TABLE 1.

Existing Evidence of Potential Contributors to the Obesity Epidemic.

Factor	Rationale	Association demonstrated in humans?	Causal evidence of weight gain in animals?	Causal evidence of effects on weight in humans?	Causal evidence of surrogate outcomes?	Can this plausibly be manipulated to reduce the obesity epidemic?
Sleep Debt1,2	Reduced sleep increases appetite and decreases energy expenditure. Average amount of sleep has declined among adults and children.	Yes	Yes	Some	Yes (food intake, decreased glucose clearance and insulin response, plasma leptin, plasma TSH, and increased plasma ghrelin)	Yes
Decreased Rates of Smoking1	Smokers typically weigh less than non-smokers, and weight gain occurs with smoking cessation. Smoking rates among American adults have declined as obesity rates have risen.	Yes	No	Yes	Yes (nicotine increases energy expenditure, suppresses food intake in animal models, increases NPY expression)	No
Increased Atmospheric CO23	May result in lower blood pH, activation of orexin neurons in the lateral hypothalamus, and increased appetite and food intake.	No	No	No	No	No
Ambient Temperature1,2	Thermoneutrality minimizes energy expenditure to maintain core body temperature. Time spent in the thermoneutral zone has increased with reductions in vocational and household exposure to variations in ambient temperatures.	Yes	Yes	No	Yes (ambient temperature variations shown to affect metabolic rate and food intake)	Yes
Technology4	Higher screen time and technology use is associated with higher obesity rates, both of which have dramatically increased with the obesity epidemic.	Yes	N/A	No	Yes (Increased food intake and choice of energy-dense foods)	Yes
Suspected Endocrine Disruptors1,2	Several hormonal regulatory processes impact weight gain and are altered by man-made chemicals and heavy metals. Suspected endocrine disruptors present in the body are positively correlated with BMI and adiposity. Food chain and tissue levels have increased.	Yes (results vary)	Yes	No	No	Possibly yes, but not easily at the individual level.
Pharmaceutical Iatrogenesis1,2	Many common medications have been shown to contribute to weight gain. Medical diagnoses and corresponding prescriptions have increased alongside obesity rates.	Yes	Yes	Yes	Yes (remodeling adipose tissue distribution)	Yes
Infections2	Some infections result in increased adiposity in animals. Ad36 infection is associated with obesity.	Yes (results vary)	Yes	No	No	Not for Infections per se, but vaccines and use of analogues of the infective agent’s mechanisms are conceivable.
The Gut Microbiome5	Gut colonization of gut microbiota results in increased adiposity in rodents. Dysbiosis of gut microbiota is associated with human obesity.	Yes	Yes	No	No	Yes
Economic Disparity and Insecurity6	May lead to physiological, cognitive, and behavioral changes resulting in increased energy intake.	Yes	Yes	Some (e.g., the Moving to Opportunity Study)	Some	Yes
Delay Discounting7	Associated with impulsivity and poor food choices.	Yes	No	No	No	Unclear
Cognitive Demand8	May result in poor food choices, greater food consumption, and weight gain.	Yes	No	No	Yes	Yes
Assortative Mating1,2	Humans assortatively mate for adiposity, which has a genetic component, producing an increased risk of obesity in offspring.	Yes	Yes	Yes	No	No
Differential Reproductive Fitness by BMI1,2	Adiposity is in part due to genetics, and BMI positively correlates with number of offspring. BMI is at least 65% heritable.	Yes	Yes	No	No	No
Intrauterine and Intergenerational Effects1,2	In-utero energy imbalances like low birth weight and overfeeding may impact offspring adiposity and pass down generations. Rates of low birth weight have climbed with obesity rates since the 1980s.	Yes	Yes	No	No	Yes
High Gravida Age1,2	Mean pregnancy age has steadily increased with obesity rates. There is a direct association between maternal age and obesity in offspring.	Yes	Yes	No	No	Yes
Fetal Drive9	Fetal genotype may alter postnatal maternal physiology impacting obesity risk and outcomes.	No	No	No	No	Not with current technology.