7312MED Epidemiology: Study Design Analysis - Griffith University 2018

This report provides a detailed analysis of an epidemiology study focusing on a quasi-experimental, longitudinal study design investigating the impact of housing improvements on smoking cessation in deprived areas of Glasgow. The analysis covers various aspects of the study, including the identification of the study design, research hypotheses, study factors, and outcomes. It examines potential biases, confounders, and the application of Bradford Hill's criteria for causality. The report also evaluates the generalizability of the study's findings and delves into the relationship between housing improvements, mental health, and smoking cessation intentions. The document concludes by assessing the validity and implications of the study's findings within the context of public health research.

Running head: PRACTICES AND PRINCIPLES: EPIDEMIOLOGY
PRACTICES AND PRINCIPLES: EPIDEMIOLOGY
Name of the Student
Name of the University
Author’s Note:

1STUDENT NAME STUDENT NUMBER
Answer to the question number 1:
In this epidemiology study conducted by Bond et al. (2013), a ‘Quasi- experimental’,
‘longitudinal’ study design was applied for this investigation.
One of the key features for Quasi- experimental study is the lack of random assignment to
either control or treatment. Another key feature is the presence of ‘pre and post testing’. In
this experiment, both of the characteristics were fulfilled by the investigators (Wells & Yang,
2008). The subjects for this investigation were not randomly assigned and the subjects were
pre tested before the intervention and post tested after the intervention.
Longitudinal study is a kind of study where data are collected during a period of time and in
this investigation data were collected over a period of two year.
Answer to the question number 2:
In this research investigation two research questions were presented and based on this
research questions following two hypotheses can be stated:
1. HI (Housing Improvements) will lead to an intention to quit smoking or reduction in
smoking.
2. An intention to quit smoking or reduction in smoking will happen as a direct consequences
of reduction in stress and improvement of mental health due to HI (Housing Improvements).
Answer to the question number 3:
The study factors for this study are the housing improvements like doors, external cladding,
roof improvement, kitchens, bathrooms, and heating.
Surveys were used to collect the data for the study factors. The groups were measured and
divided on the basis of housing improvements. The participants were asked whether they had
experienced any housing improvements mentioned in the above paragraphs in the past two

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years. Those who reported to experienced housing improvements were placed in the HI group
and those who did not reported any experiences of housing improvements were placed in the
non-HI group.
Answer to the question number 4:
The outcome of this investigation is whether there is an intention to quit smoking or
reduction in smoking. The factors which might be affecting this outcome are anxiety, stress,
depression, as well as socio- demographic variable like ethnicity, gender, education, and age.
Anxiety, stress, and depression can be used to determine the status of mental health and
mental assessment tool were used to measure this aspects. SF- 12v2 assessment tool was used
to assess the status of mental health. The composite score for mental health assessment was
determined using 12 questions as per as the SF- 12v2 procedure. Time period for these
questions was ‘over the past four weeks. Economic status of the participants was determined
on the basis of participant’s economic activities.
Answer to the question number 5:
The main findings of the Table 2 was whether participants from HI group were intended to
quit smoking in comparison with the participants from the non- HI group. The findings from
the Table 2 suggest that the participants from HI group were twice as likely quit smoking
when compared with the participants from non- HI group. The p- values of the findings were
statistically significant as well. Therefore, it can be deduced that the housing improvements
has a significant on the intention of quit smoking and hence, it can be said that the study
factors are associated with outcome factors. These findings remained significant even after
the addition of socio- demographic parameters.

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Answer to the question number 6:
The authors of this investigation determined the participants of this investigation through
random sampling to avoid the selection bias. The participants were randomly selected from
post office addresses. From the selected addresses, one adult (age greater than 16) person was
randomly chosen with their consent. However, selection bias could be introduced in this
study design (Allcott, 2015). The authors have selected 14 disadvantaged localities in
Glasgow. This was determined using Scottish Index of Multiple Deprivation. From this, it
can be seen that the authors have already pre- defined the criteria’s for locality selection.
However, a society does not only contain the deprived population. Therefore, there might be
chance of unequal distribution of sample selection. However, people from outside the chosen
locality also have the habit of smoking. Additionally, people from higher economic status
have more chance to experience housing improvements. Outcome factors like stress,
depression also presents in these communities. Therefore, the far more unbiased results could
be obtained if all other communities were involved in the study design.
Answer to the question number 7:
In this study, information bias might play a role in the concluding results. The authors have
collected data in pre- test and post- test method. There was no mention of the time frame of
the occurrence of housing improvements. They have not set up any criteria in this regard. For
example, this was longitudinal study over a period of two years. A participant might
experience housing intervention one month after the start of the investigation, six month
after, one year after or just before the completion of the two year and it is quite obvious that
the each participant will experience this intervention at different time frame. Therefore, all
the participants will not experience the effect of intervention for the same duration of time
and effect of housing intervention on smoking, if any, is bound to be erroneous. Hence, from

