Exploring the Association Between Body Mass Index and Dysmenorrhea in Adolescent Girls in Uganda.

The utilized baseline data from the Suubi4Her study, a 5-year cluster randomized controlled trial funded by the National Institute of Mental Health, was conducted in 47 public secondary schools in the greater Masaka region of Southwestern Uganda. Schools were in five geopolitical districts—Masaka, Kyotera, Lwengo, Rakai, and Kalungu. Public schools, including those with both day and boarding sections, were selected because they predominantly serve economically disadvantaged students and allow for regular family involvement, as many students return home daily. Purely boarding schools were excluded due to logistical constraints related to family engagement, while private schools were excluded to reduce socioeconomic variability that could confound study outcomes. The Suubi4Her study aimed to prevent HIV risk behaviors, improve mental health, and enhance educational outcomes among adolescent girls aged 14 to 17 years ( Mutumba et al., 2022 ; Ssewamala et al., 2018 ). All eligible participants were identified in collaboration with the school administration and the Masaka Diocese. Informational flyers outlining the study and enrollment process were then distributed to these individuals. Interested adolescents and their caregivers subsequently had individual meetings with the local project coordinator to discuss eligibility criteria, the voluntary nature, and objectives of the study; the level of participation expected; potential risks and benefits; and safety and confidentiality considerations. To meet the eligibility criteria, participants needed to be (1) female, (2) between the ages of 14 and 17, and (3) in their first or second year of secondary school. In total, 1,260 adolescent girls were enrolled between March 2018 and February 2019, as shown in the CONSORT diagram ( Figure 1 ). For details on recruitment, see the study protocol paper ( Brathwaite et al., 2024 ; Karimli et al., 2024 ; Ssewamala et al., 2018 ). Initially, the survey instruments were translated into Luganda, the local language spoken in the study area. To ensure consistency and accuracy, the survey instruments were back-translated into English and supervised by trained experts from Makerere University School of Languages, Literature, and Communication in Uganda. The translators each hold a bachelor’s degree specializing in Luganda and English at the college level. They are all trained in the local language, Luganda, and they speak Luganda. In addition, they all studied English starting from primary school throughout the university, making them fluent in both English and Luganda. The written translations were reviewed and cross-checked by at least three people to ensure accuracy in wording and meaning. Local research assistants, fluent in English and Luganda, were responsible for collecting the data. The research assistants received training in good clinical practice, data collection techniques, and human subjects’ protection and completed the Collaborative Institutional Training Initiative Human Subjects certificate. Following enrollment, participants underwent a structured interview (baseline interviews), each lasting between 60 and 90 minutes. The data used for our analyses are presented here. The outcome of interest was dysmenorrhea/menstrual pain, where participants were asked to rate the average level of pain they experienced during their menstruation period. The scale was from 0 to 10, whereby 10 was the worst pain they have ever had and 0 was no pain. The primary predictor was BMI, calculated by dividing participants’ weight in kilograms by their height in square meters. The research team collected actual height and weight measurements using a Seca Mechanical Floor Scale Model 762 and an Oxford 67-mm height rod. Weight was recorded to the nearest tenth of a kilogram, and height was measured to the nearest tenth of a centimeter. These measurements were used to calculate BMI. We used the World Health Organization’s BMI chart for girls between 5 and 19 years to determine participants’ BMI and their corresponding standard deviation ( SD ) ( WHO, 2024 ). BMI was divided into five categories: overweight (BMI = 29.7 kg/m 2 or higher at 19 years), obesity (BMI = 25.0–29.6 kg/m 2 at 19 years), normal (BMI = 18.7–24.99 kg/m 2 at 19 years), thinness (BMI = 14.7–18.6 kg/m 2 at 19 years), and severe thinness (BMI = less than 14.7 kg/m 2 at 19 years) ( WHO, 2024 ). Other variables included participants’ sociodemographic characteristics, for example (1) participants’ age ranging from 14 to 17 years, (2) orphanhood status (non-orphan, single orphan, and double orphan), (3) religion (Catholic, Protestant, Muslim, born again), (4) total number of people in a household, and (5) household asset ownership measured by a 21-item index that assessed ownership of tangible household assets. Participants were asked, “Does the family you live in own the following: