BACKGROUND: Increased body weight is common among university students; transitioning from high school to university may increase perceived stress levels, thus changing dietary habits and metabolism to promote overweight or obesity. The current study investigates the association between stress and dietary habits among university students in Jordan. MATERIALS AND METHODS: A cross-sectional study was conducted among 221 university students aged between 20 and 25 at Applied Science Private University [ASU]. A self-reported questionnaire was distributed to university students. The questionnaires were divided into three sections: the first was about general characteristics, body weight, change in body weight, and stress eating. RESULT: The survey of 208 participants showed that 64.3% were females, and 84.2% of students lived with their families. Results showed that more than half [51.1%] of the respondents were dissatisfied with their eating habits. Females [57.7%] monitored their food intake more than males did. However, most males [77.2%] reported less eating during stress compared to females. In addition, the data analysis revealed that those who ate more were less likely to monitor their food intake [χ ² =9.734, df = 1, P = .002] or quantity [χ ² =16.704, df = 1, P < .001]. Only 20.8% of the participants preferred sports or hobbies as a stress reduction activity; 29.4% took showers, while 51.1% ignored what made them stressed. Finally, 56.3% of participants reported increased weight after starting university, and it was significantly correlated with stress eating while studying for exams [χ ² =8.762, df = 2, P = .013]. Stress affects university students and can lead to unhealthy eating habits and health issues like obesity. CONCLUSION: Many students face stress during their academic years, which affects their dietary choices. Policies promoting healthy eating habits and stress-reducing activities are important for university students.

This article aims to study the different dietary fat types associated with obesity and coronary indices. A sample of 491 healthy adults was included in a cross-sectional manner. Dietary fats intake, obesity indices (conicity index (CI), body adiposity index (BAI), abdominal volume index (AVI), body roundness index (BRI), and weight-adjusted-waist index (WWI)), and cardiovascular indices (cardiometabolic index (CMI), lipid accumulation product (LAP), and atherogenic index of plasma (AIP)) were calculated and studied. Participants with an acceptable intake of omega-3 had a higher BRI score (1⋅90 ± 0⋅06v.1⋅70 ± 0⋅06). Participants with an unacceptable intake of cholesterol had a higher CI (1⋅31 ± 0⋅11v.1⋅28 ± 0⋅12;P= 0⋅011), AVI (20⋅24 ± 5⋅8v.18⋅33 ± 6⋅0;P <0⋅001), BRI (2⋅00 ± 1⋅01v.1⋅70 ± 1⋅00;P= 0⋅003), WWI (11⋅00 ± 0⋅91v.10⋅80 ± 0⋅97;P= 0⋅032), and lower AIP (0⋅46 ± 0⋅33v. 0⋅53 ± 0⋅33;P= 0⋅024). Total fat, saturated fat (SFA), and polyunsaturated fat (PUFA) intake had a significant moderate correlation with AVI and BRI. The monounsaturated fat (MUFA) intake had a significantly weak correlation with CI, AVI, BRI, WWI, and AIP. Cholesterol and omega-6 had weak correlations with all indices. Similar correlations were seen among male and female participants. The different types of fat intake significantly affected obesity and coronary indices, especially SFA and PUFA, as well as omega-3 and cholesterol. Gender and the dietary type of fat intake have a relationship to influence the indicators of both obesity and coronary indices.

Graphical abstract The association between nutrient intake and obesity and coronary problems has received great attention. Vitamin D, calcium, and magnesium are micronutrients that may affect body fat and body shape. Magnesium intake had the highest impact on coronary indices. While calcium intake had the highest impact on obesity indices. Vitamin D intake had minimal effect on obesity and coronary indices.

Introduction and Objective: Obesity has increased worldwide, and existing anti-obesity medications have treatment limitations that diminish their overall benefits. This study aimed to investigate the effects of orlistat in combination with Elettaria cardamomum “Cardamom” (CAR) extract on working memory, recognition memory, anxiety, and inflammation within hippocampal tissue. Methods: Mice were categorized into two groups: a control group (CD) and a cafeteria diet (CAF) group induced with obesity (CAF) for 10 weeks. The groups were then subdivided into a CAF group treated with orlistat (CAF-ORL), a CAF group treated with orlistat and Elettaria cardamomum (CAF-ORL-CARD), and a group that continued on the CAF. The CAF-ORL group received orlistat at a dosage of 10 mg/kg/day for four weeks, while the CAF-ORL-CARD group received 10 mg/kg/day of orlistat and 500 mg/kg of CAR extract via oral gavage. In the 14th week, various assessments were conducted, including the novel object recognition (NOR) test, Y maze test, marble-burying test (MBT), open-field test, and TNF-α levels in the hippocampus. Result: TNF-α levels in the hippocampal tissue of the CAF group were elevated compared to the CD group (p < 0.01), whereas the CAF-ORL group exhibited reduced TNF-α levels compared to the CAF group (p < 0.01). Moreover, TNF-α levels in the CAF-ORL-CARD group were significantly lower than in the CAF-ORL group (p < 0.01). The recognition index was notably higher in the CAF-ORL group compared to the CAF group (p < 0.01) and higher in the CAF-ORL-CARD group compared to the CAF-ORL group (p < 0.01). However, there were no changes in the open-field test and Y maze test (p > 0.05). Conclusions: Orlistat combined with CAR has positive effects on neuroinflammation and memory, suggesting that this combination may offer potential therapeutic benefits for cognitive impairments and hippocampal dysfunction associated with obesity.

The aim of the present study was to observe the association between obesity indices, blood glucose, and lipid profiles as indicators for its levels. In a cross-sectional study, 491 Jordanian adults were included. Socio-demographic and anthropometric data were measured. Blood samples were collected and tested for fasting plasma glucose (FPG), insulin, and lipid profile. Obesity indices [Conicity Index (CI), Body adiposity index (BAI), Abdominal volume index (AVI), A Body Shape Index (ABSI), Body Roundness Index (BRI), and Weight-adjusted-waist index (WWI)] were calculated using standard formulas. AVI, BRI, and WWI had a higher impact on FPG and lipid profile. They explain 6.2%, 6.6%, and 4.1% of changes observed in FPG and explained 3.1%, 4.1%, and 3.5% of changes observed in total cholesterol (TC), respectively. In addition, they explain 9.9%, 9.7%, and 7.9% of changes in triglyceride (TG), 9.6%, 8.4%, and 6.0% of the variability observed in the high-density lipoprotein cholesterol (HDL), as well as 1%, 1.6%, and 1.5 of change in low-density lipoprotein cholesterol (LDL), and 7.0%, 8.6%, and 6.6% in LDL/HDL ratio; respectively (p<0.001). AVI, BRI, and WWI among obesity indices had the highest impact on blood glucose and lipid profile. The most affected tests were TG, HDL, and LDL / HDL ratio. These indices may be used as noninvasive rapid indicators for high glucose and lipid profiles.