Key concepts and framing

• The topic centers on diseases moving across populations and how we measure them quantitatively; some math is unavoidable.
• Morbidity vs mortality (terminology in the transcript):
  • Morbidity is typically disease occurrence; mortality is death. The transcript notes morbidity as death, which is nonstandard, but we’ll reflect the wording there while also noting the conventional definitions.
• Mortality and morbidity provide the foundation for epidemiologic studies; standard methods of measurement are needed to compare across populations.
• Why compare populations?
  • For programming and resource allocation decisions, we need to compare disease burden across populations.
  • Populations differ in size and structure (age, sex, etc.), so raw counts are not enough; rates and standardization help.
• Key progression in analysis:
  • Start with crude rates (unadjusted).
  • Move to age/sex standardization and adjusted rates for better cross-population comparability.

Rates, counts, and what they mean

• A rate contains three key elements:
  • Event frequency (numerator): number of events of interest (e.g., deaths, new cases).
  • Population at risk (denominator): the population among which the events occur.
  • Time period over which the events are counted (time component).
• Rate base multiplier (e.g., per 1000, per 100,000):
  • Multipliers make rates interpretable and comparable. Some conventions depend on the type of event.
  • Common bases include 1,000 and 100,000.
  • Examples: infant mortality and some birth-related rates use different bases; you’ll learn these conventions as you dive into each rate type.
• Counts vs rates (conceptual):
  • Counts tell you how many events occurred in a population, but they’re sensitive to population size.
  • Rates adjust for population size and time to allow comparison across populations and over time.
• Percent (as discussed in class):
  • Percent within a country may reflect the proportion of all disease that a specific disease represents (denominator is all cases in the country, numerator is cases of the disease of interest).
  • This is different from rates, which incorporate a population-at-risk denominator and a time period.

Crude rates: definition, example, and intuition

• Definition:
  • Crude rate = number of events in a population during a specified time period divided by the population size (often at the midpoint of the year), multiplied by a base (commonly 1,000 or 100,000).
  • Not adjusted for age, sex, or other factors.
• Common example: crude mortality rate (death rate) or crude death rate.
• US crude death rate example (2017):
  • Deaths ≈ $2{,}800{,}000$ in the year.
  • Midpoint population (denominator) is used; the result is often presented as deaths per 100,000 population.
  • Reported example: about $8.64 imes 10^{2}$ deaths per $100{,}000$ population, i.e., roughly $864$ deaths per 100,000 people.
  • General form: $ext{CDR} = \frac{D}{P<em>{ ext{mid}}} imes 10^k$ where $D$ = deaths, $P</em>{ ext{mid}}$ = population at midpoint, and the base multiplier $10^k$ reflects the chosen base (e.g., $10^3$ for per 1,000, per 1,000,000, or $10^5$ for per 100,000).
• A sample of crude death rates across countries may be presented per 1,000 population (or per 1,000 people) instead of per 100,000; this affects the numeric value but not the underlying concept.
• Strengths of crude rates:
  • Simple to calculate and interpret.
  • Reflect the overall burden of a population.
• Limitations of crude rates:
  • Do not adjust for population structure (age, sex, etc.).
  • Differences between populations may reflect demographic structures rather than true differences in underlying risk.
• Discussion prompt (from transcript): factors that can increase crude death rate in a country:
  • Age structure (older populations tend to have higher death rates).
  • Safety/violence-related factors.
  • Economic and health context (wealthier vs poorer countries; older populations vs higher disease burden).
• Takeaway:
  • Crude rates are useful as a starting point, but be cautious when comparing across populations with different age and sex structures.
  • Next class will cover specific (age- and sex-specific) and adjusted rates to address these issues.
• Pros and cons recap:
  • Pros: simple to calculate, easy to interpret, reflects burden.
  • Cons: not adjusted for key demographic differences; can be misleading for cross-population comparisons.

Natality measures and perinatal periods (birth-related metrics)

