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1 Abstract

This study investigates depression and its socio-behavioral predictors in Italy using data from the European Social Survey (ESS Round 11). A composite score derived from eight CES-D items captures depressive symptoms. Linear and logistic regression models examine the impact of gender, education, vegetable intake, and social contact on depression levels.

Findings show that women, those with lower education, and individuals with less frequent social contact report significantly higher depression scores. Higher vegetable consumption is associated with lower depressive symptoms, with notable gender-specific effects. These insights highlight key risk and protective factors, supporting targeted mental health interventions. The analysis further demonstrates the utility of reproducible statistical workflows in social epidemiology.

2 Introduction

Depression is a widespread mental health condition with substantial social and economic consequences. Italy, like many European nations, faces increasing challenges in managing psychological well-being across population subgroups. Previous studies link depression to multiple demographic and behavioral factors, including gender, socioeconomic status, dietary habits, and social isolation (Balsamo & Carlucci, 2020).

This study aims to evaluate how gender, education level, frequency of vegetable consumption, and social interaction predict depression levels in Italy. Using the European Social Survey (ESS Round 11), both continuous depression scores and binary clinical thresholds are analyzed using regression techniques to generate policy-relevant findings.

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.

3 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.

4 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.

The figure below illustrates the gradient of depression scores across education groups.

5 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.

6 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.

**Multivariate Regression Model*
Linear Regression Predicting Depression Score (Continuous Outcome)
term estimate std.error statistic p.value
(Intercept) 2.007 0.010 193.41 < .001
edumedium -0.107 0.006 -17.61 < .001
eduhigh -0.179 0.006 -29.27 < .001
eatveg_groupMedium 0.025 0.006 4.56 < .001
eatveg_groupHigh 0.191 0.015 12.80 < .001
gndrFemale 0.118 0.005 24.47 < .001
sclmeet -0.061 0.002 -39.74 < .001

Table shows Linear Regression Predicting Depression Score (Continuous Outcome)

The linear regression model suggests that individuals with higher education and more frequent vegetable consumption report significantly lower depression scores. Gender also plays a role, with females having slightly elevated depression levels. Social interaction is negatively associated with depression, indicating its protective role.

To better understand the composition and performance of the depression scale, descriptive statistics for all eight CES-D items were computed. The analysis included mean values and valid response counts for each item. Additionally, a Likert summary table was generated to assess the distribution of response categories. These statistics provide insight into the relative severity and frequency of individual depressive symptoms as reported by Italian respondents and support the reliability of the composite depression score.

7 Predictor of Clinically Significant Depression

8 Logistic Regression

The logistic regression reveals that women have 1.7 times higher odds of clinical depression compared to men. Individuals with high education are significantly less likely to be clinically depressed. Higher vegetable intake and frequent social contact are also protective factors. All results were statistically significant (p < .001), indicating robust associations.

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
gndrFemale 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.

A clear gradient is observed across vegetable consumption levels. Participants with high vegetable intake show a significantly lower predicted probability of clinical depression, reinforcing the potential impact of dietary habits on mental health.

9 Interaction Effect: Gender × Vegetable Consumption

The interaction plot shows that the protective effect of vegetable consumption on depression is more pronounced for men than for women. Among women, high vegetable intake is associated with only a modest decrease in predicted depression, suggesting gender-specific mechanisms may influence dietary impacts.

# 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.

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.

10 Discussion

This study demonstrates that lifestyle and demographic factors significantly affect depression in Italy. Education, social contact, and vegetable consumption all show protective effects across both continuous and binary measures of depression. Gender emerges as a consistent risk factor, with women facing elevated depression risk.

The high internal consistency (Cronbach’s α = 0.82) validates the reliability of the depression score derived from the CES-D-8 items. The logistic model further highlights significant odds ratios for all predictors, suggesting meaningful practical implications.

However, the findings must be interpreted within the limitations of cross-sectional design, which precludes causal inference. Self-reported data may introduce bias, and potential confounders such as employment status, chronic illness, or medication use were not controlled.

Despite these limitations, the study contributes to the growing evidence base on modifiable risk factors for depression and supports public health efforts targeting dietary and social behavior.

11 Conclusion

This analysis confirms that gender, education, social interaction, and dietary behavior are significant predictors of depression in the Italian population. Public health interventions should prioritize vulnerable groups—particularly women and individuals with low education—while promoting behavioral changes such as increased social engagement and vegetable consumption.

Future research should employ longitudinal or experimental designs to clarify causal relationships and explore additional mediating variables such as income, work stress, or family structure.

12 References

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