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Association Between Neighborhood Deprivation and Gestational Diabetes: A Systematic Review and Meta-Analysis
Arathi P Rao1, Mahalaqua Nazli Khatib2, Lakshmi Thangavelu3
1Department of Health Policy, Prasanna School of Public Health, Manipal Academy of Higher Education, Manipal, India.
Abstract:
Gestational diabetes mellitus (GDM) is a major global health concern, affecting maternal and child health. Although genetic predispositions and individual medical histories are well-recognized risk factors, emerging research suggests a significant impact of external factors like neighborhood socioeconomic characteristics. This study systematically reviews and meta-analyzes the association between neighborhood deprivation and GDM incidence. We searched multiple databases up to January 10, 2024, for studies linking neighborhood deprivation with GDM. Eligible studies were selected based on predefined criteria, with the Nested Knowledge software assisting in screening and data extraction. Quality assessment utilized the Newcastle-Ottawa Scale, and a random-effects model computed the pooled relative risk (RR) using R software, version 4.3. The review included six studies varying significantly in design, sample sizes, and deprivation assessment methods. The meta-analysis combined data from five studies totaling 15 827 participants from the least deprived and 18 147 from the most deprived neighborhoods, yielding an RR of 0.909, indicating a non-significant lower risk of GDM in more deprived groups. A substantial heterogeneity (I2 = 70%) was observed, and sensitivity analysis confirmed the robustness of these findings. This analysis suggests that living in a deprived neighborhood does not significantly alter GDM risk, underscoring the necessity for further research to refine public health strategies and interventions. The variability in neighborhood deprivation definitions and potential unaccounted confounding factors highlight the need for comprehensive studies, especially from low-income and middle-income countries, to elucidate the intricate links between socioeconomic factors and GDM.
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