UNIT 5 RESEARCH PROJECT

Unit 5 Research Project
Worthing College Sports Science
Noah Peskett
2015

How does smoking affect the
aerobic performance of
performance level college aged
males?
P2: Carry out / P4: Produce

Abstract
AIM: To assess the effects of smoking on the aerobic
performance of performance level college aged males?
METHODS: 4 smokers and 16 non smokers aged between
17 and 18 years playing for Worthing Minors football
team co-operated voluntarily in the study. Aerobic
capacity was determined by Cooper's running
test. RESULTS: The values of VO2max achieved by the
smokers were significantly less than those achieved by
the non-smokers. The subjects who were heavily
dependent on nicotine had lower VO2max values than
those less dependent. CONCLUSION: The inhalation
of tobacco leads to an alteration in aerobic capacity.

Contents: General
Page 3 - Acknowledgements
Page 4 – Introduction
Page 5 – Literature Review
Page 6 – Project Hypothesis
Page 7 – Method
Page 8 – Data Collection
Page 9 – Data Analysis
Page 10- Results
Page 11 – Discussion
Page 12 – Conclusion
Page 13 – Review Part 1
Page 16 – 20 – Future Recommendations

Contents: Appendices
Page 22 – Appendix 1

Contents: Figures and Tables
Page 30 – Figures and Tables 1
Page 31 - Figures and Tables 2
Page 35 – Figures and Tables 6

Acknowledgements
I would like to say thank you to, Steve Ripper
manager of Worthing Minors under 18’s squad for
letting me use part of his training session with the
squad to complete the cooper run test with the
players. I would like to thank the helpers who gave
me a hand with recording the results of the run,
and warming up the players before they started the
cooper run. Also a big thank you to all the players
that took part in the test as without them I
wouldn't be able to do the research project in the
first place.

Introduction
How does smoking affect the aerobic performance of performance level college aged
males?
I chose this aim as I was really interested in actually finding out whether smoking has
an affect on players aerobic capacity in football. Also wanted to show players that they
would be better at the sport they play if they quit smoking or at least cut down. As
they would be able to play at a higher intensity for longer throughout the game.
Another reason is that I want to try and stop people from smoking in the first place as
it is really bad for your general health not just your aerobic capacity. I want to reduce
the number of young people smoking in sport by showing them results in black and
white (not just something they have heard about with no evidence).
What was the project timescale?
My project timescale was 6 weeks. As in this time I needed to find participants to
complete the cooper run test on. Complete smoking and PARQ questionnaires. Then
the process of analysing the data had to be done, by working out the results of 20
different players V02Max’s from their cooper run test results. Putting them into graphs
and taking the information from the smoking questionnaires to see if there is a
correlation between poor V02MAX results and smoking.

Literature Review and References
https://worthingsportscience.wordpress.com/20
15/03/03/unit-5-literacy-review-noah-peskett/

Project Hypothesis
The hypothesis for my project is, smoking will
decrease the V02 Max score of a college aged
performance level football player.
Secondly: The amount of cigarettes smoked by
the player will affect the amount of distance
they can cover in the cooper run test.

Method
Before the Cooper run could be started I had to give out PARQ questionnaire's to the participants to
complete before running. See appendix 2 for the completed PARQ sheets. The cooper run test will be
completed by 20 performance level college aged footballers. Myself and the three different helpers had
a group of 5 each. We were going to spread the 4 groups over the length of the pitch starting at bottom
of the pitch next to the goal on the line. So they all had space to run and so each helper and myself
could keep track of how far each player had run. The pitch at the Glen Owen centre where we were
doing the run is 100 metres long so the players are going to run up and down the pitch for 12 minutes
to get their results. Then are cones laid out on the touch line for every 25 metres of the pitch so at the
end the helpers can calculate the exact amount of metres they have run. Before the players start the
cooper run each helper is going to do a warm up with the players so that they are all ready to take part
in the run. The warm up will be for 5 minutes and then they will do the run for 12 minutes. So the
whole thing only took up about 20 minutes of a training session as I had to collect the results off all the
helpers at the end. To view a diagram of my method see appendix 1.
After the Cooper run had been done I gave each of the players a smoking questionnaire for them to
complete as I needed to find out who smoked out of the group of players and how much they smoked.
See appendix 3 for the smoking questionnaire of the players who smoke.
P3: Collect and record / M2: Correctly analyse & describe techniques / D1: Correctly analyse & explain techniques

