<![CDATA[Premenstrual Syndrome (PMS) significantly impacts reproductive-age females, yet the interplay of lifestyle factors in rural contexts remains under-researched. This study aimed to analyze the relationship between sleep quality and PMS severity among females in Agam Regency, West Sumatra. A quantitative survey was conducted with 124 participants selected via purposive sampling. Data were collected using the Pittsburgh Sleep Quality Index (PSQI) and the Premenstrual Symptoms Screening Tool (PSST), then analyzed using Linear Models (LM) in R. Results showed that 84.67% of respondents reported poor sleep quality. LM analysis revealed that poor sleep quality significantly predicted severity across all PMS categories: PMDD (p = 0.0054), psychological/somatic symptoms (p = 0.0013), and daily dysfunction (p = 0.0007). Additionally, higher BMI was linked to increased PMDD symptoms (p = 0.0290), while stress significantly influenced daily functional impairment (p = 0.0234). In conclusion, poor sleep quality is a primary predictor of severe PMS, exacerbated by high BMI and stress. These findings suggest that sleep hygiene and stress management are critical non-pharmacological interventions for improving menstrual health in rural populations.]]>
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