Human Energy Metabolism: Lab Report

* Most of the original graphs have not been carried over *

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Lab Report


On the role of gender in human energy metabolism and the credulity of individually calculated data.
In this report we have taken spirometer measurements as well as both an activity and food diary from a number of Biology students and aim to apply the energy equation (Energy intake = work done + heat produced + energy stored) to the resulting data in order to ascertain gender differences between students when considered against expected outcomes. These measurements were gathered by individual students, as such this report will also consider the accuracy of this data, and the likelihood that fallacious or implausible data was recorded.

The measurements collected should be suitable for assessing differences between genders in the sample group, specifically any which may affect health, the waist to hip ratio for example has been shown by numerous studies to be a significant factor in predicting numerous malady’s (Wellborn TA, 2003). In a broader sense this report can aim to make inferences about the efficacy of data collection techniques when gathering information on diet, activity and other relevant figures where information is recorded/calculated by the individual, not a trained researcher.

Markers Comments
During a lab session, students took measurements for height, weight, percentage body fat (measured using laboratory scales) and the diameter of their waist and hips (using measuring tape). A spirometer was used to measure oxygen consumption during a five minute period. Students recorded these measurements with the assistance of experienced lab personnel. Food and exercise diary’s for two consecutive 24 hour periods were recorded prior to the lab (listing activities undertaken with an activity factor and a time of day as well as a list of all foods consumed and their corresponding amounts in grams and energy content in kcal/100g).

Using these measurements in conjunction with the spirometer test and food/exercise diary’s, they then calculated the following data points: height (metres), age (years), percentage body fat, weight (kilograms), BMI, energy intake per 24 hours (Kcal/day) and resting energy expenditure per 24 hours (Kcal/day). These values were then entered anonymously into a database to be recorded. Other data points were recorded however only those which were entered into this database will be discussed here.

Calculations were required to ascertain the values of BMI, energy intake per 24 hours and energy expenditure per 24 hours.

  • BMI was calculated by dividing weight (kg) by height (metres) squared.
  • Energy intake per 24 hours (Kcal/day) was calculated by taking the total energy intake from one 24 hour period (itself found by addition of the energy content of each meal taken in one day) then dividing this figure by body weight (kg).
  • Energy expenditure per 24 hours (Kcal/day) was calculated by first attaining the Resting energy expenditure (REE) by taking the spirometer measurement and dividing it by the number of minutes the test was run for, then multiplying this figure by 4.8, then 60 and finally 24 to find the REE. To find the total energy expenditure, multiply the REE by the average daily activity factor for that day (derived from the activity diary), then divide this figure by weight (kg).


Markers Comments
Using the data from lab #924 pm session (group 3), there were 18 females and 17 males, a comparable amount. It is reasonable to assume that whr and & % body fat values will be conveyed truthfully due to the anonymity of data entry and previous study’s which have confirmed that such results are generally reported truthfully (E B Rimm et al, 1990), and as such we will assume that no individual has knowingly obfuscated data.Figure 1

From figure 1 it can be observed that men generally have a lower % body fat than women, with a variance of around 10 percentage points. This is in keeping with the general scientific consensus that women retain a higher body fat percentage than men for reproductive reasons (

Avg Age Fem Avg Age Male
18.6 19
Avg BMI Fem Avg BMI Male
22.24 23.17
Avg % fat Fem Avg % fat Male
23.44 14.64
Avg whr Fem Avg whr Male
0.81 1.31

Table 1

From Table 1 we can observe that the average female body fat % is higher than its male counterpart, while the average female whr is relatively close to the healthy 0.7 range, the male whr is a good deal higher than the optimal 0.9 – 1.0 range (Singh D, 2002).

BMI is a useful indicator of general health, and the scatterplot (Figure 2) comparing male and female BMI values would seem to indicate that both men and women in the sample place fairly consistently in the desirable 20-25 range with no significant difference between gender.

Figure 2

The final measurements to be considered are energy intake and energy output, which are compared using line diagrams, stratified by gender, to allow one to be compared against the other for each individual subject in the sample (Figure 3 & 4).

Figure 3

Figure 4

It is notable that in both Figures 3 & 4 the energy output is almost always greater than the energy input variable (in many cases by several thousand kcal/day). As such similar line graphs were produced which pooled a greater number of subjects from groups 1, 2 and 4. The greater pool of data should allow for a more accurate, robust result while the exclusion of group 3 should ensure that any anomaly’s endemic to this group are removed.

The resulting graphs (Figures 5 & 6) display the same trend pertaining to the energy input and energy output variables as the previous graphs.

Figure 5

Figure 6


Markers Comments
Discussion / Conclusion
The energy equation (Energy intake = work done + heat produced + energy stored) usually balances the exercise performed and heat generated metabolically for homeostasis to allow for a net gain of energy to be stored in the body. When, for whatever reason (extreme temperature conditions, lack of suitable nutrition, excessive exertion or some combination of these factors) there is a net loss of energy the organism in question finds itself unable to survive under such conditions for any significant period of time.

The aim of this report was to use the data gathered and calculated by Biology students to identify any significant variances in health (pertaining to diet, exercise and physical characteristics) between males and females, while assessing the accuracy of data gathered by individuals. We found in the results that a number of data variables were close to their expected outcomes, for example BMI values for the students were very close to healthy levels with predictable variation between subjects. The % body fat was also very close to what would have been expected, with women having a higher body fat than men as reproductive and evolutionary imperatives would dictate.

However, graphs comparing energy input with energy expenditure for individual subjects clearly demonstrated that the majority of individuals recorded an expenditure which vastly exceeded the intake. While this in itself is not necessarily impossible, it is highly unlikely that so many students would exhibit this energy dearth (even if many were to be considered to be anomalies) and in numerous cases these values were almost certainly preposterous (many far exceeded the energy intake by 3000-6000 kcal/day).

We can infer from the results that the data for whr, BMI and % body fat was fairly probable while the data for energy intake/output was highly improbable. The most likely reason for the more sensible results is that whr and % body fat are acquired through direct measurement using accurate, specialized apparatus while the subject is under expert supervision. BMI is acquired using a relatively simple calculation involving height and weight (calculated, again, with apparatus).

The energy equations were, relatively, much more complex in nature and used data with much more potential for error. For example, it is difficult to quantify the weight and nutritional value of numerous meals, while it is similarly difficult to quantify the intensity and duration of exercise.

Overall, this report has to some extent investigated gender differences pertaining to human diet and metabolism (with exception to the energy intake/output variables which were inadmissible), finding that the subjects were mainly comparable with the wider population. The report also produced data to suggest that individuals gathering and calculating their own data values for activity/food diary’s may be likely to produce unsatisfactory data. As such, even among undergraduate biology students, these diary’s appear to be overly complicated, making them unfit for purpose and unlikely to be useful among the general population.


Markers Comments
T A Welborn, S Dhaliwal and S A Bennett (2003), Waist–hip ratio is the dominant risk factor predicting

cardiovascular death in Australia [online], available from:

[accessed 08 November 2010]

Rimm E B et al (1990), Validity of Self-Reported Waist and Hip Circumferences in Men and Women, Epidemiology, Vol 1 issue 6,

pp 466 -473, Body Composition – Body Fat – Body Weight [online], available from:  [accessed 15 November 2010]

Singh D (2002), Female Mate Value at a Glance: Relationship of Waist-to-Hip Ratio to Health Fecundity and Attractiveness, Neuroendocrinology Letters Special Issue, Vol 23





  1. hey there! do you know what mark you got for this report?

    1. Yes, I got a B2. There were a lot of scatterplots included in the actual report as well.

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