Content uploaded by Elske M Brouwer-Brolsma
Author content
All content in this area was uploaded by Elske M Brouwer-Brolsma on Sep 29, 2020
Content may be subject to copyright.
Dairy product consumption is associated with pre-diabetes and newly
diagnosed type 2 diabetes in the Lifelines Cohort Study
Elske M. Brouwer-Brolsma
1
*, Diewertje Sluik
1
, Cecile M. Singh-Povel
2
and Edith J. M. Feskens
1
1
Division of Human Nutrition, Wageningen University, 6700 AA Wageningen, The Netherlands
2
FrieslandCampina, 3800 BN Amersfoort, The Netherlands
(Submitted 7 June 2017 –Final revision received 26 October 2017 –Accepted 11 December 2017)
Abstract
Previous studies show associations between dairy product consumption and type 2 diabetes, but only a few studies conducted detailed
analyses for a variety of dairy subgroups. Therefore, we examined cross-sectional associations of a broad variety of dairy subgroups with pre-
diabetes and newly diagnosed type 2 diabetes (ND-T2DM) among Dutch adults. In total, 112 086 adults without diabetes completed a semi-
quantitative FFQ and donated blood. Pre-diabetes was defined as fasting plasma glucose (FPG) between 5·6 and 6·9 mmol/l or HbA1c% of
5·7–6·4 %. ND-T2DM was defined as FPG ≥7·0 mmol/l or HbA1c ≥6·5 %. Logistic regression analyses were conducted by 100 g or serving
increase and dairy tertiles (T1
ref
), while adjusting for demographic, lifestyle and dietary covariates. Median dairy product intake was 324
(interquartile range 227) g/d; 25 549 (23 %) participants had pre-diabetes; and 1305 (1 %) had ND-T2DM. After full adjustment, inverse
associations were observed of skimmed dairy (OR
100 g
0·98; 95 % CI 0·97, 1·00), fermented dairy (OR
100 g
0·98; 95 % CI 0·97, 0·99) and
buttermilk (OR
150 g
0·97; 95 % CI 0·94, 1·00) with pre-diabetes. Positive associations were observed for full-fat dairy (OR
100 g
1·003; 95 % CI
1·01, 1·06), non-fermented dairy products (OR
100 g
1·01; 95 % CI 1·00, 1·02) and custard (OR
serving/150 g
1·13; 95 % CI 1·03, 1·24) with pre-
diabetes. Moreover, full-fat dairy products (OR
T3
1·16; 95 % CI 0·99, 1·35), non-fermented dairy products (OR
100 g
1·05; 95 % CI 1·01, 1·09) and
milk (OR
serving/150 g
1·08; 95 % CI 1·02, 1·15) were positively associated with ND-T2DM. In conclusion, our data showed inverse associations of
skimmed and fermented dairy products with pre-diabetes. Positive associations were observed for full-fat and non-fermented dairy products
with pre-diabetes and ND-T2DM.
Key words: Diabetes: Glucose: Dairy products: Fermentation: Cohorts
The number of people with one or more chronic diseases,
including type 2 diabetes (T2DM), is rising and lifestyle factors
seem to play an important role in this development. Scientific
literature suggests that dairy product intake may affect glucose
tolerance and hence the development of T2DM.
Mechanistically, beneficial effects of dairy product con-
sumption in the prevention of glucose intolerance and T2DM
may be explained by the presence of calcium and protein and
their favourable influence on energy balance and body weight
maintenance
(1)
. Beneficial links have also been observed
between whey protein and the regulation of particular satiety-
related hormones, lipid metabolism and insulin secretion
(2,3)
.In
addition, possible metabolic effects of dairy products have been
proposed for Mg (e.g. by promoting insulin sensitivity)
(4)
,
conjugated linoleic acid (e.g. body weight regulation)
(5)
and
lactic acid bacteria present in fermented products (e.g. gut
microbiota and satiety)
(6–8)
. Conversely, unfavourable meta-
bolic effects may occur following the consumption of dairy
products with a relatively high energy density, such as full-fat
dairy products, for instance via raising blood LDL-cholesterol
concentrations
(9)
. Moreover, given the suggested impact of
sugar-sweetened beverages on the development of T2DM
(10)
,
also adverse effects may result from the consumption of sugar-
sweetened dairy products. Given these potential favourable, as
well as less favourable, pathways of various dairy product
nutrients, it is challenging to value the actual health impact of
dairy product consumption as a whole; the different nutrients
may strengthen but also weaken each other’s effects.
As a result, several observational studies
(7,11–28)
and meta-
analyses
(29)
investigated associations between dairy product
intake and incident T2DM. Chen et al.
(11)
conducted a meta-
analysis of prospective cohort studies and concluded that there
is no convincing evidence for an association between total dairy
product consumption and incidence of T2DM (n14, relative
risk (RR) per one serving of dairy products: 0·98; 95 % CI 0·96,
1·01)
(11)
. In contrast, a meta-analysis by Aune et al.
(30)
did
suggest a link between total dairy product intake and incident
T2DM (n12, RR/400 g 0·93; 95 % CI 0·87, 0·99). Despite the null
Abbreviations: FPG, fasting plasma glucose; ND-T2DM, newly diagnosed type 2 diabetes; T2DM, type 2 diabetes.
*Corresponding author: E. M. Brouwer-Brolsma, fax +31 317 484987, email elske.brouwer-brolsma@wur.nl
British Journal of Nutrition (2018), 119, 442–455 doi:10.1017/S0007114517003762
© The Authors 2018
Downloaded from https://www.cambridge.org/core. IP address: 147.78.122.3, on 27 Sep 2020 at 18:06:45, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0007114517003762
findings for total dairy product resulting from the meta-analysis
by Chen et al., subgroup analyses did show a significant inverse
association between yoghurt consumption and T2DM
(11)
. This
illustrates that analyses of specific dairy product subgroups,
rather than total dairy products, may improve the understanding
of potential effects of the dairy product matrix. Hence, the
research field is now evolving to more detailed analyses
including different dairy product subgroups as for instance
shown by the recent meta-analysis of Gijsbers et al.
(31)
and
systematic review of meta-analyses by Drouin-Chartier et al.
(29)
.
This last mentioned research group concluded their work by
stating that current epidemiologic evidence largely points
towards neutral or beneficial associations between dairy
product intake and incident T2DM, but that recommendations
to consume low-fat dairy products instead of full-fat products
are currently insufficiently supported
(29)
.
As original studies with analyses on the dairy product sub-
group level are still scarce
(31)
, we explored associations of dairy
product intake with pre-diabetes and newly diagnosed T2DM
(ND-T2DM) prevalence –defined using the aetiological mar-
kers fasting plasma glucose (FPG) and HbA1c% –in a uniquely
large population of Dutch adults by subdividing total dairy
product intake into a broad variety of dairy product subclasses,
including skimmed dairy products, semi-skimmed dairy pro-
ducts, full-fat dairy products, non-fermented dairy products,
fermented dairy products, total milk, skimmed milk, semi-
skimmed milk, full-fat milk, total yogurt, skimmed yogurt, full-
fat yogurt, buttermilk, curd cheese/quark, custard, flavoured
yogurt drinks, total cheese, low-fat cheese and regular-fat
cheese. We also studied potential effect modification of dairy
product intake with age, sex and BMI, and mediation effects by
markers of lipid metabolism.
Methods
Participants
This cross-sectional study was performed using data of the
Lifelines Cohort Study. Lifelines is a multi-disciplinary pro-
spective population-based cohort study examining in a unique
three-generation design the health and health-related beha-
viours of 167 729 persons living in the North of the Netherlands.
It uses a broad range of investigative procedures in assessing
the biomedical, socio-demographic, behavioural, physical and
psychological factors that contribute to the health and disease of
the general population, with a special focus on multi-morbidity
and complex genetics
(32)
. Between 2006 and 2013, inhabitants
of the three Northern provinces of The Netherlands (Friesland,
Groningen and Drenthe) and their families were invited for
participation in the study, with the goal to create a three-
generation design. The first group of participants, aged 25–50
years old, was recruited through their general practitioner.
Exclusion criteria included having a severe psychiatric or phy-
sical illness, limited life expectancy (<5 years) and insufficient
knowledge of the Dutch language to complete a Dutch ques-
tionnaire. When a participant was considered to be eligible to
the study, he or she received a baseline questionnaire and was
invited to the Lifelines research site for a comprehensive health
assessment. During the visit at the research centre, participants
were also asked to indicate whether family members would be
willing to participate in the study; in case of a positive response,
family members were invited as well. In addition to this recruit-
ment strategy, inhabitants of the northern part of The Nether-
lands could also register themselves via the Lifelines website.
A more detailed description of the Lifelines study can be found in
the article on the cohort description
(32)
. All participants gave
written informed consent. The Lifelines study is conducted
according to the principles of the Declaration of Helsinki and
in accordance with the research code of the University Medical
Centre Groningen. The Lifelines study is approved by the
medical ethical committee of the UMCG, the Netherlands.
Population for analyses
In total, 144 095 out of 167 729 participants completed a baseline
FFQ. Participants with unreliable dietary data (n29 413) –that is
menwithenergyintakes<3347 kJ or >17 573 kJ and women with
energy intakes <2092 kJ or >14 644 kJ –and/or FFQ judged as
unreliable by the research dieticians, for example owing to nutrient
or food group reports below the possible under or upper limit, or
reporting to have diabetes (n2596) were excluded from the ana-
lyses. Finally, 112 086 participants were included in our analyses.
Dietary assessment
Dietary intake was assessed by the ‘flower FFQ’, which has
been developed as an alternative for the regular –often time-
consuming –FFQ. The name ‘flower FFQ’has been derived
from its design, consisting of one main questionnaire on energy
and macronutrient intake (heart), and four complementary food
questionnaires (petals) on micronutrients and eating behaviour,
with overlapping questions to provide information on covar-
iance. For the current analyses, only data of the flower heart
were available, which comprised 110 food items, including all
major food groups such as dairy products (further specified in
Table 1), bread, pasta, rice, potatoes, fruit, vegetables, legumes,
meat, fish, coffee, tea and soda/juice. Portion sizes were esti-
mated using natural portions and commonly used household
measures
(33)
. FFQ data were converted into total intakes of
energy and nutrients by means of the Dutch Food Composition
table 2011 (NEVO)
(34)
. A more detailed description of the
Flower FFQ can be found elsewhere
(35)
. Before entering the
dietary variables in the statistical models, they were all adjusted
for energy intake by means of the residual method
(36)
. The
questionnaire also included an item about whether or not
participants were on a weight loss diet at the time of the dietary
assessment. Currently, researchers are working on the valida-
tion of the ‘flower FFQ’.
