FMHS Summer Studentships 2013-2014
Final Project Report
Project Details
Student Name:
Aditya Sheth
Name of supervisor(s):
Professor Innes Asher
Supervisor department:
Project title:
Project category:
Studentship sponsor:
Supervisor letter included:
Paediatrics: Child and Youth Health
The Distribution of Fast Food Outlets in Relation to the
Prevalence and Severity of Asthma
Biomedical ☐ Clinical ☐ Public Health ☒
The Asthma Foundation
Yes ☒
No ☐
Supervisor to please indicate if your report is to be nominated for a Wallath prize:
Wallath prize nominated:
Yes ☒
No ☐
Please complete the report template and return along with a letter from your supervisor to:
healthresearch@auckland.ac.nz
Deadline for submission is Friday 28th February 2014
Please direct any queries to Liz Turle-Smith, FMHS Research Facilitator (e.turle-smith@auckland.ac.nz)
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Brief statement on how the studentship has contributed to your career development
(1 page limit):
My summer studentship has provided me with the opportunity to work with International Study of Asthma and Allergies in
Childhood (ISAAC) team at the Paediatrics Department of the University of Auckland. I received an excellent insight into the
world of medical research, as well as an introduction into the dynamic and complex nature of child health and the multitude of
factors which affect it. With the support and guidance of my supervisor and her research team, this project has been hugely
beneficial to my career development and learning.
My project required me to think about the impact of environmental factors such as diet on health on both an individual level,
such as researching the physiological responses to components of fast food and why they may be related to asthma,
rhinoconjunctivitis and eczema, and on a much larger scale; regional fast food outlet distribution and its effect on area-based
prevalence and severity. I used the knowledge gained from the literature review in various decision-making ways for my
ecological study, such as deciding which fast foods contained factors that may be relevant to the diseases of interest and how
the various fast food outlets differ in this sense. This contrast of micro- and macro-level investigation has given me the valuable
context of public health as a frame to base my clinical training on as a fourth year medical student. The project has
demonstrated to me how upstream determinants health issues have a hugely significant impact on the population, which is
something I would not necessarily gain exposure to in a clinical setting, which mostly deals with patients on an individual level.
A solid understanding of public health is hugely important in a career as a medical professional, and this project has given me a
wider perspective and context for my future work.
To begin my project I conducted a literature review on articles relating to diet and asthma, rhinoconjunctivitis and eczema. This
helped me develop my basic research skills such as systematic searching of databases and filtering of articles, as well as skills
relating to the assessment and extraction of relevant information and scientific report writing. Over the course of the project
itself I was required to carry out ecological data collection, analysis of environmental variables using Geographical Information
System (GIS) software, and various statistical analyses, most of which I learnt over the course of the project with the help of my
team. I intend to continue research over the course of my career, and I believe these skills have formed a solid and invaluable
foundation for this.
As my project is the first of its kind, it also required me to develop and test a new study protocol to collect data on fast food
outlet distribution internationally and investigate the relationship with the prevalence and severity of asthma and allergies.
Although I carried out the protocol as a pilot study, the results have indicated that a large scale study be undertaken using my
developed protocol, which I plan to have published as a scientific article.
As a result of my summer studentship I was invited to attend and present my project at the School of Medicine Research
Committee’s Summer Student presentation forum. This was an excellent opportunity to grown my presentation skills and gain
experience which will be useful for future presentations I aspire to give, both for this project and for continued research
throughout my medical career. Through this forum I was also able to learn about the various other interesting and innovative
research projects undertaken by students at the University of Auckland, which widened my outlook on the field research and
gave me an insight into the numerous research areas our University contributes to.
This process has been challenging, intellectually stimulating and taught me a wide range of research and analytical skills that I
know will be useful to me both as a clinician and for my future research.
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Research abstract – not more than 250 words:
Research Question
Is there a relationship between the distribution of fast food outlets and the prevalence of asthma, rhinoconjunctivitis and
eczema (ARE), and how can data relevant to this be efficiently and practically obtained?
Method
Prevalence and severity data on ARE from ISAAC Phase Three was used in this pilot study.
Fast food restaurant location data was obtained for New Zealand, Italy, USA, Spain, Brazil, China, Portugal and the UK. There
were 70 ISAAC centres in these countries. Restaurant location data and ISAAC centre areas were overlaid using the ArcMap
software, and the number of restaurants within each ISAAC centre was obtained. Bivariate regression analysis was used to
compare outlet density with ARE prevalence and severity.
