Epidemiological Studies and Housing Improvement
VerifiedAdded on 2023/01/23
|8
|2635
|98
AI Summary
This document discusses different types of epidemiological studies, specifically focusing on observational and interventional studies. It also explores the impact of housing improvement on smoking rates and mental health. The findings suggest that there is no significant connection between housing improvement and intention to quit smoking, but there is a positive association between housing improvement and improved mental health. The document also discusses potential biases and confounding factors in the study.
Contribute Materials
Your contribution can guide someone’s learning journey. Share your
documents today.
7312MED EPIDEMIOLOGY: PRINCIPLES AND
PRACTICES
PRACTICES
Secure Best Marks with AI Grader
Need help grading? Try our AI Grader for instant feedback on your assignments.
Table of Contents
Answer1:...............................................................................................................................................3
Answer2:...............................................................................................................................................3
Answer3:...............................................................................................................................................3
Answer4:...............................................................................................................................................3
Answer5:...............................................................................................................................................4
Answer6:...............................................................................................................................................4
Answer7:...............................................................................................................................................5
Answer8:...............................................................................................................................................5
Answer9:...............................................................................................................................................6
Answer10:.............................................................................................................................................6
Answer11:.............................................................................................................................................7
Answer12:.............................................................................................................................................7
References:............................................................................................................................................9
Answer1:...............................................................................................................................................3
Answer2:...............................................................................................................................................3
Answer3:...............................................................................................................................................3
Answer4:...............................................................................................................................................3
Answer5:...............................................................................................................................................4
Answer6:...............................................................................................................................................4
Answer7:...............................................................................................................................................5
Answer8:...............................................................................................................................................5
Answer9:...............................................................................................................................................6
Answer10:.............................................................................................................................................6
Answer11:.............................................................................................................................................7
Answer12:.............................................................................................................................................7
References:............................................................................................................................................9
Answer1:
There are different types of epidemiological studies- Observational studies and Interventional
studies. Interventional studies are further divided into randomized and non-randomized. Quasi
experimental is the non-randomized epidemiological design used in this case study.Quasi
experiments are intended to demonstrate causality between the intervention and the result.Quasi-
experimental study is similar to conventional experimental design or randomized controlled trial
except it lacks the component of random allocation or control. A quasi-experimental design has an x
and y variable -independent and dependent variables respectively. The x-variable is manipulated in
order to affect a dependent y-variable.It is a longitudinal study which involves repeatedly assessing
the categorical or continuous results calculated over time. The longitudinal study involves estimating
the baseline and comparing any changes/ deviations from the baseline. Another feature of this study
is the time series comparisons where the deviations in exposure and the symptoms level are
computed against time with every individual serve as a comparison of their own (Bond et al., 2012)..
Answer2:
As per the case study the first research hypothesis is housing improvement (HI) indicates a decline
in smoking or aim to stop smoking. Second postulate would be HI reduces the anxiety and stress,
improves mental health of the people in the underprivileged areas (Bond et al., 2012).
Answer3:
A cohort survey starts by classifying groups based on the study factor for example exposure present
or absent. Hence here housing improvementis the study factor.The number of participants are
identified by the longitudinal sample accomplished practically by using record association to
recognize members who took part in cross-sectional studies in 2006 and 2008 in the similar
localities. The longitudinal sample was categorized all together by means of record linkage (Bond et
al., 2012).
Answer4:
The outcome factors are Smoker/non-smoker/quit smoking. Once the cohort was identified, data
was recorded and stored as per the data protection rules.In 2008, the cohort group was asked if they
were exposed to the HI programme. In the cross sectional studies piloted in 2006 and 2008, the
cohorts were divided if they are regular smokers, occasional smokers, or stopped smoking or on no
occasion smoked. The responses are grouped as smoker if the participant is a regular or infrequent
smoker. Participants are classified as non-smoker if they stopped smoking or never smoked. Regular
cigarette smokers were enquired if they want to discontinue smoking in the time ahead are graded
There are different types of epidemiological studies- Observational studies and Interventional
studies. Interventional studies are further divided into randomized and non-randomized. Quasi
experimental is the non-randomized epidemiological design used in this case study.Quasi
experiments are intended to demonstrate causality between the intervention and the result.Quasi-
experimental study is similar to conventional experimental design or randomized controlled trial
except it lacks the component of random allocation or control. A quasi-experimental design has an x
and y variable -independent and dependent variables respectively. The x-variable is manipulated in
order to affect a dependent y-variable.It is a longitudinal study which involves repeatedly assessing
the categorical or continuous results calculated over time. The longitudinal study involves estimating
the baseline and comparing any changes/ deviations from the baseline. Another feature of this study
is the time series comparisons where the deviations in exposure and the symptoms level are
computed against time with every individual serve as a comparison of their own (Bond et al., 2012)..