Markers of glucose homoeostasis
Fasting blood samples were collected at baseline, processed on
the day of collection and either directly analysed or stored at
−80°C in a fully automated storage facility. FPG was determined
in venous plasma by means of the Roche glucose assay
(hexokinase/glucose-6-phosphate dehydrogenase enzymatic
Dairy products and type 2 diabetes 443
Downloaded from https://www.cambridge.org/core. IP address: 147.78.122.3, on 27 Sep 2020 at 18:06:45, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0007114517003762
reactions) and the Modular P analyser (Roche Diagnostics).
HbA1c was determined in whole blood (EDTA-anticoagulated)
by means of turbidimetric inhibition immunoassay on a Cobas
Integra 800 CTS analyser (Roche Diagnostics Netherland BV),
which has been shown to have a coefficient of variation of 2·1%
for a mean HbA1c of 5·5 %, and 1·9 % for a mean HbA1c of
10·6%
(37)
. Subsequently, pre-diabetes was defined as having a
FPG between 5·6 and 6·9 mmol/l or an HbA1c of 5·7–6·4%
(38)
.
ND-T2DM was defined as having a FPG ≥7·0 mmol/L or HbA1c
≥6·5%
(38)
.
Non-dietary covariates
Baseline data on demographic factors, education level (primary,
secondary, higher or other education), current and past active
smoking behaviour, physical activity (SQUASH)
(39)
, ethanol
consumption (none, 1–9, 10–19, ≥20 g/d), history and pre-
valence of diseases (i.e. hypertension and hypercholester-
olaemia) and family history of diseases were collected by
means of questionnaires. Weight was measured to the nearest
0·1 kg, without shoes and heavy clothing, using a calibrated
SECA 761 scale. Height was measured to the nearest 0·1 cm,
without shoes, using a calibrated SECA222 stadiometer. BMI
was calculated as weight/height squared (kg/m
2
). Waist cir-
cumference was measured twice, to the nearest 0·1 cm, midway
between the lowest rib and the top of the iliac crest at the end of
gentle expiration, using SECA 200 measuring tape. The mean of
the two measurements was used in the analyses
(40)
. Total
cholesterol (TC) and HDL-C were assessed in serum using an
enzymatic colorimetric method. LDL-C was determined in
serum with a colorimetric method. Serum TAG concentrations
were measured with a colorimetric UV method. All these
cholesterol measurements were done on a Roche Modular P
chemistry analyser (Roche)
(41)
.
Statistical analyses
Participant characteristics are reported as mean values and stand-
ard deviations, numbers and percentages. Medians and inter-
quartile ranges (IQR) were used to report skewed variables.
Differences over tertiles of total dairy product intake were tested
by means of χ
2
tests in case of categorical variables, one-way
ANOVA in case of normally distributed continuous variables and
Kruskal–Wallis test in case of skewed continuous variables.
Logistic regression analysis was conducted to calculate OR for
pre-diabetes and ND-T2DM per dairy product intake tertile, using
the lowest tertile as the reference group. OR per 100 g/d or
serving increase in dairy product intake were calculated as well.
Models were adjusted for age (years), sex (model 1), model
1+alcohol (0, 1–9, 10–19, ≥20g/d), smoking (never, former,
current), education (primary, secondary, higher, other), physical
activity (number of days/week of at least moderate intensity
physical activity) (model 2), model 2+ total energy intake (kJ/d),
intake of energy adjusted bread, pasta, rice, potato, fruit, vege-
tables, legumes, meat, fish, coffee, tea, soda/juice, other dairy
product groups (g/d) (model 3), model 3 + BMI (kg/m
2
) and waist
circumference (cm) (model 4). Potential mediation by markers of
lipid metabolism was examined by adding TC, HDL-cC, LDL-C
and TAG to model 4 (model 5). The P
for trend
across medians of
dairy product intake tertiles was calculated to study potential
dose–response associations of dairy product intake with prevalent
pre-diabetes and ND-T2DM. Possible interactions between dairy
product intake and age, sex and BMI in association with FPG and
HbA1c were tested through the inclusion of a cross-product term
Table 1. Dairy product group classification
Dairy product groups Included dairy products*
Total dairy products All dairy products, except butter
Skimmed dairy products All types of skimmed milk (0·1 g fat, 4%) and yogurt (0·2 g fat, 27%), buttermilk (0·2 g fat, 24%) and
flavoured yogurt drinks (0·2 g fat, 45%)
Semi-skimmed dairy products All types of semi-skimmed milk (1·5 g fat, 74%) and low-fat cheese (15g fat, 26 %)
Full-fat dairy products All types of full-fat milk (3·5 g fat, 23 %) and yogurt (2·9 g fat, 7 %), regular-fat cheese (≥24 g fat, 43 %),
cream (35 g fat, 3 %), milk-based ice cream (12 g fat, 12 %), chocolate milk (1·9 g fat, 12 %)
Fermented dairy products All types of yogurt (22 %), curd cheese/quark (10 %), buttermilk (15 %), cheese (34 %) and flavoured
yogurt dr inks (19 %)
Non-fermented dairy products All types of milk (73 %), custard (9 %), porridge (3 %), milk-based ice cream (11 %) and cream (4 %).
Milk All types of milk, including plain milk (63 %), coffee milk (25 %) and chocolate milk (12 %).
Skimmed milk All types of skimmed milk (0·1 g fat)
Semi-skimmed milk All types of semi-skimmed milk (1·5 g fat)
Full-fat milk All types of full-fat milk (3·5g fat)
Yogurt All types of yogurt
Skimmed yogurt All types of skimmed yogurt (0·2 g fat)
Full-fat yogurt All types of full-fat yogurt (2·9g fat)
Buttermilk All types of buttermilk
Curd cheese/quark All types of curd cheese/quark
Flavoured yogurt drinks All types of flavoured yogurt drinks
Custard All types of custard
Cheese All types of cheese, including Dutch cheeses (soft and hard cheeses) (68 %) and other cheeses
(i.e. cream cheese, foreign cheeses, cheese snack) (32 %)
Low-fat cheese All types of low-fat cheese (15 g fat)
Regular-fat cheese All types of regular-fat cheese (≥24 g fat)
Dutch cheese All types of Dutch (yellow) cheeses
* The first number following the dairy product in the second column indicates the fat quantity (g) per 100 g; the percentage (%) refers to the contribution of that specific dairy product
to that category.
444 E. M. Brouwer-Brolsma et al.
Downloaded from https://www.cambridge.org/core. IP address: 147.78.122.3, on 27 Sep 2020 at 18:06:45, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0007114517003762
in linear models and visualised through stratified analyses. A two-
sided Pvalue ≤0·05 was considered to be statistically significant
for all analyses. Analyses were performed using the statistical
package SPSS, version 22 (IBM SPSS Inc.).
Results
The characteristics of the population are described in Table 2.
Comparison of the top and bottom tertile of total dairy product
intakeshowsthatparticipantsinthetoptertileweremorelikelyto
be older, women, former smokers, overweight, to be diagnosed
with hypertension and hypercholesterolaemia and to have a higher
intake of fruits. Analyses on the key variables in this study showed
that 25 549 (23 %) participants had pre-diabetes and 1305 (1 %) had
ND-T2DM. Median dairy product intake of the total population was
324 (IQR 227) g/d. Participants consumed more semi-skimmed
dairy products than skimmed or full-fat products, and higher
quantities of non-fermented dairy products than fermented dairy
products. On the product level, milk was the largest contributor to
the total sum of dairy products –that is 98 (IQR 170) g/d.
