Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Data Collection by Observations01:08

Data Collection by Observations

Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
Longitudinal Studies01:26

Longitudinal Studies

Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
Longitudinal Research02:20

Longitudinal Research

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
Observational Studies01:11

Observational Studies

Observational studies are a type of analytical study where researchers observe events without any interventions. In other words, the researcher does not influence the response variable or the experiment's outcome.
There are three types of observational studies – Prospective, retrospective, and cross-sectional.
Prospective Study
Prospective studies, also known as longitudinal or cohort studies, are carried out by collecting future data from groups sharing similar characteristics. One example of...
Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Trajectory scanning as a predictive coding mechanism for goal-directed navigation, obstacle avoidance and episodic memory.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences·2026
Same author

Survivability in patients with rare sigmoid colon adenocarcinoma variants: exploring the influence of rural-urban continuum codes and social determinants of health in the USA.

Cancer causes & control : CCC·2026
Same author

Associations Between Football-Related Exposures, Head Injury, Tinnitus, and Neuropsychological Health Outcomes Among Professional American-Style Football Players.

Sports medicine - open·2026
Same author

HIV Self-Test Program Preferences Among Non-Hispanic Black and Hispanic Men Who Have Sex with Men in the Southern United States: A Discrete Choice Experiment.

AIDS and behavior·2026
Same author

Factors Associated With Functional Outcomes in Former Professional American-Style Football Players With Symptomatic Knee and Hip Osteoarthritis.

Orthopaedic journal of sports medicine·2026
Same author

Demographic patterns in quantitative sensory testing and clinical pain among former professional American-style football players.

Pain reports·2026

Related Experiment Video

Updated: Jun 15, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

Methods for retrospective geocoding in population studies: the Jackson Heart Study.

Jennifer C Robinson1, Sharon B Wyatt, DeMarc Hickson

  • 1School of Nursing, University of Mississippi Medical Center, 2500 North State Street, Jackson, MS 39216-4505, USA. jcrobinson@son.umsmed.edu

Journal of Urban Health : Bulletin of the New York Academy of Medicine
|February 27, 2010
PubMed
Summary
This summary is machine-generated.

Creating a reliable geographic information system (GIS) for epidemiological studies is feasible. This study details a multiphase geocoding method achieving 99% success in retrospectively geocoding 5,302 participants for spatial epidemiology research.

Related Experiment Videos

Last Updated: Jun 15, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

Area of Science:

  • Epidemiology
  • Geographic Information Systems (GIS)
  • Spatial Data Analysis

Background:

  • Geographic information systems (GIS) are increasingly used in epidemiological studies.
  • Limited details on geocoding methods hinder spatial data validity assessment.
  • Retrospective GIS creation requires robust geocoding strategies.

Purpose of the Study:

  • To describe the multiphase geocoding methods used to retrospectively create a GIS for the Jackson Heart Study (JHS).
  • To demonstrate the feasibility and accuracy of retrospective GIS development in large epidemiological cohorts.
  • To provide practical insights for enhancing geocoding success in similar studies.

Main Methods:

  • Utilized baseline data from 5,302 JHS participants (2000-2004) for retrospective geocoding.
  • Employed a multiphase approach including initial geocoding with ArcGIS, followed by interactive methods for ungeocodable addresses.
  • Incorporated data abstraction, additional maps, street reference files, and address verification for improved geocoding accuracy.

Main Results:

  • Successfully geocoded 96% of addresses initially with ArcGIS.
  • Achieved geocoding for all but 13 addresses (nearly 99% overall cohort) through interactive and verification strategies.
  • Geocoding validation confirmed highly accurate and reliable geographic data, establishing a dependable spatial database.

Conclusions:

  • Retrospectively developing a reliable GIS for large epidemiological studies is feasible.
  • The described multiphase geocoding protocol enhances accuracy and success rates.
  • The resulting spatial database supports further spatial epidemiology investigations and study validation.