Association of Unmet Social Needs With Level of Capability in People With Persistent Knee Pain

Abstract

Background

Musculoskeletal providers are increasingly recognizing the importance of social factors and their association with health outcomes as they aim to develop more comprehensive models of care delivery. Such factors may account for some of the unexplained variation between pathophysiology and level of pain intensity and incapability experienced by people with common conditions, such as persistent nontraumatic knee pain secondary to osteoarthritis (OA). Although the association of one’s social position (for example, income, employment, or education) with levels of pain and capability are often assessed in OA research, the relationship between aspects of social context (or unmet social needs) and such symptomatic and functional outcomes in persistent knee pain are less clear.

Questions/purposes

(1) Are unmet social needs associated with the level of capability in patients experiencing persistently painful nontraumatic knee conditions, accounting for sociodemographic factors? (2) Do unmet health-related social needs correlate with self-reported quality of life?

Methods

We performed a prospective, cross-sectional study between January 2021 and August 2021 at a university academic medical center providing comprehensive care for patients with persistent lower extremity joint pain secondary to nontraumatic conditions such as age-related knee OA. A final 125 patients were included (mean age 62 ± 10 years, 65% [81 of 125] women, 47% [59 of 125] identifying as White race, 36% [45 of 125] as Hispanic or Latino, and 48% [60 of 125] with safety-net insurance or Medicaid). We measured patient-reported outcomes of knee capability (Knee injury and Osteoarthritis Outcome Score for Joint Replacement), quality of life (Patient-Reported Outcome Measure Information System [PROMIS] Global Physical Health and PROMIS Global Mental Health), and unmet social needs (Accountable Health Communities Health-Related Social Needs Survey, accounting for insufficiencies related to housing, food, transportation, utilities, and interpersonal violence), as well as demographic factors.

Results

After controlling for demographic factors such as insurance status, education attained, and household income, we found that reduced knee-specific capability was moderately associated with experiencing unmet social needs (including food insecurity, housing instability, transportation needs, utility needs, or interpersonal safety) (standardized beta regression coefficient [β] = -4.8 [95% confidence interval -7.9 to -1.7]; p = 0.002 and substantially associated with unemployment (β = -13 [95% CI -23 to -3.8]; p = 0.006); better knee-specific capability was substantially associated with having Medicare insurance (β = 12 [95% CI 0.78 to 23]; p = 0.04). After accounting for factors such as insurance status, education attained, and household income, we found that older age was associated with better general mental health (β = 0.20 [95% CI 0.0031 to 0.39]; p = 0.047) and with better physical health (β = 0.004 [95% CI 0.0001 to 0.008]; p = 0.04), but effect sizes were small to negligible, respectively.

Conclusion

There is an association of unmet social needs with level of capability and unemployment in patients with persistent nontraumatic knee pain. This finding signals a need for comprehensive care delivery for patients with persistent knee pain that screens for and responds to potentially modifiable social risk factors, including those based on one’s social circumstances and context, to achieve better outcomes.

Level of Evidence

Level II, prognostic study.

Introduction

There is growing evidence of an association of social factors with an individual’s physical and mental health outcomes and general quality of life [19, 20, 22]. Consequently, healthcare systems are increasingly recognizing the importance of broadening their approach to healthcare delivery by encompassing risks influenced by an individual’s social circumstances and thereby reorienting health and social services toward comprehensive care models that account for social health [4, 7, 8, 10, 19, 23, 24, 30, 33, 40].

This approach is particularly important in the management of common musculoskeletal conditions that are substantially associated with pain intensity, level of capability, and quality of life, such as persistent knee pain secondary to osteoarthritis (OA), where the variation in outcomes is incompletely explained by individual risk factors (for example, older age, being a woman, and BMI) and pathophysiology [18]. Social health can be grouped into social status (such as markers of education level, employment type, income and wealth, and home ownership) and social context (for example, aspects of built environments, including area deprivation, safety, healthy food choices, and transportation) [33].

