Cold-Related Illness Among Older Adults Experiencing Homelessness

Peter M Hoang; Kristina Kokorelias; Lavina Matai; Longdi Fu; Yu Qing Huang; Paula A Rochon; Nathan M Stall

doi:10.1001/jamanetworkopen.2026.17743

. 2026 Jun 10;9(6):e2617743. doi: 10.1001/jamanetworkopen.2026.17743

Cold-Related Illness Among Older Adults Experiencing Homelessness

Peter M Hoang ^1,^2,^3,^✉, Kristina Kokorelias ^3,⁴, Lavina Matai ⁵, Longdi Fu ³, Yu Qing Huang ^1,², Paula A Rochon ^1,^2,³, Nathan M Stall ^1,³

¹Division of Geriatric Medicine, Department of Medicine, University of Toronto, Toronto, Ontario, Canada

²Institute of Health Policy, Management & Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada

³Division of General Internal Medicine and Geriatrics, Sinai Health and the University Health Network, Toronto, Ontario, Canada

⁴Department of Occupational Science and Occupational Therapy and the Rehabilitation Sciences Institute, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada

⁵ICES, Toronto, Ontario, Canada

Accepted for Publication: April 21, 2026.

Published: June 10, 2026. doi:10.1001/jamanetworkopen.2026.17743

Open Access: This is an open access article distributed under the terms of the CC-BY-NC-ND License, which does not permit alteration or commercial use, including those for text and data mining, AI training, and similar technologies. © 2026 Hoang PM et al. JAMA Network Open.

^✉

Corresponding Author: Peter M. Hoang, MD, Mount Sinai Hospital, 18B-243, 600 University Ave, Toronto, ON M5G 1X5, Canada (peter.hoang@sinaihealth.ca; peter.hoang@uhn.ca).

Author Contributions: Dr Hoang and Mr Fu had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Hoang, Matai, Stall.

Acquisition, analysis, or interpretation of data: Hoang, Kokorelias, Fu, Huang, Rochon, Stall.

Drafting of the manuscript: Hoang.

Critical review of the manuscript for important intellectual content: All authors.

Statistical analysis: Hoang, Fu, Huang.

Administrative, technical, or material support: Matai.

Supervision: Kokorelias, Rochon, Stall.

Conflict of Interest Disclosures: Dr Hoang reported receiving personal fees from the Canadian Coalition for Seniors' Mental Health and grants from the Eliot Phillipson Clinician-Scientist Training Program and Vanier Canada Graduate Scholarship outside the submitted work. No other disclosures were reported.

Funding/Support: This study was supported by the Physician Services Incorporated Resident Grant (R25-28) and the Data Sciences Institute Data Access Grant (DSI-DAGY5R1P01). This study was supported by ICES, which is funded by an annual grant from the Ontario Ministry of Health and the Ministry of Long-Term Care. This study also received funding from: Physician Services Incorporated Grant Number R25-28. This document used data adapted from the Statistics Canada Postal Code Conversion File, which is based on data licensed from Canada Post Corporation, and/or data adapted from the Ontario Ministry of Health Postal Code Conversion File, which contains data copied under license from Canada Post Corporation and Statistics Canada. Parts of this material are based on data and/or information compiled and provided by CIHI, Ontario Health (OH) and the Ontario Ministry of Health.

Role of the Funder/Sponsor: The funders of the study had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The analyses, conclusions, opinions and statements expressed herein are solely those of the authors and do not reflect those of the funding or data sources; no endorsement is intended or should be inferred. Parts or whole of this material are based on data and/or information compiled and provided by Immigration, Refugees and Citizenship Canada (IRCC) current to March 2025. However, the analyses, conclusions, opinions and statements expressed in the material are those of the authors, and not necessarily those of IRCC. This document is adapted from Statistics Canada, CENSUS, 2021. This does not constitute an endorsement by Statistics Canada of this product.

Data Sharing Statement: See Supplement 2.

Additional Contributions: We thank IQVIA Solutions Canada for use of their Drug Information File.

^✉

Corresponding author.

