Epidemiology & Biostatistics Lecture 4 (2024) PDF

BIOSTATISTICS & EPIDEMIOLOGY NURSING ADMINISTRATION & PSYCHIATRIC NURSING Ministry of Health & Wellness In-Service Education Unit LECTURE # 4 Presented by: Hank Williams March 6, 2024 BIOSTATISTICS The science of collecting and analyzing biologic or health data using statistical methods. KARL PEARSO...

BIOSTATISTICS & EPIDEMIOLOGY NURSING ADMINISTRATION & PSYCHIATRIC NURSING Ministry of Health & Wellness In-Service Education Unit LECTURE # 4 Presented by: Hank Williams March 6, 2024 BIOSTATISTICS The science of collecting and analyzing biologic or health data using statistical methods. KARL PEARSON (1847–1936) Widely viewed as the founder of modern statistics for the development and application of statistical methods to a wide range of topics in biology. HYPOTHESIS TESTING Statement of brief about population parameters. Evaluates the likelihood that results from a particular sample reflect those of the population from which it is drawn. STEPS IN HYPOTHESIS TESTING Construct a study hypothesis regarding the entire population. Decide on the appropriate test statistics. Select the level of significance for the statistics test. STEPS IN HYPOTHESIS TESTING (CONT’D) Determine the value the test statistic must attain to be declared significant. Perform the calculation. Draw and state the conclusion. STEP I : STATE THE RESEARCH QUESTION IN TERMS OF STATISTICAL HYPOTHESES Construct a study hypothesis regarding the entire population. Construct a null hypothesis, which is the diametric opposite of the study hypothesis. Assess the probability of obtaining your sample result if the null hypothesis was true. Reject the null hypothesis if this probability is very low. CONSTRUCT STUDY HYPOTHESIS State the problem that you are trying to solve. Document the hypothesis intended to investigate Define the variables. EXAMPLE OF STUDY HYPOTHESIS Mean systolic blood pressure of all Seattle coffee drinkers is different than mean systolic blood pressure of all Seattle noncoffee drinkers. CONSTRUCT NULL HYPOTHESIS Diametrically opposite of the study hypothesis. Assume that there is no relationship between the parameters Denoted by the notation - H0 EXAMPLE OF NULL HYPOTHESIS Mean systolic blood pressure of all Seattle coffee drinkers is equal to mean systolic blood pressure of all Seattle non-coffee drinkers. CONSTRUCT ALTERNATIVE HYPOTHESIS Statement that disagrees with the null hypothesis. Assume that there is a relationship between the parameters Denoted by the notation - Ha EXAMPLE OF ALTERNATIVE HYPOTHESIS Mean systolic blood pressure of all Seattle coffee drinkers is different to mean systolic blood pressure of all Seattle non-coffee drinkers. TWO-SIDED HYPOTHESIS The population parameter is either greater than or less than the hypothesized value. A two-sided test can detect when the population parameter differs in either direction. ONE-SIDED HYPOTHESES Determine whether the population parameter differs from the hypothesized value in a specific direction. Specify the direction to be either greater than or less than the hypothesized value. A one-sided test has greater power than a two-sided test. SUMMARY OF TWO-SIDED AND ONE-SIDED HYPOTHESES STEP 2: DECIDE ON THE APPROPRIATE TEST STATISTICS T-test is used to compare mean values between two different groups. Chi-square test is used to compare proportions between two different groups. ANOVA test is used to compare mean values across multiple groups (categorical) Regression is used to describe the relationship between two or more variables (continuous) STEP 3: DECIDE ON THE APPROPRIATE TEST STATISTICS P-values and 95% confidence intervals are tools of statistical inference. STEP 3: SELECT THE LEVEL OF SIGNIFICANCE FOR THE STATISTICAL TEST Level of significance is commonly referred to as alpha value (α) α is traditionally 0.05 (5%) P-values and 95% confidence intervals are tools of statistical inference. STEP 4: DETERMINE THE VALUE OF TEST STATISTIC TO ATTAIN SIGNIFICANCE Determine the significance value (also called the critical value) P-values and 95% confidence intervals are tools of statistical inference. STEP 5: PERFORM THE CALCULATION Perform the appropriate statistical test. Application of tests using statistical software package. STEP 6: DRAW AND STATE THE CALCULATION State the conclusion in words. The decision is either to reject or not to reject the null hypothesis. MORBIDITY Any departure, subjective or objective, from a state of physiological or psychological well-being. In practice, morbidity encompasses disease, injury, and disability. Refers to the number of persons who are ill, it can also be used to describe the periods of illness that