HD: Food Security (2011)
Citation:
Study Design:
Class:
- Click here for explanation of classification scheme.
Quality Rating:
Research Purpose:
To measure the Supplemental Nutrition Assistance Program's (SNAP) effectiveness in reducing food insecurity using a dummy endogenous variable model with instrumental variables to control for selection bias.
Inclusion Criteria:
- Household level data taken from Survey of Income and Program Participation (SIPP) panel
- 1996, 2001 and 2004 surveys
- Primary study population:
- Low-income households below 150% of the poverty threshold
- Having readily available assets of less than or equal to $4,000 or $5,000 if at least one household member is age 60 or older
- Secondary population (for robustness checks):
- Households with incomes below 130% of the poverty threshold
- Readily available assets of less than or equal to $2,000 or $3,000 if at least one household member is age 60 or older.
Exclusion Criteria:
Households above 150% of the poverty threshold.
Description of Study Protocol:
Design
- Nationally representative, non-institutional sample of between 36,000 and 46,000 households
- Household members are interviewed at four-month intervals
- Demographic, economic and topical module data collected.
Intervention
Participation in the SNAP program.
Statistical Analysis
- Using a bivariate probit model, measure the total effect (direct and indirect) of SNAP participation on food insecurity using a dummy endogenous variable model with instrumental variables (state SNAP policies):
- Equation one: Relating food insecurity to SNAP participation
- Equation two: A reduced form equation describing SNAP participation as a function of state program rules
- A naive probit model is also used for equation one to compare to the bivariate probit model to correct for selection bias (if food-insecure households are more likely to become SNAP participants)
- Naive probit model does not control for the endogeneity of SNAP receipt while bivariate probit model does control for the endogeneity of SNAP.
Data Collection Summary:
Timing of Measurements
- Surveys used for 1996, 2001 and 2004
- Households interviewed at four-month intervals within the year time frame.
Dependent Variables
- Food-related hardship variables: As measured by the "adult well-being topical module" once in each of the three panels (surveys)
- Based upon whether households have enough food to eat and whether they are able to afford balanced meals:
- Food insecure: Low or very low food security
- Very food insecure: Very low food security
- SNAP participation (equation two).
Independent Variables
- SNAP participation (equation one)
- Income
- Household structure and characteristics
- Instruments for SNAP participation
- Biometric technology
- Outreach spending
- Partial immigrant eligibility
- Full immigrant eligibility.
Control Variables
- Low-income households
- Economic variables (Bureau of Economic Analysis, 2008)
- Monthly state unemployment rates
- Annual state per capita income
- Monthly state employment-population ratio
- Quarterly gross domestic product.
Description of Actual Data Sample:
- Attrition (final N): 65,269 observations (households)
- Age: Mean 47.98 years; SD, 18.547.
Other Relevant Demographics
- 24.4% food insecure
- 10.3% very food insecure
- 28.6% receiving SNAP benefits.
Anthropometrics
SNAP recipients compared to non-SNAP recipients:
- Younger
- More minorities
- Less educated
- Female-headed households
- More children
- Include a disabled member in the household.
Location
Nationally representative, non-institutionalized sample.
Summary of Results:
Key Findings
- Food insecure:
- Bivariate probit model found receipt of SNAP benefits reduces the likelihood of food insecurity by 16.2 percentage points, P<0.01
- Utilizing measured effect of model, suggests that SNAP receipt reduces food insecurity by 31.2% in the population
- Naive probit model show that SNAP receipt is associated with higher food security:
- SNAP participation is associated with an 8.6 percentage increase in the probability of being food insecure, P<0.01
- This is consistent with the self-selection of more needy and food insecure households into SNAP
- Comparison between the two models suggests controlling for selection in SNAP is essential in measuring effect of SNAP receipt on food insecurity
- Household demographics are important determinants of food insecurity; more food insecurity is found when:
- Households are headed by younger persons
- Headed by minorities
- Headed by persons with limited education
- Households with more children
- Having a disabled person in the house
- Having a single-person-run household, compared to a two-adult-headed household
- State unemployment rate and employment-population ratio do not affect food insecurity
- A stronger economy as measured by the quarterly GDP was found to reduce food insecurity
- Very food insecure:
- Similar relationships are seen when very food insecure is measured
- Bivariate probit model suggests that SNAP receipt reduces the likelihood of being very food insecure by 3.9 percentage points, P<0.01
- Utilizing measured effect of model, suggests that SNAP receipt reduces being very food insecure by 20.2% in the population.
Other Findings
- Food insufficiency, those that report sometimes or often not having enough to eat, was 6.9% in the study sample
- SNAP participation reduces food insufficiency by 2.7 percentage points, or by 19.4% in the population.
Author Conclusion:
- SNAP reduces households' food-related hardships
- SNAP participation reduces the likelihood of being food insecure, very food insecure and food insufficient
- Estimated effects are substantial and provide evidence that SNAP is meeting its key goal of reducing food-related hardship
- This study contributes recent, nationally representative findings from models designed to control for self-selection to find that SNAP reduces food insecurity.
Funding Source:
Government: | US Department of Agriculture's Economic Research Service, Food Assistance and Nutrition Research Program |
Reviewer Comments:
Quality Criteria Checklist: Primary Research
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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) | Yes | |
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) | Yes | |
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? | Yes | |
3.1. | Was the method of assigning subjects/patients to groups described and unbiased? (Method of randomization identified if RCT) | Yes | |
3.2. | Were distribution of disease status, prognostic factors, and other factors (e.g., demographics) similar across study groups at baseline? | Yes | |
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? | Yes | |
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.) | Yes | |
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? | No | |
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? | ??? | |
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.) | ??? | |
5.3. | In cohort study or cross-sectional study, were measurements of outcomes and risk factors blinded? | ??? | |
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? | Yes | |
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? | Yes | |
6.6. | Were extra or unplanned treatments described? | Yes | |
6.7. | Was the information for 6.4, 6.5, and 6.6 assessed the same way for all groups? | Yes | |
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? | Yes | |
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? | Yes | |
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)? | Yes | |
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? | No | |
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 | |