This study examined the association between pesticide exposure and lympho-hematopoietic cancers (LHC) in central Greece. Data was collected through questionnaires administered to 354 LHC cases and 455 controls from two regional hospitals. Logistic regression found an independent association between pesticide exposure and LHC (OR 1.41, 95% CI 1.00-2.00), after controlling for potential confounders like age, sex, smoking, and family history of cancer or immunological disorders. The study also found associations between LHC and smoking during pesticide application, eating during application, handling pesticide-treated seeds, and lack of proper ventilation during use, but no association with type of pesticide used.

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Question1
A cross-sectional study was conducted to examine the effect of
gestational age on systolic blood pressure (SBP) of low birth
weight babies who weigh less than 1500 gms. Data was
collected on 60 such babies and posted on Moodle in the Excel
file Assign2Q1.xls. The dataset contains the following
variables.
ID: Participant ID number
sbp = Systolic blood pressure (mmHg)
gestage = gestational age in weeks
a) What are the study factor and the outcome factor?
b) To explore the association, calculate the correlation
coefficient and interpret it?

2. c) Conduct a simple linear regression using Stata and report the
Stata output. What are the assumptions for a linear regression?
Examine the assumptions with the support of relevant graphs
and statistics.
d) Write down the regression equation and interpret the
regression coefficients and their 95% confidence interval from
part c.
e) What is the expected systolic blood pressure of a newborn
whose gestational age is 24 weeks? Show your workings.
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PHCM9498EpidemiologyandStatistics–
Question2
A case-control study was planned to investigate whether there
was an association between a mother being diagnosed with
toxaemia (A condition in pregnancy, also known as pre-
eclampsia characterized by abrupt hypertension, albuminuria
and oedema) and the baby being born with low birth weight.
The research team wished to recruit the cases and controls from
antenatal clinics. Based on a pilot study, the team expected that
the odds ratio of the association in question would be 2.5 using
a two-sided significance test and the prevalence of toxaemia
among women giving birth to a normal weight baby is 6%.

3. a) If equal number of cases and controls could be recruited in
this study, how many in each group would be required to
achieve 90% power at 5% level of significance? Include a
screenshot of your Stata command and output with your
response.
b) One of the researchers thought that prevalence of toxaemia
among the controls would be 4%.
i. What effect will this have on the required sample size to
detect an OR of 2.5 with the same power and level of
significance as in part a)?
ii. If the prevalence of toxaemia in the control group is
uncertain, would it be preferable to assume that 4% or 6% of the
control mothers have the condition? Describe your reason.
c) A similar study on the same source population found that
approximately 80% of the mothers approached for the study
would agree to participate. From this information, how many
mothers of newborn will need to be approached to achieve the
sample size that you estimated in part a)? Show your workings.
d) The research team found that they do not have sufficient
number of cases as per the calculation in part a) and decided to
recruit 2 controls per case. How many cases and controls would
be required if the power, effect size, prevalence of exposure
among the controls and level of significance are the same as in
part a)? Include a screenshot of your Stata command and output

4. with your response.
e) For 28 of the newborns their apgar score at 5 minutes
(ranging from 0 to 10) was available. A description of apgar
score can be found here.The research team also wanted to
examine if the apgar score differs by the history of toxaemia
among the mothers. Apgar score is highly negatively skewed in
both groups and for some of the newborns it was zero. What
statistical test is appropriate for this study? Explain the reason.
Page 3 of 9
Question3
Read the Extract, which is a highly edited version of a
published paper. Use the information provided in the Extract to
answer the following questions.
a) Using PICO format, write the research question for the
study.
b) What type of study has been used to answer the research
question? What would be the best study design to answer this
research question? Provide reasons for your answers.
c) i. In your own words, briefly describe the source
population and study participants.
ii. Are there any issues of concern about selection bias in this
study? Provide reasons for your answer.

5. d) i. What is the main study factor? Are there any
problems about measurement error of the study factor?
ii. What is the outcome factor? Are there any concerns about
measurement error of the outcome factor?
e) i. How have the researchers dealt with potential
confounding in this study?
ii. Are there any problems with confounding? Provide a
reason for your answer.
f) In your own words, briefly summarise the main results of
the study shown in Table 2 of the extract. Please focus on 3
factors that are associated with LHC and one that is not
associated with LHC.
[Note:Youdonotneedtoprovidetheformalexplanationforeachsetof
values.]
g) What is your assessment of the internal and external
validity of the study findings?
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6. PHCM9498EpidemiologyandStatistics–
Question3–editedextract
Background
The causality of the various types of lympho-haematopoietic
cancers (LHC) is multifactorial and includes physical, chemical
and biological agents, for example radiation, solvents, viruses
etc. In addition, there are a number of agents that are suspected
causes ofLHC.
Several studies have suggested that occupational exposure is
associated with LHC. These include chemical and woodworking
industries and farming, particularly animal breeding and the
application of pesticides.
Pesticides, which are widely used in agriculture, comprise a
wide variety of chemicals mainly used to control damage to
plants from insects (insecticides), mould (fungicides) and weeds
(herbicides).
The aim of this study was to investigate the relationship
between exposure to pesticide and LHC in the region of central
Greece, which has a substantial agricultural labour force. The
study investigated application procedures as well as the use of
personal protective equipment (PPE) in farming and quantified
exposure using detailed questionnaires administered to patients
and controls from two hospitals in a central Greece region.
Methods
Studysetting
A study of LHC was designed and conducted in two regional

