Cargando…
Using the network scale-up method to characterise kidney trafficking in Kalai Upazila, Bangladesh
This study aimed to estimate the prevalence of illegal kidney sales in Kalai Upazila, Bangladesh, using the Network Scale-Up Method (NSUM), an ego-centric network survey-based technique used to estimate the size of hidden populations. The study estimated the size of the kidney seller population, ana...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10689364/ https://www.ncbi.nlm.nih.gov/pubmed/38035730 http://dx.doi.org/10.1136/bmjgh-2023-012774 |
_version_ | 1785152351586222080 |
---|---|
author | Li, Meng-Hao Yu, Yang Siddique, Abu Bakkar Lee, Narae Haque, Md. Reazul Rahman, Md Lutfay Tariq Ahmad, Manzur El-Amine, Hadi Koizumi, Naoru |
author_facet | Li, Meng-Hao Yu, Yang Siddique, Abu Bakkar Lee, Narae Haque, Md. Reazul Rahman, Md Lutfay Tariq Ahmad, Manzur El-Amine, Hadi Koizumi, Naoru |
author_sort | Li, Meng-Hao |
collection | PubMed |
description | This study aimed to estimate the prevalence of illegal kidney sales in Kalai Upazila, Bangladesh, using the Network Scale-Up Method (NSUM), an ego-centric network survey-based technique used to estimate the size of hidden populations. The study estimated the size of the kidney seller population, analysed the profiles of kidney sellers and kidney brokers and investigated the characteristics of villagers who are more likely to be connected to kidney sellers to identify possible biases of the NSUM estimate. The study found that the prevalence of kidney trafficking in Kalai Upazila was between 1.98% and 2.84%, which is consistent with the estimates provided by a local leader and reporters, but with much narrower bounds. The study also found that a large proportion of kidney sellers and brokers were men (over 70% and 90%, respectively) and relatively young (mean age of 33 and 39, respectively). Specific reasons for kidney sales included poverty (83%), loan payment (4%), drug addiction (2%) and gambling (2%). While most reported male sellers were farmers (56%) and female sellers were housewives (78%) in need of money, most reported brokers were characterised as rich, well-known individuals. |
format | Online Article Text |
id | pubmed-10689364 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-106893642023-12-02 Using the network scale-up method to characterise kidney trafficking in Kalai Upazila, Bangladesh Li, Meng-Hao Yu, Yang Siddique, Abu Bakkar Lee, Narae Haque, Md. Reazul Rahman, Md Lutfay Tariq Ahmad, Manzur El-Amine, Hadi Koizumi, Naoru BMJ Glob Health Original Research This study aimed to estimate the prevalence of illegal kidney sales in Kalai Upazila, Bangladesh, using the Network Scale-Up Method (NSUM), an ego-centric network survey-based technique used to estimate the size of hidden populations. The study estimated the size of the kidney seller population, analysed the profiles of kidney sellers and kidney brokers and investigated the characteristics of villagers who are more likely to be connected to kidney sellers to identify possible biases of the NSUM estimate. The study found that the prevalence of kidney trafficking in Kalai Upazila was between 1.98% and 2.84%, which is consistent with the estimates provided by a local leader and reporters, but with much narrower bounds. The study also found that a large proportion of kidney sellers and brokers were men (over 70% and 90%, respectively) and relatively young (mean age of 33 and 39, respectively). Specific reasons for kidney sales included poverty (83%), loan payment (4%), drug addiction (2%) and gambling (2%). While most reported male sellers were farmers (56%) and female sellers were housewives (78%) in need of money, most reported brokers were characterised as rich, well-known individuals. BMJ Publishing Group 2023-11-30 /pmc/articles/PMC10689364/ /pubmed/38035730 http://dx.doi.org/10.1136/bmjgh-2023-012774 Text en © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Original Research Li, Meng-Hao Yu, Yang Siddique, Abu Bakkar Lee, Narae Haque, Md. Reazul Rahman, Md Lutfay Tariq Ahmad, Manzur El-Amine, Hadi Koizumi, Naoru Using the network scale-up method to characterise kidney trafficking in Kalai Upazila, Bangladesh |
title | Using the network scale-up method to characterise kidney trafficking in Kalai Upazila, Bangladesh |
title_full | Using the network scale-up method to characterise kidney trafficking in Kalai Upazila, Bangladesh |
title_fullStr | Using the network scale-up method to characterise kidney trafficking in Kalai Upazila, Bangladesh |
title_full_unstemmed | Using the network scale-up method to characterise kidney trafficking in Kalai Upazila, Bangladesh |
title_short | Using the network scale-up method to characterise kidney trafficking in Kalai Upazila, Bangladesh |
title_sort | using the network scale-up method to characterise kidney trafficking in kalai upazila, bangladesh |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10689364/ https://www.ncbi.nlm.nih.gov/pubmed/38035730 http://dx.doi.org/10.1136/bmjgh-2023-012774 |
work_keys_str_mv | AT limenghao usingthenetworkscaleupmethodtocharacterisekidneytraffickinginkalaiupazilabangladesh AT yuyang usingthenetworkscaleupmethodtocharacterisekidneytraffickinginkalaiupazilabangladesh AT siddiqueabubakkar usingthenetworkscaleupmethodtocharacterisekidneytraffickinginkalaiupazilabangladesh AT leenarae usingthenetworkscaleupmethodtocharacterisekidneytraffickinginkalaiupazilabangladesh AT haquemdreazul usingthenetworkscaleupmethodtocharacterisekidneytraffickinginkalaiupazilabangladesh AT rahmanmdlutfaytariq usingthenetworkscaleupmethodtocharacterisekidneytraffickinginkalaiupazilabangladesh AT ahmadmanzur usingthenetworkscaleupmethodtocharacterisekidneytraffickinginkalaiupazilabangladesh AT elaminehadi usingthenetworkscaleupmethodtocharacterisekidneytraffickinginkalaiupazilabangladesh AT koizuminaoru usingthenetworkscaleupmethodtocharacterisekidneytraffickinginkalaiupazilabangladesh |