Characterizing dementia among patients with spina bifida (SB)

Introduction

Dementia, the leading cause of death and disability globally, is a decline in cognition that significantly alters independent, daily functioning. Dementia can occur due to multiple causes and has a significant societal cost that is upward of $1.3 trillion globally (1). Therefore, understanding population-level details among people living with dementia are important for identifying risk and protective factors and addressing health disparities at a system-level.

SB (SB), a complex, congenital neural tube defect, leads to sensory and motor deficits at the level of the defect, often resulting in varying degrees of physical and cognitive challenges (2). As we improve survival outcomes for patients with SB, the risk for neurodegenerative conditions remains high as patients often have hydrocephalus, cerebrovascular changes, and aging-related neurodegeneration. Individuals born with SB routinely navigate significant early neurodevelopmental and neurosurgical complications, including Chiari malformations, hydrocephalus requiring shunt placements or revisions, and executive dysfunction. In addition, medications such as anticholinergics have been a mainstay for these patients for decades, and emerging evidence points to a correlation between anticholinergic use and early-onset dementia, making dementia potentially even more prevalent in this already high-risk group (3,4).

As advancements in multidisciplinary care have drastically improved survival, allowing a large cohort of these patients to reach older adulthood, it remains fundamentally unknown how these cumulative early neurological insults interface with aging-related neurodegeneration. This study focuses on comparing dementia in patients with SB compared to the general population and understanding its impact on healthcare utilization. In addition, we elucidate the factors associated with dementia among patients with SB. This paper aims to contribute to the development of targeted interventions and support strategies, enhancing the quality of life for individuals affected by SB and dementia, and improving healthcare management. We present this article in accordance with the STROBE reporting checklist (available at https://tau.amegroups.com/article/view/10.21037/tau-2026-0205/rc).

Methods

Data source

The Department of Health Care Access and Information (HCAI) database, which captures all inpatient encounters at California-licensed hospitals from 2005 to 2017, was utilized. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Committee for Protection of Human Subjects, which serves as a California Health and Human Services Agency institutional review board and reviews all research conducted on human subjects. The data obtained were de-identified; therefore, informed consent was not necessary.

Study population

The study population was limited to patients over age 50 at the time of their health care encounters.

Relevant primary and non-primary diagnoses listed in their electronic medical record using International Classification of Diseases (ICD)-9 and -10 coding systems and Current Procedural Terminology (CPT) codes were used to identify patients with SB. ICD-9 codes from January 2005 through September 2015 and the ICD-10 codes from October 2015 to December 2017 were used to identify specific diagnoses. A list of ICD and CPT codes used are shown in Table S1. Cohort composition and creation scheme are shown in Figure 1.

Figure 1 Analytic cohort creation and composition. CPT, Current Procedural Terminology; ICD, International Classification of Diseases; SB, spina bifida.

Patients with dementia were defined as those having at least one diagnosis for any dementia including all-cause dementia, Alzheimer’s disease, vascular dementia, frontotemporal dementia, Parkinson’s, childhood brain degeneration, Lewy Body dementia, alcoholic brain degeneration, other cerebral degeneration, or cerebral degeneration-unspecified at any health care encounter. To ensure diagnostic specificity and avoid overestimation, mild cognitive impairment (MCI) was strictly excluded from the dementia definition.

SB patients were randomly frequency matched to non-SB patients 1:5 by birthyear, subsequently patients age <50 years were excluded. The first analysis was among patients with dementia, comparing those with SB (n=528) to those without SB (n=1,451). The study population was restricted to patients aged 50 years or older at the time of their encounter. This age threshold was chosen to focus explicitly on late-adulthood healthcare utilization and age-related cognitive decline, while minimizing confounding effects from early developmental or congenital cognitive impairments seen in younger cohorts.

The second analysis was limited to only SB patients. The SB patients with dementia (n=528) were randomly frequency matched to SB patients without dementia by birthyear (n=929).

Record linkage numbers (RLNs) were used to follow all the patients longitudinally. Patients lacking RLN, date of birth or California addresses were excluded from this study.

Outcomes of interest

The primary outcome was inpatient healthcare utilization as measured by number of hospital encounters and total cost of encounters.

Demographic variables

The demographic variables evaluated in this study comprised of age of the patient at the time of their encounter (years), biological sex (male, female, unknown), race [White/Caucasian, Black/African American, Asian/Pacific Islander (API), Native American/other, multiracial (non-matching race reported on separate encounters)], and ethnicity [Hispanic, non-Hispanic, mixed (Hispanic and non-Hispanic reported on separate encounters)].

