No evidence of dairy and heart disease link

New research has once again confirmed after systematically analyzing 17 studies that there is simply no evidence to substantiate claims of a link between dairy and higher risk of cardiovascular disease or death.

The evidence, in fact, shows just the opposite—drinking milk slightly reduces the risk of coronary heart disease (1). In addition, multiple studies show that milk and dairy proteins (whey and casein) may actually protect the heart by helping to maintain lower blood pressure, lower blood sugar, and lead to reduced bodyweight (2-4).

The renowned, epidemiologic and nutrition researcher Walter Willet, Ph.D., and his group at Harvard, conducted this huge analysis by looking at various types of dairy intake, ranging from milk intake to total high-fat dairy products and total low-fat dairy products and correlating to risk of cardiovascular disease (CVD), coronary heart disease (CHD), stroke and all-cause mortality. This study was a meta-analysis of many prospective cohort studies in healthy men and women (4).

Although it's always a challenging task to summarize published studies' data on food intake, Willett’s group is easily recognized as having the epidemiological expertise of doing such an analysis. Results from the group's careful analysis show:

• a statistically significant inverse association between milk intake and cardiovascular disease.
• no significant relationship between CHD, stroke, and all-cause mortality (including cancer) and total dairy of all types (high-fat, low-fat)

When they examined data on total dairy products or total high-fat dairy intake there was still no impact on CHD, but these results were based on a much smaller number of studies.

A notable strength of this methodology was the use of an advanced statistical approach for trend estimation of summarized dose-response data. This method provides uniform analysis of different studies, exposure categories and range of intakes; as well as greater power using full spectrum continuous exposure data.

These data, published in the January issue of the Journal of American Clinical Nutrition, clearly show that milk intake does not lead to cardiovascular, heart, stroke or any mortality (including cancer) and may even be beneficial in reducing cardiovascular diseases.

Several mechanisms have been discussed over the years concerning the beneficial effects of low-fat dairy intake on lowering blood pressure. For example, data from the famous DASH eating plan show systolic blood pressure reduction with a healthy diet. Inclusion of low-fat dairy products or dairy proteins showed a potential anti-hypertension effect possibly due to the natural mineral content found in dairy, particularly phosphorous.

These types of studies do not show cause and effect, but do, in fact, show that there is not an increased risk of heart disease, cardiovascular disease, stroke or all-cause mortality by drinking milk. One can only hypothesize why these associations exist—a clear possibility is that milk drinkers are taking extra dietary care by consuming natural products, perhaps in place of sugar-laden soft drinks. Diet quality is the key in reducing risk of chronic disease.

CVD is the main cause of death in the Western world claiming 17 million lives each year. Since saturated fat intake is associated with heart disease, dairy foods have often been blamed for contributing to CVD; however, the science community has yet to agree because of many conflicting studies. Although most epidemiological studies have failed to show an effect of dairy on CVD, a few have shown a positive correlation.

Likely confusion arises when results from dissimilar studies get lumped together in hopes of finding the "answer." However, combining evidence from epidemiological, case-control, prospective study designs with different age groups, genders, countries and numbers of subjects may easily explain the mixed results.

References

1. Soedamah-Authu SS, Ding EL, Al-Delaimy WK, Hu FB, Engberink MF, Willet WC and Geleijnse JM. Milk and dairy consumption and incidence of cardiovascular disease and all-cause mortality: dose-response meta-analysis of prospective cohort studies. Am J Clin Nutr 2011; 93: 158-71.
2. Petersen BL, Ward LS, Bastian ED, Jenkins AL, Campbell J, Vuksan V. A whey protein supplement decreases post-prandial glycemia. Nutr J 2009;8:47.
3. Frestedt JL, Zenk JL, Kuskowski MA, Ward LS, Bastian ED. A whey-protein supplement increases fat loss and spares lean muscle in obese subjects: a randomized human clinical study. Nutr Metab (Lond) 2008;5:8.
4. Fluegel SM, Shultz TD, Powers JR, Clark S, et al. Whey beverages decrease blood pressure in prehypertensive and hypertensive young men and women. International Dairy Journal; 1010; 753-760.

