Simulating the impact of greenspace exposure on metabolic biomarkers in a diverse population living in San Diego, California: A g-computation application.

Introduction: Growing evidence exists that greenspace exposure can reduce metabolic syndrome risk, a growing public health concern with well-documented inequities across population subgroups. We capitalize on the use of g-computation to simulate the influence of multiple possible interventions on residential greenspace on nine metabolic biomarkers and metabolic syndrome in adults (N = 555) from the 2014-2017 Community of Mine Study living in San Diego County, California. Methods: Normalized difference vegetation index (NDVI) exposure from 2017 was averaged across a 400-m buffer around the participants' residential addresses. Participants' fasting plasma glucose, total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglyceride concentrations, systolic and diastolic blood pressure, hemoglobin A1c (%), waist circumference, and metabolic syndrome were assessed as outcomes of interest. Using parametric g-computation, we calculated risk differences for participants being exposed to each decile of the participant NDVI distribution compared to minimum NDVI. Differential health impacts from NDVI exposure by sex, ethnicity, income, and age were examined. Results: We found that a hypothetical increase in NDVI exposure led to a decrease in hemoglobin A1c (%), glucose, and high-density lipoprotein cholesterol concentrations, an increase in fasting total cholesterol, low-density lipoprotein cholesterol, and triglyceride concentrations, and minimal changes to systolic and diastolic blood pressure, waist circumference, and metabolic syndrome. The impact of NDVI changes was greater in women, Hispanic individuals, and those under 65 years old. Conclusions: G-computation helps to simulate the potential health benefits of differential NDVI exposure and identifies which subpopulations can benefit most from targeted interventions aimed at minimizing health disparities.

Movement- and Posture-based Measures of Sedentary Patterns and Associations with Metabolic Syndrome in Hispanic/Latino and non-Hispanic Adults.

BACKGROUND: Sedentary behavior has been identified as a significant risk factor for Metabolic Syndrome (MetS). However, it is unclear if the sedentary pattern measurement approach (posture vs. movement) impacts observed associations or if associations differ for Hispanic/Latino communities, who have higher risk of MetS. METHODS: Participants from the Community of Mine (CoM) study (N = 602) wore hip-based accelerometers for 14 days and completed MetS-associated biomarker assessment (triglycerides, blood pressure, fasting glucose, HDL cholesterol, waist circumference). Sedentary patterns were classified using both cutpoints (movement-based) and the Convolutional Neural Network Hip Accelerometer Posture (CHAP) algorithm (posture-based). We used logistic regression to estimate associations between MetS with sedentary patterns overall and stratified by Hispanic/Latino ethnicity. RESULTS: CHAP and cutpoint sedentary patterns were consistently associated with MetS. When controlling for total sedentary time and moderate to vigorous physical activity, only CHAP-measured median sedentary bout duration (OR = 1.15, CI: 1.04, 1.28) was significant. In stratified analysis, CHAP-measured median bout duration and time spent in sedentary bouts ≥ 30 min were each associated with increased odds of MetS, but the respective associations were stronger for Hispanic/Latino ethnicity (OR = 1.71 and 1.48; CI = 1.28-2.31 and 1.12-1.98) than for non-Hispanic/Latino ethnicity (OR = 1.43 and 1.40; CI = 1.10-1.87 and 1.06-1.87). CONCLUSIONS: The way sedentary patterns are measured can impact the strength and precision of associations with MetS. These differences may be larger in Hispanic/Latino ethnic groups and warrants further research to inform sedentary behavioral interventions in these populations.

Profile of Sensory Integration Disorders in Migraine Patients-New Perspectives of Therapy.