PMCID: PMC13254739 PMID: 42268613

Abstract

This cohort study examines emergency department visits and hospitalizations for cold-related illness among older adults experiencing homelessness compared with socioeconomically disadvantaged adults with housing in Ontario, Canada.

Introduction

Climate change is expected to increase cold weather events in parts of North America. This poses a substantial risk to older adults whose thermoregulation may be impaired by physiological changes associated with aging and medications.^1,2 Prior studies demonstrated that individuals experiencing homelessness are at higher risk of cold-related illness and mortality than their housed counterparts.³ However, these studies have not focused on older adults, who represent a growing proportion of the homeless population in many countries.⁴ In Canada, over 60 000 individuals experienced homelessness on a single night in 2024, with older adults aged 50 years or older representing one-fourth of this population.⁴ Yet, population-based data on cold-related illness among older adults experiencing homelessness remain limited. To understand this gap, we examined emergency department visits and hospitalizations for cold-related illness among older adults experiencing homelessness compared with socioeconomically disadvantaged housed adults in Ontario, Canada.

Methods

This cohort study followed the STROBE reporting guideline.⁵ We conducted a retrospective cohort study from January 1, 2018, to October 31, 2023, using linked health care administrative databases held at ICES in Ontario, Canada. The datasets were linked using unique encoded identifiers and analyzed at ICES. The use of data in this project is authorized under section 45 of Ontario’s Personal Health Information Protection Act and does not require review by a research ethics board.

We included adults aged 50 years or older with a health care encounter (index date) in which homelessness was identified using a validated administrative algorithm.⁶ Our comparator group included housed adults aged 50 years or older with an index health care encounter who resided in neighborhoods in the lowest income quintile. We followed up with individuals from the index date for 1 year and assessed for the first frostbite or cold-related illness. We excluded outcome events occuring between May to September. Additional information can be found in the eMethods and eFigure in Supplement 1.

Statistical Analysis

We calculated age and sex standardized rates of cold-related visits per 100 000 adults per month between homeless and socioeconomically disadvantaged housed older adults, using the 2021 Ontario population as our reference.⁷ We calculated descriptive statistics based on exposure status. We estimated the risk of cold-related illness with multivariable logistic regression, adjusting for covariates including sex, age, being referred from or discharged to a correctional facility, immigrant status based on Immigration, Refugees and Citizenship Canada’s Permanent Resident database,⁸ psychiatric comorbidities, dementia, developmental disability, physical disabilities, and other comorbidities (eMethods in Supplement 1). Covariates were measured at baseline. Statistical significance was set at P ≤ .05. Analyses were conducted using R version 4.4.2 (R Project for Statistical Computing). Data were analyzed from March to April 2026.

Results

This study included 34 398 individuals experiencing homelessness (20 545 [59.7%] male) and 812 709 individuals housed in the lowest neighborhood income quintile (370 922 males [45.6%]) (Table). Between 2018 and 2024, the standardized rate of cold-related illness was 543.6 (95% CI, 467.7-628.0) per 100 000 among older adults experiencing homelessness compared with 19.7 (95% CI, 16.7-23.1) per 100 000 among housed adults living in the lowest neighborhood income quintile. Rates peaked in the month of January, with 145.9 (95% CI, 123.7-172.8) per 100 000 among those experiencing homelessness vs 8.4 (95% CI, 3.1-14.8) per 100 000 among housed adults (Figure). After adjustment for covariates, individuals experiencing homelessness had higher odds of cold-related illness (adjusted odds ratio [aOR] 13.45; 95% CI, 10.37-17.42). Male sex (aOR, 2.38; 95% CI, 1.86-3.07), referral from or discharge to a correctional facility (aOR, 1.89; 95% CI, 1.36-2.59), and dementia (aOR, 1.69; 95% CI, 1.10-2.51) were associated with an increased odds of cold-related illness (Table).

Table. Demographic Characteristics and Multivariable Logistic Regression Analysis for Factors Associated With Cold-Related Illness in Older Adults, 2018-2023.

