EAL

FNOA: Aging Programs (2012)

Citation:

Study Design:

Class:

- Click here for explanation of classification scheme.

Quality Rating:

Research Purpose:

To construct a series of life tables that provide cumulative percentages of the non-immigrant American population using the Food Stamp Program during their working years as well as the total and consecutive years of use across their life course
To analyze the effect of other demographics on the percentages, these data will be used to provide a new estimation of the likelihood of food insecurity across the life course.

Inclusion Criteria:

Study participant in The Panel Study of Income Dynamics (PSID) from 1967 to 1997
Of working age, defined as 20 to 65 years of age.

Exclusion Criteria:

Non-participant in the PSID
Participant in the PSID after 1997
<20 or >65 years of age.

Description of Study Protocol:

Recruitment

No recruitment. Subjects are a subsample from PSID database.
Sample is weighted to ensure it accurately reflects the non-immigrant US population.

Design

Longitudinal Study

Subsample of data from the PSID from 1967 to 1997
- PSID tracks yearly household participation in various welfare programs, including the Food Stamp Program
- Subjects were interviewed annually via telephone by PSID (in person from 1968 to 1972)
- Initial interviews of 4,800 households; continued to follow children and adults who left the household over time
- Reflects the entire non-immigrant US population
Construct a series of life tables that estimate the risk of food stamp use throughout working age adulthood (20 to 65 years old)
- Individuals contribute anywhere from one to 30 years within the life table
Construct a multivariate life table that combines life course food stamp use probabilities with race, education and gender
- Individuals who were neither black nor white were not included in analysis
Relate the derived probabilities to food insecurity.

Blinding used

Not applicable

Intervention

Not applicable

Statistical Analysis

Age specific probabilities
- Correction for left centered bias (enter study after age 20)
- Cumulative proportions of adults using food stamps
Multivariate life tables
- Logit models
- Logit coefficients
- Age specific probabilities
- Cumulative life probabilities of receiving food stamps by race, education and gender
Analysis of the combination of life probabilities and multivariate life tables above (probabilities and demographics).

Data Collection Summary:

Timing of Measurements

One-time analysis of 30 years of PSID data
PSID
- Interviewed subjects via telephone once each year (in person interviews from 1968 to 1972)
- Participants were asked, "Did you (or anyone else in your family) use government food stamps any time in (prior year)?"
- Food stamp use is household based
- One year of food stamp use is defined as any use throughout the year (ie. one month or 11 months counts for one year of use).

Dependent Variables

Total and cumulative probabilities of using Food Stamp Program
Food insecurity, generally defined as "limited or uncertain ability to acquire acceptable foods in socially acceptable ways."

Independent Variables

Impact of age, race, education and gender on probability of food stamp use in adulthood
- Age
- Race: White/black
- Education: <12 years and >12 years
- Gender: Male/female.

Description of Actual Data Sample:

Initial N:
- 239,480 person years
  - 49.3% male (118,065)
  - 50.7% female (121,415)
- Article notes "approximately 260,000 person years of information on food stamp use are analyzed"
Attrition (final N): 239,480 person years
Age: 20 to 65 years
Ethnicity: All races in US population in study, but further analyzed by "white" and "black" PSID participants
Other relevant demographics:
- Education
  - <12 years and >12 years
Anthropometrics:
Location:
- Administered by the Survey Research Center, Institute for Social Research at the University of Michigan
- Telephone surveys across the US, representative of non-immigrant US population.

Summary of Results:

Life Tables with Cumulative Proportions of Food Stamp Use (Overall patterns of food stamp use):

Likelihood of experiencing food stamp receipt:

Age (in years)	Food Stamp Program Participation (One or more years)
20	9.6%
35	34.2%
50	44.4%
65	50.8%

Likelihood of experiencing food stamp receipt:

Age (in years)	Food Stamp Program Participation (total number of years)
One or more years	50.8%
Two or more years	37.6%
Three or more years	32.6%
Four or more years	29.1%
Five or more years	23.8%

Notable life table results:

Once an individual has received food stamps, he/she is quite likely to use it again in the future
Life course probability of food stamp use is high, but the pattern of use tends to be relatively short
- Results show that 74.1% of food stamp recipients who have used food stamps will use the program at least one additional year
- Nearly half (46.9%) of all food stamp recipients will use the program in five or more separate years during their working-age adulthood
The use of food stamps tends to occur over fairly short periods of time, but these individuals are quite likely to experience poverty/welfare use again
- 50.8% of the population will use food stamps in at least one year; only 9.9% will do so in five consecutive years.