Background: The involvement of sensory integration disorders in the pathophysiology of migraine has been suggested. This study aims to analyze the relationship between symptoms of sensory integration disorders and migraine in a broad scope, including all sensory domains, and examine its impact on migraine attacks. Methods: The study included 372 people diagnosed with migraine. The Daniel Travis Questionnaire was used to assess symptoms of sensory integration disorders and their severity across six domains. The relationships between the severity of these symptoms and headache features, as well as accompanying headache symptoms, were the subject of statistical analysis. Results: Current impairment in all sensory domains was significantly associated with headaches exacerbated by everyday life activities. A significant inverse relationship was found between the occurrence of throbbing headaches and symptoms of sensory integration disorders in terms of current sensory discrimination, current motor skills, and current emotional/social skills. Past under-responsiveness and past disturbances in emotional/social abilities were significantly associated with migraine aura. Conclusions: The severity of symptoms of sensory integration disorders affects the clinical picture of migraine. The significant association between migraine and emotional/social disorders, as well as under-responsiveness in the past, needs further research to assess whether this is a cause-and-effect relationship. There is a need for in-depth diagnostics of sensory integration disorders in migraine patients, which could be an additional target of their therapy.

Dietary Acculturation Is Associated With Altered Gut Microbiome, Circulating Metabolites, and Cardiovascular Disease Risk in US Hispanics and Latinos: Results From HCHS/SOL.

BACKGROUND: Dietary acculturation, or adoption of dominant culture diet by migrant groups, influences human health. We aimed to examine dietary acculturation and its relationships with cardiovascular disease (CVD), gut microbiota, and blood metabolites among US Hispanic and Latino adults. METHODS: In the HCHS/SOL (Hispanic Community Health Study/Study of Latinos), US exposure was defined by years in the United States (50 states and Washington, DC) and US nativity. A dietary acculturation pattern was derived from 14 172 participants with two 24-hour dietary recalls at baseline (2008-2011) using least absolute shrinkage and selection operator regression, with food groups as predictors of US exposure. We evaluated associations of dietary acculturation with incident CVD across ≈7 years of follow-up (n=211/14 172 cases/total) and gut microbiota (n=2349; visit 2, 2014 to 2017). Serum metabolites associated with both dietary acculturation-related gut microbiota (n=694) and incident CVD (n=108/5256 cases/total) were used as proxy measures to assess the association of diet-related gut microbiome with incident CVD. RESULTS: We identified an empirical US-oriented dietary acculturation score that increased with US exposure. Higher dietary acculturation score was associated with higher risk of incident CVD (hazard ratio per SD, 1.33 [95% CI, 1.13-1.57]), adjusted for sociodemographic, lifestyle, and clinical factors. Sixty-nine microbial species (17 enriched from diverse species, 52 depleted mainly from fiber-utilizing Clostridia and Prevotella species) were associated with dietary acculturation, driven by lower intakes of whole grains, beans, and fruits and higher intakes of refined grains. Twenty-five metabolites, involved predominantly in fatty acid and glycerophospholipid metabolism (eg, branched-chain 14:0 dicarboxylic acid** and glycerophosphoethanolamine), were associated with both diet acculturation-related gut microbiota and incident CVD. Proxy association analysis based on these metabolites suggested a positive relationship between diet acculturation-related microbiome and risk of CVD (r=0.70, P<0.001). CONCLUSIONS: Among US Hispanic and Latino adults, greater dietary acculturation was associated with elevated CVD risk, possibly through alterations in gut microbiota and related metabolites. Diet and microbiota-targeted interventions may offer opportunities to mitigate CVD burdens of dietary acculturation.

Combined impact of dynamic air pollution and transportation noise on cardiometabolic disorders in San Diego County.

