IN BRIEF This study examined differences in household food security (HFS), household adult food security (HAFS), and indicators of diabetes management between clients using free and fee-for-service clinics for diabetes care and management. The study’s 166 participants (free clinic, n = 41; fee-for-service clinic, n =125) had a mean age of 53 ± 16 years and were primarily Caucasian (n = 147 [91.9%]). Both HFS (P <0.001) and HAFS (P <0.001) differed between the clinic groups, as did A1C (free clinic 8.7 ± 1.7%; fee-for-service 7.8 ± 1.6%; P = 0.005). A1C increased as HFS (r = 0.293, P <0.001) and HAFS (r = 0.288, P = 0.001) worsened.

In 2017, the Centers for Disease Control and Prevention estimated that 30.3 million people in the United States (9.4% of the population) have diabetes (1). Rates are more prevalent in the Diabetes Belt—comprising 644 counties across 15 states in the southern and Appalachian regions of the United States—compared to other U.S. counties (2).

Food insecurity, defined as a lack of consistent, dependable access to enough food for all household members for active, healthy living (3), has been suggested as a risk factor for the development of diabetes, with adults experiencing food insecurity being two to three times more likely to develop diabetes than their food-secure counterparts (4). Gucciardi et al. (5) reviewed the intersection of food insecurity and diabetes and found that food-insecure individuals not only have a greater risk of developing diabetes, but also face substantially more challenges managing diabetes. Berkowitz et al. (6) found that food insecurity was associated with poor glycemic and cholesterol control in patients with type 2 diabetes, even after controlling for numerous demographic, socioeconomic, and clinical factors.

The self-reported rate of diabetes in rural Appalachian Ohio, an area characterized by poverty, is greater than that of the state as a whole (11.3 vs. 7.8%), indicating that low economic status is linked to an increased risk for diabetes (7). During 2010, the timeframe for this study, the U.S. Department of Agriculture (USDA) estimated that 85.5% of U.S. households were food secure, whereas 16.5% (17.2 million households) were food insecure (low food security, 11.1%; very low food security, 5.4%) (8). Some U.S. regions/states may be more prone to food insecurity. For example, among Ohio households, from which our sample was drawn, 16.4% were classified as having low food security and 6.6% had very low food security, exceeding 2010 national estimates (8).

Managing health conditions, espe-cially those with specific dietary implications, becomes increasingly difficult without access to adequate food (9). Individuals with diabetes often must choose between buying medications and supplies needed for the management of their disease or purchasing healthy food (10). Consequently, among adults who already have diabetes, food insecurity is associated with poorer glycemic control (11). Compounding this problem is evidence that low-quality diets precipitate the development of concurrent diseases associated with diabetes (12).

Some under- and uninsured individuals turn to low-cost or free clinics for care. There is a paucity of data regarding the effectiveness of these clinics, especially with regard to diabetes management and food insecurity. Those who have health disparities (i.e., the disproportionate rate of diseases in socioeconomically poor populations) are most likely to have health care disparities (limited access to or availability of health care services) (13). Patients in rural areas such as the Appalachian region of Ohio are more likely to be uninsured or underinsured and to need to use free clinics (14). Yet, the availability of free care may not lead to improved health outcomes among individuals with diabetes (15). Such free care does not come without costs to patients. For example, individuals still must find transportation to attend appointments. Thus, although the care itself is free, many people still struggle to access this care, which often leads to appointment cancellations, lack of attendance, and ultimately inconsistency of care (15).

The purposes of this study were to assess 1) the differences in food security status and indicators of diabetes management/control between clients using free and fee-for-service clinics for diabetes care and management in a rural, Appalachian region and 2) the relationship of food security status to blood glucose control, regardless of clinic type.

The institutional review board of Ohio University in Athens approved this study.

Participants and Setting

Adult patients with diabetes (n = 166) were recruited from University-based free and fee-for-service clinics in southeastern Ohio. These clinics provide service for individuals living in Athens, Hocking, Meigs, Morgan, Perry, Vinton, and Washington counties. Table 1 describes the counties from which the participants were drawn.

TABLE 1.

