A clip on industrial food production from a new documentary. Pretty stunning stuff.
I’m not exactly sure what inspired Allison Aubrey to report on two research papers from last year as breaking news, but I’m glad she did, and glad her story has gained some legs.
New research suggests we may want to look anew.
Consider the findings of two recent studies that conclude the consumption of whole-fat dairy is linked to reduced body fat.
In one paper, published by Swedish researchers in the Scandinavian Journal of Primary Health Care, middle-aged men who consumed high-fat milk, butter and cream were significantly less likely to become obese over a period of 12 years compared with men who never or rarely ate high-fat dairy.
Yep, that’s right. The butter and whole-milk eaters did better at keeping the pounds off.
“I would say it’s counterintuitive,” says Greg Miller, executive vice president of the National Dairy Council.
The second study, published in the European Journal of Nutrition, is a meta-analysis of 16 observational studies. There has been a hypothesis that high-fat dairy foods contribute to obesity and heart disease risk, but the reviewers concluded that the evidence does not support this hypothesis. In fact, the reviewers found that in most of the studies, high-fat dairy was associated with a lower risk of obesity.
The reason I’m glad, is that this goes to a long running pet peeve of mine. All too often, the conventional wisdom in nutrition is unsupported by the data. Sometimes, it’s in direct contradiction.
When I first started becoming interested in nutrition, I came across a study headed by a Harvard study from 2005 that followed a group of 12,829 US children, aged 9 to 14 years from 1996 through 1999. The purpose of the study was to “assess the associations between milk, calcium from foods and beverages, dairy fat, and weight change over time.” Data was collected by surveys returned by mail. After looking at the data, these were their conclusions:
Children who drank the most milk gained more weight, but the added calories appeared responsible. Contrary to our hypotheses, dietary calcium and skim and 1% milk were associated with weight gain, but dairy fat was not. Drinking large amounts of milk may provide excess energy to some children.
At the time, it seemed interesting and counterintuitive and was duly filed away to some empty dendrites I had lying around. Not long after, in 2006, came news that New York City was removing whole milk from the public school cafeterias in order to combat childhood obesity. Low fat chocolate milk would be allowed, but whole milk would be banished. The report also mentioned that Los Angeles had done the same in 2000. It was reported that some states had made the same change or were considering it.
I had to wonder; had the nutritionist for a school system with 1.1 million students have missed the Harvard study? Was there other research that contradicted the 2005 study? Had anyone bothered to collect any data in Los Angeles to measure the impact of the change made in 2000? In 2006, those answers to those questions weren’t as easy to find for an amateur with a short attention span like myself. I was reduced to stewing on the fact that a very large public health intervention had been made in contradiction of the only research I could find on the issue. A huge pet peeve of mine is the willingness, especially in nutrition to undertake public policy interventions in the absence of any evidence that they will achieve the desired outcome. (I’m looking at you restaurant calorie postings.)
The one other thing I found on the issue at the time, was that hog farmers have been using skim to fatten hogs since your grandfather was in short pants. The observation that skim milk was particularly fattening was borne out by the research at the time. From the Station Bulletin, Oregon State Agricultural College – November 1930 [pdf]:
Skim milk. This is not only the very best supplement for growing pigs, but is of almost equal value for fattening purposes. Though very low in dry-matter content, milk furnishes a complete protein, which fact accounts in a large measure for the excellent returns. Milk renders the ration more palatable, inducing greater consumption and consequently greater daily gains. Also milk is a good source of minerals.
Granted, they weren’t comparing it to whole milk, but still … not a promising observation for Hansel and Gretel.
Sometime in 2011, I did finally follow up and gather all the relevant research I could find. The nearly dozen and a half papers I gathered at the time were nearly an exact match to those that the Kratz paper looked at.
METHODS: We have conducted a systematic literature review of observational studies on the relationship between dairy fat and high-fat dairy foods, obesity, and cardiometabolic disease. We have integrated these findings with data from controlled studies showing effects of several minor dairy fatty acids on adiposity and cardiometabolic risk factors, and data on how bovine feeding practices influence the composition of dairy fat.