Air pollution and noise exposure may synergistically contribute to increased cardiometabolic disorders; however, few studies have examined this potential interaction nor considered exposures beyond residential location. This study investigates the combined impact of dynamic air pollution and transportation noise on cardiometabolic disorders in San Diego County. Using the Community of Mine Study (2014-2017), 602 ethnically diverse participants were assessed for obesity, dyslipidemia, hypertension, and metabolic syndrome (MetS) using anthropometric measurements and biomarkers from blood samples. Time-weighted measures of exposure to PM2.5, NO2, road and aircraft noise were calculated using global positioning system (GPS) mobility data and Kernel Density Estimation. Generalized estimating equation models were used to analyze associations. Interactions were assessed on the multiplicative and additive scales using relative excess risk due to interaction (RERI). We found that air pollution and noise interact to affect metabolic disorders on both multiplicative and additive scales. The effect of noise on obesity and MetS was higher when air pollution was higher. The RERI of aircraft noise and NO2 on obesity and MetS were 0.13 (95%CI 0.03, 0.22) and 0.13 (95%CI 0.02, 0.25), respectively. This finding suggests that aircraft noise and air pollution may have synergistic effects on obesity and MetS.

Assessment of Skin Autofluorescence and Its Association with Glycated Hemoglobin, Cardiovascular Risk Markers, and Concomitant Chronic Diseases in Children with Type 1 Diabetes.

Skin autofluorescence (sAF) measurement is a non-invasive method used to assess tissue advanced glycation end product (AGE) accumulation. This study aims to characterize sAF's association with (1) glycated hemoglobin (HbA1c) values, (2) cardiovascular risk markers, and (3) common comorbidities (autoimmune thyroiditis, celiac disease) in children with type 1 diabetes (T1D). MATERIALS AND METHODS: A total of 348 children with T1D aged 3-18 years and 85 age- and gender-matched control subjects were enrolled. sAF was quantified using an AGE Reader (Diagnoptics BV, The Netherlands). The analysis covered HbA1c, blood lipid, and C-reactive protein (CRP) levels, ambulatory blood pressure monitoring records, and body composition parameters. The associations between variables and sAF were assessed using the Mann-Whitney U test and Spearman correlation. RESULTS: We observed significantly higher sAF values in the T1D group compared to the control (1.40 [1.27-1.53] vs. 1.20 [1.07-1.30, AU]; p = 0.004), consistent across all tested age groups. In the T1D group, sAF was positively correlated with current HbA1c, mean of historical HbA1c values, and T1D duration (r values, respectively: 0.27, 0.22, 0.14, all p < 0.01). Percentage of body fat was positively correlated with sAF (r = 0.120; p = 0.044). No significant correlations were found between sAF and lipid fractions, Z-score of BMI, parameters from 24 h ambulatory blood pressure monitoring, or the amount of albumin excreted in urine. sAF was positively correlated with CRP (r = 0.17, p < 0.05). sAF was significantly higher in patients with concomitant celiac disease (1.53 [1.43-1.63] vs. 1.40 [1.27-1.53, AU], p = 0.001). CONCLUSION: Among young T1D patients with relatively brief diabetes duration, sAF effectively mirrors prior glycemic control, as presented by historical average HbA1c. However, associations with conventional CV risk markers are not evident. The higher sAF values in patients with celiac disease warrant further exploration.

Sex and adrenal hormones in association with insecticide biomarkers among adolescents living in ecuadorian agricultural communities.

