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Obesity is caused by a prolonged positive energy balance1,2. Whether reduced energy expenditure stemming from reduced activity levels contributes is debated3,4. Here we show that in both sexes, total energy expenditure (TEE) adjusted for body composition and age declined since the late 1980s, while adjusted activity energy expenditure increased over time. We use the International Atomic Energy Agency Doubly Labelled Water database on energy expenditure of adults in the United States and Europe (n = 4,799) to explore patterns in total (TEE: n = 4,799), basal (BEE: n = 1,432) and physical activity energy expenditure (n = 1,432) over time. In males, adjusted BEE decreased significantly, but in females this did not reach significance. A larger dataset of basal metabolic rate (equivalent to BEE) measurements of 9,912 adults across 163 studies spanning 100 years replicates the decline in BEE in both sexes. We conclude that increasing obesity in the United States/Europe has probably not been fuelled by reduced physical activity leading to lowered TEE. We identify here a decline in adjusted BEE as a previously unrecognized factor.

In mammals, trait variation is often reported to be greater among males than females. However, to date, mainly only morphological traits have been studied. Energy expenditure represents the metabolic costs of multiple physical, physiological, and behavioral traits. Energy expenditure could exhibit particularly high greater male variation through a cumulative effect if those traits mostly exhibit greater male variation, or a lack of greater male variation if many of them do not. Sex differences in energy expenditure variation have been little explored. We analyzed a large database on energy expenditure in adult humans (1494 males and 3108 females) to investigate whether humans have evolved sex differences in the degree of interindividual variation in energy expenditure. We found that, even when statistically comparing males and females of the same age, height, and body composition, there is much more variation in total, activity, and basal energy expenditure among males. However, with aging, variation in total energy expenditure decreases, and because this happens more rapidly in males, the magnitude of greater male variation, though still large, is attenuated in older age groups. Considerably greater male variation in both total and activity energy expenditure could be explained by greater male variation in levels of daily activity. The considerably greater male variation in basal energy expenditure is remarkable and may be explained, at least in part, by greater male variation in the size of energy-demanding organs. If energy expenditure is a trait that is of indirect interest to females when choosing a sexual partner, this would suggest that energy expenditure is under sexual selection. However, we present a novel energetics model demonstrating that it is also possible that females have been under stabilizing selection pressure for an intermediate basal energy expenditure to maximize energy available for reproduction. (C) 2022 The Author(s). Published by Elsevier Ltd.

BACKGROUND: Race and sex differences in adolescents’ body fat are demonstrated in cross-sectional cohorts, yet a longitudinal design would better identify patterns of fat distribution over time. OBJECTIVES: The aim was to examine race and sex differences in adiposity between black and white adolescents over 2 y. METHODS: A cohort of adolescents aged 10–16 y (38% black; 52% girls; 15% overweight, 34% with obesity) underwent body composition measurements at baseline (n = 309) and 2 y later (n = 236), using DXA to quantify whole-body fat mass (FM) and MRI for abdominal subcutaneous (SAT) and visceral adipose tissue (VAT) volumes. General linear models were used to examine race and sex differences in log-transformed FM, SAT, and VAT, adjusting for age, sexual maturation, extended BMI percentile, and race-by-sex interaction. SAT and VAT models in addition controlled for baseline FM and change in FM (for change models). RESULTS: Mean (95% CI) baseline FM (kg) was higher among white [18.5 (17.9, 19.2) than among black adolescents [17.4 (16.6, 18.2), P = 0.03] and girls [19.5 (18.8, 20.3) than boys [16.5 (15.8, 17.2), P < 0.0001]. Mean (95% CI) baseline SAT (L) was higher among girls [4.4 (4.2, 4.6)] than among boys [3.9 (3.7, 4.1), P < 0.0001]. Mean (95% CI) baseline VAT (L) was higher among white [0.5 (0.5, 0.6)] than among black [0.3 (0.3, 0.4)] adolescents (P < 0.0001) and boys [0.5 (0.4, 0.5)] than girls [0.4 (0.4, 0.4), P = 0.04]. Over 2 y mean (95% CI) FM change (kg) was higher among white [3.7 (2.9, 4.5)] than among black adolescents [2.3 (1.3, 3.3), P = 0.04] and girls [4.0 (3.0, 4.9)] than boys [2.0 (1.1, 3.0), P = 0.007], but SAT change (L) did not differ by race or sex. VAT change (L) was higher among white [0.1 (0.1, 0.1)] than among black adolescents [0.0 (0.0, 0.1), P = 0.003] and boys [0.1 (0.1, 0.1)] than girls [0.0 (0.0, 0.1), P = 0.034]. CONCLUSIONS: Sex and race differences in the deposition and accumulation of excess fat are important considerations for understanding obesity prevalence and obesity-related disease risk among adolescents. This trial was registered at clinicaltrials.gov as NCT02784509.

