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Health Disparities

HD: Food Security (2011)

Citation:
Ratcliffe C, McKernan S. How much does SNAP reduce food insecurity? The Urban Institute. March 2010.
 
Study Design:
Cross-Sectional Study
Class:
D - Click here for explanation of classification scheme.
Quality Rating:
Positive POSITIVE: See Quality Criteria Checklist below.
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
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