Association Between Government Health Insurance Status and Physical Activity in American Youth

A Scoping Review to Identify Community- and Societal-Level Strategies Evaluated from 2013 to 2023 for Their Potential Impact on Child Well-Being in the United States

There is increased recognition for solutions that address the social determinants of health (SDOHs)-the context in which families are raising children. Unfortunately, implementing solutions that address inequities in the SDOHs has proven to be difficult. Many child and family serving systems and communities do not know where to start or do not have the capacity to identify and implement upstream SDOH strategies. As such, we conducted a scoping review to assess the status of evidence connecting strategies that address the SDOHs and child well-being. A total of 29,079 records were identified using natural language processing with 341 records meeting inclusion criteria (e.g., outcomes focused on child well-being, interventions happening at a population level, and evaluations of prevention strategies in the United States). Records were coded, and the findings are presented by the SDOH domain, such as strategies that addressed economic stability (n = 94), education access and quality (n = 17), food security (n = 106), healthcare access and quality (n = 96), neighborhood and built environment (n = 7), and social and community context (n = 12). This review provides an overview of the associations between population-level SDOH strategies and the impact-good and bad-on child well-being and may be a useful resource for communities and practitioners when considering equitable solutions that promote thriving childhoods.

How Should We Measure Social Deprivation in Orthopaedic Patients?

BACKGROUND

Social deprivation negatively affects a myriad of physical and behavioral health outcomes. Several measures of social deprivation exist, but it is unclear which measure is best suited to describe patients with orthopaedic conditions.

QUESTIONS/PURPOSES

(1) Which measure of social deprivation, defined as "limited access to society's resources due to poverty, discrimination, or other disadvantage," is most strongly and consistently correlated with patient-reported physical and behavioral health in patients with orthopaedic conditions? (2) Compared with the use of a single measure alone, how much more variability in patient-reported health does the simultaneous use of multiple social deprivation measures capture?

METHODS

Between 2015 and 2017, a total of 79,818 new patient evaluations occurred within the orthopaedic department of a single, large, urban, tertiary-care academic center. Over that period, standardized collection of patient-reported health measures (as described by the Patient-reported Outcomes Measurement Information System [PROMIS]) was implemented in a staged fashion throughout the department. We excluded the 25% (19,926) of patient encounters that did not have associated PROMIS measures reported, which left 75% (59,892) of patient encounters available for analysis in this cross-sectional study of existing medical records. Five markers of social deprivation were collected for each patient: national and state Area Deprivation Index, Medically Underserved Area Status, Rural-Urban Commuting Area code, and insurance classification (private, Medicare, Medicaid, or other). Patient-reported physical and behavioral health was measured via PROMIS computer adaptive test domains, which patients completed as part of standard care before being evaluated by a provider. Adults completed the PROMIS Physical Function version 1.2 or version 2.0, Pain Interference version 1.1, Anxiety version 1.0, and Depression version 1.0. Children ages 5 to 17 years completed the PROMIS Pediatric Mobility version 1.0 or version 2.0, Pain Interference version 1.0 or version 2.0, Upper Extremity version 1.0, and Peer Relationships version 1.0. Age-adjusted partial Pearson correlation coefficients were determined for each social deprivation measure and PROMIS domain. Coefficients of at least 0.1 were considered clinically meaningful for this purpose. Additionally, to determine the percentage of PROMIS score variability that could be attributed to each social deprivation measure, an age-adjusted hierarchical regression analysis was performed for each PROMIS domain, in which social deprivation measures were sequentially added as independent variables. The model coefficients of determination (r2) were compared as social deprivation measures were incrementally added. Improvement of the r2 by at least 10% was considered clinically meaningful.

