Previous studies have found Kenyan endurance runners to be in negative energy balance during training and prior to competition. The aim of the present study was to assess energy balance in nine elite Kenyan endurance runners during heavy training. Energy intake and expenditure were determined over 7 d using weighed dietary intake and doubly labelled water, respectively. Athletes were on average in negative energy balance (mean energy intake 13 241 (SD 1330) kJ/d v. mean energy expenditure 14 611 (SD 1043) kJ/d; P¼0·046), although there was no loss in body mass (mean 56·0 (SD 3·4) kg v. 55·7 (SD 3·6) kg; P¼ 0·285). The calculation of underreporting was 13 % (range 2 24 to þ9 %) and almost entirely accounted for by undereating (9 % (range 2 55 to þ 39 %)) as opposed to a lack of significant underrecording (i.e. total water intake was no different from water loss (mean 4·2 (SD 0·6) l/d v. 4·5 (SD 0·8) l/d; P¼0·496)). Fluid intake was modest and consisted mainly of water (0·9 (SD 0·5) l/d) and milky tea (0·9 (SD 0·3) l/d). The diet was high in carbohydrate (67·3 (SD 7·8) %) and sufficient in protein (15·3 (SD 4·0) %) and fat (17·4 (SD 3·9) %). These results confirm previous observations that Kenyan runners are in negative energy balance during periods of intense training. A negative energy balance would result in a reduction in body mass, which, when combined with a high carbohydrate diet, would have the potential in the short term to enhance endurance running performance by reducing the energy cost of running.Energy expenditure: Doubly labelled water: Energy intake: Undereating: Intense high-altitude training: East African endurance athletes Male Kenyan middle-and long-distance runners have dominated athletics since the 1960s, but until recently diet and nutrition in these athletes had not been comprehensively investigated. The diet of nine elite Kenyan endurance runners was investigated over a 7 d training period 1 week before the Kenyan national cross-country trials (Onywera et al. 2004). Energy intake (EI) was assessed by weighed dietary record and was significantly lower than energy expenditure (EE) as assessed by the physical activity ratio (mean EI 12 486 (SD 1225) kJ/d v. physical activity ratio 15 069 (SD 497) kJ/d), suggesting that the athletes were in negative energy balance prior to competition. The mean difference of 2585 kJ/d between EI and EE accounted precisely for the loss in body mass over the 7 d period (mean body mass 58·9 (SD 2·7) kg v. 58·3 (SD 2·6) kg, where 1 kg was assumed to be equivalent to 30 000 kJ; Westerterp et al. 1995).These results corroborated those of an earlier study evaluating the nutrient intake of Kenyan runners (Mukeshi & Thairu, 1993). The reported EI in that study was low (9781 kJ/d), and considering that the athletes were training intensely, the validity of these results was questioned by the authors of the only other study to have assessed the dietary intake of Kenyan runners (Christensen et al. 2002). Those authors studied twelve adolescent (15-20-year-old) male Kenyan r...

The food and macronutrient intake of elite Kenyan runners was compared to recommendations for endurance athletes. Estimated energy intake (EI: 2987 ± 293 kcal; mean ± standard deviation) was lower than energy expenditure (EE: 3605 ± 119 kcal; P < 0.001) and body mass (BM: 58.9 ± 2.7 kg vs. 58.3 ± 2.6 kg; P < 0.001) was reduced over the 7-d intense training period. Diet was high in carbohydrate (76.5%, 10.4 g/kg BM per day) and low in fat (13.4%). Protein intake (10.1%; 1.3 g/kg BM per day) matched recommendations for protein intake. Fluid intake was modest and mainly in the form of water (1113 ± 269 mL; 0.34 ± 0.16 mL/kcal) and tea (1243 ± 348 mL). Although the diet met most recommendations for endurance athletes for macronutrient intake, it remains to be determined if modifying energy balance and fluid intake will enhance the performance of elite Kenyan runners.

