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The Baltic Sea Diet Score: a tool for assessing healthy eating in Nordic countries

Authors:
  • Nightingale Health Oy, Finland
  • Finnish Heart Assoaciation

Abstract and Figures

The health-related effects of the Nordic diet remain mostly unidentified. We created a Baltic Sea Diet Score (BSDS) for epidemiological research to indicate adherence to a healthy Nordic diet. We examined associations between the score and nutrient intakes that are considered important in promoting public health. We also examined the performance of the BSDS under two different cut-off strategies. The cross-sectional study included two phases of the National FINRISK 2007 Study. Diet was assessed using a validated FFQ. Food and nutrient intakes were calculated using in-house software. Nine components were selected for the score. Each component was scored according to both sex-specific consumption quartiles (BSDS-Q) and medians (BSDS-M), and summed to give the final score values. A large representative sample of the Finnish population. Men (n 2217) and women (n 2493) aged 25 to 74 years. In the age- and energy-adjusted model, adherence to the diet was associated with a higher intake of carbohydrates (E%), and lower intakes of SFA (E%) and alcohol (E%, where E% is percentage of total energy intake; P < 0·01). Furthermore, the intakes of fibre, Fe, vitamins A, C and D, and folate were higher among participants who adhered to the diet (P < 0·05). After further adjustments, the results remained significant (P < 0·05) and did not differ remarkably between BSDS-Q and BSDS-M. The BSDS can be used as a measure of a healthy Nordic diet to assess diet-health relationships in public health surveys in Nordic countries.
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Public Health Nutrition: 17(8), 1697–1705 doi:10.1017/S1368980013002395
The Baltic Sea Diet Score: a tool for assessing healthy eating in
Nordic countries
Noora Kanerva
1,
*, Niina E Kaartinen
1
, Ursula Schwab
2,3
, Marjaana Lahti-Koski
4
and
Satu Ma
¨nnisto
¨
1
1
Department of Chronic Disease Prevention, National Institute for Health and Welfare, PO Box 30, FI-00270
Helsinki, Finland:
2
Department of Clinical Nutrition, Institute of Public Health and Clinical Nutrition, University of
Eastern Finland, Kuopio, Finland:
3
Institute of Clinical Medicine, Internal Medicine, Kuopio University Hospital,
Kuopio, Finland:
4
Finnish Heart Association, Helsinki, Finland
Submitted 16 November 2012: Final revision received 23 July 2013: Accepted 28 July 2013: First published online 4 September 2013
Abstract
Objective: The health-related effects of the Nordic diet remain mostly unidentified.
We created a Baltic Sea Diet Score (BSDS) for epidemiological research to indi-
cate adherence to a healthy Nordic diet. We examined associations between the
score and nutrient intakes that are considered important in promoting public
health. We also examined the performance of the BSDS under two different cut-off
strategies.
Design: The cross-sectional study included two phases of the National FINRISK
2007 Study. Diet was assessed using a validated FFQ. Food and nutrient intakes
were calculated using in-house software. Nine components were selected for the
score. Each component was scored according to both sex-specific consumption
quartiles (BSDS-Q) and medians (BSDS-M), and summed to give the final score
values.
Setting: A large representative sample of the Finnish population.
Subjects: Men (n2217) and women (n2493) aged 25 to 74 years.
Results: In the age- and energy-adjusted model, adherence to the diet was
associated with a higher intake of carbohydrates (E%), and lower intakes of SFA
(E%) and alcohol (E%, where E% is percentage of total energy intake; P,0?01).
Furthermore, the intakes of fibre, Fe, vitamins A, C and D, and folate were higher
among participants who adhered to the diet (P,0?05). After further adjustments,
the results remained significant (P,0?05) and did not differ remarkably between
BSDS-Q and BSDS-M.
Conclusions: The BSDS can be used as a measure of a healthy Nordic diet to assess
diet–health relationships in public health surveys in Nordic countries.
Keywords
Baltic Sea diet
Diet score
Diet quality
Dietary intake
Nordic countries
Nutrition is an important part of health policies due to
its critical role in chronic disease prevention
(1,2)
. The
complexity of the human diet, however, represents a
challenge for studies investigating the health effects of
single foods and nutrients. These studies often produce
controversial results which complicates policy making
(3,4)
.
Therefore, epidemiological research has expanded towards
studying whole diets using dietary pattern methods, for
example dietary scores.
A dietary score represents a summary value of eaten
foods. It intends to measure adherence to a predefined
(healthy) diet
(5)
. Thus far, several dietary scores have been
related to positive health outcomes
(6–8)
. Dietary scores
have the advantage of taking into account the complex
interactions and cumulative effects of multiple foods and
nutrients within the diet; consequently the health-related
effects may be larger and easier to detect. In addition, the
physiological complexity of chronic diseases implies that
several nutrients modulate them simultaneously. These
simultaneous effects may be captured by dietary scores.
Furthermore, research results obtained from studies utiliz-
ing dietary scores could be transformed to comprehensible
public health messages that benefit the general population,
health practitioners and policy makers
(9)
.
Despite their many advantages, challenges in using
dietary scores have appeared. Rapid expansion and
development of new scores have raised concerns about
the lack of uniform methodological guidelines
(5,10)
. The
selected score components and component cut-offs vary
among studies, which complicates comparing different
dietary scores. Even as the scoring methodology demands
unification, differences among food cultures, food resources
and ecological influences require that the scores are tailored
to fit local diets
(11,12)
.
*Corresponding author: Email noora.kanerva@thl.fi rThe Authors 2013
Although many Nordic foods are considered to have
health benefits, only little is known about the health-
related effects of the Nordic diet in its entirety
(13–17)
.
Furthermore, the Nordic nutrition recommendations
are based on single food- and nutrient-oriented research
and give guidelines regarding these
(18)
. Therefore, the
University of Eastern Finland, the Finnish Heart Associa-
tion and the Finnish Diabetes Association developed
a Baltic Sea Diet Pyramid (Fig. 1) based on a Nordic
multicentre SYSDIET study
(19)
.
The Baltic Sea Diet Pyramid is addressed to the general
healthy population to illustrate healthier dietary choices
based on foods that are typically grown in the Nordic
countries (Fig. 1). The pyramid illustrates relatively the
recommended amount of foods. Foods that are crucial to
health and should be consumed the most are located at
the bottom: Nordic vegetables, roots, cabbages, peas, and
Nordic fruits and berries. Common grains for northern
latitudes (wholegrain rye, oats and barley), which have
high fibre content, are located in the centre of the
pyramid before fish, low-fat or fat-free milk products, and
rapeseed oil. Foods that should be consumed with careful
consideration are located in the top of the pyramid:
processed meat, butter, sweets, chocolate and sweet
bakery products. Milk and sour milk are the only drinks
illustrated in the pyramid, because of their considerable
role in Nordic nutrition as the source of Ca and protein.