Table 2. Baseline characteristics according to tertiles (T) of total dairy product intake of 112 086 participants without self-reported diabetes
(Mean values and standard deviations; medians and interquartile ranges (IQR); numbers and percentages)
Tertiles of total dairy product intake
Total T1 (n34 716) T2 (n39 063) T3 (n38 307)
nMedian IQR Median IQR Median IQR Median IQR P*
Range in total dair y product intake (g/d) 11 2086 324 227 <245 245–394 ≥395
Age (years) 11 2086 <0·0001
Mean 45 42 45 46
SD 13 12 13 13
Men 11 2086 <0·0001
n46 063 16 979 14 955 14 129
% 41493837
Smoking 11 1828 <0·0001
Never
n35 672 10 579 12 771 12 322
% 32303332
Former
n52 974 14 782 18 558 19 634
% 47434751
Current
n23 182 9257 7652 6273
% 21272016
BMI (kg/m
2
) 11 2065 <0·0001
Mean 25·625·525·625·8
SD 4·04·13·94·0
Education 11 1649 <0·0001
Primary
n2405 735 840 830
% 2222
Secondary
n63 023 19 075 21 790 22 158
% 56555658
Higher
n44 150 14 236 15 572 14 342
% 40414038
Other
n2071 560 703 808
% 2222
Moderate-intensity physical activity (d/week) 104152 5 6 5 6 5 7 5 7 <0·0001
Hypertension 11 1926 <0·0001
n22 868 6263 8194 8411
% 20182122
Hypercholesterolaemia 111 924 <0·0001
n13 682 3873 4912 4897
% 12111313
Alcohol intake 112 086 <0·0001
0g/d
n2448 731 735 982
% 2223
1–9g/d
n79 231 21 879 28 170 29 182
% 71637276
10–19 g/d
n21 834 7945 7672 6217
% 19232016
Dairy products and type 2 diabetes 445
Downloaded from https://www.cambridge.org/core. IP address: 147.78.122.3, on 27 Sep 2020 at 18:06:45, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0007114517003762
Table 2. Continued
Tertiles of total dairy product intake
Total T1 (n34 716) T2 (n39 063) T3 (n38 307)
nMedian IQR Median IQR Median IQR Median IQR P*
≥20 g/d
n8573 4161 2486 1926
%81265
Pre-diabetes 110 781 <0·0001
n25 549 7167 9041 9341
% 23212325
Newly diagnosed type 2 diabetes 112 086 <0·0001
n1305 364 444 497
% 1111
Fasting plasma glucose (mmol/l) 109 343 4·93 0·61 4·90·59 4·90·62 4·90·62 0·75
HbA1c, % (mmol/mol) 110 877 37 36 37 37 0·004
Mean 5·52 5·49 5·52 5·54
SD 0·36 0·35 0·36 0·37
Creatinine (μmol/l) 111 550 <0·0001
Mean 73·474·173·272·9
SD 13·213·213·313·0
Total cholesterol (mmol/l) 111549 0·01
Mean 5·10 5·07 5·11 5·11
SD 0·40 1·01 1·01 0·99
LDL-cholesterol 111 541 <0·0001
Mean 3·24 3·22 3·24 3·25
SD 0·92 0·93 0·92 0·90
HDL-cholesterol (mmol/l) 111 549 0·07
Mean 1·51 1·48 1·52 1·52
SD 0·40 0·39 0·40 0·40
TAG (mmol/l) 111 549 0·96 0·66 0·97 0·69 0·95 0·65 0·95 0·64 <0·0001
Energy intake (kJ/d) 112 086 <0·0001
Mean 8985 9276 8655 9057
SD 2304 2432 2151 2293
Total fat (En%) 112 086 <0·0001
Mean 36 36 36 35
SD 5555
Protein (En%) 112 086 <0·0001
Mean 15 14 15 16
SD 2222
Carbohydrates (En%) 112 086 <0·0001
Mean 45 45 45 45
SD 5655
Skimmed dairy products (g/d) 112086 54 129 16 48 63 112 129 200 <0·0001
Semi-skimmed dairy products (g/d) 112 086 50 125 21 44 59 103 146 240 <0·0001
Full-fat dairy products (g/d) 112 086 59 58 49 46 63 57 67 74 <0·0001
Fermented dairy products (g/d) 112 086 121 139 69 70 134 111 202 204 <0·0001
Non-fermented dairy products (g/d) 112 086 126 168 59 71 137 115 263 210 <0·0001
Total milk (g/d) 112 086 103 160 43 63 112 112 237 207 <0·0001
Total yogurt (g/d) 112 086 17 54 0 27 23 56 34 70 <0·0001
Buttermilk (g/d) 112 086 1 35 1 2 1 34 2 119 <0·0001
Curd cheese (g/d) 112 086 1 23 1 13 1 24 1 28 <0·0001
Custard (g/d) 112 086 3 14 2 9 4 16 4 21 <0·0001
Flavoured yogurt drinks (g/d) 112 086 8 33 5 17 9 40 9 65 <0·0001
Total cheese (g/d) 112 086 26 28 23 27 27 27 27 29 <0·0001
Fruits (g/d) 112 086 111 174 87 177 111 172 149 147 <0·0001
Vegetables (g/d) 112 086 107 74 103 78 108 53 108 74 <0·0001
Legumes (g/d) 112 086 13 27 13 28 14 25 14 26 <0·0001
Bread (g/d) 112 086 142 62 147 70 143 57 136 58 <0·0001
Meat (g/d) 112 086 80 42 81 45 81 41 78 42 <0·0001
Pasta (g/d) 112086 21 19 21 22 21 19 19 17 <0·0001
Rice (g/d) 112 086 17 19 18 23 17 18 16 18 <0·0001
Potatoes (g/d) 112 086 90 61 87 66 92 59 90 59 <0·0001
Fish (g/d) 112 086 10 12 10 13 10 12 10 12 0·02
Coffee (g/d) 112086 421 358 396 419 428 343 435 336 <0·0001
Tea (g/d) 112 086 198 304 178 311 201 296 205 303 <0·0001
Soda/fruit juice (g/d) 112086 101 161 119 202 102 147 89 139 <0·0001
Current weight loss die 111 419 <0·0001
n4950 1132 1804 2014
% 4355
* Differences across quintiles are investigated using ANOVA in case of normally distributed continuous variables, Kruskal–Wallis test in case of skewed continuous variables and
χ
2
tests in case of categorical variables.
446 E. M. Brouwer-Brolsma et al.
Downloaded from https://www.cambridge.org/core. IP address: 147.78.122.3, on 27 Sep 2020 at 18:06:45, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0007114517003762
Pre-diabetes
After full adjustment (model 4), significant inverse associations
were observed of skimmed (OR per 100 g (OR
100 g
)0·98; 95 %
CI 0·97, 1·00; P=0·02 and OR of the third tertile (OR
T3
)0·95;
95 % CI 0·92, 0·99; P=0·02) and fermented dairy product intake
(OR
100 g
0·98; 95 % CI 0·97, 0·99; P=0·004 and OR
T3
0·94; 95 %
CI 0·90, 0·98; P=0·004) with pre-diabetes, showing a 2 % lower
odds of pre-diabetes with each 100-g increase in dairy product
intake for both dairy product subclasses. Positive associations
were observed for full-fat (OR
100 g
1·03; 95 % CI 1·01, 1·06;
P=0·004 and OR
T3
1·10; 95 % CI 1·06, 1·15; P<0·0001) and
non-fermented dairy products (OR
100 g
1·01; 95 % CI 1·00, 1·02;
P=0·30 and OR
T3
1·05; 95 % CI 1·00, 1·09 P=0·03) with pre-
diabetes. On the product level, a significant inverse association
was observed between buttermilk (OR
serving/150 g
0·97; 95 % CI
0·94, 1·00; P=0·04 and OR
T3
0·99; 95 % CI 0·95, 1·04; P=0·68)
and pre-diabetes, whereas a positive association was observed
for custard with pre-diabetes (OR
serving/150 g
1·13; 95 % CI 1·03,
1·24; P=0·01 and OR
T3
1·05; 95 % CI 1·01, 1·10; P=0·02)
(Table 3). No associations were observed for the intake of total
dairy products, semi-skimmed dairy products, milk, yogurt,
curd cheese, yogurt drinks or cheese with pre-diabetes. How-
ever, more specific analyses for milk, yogurt and cheese that
were further subdivided based on fat content did show positive
associations for full-fat milk (OR
serving/150 g
1·03; 95 % CI 0·99,
1·08; P=0·19 and OR
T3
1·07; 95 % CI 1·02, 1·11; P=0·002) and
full-fat yogurt (OR
serving/150 g
1·09; 95 % CI 0·99, 1·19; P=0·08
and OR
T3
1·07; 95 % CI 1·02, 1·12; P=0·007), whereas an
inverse association was observed for low-fat cheese (OR
serving/20 g
0·97; 95 % CI 0·95, 0·99; P=0·004 and OR
T3
0·96; 95 % CI 0·92,
1·00; P=0·08) (Table 4). Including markers of lipid metabolism
(model 5) –that is potential intermediates –did not affect the
associations between dairy product intake and pre-diabetes
(data not shown).
Newly diagnosed type 2 diabetes
Exploration of the associations between dairy product intake and
ND-T2DM showed significant positive associations between full-
fat (OR
100 g
1·04; 95 % CI 0·96, 1·13; P=0·29; OR
T2
1·18; 95 % CI
1·01, 1·37; P=0·03 and OR
T3
1·16; 95 % CI 0·99, 1·35; P=0·07)
and non-fermented dairy product (OR
100 g
1·05; 95 % CI 1·01,
1·09; P=0·01 and OR
T3
1·10; 95 % CI 0·95, 1·27; P=0·21) with
ND-T2DM (Table 5). On the product level, a significant positive
association was observed between milk and ND-T2DM
(OR
serving/150g
1·08; 95 % CI 1·02, 1·15; P=0·006 and OR
T3
1·10; 95 % CI 0·95, 1·27; P=0·19), which was predominantly
driven by skimmed milk consumption (OR
serving/150g
1·21; 95 %
CI 1·04, 1·41; P=0·01 and OR
T3
1·17; 95 % CI 0·94, 1·47;
P=0·16). No associations were observed for the consumption of
total, skimmed, semi-skimmed and fermented dairy product,
yogurt, buttermilk, curd cheese, custard, flavoured yogurt drinks
and cheese with ND-T2DM. Including markers of lipid metabo-
lism (model 5) did not influence the associations between dairy
product intake and –ND-T2DM (data not shown).
Moreover, although our analyses showed several significant
interactions between dairy product intake and age, sex and/or
BMI in relation to FPG and HbA1c, no consistent patterns could
be identified for these three elements (online Supplementary
Table S1).
Discussion
Our analyses of dairy product intake with pre-diabetes and ND-
T2DM among Dutch adults in the Lifelines Cohort Study
showed inverse associations of skimmed dairy products, fer-
mented dairy products, buttermilk and low-fat cheese with pre-
diabetes. Positive associations were observed for full-fat dairy
products, non-fermented dairy products, custard, full-fat milk
and full-fat yogurt with pre-diabetes. The observed associations
for dairy product intake and ND-T2DM were less convincing,
but did show positive associations for full-fat dairy products,
non-fermented dairy products, total milk and skimmed milk.
Our analyses did not point towards effect modification by age,
sex and BMI, or mediation through markers of lipid metabolism.
When comparing our data on skimmed, semi-skimmed and
full-fat dairy products with other prospective studies and meta-
analyses, our findings on pre-diabetes are partly in line with
data of the Black Women’s Health Study and the Women’s
Health Study
(17,23)
. These two studies also showed an inverse
association between low-fat dairy products and T2DM inci-
dence
(17,23)
. However, no such association was observed for
high-fat dairy products
(17,23)
. Moreover, no difference between
low-fat and high-fat products in association with incident T2DM
was observed in several other prospective studies
(11,18,21,22)
.
Yet, a meta-analysis of thirteen studies showed a 4 % lower risk
of incident T2DM per 200 g/d low-fat dairy product intake (RR
0·96; 95 % CI 0·92, 1·00), whereas no significant association was
observed for high-fat dairy product intake (RR 0·98; 95 % CI
0·93, 1·04)
(31)
. This meta-analysis also showed a 12 % lower risk
of incident T2DM for an intake of 40 g of fermented dairy
products per day (n5)
(31)
. Although we did not observe an
association between fermented dairy product intake and ND-
T2DM, we did observe a 6 % lower odds of having pre-diabetes
for participants in the highest fermented dairy products intake
tertile. To note, as there was quite some overlap between the
consumed products in the fermented dairy products and
skimmed dairy product groups in our study, the inverse asso-
ciations of skimmed and fermented dairy products with pre-
diabetes may partly be explained by the consumption of the
same products.
