Social and Economic Differences in Neighborhood Walkability Across 500 U.S. Cities

The interplay between social environment and opportunities for physical activity within the built environment: a scoping review

BACKGROUND

The association between social and built environments plays a crucial role in influencing physical activity levels. However, a thorough understanding of their combined impact remains unclear. This scoping review seeks to clarify the interplay between social environments and opportunities for physical activity within different built environments, with a particular focus on the implications of socioeconomic status and urban planning on physical activity participation.

METHODS

We conducted a systematic literature search across several databases to identify studies exploring the associations between social factors, built environment characteristics, and physical activity levels. The inclusion criteria were studies published in English between 2000 and 2022, encompassing urban, suburban, and rural contexts. Thematic analysis was employed to categorise studies based on the specific aspects of the built environment they investigated (walking infrastructure, cycling infrastructure, parks and open spaces, and sports facilities) and the social determinants they examined.

RESULTS

A total of 72 studies were included in the review, illustrating a multifaceted relationship between access to physical activity opportunities and social determinants such as socioeconomic status, community engagement, and urban design. The findings highlight the significant role of socioeconomic factors and the quality of PA infrastructure in promoting or hindering PA across communities. Effective urban planning was identified as crucial in providing expanded physical activity opportunities, notably through more pedestrian-friendly environments, comprehensive cycling infrastructure, and accessible green spaces and sports facilities.

CONCLUSIONS

This review emphasises the significant impact of socioeconomic status and urban planning on access to physical activity opportunities. This underscores the necessity for urban planning policies to adopt an inclusive approach, considering the varied needs of different population groups to ensure equitable access to physical activity resources. Such strategies are crucial for public health initiatives aimed at enhancing physical activity levels across diverse community sectors, offering a potential avenue to alleviate health disparities associated with inactivity.

Disparities in Obesogenic Environments by Income, Race/Ethnicity, and Rurality Across All US Counties

Background: Research is needed to explore inequities in physical activity (PA) and access to healthy eating resources for children on a national scale. This study examined disparities in childhood obesogenic environments across all United States (US) counties by income and race/ethnicity and their interaction with county rurality. Methods: Data for four PA variables (exercise opportunities, school proximity, walkability, crime) and six nutrition variables (grocery stores, farmers markets, fast-food restaurants, full-service restaurants, convenience stores, and births at baby-friendly hospitals) were collected for all US counties (n = 3142) to comprise the Childhood Obesogenic Environment Index (COEI). Variables were ranked and allocated a percentile for each county, and a total obesogenic environment score was created by averaging variable percentiles. Analysis of variance was used to assess differences by tertiles of county-level median household income (low/intermediate/high) and percentage of non-Hispanic (NH) White residents (low/intermediate/high). Interaction tests were used to assess effect modification by rurality, and stratified results were presented for all significant interactions. Results: There were significant differences in COEI values according to tertiles of median household income (F = 260.9, p < 0.0001). Low-income counties (M = 54.3, SD = 8.3) had worse obesogenic environments than intermediate (M = 49.9, SD = 7.9) or high (M = 45.9, SD = 8.8) income counties. There was also a significant interaction between rurality and median household income (F = 13.9, p < 0.0001). Similarly, there were significant differences in COEI values according to tertiles of race/ethnicity (F = 34.5, p < 0.0001), with low percentage NH White counties (M = 51.8, SD = 9.8) having worse obesogenic environment scores than intermediate (M = 48.7, SD = 8.4) or high (M = 49.5, SD = 8.5) NH White counties. There was also a significant interaction between rurality and race/ethnicity (F = 13.9, p < 0.0001). Conclusion: Low-income counties and those with more racial/ethnic minority residents, especially in rural areas, had less supportive PA and healthy eating environments for youth. Targeted policy and environmental approaches that aimed to address concerns specific to underserved communities are needed.

