Morbidity is illness in a population; mortality is death. Rates let nurses compare communities of different sizes and track change over time. Every rate has three parts: a numerator (events), a denominator (the population from which the events came), and a time period, multiplied by a base (100, 1,000, or 100,000) for easy reading.

Morbidity measures

Relationship: prevalence ≈ incidence × average duration (P ≈ I × D), when the disease is uncommon and conditions are stable. A cure or rapid death shortens duration and lowers prevalence; a treatment that prolongs survival without cure raises prevalence even though incidence is unchanged.

Mortality measures (US National Center for Health Statistics conventions)

The older perinatal Definition I (fetal deaths at 28 weeks or more + infant deaths under 7 days) still appears in textbooks and international comparisons; know both, and note which one a question uses. Internationally, the maternal measure per 100,000 live births is usually called the maternal mortality ratio.

Infant mortality rate is the classic single indicator of a community's overall health, because it reflects maternal health, access to prenatal care, nutrition, sanitation, and socioeconomic conditions.

Choosing the right denominator

• Only people at risk belong in an incidence denominator (exclude those who already have the disease or are immune when data allow).
• Case-fatality uses people with the disease; cause-specific death rate uses the whole population.
• Infant, neonatal, and maternal measures use live births, not the total population.

Crude vs. adjusted rates. A crude rate reflects the population's age structure. An older community will have a higher crude death rate even if its health is good. Age-adjusted (standardized) rates remove this effect so communities or years can be compared fairly. In direct standardization, each community's age-specific rates are applied to one standard population (NCHS uses the 2000 US standard population).

Other burden measures

• Years of potential life lost (YPLL): sums years lost before a set age (often 75); highlights early deaths from injury, overdose, and suicide.
• Disability-adjusted life years (DALYs) and quality-adjusted life years (QALYs): combine death and disability.
• Life expectancy: average years a person at a given age is expected to live under current death rates.

Data sources in the US: state vital records and the National Vital Statistics System (births, deaths, fetal deaths), CDC WONDER, notifiable disease reports (NNDSS), cancer registries, BRFSS and YRBSS surveys, and hospital discharge data. Causes of death are coded with the ICD-10 (the WHO International Classification of Diseases).

Calculations below use the full set-up; each answer was checked twice.

Example 1 — Cumulative incidence. At the start of the year, 20,000 adults in a town have no diabetes. During the year, 150 are newly diagnosed.

Incidence = 150 ÷ 20,000 = 0.0075 × 1,000 = 7.5 per 1,000 per year.

Example 2 — Mid-year population. A city had 200,000 residents at the start of the year and 210,000 at the end. There were 105 new Alzheimer disease diagnoses.

Mid-year population = (200,000 + 210,000) ÷ 2 = 205,000.

Incidence rate = 105 ÷ 205,000 × 100,000 = 51.2 per 100,000.

Example 3 — Point prevalence. A blood pressure screening of 10,000 adults finds 1,200 people already diagnosed and 300 new cases.

Prevalent cases = 1,200 + 300 = 1,500. Prevalence = 1,500 ÷ 10,000 × 100 = 15%. (The 300 new cases alone are not incidence here, because no at-risk group was followed over time.)

Example 4 — P ≈ I × D. Incidence is 5 per 1,000 per year and average duration is 4 years.

Prevalence ≈ 5 per 1,000 × 4 = 20 per 1,000.

Example 5 — Attack rate and secondary attack rate. Of 80 people at a banquet, 32 develop vomiting within 24 hours.

Attack rate = 32 ÷ 80 × 100 = 40%.

In the ill guests' households there are 20 susceptible contacts; 4 later become ill.

Secondary attack rate = 4 ÷ 20 × 100 = 20%.

Example 6 — Crude and cause-specific death rates, proportionate mortality. A state of 30,000,000 people records 300,000 deaths in a year, 15,000 from diabetes.

Crude death rate = 300,000 ÷ 30,000,000 × 1,000 = 10 per 1,000.

Cause-specific death rate (diabetes) = 15,000 ÷ 30,000,000 × 100,000 = 50 per 100,000.

Proportionate mortality (diabetes) = 15,000 ÷ 300,000 × 100 = 5%.

Example 7 — Case-fatality. A hepatitis A outbreak causes 100 cases and 2 deaths.

Case-fatality = 2 ÷ 100 × 100 = 2%.

Example 8 — Infant, neonatal, postneonatal. A county has 10,000 live births in a year. Thirty infants die before 28 days and 20 die between 28 days and 1 year.

