Cargando…

Social determinants of overweight and obesity in Paraguayan adults using quantile regression

Background: The World Health Organization (WHO) defines the double burden of malnutrition as the new face of malnutrition. This is a serious problem in Latin American countries, especially Paraguay, which has a high obesity rate. This study aimed to gather data to inform a national strategy for conf...

Descripción completa

Detalles Bibliográficos
Autores principales: Lee, Hocheol, Kim, Ji Eon, Amarilla, Adriana, Kang, Yanghee, Boram, Nam, Eun Woo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PAGEPress Publications, Pavia, Italy 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8764552/
https://www.ncbi.nlm.nih.gov/pubmed/34340299
http://dx.doi.org/10.4081/jphr.2021.2196
_version_ 1784634192549642240
author Lee, Hocheol
Kim, Ji Eon
Amarilla, Adriana
Kang, Yanghee
Boram,
Nam, Eun Woo
author_facet Lee, Hocheol
Kim, Ji Eon
Amarilla, Adriana
Kang, Yanghee
Boram,
Nam, Eun Woo
author_sort Lee, Hocheol
collection PubMed
description Background: The World Health Organization (WHO) defines the double burden of malnutrition as the new face of malnutrition. This is a serious problem in Latin American countries, especially Paraguay, which has a high obesity rate. This study aimed to gather data to inform a national strategy for confronting the doubleburden challenge in Paraguay by i) identifying whether the body mass index (BMI) of study subjects differed significantly according to social determinants, and ii) assessing the factors affecting BMI and the extent of their impact according to BMI quantile levels. Design and methods: Data were collected using a questionnaire adapted from the WHO World Health Survey. We collected 2,200 responses from September 16 to October 7, 2018. After excluding the questionnaires with missing data, we analyzed 1,994 respondents aged 18 years and older living in Limpio, Paraguay. The analyses included t-test and chi-squared test to identify significant differences and 10th quantile regression to assess associations. Results: Analyses showed significant differences in participants’ BMI levels based on age and diagnoses of diabetes or hypertension. In quantile regression analyses, age was significantly associated with BMI quantiles at all but one level. Educational attainment was significantly associated with the 10-40% and 60-70% quantiles of BMI. Conclusions: Age, education level, diabetes, and hypertension were significant predictors of obesity. Obesity programs that focus on people aged more than 60 years are required. In addition, targeted nutritional education may be a useful intervention.
format Online
Article
Text
id pubmed-8764552
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher PAGEPress Publications, Pavia, Italy
record_format MEDLINE/PubMed
spelling pubmed-87645522022-02-03 Social determinants of overweight and obesity in Paraguayan adults using quantile regression Lee, Hocheol Kim, Ji Eon Amarilla, Adriana Kang, Yanghee Boram, Nam, Eun Woo J Public Health Res Article Background: The World Health Organization (WHO) defines the double burden of malnutrition as the new face of malnutrition. This is a serious problem in Latin American countries, especially Paraguay, which has a high obesity rate. This study aimed to gather data to inform a national strategy for confronting the doubleburden challenge in Paraguay by i) identifying whether the body mass index (BMI) of study subjects differed significantly according to social determinants, and ii) assessing the factors affecting BMI and the extent of their impact according to BMI quantile levels. Design and methods: Data were collected using a questionnaire adapted from the WHO World Health Survey. We collected 2,200 responses from September 16 to October 7, 2018. After excluding the questionnaires with missing data, we analyzed 1,994 respondents aged 18 years and older living in Limpio, Paraguay. The analyses included t-test and chi-squared test to identify significant differences and 10th quantile regression to assess associations. Results: Analyses showed significant differences in participants’ BMI levels based on age and diagnoses of diabetes or hypertension. In quantile regression analyses, age was significantly associated with BMI quantiles at all but one level. Educational attainment was significantly associated with the 10-40% and 60-70% quantiles of BMI. Conclusions: Age, education level, diabetes, and hypertension were significant predictors of obesity. Obesity programs that focus on people aged more than 60 years are required. In addition, targeted nutritional education may be a useful intervention. PAGEPress Publications, Pavia, Italy 2021-07-31 /pmc/articles/PMC8764552/ /pubmed/34340299 http://dx.doi.org/10.4081/jphr.2021.2196 Text en ©Copyright: the Author(s) https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Article
Lee, Hocheol
Kim, Ji Eon
Amarilla, Adriana
Kang, Yanghee
Boram,
Nam, Eun Woo
Social determinants of overweight and obesity in Paraguayan adults using quantile regression
title Social determinants of overweight and obesity in Paraguayan adults using quantile regression
title_full Social determinants of overweight and obesity in Paraguayan adults using quantile regression
title_fullStr Social determinants of overweight and obesity in Paraguayan adults using quantile regression
title_full_unstemmed Social determinants of overweight and obesity in Paraguayan adults using quantile regression
title_short Social determinants of overweight and obesity in Paraguayan adults using quantile regression
title_sort social determinants of overweight and obesity in paraguayan adults using quantile regression
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8764552/
https://www.ncbi.nlm.nih.gov/pubmed/34340299
http://dx.doi.org/10.4081/jphr.2021.2196
work_keys_str_mv AT leehocheol socialdeterminantsofoverweightandobesityinparaguayanadultsusingquantileregression
AT kimjieon socialdeterminantsofoverweightandobesityinparaguayanadultsusingquantileregression
AT amarillaadriana socialdeterminantsofoverweightandobesityinparaguayanadultsusingquantileregression
AT kangyanghee socialdeterminantsofoverweightandobesityinparaguayanadultsusingquantileregression
AT boram socialdeterminantsofoverweightandobesityinparaguayanadultsusingquantileregression
AT nameunwoo socialdeterminantsofoverweightandobesityinparaguayanadultsusingquantileregression