Socioeconomic variables

Zip code tabulation area (ZCTA) of residence based on US census data was used to create neighborhood scores derived from the Diez-Roux method to assess socioeconomic status (SES). ZCTAs transforms ZIP Code data into polygonal boundaries based on Census tabulation blocks, which allows for spatial analysis, mapping, and tabulation of census statistics. Diez-roux method uses 6 domains to create a composite score, with higher scores corresponding to higher-SES neighborhoods.

Healthcare-related variables

Healthcare access was based on insurance status, classified as private, non-private (i.e., Medicare, Medicaid, workers’ compensation, government agencies), self-pay, mixed (private and non-private reported on separate encounters), and unknown (not specified). Health professional shortage areas (HPSA), which are defined as areas that have a shortage of medical providers, was also incorporated into our analysis of healthcare access.

Hospital length of stay and charge were followed for all patient’s in-hospital health encounters. Disposition was reported for each encounter and after-care was categorized into home, home health service, skilled nursing or intermediate care, death, left against medical advice, prison/jail, other, and unknown.

Patient health related variables

The Charlson comorbidity index (CCI), which has been previously described, was utilized to assess risk of mortality in relation to comorbid conditions [10].

Statistical analysis

Given the large sample size, P<0.01 was considered statistically significant. Descriptive analyses comparing characteristics between SB patients and controls utilized the Pearson’s Chi-squared test for comparing percentages and the 2-tailed independent groups Student’s t-test for comparing means. Continuous variables were reported as means and standard deviations whereas categorical variables were reported as frequencies and percentages.

Multivariable logistic regression models were constructed to evaluate independent predictors of high healthcare utilization. High utilization was defined as experiencing a total number of health encounters at or above the median value of the respective comparison group (≥10 encounters for the all-dementia cohort; ≥9 encounters for the SB cohort). Models were adjusted for patient type, sex, race, ethnicity, insurance provider type, neighborhood SES, primary care shortage area index, treatment county residency, and CCI. The all-dementia model also adjusted for individual dementia phenotypes. All analyses were performed with SAS, version 9.4.

Results

We identified 528 patients with SB and dementia (SB+D+) who were matched to 1,451 individuals with dementia (SB−D+, control) (Table 1). There were proportionately more patients who were female, multiracial, mixed ethnicity, with mixed insurance, who sought care in their county of residence in the SB+D+ cohort compared to the SB−D+ cohort. All-cause (80% vs. 85%; P=0.01), Alzheimer’s disease (23% vs. 34%; P<0.001), and Lewy Body dementia (3% vs. 6%; P=0.02) were less likely cerebral degeneration (7% vs. 4%; P=0.003) were more likely in the SB+D+ group compared to the control group. The mean CCI was significantly higher in the SB+D+ group (P<0.001).

There were 14,381 and 21,829 total health encounters for the SB+D+ and SB−D+ groups, respectively. There were significantly fewer total dementia-related encounters (13% vs. 22%; P<0.001) in the SB+D+ group compared to the SB−D+ group despite the mean for all encounters, inpatient encounters, and erectile dysfunction (ED) encounters being higher among the SB+D+ group. The mean cumulative cost for all in-hospital encounters was $677,000 for SB+D+ compared to the $387,000 for SB−D+ group (P<0.001).

To evaluate the independent factors associated with a high volume of healthcare utilization among individuals living with dementia, a multivariable logistic regression model was constructed with an outcome threshold defined as 10 or more healthcare encounters (representing the median value of encounters within the non-SB with dementia group). After adjusting for clinical and demographic characteristics, a pre-existing diagnosis of SB was found to be a strong, independent predictor of high utilization. Patients with both SB and dementia had more than double the odds of experiencing 10 or more healthcare encounters compared to the non-SB dementia cohort [adjusted odds ratio (aOR) =2.37, 95% confidence interval (CI): 1.86–3.03, P<0.001] (Table 2). Higher odds of experiencing 10 or more encounters were observed among Black patients (aOR =1.71, 95% CI: 1.06–2.76, P=0.02) and multi-racial patients (aOR =1.58, 95% CI: 1.20–2.08, P=0.001) relative to White patients, whereas API patients demonstrated lower odds (aOR =0.61, 95% CI: 0.38–0.97, P=0.03). Individuals characterized by a mixed ethnicity profile similarly showed higher odds of high utilization compared to Hispanic individuals (aOR =2.28, 95% CI: 1.47–3.52, P<0.001). Systemic medical complexity was directly associated with utilization; each one-unit increase in the CCI corresponded to a 26% increase in the odds of high healthcare encounters (aOR =1.26, 95% CI: 1.22–1.31, P<0.001). Furthermore, specific underlying dementia phenotypes significantly increased utilization odds compared to those with no documented dementia subtype, including frontotemporal dementia (aOR =1.90, 95% CI: 1.27–2.83, P=0.002), other cerebral degeneration (aOR =1.96, 95% CI: 1.10–3.46, P=0.02), unspecified cerebral degeneration (aOR =2.84, 95% CI: 1.57–5.14, P<0.001), and alcoholic brain degeneration (aOR =2.32, 95% CI: 1.15–4.68, P=0.01).

