Cross-Sectional Study.pptx

A cross-sectional study is a descriptive study in which disease and exposure status are measured simultaneously in a given population.
It measures
the prevalence of health outcomes(also called prevalence study)
or determinants of health,
or both,
In a population at a point in time or over a short period.
When the investigator draws a sample out of the study population of interest and examines all the subjects to detect
those having the disease/outcome
and those not having this disease/outcome of interest.
At the same time, finds out whether or not they have the presence of
the suspected cause (exposure)
(or give a History of such exposure in the past),
is called the Cross-sectional analytic study.

1. CROSS-SECTIONAL STUDY 1 Professor Dr. AB Rajar, MBBS, Dip-Diab, MPH, Ph.D. CPHE Director of Research and Innovative Center [IBN-E-SINA UNIVERSITY] 5/18/2023 Professor Dr AB Rajar

2. LEARNING OBJECTIVES At the end of this lecture the participants will be able: Define CSS & describe the purpose & types of CSS. Discuss in detail the steps of CSS with respective examples. Calculate the Prevalence rate, ratio, Odds ratio 2 5/18/2023 Professor Dr AB Rajar

3. Examples of CSS We can carry out a cross-sectional survey to estimate the Knowledge and Education about Artificial Intelligence among Medical & Dental Students at Muhammad Medical & Dental College, MPK. Attitudes Toward Cheating of Self and Others by College Students and Professors. Knowledge and Awareness about Genetic Problems Associated with Consanguineous Marriages among Medical & Dental Students. Associations between empathy and big five personality traits among undergraduate medical students. 3 5/18/2023 Professor Dr AB Rajar

4. CLASSIFICATION 4 5/18/2023 Professor Dr AB Rajar

5. HIERARCHY OF EVIDENCE 5 5/18/2023 Professor Dr AB Rajar

6. CROSS-SECTIONAL STUDY. A cross-sectional study is a descriptive study in which disease and exposure status are measured simultaneously in a given population. It measures the prevalence of health outcomes (also called prevalence study) or determinants of health , or both , In a population at a point in time or over a short period . 6 5/18/2023 Professor Dr AB Rajar

7. CROSS-SECTIONAL STUDY. When the investigator draws a sample out of the study population of interest and examines all the subjects to detect those having the disease/outcome and those not having this disease/outcome of interest . At the same time, finds out whether or not they have the presence of the suspected cause (exposure) (or give a History of such exposure in the past), is called the Cross-sectional analytic study. 7 5/18/2023 Professor Dr AB Rajar

8. CROSS-SECTIONAL STUDY. Cross-Sectional Studies • A type of observational study • The investigator has no control over the exposure of interest. • It involves identifying a defined population at a particular point in time At the same time, measuring the outcome of interest e.g. obesity. measuring a range of variables on an individual basis including past and current exposure. Measure the prevalence of disease and thus are often called prevalence studies . 8 5/18/2023 Professor Dr AB Rajar

9. SYNONYMS Survey Snap-shot Prevalence study 9 5/18/2023 Professor Dr AB Rajar

10. PURPOSES OF CROSS-SECTIONAL STUDY They provide clues to disease etiology and help in the formulation of an etiological hypothesis They provide background data for planning, organizing, and evaluating preventive and curative services by disease surveillance . They contribute to research by describing variations in disease occurrence by time, place, and person They provide data regarding the magnitude of disease load and types of disease problems in the community regarding morbidity and mortality rates and ratios. 10 5/18/2023 Professor Dr AB Rajar

11. CROSS-SECTIONAL STUDY May be – Descriptive – Analytical or – Both At the descriptive level: To describe the frequency and characteristics of the observed health-related phenomena at a certain point in time or It yields information about a single variable or about each of the number of separate variables in a study population. At the analytic level: To analyze the relationship between two or more health-related phenomena It provides information about the presence and strength of associations between variables, permitting testing of the hypothesis. 11 5/18/2023 Professor Dr AB Rajar

12. DESCRIPTIVE CSS Information about single /Multiple variables Estimate – Problem Point prevalence [1 st April] Period prevalence [Year] Disease and suspected risk factors population /specified individuals. 12 5/18/2023 Professor Dr AB Rajar

13. DESCRIPTIVE CROSS-SECTIONAL STUDY Dimension of positive health such as Fitness, Level of happiness, and life satisfaction. Presence of disease , disability , and symptoms of ill health . Levels of anxiety, stress, and depression, Prevalence of hepatitis B, Prevalence of self-centeredness and obsessive-compulsive disorders Attributes related to health Body measurements ( waist circumference, BMI, Blood pressure) 13 5/18/2023 Professor Dr AB Rajar

