Preventive Medicine Flashcards

A county health department conducts a screening program for hypertension using a BP threshold of ≥140/90 mmHg. The test has 85% sensitivity and 90% specificity. The prevalence of hypertension in the screened population is 8%. What is the positive predictive value (PPV) of this screening test?

Answer: 42.5%

PPV = (Sensitivity × Prevalence) / [(Sensitivity × Prevalence) + ((1 − Specificity) × (1 − Prevalence))]. Plugging in: (0.85 × 0.08) / [(0.85 × 0.08) + (0.10 × 0.92)] = 0.068 / (0.068 + 0.092) = 0.068 / 0.160 ≈ 42.5%. Low prevalence dramatically lowers PPV even with a high-specificity test — a core principle in screening program design.

Which of the following best describes the 'prevention paradox' as articulated by Geoffrey Rose?

Answer: A large number of people exposed to a small risk may generate more cases than a small number exposed to a high risk, so population-wide interventions produce most cases prevented but few personal benefit per person

Rose's prevention paradox states that because the majority of cases in a population arise from the large segment at moderate risk (not the small high-risk tail), population-wide strategies prevent more total cases than high-risk strategies — yet each individual in the population gains only a small personal benefit. This justifies broad public health measures (e.g., salt reduction) even when individual risk reduction seems trivial.

A physician identifies a 55-year-old patient with a 10-year ASCVD risk of 9.8% using the Pooled Cohort Equations. According to current ACC/AHA guidelines, which of the following best characterizes the recommended approach for statin therapy in this patient?

Answer: Engage in a clinician-patient risk discussion; a risk-enhancing factor or coronary artery calcium (CAC) score may help inform the decision

The ACC/AHA 2018 cholesterol guidelines define the 7.5–10% 10-year ASCVD risk range as a 'borderline' risk zone where the decision to initiate statin therapy should involve a risk discussion. Risk-enhancing factors (e.g., hs-CRP ≥2, ABI <0.9, LDL-C ≥160) or a CAC score (CAC = 0 favors withholding; CAC ≥100 favors initiating) are recommended to resolve borderline-risk patients — not automatic treatment or withholding.

An outbreak investigation reveals that 40 of 200 attendees at a catered banquet developed gastrointestinal illness. The attack rate among those who ate shrimp was 55%, while the attack rate among those who did not eat shrimp was 15%. What is the attributable risk percent (AR%) among the exposed?

Answer: 72.7%

AR% among the exposed = (Risk in exposed − Risk in unexposed) / Risk in exposed × 100 = (0.55 − 0.15) / 0.55 × 100 = 0.40 / 0.55 × 100 ≈ 72.7%. This means approximately 73% of illness among shrimp eaters is attributable to shrimp consumption, assuming causality — distinguishing it from relative risk or absolute risk difference alone.

A state is evaluating a mandatory childhood immunization program. Program analysis shows that for every 1,000,000 doses of a vaccine administered, 1 child develops vaccine-associated encephalitis (a severe adverse event), while the vaccine prevents 500 cases of disease, 50 hospitalizations, and 5 deaths. Which ethical principle is MOST directly in tension with the mandatory nature of this program?

Answer: Autonomy

Mandatory vaccination programs override individual choice by compelling participation regardless of personal or parental preference — directly conflicting with autonomy (the right of individuals to make informed decisions about their own medical care). While beneficence (population benefit), non-maleficence (balancing rare harms), and justice (equitable protection) are all relevant, mandating a medical intervention without consent is quintessentially an autonomy conflict, which is why exemption policies and public health ethics debates center on this tension.

In evaluating a new occupational health screening program, an investigator notes that employees found to have early-stage disease through screening appear to survive longer than historical controls diagnosed after symptom onset — even though no effective treatment exists for the condition. This observation MOST likely reflects which bias?

Answer: Lead-time bias

Lead-time bias occurs when screening detects disease earlier in its natural history, advancing the time of diagnosis without altering the biological course or time of death. Survival appears longer because the clock starts earlier, not because the patient lives longer. Length-biased sampling (a related but distinct concept) refers to screening preferentially detecting slower-progressing, less aggressive disease — but the key signal here (no effective treatment yet longer apparent survival) most directly implicates lead-time bias.