Introduction
Rezzi et al (2009, pp.357-61) claims energy balance is achieved through equilibrium between energy or dietary intake and energy expenditure as a result of metabolism. Anderson et al (2009, pp.48-50) advanced an argument that energy expenditure monitoring is instrumental towards determination of energy requirements that could support individual daily activities. In addition, Prentice et al (1989, pp.160-64) have documented that energy consumption correlates positively with heartbeat rate which makes dietary intake measurement an important process towards control of obesity and cardiovascular disorders. Determination of relationship between energy intake and energy expenditure is therefore important aspect towards determination of maximal energy expenditure, optimization of fat expenditure as secondary source of energy after carbohydrates and capacity to achieve energy balance that could contribute into weight management (Schoeller, 1990, pp.374-6). As a result, understanding of relationship between energy intake and energy expenditure could be exploited towards weight change prediction and energy balance follow up processes.
Policy implication of energy intake and energy expenditure
Knowledge of energy intake and expenditure (Bandini et al (1990, pp.422-3) is instrumental towards capacity to compare and contrast energy expenditure of different activities and workouts. Understanding correlation between energy intake and expenditure plays a leading role towards capacity of dietetics to conduct individual assessment of daily energy requirement and propose right food regimen and dietary menu for different individuals based on energy balance requirements. Livingstone et al (1992) claims energy balance competence is important towards capability of individual to choose suitable diets based on energy demands of their body and ensures weight management programs to structure optimal training intensity for different individual based on energy balance data. Studies on energy balance are important towards individual long term monitoring of variability of energy balance. Energy expenditure (Diaz et al, 1992, pp.2-6) is a function of internal heat produced and individual external mechanical work done. Acheson et al (1980) claims internal heat emerges from Basal metabolic rate (BMR) and thermic effect of food while external work done is estimated as total individual Physical Activity Level (PAL) (Livingstone et al, 1992, pp.32).
Objective of the study
The study seeks to determine difference between mean percentage nutritive intake of carbohydrates between active and non-active individuals to identify presence or absence of significance difference.
Assumptions of the study
The study assumes that the BMR for the study subjects is constant and is not affected by study-subject fitness level, height, weight and sex (Schoeller, 1990, p.374). The study further assumes there is no energy that is stored after energy intake through ingestion hence energy intake is assumed to be a sum of internal heat produced and external work done.
Energy intake = internal heat produced + external work + energy stored
Source: Bandini et al 1990, p.34
The study further assumes that thermic effect of food (TEF) intake is 10%. TEF (Diaz et al, 1992, p.21) denotes energy consumed through digestion, absorption of digested food, and stored energy).
Methods
The study investigated subjects who were aged 12-15 years who participated in an energy intake and expenditure experiement. The subejcts were exposed to equal energy intake and estimated equal energy expenditure exercises. The subjects were classified into two groups, active and non-active based on sex. The subjects were provided with an energy controled diet whose energy value was calculated and pre-determined and exposed to different aerobic exercises that were assumed to consume pre-determined energy at a pre-determined time period. This ensured that individuals were exposed to estimated individualized energy needs so that the experiemnt was condcuted within the limits of enquiry and abdided by ethical concerns without creation of a fasting event. The energy needs of the subejcts were measured based on the subjects body weight. All the subjects filled and signed an informed consent form before participation in the experiment. The procedures of the study were approved by the ethics committee of the college. The foods were weighed to a nearest 0.1g and estimated energy intake were calculated by using a computerized database and analysis program (NDS-R software, version 5.0–
3.5; the University of Minnesota). Data analysis was carried out by using test statistic (t-test: two tailed, unequal variance) in order to determine if the data collected on carbohydrate nutritive intake was consistent with the experiment null hypothesis. T-test was used because it utilizes mean of two groups and variance of the data sets through measures of spread of the data namely moments of kurtosis, moments of skewness and moments of correlation. The food sample was found to contain 44% fat, 23% protein and 33% carbohydrates. The rejection or acceptance of the null hypothesis or alternative hypothesis was based on p-value of 0.5. If p<0.5, the null hypothesis was rejected alternatively, a P>0.5 resulted into acceptance of the null hypothesis.
Results
Table 1: individual energy intake and expenditure
Table 2: Class data (stream B) of mean energy intake and energy expenditure over a two day period
Table 3: Class data (stream B) of mean percentage nutritive intake as carbohydrate
Table 4: Working out for statistical analysis
The results determined that t = 0.68; d.f. = 536 and P>0.5.
Discussion of the results
The results demonstrated that the active female subject’s energy intake (EI) in terms of carbohydrates, protein and fats was less compared to non-active female subject’s energy intake. That corresponded to energy expenditure (EE) where active females had lower EE compared to Non active females EE (table 2). However, in males, the active males had a higher energy intake (in terms of carbohydrates, protein and fats) EI than non-active males and a corresponding higher EE compared to non active males EE. Overall, the energy intake (EI) in terms of carbohydrates of the active subjects was found to be higher compared to EI of the non-active subjects (table 3). The results achieved a t = 0.68, d.f. = 536 hence a P>0.5. As a result, the mean percentage nutritive intake as carbohydrates of physically active individuals was not significantly different from non-active individuals. This implies that the mean percentage nutritive intake as carbohydrates of results of energy intake could not be used to determine if the subject was active or not active. This was subject to imbalance of the energy intake where more proteins and fats were provided to the subjects. Therefore, the subjects should have been given food that contained more carbohydrates, lesser protein and fats. The subjects mean percentage energy intake didn’t conform to standard recommended nutritive energy intake where the diet should contain 10% energy intake from protein, 30% or less energy intake from fats and 60% or more (depending on % of fat) energy intake of the carbohydrates (Diaz et al, 1992)
The results demonstrated that EI/EE of females regardless of activity was greater than 0.5. The EI/EE of active females was found to be 6178.7/10356.6 = 0.59 while the EI/EE of non-active females was found to 6709.4/10378.1 = 0.64. The EI/EE of active males was found to be 0.69 while EI/EE of non active males was found to be 0.74. This showed that males have a higher energy demand compared to females hence should have a higher energy intake.
Conclusion
Through the use of a two-tailed unequal variance t-test, the mean percentage nutritive intake as carbohydrate of physically active individuals (table 3) was not significantly different from non-active individuals (t = 0.68, d.f.=536, P>0.05) hence acceptance of the null hypothesis HA and rejection of the alternative hypothesis Ho
References
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Livingstone MBE, Prentice Am, Coward WA, et al. (1992) Validation of estimates of energy intake by weighed dietary record and diet history in children and adolescents. Am J Clin Nutr., Vol.56, pp.29–35.
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Rezzi S, Martin FP, Shanmuganayagam D, Colman RJ, Nicholson JK, Weindruch R (May 2009). “Metabolic shifts due to long-term caloric restriction revealed in nonhuman primates”. Exp. Gerontol. 44(5), pp.356–62.
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Appendices
Appendix 1: Hypotheses of the study
- H0: There is no significant difference in the mean percentage nutritive intake of carbohydrates between subjects who are physically active and subjects who are not physically active.
- HA: There is a significant difference in the mean percentage nutritive intake of carbohydrates between subjects who are physically active and subjects who are not physically active.