METHODS: Participants comprised 1912 college students (16-28 years old, 47.2% female) from three universities in Jilin Province, China, who completed the self-report assessments of psychological strains (40 items Psychological Strains Scale) and suicidal behaviors (Suicidal Behaviors Questionnaire-Revised). The demographic characteristics included four variables: health status, psychological status, academic status and economic status.
RESULTS: Approximately 15.0% (286/1912) of participants were classified as having suicide risk, based on the cut-off scores of the SBQ-R. The prevalence of suicidal behaviors among males and females was 11.9% (120/1009) and 18.4% (166/903), respectively. Value strain (OR = 1.075, 95%CI: 1.057-1.094), aspiration strain (OR = 1.082, 95%CI: 1.064-1.101), deprivation strain (OR = 1.073, 95%CI: 1.052-1.093), and coping strain (OR = 1.095, 95%CI: 1.075-1.116) were risk factors for suicidality in college students. Coping strain (OR = 1.050, 95%CI: 1.023-1.077) was still positively associated with suicide risk in multivariate logistic regression. Logistic regression analysis indicated that coping strain had the highest correlation with suicidal behaviors.
LIMITATIONS: The directionality of the relationships cannot be deduced because this study is cross-sectional.
CONCLUSION: This study confirms a strong association between psychological strains and suicidal behaviors in college students. Some measures can be taken to reduce psychological strains to mitigate suicide risk among college students. More studies investigating coping strain among college students are warranted.
OBJECTIVES: We aimed to establish the impact of including/excluding pregnancies with adverse neonatal outcomes when constructing GWG charts.
METHODS: This is an individual participant data analysis from 31 studies from low- and middle-income countries. We created a dataset that included all participants and a dataset restricted to those with no adverse neonatal outcomes: preterm < 37 wk, small or large for gestational age, low birth weight < 2500 g, or macrosomia > 4000 g. Quantile regression models were used to create GWG curves from 9 to 40 wk, stratified by prepregnancy BMI, in each dataset.
RESULTS: The dataset without the exclusion criteria applied included 14,685 individuals with normal weight and 4831 with overweight. After removing adverse neonatal outcomes, 10,479 individuals with normal weight and 3466 individuals with overweight remained. GWG distributions at 13, 27, and 40 wk were virtually identical between the datasets with and without the exclusion criteria, except at 40 wk for normal weight and 27 wk for overweight. For the 10th and 90th percentiles, the differences between the estimated GWG were larger for overweight (∼1.5 kg) compared with normal weight (<1 kg). Removal of adverse neonatal outcomes had minimal impact on GWG trajectories of normal weight. For overweight, the percentiles estimated in the dataset without the criteria were slightly higher than those in the dataset with the criteria applied. Nevertheless, differences were <1 kg and virtually nonexistent at the end of pregnancy.
CONCLUSIONS: Removing pregnancies with adverse neonatal outcomes has little or no influence on the GWG trajectories of individuals with normal and overweight.