Patterns of Social, Economic, And Health Challenges Due to the COVID-19 Pandemic Experienced by Latino Communities: A Latent Class Analysis

Gabriel Ramirez; Yinzhou Ou; Ronald Saxton; Alejandra F Miller; Melissa M Cuesta; Ana O Meza; Suzanne Grieb; Kathleen R Page; Cui Yang

doi:10.1007/s40615-025-02514-6

Patterns of Social, Economic, And Health Challenges Due to the COVID-19 Pandemic Experienced by Latino Communities: A Latent Class Analysis

J Racial Ethn Health Disparities. 2025 Jun 27. doi: 10.1007/s40615-025-02514-6. Online ahead of print.

Authors

Gabriel Ramirez¹, Yinzhou Ou¹, Ronald Saxton¹, Alejandra F Miller¹, Melissa M Cuesta¹, Ana O Meza¹, Suzanne Grieb², Kathleen R Page¹, Cui Yang³

Affiliations

¹ Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA.
² Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
³ Department of Health Behavior, Society and Policy, Rutgers School of Public Health, Piscataway, NJ, USA. cui.yang@rutgers.edu.

PMID: 40576870
DOI: 10.1007/s40615-025-02514-6

Abstract

Objective: Latino communities are diverse and necessitate in-depth knowledge of the heterogeneity of Latinos beyond a singular race or ethnicity. Each subgroup may have been impacted by the COVID-19 pandemic differently. This study examined the patterns of challenges that Latinos faced due to the COVID-19 pandemic, identified subgroups with diverse needs, and explored the association between these subgroups and health outcomes.

Methods: A total of 720 participants enrolled between August 2022 and August 2023 as part of the Rapid Acceleration of Diagnostics-Underserved Populations (RADx-UP) initiative in Maryland. Latent class analysis (LCA) was employed to identify subgroups of participants based on self-reported indicators of challenges related to the COVID-19 pandemic, including access to health care, housing, food security, access to clean water, medication, and transportation. Health outcomes included self-report health, anxiety, and depression screening. Logistic regressions were conducted to examine the relationships between class membership, sociodemographic characteristics, and various health outcomes.

Results: A four-class latent class model was identified: Class 1 (31.67%) reported no challenge across all indicators; Class 2 (32.62%) reported minor challenges in accessing health care and medicine and food security; Class 3 (35.72%) reported minor challenge in all indicators, and Class 4 (22.28%) reported major challenges across all indicators. Not having health insurance, fewer years of living in the US, and not being proficient in English were associated with belonging to a group that faced increased challenges due to the COVID-19 pandemic. Class memberships were associated with health outcomes, including depression and anxiety.

Conclusions: This study found that pandemic-associated challenges were highly heterogeneous among Latinos, which were variably associated with health outcomes, including depression and anxiety. Findings from the current research can inform post-pandemic resource allocation and future pandemic preparedness to address longstanding structural inequities. Continued investments are needed to address long-lasting social and economic hardship and public health issues, such as mental health, among the most vulnerable communities.

Keywords: COVID-19; Health inequity; Latent class analysis; Latino; Mental health.

Grants and funding

U01MD017412/National institute of Health