Dairy consumption and the Metabolic Syndrome: a Meta-Analysis

In light of more recent data indicating that saturated fats from dairy products are not associated with incident cardiovascular disease, it is interesting to speculate whether dairy consumption is linked to metabolic disorders at all. The latest meta-analysis (to my knowlegde) on this subject appeared last month in Scientific Reports and looked at the relationship between dairy products consumed and the Metabolic Syndrome (MetS). 

The meta-analysis (pooled analysis of multiple studies) which included 23 cross-sectional/prospective cohort studies with ~ 30,000 participants suggests that "higher dairy consumption significantly reduced MetS by 17% in the crosssectional/case-control studies (odds ratio=0.83, 95% confidence interval [CI], 0.73–0.94), and by 14% (relative risk [RR]=0.86, 95% CI, 0.79–0.92) in cohort studies." The researchers calculated that for each additional dairy product consumed, the risk of MetS declines by 6%. This finding was robust, even after adjustment for other lifestyle-related factors such as physical activity, smoking and alcohol consumption which helps to rule out that dairy products are just marker of a healthy diet (frequently observed). Moreover, prospective investigation of dietary intakes and incident MetS in participants argue against reverse-causation, i.e. subjects with MetS are told to reduce saturated fat intake, thus they begin to omit dairy products such as cheese etc..

Of course, several limitations remain intact such as the issue with residual confounding (confounders that are not adjusted for) and the notoriously criticized assessment of dietary intakes. Depending on your view of how stringent scientific methodology should be, you will either accept this piece of research or dismiss it completely.

(A) cross- sectional and case-control studies; (B) prospective cohort studies; M, male; F, female. OR, odds ration; CI, confidence interval. [from publication]

Chen, G.-C., Szeto, I.M.Y., Chen, L.-H., Han, S.-F., Li, Y.-J., van Hekezen, R., and Qin, L.-Q. (2015). Dairy products consumption and metabolic syndrome in adults: systematic review and meta-analysis of observational studies. Sci. Rep. 5, 14606. 

Frequently overlooked: Why dietary restriction may not be universal

One of the most robust interventions for life-extension known to us is dietary restriction (DR), usually defined as a 20-40% reduction of ingested calories compared to the ad-libitum fed scenario. DR has been shown to work in organisms ranging from yeast to rodents and is central to longevity research.

However, DR studies performed on non-human primates were rather disappointing, casting doubt whether this finding would be ever translatable to humans. Prof. Thomas Kirkwood, a well known gerontologist, pointed this out at the recently held FENS 2015 Nutrition Conference in Berlin. He argued that DR likely redistributes our body's ressources by shutting down reproductive functions in favour of somatic maintenance. If this is true, then certainly, DR would loose its attractiveness to most of its present proponents.

In addition, Prof. Kirkwood highlighted findings from a 2009 paper published by Liao et al. in the journal Aging Cell that the life-extending property of DR is not even universal within one species, namely that of laboratory inbred mice. Of the 41 strains (of both sexes) tested, only 5% of male mice strains and 21% of female mice strains showed a significant lifespan extension. Contrarily, DR shortened lifespan in approximately one fourth of all male and female strains! Their findings render DR's applicability to humans questionable, to say the least. On a more positive note, the comparison of different strains of a species upon the same treatment or intervention is a very interesting tool to delineate the genetic drivers between responsiveness and biological inertia. In fact, longevity related genes were identified as a result of this approach, advancing longevity research further, albeit unexpectedly.

Strain variation in mean lifespan of ILSXISS recombinant inbred (RI) mice under ad libitum (AL) and dietary restriction (DR) diets. Lifespans were typically obtained from 10 AL and 10 DR mice from each strain (5 males & 5 females per treatment group).The mean lifespans in the upper two panels are shown for each strain [AL (□) and DR (■)], ranked in ascending order according to the AL means (A: males, 41 strains; B: females, 39 strains). The lower two panels illustrate the deviation (positive and negative) of the mean DR lifespan from the mean AL for the same strains, ranked from the strain with the greatest increase in lifespan under DR to the strain with the greatest decrease (C: males; D: females). Error bars represent SEM. * p < 0.05, ** p < 0.01, *** p < 0.001 by t-test (no experiment-wise Bonferroni correction). [from publication]

Liao, C.-Y., Rikke, B. A., Johnson, T. E., Diaz, V. and Nelson, J. F. (2010), Genetic variation in the murine lifespan response to dietary restriction: from life extension to life shortening. Aging Cell, 9: 92–95. doi: 10.1111/j.1474-9726.2009.00533.x

Pollinators in decline: Is our nutritional health at stake?

The claim that global food availability and diversity are at risk of becoming relicts of the past, once pollinator populations decline drastically, has been made multiple times throughout recent years and has never failed to co-create doomsday-like media coverage. However, this claim has been seldomly addressed empirically: a necessity in telling fact from fiction.

