Evidence map›Paper›PMID 38512936›Full record

ArticlePloS one2024

Natural disasters, livelihood, and healthcare challenges of the people of a riverine island in Bangladesh: A mixed-method exploration.

Ahmed Hossain, Anika Tasneem Chowdhury, Masum Mahbub, Mahmuda Khan, Taifur Rahman, Azaz Bin Sharif, Heba Hijazi, Mohamad Alameddine

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
2.5field-weighted citation impact, top 11% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Pooled it
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  3. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 4 countries.

Ahmed HossainCollege of Health Sciences, University of Sharjah, Sharjah, United Arab Emirates.ORCID 0000-0003-4575-1273
Anika Tasneem ChowdhuryDepartment of Public Health, North South University, Dhaka, Bangladesh.ORCID 0000-0002-5035-2368
Masum MahbubHuman Concern USA, Carmel, Indiana, United States of America.
Mahmuda KhanHuman Concern USA, Carmel, Indiana, United States of America.
Taifur RahmanDepartment of Public Health, North South University, Dhaka, Bangladesh.
Azaz Bin SharifDepartment of Public Health, North South University, Dhaka, Bangladesh.ORCID 0000-0002-9929-1236
Heba HijaziHuman Concern USA, Carmel, Indiana, United States of America.
Mohamad AlameddineHuman Concern USA, Carmel, Indiana, United States of America.
Concern Worldwide US · USNorth South University · BD

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBangladesh's islands, because of their geographical location, frequently encounter crises like floods and river erosion, which pose significant threats to the residents' well-being and livelihoods. To delve into the effects of these disasters on livelihood and healthcare challenges, a mixed-method study was undertaken in a riverine-island near a major river of Bangladesh. METHODOLOGY: Between February 15th and February 28th, 2023, a cross-sectional study was conducted on an island in Bangladesh. The quantitative method involved conducting a survey of 442 households, with a total of 2921 participants. Additionally, 10 in-depth interviews and 10 key-informant interviews were conducted using semi-structured guidelines. Qualitative interviews were audio-recorded, transcribed verbatim, and analyzed using a thematic analysis. Triangulation was employed in this study through the integration of qualitative and quantitative analysis, resulting in the presentation of findings that offer an in-depth comprehension of the phenomenon being investigated.

resultsRiver erosions and floods are common and recurring natural disasters that significantly impact the lives of the riverine island inhabitants. These disasters often disrupted their livelihoods, forced many residents to endure substandard living conditions or relocated during flood events. The island faced a low diagnostic prevalence of chronic diseases (e.g., 5.1% of adults were hypertension and 2.5% are diabetes) because of the absence of diagnostic facilities and a shortage of certified doctors. A significant number of chronic illness people in the community turned to alternative medicine sources (39.3%) such as homeopathy, Kabiraj, and Ayurvedic medicine, especially it gets increased during periods of natural disasters. Moreover, reproductive aged women revealed that 79.4% of them gave birth at home, with 6.0% of these home deliveries resulting in miscarriage or infant death. The destruction of crops, unstable job opportunities, an inadequate educational system, and a deficient healthcare delivery system exacerbated the hardships faced by the population affected by these disasters.

conclusionThe failure to seek treatment for chronic diseases and undiagnosed diseases is a significant health issue among the aging adults on the island. Island residents face the challenge of establishing effective prevention strategies for the well-being of older adults especially at the period of natural disasters. It is crucial for the government and non-governmental organizations (NGOs) to collaborate to prevent the negative effects of floods and river erosions. This should include efforts to enhance the quality of education, healthcare services, job opportunities, and financial assistance for rebuilding homes.

Indexed as

FloodsNatural DisastersAdultAgedBangladeshChronic DiseaseCross-Sectional StudiesDelivery of Health CareFemaleHumans

Identifiers

PMID38512936
PMCPMC10956832
OpenAlexW4393063816

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.