Abstract
Background
The economic burden of traumatic injuries forces families into difficult tradeoffs between healthcare and nutrition, particularly among those with a low income. However, the epidemiology of food insecurity among individuals reporting having experienced fractures is not well understood.
Questions/purposes
(1) Do individuals in the National Health Interview Survey reporting having experienced fractures also report food insecurity more frequently than individuals in the general population? (2) Are specific factors associated with a higher risk of food insecurity in patients with fractures?
Methods
This retrospective, cross-sectional analysis of the National Health Interview Survey was conducted to identify patients who reported a fracture within 3 months before survey completion. The National Health Interview Survey is an annual serial, cross-sectional survey administered by the United States Centers for Disease Control, involving approximately 90,000 individuals across 35,000 American households. The survey is designed to be generalizable to the civilian, noninstitutionalized United States population and is therefore well suited to evaluate longitudinal trends in physical, economic, and psychosocial health factors nationwide. We analyzed data from 2011 to 2017 and identified 1399 individuals who reported sustaining a fracture during the 3 months preceding their survey response. Among these patients, 27% (384 of 1399) were older than 65 years, 77% (1074) were White, 57% (796) were women, and 14% (191) were uninsured. A raw score compiled from 10 food security questions developed by the United States Department of Agriculture was used to determine the odds of 30-day food insecurity for each patient. A multivariate logistic regression analysis was performed to determine factors associated with food insecurity among patients reporting fractures. In the overall sample of National Health Interview Survey respondents, approximately 0.6% (1399 of 239,168) reported a fracture.
Results
Overall, 17% (241 of 1399) of individuals reporting broken bones or fractures in the National Health Interview Survey also reported food insecurity. Individuals reporting fractures were more likely to report food insecurity if they also were aged between 45 and 64 years (adjusted odds ratio 4.0 [95% confidence interval 2.1 to 7.6]; p < 0.001), had a household income below USD 49,716 (200% of the federal poverty level) per year (adjusted OR 3.1 [95% CI 1.9 to 5.1]; p < 0.001), were current tobacco smokers (adjusted OR 2.8 [95% CI 1.6 to 5.1]; p < 0.001), and were of Black race (adjusted OR 1.9 [95% CI 1.1 to 3.4]; p = 0.02).
Conclusion
Among patients with fractures, food insecurity screening and routine nutritional assessments may help to direct financially vulnerable patients toward available community resources. Such screening programs may improve adherence to nutritional recommendations in the trauma recovery period and improve the physiologic environment for adequate soft tissue and bone healing. Future research may benefit from the inclusion of clinical nutritional data, a broader representation of high-energy injuries, and a prospective study design to evaluate cost-efficient avenues for food insecurity interventions in the context of locally available social services networks.
Level of Evidence
Level III, prognostic study.
Introduction
Recent studies have reported medical debt is the largest source of debt at the individual patient and family level in the United States, surpassing all debts related to credit cards, personal loans, and utilities combined [25, 27]. In 2020, the mean medical debt per American was USD 429, while the mean nonmedical debt was USD 390 [27]. Financial hardships are especially prevalent among patients suffering from traumatic injuries, with long-term consequences with respect to employment, disability, and functional independence [39, 41, 43]. A recent multicenter analysis of 857 patients with lower extremity fractures estimated a mean loss of 1758 productive work hours in the year after injury, equating to a mean economic loss of approximately USD 64,427 [28]. In a similar study of 236 patients with orthopaedic trauma, nearly two-thirds reported cutting back on general expenses, and roughly one-fourth reported missing payments on other nonmedical bills [5].
Food insecurity is defined by the United States Department of Agriculture (USDA) as “a household-level economic and social condition of limited or uncertain access to adequate food” [1, 47]. A recent study by the USDA determined that as of 2017, 15 million United States households were food insecure and faced difficulties obtaining enough food for all family members. Furthermore, 5.8 million American households were determined to have severe food insecurity, with some household members experiencing reduced food intake and disruptions to normal eating patterns [47]. Between 2016 and 2017, the proportion of households with food insecurity and severe food insecurity decreased from 12.3% to 11.8% and from 4.9% to 4.5%, respectively [28, 30, 37]. Traumatic injuries have been shown to force patients into difficult tradeoffs between medical expenditures and payments for necessities such as food or groceries [40, 41]. Considering the influence of nutritional status on fracture healing and patient outcomes, it is important to evaluate adequate access to healthy foods in the recovery period after orthopaedic trauma [11, 14, 16]. However, the nature of food insecurity among patients who sustain fractures has not, to our knowledge, been specifically studied.
