1. Estimation of authenticity of results of statistical research

2. n The necessity estimation of authenticity of results is determined by volume of research. n In full research (general aggregate), when all units of supervision are explored it is possible to get only one value of certain index. n The general aggregate is always reliable because in it included her all units of supervision are included. General aggregate official statistics can exemplify.

3. The distribution of birthwt is shown.

5. Objective To describe the distribution and frequency of a disease in population.

6. Four primary types of epidemiology studies

7. How to describe ? What is the problem of the disease? How frequent ? Who are affected?----person Where and when does it occur?----place and time

8. Three distributions Place Person Time

9. Population n Age n Behavior Sex n Race

10. 1Age n Frequency of disease n Severity of disease Young people : infectious disease Old people: noninfectious disease accumulation of environmental factors

12. Examples n Children are more susceptible to some infectious diseases, measles n Prevalence of hypertension increase with age

15. Mortality rate ---Age n Figure 6-1

16. incidence rate---Age n Figure 6-2

17. Serum HDL-cholesterol in Tromsø 1994/95 25-29 35-39 45-49 55-59 65-69 75-79 85-89 30-34 40-44 50-54 60-64 70-74 80-84 ISM, UiT HDL-cholesterol mmol/L The Tromsø Study age

18. Sex n Frequencies and severity of disease differ between male and female population. n It is helpful to identify the risk factor of disease e.g. endemic struma female > male

19. Prevalence of obesity in Han students aged 8-18 years in Urumqi, 2003

20. Race (ethnic) n Obesity, hypertension are more prevalent in blacks than in whites n T2D is very prevalent in Pima indians n Prevalence of hypertension is quite different among ethnicities. Why? Genetic Environment

21. Prevalence of obesity among ethnicities ( adjusted by age) Ethnicities Prevalence of obesity%

22. Prevalence of EH among ethnic adults (1991)

23. Death rate in the U.S. n Blacks: cause of deaths: hypertensive heart disease, stroke, tuberculosis, syphilis, and accidental death. n Whites: cardio artery disease, suicide, and leukemia.

24. Behaviors n Cigarette smoking, alcohol consumption, abuse of drugs; high salt intake, fat food, and so on. n Determined by biological and social factors.

25. Place n Countries Urban and rural Places in different altitude

26. Estimated number of people at over 35% risk of a major cardiovascular event in the next decade, by WHO sub-region

27. CHD mortality. Women and men, age adjusted rates per 100.000. Source: WHO Health statistics annual 1993/94 ISM, UiT

28. Time When does the disease occur and transmit in the population?

30. Mean Plasma Cholesterol Values in China

31. Some terms to describe the “time” of diseases n Long-term or secular trends n Periodic fluctuations (cyclical changes) seasonal trends cyclical trends n Short term fluctuations

32. Secular trends Changes in the incidence of disease over a long period of time (several years of decades) CHD have shown an upward trend in developed countries over decades.

33. Periodic fluctuations 1. Seasonal trends n Diarrhea---summer n Respiratory diseases---winter 2. Cyclical trends disease occur in cycles spread over short periods of time (day, weeks, months or years) e.g. influenza 7-10 yrs)

34. n The general aggregate is rarely used in medical-biologic research, mainly part of researches is selective. The law of large numbers is basis for forming of reliable selective aggregate. It sounds so: it is possible to assert with large authenticity, that at achievement of large number of supervisions average of sign, which is studied in a selective aggregate will be a little to differ from an average which is studied at all general aggregate.

35. n The selective aggregate always has errors, because not all units of supervision are included in research. Authenticity of selective research depends from the size of this error. That is why greater number of supervisions, teed to less error, the less sizes of casual vibrations of index. That, to decrease an error it is needed to multiply the number of supervisions.

36. Basic criteria of authenticity (representation): n Error of representation (w) n Confiding scopes n The coefficient of authenticity (the student criterion) is authenticity of difference of middle or relative sizes (t)

38. Basic criteria of authenticity (representation): n The errors of representation of /m/ are the degree of authenticity of average or relative value shows how much the results of selective research differ from results which it is possible to get from continuous study of general aggregate.

39. Basic criteria of authenticity (representation): n Confiding scopes – properties of selective aggregate are carried on general one, probability oscillation of index is shown in the general aggregate, its extreme values of minimum and maximal possibility, which the size of general aggregate can be within the limits of.

40. Basic criteria of authenticity (representation): n The coefficient of authenticity (the Student’s criterion) is authenticity of difference of middle or relative sizes (t). The student’s Criterion shows the difference of the proper indexes in two separate selective aggregates.