We then evaluated the characteristics among SB patients with (SB+D+) and without dementia (SB+D−) (Table 3). There were significantly more patients who were male, living in primary care shortage area, and in lower socio-economic quartile in SB+D+ group compared to the SB+D−. Patients in the SB+D+ group were significantly more likely to be discharged to a skilled nursing or intermediate care facility compared to the SB+D− group. The mean CCI was significantly higher in the SB+D+ group (P<0.001).

There were 14,381 and 12,035 total health encounters for SB+D+ and SB+D− groups, respectively. The mean number of encounters, inpatient and ED encounters were significantly higher in the SB+D+ group. The mean charge per in-hospital encounter was $68K for SB+D+ compared to $75K for SB+D− group (P=0.02), but the mean cumulative charge among all in-hospital encounters was significantly higher among SB+D+ patients compared to SB+D− ($677K vs. $374K, P<0.001).

A separate multivariable logistic regression model was restricted specifically to the SB population to assess independent predictors of having 9 or more healthcare encounters (the median encounter value among the SB without dementia cohort) (Table 4). Notably, when adjusting for overall comorbidity burdens, demographic characteristics, and healthcare access indices, the addition of a co-occurring dementia diagnosis among patients with SB was not associated with a statistically significant independent increase in high healthcare encounters (aOR =1.94, 95% CI: 0.83–4.51, P=0.12). High healthcare utilization within the SB cohort was primarily driven by biological sex, racial background, insurance status, overall comorbidity burden, and specific secondary neurological diagnoses. Male patients with SB had significantly lower odds of high healthcare utilization compared to female patients (aOR =0.71, 95% CI: 0.55–0.92, P=0.01).

Regarding racial subgroups, multi-racial individuals experienced elevated odds of utilization compared to White individuals (aOR =1.61, 95% CI: 1.18–2.18, P=0.002), while API individuals experienced significantly lower odds (aOR =0.46, 95% CI: 0.23–0.94, P=0.03). Insurance status remained an important factor; compared to privately insured individuals, those utilizing non-private coverage (aOR =1.81, 95% CI: 1.10–2.98, P=0.01) or possessing mixed insurance profiles (aOR =2.37, 95% CI: 1.44–3.91, P=0.001) had significantly higher odds of reaching 9 or more encounters. Each incremental point on the CCI increasing the odds of high utilization by 31% (aOR =1.31, 95% CI: 1.25–1.37, P<0.001). When analyzing individual dementia subtypes within this SB population, a concurrent diagnosis of vascular dementia was uniquely associated with significantly lower odds of frequent healthcare encounters (aOR =0.28, 95% CI: 0.13–0.59, P=0.001).

Discussion

Our data further strengthens the concept that dementia is not a monolithic disease entity and impacts different patient populations in unique ways (1). The impact of dementia on healthcare utilization among patients with SB is significantly higher compared to the general population and SB patients without dementia. There are significant sociodemographic and clinical differences among these cohorts of patients.

Our study highlights significant disparities in healthcare utilization and outcomes among individuals with SB and dementia (SB+D+). One of the most striking findings is the difference in disposition after hospital encounters, with SB+D+ patients being significantly more likely to be discharged to skilled nursing facilities (SNFs) rather than home. This suggests a higher level of dependency and need for long-term care, reinforcing the importance of optimizing support systems for these patients to improve their quality of life and reduce institutionalization rates. The financial burden associated with SNF care is substantial, with dementia-related skilled nursing costs averaging over $110,000 per year (5,6).

The pronounced rate of discharge to skilled nursing facilities observed among patients with co-occurring SB and dementia must be interpreted within the context of their lifelong baseline self-care requirements. Self-care for individuals living with SB requires significant executive capacity to perform critical tasks such clean intermittent catheterization, meticulous skin checks, and mobility adjustments. Consequently, even mild or early-stage cognitive decline can easily overwhelm an individual’s ability to execute these critical tasks safely. When this delicate equilibrium is disrupted, independent living becomes untenable, precipitating a rapid reliance on institutional post-acute care or skilled nursing facilities, which can lead to higher healthcare utilizations.