Therefore, we asked: (1) Do individuals in the National Health Interview Survey (NHIS) reporting having experienced fractures also report food insecurity more frequently than individuals in the general population? (2) Are specific factors associated with a higher risk of food insecurity in patients with fractures?
Patients and Methods
Study Design and Data Source
The present analysis used the NHIS, which is an annually recurring, serial, cross-sectional survey involving approximately 90,000 individuals from 35,000 American households [10, 23, 36]. The survey is administered by the United States Centers for Disease Control and evaluates trends in physical, economic, and psychosocial health factors nationwide [22, 33, 49]. The NHIS is designed to be generalizable to the overall, civilian, noninstitutionalized United States population, with sampling strategies focused on the inclusion of historically underrepresented minority groups [10, 15, 49]. By targeting these historically underrepresented groups for inclusion, the NHIS methodology mitigates the problem of underrepresentation and allows for greater demographic balance and broader generalizability to the overall United States population [30]. One adult from each household is randomly chosen to participate in a detailed interview regarding demographics, health status, treatments, injury episodes, and socioeconomic risk factors [8, 12]. The mean household-level response rate for the NHIS was approximately 80% between 2004 and 2017, ranging from approximately 69% to 87% [12, 13]. Nonresponses to the NHIS are generally because of the absence of an eligible adult respondent or direct refusal to participate [13, 20].
Baseline Patient Demographic Data
Between 2011 and 2017, a total of 239,168 individuals participated in the NHIS. Overall, 52% (123,913 of 239,168) of the population were women, 66% (157,707) were White, 19% (44,964) were older than 65 years, 17% (40,946) did not have health insurance, 47% (112,839) were single, 35% (84,474) fell below twice the federal poverty threshold, and 17% (39,893) smoked tobacco at the time of the survey. All racial and ethnic data were self-reported, following the classification scheme used by the United States Census Bureau [10, 46].
After selecting for patients who reported sustaining a fracture over the previous 3 months, the final study sample included 1399 people who participated in the NHIS between 2011 and 2017. Among this population, 27% (384 of 1399) were older than 65 years, 77% (1074) were White, 57% (796) were women, and 14% (191) were uninsured. Additionally, 55% (767 of 1399) of patients were single and 24% (331 of 1399) were current tobacco smokers.
Assessment of Food Insecurity
Determinations of food security and insecurity were made based on responses to a 10-item household food security questionnaire designed by the USDA [47]. The USDA questionnaire has undergone extensive psychometric validation across a variety of subgroup populations and has demonstrated high precision, internal consistency, sensitivity, and accuracy [9, 17, 26, 47]. The food security module was included in the annual administration of the NHIS beginning in 2011 and incorporates questions regarding periods of prolonged hunger, affordability of groceries, skipped meals, reduced portion sizes, and nutritional content (Table 1) [21, 47, 48]. For example, “In the last 30 days, were you worried food would run out before getting money to buy more?” or “In the last 30 days, have you ever lost weight because you did not have enough money for food?” Responses to the 10-item questionnaire were compiled into a composite score ranging from 0 to 10, where scores from 0 to 2 are defined as food secure, and scores ranging from 3 to 10 are considered food insecure, in concordance with previous recommendations from the USDA (Table 1) [48].
Table 1.