Musculoskeletal research investigating health disparities and social determinants in patients with OA to date has mostly focused on aspects of social status—primarily education level, employment type, and income—and an association of these aspects with downstream clinical effects and responses to disease and interventions [3, 6, 26, 32-34, 36]. For instance, low levels of educational attainment and nonprofessional occupations have been shown to be associated with worse health outcomes in patients with OA after adjusting for sociodemographic risk factors [33]. Further, much of the work involving social health and OA predominantly involves people who are White, and rarely accounts for diverse, underserved communities that may be most vulnerable to social barriers [23, 24, 33].

Thus, we were interested in responding to the knowledge gap that exists about the association of social factors, especially one’s social context, with level of capability in a diverse population with persistent knee pain. The Centers for Medicare and Medicaid Services characterizes aspects of social context as “unmet social needs,” which are grouped into five core domains including interpersonal violence, food insecurity, utility needs, transportation needs, and housing instability that have been incorporated into a survey to facilitate analysis [11].

We aimed to assess the following questions using this instrument: (1) Are unmet social needs associated with the level of capability in patients experiencing persistently painful nontraumatic knee conditions, accounting for sociodemographic factors? (2) Do unmet health-related social needs correlate with self-reported quality of life? A better understanding of the association of unmet social needs with level of capability and quality of life may uncover opportunities for advancing risk assessment in specialty care, primary care, and community services and addressing modifiable social factors in the whole-person management of persistent knee pain.

Patients and Methods

Study Design and Setting

This prospective, cross-sectional study occurred at a tertiary-level lower extremity orthopaedic practice involving two orthopaedic surgeons (KMK and KJB) specializing in primary and revision hip and knee arthroplasty at a university academic medical center (The Musculoskeletal Institute, Lower Extremity Integrated Practice Unit, Dell Medical School, University of Texas at Austin, Austin, TX). The practice provides a comprehensive range of nonoperative strategies for patients with persistent lower extremity joint pain secondary to nontraumatic conditions such as age-related knee OA. Treatments are provided by a multidisciplinary team including associate providers, physical therapists, behavioral health–trained social workers, nutritionists, and financial advisors, alongside orthopaedic surgeons. Patients are referred to the clinic by a combination of primary care providers (50% to 60%), specialists (20% to 30%), and self-referral (20% to 30%) for persistent joint pain secondary to OA. The clinic also treats patients presenting with other causes of nontraumatic joint pain (for example, spontaneous osteonecrosis), painful total joint replacements, and lower extremity tumors, but these are less frequent.

Participants

Between January 2021 and August 2021, we treated 384 new patients for persistent knee pain. We included participants who were fluent in English or Spanish, aged 18 years or older, and treated with nonoperative or operative treatment strategies for knee pain secondary to nontraumatic conditions (primarily OA). We excluded those with painful total joint replacements or tumors, leaving 204 eligible patients from whom we aimed to obtain informed consent. Sixty-one percent (125 of 204) were included for analysis following the exclusion of 39% (79 of 204) because of incomplete datasets or patients who declined to participate. Those who declined to participate mainly stated that their decision was because of the survey burden or the sensitive and somewhat personal nature of social health questions. Patients enrolled in the study and those who declined to participate broadly represented the general patient population in this clinic. Further, the sociodemographic profile of the patients recruited for this study was similar to that of institutional data and our prior work.

Baseline Sociodemographic Data

The study population included patients with mean age of 62 ± 10 years; 65% (132 of 204) were female, 47% (96 of 204) self-selected as White, and 36% (73 of 204) self-selected as Hispanic or Latino ethnicity (Table 1). Participants were able to select race and ethnicity from the following options: White, African American/Black, Latino/Latina/Hispanic, Asian or Pacific Islander, or other, and were given the option to select multiple designations per the institutional protocol. Patients also completed a demographic survey capturing the highest level of education, employment status, annual income bracket, and type of health insurance. Notably, 48% (98 of 204) of patients had a medical access health coverage program, reserved for underserved, low-income populations in our region, or Medicare or Medicaid coverage.