As potential dairy product effects may be related to particular
product-specific nutrients, we hypothesised that more detailed
analyses on the product level could provide more insight in the
potential link between dairy product intake and T2DM. For
instance, milk and yogurt are important sources of whey pro-
tein, which have been associated with lower postprandial glu-
cose concentrations in patients with T2DM risk
(42)
. Moreover,
both whey and casein have been shown to decrease food
intake, body weight and body fat, and beneficially affect glu-
cose tolerance and gut hormones in diet-induced obese rats
(43)
.
Beneficial associations as previously observed for fermented
products and T2DM risk
(6,7)
may be related to potential effects
on gut microbiota and satiety
(8)
. In addition, ruminant trans-fatty
acids have been associated with beneficial effects on glucose
homoeostasis as well, where the suggested pathways include
Dairy products and type 2 diabetes 447
Downloaded from https://www.cambridge.org/core. IP address: 147.78.122.3, on 27 Sep 2020 at 18:06:45, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0007114517003762
Table 3. Associations between dairy product consumption and pre-diabetes (fasting plasma glucose (FPG) 5·6–6·9 mmol/l or HbA1c 5·7–6·4 %) in Lifelines
(n110 781)
(Odds ratios and 95 % confidence intervals)
Tertiles of dairy product intake
Continuous T2 T3
OR 95 % CI T1 OR 95 % CI OR 95 % CI P
for trend
Total dairy products 100 g
Median 324 173 318 500
Total n/cases 110 781/25 549 34 352/7167 38 619/9041 37 810/9341
Crude model 1·05 1·04, 1·05 1·01·16 1·12, 1·20 1·25 1·20, 1·29 <0·0001
Model 1* 1·00 0·99, 1·01 1·00·96 0·92, 0·99 0·98 0·94, 1·02 0·40
Model 2†1·00 0·99, 1·01 1·00·96 0·92, 1·00 0·99 0·95, 1·03 0·80
Model 3‡1·00 0·99, 1·01 1·00·97 0·94, 1·01 0·98 0·94, 1·03 0·52
Model 4§ 0·99 0·99, 1·00 1·00·97 0·93, 1·01 0·97 0·93, 1·01 0·13
Skimmed dairy products 100 g
Median 54 3 53 172
Total n/cases 110 781/25 549 36 532/8544 36 712/7995 37 537/9010
Crude model 1·03 1·02, 1·05 1·00·91 0·88, 0·94 1·04 1·00, 1·07 <0·0001
Model 1* 0·97 0·96, 0·98 1·01·00 0·96, 1·03 0·92 0·89, 0·96 <0·0001
Model 2†0·98 0·97, 1·00 1·01·01 0·97, 1·05 0·96 0·92, 0·99 0·009
Model 3‡0·99 0·98, 1·00 1·01·01 0·98, 1·05 0·97 0·93, 1·01 0·07
Model 4§ 0·98 0·97, 1·00 1·00·99 0·95, 1·03 0·95 0·92, 0·99 0·02
Semi-skimmed dair y products 100 g
Median 50 5 49 187
Total n/cases 110 781/25 549 36 700/8518 36 540/8344 37 541/8687
Crude model 1·00 0·99, 1·01 1·00·98 0·95, 1·01 1·00 0·96, 1·03 0·88
Model 1* 1·02 1·00, 1·03 1·00·94 0·91, 0·98 1·00 0·97, 1·04 0·24
Model 2†1·02 1·01, 1·03 1·00·94 0·91, 0·98 1·01 0·97, 1·05 0·20
Model 3‡1·02 1·00, 1·03 1·01·00 0·96, 1·04 1·03 0·99, 1·07 0·16
Model 4§ 1·00 0·99, 1·02 1·00·98 0·94, 1·02 0·99 0·95, 1·03 0·68
Full-fat dairy products 100 g
Median 59 26 59 114
Total n/cases 110 781/25 549 36 656/7306 36 558/8445 37 567/9798
Crude model 1·15 1·13, 1·17 1·01·21 1·17, 1·25 1·42 1·37, 1·47 <0·0001
Model 1* 1·05 1·03, 1·08 1·01·02 0·98, 1·06 1·11 1·07, 1·15 <0·0001
Model 2†1·03 1·01, 1·05 1·01·02 0·98, 1·06 1·07 1·02, 1·11 0·001
Model 3‡1·02 0·99, 1·04 1·01·05 1·01, 1·09 1·07 1·02, 1·11 0·005
Model 4§ 1·03 1·01, 1·06 1·01·06 1·02, 1·11 1·10 1·06, 1·15 <0·0001
Fermented dairy products 100 g
Median 121 45 120 247
Total n/cases 110 781/25 549 36 611/8049 36 609/8264 37 561/9236
Crude model 1·05 1·04, 1·07 1·01·04 1·00, 1·07 1·16 1·12, 1·20 <0·0001
Model 1* 0·97 0·96, 0·98 1·00·95 0·91, 0·98 0·90 0·87, 0·94 <0·0001
Model 2†0·98 0·97, 0·99 1·00·97 0·93, 1·01 0·94 0·90, 0·98 0·002
Model 3‡0·98 0·97, 1·00 1·00·98 0·94, 1·02 0·95 0·91, 0·98 0·006
Model 4§ 0·98 0·97, 0·99 1·00·97 0·93, 1·01 0·94 0·90, 0·98 0·004
Non-fermented dairy products 100 g
Median 126 40 125 284
Total n/cases 110 781/25 549 36 678/7992 36 602/8504 37 501/9053
Crude model 1·03 1·02, 1·04 1·01·09 1·05, 1·13 1·14 1·10, 1·18 <0·0001
Model 1* 1·03 1·02, 1·04 1·01·05 1·01, 1·09 1·11 1·07, 1·15 <0·0001
Model 2†1·02 1·01, 1·03 1·01·03 0·99, 1·07 1·08 1·04, 1·12 <0·0001
Model 3‡1·01 1·00, 1·03 1·01·05 1·01, 1·09 1·07 1·03, 1·11 0·002
Model 4§ 1·01 1·00, 1·02 1·01·04 1·00, 1·08 1·05 1·00, 1·09 0·05
Milk Serving (150 g)
Median 103 25 101 261
Total n/cases 110 781/25 549 36 676/8192 36 610/8489 37 495/8868
Crude model 1·02 1·01, 1·04 1·01·05 1·01, 1·09 1·08 1·04, 1·12 <0·0001
Model 1* 1·03 1·02, 1·05 1·01·04 1·00, 1·08 1·07 1·04, 1·11 <0·0001
Model 2†1·02 1·01, 1·04 1·01·02 0·98, 1·06 1·05 1·01, 1·09 0·02
Model 3‡1·02 1·00, 1·03 1·01·04 1·00, 1·08 1·04 1·00, 1·08 0·08
Model 4§ 1·00 0·98, 1·02 1·01·03 0·99, 1·08 1·01 0·97, 1·06 0·76
Yogur t Serving (150 g)
Median 34 0 23 69
Total n/cases 110 781/25 549 45 770/10 587 27 357/5896 37654/9066
Crude model 1·10 1·05, 1·15 1·00·91 0·88, 0·95 1·05 1·02, 1·09 <0·0001
Model 1* 0·90 0·86, 0·95 1·01·01 0·97, 1·05 0·95 0·92, 0·99 0·003
Model 2†0·94 0·89, 0·99 1·01·03 0·99, 1·07 0·98 0·95, 1·02 0·21
Model 3‡0·96 0·91, 1·01 1·01·02 0·98, 1·07 0·99 0·95, 1·02 0·38
Model 4§ 0·98 0·93, 1·03 1·01·00 0·96, 1·04 0·99 0·96, 1·03 0·76
448 E. M. Brouwer-Brolsma et al.
Downloaded from https://www.cambridge.org/core. IP address: 147.78.122.3, on 27 Sep 2020 at 18:06:45, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0007114517003762
modulation of the hepatic fat content, expression of PPAR-γand
PPAR-α, and inflammatory state
(44)
.
