Evidence map›Paper›PMID 39888922›Full record

ArticlePloS one2025

Self-reported illnesses in Thatta: Evidence from a rural and underdeveloped district in Sindh province, Pakistan.

Muhammad Ashar Malik, Rahat Batool, Muhammad Ahmed, Imran Naeem Abbasi, Zafar Ahmed Fatmi, Sarah Saleem, Sameen Siddiqui

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Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Muhammad Ashar MalikDepartment of Community Health Sciences, Aga Khan University, Karachi, Pakistan.ORCID 0000-0001-9413-3952
Rahat BatoolDepartment of Community Health Sciences, Aga Khan University, Karachi, Pakistan.
Muhammad AhmedNED University of Engineering and Technology, Karachi, Pakistan.
Imran Naeem AbbasiDepartment of Community Health Sciences, Aga Khan University, Karachi, Pakistan.ORCID 0000-0002-9487-1303
Zafar Ahmed FatmiDepartment of Community Health Sciences, Aga Khan University, Karachi, Pakistan.
Sarah SaleemDepartment of Community Health Sciences, Aga Khan University, Karachi, Pakistan.
Sameen SiddiquiDepartment of Community Health Sciences, Aga Khan University, Karachi, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionSelf-reported illnesses (SRI) surveys are widely used as a low-cost substitute for weak Disease Surveillance Systems in low- and low-middle-income countries. In this paper, we report findings of a district-level disease prevalence survey of all types of illnesses including chronic, infectious, injuries and accidents, and maternal and child health in a rural district in Pakistan.

methodsA district-level survey was conducted in Thatta in 2019 with a population-representative sample of all ages (n = 7811) a. Survey included questions on demographics and SRIs from the respondents. Prevalence was estimated for all SRIs categorized into six major and 16 minor illnesses. The influence of important socio-demographic covariates on the illnesses and multiple comorbidities was explored by estimating prevalence ratios with a Generalized Linear Model of the Poisson family and by Zero-Inflated Poison Distribution respectively.

findings36.57% of the respondents to the survey reported at least one SRI. Prevalence of communicable illnesses was 20.7%, followed by non-communicable illnesses (4.8%), Gastrointestinal disorders (4.4%), and injuries/disabilities (1.9%). Urban inhabitants were more likely to have Chronic Obstructive Pulmonary Disorders (3.34%) and Diabetes (1.62%). Females were most likely to have injuries (1.20,), disabilities (1.59), and Musculoskeletal Disorders (1.25). Children aged < 1 year (0.80) and elderly >65 years (0.78) were more likely to have comorbidities. DISCUSSION: Our estimated prevalence of SRI is quite higher than the prevalence of unknown SRIs in national-level surveys in Pakistan. This research's findings serve as an example of aiding evidence-based priority settings within the health sector. Our findings on gender, and young and old age as positive predictors of SRI are consistent with similar surveys in a few LMICs. RECOMMENDATION AND

conclusionWe provide evidence of a complete disease profile of a district that is otherwise unavailable in the country. This study can reshape the existing health surveys and to aid evidence-based priority settings in the health sector. We, however, support strengthening the Disease Surveillance System as a reliable source of disease prevalence data.

Indexed as

Rural PopulationSelf ReportAdolescentAdultAgedChildChild, PreschoolCommunicable DiseasesFemaleHumansInfantInfant, NewbornMaleMiddle AgedPakistanPrevalence

Identifiers

PMID39888922
PMCPMC11785293

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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.