نبذة مختصرة : Competing Interests: Declarations. Ethics approval and consent to participate: The study was approved by The Institutional Review Board of the Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand (IRB 708/63), which followed the Declaration of Helsinki, the Belmont Report, CIOMS Guideline and International Conference on Harmonization in Good Clinical Practice (ICH-GCP). Access to the Thailand live birth registration data of women aged between 15 and 19 years during 2009–2018 was officially permitted by the Strategy and Planning Division of the Office of the Permanent Secretary, Thailand Ministry of Public Health without disclosing their names or personally identifiable information. The researcher used secondary data, the annual number of live births among women 15 to 19 years during 2009–2018, do not contain personally identifiable information (de-identified), and consent forms were exempted by the IRB of the Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand according to Exemption requirements AF 08 − 01/6.0 Reference by 45 CFR 46.101(b), 45 CFR 46.401(b), DOHP 400 − 4.6 “Non-Human Subject/Non-Research Determination”. Consent for publication: Not Applicable. Competing interests: The authors declare no competing interests.
Background: To meet indicator 3.7.2 in the Sustainable Development Goals (SDGs), Thailand must reduce the adolescent birth rate (ABR) to below 15 per 1,000 women aged 15-19 years by 2027, down from 20.9 per 1,000 in 2023.
Purpose: This study aims to describe ABRs geographically, identify hot and cold spots as well as spatial outliers, and determine the association between ABRs and spatial contextual factors at the district level in Thailand from 2009 to 2018.
Methods: Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) were employed to examine the spatial patterns of ABRs and the association between ABRs and spatial contextual factors, separately for the 2009-2012 and 2013-2018 periods.
Results: ABRs at the district level in Thailand during both periods were spatially random. The OLS models for both periods satisfied all OLS requirements, with no correlation issues among explanatory variables (VIF < 5.0). During the 2009-2012 period, five variables were significantly associated with an increase in ABRs: income inequality, annual per capita income, monthly per capita expenses, the percentage of female-led households, and the percentage of households led by a single parent. In the 2013-2018 period, variables associated with an increase in ABRs included income inequality, annual per capita income, the percentage of households affected by divorce, the percentage of adolescents who completed only compulsory level education and were unemployed, and the availability of Youth-Friendly Health Services and safe abortion services.
Conclusion: As there is no pronounced geographical variation in ABRs and their contextual determinants, a uniform set of policies and programs targeting the reduction of ABRs could be implemented across all districts in Thailand.
(© 2025. The Author(s).)
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