Is the Association Between Alcohol Consumption and Mental Well-Being in University Students Linear, Curvilinear or Absent?

Background: Both alcohol consumption and mental well-being problems have been found to be prevalent in higher educated students and often have severe consequences. However, previous findings of the association between these constructs are mixed, possibly because often linear models are fitted, while some theories suggest a curvilinear association between the two concepts. Objectives: To clarify previously mixed findings, the current study compared curvilinear and linear models for the relationship between alcohol consumption and mental well-being in university students. Because of potential gender differences in this relationship, these models were explored for females and males separately. Data from the first cross-sectional online survey wave of the Healthy Student Life project including 2,631 female and 998 male students was used. The Alcohol Use Disorders Identification Test-consumption was used to measure alcohol consumption. Mental well-being was assessed by six sub-concepts (i.e., depressive symptoms, anxiety, stress, life satisfaction, happiness, and self-rated mental health). Results: For females both linear (for anxiety, life satisfaction, and self-rated mental health) and curvilinear (for depression, stress, and happiness) associations were found, while for males no support for either curvilinear or linear models was found. Conclusions: Results should be interpreted with caution due to the small effect sizes in the relationships for females but may suggest that testing the curvilinear association between alcohol consumption and mental well-being is an important future endeavor.

Prevalence and clustering of health behaviours and the association with socio-demographics and mental well-being in Dutch university students.

The college years represent a vulnerable period for developing health-risk behaviours (e.g., physical inactivity/unhealthy eating habits/substance use/problematic internet use/insufficient sleep). This study examined current health behaviour levels (RQ1), health behaviour classes (RQ2) and between-class differences in socio-demographics (RQ3) and mental well-being (RQ4) among Dutch university students (n = 3771). Participants (Mage = 22.7 (SD = 4.3); 71.2% female/27.3% male/1.5% other) completed an online survey (Oct-Nov 2021). Descriptive statistics (RQ1), Latent Class Analysis (RQ2), and Kruskal-Wallis/Chi-square tests (RQ3-4) were used. RQ1: Prevalence rates suggest that a subsequent proportion of the student sample engages in health-risk behaviours. RQ2: Four classes were identified: class 1 (n = 862) "Licit substance use health-risk group", class 2 (n = 435) "Illicit and licit substance use health-risk group", class 3 (n = 1876) "Health-protective group" and class 4 (n = 598) "Non-substance use health-risk group". RQ3: Class 1 represents relatively more international students and students in a steady relationship. Class 2 represents relatively more older/male/(pre-)master students and students living with roommates/in a steady relationship/with more financial difficulty. Class 3 represents relatively more younger/female students and students living with family/with lower Body Mass Index (BMI)/less financial difficulty. Class 4 represents relatively more younger/non-Western/international/bachelor students and students living with children/single/part of LGBTIQ+ community/with higher BMI. RQ4: Class 3 has significantly higher mental well-being while class 4 has significantly lower mental well-being, relative to the other classes. Above findings provide new insights which can help educational institutes and governments better understand the clustering of students' health behaviours and between-class differences in socio-demographics and mental well-being.

Student-, Study- and COVID-19-Related Predictors of Students' Smoking, Binge Drinking and Cannabis Use before and during the Initial COVID-19 Lockdown in The Netherlands.

Tobacco, alcohol and cannabis are commonly used among university students. However, student lives and their substance use have changed dramatically since the start of the COVID-19 pandemic. This study investigated the impact of COVID-19 on (trends in) weekly smoking, weekly binge drinking and weekly cannabis use in Dutch university students and investigated associated student-, study- and COVID-19-related characteristics. Between April and June 2020, several Dutch higher educational institutes invited their students to participate in an online survey. Data of 9967 students (Mage = 22.0 (SD = 2.6); Nfemale = 7008 (70.3%)) were available for analyses. Overall, weekly smoking remained stable (±11.5%), weekly binge drinking decreased (from 27.8% to 13.9%) and weekly cannabis use increased (from 6.7% to 8.6%). Male gender, not living with parents, being a bachelor student, having less financial resources and less adherence to the COVID-19 measures were found to increase the risk of substance use (before/during the first COVID-19 lockdown). Additionally, male gender, not living with parents, being a bachelor student, not being born in the Netherlands and having a student loan contributed to the likelihood of increased substance use during COVID-19. Patterns of characteristics contributing to the likelihood of decreased weekly substance use during COVID-19 were less clear. The risk factors male gender, not living with parents and being a bachelor student do not only contribute to the likelihood of using substances but also contribute to the likelihood of increased use during a lockdown. Prevention and intervention programs should especially target these risk groups.

Maternal risk associated with the VACTERL association: A case-control study.

BACKGROUND: The VACTERL association (VACTERL) includes at least three of these congenital anomalies: vertebral, anal, cardiac, trachea-esophageal, renal, and limb anomalies. Assisted reproductive techniques (ART), pregestational diabetes mellitus, and chronic lower obstructive pulmonary disorders (CLOPD) have been associated with VACTERL. We aimed to replicate these findings and were interested in additional maternal risk factors. METHODS: A case-control study using self-administered questionnaires was performed including 142 VACTERL cases and 2,135 population-based healthy controls. Multivariable logistic regression analyses were performed to estimate confounder adjusted odds ratios (aOR) and 95% confidence intervals (95%CI). RESULTS: Parents who used invasive ART had an increased risk of VACTERL in offspring (aOR 4.4 [95%CI 2.1-8.8]), whereas the increased risk for mothers with CLOPD could not be replicated. None of the case mothers had pregestational diabetes mellitus. Primiparity (1.5 [1.1-2.1]) and maternal pregestational overweight and obesity (1.8 [1.2-2.8] and 1.8 [1.0-3.4]) were associated with VACTERL. Consistent folic acid supplement use during the advised periconceptional period may reduce the risk of VACTERL (0.5 [0.3-1.0]). Maternal smoking resulted in an almost twofold increased risk of VACTERL. CONCLUSION: We identified invasive ART, primiparity, pregestational overweight and obesity, lack of folic acid supplement use, and smoking as risk factors for VACTERL.

Causes of Variation in Food Preference in the Netherlands.

Our current society is characterized by an increased availability of industrially processed foods with high salt, fat and sugar content. How is it that some people prefer these unhealthy foods while others prefer more healthy foods? It is suggested that both genetic and environmental factors play a role. The aim of this study was to (1) identify food preference clusters in the largest twin-family study into food preference to date and (2) determine the relative contribution of genetic and environmental factors to individual differences in food preference in the Netherlands. Principal component analysis was performed to identify the preference clusters by using data on food liking/disliking from 16,541 adult multiples and their family members. To estimate the heritability of food preference, the data of 7833 twins were used in structural equation models. We identified seven food preference clusters (Meat, Fish, Fruits, Vegetables, Savory snacks, Sweet snacks and Spices) and one cluster with Drinks. Broad-sense heritability (additive [A] + dominant [D] genetic factors) for these clusters varied between .36 and .60. Dominant genetic effects were found for the clusters Fruit, Fish (males only) and Spices. Quantitative sex differences were found for Meat, Fish and Savory snacks and Drinks. To conclude, our study convincingly showed that genetic factors play a significant role in food preference. A next important step is to identify these genes because genetic vulnerability for food preference is expected to be linked to actual food consumption and different diet-related disorders.