A field tool for prediction of body fat in Sri Lankan women: skinfold thickness equation

Background: Valid skinfold thickness (SFT) equations for the prediction of body fat are currently unavailable for South Asian women and would be a potentially robust field tool. Our aim was to assess the validity of existing SFT equations against deuterium (2H2O) dilution and, if invalid, to develop and validate an SFT equation for % fat mass (%FM) in Sri Lankan women. Methods: H2O dilution was used with Fourier transform infrared (FTIR) spectroscopy as the criterion method for the assessment of %FM in urban Sri Lankan women (30\u201345 years). This data was used to assess the validity of available SFT equations and to generate and validate a new SFT equation for the prediction of %FM against the criterion method. Women (n = 164) were divided into validation and cross-validation groups for the development and validation of the new equation. The level of agreement between the %FM calculated by the final derived prediction equation and the %FM obtained by 2H2O dilution was assessed using Pearson\u2019s correlation coefficient (R) and Bland Altman plots. Student\u2019s t test was used to assess over- or underestimation, and significance was set at p < 0.05. Results: Existing equations significantly (p < 0.001) underestimated %FM compared with the 2H2O dilution method. The final equation obtained was %FM= 19.621 + (0.237*weight) + (0.259*triceps). When compared with 2H2O dilution, %FM by the equation was not significantly different. There was a significant (p < 0.001) correlation between %FM by the reference method and %FM by the equation. The limit of agreement by Bland Altman plot was narrow with a small mean positive bias. Conclusions: Existing SFT equations were not applicable to this population. The new equation derived was valid. We report a new SFT equation to predict %FM in women of South Asian ancestry suitable for field use

Predictive equation derived from 6,497 doubly labelled water measurements enables the detection of erroneous self-reported energy intake

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 >50%. 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

Greater Male Variability in Daily Energy Expenditure Develops Through Puberty

There is considerably greater variation in metabolic rates between men than between women, in terms of basal, activity and total (daily) energy expenditure (EE). One possible explanation is that EE is associated with male sexual characteristics (which are known to vary more than other traits) such as musculature and athletic capacity. Such traits might be predicted to be most prominent during periods of adolescence and young adulthood, when sexual behaviour develops and peaks. We tested this hypothesis on a large dataset by comparing the amount of male variation and female variation in total EE, activity EE and basal EE, at different life stages, along with several morphological traits: height, fat free mass and fat mass. Total EE, and to some degree also activity EE, exhibit considerable greater male variation (GMV) in young adults, and then a decreasing GMV in progressively older individuals. Arguably, basal EE, and also morphometrics, do not exhibit this pattern. These findings suggest that single male sexual characteristics may not exhibit peak GMV in young adulthood, however total and perhaps also activity EE, associated with many morphological and physiological traits combined, do exhibit GMV most prominently during the reproductive life stages

Greater male variability in daily energy expenditure develops through puberty

There is considerably greater variation in metabolic rates between men than between women, in terms of basal, activity and total (daily) energy expenditure (EE). One possible explanation is that EE is associated with male sexual characteristics (which are known to vary more than other traits) such as musculature and athletic capacity. Such traits might be predicted to be most prominent during periods of adolescence and young adulthood, when sexual behaviour develops and peaks. We tested this hypothesis on a large dataset by comparing the amount of male variation and female variation in total EE, activity EE and basal EE, at different life stages, along with several morphological traits: height, fat free mass and fat mass. Total EE, and to some degree also activity EE, exhibit considerable greater male variation (GMV) in young adults, and then a decrease in the degree of GMV in progressively older individuals. Arguably, basal EE, and also morphometrics, do not exhibit this pattern. These findings suggest that single male sexual characteristics may not exhibit peak GMV in young adulthood, however total and perhaps also activity EE, associated with many morphological and physiological traits combined, do exhibit GMV most prominently during the reproductive life stages

Children’s and adolescents’ rising animal-source food intakes in 1990–2018 were impacted by age, region, parental education and urbanicity

Animal-source foods (ASF) provide nutrition for children and adolescents’ physical and cognitive development. Here, we use data from the Global Dietary Database and Bayesian hierarchical models to quantify global, regional and national ASF intakes between 1990 and 2018 by age group across 185 countries, representing 93% of the world’s child population. Mean ASF intake was 1.9 servings per day, representing 16% of children consuming at least three daily servings. Intake was similar between boys and girls, but higher among urban children with educated parents. Consumption varied by age from 0.6 at <1 year to 2.5 servings per day at 15–19 years. Between 1990 and 2018, mean ASF intake increased by 0.5 servings per week, with increases in all regions except sub-Saharan Africa. In 2018, total ASF consumption was highest in Russia, Brazil, Mexico and Turkey, and lowest in Uganda, India, Kenya and Bangladesh. These findings can inform policy to address malnutrition through targeted ASF consumption programmes.publishedVersio

