1. Background
Various cross sectional studies (1, 2) show a positive relationship between fruit and vegetable (FAV) consumption and mental well-being, while results reported by longitudinal studies are controversial (3-5). For example, in a large longitudinal study in Australia, higher FAV consumption was associated with greater happiness, life satisfaction, and well-being (4). In a large longitudinal Canadian study, in models adjusted to other health-related factors, FAV consumption was no longer inversely associated with depression and psychological distress (3). Few investigations studied the longitudinal effects of FAV consumption on mental health, which prompted the current study.
2. Objectives
The current longitudinal study aimed at investigating the effect of FAV consumption on mental-health-related quality of life, major depressive disorder, and generalized anxiety disorder.
3. Materials and Methods
3.1. Study Design and Settings
The study employed longitudinal data from a lifestyle intervention trial of temple members with prediabetes and/or prehypertension, according to Pengpid et al. (6). The study was conducted in Nakhon Pathom province, Thailand from 2016 to 2018.
3.2. Participants
At baseline, 442 temple members (aged 35 - 65 years) from 12 randomly selected Buddhist temples were included, in case they had prediabetes and/or prehypertension (6). Participants were consecutively recruited from selected temples. Inclusion criteria were age 35 - 65 years, visiting the temple, and having a diagnosis of prehypertension and/or prediabetes; exclusion criteria were age less than 35 and above 65 years, having a diagnosis of cardiovascular disease, type 2 diabetes, hypertension, substance abuse, and taking psychotropic medication (6). Based on the sample size calculated in a similar study, 88 participants were needed to demonstrate change in mental well-being (7).
3.3. Study Procedure
Participants were assessed at baseline, 6-, 12-, and 24-month follow-up time points with questionnaires and anthropometric measures. The follow-up rate at 24 months was 80%.
3.4. Questionnaire
Three scales were employed to measure mental health in the study as follows:
The short-form 8 (SF-8) health survey was used to assess the physical component (PCS) and mental component (MCS) continuous summary scores (8). Cronbach alpha of the SF-8 in the current study was 0.76.
The patient health questionnaire-9 (PHQ-9) was employed to assess major depression (9). The PHQ-9 was validated in Thailand with high sensitivity (0.84) and specificity (0.77), using a cutoff score of ≥ 9 for major depression (10). Cronbach alpha of the PHQ-9 in the current study was 0.80.
The generalized anxiety disorder, which is a seven-item (GAD-7) scale utilized to assess the severity of generalized anxiety; scores ≥ 10 on the GAD-7 indicated moderate or severe GAD (11). Cronbach alpha of the GAD-7 in the current study was 0.87.
Daily fruit and vegetables consumption was measured from the total number of servings (80 g = 1 serving) of FAV eaten per day in a typical week (12).
Anthropometric assessments were applied using standard procedures. Body mass index (BMI) was calculated using Asian criteria: normal weight (18.5 to < 23.0 kg/m2), overweight (23.0 to < 25.0 kg/m2), and 25+ kg/m2 as obese (13).
Smoking was measured with the question: Do you currently smoke tobacco? Current smoking was defined as daily or less than daily smoking (12).
Problem drinking was measured with the alcohol use disorder identification test (AUDIT)-C (14). Cronbach alpha of the AUDIT-C in the current study was 0.86.
Physical activity was measured with the global physical activity questionnaire (GPAQ), and categorized into low, moderate, and high, following the GPAQ guidelines (15).
The assessed sociodemographic factors included gender, age, education, and subjective economic status (debt, enough to live, has savings).
3.5. Statistical Analysis
Descriptive statistics were used to describe the sample characteristics. Generalized estimating equations (GEE) regression models were utilized to estimate the associations between FAV consumption and three measures of mental health (mental-health-related quality of life scores-continuous, major depressive disorder, and generalized anxiety disorder status (binary) to account for repeated measures. GEE modelling was adjusted for sociodemographic factors, health risk behaviors, and the cluster design of the sample. P values < 0.05 were considered significant. Statistical analyses were conducted with IBM-SPSS version 25.0 (SPSS Inc., Chicago, IL, USA).
