Table 1.
Characteristics of included studies evaluating the associations between diet and SAD.
| First author, year, country | Study design, SAD screen tool | Total subjects, age (mean), Patients N | Diet, diet assessment tool | Outcome, outcome assessment tool |
Means/ frequencies |
Comparison | OR (CI) or p values | Conclusion |
|---|---|---|---|---|---|---|---|---|
| Meesters ANR, 2017, Finland (Study I) |
Cross-sectional, SPAQ | 4578, 52.1a, 123 |
Vegan, FFQ | SAD severity, SPAQ |
14.6% among vegetarians, and 3.4% among non-vegetarians | Vegetarian vs. non-Vegetarian | OR = 3.9 (1.81–8.36) | Being vegetarians is associated with higher possibility of developing SAD. However, logistic regression analysis revealed that none of the GSS item scores or the total GSS showed a significant relationship with vegetarianism. |
| GSS, SPAQ | 6.2 ± 3.6 for Vegetarians, and 5.2 ± 3.2 for non-Vegetarians | Vegetarian vs. non-Vegetarian | p > 0.05 | |||||
| The Netherlands (Study II) | Cross-sectional, DSM-IV | 257, 37.5, 257 |
Vegan, Asked by researchers whether being vegetarian |
GSS, SPAQ | 12.7 ± 4.4 for Vegetarians, and 13.5 ± 3.5 for non-Vegetarians | SAD vs. non-SAD | OR = 1.5 p < 0.05 | The logistic regression analysis showed a significant relationship between seasonal loss of energy and vegetarianism. |
| Morales-Muñoz I, 2017, Finland |
Cross-sectional, SPAQ | 8135, 55.7, 171 |
Alcoholism, M-CIDI | ADD, M-CIDI | 0.08% for SAD patients, and 0.03% for control | Case vs. control | p < 0.001 | The one-way ANOVA analysis showed that compared with control, people with SAD showed greater possibilities in having alcohol use/dependence disorder in lifetime. |
| AUD, M-CIDI | 0.12% for SAD patients, and 0.06% for control | Case vs. control | p = 0.003 | |||||
| Alcohol abuse during the past 12 months, M-CIDI | 1.09% for SAD patients, and 1.02% for control | Case vs. control | p = 0.002 | |||||
| ADD during the past 12 months, M-CIDI | 0.03% for SAD patients, and 0.01% for control | Case vs. control | p = 0.032 | |||||
| AUD during the past 12, M-CIDI | 0.04% for SAD patients, and 0.01% for control | Case vs. control | p = 0.024 | |||||
| Seasonal changes in sleep duration, SPAQ | NR | One unit change in ADD | p = 0.005 | Pearson correlation analysis showed that people diagnosed with ADD reported larger seasonal changes in sleep duration, social activity, energy, and mood; AUD patients reported larger seasonal changes in social activity and mood; patients suffered ADD past 12 months reported larger seasonal changes in sleep duration, social activity, energy, and mood; patients suffered AUD past 12 months reported larger seasonal changes in sleep duration, energy, and mood; and patients suffered alcohol abuse past 12 months reported larger seasonal changes in energy and mood. | ||||
| Seasonal change in social activity, SPAQ | NR | One unit change in ADD | p = 0.007 | |||||
| Seasonal changes in energy, SPAQ | NR | One unit change in ADD | p < 0.001 | |||||
| Seasonal changes in mood, SPAQ | NR | One unit change in ADD | p < 0.001 | |||||
| Seasonal changes in social activity, SPAQ |
NR | One unit change in AUD | p = 0.007 | |||||
| Seasonal changes in mood, SPAQ | NR | One unit change in AUD | p < 0.001 | |||||
| Seasonal changes in sleep duration, SPAQ | NR | One unit change in ADD past 12 months | p = 0.004 | |||||
| Seasonal change in social activity, SPAQ | NR | One unit change in ADD past 12 months | p = 0.003 | |||||
| Seasonal changes in energy, SPAQ | NR | One unit change in ADD past 12 months | p = 0.013 | |||||