14. ANALYTICAL CROSS-SECTIONAL STUDY. “ An analytic investigation in which subjects are sampled at a fixed point or period of time, and then the association between the concurrent presence or absence of risk factors and diseases are investigated. (Raymond S, Greenberg et all-1995) 14 5/18/2023 Professor Dr AB Rajar

15. ANALYTICAL CROSS-SECTIONAL STUDY. 15 5/18/2023 Professor Dr AB Rajar

16. DESIGN OF CROSS-SECTIONAL STUDY 16 5/18/2023 Professor Dr AB Rajar

17. Exposure and Disease Measures Simultaneously 17 5/18/2023 Professor Dr AB Rajar

18. STEPS OF CROSS-SECTIONAL STUDY Step : State your research question, research hypothesis, objectives, and background significance of the research question. Step : Define the “Total (whole, reference) /source population” and sample Step : Specify your study variables and the ‘scales’ of measurements Step : Calculate the sample size Step : Describe the sampling method Step : Ensure validity and reliability, prevent bias Step : Data Collection Step : Analysis of data 18 5/18/2023 Professor Dr AB Rajar

19. Steps in Conducting a Cross-Sectional Study Step-1 State your research question ( SMART ) Specific Measurable Realistic Time bound Research hypothesis Research Objectives Background significance of the research question 19 5/18/2023 Professor Dr AB Rajar

20. Steps in conducting Cross-sectional study Step-1 State your research question, research hypothesis, objectives, and background significance of the research question. Research question: What is the prevalence of seropositivity of HBV among voluntary blood donors at a blood bank of MMCH Research hypothesis Is prevalence of seropositivity of HBV among voluntary blood donors at a blood bank of MMCH increased or associated with the reuse of injection Research Objective To study prevalence of seropositivity of HBV among voluntary blood donors at a blood bank” To find out the risk factors associated with increased prevalence of seropositivity of HBV among voluntary blood donors 20 5/18/2023 Professor Dr AB Rajar

21. Steps in Conducting a Cross-Sectional Study Step: State your research question, research hypothesis, objectives, and background significance of the research question. Step : Define the Total (whole, reference) population and the “actual (study) population from which the sample will be drawn. Step: Specify your study variables and the ‘scales’ of measurements Step: Calculate the sample size Step: Describe the sampling method Step: Ensure validity and reliability, prevent bias Step: Data Collection Step: Analysis of data 21 5/18/2023 Professor Dr AB Rajar

22. Steps in Conducting a Cross-Sectional Study Step-2: Define the Total (whole, reference) population and the “actual (study) population from which the sample will be drawn. Ensure that the actual population is a “representative subset” of the total population. 22 5/18/2023 Professor Dr AB Rajar

23. TARGET POPULATION The population to which the main results of the study will be extrapolated For example, if we were planning a study of the IQ level of secondary school children. Next, a suitable source population needs to be identified 23 5/18/2023 Professor Dr AB Rajar

24. SOURCE POPULATION For practical and logistic reasons, the source population is generally more limited than the target population. For Example, although our target population comprises all secondary school children at MPK city , it would be impossible to include all of them in the study. The choice of the source population should be determined by the definition of the target population and by logistic constraints. 24 5/18/2023 Professor Dr AB Rajar

25. SOURCE POPULATION For logistic reasons, we might decide to conduct the study in MPK, where the study participants as mentioned are present. If this source population is small enough to be studied using the human and financial resources available, the entire population can be included. If the source population is still too large, a representative sample has to be selected. 25 5/18/2023 Professor Dr AB Rajar

26. SOURCES OF DATA Diagram illustrating the relationship between the target population and the study participants 26 5/18/2023 Professor Dr AB Rajar

27. SAMPLE A subset of the population derived from the source population If this source population is small enough to be studied using the human and financial resources available, the entire population can be included. OR If the source population is too large, a representative sample must be selected. 27 5/18/2023 Professor Dr AB Rajar

28. Steps in Conducting a Cross-Sectional Study Step: State your research question, research hypothesis , objectives, and background significance of the research question. Step: Define the Total (whole, reference) population and the “actual (study) population from which the sample will be drawn. Step : Specify your study variables and the ‘scales’ of measurements Step: Calculate the sample size Step: Describe the sampling method Step: Ensure validity and reliability, prevent bias Step: Data Collection Step: Analysis of data 28 5/18/2023 Professor Dr AB Rajar

