1. CROSS SECTIONAL STUDY

2. 2. 1. Define the problem 2. Specify the objectives 3. Select design or type of study 4. Select study population 5. Collect data 6. Analyze data 7. Determine conclusions Anatomy of Research

3. Study Design: Definition Study Design: Definition The procedures and methods, predetermined by an investigator, to be adhered to in conducting a research project Methods used to obtain valid data to answer a research question (or prove/refute a hypothesis) 3

4. Study designs Observational Descriptive Case-reports Case-series Cross-sectional Analytical Case-Control Cohort Experimental Clinical Trials Community Trials

5. 5 Relative strength of various study designs (based on level of evidence for a cause & effect relationship) Strength Design Strong Clinical trial Cohort study Case control study Cross sectional Case series Weak Case report

6. Ecological studies Cross-sectional studies Retrospective cohort study Prospective cohort study Case control study Randomized controlled trial Statistically stronger More limited answers Statistically weaker Broader answers

7. Hierarchy of Evidence Systematic Review & Meta-analysis Randomised Controlled Trials Analytical Studies Descriptive Studies

8. A cross-sectional studies – a type of observational study – the investigator 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 basise.g. include past and current dietary intake – At the same time measuring outcome of interest e. g. obesity Measurement of exposure of interest and outcome of interest is carried out at the same time (e.g. Obesity and Hypertension) There is no in-built directionality as both exposure and outcome are present in the study subject for quite some time

9. Deals 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 –Other attributes relevant to health such as blood pressure and body measurements –Factors a/w health & disease such as exposure to specific environmental exposure or defined social & behavioral attributes and demographic attributes –Determining the workload of personnel in a health program as given by prevalence

10. 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

11. Essential feature of cross-sectional studies -They collect information relating to a single specified time But, often extended to include historical information which leads to demonstration of statistical associations with past experience e.g. investigation of an epidemic Temporal association

12. Steps of cross–sectional study

14. Choose the problem & analyse it Important steps: – Problem identification – Prioritize the problem – Analyze the problem to convert it in “Research Question” Specific Measurable Realistic Time bound Questions to ask: – What is the problem? – Why should it be studied?

15. Literature review What information is already available? Helps you understand and analyze the problem – Is it the same thing which is bothering me? – Uncertainty about a health issue that the investigator wants to resolve Helps you to frame SMART research question

16. FINER RQ FINER RQ Feasible –Adequate number of subjects –Adequate technical expertise –Adequate resources (time & money) Interesting to investigator Novel –Confirms or refutes previous findings –Extends previous findings Provides new findings Ethical Relevant –For scientific knowledge –For policy implications –For future research directions

17. Research methodology Questions to be asked: – What data do we need to meet our objectives? – How will I get this? – How will it be collected? Elements: – Study population – Study subjects – Sampling & Sample size Variables – Data collection instruments & techniques & plan – Data management – data processing & analysis – Ethical clearance – Piloting

18. Choosing the study subject Good choice of study subjects serves the vital purpose of assuring that the findings in the study accurately represent what is going on in the population – Sample of subjects which are affordable in time & money, – yet it is large enough to control random error in generalizing the study findings to the population – and representative enough to control systematic error in these inferences

19. Sampling methods Probability sampling – Simple random sampling – Systematic sampling – Stratified random sampling – Cluster sampling Non-probability sampling – Consecutive sampling – Convenience sampling – Purposive (Judgmental) sampling

20. One sample situation : A. Proportion Estimating a population proportion with specified precision – Absolute – Relative Hypothesis test for population proportion B. Mean Estimating a population mean with specified precision Estimating sample size with unknown mean Hypothesis test for population mean Two sample situation A. Proportions Estimating difference between two population proportions with specified precision Hypothesis test for two population proportions B. Means Estimating difference between two population means with specified precision Hypothesis test for two population means