RESULTS: In 11 of 16 studies, high-fat dairy intake was inversely associated with measures of adiposity. Studies examining the relationship between high-fat dairy consumption and metabolic health reported either an inverse or no association. Studies investigating the connection between high-fat dairy intake and diabetes or cardiovascular disease incidence were inconsistent. We discuss factors that may have contributed to the variability between studies, including differences in the potential for residual confounding; the types of high-fat dairy foods consumed; and bovine feeding practices (pasture- vs. grain-based) known to influence the composition of dairy fat.
CONCLUSIONS: The observational evidence does not support the hypothesis that dairy fat or high-fat dairy foods contribute to obesity or cardiometabolic risk, and suggests that high-fat dairy consumption within typical dietary patterns is inversely associated with obesity risk. Although not conclusive, these findings may provide a rationale for future research into the bioactive properties of dairy fat and the impact of bovine feeding practices on the health effects of dairy fat.
The literature gathered was from 1999 to 2011. As to my earlier question about what research had been available at the time the New York school district was making the decision to eliminate whole milk from their cafeterias, seven of the studies considered were available at the time. None of them supported the idea that removing whole milk from students diets would be helpful in combatting obesity. The clear majority suggested the opposite.
I had drawn the same conclusions looking at the same literature as Kratz and company did. But, I also wondered about the studies that did show a correlation between dairy fat consumption, adiposity and metabolic health. The paper’s authors noticed the same geographic pattern that I had.
Examining Table 1, it is clear that location has a major inﬂuence on the studies’ outcomes. Of the nine studies that were conducted in Europe, eight found that dairy fat intake
is inversely associated with adiposity. Of the seven that were conducted in the United States, three found an inverse association, while four did not. Three factors stand out as possible explanations for this discrepancy.
The ﬁrst is the high potential for residual and unmeasured confounding in US cohorts. Since the 1980s, there has been a public health campaign in the United States to lower the consumption of SFA-rich foods such as animal fats. As a result, dairy fat is perceived as unhealthy in the United States, and one would expect its consumption to be associated with other behaviors that are perceived as unhealthy. Indeed, Liu et al. reported that US women in the highest quintile of high-fat dairy intake were 62 % more likely to be current smokers than women in the lowest quintile, whereas women in the highest quintile of low-fat dairy intake were 62 % less likely to smoke than the lowest quintile.
Similarly, dietary ﬁber intake was 21 % lower in the highest quintile of high-fat dairy intake compared to the lowest. Comparable trends were reported by Margolis et al., including substantially higher physical activity and income level in the top quintile of low-fat dairy intake, and substantially lower physical activity and income level in the top quintile of high-fat dairy intake . This demonstrates the cultural stigma attached to dairy fat consumption in the United States, and casts doubt upon the ability of observational studies to fully adjust for the unhealthy lifestyle patterns that associate with dairy fat consumption in this environment.
Or as I would put it: Pizza and Cheeseburgers.
So it was unsurprising, when I learned later that week that, “that an astonishing 13% of the U.S. population consumed pizza on any given day”. More disturbing:
For this large population — more than 1 out of 8 Americans — who consumed pizza in a particular day:
- Pizza accounted for 25% (among kids) and 29% (among adults) of daily food energy intake. More than a quarter of all calorie intake was pizza.
- Pizza accounted for 33% (among kids) and 39% (among adults) of daily saturated fat intake. Compared with foods in general, pizza is much heavier in saturated fat.
- Pizza accounted for 33% (among kids) and 38% (among adults) of sodium intake. Compared with foods in general, pizza is much heavier in sodium.
In recent years, USDA’s dairy checkoff program has spent many millions of dollars to increase pizza consumption among U.S. children and adults. Using the federal government’s taxation powers, the checkoff program collects a mandatory assessment of 15 cents on every hundredweight of milk that is sold for use as fluid milk or dairy products. The total mandatory assessment in 2011 was $104 million for fluid milk and $98 million for other dairy products, according to the most recent annual USDA Report to Congress. These expenditures are many times greater than federal spending on promoting fruits and vegetables, whole grains, or any of the other foods for which the Dietary Guidelines recommend increased consumption.