Impact of neighborhood disadvantage on posttrauma outcomes after sexual assault

In the United States, 8,000,000 people seek emergency care for traumatic injury annually. Motor vehicle collisions (MVCs) and sexual assault are two common sources of trauma, with evidence that reduced neighborhood-level socioeconomic characteristics increase posttraumatic pain and stress after an MVC. We evaluated whether neighborhood disadvantage was also associated with physical and mental posttrauma outcomes after sexual assault in a sample of adult women (N = 656) who presented for emergency care at facilities in the United States following sexual assault and were followed for 1 year. Neighborhood characteristics were assessed via the Area Deprivation Index, and self-reported pain, anxiety, depression, and posttraumatic stress disorder (PTSD) symptoms were collected at 6 weeks posttrauma. Adjusted log-binomial regression models examined the association between each clinical outcome and neighborhood disadvantage. Women in more disadvantaged neighborhoods were more likely to be non-White and have lower annual incomes. At 6 weeks posttrauma, the prevalence of clinically significant pain, anxiety, and depressive symptoms more than doubled from baseline (41.7% vs. 18.8%, 62.4% vs. 23.9%, and 55.2% vs. 22.7%, respectively); 40.7% of women also reported PTSD symptoms. Black, Hispanic, and lower-income participants were more likely to report pre- and postassault pain, anxiety, and depression. After adjusting for race, ethnicity, and income, no significant association existed between neighborhood disadvantage and any outcome, ps = .197 - .859. Although neighborhood disadvantage was not associated with posttrauma outcomes, these findings highlight the need for continued research in diverse populations at high risk of adverse physical and mental health symptoms following sexual assault.

The Urban Environment and Cardiometabolic Health

Urban environments contribute substantially to the rising burden of cardiometabolic diseases worldwide. Cities are complex adaptive systems that continually exchange resources, shaping exposures relevant to human health such as air pollution, noise, and chemical exposures. In addition, urban infrastructure and provisioning systems influence multiple domains of health risk, including behaviors, psychological stress, pollution, and nutrition through various pathways (eg, physical inactivity, air pollution, noise, heat stress, food systems, the availability of green space, and contaminant exposures). Beyond cardiometabolic health, city design may also affect climate change through energy and material consumption that share many of the same drivers with cardiometabolic diseases. Integrated spatial planning focusing on developing sustainable compact cities could simultaneously create heart-healthy and environmentally healthy city designs. This article reviews current evidence on the associations between the urban exposome (totality of exposures a person experiences, including environmental, occupational, lifestyle, social, and psychological factors) and cardiometabolic diseases within a systems science framework, and examines urban planning principles (eg, connectivity, density, diversity of land use, destination accessibility, and distance to transit). We highlight critical knowledge gaps regarding built-environment feature thresholds for optimizing cardiometabolic health outcomes. Last, we discuss emerging models and metrics to align urban development with the dual goals of mitigating cardiometabolic diseases while reducing climate change through cross-sector collaboration, governance, and community engagement. This review demonstrates that cities represent crucial settings for implementing policies and interventions to simultaneously tackle the global epidemics of cardiovascular disease and climate change.

Modification of the PM2.5- and extreme heat-mortality relationships by historical redlining: a case-crossover study in thirteen U.S. states

BACKGROUND

Redlining has been associated with worse health outcomes and various environmental disparities, separately, but little is known of the interaction between these two factors, if any. We aimed to estimate whether living in a historically-redlined area modifies the effects of exposures to ambient PM2.5 and extreme heat on mortality by non-external causes.

METHODS

We merged 8,884,733 adult mortality records from thirteen state departments of public health with scanned and georeferenced Home Owners Loan Corporation (HOLC) maps from the University of Richmond, daily average PM2.5 from a sophisticated prediction model on a 1-km grid, and daily temperature and vapor pressure from the Daymet V4 1-km grid. A case-crossover approach was used to assess modification of the effects of ambient PM2.5 and extreme heat exposures by redlining and control for all fixed and slow-varying factors by design. Multiple moving averages of PM2.5 and duration-aware analyses of extreme heat were used to assess the most vulnerable time windows.

RESULTS

We found significant statistical interactions between living in a redlined area and exposures to both ambient PM2.5 and extreme heat. Individuals who lived in redlined areas had an interaction odds ratio for mortality of 1.0093 (95% confidence interval [CI]: 1.0084, 1.0101) for each 10 µg m-3 increase in same-day ambient PM2.5 compared to individuals who did not live in redlined areas. For extreme heat, the interaction odds ratio was 1.0218 (95% CI 1.0031, 1.0408).