Water is generally recommended as a drink when thirsty.
Alcohol intake should be restricted and consumed at most
at a moderate consumption level.
In the present study, we designed a Baltic Sea Diet
Score (BSDS) to indicate adherence to the healthy Nordic
diet and examined whether the BSDS is associated
with nutrient intakes that are considered important in
promoting public health. Because no uniform guidelines
for the creation of dietary scores exist, we also examined
the performance of the BSDS under two different cut-off
strategies.
Materials and methods
The study included individuals aged 25 to 74 years who
participated in two phases of the National FINRISK 2007
Study. In the first phase between January and March 2007,
a random sample of 10 000 people was drawn from the
Finnish population register in five geographical areas
(20)
.
The sample was stratified by sex, 10-year age cohort and
geographical area. Participants were mailed an invitation
letter to participate in a health examination and complete
a self-administered health questionnaire. Of the invited
individuals, 6258 participated in the health examination
(participation rate was 63 %).
To gather specific information on obesity and type 2
diabetes, all participants of the first study phase were
invited to a second one, called the DIetary Lifestyle
and Genetic Determinants of Obesity and Metabolic Syn-
drome (DILGOM) Study, between April and June 2007.
The second phase included a more detailed health exam-
ination including, for example, a glucose tolerance test and
body composition analysis with a bioelectric impedance
scale. Participants filled in more in-depth questionnaires
like the FFQ. In addition, several markers of inflammation
were analysed from the blood samples. Of the invited 6258
men and women, 5024 participated (participation rate was
80 %). After exclusions of plausible under-reporters (n48),
women who were pregnant (n26), participants with
an incomplete FFQ (n74) or missing anthropometric or
background information (n166), the sample comprised
2217 men and 2493 women.
The study was conducted according to the guidelines
laid down in the Declaration of Helsinki and the ethical
guidelines of the National Institute for Health and Welfare.
Written informed consent was obtained from all partici-
pants, and the Ethics Committee of the Hospital District of
Helsinki and Uusimaa approved the study protocol in both
phases.
Diet assessment
Food consumption over the previous 12 months was
assessed using a validated, self-administered, 131-item
FFQ
(21)
updated for the current study
(22)
. Participants
recorded their average consumption of food items and
prepared dishes in nine frequency categories ranging
from ‘never or seldom’ to ‘at least six times a day’. The
participants could also report other frequently consumed
foods not included on the list. The portion size was fixed
for each food item and mixed dish (e.g. glass or slice).
Fig. 1 The Baltic Sea Diet Pyramid (created by the Finnish
Heart Association, the Finnish Diabetes Association and the
University of Eastern Finland)
1698 N Kanerva et al.
The portion sizes were calculated separately for both
sexes based on information from the National FINDIET
Surveys
(23)
. The participants completed the FFQ at the
study site, where a trained study nurse reviewed the
questionnaire. A nutritionist entered the data into the study
database, and the average daily food, nutrient and energy
intakes were calculated using the national food composi-
tion (Fineli
R
) database and in-house software
(24)
.Exclu-
sions were made due to incompletely filled FFQ (n74). In
addition, men and women (n48) were excluded if their
daily energy intake (cut-offs) corresponded to 0?5% at
either end of the daily energy-intake distribution range
(25)
.
Basic macronutrients, like SFA and PUFA (E%), carbo-
hydrates (E%), sucrose (E%), protein (E%), alcohol (E%),
and also fibre were selected for analysis. Vitamin D
was chosen since its intake is known to be too low in
Finland
(26,27)
. Furthermore, folate and Fe were inclu-
ded since the Finnish population, especially women
at childbearing age, have too low intakes. Vitamins A
and C were selected due to their antioxidant properties
that may protect from metabolic disorders which lead to
the development of chronic diseases
(28)
. Na was chosen
because too high an intake level is one major public health
concern causing hypertension
(26)
.
The Baltic Sea Diet Score (BSDS)
The Baltic Sea Diet Pyramid (Fig. 1) served as a template
for the score. The pyramid contains ten food groups:
(i) Nordic vegetables (tomato, cucumber, leafy vegetables,
roots, cabbages, legumes); (ii) Nordic fruits (apples, pears,
and berries); (iii) Nordic wholegrain cereals (rye, oats
and barley); (iv) potatoes; (v) low-fat and fat-free milk
products; (vi) Nordic fish (salmon and freshwater fish);
(vii) rapeseed oil, margarine; (viii) animal fats (butter);
(ix) red and processed meat (beef, pork, processed meat
products and sausage); and (x) sweets. Five of these (fruits,
vegetables, cereals, fish, and red and processed meat)
were included directly to the BSDS (Table 1). Due to
restrictions that our in-house software has set for nutrient
and food intake calculations, the four other components
derived from the pyramid resulted from a compromise.
For example, it was not possible to derive the consumption
of all low-fat and fat-free milk products, so only low-fat
and fat-free milk was used. Furthermore, consumption of
rapeseed oil was impossible to separate from all vegetable
oils. Instead, the ratio of PUFA to SFA1trans-fatty acids
(fat ratio) was used to illustrate fat quality. Also, two
components which are not directly illustrated in the
pyramid, but are generally part of a healthy diet were
included: alcohol consumption as ethanol consumption
and total fat intake, both as percentages of total energy
intake (E%).
Scoring of the components was done using the
proportions illustrated in the pyramid as a guideline. All
components, except alcohol, were scored according to
sex-specific population consumption quartiles (BSDS-Q;
Table 1). To test whether the selection of cut-offs affected
the results, we calculated a second BSDS using sex-specific
population consumption medians (BSDS-M) as cut-offs. In
BSDS-Q points were assigned according to the predictable
health impact of the component. For fruits and berries,
vegetables, cereals, low-fat and fat-free milk, fish and the fat
ratio, the lowest quartile was coded as 0, the second lowest
as 1, the third one as 2 and the highest quartile as 3. For
meat products and total fat, the coding was done vice versa.
Respectively, in BSDS-M, 0 or 1 point was assigned to the
components. For alcohol, the cut-offs were assigned
according to the moderate consumption level recom-
mended in Nordic countries in both BSDS-Q and BSDS-M.
