Unstable Housing and Kidney Disease: A Primer

The mediating effect of depressive syndrome on the relationship between adverse childhood experiences and chronic kidney diseases among middle-aged and older adults

Background

Chronic kidney disease (CKD) is projected to rank among the top five causes of mortality by 2050. In addition to established risk factors, adverse childhood experiences (ACEs) have recently emerged as significant contributors to health risks, including CKD and depressive syndrome (DS). However, the mechanisms linking ACEs, DS, and CKD remain unclear. This study aims to explore the role of ACEs in CKD development, with a focus on the mediating effects of DS.

Methods

This retrospective cohort study analyzed data from 10,247 participants in the China Health and Retirement Longitudinal Study (CHARLS). Logistic regression models were applied to assess the associations between ACEs, DS, and incident CKD, adjusting for demographic and lifestyle factors. Mediation analysis was conducted to evaluate the role of DS in the relationship between ACEs and CKD.

Results

Logistic regression analysis indicated that participants with a history of ACEs were at higher risk for both DS and CKD. Mediation analysis demonstrated that DS partially mediated the associations between CKD and seven specific ACEs: physical abuse, household substance abuse, household mental illness, domestic violence, unsafe neighborhood, peer bullying, and parental disability. Notably, DS fully mediated the relationship between CKD and unsafe neighborhood.

Conclusion

ACEs significantly influence CKD risk in middle-aged and older adults, with DS serving as a key mediator. These findings underscore the importance of early mental health interventions and ACE-focused preventive strategies to reduce the burden of CKD.

Food Insecurity and Risk of Hospitalization among Adults Receiving In-Center Hemodialysis

Key Points

Food insecurity was not associated with all-cause hospitalization but was associated with fluid or electrolyte-related hospitalization. Younger adults receiving hemodialysis may be more susceptible to food insecurity and should be a priority subpopulation for related interventions. Participants reporting food insecurity were more likely to miss dialysis treatments, suggesting food insecurity may affect outcomes through adherence.

Background

Food insecurity is common among people receiving in-center hemodialysis and living in residentially segregated communities. Food insecurity is associated with hospitalization in other chronic diseases but is understudied in the adult dialysis population.

Methods

We examined the association of food insecurity with all-cause hospitalization risk among adults receiving in-center hemodialysis. From February through December 2021, we conducted a prospective cohort study of adults at 17 dialysis facilities in Maryland, Washington DC, and Virginia. Participants completed a food insecurity survey at baseline and were monitored through their dialysis facility electronic medical record for 6 months. We censored participants upon change in dialysis modality, kidney transplantation, transfer to a nonparticipating dialysis facility, loss to follow-up, death, or end of the study follow-up period.

Results

We enrolled 322 participants. Of the 288 participants with survey and clinical record data, 61 (22%) reported food insecurity in the previous year and 91 (32%) experienced an all-cause hospitalization. Thirty-nine (13%) participants were censored before the end of the study period. Food insecurity was not a significant predictor of all-cause hospitalization in the full sample (adjusted hazard ratio [aHR], 1.06; 95% confidence interval [CI], 0.63 to 1.8). In exploratory analyses, all-cause hospitalization risk differed among younger and older participants reporting food insecurity, suggesting effect modification by age group (<55 years: aHR, 2.00; 95% CI, 0.91 to 4.42; ≥55 years: aHR, 0.63; 95% CI, 0.28 to 1.41; P value for interaction, 0.06). The risk of fluid or electrolyte-related hospitalizations among participants reporting food insecurity was three-fold higher than participants who were food secure (aHR, 3.04; 95% CI, 1.16 to 7.96).

Conclusions

In a cohort of adults receiving in-center hemodialysis, food insecurity was not associated with all-cause hospitalization but was associated with fluid or electrolyte-related hospitalization. Younger adults receiving in-center hemodialysis may be more susceptible to consequences of food insecurity.

Health impacts of cold exposure among people experiencing homelessness: A narrative systematic review on risks and risk-reduction approaches

OBJECTIVE

To systematically review evidence from high income countries on health risks from cold weather exposure among people experiencing homelessness (PEH) and assess evidence on risk-reduction interventions and their effectiveness.