house, rentals, land, banana plantation, coffee plantation, car, bicycle, or television?” The total number of assets was summed up to get the total number of assets. We used this index as a proxy for socioeconomic status (SES) because in the Ugandan context, characterized by informal economies and irregular income, direct income or expenditure data are often unreliable. Asset-based measures, as shown by Booysen et al. in seven sub-Saharan African countries, provide a stable, long-term indicator of household wealth and living standards ( Booysen et al., 2008 ). In addition, distance from the health center was included in the analysis. Participants were asked about the distance to the nearest medical institution, doctor, or nurse. The response options were “near” (approximately 0–2 km, within walking distance) and “far” (more than 2 km, not easily accessible by walking). We also added participants’ nutrition or dietary uptake. This dichotomous classification reflects the local context where walking is the main mode of transport, and geographic distance is a commonly used proxy for healthcare access in low-resource settings where proximity can be a key barrier ( Kim et al., 2021 ; Tanou & Kamiya, 2019 ). Participants were asked how often they ate fish, eggs, milk, and tea with sugar in the past week. The items were rated on a 5-point Likert scale (0–4), where 0 = none, 1 = once, 2 = twice, 3 = three times, and 4 = every day. Items were added up to get a composite score. The total scores ranged from 0 to 16. These specific items were selected because they are commonly consumed in Uganda and serve as significant sources of protein, calcium, and energy for adolescents. Additionally, tea with sugar is a culturally prevalent beverage contributing to sugar intake. Focusing on these items allows for a practical assessment of dietary quality in low-resource settings, where comprehensive dietary evaluations may not be feasible ( FOA, 2021 ). Substance use was assessed by asking participants about their alcohol and smoking behaviors. Specifically, participants were asked if they had ever had a drink of alcohol other than a few sips (yes = 1 vs. no = 0). Additionally, participants were asked whether they had ever tried cigarette smoking, even one or two puffs (yes = 1 vs. no = 0). Last, participants were asked whether they had ever used marijuana (yes = 1 vs. no = 0). The three items were added to get a composite score for substance use. Depressive symptoms were measured using Beck’s Depression Inventory ( Beck et al., 1961 ). The 21-item scale measures characteristic attitudes and symptoms of depression, ranked based on severity (0 = least, 3 = most). Scores range from 0 to 63 (alpha = 0.83), with higher scores indicating higher levels of depressive symptoms. Social support was measured using 30 items adapted from the Friendship Qualities Scale ( Bukowski et al., 1994 ). Items assessed the impressions of the quality of adolescents’ friendships and relationships, and they rated these on a 5-point Likert scale ranging from 1 = never to 5 = always. Scores range from 30 to 150 (alpha = 0.81), with high scores indicating higher levels of social support and relationships. Exposure to emotional and physical violence was measured using 12 items adapted from the Multiple Indicator Cluster Survey (MICS) for children aged 5 to 17 years ( UNICEF, 2018 ). Respondents were asked how adults in their households have taught them and their siblings the right behaviors and/or addressed behavioral problems in the past month. Items were binary coded as 1 = yes and 0 = no. Sample items included “shouted, yelled, screamed at you,” “hit with a belt, hairbrush, stick or another hard object,” and “called them dumb, lazy or another name.” All the data were analyzed using Stata version 18.0. Participant characteristics were summarized using means and SD s for continuous variables and percentages for categorical variables. We used mixed effects linear regression to assess the association between BMI and menstrual pain. At level 1, we included study participants, and these were clustered under the schools, which we included in level 2. We examined the models to determine that the residuals were normally distributed, there was homoskedasticity, and no multicollinearity was detected. In the model, we added an interaction term between age and BMI because the effect of BMI on menstrual hygiene differs at different ages. Without the interaction term, the model assumes that the effect of BMI is the same across all ages, which is not true. We reported the regression coefficients and their Huber–White cluster-adjusted confidence intervals (CIs), which we adjusted for clustering at the school level. We also reported random effects, including the variance of the school and participant random intercepts, the variance of the residuals, and the intraclass correlation coefficients for the school and participant levels. Statistical significance was assessed at a level of 0.05.