CONCLUSIONS

Living in areas that were historically-redlined in the 1930's increases the effects of exposures to both PM2.5 and extreme heat on mortality by non-external causes, suggesting that interventions to reduce environmental health disparities can be more effective by also considering the social context of an area and how to reduce disparities there. Further study is required to ascertain the specific pathways through which this effect modification operates and to develop interventions that can contribute to health equity for individuals living in these areas.

Individual and environmental variables related to outdoor walking among older adults: Verifying a model to guide the design of interventions targeting outdoor walking

OBJECTIVE

To estimate the relationships between individual and environmental variables and outdoor walking (OW) in older adults with OW limitations through verifying a conceptual model.

METHODS

Baseline data from 205 older adults participating in a randomized trial of a park-based OW program were analyzed using structural equation modeling. We evaluated a three latent factor model: OW (accelerometry and self-report); individual factors (balance; leg strength; walking self-confidence, speed and endurance; mental health; education; income; car access); and environmental factors (neighbourhood walkability components).

RESULTS

Mean age was 75 years; 73% were women. Individual factors was significantly associated with OW (β = 0.39, p < .01). Environmental factors was not directly associated with OW but was indirectly linked to OW through its significant covariance with the individual factors (β = 0.22, p < .01). The standardized factor loadings from the individual factors on walking self-confidence and walking capacity measures exceeded 0.65.

CONCLUSIONS

Better walking capacity and more confidence in the ability to walk outdoors are associated with higher OW in older adults. Better neighbourhood walkability is indirectly associated with more OW. The conceptual model demonstrates an individual and environment association; if the capacity of the individual is increased (potentially through walking interventions), they may be able to better navigate environmental challenges.

Pedestrian-oriented zoning moderates the relationship between racialized economic segregation and active travel to work, United States

OBJECTIVE

Pedestrian-oriented zoning, including zoning code reforms (ZCR), may be especially beneficial to racially and economically segregated communities, which may lack built environment features that support physical activity. This study examined associations between racialized economic segregation, measured by quintiles of the Index of Concentration at the Extremes, and public transit (PTW) and active travel (ATW) to work, and whether associations were moderated by pedestrian-oriented zoning provisions and ZCR, respectively.

METHODS

Zoning codes effective as of 2010 representing 3914 US municipalities (45.45% of US population) were evaluated for the presence of ZCR and eight pedestrian-oriented zoning provisions. These data were linked with American Community Survey 2013-2017 and NAVTEQ 2013 data on the outcomes and relevant covariates. Fractional logit regressions were computed with standard errors clustered on county.

RESULTS

Workers from more deprived quintiles were less likely to engage in PTW and ATW (OR = 0.22-0.55, p < 0.01), and tests revealed moderation by zoning (p < 0.05). ZCR was positively associated with PTW for the three most deprived quintiles (OR = 1.53-2.38, p < 0.01), and with ATW for the two most deprived quintiles (OR = 1.42-1.69, p < 0.01) and the second most privileged quintile (OR = 1.26, p < 0.05). In the most privileged quintile, the zoning scale score was negatively associated with PTW (OR = 0.91, p < 0.001) and ATW (OR = 0.94, p < 0.01). However, in the most deprived quintiles, the zoning scale score was positively associated with PTW (Q2: OR = 1.13, p < 0.01) and ATW (Q1-Q2: OR = 1.07-1.09, p < 0.05).

CONCLUSIONS

Pedestrian-oriented zoning can provide opportunities for ATW in the most deprived communities. Work is needed to explore zoning policy implementation in those communities.

Association between racial residential segregation and walkability in 745 U.S. cities

Despite higher chronic disease prevalence, minoritized populations live in highly walkable neighborhoods in US cities more frequently than non-minoritized populations. We investigated whether city-level racial residential segregation (RRS) was associated with city-level walkability, stratified by population density, possibly explaining this counterintuitive association. RRS for Black-White and Latino-White segregation in large US cities was calculated using the Index of Dissimilarity (ID), and walkability was measured using WalkScore. Median walkability increased across increasing quartiles of population density, as expected. Higher ID was associated with higher walkability; associations varied in strength across strata of population density. RRS undergirds the observed association between walkability and minoritized populations, especially in higher population density cities.

