Sports Nutrition Knowledge, Source of Nutrition Information and Dietary Consumption Pattern of Ugandan Endurance Athletes: A cross-sectional study of the Sebei Sub-Region

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Folasire, Nonhlanhla S. Mkumbuzi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4959741/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 May, 2025 Read the published version in BMC Sports Science, Medicine and Rehabilitation → Version 1 posted 4 You are reading this latest preprint version Abstract Background Athletes’ nutrition knowledge depends on the sources of nutrition information they are exposed to and their social status. Currently, there is a dearth of literature on the nutrition knowledge of Ugandan athletes. This study assessed endurance athletes’ sports nutrition knowledge, sources of nutrition information, and their dietary consumption patterns. Methods A cross-sectional descriptive study including 100 purposively selected (middle and long distance) athletes from four Athletic Management camps was conducted in Kapchorwa district, Uganda. Using an interviewer-administered questionnaire, trained research assistants collected athletes’ demographic information, knowledge, practices, sources of nutrition information and consumption patterns. ANOVA, Independent t-test, Chi-square analysis, and Binary logistic analyses were done using SPSS® software version 23.0. Results Most athletes 74.0% (n = 74) in this study were aged between 15–17 (17.9 ± 4.0) years with at least 2 years’ experience in athletics. Majority 68.0% (n = 68) of the athletes had good sports nutrition knowledge while 32.0% (n = 32) showed poor knowledge. About 88.0% (n = 88) knew that vitamin consumption can enhance recovery after training. Athletic trainers 49.0% (n = 49) and family/parents 28.0% (n = 28) were primary sources of nutrition information, while nutritionists/dietitians 5.0% (n = 5) and the internet 4.0% (n = 4) were less consulted. Cereals were the most consumed food group 72.0% (n = 72), followed by legumes and nuts 67.0% (n = 67) while the least consumed foods were milk/egg 33.0% (n = 33), fish 25.0% (n = 25) and meat/poultry 13.0% (n = 13). Good sports nutrition knowledge was associated with adequate dietary practices (p = 0.009). Sports nutrition knowledge differed significantly with age group (F = 4.566, p = 0.013), and between female and male (F = 21.884, p < 0.000) athletes. Age group was a significant predictor (β = 1.925, Ex(β) = 6.853, C. I = 0.882–36.096, p = 0.023) of sports nutrition knowledge. Conclusions In this study endurance athletes had good sports nutrition knowledge, and relied primarily on their coaches/trainers for sports nutrition information. It is recommended that athletic trainers be offered supplementary training in sports nutrition to ensure proper nutrition knowledge dissemination among athletes. Athlete Nutrition Sports Knowledge Endurance African athletes Figures Figure 1 Figure 2 Introduction Nutritional intake for athletes is an important part of their adequate nourishment and well-being ( 1 ). Nutrition is a key component in improving an athlete’s adaptation to endurance training and its effects ( 2 ). Endurance activities require extreme physical and mental strength from an athlete and such events include those lasting approximately 26 minutes to about 4 hours ( 2 ). These events are often associated with a high turnover of nutrients, consequently predisposing athletes to a risk of nutrient depletion on the field of play ( 3 ). As such, athletes are therefore recommended macronutrient intake of about 40%-65% carbohydrates, 30%-55% fat, and 10%-35% protein in their meals supplemented with micronutrients like vitamins C and D and Iron when deficiency cases ( 1 , 2 , 4 ). Sports nutrition knowledge (SNK) is an individual’s understanding of concepts that relate to how to maintain a healthy body mass; manage body fluid balance; and fuelling techniques before, during, and after training or competition; supplement use; and knowledge of nutrition for athletic performance ( 5 ). Good nutrition among athletes is reported to strongly influence knowledge and attitudes toward it ( 6 , 7 ). Further, SNK and access to good nutrition are also determined by one’s social status: income level, education, age, and sex ( 8 – 12 ). Several reports from athletes and non-athlete populations show that positive dietary changes are associated with good nutrition knowledge( 13 , 14 ). Research on 24-hour ultramarathon athletes reported positive dietary changes among those who had high knowledge scores( 15 ). This implies that dietary practices based on inaccurate information and misconceptions can negatively impact health and, eventually athletic performance ( 11 ). Data on elite African athletes’ nutrition knowledge especially in Uganda are generally scarce. However, some data are available for Kenyan elite endurance athletes, Ugandan recreational athletes, and Ugandan university athletes. These data show that athletes have poor nutrition knowledge of supplementation and that their sources of nutrition information are often not credible( 16 – 18 ). Additionally, these athletes rarely consult with registered dietitians and/or sports nutritionists( 18 ), which may further predispose them to misinformation and associated health risks ( 16 ). Despite the elite level at which Ugandan endurance athletes compete and their successes at this level, sports nutrition knowledge, sources of nutrition information, and dietary consumption patterns (DCP) of Ugandan endurance athletes remain unclear. Therefore, this study sought to investigate sports nutrition knowledge, sources of nutrition, and dietary consumption patterns of endurance athletes in the Sebei sub-region of Uganda. Methods And Materials Study design A cross-sectional, descriptive study of Ugandan endurance athletes in the Sebei sub-region of Uganda. Study site This study was conducted in the Eastern region of Uganda which for years has produced the most dominant athletes on the global scene, especially in distance events with the 10,000m world records claimed in the Tokyo Olympic Games 2020 and the Budapest World Championship 2023 ( 19 ). This region hosts the Ugandan National High Altitude Training Centre (NHATC) situated 2,550m above sea level and where the majority of Ugandan endurance athletes train ( 20 ). Population The study population was approximately 10,000 athletes in the Sebei sub-region; namely, Kapchorwa, Kween, and Bukwo Districts. Sampling and sample size A purposive sampling technique was used to select Kapchorwa among three ( 3 ) sporting districts and four ( 4 ) athletic management camps in Kapchorwa; and a pragmatic purposive approach to select 100 male and female athletes as study participants. The participants selected were middle-distance and long-distance athletes. The minimum required sample for the study was determined by Yamane’s formulae ( 21 ) and calculated as below. $$\:\text{n}\:=\:\text{N}/(1+\text{N}{\left(\text{x}\right)}^{2})$$ Whereby n = Sample size, N = Total population, x = Level of Precision, 1 = constant, N = 10,000 athletes, x = 10% n = 10,000/ (1+(10,000(1/100)) n = 99.009, n = 99.09 which is approximately 100 respondents. The calculated minimum required sample size was 100 athletes at a priori alpha level of 0.05. Data Collection Data were collected between October and November 2023 and involved 100 endurance athletes: 31.0% (n = 31) females and 69.0% (n = S69) males. Master’s level trained research assistants used an adapted SNK questionnaire to assess athletes' sports nutrition knowledge in their training camps. The questionnaire had 48 questions in total: on demographics (8 items), sports nutrition knowledge (15 items), dietary practices (15 items), and sources of nutrition information (3 items). A semi-quantitative Food Frequency Questionnaire (7 items) assessed the dietary consumption patterns, and food charts of locally available foods were availed to help participants to recall food consumed from different groups. On pilot testing, the questionnaire took approximately eight ( 8 ) minutes per athlete. Responses were recorded as TRUE/FALSE for nutrition knowledge and practice questions and YES/NO for other sections. The questionnaire in the current study obtained a Cronbach alpha of 0.74, comparable to that reported by the designer ( 22 ). Human ethics and consent to participate Participants were briefed on the study's purpose and the risks and benefits of participating. All participants provided verbal and written consent before participating in the study. With the majority of our participants younger than 18 years old, they provided assent, and written consent was obtained from their parent/guardian while those older than 18 years provided written consent. The study adhered to Helsinki Declaration guidelines. Ethical clearance for this study was obtained from the Uganda National Council of Science and Technology (UNCST) (REF: HG2674ES) and The Pan African University Life and Earth Science Institute (Including Health and Agriculture) - PAULESI, Ibadan, Nigeria (REF: ADM/23/249). Data Analysis and Management Quantitative data were entered into Microsoft Excel® version 2016 (Microsoft Corporation) and were analysed using SPSS software version 23.0 (Chicago, SPSS Inc). Data were reported as percentages, means, frequencies, and statistics of inference such as One-way analysis of variance (ANOVA), Logistic regression, and Chi-square were performed on the data. All correct responses of respondents were summed, and an average was computed to determine scores for the participants' nutrition knowledge and practice. The overall score was determined by summing all correctly answered question items. A percentage was generated from the scores, and classification of respondents, differentiating those that scored below (poor knowledge) and above (good knowledge) the average score. Chi-square analyses were performed to ascertain possible relationships between variables of interest, e.g., nutrition knowledge categories with dietary consumption patterns, and also to establish relationships existing between nutrition knowledge categories and dietary practices and demographic information of the athletes. One way-analysis of variance (ANOVA) was used to test the variation of the nutrition knowledge among different age groups and competition levels of athletes. An independent student t-test was tested to identify possible differences in knowledge scores for the sex and income categories of the respondents. Logistic regression analysis was performed to identify which independent variable was the best predictor for nutrition knowledge among the athlete population. Significant socio-economic variables were coded as dummy variables imputed and ran in the model and the most significant with close to p = 0.00 was considered the best predictor of knowledge. The significance level was set at p < 0.05. Results Social-demographic information Of the 100 participants, 31.0% (n = 31) were female and 69.0% (n = 69) were male. The largest proportion 75.0% (n = 75) of athletes were aged between 15–17 (17.9 ± 4.0) years while the least number 12.0% (n = 12) was from the age category 25–35 (17.9 ± 4.0) years. The highest level of education attained by 54.0% (n = 54) was secondary school, followed by 43.0% (n = 43) who attained primary school level of education and only 3.0% (n = 3) of athletes reported in this study had attained tertiary-level education. All 100.0% (n = 100) of respondents lived in rural areas (villages). There were twice as many middle-distance 67.0% (n = 67) compared to long-distance 33.0% (n = 33) athletes. The majority 79.0% (n = 793) of the respondents reported having a monthly family income of less than Uganda Shillings (UGX) 130,000 while only 21.0% (n = 21) earned more than Uganda Shillings (UGX) 130,000 monthly as seen in Table 1 below. Nutrition knowledge scores Most 68.0% (n = 68) of the athletes had good knowledge scores on sports nutrition while 32.0% (n = 32) of the respondents had poor knowledge of sports nutrition. Similarly, 44.0% (n = 44) of athletes had inadequate dietary practices while 56.0% (n = 56) had adequate dietary practices. Nutrition knowledge Table 2 Sports nutrition knowledge (SNK) among Ugandan endurance athletes from the Sebei sub-region (N = 100). Questions Correct n (%) Incorrect n (%) 1) How many times should we eat in a day? 97 (97.0) 3(3.0) 2) Do you think foods rich in carbohydrates are the main sources of energy in the body? 100 (100.0) 0 (0.0) 3) As an athlete, my food intake should increase 95 (95.0) 5 (5.0) 4) Can the lack of iron in the diet result in fatigue, injury, and illness? 