BACKGROUND: Organophosphate, pyrethroid, and neonicotinoid insecticides have resulted in adrenal and gonadal hormone disruption in animal and in vitro studies; limited epidemiologic evidence exists in humans. We assessed relationships of urinary insecticide metabolite concentrations with adrenal and gonadal hormones in adolescents living in Ecuadorean agricultural communities. METHODS: In 2016, we examined 522 Ecuadorian adolescents (11-17y, 50.7% female, 22% Indigenous; ESPINA study). We measured urinary insecticide metabolites, blood acetylcholinesterase activity (AChE), and salivary testosterone, dehydroepiandrosterone (DHEA), 17ß-estradiol, and cortisol. We used general linear models to assess linear (ß = % hormone difference per 50% increase of metabolite concentration) and curvilinear relationships (ß2 = hormone difference per unit increase in squared ln-metabolite) between ln-metabolite or AChE and ln-hormone concentrations, stratified by sex, adjusting for anthropometric, demographic, and awakening response variables. Bayesian Kernel Machine Regression was used to assess non-linear associations and interactions. RESULTS: The organophosphate metabolite malathion dicarboxylic acid (MDA) had positive associations with testosterone (ßboys = 5.88% [1.21%, 10.78%], ßgirls = 4.10% [-0.02%, 8.39%]), and cortisol (ßboys = 6.06 [-0.23%, 12.75%]. Para-nitrophenol (organophosphate) had negatively-trending curvilinear associations, with testosterone (ß2boys = -0.17 (-0.33, -0.003), p = 0.04) and DHEA (ß2boys = -0.49 (-0.80, -0.19), p = 0.001) in boys. The neonicotinoid summary score (ßboys = 5.60% [0.14%, 11.36%]) and the neonicotinoid acetamiprid-N-desmethyl (ßboys = 3.90% [1.28%, 6.58%]) were positively associated with 17ß-estradiol, measured in boys only. No associations between the pyrethroid 3-phenoxybenzoic acid and hormones were observed. In girls, bivariate response associations identified interactions of MDA, Para-nitrophenol, and 3,5,6-trichloro-2-pyridinol (organophosphates) with testosterone and DHEA concentrations. In boys, we observed an interaction of MDA and Para-nitrophenol with DHEA. No associations were identified for AChE. CONCLUSIONS: We observed evidence of endocrine disruption for specific organophosphate and neonicotinoid metabolite exposures in adolescents. Urinary organophosphate metabolites were associated with testosterone and DHEA concentrations, with stronger associations in boys than girls. Urinary neonicotinoids were positively associated with 17ß-estradiol. Longitudinal repeat-measures analyses would be beneficial for causal inference.

Assessment of the incidence and risk factors of postoperative urosepsis in patients undergoing ureteroscopic lithotripsy.

Introduction: Ureteroscopic lithotripsy (URSL) is an approved, minimally invasive, low-risk procedure for urolithiasis treatment. However, some patients may develop urinary tract infection (UTI) post-procedure, eventually leading to urosepsis. Determining the predictors of infection after URSL would help identify patients at a high risk of urosepsis, thereby enabling the early implementation of effective treatment. Therefore, we aimed to establish the incidence and predictors of urosepsis after URSL. Material and methods: We assessed 231 patients who underwent URSL using a holmium laser. The incidence of urosepsis during the 30-day post-treatment period was analysed, and potential predictors of urosepsis, including patient characteristics and individual clinical factors, were examined. Results: Statistical analysis revealed that 16.88% of patients had a confirmed positive urine culture before the procedure. Post-procedure urosepsis occurred in 4.76% of patients. Univariable analysis revealed that 3 factors were significantly associated with the risk of postoperative urosepsis: double-J stent insertion before URSL, pre-operative positive urine culture, and MDR pathogen found preoperatively. In multivariable analysis, only positive urine culture remained significantly associated with the risk of urosepsis after URSL. Conclusions: Patients with positive urine culture before URSL are at significantly higher risk of urosepsis in the postoperative period. Hence, urine culture should be routinely performed before planned endoscopic urolithiasis treatment.

Systematic review of best practices for GPS data usage, processing, and linkage in health, exposure science and environmental context research.