7. hospitals from October 2003 to October 2006. The region is one
of the thirteen in the central eastern part
of continental Greece. The total area is
14,036 square kilometres (km2), which represents 10.6% of the
area of the entire country. According to the last census
conducted in 2001 by the General Secretariat of the National
Statistical Service of Greece (ESYE), the population of the
region was approximately 740,000 inhabitants, which represents
7% of the total population of the country. The population
breakdown is 44% urban, 16% semi-urban and 40% rural. The
region ranks second among the agricultural producing regions of
Greece and contributes 14.2% of the total primary sector
produce of the country.
Cases
Five hundred and ninety-seven (597) histologically confirmed
cases of LHC were collected from the medical records of the
two hospitals within a two-year period. The FAB (French
American British) and REAL (Revised European-American
Lymphoma) classifications were used, since both were used by
the attending physicians during the study period.
During the data collection period, 35 cases died before entering
the study. There were also new cases enrolled (16), and a
number (102) of cases could not be identified due to data
missing from the medical records (incorrect address or phone
number etc). Out of the 476 available cases, 354 agreed to
participate in the study and completed the questionnaire
(response rate 74.36%).
Controls
The control group comprised subjects from the same hospitals
who were admitted for acute conditions such as orthopaedic,
eye, ear, nose, throat or surgical diagnoses and
acute cardiac conditions. Some subjects

8. Page 5 of 9
PHCM9498EpidemiologyandStatistics–
were also recruited from the internal medicine and blood donor
departments. All of them were self-declared cancer-free
patients. Cases were divided into groups with age ranges of 5
years (e.g. 60-64, 65-69 etc) and were matched according to age
and sex.
Almost all controls who were asked to participate completed the
questionnaire (response rate 93.2%).
Questionnaire
To ascertain information from both cases and controls a
structured questionnaire was developed and pre-tested. It
includes the following sections: 1) demographics, 2) residence,
3) occupation, 4) exposure and agricultural practices, 5) family
history and 6) habits and medical history.
The demographic section included the hospital where treatment
was obtained, level of education and type of insurance. The
residence section included full address, chronological
residential changes with duration of stay and residential level
(urban, suburban or rural). The assignment of the residential
level and the coding of the residence were performed using lists
from the Ministry of Internal Affairs of Greece. In the
occupational section, detailed information on previous
employment and other activities were reported.
Subjects who reported at least one year of work in farming were
asked to complete the part of the questionnaire on pesticide
exposure. The information collected included type of crop,
duration of farming, surface area of the farm, characteristics of
the adjacent farm and crop infestations.
The participants were asked to provide commercial names of

