ArticleBMC public health2026
Maternal and child health challenges during and after flooding: a qualitative study in Makassar, Indonesia.
Article in BMC public health, 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
11 authors.
Funding
Abstract
backgroundFlooding is a recurrent and worsening public health threat in Indonesia, disproportionately affecting women and children in low-elevation urban areas. Pregnant and postpartum women in Indonesia experience unique physical and emotional burdens during floods, yet their lived experiences remain underexplored. Understanding how mothers adapt to recurrent flooding is critical for developing context-relevant interventions to improve maternal and child outcomes. This study aimed to explore (1) how recurrent flooding shapes the daily lived experiences and caregiving responsibilities of pregnant and postpartum women, (2) how flooding affects access to food, water, and healthcare, and (3) what community-informed interventions mothers identify as most impactful.
methodsWe conducted a qualitative descriptive study using in-depth interviews with 20 women who gave birth within the past three years and reported prior flood experience in the Tallo District of Makassar. They were randomly selected from a mother-child cohort based out of Hasanuddin University. Sample size was determined by data saturation. Interviews were transcribed and translated from Makassarese into English. They were then coded and analyzed thematically using MAXQDA.
resultsFlooding occurs annually, with severity differing between years. Mothers bore primary responsibility for lifting furniture, protecting children, and cleaning contaminated homes. Recurrent floods disrupted food preparation and reduced meal variety. Floodwater contaminated government-owned piped water and borehole well water. Toilets overflowed and bathing was often skipped to conserve clean water. Prenatal and routine health visits were frequently postponed until floodwaters receded; however, many mothers reported wading through deep water to attend scheduled appointments. The distress of these burdens was worsened by lost income from disrupted work. Mothers identified food distribution, drain maintenance, and improved housing infrastructure as the most impactful interventions.
conclusionsThese findings provide translatable insights for flood-prone coastal urban communities. Educating households about water preparation and implementing timely food staple distribution through existing community networks can reduce illness and hunger during flooding. Supporting neighborhood-based drainage maintenance and subsidizing incremental home elevation with locally available materials can address the burdens placed on mothers during flooding.
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.