Neighborhood Socioeconomic Status, Green Space, and Walkability and Risk for Falls Among Postmenopausal Women: The Women's Health Initiative

PURPOSE

This study estimated associations between neighborhood socioeconomic status (NSES), walkability, green space, and incident falls among postmenopausal women and evaluated modifiers of these associations, including study arm, race and ethnicity, baseline household income, baseline walking, age at enrollment, baseline low physical functioning, baseline fall history, climate region, and urban-rural residence.

METHODS

The Women's Health Initiative recruited a national sample of postmenopausal women (50-79 years) across 40 U.S. clinical centers and conducted yearly assessments from 1993 to 2005 (n = 161,808). Women reporting a history of hip fracture or walking limitations were excluded, yielding a final sample of 157,583 participants. Falling was reported annually. NSES (income/wealth, education, occupation), walkability (population density, diversity of land cover, nearby high-traffic roadways), and green space (exposure to vegetation) were calculated annually and categorized into tertiles (low, intermediate, high). Generalized estimating equations assessed longitudinal relationships.

RESULTS

NSES was associated with falling before adjustment (high vs. low, odds ratio, 1.01; 95% confidence interval, 1.00-1.01). Walkability was significantly associated with falls after adjustment (high vs. low, odds ratio, 0.99; 95% confidence interval, 0.98-0.99). Green space was not associated with falling before or after adjustment. Study arm, race and ethnicity, household income, age, low physical functioning, fall history, and climate region modified the relationship between NSES and falling. Race and ethnicity, age, fall history, and climate region modified relationships between walkability and green space and falling.

CONCLUSIONS

Our results did not show strong associations of NSES, walkability, or green space with falling. Future research should incorporate granular environmental measures that may directly relate to physical activity and outdoor engagement.

The associations between place-based measures of walkability and physical activity across a range of diverse streetscapes

Walkability relates to aspects of a physical environment that have the potential to influence walking in that environment. In 2019, the Environmental Protection Agency developed the National Walkability Index (NWI), an easily accessible, U.S. Census block-group-level indicator of walkability. Although the NWI could be the metric of choice for researchers and urban planners, there is a lack of empirical evidence for its validity. The current study examined the validity of the NWI and Walk Score for predicting physical activity (PA) occurring along urban streetscapes. A wearable video device (Gogloo E7 SMART eyewear) was used to capture videos of streetscapes in 24 U.S. Census block groups in three different sized cities. The block groups varied in walkability, income level, and minority composition. The videos, collected over 10 months during 2019 at different times on weekdays and weekends, were reviewed by experts to obtain counts of walkers/h and individuals performing leisure PA/h (dependent variables). The independent variables were the NWI, its components - transit stop proximity, intersection density, employment/household occupancy mix, and employment mix, and Walk Score. Block group was the level of analysis. Linear regression indicated Walk Score, employment/household occupancy mix, and employment mix were associated with walkers/h (p < .001) while only employment/household occupancy mix, and employment mix were associated with leisure PA/h (p < .001). The NWI did not account for a significant portion of the variance in PA outcomes. A place-based examination of PA and walkability indexes favors the use of Walk Score and a modified version of the NWI.

The longitudinal association between asthma severity and physical fitness among new York City public school youth

Severe persistent childhood asthma is associated with low physical activity and may be associated with poor physical fitness. Research on the asthma severity-fitness association longitudinally and across sociodemographic subgroups is needed to inform fitness interventions targeting youth with asthma. We evaluated the relationship between asthma severity (categorized as severe, mild, or no asthma) and subsequent fitness in New York City (NYC) public school youth enrolled in grades 4-12 using the NYC Fitnessgram dataset (2010-2018). Longitudinal mixed models with random intercepts were fit to test the association between asthma severity and one-year lagged fitness z-scores by clustering repeated annual observations at the student level. Models were adjusted for sex, race/ethnicity, grade level, poverty status, time, and stratified by sociodemographic factors. The analytic sample included 663,137 students (51% male; 31% non-Hispanic Black, 40% Hispanic; 55% in grades 4-8, 70% high poverty; 87%, 11% and 1% with no, mild, and severe asthma, respectively). Students with severe asthma and mild asthma demonstrated -0.19 (95% CI, -0.20 to -0.17) and - 0.10 (95% CI, -0.11 to -0.10), respectively, lower fitness z-scores in the subsequent year relative to students without asthma. After stratifying by demographics, the magnitude of the asthma severity-fitness relationship was highest for non-Hispanic white vs. all other racial/ethnic subgroups, and was similar across sex, grade level, and household poverty status. Overall, we observed an inverse longitudinal relationship between asthma severity and subsequent fitness among urban youth, particularly non-Hispanic Whites. Future research should examine how neighborhood-level factors impact the asthma severity-fitness relationship across racial/ethnic subgroups.