• Natality refers to measures around birth; several key rates and time windows are used.
• Important time periods around birth:
  • Fetal period: begins around gestational week 20; survival outside the womb becomes plausible around ~20 weeks.
  • Late fetal period: from ~week 28 gestation to birth.
  • Neonatal period: from birth (0 days) to 28 days old.
  • Neonatal vs perinatal distinction is nuanced; focus here is on neonatal (0–28 days) and post-neonatal (28 days to 1 year).
  • Infant period: from birth to 12 months (1 year).
• Crude birth rate (CBR):
  • Definition: number of live births in a year divided by the population at the midpoint of the year, multiplied by a base (commonly 1,000).
  • Rate base multiplier: typically 1,000 for births.
  • Denominator: population size at midpoint of the year; numerator: live births in the year.
• Live birth definition (infant milestone for birth measures):
  • A live birth is a birth in which the baby shows signs of life after birth (breathing, heartbeat, umbilical cord pulsation, etc.).
• Fertility rate (fertility in demography):
  • Definition: number of live births divided by the number of women of childbearing age, typically 15–44 years, multiplied by 1,000.
  • Formula: $ext{FR} = \frac{ ext{live births}}{N_{15-44}} imes 1000.$
  • Practical note: used to track reproductive performance and potential future population growth.
• The United States fertility rate over time (illustrative):
  • The rate has fallen substantially over the 20th and early 21st centuries, with a notable rise in the postwar era and declines in more recent decades.
  • The economy is a major correlate: economic upswings often coincide with higher fertility, downturns with lower fertility.
• Infant mortality rate (IMR):
  • Definition: number of infant deaths (death before age 1) during a year divided by the number of live births in the same year, multiplied by a base (commonly 1,000).
  • Formula: $ext{IMR} = \frac{D<em>{ ext{infant}}}{B} imes 1000,$ where $D</em>{ ext{infant}}$ = infant deaths, $B$ = live births.
  • In the United States, IMR has declined markedly from the mid-20th century (e.g., from around 60 per 1,000 live births in 1935 to about 7–8 per 1,000 in more recent years).
• Neonatal and post-neonatal mortality rates:
  • Neonatal mortality rate (NMR): deaths within the first 28 days of life per 1,000 live births.
  • $ext{NMR} = \frac{D_{ ext{neonatal}}}{B} imes 1000.$
  • Post-neonatal mortality rate (PNMR): deaths from 28 days to 1 year per 1,000 live births.
  • $ext{PNMR} = \frac{D_{ ext{post-neonatal}}}{B} imes 1000.$
  • Relationship: $ext{IMR} = ext{NMR} + ext{PNMR}.$
• Fetal death rate (FDR):
  • Definition: deaths after 20 weeks gestation, typically per 1,000 live births (or per 1,000 pregnancies, depending on convention).
  • In the transcript: fetal deaths after 20 weeks or more gestation, used in calculations adding to live births in the denominator and multiplied by 1,000.
• Maternal mortality rate (MMR):
  • Definition: maternal deaths assigned to causes related to pregnancy, per 100,000 live births.
  • Formula: $ext{MMR} = \frac{D_{ ext{pregnancy-related}}}{B} imes 100{,}000.$
  • Important nuance: a death must be related to the pregnancy; deaths from unrelated causes during pregnancy do not count.
• Summary of perinatal conceptual map:
  • Fetal period (before birth) → fetal deaths counted in FDR alongside live births via denominators.
  • Neonatal period (0–28 days) and post-neonatal period (28 days–1 year) together compose IMR via NMR and PNMR.
  • Infant mortality rate (IMR) covers deaths in the first year of life; equals the sum of neonatal and post-neonatal mortality rates.
  • Birth-related measures rely on live births in the denominator and period-specific death counts (or births) in the numerator.

Population structure, interpretation, and adjustments

• Age structure matters:
  • Countries with older populations can have higher crude death rates simply due to age, not necessarily higher risk of death overall.
  • Conversely, younger populations may show lower crude death rates even if absolute disease burden is substantial.
• This is why crude rates must be used with caution when comparing across populations with different age or sex structures.
• Next steps (not covered in this class but foreshadowed): specific rates (age- and sex-specific) and adjusted rates (standardized rates) to control for population structure.

Practical takeaways and exam expectations

• Crude rates are a starting point for comparing disease frequencies but can be misleading if population structure differs.
• Be prepared to calculate and interpret the following on exams and homework:
  • Crude death rate: $ext{CDR} = \frac{D}{P_{ ext{mid}}} imes 1000 ext{ (or } imes 100{,}000 ext{)}.$
  • Infant mortality rate: $ext{IMR} = \frac{D_{ ext{infant}}}{B} imes 1000.$
  • Neonatal mortality rate: $ext{NMR} = \frac{D_{ ext{neonatal}}}{B} imes 1000.$
  • Post-neonatal mortality rate: $ext{PNMR} = \frac{D_{ ext{post-neonatal}}}{B} imes 1000.$
  • Relationship: $ext{IMR} = ext{NMR} + ext{PNMR}.$
  • Fetal death rate: $ext{FDR} = \frac{D_{ ext{fetal}}}{B} imes 1000.$
  • Maternal mortality rate: $ext{MMR} = \frac{D_{ ext{pregnancy-related}}}{B} imes 100{,}000.$
  • Fertility rate: $ext{FR} = \frac{ ext{live births}}{N_{15-44}} imes 1000.$
  • Live births and live-birth-based rates rely on population at midpoint and the appropriate multiplier.
• Ethical and practical considerations:
  • Differences in healthcare access, public health infrastructure, vaccinations, sanitation, and socioeconomic status can drive observed differences in infant and maternal mortality.
  • Crude rates do not reflect disparities within populations (e.g., by race/ethnicity); important for equity-focused work.
• Exam strategy hinted in the transcript:
  • Expect questions that require calculating the range of natality measures (fertility rate, infant mortality, neonatal and post-neonatal mortality, fetal death rate, maternal mortality) using the provided definitions and base multipliers.
  • Expect to discuss why crude rates should be used cautiously in cross-country comparisons and how standardization helps.

Quick reference: essential formulas (LaTeX)

• Crude death rate (per 1,000 or 100,000):
  • $ext{CDR} = \frac{D}{P_{ ext{mid}}} imes 10^3 ext{ or } imes 10^5.$
• Infant mortality rate (per 1,000 live births):
  • $ext{IMR} = \frac{D_{ ext{infant}}}{B} imes 1000.$
• Neonatal mortality rate (per 1,000 live births):
  • $ext{NMR} = \frac{D_{ ext{neonatal}}}{B} imes 1000.$
• Post-neonatal mortality rate (per 1,000 live births):
  • $ext{PNMR} = \frac{D_{ ext{post-neonatal}}}{B} imes 1000.$
• Infant mortality relationship:
  • $ext{IMR} = ext{NMR} + ext{PNMR}.$
• Fetal death rate (per 1,000 births):
  • $ext{FDR} = \frac{D_{ ext{fetal}}}{B} imes 1000.$
• Maternal mortality rate (per 100,000 live births):
  • $ext{MMR} = \frac{D_{ ext{pregnancy-related}}}{B} imes 100{,}000.$
• Fertility rate (per 1,000 women aged 15–44):
  • $ext{FR} = \frac{ ext{live births}}{N_{15-44}} imes 1000.$