The lack of comparable DA methods across represented countries is a major obstacle to implement comprehensive and joint nutrition-related programmes for surveillance, programme evaluation, research, and prevention. There is a need to develop new or adapt existing DA methods across countries by employing related research infrastructure that has been validated and standardized in other settings, with the view to standardizing methods for wider use.

ObjectiveTo compare the World Health Organization (WHO) body mass index (BMI)-for-age definition of obesity against measured body fatness in African children.MethodsIn a prospective multicentre study over 2013 to 2017, we recruited 1516 participants aged 8 to 11 years old from urban areas of eight countries (Ghana, Kenya, Mauritius, Morocco, Namibia, Senegal, Tunisia and United Republic of Tanzania). We measured height and weight and calculated BMI-for-age using WHO standards. We measured body fatness using the deuterium dilution method and defined excessive body fat percentage as > 25% in boys and > 30% in girls. We calculated the sensitivity and specificity of BMI z-score > +2.00 standard deviations (SD) and used receiver operating characteristic analysis and the Youden index to determine the optimal BMI z-score cut-off for classifying excessive fatness.FindingsThe prevalence of excessive fatness was over three times higher than BMI-for-age-defined obesity: 29.1% (95% CI: 26.8 to 31.4; 441 children) versus 8.8% (95% CI: 7.5 to 10.4; 134 children). The sensitivity of BMI z-score > +2.00 SD was low (29.7%, 95% CI: 25.5 to 34.2) and specificity was high (99.7%, 95% CI: 99.2 to 99.9). The receiver operating characteristic analysis found that a BMI z-score +0.58 SD would optimize sensitivity, and at this cut-off the area under the curve was 0.86, sensitivity 71.9% (95% CI: 67.4 to 76.0) and specificity 91.1% (95% CI: 89.2 to 92.7).ConclusionWhile BMI remains a practical tool for obesity surveillance, it underestimates excessive fatness and this should be considered when planning future African responses to the childhood obesity pandemic.

This study aimed to assess the validity of mid-arm circumference (MAC), also known as mid-upper arm circumference (MUAC) for classification of high body fatness in Namibian adolescent girls and women, and to test whether classification accuracy of MUAC was higher than the traditional simple proxy for high fatness, the BMI. In 206 adolescent girls aged 13–19 years, and 207 adult women aged 20-40 years we defined obesity conventionally (BMI-for-age Z score ≥2.00, adolescents; adults BMI≥30.0 kg/m2), and also defined obesity using published MAC cut-off values. Deuterium oxide dilution was used to measure TBW to define high body fat percentage (≥30% in the adolescents, ≥38% in the adults), and we compared the ability of BMI and MAC to classify high body fatness correctly using sensitivity, specificity, and predictive values. In the adolescents, obesity prevalence was 9.2% (19/206) using the BMI-for-age and 63.2% (131/206) by TBW; sensitivity of BMI-for-age was 14.5% (95% CI 9.1 to 22.0%) but was improved significantly using MAC of 22.6cm (sensitivity 96.9%; 95% CI 92.1% to 99.3%). In the adults, obesity prevalence was 30.4% (63/207) using BMI and 57.0% (118/207) using TBW, and sensitivity of BMI was 52.5% (95% CI 43.6 to 62.2%), but using a MAC of 30.6cm sensitivity was 72.8% (95% CI 66.4 to 82.6%. Surveillance of obesity in African adolescent girls and adult women is likely to be improved substantially by use of MAC as an alternative to the BMI for age and BMI.

Background: Physical activity (PA) surveillance, policy, and research efforts need to be periodically appraised to gain insight into national and global capacities for PA promotion. The aim of this paper was to assess the status and trends in PA surveillance, policy, and research in 164 countries. Methods: We used data from the Global Observatory for Physical Activity (GoPA!) 2015 and 2020 surveys. Comprehensive searches were performed for each country to determine the level of development of their PA surveillance, policy, and research, and the findings were verified by the GoPA! Country Contacts. Trends were analyzed based on the data available for both survey years. Results: The global 5-year progress in all 3 indicators was modest, with most countries either improving or staying at the same level. PA surveillance, policy, and research improved or remained at a high level in 48.1%, 40.6%, and 42.1% of the countries, respectively. PA surveillance, policy, and research scores decreased or remained at a low level in 8.3%, 15.8%, and 28.6% of the countries, respectively. The highest capacity for PA promotion was found in Europe, the lowest in Africa and low- and lower-middle-income countries. Although a large percentage of the world’s population benefit from at least some PA policy, surveillance, and research efforts in their countries, 49.6 million people are without PA surveillance, 629.4 million people are without PA policy, and 108.7 million live in countries without any PA research output. A total of 6.3 billion people or 88.2% of the world’s population live in countries where PA promotion capacity should be significantly improved. Conclusion: Despite PA is essential for health, there are large inequalities between countries and world regions in their capacity to promote PA. Coordinated efforts are needed to reduce the inequalities and improve the global capacity for PA promotion.