Participant characteristics are shown in Table 1 . The mean age of the 1,260 recruited participants was 15.37 years ( SD = 0.87 years). About 83% of participants had both parents alive, 17% had lost one or both parents, the majority of the participants (62.3%) were Catholic, and the average number of people in a household was 7. The mean score for total family assets was 11.46 ( SD = 3.26). The results indicate that a few participants reported the use of substances with a mean score of 0.07 ( SD = 0.28). We found out that the BMI of most participants (77.78%) fell into the normal category. Generally, participants reported experiencing low levels of dysmenorrhea (mean = 3.86, SD = 3.58). At baseline, 89.1% reported to have started menstruating. As shown in Table 2 , the results from the mixed regression model revealed significant associations between age, total assets, social support, depression, overweight, obesity, and dysmenorrhea. Specifically, an increase in age was associated with increased dysmenorrhea ( β = 0.35; 95% CI, 0.07–0.63; p = 0.014). An increase in total family assets was associated with decreased dysmenorrhea ( β = −0.12; 95% CI, −0.19 to −0.05; p = 0.001). Similarly, an increase in social support was associated with reduced dysmenorrhea ( β = −0.02; 95% CI, −0.03 to −0.001; p = 0.030). An increase in depression levels was associated with an increase in dysmenorrhea ( β = 0.05; 95% CI, 0.03–0.07; p = 0.001). Regarding BMI, being overweight was associated with reduced dysmenorrhea ( β = −11.70; 95% CI, −21.85 to −1.55; p = 0.024) and obesity was also associated with reduced dysmenorrhea ( β = −25.04; 95% CI, −49.87 to −0.22; p = 0.048) compared to normal weight/BMI. Additionally, the interaction between BMI and age revealed significant results. Thus, the effect of BMI on dysmenorrhea depended on age. Specifically, overweight was associated with increased dysmenorrhea for older participants than for younger participants ( β = 0.79; 95% CI, 0.13–1.44; p = 0.019); similarly, obesity was also associated with increased dysmenorrhea for older participants than younger participants ( β = 1.66; 95% CI, 0.03–3.29; p = 0.045).

This study examined the association between BMI and dysmenorrhea among adolescent girls in Uganda, while also examining the influence of various contextual and psychosocial factors, including age, dietary habits, orphanhood status, distance from health centers, socioeconomic status, substance use, social support, exposure to violence, and depression. Notably, the relationship between BMI and dysmenorrhea was moderated by age, such that the impact of overweight and obesity on menstrual pain increased as girls grew older. Mixed effects regression analysis revealed that age and depressive symptoms were associated with dysmenorrhea. In contrast, greater household assets and higher levels of social support were linked to reduced pain. Although girls with BMI in the overweight and obese categories reported less menstrual pain overall compared to those with normal BMI, the interaction between BMI and age suggests that excess body weight may be associated with increased pain in older adolescents. This finding aligns with other research showing a significant negative correlation between BMI and dysmenorrhea pain, where lower BMI was linked to higher reported pain ( Islami, 2024 ). This may be due to hormonal instability or insufficient adipose-derived estrogen. Interestingly, this result contrasts with existing literature, suggesting that the severity of dysmenorrhea often decreases with age ( Tavallaee et al., 2011 ; Unkels, 2010 ). However, data from a Ugandan study indicates that older girls (14–17 years old) are more likely to experience menstrual pain on the first day of their menstruation, with odds increasing across older age brackets ( Tanton et al., 2021 ), possibly reflecting population-specific factors such as environmental stressors, cultural norms, or nutritional influences. Further research is needed to explore this inconsistency and understand the contextual factors affecting the relationship between age and dysmenorrhea in this setting. Regarding socioeconomic status, total assets were significantly associated with reduced menstrual pain. This suggests that better economic conditions might provide resources that help manage or mitigate the experience of dysmenorrhea, potentially through better access to healthcare, improved nutrition, or reduced stress. This finding aligns with existing literature that links financial constraints to menstrual pain ( Medina-Perucha et al., 2024 ). On the contrary, results from a study in India, where 70% of the respondents experienced primary dysmenorrhea, indicated that respondents with higher socioeconomic status were 2.71 times more likely to experience primary dysmenorrhea than those who with lower socioeconomic status ( Sethi et al., 2024 ). These contradictory findings highlight the complex and context-specific nature of the relationship between socioeconomic status and primary dysmenorrhea. Social support also showed a significant association with dysmenorrhea. Higher