Epidemiology - L2

Epidemiology and Rehabilitation (PT-110) - Basics of Epidemiological Data

• Focuses on the fundamentals of epidemiological data crucial for understanding health issues

Morbidity

• Morbidity is the state of having an illness or medical condition (mental or physical)
• Subsets of morbidity include incidence and prevalence
• Comorbidity exists when a person has more than one illness simultaneously

Common types of Morbidity

• Heart disease
• Cancer
• Stroke
• Alzheimer's disease
• Influenza
• Suicide

Mortality

• Mortality refers to the number of deaths caused by a specific illness or disease during a particular time frame

• Mortality rates indicate the incidence of death within a specific population over a given time period

• Rates are typically expressed as the number of cases per 100,000

• Example: Lung cancer mortality in US males is approximately 40 per 100,000

• Excess mortality occurs when an event or disease triggers more deaths than anticipated

Epidemiological Studies

• A scientific method used to answer questions by collecting data from a selected population
• Analytical epidemiological studies are quantitative in nature
• Observational studies are qualitative

Study Designs

• Cohort Study: A forward-looking, longitudinal study (prospective or retrospective) that investigates incidence. It tracks a group of individuals to determine if exposure to a risk factor correlates with the development of a disease.
• Case-Control Study: A retrospective study that identifies a group of people with a disease and compares their exposure to a risk factor with a comparison group of people without the disease.
• Cross-Sectional Analytical Study: Examines a population's cross-section at a single point in time to measure exposure and outcome simultaneously. Example: BMI and serum cholesterol
• Cross-Sectional Observational Study: Focuses on the prevalence (how common), not the incidence of a disease. Used in investigations of non-fatal diseases.
• Ecological Study: Based on group-level data (e.g., average dietary fat intake and rates of a particular disease), not individual data. Cannot establish cause-effect relationships.

Disease Registries

• Databases specifically designed to collect information about individuals diagnosed with a particular disease.
• Registries can be built at hospital or population level.