Results
The results from the analyses showed a positive trend on a regression plot between outlet density and ARE severity, however
the results were not statistically significant, possibly type II error due to the small scale of the pilot study.
Implications
The project has shown that it is practical to systematically obtain and map fast food outlets and compare their distribution
worldwide with the prevalence and severity of diseases, in this case asthma, rhinoconjunctivitis and eczema. The devised
methodology has proven to be an efficient way to obtain and map large amounts of restaurant distribution data in a form that is
manageable and suitable for additional analysis such as comparing with area based disease prevalence. The project has proven
to be successful in demonstrating that a larger scale investigation is both feasible and warranted.
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Summary of research and its significance (1 page limit):
The aim of my project was to determine whether a correlation exists between the number of fast food restaurants and the
prevalence and severity of asthma, rhinoconjunctivitis and eczema (ARE) in 13 -14 year old children in selected centres from the
International Study of Asthma and Allergies in Childhood (ISAAC) programme. My project began with a literature review to
determine whether a scientific reason for this correlation may exist on a physiological level, and whether a similar correlation
had previously been observed. My literature review found a number of possible explanations as to why a higher intake of fast
food may cause an increase in prevalence and severity of these diseases, with factors such as saturated fats, trans fats, salt and
sugar identified as being possible contributors to inflammation of the airway and hypersensitivity to certain allergens. I then
used the literature review as a foundation for the decision making and planning of my own project.
ISAAC Phase Three collected data from 233 centres from 97 countries around the world on the prevalence and severity of ARE.
At the beginning of 2013, my supervisors published a study that showed a significant correlation between consumption of fast
foods and the severity of these diseases, using individual data from school based survey’s in these centres (1).
My project has aimed to further the investigation on this relationship by devising the methodology and conducting a pilot trial
for a future large international ecological study. The distribution of McDonald’s and Burger King, outlets were used as a
surrogate measure of fast food consumption, and were compared to the average prevalence and severity of ARE in 13-14 year
old adolescents in selected ISAAC centres. This is a new research approach, and was a novel way of investigating possible
relationships.
The project involved the use of a geographical analysis software called ArcGIS. The ISAAC team had previously mapped the
geographical boundaries of the ISAAC centres around the world using this software. I collected fast food outlet addresses across
8 countries using address data cross referenced from various sources including the restaurants’ websites, the Yellow Pages (or
each country’s equivalent) and GPS point of interest data. These addresses were converted to coordinates through a process
called geocoding. I then fed them into ArcGIS and overlaid them with the centres. The software analysed the number of fast
food restaurants within the geographical region of each centre. Restaurant data for 70 centres across 8 countries was collected
for this pilot study. As McDonald’s and Burger King were the two restaurants which were present across all 8 countries, the
study was restricted to include just these two restaurants. Using appropriate bivariate regression analysis, the number of
restaurants per 1000 13-14 year olds was compared to the prevalence and severity of asthma in 13-14 year olds for each region,
and similar regression analysis was conducted for eczema and rhinoconjunctivitis.
The results from the analyses showed a positive trend on a regression plot, particularly for severe asthma and eczema, however
the results were not statistically significant. This may be a type II error due to the relatively small scale of the study, which can
be expected as this has been a pilot study to address the validity of the methodology and that it is a practical way to collect and
analyse data for these variables. The use of address collection and online geocoding, before overlaying the ISAAC Centres in
ArcGIS, proved to be an efficient way to obtain and map large amounts restaurant distribution data in a form that is manageable
and suitable for additional analysis such as comparisons with area based disease prevalence. Thus this project was successful in
warranting a larger scale investigation which I hope to carry out over the course of the year.
With the increasing amount of fast food consumed in New Zealand, the significance of understanding the health implications of this
increase in consumption is becoming increasingly critical. The methodology devised from this pilot study may be extremely valuable
for determining relationships between diet and other diseases, and is not necessarily restricted to three diseases investigated in this
project. Information from future studies using this methodology may be highly relevant to the health sector in terms of highlighting
the need for a healthy diet, and providing reasons to cut down fast food consumption. By comparing effects between prevalence
and severity it is also possible to determine whether environmental factors have an influence which could worsen the severity of
pre-existing disease.
