Dietary Pattern and Body Composition of Professional Football Players in Ghana: Implications on fitness and performance

doi:10.21203/rs.3.rs-2073796/v1

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Dietary Pattern and Body Composition of Professional Football Players in Ghana: Implications on fitness and performance

https://doi.org/10.21203/rs.3.rs-2073796/v1

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Introduction

Good dietary practice is essential in sports as it improves the quality of training, maximizes performance and aids in the speedy recovery of players from injuries. A balanced diet provides adequate nutrients and energy to achieve these purposes. Nutritional status is also essential in ensuring optimum performance among athletes. But one may not achieve optimum nutritional status with poor dietary practices. Thus, footballers' poor dietary patterns and sub-optimal nutrition could lead to low fitness and poor performance during competitions.

Aim

This study aimed to assess the dietary pattern and body composition of professional football players in Ghana, and its implications on fitness and performance.

Methods

The study was cross-sectional. One hundred and nineteen footballers from five teams were randomly recruited for the study by quota sampling. Dietary behaviour pattern was assessed using a validated food frequency questionnaire, and body composition was measured using Omron bio-impedance body analyzer. Statistical analysis was performed using SPSS version 20 for windows and Microsoft Excel 2013. Correlations were determined among anthropometric variables, while eta-squared was used to determine associations between dietary patterns and anthropometric characteristics. Statistical significance was set at p < 0.05.

Results

The mean age of the footballers was 21.57 ± 4.3 years, with the majority (58%) within the 20–29-year group. Three dietary patterns explained 50% of the variation in diets of the footballers; 1) Fruits and vegetables, 2) energy and fiber foods (Modern Ghanaian), and 3) protein and starchy foods (Typical Ghanaian). Over 30% of the footballers were overweight. Animal protein consumption explained 9% [F (4, 130) = 2.446, p = 0.05] of the variation in BMI of the footballers with cereals and grains explaining 18% of the variation in BMI [F(4, 130) = 6.212, p < 0.001]. Percentage muscle mass negatively correlated to BMI (p < 0.01), whiles visceral fat correlated positively with BMI and body fat (p < 0.01).

Conclusion

Dietary pattern depicts low intakes of animal protein and fruits with high intakes of energy giving foods. Thus, professional footballers need targeted education on adequate diets to prevent the risk of iron deficiency which may result in low fitness and poor performance.

Professional footballers

dietary behavior

body composition

fitness and performance

Ghana

Football players must fuel properly with wholesome nutrition and water due to the high-intensity nature of practice and play (Hulton, Malone, Clarke, & MacLaren, 2022). In order to replace and regenerate depleted hormones, neurological functions, dehydration, and the transfer of electrolytes in athletes, especially football players, healthy and adequate nourishment is crucial (Afrifa, Nsiah, Appiah, & Moses, 2020), maintaining lean muscle mass, refueling energy stores and promoting optimal performance (Devlin, et al., 2016). Football players, like any other athlete participating in team sports due to the extreme demand on the cardiovascular, metabolic, and energy stores, have a special consideration when it comes to nutrition (Sale & Elliott-Sale, 2019). This is due to the high risk of suboptimal dietary intake among the players due to restrictive diet and their high requirements for certain nutrients and energy (Devlin, et al., 2016).

Research has however reported that athletes across a range of team sports consistently fail to meet energy and carbohydrate recommendations (Sarah L Jenner, Buckley, Belski, Devlin, & Forsyth, 2019). The difficulties and challenges athletes experience with regards to consuming a well-balanced diet and meeting energy recommendations have also been reported (Walsh, 2018). Numerous personal and environmental elements, such as knowledge, skills, peers, team dynamics, time restraints, resources, as well as access to wholesome foods, are some of the factors that influence the dietary intakes and behaviors of athletes (Bentley, Patterson, Mitchell, Backhouse, & Exercise, 2021; Sharples et al., 2021) especially young athletes.