STUDY DESIGN

Narrative systematic review.

METHODS

Keyword-structured searches were performed in CINAHL, Emcare, Medline, SocINDEX, Scopus, OpenGrey, Social Policy and Practice and Web of Science, and supplemented by grey literature searches in a selection of other databases, from 1973 to 2024. Articles were double-screened on title/abstract and full text. Extracted data included information on study setting and population, health risks from cold exposure, intervention characteristics and effect sizes where reported. Studies were critically appraised using Joanna Briggs Institute checklists.

RESULTS

24 studies were included, predominantly from the UK and US. People sleeping rough were found to be at greater risk than the general population of mortality due to hypothermia, and of hypothermic injury. Studies assessing health service utilisation indicated higher than population average admission rates due to cold exposure among PEH. Studies on interventions to reduce health risks from cold exposure in these populations all addressed multi-component programmes including shelter provision as a central component. Evidence of effectiveness was very limited.

CONCLUSION

PEH are at greater risk of death from hypothermia, and of hypothermic injury due to cold exposure than the general population. The use of overnight shelters and severe weather emergency plans are established approaches in high income settings for reducing risks from cold exposure among those sleeping rough, but further evidence on effectiveness is needed.

Addressing Colorectal Cancer Disparities in Unhoused Populations: A Call for Equitable Access and Compassionate Care

Housing is essential for health. Unhoused individuals have markedly worse health status than the general population culminating in higher rates of premature mortality. Cancer is a leading cause of death in older unhoused adults. Caring for unhoused patients at risk for or with colorectal cancer poses challenges at every stage of oncologic care: prevention, screening, diagnosis, treatment, and follow-up. These challenges result in later stages at diagnosis and worse overall survival. Health systems can work to advance health equity in colorectal cancer in unhoused patients by improving access to care, transitions of care, health care quality, and focusing on socioeconomic/environmental impact.

Using Large Language Models to Abstract Complex Social Determinants of Health From Original and Deidentified Medical Notes: Development and Validation Study

BACKGROUND

Social determinants of health (SDoH) such as housing insecurity are known to be intricately linked to patients' health status. More efficient methods for abstracting structured data on SDoH can help accelerate the inclusion of exposome variables in biomedical research and support health care systems in identifying patients who could benefit from proactive outreach. Large language models (LLMs) developed from Generative Pre-trained Transformers (GPTs) have shown potential for performing complex abstraction tasks on unstructured clinical notes.

OBJECTIVE

Here, we assess the performance of GPTs on identifying temporal aspects of housing insecurity and compare results between both original and deidentified notes.

METHODS

We compared the ability of GPT-3.5 and GPT-4 to identify instances of both current and past housing instability, as well as general housing status, from 25,217 notes from 795 pregnant women. Results were compared with manual abstraction, a named entity recognition model, and regular expressions.

RESULTS

Compared with GPT-3.5 and the named entity recognition model, GPT-4 had the highest performance and had a much higher recall (0.924) than human abstractors (0.702) in identifying patients experiencing current or past housing instability, although precision was lower (0.850) compared with human abstractors (0.971). GPT-4's precision improved slightly (0.936 original, 0.939 deidentified) on deidentified versions of the same notes, while recall dropped (0.781 original, 0.704 deidentified).

CONCLUSIONS

This work demonstrates that while manual abstraction is likely to yield slightly more accurate results overall, LLMs can provide a scalable, cost-effective solution with the advantage of greater recall. This could support semiautomated abstraction, but given the potential risk for harm, human review would be essential before using results for any patient engagement or care decisions. Furthermore, recall was lower when notes were deidentified prior to LLM abstraction.

Addressing Housing Issues Among People With Kidney Disease: Importance, Challenges, and Recommendations

Kidney disease disproportionately impacts people with low socioeconomic status, and low socioeconomic status is associated with worse outcomes for people with kidney disease. Unstable housing, which includes housing insecurity and homelessness, is increasing due to rising housing costs. There is mounting evidence that unstable housing and other health-related social needs are partially driving worse outcomes for people with low socioeconomic status. In this perspective, we consider the challenges to addressing housing for people with kidney disease, such as difficulty with identification of those with unstable housing, strict eligibility criteria for housing support, inadequate supply of affordable housing, and flaws in communities' prioritization of affordable housing. We discuss ways to tailor management for people experiencing unstable housing with kidney disease, and the importance of addressing safety, trauma, and emotional concerns as a part of care. We identify opportunities for the nephrology community to surmount challenges through increased screening, investment in workforce dedicated to community resource navigation, advocacy for investment in affordable housing, restructuring of communities' prioritization of affordable housing, and conducting needed research. Identifying and addressing housing needs among people with kidney disease is critical to eliminating kidney health disparities.