Characteristics of Rural, Appalachian Ohio Counties Where Participants Lived

CountyPrevalence of Diabetes in 2011 (%)aAppalachian Regional Commission Designation in Fiscal Year 2011bPoverty Level (%) and USDA Poverty Designation in 2012c,dUSDA Rural/Urban Designatione
Athens 10.9 Distressed 33.3 (Persistent Poverty) Non-metro 
Hocking 11.4 Transitional 20.1 (No Persistent Poverty) Metro 
Meigs 14.0 Distressed 22.5 (No Persistent Poverty) Non-metro 
Morgan 14.2 Distressed 18.6 (No Persistent Poverty) Non-metro 
Perry 11.7 At-Risk 19.3 (No Persistent Poverty) Metro 
Vinton 12.6 Distressed 21.9 (No Persistent Poverty) Non-metro 
Washingtonf 12.1 Transitional 16.2 (No Persistent Poverty) Non-metro 
CountyPrevalence of Diabetes in 2011 (%)aAppalachian Regional Commission Designation in Fiscal Year 2011bPoverty Level (%) and USDA Poverty Designation in 2012c,dUSDA Rural/Urban Designatione
Athens 10.9 Distressed 33.3 (Persistent Poverty) Non-metro 
Hocking 11.4 Transitional 20.1 (No Persistent Poverty) Metro 
Meigs 14.0 Distressed 22.5 (No Persistent Poverty) Non-metro 
Morgan 14.2 Distressed 18.6 (No Persistent Poverty) Non-metro 
Perry 11.7 At-Risk 19.3 (No Persistent Poverty) Metro 
Vinton 12.6 Distressed 21.9 (No Persistent Poverty) Non-metro 
Washingtonf 12.1 Transitional 16.2 (No Persistent Poverty) Non-metro 
a

Centers for Disease Control and Prevention. CDC county diabetes health data. Available from https://www.cdc.gov/diabetes/data/county.html. Accessed 7 December 2017.

b

Appalachian Regional Commission. ARC-designated distressed counties, fiscal year 2011. Available from https://www.arc.gov/program_areas/ARCDesignatedDistressedCountiesFiscalYear2011.asp. Accessed 25 January 2018.

c

U.S. Department of Agriculture. Poverty 2014 (county level data sets). Available from http://www.ers.usda.gov/data-products/county-level-data-sets/poverty.aspx#.U-6496NAJI0. Accessed 15 August 2014.

d

U.S. Department of Agriculture. Persistent poverty counties (updated 2013). Available from http://www.ers.usda.gov/data-products/county-typology-codes.aspx#.U-68eqNAJI0. Accessed 15 August 2014.

e

U.S. Department of Agriculture. Rural-urban continuum codes, 2013. Available from http://www.ers.usda.gov/data-products/rural-urban-continuum-codes.aspx#.U-66yqNAJI0. Accessed 15 August 2014.

f

County in Diabetes Belt (Centers for Disease Control and Prevention). CDC identifies diabetes belt. Available from https://www.cdc.gov/diabetes/data/county.html. Accessed 25 January 2018.

Participants were recruited and interviewed from July to December 2010. Each prospective participant received a formal briefing regarding the purposes, benefits, and risks of the study. Patients with type 1 or type 2 diabetes were eligible for inclusion; those with other conditions (e.g., gestational diabetes, prediabetes, or other endocrine conditions) were excluded. After the briefing, individuals voluntarily chose to participate in the study and signed the associated consent forms.

Study Design

Patients were administered an 86-item survey. The survey included demographic questions and the 18-item USDA Food Security Survey Module (16). The Food Security Survey Module was used to determine household food security (HFS) and household adult food security (HAFS) status (16,17). Participants’ characteristics, including age and diabetes status, as well as medical record information, were collected independent of the survey administration. Medical information included height, weight, BMI, A1C, blood lipids (total, HDL, and LDL cholesterol), systolic and diastolic blood pressure, and type 1 or type 2 diabetes diagnosis. If participants’ charts were missing needed medical information, participants were not asked to undergo additional tests for the purpose of the study.

Statistical Analysis

All surveys were analyzed using SPSS version 18.0 (IBM Corp., Chicago, Ill.). Mann-Whitney U tests were used to assess for differences between clinic groups for HFS and HAFS. t Tests were used to determine differences between clinic groups with regard to BMI; A1C; total, LDL, and HDL cholesterol; and systolic and diastolic blood pressure. Pearson r correlations were used to examine the relationship of HFS status and HAFS status to A1C. Furthermore, Mann-Whitney U tests were also used to determine the distribution of HFS and HAFS with regard to type of diabetes. Frequency functions distinguished the number of participating patients with type 1 versus type 2 diabetes, as well as the primary treatment approach to managing diabetes.

Participants (n = 166) were 53 ± 16 years of age and almost entirely Caucasian (91.9%). The majority of participants (65.8%) had type 2 diabetes and some education at the collegiate level or higher (52.8%). Demographic data are summarized in Table 2. Table 3 summarizes participant food security status. Overall, 43.5% of free clinic patients and 13.8% of fee-for-service patients lived in households characterized by low or very low food security.

TABLE 2.