70 (70.0) 30 (30.0) 5) Do you think sports drinks are the best to replace body fluids lost on the field of play? 62 (62.0) 38 (38.0) 6) Are vitamins good sources of energy? 86 (86.0) 14 (14.0) 7) Alcohol consumption can negatively affect the absorption and utilization of nutrients? 24 (24.0) 76 (76.0) 8) Eating of snacks is as good as eating home-prepared foods? 32 (32.0) 68 (68.0) 9) Do you think foods rich in sugar, jam and honey are suitable sources of energy for athletes? 93 (93.0) 7 (7.0) 10) The last meal before a competition should be consumed at least 3 hours before a competition 57 (57.0) 43 (43.0) 11) Males and females of the same group use up the same amount of energy during exercise 43 (43.0) 57 (57.0) 12) Fruits and vegetables are important sources of vitamins and minerals? 89 (89.0) 11 (11.0) 13) Vitamins can enhance recovery after competition 88 (88.0) 12 (12.0) 14) Do you think milk and milk products are good sources of calcium? 82 (82.0) 18 (18.0) 15) How many classes of nutrients do we have? 42 (42.0) 58 (58.0) Most respondents 97.0% (n = 97) knew the correct number of times an individual should eat per day and 3.0% (n = 3) did not. With regards to sources of energy, all 100.0% (n = 100) of the athletes knew that foods rich in carbohydrates are the main source of energy for the body. Nearly all 95.0% (n = 95) of the respondents had the right knowledge that as an athlete, food consumption should be higher than compared to the general population. The knowledge that iron deficiency in the diet can cause fatigue, illness, and injury was known by at least 70.0% (n = 70) while 30.0% (n = 30) were not knowledgeable. About 62.0% (n = 62) of athletes knew that sports drinks more likely aid rehydration when body fluids are lost in the field of competition; 86.0% (n = 86) knew that vitamins are not a good source of energy; 76.0% (n = 76) had good knowledge that drinking alcohol affects digestion. Slightly more than half 57.0% (n = 57) of the athletes knew that a pre-event meal should be consumed at least 3 hours before the event. The majority of the athletes 88.0% (n = 88) responded correctly to the statement that vitamins can enhance recovery after competition. A detailed summary is in Table 2 above . Dietary practice The study also found that 64.0% (n = 64) of the athletes had adequate DP, while 36.0% (n = 36) had inadequate DP. Table 3 below shows that 27.0% (n = 27) of the endurance athletes in this study use supplements such as multivitamins, while 73.0% (n = 73) do not. Most respondents 97.0% (n = 97) consume fruits and vegetables often while 3.0% (n = 3) do not; 36.0% (n = 36) skipped the pre-event meal while 64.0% (n = 64) of them did not skip the pre-event meal. Table 3 Dietary practices among Ugandan endurance athletes from the Sebei sub-region (N = 100). Questions Yes n (%) No n (%) 1) Do you use supplements like multivitamin as an athlete? 27(27.0) 73(73.0) 2) I consume lots of fruits and vegetables 97(97.0) 3(3.0) 3) I skip meals before a competition or an event 36(36.0) 64(64.0) 4) I eat just before an event 63(63.0) 37(37.0) 5) I eat just after an event 84(84.0) 16(16.0) 6) I consume sports drinks every day during practice or when I feel dehydrated 49(49.0) 51(51.0) 7) I eat an adequate diet daily 88(88.0) 12(12.0) 8) I change my pattern of eating at the time of a competition 90(90.0) 10(10.0) 9) I always take my breakfast daily 97(97.0) 3(3.0) 10) I consume lots of water during and after training/competition 100(100.0) 0(0.0) 11) I always eat at least one hour before training/competition 46(46.0) 54(54.0) 12) I prefer snacks to a special diet before training and competition 42(42.0) 58(58.0) 13) I eat at least three times daily 100(100.0) 0(0.0) 14) I consume milk and milk products daily 48(48.0) 52(52.0) 15) I consume alcohol to enhance my performance 0(0.0) 100(100.0) Source of nutrition knowledge. As shown in Fig. 1 below, athletic trainers 49.0% (n = 49), parents/family 28.0% (n = 28), others (doctors, peers, school) 6.0% (n = 6), nutritionists/dietitians 5.0% (n = 5), magazines 4.0% (n = 4), TV/Radio 4.0% (n = 4) and the internet 4.0% (n = 4) were consulted for nutrition information. Only 9.0% (n = 9) of participants had previously undertaken a nutrition course. Dietary consumption pattern Most athletes 77.0% (n = 77) frequently consumed from the cereal food group (e.g., posho, rice, wheat, sorghum, millet), 72% (n = 72) consumed from legumes/nuts group (e.g., groundnuts, sunflower seed, pumpkin seed, bean/soya seed), 55% (n = 55) consumed from vegetables/fruits group, (e.g., watermelon, mbogoya, orange, mangoes, cabbage, sukuma wiki, suja), while 46% (n = 46) consumed from root/tubers group. The least consumed food groups were milk/egg 33.0% (n = 33), fish/mukene 25.0% (n = 25) and meat/poultry 13.0% (n = 13). Sports nutrition knowledge and other variables There was a significant relationship between SNK and athletes’ family monthly income (p = 0.003), relationship status (p = 0.033), age group (p = 0.001), and athletic event (p = 0.038), but not with the highest level of education (p = 0.481), sex of athlete (p = 0.176), and with many years of participation in athletics (p = 0.272). Table 4 above shows a summary of the results. Table 5 Binary Logistic analysis of significant socio-demographic variables of Ugandan athletes. Variable β Ex(β) P C.I (95%) Lower Upper Age group 1.925 6.853 0.023* 0.882 36.096 Athletic event 1.233 3.431 0.059 0.956 12.317 Relationship status -0.880 0.415 0.047* 0.174 0.989 Monthly family income 2.010 7.461 0.065 0.882 63.144 Age was the best predictor for SNK (p = 0.023; C.I = 0.882–36.096). For every unit (1.925) increase in age, an athlete’s odds of being classified as knowledgeable were nearly seven (6.9) times. The model with all the significant socio-demographic variables accurately predicted those with good knowledge 85.0% of the time as seen in Table 5 above. SNK was significantly associated with root tuber consumption (p < 0.05) but not with the rest of the food groups shown below in Table 6 and there were no associations observed between SNK and sources of nutrition information. Also, having had a nutrition course previously did not correlate with nutrition knowledge (p = 0.159). All results are shown in Table 7. Additionally, good SNK was significantly associated with adequate dietary practices (p = 0.009) as shown below in Table 8 . SNK was different between athletes of different sex (p < 0.000), with different respondents’ family income levels (p = 0.018), with different athletic events (p < 0.05), with different age groups (p = 0.013), and with different education levels of respondents (p = 0.024). SNK did not differ with athletes’ relationship status (p = 0.746) results in Table 9 below. Table 8 SNK and DP score category and Bivariate analysis for SNK and DP of Ugandan endurance athletes (N = 100). Variable Category Respondents score n % SNK Poor Good 32 68 32.0 68.0 DP Poor Good 44 56 44.0 56.0 Bivariate analysis SNK \(\:{x}^{2}\) df p DP Poor Good 6.895 1 0.009* Poor Good 8 24 36 32 *Significant at p < 0.05 Table 9 Independent t-test analysis and ANOVA- analysis to determine variation in SNK within Ugandan athletes’ demographic (N = 100). Variables Mean SD F t P Sex Male Female 24.70 25.13 2.198 0.763 21.884 -1.067 0.000 Family monthly income Low High 24.58 25.76 1.952 1.221 5.750 -2.630 0.018 Athletic event Middle distance Long distance 24.81 24.88 2.210 0.927 21.601 − .181 0.000 ANOVA-analysis Variable df F P Age group 2 4.566 0.013 Relationship status 3 0.411 0.746 Education 2 3.874 0.024 Discussion From the findings, it is noted that male respondents constituted a bigger proportion than females. This is because generally, sports is strongly gendered in African settings and society tends to discourage females from participating in sports ( 23 ). Our findings relate to a previous study by Baranauskas et al, ( 24 ) where male athletes were more than female athletes. Additionally, we showed knowledge differences between the sexes, which differs from other studies such as Magee et al, ( 25 ). Our observed sports nutrition knowledge differences with sex could be because female adolescents are generally aware of their body image and tend to seek nutritional counselling more than their male counterparts( 26 ). This also implies that there may be a need to provide sex-specific nutrition knowledge to athletes to accommodate this sex difference. The majority of endurance athletes in this study were late adolescents and had participated for less than 2 years in athletics. This is similar to the cohort from Baranauskas et al., ( 24 ) whose respondents had a mean age of 17 years, but contrasts with a previous study conducted among Kenyan endurance athletes who were much older with the majority between 23–28 years of age with less than 3 years of participation, which is somewhat similar to our study findings ( 17 ). The highest academic achievement of most athletes in our study was secondary school level, which is to be expected given their age and generally, such education levels are commonly reported in studies of Kenyan and Ugandan athletes ( 16 , 17 ). Our report contrasts other studies whose respondents had certificates, tertiary/ university degrees as their highest level of education ( 27 – 29 ). Level of education has been associated with the level of SNK in other studies of physically active individuals ( 16 , 17 ) and in our cohort may have implications for the development of future education materials, as these need to be tailored to the level of education of our cohort. The study found that most athletes acknowledge that pre-event meals should be consumed at least three hours prior to the event, while a significant proportion of them did not know this. More than half of athletes were not knowledgeable about the six classes of nutrients. A big proportion of respondents had good knowledge that athletes’ food consumption should be higher than in non-athletes. Almost three-quarters of the athletes had the right knowledge that sports drinks are best to replace fluids lost in the field of play. In addition, the majority of the respondents in the current study had good dietary practices. This is similar to a study on undergraduate athletes from Nigeria where 63% of respondents reported adequate nutrition practices ( 22 ), as well as a study on Nepali athletes where 50% had good nutrition practice scores ( 30 ). Female athletes displayed better dietary practices compared to males in the current study just as was observed in Koch et al’s study of the Nemonit population ( 10 ). Almost 75% of the athletes did not skip meals while almost every athlete always ate their breakfast, as shown in other cohorts ( 31 ). All respondents in this cohort take a lot of water during training and eat at least three meals a day. This is consistent with the findings of previous studies on in-training water consumption ( 22 , 31 ) but contrasts with Oladunni & Sanusi., ( 32 ) who reported that 77% of athletes from Nigeria skip meals. The present findings also concur with the findings of Folasire et al., ( 22 ), which reported that 82.7% of athletes ate a pre-event meal at least three hours before the event; 57% agreed that athletes' food intake should be higher than non-athletes; 63.6% reported