Nutrition and Chronic Disease with Nicola McKeown

Next up at American College of Nutrition conference, we're about to enjoy a talk given on "Nutrition and Chronic Disease: Advantages of a Diet Pattern and Health Outcomes" given by Nicola M. McKeown, Ph.D., of the USDA Human Nutrition Research Center on Aging at Tufts University. 

"Trying to measure dietary exposures is very difficult," sayd McKeown. The nature of nutrition is extremely complex, and she quotes Walter Willet on the complexity (which makes me like her already). "A single nutrient may be confounded by an overall dietary pattern."

Single-nutrient approaches ignore complexity of diets, biological interactions, and there is difficulty to detect small effects and observe health effects of single components. 

How do we research with this complexity? We may be interested in a dietary pattern, a food group, an individual food, single nutrients, and bioactives (a top-down approach). 

Why study dietary patterns? They represent the interactions and cumulative effects of dietary components on disease risk. They capture potential foods and nutrient synergy. They help generate hypotheses about biological mechanisms, and they can translate to dietary pattern recommendations. 

In epidemiology, there are two ways to derive dietary pattern approaches are theoretical (hypothesis-oriented) and empirical (exploratory-oriented). "The data drives the patterns," she says. Most of the time it's based on food frequency questionnaires. The input variables may be frequency, weight, daily percent of energy contribution. 

With a factor analysis, the goal is to identify common factors that explain variance in the dietary data. it's based on correlation/covariance matrix of the food groups. It aggregates specific food groups on the basis of degree of use. 

She then shows examples where various food groups are weighted based on factor loading of top contributing foods. A Western dietary pattern, for example, is higher in meat, processed meat, and butter in comparison to a prudent dietary pattern. 

Cluster analysis (which you may "hear a lot about in the literature") is based on aggregates of individuals into distinct food groups. It's sensitive to extreme outliers so treatment of input variables is important. 

She gives a few examples of cluster analysis, such as: 

Cluster 1: reduced-fat dairy, fruits, and whole-grains. 

Cluster 2: refined grains and sweets.

Cluster 3: Beer (lots of men were in this category).

Cluster 4: Soda (people in this category were found to have higher fasting insulin)

From a research standpoint, there have been a few diets with great interest including the Mediterranean diet and low-carb diet. There have been indexes developed for these two diets as well as the Healthy Eating Index. 

The indexes can be used to create a "diet score," each of which are based on cut-points of various food groups with criteria that determine weight of each food that contribute to the score. [The diet scores look like a handy tool for helping people stay on track.]

The 2005 Dietary Guidelines for Americans Adherence Index (DGAI) are based on food intake recommendations and it penalizes for overconsumption of discretionary energy and energy-dense foods (chips and French fries). They also had a "variety score" when people had various foods in the diet. 

When individuals adhere to the DGAI, they had a lower prevalence of metabolic syndrome. Based on the scoring approach, McKeown says, it's possible for people to get the same score and have different dietary patterns. 

Regarding the Mediterranean dietary pattern, McKeown reminds us that "there is no single Mediterranean diet," but it's based on patterns, so a diet score can be useful for adhering to the dietary pattern. 

When discussing low-carb dietary patterns, they have similar macronutrient composition, but may have different dietary quality. There should be scores indicated depending on the choices of fat -- animal or vegetable. She is careful to note that it's important to consider that when you talk about macronutrients to consider substitutions for foods eliminated. 

She closes by saying that there is subjectivity in defining cut points in indices. Indices may be a good index of diet quality but not of disease risk. High scores are rare, but average scores can be achieved a number of different ways. Eating patterns associate with other health behaviors.