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Research report - Aims, methods, results & discussion (5 page limit):
Introduction
Asthma, rhinoconjunctivitis and eczema (ARE) are a complex set of diseases whose exact causal mechanisms are yet to be
uncovered. They are known to be multifactorial, with both a combination of genetic and environmental factors playing a part (13). Over the past 20 years the prevalence of these diseases has increased in many areas around the world , including New
Zealand, which has one of the highest rates of asthma in the world (4). The recent increase in these diseases over the last two
decades indicates that changes in environmental factors are likely to play a key role, perhaps more so than genetics. This is
further supported by the vast variation in prevalence of the diseases between and within countries, suggesting that potentially
avoidable causes may be present. Among these environmental factors, recent research has suggested that diet may be
important in the development and severity of ARE, with certain foods such as fruit and vegetables playing a protective role while
others such as fast food acting as risk and/or exacerbating factors (1-3, 5-20). The consumption of fast food is on the rise globally
(1), and the significance of understanding the health implications of this increase in consumption is becoming increasingly
critical for many chronic conditions. This study aims to determine whether there is a correlation between fast food
consumption and prevalence and severity of ARE in 6-7 year old children and 13-14 year old adolescents, using distribution and
density of fast food restaurants per selected ISAAC centre as a surrogate measure for fast food consumption.
Background
Previous Epidemiological Studies and their Limitations
It is not entirely clear from the current literature whether there is a direct causal link between the increased consumption of
these foods and asthma, due to the cross sectional nature of the majority of studies conducted so far, which doesn’t provide
insight into the temporal relation between fast food and ARE (i.e. are diets high in fast food causing ARE or are children with ARE
more likely to consume fast food). It is also not clear whether it is the fast food itself to blame or the subsequent decrease in
hypothesized protective factors such as fibre and antioxidants (selenium, vitamin C, D and E) in the diets of those who consume
high levels of fast food (1, 2, 6).
No large scale study using multiple fast food chains has been conducted comparing the distribution of fast food outlets and ARE
prevalence. As previous study using ISAAC data was conducted using McDonalds restaurants per 100,000 population in each
country, as a surrogate measure for diet, and compared this to the prevalence of current wheeze in 13-14 year old children, and
found a significant correlation after accounting for GNP as a confounder (19). As is the case with our study, this correlation may
also in part be a result of lifestyle, other environmental cofactors, culture, or economy. This is the case even more so in our
study where the information is localised to regions rather than countries. Another used ISAAC data and food frequency
questionnaires and found that frequent consumption of hamburgers showed a dose-dependent association with asthma
symptoms, and frequent takeaway consumption showed a similar association with bronchial hyper-responsiveness (15).
A major epidemiological study investigating fast food and ARE was conducted using ISAAC Phase Three 3 data and found that an
increased risk of ARE in adolescents and children was correlated with high consumption of fast food (>3 times per week). The
study was adjusted for a number of covariates such as region, gender, language, GNI, exercise, television viewing, maternal
education and current maternal smoking. BMI was omitted as a confounder as a large number of centres didn’t have BMI data
and no difference was found after running an analysis with the smaller number of centres that had BMI data. (6). Although the
study showed promising results that a correlation between fast food and ARE (particularly severe asthma) exists, a lot of work is
required to establish a causal relationship; our proposed study will be a step in this direction.
A Brazilian study also using ISAAC Phase Three data used the slightly different approach of grouping participants into two main
dietary patterns, ‘Western’ and ‘Prudent’, the Western diet having lower intake of antioxidants and higher intake of trans fats.
The Western dietary pattern was significantly associated with wheeze after adjustment for energy intake and other confounders
adjustments (7).
Physiological Plausibility
Fast foods lack many of the nutrients found in fruits and vegetables and are high in omega-6 PUFAs (trans-fats), sodium, and
added sugars (5). Hypotheses regarding the effect of the diet on asthma relate to both antioxidants and immunomodulatory
mechanisms (2, 7, 10). The complex aetiology of allergic disease has led to a variety of theories regarding the impact of diet on
ARE, many of which are relevant to this investigation on fast food consumption. Links between consumption of fast food, or high
intake of dietary components commonly found in fast food (such as trans-fats, saturated fat, sugar and salt) and symptoms of
ARE have been shown by a number of studies, outlined in further detail below.
