Difference in diet between a general population national representative sample and individuals with alcohol use disorders, but not individuals with depressive or anxiety disorders REETA RINTAMÄKI, NIINA KAPLAS, SATU MÄNNISTÖ, JUKKA MONTONEN, PAUL KNEKT, JOUKO LÖNNQVIST, TIMO PARTONEN

Rintamäki R, Kaplas N, Männistö S, Montonen J, Knekt P, Lönnqvist J, Partonen T. Difference in diet between a general population national representative sample and individuals with alcohol use disorders, but not individuals with depressive or anxiety disorders. Nord J Psychiatry 2014;68:391–400. Background: Mental disorders influence diet and food consumption, but there is a lack of consistent findings. Aims: To investigate food consumption, nutrient intakes and serum metabolic biomarkers in depressive, anxiety and alcohol use disorders in comparison with the remaining from a population-based nationwide sample. Methods: The study was based on the Health 2000 Survey data of which 5504 subjects aged 30 and over (3009 women and 2495 men) were used for the analysis. Depressive disorder, anxiety disorders and alcohol use disorders were diagnosed using the Composite International Diagnostic Interview (M-CIDI). The consumption of food and beverage items, and nutrient intakes were measured with a validated food frequency questionnaire, and the concentrations of biomarkers were determined in blood samples. Results: Overall, no similar differences with both genders were found in the intakes of energy, dietary fibre or macronutrients or in biomarkers in depressive or anxiety disorders. Women suffering from depressed disorder consumed more soft drinks (P ⫽ 0.034) and women suffering from anxiety disorders consumed more oils (P ⫽ 0.001), polyunsaturated fatty acids (P ⫽ 0.001) and less potatoes (P ⫽ 0.002) than the remaining participants. Men suffering from depressive disorder consumed less sweets and chocolate (P ⫽ 0.001) and men with anxiety disorder consumed more tea (P ⫽ 0.033) compared with the remaining participants. In alcohol use disorders, the intake of carbohydrate was lower in both genders (P ⫽ 0.001 for women, P ⫽ 0.001 for men). Conclusions: A difference in the usual diet exists between individuals with alcohol use disorders and the remaining participants on a population level. No consistent difference in both genders between those with depressive or anxiety disorders and the remaining was found. • Biomarker, Depression, Food, Macronutrient, Mood, Nutrition. Reeta Rintamäki, M.D., Ph.D., National Institute for Health and Welfare, Department of Mental Health and Substance Abuse Services, PO Box 30, Helsinki FI-00271, Finland, E-mail: [email protected]; Accepted 1 October 2013.

M

ental disorders such as depressive, anxiety and alcohol use disorders are a major health problem, influencing all social groups and geographical areas worldwide (1). Every fourth person is estimated to suffer from a mental disorder during the lifetime (1), and these disorders are an important cause of long-term disability

© 2014 Informa Healthcare

(2). Furthermore, mental disorders increase the risk of several other diseases, including type 2 diabetes (3) and cardiovascular diseases (4). Depressive, anxiety and alcohol use disorders affect daily routines, of which meals form a fundamental part, and thus may alter nutrient intake (5). On the other hand,

DOI: 10.3109/08039488.2013.851736

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deficiency of certain nutrients is suggested to predispose to these mental disorders (6). Most of the earlier studies have focused on individual nutrients. Much interest has been towards the possible preventive effect of high dietary intakes of fish and n-3 polyunsaturated fatty acids (PUFA) in depressive disorders, but both epidemiological and supplementation studies have provided controversial results (7, 8). Recent studies have indicated that dietary patterns play a role in mood disorders (9, 10). An Australian cross-sectional study of women reported that a dietary pattern comprising vegetables, fruit, beef, lamb, fish and whole-grain foods (traditional) was associated with a lower likelihood of depressive and anxiety disorders, whereas a dietary pattern comprising processed and so-called unhealthy foods (western) was associated with a higher likelihood of psychological symptoms and disorders (9). A large prospective cohort study from UK found robust associations of two dietary patterns, the whole food and the processed food patterns, with depressive symptoms. These results suggested that consumption of fruits, vegetables and fish affords protection against the onset of depressive symptoms 5 years later, whereas a diet rich in processed meat, chocolates, sweet desserts, fried food, refined cereals and high-fat dairy products increases vulnerability (11). Studies on diet in anxiety disorders are scarce. Consumption of alcoholic beverages is known to affect food and nutrient intakes towards more fatty and salty foods, higher protein and fat intakes and a lower carbohydrate intake (12–14), but it has not, to our knowledge, been studied among persons suffering from diagnosed alcohol use disorders.

Aims We investigated the whole diet, as opposed to specific nutrients, in relation to the interview-based diagnoses of depressive, anxiety and alcohol use disorders in a nationwide population-based health examination study sample. Our aim was to replicate the associations from the previous studies of diet with mental health disorders using this large population-based study in order to clarify the consistency of these findings. This study investigated also biomarkers of glucose and lipid metabolism from serum samples of women and men suffering from depressive, anxiety and alcohol use disorders in comparison to the remaining participants in a general population sample. Use of the Composite International Diagnostic Interview (M-CIDI) enabled us to assess the diagnoses of mental disorders instead of self-reported symptoms. The whole diet was included through measuring the consumption of food items and the nutrient intakes by a food frequency questionnaire (FFQ), and the serum cholesterol, glucose and gamma-glutamyltransferase (GGT) concentrations were measured to study the metabolic state.

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Materials and Methods The study was based on a nationally representative crosssectional sample of the Finnish population aged 30 years and over. The data was collected in 2000–2001 in the Health 2000 Survey (15). The subjects were invited by mail to take part in a health interview at their homes (participation rate was 87%) and thereafter in 1 month to a health examination at a health care centre in their home area (participation rate was 84%). In total, comprehensive data on both mental health and diet was obtained from 3009 women and 2495 men. After a complete description of the study to the subjects, written informed consent was obtained at the beginning of the health interview. The study was approved by the Ethics Committee for Epidemiology and Public Health of the hospital district of Helsinki and Uusimaa in Finland.