41. Measuring the Occurrence of Disease Counting Comparisons Inference Action Cases and populations Measurement Risk Methods - descriptive - analytic Association and causality Generalisability Clinical/health policy Further research

42. Epidemiological Measurements  Rates,Ratios,and Proportions  Incidence Rates  Prevalence Rates  Mortality Rates  Fatality Rates  Infection Rates

43. Ratios A ratio expresses the relationship between two numbers in the form x:y or x/y.

44. Ratios 1. The ratio of male to female births in the United States in 1979 was 1,791,000 : 1,703,000 or 1.052:1. 2. Sex ratio= number of live born males number of live born females

45. n Proportions A proportion is a specific type of ratio in which the numerator is included in the denominator, and the result value is expressed as a percentage.proportion denominator For example,the proportion of all births that were male is : Male births 179×10 4 = Male+female births (179+170)×10 4 =51.3%

46. The proportion of male students of the current class is %.

49. Proportion of Overweight in children from 7- 18 year old, Urumqi, 2003

50. A rate measures the occurrence of some particular events in a population during a given time period. Particular event: development of disease or the occurrence of death Rates

51. Rates are defined as follows: Number of events in a specified period ×K Population at risk of these events in a specified period K=100%, 1000 ‰ …

52. Five components of rate Numerator is the number of People, Episodes

53. Rate is n The rate is the measure that most clearly expresses probability or risk of disease in a defined population over a specified period of time. n In a rate numerator is part of denominator.

54. What does Rate tell us Rates tell us how fast the disease is occurring in a population. Proportion tell us what fraction of the population is affected.

55. For example, the death rate from cancer in the United States in 1980 was 186.3 per 100,000 population, the formula: Deaths from cancer among U.S residents in 1980 100,000 × U.S. population in 1980 100,000

56. Incidence Rates Incidence is defined as the number of new cases of a disease that occur during a specified period of time in a population at risk for developing the disease.

57. 1. Time of onset and the numerator

58. Denominator is population at risk. Average Population We can get this number in two ways. ( population in 12.31 of last year+this year)/2 midyear population: 7.31 24:00 3.Specification of Denominator

59. Prevalence Rates Prevalence measures the number of people in a population who have disease at a given time. Point prevalence Period prevalence

61. Formula: number of existing cases of a disease at a point in time ×K total population

62. 5 points 1.Numerator It refers to existing cases, currently affected, including new and old cases. No matter when did he get the disease, if only he has disease at the study time,he is one of numerator.

63. 2.Denominator Total population. Not population at risk.

64. 3.A point in time In survey of prevalence rate, time should be very short. Generally, time should be no more than 1 month, such as 1 week or 2 weeks. (point prevalence)

65. n Coefficient of variation is the relative measure of variety; it is a percent correlation of standard deviation and arithmetic average.

66. Terms Used To Describe The Quality Of Measurements n Reliability is variability between subjects divided by inter-subject variability plus measurement error. n Validity refers to the extent to which a test or surrogate is measuring what we think it is measuring.

67. Measures Of Diagnostic Test Accuracy n Sensitivity is defined as the ability of the test to identify correctly those who have the disease. n Specificity is defined as the ability of the test to identify correctly those who do not have the disease. n Predictive values are important for assessing how useful a test will be in the clinical setting at the individual patient level. The positive predictive value is the probability of disease in a patient with a positive test. Conversely, the negative predictive value is the probability that the patient does not have disease if he has a negative test result. n Likelihood ratio indicates how much a given diagnostic test result will raise or lower the odds of having a disease relative to the prior probability of disease.

68. Measures Of Diagnostic Test Accuracy

69. Expressions Used When Making Inferences About Data n Confidence Intervals -The results of any study sample are an estimate of the true value in the entire population. The true value may actually be greater or less than what is observed. n Type I error (alpha) is the probability of incorrectly concluding there is a statistically significant difference in the population when none exists. n Type II error (beta) is the probability of incorrectly concluding that there is no statistically significant difference in a population when one exists. n Power is a measure of the ability of a study to detect a true difference.

70. Multivariable Regression Methods n Multiple linear regression is used when the outcome data is a continuous variable such as weight. For example, one could estimate the effect of a diet on weight after adjusting for the effect of confounders such as smoking status. n Logistic regression is used when the outcome data is binary such as cure or no cure. Logistic regression can be used to estimate the effect of an exposure on a binary outcome after adjusting for confounders.

71. Survival Analysis n Kaplan-Meier analysis measures the ratio of surviving subjects (or those without an event) divided by the total number of subjects at risk for the event. Every time a subject has an event, the ratio is recalculated. These ratios are then used to generate a curve to graphically depict the probability of survival. n Cox proportional hazards analysis is similar to the logistic regression method described above with the added advantage that it accounts for time to a binary event in the outcome variable. Thus, one can account for variation in follow-up time among subjects.

72. Kaplan-Meier Survival Curves

73. Why Use Statistics?

74. Descriptive Statistics n Identifies patterns in the data n Identifies outliers n Guides choice of statistical test

75. Percentage of Specimens Testing Positive for RSV ( respiratory syncytial virus)

76. Descriptive Statistics

77. Distribution of Course Grades

78. Describing the Data with Numbers Measures of Dispersion RANGE STANDARD DEVIATION SKEWNESS

79. Measures of Dispersion RANGE highest to lowest values STANDARD DEVIATION how closely do values cluster around the mean value SKEWNESS refers to symmetry of curve

80. The Normal Distribution n Mean = median = mode n Skew is zero n 68% of values fall between 1 SD n 95% of values fall between 2 SDs. Mean, Median, Mode 11 22