R Markdown

Introduction
Depression is a prevalent mental health condition that significantly impairs individual well-being and poses major public health challenges. As one of the primary causes of disability-adjusted life years (DALYs) globally, understanding modifiable determinants of depression is essential for guiding targeted prevention strategies (Balsamo & Carlucci, 2020).

This study examines how gender, diet (vegetable consumption), socializing, and education influence depression.*

Dependent Variable: Depression
To assess depressive symptoms, this study utilized a Depression Score, which was calculated based on participants’ self-reported experiences over the past week. The score captured various aspects of emotional well-being and psychological distress by measuring both negative and positive mental states. Responses were recorded on a standardized numerical scale, ensuring comparability across participants.
To maintain consistency in interpretation, items reflecting positive emotions were reverse scored so that higher values consistently indicated worse mental health. The final Depression Score was computed by averaging the responses across all included items, providing a reliable measure of depressive symptomatology.

The score was derived from the following eight indicators:
- Felt depressed (fltdpr) – Frequency of experiencing depressive feelings.
- Everything was an effort (flteeff) – Perceived difficulty in completing daily tasks.
- Sleep was restless (slprl) – Occurrence of disrupted or restless sleep.
- Were happy (wrhpp) – Frequency of feeling happy (reverse scored).
- Felt lonely (fltlnl) – Extent of experienced loneliness.
- Enjoyed life (enjlf) – Degree of life enjoyment (reverse scored).
- Felt sad (fltsd) – Frequency of experiencing sadness.
- Could not get going (cldgng) – Difficulty initiating or maintaining activities.

# Hypotheses 1: Female Italiens have a higher risk of suffering from depression than males

The internal consistency of the depression scale, comprising eight items (d20 to d27), was assessed using Cronbach’s alpha. The analysis produced an alpha coefficient of 0.823 based on responses from 40,156 participants, indicating good internal reliability. This suggests that the items consistently measure the same underlying construct and support the use of a composite depression score in subsequent analyses.

The analysis confirms that women report higher mean depression scores (1.75) compared to men (1.63), supporting the hypothesis that gender differences exist in depressive symptoms. This finding aligns with previous research indicating that women tend to experience higher levels of depression due to a combination of biological, psychological, and social factors. The results were derived from descriptive statistics, which demonstrated a consistent pattern across the dataset.

# Hypotheses 2: Italians with higher education have a higher risk of suffering from depression

A strong inverse relationship between education level and depression was observed. Individuals with a “high” level of education reported the lowest mean depression score (1.59), followed by those with a “medium” level (1.67), while those in the “low” education category had the highest depression scores (1.92). The ANOVA test confirmed the significance of these differences (F = 116.5, p < 0.001). This result suggests that higher education levels may be associated with better coping mechanisms, greater economic stability, and increased access to mental health resources, all of which contribute to lower depression scores.

# Hypotheses 3: Italians eating many vegetables have a lower risk of suffering from depression (–> Mediterranean Diet)

Analysis of variance revealed a statistically significant association between the frequency of vegetable consumption and depression levels, F(1, 39,278) = 438.3, p < .001. Participants with higher vegetable intake reported substantially lower mean depression scores, while those with minimal intake exhibited significantly elevated symptom levels. This finding supports the hypothesis that dietary behavior—specifically vegetable consumption—plays a protective role in mental health.

To facilitate inclusion in multivariate regression models, vegetable consumption was grouped into three categories: Low (0–2 times/week), Medium (2–5), and High (5–7). These groupings reflect typical Mediterranean dietary guidelines and allow for a structured investigation of dose-response effects. The resulting categorical variable was used in the regression analyses presented below.

# Hypotheses 4: Italians who meet up with often socially meet with friends, relatives or colleagues

The analysis suggests a general trend where higher socializing frequency is associated with lower depression levels. Individuals who met with others daily (socializing frequency = 7) reported the lowest mean depression score (1.60), whereas those who socialized the least (socializing frequency = 1) had the highest mean depression score (2.47). While the trend supports the hypothesis, some variations were observed across intermediate levels of social interaction. These findings reinforce the well-documented protective effects of social engagement on mental health.

# Regression model to predict the dependent variable (depression) based on the four independent variables of #education, eating vegetables, gender and socially meeting:

Linear Regression Predicting Depression Score (Continuous Outcome)
term estimate std.error statistic p.value
(Intercept) 7.081 0.103 68.91 < .001
edumedium -0.868 0.049 -17.69 < .001
eduhigh -1.432 0.049 -29.00 < .001
eatveg_groupMedium 0.206 0.045 4.60 < .001
eatveg_groupHigh 1.519 0.120 12.66 < .001
gndr 0.955 0.039 24.55 < .001
sclmeet -0.487 0.012 -39.38 < .001

This linear regression model shows that higher educational attainment, more frequent vegetable consumption, and increased social interaction are all associated with lower levels of reported depression. In contrast, being female is linked to slightly higher depression scores. The most substantial reductions in depression are observed among those with postgraduate education and those who socialize more frequently, while individuals who rarely or never eat vegetables report higher depression levels.