Summary Physical inactivity is an important contributor to non-communicable diseases in countries of high income, and increasingly so in those of low and middle income. Understanding why people are physically active or inactive contributes to evidence-based planning of public health interventions, because effective programmes will target factors known to cause inactivity. Research into correlates (factors associated with activity) or determinants (those with a causal relationship) has burgeoned in the past two decades, but has mostly focused on individual-level factors in high-income countries. It has shown that age, sex, health status, self-efficacy, and motivation are associated with physical activity. Ecological models take a broad view of health behaviour causation, with the social and physical environment included as contributors to physical inactivity, particularly those outside the health sector, such as urban planning, transportation systems, and parks and trails. New areas of determinants research have identified genetic factors contributing to the propensity to be physically active, and evolutionary factors and obesity that might predispose to inactivity, and have explored the longitudinal tracking of physical activity throughout life. An understanding of correlates and determinants, especially in countries of low and middle income, could reduce the effect of future epidemics of inactivity and contribute to effective global prevention of non-communicable diseases.

Background: Epidemiologic data on the association between body mass index (BMI) and heart failure (HF) risk among diabetic patients is rare. Aim: To investigate the association between BMI and HF risk among patients with type 2 diabetic in the Louisiana State University Hospital-based Longitudinal study (LSUHLS). Methods: We performed a prospective cohort study of risk for HF among 31,155 patients of type 2 diabetes (11,468 men and 19,687 women). Cox proportional hazards regression models were used to estimate the association of different levels of BMI with HF risk. Results: During a mean follow-up of 7.8 years, 5,834 subjects developed HF (2,379 men and 3,455 women). The multivariable-adjusted (age, race, smoking, income and type of insurance) hazard ratios of HF associated with BMI levels (18.5-22.9, 23-24.9, 25-29.9 [reference group], 30-34.9, 35-39.9, and ≥40 kg/m2) at baseline were 0.95, 1.00, 1.00, 1.16, 1.64, and 2.02 (Ptrend Conclusions: Our study suggests a positive association between BMI and HF risk among men, and a J-shaped association between BMI and HF risk among women with type 2 diabetes.

Background: Several prospective studies have evaluated the association between body mass index (BMI) and the risk of all-cause mortality among diabetic patients; however, the results are controversial. Aim: To investigate the association of BMI levels with all-cause mortality among patients with type 2 diabetes in the Louisiana State University Hospital-based Longitudinal study (LSUHLS). Methods: We performed a prospective cohort study (2000-2009) of diabetic patients including 19,785 African Americans and 15,534 whites. Cox proportional hazards regression models were used to estimate the association of BMI levels at baseline, during follow-up and at last visit with the risk of all-cause mortality. Results: During a mean follow up of 8.7 years, 4,206 deaths were identified. The multivariable-adjusted (age, sex, smoking, income and type of insurance) hazard ratios (HRs) of all-cause mortality associated with BMI levels (2 ) at baseline were 2.53 (95% confidence interval [CI] 2.18-2.93), 1.76 (1.48-2.09), 1.23 (1.08-1.40), 1.00, 1.19 (1.02-1.38), and 1.22 (1.05-1.41) for African Americans, and 1.92 (1.63-2.27), 1.53 (1.28-1.82), 1.07 (0.95-1.21), 1.00, 1.07 (0.93-1.23), and 1.21 (1.06-1.39) for whites, respectively. When stratified by age, gender, smoking status or use of anti-diabetic drugs, a U-shaped association was still present. When we used an updated mean or last visit value of BMI, the U-shaped association of BMI with all-cause mortality risk did not change. Conclusions: The current study indicated a U-shaped association of BMI with all-cause mortality risk among African American and white patients with type 2 diabetes. A significantly increased risk of all-cause mortality was observed among African Americans with BMI2 and BMI ≥35 kg/m 2 , and among whites with BMI2 and BMI ≥40 kg/m 2 compared with patients with BMI 30-34.9 kg/m 2 .