Differences in Rural Built Environment Perceptions Across Demographic and Social Environment Characteristics

The benefits of physical activity to health and obesity prevention are well established. However, attributes of the built environment influence participation in physical activity. The purpose of this study is to assess differences in perceptions of neighborhood walkability across demographic characteristics and social environment factors among rural residents. In a telephone survey, adult respondents (N = 448) across nine rural counties in a southeastern state answered questions about perceived neighborhood walkability, demographic characteristics, and their neighborhood social environment. Study recruitment for a convenience sample occurred through collaborations with local community organizations. Prevalence of destinations and barriers were estimated according to demographic and neighborhood social environment characteristics. Multiple logistic regression models assessed the association of demographic and neighborhood social environment characteristics with neighborhood walkability and calculated adjusted prevalence. Relaxing places to walk were the most often reported destinations (62.0%), followed by retail destinations (45.7%), and communal destinations (42.6%). Traffic was the most reported barrier to safe walking (40.4%), followed by animals (37.5%), and crime (30.5%). Perceptions of retail and communal destinations varied by age and race. Perceptions of traffic and crime as barriers varied by race, weight status, and income. Community belonging and social cohesion were associated with lower perceptions of barriers. Study findings present demographic characteristics and social environment attributes as key factors that shape perceived neighborhood walkability. Findings can help inform programmatic efforts and environmental change strategies to improve walking in rural areas.

Disparity in Built Environment and Its Impacts on Youths' Physical Activity Behaviors During COVID-19 Pandemic Restrictions

Objectives

Guided by the social ecological model, this study aimed to examine the relations of built environments (i.e., walking/cycling infrastructure, recreation facilities, neighborhood safety/crime), youth’s transition abilities, and changes of youth’s physical activity (PA) and play behaviors due to COVID-19-based restrictions. Ethnic and socioeconomic status (SES) disparities were also examined on studies variables during the COVID-19 restrictions.

Method

A cross-sectional research design was used to assess an anonymous online survey completed by US parents/guardians. The final sample had 1324 children and adolescents (Mean_age = 9.75; SD = 3.95; 51.3% girls), and 35.5% the families were of upper socioeconomic class (income > $150,000). Parents reported the perceived built environment and neighborhood safety, child’s PA and play behaviors during COVID-19 pandemic shelter-in-place restrictions.

Results

Youths who had access to safe built environment were more active and played more outdoor/indoor (p < .01). It was found playing behavior in yard and neighborhood were significantly increased, but community-based play behavior was significantly reduced during COVID-19 restrictions. The SEM analysis (χ²/df = 236.04/54; CFI = .966) supported indirect and direct effects of neighborhood safety on PA changes during COVID-19 restrictions, and the youth’s ability to respond to COVID-19 restrictions served as a full mediator. Low-SES and Hispanic minority youth reported significantly less safety to walking or playing in their neighborhoods than their middle-/high-SES non-Hispanic peers (p < .001). Regardless of ethnicity, the magnitude of the reduction of MVPA was significantly higher among low-SES groups than that of the high- and middle-SES groups (p < .001).

Conclusions

These findings demonstrate a need to tailor programs and policies to help high-risk groups (e.g., low SES) stay active, healthy, and resilient during and after the COVID-19 pandemic.

Association of Area-Level Socioeconomic Deprivation With Hypoglycemic and Hyperglycemic Crises in US Adults With Diabetes

IMPORTANCE

Social determinants of health play a role in diabetes management and outcomes, including potentially life-threatening complications of severe hypoglycemia and diabetic ketoacidosis (DKA) or hyperglycemic hyperosmolar state (HHS). Although several person-level socioeconomic factors have been associated with these complications, the implications of area-level socioeconomic deprivation are unknown.

