Transcript Cross-sectional study

Cross-sectional study
Yuriko Suzuki, MD, MPH, PhD
National Institute of Mental Health, NCNP
[email protected]
Key issues
• Why research?
• Descriptive study
• Hypothesis testing
• Association
• Sampling
• An example of cross-sectional study
Why research?
• To guide health practice and policy
• Because local research is often needed to guide
local health practice and policy
• Because carrying out research strengthens research
capacity
What is a hypothesis
• A statement which describes what you expect to
find in a specific manner
• Clearly stated
• Testable and refutable
• Not a mere research question or objective
• Backed by sample size calculation, and an
appropriate design and analysis
Example
• Statement of the problem: mental health problems
are said to be common in the aftermath of a
disaster, and mental health problems are believed
to be associated with physical damage
• Aim: to describe the association between physical
damage and mental health problems
• Question: Are mental health problems associated
with physical damage in time of disaster?
• Hypothesis: elderly people with poor mental health
are more likely to have severe housing damage in
time of disaster
Advantages of hypothesisdriven research
• Greater credence given to validity of findings
• Less risk of type I and II errors
o Type I error: mistakenly see association while
there isn’t.
o Type II error: mistakenly see no association while
there is.
• Ease of replication
What do epidemiologists do?
• Describe
o Distribution of health-related states in a population
o Extent, type, severity
o Who, where, when?
• Explain
o Analytical epidemiology
o Hypothesis-driven etiological research
o Risk factors and causes
• Evaluate
o Quasi-experimental studies
o Randomized controlled trials
Association
Risk factor
Exposure
Disease
True association?
Independent
Outcome
Dependent
Chance
Confounding
Bias
Descriptive studies
• Case series
• Cross-sectional study
o Multi-center (geographic variance)
o Ecological correlation
o Repeated surveys (temporal variance)
Who to study?
• Population
• Sample
o Advantage:
• time and cost
o Disadvantages:
• sampling error,
• bias if sample is not representative of population
Random sampling
• Simple
• Systematic
• Stratified
• Multi-stage and cluster
How big a sample?
• Sample size calculation is important to avoid errors
in interpreting findings:
• Type I errors:
o The null hypothesis is rejected when it is in fact,
true (p value)
• Type II errors:
o The null hypothesis is accepted when it is, in fact,
false (power)
Prevalence study
Niigata
•
Suzuki Y, Tsutsumi A, Fukasawa M, et al. Prevalence of mental disorders and
suicidal thoughts among community-dwelling elderly adults 3 years after the
niigata-chuetsu earthquake. J Epidemiol. 21:144-50. 2011
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Earthquakes in Niigata
• In 2004: The NiigataChuetsu earthquake
•
•
•
•
2004.10.23.5:56pm
Magnitude:6.8 in Richter scale
Seismic intensity:7 in Japanese scale
Damage:68 deaths 4805 injuries
• In 2007: The Niigata
Chuetsu-oki earthquake
•
•
•
•
2007.7.16.10:13am
Magnitude:6.8 in Richter scale
Seismic intensity:6 in Japanese scale
Damage:15 deaths 2345 injuries
Prevalence of mental health disorders among community
dwelling elderly three year after the Niigata-Chuetsu
earthquake
1. Face-to-face interviews were conducted to the older people
above 65 in the severely damaged area by the NiigataChuestu earthquake
2. Diagnoses of mental disorder were confirmed using Mini
International Neuropsychiatric Interview (M.I.N.I.), and quality
of life (QOL) were measure by WHOQOL
3. The prevalence and its associated factors were described.
Methods
4. Data collection
Trained health professionals administered the
questionnaires and the following structures interviews;
5. Measurement
A) Diagnosis of mental disorders (M.I.N.I.)
