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Exploring the Relationship Between Dietary Energy, Fat Intake, and Optimal Health

Jun 2, 2023 | 0 comments

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Jun 2, 2023 | Essays | 0 comments

Dietary Energy And Fat Intake And Body Composition In A Student Population


Dietary intake, including fat intake in foods has been shown to relate to the body composition of individuals. The aim of this study was to investigate the relationships among body fat, energy intake, physical activity and body composition in a student population. 52 college students (26 males, 26 females) were recruited to participate in a cross-sectional study. Body composition was measured by anthropometric measurements, dietary energy and fat intake, and physical activity were assessed by 24-hour dietary recall and a life style questionnaire. The results indicated that females have a greater percentage body fat compared to males, energy intake is not strongly related to body fat, and the sedentary subjects are not more likely to be overweight compared with active subjects. In conclusion, dietary fat intake relates to body composition, but other factors also play a part such as physical activity, gender, and ethnicity among others.

Keywords: Body composition, energy intake, fat intake


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1. Introduction

Overweight and obesity are very common in developed countries, among adults and children. According to Public Health England (2015), the prevalence of obesity is increasing worldwide and results for 2013 showed that around 62.1% of adults were overweight or obese (67.1% of men and 57.2% of women). This trend is also evolving in developing countries where the number of people who are overweight rivals the number of underweight persons globally (FAO, 2003). This displays the great disparity in the global nutritional intake. Additionally, lifestyle choices, including increased calories, sugar and fat intake, large portion sizes of unbalanced food intake, reliance on pre-packaged food, decreased physical activity and increasing amount of fast foods and junk foods which are high in sugar, sodium and fat, have been associated with the increasing epidemic of obesity, overweight and adult onset diseases amongst adolescents such as type 2 diabetes, heart disease and disruptive sleep apnoea (Martorell et al., 2000; Dehghan et al., 2005).

Anthropometric (hip girth, waist girth, height and weight) measures provide insight and information into the patterns of eating, especially when used jointly with food observations and recalls (Isabela da Costa et al., 2005). However, literature on the current dietary intake, levels of weight status and the related illness amongst students or school-aged children is limited (Kyle et al., 2004). Furthermore, accurate standards for determining body composition for adolescents and children are critical. With the increasing levels of overweight persons, rapid changes in lifestyles and dietary patterns, and disparities, close monitoring of the prevalence towards children overweight is warranted (Wagner & Heyward, 2000). The objective of this study was to assess the body composition such as fat mass distribution and weight status and dietary energy and fat intake in a student population. The data collected will be used in investigating whether it agrees with the published studies and provide critical analysis of the used methodologies. Therefore, the aim of the present study is to evaluate the relationships among body fat, energy intake, physical activity and body composition by using anthropometric measurements and dietary intake analysis as well as to test the following three hypotheses:


(1) Females have a greater percentage body fat compared with males.

(2) Energy intake is strongly related to body fat.

(3) Sedentary subjects are more likely to be overweight compared with active subjects.

2. Literature Review

2.1 Gender and body fatness

Generally, women have a higher percentage of body fat compared to men (O’Sullivan, 2009). Men store more fat in the abdominal or visceral areas while women also store fat in the gluteal-femoral parts. Many studies document pronounced regional differences in the regional fatty acid metabolism regulation between women and men (Chumlea et al., 2002; Fomon et al., 1982; O’Sullivan 2009).

In a survey conducted in United States by the National Health and Nutrition Examination Survey III (NHANES III) with a total of 15,912 participants, the results indicated that white females who are non-Hispanic, aged between 12 and 80 years had higher fat mass than men. When comparing the results between males and females for each decade, the results increased 6-11% higher for females. (Chumlea et al., 2002).