Global Positioning System (GPS) technology is increasingly used in health research to capture individual mobility and contextual and environmental exposures. However, the tools, techniques and decisions for using GPS data vary from study to study, making comparisons and reproducibility challenging. OBJECTIVES: The objectives of this systematic review were to (1) identify best practices for GPS data collection and processing; (2) quantify reporting of best practices in published studies; and (3) discuss examples found in reviewed manuscripts that future researchers may employ for reporting GPS data usage, processing and linkage of GPS data in health studies. DESIGN: A systematic review. DATA SOURCES: Electronic databases searched (24 October 2023) were PubMed, Scopus and Web of Science (PROSPERO ID: CRD42022322166). ELIGIBILITY CRITERIA: Included peer-reviewed studies published in English met at least one of the criteria: (1) protocols involving GPS for exposure/context and human health research purposes and containing empirical data; (2) linkage of GPS data to other data intended for research on contextual influences on health; (3) associations between GPS-measured mobility or exposures and health; (4) derived variable methods using GPS data in health research; or (5) comparison of GPS tracking with other methods (eg, travel diary). DATA EXTRACTION AND SYNTHESIS: We examined 157 manuscripts for reporting of best practices including wear time, sampling frequency, data validity, noise/signal loss and data linkage to assess risk of bias. RESULTS: We found that 6% of the studies did not disclose the GPS device model used, only 12.1% reported the per cent of GPS data lost by signal loss, only 15.7% reported the per cent of GPS data considered to be noise and only 68.2% reported the inclusion criteria for their data. CONCLUSIONS: Our recommendations for reporting on GPS usage, processing and linkage may be transferrable to other geospatial devices, with the hope of promoting transparency and reproducibility in this research. PROSPERO REGISTRATION NUMBER: CRD42022322166.

Designing and Evaluating a Hierarchical Framework for Matching Food Outlets across Multi-sourced Geospatial Datasets: a Case Study of San Diego County.

Research on retail food environment (RFE) relies on data availability and accuracy. However, the discrepancies in RFE datasets may lead to imprecision when measuring association with health outcomes. In this research, we present a two-tier hierarchical point of interest (POI) matching framework to compare and triangulate food outlets across multiple geospatial data sources. Two matching parameters were used including the geodesic distance between businesses and the similarity of business names according to Levenshtein distance (LD) and Double Metaphone (DM). Sensitivity analysis was conducted to determine thresholds of matching parameters. Our Tier 1 matching used more restricted parameters to generate high confidence-matched POIs, whereas in Tier 2 we opted for relaxed matching parameters and applied a weighted multi-attribute model on the previously unmatched records. Our case study in San Diego County, California used government, commercial, and crowdsourced data and returned 20.2% matched records from Tier 1 and 18.6% matched from Tier 2. Our manual validation shows a 100% matching rate for Tier 1 and up to 30.6% for Tier 2. Matched and unmatched records from Tier 1 were further analyzed for spatial patterns and categorical differences. Our hierarchical POI matching framework generated highly confident food POIs by conflating datasets and identified some food POIs that are unique to specific data sources. Triangulating RFE data can reduce uncertain and invalid POI listings when representing food environment using multiple data sources. Studies investigating associations between food environment and health outcomes may benefit from improved quality of RFE.

Social and built neighborhood environments and sleep health: The Hispanic Community Health Study/Study of Latinos Community and Surrounding Areas and Sueño Ancillary Studies.

STUDY OBJECTIVES: To test associations between neighborhood social, built, and ambient environment characteristics and multidimensional sleep health in Hispanic/Latino adults. METHODS: Data were from San Diego-based Hispanic/Latino adults mostly of Mexican heritage enrolled in the Hispanic Community Health Study/Study of Latinos (N = 342). Home addresses were geocoded to ascertain neighborhood characteristics of greenness, walkability (density of intersections, retail spaces, and residences), socioeconomic deprivation (e.g. lower income, lower education), social disorder (e.g. vacant buildings, crime), traffic density, and air pollution (PM 2.5) in the Study of Latinos Communities and Surrounding Areas Study. Sleep dimensions of regularity, satisfaction, alertness, timing, efficiency, and duration were measured by self-report or actigraphy approximately 2 years later. Multivariable regression models accounting for study design (stratification and clustering) were used to examine associations of neighborhood variables with individual sleep dimensions and a multidimensional sleep health composite score. RESULTS: Neighborhood characteristics were not significantly associated with the multidimensional sleep health composite, and there were few significant associations with individual sleep dimensions. Greater levels of air pollution (B = 9.03, 95% CI: 1.16, 16.91) were associated with later sleep midpoint, while greater social disorder (B = -6.90, 95% CI: -13.12, -0.67) was associated with earlier sleep midpoint. Lower walkability was associated with more wake after sleep onset (B = -3.58, 95% CI: -7.07, -0.09). CONCLUSIONS: Living in neighborhoods with lower walkability and greater air pollution was associated with worse sleep health, but otherwise findings were largely null. Future research should test these hypotheses in settings with greater variability and investigate mechanisms of these associations.

