ArticlePLoS neglected tropical diseases2023
Socio-economic and environmental factors associated with high lymphatic filariasis morbidity prevalence distribution in Bangladesh.
Article in PLoS neglected tropical diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled 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.
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
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.
- Risk factors of lymphatic filariasis in Asia: a systematic review.BMC infectious diseases · 2025Pooled it
- Spatial Clustering of Lymphatic Filariasis in Relation to Potential Mansonia Mosquito Habitats in Endemic Communities of Belitung Regency, Indonesia.Acta parasitologica · 2026Article
- Environmental, socioeconomic, and health-system factors associated with NTD hotspots in southern Nigeria: a mixed-methods study.BMC infectious diseases · 2026Article
- Patient perspectives and barriers to effective home-based care in lymphatic filariasis: A mixed methods study from Puducherry, India.PLoS neglected tropical diseases · 2026Article
- mRNA based vaccines and therapeutics for parasitic infections: a comprehensive review.Journal of nanobiotechnology · 2025Review
- Social and healthcare-seeking experiences of people affected with lymphedema in Bangladesh.PLoS neglected tropical diseases · 2025Article
- Clinical profile and Mass Drug Administration coverage in patients with lymphatic filariasis: A descriptive study.Journal of family medicine and primary care · 2025Article
- Mapping lymphatic filariasis morbidities in 24 endemic districts of Ethiopia through the health extension program.Tropical medicine and health · 2024Article
- Towards Understanding the Microepidemiology of Lymphatic Filariasis at the Community Level in Ghana.Tropical medicine and infectious disease · 2024Article
- The national distribution of lymphatic filariasis cases in Malawi using patient mapping and geostatistical modelling.PLoS neglected tropical diseases · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 6 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLymphatic filariasis (LF) is a vector-borne parasitic disease which affects 70 million people worldwide and causes life-long disabilities. In Bangladesh, there are an estimated 44,000 people suffering from clinical conditions such as lymphoedema and hydrocoele, with the greatest burden in the northern Rangpur division. To better understand the factors associated with this distribution, this study examined socio-economic and environmental factors at division, district, and sub-district levels. METHODOLOGY: A retrospective ecological study was conducted using key socio-economic (nutrition, poverty, employment, education, house infrastructure) and environmental (temperature, precipitation, elevation, waterway) factors. Characteristics at division level were summarised. Bivariate analysis using Spearman's rank correlation coefficient was conducted at district and sub-district levels, and negative binomial regression analyses were conducted across high endemic sub-districts (n = 132). Maps were produced of high endemic sub-districts to visually illustrate the socio-economic and environmental factors found to be significant.
resultsThe highest proportion of rural population (86.8%), poverty (42.0%), tube well water (85.4%), and primary employment in agriculture (67.7%) was found in Rangpur division. Spearman's rank correlation coefficient at district and sub-district level show that LF morbidity prevalence was significantly (p<0.05) positively correlated with households without electricity (district rs = 0.818; sub-district rs = 0.559), households with tube well water (sub-district rs = 0.291), households without toilet (district rs = 0.504; sub-district rs = 0.40), mean annual precipitation (district rs = 0.695; sub-district rs = 0.503), mean precipitation of wettest quarter (district rs = 0.707; sub-district rs = 0.528), and significantly negatively correlated with severely stunted children (district rs = -0.723; sub-district rs = -0.370), mean annual temperature (district rs = -0.633.; sub-district rs = 0.353) and mean temperature (wettest quarter) ((district rs = -0.598; sub-district rs = 0.316) Negative binomial regression analyses at sub-district level found severely stunted children (p = <0.001), rural population (p = 0.002), poverty headcount (p = 0.001), primary employment in agriculture (p = 0.018), households without toilet (p = <0.001), households without electricity (p = 0.002) and mean temperature (wettest quarter) (p = 0.045) to be significant.
conclusionsThis study highlights the value of using available data to identify key drivers associated with high LF morbidity prevalence, which may help national LF programmes better identify populations at risk and implement timely and targeted public health messages and intervention strategies.
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.