29. Steps in Conducting a Cross-Sectional Study Step-3: Specify your study variables and the ‘scales’ of measurements. To study the prevalence of Depression, Anxiety and Stress among undergraduate medical & dental students of MMDC at MPK” 29 5/18/2023 Professor Dr AB Rajar

30. STUDY VARIABLES Main variable Other variables of secondary interest: What are the variables related to person, place and time 30 5/18/2023 Professor Dr AB Rajar

31. STUDY VARIABLES To study the prevalence of depression, anxiety, and stress among undergraduate medical & dental students at an MMDC” 1-Main variables: Name one or two variables that are most interesting to you, e.g., Depression, Anxiety & Stress. 31 5/18/2023 Professor Dr AB Rajar

32. STUDY VARIABLES 2-Variables of secondary interest: These are the variables you want to study besides the main interest variables. Try to limit these to not more than 3 to 5 (e.g. other Psychiatric diseases). 32 5/18/2023 Professor Dr AB Rajar

33. STUDY VARIABLES What are the variables related to person, place, and time according to which you will describe the “distribution” of the “ main ” and “ secondary interest ” variables, e.g. : Person related : as age groups (less than 20, 20 -22, 23 -25, more than 26); sex; socio-economic status; history of psychiatric drugs; marital status; frequency of visits to any psychiatrist; knowledge about depression, anxiety & stress. Time-related: month-wise detection of cases out of the total tested by any scale. Place related : as hostler/non-hostler, rural-urban differences of cases. 33 5/18/2023 Professor Dr AB Rajar

34. Specify the ‘scales’ of measurements Specify the ‘scales’ of measurements in respect of each of the main variables & secondary variables and those person/place/time variables on which “distribution” is to be described. whether on Continuous [3.5,35.6,50.56,100.2] Discrete [Whole numbers like: [3, 23, 35] Ordinal [Mild, Moderate, Severe] Dichotomous [Male, Female] Polychotomous scales. 34 5/18/2023 Professor Dr AB Rajar

35. Steps in Conducting a Cross-Sectional Study Step: State your research question, research hypothesis , objectives, and background significance of the research question. Step: Define the Total (whole, reference) population and the “actual (study) population from which the sample will be drawn. Step: Specify your study variables and the ‘scales’ of measurements Step : Calculate the sample size Step: Describe the sampling method Step: Ensure validity and reliability, prevent bias Step: Data Collection Step: Analysis of data 35 5/18/2023 Professor Dr AB Rajar

36. SAMPLE SIZE CALCULATION 4- Step: Calculate the sample size: n Description: n= Sample size. z= Standard Error associated with the chosen level of confidence ( typically 1.96) p= Variability / standard Deviation ( It can be taken from previous studies or Pilot study) q-1-p e = Acceptable sample error   36 5/18/2023 Professor Dr AB Rajar

37. SAMPLE SIZE CALCULATION Assume Variability (p) = 0.2 Confidence level = 95% Sampling error =5% Yamane's formula n = = n = 153 n=153   37 5/18/2023 Professor Dr AB Rajar

38. Steps in Conducting a Cross-Sectional Study Step: State your research question, research hypothesis, objectives, and background significance of the research question. Step: Define the Total (whole, reference) population and the “actual (study) population from which the sample will be drawn. Step: Specify your study variables and the ‘scales’ of measurements Step: Calculate the sample size Step : Describe the sampling method Step: Ensure validity and reliability, prevent bias Step: Data Collection Step: Analysis of data 38 5/18/2023 Professor Dr AB Rajar

39. Steps in Conducting a Cross-Sectional Study Step-5 Describe the sampling method For the selection of a sample from the source population, we need to decide on the sample design/technique. Samples are sometimes chosen There are several methods of sampling. In general, they could be classified into two major groups: Probability/Random sampling: (preferred) Non-probability sampling – 39 5/18/2023 Professor Dr AB Rajar

40. MAJOR TYPES OF SAMPLING Probability sampling Every unit in the population has a chance (greater than zero) of being selected in the sample, and this probability can be accurately determined Non-Probability sampling Some elements of the population have no chance of selection Selection of elements based on assumptions regarding the population of interest 40 5/18/2023 Professor Dr AB Rajar