Answer2:
As per the case study the first research hypothesis is housing improvement (HI) indicates a decline
in smoking or aim to stop smoking. Second postulate would be HI reduces the anxiety and stress,
improves mental health of the people in the underprivileged areas (Bond et al., 2012).
Answer3:
A cohort survey starts by classifying groups based on the study factor for example exposure present
or absent. Hence here housing improvementis the study factor.The number of participants are
identified by the longitudinal sample accomplished practically by using record association to
recognize members who took part in cross-sectional studies in 2006 and 2008 in the similar
localities. The longitudinal sample was categorized all together by means of record linkage (Bond et
al., 2012).
Answer4:
The outcome factors are Smoker/non-smoker/quit smoking. Once the cohort was identified, data
was recorded and stored as per the data protection rules.In 2008, the cohort group was asked if they
were exposed to the HI programme. In the cross sectional studies piloted in 2006 and 2008, the
cohorts were divided if they are regular smokers, occasional smokers, or stopped smoking or on no
occasion smoked. The responses are grouped as smoker if the participant is a regular or infrequent
smoker. Participants are classified as non-smoker if they stopped smoking or never smoked. Regular
cigarette smokers were enquired if they want to discontinue smoking in the time ahead are graded
as yes/no. Logistic regression was used to gauge the connexion among HI and smoking or aim to give
up smoking. Additionally logistic failure studied if the addition of psychological health weakened
links. For all investigations grouping the individuals of Go Well regions was accustomed for using
strong regular inaccuracies. Regression method was used to observe the correlation between HI and
psychological health as evaluated by SF-12.All investigations were done using STATA Version X (Bond
et al., 2012).
Answer5:
No, there was no significant connection between HI and intention to discontinue smoking. As per the
findings there was a major difference in smoking frequency amongst the HI as well as non-HI group
when compared to the baseline. For the model 1 HI group- OR is 1.99 and 95%CI value is 1.10 to 3.57
and the p value is 0.023 and in model 2 HI group - OR is 2.16, 95%CI is 1.12 to 4.16 and the p value is
0.022.The p value do not any major change which justifies that there is no major connection amid
the study factor and the outcome factor. However the number of people with the intent to stop
smoking doubled from the HI group when compared with the non-HI group in 2008 and the
connection constant remarkable with the presence of sociodemographic variables and past
announcement of objective to quit (Bond et al., 2012).
Answer6:
Selection bias can arise when researchers use improper measures for selecting a section population,
it also happens if different aspects effect the continuous participation of issues under study. In this
study the method of associating accounts from two cross-sectional examinations has outcomes for
the represent activeness of the model and potential selection bias. The probable reason for selection
bias is the 2year time duration during which the HI is done. Some participants experienced HI for
2years, some in last 6 months or less in the 2008 survey. Hence there is a high probability of losing
the effect of HI as the influence of interference may decrease.All things considered, on the off
chance that the search for lasting impacts cannot be a major issue. As far as the psychological
wellness estimates additionally the variety in the time scales have more information. The SF-12MH
inquiries about the previous month, the other two measures retrieve information of last year. The
numbers who detailed ordinary psychological wellness issues were very little, and the numbers who
detailed enhancements were little, constraining the exactness of impact gauges for this. This inquiry
regarding change in side effects likewise did not consider seriousness into record—people with
extreme issues who improved would have been gathered with participants with mellow issues who
additionally improved (Bond et al., 2012).
up smoking. Additionally logistic failure studied if the addition of psychological health weakened
links. For all investigations grouping the individuals of Go Well regions was accustomed for using
strong regular inaccuracies. Regression method was used to observe the correlation between HI and
psychological health as evaluated by SF-12.All investigations were done using STATA Version X (Bond
et al., 2012).