Our analyses on the product level showed an inverse asso-
ciation for buttermilk with pre-diabetes and a positive
association for custard intake and pre-diabetes; no associations
were observed for milk, yogurt, curd cheese, flavoured yogurt
drinks or cheese intake. Milk consumption, particularly skim-
med milk, was positively associated with ND-T2DM, whereas
Table 3. Continued
Tertiles of dairy product intake
Continuous T2 T3
OR 95 % CI T1 OR 95 % CI OR 95 % CI P
for trend
Buttermilk Serving (150 g)
Median 1 0 1 71
Total n/cases 110 781/25 549 36 833/7988 36 483/7866 37 465/9695
Crude model 1·20 1·16, 1·23 1·00·99 0·96, 1·03 1·26 1·22, 1·30 <0·0001
Model 1* 0·94 0·91, 0·96 1·00·87 0·83, 0·90 0·89 0·85, 0·92 0·005
Model 2†0·96 0·93, 0·99 1·00·86 0·82, 0·90 0·91 0·87, 0·95 0·39
Model 3‡0·97 0·94, 1·00 1·00·99 0·94, 1·04 1·00 0·96, 1·04 0·80
Model 4§ 0·97 0·94, 1·00 1·00·99 0·94, 1·04 0·99 0·95, 1·04 0·83
Curd cheese Serving (150 g)
Median 1 0 1 29
Total n/cases 110 781/25 549 36 598/8657 36 406/8115 37 777/8777
Crude model 1·00 0·93, 1·09 1·00·93 0·89, 0·96 0·98 0·94, 1·01 0·40
Model 1* 0·89 0·81, 0·97 1·00·89 0·85, 0·92 0·92 0·89, 0·96 0·16
Model 2†0·92 0·84, 1·00 1·00·88 0·84, 0·91 0·93 0·89, 0·96 0·43
Model 3‡0·93 0·85, 1·02 1·00·97 0·93, 1·02 0·97 0·93, 1·01 0·39
Model 4§ 0·94 0·86, 1·04 1·00·97 0·93, 1·01 0·97 0·94, 1·02 0·52
Custard Serving (150 g)
Median 3 0 3 26
Total n/cases 110 781/25 549 36 649/8214 36 379/8311 37 753/9024
Crude model 1·38 1·28, 1·49 1·01·03 0·99, 1·06 1·09 1·05, 1·13 <0·0001
Model 1* 1·13 1·03, 1·22 1·00·90 0·87, 0·94 0·98 0·95, 1·02 0·14
Model 2†1·08 0·99, 1·18 1·00·90 0·86, 0·94 0·96 0·92, 1·00 0·85
Model 3‡1·05 0·96, 1·15 1·01·01 0·96, 1·06 1·01 0·97, 1·05 0·84
Model 4§ 1·13 1·03, 1·24 1·01·01 0·97, 1·06 1·05 1·01, 1·10 0·008
Flavoured yogurt drinks Serving (150 g)
Median 8 0 7 63
Total n/cases 110 781/25 549 36 441/9357 36 367/8670 37 973/7522
Crude model 0·85 0·82, 0·87 1·00·91 0·88, 0·94 0·72 0·69, 0·74 <0·0001
Model 1* 1·01 0·97, 1·04 1·00·90 0·87, 0·94 0·97 0·93, 1·00 0·73
Model 2†1·00 0·96, 1·03 1·00·90 0·86, 0·93 0·95 0·91, 0·99 0·72
Model 3‡0·99 0·95, 1·02 1·00·99 0·94, 1·03 0·99 0·95, 1·03 0·78
Model 4§ 0·97 0·93, 1·00 1·00·98 0·49, 1·03 0·96 0·93, 1·01 0·10
Total cheese Serving (20 g)
Median 26 10 26 50
Total n/cases 110 781/25 549 36 820/7189 36 544/8418 37 417/9942
Crude model 1·12 1·11, 1·13 1·01·23 1·19, 1·28 1·49 1·44, 1·54 <0·0001
Model 1* 1·00 0·99, 1·01 1·00·96 0·93, 1·00 0·98 0·95, 1·02 0·63
Model 2†1·01 1·00, 1·02 1·00·98 0·94, 1·02 1·01 0·97, 1·05 0·59
Model 3‡1·01 0·99, 1·02 1·01·02 0·98, 1·06 1·02 0·98, 1·06 0·34
Model 4§ 1·00 0·99, 1·01 1·01·00 0·96, 1·04 1·00 0·96, 1·05 0·88
Dutch cheese Serving (20 g)
Median 18 5 18 39
Total n/cases 110 781/25 549 36 871/7153 36 534/8505 37 376/9891
Crude model 1·14 1·13, 1·16 1·01·26 1·22, 1·31 1·50 1·44, 1·55 <0·0001
Model 1* 1·00 0·99, 1·02 1·00·97 0·93, 1·01 0·98 0·94, 1·02 0·39
Model 2†1·00 0·98, 1·01 1·00·98 0·94, 1·02 0·97 0·93, 1·01 0·16
Model 3‡0·99 0·98, 1·01 1·01·01 0·97, 1·06 0·98 0·94, 1·02 0·20
Model 4§ 0·99 0·98, 1·01 1·01·00 0·96, 1·05 0·97 0·93, 1·01 0·11
T, tertile.
* Model 1 was adjusted for age (years, continuous) and sex (men/women).
†Model 2 was adjusted for age (years, continuous), sex (men/women), alcohol (categorical), smoking (categorical), education (categorical) and physical activity (moderate intensity
exercise, d/week).
‡Model 3 was adjusted for age (years, continuous), sex (men/women), alcohol (categorical), smoking (categorical), education (categorical), physical activity (moderate intensity
exercise, d/week), total energy intake (kJ/d, continuous) and the intake of energy-adjusted bread, pasta, rice, potato, fruit, vegetables, legumes, meat, fish, coffee, tea, soda/fruit
juice and other dairy product groups (g/d, continuous).
§ Model 4 was adjusted for age (years, continuous), sex (men/women), alcohol (categorical), smoking (categorical), education (categorical), physical activity (moderate intensity
exercise, d/week), total energy intake (kJ/d, continuous), the intake of energy-adjusted bread, pasta, rice, potato, fruit, vegetables, legumes, meat, fish, coffee, tea, soda/fruit juice,
other dairy product groups (g/d, continuous), BMI (kg/m
2
, continuous) and waist circumference (cm, continuous).
Dairy products and type 2 diabetes 449
Downloaded from https://www.cambridge.org/core. IP address: 147.78.122.3, on 27 Sep 2020 at 18:06:45, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0007114517003762
none of the other dairy products were associated with ND-T2DM.
Evaluation of the literature with respect to the different
dairy product groups shows that our null findings for milk in
relation to pre-diabetes are in line with several other observa-
tional studies
(7,12,15,21,22,24)
, but in contrast to two observational
studies in Asian populations, with relatively low milk intakes,
showing inverse associations
(25,27)
. None of the other studies
observed a positive association between milk consumption and
T2DM. Moreover, a recent meta-analysis including 11 studies
did not show a significant link between milk intake and T2DM
risk either (RR 0·97 per 200 g/d; 95 % CI 0·93, 1·02; P=0·25)
(31)
.
Although we observed significant associations of higher
fermented dairy product and buttermilk intakes and a lower
odds of pre-diabetes, we did not observe associations between
yogurt, curd cheese or flavoured yogurt drinks and T2DM or
pre-diabetes. However, full-fat yogurt was positively associated
with pre-diabetes. Other cohort studies that investigated asso-
ciations between the intake of yogurt and T2DM showed
varying results, ranging from no association
(11,14,21,22)
, border-
line non-significant inverse associations
(7,11,15)
to significant
inverse associations
(11,17,19)
. In contrast to our findings, meta-
analysis of eleven studies does suggest a significant inverse
association between yogurt intake and risk of T2DM (RR for
80 g/d: 0·86 compared with 0 g/d; 95 % CI 0·83, 0·90;
Table 4. Associations of milk, yogurt and cheese classified on the basis of fat content with pre-diabetes (PD) (fasting plasma glucose (FPG) 5·6–6·9 mmol/l
or HbA1c 5·7–6·4%) (n110 781) and newly diagnosed type 2 diabetes (ND-T2DM) (FPG ≥7·0 mmol/l) (n112 086) in Lifelines*
(Odds ratios and 95 % confidence intervals)
Tertiles of dairy product intake
Continuous T2 T3
OR 95 % CI T1 OR 95% CI OR 95 % CI P
for trend
Skimmed milk Serving (150 g)
Median 1 0·74 0·95 1·30
Total n/PD 110 781/25 549 36394/8356 36 566/8474 37 821/8719
Fully adjusted OR 1·00 0·95, 1·06 1·01·04 0·99, 1·09 1·06 0·99, 1·13 0·12
Total n/ND-T2DM 112 086/1305 36 812/418 37 005/439 38 269/448
Fully adjusted OR 1·21 1·04, 1·41 1·01·06 0·89, 1·25 1·17 0·94, 1·47 0·15
Semi-skimmed milk Serving (150 g)
Median 39 1 38 177
Total n/PD 110 781/25 549 36560/8678 36 639/8262 37 582/8609
Fully adjusted OR 1·00 0·98, 1·02 1·01·00 0·96, 1·05 0·99 0·95, 1·03 0·58
Total n/ND-T2DM 112 086/1305 37 015/455 37 025/386 38 046/464
Fully adjusted OR 1·05 0·98, 1·13 1·00·90 0·78, 1·05 0·99 0·86, 1·14 0·75
Full-fat milk Serving (150 g)
Median 10 0 10 39
Total n/PD 110 781/25 549 36735/7680 36 568/7926 37 478/9943
Fully adjusted OR 1·03 0·99, 1·08 1·01·00 0·95, 1·04 1·07 1·02, 1·11 <0·0001
Total n/ND-T2DM 112 086/1305 37 142/407 36 979/411 37 965/487
Fully adjusted OR 0·98 0·82, 1·17 1·01·02 0·87, 1·20 0·98 0·84, 1·14 0·69
Skimmed yogurt Serving (150 g)
Median 2 0 2 54
Total n/PD 110 781/25 549 36406/8604 36 767/8197 37 608/8748
Fully adjusted OR 0·95 0·90, 1·00 1·01·00 0·95, 1·05 0·97 0·93, 1·01 0·10
Total n/ND-T2DM 112 086/1305 36 858/452 37 194/427 38 034/426
Fully adjusted OR 1·06 0·86, 1·30 1·01·04 0·89, 1·23 0·99 0·86, 1·15 0·68
Full-fat yogurt Serving (150 g)
Median 2 0 2 14
Total n/PD 110 781/25 549 36681/8240 36 390/8390 37 710/8919
Fully adjusted OR 1·09 0·99, 1·19 1·01·04 0·99, 1·09 1·07 1·02, 1·12 0·02
Total n/ND-T2DM 112 086/1305 37 113/432 36 838/448 38 135/425
Fully adjusted OR 0·89 0·61, 1·30 1·00·95 0·80, 1·14 1·03 0·86, 1·23 0·40
Low-fat cheese Serving (20 g)
Median 1 0·70 1·22 14·93
Total n/PD 110 781/25 549 36848/8400 36 700/7907 37 233/9242
Fully adjusted OR 0·97 0·95, 0·99 1·01·00 0·96, 1·05 0·96 0·92, 1·00 0·02
Total n/ND-T2DM 112 086/1305 37 276/428 37 061/361 37 749/516
Fully adjusted OR 1·03 0·96, 1·11 1·00·85 0·71, 1·01 1·03 0·88, 1·19 0·08
Regular-fat cheese Serving (20 g)
Median 11 2 11 31
Total n/PD 110 781/25 549 36523/7957 36 576/7915 37 682/9677
Fully adjusted OR 1·01 0·99, 1·03 1·01·00 0·96, 1·04 1·01 0·97, 1·05 0·48
Total n/ND-T2DM 112 086/1305 36 930/407 36 965/389 38 191/509
Fully adjusted OR 1·01 0·95, 1·07 1·01·00 0·86, 1·17 1·05 0·91, 1·21 0·44
T, tertile.
* The fully adjusted OR was adjusted for age (years, continuous), sex (men/women), alcohol (categorical), smoking (categorical), education (categorical), physical activity (moderate
intensity exercise, d/week), total energy intake (kJ/d, continuous), the intake of energy-adjusted bread, pasta, rice, potato, fruit, vegetables, legumes, meat, fish, coffee, tea, soda/
fruit juice, other dairy product groups (g/d, continuous), BMI (kg/m
2
, continuous) and waist circumference (cm, continuous).