Men consuming 20 g or less and women consuming 10 g or
less of alcohol per day received 1 point; otherwise, 0 points
were given. The resulting BSDS-Q ranged from 0 to 25
points and the BSDS-M from 0 to 9 points, with higher score
values representing greater adherence to the Baltic Sea diet.
Table 1 Baltic Sea Diet Score components and cut-offs for component intakes by gender
BSDS*
Cut-off values
Score component Contents Men Women
Fruits and berries (g/d) Berries, apples, pears 32; 73-
-
; 148 50; 115; 212
Vegetables (g/d) Tomato, cucumber, cabbage, roots, peas, lettuce 138; 216; 324 177; 272; 408
Cereals (g/d) Rye, oats, barley 49; 78; 115 46; 75; 107
Low-fat milk (g/d) Fat-free milk and milk ,2 % fat 38; 215; 538 28; 170; 438
Fish (g/d) Salmon, freshwater fish 26; 43; 61 19; 30; 46
Meat products (g/d) Beef, pork, processed meat products, sausages 217; 154; 105 135; 96; 65
Total fat (E%) Total fat as a percentage of total energy intake 35; 32; 28 34; 30; 27
Fat ratio Ratio of PUFA to SFA1trans-fatty acids 0?38; 0?46; 0?53 0?43; 0?53; 0?74
Alcohol (g/d)-Ethanol 20 10
BSDS, Baltic Sea Diet Score; E%, percentage of total energy intake.
*The BSDS was calculated using the population-based consumption quartiles or medians as cut-offs.
-Because alcohol is generally not recommended to be consumed or consumed only in moderation, it was scored similarly in both cut-off methods: men
consuming 20 g or less and women consuming 10 g or less of alcohol per day received 1 point; otherwise 0 points were given.
-
-
Median cut-off values are the same values as the second quartile cut-off values.
The Baltic Sea Diet Score 1699
Anthropometric measurements and background
variables
At the study sites, specially trained nurses measured weight,
height, waist circumference and hip circumference using
standardized international protocols
(29)
. Height was mea-
suredtothenearest0?1 cm. Body weight was measured to
the nearest 0?1 kg, with all participants wearing light clothing
and no shoes. BMI was calculated as weight in kilograms
divided by the square of height in metres (kg/m
2
).
A self-administered questionnaire assessed participants’
educational level, smoking behaviour and physical activity
during leisure time. Education was measured according
to the total number of school years and divided into
birth-cohort specific tertiles (low, intermediate and high).
Smoking behaviour was placed in four categories: never
smoker, quit $0?5 years ago, quit ,0?5yearsagoand
current smoker. Leisure-time physical activity (PA) con-
sisted of activity outside work and was assessed according
into four categories: (i) inactive (mainly reading, watching
television or other light activities); (ii) moderately active
(walking, cycling, gardening or other activity at least 4 h/
week); (iii) active (brisk running, walking, cross-country
skiing, swimming or other physically demanding activities
at least 3h/week); and (iv) highly active (competition
sports and physically demanding exercises done several
times per week).
Statistical analyses
Data were analysed separately for men and women and
for BSDS-Q and BSDS-M. All analyses were performed with
the R statistical computing program, version 2?13?0
(30)
.
A value of P,0?05 was considered significant. The BSDS
was divided into quintiles, and in each quintile means with
their standard errors or percentages were calculated for
age, education, smoking, PA, BMI and energy intake.
Nutrient intakes were log-transformed in order to satisfy the
normality assumption and subsequently adjusted for each
individual’s energy intake, using the residual method
(31)
.
Next, in each quintile means with their standard errors were
calculated for age- and energy-adjusted nutrient intakes.
Linear regression was used to analyse associations between
the BSDS, a continuous independent variable, and nutrient
intake levels, which were continuous dependent vari-
ables. The differences in mean nutrient intakes among the
BSDS quintiles were analysed by ANOVA and Tukey’s
test. The analyses were controlled for the following
potential confounders: age (in years, continuous); energy
intake (kJ, continuous); education level (categorical: low,
middle, high); smoking (categorical: never smoker, quit
$0?5 years ago, quit ,0?5 years ago, current smoker);
leisure-time PA (categorical: inactive, moderately active,
active, highly active); and BMI (kg/m
2
, continuous).
To take into account possible misreporting of energy
intake, we calculated the ratio of reported energy intake
(EI) to predicted BMR
(32)
, and classified participants
as either under-reporters (EI:BMR #1?14) or plausible
reporters (EI :BMR .1?14)
(33,34)
.Finally,weconrmedour
results by re-running analyses without under-reporters.
Results
Overall, the average age of the participants was 53 years
among men and 52 years among women. Participants in the
highest BSDS quintile tended to be older compared with
participants in the lowest quintile (Table 2). The proportion
of highly educated participants, current smokers and phy-
sically inactive participants was 37 %, 21 % and 18 % in men
and 34%, 15% and 19% in women. The percentage of
highly educated participants was higher, and the percentage
of current smokers and inactive participants was lower, in
the highest BSDS-Q quintile compared with the lowest
quintile. For men, the average BMI was 27?1 kg/m
2
, and
the daily energy intake 11 700 kJ. The respective values
for women were 26?8 kg/m
2
and 9440 kJ. Furthermore,
participants in the highest BSDS quintile had lower BMI
and higher energy intake compared with the others.
The BSDS-Q values ranged between 2 and 25 points for
both men and women (Tables 3 and 4). For men, linear
regression analysis demonstrated a positive association
between the BSDS-Q and lower intakes of alcohol (E%)
and SFA and PUFA (E%), as well as a higher intake of
carbohydrates (E%; P,0?001). Sucrose intake tended to
increase by score quintile, but the trend did not make a
statistical difference. Compared with the lowest quintile
(P,0?001), men in the fifth quintile had 1?6 percentage
units lower alcohol intake and 8?5 percentage units
higher carbohydrate intake. Intake of SFA was 4?9 per-
centage units lower, but on the contrary, the intake of
PUFA was 0?3 percentage units lower in men of the fifth
compared with those in the first BSDS quintile. Women
had similar linear trends for energy-yielding nutrients and
similar differences between the highest and the lowest
quintiles (P,0?001). However, women had no linear
association between BSDS-Q and PUFA intake, and
sucrose intake (E%) was lower in the highest score
quintile of women compared with the lowest quintile
(P50?04). Intakes of fibre, vitamins A, D and C, folate, Fe
and Na had a positive linear association with BSDS-Q in
men and women (P,0?05). Moreover, the intake of these
nutrients was significantly higher in the fifth quintile than
the first quintile (P,0?001).