good knowledge of the six classes of nutrients. Further, athletes in our study displayed a high level of sports nutrition knowledge when it came to the use of recovery strategies with 75% of endurance athletes having good knowledge of the consumption of vitamins to enhance recovery. This finding was corroborated by studies that show that vitamin intake enhances muscle recovery by negating the effects of exercise-induced muscle damage( 33 , 34 ). Such recovery strategies could be adopted by endurance athletes following this position statement( 2 ). The present results are also corroborated by previous studies that report good sports nutrition knowledge in 56% of Kenyan endurance athletes and 69.42% of Ghanaian athletes ( 17 , 29 ). However, the current study contrasts the findings of Klein et al., ( 31 ) that reported low sports nutrition among their athletes. This current study further disagrees with a more recent study of young athletes that reported poor average sports nutrition knowledge of its male and female respondents ( 25 ). Our study found a statistically significant relationship between athletes’ sports nutrition knowledge and dietary practice which correlates with a review that established that nutrition knowledge had a weak positive relationship with positive dietary changes ( 13 ). Even though our results did not show a relationship between previously attending a nutrition course with sports nutrition knowledge, this phenomenon of ‘when we know better, we do better’ has also been demonstrated in other studies on sports nutrition knowledge ( 28 , 31 ), and in other health domains, such as good menstrual hygiene and child caregiving where higher literacy is associated with better behaviours ( 35 , 36 ). Hence, it is important to enhance athletes’ sports nutrition knowledge. It is noteworthy, however, that in Uganda, Nassanga et al., ( 35 ) reported that a combination of factors interplay when it comes to how knowledge is translated into proper dietary practices. Primarily, poverty, food security, the attitudes of the individuals, and the nature of jobs people are engaged in are key determinants of nutritional knowledge transfer. In our cohort, in particular, the median household income is Uganda Shillings (UGX) 100,000 which was not only associated with knowledge, but household income may not be enough to allow players to consume all the food groups in the requisite amounts. Hence, despite Ugandan athletes being knowledgeable about sports nutrition, they may not have the resources available to practice optimum sports nutrition due to low socioeconomic status ( 37 ). Concerning the source of nutrition information, the majority of the respondents identified athletic trainers as a popular source of knowledge used in the camps, followed by parents/ family. Nutritionists/Dietitians, internet, TV/Radio, magazines, and others like doctors, peers, and schools were rarely consulted for sports nutrition information. These study findings are similar to other studies, which found that coaches/trainers are popular sources athletes rely on for nutrition knowledge. ( 22 , 38 , 16 , 29 , 39 ). However, this contrasts with Kathure et al., ( 17 ) who showed that 60% of their cohort relied on the Internet as the main source of nutrition information. Further, findings from UK runners show that 33–82% of them relied on internet/web sources for nutrition information ( 40 ). Interestingly, peer-reviewed literature was identified as the main source of information by Hispanic ultra-endurance athletes ( 42 ), while nutritionists and dietitians were popular sources amongst athletes from Australia ( 23 ). In our cohort, less than a tenth consulted a nutritionist for nutrition information. This result was expected because of the lack of nutritionists/dietitians in athlete support staff in low and middle-income countries (LMICs) such as Uganda, due to inadequate budgets to cover the cost of such specialized staff ( 16 ). Generally, there exists a gap in the enrolment and training of nutritionists/dietitians within tertiary institutions in low and middle-income countries (LMICs) ( 44 , 45 ). In Uganda, the majority of graduate nutritionists and dietitians from tertiary institutions enter the job market with incompetencies in some crucial domains of practice ( 46 ). In contrast, high-income countries (HICs) tend to have specialized and rigorously licensed and certified athlete nutrition staff ( 43 , 47 ). Access to credible knowledge from nutritionists/dietitians could help inform dietary changes that in turn promote the healthy nutritional status of athletes ( 48 , 49 ) and reduce the likelihood of misinformation ( 4 , 50 ). Since African athletes rely primarily on their coaches/trainers for nutrition knowledge, it may be prudent to incorporate nutrition education in coach education ( 51 , 52 ) as well as for athletes themselves ( 53 ). Moreover, the earlier this nutrition education is done, the sooner it will shape eating habits that are carried on into their careers and adulthood ( 54 ). Cereals were the most frequently consumed. This is likely a reflection of the geographic location of the region, which is typically mountainous with no viable fishing grounds (lakes, swamps, and rivers). Fish is only obtained from markets distant from the region. Cereals like maize and millet are readily available in this region from cultivation as are legumes and nuts. This variation in the frequency is related to the accessibility of food by athletes ( 55 ). A previous report on dietary diversity supports a finding of the current study where high frequency of cereals consumption was observed by athletes as cereals (maize, wheat, and millet) make up a big part of the diet of inhabitants in Eastern, Northern and as well in the Southern African regions ( 56 ). Our cohort showed a low frequency of meat/poultry, fish/make, and milk/eggs consumption by endurance athletes. This low consumption of animal protein may indirectly translate into inadequate protein intake in this population. Similarly reported by Moss et al, protein needs were not met by their endurance athletes, especially female athletes ( 57 ). Inadequate protein intake in endurance training compromises protein synthesis, promotes muscle atrophy, and prolongs recovery ( 58 , 59 ). In contrast, Lin et al show evidence of enhanced endurance training with adequate protein intake ( 60 ). Endurance athletes require a recommended daily allowance (RDA) of protein in a range not greater than 1.6 g protein per kg ( PRO/kg) of body weight to maintain lean muscle mass ( 61 , 62 ). In the current study, root/tubers (e.g., sweet, potatoes, cassava, yams) were not consumed as highly as reported in other studies ( 32 ). Overall, the frequency of food group consumption is different from the profile observed among Nigerian athletes whose most frequently consumed food groups were, fish/meat, milk, and eggs (70.0% – 80.0%), and the least frequently consumed food groups were legumes-nuts (25%) and healthy root-tubers (15%) ( 22 ). Similar to a study on student athletes in Nigeria, knowledge positively related to the consumption of root/tubers like yams in Nigeria ( 32 ), SNK in our cohort was significantly and positively associated with root /tuber consumption. However, other studies have not observed the same ( 10 ). Kamande et al., ( 63 ) found a strong positive association between knowledge and legume and fruit consumption of Kenyan athletes unlike in the present study. This implies that Ugandan endurance athletes have a tendency to consume tuber/roots that are a key component in endurance carbohydrate fuelling techniques. Recommendations Since the athletes in this study most often consult athletic trainers for nutrition knowledge, the National Council of Sports Uganda should develop routine capacity-building programs to offer supplementary Sports nutrition training to trainers. This knowledge in turn will hopefully be disseminated to endurance athletes in training sessions in their camps. In the long term, it is important that nutritionists/dietitians be engaged as part of athlete support personnel to ensure good SNK as well as optimal consumption of nutrients in Ugandan endurance athletes. Management of athletic camps to incorporate protein-rich diets in athletes’ daily and weekly meal plans for optimal protein intake. Limitations and suggestions for future studies This study is not without limitations. Firstly, the cohort only included 100 young endurance athletes from Sebei, with a few years of experience in athletics. Hence, the results should be generalized to other Ugandan regions and different age cohorts with caution. Secondly, the study did not objectively assess athletes’ dietary intake but relied on self-reported practices and food consumption frequency from different food groups. This has the inherent weaknesses of recall bias, social desirability bias, as well as inaccuracy. Studies that prospectively assess the adequacy of nutrient intake by this population are suggested. Conclusion This study concluded that the majority of the athletes had good knowledge of sports nutrition and adequate dietary practices. Sex differences in SNK and dietary practices were observed in this cohort, which may have implications for the development of sex-specific sports nutrition educational materials. The intake of protein-rich food was inadequate, as shown by the low frequency of meat, fish, eggs, and poultry consumption. This may have implications for injury risk and athletic performance. The athletic trainer was identified as the most frequently consulted source of SNK in the camps and nutritionists/dietitians/doctors were rarely consulted. Therefore, Sports Nutrition should be included in the training of coaches/athletic trainers. Abbreviations SNK Sports Nutrition Knowledge DCP Dietary Consumption Pattern DP Dietary Practice Declarations Conflicting interests NSM is an Editor for the British Journal of Sports Medicine (BJSM) while JM and OFF declare no conflicting interests. Funding This study was entirely funded by the African Union Commission (AUC) through the Pan African University Life and Earth Sciences Institute (Including Health and Agriculture), Ibadan, Nigeria. Data availability Data presented in this study are availed upon request to the corresponding author at [email protected] . Author contributions OFF contributed to the drafts of the entire project, design of the research tools, advice in the data management and interpretation, as well as project supervisor. JM contributed to the draft of the concept note to this study, data collection, and introduction and abstract sections while NSM contributed to the introduction, table presentation, discussion section of the paper, as well as project co-supervisor and editing of the final manuscript. All authors edited and read the final draft of the manuscript before submission. Acknowledgment I extend my gratitude to the following personalities: Mr. David Chesang- the Assistant Chief Administrative Officer of Kapchorwa District (A. CAO) , Tunde Alfred-Sports Officer of Kapchorwa District, Peter Chelangat-Elite coach, and Moses Cherop-Junior Coach for their support and coordination in data collection. Many thanks to the Joshua Cheptegei Foundation (JOCDEF) for permission to access Junior Athletes. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4959741","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":348268678,"identity":"bd2103f9-da4a-44b9-8ac6-a0996abfedf8","order_by":0,"name":"Joshua Musau","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEUlEQVRIie2PMWrDQBBFVwhczQEcFKQTGEYIFALGukXqFQJNI4MhTUql9wEECuQKMoGEdAsq3PgAC2lk3DqwkMaQQLJS5SKyXAayr9oP//F3GDMY/izAGDJmNRy/3TaL5kzFRrWwg07h5wxpZXRRKDvO23RKmRS0/YDLaXQ1ThoHcESPN/VWr8zcSf67EsoscADS+LVIMQCE+eotRa0kQSh6FaaVmqPkmACO56uSt4qIn3sV2n1qJUJJqgZE8ktSAwoP2xWrkpl/XyDnnpMNrGz24fWDvqXa7G+ZQuFXTrYQ+pP9t6xpJ9+X0wjX9HLgX8LzSnpS6m7m9ikd1vIoYNfEE/WOw9Hby4faBoPB8N/4AUOqZLOIZU80AAAAAElFTkSuQmCC","orcid":"","institution":"The Pan African University Life and Earth Sciences Institute (including Health and Agriculture – PAULESI)","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Joshua","middleName":"","lastName":"Musau","suffix":""},{"id":348268679,"identity":"7faf999b-fbe6-4d0b-9b54-98125284212e","order_by":1,"name":"Oluyemisi F. Folasire","email":"","orcid":"","institution":"University of Ibadan","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Oluyemisi","middleName":"F.","lastName":"Folasire","suffix":""},{"id":348268680,"identity":"c5a56f02-b93d-4125-a889-47b707930504","order_by":2,"name":"Nonhlanhla S. Mkumbuzi","email":"","orcid":"","institution":"Northumbria University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Nonhlanhla","middleName":"S.","lastName":"Mkumbuzi","suffix":""}],"badges":[],"createdAt":"2024-08-22 17:44:43","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4959741/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4959741/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13102-025-01157-8","type":"published","date":"2025-05-02T15:57:31+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":65144183,"identity":"b907bdad-ceb6-4ff6-8ae6-a02d18eb8a62","added_by":"auto","created_at":"2024-09-24 06:02:21","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":23188,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eSources of nutrition information among Ugandan endurance athletes from the Sebei sub-region (N=100).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4959741/v1/541b04f714ac957d4b82948a.png"},{"id":65145609,"identity":"c865fff7-9122-4acd-844b-a35a0de5585b","added_by":"auto","created_at":"2024-09-24 06:10:21","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":18071,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eDietary consumption frequency of Ugandan endurance athletes from the Sebei sub-region (N=100).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4959741/v1/ac0bc4bb082f59749d98a418.png"},{"id":81987730,"identity":"07f0a9b6-31f4-4ae5-819e-da31896e8963","added_by":"auto","created_at":"2025-05-05 16:05:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1076084,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4959741/v1/c2fcd5a8-9c43-4816-a70e-879d83c3539a.pdf"},{"id":65144181,"identity":"26406d3d-85e0-4b19-9674-18794158f2fe","added_by":"auto","created_at":"2024-09-24 06:02:21","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":24090,"visible":true,"origin":"","legend":"","description":"","filename":"Tablesmanuspt.docx","url":"https://assets-eu.researchsquare.com/files/rs-4959741/v1/34430281291e0af6a4ee8fce.docx"}],"financialInterests":"Competing interest reported. NSM is an Editor for the British Journal of Sports Medicine (BJSM) while JM and OFF declare no conflicting interests.","formattedTitle":"Sports Nutrition Knowledge, Source of Nutrition Information and Dietary Consumption Pattern of Ugandan Endurance Athletes: A cross-sectional study of the Sebei Sub-Region","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNutritional intake for athletes is an important part of their adequate nourishment and well-being (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Nutrition is a key component in improving an athlete\u0026rsquo;s adaptation to endurance training and its effects (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Endurance activities require extreme physical and mental strength from an athlete and such events include those lasting approximately 26 minutes to about 4 hours (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). These events are often associated with a high turnover of nutrients, consequently predisposing athletes to a risk of nutrient depletion on the field of play (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). As such, athletes are therefore recommended macronutrient intake of about 40%-65% carbohydrates, 30%-55% fat, and 10%-35% protein in their meals supplemented with micronutrients like vitamins C and D and Iron when deficiency cases (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSports nutrition knowledge (SNK) is an individual\u0026rsquo;s understanding of concepts that relate to how to maintain a healthy body mass; manage body fluid balance; and fuelling techniques before, during, and after training or competition; supplement use; and knowledge of nutrition for athletic performance (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Good nutrition among athletes is reported to strongly influence knowledge and attitudes toward it (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Further, SNK and access to good nutrition are also determined by one\u0026rsquo;s social status: income level, education, age, and sex (\u003cspan additionalcitationids=\"CR9 CR10 CR11\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Several reports from athletes and non-athlete populations show that positive dietary changes are associated with good nutrition knowledge(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Research on 24-hour ultramarathon athletes reported positive dietary changes among those who had high knowledge scores(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). This implies that dietary practices based on inaccurate information and misconceptions can negatively impact health and, eventually athletic performance (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eData on elite African athletes\u0026rsquo; nutrition knowledge especially in Uganda are generally scarce. However, some data are available for Kenyan elite endurance athletes, Ugandan recreational athletes, and Ugandan university athletes. These data show that athletes have poor nutrition knowledge of supplementation and that their sources of nutrition information are often not credible(\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Additionally, these athletes rarely consult with registered dietitians and/or sports nutritionists(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), which may further predispose them to misinformation and associated health risks (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite the elite level at which Ugandan endurance athletes compete and their successes at this level, sports nutrition knowledge, sources of nutrition information, and dietary consumption patterns (DCP) of Ugandan endurance athletes remain unclear. Therefore, this study sought to investigate sports nutrition knowledge, sources of nutrition, and dietary consumption patterns of endurance athletes in the Sebei sub-region of Uganda.\u003c/p\u003e"},{"header":"Methods And Materials","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eA cross-sectional, descriptive study of Ugandan endurance athletes in the Sebei sub-region of Uganda.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy site\u003c/h2\u003e \u003cp\u003eThis study was conducted in the Eastern region of Uganda which for years has produced the most dominant athletes on the global scene, especially in distance events with the 10,000m world records claimed in the Tokyo Olympic Games 2020 and the Budapest World Championship 2023 (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis region hosts the Ugandan National High Altitude Training Centre (NHATC) situated 2,550m above sea level and where the majority of Ugandan endurance athletes train (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003ePopulation\u003c/h2\u003e \u003cp\u003eThe study population was approximately 10,000 athletes in the Sebei sub-region; namely, Kapchorwa, Kween, and Bukwo Districts.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eSampling and sample size\u003c/h2\u003e \u003cp\u003eA purposive sampling technique was used to select Kapchorwa among three (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) sporting districts and four (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) athletic management camps in Kapchorwa; and a pragmatic purposive approach to select 100 male and female athletes as study participants. The participants selected were middle-distance and long-distance athletes.\u003c/p\u003e \u003cp\u003eThe minimum required sample for the study was determined by Yamane\u0026rsquo;s formulae (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) and calculated as below.\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\text{n}\\:=\\:\\text{N}/(1+\\text{N}{\\left(\\text{x}\\right)}^{2})$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhereby n\u0026thinsp;=\u0026thinsp;Sample size, N\u0026thinsp;=\u0026thinsp;Total population, x\u0026thinsp;=\u0026thinsp;Level of Precision, 1\u0026thinsp;=\u0026thinsp;constant, N\u0026thinsp;=\u0026thinsp;10,000 athletes, x\u0026thinsp;=\u0026thinsp;10%\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;10,000/ (1+(10,000(1/100))\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;99.009, n\u0026thinsp;=\u0026thinsp;99.09 which is approximately 100 respondents.\u003c/p\u003e \u003cp\u003eThe calculated minimum required sample size was 100 athletes at \u003cem\u003ea priori\u003c/em\u003e alpha level of 0.05.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eData Collection\u003c/h2\u003e \u003cp\u003eData were collected between October and November 2023 and involved 100 endurance athletes: 31.0% (n\u0026thinsp;=\u0026thinsp;31) females and 69.0% (n\u0026thinsp;=\u0026thinsp;S69) males. Master\u0026rsquo;s level trained research assistants used an adapted SNK questionnaire to assess athletes' sports nutrition knowledge in their training camps. The questionnaire had 48 questions in total: on demographics (8 items), sports nutrition knowledge (15 items), dietary practices (15 items), and sources of nutrition information (3 items). A semi-quantitative Food Frequency Questionnaire (7 items) assessed the dietary consumption patterns, and food charts of locally available foods were availed to help participants to recall food consumed from different groups. On pilot testing, the questionnaire took approximately eight (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) minutes per athlete. Responses were recorded as TRUE/FALSE for nutrition knowledge and practice questions and YES/NO for other sections.\u003c/p\u003e \u003cp\u003eThe questionnaire in the current study obtained a Cronbach alpha of 0.74, comparable to that reported by the designer (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eHuman ethics and consent to participate\u003c/h2\u003e \u003cp\u003eParticipants were briefed on the study's purpose and the risks and benefits of participating. All participants provided verbal and written consent before participating in the study. With the majority of our participants younger than 18 years old, they provided assent, and written consent was obtained from their parent/guardian while those older than 18 years provided written consent.\u003c/p\u003e \u003cp\u003e The study adhered to Helsinki Declaration guidelines. Ethical clearance for this study was obtained from the Uganda National Council of Science and Technology (UNCST) (REF: HG2674ES) and The Pan African University Life and Earth Science Institute (Including Health and Agriculture) - PAULESI, Ibadan, Nigeria (REF: ADM/23/249).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis and Management\u003c/h2\u003e \u003cp\u003eQuantitative data were entered into Microsoft Excel\u0026reg; version 2016 (Microsoft Corporation) and were analysed using SPSS software version 23.0 (Chicago, SPSS Inc). Data were reported as percentages, means, frequencies, and statistics of inference such as One-way analysis of variance (ANOVA), Logistic regression, and Chi-square were performed on the data.\u003c/p\u003e \u003cp\u003eAll correct responses of respondents were summed, and an average was computed to determine scores for the participants' nutrition knowledge and practice. The overall score was determined by summing all correctly answered question items. A percentage was generated from the scores, and classification of respondents, differentiating those that scored below (poor knowledge) and above (good knowledge) the average score.