The study examined the associations between lifestyle habits and overweight/obesity among Saudi females attending health science colleges. A total of 454 female students were randomly recruited from five health science colleges at King Saud University, using a multistage stratified cluster sampling technique. Body weight and height were measured, and body mass index was calculated. All participants answered a validated questionnaire to assess physical activity (PA), sedentary behaviors (SB), sleep duration, and dietary habits. Results showed that the prevalence of overweight (21.4%) plus obesity (8.1%) among female participants was 29.5%. There was no significant difference between overweight/obese and nonoverweight/nonobese females in PA, screen time, sleep duration, or dietary habits. Overall, 50.4% of the participants were physically inactive (activity energy expenditure was 8 hours per night) (p < 0.001). It was concluded that half of the Saudi females in this study were physically inactive. Although PA positively impacted some of the lifestyle habits of college females, overweight/obesity was not associated with PA, SB, sleeping time, or dietary habits among the participants. Future research should attempt to elucidate the key factors involved in such relationship.

Poor sleep status is associated with several health problems. Nutritional biomarkers and factors related to poor sleep are understudied. This study aimed to identify nutrition biomarkers and factors related to sleep status in healthy young Saudi females. The study included 92 normal-weight and obese Saudi females aged 19–25. Fasting blood glucose, insulin, and lipid profiles were measured. Insulin resistance was calculated on the basis of the homeostasis model assessment of insulin resistance (HOMA-IR) method. Anthropometric, stress, physical activity, and dietary data were collected. Data on the polyphenol content in foods were retrieved from the Phenol-Explorer database. The sleep status was assessed using the Pittsburgh sleep quality index (PSQI). Associations between variables were assessed using the multiple logistic regression model. Around 76% of the participants had poor sleep status (PSQI > 5). Multiple logistic regression reported high polyphenol intake as a protective factor against poor sleep (OR 0.24; 95% CI 0.07–0.83; p = 0.03) and HOMA-IR as an independent risk for poor sleep (OR 4.97; 95% CI 1.11–22.31; p = 0.04). Other nutritional biomarkers and factors, such as BMI, lipid profile, and vitamins, revealed a trend but were not significant. In conclusion, poor sleep status is associated with insulin resistance and low polyphenol intake among women of reproductive age.

Polyphenols may modulate gut microbiota; however, limited studies have examined this relationship relative to obesity. We aim to investigate the association between polyphenol intake and gut microbiota composition in relation to obesity indices among Saudi Arabian females. This study included 92 adults stratified by body mass index (BMI) into controls (BMI ≥ 18.5–24.9 kg/m²; n = 48) and cases (BMI ≥ 30.0 kg/m²; n = 44), and further divided into high and low polyphenol intake by median intake (252 mg/1000 kcal/day). Fecal samples were collected to analyze the gut microbiota composition via the whole-genome shotgun sequencing technique. Results showed that Flavonifractor plautii and Clostridium bolteae were positively correlated with polyphenol intake in the total sample (r = 0.22, p = 0.03; r = 0.28, p = 0.01, respectively). There were inverse correlations between Blautia wexlerae and polyphenol intake (r = −0.56, p < 0.01) in the case group, and between Bacteroides thetaiotaomicron and polyphenol intake (r = −0.45, p = 0.03) in the control group. Those in the case group with low polyphenol intake, and those with high waist-to-hip ratio (WHR; ≥0.83), showed significantly lower alpha-diversity than those in the control group with normal WHR (<0.83), (p < 0.05). Findings suggest that polyphenols are correlated with specific bacteria and may play an important role in the modulation of gut microbiota and obesity management.