Table 1.

Patient demographics (n = 125 patients)

Variable	Value
Age in years, mean ± SD	62 ± 10
Women, % (n)	65 (81)
Race or ethnicity, % (n)a
White	47 (59)
Hispanic or Latino	36 (45)
Other or declined	17 (21)
Education (n = 124), % (n)b
Elementary or middle school	15 (18)
High school graduate	21 (26)
Some college, no degree	21 (26)
College graduate	28 (35)
Graduate degree	15 (19)
Household income in USD (n = 122), % (n)c
< 15,000	39 (47)
> 15,000 AND < 50,000	(24 (29)
> 50,000 AND < 150,000	30 (30)
> 150,000	8 (10)
Employment, % (n)
Employed	31 (39)
Unemployed	22 (27)
Disabled or unable to work	18 (23)
Other (such as retiree or student)	29 (36)
Insurance type, % (n)
Other (for example, uninsured)	11 (14)
Medicare	17 (21)
Central Health Medical Access Program or Medicaidd	48 (60)
Private	24 (30)
Unmet needs, mean ± SDe	1 ± 1
KOOS JR, mean ± SD	45 ± 19
PROMIS Global-10 Physical t-score (n = 124), median (IQR)	37 (32 to 42)
PROMIS Global-10 Mental t-score (n = 124), mean ± SD	48 ± 10

^aPatients self-selected on the survey instrument for race or ethnicity from the following choices: White, African American/Black, Latino/Latina/Hispanic, Asian or Pacific Islander, or other, and were given the option to select multiple designations to best answer this demographic question.

^bPatients were given the option to leave this answer choice blank; one such patient did not provide an answer to this question.

^cThree patients chose not to disclose their household income.

^dCentral Health Medical Access Program refers to the health coverage program for Travis County, Texas, residents with low income.

^eThis parameter is the mean number of unmet needs that the patient population in this study had based on the survey instrument; that is, the mean number of unmet needs that this population had was one, with a standard deviation of one. KOOS JR = Knee injury and Osteoarthritis Outcome Score for Joint Replacement; IQR = interquartile range; PROMIS = Patient-Reported Outcome Measurement Information System.

Outcome Measures

We collected the following outcome measures: Knee injury and Osteoarthritis Outcome Score for Joint Replacement (KOOS JR) [34], which is a validated seven-item survey with questions related to stiffness, pain, and function [34]. Scores are converted to interval scores ranging from a minimum of zero (total knee incapability) to a maximum of 100 (full knee capability). We also collected the Patient-Reported Outcomes Measurement Information System Global-10 (PROMIS Global-10) [22], a validated 10-item survey with questions related to general health, social activity, physical activity, and emotional health [22]. The survey is scored and split into overall physical health (PROMIS Global-10 Physical Health subscore) and overall mental health (PROMIS Global-10 Mental Health subscore), using t-scores ranging between 16 and 68 and between 20 and 68, respectively. Higher subscores reflect greater (better) physical and mental health.

We also used the Accountable Health Communities Health-Related Social Needs Survey [14], a tool developed by a multistakeholder, technical expert panel for the Centers for Medicare and Medicaid Services Accountable Health Communities program. The survey includes 10 questions framed around the five core domains described in the Introduction section of this article [11, 14]. Each domain is considered separately, with certain items qualifying as positive screeners for the relevant health-related unmet social need. Total survey scores range from 0 to 5, representing the number of unmet social need domains with positive screens [11].

We offered patients with any unmet social needs paper-based resources in the English or Spanish language and referred them to our departmental behavioral health–trained social worker to provide further care. We also expedited social work referrals for any patients, screening for safety concerns or other issues that arose during recruitment and data acquisition, including symptoms of psychologic distress. All sociodemographic and outcomes data were recorded on an internet-based, Health Insurance Portability and Accountability Act–compliant survey administration research tool (REDCap).