Data Collection
I am collecting my quantitative data in the main test which is the
cooper run by writing down the scores the participants in the run get,
then put it into a table which will have the names of the 20 different
participants on, and then the next column will have the score they get.
The score will be the amount of distance they cover after 12 minutes
of constant running. So someone may score 2500m in the 12 minutes
for example. The qualitative data I collect will be on the questionnaire
I give all the players asking them if they have any smoking habits and if
so how much they smoke. Also the PARQ I give each participant will
also be qualitative research as its asking about medical conditions and
health and safety precautions. See appendix 2 for Parq questionnaire's.
This would all be primary data I am collecting, as I am testing the
participants myself with the assistants of a few helpers so therefore I
am not using anyone else's results. See appendix

Data Analysis
The data I collected from the 12 minute cooper run shows a significant difference between the amount
of distance covered over 12 minutes and whether a player smokes or not. The four smokers in the 20
man sample where the ones who covered the least distance, and using the normative data provided on
the Brian Mac website I could see that all four smokers fell into the Poor section of the table. See
Figures and Graphs 5 for normative data table. Once I got the distance covered I used the Brian Mac
website V02 max calculator to convert the metres run into a V02 Max score. See appendix 4 for a link to
the Brian Mac V02 Max calculator. Once I had these scores I wanted to find out the average V02 max
scores for the smokers and non smokers. For this I put the data into Excel and worked out the Mean,
max, min, range ,mode and median for the 16 non smokers and the 4 smokers. See figures and tables 3
for the average V02 Max score Excel sheet. This gave me a clear idea of the overall score for a smoker
and non smoker. I again used Excel to put the data into Spearman Rank Order so I could try and find a
correlation between the two variables distance ran and the amount of cigarettes smoked. See figures
and tables 4 for the Spearman Rank Order Excel sheet.
I chose to analyse V02 max as it gives the most accurate idea of how good someone's aerobic capacity
is, as this is the variable that would be affected by the smoking. I chose the Spearman Rank
Correlation as this was an easy was to present my data to show how well the two variables correlated
, unfortunately my data came out as very weak, but this is because my sample size was very small and
didn’t have enough smokers in my sample. Although it did tell me other things like differences
between the different ranks. I also found out other averages like mean, median and mode to get
averages for the smokers and non smokers so that I could get an overall score as this then makes it
easier to see that the smokers had a worse V02 max than the non smokers.

Results
The results I found from the cooper run test I made the 20 participants do
shows that smoking might affect V02 max scores as the 4 smokers scored the
worse in the 12 minute cooper run. Although there were less smokers in the
sample than non smokers and I didn't take into account that the smokers may
not train as much as some of the non smoking players. Although the
difference in V02 max scores was very dramatic between the non smokers
and smokers. Using the Excel sheet on figures and tables 3, you can see that
there is a 9.19 difference in the mean average V02 max scores which for V02
Max is a very significant amount. See figures and tables 6 for Male V02 max
score rating table. Using that table you can see that 9.19 is the difference
between having a poor and excellent V02 max rating.
Using the results for trying to find a correlation in distance ran in the cooper
run and of cigarettes smoked is very hard as the sample size I had wasn't very
big and I didn't really have enough smokers to find any kind of correlation as
the spearman rank order says that there is a very weak correlation between
my two variables. See tables and figures 4 for the Spearman rank order Excel
sheet.

Discussion
I found in my results that the smokers had performed the
worse in the cooper run test and in turn had the worst
V02 max scores. My findings were what I was expecting
as in my previous research every test ended up with the
smokers doing the worst. See page 5 for link to my
previous research. The only trend I found in my data was
that the smokers all had the lowest V02 Max scores and
all the smokers had a V02 max score below 40.0 and all
the non smokers had a V02 max of over 40.0. I didn’t get
any results I wasn’t expecting but I think that it is because
my sample size wasn’t very big.

Conclusion
How does smoking affect the aerobic performance of performance level college aged
males?
The key trends for my literacy review would be that the smokers always have a
disadvantage when it comes to any cardio based exercise, as they always seem to have
worse scores in any tests given. This could be down to a few factors, firstly I believe
that smoking will affect the way in which you are able to perform at a high intensity
for a prolong period of time. Secondly a reason for why someone might smoke in the
first place is stress , stress could cause the smoker to not train as much meaning they
aren't going to be able to perform as well as someone who trains more than them.
My first hypothesis is supported by my results as the V02 max scores of the smokers
are drastically lower than the scores of the non smokers so you can clearly see a
difference in what smoking does to the V02 max of a college aged football smoker.
My second hypothesis was a hard one for me to get results that support it as my
sample size of smokers isn't big enough to find a correlation that will give me a clear
indication that the amount of cigarettes smoked will affect the amount of distance
covered by the smoker in the cooper run test.