41. MAJOR TYPES OF SAMPLING Probability Samples Simple random sample (SRS) Systematic random sample Stratified random sample Cluster sample Single, double & Multistage Sampling Non-Probability Samples Convenience sample Purposive sample Quota Snowball 41 5/18/2023 Professor Dr AB Rajar

42. Steps in Conducting a Cross-Sectional Study Step: State your research question, research hypothesis, objectives, and background significance of the research question. Step: Define the Total (whole, reference) population and the “actual (study) population from which the sample will be drawn. Step: Specify your study variables and the ‘scales’ of measurements Step: Calculate the sample size Step: Describe the sampling method Step : Ensure validity and reliability, prevent bias Step: Data Collection Step: Analysis of data 42 5/18/2023 Professor Dr AB Rajar

43. Steps in Conducting a Cross-Sectional Study Step-6: Ensure validity and reliability, prevent bias Validity: Validity is an expression of the degree to which a test is capable of measuring what it is intended to measure. Reliability: the extent to which repeated measurement of a stable phenomenon by different people and instruments at different time and place get similar results. Bias: any trend in the collection, analysis, interpretation, publication, or review of data that can lead to conclusions that are systematically different from the truth. 43 5/18/2023 Professor Dr AB Rajar

44. Steps in Conducting a Cross-Sectional Study Step: State your research question, research hypothesis, objectives, and background significance of the research question. Step: Define the Total (whole, reference) population and the “actual (study) population from which the sample will be drawn. Step: Specify your study variables and the ‘scales’ of measurements Step: Calculate the sample size Step: Describe the sampling method Step: Ensure validity and reliability, prevent bias Step : Data Collection Step: Analysis of data 44 5/18/2023 Professor Dr AB Rajar

45. Steps in Conducting a Cross-Sectional Study Step-7: Data Collection Collect the data in a predesigned form. Ensure that before you start the data collection, you have undertaken a pilot study on a sample of 10% of the total required sample (5% in case of extensive sample studies) for validating and standardizing all your instruments, questionnaire, and techniques. 45 5/18/2023 Professor Dr AB Rajar

46. Steps in Conducting a Cross-Sectional Study Step-7: Data Collection During the data collection of the actual study , frequently examine your Performa for any missing data and get back to the subjects if there is any missing data, at the earliest. If different data collectors collect data, cross-check at least 20% of the filled Performa independently to ensure data quality control and reduce observer variations. Enter data into the Master chart or computer (SPSS) periodically and at an early date. 46 5/18/2023 Professor Dr AB Rajar

47. TOOLS OF DATA COLLECTION According to which tool is used to collect data, there exist two main types of CSS: Health interview surveys (HIS): In which collection of data is carried out only using questionnaires, and Health examination surveys (HES): which are usually a combination of questionnaires and health examinations, including diagnostic and laboratory tests. 47 5/18/2023 Professor Dr AB Rajar

48. METHODS OF DATA COLLECTION In Health interview surveys: Questionnaires may be communicated to the randomly selected study subjects in three ways: mail, personal interview, or telephone interview. In Health examination surveys: The contact between participants and research personnel is personal since the health examination is a part of the CSS. In this type of survey, also questionnaires are usually communicated to the randomly selected study subjects through personal interview 48 5/18/2023 Professor Dr AB Rajar

49. Steps in Conducting a Cross-Sectional Study Step: State your research question, research hypothesis, objectives, and background significance of the research question. Step: Define the Total (whole, reference) population and the “actual (study) population from which the sample will be drawn. Step: Specify your study variables and the ‘scales’ of measurements Step: Calculate the sample size Step: Describe the sampling method Step: Ensure validity and reliability, prevent bias Step: Data Collection Step: Analysis of data 49 5/18/2023 Professor Dr AB Rajar

50. Steps in Conducting a Cross-Sectional Study Step-8: Analysis of data Getting data ready for analysis in CSS starts with drafting the questionnaire , where the codes for different answers are already predefined in respect of individual questions. The encoded data are then entered in the data matrix or spreadsheet. Data entry & data analysis should be carried out by statistical software [SPSS] or Microsoft Excel 50 5/18/2023 Professor Dr AB Rajar

51. Steps in Conducting a Cross-Sectional Study Analysis of data Prevalence is the measure of the occurrence of a disease, condition, or characteristic that can primarily be obtained from cross-sectional surveys. 51 5/18/2023 Professor Dr AB Rajar

