we analyzed pooled cross - sectional data from the national health and nutrition examination survey ( nhanes ) cycles . nhanes is a series of large , cross - sectional surveys conducted by the national center for health statistics ( nchs ) for the centers for disease control and prevention ( cdc ) in community - dwelling participants designed to generate estimates of population health ( 10 ) . since 1999 , nhanes has been conducted in 2-year survey  cycles . nhanes interviewers administer a questionnaire in randomly selected participant homes , in english or spanish or with an interpreter ( 10 ) . participants then travel to a mobile examination center ( mec ) , where physical examinations and nonfasting blood work are performed ( 10 ) . our study includes all adult nhanes participants ( 20 years of age ) with diabetes ( type 1 or type 2 ) from 1999 through 2008 , the most recent study year with available food security data . because of the relatively small number of patients who receive fasting blood work each cycle ( 10 ) , this pooling of data was necessary to ascertain a sufficient number of cases to permit robust adjustment for confounding . in accordance with prior studies ( 1214 ) and methodology used in cdc reports ( 15 ) , participants were considered to have diabetes if they answered have you ever been told by a doctor or health care professional that you have diabetes or sugar diabetes ? because prior studies have noted that some participants who are under treatment for diabetes do not report their diagnosis ( 16 ) , we also considered a participant to have diabetes if he or she was taking diabetes medications , such as a sulfonylurea , insulin , or an incretin mimetic . metformin alone was not considered evidence of diabetes because it is commonly used for nondiabetes indications . the partners healthcare human research committee exempted this study from institutional review board review . department of agriculture ( usda ) to report national rates of food security ( 4 ) . using the established scoring system ( 6 ) , responses on the food security items were converted to either food secure ( zero to two affirmative responses , categorized as  food secure  or  marginally food secure  ) or food insecure ( three or more affirmative responses ,  low food security  or  very low food security  categories ) . the items used to determine food security status remained unchanged throughout the study period . the food security survey module was validated as part of the food security measurement project , conducted by the usda food and nutrition service using data from the u.s . it is now considered  the government s primary measure of this dimension of the well - being of the u.s . population  ( 4 ) . because nhanes administers the food security survey module in accordance with recommendations from the usda , the results are highly reproducible , leading to statistics that are  directly comparable to published national statistics  ( 17 ) . we wanted to fully describe the relationship between food insecurity and the spectrum of cardiovascular control , so we considered indicators of poor glycemic , poor cholesterol , and poor blood pressure control . poor glycemic control was defined as hba1c > 9.0% ( 75 mmol / mol ) . we chose this level because reducing the proportion of diabetes participants with an hba1c > 9.0% ( 75 mmol / mol ) is a healthy people 2020 goal ( 18 ) , since  an hba1c level of 9% ( 75 mmol / mol ) constitutes a clearly modifiable , high level of risk that few , if any , persons with diabetes should be exposed to  ( 15 ) . moreover , 9.0% ( 75 mmol / mol ) was considered to represent out - of - control glycemia for all diabetic patients throughout the study period . in contrast , lower hba1c targets , such as 7.0% ( 53 mmol / mol ) , are controversial , are not intended to be applied to all patients ( 1 ) , and have not been consistently recommended throughout the 10-year study period . poor cholesterol control was defined as having an ldl > 100 mg / dl , because this is the only healthy people 2020 ldl target for patients with diabetes ( 18 ) . this was also consistent with recommendations for diabetic patients throughout the study period ( 19 ) . poor blood pressure control was defined as a mean systolic blood pressure ( sbp ) > 140 mmhg or mean diastolic blood pressure ( dbp ) > 90 mmhg , averaged over up to four readings obtained by mec staff ( 10 ) . this is higher than a blood pressure target of < 130/80 mmhg , which has at times been recommended ( 19 ) . we considered several sociodemographic factors that might confound the association between food insecurity and metabolic control . demographic variables included age ( as a continuous variable ) , sex , and race / ethnicity ( non - hispanic white , non - hispanic black , hispanic , and mixed race / other ) . educational attainment was categorized into less than high school , high school diploma , or greater than high school . income was expressed as percentage of federal poverty level , which accounts for household size and for inflation over the 10-year study period . insurance status was categorized as no insurance , private insurance , medicare , and non - medicare public insurance , including medicaid . we also considered clinical variables such as bmi ( weight in kilograms divided by height in meters squared , measured in the mec ) , smoking status ( current / former / never ) , duration of diabetes ( current age minus reported age at diabetes diagnosis ) , and having a usual place of care . for our glycemic control analysis , we ascertained diabetes medication use , according to the medications recorded by the nhanes interviewer . for our blood pressure and ldl analysis , we additionally