Improving Care for Late-Life Depression Through Partnerships With Community-Based Organizations: Results From the Care Partners Project.

OBJECTIVES: Collaborative care (CC) has demonstrated effectiveness for improving late-life depression in primary care, but clinics offering this service can find it challenging to address unmet social needs that may be contributing to their patients' depression. Clinics may benefit from better coordination and communication with community-based organizations (CBO) to strengthen depression treatment and to address unmet social needs. We evaluated the feasibility of adding a CBO to enhance standard collaborative care and the impact of such partnered care on older adults. DESIGN: Multisite, prepost evaluation. SETTING: Eight (n = 8) partnerships between primary care clinics and community-based organizations in California. PARTICIPANTS: A total of 707 depressed older adults (60 years or older) as evidenced by having a score of 10 or more on the Patient Health Questionnaire (PHQ-9) received care under the Care Partners project. INTERVENTION: A CBO partner was added to augment CC for late-life depression in primary care. MEASUREMENTS: The PHQ-9 was used to identify depressed older adults and to monitor depression symptom severity during a course of care. RESULTS: At baseline, the average PHQ-9 depression score across the partnerships was 15, indicating moderate depression severity. Participating patients saw an average 7-point reduction in their PHQ-9 score, baseline to last score assessed, with nearly half of all participants (48.4%) experiencing a 50% or greater improvement from their baseline score. CONCLUSIONS: Our findings suggest that partnering with a community-based organization is a feasible and effective way for primary care clinics to address late-life depression in their patients.

Air pollution and the sequelae of COVID-19 patients: A multistate analysis.

IMPORTANCE: Recent evidence links air pollution to the severity COVID-19 symptoms and to death from the disease. To date, however, few studies have assessed whether air pollution affects the sequelae to more severe states or recovery from COVID-19 in a cohort with individual data. OBJECTIVE: To assess how air pollution affects the transition to more severe COVID-19 states or to recovery from COVID-19 infection in a cohort with detailed patient information. DESIGN AND OUTCOMES: We used a cohort design that followed patients admitted to hospital in the Kaiser Permanente Southern California (KPSC) Health System, which has 4.7 million members with characteristics similar to the general population. Enrollment began on 06/01/2020 and ran until 01/30/2021 for all patients admitted to hospital while ill with COVID-19. All possible states of sequelae were considered, including deterioration to intensive care, to death, discharge to recovery, or discharge to death. Transition risks were estimated with a multistate model. We assessed exposure using chemical transport model that predicted ambient concentrations of nitrogen dioxide, ozone, and fine particulate matter (PM2.5) at a 1 km scale. RESULTS: Each increase in PM2.5 concentration equivalent to the interquartile range was associated with increased risk of deterioration to intensive care (HR of 1.16; 95% CI: 1.12-1.20) and deterioration to death (HR of 1.11; 95% CI: 1.04-1.17). Results for ozone were consistent with PM2.5 effects, but ozone also affected the transition from recovery to death: HR of 1.24 (95% CI: 1.01-1.51). NO2 had weaker effects but displayed some elevated risks. CONCLUSIONS: PM2.5 and ozone were significantly associated with transitions to more severe states while in hospital and to death after discharge from hospital. Reducing air pollution could therefore lead to improved prognosis for COVID-19 patients and a sustainable means of reducing the health impacts of coronaviruses now and in the future.

Trends in firearm injury in a southern California health care system from 2010 to 2020.

BACKGROUND: Firearm injury is a significant public health concern in the United States. METHODS: Data on fatal and nonfatal firearm injuries were obtained from a cohort of N = 7,473,650 members of Kaiser Permanente Southern California, a large integrated healthcare system between 2010 and 2020. Age-adjusted rates of combined fatal and nonfatal firearm injury per 100,000 members were calculated by year, with the 2010 US census as the reference population. Trends were evaluated using Poisson or negative binomial regression. RESULTS: There was an increasing trend in overall firearm injuries between 2010 and 2020 among adults in this large integrated healthcare system (p < .0001), primarily driven by non-self-inflicted firearm injuries (p < .0001). Self-inflicted injuries decreased during this time (p = .01). Injuries among youth showed no significant change. CONCLUSION: There was an increasing trend in firearm injuries between 2010 and 2020 among adults in this large integrated healthcare system, primarily driven by non-self-inflicted firearm injuries; however, self-inflicted injuries decreased during this time. Injuries among youth showed no significant change.

