Slipped capital femoral epiphysis (SCFE) is one of the common hip pathologies in adolescents and can result in persistent femoral deformity and osteoarthritis in early adulthood.1,2 Urgent surgical intervention is required to avoid serious complications including osteonecrosis of the femoral head, chondrolysis, slip progression and subsequent deformity, femoroacetabular impingement, and early onset osteoarthritis.3,4 In addition to surgery, patients with SCFE often require physical therapy and ongoing monitoring to prevent additional complications, imposing a notable burden on patients and healthcare systems. Accordingly, the direct and indirect costs associated with treating SCFE can be high, which can affect the quality of life for patients and their families; however, the exact costs still are not clear.5

Although the etiology of SCFE is multifactorial, influenced by biomechanical and biochemical factors, obesity is strongly associated with increased risk,6 and importantly, the incidence of pediatric obesity has been increasing in the United States over the past several decades.7–9 Thus, close attention to the potentially changing epidemiological landscape of SCFE is also warranted. Other proposed risk factors include male sex, race and ethnicity, and some geographic associations.1,10 The goal of this study was to evaluate the epidemiology of SCFE in the United States, specifically evaluating its incidence over the past decade and demographic risk factors for SCFE development. The results of this study can potentially inform about clinical practice and public health policy, aid in early detection and treatment of SCFE, and potentially reduce the burden of this condition on patients and healthcare systems.

Methods Overview and Data Source

After IRB approval, a retrospective cohort study was conducted using the Healthcare Cost and Utilization Project National Inpatient Sample (NIS), drawing data from years 2011 to 2020. The NIS database provides a representative sample, comprising approximately 20% of all inpatient visits in the United States. For this study, the 33 million inpatient visits recorded over a decade represent this 20% sample, which, when extrapolated, corresponds to approximately 165 million inpatient visits nationally during the same period.

Patients aged younger than 18 years with a primary diagnosis of SCFE were identified through International Classification of Diseases (ICD) 9 or 10 codes. Importantly, NIS switched from ICD-9 to ICD-10 coding halfway through the study period. To ensure suitability of our data from incidence and trend analysis, a test of continuity was done, and no stepwise function was detected.

For all patients, we collected a number of variables. Demographic variables recorded included age, race and ethnicity, sex, household income level, geographic region (West, Midwest, South, and Northeast), and insurance status. To bolster our analysis, we also drew data from Centers for Disease Control (CDC) to compare trends in SCFE diagnoses with childhood obesity rates during the study period.11 The medical definition of childhood obesity considered was a body mass index (BMI) at or above the 95th percentile on the CDC-specific growth charts.

Statistical Analysis

The incidence of SCFE per 10,000 children was calculated for each year over the study period. Multivariate regression was done to assess the association between various demographic factors and the incidence of SCFE. Regression models controlled for the aforementioned demographic variables, where appropriate, and underwent testing to ensure all assumptions were met. Confidence intervals were set at 95%, and P-value of 0.05 was considered statistically significant. Continuous variables were reported as means with standard deviations. All categorical variables given as counts and percentages. Categorical variables were tested with Chi Square (Kendall Tau C), while continuous variables were assessed with analysis of variance. All analysis was done with the R Foundation for Statistical Computing software version 4.20 with the Python package.

Results Demographics and Incidence of SCFE

A total of 33,180,028 patients, all aged younger than 18 years, were identified for inclusion in our analysis. Of these, 11,738 (0.04%) had a diagnosis of SCFE. The mean age of these patients was 11.94 years (±3.5) at the time of diagnosis. Full demographics are summarized in Table 1.