ascertained antihypertensive medication use and statin use , respectively . differences were tested for significance with  tests for categorical values and student t tests for continuous variables . we used multivariable logistic regression analysis to assess the independent association between food insecurity and poor diabetes control , controlling for the sociodemographic and clinical variables described above . to account for secular trends over the duration of the study period , we also adjusted for survey year . in order to help clinicians identify patient populations at higher risk of food insecurity , we performed descriptive statistics and univariate logistic regression to identify the factors associated with food insecurity . using a similar approach , we performed crude and multivariable logistic regression to determine the associations between food insecurity and poor ldl control , and between food insecurity and poor blood pressure control . a p value of < 0.05 on a  test , student t test , or satterthwaite adjusted f test was taken to indicate statistical significance . because only a subset of nhanes participants undergo fasting blood work , our analysis of ldl control includes only those participants for whom a fasting ldl value is reported . analyses were performed using sas ( version 9.3 , cary , nc ) and sas - callable sudaan ( version 10.0.1 , research triangle park , nc ) to account for the complex multistage survey design . as recommended by the nchs ( 11 ) , appropriate weights were used in our analysis : mec weights for glycemic and blood pressure results and fasting laboratory weights for ldl results ( 11 ) . as recommended by the nchs ( 20 ) , we excluded 19992001 food security questionnaire data when calculating population estimates . we analyzed pooled cross - sectional data from the national health and nutrition examination survey ( nhanes ) cycles . nhanes is a series of large , cross - sectional surveys conducted by the national center for health statistics ( nchs ) for the centers for disease control and prevention ( cdc ) in community - dwelling participants designed to generate estimates of population health ( 10 ) . since 1999 , nhanes has been conducted in 2-year survey  cycles . nhanes interviewers administer a questionnaire in randomly selected participant homes , in english or spanish or with an interpreter ( 10 ) . participants then travel to a mobile examination center ( mec ) , where physical examinations and nonfasting blood work are performed ( 10 ) . our study includes all adult nhanes participants ( 20 years of age ) with diabetes ( type 1 or type 2 ) from 1999 through 2008 , the most recent study year with available food security data . because of the relatively small number of patients who receive fasting blood work each cycle ( 10 ) , this pooling of data was necessary to ascertain a sufficient number of cases to permit robust adjustment for confounding . in accordance with prior studies ( 1214 ) and methodology used in cdc reports ( 15 ) , participants were considered to have diabetes if they answered have you ever been told by a doctor or health care professional that you have diabetes or sugar diabetes ? because prior studies have noted that some participants who are under treatment for diabetes do not report their diagnosis ( 16 ) , we also considered a participant to have diabetes if he or she was taking diabetes medications , such as a sulfonylurea , insulin , or an incretin mimetic . metformin alone was not considered evidence of diabetes because it is commonly used for nondiabetes indications . the partners healthcare human research committee exempted this study from institutional review board review . department of agriculture ( usda ) to report national rates of food security ( 4 ) . using the established scoring system ( 6 ) , responses on the food security items were converted to either food secure ( zero to two affirmative responses , categorized as  food secure  or  marginally food secure  ) or food insecure ( three or more affirmative responses ,  low food security  or  very low food security  categories ) . the items used to determine food security status remained unchanged throughout the study period . the food security survey module was validated as part of the food security measurement project , conducted by the usda food and nutrition service using data from the u.s . it is now considered  the government s primary measure of this dimension of the well - being of the u.s . population  ( 4 ) . because nhanes administers the food security survey module in accordance with recommendations from the usda , the results are highly reproducible , leading to statistics that are  directly comparable to published national statistics  ( 17 ) . department of agriculture ( usda ) to report national rates of food security ( 4 ) . using the established scoring system ( 6 ) , responses on the food security items were converted to either food secure ( zero to two affirmative responses , categorized as  food secure  or  marginally food secure  ) or food insecure ( three or more affirmative responses ,  low food security  or  very low food security  categories ) . the items used to determine food security status remained unchanged throughout the study period . the food security survey module was validated as part of the food security measurement project , conducted by the usda food and nutrition service using data from the u.s . it is now considered  the government s primary measure of this dimension of the well - being of the u.s . population  ( 4 ) . because nhanes administers the food security survey module in accordance with recommendations from the usda , the results are highly reproducible , leading to