Review (1/3)
The first project conclusion met my aim really well and demonstrated
that smoking will affect a footballers aerobic capacity, as my results
from my cooper run showed that the smokers had the lowest V02 max
scores of all the players in a college aged football team. See tables and
figures page 3 for these results.
Secondly my other conclusion didn’t really meet the aim as I couldn’t
state from my results that a certain amount of cigarettes smoked a day
would mean that a player performs 'X’ amount worse than someone
who smokes non. Although what I did find out from my results was
that the more cigarettes you smoke the worse your performance in a
Cooper run test becomes. See figures and tables 4 for the evidence
that the player who smokes the most cigarettes a day (Alex Gowling
who smokes 20) ran the least amount of metres in the Cooper run test.
P5: Describe / M3: Explain / D2: Justify

Review (2/3)
The positives from my research project would be the way in which I
conducted the test, managing a group of 23 people to get my Cooper
run test done as quickly and efficiently without using up too much of
my clubs training session. I was good at giving the players information
on exactly how to do the test, and gave the helpers clear instructions
on how to warm the players up and count the distance of how far each
player has run. It only took us about 20/25 minutes to complete the
test and gather all the information I needed which I would see a very
efficient.
Also the way in which I managed to gather all the questionnaire's I
gave out, both the smoking questionnaire and the PARQ completed by
each player was good.
The way I planned the test was well thought out and planned as I
managed to get all the players to run the Cooper run test at the same
time and all the helpers to gather the information. See appendix 1 for
the plan I made for the Cooper run test.

Review (3/3)
There is many areas I could improve in my research project, the first
major thing I would do is increase the size of my sample so that there
is an equal amount of smokers and non smokers as then I would be
able to find a better correlation between how many cigarettes smoked
and metres run in the Cooper run test. Also the affect of smoking on
V02 max scores would be more accurate with an equal sample size.
Secondly I would make the participants do the Cooper run on a
running track as my Cooper run wasn’t exactly the same as the one on
the Brian Mac website so my results wont be completely accurate. This
is also because the VO2 max calculator was based on the Cooper run
being run in a circle on a running track not back and fourth on a
football pitch. The reason I done the test on a football pitch is because
I didn’t have the provision easily accessible so I thought I would
improvise and get results that weren't as reliable but that is better
than none.

Future Recommendations (1/4)
My first proposal for my future research would be find an even number of smokers
and non-smokers and have at least 10 of each so that I can make more accurate
conclusions on the findings I get. I think that 10 of each is very realistic for me as I
don’t have the capacity to be able to do tests on more than 20 people and using the
facilities I have I wouldn’t be able to do a large scale test.
The recommendation will improve my study as the results I get by having a larger scale
will show a accurate difference between smoking and aerobic capacity. People
benefiting from this recommendation would be people wanting to use the data from
my test, and smokers who play football and this will hopefully want to make them
quit. I would like to be to do this on a bigger scale to see if the results I find would be
the same with a bigger population so for all under 18 teams in the West Sussex for
example. As this would give me a lot harder evidence to say that smoking does affect
the aerobic capacity of a college aged footballer.
I think that this would be slightly unrealistic for me to achieve on my own but if other
people where interested in this, I could team up with them and do the Cooper Run
test on a much bigger scale to get extremely accurate results for an area like West
Sussex or even the whole of Sussex. It would benefit smokers if we did this test on a
larger scale as we could get the results and tell smokers using the evidence that they
are not going to perform as well if they smoke and play football.
P4: Produce / P5: Describe / M3: Explain / D2: Justify

My second proposal for future research would be to do the Cooper run test on a 400m
running track as then they wouldn't have to turn back on themselves every 100m like
they had too in mine. This saves the person doing the test from losing unnecessary
energy having to turn. Also the V02 max calculator was based on them running on a
400m circular running track so for those two reasons it means my data would be much
more accurate if they were adjusted next time.
The recommendation would improve my study as there the results I get will be a lot
more accurate and fair. This recommendation would benefit people who smoke as if
the test results are accurate they will see that smoking affects your aerobic capacity
and it will make you perform a lot worse than if you weren't to smoke.
Linking to my literature review, Tchissambou, et al. (2004) done a similar test to mine
using the Cooper run test and they done it round a 400m running track and with a
sample of 126 smokers, therefore they got much more reliable data which is why I
would change this also in my own test. The data they found in there test where that
the values of VO2max achieved by the smokers were significantly less than those
achieved by the non-smokers. Which was exactly what I found in my test.

