Peer-reviewed article
Relationship of parental caregiving and child labour with developmental problems and mental health in children in low-to-middle-income countries using the socioecological resilience model.
Lin K, M KAH, Thapa S, Allan J, Buys N et al. ·
Summary
Written by AI, not yet AICS's view · claude-haiku-4-5-20251001This study analysed data from over 250,000 children across low-to-middle-income countries to understand how child labour and poor parenting practices affect child development and mental health. The researchers found that anxiety, depression, and socio-emotional difficulties were most common in the poorest countries, and were linked to poor caregiving, child labour, and low maternal education. The study used the socioecological resilience model to show that factors at individual, family, and community levels all influence child well-being. The authors conclude that addressing child development challenges requires a comprehensive approach that tackles poverty, improves education access, strengthens social protection, and promotes better caregiving.
Key points
- Prevalence of anxiety was 30.8%, depression 40.8%, and socio-emotional difficulties (mean score 0.115) were highest in low SDI countries
- Poor physical caregiving, child labour engagement, and low maternal education were significantly associated with higher socio-emotional difficulties, anxiety, and depression
- Significant variations in child labour engagement existed across countries at different economic development levels
- The socioecological resilience model demonstrates that individual, relational, and structural factors across multiple levels influence child development outcomes
- A multifaceted approach addressing poverty, education access, social protection, and caregiving practices is needed
Limitations
This is a cross-sectional analysis and cannot establish causation or the direction of relationships between variables. The study relies on data from Multiple Indicator Cluster Surveys which may have measurement limitations and varying data quality across countries.
Abstract
Background The socioecological resilience (SER) model explains that individual, relational, and structural factors influence child development and mental health. Children in low-to middle-income countries (LMICs) are affected by multiple risk factors on different SER levels. This cross-sectional study aimed assess the influence of experience of child labour and poor caregiving practices on child development in LMICs using the SER model. Method Data regarding child development, caregiving practices, and child labour collected through Multiple Indicator Cluster Surveys (MICS) by UNICEF were analysed. Differences in prevalence of developmental delays, mental illness, child labour, and poor caregiving practices were compared across countries and across different sociodemographic index (SDI) levels. Multi-level modelling was used to determine factors associated with developmental difficulties, and anxiety, and depression symptoms in children. Results 251,681 children were included in the analysis. Significant variations in child labour engagement existed across low to upper-middle SDI countries. Prevalence of anxiety (30.8%), depression (40.8%) and socio-emotional difficulties (mean score = 0.115) were highest in low SDI countries. Poor physical caregiving, engagement in child labour, and low maternal education was significantly associated with higher socio-emotional difficulties, anxiety, and depression. Conclusion To address the complex interplay between extreme poverty and adverse child health outcomes across low SDI countries, a multifaceted approach aimed at alleviating poverty, improving access to education, strengthening social protection systems, and promoting effective caregiving practices are required.