Data Interpretation

1
Data Interpretation

2
Objectives

• To describe interpretation of epidemiological
  data
• To classify the sub-group analysis based on
  hypothesized
• -exposure/risk/determinant with the
  -outcome/factor per study objectives
• To apply the type of measure of disease
  occurrence and association

3
Measurements in epidemiological study

• Main ideas and concepts
• What is being assessed?
• What are we answering?
• What variables are included?
• Calculations / Understanding ?

4
Data analysis

• Place your objectives in front of you
• Characterize the items you have mentioned in
  objective (to determine.) by the variables that
  are determining
• Prevalence (mainly the 3rd yr studies are to
  determine prevalence of KAP or any other factor
• determinants as hypothesized that any two
  factors will be associated
• Outcome as hypothesized
• List the variables / determinant /sub-groups that
  will be compared

5
Methods Review your methods and data

• Study design does it justify to the research
  question?
• Study setting internal and external validity
  concerns?
• Sampling / inclusion / exclusion criteria
  selection biases?
• Subjects demographic, socioeconomic
  characteristics selection bias?
• Variables clarity of defining exposure, outcome,
  other variables?
• Data management information bias how data were
  managed?
• Data collection questions vague, missing
  information?
• Measurement error instruments calibrated data
  collectors trained?
• Statistical methods summary statistics given
  appropriate statistical tests used?

6
Epidemiological Study design

• Cross sectional study design
• Be cautious about associations between factors
  and risks and outcomes
• As exposure and outcome are collected at the same
  time terms like being overweight is a risk for
  an outcome arthritis when data for weight and
  arthritis were collected at the same time.
• Use risk in case control, cohort
  experimental studies

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Selection of Study Participants Examples
(review selection criteria to assess
representativeness)

• Participants in the Womens Health Study were a
  random sample of all women ages 55 to 69 years
  derived from the state of Iowa automobile
  drivers license list in 1985, which represented
  approximately 94 of Iowa women in that age
  group....
• We aimed to select 5 controls for every case
  from among individuals in the study population
  who had no diagnosis of autism or other pervasive
  developmental disorders (PDD) recorded in their
  general practice record and who were alive and
  registered with a participating practice on the
  date of the PDD diagnosis in the case.

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Variables Example

• Only major congenital malformations were
  included in the analyses. Minor anomalies were
  excluded according to the exclusion list of
  European Registration of Congenital Anomalies
  (EUROCAT).
• If a child had more than 1 major congenital
  malformation of 1 organ system, those
  malformations were treated as 1 outcome in the
  analyses by organ system ...
• In the statistical analyses, factors considered
  potential confounders were maternal age at
  delivery and number of previous parities. Factors
  considered potential effect modifiers were
  maternal age at reimbursement for antiepileptic
  medication and maternal age at delivery

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Data Sources/Measurement Example

• Total caffeine intake was calculated primarily
  using U.S. Department of Agriculture food
  composition sources. In these calculations, it
  was assumed that the content of caffeine was 137
  mg per cup of coffee, 47 mg per cup of tea, 46 mg
  per can or bottle of cola beverage, and 7 mg per
  serving of chocolate candy. This method of
  measuring (caffeine) intake was shown to be valid
  in both the NHS I cohort and a similar cohort
  study of male health professionals...
  Self-reported diagnosis of hypertension was found
  to be reliable in the NHS I cohort
• Samples pertaining to cases and controls were
  always analyzed together in the same batch and
  laboratory personnel were unable to distinguish
  among cases and controls

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Measures of disease occurrence Prevalence
Comparison of smoking consumption pattern of KSU
students 2009
Source Mandil A. Bin Saeed AA, Ahmed S,
Al-Dabbagh R, AlSaadi M, Khan M. Smoking among
university students A gender analysis Journal of
Infection and Public Health (2010) 3, 179187
Explain the descriptive characteristics in data
11
Descriptive data
SDStandard Deviation
Source Humayun Q, Iqbal R, Azam I, Siddiqui AR,
Khan A, Baig-ansari N. Development and validation
of sunlight exposure measurement (SEM-Q) in
adult population residing in Pakistan. BMC Public
Health 2012, 12421 doi10.1186/1471-2458-12-421
12
Sun Exposure tested by interview /questionnaire
and comparison with Serum Vitamin D levels and
Source Humayun Q, Iqbal R, Azam I, Siddiqui AR,
Khan A, Baig-ansari N. Development and validation
of sunlight exposure measurement (SEM-Q) in
adult population residing in Pakistan. BMC Public
Health 2012, 12421 doi10.1186/1471-2458-12-421
13
Comparison of age and pretreatment ALT and
Alpha-fetoprotein tests in HCV patients with
high and low grades of inflammation on liver
biopsy.
Statistical Tests aChi Square b Students t
test, c Mann Whitney Test
ALTAlanine transaminase
Source Mirza S, Siddiqui AR, Hamid S, Umar M,
Bashir S. Extent of liver inflammation in
predicting response to Interferon alpha
Ribavirin in chronic hepatitis C patients a
cohort study Journal BMC Gastroenterology 2012
Jun 141271. doi 10.1186/1471-230X-12-71.
14
Mean pretreatment ALT at various liver
inflammation grades
Source Mirza S, Siddiqui AR, Hamid S, Umar M,
Bashir S. Extent of liver inflammation in
predicting response to Interferon alpha
Ribavirin in chronic hepatitis C patients a
cohort study Journal BMC Gastroenterology 2012
Jun 141271. doi 10.1186/1471-230X-12-71.
15
Mean levels of pretreatment ALT by inflammation
grades in males females
Source Mirza S, Siddiqui AR, Hamid S, Umar M,
Bashir S. Extent of liver inflammation in
predicting response to Interferon alpha
Ribavirin in chronic hepatitis C patients a
cohort study Journal BMC Gastroenterology 2012
Jun 141271. doi 10.1186/1471-230X-12-71.
16
Correlation Increase in mean ALT with increase
in liver inflammation grades
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Measure of association