RESULTS

Insurance classification was the social deprivation measure with the largest (absolute value) age-adjusted correlation coefficient for all adult and pediatric PROMIS physical and behavioral health domains (adults: correlation coefficient 0.40 to 0.43 [95% CI 0.39 to 0.44]; pediatrics: correlation coefficient 0.10 to 0.19 [95% CI 0.08 to 0.21]), followed by national Area Deprivation Index (adults: correlation coefficient 0.18 to 0.22 [95% CI 0.17 to 0.23]; pediatrics: correlation coefficient 0.08 to 0.15 [95% CI 0.06 to 0.17]), followed closely by state Area Deprivation Index. The Medically Underserved Area Status and Rural-Urban Commuting Area code each had correlation coefficients of 0.1 or larger for some PROMIS domains but neither had consistently stronger correlation coefficients than the other. Except for the PROMIS Pediatric Upper Extremity domain, consideration of insurance classification and the national Area Deprivation Index together explained more of the variation in age-adjusted PROMIS scores than the use of insurance classification alone (adults: r2 improvement 32% to 189% [95% CI 0.02 to 0.04]; pediatrics: r2 improvement 56% to 110% [95% CI 0.01 to 0.02]). The addition of the Medically Underserved Area Status, Rural-Urban Commuting Area code, and/or state Area Deprivation Index did not further improve the r2 for any of the PROMIS domains.

CONCLUSION

To capture the most variability due to social deprivation in orthopaedic patients' self-reported physical and behavioral health, insurance classification (categorized as private, Medicare, Medicaid, or other) and national Area Deprivation Index should be included in statistical analyses. If only one measure of social deprivation is preferred, insurance classification or national Area Deprivation Index are reasonable options. Insurance classification may be more readily available, but the national Area Deprivation Index stratifies patients across a wider distribution of values. When conducting clinical outcomes research with social deprivation as a relevant covariate, we encourage researchers to consider accounting for insurance classification and/or national Area Deprivation Index, both of which are freely available and can be obtained from data that are typically collected during routine clinical care.

LEVEL OF EVIDENCE

Level III, therapeutic study.

Disparities in Youth Sports and Barriers to Participation

Purpose of Review

Youth sports participation has shifted from a school-based, seasonal activity to club-based, year-round activity over the past 10–15 years. Single sport specialization has become increasingly common with a concurrent increase in injury and burnout. Paralleling trends seen in other aspects of health care, disparities in regard to participation in youth sports, and subsequent injury treatment exist as well. Recognition of these disparities amongst coaches, parents, and athletes involved in youth sports are essential to promote the short- and long-term health of pediatric and adolescent athletes.

Recent Findings

Multiple barriers exist for youth in regard to sports participation. Youth who come from families without extensive financial means are increasingly finding it difficult to play organized sports, with this trend holding when broken down by insurance status (public versus private). This problem is further exacerbated by the lack of community-based programming in locations where organized (albeit expensive) options do not exist. The lack of athletic trainers increases the divide, as well as the care that injured athletes receive (particularly in public schools within communities of color) is not equivalent to schools with extensive financial resources. Thus, ability to quickly return to play after injury and/or access the health care system is limited. This is further exemplified by inferior outcomes in regard to care for anterior cruciate ligament, meniscus, shoulder instability, and concussions in this population.

Summary

Youth sports participation is laden with multiple disparities. This is unfortunately reflective of historical barriers to opportunities/advancements in multiple other areas of society. These disparities place certain groups of children at an uphill battle not only for participation when healthy, but also returning to participation when injured. Larger structural changes in youth sports are necessary to promote life-long, healthy physical activities for individuals most at risk.

Social Determinants of Health: Considerations for Athletic Health Care

Health disparities are prevalent issues in the United States and a frequent topic of conversation in the public health realm. Causes of health disparities include social inequities and social determinants of health. Although social determinants of health have been suggested to contribute more to individual and population health than the health care provided, this concept in athletic health care has received little attention. Therefore, the purpose of this article is to describe social determinants of health, present examples of social determinants, and discuss awareness of actionable steps for the athletic training profession to be more culturally proficient. By increasing awareness of and acknowledging social determinants of health, athletic trainers will be positioned to improve patient outcomes more readily and contribute to ongoing conversations at the policy level of health care.

