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Health Disparities

HD: Food Security (2011)


Biros MH, Hoffman PL, Resch K. The prevalence and perceived health consequences of hunger in emergency department patient populations. Acad Emerg Med. 2005 Apr; 12 (4): 310-317.PMID: 15805321

PubMed ID: 15805321
Study Design:
Descriptive Study
D - Click here for explanation of classification scheme.
Quality Rating:
Positive POSITIVE: See Quality Criteria Checklist below.
Research Purpose:

The purpose of this study was to determine the prevalence of hunger and food insecurity in English-speaking and non-English-speaking Emergency Department (ED) patients or their parents with respect to several ethnic and socioeconomic factors. Also, this survey and analysis sought to determine whether hunger forces choices that are perceived by the patients to impact their overall health.

Inclusion Criteria:

The study population was a convenience sample which included all adult (age>17 years) non-critically ill patients or parents of non-critically ill pediatric patients who speak English, Spanish or Somali receiving treatment in the ED.  

Exclusion Criteria:

Respondents were excluded from the convenience sample if they had alterations in mental status as determined by the clinician involved with the case, were medically unstable, or spoke a language other than English, Spanish or Somali, or if the survey administration would delay or interfere with their Emergency Department (ED) care.

Description of Study Protocol:


Patients or their parents provided consent to be interviewed at the time of the ED visit. Surveys were conducted in the EDs of Hennepin County Medical Center (HCMC), a Level 1 trauma center in Minneapolis, Minnesota and Minneapolis Children's Hospital. These hospitals are in close physical proximity and treat a diverse patient populations, including large numbers of indigent, immigrant and minority patients as well as primarily white professional workforce in downtown Minneapolis.  


This was a survey of adult low-acuity ED patients or parents of pediatric patients who presented for non-critical emergency care between January 1, 2001 and August 1, 2001.  

The survey was anonymous and no specific respondent identifiers were included. Respondents were instructed that they could refuse to answer any questions they believed were too personal. All responses given were self-reported. 

Interviews were conducted by paid research associates fluent in English and either Spanish or Somali.  Five of the six were advanced-placement senior high-school students hand selected by their counselors for their maturity, scholarly standing, leadership capabilities and English fluency. The RAs could speak and read in their native language and used a survey instrument in their native language that was identical in content and format to the survey used for English-speaking patients.

Interviews were conducted when interviewers were available, usually between 5 pm and 10 pm on weeknights, and noon and 8 pm on weekends   

Content of the survey

The confidential interview lasted between five to 15 minutes, and included previously validated questions to assess the prevalence of food insecurity and hunger. The survey also asked about respondent demographics, medical history, insurance status, medications taken, frequency of ED visits, ease of access to medical care, and perceptions of their health status. Further questions considered decision making between buying food and buying medicine, or choosing other non-food items (i.e. clothes, shelter, cigarettes, alcohol, instead of purchasing prescribed medications).

Definitions: For the purpose of the survey, food insecurity was considered to be present when respondents indicated that they put off paying bills to buy food, had food but not the desired types, or used emergency food services to secure food. Hunger was defined as not having enough to eat, not eating for an entire day AND not eating because of lack of money to buy food.  

Statistical Analysis

SAS version 6.1 was used. Data was entered by study investigators first and then independently verified by graduate students in the Department of Biostatistics at the University of Minnesota. Descriptive data describe levels of food insecurity and hunger. Both standard tabular methods and logistic regression were used to examine bivariate associations between patient characteristics and hunger  or food insecurity. Multivariable analysis was conducted to determine only those factors predictive of the presence of hunger. The predictors of hunger and making choices between food and medicine were determined by forward stepwise logistic regression. No attempt was made to verify the self-reported occurrence of illness due to choosing to buy food instead of medicine. For multivariable analysis, only those questions that required a specific answer were included. For example, respondents were not considered to have a chronic illness unless they could provide a specific disease name. 

Data Collection Summary:

Outcome Variables

  • Hunger
  • Food vs. Medicine
  • Poor Health Outcomes.

Independent Variables

  • Income
  • Ethnicity
  • Education
  • Chronic illness
  • Illicit drug use
  • Cigarette use
  • Alcohol use
  • Insurance status
  • Ease of getting to medical care
  • Perception of being "in poor health". 


Description of Actual Data Sample:
  • Initial N: 1,044 patients were asked to participate   
  • Attrition (final N): 930 patients or their parents agreed (89% response rate) and completed at least 50% of the survey
  • Age: Mean age of the respondents was 33.8 (±13 years); 39.8% were male
  • Ethnicity: 77% were ethnic minorities. This is further seen in Table 1.
  • Other relevant demographics: See Table 1.

Table 1: Demographics

Race N Percent
 African American 216  24.1 
 Native American 47  5.3 
 Hispanic 315  35.2 
 Somali 70  7.8 
 White 208  23.3 
 Other 39  4.4 
Annual Income    
 <10,000 451  53.6 
 10,000-25,000 355  40.6 
 >25,000 143  17.0 
 Less than 12th grade 429  48.1 
 High School Graduate/GED 355  40.6 
 Postsecondary education 99  11.3 


Summary of Results:

The significant predictor variables for hunger are shown in Table 2. This table describes the prevalence of hunger in the presence or absence of certain socioeconomic or demographic characteristics of the respondents. For this review, all the variables in which the difference was P<0.001 are shown in this table. 