Characteristics of Adults With Diabetes Attending Free and Fee-for-Service Clinics in Rural, Appalachian Ohio

Characteristicn (%)
Race (n = 160)  
 Caucasian 147 (91.9) 
 African American 10 (6.3) 
 Hispanic 1 (0.6) 
 Native American or Native Alaskan 1 (0.6) 
 Native Hawaiian or other Pacific Islander 1 (0.6) 
Clinic used for diabetes care (n = 166)  
 Fee-for-service clinic 125 (75.3) 
 Free clinic 41 (25.7) 
Diabetes diagnosis (n = 155)  
 Type 1 diabetes 53 (34.2) 
 Type 2 diabetes 102 (65.8) 
Highest level of education (n = 163)  
 Less than high school 15 (9.2) 
 High school graduate 62 (38) 
 Some college or higher 86 (52.8) 
Characteristicn (%)
Race (n = 160)  
 Caucasian 147 (91.9) 
 African American 10 (6.3) 
 Hispanic 1 (0.6) 
 Native American or Native Alaskan 1 (0.6) 
 Native Hawaiian or other Pacific Islander 1 (0.6) 
Clinic used for diabetes care (n = 166)  
 Fee-for-service clinic 125 (75.3) 
 Free clinic 41 (25.7) 
Diabetes diagnosis (n = 155)  
 Type 1 diabetes 53 (34.2) 
 Type 2 diabetes 102 (65.8) 
Highest level of education (n = 163)  
 Less than high school 15 (9.2) 
 High school graduate 62 (38) 
 Some college or higher 86 (52.8) 
TABLE 3.

HFS and HAFS Status of Adults With Diabetes Attending Free and Fee-for-Service Clinics in Rural, Appalachian Ohio

ClinicFood Security Categoryn (%)Pa
HFS status (n = 162) 
Free Highb 12 (30.8)  
 Marginalb 10 (25.6)  
 Lowc 7 (17.9)  
 Very lowc 10 (25.6) <0.001 
Fee-for-service Highb 87 (70.7)  
 Marginalb 19 (15.4)  
 Lowc 10 (8.1)  
 Very lowc 7 (5.7)  
HAFS status (n = 162) 
Free Highb 12 (30.8)  
 Marginalb 10 (25.6)  
 Lowc 6 (15.4)  
 Very lowc 11 (28.2) <0.001 
Fee-for-Service Highb 87 (70.7)  
 Marginalb 19 (15.4)  
 Lowc 10 (8.1)  
 Very lowc 7 (5.7)  
ClinicFood Security Categoryn (%)Pa
HFS status (n = 162) 
Free Highb 12 (30.8)  
 Marginalb 10 (25.6)  
 Lowc 7 (17.9)  
 Very lowc 10 (25.6) <0.001 
Fee-for-service Highb 87 (70.7)  
 Marginalb 19 (15.4)  
 Lowc 10 (8.1)  
 Very lowc 7 (5.7)  
HAFS status (n = 162) 
Free Highb 12 (30.8)  
 Marginalb 10 (25.6)  
 Lowc 6 (15.4)  
 Very lowc 11 (28.2) <0.001 
Fee-for-Service Highb 87 (70.7)  
 Marginalb 19 (15.4)  
 Lowc 10 (8.1)  
 Very lowc 7 (5.7)  
a

Mann-Whitney U test.

b

Food secure.

c

Food insecure.

Table 4 summarizes differences between free clinic and fee-for-service clinic participants. A1C was the only statistically significant discriminating variable, with free clinic users having worse glycemic control during the past 2–3 months compared to fee-for-service clinic users (A1C 8.71 vs. 7.83%, P =0.005). Regardless of the type of clinic used, A1C values increased as HFS (r = 0.293, P <0.001) and HAFS (r = 0.288, P = 0.001) worsened.

TABLE 4.

Health Indices of Adults With Diabetes Attending Free or Fee-for-Service Clinics in Rural, Appalachian Ohio

ParameterClinicnMean ± SDPa
A1C (%) (n = 143) Free 35 8.71 ± 1.740 0.005 
Fee 108 7.83 ± 1.551 
BMI (kg/m2) (n = 156) Free 36 31.48 ± 8.568 0.139 
Fee 120 33.81 ± 8.155 
Systolic blood pressure (mmHg) (n = 159) Free 36 134.69 ± 29.895 0.226 
Fee 123 128.31 ± 16.215 
Diastolic blood pressure (mmHg) (n = 157) Free 34 77.24 ± 10.257 0.516 
Fee 123 75.93 ± 10.408 
Total cholesterol (mg/dL) (n = 128) Free 28 198.71 ± 59.594 0.391 
Fee 100 180.79 ± 105.269 
HDL cholesterol (mg/dL) (n = 127) Free 28 49.32 ± 20.937 0.348 
Fee 99 45.325 ± 14.102 
LDL cholesterol (mg/dL) (n = 123) Free 25 111.01 ± 52.652 0.109 
Fee 98 94.67 ± 43.121 
ParameterClinicnMean ± SDPa
A1C (%) (n = 143) Free 35 8.71 ± 1.740 0.005 
Fee 108 7.83 ± 1.551 
BMI (kg/m2) (n = 156) Free 36 31.48 ± 8.568 0.139 
Fee 120 33.81 ± 8.155 
Systolic blood pressure (mmHg) (n = 159) Free 36 134.69 ± 29.895 0.226 
Fee 123 128.31 ± 16.215 
Diastolic blood pressure (mmHg) (n = 157) Free 34 77.24 ± 10.257 0.516 
Fee 123 75.93 ± 10.408 
Total cholesterol (mg/dL) (n = 128) Free 28 198.71 ± 59.594 0.391 
Fee 100 180.79 ± 105.269 
HDL cholesterol (mg/dL) (n = 127) Free 28 49.32 ± 20.937 0.348 
Fee 99 45.325 ± 14.102 
LDL cholesterol (mg/dL) (n = 123) Free 25 111.01 ± 52.652 0.109 
Fee 98 94.67 ± 43.121 
a