Outcomes of mental health The presence of mental disorders during the 12 months preceding the health examination was determined by the M-CIDI, a structured computer-aided mental health interview (16, 17). The interview was performed as part of the health examination by nurses trained in the use of the programme. Diagnoses according to DSM-IV are grouped to depressive disorders comprising major depressive disorder and dysthymia; anxiety disorders comprising panic disorder, agoraphobia and social phobia; and alcohol use disorders comprising alcohol abuse and alcohol dependence. Participants suffering from none of the studied disorders or any other mental disorder as assessed with the M-CIDI interview are hereafter referred to as the remaining and can be considered as the healthy controls. Participants suffering from more than one studied disorders currently had so-called co-morbid disorders and were excluded from the analyses (n ⫽ 139). Additionally, selfreported mental well-being was measured using a modified Beck Depression Inventory (BDI) (18, 19) as part of a questionnaire given at the end of the health examination to be filled out at home and mailed back to the National Public Health Institute.

Dietary data Consumption of foods was measured by a validated 128 item FFQ (20, 21) given at the end of the health examination with the other questionnaire including among others the BDI. The subjects were asked to estimate the consumption frequency of each food item on a nine-step scale from “never or very rarely” to “6 times a day or more often” during the past 12 months. Fixed portion sizes were marked on the questionnaire, e.g. piece, slice, glass and tablespoon. When returned, questionnaires were controlled for unreliable answers by a nutritionist. The average daily food consumptions and nutrient intakes were calculated using a national food composition database NORD J PSYCHIATRY·VOL 68 NO 6·2014

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(Fineli®, National Institute for Health and Welfare, Finland). Before data analysis, credibility of all the returned FFQs was estimated by checking the amounts of food reported to be consumed and the number of empty lines. The ones seeming unreliable were excluded irrespective of mental health status. In the groups of mental disorders, the response rate on FFQ after exclusion of the unreliable answers was only slightly lower than among the remaining participants (89–91% vs. 95%).

Serum sampling Serum samples were collected at the health examination and stored at ⫺ 70°C until analysis by 6 months from sampling at the latest. Serum concentrations of total, high-density lipoprotein (HDL) and low-density lipoprotein (LDL) cholesterols, triacylglycerol and glucose were determined enzymatically (total cholesterol: CHOD PAP, TAG: GPO PAP, glucose: Hexokinase; Olympus System Reagent, Germany and HDL-cholesterol: HDL-C Plus, LDL-cholesterol: LDL-C Plus; Roche Diagnostics GmbH, Germany) and GGT by a kinetic method (IFCC/ECCLS, Konelab, Thermo Electron Oy, Finland).

Socio-demographic and lifestyle factors Birth date acquired from national register and verified at the health examination was used to calculate the age. Body mass index (BMI) was calculated using body weight and height measured at the health examination. Marital status and education history were queried at the health interview. Education level is categorized in three: basic education—vocational course or job training; secondary education—completed vocational school or matriculation examination; higher education—polytechnic or academic degree. The level of physical activity and the experience of social support were asked by a questionnaire on a questionnaire given at the end of the health interview to be filled out at home and brought along to the health examination. At least 30 min walking or cycling daily as means of transport and/or exercising four to six times a week, minimum 30 min at a time, was considered satisfactory physical activity. The social support was estimated with four questions asking who the person can trust: 1) to care about one whatever happened, 2) to cheer up when feeling blue, 3) to help when one is exhausted, and 4) to help in practical difficulties. Answer “no-one” in any of the four questions was considered low social support, and at least one in each satisfactory social support. Also tobacco smoking was categorized in two: yes or no.

Statistical analysis Continuous variables are presented as means with 95% confidence intervals (CI) and categorical variables as NORD J PSYCHIATRY·VOL 68 NO 6·2014

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absolute and relative frequencies. The intake of energy yielding nutrients was assessed as percentage of total daily energy intake. Natural logarithms were calculated for alcohol (as energy yielding nutrient), all food and beverage items and for the serum concentrations of GGT, triacylglycerol and glucose to normalize the distribution. The mean values presented for these variables are transformed back to original units from the logarithmic values. Differences in the studied variables were assessed by creating general linear models, referred to as the adjusted model, with each nutrient, food or beverage item and biomarker at a time as dependent variable and with each disorder at a time with the confounding variables as independent variables. For all studied variables, age, education level, social support and smoking were used as confounding variables. In the analyses of both genders, gender also was used as a confounding variable. Daily energy intake was added to the confounding variables in the models for food and beverage items and dietary fibre. All confounding variables were assessed individually before inclusion to the models. Level of physical activity was also considered as confounding variable, but as it was not significantly associated with none of the diagnoses for mental disorders (P ⬎ 0.3) it was not taken into the adjusted models. Due to multiple groups tested (i.e. six) and high number of dependent variables (nine macronutrients with energy and fibre, 36 food and beverage items, and six biomarkers), the level of significance was corrected using the Bonferroni rule to control for the increase in type 1 error. The statistical analysis of the data was performed using SPSS (version 15.0; SPSS, Chicago, IL, USA).

Results Group characteristics In each of the diagnosis groups, compared with the remaining participants for both women and men, the mean age was lower, the BDI sum score on average was higher, and the subjects experienced statistically significantly more often low social support, except women suffering from anxiety disorders, and the fewer subjects were married or co-habiting, except women suffering from anxiety disorders (Table 1). Women suffering from anxiety disorders had a higher BMI and men suffering from anxiety disorders had a lower BMI than the remaining. Fewer women suffering from alcohol use disorders reported physical activity of a satisfactory level than the remaining. A higher proportion of the female subjects suffering from anxiety disorders and of the male subjects suffering from alcohol use disorders had a polytechnic or an academic degree than the remaining participants.

