A lifetime of change: Measurements of total and basal energy in a large cohort of subjects at ages spanning from before birth to old age document distinct changes that occur during a human lifetime. Pontzer et al . report that energy expenditure (adjusted for weight) in neonates was like that of adults but increased substantially in the first year of life (see the Perspective by Rhoads and Anderson). It then gradually declined until young individuals reached adult characteristics, which were maintained from age 20 to 60 years. Older individuals showed reduced energy expenditure. Tissue metabolism thus appears not to be constant but rather to undergo transitions at critical junctures. —LBR

Water is essential for survival, but one in three individuals worldwide (2.2 billion people) lacks access to safe drinking water. Water intake requirements largely reflect water turnover (WT), the water used by the body each day. We investigated the determinants of human WT in 5604 people from the ages of 8 days to 96 years from 23 countries using isotope-tracking ( ² H) methods. Age, body size, and composition were significantly associated with WT, as were physical activity, athletic status, pregnancy, socioeconomic status, and environmental characteristics (latitude, altitude, air temperature, and humidity). People who lived in countries with a low human development index (HDI) had higher WT than people in high-HDI countries. On the basis of this extensive dataset, we provide equations to predict human WT in relation to anthropometric, economic, and environmental factors.

Nutritional epidemiology aims to link dietary exposures to chronic disease, but the instruments for evaluating dietary intake are inaccurate. One way to identify unreliable data and the sources of errors is to compare estimated intakes with the total energy expenditure (TEE). In this study, we used the International Atomic Energy Agency Doubly Labeled Water Database to derive a predictive equation for TEE using 6,497 measures of TEE in individuals aged 4 to 96 years. The resultant regression equation predicts expected TEE from easily acquired variables, such as body weight, age and sex, with 95% predictive limits that can be used to screen for misreporting by participants in dietary studies. We applied the equation to two large datasets (National Diet and Nutrition Survey and National Health and Nutrition Examination Survey) and found that the level of misreporting was 27.4%. The macronutrient composition from dietary reports in these studies was systematically biased as the level of misreporting increased, leading to potentially spurious associations between diet components and body mass index.

Global economic development has been associated with an increased prevalence of obesity and related health problems. Increased caloric intake and reduced energy expenditure are both cited as development-related contributors to the obesity crisis, but their relative importance remains unresolved. Here, we examine energy expenditure and two measures of obesity (body fat percentage and body mass index, BMI) for 4,213 adults from 34 populations across six continents and a wide range of lifestyles and economies, including hunter-gatherer, pastoralist, farming, and industrialized populations. Economic development was positively associated with greater body mass, BMI, and body fat, but also with greater total, basal, and activity energy expenditure. Body size–adjusted total and basal energy expenditures both decreased approximately 6 to 11% with increasing economic development, but were highly variable among populations and did not correspond closely with lifestyle. Body size–adjusted total energy expenditure was negatively, but weakly, associated with measures of obesity, accounting for roughly one-tenth of the elevated body fat percentage and BMI associated with economic development. In contrast, estimated energy intake was greater in economically developed populations, and in populations with available data (n = 25), the percentage of ultraprocessed food in the diet was associated with body fat percentage, suggesting that dietary intake plays a far greater role than reduced energy expenditure in obesity related to economic development.

Background: In Western countries, children’s diets are often low in fruits and vegetables and high in discretionary foods. Diet in early life tends to track through childhood and youth and even into adulthood. Interventions should, therefore, be delivered in periods when habitual traits are established, as in toddlerhood when children adapt to their family’s diet. Objective: In this study, we assessed the effect of the Food4toddlers eHealth intervention, which aimed to enhance toddlers’ diets by shaping their food and eating environment. Methods: The Food4toddlers randomized controlled trial was conducted in Norway in 2017-2018. Parent-child dyads were recruited through social media. In total, 298 parents completed an online questionnaire at baseline (mean child age 10.9 months, SD 1.2). Postintervention questionnaires were completed immediately after the intervention (ie, follow-up 1; mean child age 17.8 months, SD 1.3) and 6 months after the intervention (ie, follow-up 2; mean child age 24.2 months, SD 1.9). The intervention was guided by social cognitive theory, which targets the linked relationship between the person, the behavior, and the environment. The intervention group (148/298, 49.7%) got access to the Food4toddlers website for 6 months from baseline. The website included information on diet and on how to create a healthy food and eating environment as well as activities, recipes, and collaboration opportunities. To assess intervention effects on child diet from baseline to follow-up 1 and from baseline to follow-up 2, we used generalized estimating equations and a time × group interaction term. Between-group differences in changes over time for frequency and variety of fruits and vegetables and frequency of discretionary foods were assessed. Results: At follow-up 1, a significant time × group interaction was observed for the frequency of vegetable intake (P=.02). The difference between groups in the change from baseline to follow-up 1 was 0.46 vegetable items per day (95% CI 0.06-0.86) in favor of the intervention group. No other significant between-group differences in dietary changes from baseline to follow-up 1 or follow-up 2 were observed. However, there is a clear time trend showing that the intake of discretionary foods increases by time from less than 1 item per week at baseline to more than 4 items per week at 2 years of age (P<.001), regardless of group. Conclusions: A positive intervention effect was observed for the frequency of vegetable intake at follow-up 1 but not at follow-up 2. No other between-group effects on diet were observed. eHealth interventions of longer duration, including reminders after the main content of the intervention has been delivered, may be needed to obtain long-terms effects, along with tailoring in a digital or a personal form. Trial Registration: International Standard Randomized Controlled Trial Number (ISRCTN) 92980420; https://doi.org/10.1186/ISRCTN92980420