hold promise in settings lacking the political will for formal wealth redistribution.
These study’s findings are bound by certain limitations. First, baseline marital status was not included as a covariate (although separation is included as an ACE) due to its collinearity with the dichotomized exposure measure of household income. Approximately, 80% of single mothers were below the poverty line. This exclusion and other unmeasured factors may have contributed to residual confounding in the study. Factors that were not included in the study, primarily due to limitations in data availability, were paternal characteristics, parents’ own histories of adverse childhood experiences (i.e. as an indication of generational trauma) or behaviours (e.g. life course use of substances, incarceration, relationship status, etc.). Though sensitivity analyses suggest that the present study’s estimates are likely robust to unmeasured confounding, we recommend that, if available, future studies adopt a life course exposure perspective and consider these additional sources of bias as well as potential time-varying confounding. A second limitation pertains to the ACEs measured. Though we attempted to maximize the comparability of the ACEs measured in this study with those of previous studies (Felitti et al.
1998), missing in this study are ACEs of material neglect, sexual abuse, and emotional abuse (Felitti et al.
1998), as well as ACEs that might occur after age 8. These exclusions may lead to potential underestimation of childhood ACE incidence in the Scottish population. ACE incidence estimates may also be affected by higher observed attrition rates in the GUS cohort among younger mothers and households living in deprived areas (Marryat and Frank
2019). In this study, we sought to minimize this potential source of bias using the GUS longitudinal survey weights (Anderson et al.
2007). Furthermore, though available ACE measures were compiled here to form one single outcome measure of cumulative ACE incidence—in order to both accommodate data availability and account for the observation of the detrimental impact of concurrent adversities on health and social outcomes (Hughes et al.
2017)—this outcome operationalization can also lead to the interpretation of the moral or sociopolitical equivalency of each experience. The potential stigmatizing effect of this grouping of experiences is a limitation of both this study and its predecessors and may be a relevant topic of future enquiry. A third limitation is the potential measurement bias associated with self-reported data. Previous studies have noted differential self-reporting of neighbourhood characteristics across socioeconomic groups, wherein populations living in more deprived contexts under-report deprivation experiences, in part out of a need for self-preservation (Kawachi and Berkman
2003). It is possible, therefore, that income inequalities in resource access may have been underestimated in this study. To address these concerns, future studies may benefit from using multi-item indices to measure resource access (Echeverria et al.
2004). Lastly, the IPW-weighted models used rely on several operational assumptions. Where possible, we attempted to assess the potential sensitivity of findings to violations of these assumptions. Importantly, our findings appear robust to potential unmeasured confounding, and violations of practical positivity.
In conclusion, this is, to our knowledge, the first study to explore how community resources may mitigate the association between household poverty and cumulative ACE incidence. Of the resources assessed, only transportation was associated with lower ACE incidence in households above and below the poverty line. We estimated that a substantial portion (21%) of the income-based inequality in the 8-year cumulative incidence of three or more ACEs could be eliminated if all had access to adequate transportation. Though our findings require replication, they offer an initial body of evidence that can inform interventions to prevent both ACE incidence and income disparities in ACE incidence.
Acknowledgements
At the time this work was conducted, AB was supported financially by the Canadian Institutes of Health Research (CIHR) Michael Smith Travel Supplement and by a CIHR Vanier Doctoral Scholarship., and LM was is supported by the Farr Institute @ Scotland, which is supported by a 10-funder consortium: Arthritis Research UK, the British Heart Foundation, Cancer Research UK, the Economic and Social Research Council, the Engineering and Physical Sciences Research Council, the Medical Research Council (MRC), the National Institute of Health Research, the National Institute for Social Care and Health Research (Welsh Assembly Government), and the Chief Scientist Office (Scottish Government Health Directorates), (MRC Grant No: MR/K007017/1). LM sat within, and JF was supported by, the core grant to Scottish Collaboration for Public Health Research and Policy (SCPHRP) from the MRC, with half that support from the Scottish Chief Scientist Office (MR/K023209/1).
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