Exploring the impact of environmental exposure changes on metabolic biomarkers: A 6-month GPS-GIS study among women with overweight or obesity.

BACKGROUND: Little is known about the impact of environmental exposure change on metabolic biomarkers associated with cancer risk. Furthermore, this limited epidemiological evidence on metabolic biomarkers focused on residential exposure, without considering the activity space which can be done by modelling dynamic exposures. In this longitudinal study, we aimed to investigate the impact of environmental exposures change on metabolic biomarkers using GPS-GIS based measurements. METHODS: Among two weight loss interventions, the Reach for Health and the MENU studies, which included ∼460 women at risk of breast cancer or breast cancer survivors residing in Southern California, three metabolic biomarkers (insulin resistance, fasting glucose, and C-reactive protein) were assessed. Dynamic GPS-GIS based exposure to green spaces, recreation, walkability, NO2, and PM2.5 were calculated at baseline and 6 months follow-up using time-weighted spatial averaging. Generalized estimating equations models were used to examine the relationship between changes in environmental exposures and biomarker levels over time. RESULTS: Overall, six-month environmental exposure change was not associated with metabolic biomarkers change. Stratified analyses by level of environmental exposures at baseline revealed that reduced NO2 and PM2.5 exposure was associated with reduced fasting glucose concentration among women living in a healthier environment at baseline (ß -0.010, 95%CI -0.025, 0.005; ß -0.019, 95%CI -0.034, -0.003, respectively). Women living in poor environmental conditions at baseline and exposed to greener environments had decreased C-reactive protein concentrations (ß -1.001, 95%CI -1.888, -0.131). CONCLUSIONS: The impact of environmental exposure changes on metabolic biomarkers over time may be modified by baseline exposure conditions.

Objective sleep and cardiometabolic biomarkers: results from the community of mine study.

Study Objectives: Examining multiple dimensions of sleep health may better capture associations between sleep and health risks, including cardiometabolic disease (CMD). Hispanics have elevated risk for inadequate sleep and CMD biomarkers. Few studies have explored whether associations between sleep and CMD differ by Hispanic ethnicity. Methods: Leveraging data from the Community of Mine (CoM) study, a cross-sectional investigation of 602 ethnically diverse participants, we derived accelerometer-measured sleep duration and efficiency, and self-reported sleep quality. Accelerometer-measured sleep exposures were analyzed both as continuous and categorical variables. Multivariate and quantile regression models were used to assess associations between sleep and CMD biomarkers (insulin resistance, systolic blood pressure, and low-density-lipoprotein cholesterol), controlling for age, sex, ethnicity, education, smoking status, and body mass index. We examined the potential effect modification of Hispanic ethnicity. Results: We observed mixed results based on CMD biomarkers and sleep exposure. Increased sleep duration was significantly related to low-density lipoprotein cholesterol in adjusted models (estimate = 0.06; 95% CI: 0.02, 0.11). Poor sleep efficiency was associated with greater insulin resistance in the adjusted quantile (estimate = 0.20; 95% CI: 0.04, 0.36) model at the 90th percentile. Self-reported sleep quality was not associated with CMD outcomes. There was no evidence of effect modification by Hispanic ethnicity. Conclusions: In this cohort, sleep health measures were found to have mixed and at times opposing effects on CMD outcomes. These effects did not demonstrate an interaction with Hispanic ethnicity.

