Introduction The research question for the study is whether nighttime media usage (NMU) is associated with disturbed sleep patterns and poor sleep quality in college students, which in turn may contribute to obesity factors. The purpose of the study seeks to evaluate the association between nighttime media use with sleep behaviors and variation in weight status for first-semester college students. The researchers hypothesize that first-semester college students with suboptimal sleep patterns demonstrate sleep disturbances caused by NMU and will be associated with weight gain for the semester (Whipps et al., 2018). Methods The study was a quantitative one, with the primary method of data collection being a survey. Participants were aged 18-24 and were recruited through first-year seminar courses, with the instructors and the study’s main investigator explaining the study and inviting students to participate. The sample of 128 students was recruited, all signing a consent form. Data collection was done through a comprehensive survey consisting of two parts, one evaluating sleep quality and duration while the other measuring NMU. Sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI) that measures 7 variables related to sleep behavior, combining answers to formulate a score that determines the subject global sleep quality score (GSQ). Scores range from 0 to 21, with <5 being good sleepers and anything above resulting in poor sleep (Whipps et al., 2018). NMU was measured through 7 questions, with 6 of the questions using a 5-point Likert scale and the last question determining the number of nights per week that NMU is present for statistical frequency purposes. Participants were also taken to a separate room, where anthropometric measures were taken in privacy with a trained professional. Measures of height, weight, body mass index (BMI), and waist circumference were recorded, with a follow-up date of approximately 10-11 weeks later. Researchers used a combination of data analysis and statistical tests. Descriptive statistics were computed for physical traits and sample t-tests were used to determine differences between genders. Frequency distributions were used for categorical scores for the PSQI evaluation and the NMU questionnaire. Pearson correlations helped to determine the extent of electronic devices used in bed and correlate NMU to categories on the PSQI such as sleep latency, duration, quality, and effectiveness. The type-I error rate with.05 variance was used for the determination of statistical significance. All statistical analyses were performed on the SPSS software (Whipps et al., 2018). Results The mean age of the participants was 18.8 ±0.5, and 93% were of the Caucasian ethnicity, 55% being female. Only a third of the participants slept the recommended 8 hours per night, while 25.4% slept 6.5 hours or less. Based on the PSQI scale, only 59.6% of the participants were optimal sleepers, while 40.4% were borderline or poor sleepers. On average, the change in weight of the participants increased 0.6 kg ±1.92 and a BMI increase of 0.1 kg/m2 ± 5.74. The NMU questionnaire indicates that 92.1% have electronic devices in the room when sleeping, and 94.