Cargando…

Depression and obesity, data from a national administrative database study: Geographic evidence for an epidemiological overlap

BACKGROUND: Depression and obesity are two major conditions with both psychological and somatic burdens. Some data suggest strong connections between depression and obesity and more particularly associated prevalence of both disorders. However, little is known about the geographical distribution of...

Descripción completa

Detalles Bibliográficos
Autores principales: Chauvet-Gelinier, Jean-Christophe, Roussot, Adrien, Cottenet, Jonathan, Brindisi, Marie-Claude, Petit, Jean-Michel, Bonin, Bernard, Vergès, Bruno, Quantin, Catherine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6324832/
https://www.ncbi.nlm.nih.gov/pubmed/30620759
http://dx.doi.org/10.1371/journal.pone.0210507
_version_ 1783386040246992896
author Chauvet-Gelinier, Jean-Christophe
Roussot, Adrien
Cottenet, Jonathan
Brindisi, Marie-Claude
Petit, Jean-Michel
Bonin, Bernard
Vergès, Bruno
Quantin, Catherine
author_facet Chauvet-Gelinier, Jean-Christophe
Roussot, Adrien
Cottenet, Jonathan
Brindisi, Marie-Claude
Petit, Jean-Michel
Bonin, Bernard
Vergès, Bruno
Quantin, Catherine
author_sort Chauvet-Gelinier, Jean-Christophe
collection PubMed
description BACKGROUND: Depression and obesity are two major conditions with both psychological and somatic burdens. Some data suggest strong connections between depression and obesity and more particularly associated prevalence of both disorders. However, little is known about the geographical distribution of these two diseases. This study aimed to determine if there is spatial overlap between obesity and depression using data from the entire French territory. METHODS: Data for 5,627 geographic codes for metropolitan France were collected from the two national hospital databases (PMSI-MCO and RIM-P) for the year 2016. We identified people who were depressed, obese or both registered in the two public medico-administrative databases, and we assessed their location. In addition, a multivariable analysis was performed in order to determine geographic interactions between obesity and depression after controlling for age, sex, environmental and socio-economic factors (social/material deprivation, urbanicity/rurality). RESULTS: 1,045,682 people aged 18 years and older were identified. The mapping analysis showed several cold and hot regional clusters of coinciding obesity and depression. The multivariable analysis demonstrated significant geographic interactions, with an increasing probability of finding a high prevalence of obesity in regions with major depression (OR 1.29 95% CI 1.13–1.49, p = 0.0002) and an increased probability of finding a high prevalence of depression in regions with a high ration of obesity (OR 1.32, 95% CI 1.15–1.52, p<0.0001). CONCLUSION: Our study confirms the significant bidirectional relationships between obesity and depression at a group level. French geographic patterns reveal a partial overlap between obesity and depression, suggesting these two diseases can be included in a common approach. Further studies should be done to increase the understanding of this complex comorbidity.
format Online
Article
Text
id pubmed-6324832
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-63248322019-01-19 Depression and obesity, data from a national administrative database study: Geographic evidence for an epidemiological overlap Chauvet-Gelinier, Jean-Christophe Roussot, Adrien Cottenet, Jonathan Brindisi, Marie-Claude Petit, Jean-Michel Bonin, Bernard Vergès, Bruno Quantin, Catherine PLoS One Research Article BACKGROUND: Depression and obesity are two major conditions with both psychological and somatic burdens. Some data suggest strong connections between depression and obesity and more particularly associated prevalence of both disorders. However, little is known about the geographical distribution of these two diseases. This study aimed to determine if there is spatial overlap between obesity and depression using data from the entire French territory. METHODS: Data for 5,627 geographic codes for metropolitan France were collected from the two national hospital databases (PMSI-MCO and RIM-P) for the year 2016. We identified people who were depressed, obese or both registered in the two public medico-administrative databases, and we assessed their location. In addition, a multivariable analysis was performed in order to determine geographic interactions between obesity and depression after controlling for age, sex, environmental and socio-economic factors (social/material deprivation, urbanicity/rurality). RESULTS: 1,045,682 people aged 18 years and older were identified. The mapping analysis showed several cold and hot regional clusters of coinciding obesity and depression. The multivariable analysis demonstrated significant geographic interactions, with an increasing probability of finding a high prevalence of obesity in regions with major depression (OR 1.29 95% CI 1.13–1.49, p = 0.0002) and an increased probability of finding a high prevalence of depression in regions with a high ration of obesity (OR 1.32, 95% CI 1.15–1.52, p<0.0001). CONCLUSION: Our study confirms the significant bidirectional relationships between obesity and depression at a group level. French geographic patterns reveal a partial overlap between obesity and depression, suggesting these two diseases can be included in a common approach. Further studies should be done to increase the understanding of this complex comorbidity. Public Library of Science 2019-01-08 /pmc/articles/PMC6324832/ /pubmed/30620759 http://dx.doi.org/10.1371/journal.pone.0210507 Text en © 2019 Chauvet-Gelinier et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Chauvet-Gelinier, Jean-Christophe
Roussot, Adrien
Cottenet, Jonathan
Brindisi, Marie-Claude
Petit, Jean-Michel
Bonin, Bernard
Vergès, Bruno
Quantin, Catherine
Depression and obesity, data from a national administrative database study: Geographic evidence for an epidemiological overlap
title Depression and obesity, data from a national administrative database study: Geographic evidence for an epidemiological overlap
title_full Depression and obesity, data from a national administrative database study: Geographic evidence for an epidemiological overlap
title_fullStr Depression and obesity, data from a national administrative database study: Geographic evidence for an epidemiological overlap
title_full_unstemmed Depression and obesity, data from a national administrative database study: Geographic evidence for an epidemiological overlap
title_short Depression and obesity, data from a national administrative database study: Geographic evidence for an epidemiological overlap
title_sort depression and obesity, data from a national administrative database study: geographic evidence for an epidemiological overlap
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6324832/
https://www.ncbi.nlm.nih.gov/pubmed/30620759
http://dx.doi.org/10.1371/journal.pone.0210507
work_keys_str_mv AT chauvetgelinierjeanchristophe depressionandobesitydatafromanationaladministrativedatabasestudygeographicevidenceforanepidemiologicaloverlap
AT roussotadrien depressionandobesitydatafromanationaladministrativedatabasestudygeographicevidenceforanepidemiologicaloverlap
AT cottenetjonathan depressionandobesitydatafromanationaladministrativedatabasestudygeographicevidenceforanepidemiologicaloverlap
AT brindisimarieclaude depressionandobesitydatafromanationaladministrativedatabasestudygeographicevidenceforanepidemiologicaloverlap
AT petitjeanmichel depressionandobesitydatafromanationaladministrativedatabasestudygeographicevidenceforanepidemiologicaloverlap
AT boninbernard depressionandobesitydatafromanationaladministrativedatabasestudygeographicevidenceforanepidemiologicaloverlap
AT vergesbruno depressionandobesitydatafromanationaladministrativedatabasestudygeographicevidenceforanepidemiologicaloverlap
AT quantincatherine depressionandobesitydatafromanationaladministrativedatabasestudygeographicevidenceforanepidemiologicaloverlap