Low movement, deep-learned sitting patterns, and sedentary behavior in the International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE).

BACKGROUND/OBJECTIVES: Sedentary behavior (SB) has both movement and postural components, but most SB research has only assessed low movement, especially in children. The purpose of this study was to compare estimates and health associations of SB when derived from a standard accelerometer cut-point, a novel sitting detection technique (CNN Hip Accelerometer Posture for Children; CHAP-Child), and both combined. METHODS: Data were from the International Study of Childhood Obesity, Lifestyle, and the Environment (ISCOLE). Participants were 6103 children (mean ± SD age 10.4 ± 0.56 years) from 12 countries who wore an ActiGraph GT3X+ accelerometer on the right hip for approximately one week. We calculated SB time, mean SB bout duration, and SB breaks using a cut-point (SBmovement), CHAP-Child (SBposture), and both methods combined (SBcombined). Mixed effects regression was used to test associations of SB variables with pediatric obesity variables (waist circumference, body fat percentage, and body mass index z-score). RESULTS: After adjusting for MVPA, SBposture showed several significant obesity associations favoring lower mean SB bout duration (b = 0.251-0.449; all p < 0.001) and higher SB breaks (b = -0.005--0.052; all p < 0.001). Lower total SB was unexpectedly related to greater obesity (b = -0.077--0.649; p from <0.001-0.02). For mean SB bout duration and SB breaks, more associations were observed for SBposture (n = 5) than for SBmovement (n = 3) or SBcombined (n = 1), and tended to have larger magnitude as well. CONCLUSIONS: Using traditional measures of low movement as a surrogate for SB may lead to underestimated or undetected adverse associations between SB and obesity. CHAP-Child allows assessment of sitting posture using hip-worn accelerometers. Ongoing work is needed to understand how low movement and posture are related to one another, as well as their potential health implications.

Aircraft and road traffic noise, insulin resistance, and diabetes: The role of neighborhood socioeconomic status in San Diego County.

Evidence linking traffic noise to insulin resistance and diabetes is limited and unanswered questions remain regarding the potential effect modification by neighborhood socioeconomic status (nSES). We aimed to assess socioeconomic inequalities in noise exposure, whether road and aircraft noise exposures were associated with insulin resistance or diabetes, and whether nSES modified these relationships. Among the Community of Mine Study in San Diego County, road and aircraft noise exposure at enrollment was calculated based on the static (participant's administrative boundary, and circular buffer around participant homes), and dynamic (mobility data by global positioning system, GPS) spatio-temporal aggregation methods. Associations of noise with insulin resistance (HOMA-IR) or type 2 diabetes (T2DM) were quantified using generalized estimating equation models adjusted for sex, age, ethnicity, individual income, and air pollution (nitrogen dioxide) exposure. Additive interaction between noise and nSES was assessed. Among 573 participants (mean age 58.7 y), participants living in low nSES were exposed to higher levels of aircraft and road noise using noise level at the census tract, circular buffer, or Kernel Density Estimation (KDE) of GPS data. Participants exposed to road noise greater or equal to the median (53 dB(A)) at the census tract and living in low nSES had an increased level of insulin resistance (ß = 0.15, 95%CI: -0.04, 0.34) and higher odds of T2DM (Odds Ratio = 2.34, 95%CI: 1.12, 4.90). A positive additive interaction was found as participants living in low nSES had higher odds of T2DM. The impact of noise exposure on insulin resistance and T2DM differs substantially by nSES. Public health benefits of reducing exposure to road or aircraft noise would be larger in individuals living in low nSES.

Acute Tongue Swelling as a Still Unexpected Manifestation of Internal Carotid Artery Dissection: A Case Report.