I love it when a plan comes together. But, not always.
The Full-Fat Paradox: Whole Milk May Keep Us Lean
Allison Aubrey | The Salt/NPR | 12 February 2014
High dairy fat intake related to less central obesity: a male cohort study with 12 years’ follow-up.
Holmberg S, Thelin A. | Scandinavian Journal of Primary Heathcare | June 2013
The relationship between high-fat dairy consumption and obesity, cardiovascular, and metabolic disease.
M Kratz, T Baars, S Guyenet | The European Journal of Nutrition | February 2013 | [pdf]
Milk, dairy fat, dietary calcium, and weight gain: a longitudinal study of adolescents.
Berkey CS, Rockett HR, Willett WC, Colditz GA. | Archives of Pediatrics and Adolescent Medicine | June 2005
In New York Schools, Whole Milk Is Cast From the Menu
David Herszenhorn | The New York Times | 2 February 2006
Fattening Pigs for Market [pdf]
Agricultural Experiment Station | Oregon State Agricultural College | Station Bulletin | November 1930
USDA reports on pizza consumption and on dairy checkoff program initiatives to increase pizza demand
Parke Wilde | US Food Policy | 7 February 2014
1. Rachel Laudan: Is the fresh the enemy of good canned food?
2. Bill Marler: Raw Milk is a Risky Elixir
3. Michael Ruhlman and Donna Turner Ruhlman: Vegetable Porn
4. Erin Durkin – Daily News: Mayor de Blasio 5. Supports Ban On Using Food Stamps For Sugary Drinks
5. AP/USA Today: The new face of food stamps: working-age Americans
6. Jenny Hopkinson – Politico: USDA wades into unpaid meals issue – Chipotle at it again – States seek to limit farm surveillance by drones
7. Bettina Elias Seigal – Civil Eats: State of the Tray: Will Recent Improvements in School Food be Rolled Back?
8. Luke Runyon – Harvest Media: USDA predicts low corn prices here to stay
9. Layla Eplett – Food Matters – Scientific American: Seeing The Forest Through The Trees: How Wild Foods May Contribute To Food Security
10. Stephan Guyenet – Whole Health Source: Mindless Eating
It really is a sign of how few meaningful public health interventions are available to the federal government that changes in nutrition labels on food packages are seen as a substantial reform. All the things they are talking about make sense, I’m dubious about the potential impact. I’m open to being persuaded.
Quickly and With Some Degree of Confidence
One of the things that keeps me busy is administering and moderating a Facebook group called Food and Farm Discussion Lab and helping to moderate GMO SkeptiForum. This has led to a steady stream of requests for help find or evaluate information and evidence, often on things I know little about (i.e. vaccines, Morgellons). If I can, I try to see if I can get a beginner’s handle on the subject on the fly. The hitch is that I want to do this in a responsible way.
Last night I got a message from someone wanting help getting a discussion thread going to find out more about the impact of pesticide exposure on cancer rates for farmers. This morning somebody wanted to know what I knew about pesticides and water contamination. On both questions, I had read things in passing, but they weren’t issues where I have a confident handle on the topic. The member who approached me about farmers and cancer didn’t feel comfortable initiating the conversation, so I took on the task of getting the discussion rolling on cancer rates and farmer/farmworker pesticide exposure. I expect to become better informed as the discussion matures, but I wanted to start with a firm footing. I didn’t want to spend more than 20 minutes getting oriented, but I wanted to start with solid sources.
Here is how I approached that problem. It’s how I approach beginning to learn about any technical issue with non-obvious answers.
When looking at the technical literature, I start with recent broad reads. This means literature reviews and meta-analyses from the last five years. If I can’t find lit reviews or meta-analyses I move on to the largest, most robust studies I can find. On this topic there are not going to be RCT’s (random controlled trials), we’ll be looking at epidemiology. That means we are looking for longitudinal cohort studies with the largest cohorts over the longest period of time.
