Socioeconomic disparities associated with 29 common infectious diseases in Sweden, 2005-14: an individually matched case-control study.


Journal

The Lancet. Infectious diseases
ISSN: 1474-4457
Titre abrégé: Lancet Infect Dis
Pays: United States
ID NLM: 101130150

Informations de publication

Date de publication:
02 2019
Historique:
received: 23 05 2018
revised: 16 07 2018
accepted: 23 07 2018
pubmed: 19 12 2018
medline: 10 5 2020
entrez: 19 12 2018
Statut: ppublish

Résumé

Although the association between low socioeconomic status and non-communicable diseases is well established, the effect of socioeconomic factors on many infectious diseases is less clear, particularly in high-income countries. We examined the associations between socioeconomic characteristics and 29 infections in Sweden. We did an individually matched case-control study in Sweden. We defined a case as a person aged 18-65 years who was notified with one of 29 infections between 2005 and 2014, in Sweden. Cases were individually matched with respect to sex, age, and county of residence with five randomly selected controls. We extracted the data on the 29 infectious diseases from the electronic national register of notified infections and infectious diseases (SmiNet). We extracted information on country of birth, educational and employment status, and income of cases and controls from Statistics Sweden's population registers. We calculated adjusted matched odds ratios (amOR) using conditional logistic regression to examine the association between infections or groups of infections and place of birth, education, employment, and income. We included 173 729 cases notified between Jan 1, 2005, and Dec 31, 2014 and 868 645 controls. Patients with invasive bacterial diseases, blood-borne infectious diseases, tuberculosis, and antibiotic-resistant infections were more likely to be unemployed (amOR 1·59, 95% CI 1·49-1·70; amOR 3·62, 3·48-3·76; amOR 1·88, 1·65-2·14; and amOR 1·73, 1·67-1·79, respectively), to have a lower educational attainment (amOR 1·24, 1·15-1·34; amOR 3·63, 3·45-3·81; amOR 2·14, 1·85-2·47; and amOR 1·07, 1·03-1·12, respectively), and to have a lowest income (amOR 1·52, 1·39-1·66; amOR 3·64, 3·41-3·89; amOR 3·17, 2·49-4·04; and amOR 1·2, 1·14-1·25, respectively). By contrast, patients with food-borne and water-borne infections were less likely than controls to be unemployed (amOR 0·74, 95% CI 0·72-0·76), to have lower education (amOR 0·75, 0·73-0·77), and lowest income (amOR 0·59, 0·58-0·61). These findings indicate persistent socioeconomic inequalities in infectious diseases in an egalitarian high-income country with universal health care. We recommend using these findings to identify priority interventions and as a baseline to monitor programmes addressing socioeconomic inequalities in health. The Public Health Agency of Sweden.

Sections du résumé

BACKGROUND
Although the association between low socioeconomic status and non-communicable diseases is well established, the effect of socioeconomic factors on many infectious diseases is less clear, particularly in high-income countries. We examined the associations between socioeconomic characteristics and 29 infections in Sweden.
METHODS
We did an individually matched case-control study in Sweden. We defined a case as a person aged 18-65 years who was notified with one of 29 infections between 2005 and 2014, in Sweden. Cases were individually matched with respect to sex, age, and county of residence with five randomly selected controls. We extracted the data on the 29 infectious diseases from the electronic national register of notified infections and infectious diseases (SmiNet). We extracted information on country of birth, educational and employment status, and income of cases and controls from Statistics Sweden's population registers. We calculated adjusted matched odds ratios (amOR) using conditional logistic regression to examine the association between infections or groups of infections and place of birth, education, employment, and income.
FINDINGS
We included 173 729 cases notified between Jan 1, 2005, and Dec 31, 2014 and 868 645 controls. Patients with invasive bacterial diseases, blood-borne infectious diseases, tuberculosis, and antibiotic-resistant infections were more likely to be unemployed (amOR 1·59, 95% CI 1·49-1·70; amOR 3·62, 3·48-3·76; amOR 1·88, 1·65-2·14; and amOR 1·73, 1·67-1·79, respectively), to have a lower educational attainment (amOR 1·24, 1·15-1·34; amOR 3·63, 3·45-3·81; amOR 2·14, 1·85-2·47; and amOR 1·07, 1·03-1·12, respectively), and to have a lowest income (amOR 1·52, 1·39-1·66; amOR 3·64, 3·41-3·89; amOR 3·17, 2·49-4·04; and amOR 1·2, 1·14-1·25, respectively). By contrast, patients with food-borne and water-borne infections were less likely than controls to be unemployed (amOR 0·74, 95% CI 0·72-0·76), to have lower education (amOR 0·75, 0·73-0·77), and lowest income (amOR 0·59, 0·58-0·61).
INTERPRETATION
These findings indicate persistent socioeconomic inequalities in infectious diseases in an egalitarian high-income country with universal health care. We recommend using these findings to identify priority interventions and as a baseline to monitor programmes addressing socioeconomic inequalities in health.
FUNDING
The Public Health Agency of Sweden.

Identifiants

pubmed: 30558995
pii: S1473-3099(18)30485-7
doi: 10.1016/S1473-3099(18)30485-7
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

165-176

Commentaires et corrections

Type : CommentIn

Informations de copyright

Copyright © 2019 Elsevier Ltd. All rights reserved.

Auteurs

Alessandro Pini (A)

European Programme for Intervention Epidemiology Training, European Centre for Disease Prevention and Control, Stockholm, Sweden; Public Health Agency of Sweden, Solna, Sweden.

Magnus Stenbeck (M)

Public Health Agency of Sweden, Solna, Sweden; Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.

Ilias Galanis (I)

Public Health Agency of Sweden, Solna, Sweden.

Henrik Kallberg (H)

Public Health Agency of Sweden, Solna, Sweden.

Kostas Danis (K)

European Programme for Intervention Epidemiology Training, European Centre for Disease Prevention and Control, Stockholm, Sweden; Santé Publique France, Public Health Institute, Paris, France.

Anders Tegnell (A)

Public Health Agency of Sweden, Solna, Sweden.

Anders Wallensten (A)

Public Health Agency of Sweden, Solna, Sweden; Department of Medical Sciences, Uppsala University, Uppsala, Sweden. Electronic address: anders.wallensten@folkhalsomyndigheten.se.

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