Abstract
Purpose
Patient-reported outcome measures (PROMs) are widely used in hand surgery to assess symptom severity prior to surgical intervention; however, little is known about how food insecurity, an important social determinant of health, influences these scores. We aimed to measure the correlation between county-level food insecurity and baseline PROMs in a cohort of patients undergoing carpal tunnel release (CTR) for idiopathic carpal tunnel syndrome (CTS).
Methods
Baseline PROMs were prospectively collected in 114 patients with electrodiagnostic study, ultrasound, or CTS-6 confirmed CTS treated with CTR at a single tertiary referral center. Feeding America’s Map the Meal Gap Dataset was used to identify county-level food-insecurity rate, average meal cost, and percent eligible for Supplemental Nutritional Assistance Program. Correlations between food-insecurity parameters and PROMs were assessed using correlation coefficients; bivariate analyses of continuous explanatory variables were performed using linear regression.
Results
Mean age was 61.6 ± 12.7 years. A total of 57.9% were women, and 93.9% were White. In total, 14.9% and 19.3% of our cohort reside in Massachusetts counties falling within the upper quartile and upper half of food-insecurity rates, respectively. No significant correlations were found between food-insecurity variables and Patient-Reported Outcomes Measurement Information System (PROMIS) scores. Younger age was associated with worse Boston Carpal Tunnel Questionnaire–Symptom Severity Scale scores and PROMIS Pain Interference scores.
Conclusions
We found no evidence that patients with food insecurity present with greater symptom severity at time of CTR.
Type of study/level of evidence
Prognostic IIb.
Key words: Carpal tunnel release, Carpal tunnel syndrome, Food insecurity, Health disparity, Patient-reported outcome measure, Socioeconomic
Patient-reported outcome measures (PROMs) are valuable tools in hand surgery, offering clinicians and researchers meaningful insight into patients’ symptom severity and functional impairment, both before and after surgical intervention. Instruments such the Patient-Reported Outcomes Measurement Information System (PROMIS) and the Quick Disabilities of the Arm, Shoulder, and Hand (QuickDASH) provide broad assessments of upper-extremity function.1,2 Additionally, the Boston Carpal Tunnel Questionnaire (BCTQ) offers a specific evaluation of symptoms and functional limitations in patients with carpal tunnel syndrome (CTS), an upper-extremity compressive neuropathy that affects 3% to 5% of the general population.3, 4, 5
Prior studies have identified associations between socioeconomic factors and PROMs across numerous orthopedic conditions, including CTS.6, 7, 8 Although income, education, and employment have been explored in their association with PROMs, the role of food insecurity—a strong marker of social instability—has not been well-studied in the context of outcomes for hand surgery. Food insecurity, defined as the limited or uncertain availability of nutritionally adequate and safe food, is a growing public health concern in the United States. Broadly, various social determinants of health have been shown to be associated with decreased access to care in patients with CTS, with recent research suggesting utility in screening for social determinants of health in patients undergoing CTS.9,10 However, a recent systematic review examining health disparities in hand surgery identified no studies specifically evaluating food insecurity, underscoring the need to better understand how food insecurity may influence outcomes following CTS.11 The impact of food insecurity on chronic disease outcomes, surgical recovery, and health care engagement has become increasingly evident; however, its impact on musculoskeletal outcomes, particularly in patients undergoing surgery for CTS, remains largely unexamined.12,13
Thus, we performed a single-institution prospective study on patients residing in Massachusetts (MA) undergoing isolated, unilateral CTR for idiopathic CTS. Baseline pain and dysfunction was assessed through questionnaires, which included PROMIS [Pain Interference (PI), Upper Extremity (UE), and Physical Function (PF)], QuickDASH, and BCTQ. Feeding America’s 2023 Map the Meal Gap Dataset was used to identify parameters indicative of county-level food insecurity.14 The objective of this study was to measure the correlation between MA county-level food insecurity and baseline PROMs in the CTR patient population. Based on prior literature, we hypothesized that patients experiencing food insecurity were more likely to face barriers to timely care, leading to greater symptom severity at time of presentation for elective surgery.
