Gender-Specific Mental Health Outcomes in Central America: A Natural Experiment

Author:

Montesinos-Yufa Hugo1ORCID,Nagasuru-McKeever Thea2ORCID

Affiliation:

1. Department of Mathematics, Computer Science, and Statistics, Ursinus College, Collegeville, United States

2. Department of Biology, Ursinus College, Collegeville, United States

Abstract

The COVID-19 pandemic and subsequent restrictions have had profound impacts on mental health worldwide, with varying effects across different demographics and regions. Specifically, COVID lockdown measures are known to have had a disparate impact on women. This study aims to better understand this phenomenon by investigating the effect of COVID-19 stringency measures on depression rates among men and women in the Republic of Nicaragua and the Republic of Honduras. The two neighboring countries serve as a natural experiment: the former noted for its relaxed approach to the pandemic, and the latter implementing stricter lockdown measures. Using a Bayesian structural time series model, yearly depression rates were analyzed in both countries, utilizing various weather indicators as predictors, including yearly rainfall and average ground temperature data. In both countries, rates of depression among women were historically higher than among men. The difference in depression rates between women and men increased during the intervention period in both countries (p < 0.001). However, the absolute effect of the intervention in Honduras was significantly higher (p < 0.001) at 0.39 (95% CI: 0.37, 0.41) compared to Nicaragua, which was 0.26 (95% CI: 0.21, 0.31). These findings suggest that the higher stringency measures in Honduras, including prolonged lockdowns and restrictions on movement, may have disproportionately affected women's mental health. These results highlight the importance of considering women’s wellbeing when designing and implementing public health policies, particularly during crises like the COVID-19 pandemic.

Publisher

Science Publishing Group

Reference36 articles.

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1. A Sentiment Analysis of News Articles Published Before and During the COVID-19 Pandemic;International Journal on Data Science and Technology;2024-08-27

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