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Table 1. Socio-demographic and lifestyle factors grouped by diagnosis of mental disorders. Depressive disorders n ⫽ 199

Healthya n ⫽ 2855

Anxiety disorders n ⫽ 82

Alcohol use disorders n ⫽ 33

Women

Mean

s

Mean

s

Mean

s

Mean

s

Age (years) Body mass index (kg/m2) Beck Depression Inventory sum score

53.7 26.8 6.9

15.2 5.1 6.2

49.3 26.8 13.5

13.4 5.1 8.2

50.5 27.6 11.7

13.6 5.1 8.6

45.1 26.6 12.6

12.0 4.8 7.5

n

%

n

%

n

%

n

%

Married or cohabiting High educationb Satisfactory physical activityc Low social support

1893 921 974 218

66.3 32.2 34.1 7.6

117 64 63 18

58.8 32.2 31.7 9.0

55 30 31 5

67.1 36.6 37.8 6.1

21 8 7 3

63.6 24.2 21.2 9.1

n ⫽ 2371

n ⫽ 73

n ⫽ 45

n ⫽ 167

Men

Mean

s

Mean

s

Mean

s

Mean

s

Age (years) Body mass index (kg/m2) Beck Depression Inventory sum score

51.9 27.1 5.2

14.1 4.1 5.4

46.1 27.1 16.1

10.3 4.0 8.9

46.8 26.1 12.3

10.5 3.8 10.0

46.1 27.1 7.3

10.3 4.0 6.2

n

%

n

%

n

%

n

%

1858 578 701 238

78.4 24.4 29.6 10.0

44 17 17 17

60.2 23.3 23.3 23.3

29 9 17 7

64.4 20.0 37.7 15.5

114 45 49 28

65.9 30.2 28.1 20.8

Married or cohabiting High educationb Satisfactory physical activityc Low social support

s, standard deviation. aIn regard to the studied disorders. bPolytechnic or academic degree. cMinimum 30 min daily walking or cycling and/or exercising minimum 30 min 4–6 times weekly.

Food and beverage consumption The logarithmic mean consumptions of foods and beverages among women are presented in Table 2 and among men in Table 3. In depressive disorders, women consumed 44% more soft drinks than the remaining female participants, and men consumed 19% less sweets and chocolate than the remaining male participants. There were no significant differences in whole group analyses in subjects with depressive disorder. Subjects with anxiety disorders consumed 4% less potatoes (P ⫽ 0.005) and 18% less milk (P ⫽ 0.038), and 16% more rice (P ⫽ 0.033), 17% more pasta (P ⫽ 0.037) and 4% more oils (P ⫽ 0.003) than the remaining subjects. In anxiety disorders, women consumed 5% less cheese, 18% less rye, 17% less potatoes but 13% more oils than the remaining female participants, whereas men consumed 5% more tea than the remaining male participants. Subjects with alcohol use disorders consumed 11% less cereals (P ⫽ 0.002), 10% less wheat (P ⫽ 0.006) and 36% less fruits and berries (P ⫽ 0.036), but 19% more eggs (P ⫽ 0.001) than the remaining participants.

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In alcohol use disorders, women consumed 46% less fruits and berries, 39% less fermented milk products and 35% less sugar and syrups, and 45% more pasta than the remaining female participants, whereas men consumed 31% more eggs, and 13% less cereals in total and 14% less wheat than the remaining male participants. All these differences were statistically significant in the adjusted model.

Energy and macronutrient intake Based on the adjusted model, no statistically significant differences in energy and macronutrient intake were observed between subjects suffering from depressive disorders and the remaining participants (Table 4). Subjects with anxiety disorders had a higher (⫹ 6%) intake of PUFAs than the remaining participants (P ⫽ 0.001). In anxiety disorders, women had a significantly higher (⫹ 7%) intake of PUFAs than the remaining participants, whereas there were no significant differences in men. Subjects with alcohol use disorders had a significantly lower (8%) intake of carbohydrate (P ⫽ 0.001): women had 11% and men 7% lower intakes of carbohydrate than the remaining participants. In alcohol use disorders, NORD J PSYCHIATRY·VOL 68 NO 6·2014

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Table 2. Mean consumption (g/day) of foods and beverages among women grouped by diagnosis of mental disorder adjusted for age, education level, smoking and social support and daily energy intake. Healthya n ⫽ 2637

Vegetables total Fruit and berries Dairy products total Milk Fermented milk products Cheese Eggs Meat total Red meat Fish and seafood total Cereals total Rye Wheat Pasta Rice Potatoes Dietary fats total Butter Oil Coffee Tea Sweets and chocolate Sugar and syrups Soft drinks Juice Alcoholic beverages total

Depressive disorders n ⫽ 185

Anxiety disorders n ⫽ 76

Alcohol use disorders n ⫽ 31

Mean

95% CI

Mean

95% CI

Pb

Mean

95% CI

Pb

Mean

95% CI

Pb

310 250 579 323 186 44 26 159 74 46 185 49 68 6.2 30 173 47 11 8.5 382 144 16 17 62 80 54

303–319 242–259 566–592 314–334 179–193 43–46 25–27 155–162 72–76 44–47 182–188 48–50 67–70 6.0–6.5 29–32 168–178 46–48 10–11 8.3–8.9 373–390 135–153 15–17 17–18 56–68 76–85 50–58

309 251 576 322 182 46 28 168 71 45 177 44 62 7.1 32 167 45 9.4 9.0 399 142 20 16 89 85 62

276–343 221–282 527–625 286–358 152–211 40–53 24–32 150–186 64–78 41–50 166–187 39–49 58–67 5.9–8.3 27–36 146–187 42–48 8.4–10 8.3–9.7 363–435 113–171 16–24 15–18 61–117 69–101 49–74