• Risk Factors for Diarrhea in Children less than
  5 years in Low-income Settlements in Karachi
• A case control study
• Cases children lt5 years with diarrhea/dysentery
• Controls healthy children matched to cases on
  age and gender from the same community

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Inclusion Criteria

• CASE
• Diarrhea1, or Dysentery2 of lt7day
• No antibiotic use within the last 7 days of
  enrolment
• Moderate-to-severe diarrhea, defined as at least
  one of the following
• a. Sunken eyes, more than normal
• b. Loss of skin turgor
• c. Intravenous rehydration administered or
  prescribed

• CONTROL
• No diarrhea within 7 days of enrollment
• Should not have taken antibiotics in the previous
  one week
• Age, gender and neighborhood matched to index
  case
• Concomitant within 14 days of presentation of
  the index case

1Defined as 3 or more abnormally loose stools
during the previous 24 hours. 2 Presence of blood
in stools
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Household characteristics of diarrhea of cases
and controls
Household characteristics Cases (n 154) n () Cases (n 154) n () Controls (n 268) n () OR (95 CI)
Socio-economic status Socio-economic status Socio-economic status Socio-economic status
First tertile (upper) 47 (30.5) 99 (37) 99 (37) 1
Second tertile (middle) 58 (37) 99 (38) 99 (38) 1.3 (0.8-2.2)
Third tertile (lower) 49 (32) 70 (26) 70 (26) 1.5 (0.9-2.5)
Caretakers educational status Caretakers educational status Caretakers educational status Caretakers educational status
No school education 65 (42) 142 (53) 142 (53) 1
Primary education 27 (17.5) 63 (24) 63 (24) 0.9 (0.5-1.5)
Secondary education 17 (11) 19 (7) 19 (7) 0.9 (0.5-1.5)

Crowding index 5.6 (4.6) 5.3 (3.5) 5.3 (3.5) 1.0 (0.9-1.1)
Mean no. of children lt 5 years in HH ( SD) 2.25 ( 1.2) 2.42 (1.9) 2.42 (1.9) 0.9 (0.8-1)
Wealth index index based on proportionate
weighted sum of household assets Number of
people in HH / Number of rooms in HH
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Water and sanitation practices in the household
of children with diarrhea and asymptomatic
matched controls.
Water and sanitation practices Cases (n 154) n () Controls (n 268) n () Controls (n 268) n () Unadjusted OR (95 CI)
Water source in last 2 weeks Water source in last 2 weeks Water source in last 2 weeks Water source in last 2 weeks
Piped water 87 (56.5) 87 (56.5) 156 (58) 1
Bought / tanks 51 (33) 51 (33) 76 (28.4) 2.6 (0.9-8.0)
Public tap/ rain water/ borehole 11 (7) 11 (7) 9 (3.3) 1.3 (0.7-2.6)
Other sources 5 (3.2) 5 (3.2) 27 (10) 0.3 (0.1-0.9)
Fetch drinking water everyday Fetch drinking water everyday Fetch drinking water everyday Fetch drinking water everyday
No 48 (31) 50 (18.6) 50 (18.6) 1.81 (0.94-3.51)
Yes 27 (17.5) 51 (19) 51 (19) 1
sometimes 79 (51) 166 (62) 166 (62) 0.90 (0.51-1.60)
Untreated drinking water given to child in last 2 weeks Untreated drinking water given to child in last 2 weeks Untreated drinking water given to child in last 2 weeks Untreated drinking water given to child in last 2 weeks
No 110 (71) 199 (74.5) 199 (74.5) 1
Yes 44 (29) 68 (25.5) 68 (25.5) 1.1 (0.7-1.7)
p0.055 (not significant interpretation?
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contd Water and sanitation practices in the
households of study participants
Cases (n 154) n () Controls (n 268) n () Unadjusted MOR (95 CI)
Treatment of drinking water Treatment of drinking water Treatment of drinking water
Yes 82 (53) 110 (41) 1
No 72 (46.7) 157 (59) 1.9 (1.2-3)
Sometimes 6 (4) 10 (4) 2.4 (0.6-10)
Method used to treat drinking water Method used to treat drinking water Method used to treat drinking water
Boil 46 (30) 74 (27) 1
Leave in the sun/alum 2 (1.3) 8 (2.6) 0.5 (0.1-2.6)
Filtration (cloth/ other filters) 38 (25) 30 (11.2) 2.7 (1.3-5.7)
No treatment 68 (44) 156 (58) 0.6 (0.4-1)
Method of stool disposal Method of stool disposal Method of stool disposal
Toilet 112 (73) 164 (62) 1
Bury / scatter in yard 13 (8) 14 (5) 1.4 (0.6-3.3)
Bush /open sewer /field 29 (19) 88 (33) 0.4 (0.2-0.7)
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Finalizing data analysis