Table 1: Percentage fat mass in healthy white men and women who are non-Hispanic Adapted from NHANES III; Source: Chumlea et al. (2002)

Exploring the Relationship Between Dietary Energy, Fat Intake, and Optimal Health 1

Other studies also indicate that significant gender divergence in the composition of the body commences at puberty (O’Sullivan, 2009). The differences between the gender hold across all races, and ethnic groups, although the magnitude is influenced by environmental, genetic and ethnic factors (Wells, 2007). By comparing the fat mass data in women and men after puberty from studies done by Chumlea et al. (2002) and a study conducted by Fomon et al. (1982), statistics show divergence that occurs from puberty and continues to the pre-menopausal years as shown in figure 1. In conducting their study, Fomon et al. (1982) used the 50th percentile values for height and weight from the National Centre for Health Statistics (NCHS) data. The study also used data from the literature that concerns total body potassium (TBK), total body water (TBW) and total body calcium (TBCa).

Exploring the Relationship Between Dietary Energy, Fat Intake, and Optimal Health 2

Figure 1: Statistics show divergence that occurs from puberty and continues to the pre-menopausal years; Source: Chumlea et al. (2002)

2.2 Habitual energy and fat intake and body composition

In the United States, daily calorie intake has increased and this has dramatically increased body fat in parallel (Bray, 2010). These excess calories, according to Bray (2010), appears to be from protein, carbohydrates and fats at the same time. In a randomised crossover study done by Horton et al. (1995), 16 men (7 obese and 9 lean) were overfed for 14 days in two separate period by 50% of caloric needs by adding excess macronutrients of carbohydrate or fat through the diet. The subjects were given all prepared food in a research kitchen and were even allowed to consume some at home. There were 4 weeks gap between 2 periods. In the second phase, each individual was switched to overfeed fat or carbohydrate which they did not receive in the first phase. The researchers measured changes in lean mass, fat mass and body weight after 14 days. The results indicated that fat and carbohydrate overfeeding caused nearly identical increases in lean mass, fat mass and body weight, in both obese and lean groups. The graphs of changes in body weight and fat mass are shown in figure 2 below.

Exploring the Relationship Between Dietary Energy, Fat Intake, and Optimal Health 3

Figure 2: Changes in body weight during and for 21 days after fat and carbohydrate (CHO) overfeeding in 16 male subjects; Source: Horton et al. (1995)

A similar study was also done by Lammert et al. (2000) in which ten pairs of men who are lean were overfed for 21 days by 1,195 kcal per day, given as either fat rich or carbohydrate rich diet. For the entire research period, subjects ate and lived in a research setting and the study was controlled extremely well. Body composition measurement was done weekly using underwater weighing. The results indicated that between the groups, increase in body weight was similar and fat mass increase was almost identical (see figure 3).


Figure 3: Results of Fat gain during carbohydrate and fat overfeeding; Source: Lammert et al. (2000)

However, Lammert et al. (2000) observed the most interesting thing that fat gain between individuals varied tremendously due to physical fitness, genetics and other factors since some people store more fat in their body when they consume excess calories, while others burn off the fat

2.3 Habitual physical activity and body composition

Low levels of physical activity or a sedentary lifestyle can place an individual at an increased risk of obesity and other cardiovascular diseases (O’Sullivan, 2009). In contrast, physical activity has been suggested as a method of reducing and controlling body fat (Sacheck, Kuder & Economos, 2010).

Kyle et al. (2004) conducted a study to evaluate differences in the body mass index (BMI), fat-free mass index (FFMI) and Body fat mass index (BFMI) in sedentary and physically active subjects to determine the association between body composition and physical parameters in a healthy white population. Body fat free and fat mass were determined by bioelectric impedance analysis in 3,549 white men and 3,184 white women and FFMI and BFMI calculated. The definition of the physically active subject was the person who did at least 3hour/week of endurance type of physical activity for over two months (Kyle et al., 2004). The results indicated that the physically active subjects had a higher likelihood of having low BFMI, low likelihood of having very high BFMI and low FFMI as opposed to the sedentary participants.