Association Between Financial Distress with Patient and Caregiver Outcomes in Home-Based Palliative Care: A Secondary Analysis of a Clinical Trial.

BACKGROUND: Serious illness often causes financial hardship for patients and families. Home-based palliative care (HBPC) may partly address this. OBJECTIVE: Describe the prevalence and characteristics of patients and family caregivers with high financial distress at HBPC admission and examine the relationship between financial distress and patient and caregiver outcomes. DESIGN, SETTINGS, AND PARTICIPANTS: Data for this cohort study were drawn from a pragmatic comparative-effectiveness trial testing two models of HBPC in Kaiser Permanente. We included 779 patients and 438 caregivers from January 2019 to January 2020. MEASUREMENTS: Financial distress at admission to HBPC was measured using a global question (0-10-point scale: none=0; mild=1-5; moderate/severe=6+). Patient- (Edmonton Symptom Assessment Scale, distress thermometer, PROMIS-10) and caregiver (Preparedness for Caregiving, Zarit-12 Burden, PROMIS-10)-reported outcomes were measured at baseline and 1 month. Hospital utilization was captured using electronic medical records and claims. Mixed-effects adjusted models assessed survey measures and a proportional hazard competing risk model assessed hospital utilization. RESULTS: Half of the patients reported some level of financial distress with younger patients more likely to have moderate/severe financial distress. Patients with moderate/severe financial distress at HBPC admission reported worse symptoms, general distress, and quality of life (QoL), and caregivers reported worse preparedness, burden, and QoL (all, p<.001). Compared to patients with no financial distress, moderate/severe financial distress patients had more social work contacts, improved symptom burden at 1 month (ESAS total score: -4.39; 95% CI: -7.61, -1.17; p<.01), and no increase in hospital-based utilization (adjusted hazard ratio: 1.11; 95% CI: 0.87-1.40; p=.41); their caregivers had improved PROMIS-10 mental scores (+2.68; 95% CI: 0.20, 5.16; p=.03). No other group differences were evident in the caregiver preparedness, burden, and physical QoL change scores. CONCLUSION: These findings highlight the importance and need for routine assessments of financial distress and for provision of social supports required to help families receiving palliative care services.

Social Risk Factors and Desire for Assistance Among Patients Receiving Subsidized Health Care Insurance in a US-Based Integrated Delivery System.

PURPOSE: Because social conditions such as food insecurity and housing instability shape health outcomes, health systems are increasingly screening for and addressing patients' social risks. This study documented the prevalence of social risks and examined the desire for assistance in addressing those risks in a US-based integrated delivery system. METHODS: A survey was administered to Kaiser Permanente members on subsidized exchange health insurance plans (2018-2019). The survey included questions about 4 domains of social risks, desire for help, and attitudes. We conducted a descriptive analysis and estimated multivariate modified Poisson regression models. RESULTS: Of 438 participants, 212 (48%) reported at least 1 social risk factor. Housing instability was the most common (70%) factor reported. Members with social risks reported more discomfort being screened for social risks (14.2% vs 5.4%; P = .002) than those without risks, although 90% of participants believed that health systems should assist in addressing social risks. Among those with 1-2 social risks, however, only 27% desired assistance. Non-Hispanic Black participants who reported a social risk were more than twice as likely to desire assistance compared with non-Hispanic White participants (adjusted relative risk [RR] 2.2; 95% CI, 1.3-3.8). CONCLUSIONS: Athough most survey participants believed health systems have a role in addressing social risks, a minority of those reporting a risk wanted assistance and reported more discomfort being screened for risk factors than those without risks. Health systems should work to increase the comfort of patients in reporting risks, explore how to successfully assist them when desired, and offer resources to address these risks outside the health care sector.VISUAL ABSTRACT.

Longitudinal trajectories of adiposity-related measures from age 2-5 years in a population of low-income Hispanic children.