Mann-Whitney U test.

Results indicate that individuals using free clinics are less food secure and have worse glycemic control than their counterparts who use fee-for-service clinics. In addition, regardless of clinic type, as food insecurity worsens, blood glucose control also worsens.

Other studies have provided empirical evidence of a higher rate of household food insecurity among populations with diabetes versus those without diabetes (18). This study indicates that those with diabetes who seek free care are prone to food insecurity. In this rural, Appalachian Ohio sample of clients using fee-for-service clinics, HFS status (13.8%) was lower than both the national (14.5%) and Ohio (16.4%) estimates. However, household food insecurity among those using free clinics (43.5%) was about three times higher than their fee-for-service counterparts, as well as three times higher than national and state estimates. HAFS levels, a proxy for individual or “personal” food security status, were similar. The disparity in food security may also reflect income level, given that U.S. households with income at or below the poverty level had food insecurity levels of 40.2% in 2010, the time frame for this study (8).

A review of other studies underscored that food insecurity may precipitate or be associated with poorer glycemic control (18). These results support the association between food insecurity and poor blood glucose control over the past 2–3 months, also demonstrating how those seeking free care have poorer control than their fee-for-service counterparts. According to Tuerk et al. (19), programs encouraging improved patient self-management practices should be developed because patients’ relative self-management skills also account for variance in glycemic control. Yet, in the absence of adequate access to food, appropriate blood glucose control may prove to be difficult.

Limitations of this study include its small convenience sample drawn from only one rural region of the United States, which limits its generalizability. Participants at the free clinic were only accessible once per month, limiting time to recruit a comparison group. It is possible that the participants do not accurately represent individuals with diabetes in Appalachian Ohio or other rural regions of the United States. Furthermore, this study recruited participants only from a diabetes-specific free clinic, but other patients with diabetes possibly attended the primary care free clinic in the study region. We are unable to infer whether there were differences between these two populations. Finally, people had to qualify for the free clinic, and it is possible that they may have over-reported their food insecurity because of concern about possibly losing access to care.

Successful management of type 1 or type 2 diabetes is complicated by food insecurity. Thus, screening for food insecurity should be completed at all clinic visits (20). In addition, diabetes educators should consider that patients may not have access to adequate food for successful diabetes management.

This study found that long-term blood glucose control worsens in accord with the severity of food insecurity and thus should serve as a catalyst for improving diabetes education in Appalachian Ohio and similar rural areas. As rural communities grapple with system-level barriers to detecting and managing diabetes (e.g., high rates of poverty; limited access to insurance, specialty medical care, and emergency services; and minimal exposure to diabetes and nutrition education [21]), medical practitioners should articulate self-management practices to patients during potentially infrequent visits, including strategies for dealing with times when patients may lack access to food. Screening for food insecurity and referring clients to community resources may also be prudent.

Many individuals must make sacrificial decisions regarding medicine, food, or medical attention, placing them in a cycle of food insecurity and chronic disease. This is particularly acute among Medicare recipients—one of the fastest-growing medical populations in the United States. This study may increase awareness among health care providers in free and low-cost clinics about the importance of looking for innovative solutions to better help these high-risk patients. This is especially important given recent research finding that food insecurity coupled with diabetes increases health care expenditures (22). Future empirical research in both rural and metropolitan areas to analyze relationships between diabetes-related comorbidities and food insecurity would positively contribute to the dearth of literature available on this topic. In addition, interventions aimed at improving both diabetes management and food security are also warranted.

Funding

Funding for this study was provided by an Ohio University Diabetes Research Initiative Research Fellowship and an Ohio University Provost Undergraduate Research Fund Award, Ohio University, Athens, Ohio.

Duality of Interest

No potential conflicts of interest relevant to this article were reported.

Author Contributions

D.H.H. and J.H.S. supervised and K.A.B. contributed to the study design and data collection and the writing and revision of the manuscript. D.H.H. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

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