Peer-reviewed article
Estimation of district-level fertility using age-structured census data and assessment of spatial-socioeconomic differentials in Botswana, 2022.
Monamo TT, Navaneetham K ·
Summary
Written by AI, not yet AICS's view · claude-haiku-4-5-20251001This is a demographic research paper that estimates fertility rates across districts in Botswana using 2022 census data. It compares different statistical methods for calculating fertility and examines how education, child mortality, and socioeconomic factors vary by urban and rural areas. The study finds that urban districts have lower fertility rates while rural districts maintain higher fertility linked to child mortality and lower women's empowerment. While the paper discusses factors affecting fertility, it is not about evaluating interventions to improve child well-being outcomes.
Key points
- National total fertility rate in Botswana ranges between 2.6 and 3.0 children per woman, confirming advanced fertility transition
- Urban districts show below-replacement fertility associated with higher female education and delayed childbearing
- Rural districts maintain higher fertility (3.5-4.5 children per woman) linked to elevated child mortality and lower women's empowerment
- Child survival and age structure emerge as key demographic mechanisms reinforcing spatial fertility inequalities
- Census-based direct estimation methods align closely with indirect and model-based fertility estimation techniques
Limitations
This is a descriptive demographic analysis of fertility patterns, not an evaluation of interventions. It cannot provide evidence on what works to improve child health, education, or other well-being outcomes; it only documents fertility variation and associated demographic and socioeconomic factors.
Abstract
Background Reliable subnational fertility estimates are critical for evidence-based demographic policy and planning. While Botswana's national fertility decline is well documented, less is known about district-level fertility variation and the demographic and socioeconomic mechanisms underlying these patterns. This study aims to: (i) produce district-level fertility estimates using standard direct demographic procedures applied to census data; (ii) assess the consistency of direct estimates with established indirect and model-based fertility estimation techniques; and (iii) examine how women's age structure, child mortality, socioeconomic status, and marital patterns shape spatial fertility differentials across districts. Methods The analysis uses data from the 2022 Botswana Population and Housing Census for women aged 15-49. Direct fertility estimation was conducted through the calculation of age-specific fertility rates (ASFRs) and total fertility rates (TFRs). These estimates were systematically compared with indirect and model-based approaches, including Rele (1967), Hauer et al. (2013), Ponnapalli and Soren (2018), and Hauer and Schmertmann (2020), to assess robustness and internal consistency. Data quality was evaluated using parity distributions and reports of recent births, with attention to potential biases arising from recall error, proxy reporting, and reference-period misclassification. Descriptive demographic analysis was used to assess the influence of age structure, child mortality, women's socioeconomic characteristics, and marital composition on district-level fertility variation. Results Direct and model-based fertility estimates were closely aligned, with national TFR values ranging between 2.6 and 3.0 children per woman, confirming Botswana's advanced stage of fertility transition and the reliability of census-based estimation. However, substantial subnational heterogeneity was observed. Urban districts (e.g., Gaborone, Francistown, Jwaneng) exhibited below-replacement fertility, associated with higher female educational attainment, delayed entry into childbearing, and greater labour market participation. In contrast, predominantly rural districts (e.g., Ngamiland West, Barolong, Central Mahalapye) maintained higher fertility levels (approximately 3.5-4.5), linked to elevated child mortality, lower levels of women's empowerment, and persistent traditional reproductive norms. Districts undergoing socioeconomic transition displayed intermediate fertility profiles. Differences in age structure and child survival emerged as key demographic mechanisms reinforcing spatial fertility inequalities. Conclusion By integrating standard direct demographic techniques with indirect and model-based validation, this study demonstrates the robustness of census data for subnational fertility estimation in Botswana. Persistent spatial and socioeconomic disparities highlight the need for differentiated policy responses: rural districts require intensified investments in child health, female education, and reproductive health services to sustain fertility decline, while urban areas must plan for the social and economic implications of sustained below-replacement fertility. Addressing these divergent trajectories is essential for achieving balanced and equitable demographic development in Botswana.