\u003c/p\u003e \u003cp\u003eChi-square analyses were performed to ascertain possible relationships between variables of interest, e.g., nutrition knowledge categories with dietary consumption patterns, and also to establish relationships existing between nutrition knowledge categories and dietary practices and demographic information of the athletes.\u003c/p\u003e \u003cp\u003eOne way-analysis of variance (ANOVA) was used to test the variation of the nutrition knowledge among different age groups and competition levels of athletes. An independent student t-test was tested to identify possible differences in knowledge scores for the sex and income categories of the respondents. Logistic regression analysis was performed to identify which independent variable was the best predictor for nutrition knowledge among the athlete population. Significant socio-economic variables were coded as dummy variables imputed and ran in the model and the most significant with close to p\u0026thinsp;=\u0026thinsp;0.00 was considered the best predictor of knowledge. The significance level was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSocial-demographic information\u003c/h2\u003e \u003cp\u003eOf the 100 participants, 31.0% (n\u0026thinsp;=\u0026thinsp;31) were female and 69.0% (n\u0026thinsp;=\u0026thinsp;69) were male. The largest proportion 75.0% (n\u0026thinsp;=\u0026thinsp;75) of athletes were aged between 15\u0026ndash;17 (17.9\u0026thinsp;\u0026plusmn;\u0026thinsp;4.0) years while the least number 12.0% (n\u0026thinsp;=\u0026thinsp;12) was from the age category 25\u0026ndash;35 (17.9\u0026thinsp;\u0026plusmn;\u0026thinsp;4.0) years.\u003c/p\u003e \u003cp\u003eThe highest level of education attained by 54.0% (n\u0026thinsp;=\u0026thinsp;54) was secondary school, followed by 43.0% (n\u0026thinsp;=\u0026thinsp;43) who attained primary school level of education and only 3.0% (n\u0026thinsp;=\u0026thinsp;3) of athletes reported in this study had attained tertiary-level education. All 100.0% (n\u0026thinsp;=\u0026thinsp;100) of respondents lived in rural areas (villages).\u003c/p\u003e \u003cp\u003eThere were twice as many middle-distance 67.0% (n\u0026thinsp;=\u0026thinsp;67) compared to long-distance 33.0% (n\u0026thinsp;=\u0026thinsp;33) athletes. The majority 79.0% (n\u0026thinsp;=\u0026thinsp;793) of the respondents reported having a monthly family income of less than Uganda Shillings (UGX) 130,000 while only 21.0% (n\u0026thinsp;=\u0026thinsp;21) earned more than Uganda Shillings (UGX) 130,000 monthly as seen in \u003cb\u003eTable\u0026nbsp;1\u003c/b\u003e below.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eNutrition knowledge scores\u003c/h2\u003e \u003cp\u003eMost 68.0% (n\u0026thinsp;=\u0026thinsp;68) of the athletes had good knowledge scores on sports nutrition while 32.0% (n\u0026thinsp;=\u0026thinsp;32) of the respondents had poor knowledge of sports nutrition. Similarly, 44.0% (n\u0026thinsp;=\u0026thinsp;44) of athletes had inadequate dietary practices while 56.0% (n\u0026thinsp;=\u0026thinsp;56) had adequate dietary practices.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eNutrition knowledge\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSports nutrition knowledge (SNK) among Ugandan endurance athletes from the Sebei sub-region (N\u0026thinsp;=\u0026thinsp;100).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuestions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCorrect\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncorrect\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1) How many times should we eat in a day?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e97 (97.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3(3.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2) Do you think foods rich in carbohydrates are the main sources of energy in the body?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e100 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3) As an athlete, my food intake should increase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e95 (95.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (5.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4) Can the lack of iron in the diet result in fatigue, injury, and illness?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e70 (70.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30 (30.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5) Do you think sports drinks are the best to replace body fluids lost on the field of play?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e62 (62.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38 (38.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6) Are vitamins good sources of energy?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e86 (86.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14 (14.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7) Alcohol consumption can negatively affect the absorption and utilization of nutrients?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24 (24.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e76 (76.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8) Eating of snacks is as good as eating home-prepared foods?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32 (32.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68 (68.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9) Do you think foods rich in sugar, jam and honey are suitable sources of energy for athletes?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e93 (93.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7 (7.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10) The last meal before a competition should be consumed at least 3 hours before a competition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e57 (57.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43 (43.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11) Males and females of the same group use up the same amount of energy during exercise\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e43 (43.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57 (57.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12) Fruits and vegetables are important sources of vitamins and minerals?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e89 (89.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11 (11.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13) Vitamins can enhance recovery after competition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e88 (88.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12 (12.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14) Do you think milk and milk products are good sources of calcium?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e82 (82.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18 (18.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15) How many classes of nutrients do we have?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42 (42.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58 (58.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMost respondents 97.0% (n\u0026thinsp;=\u0026thinsp;97) knew the correct number of times an individual should eat per day and 3.0% (n\u0026thinsp;=\u0026thinsp;3) did not. With regards to sources of energy, all 100.0% (n\u0026thinsp;=\u0026thinsp;100) of the athletes knew that foods rich in carbohydrates are the main source of energy for the body. Nearly all 95.0% (n\u0026thinsp;=\u0026thinsp;95) of the respondents had the right knowledge that as an athlete, food consumption should be higher than compared to the general population. The knowledge that iron deficiency in the diet can cause fatigue, illness, and injury was known by at least 70.0% (n\u0026thinsp;=\u0026thinsp;70) while 30.0% (n\u0026thinsp;=\u0026thinsp;30) were not knowledgeable. About 62.0% (n\u0026thinsp;=\u0026thinsp;62) of athletes knew that sports drinks more likely aid rehydration when body fluids are lost in the field of competition; 86.0% (n\u0026thinsp;=\u0026thinsp;86) knew that vitamins are not a good source of energy; 76.0% (n\u0026thinsp;=\u0026thinsp;76) had good knowledge that drinking alcohol affects digestion. Slightly more than half 57.0% (n\u0026thinsp;=\u0026thinsp;57) of the athletes knew that a pre-event meal should be consumed at least 3 hours before the event. The majority of the athletes 88.0% (n\u0026thinsp;=\u0026thinsp;88) responded correctly to the statement that vitamins can enhance recovery after competition. A detailed summary is in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003eabove\u003c/b\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eDietary practice\u003c/h2\u003e \u003cp\u003eThe study also found that 64.0% (n\u0026thinsp;=\u0026thinsp;64) of the athletes had adequate DP, while 36.0% (n\u0026thinsp;=\u0026thinsp;36) had inadequate DP.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e below shows that 27.0% (n\u0026thinsp;=\u0026thinsp;27) of the endurance athletes in this study use supplements such as multivitamins, while 73.0% (n\u0026thinsp;=\u0026thinsp;73) do not. Most respondents 97.0% (n\u0026thinsp;=\u0026thinsp;97) consume fruits and vegetables often while 3.0% (n\u0026thinsp;=\u0026thinsp;3) do not; 36.0% (n\u0026thinsp;=\u0026thinsp;36) skipped the pre-event meal while 64.0% (n\u0026thinsp;=\u0026thinsp;64) of them did not skip the pre-event meal.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDietary practices among Ugandan endurance athletes from the Sebei sub-region (N\u0026thinsp;=\u0026thinsp;100).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuestions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1) Do you use supplements like multivitamin as an athlete?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27(27.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e73(73.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2) I consume lots of fruits and vegetables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e97(97.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3(3.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3) I skip meals before a competition or an event\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36(36.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64(64.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4) I eat just before an event\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e63(63.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37(37.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5) I eat just after an event\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e84(84.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16(16.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6) I consume sports drinks every day during practice or when I feel dehydrated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49(49.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51(51.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7) I eat an adequate diet daily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e88(88.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12(12.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8) I change my pattern of eating at the time of a competition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e90(90.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10(10.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9) I always take my breakfast daily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e97(97.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3(3.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10) I consume lots of water during and after training/competition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e100(100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0(0.