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the above discussion, it can be said that the information bias might have an effect on the final
data.
Answer to the question number 8:
Confounders are variables which influences both the dependent and independent variables
causing an unauthentic interpretation of the data (Raghunathan, Miller & Rashid, 2015).
Confounders are present in this study as well and the authors have identified those
confounders and take measures to nullify their effects. The confounders which have been
identified in this study are socio- demographic parameters like ethnicity, age, gender as well
as their employment status (employed or retired) and educational status (attained school or
not). The reason behind the consideration of the confounders by the authors is to reduce the
effect of unauthentic interpretation or erroneous results. In the data presented in Table 2, the
authors have reported that the relation between the study factor and outcome factor remained
significant even after the inclusion of confounders. The relation between the study factor and
outcome factor was that the housing improvements enhance the chance of intention to quit
smoking. Therefore, in this scenario, the confounders had no effect on the relationship
between study factors and outcome factors. The possible explanation behind this is that the
study factor is the sole contributing factor to the outcome of this investigation’s findings.
Answer to the question number 9:
The second research question which was posed by the author was “could this be explained by
improvements in mental health and/ or reductions in stress subsequent to the HI?” In the
presented data in Table 3 the authors have answered this research question. In order to do
that, the authors have constructed 4 multivariate models for examination. They have reported
that the odds ratio for HI remains significantly high for all the models. Consultation with GP
regarding emotional problem strongly associated with the intention to quit smoking, however,
it is not significantly associated with the housing improvements. In their third assessment

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model, they have shown that mental health managed to improve a person’s symptoms
significantly, although, worsening of symptoms is only marginally significant. Similar like
previous scenario, intention to quit smoking is not associated with housing improvements. In
a nutshell, mental health is positively associated with the experience of housing
improvements but negatively associated when considering about the intention to quit
smoking. Improvements in symptoms like anxiety or depression is closely associated with
intention to quit smoking but not with housing improvements. The author’s research question
was to determine whether mental health could be associated with housing improvements and
they have explored this area in detail.
Answer to the question number 10:
In this scenario, I agree with the author that the high prevalence of smoking rate in the group
is more likely due to the chance factor and it is most likely not related to the factor which is
the receipt of housing improvements. The reason behind is that the smoker does not
necessarily seek housing improvements as well as nor the housing improvements were
provided based on the smoking characteristics. Therefore, the reason behind the higher
smoking rate than national smoking rate in these two groups happened due to chance factor
and nothing more. Although, studies have shown complete opposite findings where there is a
strong correlation between reduction in smoking prevalence and housing improvements
(Blackman et al., 2001). However, the study design of these two studies is different and this
might be the reason behind the difference in findings.
Answer to the question number 11:
Bradford Hill has set out nine different criteria for the evaluation of causality in
epidemiological study (McDonald & Strang, 2016). In this study, three of these criteria can
be established. These criteria are Consistency, Temporality, and Coherence. Consistency can
be established in this regard as the authors have demonstrated the fact that there is a

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consistent observational finding between the reduction in smoking or intention to quit
smoking and housing improvements. The criteria Temporality can be established only if the
effect occurs after the cause. This is also is in line with this study’s findings. The outcome,
intention to quit smoking or reduction in smoking, happened after the cause which is housing
improvements. Similar like previous two criteria, coherence can also be established in the
context of this study. This study has reported the relationship between intention to quit
smoking with housing improvements and studies investigating in this area also presented
similar kind of findings (Helms, King & Ashley, 2017).
Answer to the question number 12:
The participants of this study were selected from the community which are below lowest 15
per cent economical deprivation cut off according to Scottish Index of Multiple Deprivation.
All of the participants were from fourteen neighborhoods belongs in the fore mentioned
criteria. No participants were chosen from any other community. Henceforth, the findings of
this study can be generalized to the individuals who are belong to the lowest 15 per cent
economical deprivation cut off according to Scottish Index of Multiple Deprivation.

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References:
Allcott, H. (2015). Site selection bias in program evaluation. The Quarterly Journal of
Economics, 130(3), 1117-1165.
Blackman, T., Harvey, J., Lawrence, M., & Simon, A. (2001). Neighbourhood renewal and
health: evidence from a local case study. Health & place, 7(2), 93-103.
Bond, L., Egan, M., Kearns, A., Clark, J., &Tannahill, C. (2013). Smoking and intention to
quit in deprived areas of Glasgow: is it related to housing improvements and
neighbourhood regeneration because of improved mental health?. J Epidemiol
Community Health, 67(4), 299-304.
Helms, V. E., King, B. A., & Ashley, P. J. (2017). Cigarette smoking and adverse health
outcomes among adults receiving federal housing assistance. Preventive medicine, 99,
171-177.
McDonald, R., & Strang, J. (2016). Are take‐home naloxone programmes effective?
Systematic review utilizing application of the Bradford Hill
criteria. Addiction, 111(7), 1177-1187.
Raghunathan, K., Miller, T. E., & Rashid, A. M. (2015). Confounders versus mediators: an
important distinction. Anesthesiology: The Journal of the American Society of
Anesthesiologists, 123(1), 234-234.
Wells, N. M., & Yang, Y. (2008). Neighborhood design and walking: a quasi-experimental
longitudinal study. American journal of preventive medicine, 34(4), 313-319.