Using Large Language Models to Annotate Complex Cases of Social Determinants of Health in Longitudinal Clinical Records

Social Determinants of Health (SDoH) are an important part of the exposome and are known to have a large impact on variation in health outcomes. In particular, housing stability is known to be intricately linked to a patient's health status, and pregnant women experiencing housing instability (HI) are known to have worse health outcomes. Most SDoH information is stored in electronic health records (EHRs) as free text (unstructured) clinical notes, which traditionally required natural language processing (NLP) for automatic identification of relevant text or keywords. A patient's housing status can be ambiguous or subjective, and can change from note to note or within the same note, making it difficult to use existing NLP solutions. New developments in NLP allow researchers to prompt LLMs to perform complex, subjective annotation tasks that require reasoning that previously could only be attempted by human annotators. For example, large language models (LLMs) such as GPT (Generative Pre-trained Transformer) enable researchers to analyze complex, unstructured data using simple prompts. We used a secure platform within a large healthcare system to compare the ability of GPT-3.5 and GPT-4 to identify instances of both current and past housing instability, as well as general housing status, from 25,217 notes from 795 pregnant women. Results from these LLMs were compared with results from manual annotation, a named entity recognition (NER) model, and regular expressions (RegEx). We developed a chain-of-thought prompt requiring evidence and justification for each note from the LLMs, to help maximize the chances of finding relevant text related to HI while minimizing hallucinations and false positives. Compared with GPT-3.5 and the NER model, GPT-4 had the highest performance and had a much higher recall (0.924) than human annotators (0.702) in identifying patients experiencing current or past housing instability, although precision was lower (0.850) compared with human annotators (0.971). In most cases, the evidence output by GPT-4 was similar or identical to that of human annotators, and there was no evidence of hallucinations in any of the outputs from GPT-4. Most cases where the annotators and GPT-4 differed were ambiguous or subjective, such as "living in an apartment with too many people". We also looked at GPT-4 performance on de-identified versions of the same notes and found that precision improved slightly (0.936 original, 0.939 de-identified), while recall dropped (0.781 original, 0.704 de-identified). This work demonstrates that, while manual annotation is likely to yield slightly more accurate results overall, LLMs, when compared with manual annotation, provide a scalable, cost-effective solution with the advantage of greater recall. At the same time, further evaluation is needed to address the risk of missed cases and bias in the initial selection of housing-related notes. Additionally, while it was possible to reduce confabulation, signs of unusual justifications remained. Given these factors, together with changes in both LLMs and charting over time, this approach is not yet appropriate for use as a fully-automated process. However, these results demonstrate the potential for using LLMs for computer-assisted annotation with human review, reducing cost and increasing recall. More efficient methods for obtaining structured SDoH data can help accelerate inclusion of exposome variables in biomedical research, and support healthcare systems in identifying patients who could benefit from proactive outreach.