The BSDS-M values ranged from 0 to 9 points (Tables 3
and 4). The associations between the BSDS-M and nutrient
intakes were generally similar to the ones derived from the
BSDS-Q. However, we tended to detect a greater differ-
ence in nutrient intakes between BSDS quintiles when
using median cut-offs instead of quartile cut-offs. Among
men, protein intake (E%) was significantly higher in the
fifth BSDS-M quintile than in the first quintile (P50?01)
and significant linear associations emerged between
BSDS-M and higher sucrose intake (E %; P50?01), whereas
1700 N Kanerva et al.
no associations emerged when using the BSDS-Q. Among
women, only the BSDS-M was positively associated
with protein (E%) intake (P,0?001). Furthermore, Ca
intake was significantly higher in the fifth BSDS-M quintile
compared with the first one (P,0?001), but no associa-
tions emerged when using the BSDS-Q. Contrarily, the
BSDS-M was not associated significantly with higher Na
intake, but the BSDS-Q was.
Table 2 Selected characteristics of participants by BSDS-Q quintile; men (n2217) and women (n2493) aged 25–74 years, representative of
the Finnish population, DIetary Lifestyle and Genetic Determinants of Obesity and Metabolic Syndrome (DILGOM) Study, April–June 2007
BSDS-Q quintile*
12345
Characteristic Mean SE Mean SE Mean SE Mean SE Mean SE P-
Men
BSDS-Q range 2–9 10–12 13–14 15–16 17–25
n494 540 411 353 419
Age (years) 48?10?651?30?653?90?654?90?758?70?6,0?001
High education (%) 29?136?638?540?542?80?002
Low physical activity (%) 28?722?115?112?89?2,0?001
Current smoker (%) 30?624?817?712?010?0,0?001
BMI (kg/m
2
)27?20?227?50?226?90?227?00?227?00?20?07
Energy intake (kJ/d) 10 350 180 11 270 170 11 950 194 12 630 210 12 820 196 ,0?001
Women
BSDS-Q range 1–9 10–12 13–14 15–17 18–25
n567 609 456 549 397
Age (years) 46?00?649?40?552?40?654?60?558?30?6,0?001
High education (%) 30?735?233?637?237?20?014
Low physical activity (%) 31?019?117?013?910?3,0?001
Current smoker (%) 21?914?412?310?97?5,0?001
BMI (kg/m
2
)27?00?226?80?226?90?226?80?226?50?20?06
Energy intake (kJ/d) 8230 130 9070 124 9370 142 10 310 130 10 500 156 ,0?001
BSDS-Q, Baltic Sea Diet Score calculated using sex-specific population consumption quartiles.
*Values are presented as means with their standard errors except where noted. Values are adjusted for age except when age was used as dependent variable
in the model.
-Linear trend across BSDS quintiles was tested with linear regression for continuous variables and with the x
2
test for binary background variables.
Table 3 Nutrient intakes of participants by Baltic Sea Diet Score; men (n2217) aged 25–74 years, representative of the Finnish population,
DIetary Lifestyle and Genetic Determinants of Obesity and Metabolic Syndrome (DILGOM) Study, April–June 2007
BSDS-Q* BSDS-M*
Q1 Q5 Q1 Q5
Mean SE Mean SE P-,-
-
Py,-
-
Mean SE Mean SE P-,-
-
Py,-
-
n512 396 – – 537 408 – –
BSDS range 2–9 17–25 – – 0–3 7–9 – –
Alcohol (E%) 3?80?22?20?2,0?001 ,0?001 4?20?22?00?2,0?001 ,0?001
SFA (E%) 15?10?110?20?1,0?001 ,0?001 14?90?110?60?3,0?001 ,0?001
PUFA (E%) 6?10?15?80?1,0?001 ,0?001 6?00?15?80?20?001 0?002
Protein (E%) 17?50?118?00?10?003 0?15 17?40?118?00?1,0?001 0?01
Carbohydrates (E%) 43?70?252?20?3,0?001 ,0?001 43?90?252?00?1,0?001 ,0?001
Sucrose (E%) 8?80?29?40?20?05 0?46 8?70?29?50?10?01 0?09
Fibre (g/d) 20?70?336?30?3,0?001 ,0?001 21?40?335?20?3,0?001 ,0?001
Vitamin A (RE) 1080 30 1250 30 ,0?001 ,0?001 1080 30 1230 31 ,0?001 ,0?001
Vitamin D (mg/d) 8?00?211?60?2,0?001 ,0?001 8?20?211?10?2,0?001 ,0?001
Vitamin C (mg/d) 128 3 228 4 ,0?001 ,0?001 128 3 221 4 ,0?001 ,0?001
Folate (mg/d) 335 3 455 4 ,0?001 ,0?001 340 3 443 4 ,0?001 ,0?001
Ca (g/d) 1?2,0?11?5,0?1,0?001 ,0?001 1?2,0?11?5,0?1,0?001 ,0?001
Fe (mg/d) 14?30?117?50?1,0?001 ,0?001 14?30?117?20?1,0?001 ,0?001
Na (g/d) 3?6,0?13?7,0?1,0?01 ,0?01 3?6,0?13
?7,0?10?001 ,0?001
BSDS, Baltic Sea Diet Score; BSDS-Q, Baltic Sea Diet Score calculated using sex-specific population consumption quartiles; BSDS-M, Baltic Sea Diet Score
calculated using sex-specific population consumption medians; Q1, first quartile; Q5, fifth quartile; E%, percentage of total energy intake; RE, retinol
equivalent.
*The first and the fifth quintiles of the BSDS constructed using quartile (BSDS-Q) or median (BSDS-M) cut-offs are presented as means with their standard
errors. Energy-yielding nutrients were adjusted for age; other nutrients were adjusted for age and energy.
-The trends were analysed by linear regression using the BSDS as a continuous exposure variable in the model.
-
-
Adjusted for age, education, leisure-time physical activity, smoking, BMI and energy intake (energy was excluded when testing energy-yielding nutrients).
yThe differences between first and fifth quintiles were analysed by Tukey’s test.
The Baltic Sea Diet Score 1701
Discussion
We created a dietary score to indicate adherence to the
healthy Nordic diet and examined whether it is associ-
ated with nutrients which are considered important in
promoting public health in Finland. Our results from this
cross-sectional study demonstrated that higher BSDS
values were associated with substantial increases in the
intakes of carbohydrates (E%) and fibre, and substantial
decreases in the intakes of SFA (E%) and alcohol (E%).
