--- title: How many high school students in Japan miss school due to premenstrual symptoms and what increases the risk? description: About 1 in 9 girls (11.9%) were absent from school due to premenstrual symptoms. Sleep problems, physical symptoms, reduced social activities, and preference url: https://niyora.com/research/papers/the-prevalence-and-risk-factors-of-school-absenteeism-due-to-premenstrual-2016/ --- - [Niyora](https://niyora.com/) - [Research](https://niyora.com/research/) - [Library](https://niyora.com/research/library/) - How many high school students in Japan miss school due to premenstrual symptoms and what increases the risk? Survey study, 2016 # How many high school students in Japan miss school due to premenstrual symptoms and what increases the risk? About 1 in 9 girls (11.9%) were absent from school due to premenstrual symptoms. Sleep problems, physical symptoms, reduced social activities, and preference for salty food increased the risk. Moderate study design 901 high school girls aged 15-19 in Sendai, Japan with regular menstrual cycles ## What they did Cross-sectional survey of 901 high school girls aged 15-19 with regular menstrual cycles in Sendai, Japan using a premenstrual symptoms questionnaire and questions about school absence (more than 1 day per month), taste preference, and exercise habits. ## What they found Moderate-to-severe PMS occurred in 9.9%, PMDD in 3.1%, and 11.9% were absent from school more than 1 day per month. Risk factors for school absence included sleep problems (odds ratio 2.27), physical symptoms (odds ratio 2.24), reduced social activities (odds ratio 2.71), and preference for salty food (odds ratio 1.89). ## What it means for you Physical and emotional premenstrual symptoms are linked to missing school, as are certain lifestyle factors. This is one city in Japan, so results may not apply to other regions or countries. 11.9% Absent from school more than 1 day per month 9.9% With moderate-to-severe PMS 3.1% With PMDD ## About the study Original title The prevalence and risk factors of school absenteeism due to premenstrual disorders in Japanese high school students-a school-based cross-sectional study Authors Tadakawa M, Takeda T, Monma Y et al. Journal BioPsychoSocial medicine Year 2016 Study design Survey study Participants 901 What was tested None Open access Yes Read the paper [doi.org/10.1186/s13030-016-0067-3](https://doi.org/10.1186/s13030-016-0067-3) Original abstract Background: Premenstrual disorders such as premenstrual syndrome (PMS) and premenstrual dysphoric disorder (PMDD) interfere with the daily lives of adolescents. The causes of PMS and PMDD are unknown, but lifestyle habits, such as regular exercise and taste preference are known to be associated. This study was conducted to investigate how premenstrual symptoms affect the school life in Japanese high school students and whether there was a risk factor for school absenteeism that is dependent on the types of premenstrual symptoms or lifestyle habits. Methods: A school-based survey was conducted in Sendai, an industrial city in Japan. A total of 901 girls aged 15-19 with regular menstrual cycles were assessed using the self-reporting premenstrual symptoms questionnaire (PSQ) and questions regarding school absence, taste preference, and exercise. We classified the girls into 'no/mild PMS', 'moderate-to-severe PMS' and 'PMDD' according to the PSQ. The girls were classified into the 'absent' group if they were absent for more than 1 day per month. We used multivariate logistic analysis to examine the risk factors for school absenteeism. Results: The rates of 'moderate-to-severe PMS' and 'PMDD' were 9.9 and 3.1 %, respectively. A total of 107 girls (11.9 %) were classified into the 'absent' group. Significant differences were observed in the prevalence of all premenstrual symptoms (p < 0.001), 'age' (p < 0.001), 'a preference for salty food' (p = 0.001), and 'lack of regular exercise' (p = 0.03) between the 'absent' and 'non-absent' groups. Multivariate analysis revealed that premenstrual symptoms such as 'insomnia or hypersomnia' (odds ratio [OR] 2.27, 95 % confidence interval [CI]: 1.46-4.17) and 'physical symptoms' (OR 2.24, 95 % CI: 1.37-3.66), 'reduced social life activities' (OR 2.71, 95 % CI 1.31-5.59), and 'a preference for salty food' (OR 1.89, 95 % CI: 1.20-2.98) were risk factors for school absenteeism. Conclusions: One in nine Japanese female high school students were absent from school due to premenstrual symptoms. Physical premenstrual symptoms and lifestyles, such as a preference for salty food and a lack of regular exercise, were identified as risk factors for school absenteeism. Reproduced under CC-BY. ## Topics [Premenstrual syndrome (PMS)](https://niyora.com/research/topics/condition-pms/)[Premenstrual dysphoric disorder (PMDD)](https://niyora.com/research/topics/condition-pmdd/)[Low mood and depression](https://niyora.com/research/topics/symptom-depression-mood/)[Exercise and yoga](https://niyora.com/research/topics/treatment-exercise/)[Work and productivity](https://niyora.com/research/topics/life-area-work/)[Students and academic performance](https://niyora.com/research/topics/life-area-education/)[Adolescents and young people](https://niyora.com/research/topics/life-area-adolescents/) Research tells you what helps on average. Niyora helps on the day it hits. Calm down, see it another way, and decide what to say, with a PMS and PMDD app built by a doctor. ## Related studies Systematic review, 2025 How common are PMS, PMDD, and painful periods in nursing students, and do they affect their schooling? Lab study, 2026 Do core stability exercises help women with PMDD? Survey study, 2024 How common is PMDD in working women and what factors are associated with it? Survey study, 2023 What percentage of women aged 20-35 have PMS symptoms and what types are most common? Survey study, 2021 How common are menstrual problems in adolescent girls? Survey study, 2016 Does PMS increase the risk of stress fractures in teenage athletes? Ask AI about this page Copy prompt ChatGPT ↗ Claude ↗ Perplexity ↗ Google AI Mode ↗ Grok ↗