Milk contributes with saturated fat, but randomized controlled trials (RCT) on the effects of dairy on the risk of type 2 diabetes (T2D) where dairy is given as whole foods are scarce. The objective of our study was to investigate the long-term effects of semi-skimmed milk on insulin sensitivity and further to compare milk with sugar-sweetened soft drinks (SSSD).
A secondary analysis of a 6-month RCT with 60 overweight and obese subjects randomly assigned to 1 L/d of either milk (1.5 g fat/100 mL), SSSD, non-calorie soft drink (NCSD), or water was conducted. Insulin sensitivity was evaluated by oral glucose tolerance test (OGTT) and plasma free fatty acids. Second, fasting blood lipids, blood pressure, and concentration of plasminogen activator inhibitor-1 were assessed.
There were no differences between milk, SSSD, NCSD, and water on insulin sensitivity assessed by OGTT (Matsuda Index, fasting, and area under the curve glucose, insulin and homeostasis model assessment values). SSSD increased total cholesterol compared to NCSD (P = 0.007), and triacylglycerol compared to NCSD and water (P = 0.045 and 0.045, respectively). None of the other parameters differed significantly between the groups.
In conclusion, there were no differences in effect between intake of milk, SSSD, NCSD, and water (1 L/d) for 6-month on risk markers of T2D in overweight and obese adults. As a secondary analysis, these results need confirmation in future studies.
Type 2 diabetes (T2D) is on the rise and currently accounts for the majority of cases of diabetes worldwide . Keeping a healthy diet can prevent or delay the onset of T2D . Today, dietary guidelines recommend intake of low-fat dairy products (milk<0.5% fat) because of the high content of saturated fatty acids (SFAs), which is known to increase low-density lipoprotein (LDL) cholesterol. However, meta-analyses of observational studies indicate that intake of dairy is not associated with increased risk of cardiovascular disease (CVD) [2, 3] and point to an inverse association between overall dairy intake and T2D [4,5,6]. Milk constitutes a considerable part of dairy consumption, but only few studies have exclusively examined the effect of milk intake on insulin and glucose, and results have been inconclusive. Two studies of 1 year and 6 weeks, respectively, found no effect on fasting insulin and glucose comparing semi-skimmed milk to skimmed milk or to a non-dairy diet [7, 8]; one study reported a significant, unbeneficial increase in fasting insulin with milk compared to a non-dairy diet after 2 weeks , and another found a significant, unbeneficial increase in glucose concentration in healthy subjects with milk compared to a low-dairy diet after 12 weeks . Sugar-sweetened soft drinks (SSSD) are a popular but questionable alternative to milk. Thus, research show that SSSD can be associated with overweight, T2D, and the metabolic syndrome [11,12,13]. Additionally, we reported in the primary study that SSSD increased ectopic fat accumulation and elevated concentration of uric acid in overweight and obese subjects [14, 15]. A comparison between milk and the somewhat controversial beverages SSSD and artificially sweetened non-caloric soft drinks (NCSD) are highly applicable to everyday choices for the normal population. The aim of this randomized controlled trial (RCT) was therefore to compare the effect of 1 L/d of semi-skimmed milk (MILK) (1.5 g fat/100 mL) with SSSD and NCSD on insulin sensitivity after 6 months of intake, measured by a 2-h oral glucose tolerance test (OGTT), and concentration of free fatty acids (FFA). The 2-h OGTT is a valid and recognized method to evaluate whole-body glucose tolerance and insulin sensitivity [16, 17]. Water (WATER) was included as a non-caloric control. Second, risk markers of CVD; fasting lipids, plasminogen activator inhibitor-1 (PAI-1), and blood pressure were reported. We hypothesized that consumption of MILK would favorably affect insulin sensitivity and risk markers of CVD in overweight and obese subjects compared with isocaloric amounts of SSSD, NCSD, and WATER.
