Abstract Background: The menstrual cycle pattern in women is related to high variability in cycle length of 21–35 days, flow lasts 4–7 days with an average loss of 15–80 ml of blood. The abnormal menstrual pattern is influenced by several factors, including dietary habits, physical exercises, family history of obesity and anthropometric parameters. Objectives: This research was carried out to establish numerous risk elements that depict abnormal menstrual cycle patterns amongst school-going adolescent girls in urban areas of Rishikesh, India. Methods: An age-matched case–control research was implemented in schools in the urban areas of Rishikesh between May and December 2019. A simple random sampling technique was carried out to choose urban wards and schools, and data were assembled in two steps. Adolescent girls (10–19 years) studying in the government and private schools (both Hindi and English medium) of urban Rishikesh areas were included and screened for abnormal menstrual patterns. Equal numbers of age-matched controls were also selected. Data were assembled using a self-scrutinised pre-designed pre-tested semi-structured questionnaire. The independent t-test, Mann–Whitney test, McNemar test, Chi-square test and Fisher’s exact tests were applied for data analysis using the SPSS software version 23.0. Results: A total of 200 school-going adolescent girls (100 cases and 100 age-matched controls) were included in this study. The strength of getting symptoms of menstruation was high amongst cases, and it was found that adolescent girls with high menstrual symptoms had more chances of developing menstrual abnormalities (odds ratio = 6.6; confidence interval = 2.9–17.2). Menstrual abnormality was found significantly associated (P < 0.05) with reduced physical activity, unhealthy dietary patterns and family history of obesity amongst school-going adolescent girls. Conclusions: Unhealthy lifestyles, improper diet, reduced physical activity and family history of obesity were strongly associated with the abnormal menstrual cycle pattern.