Self-reported sleep disturbance patterns in urban Haitians: A latent class analysis

Abstract

Sleep health is critical to overall health and quality of life. We investigated distinct patterns of sleep in Haitian men and women in post-earthquake Haiti, in an urban neighborhood impacted by non-partner sexual violence (NPSV). Latent Class Analysis enabled our development of a three-class model (3: Sleep Disturbance [SD] Often, 2: SD Sometimes, 1: No SD). We assessed relationships between class membership and SD correlates (e.g., experience of NPSV, feelings of depression, suicide intentions, physical health). More men (31.7%) than women (22.9%) experienced NPSV. Overall SD symptoms included 58% insomnia (nearly 2 times the 30% prevalence reported in the U.S.) and 40% restless sleep (>5 times the 7.7% prevalence reported outside of Haiti). Mean SD score for NPSV victims was significantly higher than that for non-victims. In multivariate models, women and men who reported higher level of suicide intentions, and poorer physical health had increased odds of membership in Class 3 (SD often). For women, odds of membership in Class 3 increased consonant with endorsement of NPSV. Reporting depression as mostly/constantly was associated with SD Class 3 for women, but not for men. Consideration of sex differences in sleep patterns and in NPSV experience is crucial and underscores healthy sleep among other critical intervention targets for recovery of NPSV traumatized residents in Haiti and in similar LMIC.

Keywords:

• Non-partner sexual violence
• Haiti earthquake
• Sleep health
• Trauma
• Latent Class Analysis
• Lower-Middle Income countries (LMIC)
• Disasters

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Disclosure statement

No potential conflict of interest was reported by any of the author(s).

Data availability statement

Due to the nature of this research, participants of this study did not agree for their data to be shared publicly, so supporting data is not available.