Materials and methods
Sixty healthy, non-diabetic subjects were recruited from two study sites at Aarhus University Hospital and University of Copenhagen. A total of 90 individuals were assessed for eligibility, 73 were recruited, and 13 (all women) dropped out after randomization (Fig. 1). The primary study was described in detail elsewhere [14, 15]; however, with fewer participants included (47). Due to logistical problems in one of the centers (pregnancy and illness) the remaining 13 participants (9 women and 4 men) were included later. The following end points included in the present study have therefore previously been published with fewer participants; fasting glucose, insulin, blood lipids, and blood pressure . The most important advantage of this study was the inclusion of OGTT and plasma concentration of FFA and PAI-1 enabling us to study the effect of MILK compared to SSSD on insulin sensitivity, not reported in the primary study. Thus, the outcome was secondary and considered explorative, as no pre-study power calculations were performed. Inclusion criteria were body mass index (BMI) (26–40 in kg/m2) and age (20–50 years). Exclusion criteria were as follows: diabetes, hypertension (>160/100 mmHg), medication affecting either blood lipids, blood glucose or body weight, smoking, pregnancy or breastfeeding, allergies to milk or suffering from phenylketonuria, and excessive physical activity (>10 h/week). All subjects gave their informed consent in writing. The study was done in agreement with the Helsinki Declaration and approved by the Ethics Committee of Middle Jutland, Denmark.
The composition of the test beverages are shown in Table 1. Using block randomization, subjects were allocated to consume either 1 of 4 test beverages for 6 months: semi-skimmed milk (1.5%), MILK (Arla Foods, Denmark), sucrose-sweetened regular cola (50% glucose and 50% fructose), SSSD and aspartame-sweetened diet cola, NCSD (Coca Cola, Denmark) or still mineral water, WATER (Aqua d’or, Brande, Denmark). The study was not blinded due to the nature of the intervention. All test beverages were free of charge and subjects were instructed to consume 1 L/day and allowed to drink water, coffee, tea, and their regular amount of alcohol. Test beverages were handed out 2–3 times/month from the research center and all subjects were instructed to bring back empty bottles/cartons for monitoring and compliance. The lifestyle changes concerning diet and physical activity were monitored at baseline and end of the intervention using a 7-day weighed dietary record (Dankost Pro dietary assessment software (Dankost)) and a validated questionnaire about physical activity .
Subjects consumed a standardized evening meal and fasted overnight. The following morning blood samples were collected (at 0800 hours) and a 2-h OGTT was performed. Blood was collected at 0, 30, 60, and 120 min but for insulin the concentration at 30 min was not measured. The subjects were instructed to refrain from medicine, alcohol, and vigorous exercise for 24 h before blood sampling. Total and high-density lipoprotein (HDL) cholesterol, triacylglycerol, and glucose were analyzed using routine laboratory methods at the hospital (Department of Clinical Biochemistry, Aarhus University Hospital). LDL cholesterol was calculated by the Friedewald equation. Commercially available kits were used to assess insulin (Human Insulin ELISA; DAKO, Glostrup, Denmark). FFAs were assessed by using an enzymatic colorimetric method assay (Wako Diagnostics-NEFA (Free Fatty Acid). The same laboratory (Department of Clinical Biochemistry, Aarhus University Hospital) carried out all analyses. Blood samples for the remaining 13 study subjects not included in the primary study  were analyzed in 2015 using the exact same routines and methods. FFA and PAI-1 were not analyzed for the primary study, thus analyses for all 60 subjects were done in 2015. Blood pressure was recorded with a digital blood pressure apparatus (Colin Press-Mate) after a 10 min rest. To evaluate insulin sensitivity, the Matsuda Index was calculated including values for glucose and insulin at all the time points during the OGTT and integrated in the following formula : 10,000/√((fasting plasma glucose × fasting plasma insulin) × (mean OGTT glucose × mean OGTT insulin)). In addition, insulin resistance was evaluated by using HOMA with the following formula : fasting serum insulin (µU/mL) × fasting plasma glucose (mmol/L)/22.5. Body composition was determined by DXA (Hologic 2000/W QDR scanner; Hologic Inc) before and after intervention with determination of fat mass (FM) and fat-free mass. The DXA output was generated with default settings of the Hologic software version 12.6.1.