Influence of insurance type on rate and type of initial concussion-related medical visits among youth

Background

A growing number of studies report increased concussion-related health care utilization in recent years, but factors impacting care-seeking behaviors among youth following a concussion are not well described. This study aimed to evaluate the influence of insurance type on the rate and type of initial concussion visits and the time from injury to the initial visit in youth.

Methods

We extracted and analyzed initial concussion-related medical visits for youth ages 10 to 17 from electronic health records. Patients must have visited Nationwide Children’s Hospital’s (NCH) concussion clinic at least once between 7/1/2012 and 12/31/2017. We evaluated the trends and patterns of initial concussion visits across the study period using regression analyses.

Results

Of 4955 unique concussion visits included, 60.1% were males, 80.5% were white, and 69.5% were paid by private insurance. Patients’ average age was 13.9 years (SD = 3.7). The rate of the initial concussion visits per 10,000 NCH visits was consistently higher in privately insured than publicly insured youth throughout the study period (P < .0001). Privately insured youth had greater odds of initial concussion visits to sports medicine clinics (AOR = 1.45, 95% CI = 1.20, 1.76) but lower odds of initial concussion visits to the ED/urgent care (AOR = 0.74, 95% CI = 0.60, 0.90) than publicly insured youth. Days from injury to initial concussion visit significantly decreased among both insurance types throughout the study (P < .0001), with a greater decrease observed in publicly insured than privately insured youth (P = .011).

Conclusions

Results on the differences in the rate, type, and time of initial concussion-related visits may help inform more efficient care of concussion among youth with different types of insurance.

Income-based inequalities in self-reported moderate-to-vigorous physical activity among adolescents in England and the USA: a cross-sectional study

OBJECTIVE

Quantify income-based inequalities in self-reported moderate-to-vigorous physical activity (MVPA) in England and the USA by sex.

DESIGN

Population-based cross-sectional study.

PARTICIPANTS

4019 adolescents aged 11-15 years in England (Health Survey for England 2008, 2012, 2015) and 4312 aged 12-17 years in the US (National Health and Nutrition Examination Survey 2007-2016).

MAIN OUTCOME MEASURES

Three aspects of MVPA: (1) doing any, (2) average min/day (MVPA: including those who did none) and (3) average min/day conditional on participation (MVPA active). Using hurdle models, inequalities were quantified using the absolute difference in marginal means (average marginal effects).

RESULTS

In England, adolescents in high-income households were more likely than those in low-income households to have done any formal sports/exercise in the last 7 days (boys: 11%; 95% CI 4% to 17%; girls: 13%; 95% CI 6% to 20%); girls in high-income households did more than their low-income counterparts (MVPA: 6 min/day, 95% CI 2 to 9). Girls in low-income households spent more time in informal activities than girls in high-income households (MVPA: 21 min/day; 95% CI 10 to 33), while boys in low-income versus high-income households spent longer in active travel (MVPA: 21 min/week; 95% CI 8 to 34). In the USA, in a typical week, recreational activity was greater among high-income versus low-income households (boys: 15 min/day; 95% CI 6 to 24; girls: 19 min/day; 95% CI 12 to 27). In contrast, adolescents in low-income versus high-income households were more likely to travel actively (boys: 11%; 95% CI 3% to 19%; girls: 10%; 95% CI 3% to 17%) and do more.

CONCLUSIONS

Policy actions and interventions are required to increase MVPA across all income groups in England and the USA. Differences in formal sports/exercise (England) and recreational (USA) activities suggest that additional efforts are required to reduce inequalities.

The Italian cross-cultural adaptations of the paediatric International Knee Documentation Committee Score and the Hospital for Special Surgery Paediatric Functional Activity Brief Scale are reliable instruments in paediatric population

PURPOSE

The aim of the present study was to translate, cross-culturally adapt, and assess the psychometric properties of the Pedi-IKDC and Pedi-FABS scores in the Italian paediatric population with various knee pathologies.