OBJECTIVE

To examine the association between area-level deprivation and the risks of experiencing emergency department visits or hospitalizations for hypoglycemic and hyperglycemic crises (ie, DKA or HHS).

DESIGN, SETTING, AND PARTICIPANTS

This cohort study used deidentified administrative claims data for privately insured individuals and Medicare Advantage beneficiaries across the US. The analysis included adults with diabetes who met the claims criteria for diabetes between January 1, 2016, and December 31, 2017. Data analyses were performed from November 17, 2020, to November 11, 2021.

EXPOSURES

Area deprivation index (ADI) was derived for each county for 2016 and 2017 using 17 county-level indicators from the American Community Survey. ADI values were applied to patients who were living in each county based on their index dates and were categorized according to county-level ADI quintile (with quintile 1 having the least deprivation and quintile 5 having the most deprivation).

MAIN OUTCOMES AND MEASURES

The numbers of emergency department visits or hospitalizations related to the primary diagnoses of hypoglycemia and DKA or HHS (ascertained using validated diagnosis codes in the first or primary position of emergency department or hospital claims) between 2016 and 2019 were calculated for each ADI quintile using negative binomial regression models and adjusted for patient age, sex, health plan type, comorbidities, glucose-lowering medication type, and percentage of White residents in the county.

RESULTS

The study population included 1 116 361 individuals (563 943 women [50.5%]), with a mean (SD) age of 64.9 (13.2) years. Of these patients, 343 726 (30.8%) resided in counties with the least deprivation (quintile 1) and 121 810 (10.9%) lived in counties with the most deprivation (quintile 5). Adjusted rates of severe hypoglycemia increased from 13.54 (95% CI, 12.91-14.17) per 1000 person-years in quintile 1 counties to 19.13 (95% CI, 17.62-20.63) per 1000 person-years in quintile 5 counties, corresponding to an incidence rate ratio of 1.41 (95% CI, 1.29-1.54; P < .001). Adjusted rates of DKA or HHS increased from 7.49 (95% CI, 6.96-8.02) per 1000 person-years in quintile 1 counties to 8.37 (95% CI, 7.50-9.23) per 1000 person-years in quintile 5 counties, corresponding to an incidence rate ratio of 1.12 (95% CI, 1.00-1.25; P = .049).

CONCLUSIONS AND RELEVANCE

This study found that living in counties with a high area-level deprivation was associated with an increased risk of severe hypoglycemia and DKA or HHS. The concentration of these preventable events in areas of high deprivation signals the need for interventions that target the structural barriers to optimal diabetes management and health.

Neighbourhood Walkability and Risk of Diabetes: Causal Relationship or Epidemiologic Association?

PURPOSE OF REVIEW

We aim to evaluate whether the current literature supports (i) a causal relationship between neighbourhood walkability and risk of diabetes or instead (ii) a strictly epidemiologic association.

RECENT FINDINGS

Both cross-sectional and longitudinal studies have reported that neighbourhoods that are scored as having higher levels of walkability have lower rates of prevalent and incident diabetes, respectively. However, other studies have been inconclusive, with more nuanced findings suggesting that this association may be limited to particular demographic groups defined by age and socio-economics. Key factors limiting this literature include disparities in the measurement of walkability, the necessary reliance on observational study designs (recognizing the infeasibility of randomized controlled trials for addressing this question), and the difficulty of disentangling the potential concomitant effects of other components of the built environment. At this time, causality cannot be ascertained in the relationship between neighbourhood walkability and risk of diabetes.

Sociodemographic, Clinical, and Treatment-Related Factors Associated With Hyperglycemic Crises Among Adults With Type 1 or Type 2 Diabetes in the US From 2014 to 2020

IMPORTANCE

Hyperglycemic crises (ie, diabetic ketoacidosis [DKA] and hyperglycemic hyperosmolar state [HHS]) are life-threatening acute complications of diabetes. Efforts to prevent these events at the population level have been hindered by scarce granular data and difficulty in identifying individuals at highest risk.

OBJECTIVE

To assess sociodemographic, clinical, and treatment-related factors associated with hyperglycemic crises in adults with type 1 or type 2 diabetes in the US from 2014 to 2020.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study analyzed administrative claims and laboratory results for adults (aged ≥18 years) with type 1 or type 2 diabetes from the OptumLabs Data Warehouse from January 1, 2014, through December 31, 2020.

