Population health

The study of population health is mostly rooted in classical epidemiology, which focuses on the distribution and determinants of disease in populations. Population health studies have a wide range of applications that include guiding public health policy and interventions, evaluating the importance and potential impact of PICO questions for clinical research, and informing clinical practice (e.g., using prevalence measures to estimate the pretest probability of a disease). The most common types of epidemiological studies used in population health are observational studies. These can be descriptive studies (e.g., ecological studies), analytical studies (e.g., cohort studies), and studies that can be both observational and analytical (e.g., cross-sectional studies). They typically seek to identify populations with particular outcomes and assess the association between potential exposures and these outcomes. This article focuses on basic concepts of population health (e.g., population pyramids, and endemic, epidemic, or pandemic diseases) and measures of disease frequency, e.g., incidence, prevalence, birth rates, mortality rates, case-fatality rates, morbidity, and disease burden.

The following concepts are discussed separately: causal relationships in research studies, other reasons for observed associations (e.g., random errors, systematic errors, confounding), measures of association commonly encountered in studies of clinical interventions (e.g., relative risk, absolute risk reduction), measures used in the evaluation of diagnostic research studies (e.g., sensitivity, specificity), precision and validity, and foundational statistical concepts (e.g., measures of central tendency, measures of dispersion, normal distribution, confidence intervals).

See also “Epidemiology,” “Statistical analysis of data,” and “Interpreting medical evidence.”

Population pyramid

• Definition: a graphical representation of the age and sex distribution of a population ^[1]
• Examples
  • Expansive pyramid
    • Represents a population in which there is a higher percentage of young people of both sexes
    • For example, a population with a high birth rate and low life expectancy
  • Stationary pyramid
    • Represents a population in which age and sex distribution remains relatively constant over time
    • For example, a population with a low birth rate, low mortality, and increasing life expectancy
  • Constrictive pyramid
    • Represents a population in which there is a higher percentage of elderly people of both sexes
    • For example, a population with a low birth rate and high life expectancy

Demographic transition

• Definition: changes that occur in a population that goes from having high birth rates and high death rates to having low birth rates and low death rates ^[1]
• Demographic Transition Model: describes, in stages, the evolving relationship between birth and death rates in a population over time ^[1]
  • Stage I: high birth rates and high death rates (low or no population growth)
  • Stage II: high birth rates and decreasing death rates (high population growth)
  • Stage III: decreasing birth rates and low death rates (slowed population growth)
  • Stage IV: low birth rates and low death rates (low or no population growth)

Endemic, epidemic, and pandemic diseases

Diseases can be classified according to their pattern of occurrence across time and geographic area.

Overview

• Measures of disease frequency can be used to: ^[3]
  • Quantify mortality and/or morbidity (i.e., incidence and prevalence of disease)
  • Describe population characteristics (e.g., at-risk populations, life expectancy)
  • Determine the association between two factors (e.g., exposure and disease)
• Data is systematically collected and analyzed and then used for planning, implementing, and evaluating public health practices (i.e., public health surveillance), in order to:
  • Detect changes in health behavior, health issues, and identify potential outbreaks and epidemics
  • Estimate the magnitude of a health issue (e.g., disease or risk factor), measure trends, and characterize a disease
  • Identify individuals with infectious diseases or exposures to environmental agents and their contacts
  • Determine the effectiveness of control measures and public health programs
  • Develop future research hypotheses

Incidence and prevalence

Incidence

• Description: number of new cases ^[4]
• Population at risk: the group of people that are at risk of developing the condition being studied (individuals at risk cannot have the condition at the time the study period starts)
• Incidence study
  • Used to determine the incidence of a particular event in a population during a certain time period (usually a year). If the event in consideration is death, the study is called a mortality study.
  • Usually performed as a cohort study to compare the incidence of an event (e.g., disease) between two groups

Prevalence

• Description: number of current (i.e., new and preexisting) cases
  • The proportion of all people with a disease to the total number of people in a population at a particular point in time or time period
  • Corresponds to disease frequency (how common a disease is)
  • Reflects the pretest probability of a disease
  • Correlates directly with the positive predictive value and inversely with the negative predictive value (see “Evaluation of diagnostic tests” below)
• Formula: total number of cases/total population during a specific time
  • The time period can be:
    • A specific point in time (point prevalence), e.g., a day
    • A specific period of observation (period prevalence), e.g., during puberty
  • For example, if a survey conducted in 2020 in a town with a population of 120,000 reveals that 451 people have lung cancer, the prevalence of lung cancer in that town would be 451 per 120,000, which would be expressed as 375.8 per 100,000.

Relationship between prevalence and incidence

• Formula: (Incidence) x (average duration of disease) = prevalence
• In a chronic disease, the prevalence is usually greater than the incidence, while in an acute disease, the values are usually similar.
• An increased prevalence with a stable incidence can be explained by factors that result in increased survival and/or prolonged duration of the disease (e.g., improved quality of care of patients).
• A decreased prevalence with a stable incidence can be the result of factors that increase mortality and/or speed of healing time.
• Extensive vaccine administration and/or the removal of risk factors can cause prevalence and incidence to decrease together.
• the population is in a steady state, the relationship between incidence rate (IR), prevalence (P), and the average duration of the disease (T) can be described mathematically as follows:
  • P/(1 - P) = IR × T
    OR
  • IR = (P/(1 - P))/T
• If the disease is extremely rare, P ≈ IR × T
• Number of new cases per unit time = IR × (population at risk)

Mortality

• Definition: the number of deaths in a population within a specific time interval

Morbidity ^[8]

• Definition: the number of individuals in a population with a disease at a specific point in time or specific time interval (i.e., disease frequency)
• Description
  • Estimated using incidence and/or prevalence data
  • Data sources include: health surveys, registries (e.g., cancer registries), hospital or general practice statistics (e.g., electronic health records)

Disease burden

The “Global Burden of Disease (GBD) Study” provides estimates of the burden of diseases globally (see “Tips and Links”).

• Definitions: estimated impact of a disease on a given population
• Can be estimated using, e.g.:
  • Disability-adjusted life years (DALYs): years of life lost due to disease, disability, and/or premature death
  • Quality-adjusted life years (QALYs): number of years a person is expected to live corrected for loss of quality of life caused by diseases and disabilities
  • Other indicators: financial cost, mortality, and/or morbidity

Other measures

• Birth rate: the number of live births divided by the number of people in a population within a specific time interval ^[5]
• Fertility rate: the number of live births among women of childbearing age (15–44 years) in a population within a specific time interval
• Health-adjusted life expectancy: average number of years a person is expected to live in full health

Leading causes of death in the US ^[9]