Table 1 - Patient Demographics and Hospital Variables Factor Total No SCFE SCFE P Total number, N (%). 33,180,028 33,168,290 (99.96) 11,738 (0.04) Age, mean (SD) 2.2 (±4.8) 2.2 (±4.8) 11.93 (±3.5) <0.001 Demographics, N (%)  Sex   Female 16,203,668 (48.88) 16,199,332 (48.88) 4,336 (37.11) <0.001   Male 16,946,480 (51.12) 16,939,133 (51.12) 7,347 (62.89)  Race   Asian or Pacific Islander 1,386,797 (4.18) 1,386,526 (4.18) 271 (2.30) <0.001   Black 4,712,258 (14.20) 4,709,108 (14.20) 3,150 (26.83)   Hispanic 6,110,769 (18.42) 6,108,759 (18.42) 2,010 (17.12)   Other 5,517,887 (16.63) 5,515,773 (16.63) 2,113 (18.00)   White 15,452,318 (46.57) 15,448,123 (46.57) 4,194 (35.73)  Household income by zip code   0-25th percentile 9,595,366 (29.36) 9,591,422 (29.36) 3,943 (34.36) <0.001   26th to 50th percentile 8,188,119 (25.05) 8,185,065 (25.05) 3,054 (26.62)   51st to 75th percentile 7,969,924 (24.39) 7,967,436 (24.39) 2,488 (21.68)   76th to 100th percentile 6,928,182 (21.20) 6,926,192 (21.20) 1,990 (17.34)  Hospital region   Midwest 6,684,060 (22.03) 6,681,799 (22.03) 2,261 (22.38) 0.007   Northeast 5,254,276 (17.32) 5,252,564 (17.32) 1,712 (16.94)   South 11,779,420 (38.82) 11,775,813 (38.82) 3,607 (35.70)   West 6,623,752 (21.83) 6,621,229 (21.83) 2,524 (24.98)  Rural/urban   Rural 1,926,334 (5.84) 1,925,439 (5.84) 895 (7.68) <0.001   Urban 31,044,656 (94.16) 31,033,896 (94.16) 10,761 (92.32)  Payer   Medicaid 15,924,063 (48.08) 15,918,522 (48.08) 5,541 (47.40) <0.001   Medicare 94,813 (0.29) 94,763 (0.29) 50 (0.43)   No charge 31,762 (0.10) 31,740 (0.10) 22 (0.18)   Other 1,051,495 (3.17) 1,050,897 (3.17) 598 (5.12)   Private insurance 14,764,069 (44.57) 14,758,892 (44.57) 5,177 (44.29)   Self-pay 1,256,499 (3.79) 1,256,196 (3.79) 302 (2.59)

SCFE = slipped capital femoral epiphysis

The annual incidence rate of SCFE increased by 142.28%, from 2.46 per 10,000 children in 2011 to 5.96 per 10,000 in 2020. A steady increase in incidence over the past decade was noted. Incidence by year is summarized in Table 2. Although the study did not test for causality, the incidence of SCFE seems to mirror the increase in obesity prevalence. These findings are shown in Figure 1.

Table 2 - Incidence of SCFE and Pediatric Obesity by Year Year SCFE per 10,000, N (SE) Pediatric Obesity, N (SE) 2011 2.46 (0.10) 13 (0.21) 2012 2.99 (0.10) 2013 2.70 (0.10) 13.7 (0.09) 2014 2.49 (0.10) 2015 3.21 (0.10) 13.9 (0.12) 2016 5.09 (0.10) 2017 5.52 (0.10) 14.8 (0.11) 2018 5.03 (0.10) 2019 5.61 (0.10) 15.5 (0.21) 2020 5.96 (0.10)

SCFE = slipped capital femoral epiphysis, SE = standard error

Figure 1:

Graph showing the rate of pediatric obesity and SCFE per 10,000 over the study period. SCFE = slipped capital femoral epiphysis.

Of those with SCFE, 7347 (62.89%) were male. Regarding race and ethnicity, 271 (2.30%) were Asian or Pacific Islander, 3,150 (26.83%) were Black, 2,010 (17.12%) were Hispanic, 4,194 (35.73%) were White, and the remaining 2,113 (18%) were classified as Other races.

Regarding household income level, patients in the lowest income quartile were overrepresented. In total, 3,943 (34.36%) lived in households in the lowest income quartiles, 3,054 (26.62%) in the third quartile, 2,488 (21.68%) in the second quartile, and 1,990 (17.34%) in the highest income quartile. The lowest income quartile had the most disproportionate representation, with children in this income quartile comprising 29.36% of the total population, but 34.36% of the SCFE population (P < 0.001). In the geographic region of the admitting hospital, 3,607 (35.70%) were in the South, 2,524 (24.98%) were in the West, 2,261 (22.38%) were in the Midwest, and 1,712 (16.94%) were in the Northeast. These demographics are summarized in Table 1.