This study is similar to a study done by Zaccagni, Barbieri & Gualdi-Russo (2014) which mainly aimed at assessing the main anthropometric characteristics that are health related in a sample of students in relation to sport discipline, physical activity and gender. The study recruited 734 students from the university as subjects, of both sexes. A self-administered questionnaire was used in the collection of socio-demographic information (age, sex) and sport participation (sport discipline, hours/week) by using the standardized procedures with anthropometric measurements. Body composition was evaluated using a skinfold method. From the study, the results indicated significant statistical differences between the two sexes in all anthropometric traits, including fat mass, percent fat, body density, Waist-to-Stature Ratio, waist circumference, and skinfold biceps, among different physical activity levels of males, and in fat free mass, arm girths, BMI and weight in females. In conclusion, physical activity plays a significant role in parameters of body composition. Males who are mostly active have the least amount of fat mass and females who are mostly active have the greatest amount of fat free mass (Baumgartner, 2000).


3.1 Design

A cross-sectional study design, which is a type of observational study involving analysis of collected data from a population or a subset representation at a specific point in time, was used in this study because it can compare different groups of population at a single time point. Moreover, it allows the researchers to compare multiple variables at the same time (Institute for Work & Health 2015).

3.2 Sample

A total of 52 students (26 men and 26 women) participated in this cross sectional study. The participants were recruited around college randomly to avoid bias since all college students were regarded as having an equal chance of participation.

3.3 Materials and procedure

Posters were put up around the college to recruit volunteers as participants. Before participating, they were asked to read and sign the consent form as an ethical step for the study to protect the confidentiality of the participants (see appendix 1). Next, each participant was given a short lifestyle activity questionnaire to complete, which was designed based on the hypotheses of the study (see appendix 2), to assess physical activity. Then they were interviewed by the researchers to obtain their dietary history using a 24 hour dietary recall, which aided in recalling and quantifying their food intake.

Body composition was assessed by anthropometric measurements using weight, height, waist and hip. The subjects were measured for height, weight, waist, and hip circumference to calculate BMI and W: H ratio. The students’ height was measured using a wall mounted stadiometer with a sensitivity of 0.5 cm (Capristo et al., 2000) while barefoot. The current body weight of the students was measured while subjects were in minimal clothing and barefoot with an electronic weighing scale with ability to measure up to 150 kg with the sensitivity of up to 100 g and results recorded to the nearest 0.1kg. The BMI, which is used as the relative adiposity index, was calculated by dividing weight (kg) by height squared (m2). Furthermore, the W:H ratio was calculated by waist girth/hip girth using tape measure. Lastly, the percent body fat was measured through the water and electrolyte component of lean tissue and hence resistance is proportional to total body water volume while barefoot using the bioelectrical impedance machine, Tanita scales (Tanita, 2015).

3.4 Data analysis

The obtained data of the diet from the 24 hour recalls was analysed using Diet plan 6.3 which is a computer software package to determine fat and energy intake. The levels of physical activity were calculated from the short questionnaire of lifestyle, grouped into 4 groups (non-active, moderate non-active, moderate active and active).

Statistical package for social sciences (SPSS) software for windows version 21 was used in performing statistical analysis. To assess all continuous data normality, the Kolmogorov-Sminrnov (KS) test was performed (Wilcox, 2012). Histograms were used to check for outliers in the data (Wilcox, 2012). Depending on the distribution normality, independent Mann-Whitney U test or sample t-test were used for hypothesis 1. To test the relationship between variables in hypothesis 2 and the strength of linear association, Spearman’s Rank or Pearson’s Rank correlation coefficient tests were used. Lastly, to find the association between the groups in hypothesis 3, Chi-Square test was used. The statistical significance cut off was set at the level of 95% (p<0.05). The descriptive data from the study were expressed as mean and S.D. Students t-test was used to assess the body composition differences between the genders.