Answer5:
No, there was no significant connection between HI and intention to discontinue smoking. As per the
findings there was a major difference in smoking frequency amongst the HI as well as non-HI group
when compared to the baseline. For the model 1 HI group- OR is 1.99 and 95%CI value is 1.10 to 3.57
and the p value is 0.023 and in model 2 HI group - OR is 2.16, 95%CI is 1.12 to 4.16 and the p value is
0.022.The p value do not any major change which justifies that there is no major connection amid
the study factor and the outcome factor. However the number of people with the intent to stop
smoking doubled from the HI group when compared with the non-HI group in 2008 and the
connection constant remarkable with the presence of sociodemographic variables and past
announcement of objective to quit (Bond et al., 2012).
Answer6:
Selection bias can arise when researchers use improper measures for selecting a section population,
it also happens if different aspects effect the continuous participation of issues under study. In this
study the method of associating accounts from two cross-sectional examinations has outcomes for
the represent activeness of the model and potential selection bias. The probable reason for selection
bias is the 2year time duration during which the HI is done. Some participants experienced HI for
2years, some in last 6 months or less in the 2008 survey. Hence there is a high probability of losing
the effect of HI as the influence of interference may decrease.All things considered, on the off
chance that the search for lasting impacts cannot be a major issue. As far as the psychological
wellness estimates additionally the variety in the time scales have more information. The SF-12MH
inquiries about the previous month, the other two measures retrieve information of last year. The
numbers who detailed ordinary psychological wellness issues were very little, and the numbers who
detailed enhancements were little, constraining the exactness of impact gauges for this. This inquiry
regarding change in side effects likewise did not consider seriousness into record—people with
extreme issues who improved would have been gathered with participants with mellow issues who
additionally improved (Bond et al., 2012).
Secure Best Marks with AI Grader
Need help grading? Try our AI Grader for instant feedback on your assignments.
Answer7:
Information bias is a distortion in the amount of association induced with the aid of a lack of correct
measurements of key experiment variables. Information bias, known as measurement bias, ascends
when crucial analysis variables (exposure, health outcome or confounders) are erroneously
calculated/categorized. Bias in the risk ratio, rate ratio, or odds ratio can be created even if
computed mistakes are matching between exposed and unexposed or amid study individuals that
have or don’t’ve the fitness result.If no errors are made in detecting the presence of the
health concern (i.e. a hundred percent sensitivity), however equal inaccuracies are made between
uncovered and unexposed in the classificationof health result fame (i.e. specificity much less than
100%),the risk ratio, charge ratio, and exposure difference (as applicable)will be biased closer to the null.
Differential misclassification evolves when misclassification of exposure don’t match between subjects
that may or may not have the health consequences, or when misclassification of the health effect is not
the same amongst exposed and unexposed matters. Differential misclassification details a bias in the risk
ratio, price ratio, or odds ratio both near and away from the null, count on the proportions of dependents
misclassified (Bond et al., 2012).
Answer8:
Confounding is the misrepresentation of the involvement joining an exposure and health effect through
minor, the 3rd variable referred as confounder. Since the disclosure of interest is hardly ever the lone
thing that fluctuates between exposed and unexposed groups, also affects the health consequence or
disease rate, confounding is a usual incidence in etiologic studies. The preceding analyses have
scrutinised the relationships joining HI and smoking. The second query was whether, if an affiliation was
found between HI and smoking or planning to leave smoking, this would possibly be defined by an
enhancement in psychological health or lessening in facing depression, anxiety or stress. To tackle the
above query the connection between HI, mental health and intention to quit is the focus. As per the
previous analyses it’s confirmed that there is no bond between current smoking and having attained a HI
(adjusting for previous smoking status), however an affiliation between intention to end smoking and a
HI, and connection among improved mental health and HI is discovered. To study if the enhancements in
mental health attenuate the liaison among HI and the goal to stop smoking, table no. 3 gives 4 - methods
analysing the connotation mid HI and target to quit and the three assessments of psychological health. All
models are adjusted as per sociodemographic factors and also accustomed for the suitable 2006 health
gauge (eg, for SF-12 Mental health (MH) 2008,we have in tune for individuals SF-12 MH 2006 ratings
etc).The odds-ratios for HI are decreased barely in models 2–4, still a the sizable impact of HI remains in
every case. Mental health as computed through SF-12MH scale is undesirably related with purpose to
stop though this is not statistically noteworthy anymore .Consulting a general practitioner about emotive
issues in the past 12 months is sturdily linked to objective to give up however was not considerably
Information bias is a distortion in the amount of association induced with the aid of a lack of correct
measurements of key experiment variables. Information bias, known as measurement bias, ascends
when crucial analysis variables (exposure, health outcome or confounders) are erroneously
calculated/categorized. Bias in the risk ratio, rate ratio, or odds ratio can be created even if
computed mistakes are matching between exposed and unexposed or amid study individuals that
have or don’t’ve the fitness result.If no errors are made in detecting the presence of the
health concern (i.e. a hundred percent sensitivity), however equal inaccuracies are made between
uncovered and unexposed in the classificationof health result fame (i.e. specificity much less than
100%),the risk ratio, charge ratio, and exposure difference (as applicable)will be biased closer to the null.