Primary and Secondary Study Objectives

Our primary objective was to assess the association between unmet social needs (measured by the Accountable Health Communities Health-Related Social Needs Survey) and level of knee capability (measured by the KOOS JR) at baseline, accounting for sociodemographic factors in patients with persistent knee pain secondary to OA.

Our secondary objectives were to assess the association between unmet social needs and general physical health (PROMIS Global-10 Physical Health subscore) and general mental health (PROMIS Global-10 Mental Health subscore).

Ethical Approval

We obtained ethical review board approval for this study.

Statistical Analyses

An a priori sample size calculation determined 124 patients would provide 80% statistical power with alpha set at 0.05 for a multivariable linear regression with five predictors if one patient-specific factor accounted for at least 8.2% of variation in the model and if the complete model accounted for 25% of overall variability. We performed descriptive statistics to evaluate demographic data, mean KOOS JR, and mean PROMIS Global-10 Physical Health and Mental Health scores. Continuous variables are reported as means with standard deviations for parametric data and as median with interquartile range for nonparametric data, and discrete variables are reported as a percentage of the total. The distribution of the outcome measures was assessed using Shapiro-Wilk and heteroskedasticity tests to determine the appropriateness of the multivariable analysis method. Multivariable analyses were performed using multivariable linear regression models (KOOS JR, PROMIS Global-10 Mental Health) and negative binomial regression models (PROMIS Global-10 Physical Health) to assess for independent associations between explanatory variables and the relevant dependent variable, accounting for potential confounding variables. All p values below 0.05 were considered statistically significant.

Results

Factors Associated With the Level of Capability

After accounting for potential confounders such as insurance status, education attained, and household income, we found reduced knee-specific capability was moderately associated with experiencing unmet social needs such as food insecurity, housing instability, transportation needs, utility needs, or interpersonal safety social needs (standardized beta regression coefficient [β] = -4.8 [95% confidence interval -7.9 to -1.7]; p = 0.002) and reduced knee-specific capability was substantially associated with unemployment (β = -13 [95% CI -23 to -3.8]; p = 0.006). Better knee-specific capability was substantially associated with having Medicare insurance (β = 12 [95% CI 0.78 to 23]; p = 0.04) (Table 2).

Table 2.

Multivariable linear regression analysis of factors associated with the magnitude of knee capability (KOOS JR) and mental health (PROMIS Global-10 Mental Score), accounting for potentially confounding variables^a

	KOOS JR		PROMIS Mental
Variable	Regression coefficient (95% confidence interval)	p value	Regression coefficient (95% confidence interval)	p value
Gender
Women	Reference value		Reference value
Men	4.5 (-1.5 to 11)	0.14	0.82 (-2.8 to 4.5)	0.66
Race or ethnicity
White	Reference value		Reference value
Hispanic or Latino	-7.7 (-16 to 0.75)	0.07	4.5 (-0.54 to 9.6)	0.08
Other or declined	-5.4 (-14 to 3.1)	0.21	4.4 (-0.72 to 9.6)	0.09
Education
Elementary or middle school	Reference value		Reference value
High school graduate	-4.7 (-15 to 5.8)	0.38	-6.0 (-13 to 0.49)	0.07
Some college, no degree	-8.9 (-21 to 3.3)	0.15	-4.4 (-12 to 3.1)	0.25
College graduate	-4.2 (-16 to 7.2)	0.46	-3.4 (-10 to 3.7)	0.35
Graduate degree	-2.4 (-17 to 12)	0.74	-0.51 (-9.4 to 8.4)	0.91
Household income in USD
< 15,000	Reference value		Reference value
> 15,000 AND < 50,000	-1.2 (-9.0 to 6.6)	0.75	-1.9 (-6.6 to 2.8)	0.42
> 50,000 AND < 150,000	3.1 (-6.5 to 13)	0.52	3.0 (-2.8 to 8.7)	0.31
> 150,000	3.1 (-12 to 18)	0.68	2.5 (-6.7 to 11)	0.60
Employment
Employed	Reference value		Reference value
Unemployed	-13 (-23 to -3.8)	0.006	-4.7 (-10 to 0.92)	0.10
Disabled or unable to work	-6.0 (-15 to 3.5)	0.21	-3.2 (-8.8 to 2.5)	0.27
Other (such as retiree, student)	1.6 (-6.5 to 9.6)	0.70	-0.46 (-5.4 to 4.5)	0.90
Insurance
Other (such as uninsured)	Reference value		Reference value
Medicare	12 (0.78 to 23)	0.04	-0.83 (-7.6 to 5.9)	0.81
Central Health Medical Access Programb or Medicaid	2.9 (-6.7 to 12)	0.55	2.1 (-3.7 to 7.8)	0.48
Private	8.8 (-2.1 to 20)	0.11	2.6 (-4.1 to 9.3)	0.44
Age	0.20 (-0.12 to 0.52)	0.22	0.20 (0.0031 to 0.39)	0.047
Total unmet needs	-4.8 (-7.9 to -1.7)	0.002	-1.6 (-3.4 to 0.24)	0.09

