Class 24-25 Flashcards
(15 cards)
Cross-sectional study
Observational studies that examine relationships of health/disease to other variables of interest AT THE SAME TIME
AKA a PREVALENCE study
Entire population or a subset is selected for study
Called cross-sectional because information gathered represents what is occurring at a point in time or time-frame across a large population
A “snap-shot” in time
Goal of Cross-Sectional studies
Focuses SIMULTANEOUSLY on disease & population characteristics, including exposures, health status, health-care utilization, etc…(depending on study)
Seeks associations (NOT Causation)
Generates and tests hypotheses
By repetition in different time periods, can be used to measure change/trends (not in same patients); repeated studies done on a monthly, annual basis
Most cross-sectional studies are surveys or databases capturing different aspects of US population:
-Data from different perspectives (ex: inpatient vs. outpatient) or via different study/survey methodologies and information captured
2 Cross-Sectional Approaches
- Collect data on each member of the population
- Pregnancy-Smoking data from KC Health Dept.
- More frequently utilized in city/state-level evaluations, if data already tracked (ongoing collection) - Take a sample of the population and draw inferences to the remainder (generalizable)
- More frequent approach for U.S.-level data
Probability samples
- Most common sampling scheme
- Every element in the population has a known (non-zero) probability of being included in sample
Examples of Probability Sampling schemes
1) Simple Random sampling
- Assign random numbers, then take randomly selected numbers to get desired sample size, OR
- Assign random numbers, then sequentially-list numbers and take desired sample size from top (or bottom) of listed numbers
2) Systematic Random sampling
- Assign random numbers, then randomly sort these random numbers, then select highest (or lowest) number, then SYSTEMATICALLY, by a pre-determined sampling-interval, take every Nth numbers to get desired sample size
3) Stratified Simple Random sampling
- Stratify sampling frame by desired characteristic (ex: gender_) then use Simple random sampling to select desired sample size
4) Stratified Disproportionate Random sampling
- Disproportionately utilizes Stratified Simple random sampling when baseline population is not at the desired proportional percentages to the referent population
- Stratified sample “weighted” to return sample population back to baseline population
- Useful for “Over-Sampling”
5) Multi-Stage Random sampling
- Uses Simple Random sampling at multiple-stages towards patient selection
- Counties (Primary Sampling Unit, PSU)
- City Blocks/Zip Codes (Secondary Sampling Unit, SSU)
- Clinic/Hospital/Household
- Individual/Individual Chart
6) Cluster Multi-Stage Random sampling
- Same as Multi-Stage Random sampling but ALL ‘elements’ clustered together (at any stage) or selected for inclusion
- ALL Clinics in a zip code
- All Households in a community
Non-Probability sampling schemes
1) ‘Quasi-Systematic’ or ‘Convenience’ samples
-Decide on what fraction of population is to be sampled and how they will be sampled
-Ex: All persons with last name M-Z
-Ex: All members of a professional business association
-Ex: All persons attending clinic every M/W/F for 6 months
-Ex: All persons referred by selected-peers
Concern: There is some known or unknown order to the sample generated by selected scheme which may introduce bias (Selection bias)
2 common broad approaches to collection of data/information for Cross-Sectional studies
1) Questionnaires/Surveys
- Either directly from patients/caregivers or their medical records
2) Physical assessments (which might involve labs, clinical, or psych tests)
Great for assessing health/disease in similar population as time changes
- NOT likely to be the same individuals year-to-year
- Many US Cross-Sectional studies are survey-based products of National Center for Health Statistics (NCHS), division of the CDC
Advantages of Cross-Sectional Studies
Quicker and easier fro the researcher when using data already collected (compared to original data collection)
-Data already collected & deidentified (Exempt IRB approval)
Less expensive for researcher than any for of prospective study
Can be analyzed like a Case-Control or Cohort study (group allocation)
Useful for estimating prevalence rates
Useful for answering research questions about a myriad of elements
Disadvantages of Cross-Sectional studies
Prevalent cases may represent survivors
Difficult to study diseases of low frequency
Unable to generate incidence rates
Problems in determining temporal relationship of presumed cause & effect
-Due to the fact that exposure & disease histories are taken at the same time
Example Cross-Sectional Surveys from NCHS
NHANES:
National Health and Nutrition Examination Survey
NHIS:
National Health Interview Survey
NAMCS:
National Ambulatory Medical Care Survey
NHCS:
National Hospital Care Survey
BRFSS:
Behavioral Risk Factor Surveillance System
NHANES
National Health and Nutrition Examination Survey
-Assesses the health and nutritional status of adults and children
- Combines interviews and physical exams
- Interviews include demographic, socioeconomic, dietary, and health-related questions
- Examination component consists of medical, dental, physiological measurements and laboratory tests
- Survey sample is selected to represent the US population of all ages
- Oversamples persons >=60 years old, Blacks, Hispanics
-These are the mobile units that go from city to city
NHIS
National Health Interview Survey
-Principal source of information on the health of the civilian, non-institutionalized population
- Survey sample is selected to represent the US population of all ages
- Has central role in other surveys such as the National Survey of Family Growth (NSFG) & NAMCS/NHCS
- Data are collected through a personal household interview (Broad range of health topics)
- Consists of a set of core questions that remain largely unchanged & a set of supplements used to respond to public health data needs as they arise
NAMCS
National Ambulatory Medical Care Survey
- A national survey designed to meet the need for objective, reliable information about the provision and use of ambulatory medical care services in the US
- Based on a sample of visits to non-federal, office-based physicians primarily engaged in direct patient care
NHCS
National Hospital Care Survey
- A combined national survey designed to describe national patterns of healthcare delivery in non-federal hospital-based settings, including:
- Discharges from inpatient departments and institutions, and visits to EDs, outpatient departments and ambulatory surgery centers
- Integrates 3 previous cross-sectional surveys:
1) NHDS: National Hospital Discharge Survey
2) NHAMCS: National Hospital Ambulatory Medical Care Survey
3) DAWN: Drug-Abuse Warning Network
BRFSS
Behavioral Risk Factor Surveillance System
- A state-based system of telephone health surveys that collects information on health risk behaviors, preventative health practices, and health care access primarily related to chronic disease and injury
- Monthly data collection in all 50 states, DC, PR, USVI, Guam
- > 506,000 adults are interviewed by telephone
- Largest landline telephone health survey in the world
- Youth BRFSS conducted by questionnaire in schools