3.6. Ethical Consideration
The study was approved by the Ethics Committee (Social Sciences) of Mahidol University (MUSSIRB: 2016/053-B1). Written informed consent was obtained from all study participants prior to the study.
4. Results
4.1. Sample Characteristics
The sample included 442 participants at time 1 (baseline, 2016) (mean age 51.5 years, SD = 7.4; range 35 - 65), 394 at time 2 (six months), 334 at time 3 (12 months, 2017), and 352 participants at time 4 (24 months, 2018). More than two-thirds (74.2%) were female, 19.6% had post-secondary education, and 28.2% described their economic status as having debt. Almost all participants (93.2%) had prehypertension and 38.6% had prediabetes, 69.5% were overweight or obese, 10.5% were current smokers, 10.9% had problem drinkers, and 27.1% engaged in low physical activity. The prevalence of depression and general anxiety disorder and the mean mental summary scores did not significantly differ across the follow-up period. FAV consumption increased over the study period (Table 1).
Table 1.Descriptive Statistics of the Study Variables Over Timea
| Variable | Time 1: 0 Month, N = 442 | Time 2: 6 Months, N = 394 | Time 3: 12 Months, N = 334 | Time 4: 24 Months, N = 352 |
|---|---|---|---|---|
| Gender (female) | 328 (74.2) | 305 (75.1) | 253 (79.3) | 264 (77.2) |
| Post-secondary education | 86 (19.6) | 85 (21.10 | 59 (18.7) | 68 (19.9) |
| Economic debt status | 124 (28.2) | 120 (29.9) | 89 (28.3) | 86 (25.1) |
| Major depression | 57 (13.0) | 50 (15.7) | 39 (12.5) | 48 (14.0) |
| General anxiety disorder | 22 (5.0) | 10 (3.1) | 11 (3.5) | 8 (2.3) |
| Overweight or obese | 308 (69.5) | 260 (71.6) | 281 (71.5) | 279 (72.8) |
| Current smoking | 46 (10.5) | 24 (7.5) | 39 (12.3) | 26 (7.6) |
| Problem drinking | 48 (10.9) | 45 (14.1) | 33 (10.4) | 38 (11.1) |
| Low physical activity | 119 (27.1) | 73 (22.9) | 102 (33.3) | 89 (26.2) |
| Age (range: 35 - 65) | 51.5 ± 7.4 | 51.6 ± 7.4 | 52.6 ± 7.4 | 53.7 ± 7.3 |
| Daily fruit and vegetable consumption (range: 0.29 - 14) | 2.14 ± 1.4 | 2.97 ± 1.8 | 2.96 ± 1.8 | 2.96 ± 1.5 |
| Daily fruit consumption (range 0.14 - 7) | 1.08 ± 0.9 | 1.20 ± 1.0 | 1.24 ± 1.1 | 1.16 ± 0.9 |
| Daily vegetable consumption (range 0.14 - 7) | 1.06 ± 0.8 | 1.77 ± 1.2 | 1.72 ± 1.1 | 1.80 ± 1.0 |
| Mental component summary | 53.6 ± 8.8 | 51.8 ± 8.6 | 53.9 ± 8.7 | 55.6 ± 9.1 |
aValues are expressed as mean ± SD or No. (%).
4.2. Longitudinal Results Between FAV Consumption, and Mental-Health-Related Quality of Life, Depression, and Anxiety
Results of GEE predicting mental-health-related quality of life found that more frequent fruit consumption was not associated with greater mental-health-related quality of life, while vegetable consumption was associated with greater mental-health-related quality of life in a fully adjusted model. FAV consumption was associated with greater mental-health-related quality of life only in the unadjusted model; once adjusted to sociodemographic factors as well as health variables, this association was no longer significant. In addition, older age was positively and having debts and low physical activity were negatively associated with mental-health-related quality of life (Table 2).