Materials and Methods
Cohort identification
This study was performed with institutional review board approval. Patients who underwent CTR for idiopathic CTS from January 1, 2023, to May 5, 2025, were eligible for inclusion. Inclusion criteria were adult patients with idiopathic CTS confirmed by electrodiagnostic testing, ultrasound, or the CTS-6 clinical diagnostic tool, who underwent isolated primary CTR during the study period by one of three fellowship-trained hand surgeons at a single tertiary referral institution (D.Z., B.E.E., P.B.). Exclusion criteria included those undergoing revision carpal tunnel surgery, a concomitant procedure at the time of CTR, or acute CTS secondary to trauma or infection. Patients with incomplete study questionnaires or residing outside of MA were also excluded from the study.
Of the 132 patients screened, 114 were included in our final study cohort. Of these, 10 reside outside of MA, 4 patients underwent a separate concomitant procedure at the time of CTR, 2 lacked an electrodiagnostic study report, and 2 completed preoperative questionnaires but did not proceed with surgery.
Patient-reported outcome measures
Three types of PROMs were collected from all patients before surgery prior to CTR surgery. The PROMs included the BCTQ, which is subdivided into the Symptom Severity Scale (SSS) and Functional Status Scale (FSS), QuickDASH, and PROMIS. The PROMIS instruments were Computer Adaptive Tests versions of the PROMIS Bank v1.1 PI, the PROMIS Bank v2.0–UE, and the PROMIS Bank v2.0–PF.
Explanatory variables
Feeding America’s 2023 Map the Meal Gap Dataset was used to identify the MA county-level food-insecurity rate, percent of food-insecure individuals eligible for Supplemental Nutritional Assistance Program (SNAP), and average meal cost.14 County-level food-insecurity rates were used to identify patients residing in the upper quartile and upper half of MA county-level food insecurity.
Additionally, the following demographic and clinical variables were collected from the electronic medical record: age, sex, race, dominant hand surgery, symptom duration, comorbid diabetes mellitus, current smoking status, English as primary language, and electrodiagnostic disease severity (mild, moderate, or severe) by the Werner and Andary criteria.15 Employment status and insurance coverage were not abstracted because, in our predominately older, White cohort, the vast majority of patients were insured and employed or retired, yielding insufficient heterogeneity for analysis of these variables.
Statistical analysis
Descriptive statistics were calculated. Complete data sets were used for analysis, and missing data are given in the footnote of Table 1. The parametricity of continuous variables was tested, and all except the percent of food-insecure individuals eligible for SNAP were found to be normal (|skewness| < 0.5). The Spearman correlation coefficient was used to assess for correlations between PROMs and the percent of food-insecure individuals eligible for SNAP, and the Pearson correlation coefficient was used for all other comparisons. Bivariate analyses of continuous explanatory variables were performed using linear regression. Bivariate analyses of categorical explanatory variables were performed using the Student t test or Mann-Whitney U test. An a priori power calculation indicated that a sample size of n = 194 yields 80% power to detect a weak correlation (ρ = 0.20) and a sample size of n = 47 yields 80% power to detect a moderate correlation (ρ = 0.40), assuming the standard significance criterion (α = 0.05).
Table 1.
Baseline Patient Characteristics (n = 114)∗
| Variable | Mean (SD) |
|---|---|
| Age (y) | 61.6 (12.7) |
| SNAP eligible (%) | 52.9 (5.9) |
| Average meal cost ($) | 4.23 (0.2) |
| Median (IQR) | |
| Food-insecurity rate (%) | 9.0 (9.0–9.5) |
| n (%) | |
| Sex | |
| Male | 48 (42.1%) |
| Female | 66 (57.9%) |
| Race | |
| White | 107 (97.3%) |
| Black | 3 (2.7%) |
| English language speaker | |
| Yes | 113 (99.1%) |
| No | 1 (0.9%) |
| Diabetes mellitus | |
| Yes | 17 (14.9%) |
| No | 97 (85.1%) |
| Smoking status | |
| Yes | 5 (4.4%) |
| No | 109 (95.6%) |
| Dominant hand involvement | |
| Yes | 64 (56.1%) |
| No | 50 (43.9%) |
| Electrodiagnostic severity | |
| Mild | 23 (20.9%) |
| Moderate | 65 (59.1%) |
| Severe | 22 (20.0%) |
Race was unknown for 4 of 114 patients. Another 4 of 114 had a confirmatory test other than electrodiagnostic study.
