Biology 4a assignment
N O N - E X P E R I M E N T A L S T U D Y D E S I G N S P A R T 2 : C O H O R T S T U D Y D E S I G N
6310-WEEK 4
MAIN NON-EXPERIMENTAL STUDY DESIGNS
• Cross-sectional study design • Cohort study design • Case-control study design
COHORT STUDY DESIGN
COHORT STUDY DESIGN
• Cohort: a group of subjects followed over time • Cohort design: A non-experimental design in which a defined
group of people (a cohort) is followed over time to study outcomes for subsets of the cohorts • Data is collected at baseline to assess exposure/characteristic • Data is collected again at later point(s) in time to examine the
development of a disease or condition • Time frame: longitudinal • Advantages:
• Allows calculation of incidence (number of new cases of a condition occurring over time)
• Establishes the time sequence of variable strengthens the process of inferring the causal basis of an association
• Types • Prospective • Retrospective • Multiple cohort
COHORT STUDY DESIGN
Over time
Baseline
Gather data at: Defined Population
Exposed
Disease No Disease
Not Exposed
Disease No Disease
STEPS IN A PROSPECTIVE COHORT STUDY
• Define selection criteria and recruit sample from the population (cohort).
• At baseline, measure predictor variables and, if appropriate, baseline level of outcome variable(s).
• Follow cohort over time, minimizing loss to follow-up. • Measure outcome variable(s) at follow-up.
STEPS IN A RETROSPECTIVE COHORT STUDY
• Identify an existing cohort that has some predictor information already recorded
• Assess loss to follow-up that has occurred • Measure outcome variable(s) that have already
occurred.
MULTIPLE-COHORT DESIGN
• Two or more separate samples: one with exposure to a potential risk factor (predictor) and one or more with no exposure.
• Next steps: measure other predictors; follow up; assess outcomes
• Note that a double-cohort design is different from the use of two samples in a case-control design • Double-cohort: two groups chosen based on level of predictor • Case-control: two groups chosen based on presence or
absence of an outcome • Strengths: Feasible approach to study rare exposures to
environmental and occupational hazards • Weaknesses: Confounding since the cohorts are
assembled from separate populations.
STATISTICAL MEASURES IN COHORT DESIGNS
• Cohort study results are usually reported in measures that reflect the concept of being at risk.* • Risk • Odds • Rate
*See the example in Hulley’s textbook and Table 7.2 on page 93 for a good example on the calculation of these measures.
RISK
• In the context of cohort studies, risk refers to the number of new cases who develop the health outcome among those at risk, over a specified time period.
• It refers to the probability that a health outcome will occur.
• It is usually expressed as a percentage (ranging from 0% to 100%).
CALCULATING RISK
• Define the population at risk • Determine the number of new cases (those who
develop the outcome/disease) • Specify the time period
Risk = Number of new cases In specified time period
Population at risk
EXAMPLE*: RISK CALCULATION
• 15,000 children, ages 2 to 8, who live in an area around high-voltage power lines were followed for 10 years or until the development of a childhood leukemia. Fifty cases were identified over the 10- year period.
• Risk = 50/15,000 = .0033 or .33% or 3.3 people per 1000 over 10 years
*This is a hypothetical example and does not reflect the actual risk of childhood leukemia. There is also no consistent body of evidence on an association between living near high-voltage power lines and childhood leukemia.
ODDS
• Odds refers to the probability (p) of an event occurring to the probability that it will not occur (1-p).
• Odds of an event = p/(1-p) • Odds ratios (OR) are used to compare the relative odds of the
occurrence of the outcome of interest (e.g. disease or disorder), given exposure to the variable of interest (e.g. health characteristic, aspect of medical history). The odds ratio can also be used to determine whether a particular exposure is a risk factor for a particular outcome, and to compare the magnitude of various risk factors for that outcome. • OR=1 Exposure does not affect odds of outcome • OR>1 Exposure associated with higher odds of outcome • OR<1 Exposure associated with lower odds of outcome
Sources: Polit DF, Beck CT. 2012. Nursing Research: Generating and Assessing Evidence for Nursing
Practice. Szumilas M. Explaining Odds Ratios. Journal of the Canadian Academy of Child and
Adolescent Psychiatry. 2010;19(3):227-229.