Table 2.Results of GEE Models Predicting Mental-Health-Related Quality of Life
| Variable | Model 1a | Model 2b | Model 3c | |||
|---|---|---|---|---|---|---|
| B (95% CI) | P Value | B (95% CI) | P Value | B (95% CI) | P Value | |
| Fruit consumption | 0.33 (-0.20 - 0.87) | 0.221 | 0.16 (-0.37 - 0.68) | 0.561 | 0.19 (-0.34 - 0.72) | 0.485 |
| Vegetable consumption | 0.53 (0.09 - 0.96) | 0.018 | 0.44 (0.02 - 0.87) | 0.043 | 0.48 (0.06 - 0.91) | 0.027 |
| Fruit and vegetable consumption | 0.33 (0.03 - 0.64) | 0.033 | 0.24 (-0.06 - 0.54) | 0.117 | 0.26 (-0.04 - 0.56) | 0.085 |
| Age, y | 0.15 (0.06 - 0.23) | < 0.001 | 0.15 (0.07 - 0.23) | < 0.001 | ||
| Gender | -1.39 (-2.80 - 0.03) | 0.055 | -1.30 (-2.79 - 0.20) | 0.090 | ||
| Education | ||||||
| No/primary school | Reference | Reference | ||||
| Secondary school | -0.03 (-1.48 - 1.43) | 0.973 | 0.18 (-1.28 - 1.63) | 0.812 | ||
| Post-secondary | 0.02 (-1.54 - 1.59) | 0.977 | 0.20 (-1.38 - 1.77) | 0.806 | ||
| Economic status | ||||||
| Enough or savings | Reference | Reference | ||||
| Debt | -1.47 (-2.66 - -0.28) | 0.016 | -1.41 (-2.60 - -0.22) | 0.020 | ||
| Overweight or obese | -0.12 (-1.31 - 1.07) | 0.842 | ||||
| Smoking | -0.30 (-2.23 - 1.64) | 0.764 | ||||
| Problem drinking | -0.13 (-1.92 - 1.65) | 0.883 | ||||
| Low physical activity | -1.30 (-2.38 - -0.21) | 0.019 | ||||
aUnadjusted.
bAdjusted for sociodemographic variables.
cAdjusted for sociodemographic and health variables.
More frequent fruit, vegetable, and FAV consumption did not significantly reduce the risk of major depression (Table 3) and generalized anxiety disorder (Table 4). In addition, debt economic status was associated with depression. In another model, subjects with a major depressive disorder at baseline were excluded, and the regression model was run with the incidence of major depressive disorder, but results were similar with those of the ones that depression at baseline was included; same results also apply to generalized anxiety disorder.
Table 3.Results of GEE Models Predicting Major Depression
| Variable | Model 1a | Model 2b | Model 3c | |||
|---|---|---|---|---|---|---|
| B (95% CI) | P Value | B (95% CI) | P Value | B (95% CI) | P Value | |
| Fruit consumption | -0.07 (-0.22 - 0.08 | 0.488 | 0.06 (-0.14 - 0.26) | 0.570 | 0.06 (-0.14 - 0.26) | 0.566 |
| Vegetable consumption | 0.09 (-0.05 - 0.24) | 0.206 | 0.12 (-0.04 - 0.27) | 0.142 | 0.11 (-0.05 - 0.26) | 0.173 |
| Fruit and vegetable consumption | 0.06 (-0.04 - 0.16) | 0.235 | 0.07 (-0.04 - 0.18) | 0.264 | 0.07 (-0.05 - 0.18) | 0.252 |
| Age | 0.004 (-0.02 - 0.03) | 0.782 | 0.007 (-0.02 - 0.03) | 0.610 | ||
| Gender | 0.22 (-0.28 - 0.72) | 0.394 | 0.43 (-0.08 - 0.94) | 0.100 | ||
| Education | ||||||
| No/primary school | Reference | Reference | ||||
| Secondary school | -0.09 (-0.56 - 0.38) | 0.707 | -0.04 -0.52 - 0.44 | 0.878 | ||
| Post-secondary | 0.48 (-0.11 - 1.07) | 0.110 | 0.53 -0.05 - 1.12 | 0.074 | ||
| Economic status | ||||||
| Enough or savings | Reference | Reference | ||||
| Debt | 0.82 (0.44 - 1.20) | < 0.001 | 0.77 (0.39 - 1.15) | < 0.001 | ||
| Overweight or obese | 0.15 (-0.28 - 0.59) | 0.487 | ||||
| Smoking | -0.40 (-1.02 - 0.22) | 0.204 | ||||
| Problem drinking | -0.31 (-0.87 - 0.26) | 0.284 | ||||
| Low physical activity | -0.30 (-0.65 - 0.05) | 0.096 | ||||
aUnadjusted.
bAdjusted for sociodemographic variables.
cAdjusted for sociodemographic and health variables.