NS NS NS NS NS NS NS NS NS NS NS NS NS NS NS NS NS NS NS NS NS NS NS 0.034 NS NS

312 255 480 254 158 42 28 168 72 52 185 40 72 7.8 34 144 46 9.7 9.6 418 165 21 17 76 95 66

269–355 212–299 410–551 206–303 122–194 35–48 23–32 144–192 62–83 42–62 168–203 32–48 64–81 6.0–9.6 26–42 125–164 41–51 8.3–11 8.4–11 347–489 118–211 16–26 14–19 37–116 67–122 41–90

NS NS NS NS NS 0.043 NS NS NS NS NS 0.013 NS NS NS 0.002 NS NS ⬍ 0.001 NS NS NS NS NS NS NS

274 134 536 354 114 48 25 186 81 40 161 46 52 11.2 35 180 47 9.3 9.4 348 168 15 11 76 70 150

215–333 82–185 396–677 234–473 63–165 35–62 19–31 157–216 68–94 32–48 137–186 34–58 42–62 7.1–15.2 25–46 137–222 38–55 6.6–12 7.8–11 282–409 85–251 5.2–25 7.8–15 25–127 38–101 113–188

NS ⬍ 0.001 NS NS 0.038 NS NS NS NS NS NS NS NS 0.005 NS NS NS NS NS NS NS NS 0.022 NS NS 0.009

NS, not significant. aIn regard to studied disorders. bCompared with healthy in a linear model adjusted for age, education level, social support, smoking and daily energy intake, Bonferroni rule applied to control the increase in Type I error due to multiple tests.

women had a significantly lower intake of sucrose (⫺ 25%) and significantly higher intakes of fats (⫹ 8%) and monosaturated fatty acids (MUFA, ⫹ 27%), whereas men had a significantly lower intake of dietary fibres (⫺ 12%) than the remaining participants. As expected, ethanol intake was significantly higher (63%) among subjects with alcohol use disorders than among the remaining participants.

Serum biomarkers Subjects suffering from alcohol use disorders had significantly lower (2%) concentrations of HDL (P ⫽ 0.009) and higher (42%) concentrations of GGT (P ⬍ 0.001) than the remaining participants. When analysed by both gender, only men suffering from alcohol use disorders had a significantly higher (39%) concentration of GGT than the remaining participants (Table 5). There were no other significant differences in serum biomarkers in the adjusted model in subjects suffering from depressive disorder, anxiety disorder or alcohol use disorders. NORD J PSYCHIATRY·VOL 68 NO 6·2014

Conclusion Diet in depressive disorders Studies on the association between diet and depression have focused primarily to specific nutrients such as fatty acids or vitamins. In earlier studies, low fish consumption and n-3 PUFA intake have been associated with depressive disorders (22–24), but there are also controversial results (7, 8). In addition, a couple of studies have demonstrated recently that unhealthy dietary patterns are associated with mood disorders (9–11). In our study, depressed women consumed more soft drinks and depressed men consumed less sweets and chocolate than the remaining participants. No other sample differences were, however, detected among either women or men suffering from depressive disorders compared with the remaining participants. Our findings disagree with a previous cross-sectional study where higher depressive symptoms were associated with greater chocolate consumption (25). There is a lack of studies about consuming of soft drinks and sweets and chocolate in depressed subjects.

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Table 3. Mean consumption (g/day) of foods and beverages among men grouped by diagnosis of mental disorder adjusted for age, education level, smoking and social support and daily energy intake. Healthya n ⫽ 2171

Vegetables total Fruit and berries Dairy products total Milk Fermented milk products Cheese Eggs Meat total Red meat Fish and sea food total Cereals total Rye Wheat Pasta Rice Potatoes Dietary fats total Butter Oil Coffee Tea Sweets and chocolate Sugar and syrups Soft drinks Juice Alcoholic beverages total

Depressive disorders n ⫽ 61

Anxiety disorders n ⫽ 40

Alcohol use disorders n ⫽ 150

Mean

95% CI

Mean

95% CI

Pb

Mean

95% CI

Pb

Mean

95% CI

Pb

242 173 593 379 148 40 29 186 89 47 199 52 80 6.0 31 185 50 12 9.2 438 108 16 22 99 76 141

234–249 166–181 577–608 366–392 140–155 38–41 28–30 182–190 87–91 46–49 196–203 50–53 79–82 5.7–6.2 29–32 181–191 49–51 12–13 9.0–9.4 428–449 100–115 15–17 22–23 92–105 72–81 131–151

236 205 647 399 182 39 39 196 98 47 194 48 83 5.2 32 206 51 12 9.7 440 115 13 22 113 92 145

195–277 128–281 558–735 320–478 131–233 31–47 31–47 171–222 85–111 35–59 173–215 32–57 69–96 3.7–6.7 25–40 161–250 44–58 9.2–14 8.3–11 366–1515 57–173 8.7–17 18–27 52–174 63–120 81–209

NS NS NS NS NS NS NS NS NS NS NS NS NS NS NS NS NS NS NS NS NS 0.002 NS NS NS NS

229 211 536 352 117 42 34 202 88 47 207 55 78 6.8 40 187 56 12 10 423 163 15 23 79 89 173

173–285 129–292 425–648 256–447 67–166 33–51 26–42 164–240 72–104 37–57 177–236 41–68 62–95 4.9–8.8 27–53 145–229 41–70 8.8–14 7.7–12 344–503 78–247 7.7–22 18–27 39–120 46–131 77–269

NS NS NS NS NS NS NS NS NS NS NS NS NS NS NS NS NS NS NS NS 0.033 NS NS NS NS NS

238 142 552 375 110 40 38 196 88 47 173 44 69 6.0 30 161 48 11 9.1 425 104 17 19 116 86 322

204–272 116–167 458–605 327–422 90–131 34–46 29–42 182–209 81–96 41–53 160–185 39–49 62–76 5.0–7.0 25–34 147–175 44–51 9.4–12 8.3–9.8 381–468 74–134 14–20 17–21 89–143 65–108 241–403

NS NS NS NS NS NS ⬍ 0.001 NS NS NS 0.04 NS 0.016 NS NS NS NS NS NS NS NS NS NS NS NS ⬍ 0.001

NS, not significant. aIn regard to studied disorders. bCompared with healthy in a linear model adjusted for age, education level, social support, smoking and daily energy intake, Bonferroni rule applied to control the increase in Type I error due to multiple tests.