RATE
• Rate refers to the number of subjects who develop an outcome (new cases) divided by the person-time at risk
• Rate accounts for the reality of a changing population through the person-time concept
• Person-time is an estimate of the actual time each person remains at risk for the health outcome (in years, months, or days). It is the sum of each participant’s time at risk before developing the outcome, leaving the study, being lost to follow-up, or dying.
Rate = Number of new cases Person-time at risk
ADDITIONAL RESOURCES
• For more information on prevalence, incidence, risk and rate, click here.
• For more information on the concept of person- year, watch the following video, available here (6:09 minutes).
ISSUES TO CONSIDER WHEN EVALUATING COHORT STUDIES
• Subjects are: • appropriate to research question, • available for follow-up, and • representative of the population to which findings will be
generalized. • Number of subjects provides adequate power. • Measurements of predictor and outcome variables
are precise and accurate. • Potential confounders are measured. • Loss to follow-up is minimized.
BIAS SPECIFIC TO COHORT STUDY DESIGNS
• Bias specific to cohort study designs • Attrition bias resulting from losing people to follow-up
• To assess the extent of attrition bias, compare baseline characteristics of those who were available and not available for follow-up
• To minimize attrition bias, • Use incentives • Collect multiple contact information items • Incorporate additional contact attempts • Include follow-ups between data collection points
EXAMPLES COHORT STUDIES
FRAMINGHAM HEART STUDY
• Objective: To identify risk factors for cardiovascular disease (CVD) by following its development over a long period of time in a large group of participants who had not yet developed overt symptoms of CVD or suffered a heart attack or stroke.
• Sample: 5,209 men and women between the ages of 30 and 62 from the town of Framingham, Massachusetts.
• Extensive physical examinations and lifestyle interviews to analyze common patterns related to CVD development. • Since 1948, subjects return to the study every two years. • In 1971, the Study enrolled a second generation: 5,124 of the original participants'
adult children and their spouses. • In 1994, a different cohort was enrolled to reflect a more diverse community of
Framingham (Omni cohort of the Framingham Heart Study). • In April 2002 the Study enrolled a third generation of participants (grandchildren of
Original Cohort). In 2003, a second group of Omni participants was enrolled. • Results: identification of major CVD risk factors - high blood pressure, high
blood cholesterol, smoking, obesity, diabetes, and physical inactivity. • Click here if you are interested in more information on the Framingham
Heart Study.
NURSES HEALTH STUDY
• Objective: To investigate factors that influence women’s health with a primary focus on cancer prevention.
• 1976 baseline sample: 122,000 registered nurses ages 30 to 55 years.
• Results: diet, physical activity and other lifestyle factors can promote better health.
• Click here if you are interested in more information on the Nurses Health Study.
HISPANIC EPESE
• Hispanic Established Populations for the Epidemiologic Study of the Elderly
• Objectives • Estimate the prevalence of key physical and mental health conditions and
functional impairments in older Mexican Americans. • Investigate predictors of physical and mental health conditions and
functional status at baseline. • Study changes in health and functioning among survivors • Examine changes in health behaviors and key social mediators of health
status (social networks and support, various key transitions such as changes in living arrangements, widowhood, etc.).
• Sample: 1993-94 representative sample of community-dwelling Mexican-American elderly, aged 65 years and older, residing in the five southwestern states of Arizona, California, Colorado, New Mexico, and Texas. • Five follow-ups. • N = 3,050 participants with an additional 902 added at 4th follow-up.
• Note that analysis of baseline data serves as a cross-sectional study.
• Click here if you interested in more information on the H-EPESE.
- 6310-Week 4
- Main Non-Experimental Study Designs
- Cohort Study Design
- Cohort Study Design
- Cohort Study Design
- Steps in a Prospective �Cohort Study
- Steps in a Retrospective �Cohort Study
- Multiple-Cohort Design
- Statistical Measures �in Cohort Designs
- Risk
- Calculating Risk
- Example*: Risk Calculation
- Odds
- Rate
- Additional Resources
- Issues to Consider when Evaluating Cohort Studies
- Bias Specific to �Cohort study designs
- Examples
- Framingham Heart Study
- Nurses Health Study
- Hispanic EPESE