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Journal Article

Citation

Lin S. J. Affect. Disord. 2022; ePub(ePub): ePub.

Copyright

(Copyright © 2022, Elsevier Publishing)

DOI

10.1016/j.jad.2022.08.131

PMID

36058359

Abstract

BACKGROUND: Pandemic-induced social distancing and stay-at-home orders, while successful in decreasing the transmission of COVID-19, could exacerbate loneliness. Few studies have examined how pandemic-related social determinants intersect to shape pandemic loneliness and its relations to mental health care in Canada.

METHODS: A population-representative sample of 3772 adults from the Canadian Perspective Survey Series (CPSS-6; January 25 to 31, 2021) was analyzed. Gender-specific logistic regression was employed to investigate the association between three-item loneliness scale (UCLA-3) with socio-demographics, job precarity, health behaviours, social isolation indicators, and mental health help-seeking. Classification and Regression Tree (CART) modelling was also used to identify intersecting risk factors and the most important predictor of severe loneliness (UCLA-3 score ≥ 7).

RESULTS: The estimated prevalence of severe loneliness was 34.7 % in Canada, with women significantly higher than men (38.1 % vs 31.3 %, p < 0.001). Pandemic loneliness were more prevalent in female (OR = 1.53, 99 % CI: 1.26-1.85), those who were younger (OR's range 1.42-3.00), women without college degree (OR = 1.44, 99 % CI: 1.01-2.04), those living alone (OR = 1.56, 99 % CI: 1.09-2.23), immigrant men (OR = 1.79, 99 % CI: 1.23-2.60), those with small network (OR's range: 1.73-3.26), those who were absent from work due to COVID-19 related reasons (OR = 2.11, 99 % CI: 1.04-4.28), past-month binge drinkers (OR's range: 1.39-1.70) and cannabis user (OR = 1.47, 99 % CI: 1.12-1.93). The CART algorithm identifies that immigrants who experienced pandemic-triggered job insecurity were the most-at-risk group of severely loneliness. Loneliness was positively associated with formal help-seeking from mental health professionals (OR = 1.71, 99 % CI: 1.21-2.41), informal help-seeking from social circle (OR = 1.51, 99 % CI: 1.17-1.95), and unmet mental health needs (OR = 1.78, 99 % CI: 1.29-2.49). LIMITATIONS: Cross-sectional data prohibits causal inferences.

CONCLUSION: The COVID-19 pandemic converges with loneliness epidemic in Canada. Prevention and intervention programs should target upstream social determinants of mental health, especially the intersection of migration status and job precarity, to eliminate loneliness during the pandemic.


Language: en

Keywords

Machine learning; COVID-19; General population; Loneliness; Psychiatric epidemiology

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