Diet in anxiety disorders Subjects with anxiety disorder consumed more oils and the intakes of PUFAs were higher as the remaining subjects. Also they consumed less potatoes and milk. However, these finding showed only in women when analysed both genders separate. Here, in women with anxiety disorders, the intake of PUFA was higher, because they consumed more oils than the remaining female participants. Also they consumed less cheese, less ryes, less potatoes than the remaining female participants. Men with anxiety disorders consumed more tea than the remaining male participants. No other differences in diet were detected between those suffering from anxiety disorders and the remaining participants. It is of note here that an Australian cross-sectional study of women reported association between a “traditional” dietary pattern characterized by vegetables, fruit, meat, fish, and whole grains and the lowered odds for anxiety disorders (9). Our current result showing no difference deviates from a Greek population study (26), which found higher consumption

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of red meat and sweets among women having high anxiety scores compared with those having low anxiety scores. The anxiety trait is substantially different from the diagnosis of anxiety disorder, which complicates the comparison. Earlier, the intake of n-3 PUFAs has been associated with mood disorders. There just a few studies about the associations of PUFAs and anxiety disorders. In a casecontrol study, non-depressed patients with social anxiety disorder reported reduced levels of most n-3 PUFAs in erythrocytes compared with healthy controls (27). Previously, it has been reported that in a cross-sectional study on women the dietary intake of docosahexaenoic acid (DHA) intake associated linear with anxiety disorders (28). There was no association between anxiety disorder and other PUFAs. In this study, the higher intake of PUFAs was found only in women suffering from anxiety disorders. This finding is consistent with the results of the Health 2000 study where the proportion of soft fat was bigger on the NORD J PSYCHIATRY·VOL 68 NO 6·2014

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Table 4. Mean daily intakes of energy, dietary fibre and macronutrients grouped by diagnosis of mental disorder adjusted for age, education level, smoking and social support. Healthya Mean

Men Energy (MJ/day) Dietary fibre (g/day) Percentage of daily energy intake Fat SFA MUFA PUFA n-3 PUFA Protein Carbohydrate Sucrose Alcohol

Mean

n ⫽ 2637

Women Energy (MJ/day) Dietary fibre (g/day) Percentage of daily energy intake Fat SFA MUFA PUFA n-3 PUFA Protein Carbohydrate Sucrose Alcohol

95% CI

Depressive disorders

Anxiety disorders

95% CI

n ⫽ 185

Mean

95% CI

n ⫽ 76

Pb

Alcohol use disorders Mean

95% CI n ⫽ 31

Pb

Pb

9.2 26

89.1–9.3 26–26

9.2 25

8.8–9.7 23–26

NS NSc

9.2 25

8.4–9.9 23–28

NS NSc

8.8 22

7.8–9.8 19–25

NS NSc

36 14 11 5.4 1.1 18 45 8.9 1.0

36–36 14–14 11–11 5.3–5.4 1.1–1.1 17–18 45–46 8.7–9.0 0.9–1.1

36 14 12 5.5 1.1 18 45 9.2 1.1

36–37 13–14 11–12 5.3–5.7 1.1–1.2 17–18 44–46 8.6–9.6 0.9–1.3

NS NS NS NS NS NS NS NS NS

37 14 12 5.8 1.2 18 44 8.7 1.1

36–39 13–14 11–12 5.5–6.0 1.1–1.3 17–18 43–45 8.2–9.3 0.8–1.5

NS NS NS ⬍ 0.001 NS NS NS NS NS

39 15 13 5.8 1.1 18 40 6.6 2.8

37–40 14–15 12–13 5.4–6.2 1.0–1.1 17–19 38–42 5.4–7.8 2.1–3.5

0.018 NS 0.017 NS NS NS 0.001 0.024 0.005

10.0 25

9.9–10.2 24–25

10.3 24

9.3–11.3 22–27

NS NSc

10.4 25

9.1–11.7 22–29

NS NSc

9.8 22

9.2–10.3 20–23

NS 0.049c

36 14 12 5.3 1.1 17 44 8.6 2.2

37–37 14–14 11–12 5.2–5.3 1.0–1.1 17–17 44–44 8.4–8.8 2.1–2.4

37 14 12 5.3 1.0 17 44 8.5 2.1

36–38 14–15 11–12 5.0–5.6 1.0–1.1 17–18 42–45 7.6–9.4 1.3–2.9

NS NS NS NS NS NS NS NS NS

37 14 12 5.4 1.1 17 43 8.5 2.9

36–39 13–15 11–13 4.9–5.9 1.0–1.2 16–18 41–45 7.5–9.6 1.5–4.3

NS NS NS NS NS NS NS NS NS

37 14 12 5.4 1.1 17 41 8.3 4.5

36–38 14–15 12–12 5.2–5.6 1.0–1.1 17–17 41–42 7.8–8.8 3.6–5.4

n ⫽ 2171

n ⫽ 61

n ⫽ 40

n ⫽ 150

NS NS NS NS NS NS 0.001 NS ⬍ 0.001

NS, not significant; SFA, saturated fatty acids; MUFA, monounsaturated fatty acids; PUFA, polyunsaturated fatty acids. aIn regard to the studied disorders. bCompared with healthy in a linear model adjusted for age, education level, social support and smoking. Bonferroni rule applied to control the increase in Type I error due to multiple tests. cAdditionally adjusted for daily energy intake.

women’s diet than men and women ate vegetables, fruits and berries more than men (29). It is a new finding that men with anxiety disorder consumed more tea than the remaining participants. There are now previous similar findings.