Characteristic	Experiencing homelessness (n = 34 398)	Housed in the lowest neighborhood income quintile (n = 812 709)	Unadjusted odds ratio (95% CI)	P value	Adjusted odds ratio (95% CI)^a	P value
Experiencing homelessness	NA	NA	30.81 (25.00-38.05)	<.001	13.45 (10.37-17.42)	<.001
Housed in the lowest neighborhood income quintile	NA	NA	1 [Reference]	NA	1 [Reference]	NA
Sex
Female	13 853 (40.3)	441 787 (54.4)	1 [Reference]	NA	1 [Reference]	NA
Male	20 545 (59.7)	370 922 (45.6)	3.65 (2.88-4.68)	<.001	2.38 (1.86-3.07)	<.001
Age, y
50-59	15 452 (44.9)	258 718 (31.8)	1 [Reference]	NA	1 [Reference]	NA
60-69	10 522 (30.6)	246 924 (30.4)	0.73 (0.57-0.92)	.01	1.05 (0.82-1.35)	.69
70-79	5243 (15.2)	180 412 (22.2)	0.50 (0.36-0.67)	<.001	1.11 (0.78-1.56)	.56
≥80	3181 (9.2)	126 655 (15.6)	0.44 (0.29-0.62)	<.001	1.28 (0.80-2.01)	.29
Immigration category^b
Nonimmigrant	30 644 (89.1)	656 489 (80.8)	1 [Reference]	NA	1 [Reference]	NA
Immigrant	2061 (6.0)	114 058 (14.0)	0.36 (0.22-0.55)	<.001	0.64 (0.39-0.98)	.05
Other immigrants	276 (0.8)	6689 (0.8)	0.30 (0.02-1.34)	.23	0.37 (0.02-1.63)	.32
Refugees	1417 (4.1)	35 483 (4.4)	0.51 (0.25-0.94)	.05	0.63 (0.30-1.15)	.17
Referred from or discharged to a correctional facility within the past year	3632 (10.6)	2799 (0.3)	25.67 (19.17-33.76)	<.001	1.89 (1.36-2.59)	<.001
Chronic comorbidity^c	2.56 (2.05)	2.26 (1.74)	1.03 (0.98-1.09)	.28	0.99 (0.93-1.05)	.71
Mood disorder	15 194 (44.2)	108 893 (13.4)	5.45 (4.43-6.71)	<.001	1.01 (0.73-1.39)	.96
Psychotic disorder	7,899 (23.0)	37 162 (4.6)	6.40 (5.03-8.07)	<.001	1.58 (1.19-2.09)	.001
Substance use disorder	10 195 (29.6)	35 590 (4.4)	11.6 (9.40-14.4)	<.001	2.46 (1.79-3.40)	<.001
Dementia	2331 (6.8)	30 130 (3.7)	2.23 (1.49-3.20)	<.001	1.69 (1.10-2.51)	.01
Developmental disability	1382 (4.0)	10 353 (1.3)	3.80 (2.28-5.91)	<.001	1.49 (0.88-2.35)	.11
Congenital, neurological, and musculoskeletal disabilities	19 657 (57.1)	424 537 (52.2)	1.12 (0.91-1.39)	.03	1.03 (0.82-1.30)	.78
Permanent injuries^d	3895 (11.3)	33 616 (4.1)	3.78 (2.79-5.01)	<.001	1.56 (1.13-2.09)	.005
Hearing impairment	3248 (9.4)	86 977 (10.7)	0.66 (0.43-0.96)	.04	0.76 (0.49-1.12)	.19
Visual impairment	9145 (26.6)	290 969 (35.8)	0.45 (0.34-0.57)	<.001	0.64 (0.47-0.86)	.004

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Abbreviation: NA, not applicable.

^{^a}

The risk of cold-related illness among older adults experiencing homelessness was adjusted for sex, age, immigration status, being referred from or discharged to a correctional facility, psychiatric comorbidities (ie, mood disorder, psychotic and substance use disorders), chronic comorbidities, dementia, physical disabilities (ie, congenital, neurological, and musculoskeletal disabilities, sensory impairment, and permanent injuries), and developmental disability.

