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Milk Consumption and Mortality from All Causes, Cardiovascular Disease, and Cancer: A Systematic Review and Meta-Analysis

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Results from epidemiological studies of milk consumption and mortality are inconsistent. We conducted a systematic review and meta-analysis of prospective studies assessing the association of non-fermented and fermented milk consumption with mortality from all causes, cardiovascular disease, and cancer. PubMed was searched until August 2015. A two-stage, random-effects, dose-response meta-analysis was used to combine study-specific results. Heterogeneity among studies was assessed with the I² statistic. During follow-up periods ranging from 4.1 to 25 years, 70,743 deaths occurred among 367,505 participants. The range of non-fermented and fermented milk consumption and the shape of the associations between milk consumption and mortality differed considerably between studies. There was substantial heterogeneity among studies of non-fermented milk consumption in relation to mortality from all causes (12 studies; I² = 94%), cardiovascular disease (five studies; I² = 93%), and cancer (four studies; I² = 75%) as well as among studies of fermented milk consumption and all-cause mortality (seven studies; I² = 88%). Thus, estimating pooled hazard ratios was not appropriate. Heterogeneity among studies was observed in most subgroups defined by sex, country, and study quality. In conclusion, we observed no consistent association between milk consumption and all-cause or cause-specific mortality.
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Nutrients 2015,7, 7749-7763; doi:10.3390/nu7095363 OPEN ACCESS
nutrients
ISSN 2072-6643
www.mdpi.com/journal/nutrients
Article
Milk Consumption and Mortality from All Causes,
Cardiovascular Disease, and Cancer: A Systematic Review and
Meta-Analysis
Susanna C. Larsson 1, *, Alessio Crippa 1, 2, Nicola Orsini 1 ,2 , Alicja Wolk 1and
Karl Michaëlsson 3
1Unit of Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet,
SE-171 77 Stockholm, Sweden; E-Mails: alessio.crippa@ki.se (A.C.); nicola.orsini@ki.se (N.O.);
alicja.wolk@ki.se (A.W.)
2Unit of Biostatistics, Institute of Environmental Medicine, Karolinska Institutet,
SE-171 77 Stockholm, Sweden
3Department of Surgical Sciences, Uppsala University, SE-751 85 Uppsala, Sweden;
E-Mail: karl.michaelsson@surgsci.uu.se
*Author to whom correspondence should be addressed; E-Mail: susanna.larsson@ki.se;
Tel.: +46-8-52486059.
Received: 9 July 2015 / Accepted: 27 August 2015 / Published: 11 September 2015
Abstract: Results from epidemiological studies of milk consumption and mortality are
inconsistent. We conducted a systematic review and meta-analysis of prospective studies
assessing the association of non-fermented and fermented milk consumption with mortality
from all causes, cardiovascular disease, and cancer. PubMed was searched until August
2015. A two-stage, random-effects, dose-response meta-analysis was used to combine
study-specific results. Heterogeneity among studies was assessed with the I2statistic.
During follow-up periods ranging from 4.1 to 25 years, 70,743 deaths occurred among
367,505 participants. The range of non-fermented and fermented milk consumption and
the shape of the associations between milk consumption and mortality differed considerably
between studies. There was substantial heterogeneity among studies of non-fermented
milk consumption in relation to mortality from all causes (12 studies; I2= 94%),
cardiovascular disease (five studies; I2= 93%), and cancer (four studies; I2= 75%) as well
as among studies of fermented milk consumption and all-cause mortality (seven studies;
I2= 88%). Thus, estimating pooled hazard ratios was not appropriate. Heterogeneity among
studies was observed in most subgroups defined by sex, country, and study quality. In
Nutrients 2015,77750
conclusion, we observed no consistent association between milk consumption and all-cause
or cause-specific mortality.
Keywords: cancer; cardiovascular disease; meta-analysis; milk; mortality
1. Introduction
Milk is a widely consumed dairy product. Being rich in protein, saturated fat (whole milk), lactose,
calcium, and other essential nutrients, milk consumption may influence the risk of disease and mortality.
Evidence indicates that milk consumption may be associated with an increased risk of prostate cancer [1]
but with a reduced risk of colorectal cancer [2]. Milk consumption has been inconsistently associated
with cardiovascular disease [35] and type 2 diabetes [6,7], and does not appear to reduce the risk of
hip fractures [8]. Whether milk consumption is related to all-cause mortality remains unclear. We
therefore conducted a systematic review and meta-analysis to evaluate any potential association between
non-fermented milk consumption and mortality from all causes, overall cardiovascular disease, and
overall cancer. In addition, we assessed whether consumption of fermented milk, which might have
antioxidant and anti-inflammatory effects [9,10], is associated with all-cause mortality.
2. Experimental Section
2.1. Literature Search
We followed standard criteria for performing and reporting of meta-analyses of observational
studies [11]. Studies were identified by a systematic review of the literature until August 2015 by
using the electronic PubMed database. No restrictions were imposed. We used the search terms:
(dairy OR milk OR yogurt) AND (mortality or death) AND (cohort OR prospective). In addition, we
manually searched the reference lists of recent reviews and other retrieved publications to search for
further articles.
2.2. Study Selection
We included prospective studies that provided hazard ratios (HRs) with 95% confidence intervals (CI)
for at least three categories (including the reference group) of milk consumption in relation to mortality
from all causes, overall cardiovascular disease, or overall cancer, We omitted studies that only reported
results for total milk products or combined non-fermented and fermented milk because non-fermented
and fermented milk may have different associations with mortality.
