Theoretical Foundations of Public Health

56 topics across 7 chapters

Chapter 1

Public health as a field: history, philosophy, and core concepts

Public health vs. clinical medicine; core functions and essential services

Historical milestones and paradigm shifts (sanitation, germ theory, chronic disease, modern PH)

Levels of prevention (primary/secondary/tertiary) and the prevention paradox

Population health frameworks (e.g., socioecological model) and why “population” is a unit of analysis

Chapter 2

Determinants of health and health inequities: conceptual models

Social determinants of health (SDOH): pathways from social conditions to health outcomes

Conceptualizing and measuring inequities: definitions, comparisons, and stratification

2 subtopics

Equity metrics: absolute vs. relative differences; rate differences vs. rate ratios

Intersectionality and decomposition basics: thinking beyond single-axis disparities

Structural racism/sexism and systems of power as upstream drivers: core theoretical claims and implications

Environmental and occupational health conceptual models (exposure pathways, dose, vulnerability)

Life-course perspective: critical periods, accumulation, and intergenerational effects

Chapter 3

Epidemiologic theory and causal thinking

Disease frequency and association: core epidemiologic quantities

2 subtopics

Incidence vs. prevalence; risk vs. rate; person-time reasoning

Measures of association (RR, OR, HR): interpretation and common pitfalls

Study designs and validity: how design choices shape causal claims

3 subtopics

RCTs, cohort, case-control, cross-sectional: when each design answers a question well

Selection bias and information bias: mechanisms, examples, and prevention strategies

Ecologic and multilevel designs: what they can and cannot identify

Confounding, effect modification, and mediation: conceptual distinctions and why they matter

Causal inference frameworks: DAGs and counterfactual reasoning

2 subtopics

Causal diagrams (DAGs): backdoor paths, colliders, and adjustment sets

Counterfactuals/potential outcomes: causal contrasts and identification intuition

Screening and diagnostic test theory: sensitivity, specificity, PPV/NPV, and base rates

Chapter 4

Measurement, data, and biostatistical reasoning for public health

Data types, distributions, and summary measures (mean/median, variance, rates, standardization intuition)

Statistical inference: uncertainty, sampling, and error rates

3 subtopics

Probability and sampling distributions: what repeated sampling means in practice

Confidence intervals vs. p-values; hypothesis testing and Type I/II error

Multiple comparisons and reproducibility basics (p-hacking, preregistration, robustness)

Regression thinking for public health (prediction vs explanation, adjustment, interpretation)

2 subtopics

Linear vs. logistic regression: assumptions, link functions, and interpretation of coefficients

Confounding control via modeling: stratification vs adjustment; overadjustment intuition

↗ Causal inference frameworks: DAGs and counterfactual reasoning (see Chapter 3)

Data quality: missing data mechanisms and measurement error (and how they bias conclusions)

Power, sample size, and communicating uncertainty (practical interpretation, not just formulas)

Chapter 5

Health behavior, social, and organizational theory

Individual behavior change theories: HBM, TPB, and Transtheoretical Model (what each explains)

Social and community theories: Social Cognitive Theory and Diffusion of Innovations

Organizational and implementation theories: CFIR, RE-AIM, and why interventions fail to scale

Risk perception, communication, and health literacy: core theoretical ideas and common failures

Program theory and logic models: mapping inputs → activities → outputs → outcomes

Chapter 6

Health systems, policy, and governance: theoretical lenses

Health system structures and financing models (Beveridge/Bismarck/mixed; incentives and tradeoffs)

Policy process theories: Kingdon’s Multiple Streams and Advocacy Coalition Framework

Governance and public health law basics: authority, enforcement, and federalism tradeoffs

Economics for public health: externalities, public goods, market failure, and cost-effectiveness logic

Quality, performance, and accountability frameworks (access, quality, equity; measurement implications)

Chapter 7

Ethics and evidence-to-action: turning theory into decisions

Ethical theories for public health: utilitarianism, deontology, and principlism (how they conflict)

Human subjects research principles and IRBs: Belmont principles and informed consent challenges

Evidence hierarchies and guideline development: why “best evidence” depends on the question

↗ Program theory and logic models: mapping inputs → activities → outputs → outcomes (see Chapter 5)

Knowledge translation and dissemination: moving evidence into practice and policy

Evaluation theory: formative vs process vs outcome vs impact; attribution vs contribution