Questions given by a USDA supplement to ascertain family food security statusa
| Question | Possible responses |
| “Family worried food would run out before got money to buy more, last 30 days” | Often true, sometimes true, never true, unknown |
| “Food did not last until family had money to get more, last 30 days” | Often true, sometimes true, never true, unknown |
| “Family could not afford to eat balanced meals, last 30 days” | Often true, sometimes true, never true, unknown |
| “Family members cut size or skipped meals because not enough money, last 30 days” | Yes, no, unknown |
| “Number of days any family members cut size or skipped meals for financial reasons, last 30 days” | 1-30, unknown |
| “Ever ate less than felt should because not enough money, last 30 days” | Yes, no, unknown |
| “Ever hungry but did not eat because not enough money, last 30 days” | Yes, no, unknown |
| “Ever lost weight because not enough money for food, last 30 days” | Yes, no, unknown |
| “Any family members not eat for a whole day because not enough money for food, last 30 days” | Yes, no, unknown |
| “Number of days any family member did not eat due to lack of money, last 30 days” | Yes, no, unknown |
A raw score ranging from 0 to 10 was assembled based on the number of affirmative responses to the questions given by the USDA supplement. “Food security” was defined as having a raw score of 0 to 2, whereas “food insecurity” was defined as having a raw score of 3 to 10 in concordance with USDA protocol. USDA = United States Department of Agriculture.
Injury Characteristics
Since 1997, the NHIS has included a variety of questions assessing injury characteristics such as mechanism, environment, treatments, and return-to-work patterns [30, 52]. All 1399 survey respondents reporting a fracture were prompted to describe injuries experienced during the previous 3 months and describe the type and location of each injury sustained. Individuals reporting a broken bone or fracture within the past 3 months were selected for the present analysis, whereas those with other injury patterns (such as cut, bruise, burn, animal bite, sprain, and other) were excluded. In plain language, survey respondents also described the anatomic regions of injury, which were grouped into upper extremity, lower extremity, spine, and other. Injury mechanisms varied; 47% (663 of 1399) were because of falls, 6% (77) were because of motor vehicle collisions, and 1% (15) were pedestrians struck by motor vehicles (Table 2). Furthermore, the anatomic region of fractures varied: 33% (463 of 1399) of fractures were in the upper extremity, 43% (596) were in the lower extremity, and 5% (73) were in the spine. Sixty-four percent (893 of 1399) of fractures were treated in the emergency room, and 18% (257) of patients were admitted to the hospital for at least one day (Table 2).
Table 2.
Characteristics of patients sustaining and not sustaining orthopaedic injuries in the National Health Interview Survey dataset
| Variable | All survey respondents (n = 239,168) | Individuals reporting fractures | |
| No (n = 237,769) | Yes (n = 1399) | ||
| Age in years | |||
| 65 and above | 19 (44,964) | 19 (44,580) | 27 (384) |
| 45-64 | 34 (82,441) | 34 (81,969) | 34 (472) |
| 18-44 | 47 (111,763) | 47 (111,220) | 39 (543) |
| Race or ethnicitya | |||
| White | 66 (157,707) | 66 (156,633) | 77 (1074) |
| Black | 12 (27,839) | 12 (27,692) | 11 (147) |
| Hispanic | 15 (35,852) | 15 (35,715) | 10 (137) |
| Other | 7 (17,770) | 7 (17,729) | 3 (41) |
| Women | 52 (123,913) | 52 (123,117) | 57 (796) |
| US citizenship | 92 (219,987) | 92 (218,624) | 97 (1363) |
| US-born | 82 (197,027) | 82 (195,749) | 91 (1278) |
| Under 200% federal poverty threshold | 35 (84,474) | 35 (83,938) | 38 (536) |
| Uninsured | 17 (40,946) | 17 (40,755) | 14 (191) |
| Single | 47 (112,839) | 47 (112,072) | 55 (767) |
| No college | 70 (166,748) | 70 (165,721) | 73 (1027) |
| Injury mechanism | |||
| Other | 46 (644) | ||
| Fall | 47 (663) | ||
| Motor vehicle collision | 6 (77) | ||
| Pedestrian struck by vehicle | 1 (15) | ||
| Injury region | |||
| Other | 19 (267) | ||
| Lower extremity | 43 (596) | ||
| Spine | 5 (73) | ||
| Upper extremity | 33 (463) | ||
| Treated in emergency room | 64 (893) | ||
| Admitted to hospitalb | 18 (257) | ||
| Days of missed work | |||
| Less than 1 | 23 (316) | ||
| 1 or more | 28 (386) | ||
| Unemployed | 50 (697) | ||
| Tobacco smoking status | |||
| Never | 61 (146,395) | 61 (145,702) | 50 (693) |
| Current | 17 (39,893) | 17 (39,562) | 24 (331) |
| Former | 22 (52,880) | 22 (52,505) | 27 (375) |
| Weekly alcohol use | |||
| None | 35 (84,235) | 35 (83,715) | 37 (520) |
| 3 units or fewer | 56 (135,058) | 56 (134,287) | 55 (771) |
| 4 units or more | 8 (19,875) | 8 (19,767) | 8 (108) |
Data are presented as % (n).
