Question: Will the CDC adopt a Health at Every Size approach towards addressing obesity before 2035?
Background: From [Wikipedia](https://en.wikipedia.org/wiki/Health_at_Every_Size),

> Health at Every Size (HAES) is a hypothesis advanced by certain sectors of the fat acceptance movement. It is promoted by the Association for Size Diversity and Health, a tax-exempt nonprofit organization that owns the phrase as a registered trademark. Proponents reject the scientific consensus regarding the negative health effects of greater body weight, and argue that traditional interventions focused on weight loss, such as dieting, do not reliably produce positive health outcomes. The benefits of lifestyle interventions such as nutritious eating and exercise are presumed to be real, but independent of any weight loss they may cause. At the same time, HAES advocates argue that sustained, large-scale weight loss is difficult to the point of effective impossibility for the majority of people, including those who are obese.

Advocates of the Health at Every Size hypothesis sometimes cite a [2013 meta analysis](https://pubmed.ncbi.nlm.nih.gov/23280227/) which found that mildly overweight people (by BMI) had lower all-cause mortality than people in the normal weight group. This result has also been picked up by prominent researchers. From UC Berkeley's blog, [Ask The Dietitian](https://uhs.berkeley.edu/news/ask-dietitian-health-every-size),

> As part of a social movement called Health at Every Size (HAES), dietitians and doctors are moving away from assessing people’s health according to their weight. The HAES philosophy is based on the idea that people of all sizes deserve respect and good health, and that size does not determine health.

> Research shows that there are a high percentage of people in the "overweight" or even "obese" category according to Body Mass Index (BMI) that are metabolically healthy. At the same time, there are a significant percentage of "normal" weight people who are unhealthy, with diseases like diabetes, hypertension or high cholesterol. In addition, people in the overweight category actually live the longest. Maybe BMI has gotten it wrong all these years?

Other researchers, however, are not convinced. From [Fontana et al.](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4032609/),

> The validity of [the 2013 meta-analysis] has been challenged due to several major methodological problems (Tobias & Hu, 2013). First, many high-quality prospective studies and consortia (including >6 million participants) were excluded from the meta-analyses because they did not use standard BMI categories (i.e., 18.5–24.9 for normal weight, 25–29.9 for overweight, and ≥30 for obesity). These large studies generally benefited from sufficient statistical power to allow for the analysis of finer BMI categories, and therefore had no reason to use such broad categories. In most of these omitted studies, the BMI range associated with the lowest mortality was around 22.5–25, particularly after accounting for smoking status and reverse causation due to prevalent diseases (Tobias & Hu, 2013). Second, the meta-analysis included numerous studies conducted among elderly or sick populations as well as current and past smokers. In particular, the broad reference group (BMI 18.5–24.9) contains not only individuals who are lean and active, but also heavy smokers, the frail and elderly, and those who are ill with previous weight loss or diminished weight gain due to existing diseases. Because the overweight and obese groups were compared with this heterogeneous group, the associations with the higher-BMI groups were seriously underestimated, creating an artifact of reduced mortality among the overweight and moderately obese groups (Willett et al., 2013).

Nonetheless, Fontana et al. state,

> the prevention of weight gain is more important than weight loss because once an individual becomes obese, it is very difficult to achieve long-term weight loss and maintenance.

reflecting partial agreement with [policy suggestions given by advocates of HAES](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3935663/).
Source: metaculus
Resolved outcome (1 = yes, 0 = no): 0