BACKGROUND: We estimated longitudinal trajectories of body mass index (BMI) z-score and percentile, weight for height (WFH) z-score and percentile, and percentage of the 95th BMI percentile (BMIp95) among low-income Hispanic children ages 2-5 years to provide normative data for this population and compare the behavior of different measures. METHODS: Longitudinal height and weight measurements obtained from 18,072 Hispanic children aged 2-5 years enrolled in the Special Supplemental Nutrition Program for Women, Infants and Children in Los Angeles County were analyzed. Trajectories of adiposity-related measures were estimated using mixed models, stratified by sex and BMI percentile at age 2 years. RESULTS: For children in the 5th-85th BMI percentile at age 2 years, all adiposity-related measures rose during ages 2-3.5 years; during ages 3.5-5 years, BMI-based measures increased, BMIp95 decreased, and WFH-based measures were stable. For children exceeding the 85th BMI percentile at age 2 years, measures generally trended downward during ages 2-5 years, except for BMIp95, which had variable trends. CONCLUSIONS: Adiposity measures changed at different rates as children grew during ages 2-3.5 years compared to ages 3.5-5 years, and different measures displayed different trends. Studies should consider examining multiple measures and focusing on change relative to a comparison group. IMPACT: To address the childhood obesity epidemic, information on normative trajectories of adiposity-related measures in at-risk populations of young children is needed. Longitudinal analysis of data collected from low-income Hispanic children during ages 2-5 years revealed different patterns for different adiposity measures and for ages 2-3.5 years versus 3.5-5 years. Child obesity studies should consider examining multiple adiposity measures and focus on change relative to a comparison group to avoid misinterpreting longitudinal patterns.

Identifying patients with symptoms suspicious for COVID-19 at elevated risk of adverse events: The COVAS score.

OBJECTIVE: Develop and validate a risk score using variables available during an Emergency Department (ED) encounter to predict adverse events among patients with suspected COVID-19. METHODS: A retrospective cohort study of adult visits for suspected COVID-19 between March 1 - April 30, 2020 at 15 EDs in Southern California. The primary outcomes were death or respiratory decompensation within 7-days. We used least absolute shrinkage and selection operator (LASSO) models and logistic regression to derive a risk score. We report metrics for derivation and validation cohorts, and subgroups with pneumonia or COVID-19 diagnoses. RESULTS: 26,600 ED encounters were included and 1079 experienced an adverse event. Five categories (comorbidities, obesity/BMI ≥ 40, vital signs, age and sex) were included in the final score. The area under the curve (AUC) in the derivation cohort was 0.891 (95% CI, 0.880-0.901); similar performance was observed in the validation cohort (AUC = 0.895, 95% CI, 0.874-0.916). Sensitivity ranging from 100% (Score 0) to 41.7% (Score of ≥15) and specificity from 13.9% (score 0) to 96.8% (score ≥ 15). In the subgroups with pneumonia (n = 3252) the AUCs were 0.780 (derivation, 95% CI 0.759-0.801) and 0.832 (validation, 95% CI 0.794-0.870), while for COVID-19 diagnoses (n = 2059) the AUCs were 0.867 (95% CI 0.843-0.892) and 0.837 (95% CI 0.774-0.899) respectively. CONCLUSION: Physicians evaluating ED patients with pneumonia, COVID-19, or symptoms suspicious for COVID-19 can apply the COVAS score to assist with decisions to hospitalize or discharge patients during the SARS CoV-2 pandemic.

Obesity and Mortality Among Patients Diagnosed With COVID-19: Results From an Integrated Health Care Organization.