All racial and ethnic data were self-reported by survey respondents following the classification scheme used by the United States Census Bureau.
Indicates response to the survey question “Were you hospitalized for at least one night as a result of this injury?”
Ethical Approval
This study was considered exempt from local institutional board review because of the use of public, deidentified data and absence of any protected health information as defined by section 45 of the Code of Federal Regulations 46.102(d) and (f) of the Department of Health and Human Services’ Code of Federal Regulations [50]. Written informed consent was obtained from all survey participants in the NHIS, and all interview protocols were reviewed and approved by the National Center for Health Statistics research ethics review board [10, 49]. Further details are available on the NHIS data and documentation website [49].
Statistical Analysis
In an initial bivariate analysis, we used a Pearson chi-square test with Rao and Scott adjustment to assess for statistically significant differences across subgroups. Variables with p values below 0.2 were advanced to a subsequent multivariable analysis, using food insecurity as a binary outcome measure in accordance with USDA guidelines. We constructed multivariable logistic regression models to assess factors associated with an increased odds of food insecurity among patients reporting fractures, while controlling for confounding from other demographic, socioeconomic, and behavioral factors. Adjusted odds ratios were calculated as well as 95% confidence intervals. Statistical significance was determined using a Wald test. All statistical analyses were performed with R Version 4.0.2 with the R “survey” package (version 4.0) to account for the multistage, complex sampling design of the NHIS, in concordance with published methodology [2, 8, 31]. A predetermined significance threshold of p < 0.05 was used for all analyses.
Results
Prevalence of Food Insecurity Among Individuals Reporting Having Experienced Fractures
Individuals reporting broken bones or fractures reported food insecurity more frequently than the overall population in the NHIS. Among the 1399 individuals reporting fractures, the prevalence of food insecurity was determined to be 17% (241 of 1399) between 2011 and 2017. Meanwhile, among the 237,769 individuals not reporting a fracture during the same period, the prevalence of food insecurity was 11% (25,679 of 237,769). The annual prevalence of food insecurity among the study population ranged from 13% (4720 of 36,305) in 2014 to 23% (7627 to 32,733) in 2012; however, no trend in increasing or decreasing food insecurity was observed during the study period. The mean annual percentage of food insecurity among individuals reporting fractures was 17% ± 4% (Table 3).
Table 3.
Patient and injury characteristics of individuals in the National Health Interview Survey Dataset reporting having experienced fractures
| Variable | All patients with fractures (n = 1399) | Food-securea (n = 1158) | Food-insecurea (n = 241) | p value |
| Age in years | < 0.001 | |||
| 65 and above | 27 (384) | 31 (355) | 12 (29) | |
| 45-64 | 34 (472) | 32 (369) | 43 (103) | |
| 18-44 | 39 (543) | 37 (434) | 45 (109) | |
| Race or ethnicityb | < 0.001 | |||
| White | 77 (1074) | 79 (920) | 64 (154) | |
| Black | 11 (147) | 9 (99) | 20 (48) | |
| Hispanic | 10 (137) | 9 (105) | 13 (32) | |
| Other | 3 (41) | 3 (34) | 3 (7) | |