Background. The understanding of obesity as a growing health problem in Africa and Tanzania in particular is hampered by lack of data as well as sociocultural beliefs in which overweight and obesity are revered. This study sought to determine the prevalence of overweight and obesity among primary school children aged 8–13 years in Dar es Salaam, Tanzania. Method. A cross-sectional analytical research design was used to study overweight and obesity in primary schools in Dar es Salaam, Tanzania. The target population was 150,000 children aged 8–13 years. Stratified random sampling was used to select 1781 children. Weight and height were taken and WHO standards for children were used to determine weight status. Results. Findings showed that the prevalence of overweight and obesity was 15.9% and 6.7%, respectively (N = 1781). However, 6.2% of the children were underweight. There were significant differences in mean BMI between children in private and public schools (p = 0.021), between male and female (p < 0.001), and across age groups of 8–10 and 11–13 years (p < 0.001). Conclusion. The prevalence of overweight and obesity among primary school children is significant and requires management and prevention strategies.

BackgroundAlthough habitual physical activity energy expenditure (PAEE) and cardio-respiratory fitness (CRF) are now well-established determinants of metabolic disease, there is scarcity of such data from Africa. The aim of this study was to describe objectively measured PAEE and CRF in different ethnic populations of rural Kenya.MethodsA cross-sectional study was done among 1,099 rural Luo, Kamba, and Maasai of Kenya. Participants were 17–68 years old and 60.9% were women. Individual heart rate (HR) response to a submaximal steptest was used to assess CRF (estimated VO2max). Habitual PAEE was measured with combined accelerometry and HR monitoring, with individual calibration of HR using information from the step test.ResultsMen had higher PAEE than women (∼78 vs. ∼67 kJ day−1 kg−1, respectively). CRF was similar in all three populations (∼38 and ∼43 mlO2·kg−1 min−1 in women and men, respectively), while habitual PAEE measures were generally highest in the Maasai and Kamba. About 59% of time was spent sedentary (<1.5 METs), with Maasai women spending significantly less (55%). Both CRF and PAEE were lower in older compared to younger rural Kenyans, a difference which was most pronounced for PAEE in Maasai (−6.0 and −11.9 kJ day−1 kg−1 per 10-year age difference in women and men, respectively) and for CRF in Maasai men (−4.4 mlO2·min−1 kg−1 per 10 years). Adjustment for hemoglobin did not materially change these associations.ConclusionPhysical activity levels among rural Kenyan adults are high, with highest levels observed in the Maasai and Kamba. The Kamba may be most resilient to age-related declines in physical activity. Am. J. Hum. Biol. 2012. © 2012 Wiley Periodicals, Inc.

These results demonstrate that elite Kenyan endurance runners remain well hydrated day-to-day with an ad libitum fluid intake; a pattern and volume of fluid intake that is consistent with previous observations of elite Kenyan endurance runners.

Breakfast as the first meal of the day is one of the most skipped meals by adolescent students. Several research studies indicated that unhealthy food consumption and breakfast skipping contribute to low glyceamic level, poor cognition and academic performance as well as increasing prevalence of poor nutritional status among children (5-19) years. This study determined prevalence of breakfast and food consumption pattern and nutritional status of students in public secondary schools. This study's design was cross-sectional and multistage random sampling was used to select 515 participants, (343 girls and 172 boys) from 8 public secondary schools in study area. Self-reported 24 h recall dietary questionnaire was used to collect data on breakfast and food consumption of participants. Digital bathroom scale and stadiometer were used to collect data on weight and height of participants. Data were cleaned, coded and analyzed using (SPSS Version 20) and WHO anthroplus software. Results indicated that 54.0% o f participants were (15/6-18/5) years/months, 77% consumed breakfast daily and 52% added (1-2) teaspoons of sugar daily to beverages. Furthermore, participants mostly consumed refined carbohydrates such as doughnut and biscuits (2.36±0.99 times per week), while mostly consumed fat and oil such as vegetable oil in soup (2.54±0.96 times per week), mostly consumed snacks such as fish pies and fish rolls (2.71±0.87 times per week), while mostly consumed protein such as eggs (2.15±0.69 times per week) and mostly consumed fruit such as pawpaw (2.56±0.89 times per week). Overall Nutritional status indicated that underweight was 29.1%, overweight was 4.7%, obesity was 0.2 and 66.0% were of normal weight. Furthermore, Nutritional status for both boys and girls indicated that underweight was (47.7 and 19.8%), overweight was (0.6 and 6.7%), obese was (0 and 0.3%) and normal weight was (51.7 and 73.2%), respectively. Relationship between food consumption and nutritional status of participants was positive but not significant (r = 0.012, p = 0.785). Analysis of variance showed positive significant relationship (p = 0.001) between food consumption and nutritional status. Despite that majority of participants consumed breakfast, the participants low frequency of food consumption is still of concern and this may influence their nutritional status negatively. Parents and other stakeholders should encourage breakfast consumption by participants as well as the consumption of nutritious food in order to meet their daily dietary allowance.