Multivariate Life Tables (Impact of demographics):

Cumulative Proportions of Food Stamp use by Race, Education and Gender:

Age	White	Black	>12 Years Ed	<12 Years Ed	Male	Female
20	6.3%	26.8%	7.1%	11.4%	8.1%	11.1%
25	15.1%	49.6%	18.7%	26.7%	19.2%	24.0%
35	24.3%	66.0%	29.0%	43.4%	30.1%	35.9%
65	37.3%	85.6%	38.3%	64.3%	45.6%	51.8%

Notable multivariate table results:

Both race and education exert a strong influence on the life course probability of using food stamps
- For black Americans, 26.8% use food stamps by age 20; by age 65, 85.6% of black Americans have participated in the food stamp program
- For white Americans, 37.3% will participate in the program by age 65
- By age 65, 38.3% of those with greater than 12 years of education will have used food stamps, compared with 64.3% of those with less than 12 years of education
Gender has less influence on the life course probability of using food stamps
- Women are slightly more likely to use food stamps than men; by age 65, 51.8% of females and 45.6% of males will have used food stamps
- Marriage and combining of households results in identical gender odds during those years
When combining probabilities of food stamp participation with demographic characteristics, race, education and to a much lesser extent, gender exerts a profound influence on the likelihood of using food stamps across adulthood
- For example, by age 65, 27.3% of white males with more than 12 years of education will have used the food stamp program, compared to 92.4% of black females with less than 12 years of education.
Can estimate a lower boundary of food insecurity across adulthood by using the knowledge that about half of all households receiving food stamps will also experience food insecurity (earlier cited research). This lower boundary captures individuals who will never receive food stamps, yet will experience food insecurity which would elevate estimates derived only from food stamp participation.
- By age 45, 33.6% of adults will have encountered food insecurity, and by age 65, 42.0% of individuals will have experienced food insecurity for at least one year in adulthood.
Overall, this approach demonstrates that although food insecurity may be low in any given year, the risk of food insecurity becomes sizable as individuals progress through the adulthood years.

Author Conclusion:

Over the working adulthood years, life table data shows a substantial need and use of food stamps among the United States population. Race, education and to a lesser extent gender exert a profound influence on the likelihood of using food stamps throughout adulthood. Data also show a significant risk of food insecurity in the working adult years.

Funding Source:

Government:

US Department of Agriculture grant

Reviewer Comments:

PSID survey did not analyze immigrant populations (due to small numbers in final sample), which in light of US demographic changes in recent years would be interesting insight
Food stamp use was categorized as a dichotomous variable (received it or did not receive for one year) which was likely a function of the wording of the PSID survey question. Information on actual usage, given the known sporadic use of food stamps, would offer greater insight.
Final N noted in article as "approximately 260,000 person years of information analyzed," but cited final N as actual gender data numbers since this was lower on the reported results tables.
Weighted sample to ensure representative of the US population, and corrected the original sampling bias and were adjusted annually to account for attrition.

Quality Criteria Checklist: Primary Research
Relevance Questions
	1.	Would implementing the studied intervention or procedure (if found successful) result in improved outcomes for the patients/clients/population group? (Not Applicable for some epidemiological studies)	N/A
	2.	Did the authors study an outcome (dependent variable) or topic that the patients/clients/population group would care about?	Yes
	3.	Is the focus of the intervention or procedure (independent variable) or topic of study a common issue of concern to dieteticspractice?	Yes
	4.	Is the intervention or procedure feasible? (NA for some epidemiological studies)	N/A