Different eating patterns and nutritional intake have been frequently reported for athletes with markedly different physiological demands (Desbrow et al., 2019; Sarah L Jenner et al., 2019). The type, intensity, and duration of exercise affect substrate utilization and nutrient needs (Griffiths et al., 2019). Furthermore, it has been described that athletes practicing sports with high endurance demands show a spontaneous tendency towards a higher carbohydrate (CHO) intake (Louis, Vercruyssen, Dupuy, Bernard, & activity, 2019; Margaritis & muscle, 2019). In football, players in those positions with an activity profile that includes a higher proportion of aerobic energy production (full-backs, midfielders, and wingers) show significant differences in their performance capabilities (Borghi et al., 2021), physiological as well as anthropometric characteristics compared with those whose work-rate profiles emphasize more anaerobic energy production (goalkeepers, centre-backs, and forwards) (Modric, Versic, & Sekulic, 2021).

To build a body that can withstand training loads and meet demands, coaches and high-performance staff regularly assign athletes body composition targets like reducing body fat and increasing lean muscle mass (Bilsborough, et al., 2016). These objectives will probably have an impact on how much food athletes eat. Hence, in order to attain body composition goals, nutritional consumptions may be restricted.

High training loads may hinder recuperation, increase the risk of injury or illness, and lower overall performance during these times (i.e., symptoms of overtraining) (Burke, 2001). In order to inform strategies for supporting athletes and assisting them in maintaining adequate dietary intakes required for performance, it is crucial to investigate the extent to which body composition goals influence dietary intakes. Body composition measurements may be taken during various training phases. According to research, when there are body composition goals (i.e., required to maintain a lean physique or lose fat mass), an energy deficit and the amount of macronutrients needed for refueling and recovery are typically decreased (Sarah Louise Jenner et al., 2018).

There have been earlier investigations into the potential causes of athletes failing to take enough nutrition and energy after weeks of intense training ((Meade, McLaren, & Bennett, 2022; Melin, Heikura, Tenforde, & Mountjoy, 2019; Schubert, Sabapathy, Leveritt, & Desbrow, 2014). On important training days, an athlete's capacity to absorb the necessary amounts of nutrients and energy may be impacted by physiological factors like hormones (Logue et al., 2020). Education that ties food intake to performance could encourage behavior modification and lessen the influence of other factors, including body composition measurements, on intake. (Jenner et al., 2018). For high-intensity aerobic sports like the division one football matches, carbohydrate is a crucial fuel source and is essential as a muscle substrate for performance and recovery (Książek, Zagrodna, Słowińska-Lisowska, & Health, 2020). Therefore, a lack of available carbohydrates can result in the depletion of muscle glycogen, which then causes fatigue, attention problems, and a reduction in physical performance (Dearlove et al., 2021).

Therefore, individuals may limit their consumption of carbohydrates in order to achieve their body composition goals (Minderis, Fokin, Dirmontas, Kvedaras, & Ratkevicius, 2021). According to a study by Jenner et al., there is little information of carbohydrate guidelines (Jenner et al., 2018). Previous research reveals that athletes have an incorrect perception of the availability of carbohydrates (i.e. carbohydrate intake is related to body fat gains). There is a knowledge gap about the significance of carbs as a primary fuel (Jenner, 2018). Although significant research has been done on the importance of nutrition for football players, less has been done on the dietary habits and body composition of professional footballers, particularly in Africa and in Ghana.

A cross-sectional study design was used to assess professional footballers' dietary behaviour and body composition in northern Ghana.

Sampling and Study Subjects

Five professional division one football teams were enrolled into the study. Proportionate sampling was used to select participants to ensure a fair representation from the teams as they vary in size. One hundred and thirty (130) professional footballers were randomly selected from all five teams for the study. The teams recruited included Galaxy (n = 40), Real Tamale United (n = 50), Tamale All Stars (n = 34), Gwan United (n = 31) and Tamale Utrecht (n = 36). All five teams are located within the northern region of Ghana.

Study measures and data collection procedure

Demographic characteristics

Respondent's age in completed years, marital status, religion, and level of education were all obtained.