Neonatal = 30 ÷ 10,000 × 1,000 = 3.0 per 1,000 live births.

Postneonatal = 20 ÷ 10,000 × 1,000 = 2.0 per 1,000 live births.

Infant = (30 + 20) ÷ 10,000 × 1,000 = 5.0 per 1,000 live births (neonatal + postneonatal).

Example 9 — Perinatal (Definition III). There are 2,000 live births, 40 fetal deaths at 20 weeks or more, and 10 infant deaths under 7 days.

Perinatal = (40 + 10) ÷ (2,000 + 40) × 1,000 = 50 ÷ 2,040 × 1,000 = 24.5 per 1,000.

Example 10 — Maternal mortality. Three maternal deaths (as defined above) occur among 15,000 live births. (CDC also tracks "pregnancy-related" deaths up to 1 year after pregnancy through separate surveillance and review committees; that is a different measure.)

Maternal mortality = 3 ÷ 15,000 × 100,000 = 20 per 100,000 live births.

Example 11 — Direct age adjustment. A standard population has 60,000 younger and 40,000 older adults (total 100,000). Town A's death rates are 2 per 1,000 (younger) and 30 per 1,000 (older).

Expected deaths = (60,000 × 0.002) + (40,000 × 0.030) = 120 + 1,200 = 1,320.

Age-adjusted rate = 1,320 ÷ 100,000 × 1,000 = 13.2 per 1,000. Repeating this for Town B with the same standard population allows a fair comparison.

• Calculate and interpret rates correctly for community assessment and grant or program reports.
• Choose incidence to study causes, outbreaks, and program impact; choose prevalence to plan services, staffing, and supplies.
• Report births, deaths, and reportable diseases accurately and on time; accurate death certificate data depend on good clinical documentation.
• Compare local rates with state and national data and with Healthy People 2030 targets, using age-adjusted rates when populations differ in age structure.
• Communicate numbers clearly to community members and decision makers (per 1,000 or per 100,000, with the time period stated).

• Births, deaths, and fetal deaths are registered under state vital records laws; data flow to the National Vital Statistics System.
• Small-number rates can identify individuals; health departments suppress or combine cells with very small counts to protect privacy.
• HIPAA permits reporting of vital events and disease data to public health authorities without authorization.
• Present disparities data (for example, higher infant or maternal mortality in some racial groups) with context about structural causes, not as a trait of the group, to avoid stigma.

Case 1 — Incidence or prevalence? A health department wants to know whether a new school-based asthma program reduced new asthma diagnoses.

Correct action: measure incidence before and after. Why: incidence reflects new occurrence; prevalence would also count children with long-standing asthma.

Case 2 — Misleading crude rate. A retirement community has a higher crude death rate than a college town, and a board member concludes its health care is worse.

Correct action: compare age-adjusted rates. Why: an older population has more deaths regardless of care quality.

Case 3 — Survival paradox. After a new HIV therapy becomes widely used, HIV prevalence in the county rises.

Correct action: explain that longer survival increases duration, so prevalence rises even if incidence falls. Why: P ≈ I × D.

• Using total population as the case-fatality denominator (use people with the disease).
• Calling deaths under 1 year the "neonatal" rate — that is the infant rate; neonatal is under 28 days.
• Using total population instead of live births for infant and maternal measures.
• Forgetting fetal deaths in the perinatal denominator.
• Counting only new cases for prevalence; prevalence includes old + new cases.
• Confusing case-fatality (severity of a disease) with cause-specific death rate (mortality burden in the population).
• Comparing crude death rates across populations with different age structures.
• Mixing perinatal Definition I (28 weeks) and Definition III (20 weeks) in one comparison.

• Incidence = new cases ÷ population at risk over time; prevalence = all existing cases ÷ population at a point or period.
• Prevalence ≈ incidence × duration; longer survival raises prevalence.
• Attack rate = incidence during an outbreak; secondary attack rate uses susceptible contacts.
• Crude death rate uses the mid-year population; textbooks often use per 1,000, while NCHS reports per 100,000.
• Case-fatality = deaths ÷ cases × 100 (severity).
• Infant (under 1 year), neonatal (under 28 days), postneonatal (28 days to under 1 year) — all per 1,000 live births.
• NCHS perinatal Definition III = fetal deaths at 20 weeks or more + infant deaths under 7 days, per 1,000 live births + those fetal deaths.
• Maternal mortality per 100,000 live births (deaths during pregnancy or within 42 days).
• Infant mortality is the best single indicator of a community's health.
• Age-adjusted rates are required to compare populations with different age structures.