A literature review is just what it sounds like. Researchers systematically find all the relevant literature, they read it, they weigh it all out and then they try to fairly summarize what it all means and what conclusions can be drawn from the best available evidence at the time. To over-simplify, a meta-analysis is done by gathering all the well conducted studies on a given topic and trying to combine the data into a single larger data set from which more robust conclusions can be drawn. A longitudinal cohort study follows a group of people over time, trying to accurately record data on a number of variables and then crunch the data to see if their are significant correlations that correspond to credible hypotheses.
If I’m new to the topic, then I will not have the chops to evaluate single studies. I don’t know what variables aren’t being taken into account. I will not have an eye for possible confounders. I may have prejudices that affect which single studies I give more weight to. The first studies I look at will cause have a first impression effect that can be hard to shake. Cognitive psychologists call this anchor bias. If I start with an poorly conducted or unrepresentative study, that could bias me in unproductive ways. That’s why I try to stick to lit reviews and meta-analyses.
In this case, I have previously read that farmers have lower cancer rates than the rest of the population. My union organizer loyalties tell me that farmworkers are more likely to be getting screwed when it comes to exposure and proper handling of pesticides. Those things may or may not be true, but I’m inclined to believe them and I don’t need Daniel Kahneman to tell me that if I dive into a stack of conflicting small studies, then my confirmation bias will almost certainly lead me to those two conclusions because of anchor bias and tribal loyalties.
Before I dive into the technical literature, I try to see if I can get the lay of the land first.
I’m going to let you in on a nifty google hack for separating the wheat from the chafe and find reliable answers to difficult questions. We are going to limit our search to university websites. That means when we do a search on “farmers cancer pesticides” we will be looking almost entirely at results from university ag school and ag extension pages. This could spare us hundreds of pages of irresponsible headlines and poor reporting on the subject. Instead we will find pages soberly summarizing what is known about the subject, put together by professors or more likely grad students with a background on the subject. A big step up from your average health reporter.
This how you do it. Enter your search term into the search box followed by site:edu. This is a variation on site search which allows you to search single website. In this case our search looks like this:
I clicked around and found a few pages that gave me an overview. Poke around, see what you find.
3. Now that I’ve read some summaries by academics, I’m ready to look at the research. I go to Google Scholar and enter “farmers cancer pesticides” I give a quick scan to the results and see that they are mostly from the 90′s. I know I don’t want to rely on those studies, because I know that pesticides have changed drastically in the last few decades. More importantly (and universally) I don’t know the body of literature, so I have no way of knowing if the results of those old studies have since been replicated, overturned, withdrawn. retracted, etc. The other advantage recent research offers me is that papers summarize the relavant literature, so one of my next steps, if I decide I really want to dig into the topic is to start ransacking the footnotes for further study. Recent papers will give me a better map of the literature.
So, in the interest of speed, instead of custom defining a five year window, I click on the box to the left and redefine my search to “Since 2010″. Scanning down through the first thirty results, three look promising.
We reviewed epidemiologic evidence related to occupational pesticide exposures and cancer incidence in the Agricultural Health Study (AHS) cohort.
Data sources:Studies were identified from the AHS publication list available at http://aghealth.nci.nih.gov as well as through a Medline/PubMed database search in March 2009. We also examined citation lists. Findings related to lifetime-days and/or intensity-weighted lifetime-days of pesticide use are the primary focus of this review, because these measures allow for the evaluation of potential exposure–response relationships.
Data synthesis: We reviewed 28 studies; most of the 32 pesticides examined were not strongly associated with cancer incidence in pesticide applicators. Increased rate ratios (or odds ratios) and positive exposure–response patterns were reported for 12 pesticides currently registered in Canada and/or the United States (alachlor, aldicarb, carbaryl, chlorpyrifos, diazinon, dicamba, S-ethyl-N,N-dipropylthiocarbamate, imazethapyr, metolachlor, pendimethalin, permethrin, trifluralin).