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11) I always eat at least one hour before training/competition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46(46.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54(54.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12) I prefer snacks to a special diet before training and competition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42(42.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58(58.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13) I eat at least three times daily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e100(100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0(0.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14) I consume milk and milk products daily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e48(48.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52(52.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15) I consume alcohol to enhance my performance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0(0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100(100.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eSource of nutrition knowledge.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e below, athletic trainers 49.0% (n\u0026thinsp;=\u0026thinsp;49), parents/family 28.0% (n\u0026thinsp;=\u0026thinsp;28), others (doctors, peers, school) 6.0% (n\u0026thinsp;=\u0026thinsp;6), nutritionists/dietitians 5.0% (n\u0026thinsp;=\u0026thinsp;5), magazines 4.0% (n\u0026thinsp;=\u0026thinsp;4), TV/Radio 4.0% (n\u0026thinsp;=\u0026thinsp;4) and the internet 4.0% (n\u0026thinsp;=\u0026thinsp;4) were consulted for nutrition information. Only 9.0% (n\u0026thinsp;=\u0026thinsp;9) of participants had previously undertaken a nutrition course.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eDietary consumption pattern\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMost athletes 77.0% (n\u0026thinsp;=\u0026thinsp;77) frequently consumed from the cereal food group (e.g., posho, rice, wheat, sorghum, millet), 72% (n\u0026thinsp;=\u0026thinsp;72) consumed from legumes/nuts group (e.g., groundnuts, sunflower seed, pumpkin seed, bean/soya seed), 55% (n\u0026thinsp;=\u0026thinsp;55) consumed from vegetables/fruits group, (e.g., watermelon, mbogoya, orange, mangoes, cabbage, sukuma wiki, suja), while 46% (n\u0026thinsp;=\u0026thinsp;46) consumed from root/tubers group. The least consumed food groups were milk/egg 33.0% (n\u0026thinsp;=\u0026thinsp;33), fish/mukene 25.0% (n\u0026thinsp;=\u0026thinsp;25) and meat/poultry 13.0% (n\u0026thinsp;=\u0026thinsp;13).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eSports nutrition knowledge and other variables\u003c/h2\u003e \u003cp\u003e\u003cimg 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\" height=\"528\" width=\"561\"\u003e\u003c/p\u003e\u003cp\u003eThere was a significant relationship between SNK and athletes\u0026rsquo; family monthly income (p\u0026thinsp;=\u0026thinsp;0.003), relationship status (p\u0026thinsp;=\u0026thinsp;0.033), age group (p\u0026thinsp;=\u0026thinsp;0.001), and athletic event (p\u0026thinsp;=\u0026thinsp;0.038), but not with the highest level of education (p\u0026thinsp;=\u0026thinsp;0.481), sex of athlete (p\u0026thinsp;=\u0026thinsp;0.176), and with many years of participation in athletics (p\u0026thinsp;=\u0026thinsp;0.272). Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e4\u003c/span\u003e above shows a summary of the results.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBinary Logistic analysis of significant socio-demographic variables of Ugandan athletes.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eVariable\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eβ\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eEx(β)\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eP\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eC.I (95%)\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eLower\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eUpper\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eAge group\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e1.925\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e6.853\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e0.023*\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e0.882\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e36.096\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eAthletic event\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e1.233\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e3.431\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e0.059\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e0.956\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e12.317\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eRelationship status\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e-0.880\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e0.415\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e0.047*\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e0.174\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e0.989\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eMonthly family income\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e2.010\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e7.461\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e0.065\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e0.882\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e63.144\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAge was the best predictor for SNK (p\u0026thinsp;=\u0026thinsp;0.023; C.I\u0026thinsp;=\u0026thinsp;0.882\u0026ndash;36.096). For every unit (1.925) increase in age, an athlete\u0026rsquo;s odds of being classified as knowledgeable were nearly seven (6.9) times. The model with all the significant socio-demographic variables accurately predicted those with good knowledge 85.0% of the time as seen in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e5\u003c/span\u003e above.\u003c/p\u003e \u003cp\u003eSNK was significantly associated with root tuber consumption (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) but not with the rest of the food groups shown below in \u003cb\u003eTable\u0026nbsp;6\u003c/b\u003e and there were no associations observed between SNK and sources of nutrition information. Also, having had a nutrition course previously did not correlate with nutrition knowledge (p\u0026thinsp;=\u0026thinsp;0.159). All results are shown in \u003cb\u003eTable\u0026nbsp;7.\u003c/b\u003e Additionally, good SNK was significantly associated with adequate dietary practices (p\u0026thinsp;=\u0026thinsp;0.009) as shown below in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e8\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eSNK was different between athletes of different sex (p\u0026thinsp;\u0026lt;\u0026thinsp;0.000), with different respondents\u0026rsquo; family income levels (p\u0026thinsp;=\u0026thinsp;0.018), with different athletic events (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with different age groups (p\u0026thinsp;=\u0026thinsp;0.013), and with different education levels of respondents (p\u0026thinsp;=\u0026thinsp;0.024). SNK did not differ with athletes\u0026rsquo; relationship status (p\u0026thinsp;=\u0026thinsp;0.746) results in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e9\u003c/span\u003e below.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSNK and DP score category and Bivariate analysis for SNK and DP of Ugandan endurance athletes (N\u0026thinsp;=\u0026thinsp;100).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c5\" namest=\"c3\" rowspan=\"2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c10\" namest=\"c6\"\u003e \u003cp\u003eRespondents score\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSNK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e32\u003c/p\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e32.0\u003c/p\u003e \u003cp\u003e68.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e44\u003c/p\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e44.0\u003c/p\u003e \u003cp\u003e56.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBivariate analysis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eSNK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{x}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e6.895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c9\" namest=\"c8\" rowspan=\"2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.009*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e36\u003c/p\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003e*Significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIndependent t-test analysis and ANOVA- analysis to determine variation in SNK within Ugandan athletes\u0026rsquo; demographic (N\u0026thinsp;=\u0026thinsp;100).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.70\u003c/p\u003e \u003cp\u003e25.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e2.198\u003c/p\u003e \u003cp\u003e0.763\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21.884\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e-1.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily monthly income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.58\u003c/p\u003e \u003cp\u003e25.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1.952\u003c/p\u003e \u003cp\u003e1.221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.750\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e-2.630\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAthletic event\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eMiddle distance\u003c/p\u003e \u003cp\u003eLong distance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.81\u003c/p\u003e \u003cp\u003e24.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e2.210\u003c/p\u003e \u003cp\u003e0.927\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21.601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eANOVA-analysis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e4.566\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eRelationship status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e0.411\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e0.746\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e3.874\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eFrom the findings, it is noted that male respondents constituted a bigger proportion than females. This is because generally, sports is strongly gendered in African settings and society tends to discourage females from participating in sports (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Our findings relate to a previous study by Baranauskas et al, (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) where male athletes were more than female athletes. Additionally, we showed knowledge differences between the sexes, which differs from other studies such as Magee et al, (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Our observed sports nutrition knowledge differences with sex could be because female adolescents are generally aware of their body image and tend to seek nutritional counselling more than their male counterparts(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). This also implies that there may be a need to provide sex-specific nutrition knowledge to athletes to accommodate this sex difference.