MAIN OUTCOMES AND MEASURES

Rates of emergency department or hospital visits with a primary diagnosis of DKA or HHS (adjusted for age, sex, race/ethnicity, and region, and for year when calculating annualized rates) were calculated separately for patients with type 1 diabetes and type 2 diabetes. The associations of sociodemographic factors (age, sex, race/ethnicity, region, and income), clinical factors (comorbidities), and treatment factors (glucose-lowering medications, hemoglobin A1c) with DKA or HHS in patients with type 1 or type 2 diabetes were assessed using negative binomial regression.

RESULTS

Among 20 156 adults with type 1 diabetes (mean [SD] age, 46.6 [16.5] years; 51.2% male; 72.6% White race/ethnicity) and 796 382 with type 2 diabetes (mean [SD] age, 65.6 [11.8] years; 50.3% female; 54.4% White race/ethnicity), adjusted rates of hyperglycemic crises were 52.69 per 1000 person-years (95% CI, 48.26-57.12 per 1000 person-years) for type 1 diabetes and 4.04 per 1000 person-years (95% CI, 3.88-4.21 per 1000 person-years) for type 2 diabetes. In both groups, factors associated with the greatest hyperglycemic crisis risk were low income (≥$200 000 vs <$40 000: type 1 diabetes incidence risk ratio [IRR], 0.61 [95% CI, 0.46-0.81]; type 2 diabetes IRR, 0.69 [95% CI, 0.56-0.86]), Black race/ethnicity (vs White race/ethnicity: type 1 diabetes IRR, 1.33 [95% CI, 1.01-1.74]; type 2 diabetes IRR, 1.18 [95% CI, 1.09-1.27]), high hemoglobin A1c level (≥10% vs 6.5%-6.9%: type 1 diabetes IRR, 7.81 [95% CI, 5.78-10.54]; type 2 diabetes IRR, 7.06 [95% CI, 6.26-7.96]), history of hyperglycemic crises (type 1 diabetes IRR, 7.88 [95% CI, 6.06-9.99]; type 2 diabetes IRR, 17.51 [95% CI, 15.07-20.34]), severe hypoglycemia (type 1 diabetes IRR, 2.77 [95% CI, 2.15-3.56]; type 2 diabetes IRR, 4.18 [95% CI, 3.58-4.87]), depression (type 1 diabetes IRR, 1.62 [95% CI, 1.37-1.92]; type 2 diabetes IRR, 1.46 [95% CI, 1.34-1.59]), neuropathy (type 1 diabetes IRR, 1.64 [95% CI, 1.39-1.93]; type 2 diabetes IRR, 1.25 [95% CI, 1.17-1.34]), and nephropathy (type 1 diabetes IRR, 1.22 [95% CI, 1.01-1.48]; type 2 diabetes IRR, 1.23 [95% CI, 1.14-1.33]). Age had a U-shaped association with hyperglycemic crisis risk in patients with type 1 diabetes (compared with patients aged 18-44 years: 45-64 years IRR, 0.72 [95% CI, 0.59-0.87]; 65-74 years IRR, 0.62 [95% CI, 0.47-0.80]; ≥75 years IRR, 0.96 [95% CI, 0.66-1.38]). In type 2 diabetes, risk of hyperglycemic crises decreased progressively with age (45-64 years IRR, 0.57 [95% CI, 0.51-0.63]; 65-74 years IRR, 0.44 [95% CI, .39-0.49]; ≥75 years IRR, 0.41 [95% CI, 0.36-0.47]). In patients with type 2 diabetes, higher risk was associated with sodium-glucose cotransporter 2 inhibitor therapy (IRR, 1.30; 95% CI, 1.14-1.49) and insulin dependency (compared with regimens with bolus insulin: regimens with basal insulin only, IRR, 0.69 [95% CI, 0.63-0.75]; and without any insulin, IRR, 0.36 [95% CI, 0.33-0.40]).

CONCLUSIONS AND RELEVANCE

In this cohort study, younger age, Black race/ethnicity, low income, and poor glycemic control were associated with an increased risk of hyperglycemic crises. The findings suggest that multidisciplinary interventions focusing on groups at high risk for hyperglycemic crises are needed to prevent these dangerous events.