Comparing agricultural cohorts with the general population is challenging because the general healthiness of farmers may mask potential adverse health effects of farming. Using data from the Agricultural Health Study, a cohort of 89,656 pesticide applicators and their spouses (N = 89, 656) in North Carolina and Iowa, the authors computed standardized mortality ratios (SMRs) comparing deaths from time of the enrollment (1993–1997) through 2007 to state-specific rates.
Objective: To systematically evaluate epidemiologic studies on pesticides and colon cancer and rectal cancer in agricultural pesticide applicator populations using a transparent “weight-of-evidence” (WOE) methodological approach.
Methods: Twenty-nine (29) publications from the Agricultural Health Study (AHS) and 13 additional epidemiologic studies were identified that reported data for pesticide applicators and/or specific pesticide compounds and colorectal, colon, or rectal cancer. The AHS evaluated pesticide applicators as well as dose–response associations for specific pesticide compounds, whereas the large majority of non-AHS evaluated applicators but did not analyze specific compounds or dose–response trends. This WOE assessment of 153 different pesticide–outcome pairs emphasized several key evidentiary features: existence of statistically significant relative risks, magnitude of observed associations, results from the most reliable exposure assessments, and evidence of convincing dose–response relationships (i.e., those monotonically increasing, with statistically significant trend tests).
There is one more that is about kids, not farmers but it catches my eye as a pretty robust study, so I flag that as well: Exposure to pesticides and risk of childhood cancer: a meta-analysis of recent epidemiological studies
Now, I feel like I have a firm footing to start from. Will it be the last word? No. Is it guaranteed to get me to the right answer? No. But by and large I think this approach points me in the right direction better than 9 out of 10 times. This is how I do a quick and dirty search. There are a two dozen limitations to this approach, but my goal isn’t to master the topic in an hour. I just want to be confident that I’m heading in the right direction and won’t embarrass myself in public.
I want to make Google my bitch. Not the other way around.
How I approach a deeper dive will have to wait for another day.
1. Keith Good – Farm Policy: Farmbill; Ag Economy; Biotech; and Immigration Monday
2. NPR: What Honest Abe’s Appetite Tells Us About His Life
3. Twilight Greenway – Civil Eats: Test-Tube Scramble: This Scientist Has a Fix For Our Protein Problem
4. Jeremy Bernfield – Harvest Media: Farmers worry about sharing Big Data
5. Kevin Folta – Illumination: GMOs and Leukemia Debunked
6. Nathanael Johnson – Grist: The Secret Ingredient to Slow Food: Slow Cash
7. Harvest Media: Researchers strive to breed better chickens to improve food security in Africa
8. Allison Aubrey – The Salt | NPR: The Full-Fat Paradox: Whole Milk May Keep Us Lean
9. Alan Greenblatt – The Salt | NPR: After 23 Years, Your Waiter Is Ready For A Raise
10. Jerry Hagstrom | Progressive Farmer: President Promises Drought Aid, Talks About Climate Change
Let’s talk about those GMO funded studies. You know the ones. The ones you always hear about from Anti-GMO folks when you read the comment section for any story about GMOs. According to those folks, the whole scientific consensus on GMOs is based on those studies. According to peanut gallery, the only studies that show that GMOs pose no different risks than conventionally bred crops were all bought and paid for by Monsanto. That would make the consensus suspicious right? It would if there weren’t also a ton of independently funded studies that show the same thing.
Instead, what the complaints about industry funded studies show is an ignorance of the literature and a lazy desire to dismiss inconvenient evidence in order to preserve predetermined ideological commitments. It’s just plain old confirmation bias and motivated reasoning run amok.
Let’s put aside the fact that this line of thinking would mean that while fossil fuel behemoths Exxon Mobil (market cap:$394.83B), Chevron (market cap:$215.45B) and BP (market cap:$150.07B) (total: $760.35B) have been completely stymied in their efforts to buy the scientific consensus they desire on climate change, but a medium large company like Monsanto (market cap: $57.43B) has been able to manipulate tens of thousands of scientists performing thousands of studies for three decades with no whistleblowers resulting in a scientific consensus that has been bent completely to their will. Let’s put that aside.