Validity Questions
1.	Was the research question clearly stated?		Yes
	1.1.	Was (were) the specific intervention(s) or procedure(s) [independent variable(s)] identified?	Yes
	1.2.	Was (were) the outcome(s) [dependent variable(s)] clearly indicated?	Yes
	1.3.	Were the target population and setting specified?	Yes
2.	Was the selection of study subjects/patients free from bias?		Yes
	2.1.	Were inclusion/exclusion criteria specified (e.g., risk, point in disease progression, diagnostic or prognosis criteria), and with sufficient detail and without omitting criteria critical to the study?	Yes
	2.2.	Were criteria applied equally to all study groups?	Yes
	2.3.	Were health, demographics, and other characteristics of subjects described?	Yes
	2.4.	Were the subjects/patients a representative sample of the relevant population?	Yes
3.	Were study groups comparable?		N/A
	3.1.	Was the method of assigning subjects/patients to groups described and unbiased? (Method of randomization identified if RCT)	N/A
	3.2.	Were distribution of disease status, prognostic factors, and other factors (e.g., demographics) similar across study groups at baseline?	N/A
	3.3.	Were concurrent controls or comparisons used? (Concurrent preferred over historical control or comparison groups.)	N/A
	3.4.	If cohort study or cross-sectional study, were groups comparable on important confounding factors and/or were preexisting differences accounted for by using appropriate adjustments in statistical analysis?	N/A
	3.5.	If case control study, were potential confounding factors comparable for cases and controls? (If case series or trial with subjects serving as own control, this criterion is not applicable.)	N/A
	3.6.	If diagnostic test, was there an independent blind comparison with an appropriate reference standard (e.g., "gold standard")?	N/A
4.	Was method of handling withdrawals described?		N/A
	4.1.	Were follow-up methods described and the same for all groups?	N/A
	4.2.	Was the number, characteristics of withdrawals (i.e., dropouts, lost to follow up, attrition rate) and/or response rate (cross-sectional studies) described for each group? (Follow up goal for a strong study is 80%.)	N/A
	4.3.	Were all enrolled subjects/patients (in the original sample) accounted for?	N/A
	4.4.	Were reasons for withdrawals similar across groups?	N/A
	4.5.	If diagnostic test, was decision to perform reference test not dependent on results of test under study?	N/A
5.	Was blinding used to prevent introduction of bias?		Yes
	5.1.	In intervention study, were subjects, clinicians/practitioners, and investigators blinded to treatment group, as appropriate?	N/A
	5.2.	Were data collectors blinded for outcomes assessment? (If outcome is measured using an objective test, such as a lab value, this criterion is assumed to be met.)	Yes
	5.3.	In cohort study or cross-sectional study, were measurements of outcomes and risk factors blinded?	N/A
	5.4.	In case control study, was case definition explicit and case ascertainment not influenced by exposure status?	N/A
	5.5.	In diagnostic study, were test results blinded to patient history and other test results?	N/A
6.	Were intervention/therapeutic regimens/exposure factor or procedure and any comparison(s) described in detail? Were interveningfactors described?		Yes
	6.1.	In RCT or other intervention trial, were protocols described for all regimens studied?	N/A
	6.2.	In observational study, were interventions, study settings, and clinicians/provider described?	Yes
	6.3.	Was the intensity and duration of the intervention or exposure factor sufficient to produce a meaningful effect?	N/A
	6.4.	Was the amount of exposure and, if relevant, subject/patient compliance measured?	N/A
	6.5.	Were co-interventions (e.g., ancillary treatments, other therapies) described?	N/A
	6.6.	Were extra or unplanned treatments described?	N/A
	6.7.	Was the information for 6.4, 6.5, and 6.6 assessed the same way for all groups?	N/A
	6.8.	In diagnostic study, were details of test administration and replication sufficient?	N/A
7.	Were outcomes clearly defined and the measurements valid and reliable?		Yes
	7.1.	Were primary and secondary endpoints described and relevant to the question?	Yes
	7.2.	Were nutrition measures appropriate to question and outcomes of concern?	Yes
	7.3.	Was the period of follow-up long enough for important outcome(s) to occur?	Yes
	7.4.	Were the observations and measurements based on standard, valid, and reliable data collection instruments/tests/procedures?	Yes
	7.5.	Was the measurement of effect at an appropriate level of precision?	Yes
	7.6.	Were other factors accounted for (measured) that could affect outcomes?	Yes
	7.7.	Were the measurements conducted consistently across groups?	N/A
8.	Was the statistical analysis appropriate for the study design and type of outcome indicators?		Yes
	8.1.	Were statistical analyses adequately described and the results reported appropriately?	Yes
	8.2.	Were correct statistical tests used and assumptions of test not violated?	Yes
	8.3.	Were statistics reported with levels of significance and/or confidence intervals?	N/A
	8.4.	Was "intent to treat" analysis of outcomes done (and as appropriate, was there an analysis of outcomes for those maximally exposed or a dose-response analysis)?	N/A
	8.5.	Were adequate adjustments made for effects of confounding factors that might have affected the outcomes (e.g., multivariate analyses)?	Yes
	8.6.	Was clinical significance as well as statistical significance reported?	Yes
	8.7.	If negative findings, was a power calculation reported to address type 2 error?	N/A
9.	Are conclusions supported by results with biases and limitations taken into consideration?		Yes
	9.1.	Is there a discussion of findings?	Yes
	9.2.	Are biases and study limitations identified and discussed?	Yes
10.	Is bias due to study's funding or sponsorship unlikely?		Yes
	10.1.	Were sources of funding and investigators' affiliations described?	Yes
	10.2.	Was the study free from apparent conflict of interest?	Yes