^aThe adjusted r² for the model with KOOS JR is 0.39, which represents a proportion of the variance in the response variable that can be explained by the predictor variables in the model. This number represents that the predictor variables slightly to modestly explain the proportion of the variance in the KOOS JR. The adjusted r² for the model with PROMIS Global Health Mental is 0.20, which represents a proportion of the variance in the response variable that can be explained by the predictor variables in the model. This number represents that the predictor variables slightly to modestly explain the proportion of the variance in the PROMIS Global Health Mental.

^bCentral Health Medical Access Program refers to the health coverage program for Travis County, Texas, which is a safety-net insurance similar to Medicaid. KOOS JR = Knee injury and Osteoarthritis Outcome for Joint Replacement Score; PROMIS = Patient-Reported Outcome Measurement Information System.

Factors Associated With General Physical Health

After accounting for potential confounders such as insurance status, education attained, and household income, we found that the association between general physical health and older age was statistically significant with negligible correlation (β = 0.0041 [95% CI 0.00017 to 0.0081]; p = 0.04) (Table 3).

Table 3.

Negative binomial regression analysis of factors associated with general health (PROMIS Global-10 Physical Score), accounting for potential confounding variables

Variable	Regression coefficient (95% confidence interval)	p value
Race or ethnicity
White	Reference value
Hispanic or Latino	0.095 (-0.0064 to 0.20)	0.07
Other or declined	0.011 (-0.093 to 0.11)	0.84
Education
Elementary or middle school	Reference value
High school graduate	-0.059 (-0.19 to 0.075)	0.39
Some college, no degree	0.054 (-0.10 to 0.21)	0.48
College graduate	0.054 (-0.088 to 0.20)	0.46
Graduate degree	0.15 (-0.026 to 0.33)	0.09
Household income in USD
< 15,000	Reference value
15,000 AND < 50,000	-0.020 (-0.12 to 0.077)	0.69
> 50,000 AND < 150,000	0.10 (-0.011 to 0.22)	0.08
> 150,000	0.042 (-0.14 to 0.22)	0.64
Employment
Employed	Reference value
Unemployed	-0.049 (-0.16 to 0.066)	0.41
Disabled or unable to work	-0.037 (-0.15 to 0.079)	0.54
Other (such as retiree, student)	0.019 (-0.077 to 0.12)	0.69
Insurance
Other (for example, uninsured)	Reference value
Medicare	0.062 (-0.070 to 0.19)	0.36
Central Health Medical Access Program or Medicaida	0.014 (-0.10 to 0.13)	0.81
Private	0.087 (-0.044 to 0.22)	0.19
Age	0.0041 (0.00017 to 0.0081)	0.04
Total unmet needs	-0.020 (-0.058 to 0.018)	0.29

^aCentral Health Medical Access Program refers to the health coverage program for Travis County, Texas. PROMIS = Patient-Reported Outcome Measurement Information System.