The sample used in the study was 52 college students (men= 26 and women= 26) of ages ranging from 18 years to 30 years. An Independent t-test (normal distributed) analysis was used to examine that there was a difference of the percentage body fat between males and females. The results are presented in Table 2. The results from the different sexes showed that the percentage body fat was positively significantly different between males and females (P<0.001, t (50) = -4.007). Females were more likely to have a greater percentage body fat (Mean=28.038, SD= 7.6445) compared with males (Mean=19.308, SD= 8.0636). The statistical results indicated that hypothesis 1 was proven to show that females have a greater percentage body fat compared to males. The greater percentage of fat amongst women than men correlated with the studies done by the National Health and Nutrition Examination Survey III (NHANES III) which also found women having higher percent body fat than men (Chumlea et al., 2002).

Table 2: Shows the statistical results from independent t-test.

Group Statistics
Gender N Mean Std. Deviation Std. Error Mean
%Body Fat Males 26 19.308 8.0636 1.5814
Females 26 28.038 7.6445 1.4992

The relation between energy intake and percentage body fat of the participants is shown in Table 3. By using Pearson’s correlation (normal distributed) in testing hypothesis 2, the results revealed that there was no significant positive association between energy intake and body fat (P= 0.560, r = -0.083). The statistical results proved hypothesis 2 to be null and void to show that energy intake is not strongly related to body fat. The findings correlated to a study done by Lammert et al. (2000) who observed that fat gain between individuals varied tremendously due to physical fitness, since some people store more fat in their body when they consume excess calories, while others burn off.

Table 3: Shows the statistical results from Pearson’s correlation

Energy_intake_kcal Body_Fat_Percent
Energy intake (kcal) Pearson Correlation 1 -.083
Sig. (2-tailed) .560
N 52 52
%Body Fat Pearson Correlation -.083 1
Sig. (2-tailed) .560
N 52 52

The question of whether participants who engaged in less physical activity would be more overweight, this was examined by using a Chi-Square analysis. As can be seen in Table 4, the results indicated that there was no significant statistical difference between active subjects and sedentary subjects (P= 0.359, Chi2= 0.84, df = 1). Of the original 52 samples, 14 subjects were overweight (BMI>25). Out of the 28 active participants, 9 participants (32.14%) were overweight. However, 5 participants (20.83%) out of 24 sedentary participants were overweight. Active students were more likely to be overweight compared to sedentary students, so there is no association between a sedentary lifestyle and being overweight. The statistical results proved hypothesis 3 to be null and void to show that sedentary subjects are not more likely to be overweight compared with active subjects.

Table 4: Shows the statistical results from Chi-Square Tests

Overweight * Active Crosstabulation Pearson Chi-Square
Active Inactive Total Asymp. Sig. (2-sided)
Not overweight

BMI <=25

Count 19 19 38 .359
Expected Count 20.5 17.5 38.0

BMI > 25

Count 9 5 14
Expected Count 7.5 6.5 14.0
Total Count 28 24 52
Expected Count 28.0 24.0 52.0


5.1 Higher body fat percentage among women than men

In relation to hypothesis 1, the results found that females have a higher percentage body fat than males, and, therefore, the findings agree with hypothesis 1. In the literature review, it was evident that females have higher percent body fat compared to the men. The explanation for the disparity in the body fat between men and women can be explained from different angles. According to Blaak (2001), fat in normal women is usually between 18%-20% of body weight while in men is between 10%-15%. The higher percentage of fat in women is that at some point in women’s lives, they may nourish a foetus using their fat reserves; hence they stock energy in the form of fat in readiness of future pregnancies (Blaak 2001).

Another biological reason for the differences is that women need fewer calories per body weight pound daily than men (Pomroy & Adamson 2013). Moreover, the hormones of the females make it easier for converting food into fat. For instance, oestrogen hormone alone causes increased fat deposition (Pomroy & Adamson 2013). Blaak (2001) also pointed out that females experience more hydration level changes compared to men due to their menstrual cycle, and this has a potential of affecting measurement of body fat, especially when the BIA method is used.