Fortunately, researchers from the Gund Institute for Ecological Economics at the University of Vermont, USA, were asking themselves the exact same question. By combining data on food consumption, including nutrient composition and data on pollination requirements of crop plants, they evaluated the associated nutritional health risks of different pollinator scenarios. Since pollinator-dependent effects on nutritional deficiencies may be more pronounced in developing countries, where food consumption is less flexible, their analysis set a spotlight on four countries of this category: Bangladesh, Mozambique, Uganda and Zambia. In addition, results were only presented for children aged 1-3 years old as they are likely to represent the most vulnerable group to changes in food availability and diversity.

They found out that of the nutrients examined (Vit. A, zinc, iron, folate, calcium) only Vitamin A intake depended strongly on pollinators as illustrated below (Fig 1.). Vegetables (green) and fruits (red) contributed most to the Vitamin A intake (more precisely pre-Vitamin A). The darker the respective colour, the higher the extent to which pollinators contributed to this specific food subgroup within the food group. For instance, in Uganda more than 25% of total Vitamin A intake depends heavily on vegetables which require pollination to a very high degree (95%).

Fig 1. Average proportion of dietary intake of vitamin A from different sources for children 1 to 3 years old.

Numbers in the slices of the legend indicate the percent yield due to pollinators. Darker slices are foods that depend heavily on pollinators. “Other” refers to oils, flavorings, drinks, candy, honey, and other items that do not fit into other food groups [from publication]

Next, they investigated whether a switch of scenarios from "full pollination" to "no pollinators" would result in any changes regarding the proportion of the population (1-3 y olds) which is at risk of nutritional deficiencies (Tab 1). Indeed, 0-56% of populations would be newly at risk of nutritional deficiencies - an alarming prediction. However, the underlying analysis also showed that generalizations are impossible to make. For example, in Bangladesh only a small percentage of children would become newly at risk of developing Vitamin A deficiency, but this is not because pollination is an insignificant contributor to Vitamin A intake - it is because most individuals in Bangladesh are already malnourished as the researchers state, shrinking the total numbers of newly deficient children.

Tab 1. Differences in proportion of population at risk of nutrient deficiency between the ‘no pollinators’ and ‘full pollination’ scenarios. [from publication]

Despite these obstacles to a clear-cut interpretation of the data, the investigators summarize their findings as following. Firstly, the loss of pollinators are likely to affect the nutritional health of populations which depend heavily on vegetables and fruits (in contrast to dairy and grain). Secondly, populations which are already severely malnourished or obtain nutrient intakes well above the requirements won't be disproportionately affected. Thirdly, inflexible populations regarding the inability to substitute for the loss of pollination-related foods will be at higher risk. And lastly, populations without any access to fortification or targeted nutrition programs may suffer from loss of pollinators.

Ellis AM, Myers SS, Ricketts TH (2015) Do Pollinators Contribute to Nutritional Health? PLoS ONE 10(1): e114805. doi:10.1371/journal.pone.0114805

Navigating through Nutritional Landscapes

In contrast to classical hypothesis testing which begins with the formulation of a testable research question, more and more researchers, including nutrition scientists, have been taken a different approach. Given the vast amounts of nutrition and food data being available, data-driven analysis methods are becoming increasingly popular in this field.

In March of this year (2015), a paper was published¹, presenting a comprehensive view of interrelationships between raw foods and nutrients in a network-pattern fashion. The researchers (interestingly with the majority of them having a physics background) generated a food-to-food network of 654 food items which links foods of similar nutritional composition resulting in the formation of hierarchical clusters of food groups (Fig.1). At the highest level two groups can be distinguished, the animal-derived foods group (left) and the plant-derived foods group (right). The underlying reason for this clustering pattern is mainly attributable to the reciprocal contents of protein and carbohydrates in animal and plant products.

Apart from being a simple visualization of already existing nutritional knowledge, a few things stand out. Most importantly, the researchers introduced the term 'nutritional fitness' to identify nutritionally favorable foods. As you may imagine for physicists doing nutrition research, it's a quite technical term. Nutritional fitness measures the frequency by which a single food item is part of an irreducible food set of 4 food items that meets, but do not exceed the daily nutrient demand of an average person. The more often a food item pops up in one of those irreducible food sets after assessing all possible combinations of foods, the higher its nutritional fitness. Almonds, chia seeds, cherimoya (exotic fruit), oecean perch are all foods of high nutritional fitness as indicated by the size of each node in the figure below. In encourage you to read the original article to understand why this is! ;)

Fig 1. The Food-Food Network.

(A–C) Large-scale to small-scale overviews of the network. Each node represents a food, and nodes are connected through links that reflect the similarities between the nutrient contents of foods. In (A–C), each node is colored according to the food category. The size of each node corresponds to the nutritional fitness (NF) of the food. [from publication]

In a very similar manner, the researchers constructed a nutrient-to-nutrient network illustrating positive as well as negative correlations between the abundance of single nutrients across foods (Fig 2.). As was already evident from the food-to-food network protein and carbohydrate contents are inversely correlated. In addition, carbohydrates are also inversely correlated with total lipid content. I am sure you can find correlations that you are particularly interested in! For instance, I am baffled over the positive connection between betaine and trans fats. Betaine is mainly found in beets, other vegetables, cereals and pseudocereals such as quinoa. Trans fats are commonly associated with processed foods, however, this study only involved raw foods. To conclude, networks such as these are very interesting to look at. At first glance, they may just appear to represent common knowledge, but a few moments later, you'll be intrigued by them.