Factors Associated With General Mental Health

Finally, after accounting for potential confounders, such as insurance status, education attained, and household income, we found that the association between general mental health and older age was statistically significant with minimal correlation (β = 0.20 [95% CI 0.0031 to 0.39]; p = 0.047) (Table 2).

Discussion

Social health has been conceptualized as a composite of an individual’s socioeconomic status (for example, markers of income, education, and employment) and aspects related to social circumstances and interactions with their environment and community (as categorized by five domains of unmet social needs in this study) [14, 33]. Although a few studies have shown an association between specific markers of social status and health outcomes in patients with persistent lower extremity joint pain [12, 31, 35], the interaction of an individual’s social context with level of capability and quality of life is less clear. An improved understanding of the association between broader, upstream, and social determinants of health outcomes may stimulate opportunities and approaches to better respond to social health concerns as potentially modifiable risk factors in patients with persistently painful nontraumatic musculoskeletal conditions.

Limitations

First, the generalizability of our findings could be questioned, given that our findings were generated in a practice delivering comprehensive multidisciplinary team-based care for patients with joint pain—a relatively uncommon model of musculoskeletal care in the United States. However, such settings also provide an ideal health services research setting for such work, given the opportunity to actively respond to potential social health concerns raised during recruitment, data collection, and initial care, using supportive services. Second, although our study was sufficiently powered to respond to the study objectives, the size of our cohort limits our ability to perform an additional interesting subgroup analysis, such as an examination of the relative association (and potentially the relative risk) between specific unmet needs and health outcomes. Third, our capture of self-selected race (physical and biological affiliation) and ethnicity (cultural affiliation) data was somewhat crude for a study evaluating unmet social needs and aiming to account for social health disparities across a community. Although our categorization of this important covariate aligns with institutional registration protocols and designations by United States Census and research organizations [2], a more detailed set of selections, particularly in the Latino/Latina/Hispanic category, could be more representative of the heterogeneity in our population, yielding additional insights. For instance, a Latino/Latina/Hispanic selection includes those identifying as Mexican American (most common in our population from Central Texas), as well as individuals from South or Central America or another Spanish-speaking culture or origin, regardless of race. Future studies may adopt a more comprehensive breakdown, such as that recommended by national research organizations in the United Kingdom, which also promote analytical frameworks for health equality that account for minority ethnic groups [38]. Finally, we did not account for interventions potentially initiated before study enrollment, such as use of food banks, food stamps, or community services for housing and transportation, which may have influenced responses to the unmet social needs survey.

Although the variation in sociodemographic characteristics, including insurance status (particularly patients with safety-net insurance) and racial and ethnic mix in this study, offers a diverse population for study, further larger-scale, multicenter population studies could overcome many of these limitations. Extended evaluation may enable more-granular segmentation of the population by geography, unmet social needs, race or ethnicity, and interventions, enhancing analysis and extending the scope of this work.

Discussion of Key Findings

This study demonstrated an association between lower levels of knee capability in patients with persistent knee pain and unmet social needs (food insecurity, housing instability, utility needs, transportation needs, and interpersonal violence) [17]. In 2019, approximately 68% of American adults experienced at least one of these unmet social needs in a representative sample of more than 1000 United States adults [29, 39]. However, wide variations remain in the assessment and management of aspects of an individual’s social construct in routine musculoskeletal practice [25]. One cross-sectional study of 2190 physician practices and 739 hospitals in the United States highlighted that only 24% of hospitals and 16% of physician practices consistently screened for food insecurity, housing instability, utility needs, transportation needs, and interpersonal violence [17].

We also observed an association between worse knee capability and unemployment. Unemployment, which leads to a loss of financial stability, resources, social connection, and purpose, may contribute to stress, distress, and unhealthy behaviors, thereby having a negative association with capability [15]. This self-perpetuating cycle of unemployment and disability, although affecting other health conditions, has been associated with clinically meaningful levels of worse outcomes for musculoskeletal conditions such as leg pain and back pain after surgery. Although education level and income were not selected in the regression analysis in this study, these markers of socioeconomic status, along with employment, may be associated with an individual’s health outcomes as proxies of their problem-solving abilities and knowledge attainment, their social networks and standing, and translation of wealth and assets to accessing higher-quality health-promoting resources (such as better nutrition and housing) [13, 21]. Studies have shown there is an association between educational attainment and OA outcomes [16, 21, 28, 39].