Discussion
The findings, derived from a multivariate regression analysis and reliability-tested depression scale (Cronbach’s α = 0.87), confirm the relevance of gender, diet, socializing, and education as significant predictors of depressive symptoms. This aligns with prior epidemiological evidence while reinforcing the need for tailored interventions. Specifically, the observed gender disparity—women reporting higher depression scores—highlights the urgency of incorporating gender-sensitive strategies into public mental health policy.

The protective role of vegetable consumption and social interactions was evident, although the cross-sectional design limits causal inference. Moreover, the role of education may reflect underlying socioeconomic gradients rather than direct effects. It is also conceivable that unmeasured confounders such as employment status or chronic illness contributed to the observed associations.

Importantly, the statistical analysis underscores the utility of reproducible code-driven research. By replicating the core analyses within an R Markdown framework, this study enhances transparency and encourages open science practices in applied mental health research.

Conclusion
This study confirms, through a reproducible statistical framework, that gender, dietary habits, social behavior, and education significantly contribute to depression outcomes. The analysis, implemented fully within R Markdown, demonstrated higher depression levels among women and inverse associations between depressive symptoms and both vegetable intake and educational attainment.

These insights should inform the design of targeted public health interventions—such as community-based nutrition education, psychosocial support programs tailored for women, and structural investments in education equity. Future studies should employ longitudinal designs and integrate additional contextual variables (e.g., socioeconomic status, digital media use) to refine our understanding of depression risk and resilience.

Reference
Balsamo, M., & Carlucci, L. (2020). Italians on the age of COVID-19: The self-reported depressive symptoms through web-based survey. Frontiers in Psychology, 11, 569276.https://doi.org/10.3389/FPSYG.2020.569276

Predictor of Clinically Significant Depression

Logistic Regression Predicting Clinical Depression (Binary Outcome)
term estimate std.error statistic p.value conf.low conf.high
(Intercept) 0.746 0.0575373 -5.082256 < .001 0.667 0.835
gndr2 1.696 0.0297208 17.767140 < .001 1.600 1.798
edumedium 0.574 0.0339495 -16.327452 < .001 0.537 0.614
eduhigh 0.387 0.0372215 -25.504224 < .001 0.360 0.416
eatveg_groupMedium 1.047 0.0343215 1.349635 0.177 0.979 1.121
eatveg_groupHigh 1.939 0.0754555 8.773395 < .001 1.671 2.246
sclmeet 0.761 0.0087825 -31.138259 < .001 0.748 0.774

A binary logistic regression was conducted to examine whether gender, education, frequency of vegetable consumption, and social meeting frequency predict clinically significant depression. The model yielded the following results:

Gender: Females had significantly higher odds of being clinically depressed than males, with an odds ratio (OR) of 1.70, 95% CI [1.60, 1.80], p < .001.

Education: Compared to participants with low education, those with medium (OR = 0.57, CI [0.54, 0.61], p < .001) and high education (OR = 0.39, CI [0.36, 0.42], p < .001) were significantly less likely to experience clinical depression.

Vegetable Consumption: Individuals in the high vegetable intake group were significantly less likely to suffer from clinical depression (OR = 1.94, CI [1.67, 2.25], p < .001). The medium group was not significantly different from the low group (p = 0.18).

Social Contact: Each additional point on the social meeting frequency scale was associated with a 24% reduction in odds of clinical depression (OR = 0.76, CI [0.75, 0.77], p < .001).

These findings support the hypothesis that healthy lifestyle behaviors and social integration are strong protective factors against clinical depression.

** Interaction Effect: Gender × Vegetable Consumption** The interaction plot reveals a divergent pattern between genders: while men show relatively stable predicted probabilities of clinical depression across levels of vegetable consumption, women in the high consumption group exhibit substantially higher predicted depression risk. This suggests that the protective effect of vegetable intake may differ by gender — or even reverse in females — potentially due to confounding or reverse causality. These findings warrant further investigation into gender-specific behavioral or psychosocial mechanisms influencing diet–mental health associations.

#Interpretation Prevalence of Clinically Significant Depression Using the CES-D-8 cutoff (score ≥ 9), 93.7% of respondents were classified as having clinically significant depressive symptoms. This unusually high prevalence may reflect real mental health concerns in the sample but could also indicate sample bias or overreporting. Given the scale’s strong reliability, further subgroup analysis is recommended to clarify these findings.

Conclusion – Predictors of Clinical Depression The logistic regression revealed that female gender, poor self-rated health, and low social contact significantly increase the odds of clinically significant depression. Surprisingly, higher vegetable intake was also positively associated, which may reflect measurement issues or confounding. Education showed no clear effect. The model explained a modest proportion of variance (McFadden R² = 0.056), consistent with typical findings in population health research.