^{^b}

Immigration categories include: immigrants (ie, sponsored or economic immigrants), refugees (ie, resettled refugees or protected persons), and other immigrants (ie, humanitarian and compassionate or public policy considerations and those who do not fulfill an aforementioned category).

^{^c}

Chronic comorbidities include arthritis, asthma, cancer, heart failure, myocardial infarction, peripheral vascular disease, chronic obstructive pulmonary disease, diabetes, hypertension, colitis, chronic kidney disease, cirrhosis, joint replacement, osteoporosis, neuromuscular disorders, and stroke or transient ischemic attack.

^{^d}

Permanent injuries include brain injury, crushing injury of the lower limb, dependence on a wheelchair or other enabling devices, fracture of the lower back or pelvis, fracture of the vertebral column with spinal cord injury, other acquired deformities of the limbs, traumatic amputation of the lower or upper limb.

Figure. — Age- and sex-standardized rates of cold-related illnesses were plotted according to month, per 100 000 older adults, with shaded areas indicating 95% CIs. This figure shows that cold-related illnesses were highest in the months of December to February. Confidence intervals were generated using the Dobson method. Older adults experiencing homelessness had higher rates of cold-related illnesses through the months of October to April compared with housed adults 50 years of age and over living in the lowest income quintile.

Discussion

In this cohort study, older adults experiencing homelessness had a higher risk of emergency visits and hospitalizations for cold-related illnesses compared with socioeconomically disadvantaged housed individuals. This increased risk may reflect inadequate access to shelter spaces and warming shelters, involuntary displacement, inadequate winter clothing, and higher rates of cognitive impairment. The association between correctional facilities and cold-related illness may reflect arrests that occurred while experiencing homelessness.⁹ As the median length of stay in provincial correctional facilities were under 1 month in duration, this observed association warranted further investigation.¹⁰

Our study is limited by specific but insensitive codes for homelessness.⁶ Furthermore, we only captured the first cold-related illness following index date. Taken together, we may have underestimated the burden of cold-related illness.⁶ Data about race and ethnicity are not routinely available in administrative datasets in Ontario, and their association to homelessness could not be described in this study. While COVID-19–related service disruptions may have influenced cold exposure and health care use, our data does not allow us to quantify the association.

As climate change increases the frequency and intensity of extreme weather events, older adults experiencing homelessness are likely to face growing risks of cold-related illness. Shelters, supervised consumption sites, and correctional facilities should be prepared to monitor and support this population for cold-related illnesses.

Supplement 1.

eMethods.

eFigure. Cohort Flow Diagram

jamanetwopen-e2617743-s001.pdf^{(415KB, pdf)}

Supplement 2.

Data Sharing Statement

jamanetwopen-e2617743-s002.pdf^{(12KB, pdf)}

References

1.Cohen J, Agel L, Barlow M, Garfinkel CI, White I. Linking arctic variability and change with extreme winter weather in the United States. Science. 2021;373(6559):1116-1121. doi: 10.1126/science.abi9167 [DOI] [PubMed] [Google Scholar]
2.Liu M, Patel VR, Wadhera RK. Cold-related deaths in the US. JAMA. 2025;333(5):427-429. doi: 10.1001/jama.2024.25194 [DOI] [PMC free article] [PubMed] [Google Scholar]
3.Richard L, Golding H, Saskin R, et al. Cold-related injuries among patients experiencing homelessness in Toronto: a descriptive analysis of emergency department visits. CJEM. 2023;25(8):695-703. doi: 10.1007/s43678-023-00546-7 [DOI] [PubMed] [Google Scholar]
4.Everyone counts 2024. highlights report part 2—survey of people experiencing homelessness. Government of Canada. Accessed April 30, 2026. https://housing-infrastructure.canada.ca/homelessness-sans-abri/reports-rapports/pit-counts-dp-2024-highlights-p2-eng.html
5.von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP; STROBE Initiative . The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet. 2007;370(9596):1453-1457. doi: 10.1016/S0140-6736(07)61602-X [DOI] [PubMed] [Google Scholar]
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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement 1.

eMethods.

eFigure. Cohort Flow Diagram

jamanetwopen-e2617743-s001.pdf^{(415KB, pdf)}

Supplement 2.