BACKGROUND: Obesity, race/ethnicity, and other correlated characteristics have emerged as high-profile risk factors for adverse coronavirus disease 2019 (COVID-19)-associated outcomes, yet studies have not adequately disentangled their effects. OBJECTIVE: To determine the adjusted effect of body mass index (BMI), associated comorbidities, time, neighborhood-level sociodemographic factors, and other factors on risk for death due to COVID-19. DESIGN: Retrospective cohort study. SETTING: Kaiser Permanente Southern California, a large integrated health care organization. PATIENTS: Kaiser Permanente Southern California members diagnosed with COVID-19 from 13 February to 2 May 2020. MEASUREMENTS: Multivariable Poisson regression estimated the adjusted effect of BMI and other factors on risk for death at 21 days; models were also stratified by age and sex. RESULTS: Among 6916 patients with COVID-19, there was a J-shaped association between BMI and risk for death, even after adjustment for obesity-related comorbidities. Compared with patients with a BMI of 18.5 to 24 kg/m2, those with BMIs of 40 to 44 kg/m2 and greater than 45 kg/m2 had relative risks of 2.68 (95% CI, 1.43 to 5.04) and 4.18 (CI, 2.12 to 8.26), respectively. This risk was most striking among those aged 60 years or younger and men. Increased risk for death associated with Black or Latino race/ethnicity or other sociodemographic characteristics was not detected. LIMITATION: Deaths occurring outside a health care setting and not captured in membership files may have been missed. CONCLUSION: Obesity plays a profound role in risk for death from COVID-19, particularly in male patients and younger populations. Our capitated system with more equalized health care access may explain the absence of effect of racial/ethnic and socioeconomic disparities on death. Our data highlight the leading role of severe obesity over correlated risk factors, providing a target for early intervention. PRIMARY FUNDING SOURCE: Roche-Genentech.

Generalizability of an Automatic Explanation Method for Machine Learning Prediction Results on Asthma-Related Hospital Visits in Patients With Asthma: Quantitative Analysis.

BACKGROUND: Asthma exerts a substantial burden on patients and health care systems. To facilitate preventive care for asthma management and improve patient outcomes, we recently developed two machine learning models, one on Intermountain Healthcare data and the other on Kaiser Permanente Southern California (KPSC) data, to forecast asthma-related hospital visits, including emergency department visits and hospitalizations, in the succeeding 12 months among patients with asthma. As is typical for machine learning approaches, these two models do not explain their forecasting results. To address the interpretability issue of black-box models, we designed an automatic method to offer rule format explanations for the forecasting results of any machine learning model on imbalanced tabular data and to suggest customized interventions with no accuracy loss. Our method worked well for explaining the forecasting results of our Intermountain Healthcare model, but its generalizability to other health care systems remains unknown. OBJECTIVE: The objective of this study is to evaluate the generalizability of our automatic explanation method to KPSC for forecasting asthma-related hospital visits. METHODS: Through a secondary analysis of 987,506 data instances from 2012 to 2017 at KPSC, we used our method to explain the forecasting results of our KPSC model and to suggest customized interventions. The patient cohort covered a random sample of 70% of patients with asthma who had a KPSC health plan for any period between 2015 and 2018. RESULTS: Our method explained the forecasting results for 97.57% (2204/2259) of the patients with asthma who were correctly forecasted to undergo asthma-related hospital visits in the succeeding 12 months. CONCLUSIONS: For forecasting asthma-related hospital visits, our automatic explanation method exhibited an acceptable generalizability to KPSC. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/resprot.5039.

Identifying Financially Sustainable Pricing Interventions to Promote Healthier Beverage Purchases in Small Neighborhood Stores.

INTRODUCTION: Residents of low-income communities often purchase sugar-sweetened beverages (SSBs) at small, neighborhood "corner" stores. Lowering water prices and increasing SSB prices are potentially complementary public health strategies to promote more healthful beverage purchasing patterns in these stores. Sustainability, however, depends on financial feasibility. Because in-store pricing experiments are complex and require retailers to take business risks, we used a simulation approach to identify profitable pricing combinations for corner stores. METHODS: The analytic approach was based on inventory models, which are suitable for modeling business operations. We used discrete-event simulation to build inventory models that use data representing beverage inventory, wholesale costs, changes in retail prices, and consumer demand for 2 corner stores in Baltimore, Maryland. Model outputs yielded ranges for water and SSB prices that increased water demand without loss of profit from combined water and SSB sales. RESULTS: A 20% SSB price increase allowed lowering water prices by up to 20% while maintaining profit and increased water demand by 9% and 14%, for stores selling SSBs in 12-oz cans and 16- to 20-oz bottles, respectively. Without changing water prices, profits could increase by 4% and 6%, respectively. Sensitivity analysis showed that stores with a higher volume of SSB sales could reduce water prices the most without loss of profit. CONCLUSION: Various combinations of SSB and water prices could encourage water consumption while maintaining or increasing store owners' profits. This model is a first step in designing and implementing profitable pricing strategies in collaboration with store owners.