450 E. M. Brouwer-Brolsma et al.
Downloaded from https://www.cambridge.org/core. IP address: 147.78.122.3, on 27 Sep 2020 at 18:06:45, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0007114517003762
Table 5. Associations between dairy product consumption and newly diagnosed type 2 diabetes (fasting plasma glucose (FPG) ≥7·0 mmol/l) in Lifelines
(n112 086)
(Odds ratios and 95 % confidence intervals)
Tertiles of dairy product intake
Continuous
T1
T2 T3
OR 95 % CI OR 95 % CI OR 95 % CI P
for trend
Total dairy products 100 g
Median 324 173 318 500
Total n/cases 112 086/1305 34 716/364 39 063/444 38 307/497
Crude model 1·05 1·02, 1·08 1·01·09 0·94, 1·25 1·24 1·08, 1·42 0·002
Model 1* 1·01 0·98, 1·04 1·00·90 0·78, 1·04 0·99 0·86, 1·13 0·92
Model 2†1·02 0·99, 1·05 1·00·91 0·79, 1·06 1·03 0·89, 1·19 0·53
Model 3‡1·03 1·00, 1·07 1·00·96 0·83, 1·12 1·11 0·95, 1·29 0·12
Model 4§ 1·03 1·00, 1·06 1·00·98 0·84, 1·14 1·10 0·94, 1·28 0·16
Skimmed dairy products 100g
Median 54 3 53 172
Total n/cases 112 086/1305 36 977/445 37 107/395 38 002/465
Crude model 1·03 0·98, 1·08 1·00·88 0·77, 1·01 1·02 0·89, 1·16 0·44
Model 1* 0·98 0·93, 1·03 1·01·01 0·88, 1·15 0·94 0·82, 1·07 0·30
Model 2†1·00 0·96, 1·06 1·01·03 0·89, 1·18 1··00 0·87, 1·15 0·93
Model 3‡1·03 0·98, 1·09 1·01·06 0·92, 1·23 1·08 0·94, 1·24 0·35
Model 4§ 1·03 0·98, 1·09 1·01·02 0·88, 1·18 1·08 0·93, 1·24 0·30
Semi-skimmed dair y products 100 g
Median 50 5 49 187
Total n/cases 112 086/1305 37 126/426 36 951/411 38 009/468
Crude model 1·05 1·01, 1·09 1·00·97 0·85, 1·11 1·07 0·94, 1·23 0·18
Model 1* 1·06 1·02, 1·11 1·00·98 0·85, 1·13 1·08 0·94, 1·23 0·17
Model 2†1·05 1·01, 1·10 1·00·99 0·86, 1·15 1·07 0·93, 1·23 0·30
Model 3‡1·06 1·02, 1·11 1·01·03 0·88, 1·19 1·11 0·96, 1·28 0·15
Model 4§ 1·04 0·99, 1·09 1·01·01 0·87, 1·17 1·05 0·90, 1·21 0·52
Full-fat dairy products 100 g
Median 59 26 59 114
Total n/cases 112 086/1305 37 005/349 37 016/458 38 065/498
Crude model 1·11 1·05, 1·19 1·01·32 1·14, 1·51 1·39 1·21, 1·60 <0·0001
Model 1* 1·02 0·95, 1·10 1·01·15 1·00, 1·33 1·11 0·96, 1·27 0·29
Model 2†1·00 0·93, 1·08 1·01·14 0·98, 1·32 1·07 0·92, 1·23 0·63
Model 3‡1·02 0·95, 1·11 1·01·17 1·01, 1·36 1·12 0·97, 1·31 0·27
Model 4§ 1·04 0·96, 1·13 1·01·18 1·01, 1·37 1·16 0·99, 1·35 0·13
Fermented dairy products 100 g
Median 121 45 120 247
Total n/cases 112 086/1305 37 061/450 37 010/401 38 015/454
Crude model 1·02 0·97, 1·06 1·00·89 0·78, 1·02 0·98 0·86, 1·12 0·98
Model 1* 0·95 0·91, 1·00 1·00·85 0·74, 0·97 0·82 0·71, 0·93 0·006
Model 2†0·98 0·94, 1·03 1·00·87 0·76, 1·01 0·89 0·77, 1·02 0·14
Model 3‡1·01 0·97, 1·06 1·00·92 0·80, 1·07 0·97 0·84, 1·13 0·85
Model 4§ 1·02 0·97, 1·07 1·00·93 0·81, 1·08 1·00 0·86, 1·15 0·92
Non-fermented dairy products 100 g
Median 126 40 125 284
Total n/cases 112 086/1305 37 074/396 37 012/410 38 000/499
Crude model 1·07 1·03, 1·10 1·01·04 0·90, 1·19 1·23 1·08, 1·41 0·001
Model 1* 1·06 1·02, 1·10 1·01·00 0·87, 1·15 1·16 1·01, 1·32 0·02
Model 2†1·05 1·02, 1·09 1·00·96 0·83, 1·11 1·10 0·96, 1·27 0·10
Model 3‡1·06 1·02, 1·10 1·00·98 0·85, 1·14 1·14 0·98, 1·31 0·05
Model 4§ 1·05 1·01, 1·09 1·00·97 0·84, 1·13 1·10 0·95, 1·27 0·13
Milk Serving (150 g)
Median 103 25 101 261
Total n/cases 112 086/1305 37 084/408 37 011/401 37 991/496
Crude model 1·10 1·04, 1·15 1·00·99 0·86, 1·13 1·19 1·04, 1·36 0·003
Model 1* 1·10 1·05, 1·16 1·00·98 0·86, 1·13 1·16 1·02, 1·33 0·01
Model 2†1·09 1·03, 1·15 1·00·95 0·82, 1·09 1·11 0·97, 1·27 0·07
Model 3‡1·11 1·05, 1·18 1·00·97 0·84, 1·13 1·15 1·00, 1·33 0·02
Model 4§ 1·08 1·02, 1·15 1·00·97 0·84, 1·13 1·10 0·95, 1·27 0·11
Yogur t Serving (150 g)
Median 17 0 23 69
Total n/cases 112 086/1305 46 351/581 27 667/310 38 068/414
Crude model 0·92 0·77, 1·11 1·00·89 0·78, 1·03 0·87 0·76, 0·98 0·03
Model 1* 0·80 0·66, 0·96 1·01·04 0·90, 1·20 0·82 0·72, 0·94 0·002
Model 2†0·86 0·71, 1·04 1·01·07 0·92, 1·24 0·88 0·77, 1·00 0·04
Model 3‡0·94 0·78, 1·14 1·01·06 0·92, 1·23 0·93 0·81, 1·06 0·22
Model 4§ 1·02 0·84, 1·23 1·01·02 0·88, 1·18 0·97 0·84, 1·11 0·59
Dairy products and type 2 diabetes 451
Downloaded from https://www.cambridge.org/core. IP address: 147.78.122.3, on 27 Sep 2020 at 18:06:45, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0007114517003762
P<0·0001)
(31)
. Finally, in line with our findings on total cheese
intake, most other studies exploring the association between
cheese intake and the development of T2DM, although
not all
(7,11)
, do not point towards an association
(11,14,15,21,22,24)
.
In line, a recent meta-analyses by Gijsbers and colleagues
(2016) did not detect a significant relationship for this dairy
product and incident T2DM (n12, RR 1·00 per 10 g/d)
(31)
.
However, our analyses did show a significant inverse
Table 5. Continued
Tertiles of dairy product intake
Continuous
T1
T2 T3
OR 95 % CI OR 95 % CI OR 95 % CI P
for trend
Buttermilk Serving (150 g)
Median 1 0 1 71
Total n/cases 112 086/1305 37 244/411 36 896/413 37 946/481
Crude model 1·11 1·00, 1·22 1·01·02 0·88, 1·16 1·15 1·01, 1·31 0·02
Model 1* 0·89 0·80, 0·99 1·00·96 0·83, 1·11 0·88 0·76, 1·01 0·07
Model 2†0·95 0·85, 1·06 1·00·97 0·83, 1·13 0·95 0·82, 1·10 0·61
Model 3‡1·01 0·90, 1·13 1·00·99 0·82, 1·19 1·03 0·88, 1·20 0·58
Model 4§ 1·02 0·91, 1·14 1·01·00 0·83, 1·21 1·03 0·88, 1·21 0·67
Curd cheese Serving (150 g)
Median 1 0 1 29
Total n/cases 112 086/1305 37 048/450 36 864/458 38 174/397
Crude model 0·70 0·49, 1·00 1·01·02 0·90, 1·17 0·86 0·75, 0·98 0·006
Model 1* 0·70 0·49, 1·00 1·01·08 0·94, 1·24 0·89 0·78, 1·03 0·01
Model 2†0·83 0·58, 1·18 1·01·10 0·95, 1·27 0·98 0·84, 1·13 0·28
Model 3‡0·90 0·63, 1·29 1·01·11 0·95, 1·31 1·01 0·87, 1·18 0·55
Model 4§ 0·95 0·66, 1·36 1·01·11 0·95, 1·31 1·04 0·89, 1·21 0·80
Custard Serving (150 g)
Median 3 0 3 26
Total n/cases 112 086/1305 37 076/427 36 813/434 38 197/444
Crude model 1·05 0·76, 1·44 1·01·02 0·90, 1·17 1·01 0·88, 1·15 0·99
Model 1* 0·79 0·67, 1·09 1·00·97 0·84, 1·12 0·95 0·83, 1·09 0·50
Model 2†0·78 0·55, 1·09 1·00·98 0·85, 1·14 0·95 0·82, 1·09 0·47
Model 3‡0·78 0·55, 1·10 1·00·99 0·83, 1·17 0·95 0·82, 1·10 0·45
Model 4§ 0·93 0·66, 1·30 1·01·01 0·85, 1·20 1·06 0·91, 1·24 0·40
Flavoured yogurt drinks Serving (150 g)
Median 8 0 7 63
Total n/cases 112 086/1305 36 933/492 36 809/442 38 344/371
Crude model 0·88 0·77, 1·01 1·00·90 0·79, 1·02 0·72 0·63, 0·83 <0·0001
Model 1* 1·07 0·95, 1·20 1·00·97 0·85, 1·11 1·05 0·91, 1·21 0·33
Model 2†1·05 0·93, 1·19 1·00·98 0·85, 1·13 1·03 0·89, 1·20 0·54
Model 3‡1·05 0·93, 1·20 1·00·99 0·84, 1·16 1·04 0·89, 1·21 0·53
Model 4§ 1·02 0·90, 1·16 1·01·01 0·86, 1·19 1·02 0·88, 1·19 0·80
Total cheese Serving (20 g)
Median 26 10 26 50
Total n/cases 112 086/1305 37 170/350 36 968/424 37 948/531
Crude model 1·12 1·08, 1·16 1·01·22 1·06, 1·41 1·49 1·30, 1·71 <0·0001
Model 1* 1·02 0·97, 1·06 1·00·98 0·85, 1·14 1·01 0·88, 1·17 0·77
Model 2†1·02 0·98, 1·07 1·01·03 0·88, 1·19 1·08 0·93, 1·25 0·28
Model 3‡1·04 1·00, 1·09 1·01·08 0·93, 1·26 1·15 0·99, 1·34 0·07
Model 4§ 1·03 0·99, 1·08 1·01·04 0·89, 1·22 1·10 0·95, 1·28 0·21
Dutch cheese Ser ving (20 g)
Median 18 5 18 39
Total n/cases 112 086/1305 37 192/321 37 000/466 37 894/518
Crude model 1·15 1·10, 1·20 1·01·47 1·27, 1·69 1·59 1·38, 1·83 <0·0001
Model 1* 1·02 0·97, 1·07 1·01·15 1·00, 1·34 1·05 0·91, 1·22 0·87
Model 2†1·01 0·96, 1·06 1·01·20 1·03, 1·39 1·07 0·92, 1·25 0·81
Model 3‡1·02 0·97, 1·08 1·01·26 1·08, 1·47 1·14 0·98, 1·33 0·35
Model 4§ 1·02 0·97, 1·07 1·01·23 1·06, 1·44 1·11 0·95, 1·30 0·49
T, tertile.