Nutrients 2015,77751
2.3. Data Extraction and Quality Assessment
From each publication, we extracted the first author’s last name, year of publication, name of the
cohort, country, sex, age range of the study population, sample size, number of deaths, duration of
follow-up, variables adjusted for in the statistical analysis, and HRs with 95% CIs for each category of
milk consumption. We extracted the HRs from the most fully adjusted model, except when adjustments
were made for major components of milk, such as dietary calcium. Data were extracted separately
for women and men if sex-specific results were provided. Study quality was assessed using the
Newcastle-Ottawa Scale [12]. The score ranged from 0–9 stars (9 representing the highest quality).
2.4. Statistical Analysis
A two-stage, random-effects, dose-response meta-analysis [13,14] was conducted to assess potential
nonlinear associations between milk consumption and mortality. This was done by modeling milk
consumption by using restricted cubic splines with three knots at fixed percentiles [14]. First, a
restricted cubic spline model with two spline transformations was fitted, taking into account the
correlation within each set of published relative risks [13,14]. Second, the two regression coefficients
and the variance/covariance matrices estimated for each study were combined using a multivariate
random-effects meta-analysis [15]. An overall p-value was computed by testing that the two regression
coefficients were equal to zero. We calculated a p-value for nonlinearity by testing that the coefficient of
the second spline was equal to zero [16]. The dose-response meta-analysis method requires that (1) risk
estimates with CIs are available for at least three exposure categories (including the reference group);
(2) the number of cases and participants (or person-time) for each category are known (to be able to
estimate variance/covariance matrices); and (3) the mean or median milk consumption for each exposure
category is reported in the article or can be estimated.
Heterogeneity among studies was evaluated using the I2statistics [17]. Low, moderate-to-high, and
substantial heterogeneity was defined by I2-values of <25%, 25%–75%, and >75%, respectively. To
investigate the influence of single studies on the overall results, we conducted a sensitivity analysis in
which one study at a time was removed and the rest analyzed. Potential sources of heterogeneity due
to sex, country, and study quality were assessed using stratified analysis. The statistical analyses were
conducted using the dosresmeta [18] and metaphor [19] packages in R (R Foundation for Statistical
Computing, Vienna, Austria) [20]. p-values < 0.05 were considered statistically significant.
3. Results
3.1. Literature Search
We identified 12 prospective studies [2131] (one article presented results from two separate
cohort studies [30]) that reported HRs of mortality from all causes (n= 12), cardiovascular disease
(n= 5), or cancer (n= 4) in relation to non-fermented milk consumption (Figure 1). Six of those
studies (five articles) also provided results on fermented milk (yogurt and/or soured milk) [2528,30]
consumption. We identified an additional study on consumption of yogurt in relation to mortality [32].
Nutrients 2015,77752
Nutrients 2015, 7 4
Figure 1. Flow diagram of literature search and study selection. Studies excluded based on
title and abstract included experimental studies in animals and in vitro, review articles, and
other studies unrelated to milk consumption and mortality. * One article reported results
from two separate cohorts and one article reported results for fermented milk only.
3.2. Study Characteristics
Characteristics of the included studies on non-fermented milk consumption in relation to all-cause
mortality are shown in Table 1. Four studies were conducted in the UK or Scotland, two in Sweden, two
in the US, and one each in the Netherlands, Japan, and Australia. One study included cohorts from
10 European countries. Combined, these 12 studies included 70,743 deaths among 367,505 participants.
All studies controlled for age and sex (if applicable). Most studies also adjusted for smoking (n = 11),
body mass index (n = 10), alcohol consumption or drinking status (n = 9), total energy intake (n = 8),
physical activity (n = 7), and markers of socioeconomic status (n = 7). Few studies adjusted for other
food items or a healthy eating pattern (n = 5). Information on milk consumption was obtained through
self-report in all studies. Table S1 presents the scores assigned to each study and Figure S1 lists details
of how the criteria of study quality were applied.
Figure 1. Flow diagram of literature search and study selection. Studies excluded based
on title and abstract included experimental studies in animals and in vitro, review articles,
and other studies unrelated to milk consumption and mortality. * One article reported results
from two separate cohorts and one article reported results for fermented milk only.
3.2. Study Characteristics
Characteristics of the included studies on non-fermented milk consumption in relation to all-cause
mortality are shown in Table 1. Four studies were conducted in the UK or Scotland, two in Sweden, two
in the US, and one each in the Netherlands, Japan, and Australia. One study included cohorts from 10
European countries. Combined, these 12 studies included 70,743 deaths among 367,505 participants.
All studies controlled for age and sex (if applicable). Most studies also adjusted for smoking (n= 11),
body mass index (n= 10), alcohol consumption or drinking status (n= 9), total energy intake (n= 8),
physical activity (n= 7), and markers of socioeconomic status (n= 7). Few studies adjusted for other
food items or a healthy eating pattern (n= 5). Information on milk consumption was obtained through
self-report in all studies. Table S1 presents the scores assigned to each study and Figure S1 lists details
of how the criteria of study quality were applied.
Nutrients 2015,77753
Table 1. Characteristics of studies included in meta-analysis of milk consumption and all-cause mortality.
First Author,
Year Cohort Name Country No. of
Deaths
Sex (No. of
Participants)
Age
Range,
Years
Duration
of
Follow-up,
Years
Milk Intake
Categories HR (95% CI) Adjustments
Mann,
1997 [21]NA UK 392 Women and
men (10,802) 16–79 13.3
<280 mL/day a1.00 (ref.)
