Snap shot. Cross-sectional surveys. FETP India

Transcription

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 Collection of information on prevalence during a survey Dietary intake Costs and utilization of health care services Healthy / unhealthy behaviours Physiologic measurements Concept of survey

10 Collection of information on incidence during a survey The logistic of the survey is always crosssectional 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 1 Albert D. 2 Richard D. 3 Belle H. 4 Raymond L. 5 Stéphane B. 6 Albert T. 7 Jean William V. 8 André D. 9 Denis C. 10 Anthony Q. 11 James B. 12 Denis G. 13 Amanda L. 14 Jennifer L. 15 Philippe K. 16 Eve F. 17 Priscilla O. 18 Frank V.L. 19 Brian F. 20 Hellène H. 21 Isabelle R. 22 Jean T. 23 Samanta D. 24 Berthe L. Numbers are selected at random 25 Monique Q. 26 Régine D. 27 Lucille L. 28 Jérémy W. 29 Gilles D. 30 Renaud S. 31 Pierre K. 32 Mike R. 33 Marie M. 34 Gaétan Z. 35 Fidèle D. 36 Maria P. 37 Anne-Marie G. 38 Michel K. 39 Gaston C. 40 Alain M. 41 Olivier P. 42 Geneviève M. 43 Berthe D. 44 Jean Pierre P. 45 Jacques B. 46 François P. 47 Dominique M. 48 Antoine C.

19 Example of systematic sampling Every eighth house is selected

20 Example of cluster sampling Section 1 Section 2 Section 3 Section 5 Section 4 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 Anemia and use of iron/ folic acid (IFA) tablets among pregnant women, Dhenkanal district, Orissa, India, 2004 Number Total Percentage Hb < 11 g/dl % IFA coverage according to health workers IFA consumption according to women 100 days % < 100 days % 90 days % < 90 days % 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 Presentation of the data of an analytical cross-sectional study in a 2 x 2 table Ill Non-ill Total Exposed a b a+b Non-exposed c d c+d Total a+c b+d a+b+c+d 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