Fig 2. The Nutrient-Nutrient Network.

Each node represents a nutrient, and the nodes are connected through correlations between the abundances of nutrients across all foods. Each node is colored according to the nutrient type. The shape of each node indicates the hierarchical or ‘taxonomic’ level of a nutrient, from ‘Highest’ (a general class of nutrients) to ‘Lowest’ (a specific nutrient). The color and thickness of each link correspond to the sign and magnitude of the correlation, respectively.

1 Citation: Kim S, Sung J, Foo M, Jin Y-S, Kim P-J (2015) Uncovering the Nutritional Landscape of Food. PLoS ONE 10(3): e0118697. doi:10.1371/journal.pone.0118697

Dietary patterns on a global scale

We know that a country's food consumption changes in parallel to its degree of industrialization. Moreover, both food consumption and the state of economic developement determine how much green house gases are being emitted by a country. For instance, higher consumption of animal products in industrialized countries are linked to higher green house gas emissions.

In an attempt to elucidate global dietary patterns and their impact on agriculture related green house gas emissions, researchers from the Potsdam Institute for Climate Impact Research and the Department of Geo- and Environmental Sciences of the University of Potsdam impressively revealed transition pathways along the industrialization axis. Before they could do this, they characterized dietary patterns across the globe and came up with 16 dietary patterns:

Those are categorized according to their caloric value into low, moderate and high calorie diets with <2100 kcal per person per year, 2100-2400 kcal per person per year and >2800 kcal per person per year, respectively. The investigators found out that, among many interesting things, that certain food items were more frequently associated with higher degrees of industrialization as measured by the human developement index. Meaning, industrialized countries can be distinguished by their higher consumption of food in general, animal products, sweeteners, vegetable oils and vegetables.

Global dietary transition pathways. Arrows indicate frequency of  undergone transition from one type of diet to another based on food consumption data of  > 200 countries between the years 1961 and 2007.

Coming back to the transition data, a few important observations can be made. As civilizations "progress" (that is the forward direction of arrows), food consumption and energy intake increase. In parallel, dietary patterns shift towards animal products and vegetable oils with a concomitant decrease, for instance, in the consumption of starchy roots (with low calorie diets). Likewise, industrialization is associated with increasingly higher agricultural green house gas emissions (low emission= blue to green, high emission=yellow-orange-red). Transition pathways from the lower (blue) end of the spectrum to the higher (red) end of the spectrum are heavily favored (tickness of arrow) which means that societies most frequently move towards higher carbon dioxide emissions.

In summary, although high food and energy consumption are associated with higher measures of human developement which should be our aim for as many countries as possible; this shift comes with a considerable burden on our environment as can be seen by higher green house gas emission of industrialized nations. The consumption of animal products certainly contribute to this unfavorable shift.


Pradhan P, Reusser DE, Kropp JP (2013) Embodied Greenhouse Gas Emissions in Diets. PLoS ONE 8(5): e62228. doi:10.1371/journal.pone.0062228

Blog posts written in the english language are soon to come

I decided to leave the path of convenience - that is the German language - in order to reach out to many more people. Stay tuned for my short but regular postings about nutrition, science and beyond!

Thomas

Was macht ein gutes Frühstück aus?

Eine recht amüsante und eigenwillige Vorstellung darüber, was ein gutes Frühstück ausmacht, ist der PR-Abteilung von Knoppers entsprungen. Bekanntermaßen wird die kleine Waffelschnitte mit dem Slogan umworben eine hervorragende Wahl für das schnelle Frühstückchen zwischendurch zu sein. Anders sah das offenbar ein kritischer Kunde, der sich auf diese vermeintliche Anmaßung hin prompt an die von der Verbraucherzentrale des Bundes und des Bundeslandes Hessen betriebene Plattform lebensmittelklarheit gewandt hatte, um seinen Ärger um diese Täuschung Luft zu machent. Im Klartext liest sich der Beschwerdetext wie folgt:

Customized Vitamins - What they don't tell you

In case you have never heard of it before: Customized vitamins are promoted as the opposite of what you purchase when you usually put a box of vitamins into your shopping cart. They are supposed to be well-adjusted to your personal lifestyle and eating patterns and are meant only to provide the amounts of vitamins you really need to reach the requirements. In this light, the incentives for potential customers are clear: you get what you need and you stop wasting money on what you actually don't need. Most of these corporations established themselves only a few years ago and are often led by young enthusiastic entrepreneurs with high affinity to social media. From what we have heard about it so far, nothing seems to warrant a reference on my blog until you ask yourself the question, how do they know what YOU need? That's when my skeptic's alarm clock went off. Loyal readers of my blog will notice. BEWARE, NOT AGAIN!