Age, sex, smoking, and social class
280 mL/day 0.70 (0.55–0.88)
>280 mL/day 0.87 (0.68–1.13)
Ness, 2001 [22]Collaborative
Study Scotland 2350 Men (5,765) 35–64 25
<190 mL/day a1.00 (ref.) Age, education, social class, father’s social class,
smoking, BMI, diastolic blood pressure,
cholesterol, adjusted FEV1, deprivation category,
siblings, car user, angina, ECG ischemia,
bronchitis, and alcohol intake
190–750
mL/day 0.90 (0.83–0.97)
ě760 mL/day 0.81 (0.61–1.09)
Elwood,
2004 [23]
Caerphilly
Cohort Study UK 811 Men (2512) 45–59 20–24
0 1.00 (ref.) Age, social class, smoking, BMI, systolic blood
pressure, prior vascular disease, intake of fat,
alcohol, and total energy
<280 mL/day a0.99 (0.73–1.34)
280–570
mL/day 0.98 (0.72–1.35)
>570 mL/day 1.20 (0.80–1.80)
Paganini-Hill,
2007 [24]
Leisure World
Cohort Study US 11,396 Women and
men (13,624) 44–101 23
0 glasses/day 1.00 (ref.) Age, sex, smoking, BMI, exercise, histories of
hypertension, angina, heart attack, stroke,
diabetes, rheumatoid arthritis, and cancer,
alcohol intake
<1 glasses/day 0.95 (0.90–1.00)
1 glasses/day 1.01 (0.96–1.06)
ě2 glasses/day 1.04 (0.98–1.10)
Bonthuis,
2010 [25]NA Australia 177 Women and
men (1529) 25–78 14.4
<198 g/day 1.00 (ref.) Age, sex, school leaving age, smoking, BMI,
physical activity level, dietary supplement use,
beta-carotene treatment during trial, presence of
any medical condition, and alcohol and total
energy intake
198–328 g/day 0.85 (0.54–1.33)
ě329 g/day 0.93 (0.59–1.48)
Nutrients 2015,77754
Table 1. Cont.
First Author,
Year Cohort Name Country No. of
Deaths
Sex (No. of
Participants)
Age
Range,
Years
Duration
of
Follow-up,
Years
Milk Intake
Categories HR (95% CI) Adjustments
Goldbohm,
2011 [26]
Netherlands
Cohort Study Netherlands
5478 in
women:
10,658 in men
Women
(62,573) and
men (58,279)
55–69 10
Women Women
Age, education, smoking, BMI, non-occupational
and occupational physical activity, multivitamin
use, intake of fruits and vegetables,
monounsaturated fat, polyunsaturated fat, alcohol,
and total energy
Q1: 0 g/day c1.00 (ref.)
Q2: 21 g/day 0.96 (0.87–1.05)
Q3: 52 g/day 0.96 (0.88–1.04)
Q4: 107 g/day 0.94 (0.86–1.04)
Q5: 238 g/day 1.00 (0.91–1.09)
Men Men
Q1: 0 g/day c1.00 (ref.)
Q2: 34 g/day 0.99 (0.93–1.05)
Q3: 90 g/day 1.00 (0.94–1.08)
Q4: 156 g/day 1.01 (0.94–1.08)
Q5: 342 g/day 1.02 (0.95–1.09)
Soedamah-Muthu,
2013 [27]
Whitehall II
prospective
cohort study
UK 237 Women and
men (4526) 56 b11.7
147 g/day 1.00 (ref.) Age, sex, ethnicity, employment grade, smoking,
BMI, physical activity, family history of
CHD/hypertension, fruit and vegetables, bread,
meat, fish, coffee, tea, alcohol, and total
energy intake
294 g/day 0.98 (0.72–1.34)
441 g/day (median) 0.89 (0.64–1.25)
Dik, 2014 [28]
European
Prospective
Investigation
into Cancer
and Nutrition
10
European
countries
d
1525 Women and
men (3859)e64.2 b4.1
<24 g/day 1.00 (ref.)
Age, sex, center, smoking, pre-diagnostic BMI,
tumor sub-site (colon and rectum), disease stage,
differentiation grade, and total energy intake
24–147 g/day 1.05 (0.90–1.23)
48–293 g/day 1.04 (0.89–1.22)
>293 g/day 1.21 (1.03–1.43)
Yang,
2014 [29]
Cancer
Prevention
Study II
Nutrition
Cohort
US 949 Women and
men (2284) e64 b17
Q1 f1.00 (ref.)
Age, sex, tumor stage, folate and total
energy intake
Q2 1.01 (0.84–1.23)
Q3 0.99 (0.82–1.19)
Q4 0.95 (0.79–1.15)
Nutrients 2015,77755
Table 1. Cont.
First Author,
Year Cohort Name Country No. of
Deaths
Sex (No. of
Participants)
Age
Range,
Years
Duration
of
Follow-up,
Years
Milk Intake
Categories HR (95% CI) Adjustments
Michaëlsson,
2014 [30]
Swedish
Mammography
Cohort
Sweden 15,541 Women
(61,433) 39–74 20.1
<200 g/day 1.00 (ref.) Age, education, living alone, smoking status,
BMI, height, physical activity, cortisone use, use
of estrogen replacement therapy, nulliparity,
Charlson’s comorbidity index, calcium and
vitamin D supplementation, healthy dietary
pattern, alcohol and total energy intake
200–399 g/day 1.21 (1.16–1.25)
400–599 g/day 1.60 (1.53–1.68)
ě600 g/day 1.93 (1.80–2.06)
Michaëlsson,
2014 [30]
Cohort of
Swedish Men Sweden 10,112 Men (45,339) 45–79 11.2
<200 g/day 1.00 (ref.) Age, education, living alone, smoking status,
BMI, height, physical activity, cortisone use,
Charlson’s comorbidity index, calcium and
vitamin D supplementation, healthy dietary
pattern, alcohol and total energy intake
200–399 g/day 0.99 (0.94–1.05)
400–599 g/day 1.05 (1.00–1.11)
ě600 g/day 1.10 (1.03–1.17)
Wang,
2015 [31]
Japan
Collaborative
Cohort Study
Japan
9572 in
women;
12,203 in men
Women
(55,341);
Men (39,639)
40–79 19
Women Women
Age, education, smoking status, drinking status,
BMI, physical activity, sleeping duration,
participation in health check-ups, history of
hypertension, diabetes, and liver disease,
green-leafy vegetable intake
Never 1.00 (ref.)