Instead, let’s first take a look at the evidence, before moving to unravel some of pretzeled logic often employed to dismiss the weight of that evidence in support of the scientific consensus on GMOs.
Take for example the EU. Politicians in the EU aren’t that friendly to GMOs and they wanted to be very careful about them. So they ponied up €200 million over the course of decade to look into the matter. The studies they carried out are neatly summarized in A Decade of EU Funded GMO Research [pdf].
This new publication presents the results of 50 projects, involving more than 400 research groups and representing European research grants of some EUR 200 million. This figure brings the total Commission funding of research on GMO safety to more than EUR 300 million since its inception in 1982 in the Biomolecular Engineering programme.
. . . The main conclusion to be drawn from the efforts of more than 130 research projects, covering a period of more than 25 years of research, and involving more than 500 independent research groups, is that biotechnology, and in particular GMOs, are not per se more risky than e.g. conventional plant breeding technologies.
Elsewhere, the fine folks at Biofortified have begun working on a database of GMO research, while that work is still in progress, they have gathered a collection of 126 studies with independent funding. Not all of the studies are supportive of the position that GMOs are no riskier than their conventionally bred counterparts, but the vast majority support that proposition.
Let’s look at two types of papers from the list that are of particular value to the non-scientists among us. For the lay person, sticking with literature reviews and meta-analyses are a great way for getting a sense of the weight of the evidence on a given topic. They help us avoid single study syndrome and keep us from missing the forest for the trees. Here are four of those types papers from the Biofortified list of studies with independent funding.
The aim of this systematic review was to collect data concerning the effects of diets containing GM maize, potato, soybean, rice, or triticale on animal health. We examined 12 long-term studies (of more than 90 days, up to 2 years in duration) and 12 multigenerational studies (from 2 to 5 generations). We referenced the 90-day studies on GM feed for which long-term or multigenerational study data were available. Many parameters have been examined using biochemical analyses, histological examination of specific organs, hematology and the detection of transgenic DNA. The statistical findings and methods have been considered from each study. Results from all the 24 studies do not suggest any health hazards and, in general, there were no statistically significant differences within parameters observed.
Honey bees (Apis mellifera L.) are the most important pollinators of many agricultural crops worldwide and are a key test species used in the tiered safety assessment of genetically engineered insect-resistant crops. There is concern that widespread planting of these transgenic crops could harm honey bee populations.
Methodology/Principal Findings: We conducted a meta-analysis of 25 studies that independently assessed potential effects of Bt Cry proteins on honey bee survival (or mortality). Our results show that Bacillus thuringiensis (Bt) Cry proteins used in genetically modified crops commercialized for control of lepidopteran and coleopteran pests do not negatively affect the survival of either honey bee larvae or adults in laboratory settings.
Conclusions/Significance: Although the additional stresses that honey bees face in the field could, in principle, modify their susceptibility to Cry proteins or lead to indirect effects, our findings support safety assessments that have not detected any direct negative effects of Bt crops for this vital insect pollinator.
Although scores of experiments have examined the ecological consequences of transgenic Bt crops, debates continue regarding the nontarget impacts of this technology. Quantitative reviews of existing studies are crucial for better gauging risks and improving future risk assessments. To encourage evidence-based risk analyses, we constructed a searchable database for nontarget effects of Bt crops. A meta-analysis of 42 field experiments indicates that nontarget invertebrates are generally more abundant in Bt cotton and Bt maize fields than in nontransgenic fields managed with insecticides. However, in comparison with insecticide-free control fields, certain nontarget taxa are less abundant in Bt fields.
There is one more literature review from the Biofortified list that I want to look at, but in the context of making an important point.
The point is this. Yes, there are lots of industry funded studies. The majority in fact. But, as I hope that I’ve demonstrated, there is a robust literature of independent studies. How can we judge if the results of the industry funded studies are reliable? Well, one indicator would be if that the independent studies and the industry studies, in the aggregate, come to the same conclusions. When we look, that is in fact, what we find.