statistics that are  directly comparable to published national statistics  ( 17 ) . we wanted to fully describe the relationship between food insecurity and the spectrum of cardiovascular control , so we considered indicators of poor glycemic , poor cholesterol , and poor blood pressure control . poor glycemic control was defined as hba1c > 9.0% ( 75 mmol / mol ) . we chose this level because reducing the proportion of diabetes participants with an hba1c > 9.0% ( 75 mmol / mol ) is a healthy people 2020 goal ( 18 ) , since  an hba1c level of 9% ( 75 mmol / mol ) constitutes a clearly modifiable , high level of risk that few , if any , persons with diabetes should be exposed to  ( 15 ) . moreover , 9.0% ( 75 mmol / mol ) was considered to represent out - of - control glycemia for all diabetic patients throughout the study period . in contrast , lower hba1c targets , such as 7.0% ( 53 mmol / mol ) , are controversial , are not intended to be applied to all patients ( 1 ) , and have not been consistently recommended throughout the 10-year study period . poor cholesterol control was defined as having an ldl > 100 mg / dl , because this is the only healthy people 2020 ldl target for patients with diabetes ( 18 ) . this was also consistent with recommendations for diabetic patients throughout the study period ( 19 ) . poor blood pressure control was defined as a mean systolic blood pressure ( sbp ) > 140 mmhg or mean diastolic blood pressure ( dbp ) > 90 mmhg , averaged over up to four readings obtained by mec staff ( 10 ) . this is higher than a blood pressure target of < 130/80 mmhg , which has at times been recommended ( 19 ) . we considered several sociodemographic factors that might confound the association between food insecurity and metabolic control . demographic variables included age ( as a continuous variable ) , sex , and race / ethnicity ( non - hispanic white , non - hispanic black , hispanic , and mixed race / other ) . educational attainment was categorized into less than high school , high school diploma , or greater than high school . income was expressed as percentage of federal poverty level , which accounts for household size and for inflation over the 10-year study period . insurance status was categorized as no insurance , private insurance , medicare , and non - medicare public insurance , including medicaid . we also considered clinical variables such as bmi ( weight in kilograms divided by height in meters squared , measured in the mec ) , smoking status ( current / former / never ) , duration of diabetes ( current age minus reported age at diabetes diagnosis ) , and having a usual place of care . for our glycemic control analysis , we ascertained diabetes medication use , according to the medications recorded by the nhanes interviewer . for our blood pressure and ldl analysis , we additionally ascertained antihypertensive medication use and statin use , respectively . differences were tested for significance with  tests for categorical values and student t tests for continuous variables . we used multivariable logistic regression analysis to assess the independent association between food insecurity and poor diabetes control , controlling for the sociodemographic and clinical variables described above . to account for secular trends over the duration of the study period , we also adjusted for survey year . in order to help clinicians identify patient populations at higher risk of food insecurity , we performed descriptive statistics and univariate logistic regression to identify the factors associated with food insecurity . using a similar approach , we performed crude and multivariable logistic regression to determine the associations between food insecurity and poor ldl control , and between food insecurity and poor blood pressure control . a p value of < 0.05 on a  test , student t test , or satterthwaite adjusted f test was taken to indicate statistical significance . because only a subset of nhanes participants undergo fasting blood work , our analysis of ldl control includes only those participants for whom a fasting ldl value is reported . analyses were performed using sas ( version 9.3 , cary , nc ) and sas - callable sudaan ( version 10.0.1 , research triangle park , nc ) to account for the complex multistage survey design . as recommended by the nchs ( 11 ) , appropriate weights were used in our analysis : mec weights for glycemic and blood pressure results and fasting laboratory weights for ldl results ( 11 ) . as recommended by the nchs ( 20 ) , we excluded 19992001 food security questionnaire data when calculating population estimates . we excluded 169 participants who did not have an hba1c value , which left a sample of 2,557 for analysis of hba1c and blood pressure control . for our analysis of ldl control , over 12% of adults with diabetes ( n = 371 ) in our sample were food insecure , representing 2 million americans . sixteen percent ( n = 414 ) of adults with diabetes had an hba1c > 9.0% ( 75 mmol / mol ) , representing > 2.1 million americans . of these , 22% were food insecure , representing 480,000 americans . among the subset who also had a fasting blood draw , 53% ( n = 493 ) had ldl > 100 mg / dl . this represents 7.1 million adults with diabetes who have out - of - control ldl cholesterol , of whom 1.1 million are food insecure . adults with food insecurity comprised a significantly higher proportion of those with poor glycemic ( 27.0 vs. 13.3% , p < 0.001 ) and ldl control ( 68.8 vs. 49.8% , p = 0.002 ) but not of those with poor blood pressure control ( table 1 ) . sample characteristics of adults with diabetes overall and by metabolic control table 2 presents the relationship between food insecurity and metabolic