Diet in alcohol use disorders Our results of the nutrient intake of the subjects suffering from alcohol use disorders are in agreement with earlier studies investigating the relationship of alcohol intake with the intake of macronutrients: alcohol replaced mainly carbohydrates as a source of the energy intake (12–14). A Finnish cross-sectional study of women and men aged 25–64 years (n ⫽ 1847) reported a lower carbohydrate intake measured with a 3-day food record among those consuming alcoholic beverages compared with abstainers (12). A French cross-sectional study of middle-aged men (n ⫽ 1110) using a 3-day food record (13) and a German cross-sectional study of women and men aged 35–65 years (n ⫽ 24,894) using a 12-month FFQ (14) reported a NORD J PSYCHIATRY·VOL 68 NO 6·2014

lowering carbohydrate intake with an increasing ethanol intake. The differences in carbohydrate intake were derived from the lower consumption of fruit and berries, sugar and syrups and cereals, which are rich in carbohydrate. In addition, the intake of dietary fibre, which is derived largely from cereals and fruits, was lower among men. In terms of consumption of food items the results agreed with the French study of middle-aged men (n ⫽ 1110) (13) and the German study of women and men (n ⫽ 24,894) (14). Women with alcohol use disorders had a higher intake of fats, MUFAs in particular, and consumed less fermented milk products than the remaining participants.

Serum biomarkers The higher GGT concentrations of men suffering from alcohol use disorders compared with the remaining participants are logical as serum GGT is used as a marker of liver damage and excessive alcohol consumption (30). Recently serum GGT has also been suggested to be a

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Table 5. Mean concentrations (mmol/l) of metabolic biomarkers in serum grouped by diagnosis of mental disorder adjusted for age, education level, smoking and social support. Healthya Mean 95% CI Women Total cholesterol HDL-cholesterol LDL-cholesterol Triacylglycerol Glucose GGT (U/l) Men Total cholesterol HDL-cholesterol LDL-cholesterol Triacylglycerol Glucose GGT (U/l)

n ⫽ 2831 5.9 1.4 3.6 1.4 5.5 26

5.9–6.0 1.4–1.5 3.6–3.7 1.4–1.4 5.4–5.5 25–27

Depressive disorders Mean

n ⫽ 2353 6.0 1.2 3.8 1.8 5.6 45

5.9–6.0 1.2–1.2 3.8–3.9 1.7–1.8 5.5–5.6 43–47

95% CI

n ⫽ 155 5.8 1.5 3.7 1.3 5.3 28

Anxiety disorders

5.7–6.0 1.4–1.5 3.6–3.9 1.2–1.4 5.2–5.4 23–34

Mean

NS NS NS NS NS NS

5.9 1.4 3.8 1.4 5.4 30

NS NS NS NS NS NS

5.7 1.2 3.6 1.8 5.7 55

n ⫽ 60 5.8 1.2 3.7 1.8 6.2 47

5.6–6.0 1.1–1.3 3.8–3.8 1.7–1.8 5.6–6.7 38–57

95% CI

n ⫽ 82

Pb

Alcohol use disorders

5.7–6.2 1.4–1.5 3.6–4.0 1.3–1.6 5.2–5.5 25–35

Mean

NS NS NS NS NS NS

5.5 1.4 3.3 1.3 5.4 45

NS NS NS NS NS NS

6.0 1.3 3.7 2.0 5.7 74

n ⫽ 45 5.4–6.0 1.2–1.3 3.3–4.0 1.3–2.3 5.4–6.1 17–92

95% CI

n ⫽ 32

Pb

5.1–5.9 1.3–1.6 3.1–3.8 1.1–1.5 4.9–6.7 26–63

Pb NS NS NS NS NS NS

n ⫽ 158 5.8–6.2 NS 1.2–1.3 NS 3.4–3.9 NS 1.7–2.2 NS 5.5–5.9 NS 56–92 ⬍ 0.001

NS, not significant; HDL, high-density lipoprotein; LDL, low-density lipoprotein; GGT. gamma-glutamyltransferase. regard to the studied disorders. bCompared with healthy in a linear model adjusted for age, education level,social support and smoking, Bonferroni rule applied to control the increase in Type I error due to multiple tests. aIn

marker of oxidative stress (31), which has been linked to both depressive and anxiety disorders (32). Furthermore, elevated serum GGT within the normal range has been proposed to be a predictor of type 2 diabetes mellitus (33) and cardiovascular diseases (34). Epidemiologically type 2 diabetes seems to have a link to both depression (3, 35) and anxiety (36). Moreover, the results of our current study do not give support to the earlier findings of a statistically significant inverse association between concentrations of serum total cholesterol and the risk of depression (37). In a recent meta-analysis, the association was weaker in the studies using diagnostic interviews, as were used here, than the studies using self-reported symptoms (37).

Strengths and limitations The strengths of this study include the large sample size, in range of the earlier studies, and the sample being representative of the Finnish general population aged 30 years and over. The participation rate was extremely high, data on both mental health and diet was obtained for 69% of the invited sample. The data is comprehensive on a wide range of health parameters. Data on mental disorders was collected by a diagnostic interview, M-CIDI, which is documented to be a sensitive diagnostic tool for the studied mental disorders (16). Additionally, BDI was used for estimating the severity of depression symptoms (18, 19). Food and beverage consumption in the diet as a whole was measured, whereas earlier studies have mainly concentrated on selected dietary components, such as fish.