Food frequency and dietary pattern

Over 100 different food items were divided into eight groups using a 7-day Food Frequency Questionnaire (FFQ), including animal protein, vegetable protein, vegetables, soft drinks and sweets, cereals and grains, tubers, fruits, and fruit juices. The Food Frequency Questionnaire is an easy tool that is inexpensive, quick to use, and only slightly burdensome for the subject (Kristjansdottir, Andersen, Haraldsdottir, De Almeida, & Thorsdottir, 2006). The number of times each constituent food item (or group of food items) was ingested over the course of the previous seven days was used to calculate consumption of food items/subgroups by summation of the number of times each food was consumed. In linear regression techniques, factor scores for each detected pattern using principal component analysis (PCA) were saved.

Body Composition and Anthropometry

The Charder HM200P portable stadiometer (Charder Electronic co., Ltd., Taichung, Taiwan), which has a vertical rod with a fixed measuring tape and a flat board on which the participants stood, was used to measure height. It was calibrated to 0.1 cm. On the platform, each participant took a straight stance with their feet together and their arms at their sides. The height was then measured using the scale and recorded in centimeters, to the nearest decimal point.

Using the participants' heights and ages, the Omron Body Composition Monitor and Scale (Model HBF-516) was used to determine their weight, BMI, percentage of muscle mass, percentage of body fat, and visceral fat. The date and time were set, the batteries were securely fastened, and the portable device was placed on a hard, level surface. Participants were asked to stand on the equipment with their backs straight, and eyes forward. They had to hold the display unit in front of them while raising their hands horizontally so that their elbows formed a 90-degree angle with their bodies.

In order to conduct the survey, gather nutritional information by adhering to ethical guidelines for research involving professional football players, five research assistants underwent training. Two non-participating football teams from the northern region pre-tested the study tools. Study instruments lasted between 30 minutes and an hour and were administered by interviewers. To aid in participant remembering, the research assistants asked about daily, weekly, and mixed meal options. Participants were also urged to mention any meals they had eaten that weren't on the offered list.

Data Analysis

Data analysis was performed using the Statistical Package for Social Sciences (SPSS) version 20 for windows and Microsoft Excel 2013. Frequency distributions were summarized in tables for categorical demographic characteristics. Arithmetic means were determined for continuous variables. Preliminary tests were carried out on data to check for normality/ distribution (z- scores for outliers, Kolmogorov Smirnov test, Q-Q plots) and also reliability test (Cronbach's alpha test statistic) performed on items included in Principal Component analyses (PCA).

Respondents were classified as underweight, normal weight, overweight or obese based on their body mass index (BMI) (WHO, 2021). Overweight and obesity were defined as BMI between 25kg/m² – 29.99kg/m²and30kg/m² and above respectively; normal (nonobese/overweight) was defined as BMI between 18.5kg/m²– 24.99kg/m²; whiles underweight was defined as BMI of 18.49kg/m²or less (WHO, 2021).

Dietary patterns were assessed using principal component analysis (PCA) based on data collected with a food frequency questionnaire (FFQ). To ensure that > 5% of respondents consumed each food item included in PCA, food items were categorized into several subgroups based on shared nutritional value/significance. Subgroups of foods created for PCA are: Fruits; Soft drinks; Vegetables; Fruit juice; Plant protein; tubers; Cereals and grains; Animal protein. Thus, a total of 8 items were subjected to PCA to identify foods highly correlated with each other and possibly combined to describe the significant patterns in respondent diets. PCA used orthogonal rotation (varimax) and a number of components determined by Kaiser's stopping rule (factors with Eigen values over 1.0 are considered in analysis) (Kaiser, 1960) and examination of scree plots. Varimax rotation was used to maximize the factor loadings onto each component to interpret patterns easily.

On the basis of factor loadings > 0.4 and 0.4, patterns were identified. Acceptable cut-offs for the Kaiser-Meyer-Olken (KMO) Measure test and Bartlett's test of sphericity were used to determine whether the data were appropriate for factor analysis. The elements of each isolated component accounting for variance in diets were accurately reflected in the labels applied to the dietary patterns produced by PCA. Consequently, a dietary pattern refers to a recognizable group of closely linked foods as found in PCA (Alangea, Aryeetey, Gray, Laar, & Adanu, 2018).