| Seasonal changes in mood, SPAQ | NR | One unit change in ADD past 12 months | p < 0.001 | |||||
| Seasonal changes in sleep duration | NR | One unit change in AUD past 12 months | p = 0.004 | |||||
| Seasonal changes in energy | NR | One unit change in AUD past 12 months | p = 0.006 | |||||
| Seasonal changes in mood | NR | One unit change in AUD past 12 months | p < 0.001 | |||||
| Seasonal changes in energy | NR | One unit change in alcohol abuse past 12 months | p = 0.027 | |||||
| Seasonal changes in mood | NR | One unit change in alcohol abuse past 12 months | p < 0.001 | |||||
| Krauchi K, 1987, Switzerland | Case-control, DSM-III | 54, 40.7a, 28 |
Food frequency, FDFQ | Starch-rich foods intake amount (portions/month), FDFQ | 50.3 ± 15.1 for case, and 61.7 ± 15.5 for control | Case vs. Control | p < 0.05 | One-way ANOVA showed that compare with control, SAD patients had more preference of consuming starch and fiber-rich foods, but similar frequencies of taking sugar-rich foods, dairy-rich foods, protein-rich foods, and caffeine-containing beverages. |
| Fiber-rich foods intake amount (portions/month), FDFQ | 61.6 ± 20.4 for case, and 82.8 ± 27.9 for control | Case vs. Control | p < 0.01 | |||||
| Sugar-rich foods intake amount (portions/month), FDFQ | 34.4 ± 20.3 for case, and 41.3 ± 15.7 for control | Case vs. Control | p > 0.05 | |||||
| Protein-rich foods intake amount (portions/month) | 26.4 ± 12.7 for case, and 26.2 ± 9.8 for control | Case vs. Control | p > 0.05 | |||||
| Dairy intake amount (portions/month) | 59.4 ± 29.1 for case, and 53.5 ± 27.1 for control | Case vs. Control | p > 0.05 | |||||
| alcohol intake amount (dl/month) | 5.0 ± 3.7 for case, and 4.4 ± 4.7 for control | Case vs. Control | p > 0.05 | |||||
| Caffeine-containing drinks amount (portions/month) | 70.7 ± 14.7 for case, and 80.2 ± 21.7 for control | Case vs. Control | p > 0.05 | |||||
| Seasonal variation of starch-rich foods intake, FDFQ | NA | (Case vs. Control) * Seasons | p > 0.05 | Two-way ANOVA for repeated measures analysis showed that there was no interaction between case vs. control and seasonality on seasonal variation of food item intake. However, significant seasonal variations were found in starch-rich foods and dairy products in cases. | ||||
| Seasonal variation of fiber-rich foods intake amount, FDFQ | NA | (Case vs. Control) * Seasons | p > 0.05 | |||||
| Seasonal variation of sugar-rich foods intake amount, FDFQ | NA | (Case vs. Control) * Seasons | p > 0.05 | |||||
| Seasonal variation of protein-rich foods intake amount, FDFQ | NA | (Case vs. Control) * Seasons | p > 0.05 | |||||
| Seasonal variation of dairy intake amount, FDFQ | NA | (Case vs. Control) * Seasons | p > 0.05 | |||||
| Seasonal variation of alcohol intake amount, FDFQ | NA | (Case vs. Control) * Seasons | p > 0.05 | |||||
| Seasonal variation of caffeine-containing drinks amount, FDFQ | NA | (Case vs. Control) * Seasons | p > 0.05 |
FFQ, Food Frequency Questionnaire; SPAQ, Seasonal Pattern Assessment Questionnaire; GSS, Global Seasonality Score; DSM, Diagnostic and Statistical manual of Mental disorders; M-CIDI, The World Health Organization Composite International Diagnostic Interview, the Munich version; ADD, Alcohol dependence disorder in lifetime; AUD, Alcohol use disorder in lifetime; SIGH-SAD, Structured Interview Guide for the Hamilton Depression Rating Scale, Seasonal Affective Disorders; SCID, DSM-IV Structured Clinical Interview for Depression; NR, Not report; Underlined context, detailed data not shown in the publication; Bold text, Statistically significant.
a
Calculated according to the information provided.