Paving a Path to Equity in Cardiorenal Care

Cardiorenal syndrome encompasses a dynamic interplay between cardiovascular and kidney disease, and its prevention requires careful examination of multiple predisposing underlying conditions. The unequal distribution of diabetes, heart failure, hypertension, and kidney disease requires special attention because of the influence of these conditions on cardiorenal disease. Despite growing evidence regarding the benefits of disease-modifying agents (e.g., sodium-glucose cotransporter 2 inhibitors) for cardiovascular, kidney, and metabolic (CKM) disease, significant disparities remain in access to and utilization of these essential therapeutics. Multilevel barriers impeding their use require multisector interventions that address patient, provider, and health system-tailored strategies. Burgeoning literature also describes the critical role of unequal social determinants of health, or the sociopolitical contexts in which people live and work, in cardiorenal risk factors, including heart failure, diabetes, and chronic kidney disease. This review outlines (i) inequality in the burden and treatment of hypertension, type 2 diabetes, and heart failure; (ii) disparities in the use of key disease-modifying therapies for CKM diseases; and (iii) multilevel barriers and solutions to achieve greater pharmacoequity in the use of disease-modifying therapies. In addition, this review provides summative evidence regarding the role of unequal social determinants of health in cardiorenal health disparities, further outlining potential considerations for future research and intervention. As proposed in the 2023 American Heart Association presidential advisory on CKM health, a paradigm shift will be needed to achieve cardiorenal health equity. Through a deeper understanding of CKM health and a commitment to equity in the prevention, detection, and treatment of CKM disease, we can achieve this critical goal.

Social and Behavioral Barriers to Effective Care During the Transition to End-Stage Kidney Care

Individuals living with CKD are disproportionately burdened by a multitude of adverse clinical and person-centered outcomes. When patients transition from advanced kidney disease to kidney failure, the psychosocial effects as well as social determinants of health challenges are magnified, making this a particularly difficult time for patients beginning kidney replacement therapy. The key social determinants of health challenges often include food and housing insecurity, poverty, unreliable transportation, low level education and/or health literacy, lack of language interpreters and culturally concordant educational materials, lack of health care insurance coverage, and mistrust of the health care system. Psychosocial and physical stressors, such as depression, anxiety, sexual dysfunction, sleep difficulty, fatigue, and pain, are often part of the illness burden among individuals living with CKD and can interact synergistically with the social challenges making the transition to kidney replacement therapy particularly challenging. To better support patients during this time, it is critical that social and structural determinants of health as well as mental health be assessed and if needs are identified, that services be provided.

Association of Housing Status With Types of Operations and Postoperative Health Care Utilization

OBJECTIVE

To analyze the association between housing status and the nature of surgical care provided, health care utilization, and operational outcomes.

BACKGROUND

Unhoused patients have worse outcomes and higher health care utilization across multiple clinical domains. However, little has been published describing the burden of surgical disease in unhoused patients.

METHODS

We conducted a retrospective cohort study of 111,267 operations from 2013 to 2022 with housing status documented at a single, tertiary care institution. We conducted unadjusted bivariate and multivariate analyses adjusting for sociodemographic and clinical characteristics.

RESULTS

A total of 998 operations (0.8%) were performed for unhoused patients, with a higher proportion of emergent operations than housed patients (56% vs 22%). In unadjusted analysis, unhoused patients had longer length of stay (18.7 vs 8.7 days), higher readmissions (9.5% vs 7.5%), higher in-hospital (2.9% vs 1.8%) and 1-year mortality (10.1% vs 8.2%), more in-hospital reoperations (34.6% vs 15.9%), and higher utilization of social work, physical therapy, and occupational therapy services. After adjusting for age, sex, comorbidities, insurance status, and indication for operation, as well as stratifying by emergent versus elective operation, these differences went away for emergent operations.

CONCLUSIONS

In this retrospective cohort analysis, unhoused patients more commonly underwent emergent operations than their housed counterparts and had more complex hospitalizations on an unadjusted basis that largely disappeared after adjustment for patient and operative characteristics. These findings suggest issues with upstream access to surgical care that, when unaddressed, may predispose this vulnerable population to more complex hospitalizations and worse longer term outcomes.

Unstable Housing and Mortality Among US Veterans Receiving Dialysis

Importance

Housing status is an important health determinant, yet little is known about unstable housing among individuals receiving dialysis.

Objective

To determine factors associated with unstable housing among US veterans receiving dialysis and to estimate the association of unstable housing with risk of death.

Design, Setting, and Participants

This retrospective cohort study used data from the US Veterans Health Administration (VHA) and the US Renal Data System for patients who initiated dialysis between October 1, 2012, and December 31, 2018. Veterans were included if they used VHA outpatient services and completed 1 or more unstable housing screenings within a 3-year period before starting dialysis. Data analysis was conducted from January 24 to June 16, 2023.

Exposures

Unstable housing was defined as self-report of not having stable housing within the past 2 months or having concerns about stable housing in the next 2 months.