Risk Factors for SCFE

The effect size of demographic variables assessed through a multivariate regression test is shown in Figure 2. For the combined patient cohort, female sex reduced the risk of SCFE (odds ratio [OR], 0.462; P < 0.001). Relative to White patients, Black (OR, 2.426; P < 0.001) and Hispanic (OR, 1.156; P = 0.033) populations had an increased risk of SCFE. Regarding the geographic region, patients in the West had increased odds of SCFE (OR, 1.513; P < 0.001).

Figure 2:

Graph showing the effect size of risk factors for SCFE. SCFE = slipped capital femoral epiphysis.

Discussion

The study provides an update on SCFE epidemiology. We found a notable increase in the incidence of SCFE over the past decade and identified male sex, Black and Hispanic ethnicity, and residency in the geographic West as groups at risk. Importantly, we found that patients of lower socioeconomic status (SES), as measured through household income level quartile, were overrepresented in the SCFE cohort.

The relationship between lower SES and SCFE has previously been reported in the literature. Perry et al12 found a greater incidence of SCFE in areas with higher socioeconomic deprivation. Notably, they also found strong associations between SCFE and obesity. Indeed, these two metrics—SES and obesity—are intertwined, and the association between lower SES and SCFE may be mediated by increased risk and prevalence of obesity in lower income communities. Findings by Luster et al13 suggest that the association between SCFE and SES may be due to food deserts, accounting for higher rates of obesity secondary to low quality foods. Limited access to nutritious food, among other associated factors, may contribute to increased obesity in children of lower SES, ultimately predisposing them to SCFE. Furthermore, patients of lower SES may fare worse, with reports of early loss to follow-up, delayed diagnosis, and greater slip severity in this demographic.14,15

Aside from this association, the increasing incidence of SCFE is cause for concern independently. SCFE is a frequently missed diagnosis, due to its various presentations and similarity to more common and relatively benign conditions leading to delays in treatment.16–18 These delays allow for additional slip progression and can predispose patients to worse outcomes.19 Indeed, Kocher et al20 found that the median delay in diagnosis of SCFE was 8 weeks and that greater delays were associated with greater slip severity. Greater slip severity also increases the risk of serious complications and sequelae, including osteonecrosis of the femoral head, chondrolysis, and hip impingement.21 Furthermore, patients with more severe slips have worse hip function in long-term follow-up, as measured by multiple functional scores and patient-reported outcomes measures, and are at greater risk for arthritis.22–24

Unfortunately, many children suffer sequelae of the condition, and with rising rates, SCFE threatens to become a larger public health issue. Aside from the substantial burden, SCFE hospitalization places on the healthcare system in cost and length of stay, an estimated 45% of patients diagnosed with SCFE require total hip arthroplasty before age 50.25 This can be due to osteonecrosis or chondrolysis, but more commonly is due to progressive labrum and cartilage damage, typically from residual deformity. There is also some evidence that these patients may be at increased risk of requiring revision arthroplasty, although this may be secondary to the younger age at the time of primary arthroplasty, and the literature regarding this population is scarce.26

The study shows a positive association between SCFE incidence and obesity rates. Although the exact mechanisms through which obesity predisposes adolescents to the disease are not yet fully understood, there are various theories regarding the mechanism underlying this relationship. Mechanical theories focus on the increased biomechanical stress exerted on the proximal femoral physis by excess of body weight, which may compromise the structural integrity of the epiphyseal plate.1,27,28 Metabolic theories, on the other hand, propose that the hormonal changes associated with obesity, such as earlier onset of puberty and associated delays in epiphyseal plate closure, contribute to SCFE. In addition, obesity-related alterations in in the epiphyseal plate morphology, including changes in the shape, size, and alignment of physeal chondrocytes, have been implicated.29–32 Our analysis, using CDC data, shows a strikingly similar trend in childhood obesity and SCFE incidence over the study period; however, this observation is descriptive and intended to highlight concurrent trends without implying causality. Manoff et al33 found obesity is highly correlated with SCFE, finding that almost twice as many patients with SCFE had a BMI above the 95% percentile relative to those without SCFE, regardless of patient age and sex. Murry and Wilson also concluded similarly, attributing many of their findings to obesity, after detecting a strong correlation between rising rates of both SCFE and obesity.1 Benson et al,34 assessing the incidence of SCFE in New Mexico (a state with markedly lower reported rates of SCFE) longitudinally, found that rates had risen from 2.13 in the 1960s to 5.99 per 100,000 in their study period of 1995 to 2006. Similarly, they concluded that rising obesity rates, which had tripled in their state over a similar period, likely contributed to the marked increase in SCFE. Although the study does show a strong correlation between increased SCFE incidence and the prevalence of obesity—a known risk factor, the nature of this correlation is not assumed to be causative. The notable increase in SCFE incidence is likely multifactorial, including but not limited to, advancements in diagnostic techniques and changes in population demographics at risk.35