Furthermore, the BSDS was associated with higher
intakes of food-derived vitamin D, folate and Fe. The
two different cut-off strategies (quartiles v. median) gave
generally similar results, although using the median cut-
offs yielded slightly stronger associations.
The developed BSDS may facilitate research work by
enhancing exploration of associations between the whole
diet and diseases in large epidemiological studies, which
would otherwise be complex
(35)
. Using the score as a
research tool may also prove useful in public health pro-
motion. The results obtained are easily interpretable for
decision makers and authorities who need evidence-based
facts in health policy making
(9)
. For example, the Healthy
Eating Index, based on US nutrition recommendations,
has been successfully used to produce research results
for health policy purposes
(36)
. Furthermore, the Nordic
Council of Ministers and several Nordic health organiza-
tions may utilize the BSDS in their health communication.
They could give a simple diet-level health message instead
of communicating specific recommendations to each
nutrient. A simple message is more likely to transform
into real action than many nutrient-level recommenda-
tions, especially when the message is adapted to the local
food culture and supply
(37,38)
. Besides health policy,
the food industry can effectively direct consumers’ daily
food choices. One way to inform consumers about the
healthiness of a food product is to use a front-of-pack
nutrition icon. In Finland, the most known nutrition icon
is the Heart Symbol
(39)
. Similarly, the Nordic food industry
could exploit the BSDS to indicate the healthiness and
locality of the product. In the future, the BSDS may also
have its place as a part of clinical consulting work of
dietitians and other health professionals.
All nutrients were not associated with the BSDS in the
way we expected. First, the associations between the
BSDS and protein and sucrose intakes were weak or non-
existent. The small variation in protein intake in the Finnish
population may explain the protein finding
(22)
. Similarly,
most individuals get sugars evenly from natural sources,
thus it may not be reasonable to expect that the BSDS
associates with them. From a technical point of view, the
BSDS does not include a specific component that would
illustrate the intake of sugars (e.g. sucrose) and therefore it
may not associate with it. Theoretically, the consumption
of fruits and milk, the two most important natural sources
of sugars in Finland
(23)
, should increase towards higher
BSDS. Thus, individuals in the highest BSDS quintile are
likely to get sucrose mostly from these foods. High intake
Table 4 Nutrient intakes of participants by Baltic Sea Diet Score; women (n2493) aged 25–74 years, representative of the Finnish
population, DIetary Lifestyle and Genetic Determinants of Obesity and Metabolic Syndrome (DILGOM) Study, April–June 2007
BSDS-Q* BSDS-M*
Q1 Q5 Q1 Q5
Mean SE Mean SE P-,-
-
Py,-
-
Mean SE Mean SE P-,-
-
Py,-
-
n517 462 – – 599 213 – –
BSDS range 2–9 17–25 – – 0–3 8–9 – –
Alcohol (E%) 1?50?11?20?10?002 ,0?001 2?10?10?70?1,0?001 ,0?001
SFA (E%) 15?00?19?60?1,0?001 ,0?001 14?50?19?50?2,0?001 ,0?001
PUFA (E%) 5?80?15?80?10?04 –|| 6?00?15?50?1,0?001 ,0?001
Protein (E%) 17?90?117?70?10?08 –|| 17?50?118?00?1,0?001 0?19
Carbohydrates (E%) 46?80?354?30?3,0?001 ,0?001 46?50?255?50?4,0?001 ,0?001
Sucrose (E%) 10?60?210?30?10?54 0?04 10?30?210?40?20?80 –||
Fibre (g/d) 23?50?343?70?3,0?001 ,0?001 25?40?343?50?5,0?001 ,0?001
Vitamin A (RE) 1130 30 1390 30 ,0?001 ,0?001 1160 30 1290 40 ,0?001 0?002
Vitamin D (mg/d) 7?90?29?90?2,0?001 ,0?001 7?40?210?20?3,0?001 ,0?001
Vitamin C (mg/d) 150 4 294 4 ,0?001 ,0?001 162 4 291 7 ,0?001 ,0?001
Folate (mg/d) 346 4 506 4 ,0?001 ,0?001 362 4 499 6 ,0?001 ,0?001
Ca (g/d) 1?6,0?11?5,0?1,0?001 –|| 1?4,0?11?7,0?1,0?001 ,0?001
Fe (mg/d) 14?20?118?40?1,0?001 ,0?001 14?70?118?00?2,0?001 ,0?001
Na (g/d) 3?5,0?13?6,0?10?002 ,0?001 3?5,0?13?5,0?10?06 0?36
BSDS, Baltic Sea Diet Score; BSDS-Q, Baltic Sea Diet Score calculated using sex-specific population consumption quartiles; BSDS-M, Baltic Sea Diet Score
calculated using sex-specific population consumption medians; Q1, first quartile; Q5, fifth quartile; E%, percentage of total energy intake; RE, retinol
equivalent.
*The first and the fifth quintiles of the BSDS constructed using quartile (BSDS-Q) or median (BSDS-M) cut-offs are presented as means with their standard
errors. Energy-yielding nutrients were adjusted for age; other nutrients were adjusted for age and energy.
-The trends were analysed by linear regression using the BSDS as a continuous exposure variable in the model.
-
-
Adjusted for age, education, leisure-time physical activity, smoking, BMI and energy intake (energy was excluded when testing energy-yielding nutrients).
yThe differences between first and fifth quintiles were analysed by Tukey’s test.
||Tukey’s test was not performed since ANOVA indicated non-significant difference between BSDS quintiles.
1702 N Kanerva et al.
of sugars is commonly perceived as unhealthy, because of
its associations with chronic diseases, such as obesity
(40)
.It
is equivocal, however, whether this risk is related to sugars
originating from natural ‘good’ sources (e.g. fruits) or only
to sugars originating from ‘bad’ sources (e.g. added sugar,
sweets, chocolate and soft drinks)
(40)
. Consequently, all
sugar in the diet may not be harmful. Second, the BSDS
was negatively associated with PUFA intake. Adding total
fat intake to the score could cause this result. However, the
fatty acid ratio seemed to stay beneficial as the intake of
SFA had a steeper decrease than that of PUFA. Third, the
BSDS was positively associated with high intake of Na,
although the increase was not substantial. This finding
could be due to high consumption of rye bread and fish in
the fifth BSDS quintile
(41)
. The relationship of the BSDS
and hypertension should be studied to ensure that no
positive association exists.