5.2 Energy intake and body fat

In relation to hypothesis 2, the more energy intake does not mean that there will be more body fat and, therefore, disagrees with the hypothesis 2. This is also echoed in a study by Lammert et al. (2000) who observed fat gain between individuals varied tremendously due to physical fitness, genetics and other factors since some people store more fat in their body when they consume excess calories, while others burn off fat.

There are many causes of body fat including energy intake, but intake of energy is not the only cause of body fatness. According to Rothblum & Solovay (2009), the first cause of fat is unhealthy diet practices involving the intake of junk food and excessive oil in the diet. Additionally, lack of exercise causes body fat due to slow metabolism of food in the body. Rothblum & Solovay (2009) also indicated that genetic factors also cause disparities in body fat. Furthermore, hormones that are irregular can also cause excess fat deposition in body areas and can result in obesity. For instance, men who develop “female buttocks” and “man boobs” as a result of increased female hormone oestrogen secretion in higher quantity compared to the testosterone hormone in males.

5.3 Sedentary and active people and their likelihood of being overweight

In relation to hypothesis 3, being sedentary is not a prerequisite for being overweight. Non-active people may not exceed calorie intake so they can burn fat and manage to be the regular weight (Kyle et al., 2004). In contrast, even though some people might do exercise every day, they consume total energy intake more than energy expenditure, therefore, they are more likely overweight. Moreover, there are many factors that can cause overweight than the sedentary lifestyle among individuals such as ethnicity, age, energy intake, hormones among others (Kyle et al., 2004). Additionally, to use BMI > 25 as an index of overweight people may be not appropriate since some people have higher muscle than fat that might affect their weight such as athletes (Kyle et al., 2004).

As much as sedentary lifestyle can cause overweight to an individual, there are additional factors that can cause overweight even to the active people (Martorell et al., 2000; Sacheck, Kuder & Economos., 2010). Environment of an individual can also cause overweight amongst persons such as tight work schedules that limits the time for physical activity (Martorell et al., 2000). Moreover, lack of sidewalks in the neighbourhoods and recreational places and affordable gyms for people to be active physically (Kuder & Economos., 2010). Oversized portion of food in the environment such as in restaurants, gas stations, fats food places, supermarkets movie theatres and even at home (Martorell et al., 2000; Sacheck). Lammert et al. (2000) pointed out the food adverts that surround people everywhere majorly targeting children with their sugary drinks and high-fat snacks.

5.4 Limitations and implications of the study

The limitations of this study might be the small sample size used in the study and a short period of data collection compared to the other research discussed in the literature review. The percentage body fat measurement may not also be the same as the reality because possibly there was bias in regard to the Tanita Scales measurements. For example, the subject should not consume any food or drink in the previous 4 hours before testing. Moreover, there could also be some bias in using 24-hour recall since the accuracy of the total energy intake data had to rely on the memory of the participants and it might not be the habitual intake of them.

The final results of the study indicated a significant relation between weight status and dietary intake. However, the results showed some insight into the patterns of eating, environmental influence and the changing economy on dietary habits and lifestyle, weight status and offered valuable information on improving on future methods of collection of data on college students.

6. Conclusion

In summary, the paper was a study on dietary energy and fat intake and body composition in a student population. The study was aimed at investigating whether the data collected agrees with the studies published and also aimed at testing the three hypotheses proposed. The cross-sectional study design of 52 participants found that females have a greater percentage of body fat compared to males. However, the study disagreed with the hypotheses that energy intake is strongly related to body fat, and that sedentary subjects are more likely to be overweight compared with the active individuals. The data collected agrees with most studies published as discussed. The limitations of the study included small sample size, technique used, possible biases during the study. To warrant the outcomes, long-term research, larger sample and different technique used are needed in further studies. Additional work is also needed to investigate on the dietary energy and fat intake and body composition of black/white/Hispanic student population, since body composition also is influenced by ethnicity/race.


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