Differential misclassification evolves when misclassification of exposure don’t match between subjects
that may or may not have the health consequences, or when misclassification of the health effect is not
the same amongst exposed and unexposed matters. Differential misclassification details a bias in the risk
ratio, price ratio, or odds ratio both near and away from the null, count on the proportions of dependents
misclassified (Bond et al., 2012).
Answer8:
Confounding is the misrepresentation of the involvement joining an exposure and health effect through
minor, the 3rd variable referred as confounder. Since the disclosure of interest is hardly ever the lone
thing that fluctuates between exposed and unexposed groups, also affects the health consequence or
disease rate, confounding is a usual incidence in etiologic studies. The preceding analyses have
scrutinised the relationships joining HI and smoking. The second query was whether, if an affiliation was
found between HI and smoking or planning to leave smoking, this would possibly be defined by an
enhancement in psychological health or lessening in facing depression, anxiety or stress. To tackle the
above query the connection between HI, mental health and intention to quit is the focus. As per the
previous analyses it’s confirmed that there is no bond between current smoking and having attained a HI
(adjusting for previous smoking status), however an affiliation between intention to end smoking and a
HI, and connection among improved mental health and HI is discovered. To study if the enhancements in
mental health attenuate the liaison among HI and the goal to stop smoking, table no. 3 gives 4 - methods
analysing the connotation mid HI and target to quit and the three assessments of psychological health. All
models are adjusted as per sociodemographic factors and also accustomed for the suitable 2006 health
gauge (eg, for SF-12 Mental health (MH) 2008,we have in tune for individuals SF-12 MH 2006 ratings
etc).The odds-ratios for HI are decreased barely in models 2–4, still a the sizable impact of HI remains in
every case. Mental health as computed through SF-12MH scale is undesirably related with purpose to
stop though this is not statistically noteworthy anymore .Consulting a general practitioner about emotive
issues in the past 12 months is sturdily linked to objective to give up however was not considerably
related thru HI (see table 1). For the third assessment of psychological health, there is a robust
relationship between experiencing an upgrading in symptoms—and a slightly statistically considerable
affiliation between symptoms remaining the same or turning into worse—and intention to quitsmoking.
Again, however, these are not related with HI (Bond et al., 2012).
In short:
1. Mental fitness as measured with the aid of SF12-MH used to be clearly associated with having a HI but
discouragingly related with intention to quit smoking
2. Seeing a GP about emotional troubles in the last 12 months was no longer related with possessing a HI
however was surely related with purpose to quit smoking
3. Feeling a progress in depression/anxiety signs was related with purpose to end smoking but not with
HI.
Answer9:
While its observed no drop in smoking rates for folks who had an HI, its discovered that there are
variations amongst the HI and non-HI groups concerning their goal to stop smoking, where the HI
set substantially extra probable to have an plan to quit.These variations have been no longer defined
through baseline variations in target to quit. Additionally no proof was found if there’s any procedure
to know if HI may function on residents’ purpose to quit smoking via progress in mental health or
lessening the stress, as suggested by using Blackman et al.21 Thus whilst a positive affiliation is
discovered amid HI and increased mind health (as measured by SF-12) that is compatible with former
research, participants who wanted to leave smoking had worse intellectual fitness ratings in 2008 when
compared to 2006,using the SF-12 MH measure (although it’s not statistically significant anymore).