1–2
times/month 1.00 (0.91–1.05)
1–2 times/week 0.98 (0.91–1.05)
3–4 times/week 0.91 (0.85–0.98)
Almost daily 0.96 (0.91–1.01)
Men Men
Never 1.00 (ref.)
1–2
times/month 0.92 (0.86–0.99)
1–2 times/week 0.91 (0.85–0.96)
3–4 times/week 0.89 (0.84–0.96)
Almost daily 0.93 (0.89–0.98)
Abbreviations: BMI, body mass index; CHD, coronary heart disease; CI, confidence interval; ECG, electrocardiogram; FEV1, forced expiratory volume in the first
second. HR, hazard ratio; NA, not available; Q, quartile or quintile. aAmount was expressed in pints (1 pint = 568 mL). bMean age. cMedian intake in each tertile.
dIncluding Denmark, France, Germany, Greece, Italy, Netherlands, Norway, Spain, Sweden, and UK. eColorectal cancer patients. fQuartiles for women were 0,
0.1–5.0, 5.1–10.0, and ě10.1 serving/week; quartiles for men were 0, 0.1–5.6, 5.7–10.4, and ě10.5 serving/week. One serving was assumed to equal 200 mL.
Nutrients 2015,77756
3.3. Non-Fermented Milk
The range of non-fermented milk consumption and the shape of the association between milk
consumption and all-cause mortality differed between studies (Figure 2). Due to substantial
heterogeneity among studies (I2= 94%), estimating a pooled HR was not appropriate. In a sensitivity
analysis, in which one study at the time was removed and the rest analyzed to assess the influence of
single studies on the overall results, we found that the Swedish Mammography Cohort [30] contributed
most to the heterogeneity. After excluding this study, the heterogeneity was reduced (I2= 58%).
Heterogeneity among studies was observed in most subgroups defined by sex (women: I2= 93.9%;
men I2= 70%; both: I2= 47%), country (UK/Scotland: I2= 44%; Sweden: I2= 99%; rest of Europe:
I2= 19%; US: I2= 40%), and study quality (Newcastle-Ottawa Scale < 7: I2= 45%; ě7: I2= 97%).
Nutrients 2015, 7 8
3.3. Non-Fermented Milk
The range of non-fermented milk consumption and the shape of the association between milk
consumption and all-cause mortality differed between studies (Figure 2). Due to substantial
heterogeneity among studies (I
2
= 94%), estimating a pooled HR was not appropriate. In a sensitivity
analysis, in which one study at the time was removed and the rest analyzed to assess the influence of
single studies on the overall results, we found that the Swedish Mammography Cohort [30] contributed
most to the heterogeneity. After excluding this study, the heterogeneity was reduced (I
2
= 58%).
Heterogeneity among studies was observed in most subgroups defined by sex (women: I
2
= 93.9%;
men I
2
= 70%; both: I
2
= 47%), country (UK/Scotland: I
2
= 44%; Sweden: I
2
= 99%; rest of Europe: I
2
= 19%; US: I
2
= 40%), and study quality (Newcastle-Ottawa Scale < 7: I
2
= 45%; 7: I
2
= 97%).
Figure 2. Dose-response association between non-fermented milk consumption and
all-cause mortality in individual studies. The hazard ratios are plotted on a log scale.
Figure 2. Dose-response association between non-fermented milk consumption and
all-cause mortality in individual studies. The hazard ratios are plotted on a log scale.
The dose-response associations of milk consumption with cardiovascular disease and cancer mortality
in individual studies are shown in Figures 3and 4respectively. There was substantial heterogeneity
among studies of cardiovascular disease (I2= 93%) and cancer (I2= 75%) mortality.
Nutrients 2015,77757
Figure 3. Dose-response association between non-fermented milk consumption and
cardiovascular disease mortality in individual studies. The hazard ratios are plotted on a
log scale.
Nutrients 2015, 7 10
Figure 4. Dose-response association between non-fermented milk consumption and cancer
mortality in individual studies. The hazard ratios are plotted on a log scale.
3.4. Fermented Milk
The HRs of all-cause mortality by levels of fermented milk consumption are presented in Table S2.
Most studies indicated a U-shaped association between fermented milk consumption and all-cause
mortality (Figure S2). The range of fermented milk consumption differed among studies and there was
substantial heterogeneity among studies (I
2
= 88%).
4. Discussion
This systematic review and meta-analysis found substantial heterogeneity among studies of
non-fermented and fermented milk consumption and mortality from all causes, cardiovascular disease,
Figure 4. Cont.
Nutrients 2015,77758
Nutrients 2015, 7 10
Figure 4. Dose-response association between non-fermented milk consumption and cancer
mortality in individual studies. The hazard ratios are plotted on a log scale.
3.4. Fermented Milk
The HRs of all-cause mortality by levels of fermented milk consumption are presented in Table S2.
Most studies indicated a U-shaped association between fermented milk consumption and all-cause
mortality (Figure S2). The range of fermented milk consumption differed among studies and there was
substantial heterogeneity among studies (I
2
= 88%).
4. Discussion
This systematic review and meta-analysis found substantial heterogeneity among studies of
non-fermented and fermented milk consumption and mortality from all causes, cardiovascular disease,
Figure 4. Dose-response association between non-fermented milk consumption and cancer
mortality in individual studies. The hazard ratios are plotted on a log scale.
3.4. Fermented Milk
The HRs of all-cause mortality by levels of fermented milk consumption are presented in Table
S2. Most studies indicated a U-shaped association between fermented milk consumption and all-cause
mortality (Figure S2). The range of fermented milk consumption differed among studies and there was
substantial heterogeneity among studies (I2= 88%).