| Women | 57 (796) | 57 (657) | 58 (139) | 0.87 |
| US citizenship | 97 (1363) | 98 (1134) | 95 (229) | 0.11 |
| US-born | 91 (1278) | 91 (1059) | 91 (219) | 0.87 |
| US region | 0.32 | |||
| Northeast | 19 (271) | 18 (211) | 25 (60) | |
| Midwest | 23 (321) | 23 (263) | 24 (58) | |
| South | 35 (489) | 35 (410) | 33 (79) | |
| West | 23 (318) | 24 (274) | 19 (44) | |
| Under 200% federal poverty threshold | 38 (536) | 31 (364) | 71 (172) | < 0.001 |
| Uninsured | 14 (191) | 10 (116) | 31 (75) | < 0.001 |
| Single | 55 (767) | 52 (597) | 71 (170) | 0.004 |
| No college | 73 (1027) | 71 (818) | 87 (209) | < 0.001 |
| Injury mechanism | 0.29 | |||
| Other | 46 (644) | 45 (523) | 50 (121) | |
| Fall | 47 (663) | 49 (563) | 42 (100) | |
| Motor vehicle collision | 6 (77) | 5 (61) | 7 (16) | |
| Pedestrian struck | 1 (15) | 1 (11) | 2 (4) | |
| Injury region | 0.43 | |||
| Other | 19 (267) | 17 (201) | 27 (66) | |
| Lower extremity | 43 (596) | 43 (493) | 43 (103) | |
| Spine | 5 (73) | 5 (57) | 7 (16) | |
| Upper extremity | 33 (463) | 35 (407) | 23 (56) | |
| Treated in emergency room | 64 (893) | 63 (734) | 66 (159) | 0.02 |
| Admitted to hospitalc | 18 (257) | 19 (215) | 17 (42) | 0.76 |
| Days of missed work | 0.003 | |||
| Less than 1 | 23 (316) | 25 (286) | 13 (30) | |
| 1 or more | 28 (386) | 27 (316) | 29 (70) | |
| Unemployed | 50 (697) | 48 (556) | 59 (141) | |
| Tobacco smoking status | < 0.001 | |||
| Never | 50 (693) | 54 (621) | 30 (72) | |
| Current | 24 (331) | 18 (211) | 50 (120) | |
| Former | 27 (375) | 28 (326) | 21 (49) | |
| Weekly alcohol use | 0.27 | |||
| None | 37 (520) | 38 (435) | 35 (85) | |
| 3 units or less | 55 (771) | 55 (637) | 56 (134) | |
| 4 units or more | 8 (108) | 7 (86) | 9 (22) |
Data are presented as the % (n).
A raw score for food security ranging from 0 to 10 was determined based on the number of affirmative responses to the questions given by the USDA supplement. “Food security” was defined as having a raw score of 0 to 2 whereas “food insecurity,” the main outcome for this study, was defined as having a raw score of 3 to 10 in concordance with USDA protocol.
All racial and ethnic data were self-reported by survey respondents following the classification scheme used by the United States Census Bureau.
Indicates response to the survey question “Were you hospitalized for at least one night as a result of this injury?” USDA = United States Department of Agriculture.
Factors Associated With Food Insecurity Among Individuals Reporting Fractures
After controlling for potentially confounding variables such as gender, marital status, and educational attainment, we found age 45 to 64 years (adjusted OR 4.0 [95% CI 2.1 to 7.6]; p < 0.001), income below 200% of the federal poverty threshold (adjusted OR 3.1 [95% CI 1.9 to 5.1]; p < 0.001), current tobacco smoking (adjusted OR 2.8 [95% CI 1.6 to 5.1]; p < 0.001), and no college education (adjusted OR 2.3 [95% CI 1.2 to 4.4]; p = 0.01) were associated with increased odds of food insecurity. Additionally, being unemployed (adjusted OR 2.2 [95% CI 1.1 to 4.1]; p = 0.02), Black race (adjusted OR 1.9 [95% CI 1.1 to 3.4]; p = 0.02), and a lack of healthcare insurance (adjusted OR 1.9 [95% CI 1.0 to 3.4]; p = 0.04) were also associated with an increased odds of experiencing food insecurity. Conversely, variables such as the mechanism of injury, whether a person was married, hospitalization, and emergency room use were not associated with having food insecurity (Table 4).
Table 4.