a. Major depression (current, since the earthquake)
b. Minor depression (current, since the earthquake)
c. Suicidal tendency (current, since the earthquake)
d. Posttraumatic stress disorder (current)
e. Alcohol dependence and abuse (current)
B) QOL：WHO/QOL-BREF
a. Physical
b. Psychological
c. Social
d. Environmental
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Results（１）：Flow of the study
(2007.10.1-2008.1.11)
Population of the older adults (65 and over) in the severely
affected areas in Ojiya city (n=902)
Exclusion
Dead (n=42)
Hospitalized (n=20)
Institutionalized( n=15)
Moved out (n=24)
Community-dwelling older adults (n=799)
Unable to interview
Absents (n=27)
Due to disability (hearing, seeing, etc) (n=71)
Refusal to interview (n=215)
Completed interviews (n=496), Completion rate 62.1%
Results（2）
Table 1. Characteristics of participants of the study of three year after the
Niigata-Chuetsu earthquake in 2004 (n=473)
n
%
Mean
95% CI
Gender
Male
190
40.2
Age
65-74
209
44.2
75+
264
55.8
75.4-76.6
Average age
76.0
Marital status
Married
328
69.3
Divorced
3
0.6
Bereaved
140
29.6
Never married
2
0.4
Education
Elementary school
128
27.5
Koutouka
112
24.0
Chugakko
167
35.8
Koukou
20
4.3
Others
8.1-8.4
Numbers of year in education
8.2
3.7-4.1
Number of cohabitant
3.9
Previous psychiatric visit
19
4.3
Digit spam (3 digits)
Incorrect
29
11.2
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Results（3）
I. Prevalence study
Severity of disaster damage
In 2007
In 2004
2% 1%
1%
0%
3%
10%
8%
41%
38%
96%
1
2
3
4
5
6
Total collapse
Mostly collapse
Half collapse
Partial collapse
None
Unknown
1
2
3
4
Half collapse
Partial collapse
None
Unknown
Prevalence of mental disorders in 2 weeks and past 3 years
Results（4）
Prevalence rate (%)
among the older people living in community by gender (n=444)
Male
Female
**:p<0.05
**
10.4
**
**
8.0
7.1
**
6.0
4.7
1.7
0.8
0.6
2w 3y
Major
depression
4.2
4.1
2.4
1.7
1.6
0.0
0.0 0.0
0.0
2w
3y
Major and Minor
depression
3.5
Current PTSD
Earthquake
Other events
0.0
0.0
Current
alcoholdependence, abuse
2w 3y
Suicidal
tendency
Results（5）
The percentage of those who met criterion A and B of PTSD in
DSM-IV-TR by exposure of the earthquake and the other events
A1:Experience
A2:Fear
B:Re-experience
98.7
46.5
36.4
16.0
4.5
Chuetsu earthquake
(n=446) (n=443) (n=245)
1.96
Other events
(n=445) (n=88) (n=51)
Results（7）
3.9
Chart of mean score of 4 subdomains in WHOQOL26
3.8
3.7
Physical
QOL mean
: male 3.54 (95%CI:3.47-3.60)
female 3.48 (95%CI:3.43-3.53)
3.6
Series1
3.5
3.4
Series2
Males, Females
3.3
3.2
Environmental
3.1
Social
Psychological
Results（8）
Results of regression analysis for quality of life and interviewees’ basic
characteristics (n=439)
Variables
Physical
Coef.
Psychologic
al
Coef.
Social
Environmental Mean QOL score
Coef.
Coef.
Coef.
Gender
(male=0, female=1)
-0.05
-0.07
0.07
-0.10
Age
year
-0.01
0.00
0.00
0.00
0.00
0.03
0.01
-0.08
-0.04
0.00
0.02
0.03 *
0.02
Marital status
*
-0.05
(not married=0, married=1)
Number of cohabitants
0.03 **
0.03
Years in education
-0.03
0.00
0.00
-0.01
-0.01
Previous psychiatric visit
-0.13
-0.03
-0.06
0.04
-0.03
-0.03
-0.04
-0.03
-0.04
*
(never=0, yes=1)
Severity of disaster damage -0.05
in 2004
*
Physical illness
-0.29 **
-0.17 **
-0.01
0.00
Intercept
Adjusted R2
4.9
0.060
3.6
0.022
4.1
0.003
3.6
0.015
*:p<0.05, **:p<0.01
*
-0.15 **
3.9
0.034
Discussion（1）
• Prevalence of major depression and PTSD was lower than
previous researches in disaster settings in other countries（6.411%, 4.4-25% respectively in literature）.
• The prevalence of major depression since the earthquake was
4.4%, within the range of the prevalence in non-disaster
community studies (0.9-9.4% in literature).
• Among males, the alcohol related problems were reported in
6.0% and among females, major or minor depression were
reported in 10.0%, and suicidal tendency were seen in 8.0% of
the interviewees.
• Pathological level→about same level as usual
• Subclinical level → require further attention to promote their
mental health
Discussion（2）
• In general, having fewer cohabitants, and greater degree of
disaster damage, and any physical illness were attributing to the
worse quality of life.
• The risk factors for poor QOL were severity of disaster damage,
and physical illness in physical domain, fewer cohabitants and
physical illness in psychological domain, being female, and fewer
cohabitants in environmental domain.
• Mental health and physical health care would be better if
provided hand in hand, and social support persistently had
favorable effects on QOL among disaster affected elderly
people.