ArticlePloS one2026
Regional trends and forecasting of under-five child mortality in Bangladesh: A mixed method approach of Functional ANOVA and Bayesian spatiotemporal modeling.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis study aims to estimate historical under-five mortality rates from 1990 to 2022 across the eight divisions of Bangladesh, analyze regional disparities, and forecast under-five mortality rates trends up to 2030 considering both temporal and spatial dynamics.
methodsA cross-sectional study design was employed, utilizing nationally representative data from the Bangladesh Demographic and Health Survey 2022. The study included 64,697 records of children representing births from eligible women with full birth history across the eight divisions of Bangladesh. The dataset spans 33 years, enabling a detailed examination of under-five mortality rates trends at the sub-national level. The analysis included historical under-five mortality rates estimation and Functional ANOVA was conducted to explore regional disparities, while a Bayesian Spatiotemporal model was employed to forecast under-five mortality rates trends up to 2030. The permutation F-test was used to assess the statistical significance of the regional differences.
resultsThe permutation F test conclude that while regional differences in child mortality rates were not globally significant over the entire period from 1990 to 2022, significant disparities did emerge during specific years (early 1990s and late 2010s). Barishal, Rangpur, and Sylhet showed high variability in under-five mortality rates reductions in the early 1990s, while Dhaka and Khulna exhibited more consistent progress. ICAR spatial effects indicate that Sylhet and Rangpur, have slower reductions, highlighting persistent challenges in these areas despite national progress. Additionally, spatiotemporal modeling indicates all divisions in Bangladesh show significant reductions from 1990 to 2022, with Sylhet consistently having the highest rates and Khulna the lowest. Projections indicate a plateauing trend, with most divisions nearing the sustainable development goal target of 25 deaths per 1000 live births by 2030, though Sylhet and Rangpur may require additional interventions.
conclusionsFuture strategies should focus on reinforcing healthcare infrastructure, enhancing maternal and child health services, and reducing socioeconomic inequalities to achieve faster improvements in high-mortality regions. Targeted interventions in these areas are necessary to achieve the SDG target by 2030, thereby improving child health outcomes nationwide.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.