Results
Cohort characteristics
Our cohort comprised 114 patients who underwent primary, isolated CTR for idiopathic CTS, confirmed by EMG, ultrasound, or CTS-6. The mean age was 61.6 ± 12.7 years. In total, 57.9% were women, and 97.3% were White. Overall, 14.9% had diabetes mellitus, and 4.4% were active smokers. Of the 96.5% of patients with preoperative electrodiagnostic studies, 20.9% had mild CTS, 59.1% had moderate CTS, and 20.0% severe CTS (Table 1).
In MA, the mean food-insecurity rate across all counties is 11.0% ± 2.1%; counties with the most food insecurity (upper quartile) include Hampden, Suffolk, and Bristol. Expanding to the upper half of food-insecurity rates, additional counties include Franklin, Berkshire, Worcester, and Essex (Table 2). Among the 114 patients, the majority (50.9%) resided in Plymouth County, followed by 23.7% in Norfolk County and 13.2% in Bristol County. Thus, only 14.9% and 19.3% of our cohort reside in counties falling within the upper quartile and upper half of food-insecurity rates, respectively (Fig.). The median food-insecurity rate among counties in our cohort was 9.0% (interquartile range [IQR]: 9.0%–9.5%). The mean percentage of food-insecure individuals at or below the SNAP threshold was 52.9% ± 5.9%. The average cost per meal in these counties was $4.23 ± $0.21 (Table 1).
Table 2.
Distribution of Study Cohort and County-Level Food Insecurity Metrics in Massachusetts Based on the 2023 Feeding America’s Map the Meal Gap Dataset
| County in MA | % of Study Cohort | Overall Food-Insecurity Rate | % FI ≤ SNAP Threshold | Cost Per Meal |
|---|---|---|---|---|
| Nantucket | - | 8.0% | 56% | $5.16 |
| Norfolk | 23.68% | 8.8% | 45% | $4.46 |
| Plymouth | 50.88% | 9.0% | 53% | $4.21 |
| Dukes | - | 9.4% | 53% | $5.16 |
| Middlesex | 2.63% | 9.5% | 48% | $4.38 |
| Barnstable | 3.51% | 10.2% | 52% | $4.63 |
| Hampshire | - | 10.5% | 59% | $4.48 |
| Essex | 1.75% | 11.1% | 60% | $4.10 |
| Worcester | 2.63% | 11.4% | 60% | $4.01 |
| Berkshire | - | 12.3% | 64% | $4.24 |
| Franklin | - | 12.7% | 70% | $4.12 |
| Bristol | 13.16% | 12.8% | 64% | $3.82 |
| Suffolk | 1.75% | 14.2% | 68% | $4.40 |
| Hampden | - | 14.6% | 72% | $3.90 |
| MA average | 11.0% | 58.7% | $4.36 |
FI, food insecurity.
Figure.
Bar graph demonstrating the percentage of the study cohort in each of the four quartiles of Massachusetts county food insecurity. Percentages in parentheses indicate the food-insecurity rate of that county. No individuals in the study were from Nantucket, Dukes, Hampshire, Franklin, or Hampden counties.
Patient-reported outcome measures
Baseline pain was assessed using the BCTQ–SSS (mean: 3.0 ± 0.7) and PROMIS–PI (mean: 57.4 ± 7.6).
Baseline function was assessed using the BCTQ–FSS (mean: 2.3 ± 0.9), QuickDASH (mean: 38.6 ± 20.2), PROMIS–UE (mean: 36.9 ± 8.8), and PROMIS–PF (mean: 45.5 ± 8.5).