\u003c/p\u003e \u003cp\u003eThe majority of endurance athletes in this study were late adolescents and had participated for less than 2 years in athletics. This is similar to the cohort from Baranauskas et al., (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) whose respondents had a mean age of 17 years, but contrasts with a previous study conducted among Kenyan endurance athletes who were much older with the majority between 23\u0026ndash;28 years of age with less than 3 years of participation, which is somewhat similar to our study findings (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe highest academic achievement of most athletes in our study was secondary school level, which is to be expected given their age and generally, such education levels are commonly reported in studies of Kenyan and Ugandan athletes (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Our report contrasts other studies whose respondents had certificates, tertiary/ university degrees as their highest level of education (\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Level of education has been associated with the level of SNK in other studies of physically active individuals (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) and in our cohort may have implications for the development of future education materials, as these need to be tailored to the level of education of our cohort.\u003c/p\u003e \u003cp\u003eThe study found that most athletes acknowledge that pre-event meals should be consumed at least three hours prior to the event, while a significant proportion of them did not know this. More than half of athletes were not knowledgeable about the six classes of nutrients. A big proportion of respondents had good knowledge that athletes\u0026rsquo; food consumption should be higher than in non-athletes. Almost three-quarters of the athletes had the right knowledge that sports drinks are best to replace fluids lost in the field of play. In addition, the majority of the respondents in the current study had good dietary practices. This is similar to a study on undergraduate athletes from Nigeria where 63% of respondents reported adequate nutrition practices (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), as well as a study on Nepali athletes where 50% had good nutrition practice scores (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Female athletes displayed better dietary practices compared to males in the current study just as was observed in Koch et al\u0026rsquo;s study of the Nemonit population (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlmost 75% of the athletes did not skip meals while almost every athlete always ate their breakfast, as shown in other cohorts (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). All respondents in this cohort take a lot of water during training and eat at least three meals a day. This is consistent with the findings of previous studies on in-training water consumption (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e) but contrasts with Oladunni \u0026amp; Sanusi., (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e) who reported that 77% of athletes from Nigeria skip meals. The present findings also concur with the findings of Folasire et al., (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), which reported that 82.7% of athletes ate a pre-event meal at least three hours before the event; 57% agreed that athletes' food intake should be higher than non-athletes; 63.6% reported good knowledge of the six classes of nutrients.\u003c/p\u003e \u003cp\u003eFurther, athletes in our study displayed a high level of sports nutrition knowledge when it came to the use of recovery strategies with 75% of endurance athletes having good knowledge of the consumption of vitamins to enhance recovery. This finding was corroborated by studies that show that vitamin intake enhances muscle recovery by negating the effects of exercise-induced muscle damage(\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Such recovery strategies could be adopted by endurance athletes following this position statement(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). The present results are also corroborated by previous studies that report good sports nutrition knowledge in 56% of Kenyan endurance athletes and 69.42% of Ghanaian athletes (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). However, the current study contrasts the findings of Klein et al., (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e) that reported low sports nutrition among their athletes. This current study further disagrees with a more recent study of young athletes that reported poor average sports nutrition knowledge of its male and female respondents (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur study found a statistically significant relationship between athletes\u0026rsquo; sports nutrition knowledge and dietary practice which correlates with a review that established that nutrition knowledge had a weak positive relationship with positive dietary changes (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Even though our results did not show a relationship between previously attending a nutrition course with sports nutrition knowledge, this phenomenon of \u0026lsquo;when we know better, we do better\u0026rsquo; has also been demonstrated in other studies on sports nutrition knowledge (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), and in other health domains, such as good menstrual hygiene and child caregiving where higher literacy is associated with better behaviours (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Hence, it is important to enhance athletes\u0026rsquo; sports nutrition knowledge. It is noteworthy, however, that in Uganda, Nassanga et al., (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e) reported that a combination of factors interplay when it comes to how knowledge is translated into proper dietary practices. Primarily, poverty, food security, the attitudes of the individuals, and the nature of jobs people are engaged in are key determinants of nutritional knowledge transfer. In our cohort, in particular, the median household income is Uganda Shillings (UGX) 100,000 which was not only associated with knowledge, but household income may not be enough to allow players to consume all the food groups in the requisite amounts. Hence, despite Ugandan athletes being knowledgeable about sports nutrition, they may not have the resources available to practice optimum sports nutrition due to low socioeconomic status (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eConcerning the source of nutrition information, the majority of the respondents identified athletic trainers as a popular source of knowledge used in the camps, followed by parents/ family. Nutritionists/Dietitians, internet, TV/Radio, magazines, and others like doctors, peers, and schools were rarely consulted for sports nutrition information. These study findings are similar to other studies, which found that coaches/trainers are popular sources athletes rely on for nutrition knowledge. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). However, this contrasts with Kathure et al., (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) who showed that 60% of their cohort relied on the Internet as the main source of nutrition information. Further, findings from UK runners show that 33\u0026ndash;82% of them relied on internet/web sources for nutrition information (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Interestingly, peer-reviewed literature was identified as the main source of information by Hispanic ultra-endurance athletes (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e), while nutritionists and dietitians were popular sources amongst athletes from Australia (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn our cohort, less than a tenth consulted a nutritionist for nutrition information. This result was expected because of the lack of nutritionists/dietitians in athlete support staff in low and middle-income countries (LMICs) such as Uganda, due to inadequate budgets to cover the cost of such specialized staff (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Generally, there exists a gap in the enrolment and training of nutritionists/dietitians within tertiary institutions in low and middle-income countries (LMICs) (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). In Uganda, the majority of graduate nutritionists and dietitians from tertiary institutions enter the job market with incompetencies in some crucial domains of practice (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). In contrast, high-income countries (HICs) tend to have specialized and rigorously licensed and certified athlete nutrition staff (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). Access to credible knowledge from nutritionists/dietitians could help inform dietary changes that in turn promote the healthy nutritional status of athletes (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e) and reduce the likelihood of misinformation (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e). Since African athletes rely primarily on their coaches/trainers for nutrition knowledge, it may be prudent to incorporate nutrition education in coach education (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e) as well as for athletes themselves (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). Moreover, the earlier this nutrition education is done, the sooner it will shape eating habits that are carried on into their careers and adulthood (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCereals were the most frequently consumed. This is likely a reflection of the geographic location of the region, which is typically mountainous with no viable fishing grounds (lakes, swamps, and rivers). Fish is only obtained from markets distant from the region. Cereals like maize and millet are readily available in this region from cultivation as are legumes and nuts. This variation in the frequency is related to the accessibility of food by athletes (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e). A previous report on dietary diversity supports a finding of the current study where high frequency of cereals consumption was observed by athletes as cereals (maize, wheat, and millet) make up a big part of the diet of inhabitants in Eastern, Northern and as well in the Southern African regions (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur cohort showed a low frequency of meat/poultry, fish/make, and milk/eggs consumption by endurance athletes. This low consumption of animal protein may indirectly translate into inadequate protein intake in this population. Similarly reported by Moss et al, protein needs were not met by their endurance athletes, especially female athletes (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). Inadequate protein intake in endurance training compromises protein synthesis, promotes muscle atrophy, and prolongs recovery (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e). In contrast, Lin et al show evidence of enhanced endurance training with adequate protein intake (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e). Endurance athletes require a recommended daily allowance (RDA) of protein in a range not greater than 1.6 g protein per kg ( PRO/kg) of body weight to maintain lean muscle mass (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the current study, root/tubers (e.g., sweet, potatoes, cassava, yams) were not consumed as highly as reported in other studies (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Overall, the frequency of food group consumption is different from the profile observed among Nigerian athletes whose most frequently consumed food groups were, fish/meat, milk, and eggs (70.0% \u0026ndash; 80.0%), and the least frequently consumed food groups were legumes-nuts (25%) and healthy root-tubers (15%) (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Similar to a study on student athletes in Nigeria, knowledge positively related to the consumption of root/tubers like yams in Nigeria (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), SNK in our cohort was significantly and positively associated with root /tuber consumption. However, other studies have not observed the same (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Kamande et al., (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e) found a strong positive association between knowledge and legume and fruit consumption of Kenyan athletes unlike in the present study. This implies that Ugandan endurance athletes have a tendency to consume tuber/roots that are a key component in endurance carbohydrate fuelling techniques.