Multilevel interactions between family and neighbourhood socioeconomic indices in childhood and later risks of self-harm and violent criminality in Denmark: a national cohort study

Ejlskov, Linda; Antonsen, Steen; Wulff, Jesper; Agerbo, Esben; Plana‐Ripoll, Oleguer; Sabel, Clive E.; Fan, Chun; Thompson, Wesley K.; Mok, Pearl L. H.; Pedersen, Carsten Bøcker; Webb, Roger

doi:10.1016/s2468-2667(22)00292-4

Cited by 11 publications

(4 citation statements)

References 36 publications

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“…55 Our SDOH findings reflect distinct racial and ethnic differences. White children were overrepresented in affluent and high-stigma environments, whereas Black and Hispanic children were overrepresented in socioeconomically deprived areas, derived from discriminatory housing policies and resource accessibility 56 and reflecting systemic racism and socioeconomic marginalization that restrict Black and Hispanic children's access to opportunities. 57 The higher rates of crime, low education, and dense populations in areas populated by Hispanic and Black residents may influence the mental, cognitive, and physical health of these children, as suggested by prior studies.…”

Section: Discussionmentioning

confidence: 99%

Patterns of Social Determinants of Health and Child Mental Health, Cognition, and Physical Health

Xiao,

Mann,

Chow

et al. 2023

JAMA Pediatr

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ImportanceSocial determinants of health (SDOH) influence child health. However, most previous studies have used individual, small-set, or cherry-picked SDOH variables without examining unbiased computed SDOH patterns from high-dimensional SDOH factors to investigate associations with child mental health, cognition, and physical health.ObjectiveTo identify SDOH patterns and estimate their associations with children’s mental, cognitive, and physical developmental outcomes.Design, Setting, and ParticipantsThis population-based cohort study included children aged 9 to 10 years at baseline and their caregivers enrolled in the Adolescent Brain Cognitive Development (ABCD) Study between 2016 and 2021. The ABCD Study includes 21 sites across 17 states.ExposuresEighty-four neighborhood-level, geocoded variables spanning 7 domains of SDOH, including bias, education, physical and health infrastructure, natural environment, socioeconomic status, social context, and crime and drugs, were studied. Hierarchical agglomerative clustering was used to identify SDOH patterns.Main Outcomes and MeasuresAssociations of SDOH and child mental health (internalizing and externalizing behaviors) and suicidal behaviors, cognitive function (performance, reading skills), and physical health (body mass index, exercise, sleep disorder) were estimated using mixed-effects linear and logistic regression models.ResultsAmong 10 504 children (baseline median [SD] age, 9.9 [0.6] years; 5510 boys [52.5%] and 4994 girls [47.5%]; 229 Asian [2.2%], 1468 Black [14.0%], 2128 Hispanic [20.3%], 5565 White [53.0%], and 1108 multiracial [10.5%]), 4 SDOH patterns were identified: pattern 1, affluence (4078 children [38.8%]); pattern 2, high-stigma environment (2661 children [25.3%]); pattern 3, high socioeconomic deprivation (2653 children [25.3%]); and pattern 4, high crime and drug sales, low education, and high population density (1112 children [10.6%]). The SDOH patterns were distinctly associated with child health outcomes. Children exposed to socioeconomic deprivation (SDOH pattern 3) showed the worst health profiles, manifesting more internalizing (β = 0.75; 95% CI, 0.14-1.37) and externalizing (β = 1.43; 95% CI, 0.83-2.02) mental health problems, lower cognitive performance, and adverse physical health.ConclusionsThis study shows that an unbiased quantitative analysis of multidimensional SDOH can permit the determination of how SDOH patterns are associated with child developmental outcomes. Children exposed to socioeconomic deprivation showed the worst outcomes relative to other SDOH categories. These findings suggest the need to determine whether improvement in socioeconomic conditions can enhance child developmental outcomes.