We also explored if using different cut-off strategies
makes any difference regarding the results, and found
generally a minor effect. The median cut-offs tended to
produce stronger associations than the quartile cut-offs.
This might occur because of larger power due to larger
group size. In addition, that the median cut-off score
performed slightly better may be just a chance finding
since there is no methodology to support one or the other
strategy. In the literature, three strategies have been used
to quantify score components. The Mediterranean diet
scores
(42,43)
use population- and sex-specific median cut-
offs. Dietary scores such as the Diet Quality Index
(44)
use
quantiles in order to get low, intermediate and upper
ranges for cut-off values. The Healthy Eating Index
(36)
uses scoring proportional to the extent to which the
dietary guidelines are met. Researchers might prefer
single cut-off values because they are simpler and easier.
On the other hand, single cut-offs cannot distinguish
among associations of the outcome variables from indi-
viduals with intermediate intake levels from those with
extreme intake levels. Therefore, quartile cut-offs are
better suited for precise examination of the different
impact levels. Various dietary scores have successfully
illustrated a healthy diet regardless of the cut-off method
used, however
(45–47)
.
The strengths of the present study included the large
and representative sample. Despite this, health-conscious
people tend to participate in health surveys more readily,
whichmighthavehadanimpactonourresults.Further-
more, the study’s cross-sectional design limits the conclu-
sions that can be derived. We used a frequently validated
FFQ
(21,22,48)
. The FFQ method has been shown to provide
a valid estimate of diet quality as assessed by dietary
score
(45)
. However, overestimation of healthy and under-
estimation of unhealthy foods’ consumption could have
led to some misclassifications in the BSDS quintiles or
weakened observed associations
(49)
. Our FFQ has been
found to overestimate the consumption of vegetables, long-
chain n-3 fatty acids, carotenoids and vitamin C, and
underestimate alcohol and margarine consumption
(48)
.
Since the FFQ has good ability to rank individuals accord-
ing to relative nutrient intakes, the misreporting may not be
problematic in the present study
(21,22)
. Vitamin and mineral
supplement usage was not taken into account; but this
may not influence the results however, since supplement
users are likely also to have higher vitamin intakes from
foods and thus be classified correctly
(50–52)
. Furthermore,
the FFQ overestimates energy intake compared with diet
records, but the results at the group level were found to
be satisfactory, and all nutrient intake levels were cor-
rected with energy intake, using the residual method
(31)
.
The dietary score has some weaknesses. The selection
of the score components is influenced by a subjective view
to some extent. Methodological problems, such as inflex-
ible nutrient calculation software or scoring based on study
population cut-offs instead of some recommended intake
level cut-offs, could also impact the results.
Conclusion
In conclusion, the novel BSDS provides associations with
various nutrients, such as higher intakes of carbohydrates
(E%), fibre, vitamins and minerals, and lower intakes
of SFA (E%) and alcohol (E%). Some nutrients might
associate poorly with the BSDS, which needs to be taken
into account when interpreting the results. Although the
two cut-off methods did not yield substantially different
results of nutrient intake levels in the Baltic Sea diet, the
median cut-off based method is simpler to use and tends
to have stronger associations with nutrient intake levels.
The BSDS seems to be a valid tool to indicate a healthy
diet and can be utilized to assess diet–disease relation-
ships in public health surveys.
Acknowledgements
Sources of funding: This study was supported by the
Academy of Finland (grant no. 136895 and 263836). The
Academy of Finland had no role in the design, analysis or
writing of this article. Conflicts of interest: The authors
declare no personal or financial conflicts of interest.
Authors’ contributions: N.E.K. and S.M. participated in the
design and conducted the research. N.K., S.M. and U.S.
were responsible for creating the Baltic Sea Diet Score.
S.M. and N.K. were responsible for the original study
idea. N.K. performed the statistical analyses, wrote the
manuscript and had primary responsibility for the final
content. M.L.-K. contributed to manuscript preparation.
All authors have read and approved the final manuscript.
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The Baltic Sea Diet Score 1705
... Dietary quality indices have been developed to assess adherence to desirable diets comprehensively. For example, the Baltic Sea Diet Score (BSDS) has been developed to illustrate a healthy dietary pattern in Nordic countries (10,11) . A higher BSDS has been associated with better periodontal health in adults (12,13) . ...
... Overall diet quality was assessed using BSDS, which is based on foods typically consumed by the general population in the Nordic countries (10) . BSDS was calculated by summing the scores of six components of food consumption and two components of nutrient intake in quartiles of the present population of children, as described earlier (23) . ...
... high-fibre grain products, milk and fish, which are considered protective for dental health (7,9,34,35) , and that diet including these foods tends to restrict the consumption of high-sugar products, such as sweets and ice cream (10) . Although BSDS does not include high-sugar products, a higher BSDS was associated with lower caries experience at baseline and with a decrease in caries experience over 2 years. ...
Article
We examined cross-sectional and longitudinal associations of dietary factors with caries experience in a population sample of 487 children aged 6–9 years at baseline examinations of the Physical Activity and Nutrition in Children (PANIC) Study. Altogether, 406 of these children attended 2-year follow-up examinations. Food consumption and eating frequency were assessed using 4-day food records, diet quality using the Baltic Sea Diet Score (BSDS), and eating behaviour using the Children’s Eating Behavior Questionnaire. Caries experience was examined clinically. The cross-sectional associations of dietary factors with caries experience at baseline were analysed using linear regression and the longitudinal associations of dietary factors with a change in caries experience over follow-up using generalised mixed-effects regression adjusted for other risk factors. Higher consumption of high-fibre grain products (standardised regression coefficient β = -0.16, p = 0.003), milk (β = -0.11, p = 0.025) and higher BSDS (β = -0.15, p = 0.007) were associated with lower caries experience, whereas higher consumption of potatoes (β = 0.11, p = 0.048) and emotional overeating (β = 0.12, p = 0.025) were associated with higher caries experience. Higher snacking frequency (fixed coefficient β = 0.07, p = 0.033), desire to drink (β = 0.10, p = 0.046), slowness in eating (β = 0.12, p = 0.027), and food fussiness (β = 0.12, p = 0.018) were associated with higher caries experience, whereas enjoyment of food (β = -0.12, p = 0.034) and higher BSDS (β = -0.02, p = 0.051) were associated with lower caries experience.