levels of social support were linked to lower levels of menstrual pain, highlighting the importance of strong social networks in managing MH. These findings align with previous research indicating that social support has a positive effect on menstrual pain ( Alonso & Coe, 2001 ; Whittle et al., 1987 ). Depression was another significant factor, with higher levels of depression being associated with increased menstrual pain. This highlights the complex interaction between mental health and physical symptoms, suggesting that interventions aimed at reducing dysmenorrhea should also incorporate psychological support. Our findings are consistent with previous research that has documented a similar relationship between depression and primary dysmenorrhea ( Padda et al., 2021 ). The study did not find significant associations between dietary factors and dysmenorrhea, which contrasts with previous research suggesting that a healthier diet is associated with lower levels of menstrual pain ( Bajalan et al., 2019 ; Balbi et al., 2000 ). For example, a study among Spanish students found that consuming fewer than two pieces of fruit per day significantly increased the likelihood of experiencing menstrual pain ( Onieva-Zafra et al., 2020 ). Regarding substance use, although not statistically significant in this study, previous studies have demonstrated a correlation between substance use and dysmenorrhea ( Jenabi et al., 2019 ) ( Qin et al., 2020 ). Additionally, factors such as distance from the health center, exposure to violence, and orphanhood status were not significant. This might indicate that while these factors are essential in general adolescent health, their direct impact on menstrual pain is less pronounced in this context. One notable exception in the BMI category was the finding that overweight and obesity were significantly associated with reduced menstrual pain. While this contrasts with some literature suggesting that higher BMI increases the risk of dysmenorrhea ( Itriyeva, 2022 ; Tang et al., 2020 ), similar results have been observed elsewhere. For example, Khodakarami et al. (2015) found that the frequency and severity of dysmenorrhea were higher among individuals with normal BMI, and no significant relation was found between BMI and the severity of menstrual pain. This suggests that the association between BMI and dysmenorrhea may be nonlinear and context-dependent.

Overall, these results underscore the importance of considering a multifaceted approach to addressing dysmenorrhea and incorporating economic and psychological support into health interventions. Future research should develop region-specific growth references and employ mixed-method approaches to further understand the underlying mechanisms influencing BMI and menstrual pain. This study provides valuable insights for policymakers, health practitioners, and researchers advocating for integrated strategies to enhance MH and the overall well-being of adolescent girls in Uganda.

Using self-reported data for variables such as dietary habits, substance use, and menstrual pain introduces the possibility of recall bias and social desirability bias, which could affect the accuracy of the findings. Additionally, the study was conducted in a specific region of Uganda and included only public secondary schools, excluding purely boarding and private schools. While this approach helped to maintain a relatively homogeneous sample and minimize variability in socioeconomic background, it may limit the generalizability of the findings to other areas with different educational settings and distinct cultural, socioeconomic, and environmental contexts. Furthermore, although BMI is widely used to indicate health and nutritional status, it has notable limitations. It does not distinguish between fat and lean tissue and fails to reflect how fat is distributed throughout the body. These aspects are important in evaluating metabolic and reproductive health. BMI provides only a limited view of adiposity and does not capture the biological, genetic, and physiological diversity of obesity ( Bray, 2023 ). More advanced methods like waist circumference, body composition analysis, or imaging technologies may provide more accurate assessments. Future studies should consider integrating such approaches to better capture the complexity of body composition and its relationship with menstrual pain. Additionally, the dietary indicators used in this study, including consumption of fish, eggs, milk, and tea with sugar, may not fully represent nutritional adequacy. Key food groups such as fruits and vegetables were not included, which limits the comprehensiveness of the dietary measure and should be addressed in future research. Last, healthcare access was measured using self-reported geographic distance to the nearest facility, which, while practical in low-resource settings, may not fully capture other critical dimensions such as service availability, quality of care, affordability, or provider attitudes. Future studies should consider more comprehensive measures to assess access to healthcare.