Objectives Physical activity is beneficial for metabolic health but the extent to which this may differ by ethnicity is still unclear. Here, the objective was to characterize the association between physical activity energy expenditure (PAEE) and cardiometabolic risk among the Luo, Kamba, and Maasai ethnic groups of rural Kenya. Methods In a cross‐sectional study of 1084 rural Kenyans, free‐living PAEE was objectively measured using individually‐calibrated heart rate and movement sensing. A clustered metabolic syndrome risk score (zMS) was developed by averaging the sex‐specific z‐scores of five risk components measuring central adiposity, blood pressure, lipid levels, glucose tolerance, and insulin resistance. Results zMS was 0.08 (−0.09; −0.06) SD lower for every 10 kJ/kg/day difference in PAEE after adjustment for age and sex; this association was modified by ethnicity (interaction with PAEE P < 0.05). When adjusted for adiposity, each 10 kJ/kg/day difference in PAEE was predicted to lower zMS by 0.04 (−0.05, −0.03) SD, without evidence of interaction by ethnicity. The Maasai were predicted to have higher cardiometabolic risk than the Kamba and Luo at every quintile of PAEE, with a strong dose‐dependent decreasing trend among all ethnicities. Conclusion Free‐living PAEE is strongly inversely associated with cardiometabolic risk in rural Kenyans. Differences between ethnic groups in this association were observed but were explained by differences in central adiposity. Therefore, targeted interventions to increase PAEE are more likely to be effective in subgroups with high central adiposity, such as Maasai with low levels of PAEE.

Background: In Low- and Middle-Income Countries (LMIC), including Kenya, undernutrition has been the most significant contributor to child morbidity and mortality. Knowledge and practices of mothers/caregivers have been identified as a key sustainable factor for consideration in determining the nutritional status of children. The study aim was to determine how caregiver knowledge and socio-economic status will impact on nutritional status of children under 5 years. Methods: This study was conducted in Kwale County, Kenya, to assess baseline maternal and child parameters. Seven hundred pairs; children and their primary caregivers were sampled at baseline. Results: A total of 681 households comprised of caregiver and index child pair participated in the survey from the sampled 700. Knowledge scores of food functions, breastfeeding and complementary feeding were combined to assess caregivers’ nutritional knowledge with a maximum score of 24. The median score was 11 (IQR: 9-12) and ranged from 0 to 24. Those with scores of 12 and above (50% plus) were 230 (33.2%). Stunting was 29.8% and the level of under-weight was 16.4%. No significant association was found between nutritional knowledge of the caregivers and nutritional indicators of children under 5 years, but there were significant differences (P= 0.002) in the Knowledge score of caregivers between the five wealth quintiles. Conclusion: Most of the caregivers did not have any nutritional knowledge which was assessed as knowledge of food groups and sources and functions of different foods as well as knowledge in breastfeeding and complementary feeding.