The metabolic energy cost of walking is determined, to a large degree, by body mass, but it is not clear how body composition and mass distribution influence this cost. We tested the hypothesis that walking would be most expensive for obese women compared with obese men and normal-weight women and men. Furthermore, we hypothesized that for all groups, preferred walking speed would correspond to the speed that minimized the gross energy cost per distance. We measured body composition, maximal oxygen consumption, and preferred walking speed of 39 (19 class II obese, 20 normal weight) women and men. We also measured oxygen consumption and carbon dioxide production while the subjects walked on a level treadmill at six speeds (0.50-1.75 m/s). Both obesity and sex affected the net metabolic rate (W/kg) of walking. Net metabolic rates of obese subjects were only approximately 10% greater (per kg) than for normal-weight subjects, and net metabolic rates for women were approximately 10% greater than for men. The increase in net metabolic rate at faster walking speeds was greatest in obese women compared with the other groups. Preferred walking speed was not different across groups (1.42 m/s) and was near the speed that minimized gross energy cost per distance. Surprisingly, mass distribution (thigh mass/body mass) was not related to net metabolic rate, but body composition (% fat) was (r2= 0.43). Detailed biomechanical studies of walking are needed to investigate whether obese individuals adopt novel energy saving mechanisms during walking.

Micronutrient powder (MNP) can reduce iron deficiency in young children, which has been well established in efficacy trials. However, the cost of different delivery platforms has not been determined. We calculated the cost and cost-efficiency of distributed MNP through community-based mechanisms and in health facilities in a primarily rural district in Uganda. An endline survey (n = 1072) identified reach and adherence. During the 9-month pilot, 37,458 (community platform) and 12,390 (facility platform) packets of MNP were distributed. Each packet consisted of 30 MNP sachets. In 2016, total costs were $277,082 (community platform, $0.24/sachet) and $221,568 (facility platform, $0.59/sachet). The cost per child reached was lower in the community platform ($53.24) than the facility platform ($65.97). The cost per child adhering to a protocol was $58.08 (community platform) and $72.69 (facility platform). The estimated cost of scaling up the community platform pilot to the district level over 3 years to cover approximately 17,890 children was $1.23 million (scale-up integrated into a partner agency program) to $1.62 million (government scale-up scenario). Unlike previous estimates, these included opportunity costs. Community-based MNP delivery costs were greater, yet more cost-efficient per child reached and adhering to protocol than facility-based delivery. However, total costs for untargeted MNP delivery under program settings are potentially prohibitive.

Mathematical models can be used to predict exercise performance, but the specific factors contributing to the fatigue component of these models are unknown. This study was designed to determine the contribution of nutrition and psychometric factors to the fatigue component of a performance prediction model for endurance running. It was hypothesized that there would be a positive correlation between both nutritional intake and psychometric factors, and the modeled fatigue. One experienced male marathon and ultra-marathon runner was monitored during 18-weeks of training, involving a weekly performance test (mean ± SD; distance = 10508 ± 113 m), nutritional diaries, and psychometric questionnaires (POMS and RESTQ-Sport). A dose-response based model incorporating two antagonistic components, fitness and fatigue, and training data, was used to calculate modeled performance, which was correlated against actual performance. The performance fit was low (r 2 = 0.24, P = 0.05) when modelled for the total 122 day period, however the fit was increased when the model was divided into two separate training periods (days 1 -66: r 2 = 0.55, P = 0.02; days 66 -122: r 2 = 0.87, P = 0.002). There were significant (P <0.01) positive correlations between modelled fatigue and the nutritional data (Fat r 2 = 0.78), POMS (Vigour r 2 = 0.92), and RESTQ-Sport (General Recovery r 2 = 0.74; Sports Recovery r 2 = 0.71; Global Recovery r 2 = 0.78). The results indicate a high correlation between nutritional intake and scores on the psychometric questionnaires, and the fatigue parameter of the model. Therefore, these factors should be measured and used in models of fatigue.