4. Discussion
This systematic review and meta-analysis found substantial heterogeneity among studies of
non-fermented and fermented milk consumption and mortality from all causes, cardiovascular disease,
and cancer. Due to the large variation in the range of milk consumption across populations and the
considerable heterogeneity, it was not appropriate to pool the results.
Among the 12 studies of non-fermented milk consumption, Michaëlsson et al. [30] observed
statistically significant positive associations of non-fermented milk consumption with all-cause and
cardiovascular disease mortality in cohorts of Swedish women and men. In the same study [30],
non-fermented milk consumption was also positively associated with cancer mortality in the female
cohort (but the association was weaker than for all-cause and cardiovascular disease mortality) but not
in the male cohort. Likewise, Dik et al. [28] observed a positive association between high consumption
of non-fermented milk and all-cause mortality in a pooled analysis of cohort studies from 10 European
countries. In contrast, Mann et al. [21] and Ness et al. [22] found some indication of an inverse relation
between non-fermented milk consumption and all-cause mortality. The study by Mann et al. [21] did
not control for potential confounders such as body mass index, physical activity, alcohol consumption,
and diet. Wang et al. [31] observed a U-shaped association of non-fermented milk consumption
with all-cause and cardiovascular disease mortality in a population of Japanese adults with very low
milk consumption. The other six studies reported no significant relation between non-fermented milk
consumption and all-cause [2327,29] or cardiovascular disease [25] mortality. A potential explanation
for the inconsistent findings may be related to the different range of milk consumption in different
populations. Milk consumption was high and the range of consumption was large in the studies by
Michaëlsson et al. [30]. Although there was a wide range of milk consumption also in the studies
by Ness et al. [22] and Elwood et al. [23], those studies had limited power to detect a statistically
Nutrients 2015,77759
significant association because of a small number of deaths and participants in the highest exposure
category. Furthermore, it was not totally clear if the reported milk consumption in those two studies
included non-fermented milk only or also fermented milk.
In addition to the different range of milk consumption, the proportion of different types of milk (e.g.,
whole milk, reduced-fat and fat-free milk, organic milk, and lactose-free milk) consumed is likely to
vary and could contribute to the disparate findings. Moreover, the composition of milk may differ.
For example, the proportion of conjugated linoleic acid in milk fat depends on what the cows are
fed [33]. Studies with animal models have shown that the predominant conjugated linoleic acid isomer
(cis-9,trans-11) has anti-carcinogenic and anti-atherogenic activities [33].
The confounders controlled for in the included studies differed, and this may also, in part, explain
the inconsistent results. Whereas most studies adjusted for major risk factors for mortality (e.g., age,
sex, smoking, body mass index, physical activity, and alcohol consumption), few studies controlled
for other foods [26,27,31] or a healthy food pattern [30]. Potential dietary confounders include fruits
and vegetables [34], red meat and processed meat [35], and coffee [36] which have been associated
with all-cause mortality. Most studies had a long follow-up (usually between 10 and 25 years) and,
with the exception of the study in women by Michaëlsson et al. [30], did not update information on
milk consumption during follow-up. This along with the use of a dietary questionnaire to assess milk
consumption would most likely have resulted in some misclassification and attenuated HRs. In fact, in
the study of Swedish women by Michaëlsson et al. [30], the HRs were attenuated when only a single
exposure assessment was applied and were similar to the HRs obtained in the Swedish male cohort,
which was based on a single assessment of diet.
Two previous meta-analyses have examined the association between total milk consumption
(non-fermented and fermented milk/yogurt combined) and all-cause mortality. One of the meta-analyses
included eight prospective studies and showed a HR of all-cause mortality of 0.99 (95% CI 0.95–1.03)
per 200-g/day increment of total milk consumption [37], but a meta-regression analytical approach to
detect non-linear patterns in risk was not applied. In the other meta-analysis, based on five prospective
studies, the HR of all-cause mortality was 1.01 (95% CI 0.92–1.11) for the highest versus lowest category
of total milk consumption [38]. Five of the studies included in one or both of those meta-analyses were
excluded from the current meta-analysis because results were only presented for total milk products [39],
for milk and yogurt combined [40], or for comparisons of types of milk (skimmed and semi-skimmed
versus whole milk) [41], results were unpublished [42], or odds ratios without CIs were reported [43].
Among the excluded studies, Fortes et al. [40] observed an inverse association between combined milk
and yogurt consumption and all-cause mortality (HR = 0.38; 95% CI, 0.14–1.01, for ě3 times/week
versus <1 time/week) in a cohort of 162 Italians, whereas Knoops et al. [39] reported a positive
association between total milk products and all-cause mortality (HR = 1.10; 95% CI, 1.00–1.21, for
consumption above versus below the median) in a cohort of 3117 elderly adults from 10 European
countries. No association was observed in the other three studies [4143].
Nutrients 2015,77760
5. Conclusions
In summary, we observed no consistent association between non-fermented or fermented milk
consumption and mortality. Further large prospective studies assessing the relation between milk
consumption and mortality are warranted.
Acknowledgments
This research was supported by a Young Scholars Award Grant from the Strategic Research Area in
Epidemiology at Karolinska Institutet.
Author Contributions
Susanna Larsson designed the research, handled funding, interpreted the data, and drafted the
manuscript. Alessio Crippa performed the statistical analysis and made critical revision of the
manuscript. Nicola Orsini handled funding, contributed to the statistical analysis, and made critical
revision of the manuscript. Alicja Wolk made critical revision of the manuscript. Karl Michaëlsson
interpreted the data and made critical revision of the manuscript. All authors read and approved the
final manuscript.
Conflicts of Interest
The authors declare no conflict of interest.
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© 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article
distributed under the terms and conditions of the Creative Commons Attribution license
(http://creativecommons.org/licenses/by/4.0/).
