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Risk factors for acute gastrointestinal illness in a Canadian population-based linkage cohort

Published online by Cambridge University Press:  07 October 2025

Anthony Justin Gilding*
Affiliation:
School of Occupational and Public Health, Toronto Metropolitan University , Toronto, ON, Canada
Ian Young
Affiliation:
School of Occupational and Public Health, Toronto Metropolitan University , Toronto, ON, Canada
Lauren E. Grant
Affiliation:
Department of Population Medicine, University of Guelph , Guelph, ON, Canada
M. Anne Harris
Affiliation:
School of Occupational and Public Health, Toronto Metropolitan University , Toronto, ON, Canada Dalla School of Public Health, University of Toronto, Toronto, ON, Canada
*
Corresponding author: Anthony Justin Gilding; Email: anthony.gilding@torontomu.ca
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Abstract

Acute gastrointestinal illness (AGI) remains a significant public health issue and differences in risk based on a comprehensive set of sociodemographic characteristics remain poorly understood. Thus, this retrospective cohort study was conducted to identify the risk of incurring an AGI-related emergency department (ED) visit or inpatient hospitalization based on various sociodemographic factors. Linked respondents of Canadian Community Health Survey cycles 2.1, 3.1, and 2007–2015 were followed from their interview date until 31 December 2017, using the National Ambulatory Care Reporting System (NACRS) and the Discharge Abstract Database (DAD) to capture emergency ED visits and hospitalizations due to AGI, respectively. Effects of identified potential risk factors for the incidence of AGI-related ED visits or hospitalizations were estimated Cox proportional hazards regression to generate hazard ratios (HRs) with 95% confidence intervals (CIs). A total of 190,700 respondents were linked to NACRS and 470,700 were linked to DAD. Six per cent of respondents visited an ED and 2% were hospitalized for AGI. Fully-adjusted estimates revealed that high-risk groups with the strongest effects were people with poor self-perceived health (ED visits: HR 1.47 (95% CI 1.40–1.54), hospitalizations: HR 1.92 (95% CI 1.82–2.02)), and people living with at least one chronic condition (ED visits: HR 1.54 (95% CI 1.47–1.61), hospitalizations: HR 1.65 (95% CI 1.57–1.73)). This study identified risk factors for requiring hospital care for AGI in the Canadian context. Additional research is needed to investigate mechanisms for differential exposure to pathogens by sociodemographic characteristics that might lead to increased risks of AGI.

Information

Type
Original Paper
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0), which permits non-commercial re-use, distribution, and reproduction in any medium, provided that no alterations are made and the original article is properly cited. The written permission of Cambridge University Press must be obtained prior to any commercial use and/or adaptation of the article.
Copyright
© The Author(s), 2025. Published by Cambridge University Press
Figure 0

Figure 1. Assembly of analytic cohorts from Canadian Community Health Survey (CCHS) cycles 2003–2015. AGI: Acute Gastrointestinal Illness. CCHS: Canadian Community Health Survey. DAD: Discharge Abstract Database. ED: emergency department. NACRS: National Ambulatory Care Reporting System.

Figure 1

Table 1. Description of datasets used in study linking Canadian health survey data to health records for cohort study of acute gastrointestinal illness

Figure 2

Table 2. Demographic and health status characteristics of the linked cohorts

Figure 3

Table 3. Cox proportional hazards modelling results estimating unadjusted (Model 1), minimally adjusted (Model 2) and fully adjusted (Model 3) associations of hospitalization and ED visits for acute gastrointestinal illness in cohorts linking Canadian national survey data to health care records

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