52. Steps in Conducting a Cross-Sectional Study Analysis of data Example: Suppose a cross-sectional survey was carried out to assess the prevalence of breast cysts in a particular female population. A sample of 5891 women randomly selected from that population was examined, and 201 were found to have breast cysts . 52 5/18/2023 Professor Dr AB Rajar

53. Steps in Conducting a Cross-Sectional Study Analysis of data The prevalence of breast cysts in this population at the time of the survey was thus: 201 / 5891 = 3.4% . 53 5/18/2023 Professor Dr AB Rajar

54. Steps in Conducting a Cross-Sectional Study Analysis of data To examine the association between a putative risk factor for the attribute of interest and the attribute itself, the population is first subdivided into those exposed and those not exposed to the factor under study. The prevalence of the attribute in each group is calculated and compared. A prevalence ratio can then be computed as the ratio of the prevalence of the attribute of interest in those exposed to the putative risk factor relative to the prevalence in those unexposed . 54 5/18/2023 Professor Dr AB Rajar

55. DATA ANALYSIS A cross-sectional study was conducted among 5891 females of reproductive age; among them, 3247 had been using contraceptives for the last 10 years. In the contraceptive user group, 124 were positive for cysts, while among the non-user, 2567 did not reveal cysts. Find out the prevalence ratio? 55 5/18/2023 Professor Dr AB Rajar

56. DATA ANALYSIS Breast Cyst Lifetime use of oral contraceptives Total Ever used Never used Yes 124 No 2567 5690 Total 3247 5891 Prevalence of breast cysts among ever users = Prevalence of breast cysts among never users = Prevalence ratio= A cross-sectional study was conducted among 5891 ; among them, 3247 were using contraceptives for the last 10 years in the contraceptive user group, 124 were positive for cysts, while among the non-user, 2567 did not reveal cysts find out the prevalence ratio 56 5/18/2023 Professor Dr AB Rajar

57. DATA ANALYSIS Breast Cyst Lifetime use of oral contraceptives Total Ever used Never used Yes 124 77 201 No 3123 2567 5690 Total 3247 2644 5891 Prevalence of breast cysts among ever users =124/3247=3.8% Prevalence of breast cysts among never users =77/2644=2.9% Prevalence ratio=ever user /never user=3.8/2.9=1.3 Suppose that in the hypothetical survey described in the above example, the investigators wished to assess whether the prevalence of breast cysts was associated with having ever used OC 57 5/18/2023 Professor Dr AB Rajar

58. INTERPRETATION The prevalence of breast cysts was higher in ever-users of oral contraceptives compared to never-users . It should be noted that the prevalence ratio is a good estimate of the incidence rate ratio only if the prevalence of the outcome of interest among those unexposed is low (less than 10%) and the duration of the disease is the same among those who were exposed and those who were unexposed to the factor of interest. 58 5/18/2023 Professor Dr AB Rajar

59. Prevalence Odd ratio Breast Cyst Lifetime use of oral contraceptives Total Ever used Never used Yes 124 77 201 No 3123 2567 5690 Total 3247 2644 5891 Prevalence of breast cysts among ever users =124/3247=3.8% Prevalence of breast cysts among never users =77/2644=2.9% Prevalence ratio=ever user /never user=3.8/2.9=1.3 From this hypothetical study example, We can calculate the odds of having ever-used oral contraceptives among women with (cases) and without (controls) breast cysts. Odds of exposure to oral contraceptives among ‘cases’=124/77=1.61 Odds of exposure to oral contraceptives among ‘controls’=3123/2667=1.22 Odds ratio=1.61/1.22=1.3 59 5/18/2023 Professor Dr AB Rajar

60. Prevalence Odd ratio From this hypothetical study example, We can calculate the odds of having ever-used oral contraceptives among women with (cases) and without (controls) breast cysts. Odds of exposure to oral contraceptives among ‘cases’=124/77=1.61 Odds of exposure to oral contraceptives among ‘controls’=3123/2667=1.22 Odds ratio=1.61/1.22=1.3 60 5/18/2023 Professor Dr AB Rajar

61. Analysis of Descriptive Cross-sectional Study Objective: To describe the disease in time, place, and person To generate a hypothesis Analysis: Means & SD Median & percentile Proportions – Prevalence Ratios Age, sex, or other group-specific analysis 61 5/18/2023 Professor Dr AB Rajar