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRecommendations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSince the athletes in this study most often consult athletic trainers for nutrition knowledge, the National Council of Sports Uganda should develop routine capacity-building programs to offer supplementary Sports nutrition training to trainers. This knowledge in turn will hopefully be disseminated to endurance athletes in training sessions in their camps. In the long term, it is important that nutritionists/dietitians be engaged as part of athlete support personnel to ensure good SNK as well as optimal consumption of nutrients in Ugandan endurance athletes.\u003c/p\u003e\n\u003cp\u003eManagement of athletic camps to incorporate protein-rich diets in athletes\u0026rsquo; daily and weekly meal plans for optimal protein intake.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations and suggestions for future studies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study is not without limitations. Firstly, the cohort only included 100 young endurance athletes from Sebei, with a few years of experience in athletics. Hence, the results should be generalized to other Ugandan regions and different age cohorts with caution.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSecondly, the study did not objectively assess athletes\u0026rsquo; dietary intake but relied on self-reported practices and food consumption frequency from different food groups. This has the inherent weaknesses of recall bias, social desirability bias, as well as inaccuracy. Studies that prospectively assess the adequacy of nutrient intake by this population are suggested.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study concluded that the majority of the athletes had good knowledge of sports nutrition and adequate dietary practices. Sex differences in SNK and dietary practices were observed in this cohort, which may have implications for the development of sex-specific sports nutrition educational materials. The intake of protein-rich food was inadequate, as shown by the low frequency of meat, fish, eggs, and poultry consumption. This may have implications for injury risk and athletic performance. The athletic trainer was identified as the most frequently consulted source of SNK in the camps and nutritionists/dietitians/doctors were rarely consulted. Therefore, Sports Nutrition should be included in the training of coaches/athletic trainers.\u003c/p\u003e "},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSNK\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSports Nutrition Knowledge\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eDCP\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDietary Consumption Pattern\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eDP\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDietary Practice\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflicting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNSM\u0026nbsp;\u003c/strong\u003eis an Editor for the British Journal of Sports Medicine (BJSM) while \u003cstrong\u003eJM\u003c/strong\u003e and \u003cstrong\u003eOFF\u003c/strong\u003e declare no conflicting interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was entirely funded by the African Union Commission (AUC) through the Pan African University Life and Earth Sciences Institute (Including Health and Agriculture), Ibadan, Nigeria.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData presented in this study are availed upon request to the corresponding author at [email protected].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOFF\u003c/strong\u003e contributed to the drafts of the entire project, design of the research tools, advice in the data management and interpretation, as well as project supervisor. \u003cstrong\u003eJM\u003c/strong\u003e contributed to the draft of the concept note to this study, data collection, and introduction and abstract sections while \u003cstrong\u003eNSM\u003c/strong\u003e contributed to the introduction, table presentation, discussion section of the paper, as well as project co-supervisor and editing of the final manuscript. All authors edited and read the final draft of the manuscript before submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eI extend my gratitude to the following personalities: \u0026nbsp;Mr. David Chesang- the Assistant Chief Administrative Officer of Kapchorwa District \u003cstrong\u003e(A. CAO)\u003c/strong\u003e, Tunde Alfred-Sports Officer of Kapchorwa District, Peter Chelangat-Elite coach, and Moses Cherop-Junior Coach for their support and coordination in data collection. Many thanks to the Joshua Cheptegei Foundation \u003cstrong\u003e(JOCDEF)\u0026nbsp;\u003c/strong\u003efor permission to access Junior Athletes.\u003c/p\u003e\n\u003cp\u003eI also thank all the management of PAULESI for the support during this study tract and more especially Prof A.O. Fadojou Head of Department, Human Kinetics, University of Ibadan, Nigeria.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCosta RJS, Knechtle B, Tarnopolsky M, Hoffman MD. Nutrition for Ultramarathon Running: Trail, Track, and Road. Int J Sport Nutr Exerc Metab [Internet]. 2019 Mar 1 [cited 2022 Nov 20];29(2):130\u0026ndash;40. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://journals.humankinetics.com/view/journals/ijsnem/29/2/article-p130.xml\u003c/span\u003e\u003cspan address=\"https://journals.humankinetics.com/view/journals/ijsnem/29/2/article-p130.xml\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBurke LM, Castell LM, Casa DJ, Close GL, Costa RJS, Desbrow B et al. International Association of Athletics Federations Consensus Statement 2019: Nutrition for Athletics. 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Afr J Food Agric Nutr Dev [Internet]. 2022 Jun 15 [cited 2023 Apr 2];22(4):20148\u0026ndash;60. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://ajfand.net/Volume22/No4/Kamande22385.pdf\u003c/span\u003e\u003cspan address=\"http://ajfand.net/Volume22/No4/Kamande22385.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-sports-science-medicine-and-rehabilitation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ssmr","sideBox":"Learn more about [BMC Sports Science, Medicine and Rehabilitation](http://bmcsportsscimedrehabil.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ssmr/default.aspx","title":"BMC Sports Science, Medicine and Rehabilitation","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Athlete, Nutrition, Sports, Knowledge, Endurance, African athletes","lastPublishedDoi":"10.21203/rs.3.rs-4959741/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4959741/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAthletes\u0026rsquo; nutrition knowledge depends on the sources of nutrition information they are exposed to and their social status. Currently, there is a dearth of literature on the nutrition knowledge of Ugandan athletes. This study assessed endurance athletes\u0026rsquo; sports nutrition knowledge, sources of nutrition information, and their dietary consumption patterns.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA cross-sectional descriptive study including 100 purposively selected (middle and long distance) athletes from four Athletic Management camps was conducted in Kapchorwa district, Uganda. Using an interviewer-administered questionnaire, trained research assistants collected athletes\u0026rsquo; demographic information, knowledge, practices, sources of nutrition information and consumption patterns. ANOVA, Independent t-test, Chi-square analysis, and Binary logistic analyses were done using SPSS\u0026reg; software version 23.0.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eMost athletes 74.0% (n\u0026thinsp;=\u0026thinsp;74) in this study were aged between 15\u0026ndash;17 (17.9\u0026thinsp;\u0026plusmn;\u0026thinsp;4.0) years with at least 2 years\u0026rsquo; experience in athletics. Majority 68.0% (n\u0026thinsp;=\u0026thinsp;68) of the athletes had good sports nutrition knowledge while 32.0% (n\u0026thinsp;=\u0026thinsp;32) showed poor knowledge. About 88.0% (n\u0026thinsp;=\u0026thinsp;88) knew that vitamin consumption can enhance recovery after training. Athletic trainers 49.0% (n\u0026thinsp;=\u0026thinsp;49) and family/parents 28.0% (n\u0026thinsp;=\u0026thinsp;28) were primary sources of nutrition information, while nutritionists/dietitians 5.0% (n\u0026thinsp;=\u0026thinsp;5) and the internet 4.0% (n\u0026thinsp;=\u0026thinsp;4) were less consulted. Cereals were the most consumed food group 72.0% (n\u0026thinsp;=\u0026thinsp;72), followed by legumes and nuts 67.0% (n\u0026thinsp;=\u0026thinsp;67) while the least consumed foods were milk/egg 33.0% (n\u0026thinsp;=\u0026thinsp;33), fish 25.0% (n\u0026thinsp;=\u0026thinsp;25) and meat/poultry 13.0% (n\u0026thinsp;=\u0026thinsp;13). Good sports nutrition knowledge was associated with adequate dietary practices (p\u0026thinsp;=\u0026thinsp;0.009). Sports nutrition knowledge differed significantly with age group (F\u0026thinsp;=\u0026thinsp;4.566, p\u0026thinsp;=\u0026thinsp;0.013), and between female and male (F\u0026thinsp;=\u0026thinsp;21.884, p\u0026thinsp;\u0026lt;\u0026thinsp;0.000) athletes. Age group was a significant predictor (β\u0026thinsp;=\u0026thinsp;1.925, Ex(β)\u0026thinsp;=\u0026thinsp;6.853, C. I\u0026thinsp;=\u0026thinsp;0.882\u0026ndash;36.096, p\u0026thinsp;=\u0026thinsp;0.023) of sports nutrition knowledge.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eIn this study endurance athletes had good sports nutrition knowledge, and relied primarily on their coaches/trainers for sports nutrition information. It is recommended that athletic trainers be offered supplementary training in sports nutrition to ensure proper nutrition knowledge dissemination among athletes.\u003c/p\u003e","manuscriptTitle":"Sports Nutrition Knowledge, Source of Nutrition Information and Dietary Consumption Pattern of Ugandan Endurance Athletes: A cross-sectional study of the Sebei Sub-Region","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-24 06:02:16","doi":"10.21203/rs.3.rs-4959741/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-09-02T08:50:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-09-02T08:27:35+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-08-26T00:43:38+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Sports Science, Medicine and Rehabilitation","date":"2024-08-22T17:43:20+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-sports-science-medicine-and-rehabilitation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ssmr","sideBox":"Learn more about [BMC Sports Science, Medicine and Rehabilitation](http://bmcsportsscimedrehabil.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ssmr/default.aspx","title":"BMC Sports Science, Medicine and Rehabilitation","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"65e50a82-ee2c-442d-9798-77f52907dd5f","owner":[],"postedDate":"September 24th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-05-05T16:00:52+00:00","versionOfRecord":{"articleIdentity":"rs-4959741","link":"https://doi.org/10.1186/s13102-025-01157-8","journal":{"identity":"bmc-sports-science-medicine-and-rehabilitation","isVorOnly":false,"title":"BMC Sports Science, Medicine and Rehabilitation"},"publishedOn":"2025-05-02 15:57:31","publishedOnDateReadable":"May 2nd, 2025"},"versionCreatedAt":"2024-09-24 06:02:16","video":"","vorDoi":"10.1186/s13102-025-01157-8","vorDoiUrl":"https://doi.org/10.1186/s13102-025-01157-8","workflowStages":[]},"version":"v1","identity":"rs-4959741","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4959741","identity":"rs-4959741","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}