... Discrepant results regarding IHD risk from milk intake may be due to different types of milk products investigated and different amounts of milk consumed. Study-related factors may also underly differences in findings, including sample size, follow-up time, variability in the range of intakes [28], pooled results for women and men, self-reported versus complete registerbased identification of cases, and standardized 200 mL/ day intake measures that can obscure non-linear associations [6][7][8][29][30][31]. In meta-analyses, the underlying cohort studies have varied considerably in average intake levels, from < 20 mL/day to > 200 mL/day, with ranges that do not overlap at the high intake ranges [27,28]. ...
... Study-related factors may also underly differences in findings, including sample size, follow-up time, variability in the range of intakes [28], pooled results for women and men, self-reported versus complete registerbased identification of cases, and standardized 200 mL/ day intake measures that can obscure non-linear associations [6][7][8][29][30][31]. In meta-analyses, the underlying cohort studies have varied considerably in average intake levels, from < 20 mL/day to > 200 mL/day, with ranges that do not overlap at the high intake ranges [27,28]. ...
Article
Full-text available
Background The effect of milk on the risk of ischemic heart disease (IHD) and acute myocardial infarction (MI) is unclear. We aimed to examine the association between non-fermented and fermented milk consumption on these endpoints and investigate the relationship between milk intake and cardiometabolic-related proteins in plasma. Methods Our study is based on two Swedish prospective cohort studies that included 59,998 women and 40,777 men without IHD or cancer at baseline who provided repeated measures of diet and lifestyle factors and plasma proteomics data in two subcohorts. Through registry linkage, 17,896 cases with IHD were documented during up to 33 years of follow-up, including 10,714 with MI. We used time-updated multivariable Cox regression analysis to examine non-fermented or fermented milk intake with time to IHD or MI. Using high-throughput multiplex immunoassays, 276 cardiometabolic plasma proteins were measured in two subcohorts. We applied multivariable-adjusted regression models using a discovery-replication design to examine protein associations with increasing consumption of non-fermented or fermented milk. Results The results for non-fermented milk differed by sex (p-value for interaction = 0.01). In women, we found a pattern of successively greater risk of IHD and MI at non-fermented milk intake levels higher than 1.5 glasses/day. Compared with an intake of 0.5 glass/day (100 mL/day), non-fermented milk intake of 2 glasses/day in women conferred a multivariable-adjusted hazard ratio (HR) of 1.05 (95% CI 1.01–1.08) for IHD, an intake of 3 glasses/day an HR of 1.12 (95% CI 1.06–1.19), and an intake of 4 glasses/day an HR of 1.21 (95% CI 1.10–1.32). Findings were similar for whole, medium-fat, and low-fat milk. We did not detect higher risks of IHD with increasing milk intakes in men. Fermented milk intake was unrelated to the risk of IHD or MI in either sex. Increasing non-fermented milk intake in women was robustly associated with a higher concentration of plasma ACE2 and a lower concentration of FGF21. Conclusions We show a positive association between high amounts of non-fermented milk intake and IHD in women but not men. We suggest metabolic pathways related to ACE2 and FGF21 potentially underlie the association. Graphical abstract Our analysis of two large cohort studies involving 100,775 participants and 17,896 clinically confirmed IHD events supports a dose–response positive association between non-fermented milk intake higher than 300 mL/day with higher rates of IHD (and acute MI specifically) in women, but not in men. The higher risk of IHD with high milk intake in women was evident, irrespective of the fat content of the milk. Fermented milk intake was unrelated to the risk of IHD in both women and men. Non-fermented milk intake was associated in different directions with circulating levels of ACE2 and FGF21 in women—two essential cardiometabolic proteins, also related to IHD in women in our study.
... 1,2 Dairy product consumption, which increases protein, calcium, and essential vitamin intake, is directly correlated with societal health and advancement. 3,4 Official statistics from the past decade indicate that Iran's per capita dairy consumption remains below 50 kg, lower than the global average. 5 In contrast, most European countries, particularly Western Europe, consume over 200 kg of milk per person annually. ...
... 7 Nutritionists have identified numerous side effects of inadequate dairy consumption, including osteoporosis, metabolic syndrome, impaired vision, infectious diseases, and sleep disorders, among others. 3,[8][9][10] Numerous studies have investigated the relationship between dairy product consumption and the risk of noncommunicable diseases. A systematic review and metaanalysis found that higher total dairy product intake was associated with a lower risk of cardiovascular disease (CVD). ...
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Background: Over the past decade, Iranian households have experienced a decline in dairy product consumption. This study aimed to evaluate the population-attributable risk of prevalent non-communicable diseases related to dairy product consumption. Methods: This cross-sectional analytical study involved 628 adults over 18 years old in Hamadan City in 2021. Clusters were selected based on comprehensive urban health centers. The standardized Iranian version of the food frequency questionnaire was used. Participants were categorized into 3 levels of dairy product consumption: >1 serving per day, 1–2 servings per day, and ≥3 servings per day. Results: The mean age of the 628 participants was 38.05 (SD: 12.5), with 42.36% being male. Cheese (54.5%), yogurt (39.7%), and milk (30.4%) were consumed most frequently. The prevalence of insufficient dairy product consumption was 48.6%, higher than that reported in previous studies. Insufficient dairy product consumption was associated with hypertension (9.3%), cardiovascular disease (5.6%), and osteoporosis (5.1%). Conclusion: Individuals with lower education levels, female gender, lowest quartile of socioeconomic status, and those diagnosed with cardiovascular disease were more likely to have insufficient dairy product consumption. Insufficient dairy product consumption was associated with hypertension, cardiovascular disease, and osteoporosis.
