The Men's Health Big Book Of Food Nutrition: ...
Manufactured hydrogenated oils, which your body cannot digest, are a serious risk to heart health. Many Americans are still unaware that the one of the most harmful heart-health trends of the last century was the gradual replacement of healthy natural fats with foods such as margarine. Many margarines were formed by hydrogenating or partially hydrogenating Read More
The Men's Health Big Book of Food Nutrition: ...
We have subjected the science underpinning nutritional health claims in relation to red and processed meat and soy protein to serious scrutiny. We believe the FDA should take account of our methods as it considers food health claims. Yet we care even more about reforming the procedures the FDA uses in general to assess nutritional science.
The consequences of FDA regulation are at least as consequential, for they affect the food and drink consumed by every American. So therefore are the consequences of FDA mis-regulation. Inaccurate labels can mislead consumers, not least by encouraging them to adopt fad diets that present health risks. Furthermore, every company in the food sector, which involved $6.22 trillion dollars in annual sales in 2020, depends for its livelihood on accurate labeling of food products. Mislabeling health benefits can give a company a larger market share than it deserves.
Scientists conduct statistical comparisons to establish the association between FFQ dietary data items and health outcomes to produce multiple research papers. They then conduct further statistical analyses using meta-analyses of the individual research papers, which combine data from multiple published studies that address a common research question, such as the association between a particular food and a particular disease.20 For example, one meta-analysis combines data of all published studies that examine the claim that high salt intake is associated with gastric cancer.21
The number of possible questions at issue can increase extraordinarily rapidly in a cohort study. Consider this hypothetical cohort study of the relationship between a food substance and a disease or health-related condition:
Nutritional epidemiology applies epidemiological methods to the study at the population level of how diet affects health and disease in humans. Nutritional epidemiologists base most of their inferences about the role of diet (i.e., foods and nutrients) in causing or preventing chronic diseases on observational studies. Since the 1980s, food frequency questionnaires (FFQs), which are easy to use, place low burdens on participants, and aspire to capture long-term dietary intake, have become the most common method by which nutritional epidemiologists measure dietary intake in large observational study populations.82
Inaccurate labels can mislead consumers, not least by encouraging them to adopt fad diets that present health risks.92 Furthermore, every company in the food sector, which involved $6.22 trillion dollars in annual sales in 2020,93 depends for its livelihood on accurate labeling of food products. Mislabeling health benefits can give a company a larger market share than it deserves.
Figure 3 shows how frequently researchers use FFQ data to investigate 18 separate health outcomes. Scientists appear particularly interested in investigating the association between obesity and particular foods, but they also investigate more unexpected topics, such as the association between particular foods and erectile dysfunction. They are, as a group, thorough in seeking out possible associations.
The Johnston research group (Vernooij et al.) recently published a systematic review and meta-analysis of cohort studies pertaining to food health claims of red and processed meat.122 We selected 6 of 30 health outcomes that they reported on for further investigation: all-cause mortality, cancer mortality and incidence, cardiovascular mortality, nonfatal coronary heart disease, fatal and nonfatal myocardial infarction, and type 2 diabetes. We chose the 6 health outcomes studied most frequently in the base study papers.
Each of these risk factors is a predictor, each type of health effect is an outcome. Scientists may further analyze an association between a particular food component and a particular health outcome with reference to categories of analysis such as age and sex. Researchers call these further yes/no categories of analysis covariates; covariates may affect the strength of the association, but they are not the direct objects of study.
In Figure 13, we have simulated a nutritional epidemiology study using a hypothetical single cohort data set analyzing associations between 5 individual foods and 20 health outcomes. Remember, these numbers were picked at random. 041b061a72