Table 4.Results of GEE Models Predicting Generalized Anxiety Disorder
| Variable | Model 1a | Model 2b | Model 3c | |||
|---|---|---|---|---|---|---|
| B (95% CI) | P Value | B (95% CI) | P Value | B (95% CI) | P Value | |
| Fruit consumption | -0.02 (-0.27 - 0.22) | 0.851 | -0.03 (-0.30 - 0.24) | 0.832 | -0.05 (-0.33 - 0.24) | 0.751 |
| Vegetable consumption | 0.18 (-0.18 - 0.54) | 0.329 | 0.20 (-0.16 - 0.56) | 0.285 | 0.15 (-0.20 - 0.51) | 0.399 |
| Fruit and vegetable consumption | 0.06 (-0.13 - 0.25) | 0.514 | 0.07 (-0.13 - 0.27) | 0.495 | 0.05 (-0.15 - 0.25) | 0.634 |
| Age | -0.009 (-0.05 - 0.03) | 0.666 | -0.01 (-0.05 - 0.03) | 0.588 | ||
| Gender | -0.002 (-0.87 - 0.86) | 0.996 | -0.11 (-1.04 - 0.82) | 0.818 | ||
| Education | ||||||
| No/primary school | Reference | Reference | ||||
| Secondary school | -0.09 (-0.92 - 0.75) | 0.841 | -0.05 (-0.92 - 0.82) | 0.914 | ||
| Post-secondary | 0.31 (-0.65 - 1.27) | 0.527 | 0.47 (-0.59 - 1.52) | 0.389 | ||
| Economic status | ||||||
| Enough or savings | Reference | Reference | ||||
| Debt | 0.49 (-0.19 - 1.17) | 0.154 | 0.59 (-0.08 - 1.26) | 0.083 | ||
| Overweight or obese | 0.43 (-0.33 - 1.18) | 0.265 | ||||
| Smoking | 0.30 (-0.94 - 1.53) | 0.640 | ||||
| Problem drinking | 0.13 (-0.87 - 1.12) | 0.799 | ||||
| Low physical activity | -0.18 (-0.87 - 0.48) | 0.587 | ||||
aUnadjusted.
bAdjusted for sociodemographic variables.
cAdjusted for sociodemographic and health variables.
5. Discussion
The current study employed a longitudinal sample to examine the possible relationship between FAV consumption and three measures of mental health. After controlling the possible confounders including sociodemographic, lifestyle, BMI, and physical activity, no association was observed between FAV consumption frequency and mental-health-related quality of life or between FAV consumption frequency and major depressive and generalized anxiety disorders. The current study findings were consistent with those of a study in Canada when adjusted models no longer found a negative association between FAV consumption and depression and mental distress (3). However, when analyzing FAV consumption separately, more frequent vegetable consumption was associated with greater mental-health-related quality of life in a fully adjusted model. Similar results were observed in a study among female subjects in rural areas of Ghana (16). The relationship between FAV consumption and mental health seems to be more complex, and other factors such as poor economic status and other life style factors such as physical inactivity may be more likely to influence mental health.
The study found that with the increasing of age, mental-health-related quality of life increased, and having debt and engagement in low physical activity were negatively associated with mental-health-related quality of life. Having debt was also significantly associated with major depression. In a recent review, it was found that sedentary behavior increases the risk of depression or poor mental health (17). Poor mental health and depression can be trigged by stressful life events such as having debts or having a chronic illness (18).
Study limitations were that the study assessed FAV consumption by self-report instead of also measuring urine or blood biomarkers for nutrients in FAVs. Factors such as age, gender, education, chronic illness, smoking, genetic, social, and spiritual may have an etiological role in depression and generalized anxiety disorder. The study groups were not matched by such factors, which was another limitation of the study.
5.1. Conclusions
The current longitudinal study did not find evidence that more frequent FAV consumption was associated with mental-health-related quality of life, depression, and anxiety. However, more frequent vegetable consumption was associated with greater mental-health-related quality of life.