The association between dietary pattern factor scores and body composition was examined using simple linear regression. To identify key elements connected to each of the three dietary patterns, multiple linear regression was used (Alangea et al., 2018). The statistical significance was determined at an alpha level of 0.05.

Ethical Clearance

The University of Ghana's School of Biomedical and Allied Health Sciences' Ethics and Protocol Review Committee granted clearance for this studies to be conducted (SBAHS-ET./0209831488/AA/7A/2012-2013). A thorough description of the research's goal and its risks and advantages was given to the teams' management and the participants themselves on the field. Permission was then requested. Before taking part in the study, participants were also given written informed consent forms to fill out and sign. Results of laboratory tests and information gathered from each study participant throughout the survey were kept private and confidential.

Demographic Characteristics

The sociodemographic details of the football players are displayed in Table 1. There were 119 football players in all that participated in this study. The football players' average age was 21.57 ± 4.3 years. Majority (58%) belonged to the 20-29 age group. There were just 8 married football players (6.7%). The football players were all educated to some extent. The majority's (63.9%) highest educational achievement was Senior High School (SHS).

Table 1: Socio-demographic characteristics of the footballers who participated in the study (n = 119)

Variable	Categorization	Number	Percentage (%)
Age	10 – 19	43	36
	20 – 29	69	58
	30 – 39	7	6
Marital Status	Married	8	6.7
	Not Married	111	93.3

Education	JHS	38	31.9
	SHS	76	63.9
	Diploma	5	4.2

SHS: Senior High School; JHS: Junior High School

Emerging dietary patterns

The PCA results yielded a KMO = 0.648, which is meritorious (Field, 2009). Also, the used items had enough significant correlations for PCA (Bartlett’s test of sphericity = χ2 (28) = 104.664, p < .001). Examining the scree plot, which displayed an inflection at the third component, provided information on the number of decided components. Three dietary patterns were found by PCA to account for nearly 50% of the variation in respondents' diets (see Table 2). The label given to each component was determined by its high loading items and the factors' interpretability. Fruits and vegetables topped the list, followed by modern Ghanaian/soft drinks and plant proteins, and finally, typical Ghanaian foods/protein and energy giving foods The different food items and the solution with shortened components are displayed in supplementary table 1.

Table 2 Dietary patterns of footballers determined using principal component analysis

Components		% of variance	Label for dietary pattern
Component 1	Fruits	20.206	Fruits and vegetables
	Fruit juice
	vegetables
Component 2	Soft drinks	15.966	Energy and fiber foods (Modern Ghanaian)
	Plant protein

Component 3	Tuber	13.744	Protein and starchy foods (Typical Ghanaian)
	Cereals and grains
	Animal protein

%: Percentage

Anthropometric Characteristics of the Footballers

The anthropometric dimensions of the DOL footballers are shown in supplementary Table 2. The average weight was 65.04 kg, and the average height was 162.34 ±16.4 cm. The football players' percentage of muscle mass was generally high, ranging from 24.40 to 48.20%, with a mean of 41.73 ±3.1. With a mean of 24.48 ±4.0kg/m2, BMI varied from 18.10 to 36.3kg/m2. Visceral fat, body fat, and muscle mass all had average values of 41.73%, 20.25%, and 6.29, respectively.

Nutritional status based on BMI

Using BMI categorization to assess the nutritional status of the footballers (Fig. 1), seventy-two respondents (60.5%) had normal nutritional status, and only three (2.5%) were obese.

Correlation between anthropometric variables

According to correlational data, there was a strong negative correlation between a number of variables, including percentage muscle mass and BMI (p=0.01), percentage muscle mass and body fat (p=0.01), and percentage muscle mass and visceral fat (p=0.01). On the other hand, there were significant positive correlations between visceral fat and BMI (p0.01) and visceral fat and percentage body fat (p0.01) (Supplementary table 3).