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Section: Discussionmentioning

confidence: 99%

Patterns of Social Determinants of Health and Child Mental Health, Cognition, and Physical Health

Xiao,

Mann,

Chow

et al. 2023

JAMA Pediatr

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“…The protocol for this study was pre-registered before any analyses were commenced. 18 We designed a population-based cohort study including all individuals who were: i) born in Denmark between January 1 st , 1986 and December 31 st , 1996, ii) alive and residing in Denmark on 15 th birthday, and iii) possible to link to both parents to enable identification of full siblings. The Danish Civil Registration System 19,20 maintains continuously updated information such as sex, date of birth, emigration, and death of all residents.…”

Section: Methodsmentioning

confidence: 99%

Interpretational fallacies in sibling comparison designs with social exposures: A case study of childhood income and mental disorders

Ejlskov

Esen

Hakulinen

et al. 2023

Preprint

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Background In previous studies, null results from sibling comparison designs have been used to infer that no causal association exists between childhood family income and subsequent risk of mental disorders. The aim of our study is to replicate the findings from previous studies and propose three alternative explanations based on i) variability in income and mental health between siblings, ii) life course models, and iii) detailed descriptive statistics. Methods We followed a nationwide Danish cohort born from 1986 to 1996 (n = 643,814, including 404,179 siblings) from age 15 until diagnosis of severe mental disorders or censoring. Adjusted hazard ratios (aHR) were estimated between childhood family income and subsequent mental disorders, accompanied by comprehensive descriptive statistics and triangulation analyses that help in interpreting the findings. Results We observed an association between a $15,000 increase in family income and severe mental disorders (0.78; 0.76-0.81), but the sibling comparison design showed null results (1.02; 0.94-1.11). Siblings were typically born three years apart, with a difference in monthly average income at age 14 of $496 (interquartile range: $150-$641). A pseudo-sibling cohort also indicated null results (0.93; 0.85-1.01), although siblings were not family members. Family income measured yearly demonstrated comparable estimates across ages 1-14 (from 0.67 to 0.82). Conclusion Our investigation suggests that the null associations between childhood income and mental health estimated through sibling comparison designs may be explained by the fact that siblings are close together in age and residing within the same family income environment with only minor income fluctuations. Additionally, a sibling comparison design is useful to test a critical/sensitive period, but our analyses suggest that no age posits a critical risk age for this research question. This raises caution on the current practice of relying on sibling comparison designs to estimate the association between childhood income and mental health.

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“…The multifaceted nature of these disparities, cutting across diverse demographic and socio-economic strata, underscores the critical need for comprehensive investigations [2]. Beyond merely reflecting disparities in health outcomes, these inequalities highlight systemic and structural issues contributing to differential health experiences among various population groups [3]. Addressing these disparities is crucial, not only for promoting individual well-being but also for fostering a more equitable and just healthcare system [4].…”

Section: Introductionmentioning

confidence: 99%

“…Variables with missing values (%): Social class (4.5), Chronic conditions (0.1), Pain (0.1), BMI (5.3) 2. Based on occupation 3. Chronic or long-term health condition or problem 4.…”

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confidence: 99%

Exploring the Influence of Social Class and Sex on Self-Reported Health: Insights from a Representative Population-Based Study

Prieto

2024

Life

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This study investigates the intricate interplay between social class, sex, and self-reported health (SRH) using data from the European Health Survey of Spain 2020 (EESE2020). Employing a cross-sectional design and a representative sample of 22,072 individuals, the analysis explores the persistence of disparities after adjusting for covariates, focusing on health-related variables. The study employs logistic regression models and directed acyclic graphs (DAGs) to delineate the direct effects of social class and sex on SRH, identifying a minimum adjustment set to control for confounding variables. Results reveal a gradient effect of social class on SRH, emphasizing the enduring impact of socioeconomic factors. Sex-based disparities in SRH diminish after considering additional health-related variables, highlighting the importance of a holistic approach. DAGs serve as transparent tools in disentangling complex relationships, guiding the identification of essential covariates. The study concludes that addressing health inequalities requires comprehensive strategies considering both individual health behaviours and socio-economic contexts. While recognizing limitations, such as the cross-sectional design, the findings contribute to a nuanced understanding of health disparities, informing evidence-based interventions and policies for a more equitable healthcare system.

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Multilevel interactions between family and neighbourhood socioeconomic indices in childhood and later risks of self-harm and violent criminality in Denmark: a national cohort study

Cited by 11 publications

References 36 publications

Patterns of Social Determinants of Health and Child Mental Health, Cognition, and Physical Health

Patterns of Social Determinants of Health and Child Mental Health, Cognition, and Physical Health

Interpretational fallacies in sibling comparison designs with social exposures: A case study of childhood income and mental disorders

Exploring the Influence of Social Class and Sex on Self-Reported Health: Insights from a Representative Population-Based Study

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