Spss statistics for macintosh version 24

Normally distributed continuous variables are reported as means [standard deviations (SD)] and as medians [interquartile ranges (IQR)] when skewed. Discrete data are presented as numbers and percentages. The Chi-square test and the Student’s T test were used to calculate differences between the primary prevention and the secondary prevention groups accordingly. The Kaplan–Meier and log-rank tests assessed the cumulative survival differences between the primary prevention group versus secondary prevention. A p value < 0.05 represents a statistically significant difference. Statistical analyses were performed using SPSS Statistics for Macintosh version 24.0 (IBM, USA).

Analyses were carried out using IBM SPSS v.24 (IBM Corp. Released 2016. IBM SPSS Statistics for Macintosh, Version 24.0. Armonk, NY: IBM Corp). Average daily volume consumption was compared using 2-way analysis of variance (ANOVA) with treatment and solution as main effects and with Šidák's post hoc tests for multiple comparisons. The intake of each nutrient was calculated (mg) and presented as intake per bee. Consumption of nutrients (mg) was compared using multiple analysis of variance (MANOVA) with total EAA, lipid and carbohydrate intake as dependent variables. Intake targets were identified using Šidák post hoc tests. To assess the differences in daily consumption of nutrients, repeated measures ANOVA was applied to daily consumption values of EAA, carbohydrate and lipid, with EAA:L treatment as the main effect. Survival data were analysed using Cox regression (Cox proportional hazards model). In the confined assay, the 1:0 (no lipid) diet was used as the indicator variable. Survival in the protein-paired and lipid-paired assays were also analysed with Cox regression using the most dilute lipid diet as the indicator variable. The effect of EAA:L treatment on abdominal fat content was compared using a one-way ANOVA. HPG acini diameter was applied as the dependent variable in a one-way ANOVA with EAA:L treatment as the main effect.

Descriptive statistics were used to describe the sample. Chi-squared (χ²) tests and univariate linear regression models were used to determine if significant differences existed between the demographic variables of food-secure and food-insecure households. Chi-squared tests were then used to determine whether differences existed between food-secure and food-insecure households in terms of reported barriers to buying and preparing/cooking vegetables. A mixed-effects linear regression was used to examine the associations between the scores for barriers to buying, barriers to preparing/cooking, and food security on the home availability of vegetables score, with random effects at the school level to account for clustering by schools. Interactions between food insecurity and buying and preparing/cooking scores on the home availability of vegetables score were tested. Race/ethnicity, parent education, number of children in the household, and receipt of Supplemental Nutrition Assistance Program (SNAP) benefits were used as covariates. All analyses were conducted using SPSS Statistics for Macintosh, version 24.0 (IBM Corp, Armonk, NY, USA), and an alpha level of p = 0.05 was used for significance.