* Model 1 was adjusted for age (years, continuous) and sex (men/women).
†Model 2 was adjusted for age (years, continuous), sex (men/women), alcohol (categorical), smoking (categorical), education (categorical) and physical activity (moderate intensity
exercise, d/week).
‡Model 3 was adjusted for age (years, continuous), sex (men/women), alcohol (categorical), smoking (categorical), education (categorical), physical activity (moderate intensity
exercise, d/week), total energy intake (kJ/d, continuous) and the intake of energy-adjusted bread, pasta, rice, potato, fruit, vegetables, legumes, meat, fish, coffee, tea, soda/fruit
juice and other dairy product groups (g/d, continuous).
§ Model 4 was adjusted for age (years, continuous), sex (men/women), alcohol (categorical), smoking (categorical), education (categorical), physical activity (moderate intensity
exercise, d/week), total energy intake (kJ/d, continuous), the intake of energy-adjusted bread, pasta, rice, potato, fruit, vegetables, legumes, meat, fish, coffee, tea, soda/fruit juice,
other dairy product groups (g/d, continuous), BMI (kg/m
2
, continuous) and waist circumference (cm, continuous).
452 E. M. Brouwer-Brolsma et al.
Downloaded from https://www.cambridge.org/core. IP address: 147.78.122.3, on 27 Sep 2020 at 18:06:45, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0007114517003762
association for low-fat cheese and pre-diabetes. Conversely, our
data did not indicate that the association between Dutch cheese
and glucose homoeostasis is any different from the impact of
total cheese.
It may be noted that, in contrast to the suggested favourable
effect of trans-ruminant fatty acids on glucose homoeostasis
(44)
,
our data showed positive associations for full-fat dairy products
as a whole, as well as various full-fat dairy products. We do not
have a clear-cut explanation for the positive associations as
observed in our study other than that full-fat dairy products
have a higher energy content and hence may contribute to
weight gain and as such glucose intolerance. On the contrary,
adding BMI did not change the associations, which does not
support this speculation on energy content. In addition, the
positive association for full-fat dairy products with pre-diabetes
in this population was predominantly driven by the subgroups
with the lowest fat content within this full-fat dairy product
subclass –that is full-fat milk (3·5 g fat) (fully adjusted OR
per serving (150 g): 1·03, 95 % CI 0·99, 1·08), full-fat yogurt
(2·9 g fat) (fully adjusted OR per serving (150 g) 1·09; 95 % CI
0·99, 1·19) and milk-based ice cream (12 g fat) (fully adjusted
OR per serving (75 g) 1·31; 95 % CI 1·16, 1·48), whereas asso-
ciations for the three food groups with the highest fat content
within this full-fat dairy product subclass –that is cream (35 g
fat) (fully adjusted OR per serving (30 g) 1·17; 95 % CI 0·94,
1·44), regular-fat cheese (≥24 g fat) (fully adjusted OR
per serving (20 g) 1·01; 95 % CI 0·99, 1·03) and chocolate milk
(1·9 g fat) (fully adjusted OR per serving (150 g) 0·98; 95 % CI
0·91, 1·06) –with pre-diabetes were less pronounced or even
absent. These findings stress the confusing aspect of dairy food
categorisation based on ‘fat content’in association with
diabetes-related outcomes and call for future studies investi-
gating the impact of dairy products in even more detail (i.e.
individual dairy products).
In addition to above summarised studies, our findings display
important resemblances with the recently published cross-
sectional (Dutch) Maastricht Study with data of 2391 partici-
pants
(45)
, which also showed significant inverse associations of
skimmed dairy products (OR
T3
0·73; 95 % CI 0·55, 0·96) and
fermented dairy products (OR
T3
0·74; 95 % CI 0·54, 0·99) with
impaired glucose metabolism, whereas no associations for
skimmed dairy products and fermented dairy products were
observed for ND-T2DM. Moreover, in line with our findings,
the Maastricht study also showed a positive association
between full-fat dairy product (OR
T3
2·01; 95 % CI 1·16, 3·47)
consumption and ND-T2DM. In contrast to the Maastricht
Study, we did not observe a significant inverse association
between total dairy product consumption and ND-T2DM.
Even with the important resemblances, it needs to be noted
that the associations observed in the Maastricht Study are
substantially stronger than the associations observed in the
Lifelines population. Although we do not have a straightforward
explanation for this difference, the cut-offs for the lowest tertiles
in the Maastricht Study are markedly lower than the cut-offs in
our study, which may partly explain the difference in strength
of the associations. Another explanation may be that the
Maastricht Study was conducted among adults between 40 and
75 years of age, while we included men and women aged 18
years and over. As suggested by the meta-analysis of Gijsbers
et al.
(31)
, associations between dairy product intake and glucose
homoeostasis tend to be stronger in older populations. Then
again, we did not observe consistent interactions between
markers of glucose homoeostasis and age. Moreover, dairy
product intake was not associated with any dairy product
subclass in older Dutch adults aged ≥55 years participating in
the Rotterdam study
(28)
. Finally, we do not have a direct
explanation for the different findings for pre-diabetes and
ND-T2DM as shown in these two studies. It may be postulated
that the null associations for ND-T2DM are related to the low
number of ND-T2DM cases and hence reflect a power issue.
This idea is strengthened by the fact that Lifelines data do
show significant associations for non-fermented dairy products
(5 % higher odds of ND-T2DM per 100 g) and milk (8 % higher
odds of ND-T2DM per serving/150 g) with ND-T2DM when
analysed continuously.
A limitation of this study is that we only had cross-sectional data.
Therefore, it may be that it was not dairy product consumption
that affected glucose homoeostasis, but that people with impaired
glucose homoeostasis made other decisions regarding their dietary
behaviours and hence their dairy product intake. However, as we
had the possibility to study pre-diabetes and ND-T2DM defined
based on aetiologic markers rather than self-report, where all self-
reported diabetics were excluded to prevent the introduction of
reverse causation, we feel that we successfully prevented the
introduction of reverse causation. Specifically, analyses on dairy
product intake and self-report T2DM within this study showed
clear patterns of reverse causation, including a positive association
between semi-skimmed dairy products and self-reported T2DM
and inverse associations of full-fat dairy products and custard with
self-reported T2DM (data not shown), whereas our analyses using
the aetiologic markers to define pre-diabetes/T2DM did not.
Important advantages of the current analyses include the detailed
inquiry of dairy product intake (i.e. ranging from the intake of
skimmed dairy products to full-fat dairy products, non-fermented
to fermented dairy products and milk to flavoured yogurt drinks),
the relatively large range in dairy product intake, its huge sample
size (n≥100 000) and the possibility to conduct well-powered
stratified analyses for age (<50, 50–65 and ≥65 years), sex and
BMI (<25, 25–30, ≥30 kg/m
2
). Moreover, the dairy product intake
in this population was very comparable to the dairy product intake
as estimated in the most recent Dutch Food Consumption Survey
(i.e. 355 g/d)
(46)
, suggesting that the Lifelines population is a
representative sample with respect to Dutch dairy product intakes.
Finally, we had the possibility to include many potential covari-
ates, including all other major food groups, while retaining
sufficient power.
In conclusion, these detailed cross-sectional data on dairy
products intake within the Lifelines Cohort Study showed
inverse associations of skimmed dairy products, fermented
dairy products and buttermilk with pre-diabetes. Moreover,
positive associations were observed for full-fat dairy products,
non-fermented dairy products and custard, and pre-diabetes.
Finally, full-fat dairy products, non-fermented dairy products
and milk were positively associated with ND-T2DM. On the
basis of our results, it may be speculated that the aspect of
fermentation is important to determine whether dairy products
Dairy products and type 2 diabetes 453
Downloaded from https://www.cambridge.org/core. IP address: 147.78.122.3, on 27 Sep 2020 at 18:06:45, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0007114517003762
is beneficial for diabetes prevention or increases the risk. Future
prospective analyses, focusing on a wide range of dairy pro-
ducts, within Lifelines, as well as other mega-cohorts, are
wanted to verify the findings of the current study.
Acknowledgements
The authors wish to acknowledge the services of the Lifelines
Cohort Study, the contributing research centres delivering data
to Lifelines and all the study participants.
The epidemiological analyses were supported by a grant
from FrieslandCampina. FrieslandCampina had no role in the
design, analysis or writing of this article.
E. J. M. F. designed the research and had primary responsi-
bility for final content. E. M. B.-B. analysed data and wrote the
paper. D. S., C. M. S.-P. and E. J. M. F. reviewed and contributed
to the manuscript. All authors have read and approved the final
manuscript.
The authors declare that there are no conflicts of interest.
Supplementary material
For supplementary material/s referred to in this article, please
visit https://doi.org/10.1017/S0007114517003762
References
1. Astrup A, Chaput JP, Gilbert JA, et al. (2010) Dairy beverages
and energy balance. Physiol Behav 100,67–75.