Associations between body composition and food groups consumed by the footballers

Associations between body composition (BMI, %muscle mass, %body fat, and visceral fat) and the various food groups consumed by the division one footballers in the northern part of Ghana were determined. Animal protein consumption explained 8% [F(4, 130) = 2.446, p = 0.05] of the variation in BMI of the footballers with cereals and grains explaining 18% [F(4, 130) = 6.212, p < 0.001]. There was no significant association between BMI and the other food groups.

Animal protein [F(4, 130) = 3.366, p = 0.012], vegetable protein [F(4, 130) = 2.532, p < 0.05], and cereals and grains [F(4, 130) = 4.072, p < 0.01] were significantly associated with percentage muscle mass of the footballers. Fruit juice [F(4, 130) = 2.243, p = 0.05] had a borderline association with percentage muscle mass. Animal protein contributed about 19% to the variation in percentage muscle mass. Cereals and grains, vegetable protein, fruit juice contributed 13%, 8%, and 9% respectively to the variation in percentage muscle mass.

Some associations were also observed between animal proteins [F(4, 130) = 3.254, p < 0.05], cereals and grains [F(4, 130) = 5.507, p < 0.001], tubers [F(4, 130) = 2.277, p = 0.05] and visceral fat. Animal proteins contributed to 17% of the variation in visceral fat, cereals and grains contributed 16%, whereas tubers also contributed 9% of the variation in visceral fat.

Details of the strength of association between body composition and food groups are shown in Supplementary Table 4.

This study aimed to assess professional footballers' dietary behaviour and body composition in the Tamale Metropolis in Northern Ghana. This is the first study to assess dietary patterns and body composition among professional footballers in Northern Ghana to the best of our knowledge. In that regard, three dietary patterns were identified: fruits and vegetables, soft drinks and plant proteins/modern Ghanaian and protein and energy giving foods/typical Ghanaian. There were negative but significant associations between percentage muscle mass and BMI, percentage muscle and body fat, and percentage muscle mass and visceral fat. However, significant and positive relationships were observed between visceral fat and BMI and between percentage body fat and visceral fat. There were associations between the percentage muscle mass of the footballers and animal protein, vegetable protein, cereals, and grains.

Dietary Patterns

We identified fruits and vegetables as the first primary dietary pattern consumed by the footballers in this study. The second and third dietary patterns identified in the study included soft drinks, plant proteins (modern Ghanaian), and typical Ghanaian foods. The second dietary pattern identified primarily consisted of westernized foods. With the advent global advent of modernity and the expansion of the global market (Popkin, Adair, & Ng, 2012), it is no surprise that footballers in this study are also adopting modernized diets which are in vogue. The footballers' adoption of this modern Ghanaian pattern could also have been influenced by emulating their foreign counterparts.

Additionally, footballers may face other external influences that influence diet accuracy and recovery. Furthermore, obtaining a desired body composition and pressure from authorities may compel the adoption of these dietary patterns (Jenner et al., 2018). Football involves regular training and competition and thus requires individuals to eat energy giving foods to maintain peak performance. This reason could have also explained the energy giving foods dietary pattern as observed among the footballers in this study. Furthermore, these energy-giving staples are a dominant component of the typical Ghanaian diet. Protein foods were also found in two patterns. Earlier studies have shown that increased protein intake can help preserve muscle mass (Areta et al., 2014).

Anthropometric Characteristics Of The Footballers

We found in our study that 35.3% and 2.5% of the participants were overweight and obese, respectively. These results vary from a recent study conducted in Ghana in which 8.4% were overweight, and none were obese (Afrifa, Nsiah, Appiah, & Moses, 2020). The obesity prevalence reported in our study is lower than what was reported earlier by Stiefel and colleagues (Stiefel et al., 2013). The observation of obesity among footballers in this study is essential for football authorities to acknowledge that they may overlook obesity during medical screening of footballers. It also brings the need for adherence to lifestyle and exercise modifications. The current study found a negative association between muscle mass and BMI fat. Similar findings were reported that BMI was not a good correlate of muscle mass. The authors explained that BMI does not provide precise information about body fat but body size (Gacesa Popadic et al., 2011). Our data also revealed a negative relationship between percentage muscle mass and body fat. This resonates with an earlier study by Davison, who also reported that high muscle mass was correlated to low body fat (Davinson, Ford, Cogswell, & Dietz, 2002). Another negative relationship was found between percentage muscle mass and visceral fat. This could be explained by the continuous burning of visceral fat associated with footballing activities.