21. Sample size Absolute N=Z2p(1-p)/d2 Relative – N=Z2p(1-p)/e2p Hypothesis test – N={Z1- α * sqrt[p0(1-p0)+ Z1- β * sqrt[pa(1- pa)]}2/(p0-pa)2 Note – Replace α by α /2 for two tailed hypothesis

22. variables variables Type of variable characteristicexampleAppropriate statistics Information content & power NominalUnordered categories Sex, blood group Counts rate proportion, RR, chi square low OrdinalOrdered categories with interval Degree of pain Above & median rank correlation Intermediate Continuous or discrete Ranked spectrum with quantifiable intervals Weight, number, cigarettes /day Mean, SD t- test, ANNOVA high

23. Data collection  Data collection instrument  Data collection plan  Quality check plan

24. Data collection instrument / Questionire /interview schedule General: –Brief description of purpose of study –Instructions specifying how to fill –Group the questions concerning major subject area under a short heading –Warm-up questions Open-ended & close-ended questions Instrument format –Format should make it as easy as possible for filling and avoiding data entry confusions Wording –Clarity, simplicity, neutrality, double-barreled questions, time frame Codes, scores and scales

25. Steps in designing questionire Make a list of variables Borrow from other instruments Write a draft Revise Pretest Shorten and revise again Precode

26. Precision & accuracy PrecisionAccuracy DefnThe degree to which the variable has same value when measured several times the degree to which a variable actually represents what is supposed to represent Best way to assessComparing among repeated measures Comparison with a reference standard Value of study increase power to detect effects Increase validity of conclusion Threatened byRandom errorSystemic error

27. Sources of error Systematic error (bias): –Confounding bias: Lack of comparability between the exposed & unexposed with regards to other factors that affect the risk of developing the disease –Misclassification bias: Errors in the classification of subjects according to exposure or disease – interviewer bias, response bias, recall bias –Selection bias: Selection of subjects or their participation in the study is influenced by the disease under study – Sample bias – non-representative sample selection – Non-response bias – Non-participant bias – Berkson’s bias – Membership bias Random error (chance): Uncertainty introduced by small number of observatio ns

28. Strategies in dealing with systemic error Confounding bias: –Restriction –Matching –Stratified analysis/Multivariate analysis Misclassification bias: –Blinding –Minimal gap between theoretical and empirical definition of exposure/disease Selection bias: –Population should be defined independently of disease of interest –All information on the subjects should be secured to avoid selective loss of information –Prevent loss to follow-up

29. Uses of cross sectional study 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. Guideline for critical appraisal of prevalence study 1. Are the study design & sampling method appropriate for the RQ? 2.Is the sampling frame appropriate? 3.Is the sample size adequate? 4.Are objective, suitable and standard criteria used to measure the health outcome? 5.Is the health outcome measured in unbiased manner? 6.Is the response rate adequate? Are the refusers described? 7.Are the estimates of prevalence given with CI & in detail by subgroup – if appropriate? 8.Are the study subjects and the setting described in detail and similar to those of interest to you?

32. Cross sectional study advantage Cheap and quick studies. Data is frequently available through current records or statistics. Ideal for generating new hypothesis

33. Cross sectional study Disadvantage The importance of the relationship between the cause and the effect cannot be determined. Temporal weakness: – Cannot determine if cause preceded the effect or the effect was responsible for the cause. – The rules of contributory cause cannot be fulfilled.

35. Choice of strategy Choice of strategy

36. Advantage & disadvantage of different observational study design Ecological study Cross sectional Case control cohort Probability of Selection biasNAmediumHighlow Recall biasNAhigh low Loss to follow up NA lowhigh confoundingHIGHmedium low Time required LOWmedium high costLOWmedium high

37. Reference Oxford Textbook of Public health, Fourth Edition, oxford university press. Rajivir Bhalwar Text Book of Public Health and Community Medicine. Study design options in epidemiological research at MGIMS Sevagram 2011.