Fat consumption
It has been shown that consumption of a fatty meal causes the activation of the innate immune system, resulting in an increased
inflammatory state, both systemically and in the airway, in otherwise healthy volunteers (21). This may lead to an increased risk
of developing asthma, due to alterations in eicosanoid synthesis, including leukotrienes and prostaglandins. Dietary fat intake
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affects cell membrane composition, which can induce changes in gene expression. In addition, fatty acids can activate innate
immune receptors such as toll-like receptors, leading to the altered activity of transcription factors which play a key role in
regulating immune response, such as NF-κB. Fat intake has also been shown to be positively associated (and fibre intake
negatively associated with) the percentage of eosinophils (the white blood cell primarily concerned with allergic response) in the
airway, while saturated fat intake has been positively associated with percentage of eosinophils in the sputum (8).
Plasma triglyceride levels have been reported to be elevated in subjects with adult onset wheeze, trans polyunsaturated fatty
acids have been associated with increased asthma prevalence, and margarine intake, a source of trans fats, has been related to
increased asthma risk (8, 21).
Salt consumption
Sodium intake has been shown to be correlated to airway responsiveness, possibly through increased sodium causing
hyperpolarization of bronchial smooth muscle, leading to asthma symptom exacerbation (8, 21). Contrary evidence suggests
that a low sodium diet has no therapeutic benefit for bronchial reactivity in adults with asthma (22). In addition,
another study demonstrated that airway responsiveness and urinary sodium excretion, a direct indicator of dietary sodium
intake, had no relationship (23). However, consumption of salty snacks in a 2011 study was associated with a 4.8-times higher
likelihood of having asthma symptoms, irrespective of potential confounders (11). Therefore the relationship between sodium
and ARE is not as clear, and it may be that while a low sodium diet may not have additional benefits to lung function and
bronchial reactivity, a higher sodium intake has the potential negative effect of exacerbating asthma symptoms.
Sugar consumption
Asthma has also been attributed to high sugar intake, particularly in children. Hypothesised mechanisms for this include
interactions between molecular and cellular components of the pulmonary innate immune system such as the carbohydrate
recognition molecule surfactant protein-D (SP-D) and dendritic cells which may regulate susceptibility to airway inflammatory
diseases such as asthma. A high sucrose diet impairs the immunoprotective action of SP-D and increases susceptibility to airway
inflammation. A Swiss study using mice to investigate the effect of sugar on the airways showed that mice fed sugar water
developed hyper-responsive airways. The mice with airway inflammation were shown to be twice as susceptible to asthma. A
sugar rich diet may contribute to priming the innate immune system of the airways to allergic inflammation, similarly to how
saturated and trans-fats are believed to (24).
A 2011 study using ISAAC asthma data and sugar consumption data extracted from United Nations Food and Agriculture
(UNFAO) food balance sheets found a moderate association (P = 0.012) between per capita sugar consumption during the
perinatal period and subsequent prevalence of severe childhood asthma symptoms. This study demonstrated an ecological
association between perinatal sugar consumption and subsequent risk of severe asthma symptoms in six and seven year-olds
(25).
Protective dietary factors
A number of studies have shown the protective effects of certain nutrients, many through the use of the ‘Mediterranean diet’,
which refers to dietary patterns found in olive-growing areas of the Mediterranean region, which is low in saturated fatty acids;
rich in carbohydrates, fibre, and antioxidants; and has a high content of monounsaturated fatty acids and n-3 polyunsaturated
fatty acids (PUFA), which are primarily derived from olive oil, and in some regions from fish (1, 2, 5-7, 11, 26).
Some epidemiological studies reported a protective effect of adherence to Mediterranean diet on asthma in
children/adolescents (6, 11, 26); a major meta-analysis of studies investigating the effect of Mediterranean diet on asthma
symptoms in children found a significant protective effect (6). Studies which examined both fast foods and fruits and vegetables
in conjugation found a higher negative effect from the fast foods than a positive effect of diets high in fruit and vegetables (1),
however studies such as these may be subject to interplay between the two overlapping dietary patterns.