control after consideration of other potential confounders . after adjustment for sociodemographic factors , smoking status , bmi , duration of diabetes , diabetes medication use , and presence of a usual source of care , participants with food insecurity remained significantly more likely to have poor glycemic control ( odds ratio [ or ] 1.53 [ 95% ci 1.072.19 ] ) . participants with food insecurity were also more likely to have an ldl > 100 mg / dl after adjustment ( 1.86 [ 1.013.44 ] ) for sociodemographic factors , smoking status , bmi , duration of diabetes , statin use , and presence of a usual source of care . there was no evidence of an association between food insecurity and the proportion of participants with sbp > 140 mmhg or dbp > 90 mmhg before ( 31.8% in food insecure vs. 32.9% in food secure , p = 0.75 ) or after adjustment ( or 1.10 [ 0.751.61 ] ) . table 2 presents the full results of our adjusted models for poor glycemic , ldl cholesterol , and blood pressure control . factors associated with poor glycemic , ldl , and blood pressure control after adjustment table 3 presents the factors associated with food insecurity among adults with diabetes overall and among those with poor glycemic control . those with younger age , less education or income , race / ethnicity other than non - hispanic white , and either no or public insurance other than medicare were significantly more likely to report food insecurity . younger age , no insurance , public insurance other than medicare , and low income were also commonly associated with food insecurity in those with hba1c adults with diabetes , food insecurity was associated with poor glycemic and cholesterol control even after adjusting for numerous demographic , socioeconomic , and clinical factors . however , we found no evidence of an association between food security and blood pressure control . these data suggest that > 2.1 million adults with diabetes have inadequate glycemic control , and of these , nearly 25% are food insecure . ldl cholesterol reduction may be more important than glycemic control for cardiovascular disease outcomes in diabetic patients ( 21 ) . because of this , our observation that nearly 70% of food - insecure participants with diabetes had poorly controlled cholesterol may be particularly relevant . previous clinic - based studies noted worse glycemic control among food - insecure diabetic patients in safety - net clinics ( 8,9 ) , but did not evaluate lipid control . additionally , no population - based study had previously examined glycemic , lipid , and blood pressure control among all adults with diabetes . a prior study ( 22 ) restricted to younger , low - income participants did report an association with glycemic control but did not evaluate lipid or blood pressure control in participants with diabetes . furthermore , because the methodology of this study would have excluded over two - thirds of our sample , it was not clear that the glycemic control findings would be generalizable to a nationally representative sample . finally , because there was no adjustment for important variables such as insurance status , medications , bmi , or having a usual source of care , it was not known whether these factors confounded the observed association . by providing robustly controlled estimates from nationally representative data , we have demonstrated that food insecurity is associated with poor glycemic and cholesterol control in a broad population of adults with diabetes , independent of several important potential confounders . our observation that food insecurity worsens glycemia and ldl cholesterol levels , but not blood pressure , suggests distinct physiological processes for these cardiometabolic parameters . this finding is consistent with the results of a factor analysis from the framingham cohort that noted that insulin resistance , higher blood glucose , and adverse serum lipid levels cluster together and often track differently from blood pressure ( 23 ) . although this does suggest a possible pathophysiologic pathway , further research will be required to more finely delineate mechanisms that underlie these associations . beyond this possible pathophysiology , however , food insecurity likely increases risk for poor metabolic control in two other ways ( 5 ) . first , food insecurity can lead to the substitution of low - cost , calorically dense food , such as processed carbohydrates and fats , for higher - cost , less calorically dense foods , such as whole grains and fresh fruits and vegetables . secondly , the circumstances of food insecurity force competing choices that may direct resources away from successful self - management of diabetes . our work has important public health implications because of the substantial morbidity and mortality associated with poor metabolic control in diabetes . nearly 480,000 patients with out - of - control hyperglycemia are food insecure , as are nearly 1.1 million of those with out - of - control lipid levels . our findings have clinical implications as well . because extreme hyperglycemia is very sensitive to diet ( 24,25 ) , it may be difficult to improve hyperglycemia in these patients without addressing food insecurity . however , the circumstances of material deprivation , which produce food insecurity , are not readily amenable to intervention via the traditional provider - patient encounter . to address these circumstances , we need to expand clinical care to include population - based health care strategies that identify and intervene in the case of those at high risk of morbidity due to social circumstances . programs like the south side diabetes project ( 25 ) , which addresses community factors such as the built environment