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To our knowledge, no other studies combining the whole diet with the clinical diagnoses of these mental disorders have been reported. Reproducibility and reliability of the validated FFQ were on the same range with previously reported in Finland, and in general the reliability was good (20, 21, 38). Due to the number of variables tested, the Bonferroni rule was applied to control for the increase in type 1 error. A limitation of this study is that the data are crosssectional, thus not revealing causalities. Despite the high participation rate and the use of the entire population as the target population in sampling, it is possible that subjects suffering from serious illnesses, having physical disabilities or residing in institutions, found it more challenging to participate. Men with alcohol disorders as well as women with anxiety disorders had a higher educational level than the rest of the study participants, which indicates that a higher proportion of the less educated with those disorders might have not participated. This might have attenuated the real differences between the groups.

Clinical implications We suggest that the diet of patients suffering from mental health disorders will be assessed in order to evaluate whether it qualifies the nutritional recommendations. In future, longitudinal studies are needed, and with help from their findings, the underlying physiological mechanisms with links between the dietary intake and mental health might be identified. NORD J PSYCHIATRY·VOL 68 NO 6·2014

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Conclusion There were no similar and consistent differences in food consumption or nutrient intake in both genders among women and men suffering from depressive or anxiety disorder compared with the remaining participants. When, both genders analysed separately there were some significant differences in food consumption and nutrients intake, example the intake of PUFAs and oils was higher in women, and the consumption of tea was higher in men suffering from anxiety disorders than the remaining participants. Carbohydrate intake and consumption of certain carbohydrate rich foods were lower among individuals suffering from alcohol use disorders compared with the remaining participants. No differences in biomarkers were found among women and men suffering from depressive disorders or anxiety disorders compared with the remaining participants on a population level.

Acknowledgements—The

authors warmly thank all those contributing to the data collection. Mr Juhani Mäki is acknowledged for his kind guidance in statistics. The Finnish Cultural Foundation, the Finnish Medical Foundation and the Juho Vainio Foundation are gratefully acknowledged for their financial support. Declaration of interest: Dr Rintamäki has received working grants from Finnish Medical Foundation and Finnish Cultural Foundation, no conflict of interest. Ms. Kaplas has received working grants from Juho Vainio Foundation and Finnish Cultural Foundation, no conflict of interest. Dr Männistö, Dr Montonen, Dr Knekt, Prof. Lönnqvist and Dr Partonen: no conflict of interest. The authors alone are responsible for the content and writing of the paper.

References 1. The World Health Report. Mental health: New understanding, new hope. Geneva: World Health Organization; 2001. 2. Prince M, Patel V, Saxena S, Maj M, Maselko J, Phillips MR, et al. No health without mental health. Lancet 2007;370:859–77. 3. Mezuk B, Eaton WW, Albrecht S, Golden SH. Depression and type 2 diabetes over the lifespan: A meta-analysis. Diabetes Care 2008;31:2383–90. 4. Kuper H. Systematic review of prospective cohort studies of psychosocial factors in the etiology and prognosis of coronary heart disease. Semin Vasc Med 2002;2:267–314. 5. American Psychiatric Association. Diagnostic and statistical manual of mental disorders. Washington DC: APA; 1994. 6. Rogers PJ. A healthy body, a healthy mind: Long-term impact of diet on mood and cognitive function. Proc Nutr Soc 2001;60:135–43. 7. Appleton KM, Woodside JV, Yarnell JWG, Arveiler D, Haas B, Amouyel P, et al. Depressed mood and dietary fish intake: Direct relationship or indirect relationship as a result of diet and lifestyle? J Affect Disord 2007;104:217–23. 8. Hakkarainen R, Partonen T, Haukka J, Virtamo J, Albanes D, Lonnqvist J. Is low dietary intake of omega-3 fatty acids associated with depression? Am J Psychiatry 2004;161: 567–69.

