A Cross-Sectional Study on the Diet and Nutritional Status of Recreational Athletes: A Pilot Study

Catovic, A.^1*, Pleho-Kapić, A.², Voljevica, A.³, Suljević, A.⁴ & Suke, S.⁴

¹Department of Hygiene, Faculty of Medicine, University of Sarajevo, Bosnia and Herzegovina
²Department of Pathophysiology, Faculty of Medicine, University of Sarajevo, Bosnia and Herzegovina
³Department of Anatomy, Faculty of Medicine, University of Sarajevo, Bosnia and Herzegovina
⁴Faculty of Medicine, University of Sarajevo, Bosnia and Herzegovina

*Correspondence to: Dr. Catovic, A., Department of Hygiene, Faculty of Medicine, University of Sarajevo, Bosnia and Herzegovina.

Copyright © 2021 Dr. Catovic, A., et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abbreviations

BMR - basal metabolic rate
BMI - body mass index
FFQ - food frequency questionnaire
SD - standard deviation
TEF - thermic effect of food
WHO - World Health Organization
WHR - waist hip ratio

Introduction
There are three basic components of a person’s energy output: maintenance expenditure, activity-induced energy expenditure, and diet-induced expenditure [1]. The basal metabolic rate (BMR) is the minimum energy expended to keep a metabolism at work in a day. There are variations in the expenditure of energy for life-sustaining activities, depending on sex, age, and body mass. The highest BMR is seen with people who are growing and who are physically fit with significant lean body mass [2,3]. The diet-induced expenditure is energy required to process food. Because of heat production this is named as thermic effect of food (TEF) [4]. Activity energy expenditure is the most variable and the most changeable component of energy expenditure. It has significant influence on weight. Differences in weight do not mean the same variation in body composition of athletes and inactive people [3,5]. Body weight consists of fat (adipose), lean body mass, and water. Components of lean body mass are muscle, organs, and bone. There is an ample reserve of energy between 50,000 to 200,000 kcalories in healthy-weight adult that can be used between meals. One aspect of body composition is distribution of fat in the body. Upper-body fat or central obesity is visceral fat that is stored around the organs of the abdomen. Lower-body fat is subcutaneous fat around the hips and thighs [3,6]. Aerobic exercise can decrease visceral fat stores in general populations [7]. A recreational athletes participate in physically activities to be healthy, physically fit, socially involved, and to have fun. They train at various intensity levels. To perform at an optimal level they need a variety of food choices [8].

This study aimed to assess correlation between nutritional status indicators and dietary pattern in recreational athletes.

Materials and Methods

Design and Sample
A cross-sectional study was conducted during March and April 2017 in the area of Sarajevo Canton. The study covered 50 recreational athletes of both sexes and different age groups. Simple random sampling was used to select participants from different age groups.

The study was conducted according to the research ethics guidelines laid down in the Declaration of Helsinki [9]. Verbal informed consent was obtained from all participants.

Data Collection
Anthropometric data included height, weight, as well as waist and hip circumference. The whole-body level of body composition is described by body mass index (BMI) and waist hip ratio (WHR). BMI is calculated using weight in kilograms and height in meters (kg/m²). According to WHO guidelines [10] weight status is classified into four categories: under-weight (BMI ≤ 18.5), normal weight (BMI between 18.5-24.9), overweight (BMI between 25-29.9), and obese (BMI ≥ 30). WHR (i.e. the waist circumference divided by the hip circumference) is a measure of body fat distribution. It provides an index of both subcutaneous and intraabdominal adipose tissue. Abdominal obesity is defined as WHR above 0.90 for males and above 0.85 for females (determined for European men and women, respectively) [11]

Dietary data were obtained by food frequency questionnaire (FFQ) [12]. The used items in the FFQ were divided into 16 food and beverage’s groups: fruits, vegetables, nuts, red meat, white meat, eggs, milk and dairy products, grains, cakes, sweets, chips, fried potatoes, fast food (hamburger, hotdog, sausages), coffee, fruits juices, sodas. The FFQ asked how often each food or beverage group, was usually consumed with five possible answers for each of the food categories: (1) several times per day, (2) at least one time per day, (3) two to three times per week, (4) two to three times per month, and (5) never.

