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. 2024 Dec 2;193(12):1758-1767.
doi: 10.1093/aje/kwae107.

Improving prevalence estimates of mental health and well-being indicators among sexual minority men: a propensity-weighting approach

Christoffer Dharma  1 , Peter M Smith  1   2   3 , Michael Escobar  1 , Travis Salway  4   5   6 , Victoria Landsman  1   2 , Ben Klassen, Nathan J Lachowsky  7   8   9 , Dionne Gesink  1
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Improving prevalence estimates of mental health and well-being indicators among sexual minority men: a propensity-weighting approach

Christoffer Dharma et al. Am J Epidemiol. .

Abstract

The prevalence and relative disparities of mental health outcomes and well-being indicators are often inconsistent across studies of sexual minority men (SMM) due to selection biases in community-based surveys (nonprobability sample), as well as misclassification biases in population-based surveys where some SMM often conceal their sexual orientation identities. The present study estimated the prevalence of mental health related outcomes (depressive symptoms, mental health service use, anxiety) and well-being indicators (loneliness and self-rated mental health) among SMM, broken down by sexual orientation using the adjusted logistic propensity score (ALP) weighting. We applied the ALP to correct for selection biases in the 2019 Sex Now data (a community-based survey of SMMs in Canada) by reweighting it to the 2015-2018 Canadian Community Health Survey (a population survey from Statistics Canada). For all SMMs, the ALP-weighted prevalence of depressive symptoms was 15.96% (95% CI, 11.36%-23.83%), while for mental health service use, it was 32.13% (95% CI, 26.09%-41.20%). The ALP estimates lie in between the crude estimates from the two surveys. This method was successful in providing a more accurate estimate than relying on results from one survey alone. We recommend to the use of ALP on other minority populations under certain assumptions. This article is part of a Special Collection on Mental Health.

Keywords: LGBTQ+; depressive symptoms; health services; measurement bias; mental health; propensity scores; selection bias; sexual orientation.

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Conflict of interest statement

The authors have no relevant conflict of interest to declare.

Figures

Figure 1
Figure 1
Step-by-step illustration of reweighting a community-based sample of sexual minority men to a population-based sample using the adjusted logistic propensity method (ALP) and an iterative data-driven approach. Note: The data-driven approach of finding the most appropriate model is not part of the ALP method. This iterative process of examining the SMDs between two groups is a method commonly used when assessing balance between two groups with propensity score analyses. CCHS, Canadian Community Health Survey, SMD, standardized mean difference.
Figure 2
Figure 2
Flow diagram of study participants at different stages of the analysis. ALP, adjusted logistic propensity; CCHS, Canadian Community Health Survey; SMM, sexual minority men.
Figure 3
Figure 3
Prevalence and 95% confidence interval of numerous mental health and well-being indicators among sexual minority men using the different methods of estimations from the 2019 Sex Now data and the Canadian Community Health Survey (CCHS 2015-2018). A table version of this figure with more details on the exact numbers, exact sample sizes for each group and outcomes can be found in Table S2.
See this image and copyright information in PMC

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