In this secondary analysis, the effects of four beverages on insulin and glucose evaluated by OGTT at baseline and after 6 months were assessed by using a linear mixed analysis of covariance (ANCOVA) model including interaction between time and treatment to assess if time modified the effect of the beverage groups during the time of the 2-h OGTT. An approximate F-test was used to evaluate the interaction between time and treatment and if non-significant another approximate F-test was used to evaluate if there was a time-independent treatment effect. Random effects were included to account for between-subject variation and to account for year of analysis of blood samples (2011/2015). The time course of the estimated treatment effect for all four beverages was shown graphically with the corresponding standard errors. Other outcome variables were analyzed using an ANCOVA model including the treatment. The treatment effect was evaluated by means of an F-test. To adjust for differences between beverages and to take biological variation into account, baseline values were included as well as covariates; age, gender, baseline BMI, and change in FM (kg). All models were also adjusted for year of analysis of blood samples (2011/2015) besides models for blood pressure, PAI-1, and FFA (all 60 analyzed at the same time). For dietary records and anthropometric outcomes, statistical differences were also analyzed using ANCOVA model with baseline and gender (only anthropometric) as covariates. If a model showed treatment effect, pairwise comparisons between the four beverages were subsequently done with Tukey method for multiple comparisons. Treatment differences were reported in terms of unadjusted mean levels with corresponding standard errors. All models were validated by graphical assessment of normal quantile plots and residual vs. fitted plots. When departures were detected, the variables were transformed using the logarithm transformation. We tested for variance homogeneity and the test showed similar variance. A two-tailed P-value < 0.05 was considered significant. The statistical software R version 3.1.3 2015 was used for all statistical evaluations.
Of the 73 randomly assigned subjects, 60 completed the 6 months intervention. Five subjects in the SSSD group, four subjects in the NCSD group, four subjects in the WATER group, and none in the MILK group dropped out (all women). Baseline characteristics of the 60 subjects who completed the study are listed in Tables 2 and 3. Results showed no difference between the four intervention groups; however the distribution of gender was unequal and the models were adjusted accordingly. Anthropometric measures and body composition pre-intervention and post-intervention are listed in Table 2. No significant differences were observed after 6 months.
Insulin and glucose changes
Analysis of the OGTT measured before and after the intervention showed no significant time× treatment effect or treatment effect during the 2 h test for glucose (P = 0.601 and 0.835, respectively) or insulin (P = 0.349 and 0.552, respectively) (Fig. 2a, b). Calculated Matsuda Index and AUC for glucose and insulin based on OGTT data, fasting glucose and insulin, as well as calculated HOMA values based on fasting and AUC for glucose and insulin are all listed in Table 3. In line with the OGTT test results, there were no differences between the groups.
Results from fasting blood lipid concentrations measured after 6 months intervention are listed in Table 3. The analysis showed significant differences between the groups for total cholesterol and triacylglycerol (P = 0.01 and 0.02, respectively). For total cholesterol, the pairwise comparisons showed that SSSD was statistically higher compared to NCSD (P = 0.007), whereas there was a tendency for total cholesterol to be lower after NCSD compared to MILK and WATER (P = 0.089 and 0.074, respectively). For triacylglycerol, the pairwise comparisons showed a significantly higher concentration with SSSD compared to NCSD and WATER (P = 0.045 and 0.045, respectively). For LDL, HDL, and total:HDL cholesterol, there were no differences between the four beverage groups after 6 months.
Blood pressure, PAI-1, and FFA
Results from the blood pressure measurements and concentration of PAI-1 and FFA after 6 months intervention are listed in Table 3. There were no differences between the four beverage groups.
Results from the 7-day weighed dietary records before and during the intervention are listed in Table 4. No differences were observed in energy intake between the beverage groups. Overall, the intake of macronutrients followed the pattern expected with the different beverages. However, the intake of fat (percentage of fat) was significantly higher with WATER compared to MILK and SSSD (P < 0.05 and P < 0.01, respectively) but not compared to NCSD. When fat intake was calculated in grams, there were no differences between the beverage groups. Calcium intake was significantly higher with MILK compared to all other groups before intervention and during intervention (P = 0.01 and P < 0.001, respectively). A student's t test within the MILK beverage group showed a significantly higher calcium intake after 6 months compared to before (t-test: P < 0.001).