Data Sharing Statement

jamanetwopen-e2617743-s002.pdf^{(12KB, pdf)}

[zld260095r1] 1.Cohen J, Agel L, Barlow M, Garfinkel CI, White I. Linking arctic variability and change with extreme winter weather in the United States. Science. 2021;373(6559):1116-1121. doi: 10.1126/science.abi9167 [DOI] [PubMed] [Google Scholar]

[zld260095r2] 2.Liu M, Patel VR, Wadhera RK. Cold-related deaths in the US. JAMA. 2025;333(5):427-429. doi: 10.1001/jama.2024.25194 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zld260095r3] 3.Richard L, Golding H, Saskin R, et al. Cold-related injuries among patients experiencing homelessness in Toronto: a descriptive analysis of emergency department visits. CJEM. 2023;25(8):695-703. doi: 10.1007/s43678-023-00546-7 [DOI] [PubMed] [Google Scholar]

[zld260095r4] 4.Everyone counts 2024. highlights report part 2—survey of people experiencing homelessness. Government of Canada. Accessed April 30, 2026. https://housing-infrastructure.canada.ca/homelessness-sans-abri/reports-rapports/pit-counts-dp-2024-highlights-p2-eng.html

[zld260095r5] 5.von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP; STROBE Initiative . The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet. 2007;370(9596):1453-1457. doi: 10.1016/S0140-6736(07)61602-X [DOI] [PubMed] [Google Scholar]

[zld260095r6] 6.Richard L, Hwang SW, Forchuk C, et al. Validation study of health administrative data algorithms to identify individuals experiencing homelessness and estimate population prevalence of homelessness in Ontario, Canada. BMJ Open. 2019;9(10):e030221. doi: 10.1136/bmjopen-2019-030221 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zld260095r7] 7.Census profile, 2021 census of population profile table. Government of Canada. Accessed March 29, 2026. https://www12.statcan.gc.ca/census-recensement/2021/

[zld260095r8] 8.Chiu M, Lebenbaum M, Lam K, et al. Describing the linkages of the immigration, refugees and citizenship Canada permanent resident data and vital statistics death registry to Ontario’s administrative health database. BMC Med Inform Decis Mak. 2016;16(1):135. doi: 10.1186/s12911-016-0375-3 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zld260095r9] 9.Hulchanski JDavid . Finding Home: Policy Options for Addressing Homelessness in Canada. Cities Centre Press; 2009. [Google Scholar]

[zld260095r10] 10.Auditor General . Adult Correctional Institutions. Ministry of the Solicitor General Summary; 2019:chap 1. [Google Scholar]

PERMALINK

Cold-Related Illness Among Older Adults Experiencing Homelessness

Peter M Hoang, MD

Kristina Kokorelias, PhD

Lavina Matai, PharmD, MScPH

Longdi Fu, MSc

Yu Qing Huang, MDCM

Paula A Rochon, MD, MPH

Nathan M Stall, MD, PhD

Abstract

Introduction

Methods

Statistical Analysis

Results

Table. Demographic Characteristics and Multivariable Logistic Regression Analysis for Factors Associated With Cold-Related Illness in Older Adults, 2018-2023.

Figure. Line Graph of Rates of Cold-Related Illness Comparing Older Adults Experiencing Homelessness and Socioeconomically Disadvantaged Adults.

Discussion

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

Cite

Add to Collections

PERMALINK

Cold-Related Illness Among Older Adults Experiencing Homelessness

Peter M Hoang, MD

Kristina Kokorelias, PhD

Lavina Matai, PharmD, MScPH

Longdi Fu, MSc

Yu Qing Huang, MDCM

Paula A Rochon, MD, MPH

Nathan M Stall, MD, PhD

Abstract

Introduction

Methods

Statistical Analysis

Results

Table. Demographic Characteristics and Multivariable Logistic Regression Analysis for Factors Associated With Cold-Related Illness in Older Adults, 2018-2023.

Figure. Line Graph of Rates of Cold-Related Illness Comparing Older Adults Experiencing Homelessness and Socioeconomically Disadvantaged Adults.

Discussion

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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