... Further, potential contradictions also appear when examining mortality risk in association with consumption levels for individual food sources for animal protein. Here, studies have generally reported increased risks of all-cause, cardiovascular, and cancer-related mortality in relation to higher intakes of red and processed meat [18][19][20][21][22], whereas mostly inverse risk relationships have been found for consumption of poultry [20,23,24] or dairy products [25,26], with some degree of heterogeneity across different studies, particularly, for the association of dairy intake with all-cause, cardiovascular, and cancer mortality [27][28][29]. These heterogeneous findings across main food groups contributing to animal protein intake raise the question of whether animal protein itself, as a nutrient, is a genuine cause contributing to higher mortality risk. ...
... It is worth noting that the associations of food intake levels with overall and causespecific mortality found in the EPIC-Heidelberg cohort, contrasting as they were for differ-ent main sources of animal protein, are mostly in line with findings from other prospective studies. Although differences in the time period, study population, type of dietary assessment tools used, or covariate adjustments may have led to heterogeneity across prospective studies worldwide, meta-analyses showed mostly higher risks of overall cardiovascular and cancer-related mortality in relation to red meat or processed meat intake and lower risks in relation to consumption levels of poultry, cheese or milk [19][20][21][23][24][25][26][43][44][45], even though findings for dairy products have been more diverse across different studies [27][28][29]. We found that most of the associations disappeared after considering mortality endpoints grouped by their known relationships with smoking, alcohol intake, and adiposity and when careful adjustments were made for the latter risk factors. ...
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While prior prospective iso-caloric substitution studies show a robust association between higher intake of animal protein and risk of mortality, associations observed for mortality risk in relation to major food sources of animal protein have been generally more diverse. We used the EPIC-Heidelberg cohort to examine if confounding, notably, by smoking, adiposity, or alcohol intake, could cause inconsistencies in estimated mortality hazard ratios (HR) related to intake levels of different types of meat and dairy products. Higher intakes of red or processed meats, and lower intakes of milk or cheese, were observed among current heavy smokers, participants with obesity, or heavy alcohol drinkers. Adjusting for age, sex, and total energy intake, risk models showed increased all-cause, cardiovascular, and cancer-related mortality with higher red or processed meat intakes (HR ranging from 1.25 [95% confidence interval = 1.15–1.36] to 1.76 [1.46–2.12] comparing highest to lowest tertiles), but reduced risks for poultry, milk, or cheese (HR ranging from 0.55 [0.43–0.72] to 0.88 [0.81–0.95]). Adjusting further for smoking history, adiposity indices, alcohol consumption, and physical activity levels, the statistical significance of all these observed was erased, except for the association of processed meat intake with cardiovascular mortality (HR = 1.36 [CI = 1.13–1.64]) and cheese intake with cancer mortality (HR = 0.86 [0.76–0.98]), which, however, were substantially attenuated. These findings suggest heavy confounding and provide little support for the hypothesis that animal protein, as a nutrient, is a major determinant of mortality risk.
... These studies quite consistently indicated increased risks of all-cause and cardiovascular mortality, but not of cancer-related mortality, in association with higher proportions of dietary energy derived from animal protein [13][14][15][16][17], which seems to contradict observations from international correlation studies [5,6]. Further, potential contradictions also appear when examining mortality risk in association with consumption levels for individual food sources for animal protein: Here, studies have generally reported increased risks of all-cause, cardiovascular, and cancer-related mortality in relation to higher intakes of red and processed meat [18][19][20][21][22], whereas mostly inverse risk relationships have been found for consumption of poultry [20,23,24] or dairy products [25,26], with some degree of heterogeneity across different studies particularly for the association of dairy intake with all-cause, cardiovascular, and cancer mortality [27][28][29]. These heterogeneous findings across main food groups contributing to animal protein intake raise the question whether animal protein itself, as a nutrient, is a genuine cause contributing to higher mortality risk. ...
... It is worth noting, that the associations of food intake levels with overall and cause-specific mortality found in the EPIC-Heidelberg cohort, contrasting as they were for different main sources of animal protein, are mostly in line with findings from other prospective studies. Although differences in time period, study population, type of dietary assessment tools used, or covariate adjustments may have led to heterogeneity across prospective studies worldwide, meta-analyses showed mostly higher risks of overall, cardiovascular and cancer-related mortality in relation to red meat or processed meat intake and lower risks in relation to consumption levels of poultry, cheese or milk [19][20][21][23][24][25][26][43][44][45], even though findings for dairy products have been more diverse across different studies [27][28][29]. We found that most of the associations disappeared after considering mortality endpoints grouped by their known relationships with smoking, alcohol intake and adiposity, and when careful adjustments were made for the latter risk factors. ...
... A modest, beneficial effect on blood pressure was reported in most studies. We identified 10 new systematic reviews and/or meta-analyses study published regarding the intake of dairy and all-cause mortality (35,37,(105)(106)(107)(108)(109)(110)(111)(112). Most of the studies found no association between total dairy intake and all-cause mortality. ...
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Milk and dairy products are major sources of protein, calcium, and other micronutrients. Milk and dairy products contribute with approximately half of the total intake of saturated fat in the Nordic and Baltic diets. Saturated fat is an important determinant of plasma total and low density lipoprotein (LDL)-cholesterol concentrations, and a causal relationship between high LDL-cholesterol and atherosclerotic cardiovascular disease has consistently been documented. The aim of this scoping review is to describe the evidence for the role of milk and dairy products for health-related outcomes as a basis for setting and updating food-based dietary guidelines. Two qualified systematic reviews were included (World Cancer Research Fund and a systematic review for the US Dietary Guidelines Advisory Committee 2020). In addition, systematic reviews published between January 2011 and January 2022 were considered, screened (555 records) and evaluated (159 records) for this review. The systematic reviews suggest that milk or dairy consumption is not associated with increased risk of cardiovascular disease and dyslipidaemia. Current evidence suggests an inverse association with some cardiometabolic risk factors, such as total and LDL-cholesterol, especially regarding fermented dairy products (i.e. yogurt and cheese). There was evidence of an association between intake of dairy products and reduced risk of colorectal cancer. Some studies reported an inverse association between intake of dairy and type 2 diabetes or markers of impaired glucose homeostasis, especially for low-fat dairy, yoghurt, and cheese. Most studies suggest that intake of milk or dairy is not associated with increased risk of cardiovascular risk and some suggestions of inverse association, especially with low-fat products and fermented dairy products, were found with respect to cardiovascular disease, type 2 diabetes, and colorectal cancer. Milk or dairy products are important dietary sources of calcium and iodine, and are fully compatible with a healthy dietary pattern.
