1. Snap shot Cross-sectional surveys FETP India

2. Competency to be gained from this lecture Design the concept of a cross-sectional survey

3. Key areas The concept of a survey Planning a survey Analytical cross-sectional studies

4. Definition of a survey Oxford English Dictionary  The act of viewing/examining / inspecting in detail especially for some specific purpose Merriam Webster Online Dictionary  To query (someone) in order to collect data for the analysis of some aspect of a group or area Abrahmson  An investigation in which information is systematically collected, but in which the experimental method is not used Concept of survey

5. Survey: The epidemiological concept Observation of a cross-section of a population at a single point in time  Unit of observation and analysis: The individual Usually conducted to collect information about prevalence  Also known as “prevalence studies” No independent reference groups May be repeated:  Surveillance of risk factors for cardio-vascular diseases Concept of survey

6. Examples of research questions that can be addressed through a survey What is the prevalence of hypertension in Chennai? What is the prevalence and distribution of known risk factors for cardio-vascular diseases in rural Tamil Nadu? How satisfied are patients attending government hospitals in Chennai? Concept of survey

7. Uses of cross-sectional surveys in public health Estimate prevalence of disease or their risk factors Estimate burden Measure health status in a defined population Plan health care services delivery Set priorities for disease control Generate hypotheses Examine evolving trends  Before / after surveys  Iterative cross-sectional surveys Concept of survey

8. The place of surveys among other study designs Observational  Not interventional Cross-sectional in logistic  The logic maybe cross-sectional or retrospective Concept of survey

9. Disease Exposure to potential risk factors Practices  Dietary intake  Costs and utilization of health care services  Healthy / unhealthy behaviours  Physiologic measurements Collection of information on prevalence during a survey Concept of survey

10. Collection of information on incidence during a survey The logistic of the survey is always cross- sectional The logic maybe retrospective to estimate retrospective incidence  Village visit to estimate the retrospective incidence of measles  Retrospective cohort the day following a food poisoning Concept of survey

11. Important considerations in planning cross-sectional surveys 1.Study objectives 2.Study population 3.Analysis plan 4.Information to collect 5.Data collection methods 6.Sampling methods 7.Sample size 8.Data recording and processing Preparing a survey

12. 1. Potential objectives of a cross-sectional study Descriptive  Estimate prevalence Analytic  Compare the prevalence of a disease in various subgroups, exposed and unexposed  Compare the prevalence of an exposure in various subgroups, affected and unaffected Preparing a survey

13. 2. Populations that may be studied with a survey General  District survey  National survey Specific  School survey  Institutional survey  Populations with specific behaviours (e.g., injection drug users) or characteristics (e.g., diabetic patients) Preparing a survey

14. 3. Analysis plan for a survey Define the indicator needed Identify the information needed to calculate the indicator Example: Dental caries indicators require information on:  Number of permanent teeth decayed  Number of teeth missing  Number of teeth filled Preparing a survey

15. 4. Information to collect: Operational definitions Need precision to reduce inter-observation variability Examples of definitions of obesity  A weight, in under clothes without shoes which exceeds by 10% or more of standard weight for age, height in a specified population  Sex and a skin fold thickness of 25mm or more, measured with a Harpenden skinfold caliper at the back of the right upper arm, midway between the tip of the acromial process and tip of the olecranon process Preparing a survey

16. 5. Data collection methods during a survey Interviews  Phone interview, direct interview Record reviews  Medical records for nosocomial infection survey Structured observations  E.g., Health care facility surveys to describe health care delivery Measurements (e.g., WHO STEPWISE approach)  Anthropometry (e.g., height and weight)  Biological measurements (e.g., blood tests) Preparing a survey

17. 6. Sampling strategies during a survey Simple random sampling  Sampling frame available  Study participants selected at random Systematic sampling  Sampling frame organized sequentially  Selection of every n th individual Cluster sampling  Selection of clusters / communities with a probability proportional to population size  Selection of an equal number of individuals within each cluster / community Preparing a survey

18. Example of simple random sampling Numbers are selected at random

19. Example of systematic sampling Every eighth house is selected

20. Example of cluster sampling Section 4 Section 5 Section 3 Section 2Section 1 Preparing a survey

21. 7. Sample size for a survey Use formula / software Parameters:  Expected frequency  Prevision  Confidence level Need to double sample size if comparisons required:  Before / after  Exposed / unexposed (analytical survey) Preparing a survey

22. 8. Data recording /processing Establish the structure of the database  Unique level  Multiple levels Village Household Individual Set up relational link between databases if required Preparing a survey

23. Example of survey results NumberTotalPercentage Hb < 11 g/dl28545663% IFA coverage according to health workers 100 days40445689% < 100 days5245611% IFA consumption according to women 90 days38245684% < 90 days7445616% Anemia and use of iron/ folic acid (IFA) tablets among pregnant women, Dhenkanal district, Orissa, India, 2004 Preparing a survey

24. Advantages of cross-sectional surveys Fairly quick Easy to perform Less expensive Adapted to chronic / indolent diseases Preparing a survey

25. Limitations of cross-sectional surveys Limited capacity to document causality (exposure and outcome measured at the same time) Not useful to study disease etiology Not suitable for the study of rare / short diseases Not adapted to severe / acute diseases  NEYMAN BIASE Not adapted to incidence measurement Preparing a survey

26. IllNon-illTotal Exposedaba+b Non-exposedcdc+d Totala+cb+da+b+c+d Presentation of the data of an analytical cross-sectional study in a 2 x 2 table Known simultaneously when the study is completed Analytical surveys

27. Limitations of causal inference in analytical cross-sectional studies Prevalent cases Exposure and outcome examined at the same time Analytical surveys

28. Measuring association in analytical cross-sectional surveys Prevalence ratio Prevalence among exposed / prevalence among unexposed Formula equivalent to risk ratio Concept different  No incidence  Only prevalence

29. Take home messages Surveys are a snap shot that can look back or compare to generate hypotheses Surveys require careful preparation and detailed protocol writing Analytical cross-sectional surveys require (1) double sample size and (2) caution in interpretation