62. Analysis of Analytical Cross-sectional Study Objective: Is there any association? If “YES”, then what is the strength of the association? Analysis: Is there any association? Chi-square, student-t-test, etc What is the strength of association? Odds ratio, Rate ratio, Rate difference, Difference between mean, Correlation, Regression coefficient. Measure of impact : Risk factor: Attributable fraction (exposed) & Attributable fraction (population) Protective factor: Prevented fraction (exposed) & Prevented fraction (population) 62 5/18/2023 Professor Dr AB Rajar

63. MEASURE OF PREVALENCE Prevalence proportion : Proportion of the subjects who have the disease at a point in time. Example: Of 1800 middle-aged women 30 had diabetes on January 1, 2007. The prevalence proportion of diabetes was 30/1800 = 0.016 or 1.6% Point prevalence Period prevalence. 63 5/18/2023 Professor Dr AB Rajar

64. Point and Period prevalence Point Prevalence: P= Period prevalence: P =   64 5/18/2023 Professor Dr AB Rajar

65. MEASURE OF ASSOCIATION Measures of association: odds ratio   Odds Ratio- the ratio of one odds to another. It is the probability that something is so or will occur to the probability that it is not so or will not occur. Example: Exposure to fumes Headache Present Headache Absent Total Factor Present a = 10 b= 90 a+b= 100 Factor Absent c= 50 d=850 c +d = 900 Total a +c = 60 b +d= 940 n=1000 65 5/18/2023 Professor Dr AB Rajar

66. Odds Ratio Disease OR= Exposure OR=   66 5/18/2023 Professor Dr AB Rajar

67. Rate Ratio: Prevalence ratio = {a/(a+b)}/{c/(c+d)} = 1.8 Exposure ratio = {a/(a+c)}/{b/( b+d )} = 1.74 Rate differences Prevalence difference = {a/(a+b)} - {c/( c+d )} = 0.0444 Exposure difference = {a/( a+c )} - {b/( b+d )} = 0.07 Number needed to avoid one case in un-exposed group = 1/prevalence difference = 1/0.0444=22.5 67 5/18/2023 Professor Dr AB Rajar

68. Measure of impact If the factor is a risk factor: Excess risk among exposed = {a/(a+b)} - {c/(c+d)} = 0.0444 Population excess risk: = ( a+c )/n – c/(c+d) = 0.004 Attributable fraction (exposed): = [(Prevalence ratio – 1)/Prevalence ratio] *100= 44.4 Attributable fraction (population): = [(Prevalence ratio – 1)*E]/{1+[(Prevalence ratio -1)*E]} *100= 7.4. E = exposure rate in a population 68 5/18/2023 Professor Dr AB Rajar

69. Measure of impact [protective factor] If the factor is protective factor Excess risk among unexposed = c/(c+d) – a(a+b) Population excess risk = ( a+c )/n – a(a+b) Prevented fraction (exposed) ={[c/(c+d) – a(a+b)]/[c/(c+d)}*100 Prevented fraction (population) ={[( a+c )/n – a(a+b)]/[( a+c )/n]}*100 69 5/18/2023 Professor Dr AB Rajar

70. USES OF CROSS- SECTIONAL STUDY Used as a tool in community health care: Community Diagnosis Health care Determinants of health & disease Identification of group requiring special care Surveillance Community education & community involvement Evaluation of community health care Can contribute to clinical care (community-oriented primary care) Can provide new knowledge (studies on etiology, growth & development) 70 5/18/2023 Professor Dr AB Rajar

71. Guidelines for critical appraisal of the prevalence study Are the study design & sampling method appropriate for the RQ? Is the sampling frame appropriate? Is the sample size adequate? Are objective, suitable, and standard criteria used to measure the health outcome? Is the health outcome measured in an unbiased manner? Is the response rate adequate? Are the refusers described? Are the estimates of prevalence given with CI & in detail by subgroup – if appropriate? Are the study subjects and the setting described in detail ? 71 5/18/2023 Professor Dr AB Rajar

72. Advantages of Cross-Sectional Study Cheap and quick studies. Data is frequently available through current records or statistics.   Ideal for generating new hypotheses. Correlation between two continuously distributed phenomenon can be studied. Prevalence of the disease. Starting point of the cohort study. 72 5/18/2023 Professor Dr AB Rajar

73. Disadvantages of Cross-Sectional Study Needs a large sample size. Large number of logistic support needed. 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.  73 5/18/2023 Professor Dr AB Rajar

74. 74 5/18/2023 Professor Dr AB Rajar