The association between greater knee capability and Medicare insurance may also reflect increased access to care conferred to eligible beneficiaries in this program. For instance, Medicare beneficiaries have access to preventive health screens and a broad range of other outpatient preventive therapies. Further work is required to understand the association between musculoskeletal health outcomes and the range of beneficiary types in this program.

Finally, we found that better general physical and mental health was associated with older age; however. both these findings had low effect sizes. Interestingly, we did not find a statistically significant association of general physical health or general mental health with experiencing unmet social needs. The KOOS JR, a condition-specific score, may have more effectively quantified the level of capability and physical limitations in this study than a general measure of physical health. Prior work has demonstrated the association of unmet social needs, such as greater food insecurity, with a higher incidence of poor mental health including symptoms of depression and anxiety [1, 5, 9, 20, 37]. Given that social health and mental health are intrinsically linked, a negative association with one’s social status (for example, because of unemployment) or social constructs and circumstances (such as housing instability) may contribute to symptoms of psychologic distress and unhealthy behaviors. This has been shown to have a dominant association with decreased level of capability [41].

Our findings signal some important considerations for responding to unmet social needs in patients with persistent knee pain, starting with screening of potentially modifiable risk factors to trigger appropriate interventions and relationship-building opportunities between patients and care teams. The use of simple screening tools for baseline assessment before clinic consultations, while respecting sensitivities and stigmas about self-reporting such concerns, may provide rich insights without disrupting clinical workflow and efficiency. Specialist nurses, care navigators, and particularly social workers, especially those trained in behavioral health, may be valuable assets to integrate social support plans in comprehensive musculoskeletal treatment strategies. Such personnel can facilitate engagement with local health authorities, recuperative community care programs, and shelters for those facing housing instability and homelessness. Community resources and local alliances could also be engaged to respond to interpersonal and domestic violence to develop risk assessment and safety plans alongside access to more affordable energy programs, wireless connectivity, and partnerships with public and private transportations for low-income and underserved populations. Further, food insecurity might be addressed by helping patients access food banks and apply for public health benefits including supplemental nutritional assistance. Providers focused on addressing unmet social needs may also benefit from the development of practical communication channels that allow them to respond to unmet social needs in real time, alongside broader networks with public health practitioners that may widen the net to regional and state-wide community resources.

Future population-level studies might expand on our findings and build on comprehensive frameworks such as that developed by Luong et al. [33] that conceptualize the relationship between social position, social context, and OA health outcomes. Such work should identify the potential personal factors and psychosocial influences (including instrumental and emotional social support and coping strategies) that mediate or moderate the pathophysiologic processes and individual health outcomes of those with OA.

Conclusion

The association between worse knee-specific capability and unmet social needs such as food insecurity, housing instability, transportation difficulties, utility needs, and interpersonal safety concerns signals a call to action for musculoskeletal care teams to anticipate potential social health priorities among people seeking care for persistent knee pain. Based on our findings, we think it is important to understand how unmet social needs contribute to musculoskeletal conditions such as chronic knee pain. The importance of screening and providing support for unmet social needs in clinical practice is well recognized by multiple stakeholders, including patients [27]. Regardless of practice setting, screening tools are a gateway to better assessment, detection, and action regarding unmet social needs. This is an active area in clinical care and could inform interventions that provide whole-person, patient-centered care. Similar to physical health factors (for example, smoking status or BMI) or mental health factors (such as depression or anxiety), social factors provide greater context for understanding our patients and their musculoskeletal health outcomes. Thus, further research should seek to understand not only these associations, but also the interplay between individual-level unmet needs and clinical practice, community interventions, and implemented health policy.