Table 2: Prevalence of Hunger in the Presence/Absence of Certain Socioeconomic/Demographic Characteristics (Bivariate Analysis)

Characteristic Prevalence when characteristic is present N (%)* Prevalence when characteristic is absent
N (%)**
Hispanic 97/306 (31.7%)  107/577 (18.5%) 0.001 
Gender-male 101/332 (30.4%)  101/515 (19.6%) 0.001  
Education <12 years/no GED 140/414 (33.8%) 65/450 (14.4%) 0.001  
Annual income <$10,000 154/449 (34.3%)  41/384 (10.7%) 0.001  
Insurance, none  97/282 (34.4%) 107/592 (18.1%) 0.001  
Insurance, no private  178/670 (26.6%) 26/204 (12.8%) 0.001  
Cigarette use  85/279 (30.5%) 121/597 (20.3%) 0.001  
Illicit drug use  28/48 (58.3%) 178/827 (21.5%) 0.001  
Chronic health problems  114/376 (29.5%) 98/511 (19.2%) 0.001  
Health status poor/fair  122/376 (32.5%) 91/512 (17.8%) 0.001  
Not easy to get medical care  134/366 (36.6%) 75/517 (14.5%) 0.001  

*N=number of respondents fighting hunger; N=number of respondents in the group; n/N (%) equal prevalence 

**If P, 0.0095, it is rounded up to the nearest 1/1,000

***Each of the subcategories is compared with all others combined

The prevalence of hunger is lower in Somalis or whites,  those who have at least 12 years of education, and those with incomes greater than $10,000 per year.

Multivariable analysis was performed to determine predictive variables for hunger, for having to choose between food and medicine, and for perceived poor health outcome following this choice (of food instead of medicine). Low income, lack of insurance and chronic health problems are predictive factors in all analysis. 

These findings indicate that hunger often forces the choice between buying medicine and buying food.  Patients are aware that this choice may acutely and adversely affect their health, and perceive that when this choice is necessary, it results in subsequent potentially avoidable ED visits and hospitalizations. The respondents in this study prioritized food over medication, but not other items (i.e. alcohol, shelter, clothing) over medication. 

Table 2: Multivariable Analysis of Outcomes in Relationship to Socioeconomic/Demographic Variables, Outcome [OR (95% CI)]

Variable       Hunger* Food vs. Medicine** Poor Health Outcome***
Income, $10,000 3.3 [2.2, 5.1] 2.5 [1.6, 3.9]  
Hispanic ethnicity 1.9 [1.2, 3.0]    
Education <12 years 1.6 [1.0, 2.5]    
Chronic illness   2.1 [1.4, 3.0] 2.4 [1.7, 3.8] 1.8 [1.1, 3.3]
Illicit drug use 5.5 [2.7, 11.1]    
No insurance   1.8 [1.2, 2.7] 3.4 [2.2, 5.1] 2.8 [1.7, 4.6]

African American race


2.0 [1.2, 3.3]

In poor health     1.9 [1.4, 2.6]

*N=768 responses; cases=178; prevalence=23.2%; concordance=74%

** N=752 responses; cases=136; prevalence=18.1%; concordance=66%

***N=831 responses; cases=87; prevalence=10.5%; concordance=71%

Predictors of food insecurity/hunger and choosing food instead of medicine included low income, lack of insurance and chronic health problems. 

Author Conclusion:

Hunger often forces a choice between buying medicine and buying food. Patients are aware that this choice may acutely and adversely affect their health. Predictors of food insecurity and hunger, and choosing food instead of medicine were similar to those they found in the current study. 

This study reinforces that low income, lack of insurance, and chronic illness are predictors of the three primary outcome variables: Hunger, food vs. medicine and poor health outcomes. 

EDs often provide primary care for patients who have few resources, chaotic and dysfunctional lifestyles and limited access to medical care. What the ED health care provider construes as a patient's medical non-compliance may in fact be related to the more fundamental issue of hunger, its effects on chronic health, and the choices it forces. Emergency physicians should consider this social issue when evaluating the patient's ability to comply with suggested treatment. Public health officials should also be aware of the potential impact of policy changes on the health-related choices patients may be forced to make.


Funding Source:
Government: County Hospital
Reviewer Comments:

This is a simple but very useful study. The authors list a number of limitations but I do not see that those limitations affect the quality of the study in any way. The study is done at two hospitals in Minneapolis, quite close to each other, and therefore, the results may not translate to other minority populations. They relied mostly on high-school students for the translation and this limited hours to between five to nine pm or weekends. It is unknown whether this skewed the results in any way. 

Finally, the other significant limitation is that only the questions related to hunger and food insecurity have been validated. The similar questions about choosing between medicine and non-food items were modeled as closely as possible to those validated for hunger. 

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? N/A
  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? ???
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? Yes
  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%.) No
  4.3. Were all enrolled subjects/patients (in the original sample) accounted for? N/A
  4.4. Were reasons for withdrawals similar across groups? ???
  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? N/A
  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.) N/A
  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? N/A
  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? N/A
  7.4. Were the observations and measurements based on standard, valid, and reliable data collection instruments/tests/procedures? N/A
  7.5. Was the measurement of effect at an appropriate level of precision? N/A
  7.6. Were other factors accounted for (measured) that could affect outcomes? No
  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? 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)? 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? N/A
  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