Background: Although coronary heart disease (CHD), heart failure (HF), stroke, and end-stage renal disease (ESRD) are major microvascular and macrovascular complications of diabetes, they are less clear for diabetic subgroups especially on those with middle and low income. Aim: To investigate racial disparities in the incidence of diabetic complications in middle and low income adults. Methods: We performed a prospective cohort study (1985-2010) on diabetic patients enrolled in the LSU Hospital-Based Longitudinal Study. Study cohorts included 89,353 diabetic patients (16,326 White men, 21,496 White women, 19,422 African American men and 32,109 African American women) who were 30 to 96 years of age. We calculated the gender specific age-standardized incident rates using the direct method to the year 2010 Census population. Cox proportional hazard models were used to compare racial or gender specific hazard ratios for CHD, HF, stroke and ESRD after adjustment for age, race, type of health insurance, family income, body mass index, smoking, systolic blood pressure, LDL cholesterol, HDL cholesterol, HbA 1c , estimated GFR, albuminuria, and drug treatments for diabetes, hypertension and hyperlipidemia. Results: During an average 4.0 years of follow-up, 16,935 CHD, 13,421 HF, 6,804 stroke, and 13,281 ESRD incident cases were ascertained. The age-standardized incident rates of the four diabetic complications are presented in table 1 . Compared with White diabetic patients, African Americans experienced higher rates of ESRD and lower rates of CHD, HF, and stroke. Female diabetic patients had lower rates of the four complications than males. Results of the Cox proportional hazard models confirmed the racial disparity and gender difference we found in the age-standardized incident rates. Conclusions: The results support the existence of racial differences in the incidence of diabetic complications in this population. Table 1 Age-adjusted incident rates of type 2 diabetes complications in the LSUHLS study Age-standardized incident rates White African American Male Female Male Female Coronary Heart Disease 101.6 (98.8-104.5) 62.0 (60.4-63.7) 50.7 (49.2-52.2) 44.4 (43.4-45.5) Heart Failure 54.9 (52.9-56.8) 41.9 (40.6-43.1) 43.4 (42.0-44.8) 38.4 (37.4-39.3) Stroke 22.1 (20.9-23.3) 20.7 (19.8-21.6) 19.9 (19.0-20.8) 18.5 (17.8-19.1) End-stage Renal Disease 43.3 (41.6-45.0) 33.4 (32.2-34.5) 51.4 (50.0-52.9) 35.2 (34.3-36.1)

Summary To implement effective non-communicable disease prevention programmes, policy makers need data for physical activity levels and trends. In this report, we describe physical activity levels worldwide with data for adults (15 years or older) from 122 countries and for adolescents (13–15-years-old) from 105 countries. Worldwide, 31·1% (95% CI 30·9–31·2) of adults are physically inactive, with proportions ranging from 17·0% (16·8–17·2) in southeast Asia to about 43% in the Americas and the eastern Mediterranean. Inactivity rises with age, is higher in women than in men, and is increased in high-income countries. The proportion of 13–15-year-olds doing fewer than 60 min of physical activity of moderate to vigorous intensity per day is 80·3% (80·1–80·5); boys are more active than are girls. Continued improvement in monitoring of physical activity would help to guide development of policies and programmes to increase activity levels and to reduce the burden of non-communicable diseases.

As use of self-reported data to classify obesity continues, ethnic differences in reporting errors remain unclear. The objective of this study is to elucidate misreporting disparities between African Americans (AAs) and European Americans (EAs). The Pennington Center Longitudinal Study (PCLS) is an ongoing investigation of environmental, behavioral, and biological factors associated with obesity, diabetes, and other common diseases. Self-reported and measured height and weight were collected during initial screening for eligibility in various studies by telephone and clinic visits. All ethnicity-sex groups (15,656 adults aged 18-65 years, 53% obese, 34% AA, 37% men) misreported heights and weights increasingly as measured values increased (P < 0.0001). More AA vs. EA women (P < 0.001) misreported height and weight, but more EA vs. AA men misreported their weight (P < 0.02). Obesity was underestimated more in AA vs. EA women (self-reported - measured prevalence = -4.0% (AA) vs. -2.6% (EA), P < 0.0001), but less in AA vs. EA men (-3.2% (AA) vs. -4.2% (EA), P < 0.0001)). With measured obesity prevalence equalized at 53% in all groups, the self-reported obesity prevalence in women was 50.4% (AA) vs. 49.6% (EA), and in men 49.8% (AA) vs. 47.3 (EA). Underestimation in women was -2.6% (AA) vs. -3.4% (EA); in men it was -3.2% (AA) vs. -5.7% (EA), P < 0.003. Self-reported height and weight portend underestimation of obesity prevalence and the effect varies by ethnicity and gender. However, comparisons depend on the true prevalence within ethnicity-gender groups. After controlling for obesity prevalence, disparity in underestimation was greater in EA than in AA men (P < 0.003) but not women.