Associations Between Body Composition And Food Groups Consumed By The Footballers

The present study found that animal protein consumption explained variation in the BMI of footballers. Though not in the same population, similar observations were made in population-based studies in which positive associations were found between protein intake and BMI (Pasiakos, Lieberman, & Fulgoni, 2015; Westerterp-Plantenga, Nieuwenhuizen, Tomé, Soenen, & Westerterp, 2009). A plausible explanation for this observation is that protein diets are likely to have short-term favourable effects on weight loss over weeks to months and with no long-term effects. Our study also reported that proteins of all kinds were significantly associated with the muscle mass of footballers. This is consistent with what was reported by Aubertin-Leheudre and Adlercreutz, who also found a positive correlation between protein intake and muscle mass index (Aubertin-Leheudre & Adlercreutz, 2009).

Proteins form the foundation for gaining muscle. Proteins and amino acids constitute the building blocks for developing muscle tissue in the human body. Though other macronutrients contribute to muscle mass development, proteins are credited for building strong muscles. There were also significant variations in body mass in visceral fat and muscle mass explained by cereals, vegetables, and fruits. Though fruits and vegetables do not come to mind when visceral and muscle mass formation is described, they contain Potassium which helps with muscle growth. Potassium helps build muscle, and the carbohydrates they contain also spares the body from burning the muscle for fuel. Football involves strenuous exercises that produce chemical reactions that could damage cells, but fruits and vegetables contain antioxidants that prevent muscles from undergoing oxidative damage (Evert et al., 2019).

We identified three dietary intake patterns among the football players: fruits and vegetables, energy and fibre foods, and protein and starchy foods. We found a co-existence of westernized and traditional dietary patterns among the footballers. Overall, the prevalence of obesity and overweight among footballers was 2.5% and 35.3%, respectively. Our study found negative correlations between muscle mass and BMI, body fat and visceral fat, while positive associations were identified between visceral fat and BMI and body fat. If not checked, the prevalence of overweight could metamorphose into obesity and could have implications on their fitness and performance, hence their competitiveness. This presents an opportunity to advocate for healthy food choices even among physically active individuals such as footballers, to keep them fit for optimum performance.

Ethics approval and consent to participate

Approval was obtained from the Ethics and Protocol Review Committee of the School of Biomedical and Allied Health Sciences (SBAHS-ET./0209831488/AA/7A/2012-2013). On the field, consent was sought from the management of the teams and the participants themselves after a detailed explanation of the purpose of the research and risks and benefits were made known to them. Participants were also given a written informed consent forms to fill and sign before they took part in the study. Data collected during the survey from each study participant and results of laboratory tests were kept confidential. All methods and procedures were carried out in accordance with relevant guidelines and regulations.

Consent for publication

Not applicable

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

This study was self-funded

Authors' contributions

KA, FEAH and CAB conceptualized the idea. KA, FEAH and CAB worked the methodology designed the study. KA, WKA and ARA helped with data analysis and drafting of first version of the manuscript. All authors participated in revising the first draft of the article and accepted its final version.

Acknowledgements

We thank the division one footballers in Tamale Metropolis for agreeing to take part in this research. We are also grateful to management boards of the various teams recruited for allowing us access to their teams, and also facilitating our data collection process. Finally, we are thankful to all the research assistants who were recruited to help with data collection.

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No competing interests reported.

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Dietary Pattern and Body Composition of Professional Football Players in Ghana: Implications on fitness and performance

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Abstract

Introduction

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Introduction

Material And Methods

Food frequency and dietary pattern

Results

Discussion

Dietary Patterns

Anthropometric Characteristics Of The Footballers

Associations Between Body Composition And Food Groups Consumed By The Footballers

Conclusion

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References

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