Main Outcomes and Measures

The main outcome was all-cause mortality. Characteristics associated with unstable housing at the time of dialysis initiation were examined. The multivariate Fine and Gray cumulative incidence model was used, treating transplant as a competing risk and age as an effect modifier, to examine the risk of death associated with unstable housing.

Results

This study included 25 689 veterans, with a median age of 68 (IQR, 62-74) years. Most participants were men (98%), and more than half (52%) were White. There were 771 veterans (3%) with a positive screen for unstable housing within a 3-year period before starting dialysis. Compared with veterans with stable housing, those with unstable housing were younger (mean [SD] age, 61 [8] vs 68 [10] years), were more likely to be Black (45% vs 32%) or Hispanic (9% vs 7%), and were more likely to start dialysis with a central venous catheter (77% vs 66%), receive in-center hemodialysis (96% vs 91%), and have non-Medicare insurance (53% vs 28%). Factors associated with unstable housing included Hispanic ethnicity, non-arteriovenous fistula vascular access, lack of predialysis nephrology care, and non-Medicare insurance. Veterans with unstable housing had higher all-cause mortality (adjusted hazard ratio [AHR], 1.20 [95% CI, 1.04 to 1.37] for a median age of 68 years), and risks increased with age (P = .01 for interaction). In age-stratified analyses, unstable housing was associated with higher mortality among veterans aged 75 to 85 years (AHR, 1.64 [95% CI, 1.18 to 2.28]), but associations were not observed for other age groups.

Conclusions and Relevance

In this cohort study of veterans receiving dialysis, unstable housing experienced before starting dialysis was associated with increased risk of all-cause mortality, and risks increased with age. Further efforts are needed to understand the experiences of older adults with unstable housing and to estimate the scope of unstable housing among all individuals receiving dialysis.

Material Need Insecurities among People on Hemodialysis: Burden, Sociodemographic Risk Factors, and Associations with Substance Use

Key Points

Food insecurity and housing instability may affect dialysis outcomes through health behaviors like treatment adherence and their effect on access to transplantation or home dialysis therapies. People on hemodialysis who were younger, with less educational attainment, with lower incomes, or experiencing financial strain were more likely to experience material need insecurities. Participant race was not associated with material need insecurities, although residential segregation moderated associations between age, sex, and food insecurity.

Background

Despite their relevance to health outcomes, reports of food insecurity and housing instability rates among adults on hemodialysis are limited. Their relation to sociodemographic and behavioral factors are unknown for this population.

Methods

We enrolled a convenience sample of people receiving hemodialysis at Baltimore and Washington, DC metropolitan area facilities. Participants completed measures of socioeconomic position, food insecurity, housing instability, and substance use disorder. We cross-referenced participant and facility zip codes with measures of area poverty and residential segregation. We examined associations between individual-level and area-level sociodemographic characteristics, food insecurity, and housing instability using multivariable logistic regression models.

Results

Of the 305 participants who completed study surveys, 57% were men and 70% were Black, and the mean age was 60 years. Thirty-six percent of the sample reported food insecurity, 18% reported housing instability, and 31% reported moderate or high-risk substance use. People on hemodialysis who were younger, with lower educational attainment, with lower incomes, or experiencing financial strain were more likely to have material need insecurities (P < 0.05 for all). Among participants living in segregated jurisdictions, men had increased odds of food insecurity compared with women (odds ratio 3.7; 95% confidence interval, 1.61 to 8.53); younger participants (age <55 years) had increased odds of food insecurity compared with older participants (odds ratio 3.3; 95% confidence interval, 1.49 to 7.32). Associations between sex or younger age category and food insecurity were not statistically significant in less segregated counties (P interaction for residential segregation×sex: P = 0.006; residential segregation×younger age category: P = 0.12).

Conclusions

Food insecurity, housing instability, and substance use were common among this sample of adults on hemodialysis. Younger adults on hemodialysis, particularly those living in residentially segregated jurisdictions, were at increased risk for food insecurity. Future research should examine whether material need insecurities perpetuate disparities in dialysis outcomes.

Podcast

This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/K360/2023_12_01_KID0000000000000279.mp3