Modelling Maternal Depression: An Agent-Based Model to Examine the Complex Relationship between Relative Income and Depression

A Longitudinal Study of Income Inequality and Mental Health Among Canadian Secondary School Students: Results From the Cannabis, Obesity, Mental Health, Physical Activity, Alcohol, Smoking, and Sedentary Behavior Study (2016-2019)

PURPOSE

Depression and anxiety among adolescents are major public health concerns. Findings indicate that income inequality was associated with increased risk for depression and anxiety among adolescents; however, this has not been tested longitudinally. We aim to quantify the longitudinal association between income inequality and depression and anxiety among Canadian adolescents.

METHODS

We used longitudinal data on 21,141 students from three waves (2016/17-2018/19) of the Cannabis, Obesity, Mental health, Physical activity, Alcohol, Smoking, and Sedentary behavior (COMPASS) school-based study. Multilevel modeling was used to assess the association between census division (CD)-level income inequality and depressive and anxiety symptoms and odds for depression and anxiety over time.

RESULTS

Across CDs, the mean Gini coefficient was 0.37 (range: 0.30, 0.46). Attending schools in CDs with higher levels of income inequality was associated with higher depressive scores (ß = 0.08; 95% confidence interval [CI] = 0.02, 0.14) and an increased odds for depression (odds ratio = 1.55, 95% CI = 1.06, 2.28) over time. Income inequality was not significantly associated with anxiety symptoms or experiencing anxiety over time. Additional analyses showed that income inequality was associated with higher depressive scores among females (ß = 0.10; 95% CI = 0.01, 0.18) and males (ß = 0.08, 95% CI = 0.01, 0.15) and for anxiety scores among females (ß = 0.13, 95% CI = 0.04, 0.22), but not among males (ß = -0.01, 95% CI = -0.09, 0.06).

DISCUSSION

Findings from this study indicated that income inequality is associated with depression over time among adolescents. This study highlights key points of intervention for the prevention of mental illness in adolescents.

Maternal Metabolites Indicative of Mental Health Status during Pregnancy

Approximately 25% of individuals report poor mental health during their pregnancy or postpartum period, which may impact fetal neurodevelopment, birth outcomes, and maternal behaviors. In the present study, maternal serum samples were collected from pregnancies at 28-32 weeks gestation from the All Our Families (Alberta, Canada) cohort and assessed using nuclear magnetic resonance spectroscopy (¹H-NMR) and inductively coupled plasma-mass spectrometry (ICP-MS). Individuals with poor mental health at 34-36 weeks gestation were age-matched with mentally healthy pregnant controls. Metabolites were examined against validated self-reported mental health questionnaires for associations with depressive symptoms (Edinburgh Perinatal Depression Scale) and anxiety symptoms (Spielberger State-Trait Anxiety Inventory). ¹H-NMR metabolites were identified for depression (alanine, leucine, valine, methionine, phenylalanine, glucose, lactate, 3-hydroxybutyrate, and pyruvate) and anxiety (3-hydroxybutyrate). For ICP-MS, antimony and zinc were significant for depression and anxiety, respectively. Upon false discovery rate (FDR) correction at 10%, five ¹H-NMR metabolites (alanine, leucine, lactate, glucose, and phenylalanine) for depression remained significantly increased. Although results warrant further validation, the identified metabolites may serve as a predictive tool for assessing mental health during pregnancy as earlier identification has the potential to aid intervention and management of poor mental health symptomology, thus avoiding harmful consequences to both mother and offspring.

Agent-Based Modelling of Health Inequalities following the Complexity Turn in Public Health: A Systematic Review

There is an increasing focus on the role of complexity in public health and public policy fields which has brought about a methodological shift towards computational approaches. This includes agent-based modelling (ABM), a method used to simulate individuals, their behaviour and interactions with each other, and their social and physical environment. This paper aims to systematically review the use of ABM to simulate the generation or persistence of health inequalities. PubMed, Scopus, and Web of Science (1 January 2013-15 November 2022) were searched, supplemented with manual reference list searching. Twenty studies were included; fourteen of them described models of health behaviours, most commonly relating to diet (n = 7). Six models explored health outcomes, e.g., morbidity, mortality, and depression. All of the included models involved heterogeneous agents and were dynamic, with agents making decisions, growing older, and/or becoming exposed to different health risks. Eighteen models represented physical space and in eleven models, agents interacted with other agents through social networks. ABM is increasingly contributing to our understanding of the socioeconomic inequalities in health. However, to date, the majority of these models focus on the differences in health behaviours. Future research should attempt to investigate the social and economic drivers of health inequalities using ABM.

Prevalence of Congenital Anomaly and Its Relationship with Maternal Education and Age According to Local Development in the Extreme South of Brazil

Congenital anomalies (CA) contribute to disabilities and health conditions throughout life. Furthermore, they can cause emotional distress to the mothers and children, who may also experience limitations in individual and social development. This study investigated the prevalence of CA and the relationship with maternal education and age according to local development in the extreme south of Brazil. This is a retrospective observational study with birth data from the Live Birth Information System from 2000 to 2017. The association between age and maternal education with the presence of CA was verified using multiple Poisson regression for robust variances in models adjusted for those variables with a preliminary significant association. A total of 5131 (1.5%) had some CA identified at birth between 2000 and 2017. Only advanced age (≥36 years) was associated with CA regardless of macro-region development (p ≤ 0.001). The highest risk was observed in regions with medium development (RR = 1.60; 95% CI 1.30−1.97). Maternal education (<8 years of study) was associated with CA only in mothers from macro-regions with very high development (RR = 1.27; 95% CI 1.03−1.54). These analyses confirmed that women of advanced age are at greater risk of having children with a CA regardless of maternal education and local development, but social characteristics can also have an influence, as regions with higher development had lower prevalence of CA.