Methods
ISAAC Data
ISAAC is a multicentre, multi-country, multiphase cross-sectional study, which effectively ‘mapped’ the prevalence of asthma,
rhinoconjunctivitis and eczema in 237 centres across 98 countries, and involved 1,187,496 children and adolescents. ISAAC
Phase Three involved 13–14-year-old adolescents and 6–7-year-old children chosen from a random sample of schools in defined
geographical areas. Phase Three used standardised core written questionnaires as well as an optional environmental
questionnaire, which asked questions about diet, height, weight, heating and cooking fuels, exercise, pets, family size and birth
order, socioeconomic status, immigration and tobacco smoke exposure. A video with scenes of young people with clinical
symptoms and signs of asthma was shown to the adolescent group and written questionnaires on the symptom prevalence of
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asthma, rhinoconjunctivitis and eczema were completed by the 13–14-year-old adolescents and by the parents/guardians of 6–
7-year-old children.
For this study, 8 countries were used to obtain information on fast food outlets and data on ARE from 70 ISAAC centres from
these 8 countries was used.
Fast Food Restaurant Data
The following points are the detailed methods developed for this project for mapping the fast food outlets and
ISAAC centres, written as instructions.
1.
Open ArcMap (ver 10.2). To create a basemap download the map file from http://www.naturalearthdata.com >
downloads> Large scale data, 1:10m > Cultural > download countries. Extract entire contents of downloaded zip file
into a separate folder.
2. In ArcMap, click File > Add Data and locate and click on the .shp file previously extracted from the zip file. This will
present as a world map within the ArcMap software.
3. Obtain a list of the addresses of all restaurants of a particular chain in the country using the yellow pages website
(http://yellow.co.nz/)
4. Copy and paste the restaurant address information onto a word document and reformat the information to include just
the addresses, one line per address
i.e.:
[address 1]
[address 2]
[address 3] etc.
Ensure all addresses are coded using a street number and street name, suburb name and city, as opposed to for
example the name of a mall, cross roads, name of motorway etc. To verify street addresses of restaurants which aren’t
already coded in the correct format, use either the restaurant website or google maps to obtain the street number and
name.
5. Go to http://batchgeo.com/ and copy and paste the address data from the word document into the area as shown on
home page of the website
6. Use the “Map Now” function and allow the addresses to be geocoded into a map. Any addresses that could not be
found will be listed. These are likely not in the correct format and need to be adjusted in the spreadsheet above. As
batchgeo.com uses a google maps API, as long as the address can be found using google maps, batchgeo.com should
also be able to find it.
7. Save and Continue once all address have been located. On the following page a map with all restaurants plotted will be
shown. Scroll down and the option to download a KML version of the map will be available. Download the KML file and
save it to a known location.
8. From ArcMap, go to Geoprocessing > Arc Toolbox > Conversion Tools > From KML > KML to Layer. Choose the
downloaded KML file with the restaurant address data as your input KML file, choose desired output location and data
name. This will import the restaurant locations into ArcMap.
9. Repeat steps 2-8 for each desired restaurant chain, and for each country. The included countries for this study are New
Zealand, Spain, USA, Italy, Brazil, China, Portugal and the United Kingdom.
10. Import the .shp file for ISAAC centres into ArcMap. This will allow the restaurant location data and ISAAC centre areas
to be overlayed, and the number of restaurants within each ISAAC center can be generated onto a spreadsheet.
11. Export the spreadsheet and using the COUNTIF function on excel the number of outlets in each centre can be obtained.
12. For each geographic centre divide the number of total outlets by the total population of 13-14 year olds x 1000 to
obtain number of outlets per 1000 children (outlet density).
Data Analysis
Multiple linear regressions were performed to compare fast food outlet density to % current asthma, % severe asthma, %
current rhinoconjunctivitis (symptoms), % severe rhinoconjunctivitis, % current eczema (symptoms), % severe eczema.
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Results
As McDonald’s and Burger King were the only two fast food restaurants which were common across all 8 countries that were
surveyed, the study was restricted to use of only these two restaurants in the analysis. A number of centres were excluded from
the analysis due to inaccurate population values either due to a reporting error or not all schools in the area being included in
the sampling frame.
The ‘Current’ category for each of the three diseases included all 13-14 year olds who exhibited symptoms in the past 12 months
of that particular disease. The ‘Severe’ category for asthma used the percentage of children with wheeze in the past 12 months
who also exhibited severe symptoms such as sleep disturbance, wheeze affecting speech, 4 or more acute attacks, exercise
wheeze and night cough. ‘Severe’ rhinoconjunctivitis was a combination of current nose symptoms, current nose symptoms and
itchy-watery eyes and the answer “A lot” to having this nose problem interfere with daily activities. ‘Severe’ eczema used a
combination of those with current symptoms and those with sleep disturbance 1 or more nights per week.
