DPH Prelims Vocabulary Flashcards: Health, Epidemiology, Prevention, and Biostatistics

Vocabulary-style flashcards for key terms found in the lecture notes, covering health concepts, epidemiology, prevention, and biostatistics.

Health (WHO definition)

State of complete physical, social and mental well-being, not merely the absence of disease or infirmity.

Determinants of Health

12 major factors identified by the Public Health Agency of Canada and WHO that influence health outcomes.

Income and Social Status

Health improves with higher income and better social standing; equitable wealth distribution supports healthier populations.

Employment

Unemployment, underemployment, and job stress are linked to poorer health; more control over work favors better health.

Education

Higher education correlates with better health through income, security, and sense of control.

Social Environments

Societal values, norms, stability, safety, and support networks shape health and well‑being.

Physical Environments

Air, water quality, housing, workplace safety, and road design influence health.

Healthy Child Development

Prenatal and early childhood experiences profoundly affect later health and coping skills.

Personal Health Practices and Coping Skills

Diet, activity, smoking, drinking, and coping with stress affect health.

Health Services

Access to and use of preventive and curative services influence health outcomes.

Social Support Networks

Support from family and friends buffers stress and improves health.

Biology and Genetic Endowment

Inherited factors affect lifespan, health, and disease risk.

Gender

Men and women experience different diseases at different ages.

Culture

Cultural beliefs, practices, and norms affect health behaviors and outcomes.

Physical Dimension of Health

Ability of the body to function; fitness results from genetics, environment, and lifestyle.

Social Dimension of Health

Ability to interact with others and participate in society.

Mental Dimension of Health

Ability to process information and think clearly.

Emotional Dimension of Health

Ability to cope, adapt and manage emotions.

Spiritual Dimension of Health

Belief systems and search for meaning beyond the material; psychospiritual well‑being.

Environmental Dimension of Health

External and internal environmental factors affecting health.

Germ Theory of Disease / Monocausal

Disease caused by a transmissible agent; one agent, one disease.

Epidemiological Triad

Disease results from interactions among agent, host, and environment.

Web of Causation

Disease arises from multiple interacting risk factors; no single cause.

Theory of General Susceptibility

Some groups have higher mortality/morbidity due to complex interactions.

Socio‑environmental Approach

Health is shaped by social and physical environments; improving health requires changing these environments.

Socio‑environmental Model (4 factors)

Human biology, lifestyle factors, environmental factors, and health care system factors.

Primordial Prevention

Prevent emergence of risk factors in populations where they have not yet appeared.

Primary Prevention

Actions before onset of disease to prevent it in healthy populations.

Secondary Prevention

Actions at incipient disease stage to halt progression and prevent complications.

Tertiary Prevention

Measures to reduce disability and prevent recurrence in established disease.

High‑risk (Target) Strategy

Preventive care focused on individuals at high risk; pros include motivation and fit, cons include at‑risk criteria and cost.

Mass (Whole Population) Strategy

Prevention applied to entire population; pros include broad reach, cons include dilution of effects.

Barriers to Preventive Strategies

Diversity, beliefs, advertising, pressure groups, access, and resources can impede prevention.

Transition of Disease Process

Transition sequence: disease → impairment → disability → handicap.

Prevention of Bias

Design considerations to minimize bias, including avoiding selection and information biases.

Screening

Testing apparently healthy individuals to detect unrecognized disease early for prevention or better prognosis.

Mass Screening

Screening of entire populations or large subgroups, usually without risk targeting.

High‑Risk / Selective Screening

Screening aimed at individuals known to be at higher risk.

Multiphasic Screening

Using two or more screening tests together on many people.

Opportunistic Screening

Screening performed when the opportunity arises, often in clinical settings.

Two‑Stage Screening

Positive screen leads to recall for further testing; reduces invasiveness and cost.

Validity

The accuracy of a test to measure what it intends; includes sensitivity and specificity.

Sensitivity

Ability of a test to correctly identify those with the disease (true positives).

Specificity

Ability of a test to correctly identify those without the disease (true negatives).

Association (Covariation)

Change in one variable coincides with change in another; not necessarily causal.

Causation

A cause or set of factors that produces disease; can be necessary, sufficient, both, or neither.

Predisposing Factors

Like age, sex, prior illness that create susceptibility to disease.

Enabling Factors

Circumstances that assist in recovery or maintenance of health (e.g., income, housing).

Precipitating Factors

Exposures to a specific or noxious agent triggering disease.

Reinforcing Factors

Repeated exposures or burden that exacerbate disease.

Temporal Relation (Causation Guideline)

Cause must precede effect in time.

Plausibility

Biological or logical rationale linking cause to effect.

Consistency

Findings are repeatedly observed across studies and settings.

Strength

Magnitude of association between exposure and disease.

Dose–Response Relationship

Increasing exposure leads to greater disease risk.

Reversibility

Removal of exposure reduces risk or removes effect.

Study Design

Appropriate research design strengthens causal inference.

Judging the Evidence

Systematic appraisal of all evidence for causation.

Biostatistics

Branch of statistics applied to biological, medical, or health data.

Descriptive vs Inferential Statistics

Descriptive summarizes data; inferential draws conclusions about a population.

Variable

A factor that can take different values among individuals in a study.

Data Type (Numerical vs Categorical)

Data can be numeric (quantitative) or categorical (qualitative).

Nominal Data

Categorical data with no natural order (e.g., gender: male/female).

Ordinal Data

Categorical data with a natural order (e.g., stages).

Interval Data

Numeric data with meaningful differences but no true zero (e.g., temperature in C).

Ratio Data

Numeric data with a true zero and meaningful ratios (e.g., height, weight).

Descriptive Measures of Central Tendency

Mean, median, and mode describe data center.

Centiles

Percentiles that divide a distribution into equal parts (e.g., 25th, 75th).

Variance

Average of squared deviations from the mean; measure of dispersion.

Standard Deviation

Square root of variance; expresses dispersion in original units.

Confidence Interval

Range likely to contain the true population parameter with a given probability.

Normal Distribution

Bell-shaped distribution where data cluster around the mean; defined by mean and SD.

T‑Distribution

Used for small samples; adjusts SE when n is small (typically n ≤ 60).

Binomial Distribution

Distribution of successes in n independent yes/no trials; basis for binomial tests.

Chi‑Square Distribution

Distribution used in tests of independence and goodness of fit.

Pearson Chi‑Square Test

Statistical test for association between categorical variables.

Sampling

Process of selecting a subset of a population for study.

Probability Sample

Each element has a known, nonzero chance of selection.

Random Sample

All elements have an equal chance of being selected.

Systematic Sample

Select every nth element from a list; easier in practice.

Stratified Random Sample

Population divided into strata; random samples drawn from each.

Cluster Sample

Population divided into clusters; clusters are randomized and all elements in selected clusters are used.

Convenience Sample

Non‑probability sample based on readily available subjects.

Quota / Snowball / Volunteer Samples

Non‑probability sampling methods with varying biases.

Statistical Packages

Software (e.g., spreadsheets, SAS, SPSS) used to perform analyses.

Fields vs Records (Database Terms)

Fields are variables (columns); records/cases are individuals (rows).

Variable Names and Labels

Code names (e.g., SBP) with descriptive labels for clarity.

Data Type Integrity (Numbers, Not Text)

Statistical calculations require numeric data; nominal/ordinal should be coded numerically.