1. Mpundu MKC MSc Epidemiology and Biostatistics, BSc Nursing, RM, RN
Epidemiology MPH 531 AnalyticAL Epidemiology CROSS SECTIONAL STUDIES (SURVEYS)
Mpundu MKC
MSc Epidemiology and Biostatistics, BSc Nursing, RM, RN

2. Observational Studies
1. Cross-sectional Studies (Surveys)
This is a snap shot study in which the exposure and the outcome are assessed
at the same time
At same point in time assess Exposure
(Exposed /Unexposed) and Outcome
( Disease/No disease

3. cross sectional Synonyms
Surveys
Instantaneous study
Prevalence study
Simultaneous study

4. Cross-sectional studies
May be
Descriptive
Analytical or
Both
At descriptive level, it yields information about a single variable, or about each of number of separate variables in a study population
At analytic level, it provides information about the presence and strength of associations between variables, permitting testing of hypothesis

5. Cross-sectional studies
Cross-sectional studies include surveys
Can combine a cross-sectional study with follow-up to create a cohort study.
Can conduct repeated cross-sectional studies to measure change in a population.
By conducting surveys with the same methodology on a periodic basis, detection and analysis of trends over time are possible

6. Cross-sectional studies
Cross-sectional studies are most familiar to us as surveys.
In a cross-sectional study, people are studied at a “point” in time.
Follow-up is not generally a part of the cross- sectional study, though sometimes a cross- sectional study serves as the baseline for a cohort study or intervention trial.

7. cross-sectional studies
Sometimes, cross-sectional studies are carried out repeatedly in the same population(s), so that results can be compared across time and changes observed.
However, the basic cross-sectional design is simply a single survey.
By conducting surveys with the same methodology on a periodic basis, detection and analysis of trends over time are possible

9. cross-sectional studies
a type of observational study
the researcher has no control over the exposure of interest (e.q. diet).
It involves
identifying a defined population at a particular point in time
measuring a range of variables on an individual basis
e.g. include past and current dietary intake
At the same time measuring outcome of interest
e. g. obesity

10. cross-sectional studies
Can measure attitudes, beliefs, behaviours, life style, personal or family history, genetic factors, existing or past health conditions, that does not require follow-up to assess.
The source of most of what we know about the population
Cross-sectional studies measure prevalence of health conditions, exposures, and other characteristics of the population. They provide a “snapshot” or “still life portrait”. The cross-sectional design can be used to measure any factor that can be reported by respondents or assayed noninvasively and that does not require follow-up to assess. Cross-sectional studies are the source of most of what we know about the population

11. Cross-sectional studies
An “observational” design that surveys exposures and disease status at a single point in time (a cross-section of the population)
Cross section al studies are some of the first studies completed because of ease and low cost
Study only exists at this point in time
Single point time

12. cross-sectional studies
Measurement of exposure of interest and outcome of interest is carried out at the same time (e.g. Obesity)
There is no in-built directionality as both exposure and outcome are present in the study subject for quite some time

13. cross-sectional studies
E-unexposed
E+Exposed
O+Disease
O-No disease
At same point in time assess Exposure (E- / E+) and Outcome (O+ / O-)
Prevalence ratio

14. Cross-sectional Studies
Factor present
No Disease
Factor absent
Study
population
Factor present
Disease
Factor absent
Cross-sectional studies examine a point in time
time
Study only exists at this point in time

15. Cross-sectional studies
Concerned with the situation existing at a given time (or during a given period) in a group or population
These may be concerned with:
The presence of disorders such as diseases, disabilities and symptoms of ill health
Dimensions of positive health, such as physical fitness

16. Cross-sectional studies
Cross sectional studies can investigate
Attributes relevant to health such as blood pressure and body measurements
Factors of health & disease such as exposure to specific environmental exposure or defined social & behavioral, life style and demographic attributes
Determining the workload of personnel in a health program as given by prevalence

17. MEASURES IN CROSS-SECTIONAL STUDIES 1 Measures of disease occurrence 2
MEASURES IN CROSS-SECTIONAL STUDIES 1 Measures of disease occurrence 2. Measures of association

18. Measures of Disease Occurrence
Prevalence
Prevalence = number of persons with condition or disease at a given point in time
Prevalence is really a ratio
Numerator = number of persons with disease
Denominator = all persons in population

19. Measures of Disease occurrence
Prevalence can be expressed as:
At a given point in time - eg, January 1st, 2015
Or on entry to university or military service
Or can be for a period or time, eg., prevalence during medical school or a five year period of time

20. Measures of disease association
1. Prevalence Odds Ratio
In a prevalence survey, 60 individuals were found to have diabetes out of 1,000 surveyed
Obesity
Not Obesity
Totals
Diabetes 27 33 60
No Diabetes
200
740
940

21. 1. Prevalence Odds Ratio Prevalence of diabetes total = 6%
Prevalence of diabetes among obese persons = 27/227 = 11.89%
Prevalence of diabetes in non obese persons = 33/773 = 4.3%

22. Measures of disease association
Prevalence Odds Ratio
Express the findings as prevalence odds
i.e., odds of exposure if disease
Obesity
Not Obesity
Totals
Diabetes 27 33 60
No Diabetes
200
740
940

23. 1.Prevalence Odds Ratio Odds of obesity if diabetic
Odds of obesity if not diabetic
= c/d = 200/740 = 0.27
Prevalence odds ratio (POR)
= 0.81/0.27 = 3.0
For cross-sectional or prevalence studies the prevalence odds ratio is the same as the ratio of the prevalence of disease in persons with and without the risk factor

24. Measures of Disease Association 2. Odds Ratios
e.g
60 females with lung cancer = cases
60 females selected without lung cancer = controls
Exposure in question is current smoking
Smokers
Non Smokers
Totals
Lung Cancer (cases) 41 19 60
No lung cancer (controls) 28 32

25. Calculation of Odds Ratio - example
Odds of smoking if cancer
= 41/19 = 2.16
Odds of smoking if no cancer
= 28/32 = 0.875
ODDS RATIO of smoking if lung cancer
= 2.16 / = 2.5

26. Advantages of Cross sectional studies
Cheap and quick and easy to conduct
Data on all variables is collected once.
Can collect data on large number of subjects
Multiple outcomes and exposures can be studied
Good for descriptive analyses and for hypotheses generation

27. Disadvantages of Cross-Sectional Studies
Not suitable for studying rare diseases or outcomes with short duration
Can only measure prevalence estimate of disease (i.e., existing cases of disease)
Un able to estimate the incidence of the disease

28. Disadvantages of Cross-Sectional Studies
The relationship between the cause and the effect cannot be determined.
Cannot determine whether the outcome followed the exposure or exposure resulted from outcome.
which came first? Disease or exposure (Chicken or egg?)

29. Uses of CROSS SECTIONAL studies
The findings may be used to promote the health of the population studied i.e. can be used as tool in community health care
Can contribute to clinical care
Can provide “new knowledge”
The uses are not mutually exclusive & single study can fulfill more than one purpose

30. Uses in community health care
Community diagnosis
Health status
Determinants of health & disease
Association between variables
Identification of groups requiring special care
Surveillance
Community education & community involvement
Evaluation of community’s health care

31. Which came first?
?? Causality