Seeking GP counsel and/or facing mind health troubles regularly, whether recovering, remained same or
deteriorated, were individualistically related with a greater chance of objective to quit. The former could
be due to doctor’s quick inspirational recommendation to quit, or it can also replicate a bigger prevalent
inclination/ability to take act amongst this team (Bond et al., 2012).
Answer10:
There’s a huge dissimilarity in the occurrence of smoking rates in 2006 amongst the two clusters, where
the smoking rate is 10% lower between those who in consequence got a HI. In both cases, the smoking
charge used to be well beyond the national average of 26% for males and 23% for ladies. Nonetheless,
this alteration in incidence at reference point was possibly owing to hazard or aspects no longer
correlated to getting HI. HI is furnished on a zone or assets groundwork (constructions requiring
enhancements), not on householder features, nor are they as long as in answer to householders’
relationship between experiencing an upgrading in symptoms—and a slightly statistically considerable
affiliation between symptoms remaining the same or turning into worse—and intention to quitsmoking.
Again, however, these are not related with HI (Bond et al., 2012).
In short:
1. Mental fitness as measured with the aid of SF12-MH used to be clearly associated with having a HI but
discouragingly related with intention to quit smoking
2. Seeing a GP about emotional troubles in the last 12 months was no longer related with possessing a HI
however was surely related with purpose to quit smoking
3. Feeling a progress in depression/anxiety signs was related with purpose to end smoking but not with
HI.
Answer9:
While its observed no drop in smoking rates for folks who had an HI, its discovered that there are
variations amongst the HI and non-HI groups concerning their goal to stop smoking, where the HI
set substantially extra probable to have an plan to quit.These variations have been no longer defined
through baseline variations in target to quit. Additionally no proof was found if there’s any procedure
to know if HI may function on residents’ purpose to quit smoking via progress in mental health or
lessening the stress, as suggested by using Blackman et al.21 Thus whilst a positive affiliation is
discovered amid HI and increased mind health (as measured by SF-12) that is compatible with former
research, participants who wanted to leave smoking had worse intellectual fitness ratings in 2008 when
compared to 2006,using the SF-12 MH measure (although it’s not statistically significant anymore).
Seeking GP counsel and/or facing mind health troubles regularly, whether recovering, remained same or
deteriorated, were individualistically related with a greater chance of objective to quit. The former could
be due to doctor’s quick inspirational recommendation to quit, or it can also replicate a bigger prevalent
inclination/ability to take act amongst this team (Bond et al., 2012).
Answer10:
There’s a huge dissimilarity in the occurrence of smoking rates in 2006 amongst the two clusters, where
the smoking rate is 10% lower between those who in consequence got a HI. In both cases, the smoking
charge used to be well beyond the national average of 26% for males and 23% for ladies. Nonetheless,
this alteration in incidence at reference point was possibly owing to hazard or aspects no longer
correlated to getting HI. HI is furnished on a zone or assets groundwork (constructions requiring
enhancements), not on householder features, nor are they as long as in answer to householders’
proactively considering for HI. Its no longer considered that citizens are supplied with HI on the
underpinning of their smoking grade, or that non-smokers have been in a position to proactively are
seeking these progresses .Our findings are in blatant distinction to those through Blackman et al 21 who
stated a great massive drop in the frequency of smoking for these acceptance some kind of housing
repair. But, there are some vital variations between the actual results and the reported parameters. On
the one hand, the Blackman report stated on a 5 year sequel and possibly one wants to allow for extra
period to see any drifts on smoking, although this may not happen. On the separate hand, the study used
to be trivial and consequently constrained in its size to modify for confounders and they don’t take
account of the collected nature of their data: 98 households, 209 respondents.Our find out about is large
and comprises an increased share of people in quite terrible situations, who are extra possibly to smoke
and much less in all likelihood helpful at renouncing (Bond et al., 2012).
Answer11:
The nine “aspects of association” of Bradford Hill’s criteria are (strength of association, consistency,
specificity, temporality, biological gradient, plausibility, coherence, experiment, and analogy) have been
used to consider endless theorized relationships between working and ecological exposures
and disorder results. For HI and intention to stop smoking the first criteria is Consistency when multiple
epidemiologic research the use of a range of locations, residents, and strategies exhibit a constant
friendship concerning two variables with recognize to the null supposition. Defined that proof is drawn
from investigational control—predominantly epidemiologic readings in disorder hazard regressions
following an intrusion or interruption of exposure—may lead to the toughest help for causal inference.