My third recommendation would be to do other tests for V02 max
other than just the Cooper run test as the person as taking part in the
test may not be motivated to run in a circle for 12 minutes. So I would
do 3 other tests which I have selected from the Brianmac website and
then take each participants highest score on each test as their overall
V02 max score. The 3 other tests I would use are the VO2 max step
text, the 2000m Row test and the treadmill V02 max test.
As the results of the tests would be maximal you would take the best
V02 max score as this is the most accurate way to get their V02 max
score.
I wouldn’t change the measure of V02 max as it is the best measure for
smoking as it is proven to be affected by smoking.
So therefore the other tests make it fairer for people who get bored
just running in a circle and didn’t really compete in the test to their
best.

The final recommendation I would like to make is that I would have
liked to go into more detail about how much players smoke and if this
has more of an affect on their aerobic performance.
I from the 4 smokers I had doing my test it did show that the more the
player smoked the worse their V02 Max was, therefore I would say
that a future recommendation would be to get a bigger sample of
smoker so 10 for example and get them all to do the Cooper run test
and see if the amount they smoke affects their V02 max score. As I
done it with only 4 people and that isn’t very fair or accurate.
This recommendation would improve my study as it I would be able to
tell the players if they cut down to just 5 a day from 20 a day for
example they would increase their V02 max scores by ‘x’ amount. This
would benefit the players as they wouldn't be more inclined to cut
down on their smoking habits which will have a roll on affect on the
NHS who will have less strain of people getting smoking related
diseases.

Appendix 4
http://www.brianmac.co.uk/gentest.htm

Research Project Figures
and Tables

Figures and Tables 1
Player Name Distance Ran in Metres
George Peskett 2525
Aidan Gravett 2150
Ben Sheppard 2825
Kyle Ashworth 2700
Zac Ripper 2350
Alex Hollis 2100
Martin Felton 2325
Miles Bennett 2450
Daniel Fadaju 2800
Joe Hazeldine 2500
Alex Growling 2025
Ryan Durrant 2400
James Curtis 2750
Brandon Osborne 2525
Oliver Hartfield 2450
Adam Lelliot 2675
Ryan Constable 2750
Harry Finch 2250
Josh Amos 2450
Tom Armstrong 2550
Cooper Run Test Results

Player Name V02 Max Score
George Peskett 45.16
Aidan Gravett 36.78
Ben Sheppard 51.87
Kyle Ashworth 49.07
Zac Ripper 41.25
Alex Hollis 35.66
Martin Felton 40.69
Miles Bennett 43.49
Daniel Fadoju 51.31
Joe Hazeldine 44.60
Alex Gowling 33.98
Ryan Durrant 42.37
James Curtis 50.19
Brandon Osborne 45.16
Oliver Hartfield 43.49
Adam Lelliot 48.52
Ryan Constable 48.52
Harry Finch 39.01
Josh Amos 43.49
Tom Armstrong 45.72
VO2 Max Scores

Average V02 Max Results for Smokers and non Smokers

Spearman Rank Order for all participants

Age Excellent Above Average Average Below Average Poor
13-14 >2700m 2400-2700m 2200-2399m 2100-2199m <2100m
15-16 >2800m 2500-2800m 2300-2499m 2200-2299m <2200m
17-19 >3000m 2700-3000m 2500-2699m 2300-2499m <2300m
20-29 >2800m 2400-2800m 2200-2399m 1600-2199m <1600m
30-39 >2700m 2300-2700m 1900-2299m 1500-1999m <1500m
40-49 >2500m 2100-2500m 1700-2099m 1400-1699m <1400m
>50 >2400m 2000-2400m 1600-1999m 1300-1599m <1300m
Normative Data for Cooper run: Males

Male V02 Max score rating table
Age Very Poor Poor Fair Good Excellent Superior
13-19 <25 25 - 30 31 - 34 35 - 38 39 - 41 >41
20-29 <24 24 - 28 29 - 32 33 - 36 37 - 41 >41
30-39 <23 23 - 27 28 - 31 32 - 36 37 - 40 >40
40-49 <21 21 - 24 25 - 28 29 - 32 33 - 36 >36
50-59 <20 20 - 22 23 - 26 27 - 31 32 - 35 >35
60+ <17 17 - 19 20 - 24 25 - 29 30 - 31 >31

UNIT 5 RESEARCH PROJECT

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