Given the association between socioeconomic status and reduced dysmenorrhea, the research underscores the critical role of policy frameworks integrating economic support programs to improve living conditions and access to healthcare services, including those that address menstrual and mental health and access to nutritious foods for adolescents. Moreover, policies should incorporate comprehensive health education programs in schools that address MH and physical activity. This can help adolescents better manage dysmenorrhea and improve overall well-being. Health practitioners should adopt a holistic approach when addressing menstrual pain, considering physical, emotional, socioeconomic status, and mental health. Also, mental health support should be integrated into treatment plans for dysmenorrhea, as higher levels of depression are associated with increased menstrual pain. The context-specific nature of these results underscores the need for further research to understand the underlying mechanisms and to develop targeted interventions that can effectively address menstrual pain across different BMI categories. Understanding why overweight and obesity are associated with reduced menstrual pain in this context could lead to more effective interventions.

Adolescence encompasses the age range of 10 to 19 years and represents a transitional phase from childhood, characterized by significant physical, sexual, psychological, and social transformations ( WHO, 2025 ). Additionally, adolescence is a critical period during which significant decisions are made and young individuals develop skills and competencies that will be employed throughout adulthood ( Bahadori et al., 2023 ). Furthermore, adolescence is the stage at which the distinguishing characteristics of puberty emerge, including the maturation of sexual traits and the onset of menstruation ( Boxer et al., 1983 ). As such, menstruation represents a key milestone in female adolescent development and marks the transition into reproductive maturity ( DiVall & Radovick, 2008 ). The age at which girls experience onset of menstruation varies ( Marshall & Tanner, 1969 ). However, in some contexts, such as among Black adolescents in South Africa and girls in the United States, menarche typically occurs between 12 and 13 years of age, with median ages reported at 12.4 and 12.5 years, respectively ( Biro et al., 2018 ; Jones et al., 2009 ). In Cameroon, studies have shown variation by location, with mean ages at menarche onset of 13.18 years for urban girls, 13.98 years for those in suburban areas, and 14.27 years for girls in rural areas ( Pasquet et al., 1999 ). In Uganda, menarche has been reported to occur between 9 and 15 years ( Nsimenta, 2024 ), illustrating the wide variability across populations and settings. Factors influencing the early onset of menstruation have been thought to include dietary habits, socioeconomic position, overall health status, physical activity levels, family size, seasonal variations, and genetics ( Lacroix et al., 2017 ). Adolescent females and adult women commonly experience menstrual pain, medically termed dysmenorrhea, which is characterized by cramp-like abdominal discomfort that may arise before or during the menstrual cycle ( Bernardi et al., 2017 ). Primary dysmenorrhea, distinguished by the absence of pathological abnormalities in the pelvic organs, is more prevalent ( Davis & Westhoff, 2001 ; Hewitt & Gerancher, 2018 ). Conversely, secondary dysmenorrhea is associated with underlying pelvic pathologies, such as endometriosis ( Franjić, 2019 ). Dysmenorrhea significantly contributes to educational disruption due to school absenteeism among adolescent females ( Franjić, 2019 ) and also results in workplace absence in adult women ( Ponzo et al., 2022 ). Generally, menstrual pain is associated with disruption of daily activities ( Rafique & Al‐Sheikh, 2018 ). The clinical manifestations of dysmenorrhea are diverse and can include headache, emesis, vertigo, abdominal cramping, diarrhea, insomnia, depressive states, and increased irritability ( Harel, 2006 ). Research has established a correlation between dietary intake and dysmenorrhea prevalence. A study by Balbi et al. suggested an association between the intake of fish, eggs, and fruits and the alleviation of dysmenorrhea symptoms ( Balbi et al., 2000 ). Dysmenorrhea is reported to impact between 50% and 90% of menstruating adolescents, exerting a considerable influence on their physical and psychosocial well-being ( Kciuk & Kives, 2021 ). Effective management of this condition is essential for maintaining health and includes empiric and complementary therapies. Empiric treatments may encompass the use of nonsteroidal anti-inflammatory drugs (NSAIDs) and hormonal contraceptives (e.g., implant, patch, Depo-Provera, vaginal ring), which have been shown to alleviate symptoms ( Zahradnik et al., 2010 ). In addition, complementary interventions such as dietary modification, including