... Such an approach has been critiqued because it does not take the level of intake into account and extrapolates results from studies with small exposure ranges to cover larger ranges. In another systematic review, the heterogeneity was too large to be able to perform a meta-analysis (21) . ...
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The association between consumption of dairy products and risk of cardiovascular diseases (CVD) has been inconsistent. There is a lack of studies in populations with high intakes of dairy products. We aimed to examine the association between intake of dairy products and risk of incident major adverse coronary events and stroke in the Swedish Malmö Diet and Cancer cohort study. We included 26,190 participants without prevalent CVD or diabetes. Dietary habits were obtained from a modified diet history and endpoint data were extracted from registers. Over an average of 19 years of follow-up, 3,633 major adverse coronary events cases and 2,643 stroke cases were reported. After adjusting for potential confounders, very high intakes of non-fermented milk (>1000 g/day) compared with low intakes (<200 g/day) were associated with 35% (95% CI 8-69%) higher risk of major adverse coronary events. In contrast, moderate intakes of fermented milk (100-300 g/day) were associated with a lower risk of major adverse coronary events compared with no consumption. Intakes of cheese (only in women) and butter were inversely associated with the risk of major adverse coronary events. We observed no clear associations between any of the dairy products and stroke risk. However, high intake of non-fermented milk was associated with decreased risk of ischemic stroke (P trend=0.05), but increased risk of other stroke types (P trend=0.04). These results highlight the importance of studying different dairy foods separately. Further studies in populations with high dairy consumption are warranted.
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Milk was a source of important nutrients for humans and was especially important for children and adolescents. The modern dairy animal production pattern had contributed to residual sex steroid hormones in milk. When this milk was consumed by humans, these hormones entered the body leading to hormonal disruptions and potentially increasing the risk of various types of cancers. This article reviewed the presence of residual sex steroid hormones in milk, their potential risks on human health, and their possible association with the incidence of breast and prostate cancer. The potential linkage between dairy consumption and these cancers were described in detail. The hormones present in dairy products could affect the development and progression of these types of cancer. Sex steroid hormones could interact with different signaling pathways, influencing carcinogenic cascades that could eventually lead to tumorigenesis. Given these potential health risks, the article suggested appropriate consumption of dairy products. This included being mindful not just of the amount of dairy consumed, but also the types of dairy products selected. More scientific exploration was needed, but this review provided valuable insights for health-conscious consumers and contributed to the ongoing discussion on dietary guidelines and human health.
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Milk is a food enriched in essential components for human health. Especially, in the Mediterranean area, besides cow’s milk, milk from goats, sheep, and donkeys, is largely used. The consumption of animal milk is an important component of the Mediterranean (MED) diet, even if in moderate amounts. Milk is a complete food since it contains proteins, carbohydrates, and fats, as well as micronutrients (minerals and vitamins). Milk-fermented products are largely consumed in the MED diet, such as cheese and yogurt, which are rich in essential metabolites, bioactive compounds, vitamins, minerals, and exopolysaccharides. A large body of evidence suggests that consumption of milk and dairy products does not increase the risk of all-cause mortality, type 2 diabetes, and cardiovascular disease, even if some earlier studies have reported harmful effects associated with their higher consumption. Also, in Japan, despite the lower consumption of milk than in Western countries, intake of bovine milk is associated with healthy effects. The present review describes the effects of the various constituents of animal milk on human health, with special reference to the Mediterranean area and Japan. Experimental data and clinical trials support the ability of milk and dairy products to lower the risk of chronic diseases.
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Food-based dietary guidelines (FBDG) need to be evidence-based. As part of the development of Ethiopian FBDG, we conducted an umbrella review to develop dietary recommendations. Protein-energy malnutrition, deficiencies of vitamin A, zinc, calcium, or folate, cardiovascular diseases (CVD), and type 2 diabetes mellitus (T2DM) were selected as priority. Systematic reviews were eligible if they investigated the impact of foods, food groups, diet, or dietary patterns on priority diseases. After a search, 1513 articles were identified in PubMed, SCOPUS, and Google Scholar published from January 2014 to December 2021. The results showed that 19 out of 164 systematic reviews reported the impact of diet on protein-energy malnutrition or micronutrient deficiencies. Daily 30-90g whole grain consumption reduces the risk of CVD and T2DM. Pulses improve protein status, and consuming 50-150g/day is associated with a reduced incidence of CVD and T2DM. Nuts are a good source of minerals, and consuming 15-35g/day improves antioxidant status and is inversely associated with CVD risk. A daily intake of 200-300 ml of milk and dairy foods is a good source of calcium and contributes to bone mineral density. Limiting processed meat intake to less than 50g/day reduces CVD risk. Fruits and vegetables are good sources of vitamins A and C. CVD and T2DM risks are reduced by consuming 200-300g of vegetables plus fruits daily. Daily sugar consumption should be below 10% of total energy to lower the risk of obesity, CVD, and T2DM. Plant-based fat has favorable nutrient profiles and modest saturated fat content. The association of saturated fatty acids with CVD and T2DM is inconclusive, but intake should be limited because of the LDL-cholesterol-raising effect. Plant-based diets lower the risk of CVD and T2DM but reduce micronutrient bioavailability. The review concludes with nine key dietary recommendations proposed to be implemented in the Ethiopian FBDG.
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