• Writing an abstract

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Predicting tobacco use among high school students
by using the global youth tobacco survey in
Riyadh, Saudi Arabia.
Time
Eligible persons
Good response-low selection bias
Place/setting

• OBJECTIVE To identify the predictors that lead
  to cigarette smoking among high school
• students by utilizing the global youth tobacco
  survey in Riyadh, Kingdom of Saudi Arabia
• (KSA). METHODS A cross-sectional study was
  conducted among high school students
• (grades 10-12) in Riyadh, KSA, between April 24,
  2010, and June 16, 2010. RESULTS The
• response rate of the students was 92.17. The
  percentage of high school students who had
• previously smoked cigarettes, even just 1-2
  puffs, was 43.3 overall. This behavior was more
• common among male students (56.4) than females
  (31.3). The prevalence of students
• who reported that they are currently smoking at
  least one cigarette in the past 30 days was
• 19.5 (31.3 and 8.9 for males and females,
  respectively). "Ever smoked" status was
• associated with male gender (OR 2.88,
  confidence interval CI 2.28-3.63), parent
• smoking (OR 1.70, CI 1.25-2.30) or other
  member of the household smoking (OR 2.11, CI
• 1.59-2.81) who smoked, closest friends who
  smoked (OR 8.17, CI 5.56-12.00), and lack of
• refusal to sell cigarettes (OR 5.68, CI
  2.09-15.48). CONCLUSION Several predictors of
• cigarette smoking among high school students were
  identified.

Vague predictor Who is selling?
Outcomes Defined clear Low information bias
Predictors shown by data OR, 95 CI
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EXERCISE SELF WORK
25
Massive outbreak of viral gastroenteritis
associated with consumption of municipal drinking
water in a European capital city.

• On 24 August 2008, an outbreak alert
  regarding cases of acute gastroenteritis in
  Podgorica triggered investigations to guide
  control measures. From 23 August to 7 September,
  1699 cases were reported in Podgorica (population
  136000) an estimated size of the outbreak is
  about 10000-15000 corresponding to an attack rate
  of 10. We conducted an age-and
  neighborhood-matched case-control study,
  microbiologically analyzed fecal and municipal
  water samples and assessed the water distribution
  system. All cases (83/83) and 90 (89/90) of
  controls drank un-boiled chlorinated municipal
  water matched odds ratio (mOR) 112, 95
  confidence interval (CI), l6-8. Consumption of
  bottled water was inversely associated with
  illness (mOR 03, 95 CI 0.1-0.8). Analyses of
  fecal samples identified six norovirus génotypes
  (21/38 samples) and occasionally other viruses.
  Multiple defects in thè water distribution System
  were noted. These results suggest that the
  outbreak was caused by fecally contaminated
  municipal water. It is unusual to have such a
  large outbreak in a European city especially when
  the municipal water supply is chlorinated.
  Therefore, it is important to establish effective
  multiple-barrier water-treatment Systems whenever
  possible, but even with an established
  chlorinated supply, sustained vigilance is
  central to public health.

26
Massive outbreak of viral gastroenteritis
associated with consumption of municipal drinking
water in a European capital city.
Time
Affected population
Setting/place
Design

• On 24 August 2008, an outbreak alert regarding
  cases of acute gastroenteritis in Podgorica
  triggered investigations to guide control
  measures. From 23 August to 7 September, 1699
  cases were reported in Podgorica (population
  136000) and we estimated the total size of the
  outbreak to be 10000-15000 corresponding to an
  attack rate of 10. We conducted an age-and
  neighbourhood-matched case-control study,
  microbiologically analysed faecal and municipal
  water samples and assessed the water distribution
  System. All cases (83/83) and 90 (89/90) of
  controls drank unboiled chlorinated municipal
  water matched odds ratio (mOR) 112, 95
  confidence interval (CI), l6-8. Consumption of
  bottled water was inversely associated with
  illness (mOR 03, 95 CI 0.1-0.8). Analyses of
  faecal samples identified six norovirus génotypes
  (21/38 samples) and occasionally other viruses.
  Multiple defects in thè water distribution System
  were noted. These results suggest that the
  outbreak was caused by faecally contaminated
  municipal water. It is unusual to have such a
  large outbreak in a European city especially when
  the municipal water supply is chlorinated.
  Therefore, it is important to establish effective
  multiple-barrier water-treatment Systems whenever
  possible, but even with an established
  chlorinated supply, sustained vigilance is
  central to public health.

Attack rate
H0
Not clear ?
Lab results
Predictors shown by data OR, 95 CI