9. pesticide products, number of applications per year, total years
of use and type of application (spraying,
during planting and usage of treated seeds). To provide help to
the participants in recalling the pesticides used, a list of the
most common brand names was provided. Moreover, questions
were included regarding adherence to application guidelines and
familiarity with caution signs/first aid help. The type and
purpose of the use of PPE (e.g. uniforms, masks, boots etc), the
use of equipment machinery, the frequency of consulting
experts, aspects of product handling (e.g. location of storage)
and the existence of an integrated farm system were also
investigated. In addition, information on certain habits such as
changing clothes before entering the house, smoking, eating and
accidents (e.g. accidental poisoning), was also collected.
Finally, details of work with animals and pet ownership were
considered. In the family history section, all types of cancers,
LHC and immunological disorders as well as the family
proximity (first, second- and third-degree relatives) were
recorded.
Categories for smoking habit and alcohol consumption
according to the Centers for Diseases Control and Prevention
(CDC) 2002 classifications were adopted. Information regarding
the subject’s medical history included other cancers,
cardiovascular disorders, respiratory diseases, immunological
disorders, inflammatory diseases, endocrine disorders, diabetes
mellitus and other metabolic disorders.
The questionnaire was pilot tested among both cases and
controls aged 27 to 73 years and modifications were made
according to the results obtained. The time needed to fill the
questionnaire was reasonable with the only delay at the section
regarding the specific pesticides used. The interviews were
conducted by a trained occupational
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10. PHCM9498EpidemiologyandStatistics–
physician and the date of diagnosis was used as a reference date
for both cases and controls.
Due to changes in pesticide exposure over time, an expert
phytopathologist evaluated each questionnaire and the data
collected regarding pesticide exposure and handling practices,
as well as commercial names of pesticides and types of
application. All active ingredients were grouped according to
the target pest into three major categories: 1) insecticides 2)
fungicides and 3) herbicides.
A new variable was developed for total pesticide exposure for
all subjects, in order to classify them in the “Low/No”
(referent), “Medium/High” category. Participants who had never
worked in the agricultural sector as their main or secondary
occupation and declared urban or suburban residences were
classified in the “Low/No” exposure category.
In order to avoid reporting exposure that occurred after LHC
diagnosis and to allow a minimum latency period, the period
preceding one year before the reference date for both cases and
controls was used for recorded exposure.
Statisticalanalysis
Standard statistical procedures were carried out using the
epidemiological software Epi-info (version 3.4.3) and the
Statistical Package for Social Sciences (SPSS) (version 15.0).
Data were validated for completeness before statistical analysis
was performed. Descriptive analysis was conducted for each
variable including frequencies, ranges, means ± SD, median
values and interquartile ranges (IQR) for both cases and
controls. The chi-square or Fisher exact test was used to analyze
qualitative data, whereas the student t-test
or Mann-Whitney test was used for

11. quantitative data. Total pesticide exposure and smoking habit as
well as smoking and eating during farming were made
categorical (yes/no) variables. Agricultural occupations were
grouped together (farmer, pesticide applier, seasonal farm
worker, animal breeder) and compared to the group of other
occupations (e.g. teacher, trader, public servant, unemployed
etc.).
Logistic regression analysis was used to control for confounders
and to identify independent risk factors. Exposure to pesticides
was an independent categorical variable. Age, sex, smoking and
family history (all types of cancer, LHC and immunological
disorders) were included as confounders. Differences were
considered statistically significant when the two-sided p value
was ≤ 0.05.
Ethics
The study was approved by the University of Thessaly
Scientific Committee which is responsible for ethics. The
Institutional Scientific Committee of both hospitals approved
access to patients’ files and allowed interviews. The
participants provided informed verbal consent and no monetary
incentives for participation were offered.
Results
Overall, 354 cases and 455 controls (81 orthopaedics, 84
otolaryngology, 64 ophthalmology, 93 surgery, 42 cardiology,
59 internal medicine and 32 blood donors) were collected. In
Table 1 the characteristics of the study population, including
sex, agricultural occupation, pesticide exposure and smoking
habit, are presented. The median age of both cases and controls
was 70 years (IQR 62-
76).

12. Page 7 of 9
PHCM9498EpidemiologyandStatistics–
The results of univariate data analysis for LHC and different
exposures are shown in Table 2 including specific protective
behaviours. No association was found between the types of
pesticides and LHC (data not shown).
Using logistic regression analysis, pesticide exposure was found
to be independently associated with a LHC (OR 1.41, 95% CI
1.00-2.00) after controlling for the following confounders: age,
sex, smoking and first-degree family history of all types of
cancer, family history of LHC and family history of
immunologicaldisorders.

13. Page 8 of 9
PHCM9498EpidemiologyandStatistics
Table1:Descriptionofstudyparticipants
CasesControls
Sex Male 188 53.1% 238 52.3%
Female 166 46.9% 217 47.7%
Agricultural occupation Yes 185 52.2% 212 46.6%
No 169 47.7% 243 53.4%

14. Pesticide exposure Yes 282 79.6% 331 72.7%
Low/No 72 20.3% 124 27.2%
Smoking Yes 148 41.8% 205 45.0%
No 206 58.2% 250 54.9%
Total 354 455
Table2:UnivariateanalysisofexposuresamongLHCcasesandcontro
ls
ExposureOR95%CI
Agricultural occupation 1.25 0.95-1.65
Pesticides 1.46 1.05-2.04
Smoking during pesticide application 3.29 1.81-5.98
Eating during pesticide application 18.18 2.38-381.17
Not changing clothes after work 1.51 1.00-2.29
Handling pesticide-treated seeds 3.01 1.19-7.77
No proper ventilation when using pesticides 3.60 1.77-7.31
Self-application of pesticides 1.14 0.82-1.60
ProtectivepracticesOR95%CI
Compliance with product labels 0.85 0.56-1.28

15. Use of PPE during application 0.86 0.53-1.38
Familiarity with caution signs 1.05 0.66-1.65
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