Relationship between PROMIS and food insecurity
We found no correlations between county-level food-insecurity rate and BCTQ–SSS (ρ = 0.01, P = .94), BCTQ–FSS (ρ = 0.05, P = .58), QuickDASH (ρ = 0.06, P = .51), PROMIS–PI (ρ = 0.07, P = .49), PROMIS–UE (ρ = 0.00, P = .98), and PROMIS–PF (ρ = –0.01, P = .94). Similarly, we found no correlation between percent of food-insecure individuals eligible for SNAP and BCTQ–SSS (ρ = 0.04, P = .70), BCTQ–FSS (ρ = 0.06, P = .50), PROMIS–PI (ρ = 0.10, P = .30), PROMIS–UE (ρ = –0.06, P = .52), PROMIS–PF (ρ = –0.02, P = .80), or QuickDASH (ρ = 0.08, P = .40). Finally, we found no correlation between average meal cost and BCTQ–SSS (ρ = –0.13, P = .16), BCTQ–FSS (ρ = –0.18, P = .06), QuickDASH (ρ = –0.16, P = .09), PROMIS–PI (ρ = –0.18, P = .06), PROMIS–UE (ρ = 0.11, P = 0.25), or PROMIS–PF (ρ = –0.05, P = .61).
Bivariate analyses revealed no significant associations between food-insecurity variables and BCTQ–SSS, BCTQ–FSS, QuickDASH, PROMIS–UE, PROMIS–PF, and PROMIS–PI (P > .05) (Tables S1–S6, available online on the Journal’s website at https://www.jhsgo.org). Younger age was significantly associated with worse BCTQ–SSS scores (P < .05) and PROMIS–PI scores (P < .05).
Discussion
Carpal tunnel release is a safe and effective treatment option for CTS; however, access to elective procedures may be affected by broader socioeconomic factors.16, 17, 18, 19, 20 Food insecurity is an understudied socioeconomic metric, particularly in chronic conditions where the treatment is elective. If patients feel the economic burden of uncertainty access to adequate or safe food, it is possible that they delay discretionary care until symptoms are more severe. With this rationale, we sought to investigate the relationship between baseline PROMs and food insecurity in patients presenting for CTR for idiopathic CTS. In our study, we found no significant associations between county-level food-insecurity rates and baseline PROMs. Despite the initial hypothesis that higher food insecurity might be associated with greater symptom burden in patients with CTS because of delayed care or lack of access to resources, our results suggests that food insecurity at the county level in our study population did not meaningfully influence symptom severity at the time that patients elect surgical treatment.
Our findings that younger age is associated with worse baseline BCTQ–SSS and PROMIS–PI scores perhaps suggest that younger patients may experience or report greater symptoms of painful paresthesias at presentation, which may be because of greater occupational demands or differences in pain perception. These findings are in contrast to previous research, which have suggested an increase in PI scores with older age.21 Nonetheless, we recognize that the effect sizes for our study were small, and the clinical significance of these associations remain uncertain.
Additionally, the limitations for this study should be noted. First, individual-level food-insecurity data were not collected in our study; we used county-level food insecurity estimates as a proxy for patient risk. We acknowledge that this may not reflect the socioeconomic status at the household, individual, or at-risk group (eg, elderly) level and limits the granularity of our analysis. Future studies may benefit from the use of validated food-insecurity questionnaires such as the Hunger Vital Sign tool or the six-item United States Department of Agriculture Household Food Security Module to more accurately capture the relationship between food insecurity and severity of symptoms at time of presentation for elective hand surgery.13,22,23 Second, our cohort was treated at an urban tertiary care center in a single state in the United States, which limits the generalizability of a study on access to care. More specifically, most participants in this cohort reside in MA, which is one of the least food-insecure states, ranking fourth lowest in food insecurity nationwide.14 Additionally, the study population largely came from counties with the least amount of food insecurity (lower quartile). Given these limitations, future studies in more diverse geographic regions are needed to better clarify the role of food insecurity in access and time to elective hand surgery. Third, preoperative PROMs were collected for this study and do not capture longitudinal assessment of symptom progression or recovery. Lastly, although we were sufficiently powered to detect moderate correlations between county-level food insecurity and PROMs with a study cohort size of 114 patients, our study was underpowered to detect weak correlations.
Our results contribute to the growing body of literature examining the role of social determinants of health in elective surgical procedures. Although food insecurity has been associated with poor outcomes in the acute settings, its role in elective hand surgery conditions may be more nuanced than how it is currently understood.7,8 We found no evidence that county-level food insecurity contributes to greater symptom severity at time of presentation for CTR in our study population.
Conflicts of Interest
No benefits in any form have been received or will be received related directly to this article.
Supplementary Data
References
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