Additionally, dementia-related encounters account for 13% of all healthcare visits among SB+D+ patients, underscoring the substantial burden dementia places on this population. Given the high healthcare utilization associated with dementia, preventative strategies are critical. While our dataset does not contain individual-level pharmacy or prescription records to verify drug exposure, chronic exposure to anticholinergic medications—a historical mainstay for neurogenic bladder management in SB—remains a plausible structural factor that warrants prospective study as a potential modifiable contributor to cognitive risk. Beyond pharmacological risk management, optimizing non-medication interventions offers a crucial avenue for mitigating cognitive decline and supporting independence in aging adults with SB. Incorporating structured cognitive rehabilitation, adaptive physical exercise regimens tailored to individual motor limitations, and robust community engagement initiatives can preserve executive functioning and build vital cognitive reserve. Furthermore, establishing proactive caregiver support networks early in the transition to late adulthood is essential for managing changing care dynamics. From a life-course perspective, these efforts should ideally build upon developmental and school-based interventions initiated during childhood. Early academic accommodations and executive function coaching provide a critical foundation, maximizing baseline cognitive reserve and establishing adaptive coping frameworks that may help buffer against the clinical manifestation of neurodegenerative changes later in life.

Furthermore, our findings demonstrate that SB+D+ patients have significantly higher healthcare utilization and costs compared to their SB+D− counterparts. The increased number of encounters and cumulative healthcare charges highlight the economic and clinical burden of dementia in this population. Dementia-related healthcare costs are projected to reach $1 trillion globally by 2050 (7,8). Addressing modifiable risk factors, such as medication management and early cognitive screening, may help reduce healthcare costs while improving patient outcomes (9).

Despite the strengths of this population-based analysis, several limitations should be acknowledged. First, our study relies on hospital-based administrative data, which does not capture outpatient visits or primary care encounters. Therefore, alternative dementia screening methods, such as cognitive assessments, performed in outpatient settings are not captured here. Additionally, we utilize ICD-9 and ICD-10 codes to identify diagnoses, coding inaccuracies or misclassification may have led to underestimation or overestimation of dementia prevalence and healthcare utilization. Third, while we controlled for SES and healthcare access, residual confounding may exist due to unmeasured variables, such as caregiver support, medication adherence, and individual health behaviors. Furthermore, granular data on the subtype of SB, neurosurgical history and concurrent developmental disorders is not reliably available and was not included in this analysis, which can be confounders. Additionally, our study is limited to California hospital data, which may not be generalizable to other regions with different healthcare systems and population demographics. Finally, while we highlight the potential impact of anticholinergic medications on dementia risk, our study does not directly assess medication use patterns or duration. Future research should explore longitudinal medication exposure and its effects on cognitive decline in SB patients.

Despite these limitations, our findings provide valuable insights into the healthcare disparities and challenges faced by individuals with SB and dementia, emphasizing the need for targeted interventions and improved screening strategies in this vulnerable population.

Conclusions

Our study highlights the significant healthcare burden faced by individuals with SB and dementia, emphasizing disparities in healthcare utilization, costs, and post-hospital disposition. The increased likelihood of discharge to skilled nursing facilities rather than home underscores the need for improved long-term care strategies tailored to this vulnerable population. Additionally, the high proportion of dementia-related healthcare encounters among SB patients signals an urgent need for preventative measures, particularly in reducing the use of anticholinergic medications, which may contribute to cognitive decline. Given the substantial economic and clinical impact of dementia in SB patients, future efforts should focus on optimizing care models, enhancing early screening, and implementing patient-centered interventions to mitigate disease progression. Addressing these challenges through multidisciplinary collaboration and healthcare system improvements will be critical in ensuring better outcomes and quality of life for individuals living with both SB and dementia

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://tau.amegroups.com/article/view/10.21037/tau-2026-0205/rc

Peer Review File: Available at https://tau.amegroups.com/article/view/10.21037/tau-2026-0205/prf

Funding: This study was supported by a grant from National Institute on Aging (No. 1K76AG079091-01A1). The Lifetime Congenital Urology Program was supported by the James A. Vlantis Fund.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tau.amegroups.com/article/view/10.21037/tau-2026-0205/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are 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. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Committee for Protection of Human Subjects, which serves as a California Health and Human Services Agency institutional review board and reviews all research conducted on human subjects. The data obtained were de-identified; therefore, informed consent was not necessary.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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