All linear regressions showed a positive trend except for % Current Wheeze, which showed a negative trend. The most
significant of these was the relationship between Current Eczema and Outlet Density.
None of the analyses reached statistical significance, which may be due to the small sample size, or may mean that a correlation
does not actually exist.
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Discussion
The project has shown that it is practical to systematically obtain and map fast food outlets and compare their distribution
worldwide with the prevalence and severity of diseases, in this case asthma, rhinoconjunctivitis and eczema. The devised
methodology has proven to be an efficient way to obtain and map large amounts of restaurant distribution data in a form that is
manageable and suitable for additional analysis such as comparing with area based disease prevalence. Thus the project has
proven to be a feasible and successful in indicating a larger scale investigation. A future study should include a systematic and
documented process to obtain restaurant data for all possible countries included in ISAAC Phase Three, and perhaps a more
thorough investigation of fast food outlets in each country, as the types of fast food available differ greatly from country to
country. It may be interesting to compare an analysis using only common restaurants an analysis using all available restaurants,
and observing whether results differ. In this study, after exclusions were applied, 6 of the 53 centres (11%) had neither a
McDonald’s nor a Burger King restaurant within the region, and therefore had an outlet density of 0. These areas may well have
had a number of local chains of similar fast food type restaurants which haven’t been accounted for in this study, which may
bias the data. However obtaining outlet distribution data for small, local chains would not only be time consuming and
challenging, but may have introduced a bias of its own if data for local chains were more easily obtainable for some areas rather
than others. This study also only looked at ISAAC data for 13-14 year olds, as this was available for a higher proportion of the
investigated centres, but a future study with a larger sample of centres should also utilise the ISAAC data for 6-7 year olds. It
may be of use to compare analyses between the two as there are likely differences in the consumption of fast food between the
two age groups.
In terms of validity, there are a number of measures that need to be addressed in future studies to ensure minimisation of bias
in the results. Adjustment of potential confounders is an important part of the analysis and ISAAC has individual data of
numerous covariates such as television watching, maternal smoking, maternal education, language, exercise and GNI. Ecological
studies tend to be susceptible to confounding in general, and in this particular case, dealing with multifactorial diseases such as
asthma and allergy, accounting for this is especially important. Other potential confounders to adjust for may include
socioeconomic position and obesity (BMI). The nature of this study (the timescale) does impose limitations on the ability to
accurately gauge and adjust for confounders, however, particularly when dealing with differences within individual centres.
ISAAC centres are geographical areas which vary vastly in size, ranging from small rural towns to entire states such as North
Carolina. As an example, the Auckland region is accounted for as a single ISAAC centre, but has a wide range of difference within
it for variables such as socioeconomic position, which makes accounting for these variables challenging. For this methodology
the confounders would need to be converted from individual based measures to area based means (or medians), which wasn’t
practical for this study given the timescale, but would definitely be achievable for a future study. In addition, the Inclusion of
more low and middle income countries would strengthen the results.
It is interesting to note that the only variable in this study which seemed to show a clearly observable positive association was
between outlet density and current eczema, more so than for severe categories of any of the diseases. This is in contrast with
the 2013 ISAAC study using individual data, which found greatest correlation with severity of ARE and fast food, rather than
prevalence. The inference that fast food may worsen the severity of ARE in individuals with one of the diseases, rather than
affecting the prevalence of said disease, is only supported for asthma in this study.
As the significance of all results is quite low and the sample size quite limited, all above inferences are made with caution. The
main aim of this project was to determine the feasibility of the methodology of investigating fast food and ARE in this way, and
from that standpoint the project has been a success. With the growing fast food industry and increasing consumption of these
foods in New Zealand and internationally, with an increasing burden of non-communicable diseases, the significance of
understanding the health implications of these changes is becoming increasingly relevant for healthcare both at a population health
level and for individual care. The methods devised from this project for obtaining and analysing the distribution of fast food outlets
may be extremely valuable for determining relationships between diet and disease. The method is not necessarily restricted in
scope to asthma, rhinoconjunctivitis and eczema used in this project, and in the future may be used for a more expansive list of
disease. Information from future studies using this methodology may be highly relevant to the health sector in terms of highlighting
the need for a healthy diet, and providing reasons to cut down on fast food, especially to children and adults affected by chronic
diseases.
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