Although this study reports valuable data on the incidence, economic and healthcare systems burden, and risk factors for SCFE, it is not without limitations. Importantly, the NIS is a sample of discharges after inpatient visits. Although we are able to extrapolate our sample to represent the entire inpatient population, it may not be perfectly representative of the general population. Instead, our incidence report is more directly representative of SCFE in the inpatient population.

Second, as the NIS reports discharge records, not individual patient records, it is possible that individuals may be counted multiple times from multiple hospitalizations. To mitigate this, we ensured that SCFE was the primary diagnosis or procedure for that particular visit. Despite its imperfections, the NIS, due to its exceptional sample size and robust sampling methods, remains a powerful and commonly used tool to assess nationwide incidence. Furthermore, the primary message of this study, that the incidence of SCFE is rising, remains true, regardless of our ability to extrapolate from the inpatient to the general population.

Third, the NIS does not provide weight or BMI. Instead, we overlaid CDC data on childhood obesity over the study period with our incidence data. Still, even with our limited information on the matter, our analysis suggests an association between rising rates of childhood obesity and SCFE, consistent with the literature. Finally, we did not assess patients for endocrine conditions, which are known to be associated with SCFE. Although our primary goal focused on analyzing the incidence trends of SCFE, the omission of these variables does not detract from our findings regarding incidence rates. However, future research should aim to investigate the role of endocrine pathology and related conditions in predisposing children to SCFE, more thoroughly, thereby addressing critical gaps in the current literature. In addition, we recognized that a transition from reporting practices from ICD-9 to ICD-10 coding in 2015 paired with growing clinical awareness of the condition and enhanced detection practices may contribute to the observed increase in SCFE incidence. Although these factors likely influenced the reported rates, our analysis indicates that the trend is not solely attributable to changes in coding practices, suggesting a genuine change in incidence rates during this period.

Conclusions

The incidence of SCFE is rising in the United States, standing at 5.96 per 10,000 children in 2020. Black and Hispanic race, male patients, and residents of the geographic West in the United States seem to be at increased risk of SCFE. Furthermore, children of lower SES were also overrepresented in the SCFE cohort. As SCFE necessitates urgent intervention to avoid the worst complications, healthcare providers need to be cognizant of this condition, its increasing incidence, and groups at risk, to facilitate a timely diagnosis.

Acknowledgments

All coauthors listed met criteria for authorship. Listed below are the respective contributions: Mr. Singh: Substantial contributions to the conception and interpretation of data for the work; drafting the work and revising for important intellectual content; final approval of the version to be published; and agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Mr. Kotzur: Acquisition, analysis, and interpretation of data for the work; revising for important intellectual content; final approval of the version to be published; and agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Mr. Momtaz: Substantial contributions to the conception or design of the work; revising for important intellectual content; final approval of the version to be published; agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Mr. Gonuguntla: Interpretation of data for the work; revising for important intellectual content; final approval of the version to be published; and agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Dr. Hoveidaei: Revising for important intellectual content; final approval of the version to be published; and agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Dr. Seifi: Acquisition, analysis, and interpretation of data for the work; revising the work for important intellectual content; final approval of the version to be published; and agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Dr. Galán-Olleros: Drafting the work and revising for important intellectual content; final approval of the version to be published; and agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Dr. Torres-Izquierdo: Drafting the work and revising for important intellectual content; final approval of the version to be published; and agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Dr. Hosseinzadeh: Substantial contributions to the conception or design of the work; drafting the work and revising for important intellectual content; final approval of the version to be published; and agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

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