Data Analysis
Statistical analyses were performed using the Statistical Package for Social Sciences (version 13.0, SPSS, Inc) software. Continuous data were presented as mean and standard deviation (SD) and compared using Student t-test. In the bivariate analysis, the association of anthropometric measures were estimated according to age and the foodstuffs consumption pattern. Differences were considered statistically significant at p<0.05.

Results
A sample included 50 participant, of which 27 (54.0%) were female and 23 (46.0%) were male.

The mean age of female participants was 21.82±1.35 year, and for male participants was 25.22±1.14. There was no significant difference between genders in relation to age (Student t test: p=0.065; p<0.05).

The anthropometric characteristics of participants were presented in Table 1.

For females the mean weight was 58.19±1.85kg, the mean height was 166.56±1.19cm, the mean BMI was 21.82±1.35kg/m₂, the mean waist circumference was 70.76±1.17cm, the mean hip circumference was 86.02±1.50, and mean WHR was 0.82±0.01. For males the mean weight was 80.09±2.95kg and the mean height was 182.6±1.36cm, the mean BMI was 25.22±1.14kg/m₂, the mean waist circumference was 86.49±1.86cm, the mean hip circumference was 94.72±1.59, and mean WHR was 0.91±0.01.

Between gender there were significant differences in relation to anthropometric measures.

It is showed by Table 2 that the majority of the participants (68.0%) were of normal weight. BMI > 24.9 was found at 11(22.0%) participants, whereas 5 (10.0%) participants were underweight. Abdominal adiposity, defined by WHR, was found at 6(12.0%) participants.

Comparison of consumption frequency of different food stuff revealed no statistically significant difference between genders, expect for consumption frequency of white meat and sweets (Table 3). One quarter of the sample of male population (26.1%) restricts consumption of fruits to two to three times per week.

Correlation between nourishment status, age and dietary pattern is showed in table 4.

*Correlation is significant at the 0.05 level **Correlation is significant at the 0.01 level

Females displayed positive correlation between measures of adiposity and age. Pattern of coffee consumption correlated with measures of adiposity in different way for females and males. Females who consumed coffee less frequently, had a higher weight, BMI and waist circumference. On the contrary, males who consumed less frequently had a lower waist circumference. Our study showed that less frequent cake consumption correlated with higher hip circumference for females. As for the male sample, we found WHR was higher with less frequent consumption of milk and milk products, whereas waist and hip circumference was higher with more rear consumption of fruits. More frequent consumption of sodas correlated with higher waist circumference and WHR.

Discussion
The purpose of this study was to investigate the relationships of nutritional status indicators and dietary pattern in a sample of 50 recreational athletes. A cross-sectional study was conducted during March and April 2017 in the area of Sarajevo Canton. Nutritional status indicators used were anthropometric measures: height, weight, waist and hip circumference, as well as their derivates: BMI and WHR. BMI is adopted as the anthropometric measure of body size for general population. WHO stated that in 2016, 39% of adults, aged 18 years and over, were overweight based on BMI, and 13% were obese [13]. In our sample we found BMI > 24.9 at 11(22.0%) participants. Alternative measure that reflect abdominal adiposity is WHR. In our sample abdominal adiposity, defined by WHR ≥0.95 for males and ≥0.85 for females, was found at 6(12.0%) participants. Muscles are more dense and heavier than fat, and muscular athletes may be classified as overweight by BMI standards, but not be fat [3]. Moreover using BMI categories as the main indicator of health, there is possibility of misclassification of cardiometabolic health [14]. In our study there was positive correlation between measures of adiposity and age at females. There is smaller elevation in whole body adiposity across age in the exercising women [15]. Dietary pattern of males revealed that less frequent consumption of milk and milk products, as well as fruits correlated with higher value of anthropometric indicators. On the other hand, more frequent consumption of sodas correlated with higher waist circumference and WHR. The impact of sodas on adiposity was evaluated in numerous studies with opposite results [16], as well as the impact on health [17].