How prices and income influence global patterns in saturated fat intake by age, sex and world region: a cross-sectional analysis of 160 countries

Objective When considering proposals to improve diets, it is important to understand how factors like price and income can affect saturated fat (SF) intake and demand. In this study, we examine and estimate the influence of price and income on intake across 160 countries, by age and sex, and derive sensitivity measures (price elasticities) that vary by age, sex and world region. Design We econometrically estimate intake responsiveness to income and prices across countries, accounting for differences by world region, age and sex. Intake data by age, sex and country were obtained from the 2018 Global Dietary Database. These data were then linked to global price data for select food groups from the World Bank International Comparison Programme and income data from the World Development Indicators Databank (World Bank). Results Intake differences due to price were highly significant, with a 1% increase in price associated with a lower SF intake (% energy/d) of about 4.3 percentage points. We also find significant differences across regions. In high-­ income countries, median (age 40) intake reductions were 1.4, 0.8 and 0.2 percentage points, given a 1% increase in the price of meat, dairy, and oils and fats, respectively. Price elasticities varied with age but not sex. Intake differences due to income were insignificant when regional binary variables were included in the analysis. Conclusion The results of this study show heterogeneous associations among prices and intake within and across countries. Policymakers should consider these heterogeneous effects as they address global nutrition and health challenges.publishedVersio

Incident type 2 diabetes attributable to suboptimal diet in 184 countries

The global burden of diet-attributable type 2 diabetes (T2D) is not well established. This risk assessment model estimated T2D incidence among adults attributable to direct and body weight-mediated effects of 11 dietary factors in 184 countries in 1990 and 2018. In 2018, suboptimal intake of these dietary factors was estimated to be attributable to 14.1 million (95% uncertainty interval (UI), 13.8–14.4 million) incident T2D cases, representing 70.3% (68.8–71.8%) of new cases globally. Largest T2D burdens were attributable to insufficient whole-grain intake (26.1% (25.0–27.1%)), excess refined rice and wheat intake (24.6% (22.3–27.2%)) and excess processed meat intake (20.3% (18.3–23.5%)). Across regions, highest proportional burdens were in central and eastern Europe and central Asia (85.6% (83.4–87.7%)) and Latin America and the Caribbean (81.8% (80.1–83.4%)); and lowest proportional burdens were in South Asia (55.4% (52.1–60.7%)). Proportions of diet-attributable T2D were generally larger in men than in women and were inversely correlated with age. Diet-attributable T2D was generally larger among urban versus rural residents and higher versus lower educated individuals, except in high-income countries, central and eastern Europe and central Asia, where burdens were larger in rural residents and in lower educated individuals. Compared with 1990, global diet-attributable T2D increased by 2.6 absolute percentage points (8.6 million more cases) in 2018, with variation in these trends by world region and dietary factor. These findings inform nutritional priorities and clinical and public health planning to improve dietary quality and reduce T2D globally.publishedVersio

Author Correction: Predictive equation derived from 6,497 doubly labelled water measurements enables the detection of erroneous self-reported energy intake

Correction to: Nature Food https://doi.org/10.1038/s43016-024-01089-5, published online 13 January 2025. In the version of this article initially published, there was an error in the application of the equation used to predict the total energy expenditure of individuals in the NDNS and NHANES surveys. The output of the equation is in MJ, the two survey intake estimates are in kJ, and while the predicted values were converted to kJ, the value for total energy expenditure, using kJ, was mistakenly inserted into the equations used to derive the extent of over- and underreporting, resulting in an overestimation of underreporting. For instance, the original abstract reported that the level of misreporting was >50%, whereas it is now determined to be 27.4%. The corrected calculations led to revisions throughout the text, Tables 2–4, Figs. 2 and 3, and the Supplementary Information. Other minor errors were also corrected in this new version. For transparent comparison, the original, uncorrected article is available alongside this amendment. The changes have been made in the HTML and PDF versions of the article. The authors sincerely apologise for these errors and any inconvenience caused. Please direct any correspondence to John R. Speakman

Predictive equation derived from 6,497 doubly labelled water measurements enables the detection of erroneous self-reported energy intake

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 >50%. 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