In the present study, we observed that 1 L/d of semi-skimmed milk (MILK) did not differ from beverages such as SSSD, NCSD, or WATER in effects on risk markers of T2D evaluated by OGTT in overweight and obese men and women after 6 months’ intake. Moreover, the beverages did not differ in effects on plasma concentrations of PAI-1, FFA, or blood lipids. Unexpectedly, SSSD showed no adverse effect on insulin sensitivity; however, as expected SSSD significantly increased plasma concentration of total cholesterol and triacylglycerol as compared to NCSD and plasma triacylglycerol concentration as compared to WATER. The fact that the study subjects remained weight-stable throughout the intervention indicated that the results were independent of changes in body weight. In comparison, Maki et al. found a beneficial effect of dairy in relation to insulin sensitivity in a 2 × 6 week crossover study comparing dairy (474 mL/d 2% milk and 170 g/d low-fat yoghurt) with sugar-sweetened products (710 mL/d non-diet soda and 108 g/d non-dairy pudding) in 33 adults at risk of T2D. The study found less favorable values for insulin sensitivity (HOMA) and a liquid meal tolerance test during the sugar-sweetened product period compared to dairy . Although, the amount of sugar-sweetened beverage intake was similar to the present study, the dairy was a mix of milk and yoghurt, and it was therefore not possible to differentiate the effect. Recent large meta-analysis of subtypes of dairy products reported no association between milk intake and risk of T2D [4, 5] and a Mendelian randomization study also confirmed these results . Overall, current evidence therefore does not confirm a specific effect of milk on insulin sensitivity in healthy overweight and obese subjects.
Evidence from observational studies support a strong association between intake of SSSD and risk of T2D, independent of adiposity . In the primary paper, results showed that SSSD increased ectopic fat storage compared to the other beverages . Ectopic fat accumulation by increased fructose metabolism in the liver is believed to be one biological mechanism linking SSSD to increased risk of T2D ; however, this did not reflect in risk markers of T2D after 6-month SSSD intake.
Results showed no difference between MILK and SSSD in blood lipids. This is in line with the study by Maki et al., who found no difference in lipid concentration between the diets, except a decrease (4.2%) in HDL cholesterol during the sugar-sweetened product diet compared to dairy. SSSD increased plasma triacylglycerol concentrations compared to NCSD and WATER, and total cholesterol concentrations compared to NCSD. This implies that MILK is beneficial compared to SSSD regarding risk of CVD. Overall, the unbeneficial effects of SSSD on CVD is well-established [22,23,24]. In the present study, we showed no difference between the beverage groups in blood pressure. RCTs have shown a beneficial effect of milk intake on blood pressure; however other studies along with the present study found no decrease in blood pressure [25, 26].
The dietary records showed that the mean difference in SFAs corresponded to the difference expected (~10 g/d) based on nutritional content of the beverages for SSSD and NCSD but not for WATER. The lack of difference between WATER and MILK in SFAs could be explained by an overall high-fat intake (38.5%) with WATER compared to the other beverage groups.
The strengths of the present RCT were the long duration including the thorough estimation of risk of T2D with an OGTT. It is, however, a limitation that as a secondary analysis, no power calculation was performed for the OGTT. The free-living design of the study was a limitation due to potential confounding by other dietary and lifestyle factors. Moreover, the study was not blinded because the appearance of the test beverages could not be concealed.
In conclusion, the results of the present study showed no difference between 6 months' intake of MILK, SSSD, NCSD, and WATER in effect on risk markers of T2D in overweight and obese adults. As a secondary analysis, these results need confirmation in future studies.
No reprints available
The trial is registered at: www.clinicaltrial.gov (NCT00777647)
We thank Christian Ritz for support with the statistical analyses. We gratefully acknowledge the work of Maria Maersk and Anita Belza, who conducted the intervention and helped planning the study. The authors’ responsibilities were following—S.E.: performed the statistical analysis, wrote the manuscript with primary responsibility for final content; J.M.B.: responsible for the analysis of PAI-1 and FFA; T.T. and A.R.: initiated the current analyses and supplied valuable knowledge and scientific consultation during the process; A.A. and B.R.: took part in the funding and design; all authors: read and approved the final manuscript. A.A. has received research grants from Arla Foods, Denmark; The Danish Dairy Research Foundation; Global Dairy Platform, USA; and the Danish Agriculture and Food Foundation. T.T. has received research grants from Arla Foods, Denmark; The Danish Dairy Research Foundation; and the Dairy Institute, Rosemont, IL. A.R. has received research funding from the Dairy Research Industry, Rosemont, IL, and The Danish Agriculture and Food Council.