Critical Appraisal Report: Obesity and Depression Studies in PUBH6005

This report presents a critical appraisal of three epidemiological studies investigating the relationship between obesity and depression. The studies include a cohort study by Mulugeta et al. (2018), a case-control study by Koski & Naukkarinen (2017), and a cross-sectional study by Cui et al. (2018). The appraisal assesses each study's methodology, including study design, recruitment, measurement of exposure and outcome, confounding factors, and the generalizability of the results. The report also includes a literature search strategy, keywords, and database selection. Each study is analyzed using a structured appraisal questionnaire, evaluating the strengths and limitations of each study design. The findings are synthesized to provide a comprehensive overview of the evidence linking obesity and depressive symptoms. The report concludes with a discussion of the implications of the studies and the need for further research. The introduction highlights the global prevalence of obesity and depression and their potential correlation. The results section provides detailed appraisals of each study, addressing the research questions, study designs, methods, and findings. The report emphasizes the importance of understanding the methodological rigor and limitations of each study to interpret the evidence accurately. The report is structured to provide a comprehensive and critical evaluation of the selected studies, contributing to a deeper understanding of the complex relationship between obesity and depression.

Part A
Table 1 Cohort Study (Mulugeta, Zhou, Power, & Hyppönen, 2018)
Paper for appraisal and reference: Mulugeta, A., Zhou, A., Power, C., & Hyppönen, E. (2018).
Obesity and depressive symptoms in mid-life: a population-based cohort study. BMC
Psychiatry, 18.
Appraisal
question
Yes No Can’t tell
1. Did the study
address a clearly
focused issue?
The study presents a
focused issue as the title
mentions the population,
intervention. It also
mentions the type of study
that is cohort study, which
helps in search through the
database.
2. Was the cohort
recruited in an
acceptable way?
The data was used
from 1958 British
birth cohort, so, the
recruitment of the
cohort was not done
in an appropriate
manner as it was
done for the purpose
of the study to be
undertaken.
3. Was the
exposure
accurately
measured to
Clinical Interview
Schedule-Revised (CIS-R)
and Mental Health
Inventory − 5 (MHI-5) were

minimise bias? used to investigate the
depressive symptoms. Both
of which have justifiable
validity.
4. Was the outcome
accurately
measured to
minimise bias?
Weight, height and waist
circumference (WC) were
measured by skilled nurses
via Tanita solar scales,
stadiometer and body
tension tape, waist
circumference respectively.
BMI was calculated.
5. (a) Have the
authors
identified all
important
confounding
factors?
Authors took into account
risk sociodemographic and
lifestyle factors and
existence of symptoms of
depression at baseline.
(b) Have they
taken account of
the confounding
factors in the
design and/or
analysis?
Yes confounding factors
such as sex, region, and
social class and various
lifestyle factors were taken
into account.
7. (a) Was the
follow up of
subjects
complete
enough?
Yes
(b) Was the
follow up of
Yes, it followed up for 5
years.

subjects long
enough?
9. What are the
results of this
study?
At 45 years, nearly 25% and
35% respondents were
categorized as having
general obesity and central
obesity, respectively.
Incidence of depression
8.4% at 45 years and 12.4%
at 50 years.
Sociodemographic and
certain lifestyle aspects that
were related to increased
incidence of general and
central obesity were also
related to increased
incidence of depressive
symptoms.
10. How precise are
the results?
Results were precise as per
the CI ranges.
11. Do you believe
the results?
Results are believable as the
support the findings of
previous studies.
12. Can the results
be applied to the
local population?
No, because,
representativeness is
a limitation of the
study as the
demographic
structure of the
current UK
population has more

diversity than
included in this
study. So, the
results may not be
generalizable.
13. Do the results of
this study fit
with other
available
evidence?
Yes, it did correspond with
previous researches.
14. What are the
implications of
this study for
practice?
The study implicates that
while managing depression,
obesity and other lifestyle
factors could be one of the
management approaches.
Table 2 Case control study (Koski & Naukkarinen, 2017)
Paper for appraisal and reference: Koski, H. M., & Naukkarinen, H. (2017). The Relationship
between Depression and Severe Obesity: A Case-Control Study. Open Journal of
Psychiatry, 7(4), 276-293. doi:10.4236/ojpsych.2017.74024
Appraisal question Yes No Can’t tell
1. Did the study address a
clearly focused issue?
The population
included in the
study is retired
individual which
is not mentioned
in the title of the
study.