Termination of exposure as Hill described might additionally no longer contrary or significantly gradual
the development of the ailment. In some circumstances, a couple of danger factors, together with food,
exercise, smoking, biochemical exposures, and genetic tendency can contribute to ailment inception and
advancement. Thus, whilst the mixture of these elements can also end in disease, investigational
handling of a single causative aspect can or no longer result in visible declines in ailment incidence (Bond
et al., 2012).
Answer12:
Providing inhabitants in destitute areas with enhanced housing may additionally inspire residents to
think through leaving smoking. Though, few people without a doubt stop, demonstrating that inhabited
enhancements or modifications to the bodily surroundings were also not enough catalyst for individual
behavioural transformation. It would make wisdom to tie health amenities to housing revival tasks to
maintenance modifications in health behaviours at a period when ecological exchange seems to mark
behavioural modification extra possible (Bond et al., 2012).
underpinning of their smoking grade, or that non-smokers have been in a position to proactively are
seeking these progresses .Our findings are in blatant distinction to those through Blackman et al 21 who
stated a great massive drop in the frequency of smoking for these acceptance some kind of housing
repair. But, there are some vital variations between the actual results and the reported parameters. On
the one hand, the Blackman report stated on a 5 year sequel and possibly one wants to allow for extra
period to see any drifts on smoking, although this may not happen. On the separate hand, the study used
to be trivial and consequently constrained in its size to modify for confounders and they don’t take
account of the collected nature of their data: 98 households, 209 respondents.Our find out about is large
and comprises an increased share of people in quite terrible situations, who are extra possibly to smoke
and much less in all likelihood helpful at renouncing (Bond et al., 2012).
Answer11:
The nine “aspects of association” of Bradford Hill’s criteria are (strength of association, consistency,
specificity, temporality, biological gradient, plausibility, coherence, experiment, and analogy) have been
used to consider endless theorized relationships between working and ecological exposures
and disorder results. For HI and intention to stop smoking the first criteria is Consistency when multiple
epidemiologic research the use of a range of locations, residents, and strategies exhibit a constant
friendship concerning two variables with recognize to the null supposition. Defined that proof is drawn
from investigational control—predominantly epidemiologic readings in disorder hazard regressions
following an intrusion or interruption of exposure—may lead to the toughest help for causal inference.
Termination of exposure as Hill described might additionally no longer contrary or significantly gradual
the development of the ailment. In some circumstances, a couple of danger factors, together with food,
exercise, smoking, biochemical exposures, and genetic tendency can contribute to ailment inception and
advancement. Thus, whilst the mixture of these elements can also end in disease, investigational
handling of a single causative aspect can or no longer result in visible declines in ailment incidence (Bond
et al., 2012).
Answer12:
Providing inhabitants in destitute areas with enhanced housing may additionally inspire residents to
think through leaving smoking. Though, few people without a doubt stop, demonstrating that inhabited
enhancements or modifications to the bodily surroundings were also not enough catalyst for individual
behavioural transformation. It would make wisdom to tie health amenities to housing revival tasks to
maintenance modifications in health behaviours at a period when ecological exchange seems to mark
behavioural modification extra possible (Bond et al., 2012).
Paraphrase This Document
Need a fresh take? Get an instant paraphrase of this document with our AI Paraphraser
References:
Bond, L., Egan, M., Kearns, A., Clark, J. and Tannahill, C. (2012). Smoking and intention to
quit in deprived areas of Glasgow: is it related to housing improvements and neighbourhood
regeneration because of improved mental health?. Journal of Epidemiology and Community
Health, 67(4), pp.299-304.
Bond, L., Egan, M., Kearns, A., Clark, J. and Tannahill, C. (2012). Smoking and intention to
quit in deprived areas of Glasgow: is it related to housing improvements and neighbourhood
regeneration because of improved mental health?. Journal of Epidemiology and Community
Health, 67(4), pp.299-304.
1 out of 8
Your All-in-One AI-Powered Toolkit for Academic Success.
+13062052269
info@desklib.com
Available 24*7 on WhatsApp / Email
Unlock your academic potential
© 2024 | Zucol Services PVT LTD | All rights reserved.