nutritional supplements like vitamin D, and engagement in regular physical activity have been associated with reducing symptom severity ( Gerancher, 2018 ). Indeed, evidence from clinical studies suggests that vitamin D supplementation can contribute to the improvement of dysmenorrhea ( Bahrami et al., 2018 ). Adolescence is marked by critical developmental milestones, including substantial changes in body composition and weight, often quantified by the body mass index (BMI), an anthropometric measurement calculated as weight in kilograms divided by the square of height in meters ( CDC, 2011 ). While BMI is a common proxy for nutritional and health status ( Bahrami et al., 2018 ), it does not capture changes in body fat composition ( Bray, 2023 ). Adipose tissue, however, functions as an endocrine organ and can alter estrogen levels, potentially contributing to menstrual irregularities and dysmenorrhea ( Bray, 2004 ). Research has shown that higher BMI levels are associated with heavier menstrual bleeding and more intense menstrual pain, likely due to hormonal and inflammatory disruptions ( Itriyeva, 2022 ; Tang et al., 2020 ). Physiologically, dysmenorrhea is primarily caused by elevated levels of prostaglandins released during menstruation, which trigger strong uterine contractions. These contractions can result in tissue hypoxia and ischemia, leading to menstrual pain ( Nagy et al., 2023 ). Conversely, inadequate body fat may delay menarche or result in amenorrhea. Early research by Frisch et al. indicates that a minimum of 17% body fat is necessary to initiate menarche and about 22% is needed by age 18 to sustain a regular menstrual cycle ( Baker, 1985 ; Frisch, 1984 ; Frisch & McArthur, 1974 ). Empirical evidence supports these findings. A study of 8,579 women found that being underweight or obese significantly increased the risk of dysmenorrhea, with BMI shifts in and out of the underweight category associated with a 30% higher risk ( Ju et al., 2015 ). Similarly, research involving 400 girls in Rajasthan found that dysmenorrhea was more common among those who were underweight. While the majority of girls without menstrual pain had normal BMI, a small proportion of girls with normal BMI also experienced mild dysmenorrhea. Specifically, 0.97% of rural girls and 7.07% of urban girls with normal BMI reported mild menstrual pain, indicating that normal BMI does not entirely preclude the occurrence of dysmenorrhea ( Chauhan & Kala, 2012 ). Additionally, dysmenorrhea was found to be 1.5 times more prevalent in underweight Turkish women than in those who were overweight ( Ozerdogan et al., 2009 ). In Spain, 40% of adolescents who attempted weight reduction experienced menstrual pain and cycle irregularities, regardless of their BMI classification ( Montero et al., 1996 ). These findings underscore the importance of maintaining a healthy body composition to support menstrual health (MH). Additional research supports the protective effect of proper nutrition and regular exercise in reducing menstrual pain ( Chauhan & Kala, 2012 ; Hirata et al., 2002 ; Itriyeva, 2022 ). In low-resource settings such as Uganda, poverty remains a pressing concern that directly affects adolescent girls’ health and well-being. As of 2019–2020, approximately 20.3% of the population lived below the national poverty line; this figure was about 30% when applying a revised poverty line ( UBOS, 2021 ; Worldbank, 2023 ). Multidimensional poverty affected 42.1% of the population ( UBOS, 2022 ), while the average of the absolute poverty rate stood at 16.9%. This socioeconomic disadvantage contributes to MH challenges, potentially by constraining access to nutritious food, which may ultimately have long-term impacts on MH ( Kwak et al., 2019 ; Medina-Perucha et al., 2024 ). Moreover, the stress and anxiety resulting from economic hardship can exacerbate mental health issues, such as depression, which have been linked to increased prevalence and severity of dysmenorrhea ( Li et al., 2023 ). Furthermore, the phenomenon of period poverty is linked to dysmenorrhea, wherein the lack of access to sanitary products leads women to use less-hygienic alternatives, potentially resulting in urinary tract infections that contribute to menstrual discomfort ( Das et al., 2015 ). Dysmenorrhea affects both individual well-being and the economy, as it reduces work productivity ( Kanwal et al., 2019 ). It is a prevalent cause of recurrent short-term absenteeism among women of reproductive age, leading to missed school and workdays. Studies have shown that students experiencing moderate to severe menstrual pain are more likely to report difficulty concentrating in class, inability to complete assignments, and lower academic achievement ( Mahwish et al., 2024 ; Mesele et al., 2022 ). In the workplace, women experiencing dysmenorrhea often had diminished productivity and increased absenteeism, leading to substantial economic losses ( Schoep et al., 2019 ; Yáñez-Sarmiento