Hispanic-White Differences in Lifespan Variability in the United States.

This study is the first to investigate whether and, if so, why Hispanics and non-Hispanic whites in the United States differ in the variability of their lifespans. Although Hispanics enjoy higher life expectancy than whites, very little is known about how lifespan variability-and thus uncertainty about length of life-differs by race/ethnicity. We use 2010 U.S. National Vital Statistics System data to calculate lifespan variance at ages 10+ for Hispanics and whites, and then decompose the Hispanic-white variance difference into cause-specific spread, allocation, and timing effects. In addition to their higher life expectancy relative to whites, Hispanics also exhibit 7 % lower lifespan variability, with a larger gap among women than men. Differences in cause-specific incidence (allocation effects) explain nearly two-thirds of Hispanics' lower lifespan variability, mainly because of the higher mortality from suicide, accidental poisoning, and lung cancer among whites. Most of the remaining Hispanic-white variance difference is due to greater age dispersion (spread effects) in mortality from heart disease and residual causes among whites than Hispanics. Thus, the Hispanic paradox-that a socioeconomically disadvantaged population (Hispanics) enjoys a mortality advantage over a socioeconomically advantaged population (whites)-pertains to lifespan variability as well as to life expectancy. Efforts to reduce U.S. lifespan variability and simultaneously increase life expectancy, especially for whites, should target premature, young adult causes of death-in particular, suicide, accidental poisoning, and homicide. We conclude by discussing how the analysis of Hispanic-white differences in lifespan variability contributes to our understanding of the Hispanic paradox.

Using a computational model to quantify the potential impact of changing the placement of healthy beverages in stores as an intervention to "Nudge" adolescent behavior choice.

BACKGROUND: Product placement influences consumer choices in retail stores. While sugar sweetened beverage (SSB) manufacturers expend considerable effort and resources to determine how product placement may increase SSB purchases, the information is proprietary and not available to the public health and research community. This study aims to quantify the effect of non-SSB product placement in corner stores on adolescent beverage purchasing behavior. Corner stores are small privately owned retail stores that are important beverage providers in low-income neighborhoods--where adolescents have higher rates of obesity. METHODS: Using data from a community-based survey in Baltimore and parameters from the marketing literature, we developed a decision-analytic model to simulate and quantify how placement of healthy beverage (placement in beverage cooler closest to entrance, distance from back of the store, and vertical placement within each cooler) affects the probability of adolescents purchasing non-SSBs. RESULTS: In our simulation, non-SSB purchases were 2.8 times higher when placed in the "optimal location"--on the second or third shelves of the front cooler--compared to the worst location on the bottom shelf of the cooler farthest from the entrance. Based on our model results and survey data, we project that moving non-SSBs from the worst to the optional location would result in approximately 5.2 million more non-SSBs purchased by Baltimore adolescents annually. CONCLUSIONS: Our study is the first to quantify the potential impact of changing placement of beverages in corner stores. Our findings suggest that this could be a low-cost, yet impactful strategy to nudge this population--highly susceptible to obesity--towards healthier beverage decisions.

Why the racial gap in life expectancy is declining in the United States.

BACKGROUND: Blacks have lower life expectancy than whites in the United States. That disparity could be due to racial differences in the causes of death, with blacks being more likely to die of causes that affect the young, or it could be due to differences in the average ages of blacks and whites who die of the same cause. Prior studies fail to distinguish these two possibilities. OBJECTIVE: In this study we determine how much of the 2000-10 reduction in the racial gap in life expectancy resulted from narrowing differences in the cause-specific mean age at death for blacks and whites, as opposed to changing cause-specific probabilities for blacks and whites. METHOD: We introduce a method for separating the difference-in-probabilities and difference-inage components of group disparities in life expectancy. RESULTS: Based on the new method, we find that 60% of the decline in the racial gap in life expectancy from 2000 to 2010 was attributable to reduction in the age component, largely because of declining differences in the age at which blacks and whites die of chronic diseases. CONCLUSION: Our findings shed light on the sources of the declining racial gap in life expectancy in the United States, and help to identify where advances need to be made to achieve the goal of eliminating racial disparities in life expectancy.