Multivariable logistic regression analysis of factors associated with food insecurity among individuals reporting having experienced fractures, 2011 to 2017a
| Variable | Adjusted OR (95% CI) | p value |
| Age in years | ||
| 65 and above | 1 (Reference) | |
| 45-64 | 4.0 (2.1 to 7.6) | < 0.001 |
| 18-44 | 2.8 (1.5 to 5.2) | 0.001 |
| Race or ethnicityb | ||
| White | 1 (Reference) | |
| Black | 1.9 (1.1 to 3.4) | 0.02 |
| Hispanic | 1.3 (0.6 to 3.0) | 0.47 |
| Other | 1.1 (0.5 to 2.5) | 0.86 |
| Federal poverty threshold | ||
| 200% or above | 1 (Reference) | |
| Under 200% | 3.1 (1.9 to 5.1) | < 0.001 |
| Insurance status | ||
| Insured | 1 (Reference) | |
| Uninsured | 1.9 (1.0 to 3.4) | 0.04 |
| Marital status | ||
| Married | 1 (Reference) | |
| Single | 1.1 (0.7 to 1.8) | 0.65 |
| Educational attainment | ||
| Some college | 1 (Reference) | |
| No college | 2.3 (1.2 to 4.4) | 0.01 |
| Treated in emergency room | ||
| No | 1 (Reference) | |
| Yes | 1.1 (0.7 to 1.6) | 0.82 |
| Days of missed work | ||
| Less than 1 | 1 (Reference) | |
| 1 or more | 1.5 (0.8 to 3.1) | 0.23 |
| Unemployed | 2.2 (1.1 to 4.1) | 0.02 |
| Tobacco smoking status | ||
| Never | 1 (Reference) | |
| Current | 2.8 (1.6 to 5.1) | < 0.001 |
| Former | 1.1 (0.6 to 2.0) | 0.73 |
A raw score for food security ranging from 0 to 10 was determined based on the number of affirmative responses to the questions given by the USDA supplement. “Food security” was defined as having a raw score of 0 to 2, whereas “food insecurity,” the main outcome for this study, was defined as having a raw score of 3 to 10 in concordance with USDA protocol.
All racial and ethnic data were self-reported by survey respondents following the classification scheme used by the United States Census Bureau. USDA = United States Department of Agriculture.
Discussion
The present analysis determined that approximately one of five individuals reporting fractures experience food insecurity after injury. The factors associated with food insecurity in this population were age between 45 and 64 years, household income below twice the federal poverty limit, smoking tobacco, lower educational attainment, unemployment at the time of injury, Black race, and a lack of healthcare insurance. Considering recent USDA estimates that approximately 1 of 10 American households struggle with food insecurity [18, 39], the present findings raise concerns that patients who sustain fractures face an elevated risk. The expansion of existing social-determinant screening protocols to include food insecurity may help direct high-risk individuals toward resources in the state and local social service networks or governmental subsidy programs [38]. These may include, but are not limited to, community food pantries, charitable organizations such as Meals on Wheels America, or the Supplemental Nutritional Assistance Program [7, 34, 37].
Limitations
First, the information collected by the NHIS is self-reported and does not undergo additional validation with any third-party governmental or administrative datasets. Details about injuries are vulnerable to recall bias; however, the NHIS limits its scope to episodes during the past 3 months to mitigate this issue. Second, the NHIS does not collect data regarding injury classifications, fracture patterns, or inpatient versus outpatient clinical management. However, they do collect data regarding hospitalization and mechanisms of injury, which we used to provide a rudimentary classification in this study. Third, only 18% of patients were hospitalized, suggesting the current results may be skewed toward smaller, isolated injuries. This likely underestimated the prevalence of food insecurity among patients with severe injuries, high-energy mechanisms, and polytrauma. Fourth, although the USDA questionnaire used for this study has been widely validated, it is limited in scope and does not assess contextual factors such as proximity to grocery stores, access to transportation, clinical markers of malnutrition, or chronic disease progression [1, 17, 26]. Fifth, the retrospective, cross-sectional design of this study precludes an assessment of causal relationships or the direction of associations between demographic and socioeconomic variables. For instance, it is possible that many of the patients in the present analysis were experiencing food insecurity at baseline and were therefore socioeconomically predisposed to experiencing a fracture. Conversely, it is conceivable that the direct financial consequences of the injury and corresponding treatments predisposed these patients to difficulties affording nutritious foods. Considering nearly half of all survey respondents in the present analysis were unemployed immediately before their injury, these patients may not experience the same degree of indirect financial distress because of lost earning, which has been described [29].