and food availability , may point toward interventions that are particularly important for vulnerable patients . we identified several participant characteristics that are associated with food insecurity , some of which are more readily accessible to clinicians than others . for example , low income is closely associated with food insecurity , but clinicians may not have access to this data . in contrast , factors such as patient educational attainment or insurance status , which is often available from administrative data , could be used to target screening for food insecurity identification when it is not practical to assess food security in the entire population . more than one in four of participants with diabetes and poor glycemic control under 65 years of age were food insecure , as were one - third of those with no or public insurance . despite the increased risk in these groups , however , it is important to note that almost 15% of participants with private insurance and almost one in five out - of - glycemic - control participants with some college education were food insecure . although no studies , to our knowledge , have demonstrated improved glycemic or cholesterol control with food insecurity interventions , patients identified in this way can nevertheless be assisted through established food security promotion programs such as the supplemental national assistance program ( snap , formerly the food stamp program ) and local food banks . because food banks may promote food sources associated with worse diabetes management , such as refined carbohydrates and fats ( 26 ) , nutritional counseling explicitly incorporating advice recognizing the unique circumstances of diabetic patients with food insecurity should be a cornerstone of disease management in this population . food security is a household - level variable , whereas disease control is measured at an individual level . although this study used a robust set of controls for confounding , unmeasured confounders , such as neighborhood effects , could not be controlled for . physical activity , which has been associated with diabetes ( 27 ) , underwent a change in assessment during the study period and thus could not be included in our models . however , because prior studies in nhanes reported that food insecurity is not associated with physical activity ( 7 ) and because , in conceptual models of food insecurity ( 5 ) , physical inactivity can be considered a mediator of poor health outcomes , we do not believe physical inactivity to be a confounder of our results . given these limitations , and because we analyzed cross - sectional data , this study can not establish that food insecurity causes poor glycemic and ldl cholesterol control . nevertheless , our study does suggest that food insecurity indicates a group at high risk for poor disease control . the study sample comprised a large , nationally representative set of participants with robust interview , examination , and laboratory data . other self - reported items were collected from consistent , validated instruments , and examination measures were performed by trained personnel in controlled settings . laboratory results were all standardized . by combining 10 years of data , we ascertained enough cases to adjust for demographic , socioeconomic , and clinical variables . we used a conservative analytic strategy that included factors , such as bmi , that might plausibly be on the causal pathway between food insecurity and metabolic control ( 28 ) and a robust set of controls , yet still detected a significantly increased risk for poor metabolic control in food - insecure participants . in summary , food insecurity is significantly associated with poor metabolic control in adults with diabetes . with increasing interest in advanced population management , we should consider interventions that address social circumstances such as food insecurity to help successfully manage chronic disease in vulnerable patients .
objectivewe sought to determine whether food insecurity is associated with worse glycemic , cholesterol , and blood pressure control in adults with diabetes.research design and methodswe conducted a cross - sectional analysis of data from participants of the 19992008 national health and nutrition examination survey . 
 all adults with diabetes ( type 1 or type 2 ) by self - report or diabetes medication use were included . 
 food insecurity was measured by the adult food security survey module . 
 the outcomes of interest were proportion of patients with hba1c > 9.0% ( 75 mmol / mol ) , ldl cholesterol > 100 mg / dl , and systolic blood pressure > 140 mmhg or diastolic blood pressure > 90 mmhg . 
 we used multivariable logistic regression for analysis.resultsamong the 2,557 adults with diabetes in our sample , a higher proportion of those with food insecurity ( 27.0 vs. 13.3% , p < 0.001 ) had an hba1c > 9.0% ( 75 mmol / mol ) . 
 after adjustment for age , sex , educational attainment , household income , insurance status and type , smoking status , bmi , duration of diabetes , diabetes medication use and type , and presence of a usual source of care , food insecurity remained significantly associated with poor glycemic control ( odds ratio [ or ] 1.53 [ 95% ci 1.072.19 ] ) . 
 food insecurity was also associated with poor ldl control before ( 68.8 vs. 49.8 , p = 0.002 ) and after ( 1.86 [ 1.013.44 ] ) adjustment . 
 food insecurity was not associated with blood pressure control.conclusionsfood insecurity is significantly associated with poor metabolic control in adults with diabetes . 
 interventions that address food security as well as clinical factors may be needed to successfully manage chronic disease in vulnerable adults .