Snap shot Cross-sectional surveys FETP India
Competency to be gained from this lecture Design the concept of a cross-sectional survey
Key areas The concept of a survey Planning a survey Analytical cross-sectional studies
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
Example of systematic sampling Every eighth house is selected
Example of cluster sampling Section 1 Section 2 Section 3 Section 5 Section 4 Preparing a survey
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
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
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 285 456 63% IFA coverage according to health workers IFA consumption according to women 100 days 404 456 89% < 100 days 52 456 11% 90 days 382 456 84% < 90 days 74 456 16% Preparing a survey
Advantages of cross-sectional surveys Fairly quick Easy to perform Less expensive Adapted to chronic / indolent diseases Preparing a survey
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
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
Limitations of causal inference in analytical cross-sectional studies Prevalent cases Exposure and outcome examined at the same time Analytical surveys
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
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