METHODS

In accordance with the Paediatric Anterior Cruciate Ligament Monitoring Initiative (PAMI) research protocol, the original English versions of the questionnaires were translated into Italian. All patients aged 8-16 and scheduled for knee surgery were considered eligible in the study. An open-source platform was implemented to collect responses to the surveys which included general patient information, the questionnaires Pedi-IKDC, and Pedi-FABS. Two surveys were sent under stable clinical conditions before surgery (Q₁ and Q₂); a third survey was sent 3-4 months after surgery (Q₃). The following properties were calculated: reliability, internal consistency, criterion validity, responsiveness, and floor/ceiling effects.

RESULTS

Eighty-nine patients completed Q₁, 81 patients completed Q₂, and 49 patients completed Q₃. Both questionnaires demonstrated acceptable properties. Pedi-IKDC: standard error of measurement (SEM) = 4.4, smallest detectable change (SDC) = 12.3, interclass correlation coefficient (ICC) = 0.96, Cronbach alpha (α) = 0.92, moderate-to-low correlation to Pedi-FABS, effect size (ES) = 0.79, standardized response mean (SRM) = 0.86, floor = 0%, ceiling = 22%. Pedi-FABS: SEM = 2.1, SDC = 5.8, ICC = 0.94, Cronback alpha (α) = 0.93, moderate-to-low correlation to Pedi-IKDK, ES = 0.60, SRM = 0.51, floor = 19%, ceiling = 0%.

CONCLUSIONS

The Italian version of Pedi-IKDC and Pedi-FABS is valuable tools for patient assessment, by demonstrating good psychometric properties. In clinical setting, these questionnaires can be used to properly evaluate outcomes in Italian pediatric patients with knee pathologies.

LEVEL OF EVIDENCE

II.

Time interval affects physical activity scores: a comparison of the Marx Activity Rating Scale and the Hospital for Special Surgery Pediatric Functional Activity Brief Scale

PURPOSE

The Marx Activity Rating Scale (Marx Scale) is a commonly used activity-related patient-reported outcome which evaluates the highest activity level within the last year, whereas the Hospital for Special Surgery Pediatric Functional Activity Brief Scale (HSS Pedi-FABS) assesses highest activity level within the last month. This study aims to determine whether the different timeframes used for the common items of Marx Scale and HSS Pedi-FABS affect scores, and if so, to determine whether age or injury status affect this difference.

METHODS

The Marx Scale and four analogous items on the HSS Pedi-FABS were administered in random order to patients being evaluated for knee injuries and in addition to healthy controls to enroll an uninjured comparison group. Responses to each question were scored from 0 to 4 for a maximum overall score of 16. Paired and independent-sample t tests were used to determine mean differences between groups.

RESULTS

The final cohort included 88 participants of which 47% were children (ages 10-17) and 51% had a knee injury. All participants except for healthy adults scored significantly lower on the HSS Pedi-FABS than the Marx Scale (p < 0.05). On the HSS Pedi-FABS activity scale, healthy participants scored significantly higher than injured participants (p < 0.01), but there were no significant differences based on age. Conversely, on the Marx Scale, children scored higher than adults (p ≤ 0.001), but there were no significant differences based on injury.

CONCLUSION

Physical activity level differs when evaluated with the Marx Scale or the analogue part of HSS Pedi-FABS with timeframe being the only difference between the two. The lower scores on the HSS Pedi-FABS are likely due to seasonal changes in activity which do not affect the Marx Scale. HSS Pedi-FABS analyzes a shorter window and it is more likely to capture changes in physical activity due to a recent injury than the Marx Scale which is better suited for assessing general physical activity level unaffected by seasonality or recent injury. Understating the differences between these physical activity scales can better guide clinicians when using them and interpreting scores.

LEVEL OF EVIDENCE

II.