2. Jakubowicz D & Froy O (2013) Biochemical and metabolic
mechanisms by which dietary whey protein may combat
obesity and type 2 diabetes. J Nutr Biochem 24,1–5.
3. Pal S, Ellis V & Dhaliwal S (2010) Effects of whey protein
isolate on body composition, lipids, insulin and glucose in
overweight and obese individuals. Br J Nutr 104, 716–723.
4. Dong JY, Xun P, He K, et al. (2011) Magnesium intake and
risk of type 2 diabetes: meta-analysis of prospective cohort
studies. Diabetes Care 34, 2116–2122.
5. Salas-Salvado J, Marquez-Sandoval F & Bullo M (2006) Con-
jugated linoleic acid intake in humans: a systematic review
focusing on its effect on body composition, glucose, and lipid
metabolism. Crit Rev Food Sci Nutr 46, 479–488.
6. Diaz-Lopez A, Bullo M, Martinez-Gonzalez MA, et al. (2016)
Dairy product consumption and risk of type 2 diabetes
in an elderly Spanish Mediterranean population at high
cardiovascular risk. Eur J Nutr 55, 349–360.
7. Sluijs I, Forouhi NG, Beulens JW, et al. (2012) The amount and
type of dairy product intake and incident type 2 diabetes:
results from the EPIC-InterAct Study. Am J Clin Nutr 96,
382–390.
8. Tremblay A, Doyon C & Sanchez M (2015) Impact of yogurt
on appetite control, energy balance, and body composition.
Nutr Rev 73, Suppl. 1, 23–27.
9. Brassard D, Tessier-Grenier M, Allaire J, et al. (2017) Com-
parison of the impact of SFAs from cheese and butter on
cardiometabolic risk factors: a randomized controlled trial.
Am J Clin Nutr 105, 800–809.
10. Imamura F, O’Connor L, Ye Z, et al. (2016) Consumption of
sugar sweetened beverages, artificially sweetened beverages,
and fruit juice and incidence of type 2 diabetes: systematic
review, meta-analysis, and estimation of population attribu-
table fraction. Br J Sports Med 50, 496–504.
11. Chen M, Sun Q, Giovannucci E, et al. (2014) Dairy con-
sumption and risk of type 2 diabetes: 3 cohorts of US adults
and an updated meta-analysis. BMC Med 12, 215.
12. Elwood PC, Pickering JE & Fehily AM (2007) Milk and dairy
consumption, diabetes and the metabolic syndrome: the
Caerphilly prospective study. J Epidemiol Community Health
61, 695–698.
13. Ericson U, Sonestedt E, Gullberg B, et al. (2013) High intakes
of protein and processed meat associate with increased inci-
dence of type 2 diabetes. Br J Nutr 109, 1143–1153.
14. Grantham NM, Magliano DJ, Hodge A, et al. (2013) The
association between dairy food intake and the incidence of
diabetes in Australia: the Australian Diabetes Obesity and
Lifestyle Study (AusDiab). Public Health Nutr 16, 339–345.
15. Kirii K, Mizoue T, Iso H, et al. (2009) Calcium, vitamin D and
dairy intake in relation to type 2 diabetes risk in a
Japanese cohort. Diabetologia 52, 2542–2550.
16. Lecomte P, Vol S, Caces E, et al. (2007) Five-year predictive
factors of type 2 diabetes in men with impaired fasting
glucose. Diabetes Metab 33, 140–147.
17. Liu S, Choi HK, Ford E, et al. (2006) A prospective study
of dairy intake and the risk of type 2 diabetes in women.
Diabetes Care 29, 1579–1584.
18. Louie JC, Flood VM, Rangan AM, et al. (2013) Higher regular
fat dairy consumption is associated with lower incidence of
metabolic syndrome but not type 2 diabetes. Nutr Metab
Cardiovasc Dis 23, 816–821.
19. Margolis KL, Wei F, de Boer IH, et al. (2011) A diet high in
low-fat dairy products lowers diabetes risk in postmenopausal
women. J Nutr 141, 1969–1974.
20. Montonen J, Jarvinen R, Heliovaara M, et al. (2005) Food
consumption and the incidence of type II diabetes mellitus.
Eur J Clin Nutr 59, 441–448.
21. Soedamah-Muthu SS, Masset G, Verberne L, et al. (2013)
Consumption of dairy products and associations with incident
diabetes, CHD and mortality in the Whitehall II study. Br J
Nutr 109, 718–726.
22. Struijk EA, Heraclides A, Witte DR, et al. (2013) Dairy product
intake in relation to glucose regulation indices and risk of type
2 diabetes. Nutr Metab Cardiovasc Dis 23, 822–828.
23. van Dam RM, Hu FB, Rosenberg L, et al. (2006) Dietary cal-
cium and magnesium, major food sources, and risk of type 2
diabetes in U.S. black women. Diabetes Care 29, 2238–2243.
24. Vang A, Singh PN, Lee JW, et al. (2008) Meats, processed
meats, obesity, weight gain and occurrence of diabetes among
adults: findings from Adventist Health Studies. Ann Nutr
Metab 52,96–104.
25. Villegas R, Gao YT, Dai Q, et al. (2009) Dietary calcium
and magnesium intakes and the risk of type 2 diabetes:
the Shanghai Women’s Health Study. Am J Clin Nutr 89,
1059–1067.
26. von Ruesten A, Feller S, Bergmann MM, et al. (2013) Diet and
risk of chronic diseases: results from the first 8 years of follow-
up in the EPIC-Potsdam study. Eur J Clin Nutr 67, 412–419.
27. Zong G, Sun Q, Yu D, et al. (2014) Dairy consumption, type 2
diabetes, and changes in cardiometabolic traits: a prospective
cohort study of middle-aged and older Chinese in Beijing and
Shanghai. Diabetes Care 37,56–63.
28. Brouwer-Brolsma EM, van Woudenbergh GJ, Oude Elferink SJ,
et al. (2016) Intake of different types of dairy and its
prospective association with risk of type 2 diabetes: The
Rotterdam Study. Nutr Metab Cardiovasc Dis 26,987–995.
29. Drouin-Chartier JP, Brassard D, Tessier-Grenier M, et al.
(2016) Systematic review of the association between dairy
product consumption and risk of cardiovascular-related
clinical outcomes. Adv Nutr 7, 1026–1040.
454 E. M. Brouwer-Brolsma et al.
Downloaded from https://www.cambridge.org/core. IP address: 147.78.122.3, on 27 Sep 2020 at 18:06:45, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0007114517003762
30. Aune D, Norat T, Romundstad P, et al. (2013) Dairy products
and the risk of type 2 diabetes: a systematic review and dose-
response meta-analysis of cohort studies. Am J Clin Nutr 98,
1066–1083.
31. Gijsbers L, Ding EL, Malik VS, et al. (2016) Consumption of
dairy foods and diabetes incidence: a dose-response
meta-analysis of observational studies. Am J Clin Nutr 103,
1111–1124.
32. Scholtens S, Smidt N, Swertz MA, et al. (2015) Cohort profile:
lifelines, a three-generation cohort study and biobank. Int J
Epidemiol 44, 1172–1180.
33. Donders-Engelen M, van der Heijden L & Hulshof K (2003)
Maten, gewichten en codenummers 2003; Food Portion
Sizes and Coding Instructions. Wageningen: Wagenigen
University/TNO Nutrition Zeist.
34. Nederlands Voedingsstoffenbestand (2006) NEVO-tabel:
Nederlands Voedingsstoffenbestand 2006. Den Haag:
Voedingscentrum.
35. Brouwer-Brolsma E, Streppel M, van Lee L, et al. (2017) A
National Dietary Assessment Reference Database (NDARD)
for the Dutch Population: rationale behind the design. Nutri-
ents 9, 1136.
36. Willett WC (1989) Nutritional Epidemiology, 2nd ed.
New York: Oxford University Press.
37. Jansen H, Stolk RP, Nolte IM, et al. (2013) Determinants of
HbA1c in nondiabetic Dutch adults: genetic loci and clinical
and lifestyle parameters, and their interactions in the Lifelines
Cohort Study. J Intern Med 273, 283–293.
38. American Diabetes Association (2016) 2. Classification and
diagnosis of diabetes. Diabetes Care 39, Suppl. 1, S13–S22.
39. Wendel-Vos GC, Schuit AJ, Saris WH, et al. (2003) Reprodu-
cibility and relative validity of the short questionnaire to
assess health-enhancing physical activity. J Clin Epidemiol 56,
1163–1169.
40. van der Ende MY, Hartman MH, Hagemeijer Y, et al. (2017) The
LifeLines Cohort Study: prevalence and treatment of cardio-
vascular disease and risk factors. Int J Cardiol 228, 495–500.
41. Slagter SN, van Vliet-Ostaptchouk JV, Vonk JM, et al. (2014)
Combined effects of smoking and alcohol on metabolic
syndrome: the LifeLines cohort study. PLOS ONE 9, e96406.
42. Frid AH, Nilsson M, Holst JJ, et al. (2005) Effect of whey on
blood glucose and insulin responses to composite breakfast
and lunch meals in type 2 diabetic subjects. Am J Clin Nutr
82,69–75.
43. Pezeshki A, Fahim A & Chelikani PK (2015) Dietary whey and
casein differentially affect energy balance, gut hormones,
glucose metabolism, and taste preference in diet-induced
obese rats. J Nutr 145, 2236–2244.
44. Tremblay BL & Rudkowska I (2017) Nutrigenomic point of
view on effects and mechanisms of action of ruminant trans
fatty acids on insulin resistance and type 2 diabetes. Nutr Rev
75, 214–223.
45. Eussen SJPM, van Dongen MCJM, Wijckmans N, et al. (2016)
Consumption of dairy foods in relation to impaired glucose
metabolism and type 2 diabetes mellitus: The Maastricht
Study. Br J Nutr 115, 1453–1461.
46. van Rossum CTM (2016) The Diet of the Dutch: Results of the
First Two Years of the Dutch National Food Consumption
Survey 2012-2016. Bilthoven: National Institute for Public
Health and the Environment.
Dairy products and type 2 diabetes 455
Downloaded from https://www.cambridge.org/core. IP address: 147.78.122.3, on 27 Sep 2020 at 18:06:45, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0007114517003762