Neighborhood factors associated with late effects among survivors of adolescent and young adult cancer.

PURPOSE: The purpose of this study is to evaluate the associations between neighborhood income, education, and neighborhood racial composition (measured as a low percentage of white residents) and risk of developing cardiovascular diseases (CVD), diabetes (DM), and severe depression among survivors of AYA cancer and matched non-cancer peers. METHODS: Two-year survivors of AYA cancers diagnosed at age 15-39 yrs at Kaiser Permanente Southern California (diagnosed 2000-2012) and individually matched (1:13) non-cancer subjects were included. The development of CVD, DM, and severe depression was ascertained via electronic health records. Neighborhood characteristics were obtained from census-based geocoded data. Cox regression evaluated associations between neighborhood characteristics and the health outcomes of interest among both the cancer survivors and the non-cancer comparison cohort and effect modification by cancer survivor status on these relationships. RESULTS: Among cancer survivors (n = 6774), living in mostly non-white neighborhoods, was associated with risk of CVD (hazard ratio (HR) = 1.54 (95% CI 1.00-2.36)), while lower education level (HR = 1.41 (95% CI 1.02-1.94)) was associated with risk of severe depression. None of the neighborhood characteristics were associated with risk of DM. Effect modification was found for neighborhood education and risk of DM and severe depression. CONCLUSION: When jointly considered, cancer survivors who resided in the most disadvantaged neighborhoods were at the highest risk of developing these health outcomes compared to other subgroups. IMPLICATIONS FOR CANCER SURVIVORS: Our findings may inform screening strategy and addressing social determinants of health among AYA cancer survivors.

Rationale and design of the KP ENRICH trial: A food is medicine intervention in low-income high-risk adults with diabetes within Kaiser Permanente.

BACKGROUND: Food insecurity is associated with poor glycemic control and increased risk for diabetes-related complications. The clinical benefit of addressing these challenges through a medically supportive grocery prescription (GRx) program in patients with type 2 diabetes mellitus (T2D) remains unclear. We report the aims and design of a randomized clinical trial to evaluate the effectiveness of a 6-month GRx intervention on hemoglobin A1c (HbA1c) levels among low-income adults with T2D. METHODS: The Kaiser Permanente Evaluating Nutritional Interventions in Food-Insecure High-Risk Adults (KP ENRICH) Study is a pragmatic randomized trial enrolling 1100 participants within Kaiser Permanente Northern California and Southern California, two integrated health care delivery systems serving >9 million members. Medicaid-insured adults with T2D and baseline HbA1c ≥7.5% will be randomized at a 1:1 ratio to either GRx, delivered as $100 per month for select items from among a curated list of healthful food groups in an online grocery ordering and home-delivery platform along with biweekly digital nutrition educational materials, or control, consisting of free membership and deliveries from the online grocery platform but without curated food groups or purchasing dollars. The primary outcome is 6-month change in HbA1c. Secondary outcomes include 12-month change in HbA1c, and 6- and 12-month change in medical resource utilization, food security, nutrition security, dietary habits, diabetes-related quality of life, and dietary self-efficacy. CONCLUSIONS: The results of this large randomized clinical trial of GRx will help inform future policy and health system-based initiatives to improve food and nutrition security, disease management, and health equity among patients with T2D.

Associations of Physical Inactivity and COVID-19 Outcomes Among Subgroups.