these persons experienced, or the duration of these illnesses. In practice, morbidity encompasses disease, injury and disability. MORBIDITY Measure of Morbidity  Prevalence  Incidence Measures of Association  Relative Risk  Odds Ratio PREVALENCE Proportion of persons in a population who have a particular disease or attribute at a specified point in time or over a specified period of time. TYPES OF PREVALENCE Point Prevalence the prevalence measured at a particular point in time. It is the proportion of persons with a particular disease or attribute on a particular date. Period Prevalence prevalence measured over an interval of time. It is the proportion of persons with a particular disease or attribute at any time during the interval. CLASSWORK #13 In a survey of 1,150 women who gave birth in Maine in 2000, a total of 468 reported taking a multivitamin at least 4 times a week during the month before becoming pregnant. Calculate the prevalence of frequent multivitamin use in this group. CLASSWORK #13 In a survey of 1,150 women who gave birth in Maine in 2000, a total of 468 reported taking a multivitamin at least 4 times a week during the month before becoming pregnant. Calculate the prevalence of frequent multivitamin use in this group. Numerator = 468 multivitamin users Denominator = 1,150 women Prevalence = (468 ⁄ 1,150) × 100 = 0.407 × 100 = 40.7% INCIDENCE The occurrence of new cases of disease or injury in a population over a specified period of time. Although some epidemiologists use incidence to mean the number of new cases in a community, others use incidence to mean the number of new cases per unit of population. TYPES OF INCIDENCE Incidence Proportion the proportion of an initially disease-free population that develops disease, becomes injured, or dies during a specified (usually limited) period of time. TYPES OF INCIDENCE Incidence Rate  a measure of incidence that incorporates time directly into the denominator. A person-time rate is generally calculated from a long-term cohort follow-up study, wherein enrollees are followed over time and the occurrence of new cases of disease is documented.. INCIDENCE PROPORTION CLASSWORK #14 In the study of diabetics, 100 of the 189 diabetic men died during the 13-year follow-up period. Calculate the risk of death for these men. CLASSWORK #14 In the study of diabetics, 100 of the 189 diabetic men died during the 13-year follow-up period. Calculate the risk of death for these men. Numerator = 100 deaths among the diabetic men Denominator = 189 diabetic men 10n = 102 = 100 Risk = (100 ⁄ 189) × 100 = 52.9% CLASSWORK #15 In an outbreak of gastroenteritis among attendees of a corporate picnic, 99 persons ate potato salad, 30 of whom developed gastroenteritis. Calculate the risk of illness among persons who ate potato salad. CLASSWORK #15 In an outbreak of gastroenteritis among attendees of a corporate picnic, 99 persons ate potato salad, 30 of whom developed gastroenteritis. Calculate the risk of illness among persons who ate potato salad. Numerator = 30 persons who ate potato salad and developed gastroenteritis Denominator = 99 persons who ate potato salad 10n = 102 = 100  Risk = “Food-specific attack rate” = (30 ⁄ 99) × 100 = 0.303 × 100 = 30.3% INCIDENCE RATE CLASSWORK #16 The diabetes follow-up study included 218 diabetic women and 3,823 nondiabetic women. By the end of the study, 72 of the diabetic women and 511 of the nondiabetic women had died. The diabetic women were observed for a total of 1,862 person years; the nondiabetic women were observed for a total of 36,653 person years. Calculate the incidence rates of death for the diabetic and nondiabetic women. CLASSWORK #16 For diabetic women, numerator = 72 and denominator = 1,862 Person-time rate = 72 ⁄ 1,862 = 0.0386 deaths per person-year = 38.6 deaths per 1,000 person-years For nondiabetic women, numerator = 511 and denominator = 36,653 Person-time rate = 511 ⁄ 36,653 = 0.0139 deaths per person-year = 13.9 deaths per 1,000 person-years CLASSWORK #17 In 2003, 44,232 new cases of acquired immunodeficiency syndrome (AIDS) were reported in the United States. The estimated mid-year population of the U.S. in 2003 was approximately 290,809,777. Calculate the incidence rate of AIDS in 2003. CLASSWORK #17 In 2003, 44,232 new cases of acquired immunodeficiency syndrome (AIDS) were reported in the United States. The estimated mid-year population of the U.S. in 2003 was approximately 290,809,777. Calculate the incidence rate of AIDS in 2003. Numerator = 44,232 new cases of AIDS Denominator = 290,809,777 estimated mid-year population 10n = 100,000 Incidence rate = (44,232 ⁄ 290,809,777) × 100,000 = 15.21 new cases of AIDS per 100,000 population