Conclusions
There are two main limitation of our study: its cross-sectional design and lack of information about serving size of commodities. Nevertheless it provides baseline information about anthropometric indicators and dietary pattern. Maintaining an active life-style is important for fitness and health. There are different recommendation about physical activity that can be adopted in group. Sometimes nutritional needs are underestimated and restriction of some food group, like fruits may be adopted. Recreational athletes train at various intensity so they need a variety of food choices that will provide a balance of nutrients in order to perform at an optimal level.

Conflict of Interests
The authors declare that they have no competing interests.

Bibliography

1. Westerterp, K. R. (2019). Physical activity and body-weight regulation. Am J Clin Nutr., 110(4), 791-792.
2. McMurray, R. G., Soares, J., Casparsen, C. J. & McCurdy, T. (2014). Examining Variations of Resting Metabolic Rate of Adults: A Public Health Perspective. Med Sci Sports Exerc., 46(7), 1352-1358.
3. Whitney, E. N. & Rolfes, S. R. (2017). Understanding Nutrition, 15^th edition, Wadsworth Cengage.
4. Ho, K. K. Y. (2018). Diet-induced thermogenesis: fake friend or foe? J Endocrinol., 238(3), R185-R191.
5. Neilson, H. K., Robson, P. J., Friedenreich, C. M. & Csizmadi, I. (2008). Estimating activity energy expenditure: how valid are physical activity questionnaires? Am J Clin Nutr., 87(2), 279-291.
6. Wells, J. C. K. & Fewtrll, M. S. (2006). Measuring body composition. Arch Dis Child., 91(7), 612-617.
7. Ohkawara, K., Tanaka, S., Miyachi, M., Ishikawa-Takata, K. & Tabata, I. (2007). A dose-response relation between aerobic exercise and visceral fat reduction: Systematic review of clinical trials. Int. J. Obes (Lond)., 31(12), 1786-1797.
8. Laquale, K. M. (2009). Nutritional needs of the recreational athlete. In Movement Arts, Health Promotion and Leisure Studies Faculty Publications. Paper 30.
9. World Medical Association (2013). World Medical Association Declaration of Helsinki: Ethical Principles for Medical Research Involving Human Subjects. JAMA., 310(20), 2191-2194.
10. World Health Organization (2000). Obesity. Preventing and managing the global epidemic. Report on a WHO consultation on Obesity. Geneva, Switzerland.
11. World Health Organization (2011). Waist circumference and waist-hip ratio: report of a WHO expert consultation. 2008. Geneva, Switzerland.
12. Thompson, F. E. & Subar, A. F. (2017). Dietary assessment methodology. Nutr Prev Treat Dis., 4^th ed.
13. World Health Organization (2020). “Obesity and overweight Fact sheet”.
14. Tomiyama, A. J., Hunger, J. M., Nguyen-Cuu, J. & Wells, C. (2016). Misclassification of cardiometabolic health when using body mass index categories in NHANES 2005-2012. International Journal of Obesity, 40, 1-4.
15. Van Pelt, R. E., Davy, K. P., Stevenson, E. T., Wilson, T. M., Jones, P. P., Desouza, C. A. & Seals, D. R. (1998). Smaller differences in total and regional adiposity with age in women who regularly perform endurance exercise. Am J Physiol., 275(4), E626-E634.
16. Bleich, S. N., Vercammen, K. A., Koma, J. W. & Li, Z. (2017). Trends in Beverage Consumption Among Children and Adults, 2003-2014. Obesity., 26(2), 432-441.
17. Prinz, P. (2019). The role of dietary sugars in health: molecular composition or just calories? Eur J Clin Nutr., 73(93), 1216-1223.