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9. Jacka FN, Pasco JA, Mykletun A, Williams LJ, Hodge AM, O’Reilly SL, Nicholson GC, Kotowicz MA, Berk M. Association of Western and traditional diets with depression and anxiety in women. Am J Psychiatry 2010;167:305–11. 10. Davison KM, Kaplan BJ. Food intake and blood cholesterol levels of a community-based adults with mood disorders. BMC Psychiatry 2012;12:10. 11. Akbaraly TN, Brunner EJ, Ferrie JE, Marmot MG, Kivimaki M, Singh-Manoux A. Dietary pattern and depressive symptoms in middle age. Br J Psychiatry. 2009;195:408–13. 12. Männistö S, Uusitalo K, Roos E, Fogelholm M, Pietinen P. Alcohol beverage drinking, diet and body mass index in a cross-sectional survey. Eur J Clin Nutr 1997;51:326–32. 13. Ruidavets J-B, Bataille V, Dallongeville J, Simon C, Bingham A, Amouyel P, et al. Alcohol intake and diet in France, the prominent role of lifestyle. Eur Heart J 2004;25:1153–62. 14. Ruf T, Nagel G, Altenburg HP, Miller AB, Thorand B. Food and nutrient intake, anthropometric measurements and smoking according to alcohol consumption in the EPIC Heidelberg Study. Ann Nutr Metab 2005;49:16–25. 15. Aromaa A, Koskinen S, editors. Health and functional capacity in Finland Baseline results of the Health 2000 Health Examination Survey. Helsinki: National Public Health Institute; 2004. 16. Wittchen HU, Lachner G, Wunderlich U, Pfister H. Test–retest reliability of the computerized DSM-IV version of the MunichComposite International Diagnostic Interview (M-CIDI). Soc Psychiatry Psychiatr Epidemiol 1998;33:568–78. 17. Pirkola S, Isometsä E, Suvisaari J, Aro H, Joukamaa M, Poikolainen K, et al. DSM-IV mood-, anxiety- and alcohol use disorders and their comorbidity in the Finnish general population. Soc Psychiatry Psychiatr Epidemiol 2005;40:1–10. 18. Beck AT. An inventory for measuring depression. Arch Gen Psychiatry. 1961;4:561–71. 19. Raitasalo R. Depression and its association with the need of psychotherapy [in Finnish: Depressio ja sen yhteys psykoterapian tarpeeseen]. Helsinki: The Social Insurance Institution of Finland; 1977. 20. Paalanen L, Mannisto S, Virtanen MJ, Knekt P, Rasanen L, Montonen J, et al. Validity of a food frequency questionnaire varied by age and body mass index. J Clin Epidemiol 2006;59: 994–1001. 21. Männistö S, Virtanen M, Mikkonen T, Pietinen P. Reproducibility and validity of a food frequency questionnaire in a case–control study on breast cancer. J Clin Epidemiol 1996;49:401–9. 22. Astorg P, Couthouis A, Bertrais S, Arnault N, Meneton P, Guesnet P, et al. Association of fish and long-chain n-3 polyunsaturated fatty acid intakes with the occurrence of depressive episodes in middle-aged French men and women. Prostaglandins, Leukotrienes and Essential Fatty Acids 2008;78:171–82. 23. Timonen M, Horrobin D, Jokelainen J, Laitinen J, Herva A, Räsänen P. Fish consumption and depression: The Northern Finland 1966 birth cohort study. J Affect Disord 2004;82:447–52. 24. Jacka FN, Pasco JA, Henry MJ, Kotowicz MA, Nicholson GC, Berk M. Dietary omega-3 fatty acids and depression in a community sample. Nutr Neurosci 2004;7:101–6. 25. Rose N, Koperski S, Golomb BA. Mood food: Chocolate and depressive symptoms in a cross-sectional analysis. Arch Intern Med. 2010;26:699–703. 26. Yannakoulia M, Panagiotakos DB, Pitsavos C, Tsetsekou E, Fappa E, Papageorgiou C, et al. Eating habits in relations to anxiety symptoms among apparently healthy adults: A pattern analysis from the ATTICA Study. Appetite 2008;51:519–25. 27. Green P, Hermesh H, Monselise A, Marom S, Presburger G, Weizman A. Red cell membrane omega-3 fatty acids are decreased in nondepressed patients with social anxiety disorder. Eur Neuropsychopharmacol. 2006;16:107–13. 28. Jacka FN, Pasco JA, Williams LJ, Meyer BJ, Digger R, Berk M. Dietary intake of fish and PUFA, and clinical depressive and anxiety disorders in women. Br J Nutr. 2012;10:1–8. 29. Montonen J, Männistö S, Sarkkola C, Järvinen R, Hakala P, Sääksjärvi K, et al. Socio-demographic differences in diet. Health 2000 Survey. Publications of the National Public Health Institute, B 38 / 2008.

399

R RINTAMÄKI ET

AL.

30. Whitfield JB. Gamma glutamyl transferase. Crit Rev Clin Lab Sci 2001;38:263–355. 31. Lim J-S, Yang J-H, Chun B-Y, Kam S, Jacobs JDR, Lee D-H. Is serum [gamma]-glutamyltransferase inversely associated with serum antioxidants as a marker of oxidative stress? Free Radic Biol Med 2004;37:1018–23. 32. Ng F. Oxidative stress in psychiatric disorders: Evidence base and therapeutic implications. Int J Neuropsychopharmacol 2008;11: 851–76. 33. Wannamethee SG, Shaper AG, Lennon L, Whincup PH. Hepatic enzymes, the metabolic syndrome, and the risk of type 2 diabetes in older men. Diabet Care 2005;28:2913–18. 34. Fraser A, Harris R, Sattar N, Ebrahim S, Smith GD, Lawlor DA. Gamma-glutamyltransferase is associated with incident vascular events independently of alcohol intake: Analysis of the British Women’s Heart and Health Study and Meta-Analysis. Arterioscler Thromb Vasc Biol 2007;27:2729–35. 35. McIntyre RS, Soczynska JK, Konarski JZ, Woldeyohannes HO, Law CWY, Miranda A, et al. Should depressive syndromes be reclassified as “metabolic syndrome type II”? Ann Clin Psychiatry 2007;19:257–64. 36. Grigsby AB, Anderson RJ, Freedland KE, Clouse RE, Lustman PJ. Prevalence of anxiety in adults with diabetes—A systematic review. J Psychosom Res 2002;53:1053–60. 37. Shin JY. Are cholesterol and depression inversely related? A meta-analysis of the association between two cardiac risk factors. Ann Behav Med 2008;36:33–43.

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38. Pietinen P, Hartman AM, Haapa E, Räsänen L, Haapakoski J, Palmgren J, et al. Reproducibility and validity of dietary assessment instruments. I. A self-administered food use questionnaire with a portion size picture booklet. Am J Epidemiol 1988;128: 655–66. Reeta Rintamäki, M.D., Ph.D., National Institute for Health and Welfare, Department of Mental Health and Substance Abuse Services, Helsinki FI-00271, Finland. Niina Kaplas, M.Sc., National Institute for Health and Welfare, Department of Mental Health and Substance Abuse Services, Helsinki FI-00271, Finland, and Department of Public Health, University of Turku, Turku, Finland. Satu Männistö, Ph.D., Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland. Jukka Montonen, Ph.D., Department of Health, Functional Capacity and Welfare, National Institute for Health and Welfare, Helsinki, Finland. Paul Knekt, Ph.D., Department of Health, Functional Capacity and Welfare, National Institute for Health and Welfare, Helsinki, Finland. Jouko Lönnqvist, M.D., Ph.D., National Institute for Health and Welfare, Department of Mental Health and Substance Abuse Services, Helsinki FI-00271, Finland. Timo Partonen, M.D., Ph.D., National Institute for Health and Welfare, Department of Mental Health and Substance Abuse Services, Helsinki FI-00271, Finland.

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