... The most notable difference between Nordic diet pattern and Mediterranean diet score is the source of added fats, which is rapeseed oil or canola oil in Nordic diet, instead of olive oil in Mediterranean diet. HNFI was created by Olsen et al. (18) and includes only 6 foods with the health bene ts of a traditional Nordic diet including whole-grain bread, apples and pears, cabbages, sh, barley, and root vegetables, whereas BSDS was designed to demonstrate adherence to the healthy Nordic diet based on foods commonly cultivated in the Nordic counters and includes fruits and berries, vegetables, low-fat milk, cereals, meat products, alcohol, total fat and fat ratio (19). Although, to date no study has investigated the association between BSDS and HNFI and risk of any type of cataract, but a signi cant negative association between adherence to Nordic dietary pattern and risk of diabetes (20) and abdominal obesity (21), which were previously purported to be potential risk factors for ARC (8, 22), was reported in recent studies. ...
... The BSDS was developed using the techniques described in Kanerva et al. (19) and included the following nine components: 1) fruits and berries (all fruits, berries); 2) vegetables (roots, pulses and vegetables); 3) cereals (whole grains excluding rice and pasta); 4) sh; 5) meat (processed and unprocessed meat); 6) milk (low fat or fat free milk); 7) ratio of PUFAs to the SFAs and trans fatty acids (fat ratio); 8) alcohol (since alcohol is not permissible in Iran, it was excluded from the BSDS); and 9) total fat (total fat as a percentage of total energy). Each component of the BSDS was categorized into quartiles (Q1-Q4) according to the intake of the control group. ...
Full-text available
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Background Age-related cataract (ARC) is a multifactorial and progressive disease that causes blindness globally. Dietary antioxidants like vitamins and carotenoids have been reported to attenuate oxidative stress the main cause of ARC. However, the association between adherence to dietary healthy dietary patterns and ARC has yet to be understood. Since, adherence to Nordic diet style measured by two indices including Healthy Nordic Food Index (HNFI) and Baltic Sea Dietary Score (BSDS) was associated to some chronic diseases, in this study we aimed to investigate the association between HNFI and BSDS and the odds of ARC in a case-control study, in Iran. Methods This hospital-based case-control study was conducted on 98 patients with cataract and 198 healthy controls selected based inclusion criteria. A valid 168-item food frequency questionnaire (FFQ) was used to assess dietary intake over last year. To investigate the association between HNFI and BSDS and risk of ARC, the logistic regression tests was performed. Results Individuals in case and control groups were significantly different in body mass index (BMI), history of diabetes, hypertension and family history of hypertension. The intake of vitamin C, vitamin A and vitamin D showed significant difference between two groups of study. The adherence to BSDS and HNFI were associated with lower risk of ARC in crude and adjusted models. After adjustment for potential cofounders, participants in the highest tertile of HNFI and BSDS (compared to the lowest tertile) had 99.1% and 74% lower ARC risk (OR = 0.09; 95% CI = 0.03–0.22 and OR = 0.26; 95% CI = 0.11–0.58, respectively). Conclusion Our results support previous findings on protective effects of dietary patterns rich in antioxidant on cataract. Adherence to Nordic eating style measured by BSDS and HNFI consist of fruits and root vegetables, whole grain, fish and health fats may reduce risk of ARC.
... The applicability of these dietary patterns to northern European countries is limited by cultural values and preferences and the availability/costs of specific foods [22][23][24]. Nordic dietary patterns, known variably as the Nordic diet [25], New Nordic Diet [26], healthy Nordic diet [27,28] and Baltic Sea diet [29], include foods that are typically consumed as part of traditional Nordic diets and that are consistent with Nordic dietary guidelines [26,30]. These foods include whole-grain cereals (especially rye, oats and barley), berries, other temperate fruits (especially apples and pears), vegetables (especially root and cruciferous vegetables), legumes, fish/shellfish, nuts and canola oil/rapeseed oil (as primary fat sources) and low-fat dairy foods [26,27,29,31]. ...
... Nordic dietary patterns, known variably as the Nordic diet [25], New Nordic Diet [26], healthy Nordic diet [27,28] and Baltic Sea diet [29], include foods that are typically consumed as part of traditional Nordic diets and that are consistent with Nordic dietary guidelines [26,30]. These foods include whole-grain cereals (especially rye, oats and barley), berries, other temperate fruits (especially apples and pears), vegetables (especially root and cruciferous vegetables), legumes, fish/shellfish, nuts and canola oil/rapeseed oil (as primary fat sources) and low-fat dairy foods [26,27,29,31]. The benefits of Nordic dietary patterns have been recognised in major clinical practice guidelines on obesity [32], and diabetes [33][34][35][36]. ...
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Aims/hypothesis Nordic dietary patterns that are high in healthy traditional Nordic foods may have a role in the prevention and management of diabetes. To inform the update of the EASD clinical practice guidelines for nutrition therapy, we conducted a systematic review and meta-analysis of Nordic dietary patterns and cardiometabolic outcomes. Methods We searched MEDLINE, EMBASE and The Cochrane Library from inception to 9 March 2021. We included prospective cohort studies and RCTs with a follow-up of ≥1 year and ≥3 weeks, respectively. Two independent reviewers extracted relevant data and assessed the risk of bias (Newcastle–Ottawa Scale and Cochrane risk of bias tool). The primary outcome was total CVD incidence in the prospective cohort studies and LDL-cholesterol in the RCTs. Secondary outcomes in the prospective cohort studies were CVD mortality, CHD incidence and mortality, stroke incidence and mortality, and type 2 diabetes incidence; in the RCTs, secondary outcomes were other established lipid targets (non-HDL-cholesterol, apolipoprotein B, HDL-cholesterol, triglycerides), markers of glycaemic control (HbA 1c , fasting glucose, fasting insulin), adiposity (body weight, BMI, waist circumference) and inflammation (C-reactive protein), and blood pressure (systolic and diastolic blood pressure). The Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach was used to assess the certainty of the evidence. Results We included 15 unique prospective cohort studies ( n =1,057,176, with 41,708 cardiovascular events and 13,121 diabetes cases) of people with diabetes for the assessment of cardiovascular outcomes or people without diabetes for the assessment of diabetes incidence, and six RCTs ( n =717) in people with one or more risk factor for diabetes. In the prospective cohort studies, higher adherence to Nordic dietary patterns was associated with ‘small important’ reductions in the primary outcome, total CVD incidence (RR for highest vs lowest adherence: 0.93 [95% CI 0.88, 0.99], p =0.01; substantial heterogeneity: I ² =88%, p Q <0.001), and similar or greater reductions in the secondary outcomes of CVD mortality and incidence of CHD, stroke and type 2 diabetes ( p <0.05). Inverse dose–response gradients were seen for total CVD incidence, CVD mortality and incidence of CHD, stroke and type 2 diabetes ( p< 0.05). No studies assessed CHD or stroke mortality. In the RCTs, there were small important reductions in LDL-cholesterol (mean difference [MD] −0.26 mmol/l [95% CI −0.52, −0.00], p MD =0.05; substantial heterogeneity: I ² =89%, p Q <0.01), and ‘small important’ or greater reductions in the secondary outcomes of non-HDL-cholesterol, apolipoprotein B, insulin, body weight, BMI and systolic blood pressure ( p< 0.05). For the other outcomes there were ‘trivial’ reductions or no effect. The certainty of the evidence was low for total CVD incidence and LDL-cholesterol; moderate to high for CVD mortality, established lipid targets, adiposity markers, glycaemic control, blood pressure and inflammation; and low for all other outcomes, with evidence being downgraded mainly because of imprecision and inconsistency. Conclusions/interpretation Adherence to Nordic dietary patterns is associated with generally small important reductions in the risk of major CVD outcomes and diabetes, which are supported by similar reductions in LDL-cholesterol and other intermediate cardiometabolic risk factors. The available evidence provides a generally good indication of the likely benefits of Nordic dietary patterns in people with or at risk for diabetes. Registration ClinicalTrials.gov NCT04094194. Funding Diabetes and Nutrition Study Group of the EASD Clinical Practice. Graphical abstract
... described as dietary patterns with emphasis on foods that have traditionally been used and cultivated in the Nordic region, such as fish, wholegrains like rye and oats, root vegetables, cabbages, fruits like apples and pears, rapeseed oil and, to a varying degree, including low-fat dairy products [1,2]. ...