Prevalence of Food Insecurity Among Individuals Reporting Having Experienced Fractures
Individuals reporting broken bones or fractures reported food insecurity more frequently than the overall population in the NHIS. Previous research has demonstrated approximately one in four patients undergoing orthopaedic trauma experience high levels of financial distress, while more than half of these patient are reported to deplete a large portion of personal savings in the postinjury period [5]. Several studies have identified associations between having food insecurity and poor health outcomes across a wide variety of clinical subgroups [3, 6, 18]. Many investigations have described a bidirectional relationship of food insecurity with worsening chronic conditions such as diabetes, hypertension, and depression, as well as healthcare expenditures [19, 24]. Proposed mechanisms have included declining health status leading to increased individual cost burden and economic constraints on food access, as well as declining food access leading to poor nutrition and worsening of existing medical comorbidities [18]. Although social determinants of health have been discussed in the context of surgery, only a few studies have directly analyzed the impact of food security status on postoperative outcomes or complications [40, 44]. For instance, one single-center retrospective analysis of 152 patients undergoing revascularization procedures for chronic limb-threatening ischemia found those residing in food deserts to have higher odds of 30-day readmission [45]. Considering the relatively high prevalence of food insecurity among patients reporting fractures, future prospective studies may be required to differentiate pre-existing from new-onset food insecurity and evaluate potential causal pathways between food insecurity and patient outcomes in the postinjury recovery period.
Factors Associated With Food Insecurity Among Individuals Reporting Fractures
We found that patients between 45 and 64 years old, those with an income below 200% of the federal poverty threshold, those who smoked tobacco at the time of the survey, and those without a college degree had a higher odds of experiencing food insecurity. Previous epidemiologic analyses of food insecurity have reported income, race, and level of education as primary risk factors, but the present study is unique in the finding of tobacco smoking as having an association [32, 39]. Prior research has shown that when faced with large, often unexpected expenses, Americans in the low-income bracket are forced to make challenging tradeoffs among competing budgetary priorities such as rent, utilities, and hospital bills [28, 41, 51]. One such study demonstrated the probability of food insecurity increased in direct response to increasing out-of-pocket medical expenditures [41]. Similarly, food insecurity in the setting of recent traumatic injury may signify major financial hardship and a decreased prioritization of routine health maintenance or primary care visits [4, 35, 42].
Conclusion
We found that approximately one of five patients reporting fractures experience food insecurity in the postinjury period. Furthermore, these patients were more likely to be middle-aged, low-income, less educated, smokers, Black Americans, and unemployed. This is important because among individuals recovering from fractures, food insecurity screening in addition to routine nutritional assessments may help to direct financially vulnerable patients toward available community resources. Such screening programs may improve adherence to nutritional recommendations in the trauma recovery period and improve the physiologic environment for adequate soft tissue and bone healing. Future research using injury registries, clinical nutritional data, and prospective study designs are needed to assess the relationship between food insecurity and long-term injury and treatment outcomes. Where possible, such studies should incorporate clinical nutritional information and include patients across a wide range of injury severity strata.
Footnotes
Each author certifies that there are no funding or commercial associations (consultancies, stock ownership, equity interest, patent/licensing arrangements, etc.) that might pose a conflict of interest in connection with the submitted article related to the author or any immediate family members.
All ICMJE Conflict of Interest Forms for authors and Clinical Orthopaedics and Related Research® editors and board members are on file with the publication and can be viewed on request.
Ethical approval was not sought as the study was deemed exempt from local institutional board review due to the use of public, deidentified data and absence of any protected health information.
This work was performed at Case Western Reserve University School of Medicine, Cleveland, OH, USA.
Contributor Information
Thomas B. Cwalina, Email: tbc21@case.edu.
Jenna E. Schmidt, Email: schmidtjenna16@gmail.com.
Victoria S. Wu, Email: vsw9@case.edu.
Taylor M. Yong, Email: taylormyong9@gmail.com.
Heather A. Vallier, Email: heathervallier@yahoo.com.
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