Measuring Population Health Metrics

A state of complete physical, mental, and social well-being, not merely the absence of disease or infirmity.

The ability to lead socially and economically productive lives.

A state of optimal well-being in all dimensions of health.

A state of being healthy in the absence of disease or injury.

Health is dynamic and can be improved over time, meaning it should not be measured in a fixed, finite way.

A quantitative health metric that measures the number of deaths in a population.

The average number of years a person is expected to live in a given population.

A quantitative health metric that measures the number of deaths in infants under one year of age.

A measurement of the health burden of a disease by adding years of life lost due to premature death and years lived with disability.

A health metric focusing on the number of years a person lives in 'good' health.

A measurement of the impact of specific diseases on a population by quantifying the number of years of healthy life lost due to the disease.

Health metrics beyond mortality, focusing on the impact of disease on quality of life.

This refers to the use of quantitative and qualitative factors to understand the overall health of a population, going beyond just the presence or absence of disease.

The shift from focusing only on disease reporting to include the underlying causes of disease, such as negative health behaviors, which are amenable to intervention.

Factors that increase the likelihood of developing a particular health problem or condition.

Genetic inheritance, aging, and other biological factors that influence health.

Environmental factors that can impact health, such as food, air, water, and exposure to infectious diseases.

Lifestyle choices that contribute to health risks, such as diet, exercise, and smoking.

Includes factors like poverty, stress, personality, and cultural influences that impact health.

The availability and accessibility of healthcare services for a population.

The interconnectedness of various risk factors, showing how one can influence another, leading to specific negative health outcomes.

A study that follows a large group of people over time to see if differences in exposure to a factor (like diet) lead to differences in outcomes (like heart disease).

Comparing a group with a specific condition (like heart disease) to a similar group without the condition to investigate potential causes by examining past exposure to factors like diet.

Factors (like age, lifestyle) that can influence both exposure to something and the development of a disease, making it difficult to determine the true impact of the exposure.

A type of bias that occurs when participants are chosen in a way that skews the results. This can happen when specific types of individuals are more likely to join a study.

A bias that arises when participants with the condition being studied (e.g., heart disease) are more likely to recall or report past exposures differently compared to those without the condition, even if the exposures were actually the same.

A measurement of income inequality within a population. It takes values from 0 to 1, where 0 represents perfect equality (all individuals have the same income) and 1 represents maximal inequality (one individual has all the income).

The study of the distribution and determinants of the occurrence and patterns of health outcomes in human populations.

The rate of new cases of a disease within a defined population over a specific time period.

The total number of cases of a disease existing in a defined population at a specific point in time.

A measure of association between exposure and outcome in a case-control study. It estimates the relative risk that would have been observed if a cohort study had been conducted.

The ratio of the incidence rate of a disease in an exposed group to the incidence rate in an unexposed group. It measures the strength of the association between an exposure and a health outcome.

A research study designed to test the effectiveness of a new treatment or intervention by comparing a group that receives the treatment to a control group that does not.

A type of intervention study where participants are randomly assigned to either the treatment group or the control group, and neither the participants nor the researchers know who is in each group.

A type of intervention study that involves testing a new drug or vaccine in a controlled setting to assess its safety and effectiveness.

A health outcome that develops slowly and may not be immediately apparent.

A health outcome that appears quickly and is often severe.

The concept that within developed countries, it is the nations with the most equal income distribution, not the richest ones, that have the highest life expectancy.

The concept that individual wealth alone does not guarantee good health, and that relative wealth (income inequality) plays a significant role in health outcomes.

The concept that imprecise measurement of health data, especially related to socioeconomic status, can lead to inaccurate estimations of differences in health outcomes between economic groups.