et al., 2024 ). Additionally, dysmenorrhea is linked to increased healthcare costs, as shown in a study in which women with primary and secondary dysmenorrhea had 2.2 and 2.9 times higher expenditures than controls ( Akiyama et al., 2017 ). Regarding substance use, studies have demonstrated a correlation between smoking and dysmenorrhea ( Jenabi et al., 2019 ), with smoking women experiencing more detrimental reproductive health consequences ( Qin et al., 2020 ). This intersection of behavioral and reproductive health underscores the multifaceted nature of menstrual disorders. Social support is another factor related to menstrual pain. Disruptions in social relationships can intensify the impact of negative emotions, such as depression and anxiety, which are strongly associated with increased menstrual pain severity ( Alonso & Coe, 2001 ). A study by Whittle et al. (1987) found that women who experienced a loss of social support reported more severe menstrual symptoms compared to those with stable social support. Furthermore, body image concerns have also been linked to dysmenorrhea. Adolescents who experience menstrual pain often report greater dissatisfaction with their body appearance and are more prone to depressive symptoms, suggesting that negative body image may exacerbate the perception and severity of menstrual discomfort ( Allyn et al., 2019 ; Ambresin et al., 2012 ). In addition, exposure to physical or sexual violence increases the risk of menstrual disorders ( Islas-Preciado et al., 2021 ; Moussaoui & Grover, 2022 ). Psychological stress may activate the hypothalamic–pituitary–adrenal axis, which may disrupt hormonal balance and amplify pain sensitivity, thereby worsening dysmenorrhea symptoms ( Herman et al., 2016 ). In this study, we examined whether BMI is associated with dysmenorrhea among adolescent girls in Uganda. Guided by the biopsychosocial model, we explore whether contextual and psychosocial factors, including age, dietary habits, orphanhood status, distance from the health center, socioeconomic status, substance use, social support, exposure to violence, and depression, influence this relationship. We hypothesize that BMI is associated with dysmenorrhea and that this relationship may be shaped by the factors listed above. While the relationship between BMI and dysmenorrhea has been widely studied in other regions, there remains a significant gap in the literature regarding how BMI specifically impacts dysmenorrhea in the context of Uganda. To the best of our knowledge, this is the first study in Uganda to examine the association between BMI and dysmenorrhea among adolescent girls and to explore the extent to which contextual and psychosocial factors may influence this relationship, thereby contributing valuable insights to understanding the unique experiences and challenges this population faces. The biopsychosocial model serves as the guiding theory for this study. The model by George Engel (1977) is an interdisciplinary framework that posits that a dynamic interaction among biological, psychological, and social factors determines health and illness. This holistic approach provides a comprehensive understanding of an individual’s health status by considering the complex interplay of these dimensions. In the context of MH, the biopsychosocial model can be applied to understand the relationship between BMI and dysmenorrhea. Biologically, both high and low BMI can disrupt hormonal balance ( Silvestris et al., 2018 ), leading to an irregular menstrual cycle. For instance, higher BMI is associated with elevated estrogen levels, which may cause heavier or more painful menstrual periods. In comparison, lower BMI may reduce estrogen production, potentially leading to amenorrhea or cycle irregularities ( Chisholm, 2023 ). Psychologically, stress and emotional well-being, which can be influenced by an individual’s body image and BMI-related self-esteem, may also impact MH. High levels of stress ( Vigil et al., 2022 ) and negative body image can lead to hormonal imbalances ( Nuriannisa & Faradiba, 2023 ) that affect menstrual regularity. For example, biologically, higher BMI may increase estrogen levels, leading to irregular menstrual cycles or more intense uterine contractions, contributing to menstrual pain. Psychologically, negative body image associated with a higher BMI can increase stress, which further disrupts hormonal regulation ( Segal & Gunturu, 2024 ) and worsens menstrual symptoms. Socially, adolescents with higher BMI may experience stigma related to their body size, which can occur in schools, workplaces, and healthcare settings ( Fulton et al., 2023 ). Such stigma may discourage them from seeking services, including medical care for menstrual pain, due to concerns about judgment or being treated unfairly. Avoidance of healthcare services can contribute to unmanaged symptoms and increased discomfort ( Casola et al., 2021 ), thereby intensifying the experience of dysmenorrhea.