INTRODUCTION: Physical activity before COVID-19 infection is associated with less severe outcomes. The study determined whether a dose‒response association was observed and whether the associations were consistent across demographic subgroups and chronic conditions. METHODS: A retrospective cohort study of Kaiser Permanente Southern California adult patients who had a positive COVID-19 diagnosis between January 1, 2020 and May 31, 2021 was created. The exposure was the median of at least 3 physical activity self-reports before diagnosis. Patients were categorized as follows: always inactive, all assessments at 10 minutes/week or less; mostly inactive, median of 0-60 minutes per week; some activity, median of 60-150 minutes per week; consistently active, median>150 minutes per week; and always active, all assessments>150 minutes per week. Outcomes were hospitalization, deterioration event, or death 90 days after a COVID-19 diagnosis. Data were analyzed in 2022. RESULTS: Of 194,191 adults with COVID-19 infection, 6.3% were hospitalized, 3.1% experienced a deterioration event, and 2.8% died within 90 days. Dose‒response effects were strong; for example, patients in the some activity category had higher odds of hospitalization (OR=1.43; 95% CI=1.26, 1.63), deterioration (OR=1.83; 95% CI=1.49, 2.25), and death (OR=1.92; 95% CI=1.48, 2.49) than those in the always active category. Results were generally consistent across sex, race and ethnicity, age, and BMI categories and for patients with cardiovascular disease or hypertension. CONCLUSIONS: There were protective associations of physical activity for adverse COVID-19 outcomes across demographic and clinical characteristics. Public health leaders should add physical activity to pandemic control strategies.

Air pollution and meteorology as risk factors for COVID-19 death in a cohort from Southern California.

BACKGROUND: Recent evidence links ambient air pollution to COVID-19 incidence, severity, and death, but few studies have analyzed individual-level mortality data with high quality exposure models. METHODS: We sought to assess whether higher air pollution exposures led to greater risk of death during or after hospitalization in confirmed COVID-19 cases among patients who were members of the Kaiser Permanente Southern California (KPSC) healthcare system (N=21,415 between 06-01-2020 and 01-31-2022 of whom 99.85 % were unvaccinated during the study period). We used 1 km resolution chemical transport models to estimate ambient concentrations of several common air pollutants, including ozone, nitrogen dioxide, and fine particle matter (PM2.5). We also derived estimates of pollutant exposures from ultra-fine particulate matter (PM0.1), PM chemical species, and PM sources. We employed Cox proportional hazards models to assess associations between air pollution exposures and death from COVID-19 among hospitalized patients. FINDINGS: We found significant associations between COVID-19 death and several air pollution exposures, including: PM2.5 mass, PM0.1 mass, PM2.5 nitrates, PM2.5 elemental carbon, PM2.5 on-road diesel, and PM2.5 on-road gasoline. Based on the interquartile (IQR) exposure increment, effect sizes ranged from hazard ratios (HR) = 1.12 for PM2.5 mass and PM2.5 nitrate to HR âˆ¼ 1.06-1.07 for other species or source markers. Humidity and temperature in the month of diagnosis were also significant negative predictors of COVID-19 death and negative modifiers of the air pollution effects. INTERPRETATION: Air pollution exposures and meteorology were associated the risk of COVID-19 death in a cohort of patients from Southern California. These findings have implications for prevention of death from COVID-19 and for future pandemics.

Factors Associated With Firearm Injury Among Pediatric Members of a Large Integrated Healthcare System.

BACKGROUND AND OBJECTIVES: Few studies have tested multiple socio-ecological risk factors assocated with firearm injury among pediatric populations and distinguished self-inflicted from non-self-inflicted injury. To address this gap, the current study examined demographic, individual psychosocial, and neighborhood variables as risk factors for firearm injury among a large cohort of children and adolescents. METHODS: Retrospective cohort study. Data were obtained from the electronic health records of a large integrated healthcare system. The cohort included children <18 years with at least one clinical encounter between January 1, 2010 and December 31, 2018. Poisson regression was used to examine demographic (age, gender, race and ethnicity, Medicaid status), psychosocial (depression, substance use disorder, medical comorbidities), and neighborhood education variables as potential risk factors for non-self-inflicted and self-inflicted firearm injuries. RESULTS: For non-self-inflicted injury, the highest relative risk was found for children age 12-17 years old compared to 0-5 year olds (RR = 37.57); other risk factors included male gender, Black and Hispanic race and ethnicity (compared to White race), being a Medicaid recipient, lower neighborhood education, and substance use disorder diagnosis. For self-inflicted injury, only age 12-17 years old and male gender were associated with increased risk. CONCLUSIONS: These results reinforce the established higher risk for firearm injury among adolescent males, highlight differences between self-inflicted and non-self-inflicted injuries, and the need to consider demographic, psychosocial, and neighborhood variables as risk factors to inform interventions aimed to reduce firearm injuries among children and adolescents.