... We have considered consumption of five traditional Nordic food groups as exposure of interest, selected to reflect components of a healthy Nordic diet [1,2]; Nordic fruits and vegetables (apples/pears, broccoli/cauliflower, cabbage, carrots, swede); fatty fish classified as fish with ≥ 4% fat in the meat (salmon, trout, herring, mackerel); lean fish containing < 4% fat in the meat (cod, haddock, plaice) excluding products like fish cakes, fish balls, fish spread and stew; wholegrain products (wholegrain bread and breakfast cereals); low-fat dairy products (skimmed-and semi-skimmed milk, and yoghurt). We analysed lean and fatty fish separately because they are specified in our dietary guidelines as sources of specific essential nutrients such as vitamin D and omega-3 fatty acids from fatty fish, and iodine from lean fish [21]. ...
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Background The shape of the associations between intake of foods basic in a healthy Nordic diet and long-term health is not well known. Therefore, we have examined all-cause mortality in a large, prospective cohort of women in Norway in relation to intake of: Nordic fruits and vegetables, fatty fish, lean fish, wholegrain products, and low-fat dairy products. Methods A total of 83 669 women who completed a food frequency questionnaire between 1996 and 2004 were followed up for mortality until the end of 2018. Cox proportional hazards regression models were used to examine the associations between consumption of the Nordic food groups and all-cause mortality. The Nordic food groups were examined as categorical exposures, and all but wholegrain products also as continuous exposures in restricted cubic spline models. Results A total of 8 507 women died during the 20-year follow-up period. Nordic fruits and vegetables, fatty fish and low-fat dairy products were observed to be non-linearly associated with all-cause mortality, while higher intake of lean fish and wholegrain products reduced all-cause mortality. Intake levels and hazard ratios (HR) and 95% confidence intervals (CI) associated with lowest mortality were approximately 200 g/day of Nordic fruits and vegetables (HR 0.83 (95% CI: 0.77–0.91)), 10–20 g/day of fatty fish (10 g/day: HR 0.98 (95% CI: 0.94–1.02)) and 200 g/day of low-fat dairy products (HR 0.96 (95% CI: 0.81–1.01)) compared to no consumption. Consumption of fatty fish ≥ 60 g/day compared to no intake statistically significantly increased the mortality (60 g/day: HR 1.08 (95% CI: 1.01–1.16)), as did consumption of low-fat dairy products ≥ 800 g/day compared to no intake (800 g/day: HR 1.10 (95% CI: 1.02–1.20)). After stratification by smoking status, the observed association between Nordic fruits and vegetables and all-cause mortality was stronger in ever smokers. Conclusion The associations between intake of foods basic in healthy Nordic diets and all-cause mortality may be non-linear. Therefore, assumptions of linear associations between traditional Nordic food groups and health outcomes could lead to wrong conclusions in analyses of healthy Nordic diets.
... The cumulative average of each participant's dietary intake was used to assess the relationship between the Nordic diet and the CVD incidents. The Nordic diet score was calculated using a formerly published method by Kanerva et al. (22). The Nordic diet comprises nine components, including fruit and berries, vegetables, cereals, low-fat milk, sh, meat products, alcohol, total fat, and fat ratio. ...
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Background Although both observational and interventional studies have demonstrated the beneficial effects of the Nordic diet on cardiovascular disease (CVD) risk factors, the association between adherence to this diet and CVD incidents is unknown. Therefore, in the present study, we aimed to investigate the association between adherence to the Nordic diet and the risk of CVD events in non-Nordic adults. Methods In the present cohort study, 2918 participants from the third wave of the Tehran Lipid and Glucose Study (TLGS) were included. All the participants who were free of CVD at baseline were followed up for 10.6 years. The Nordic diet score was assessed by applying a validated food frequency questionnaire (FFQ). Patients’ medical records were used to evaluate cardiovascular events, including coronary heart disease (CHD), stroke, and CVD-related mortality. Results During a median follow-up of 10.6 years, 203 subjects experienced cardiovascular events. Participants in the third and fourth quartiles of the Nordic diet had a 46% (HR: 0.64; 95% CI: 0.44, 0.93) and 58% (HR: 0.48; 95% CI: 0.28 to 0.62) lower risk of CVD than those in the lowest quartile. Among components of the Nordic diet, each score increase in cereals was associated with a 24% (HR: 0.76; 95% CI: 0.67 to 0.87), low-fat milk with a 23% (HR: 0.77; 95% CI: 0.68 to 0.87), and fish with a 22% (HR: 0.78; 95% CI: 0.69 to 0.89) lower risk of CVD. Conclusion We found high adherence to the Nordic diet might be beneficial in the prevention of cardiovascular events in the non-Nordic community. The main components of the Nordic diet that indicated an inverse relationship with CVD were cereals, fish, and low-fat milk.
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