2. Did the authors use an
appropriate method to
answer their question?
Yes
3. Were the cases recruited
in an acceptable way?
Cases were based
on people who
were getting a
disability pension
because of
obesity.
4. Were the controls
selected in an acceptable
way?
The controls were
chosen by random
sampling and
matched with
cases as per the
residence and sex.
5. Was the exposure
accurately measured to
minimise bias?
A personal
psychiatric
interview and the
Beck Depression
Inventory were
used to measure
the prevalence of
depression.
6. (a) Aside from the
experimental
intervention, were the
groups treated equally?
There is no
mention of non-
experimental
treatment.
(b) Have the authors
taken account of the
potential confounding
factors in the design
The study group
was effectively
matched with the
control group with

and/or in their analysis? matching
occupational and
social statuses.
The impact of the
cases’ life
situation was
minimized as
individuals in the
control group had
also been getting a
pension for the
similar duration.
7. How large was the
treatment effect?
Subject group
demonstrated
increased
diagnosis of
depression as
compared to
control group as
per the psychiatric
interview. On the
basis of
conditional
logistic linear
model, people
having severe
obesity had
increased
likelihood of
depression as
compared to the

individuals in the
control group.
8. How precise was the
estimate of the treatment
effect?
Some cases did
not have specific
variables and the
number of
observations
presented for
comparisons was
lowered further.
People who
refused for
participation in the
study had same
age, level of
education, and sex
distribution as the
people who
participated.
9. Do you believe the
results?
Yes
10. Can the results be applied
to the local population?
No as the sample
size was small.
11. Do the results of this
study fit with other
available evidence?
Yes the available
evidence fits the
findings of the
study
Table 3 Cross sectional study (Cui, et al., 2018)

Paper for appraisal and reference: Cui, J., Sun, X., Li, X., Ke, M., Sun, a., & Yasmeen, N.
(2018). Association Between Different Indicators of Obesity and Depression in Adults in
Qingdao, China: A Cross-Sectional Study. Front Endocrinol (Lausanne), 9.
doi:https://dx.doi.org/10.3389%2Ffendo.2018.00549
1. Did the study address a
clearly focused
question / issue?
Yes. It
mentioned
population,
exposure-
outcome, and
type of study.
The title was
explanatory and
elaborate and the
reader can judge its
usefulness for their
research just by
reading title.
2. Is the study design
appropriate for
answering the research
question?
Yes, as the
research also
aims to identify
various
indicators of
obesity.
This large
population-based
cross-sectional
survey could
examine potential
association between
depression and
various body
weights.
3. Is the method of
selection of the subjects
clearly described?
6,100 adults
between the age
of 35 and 74
years old took
part with a
stratified,
random cluster
sampling
process.
Researchers clearly
mentioned the
procedure they used
for invitation.
4. Could the way the
sample was obtained
No, as
nearly
Care was taken to
prevent or

introduce (selection)
bias?
10% of
participa
nts were
excluded
because
of a poor
Zung
score or
BMI or
WC or
waist-to-
hip ratio
(WHR).
minimize the
introduction of
selection bias by
accounting for the
various weight
level measures.
5. Was the sample of
subjects representative
with regard to the
population to which the
findings will be
referred?
No, as
the study
was
conducte
d on a
comparat
ively
small
sample
size of
the adult
populatio
n in
Qingdao,
China to
which
findings
will be
The study holds the
problem of
representativeness
due to the small
sample size.

referred.
6. Was the sample size
based on pre-study
considerations of
statistical power?
Yes The sample size is
based on pre-study
considerations of
statistical power as
age-standardized
prevalence of
depression was
measured as per
various obesity
parameter for the
age group of 35–74
years, using data
from the 2010
census in Qingdao.
7. Was a satisfactory
response rate achieved?
5,110 people
took part in the
survey, with a
response rate of
83.8%.
The response rate
was satisfactory.
8. Are the measurements
(questionnaires) likely
to be valid and reliable?
The
questionnaire
was designed to
gather basic
information
including age,
gender, marital
status,
educational
level,
occupation,

smoking status,
and alcohol
intake.
9. Was the statistical
significance assessed?
Sensitivity
analysis was
performed on
the basis of the
Asian and
WHO criteria of
obesity.
10. Are confidence intervals
given for the main
results?
Yes
11. Could there be
confounding factors that
haven’t been accounted
for?
Confoun
ding
factors
such as
gender,
age,
hypertens
ion,
diabetes,
resident
districts,
marital
status,
education
al
attainmen
t,
occupatio

nal PA,
smoking
habits,
alcohol
intake,
and
personal
monthly
salary
12. Can the results be
applied to your
organization?
No,
because
the study
was
conducte
d on
comparat
ively
small
sample
size of
the adult
communi
ty in
Qingdao,
China
Part B
Introduction
The incidence of overweight and obesity in 2017, was nearly 39% and 13% in adults aged 18
years and over respectively across the globe (WHO, 2018). WHO estimated that in 2018,