The diagnosis of internal carotid artery dissection (ICAD) at the stage of local signs is essential in the prevention of the life-treating cerebral complication; however, making this diagnosis has significant difficulties. We present the case of a 36-year-old female with left ICAD with asymmetric left-sided tongue swelling as an unusual and still unexpected symptom. The patient's complaints at admission were left-sided numbness of the tongue and swallowing difficulties but its movements were intact. Despite the provided treatment for suspected angioedema, no improvement was noted. Additional examination revealed left-sided tongue weakness, ipsilateral soft palate palsy, paralysis and reduced tension of the left vocal fold, and left-sided Horner's syndrome. Another suspected diagnosis was a dysfunction of the IX, X, and XII cranial nerves. A head MRI revealed an intramural hematoma of the left internal carotid artery. The radiologists suggested ICAD. The angio-MRI of the head arteries confirmed this diagnosis. The patient received dual antiplatelet therapy. The neuro-logopaedic therapy was also implemented. Currently, the patient's symptoms are gradually improving with significantly better results on follow-up neuroimaging. Among the possible local symptoms of ICAD, proper attention should be paid to asymmetric swelling of the tongue as an atypical manifestation of damage to the hypoglossal nerve.

Did the COVID-19 Pandemic Restrict Access to Emergency Urological Services: Assessment of Reorganisation Effectiveness for Hospital Treatment.

Urolithiasis derived renal colic is a common urological condition. If treated properly, the disease resolves without complications; if not treated, it causes infection and renal failure. The COVID-19 restrictions impacted hospitalised treatment of diseases. We analysed the impact of COVID-19 on renal colic treatment at a hospital in Poland. Clinical and demographic data of patients treated during the COVID-19 era were compared with those treated before this pandemic. During the COVID-19 restrictions, renal colic patient hospital admissions fell significantly. However, more patients presented with chronic renal colic symptoms and urinary tract infections. Nevertheless, the degree of hydronephrosis and the number and location of stones did not differ between the two groups. No marked changes were observed in the chosen treatment options. The observed decrease in emergency admissions of patients with acute renal colic with a simultaneous increase in the rate of infectious stones might indicate that some patients requiring urgent medical help did not report to the emergency department or came later than they would before the pandemic, reporting more serious symptoms. One plausible explanation for this may be that the reorganisation of the healthcare system restricted access to urological care. Moreover, some patients may have delayed their visit to the hospital due to the fear of contracting the SARS-CoV-2 coronavirus.

Neighborhood disadvantage is associated with KRAS-mutated non-small cell lung cancer risk.

PURPOSE: It remains unclear why individuals living in disadvantaged neighborhoods have shorter non-small cell lung cancer (NSCLC) survival. It is possible that living in these deprived areas is linked with increased risk of developing aggressive NSCLC biology. Here, we explored the association of somatic KRAS mutations, which are associated with shorter survival in NSCLC patients, and 11 definitions of neighborhood disadvantage spanning socioeconomic and structural environmental elements. METHODS: We analyzed data from 429 NSCLC patients treated at a Comprehensive Cancer Center from 2015 to 2018. Data were abstracted from medical records and each patient's home address was used to assign publicly available indices of neighborhood disadvantage. Prevalence Ratios (PRs) for the presence of somatic KRAS mutations were estimated using modified Poisson regression models adjusted for age, sex, smoking status, race/ethnicity, educational attainment, cancer stage, and histology. RESULTS: In the NSCLC cohort, 29% had KRAS mutation-positive tumors. We found that five deprivation indices of socioeconomic disadvantage were associated with KRAS mutation. A one decile increase in several of these socioeconomic disadvantage indices was associated with a 1.06 to 1.14 increased risk of KRAS mutation. Measures of built structural environment were not associated with KRAS mutation status. CONCLUSION: Socioeconomic disadvantage at the neighborhood level is associated with higher risk of KRAS mutation while disadvantage related to built environmental structural measures was inversely associated. Our results indicate not only that neighborhood disadvantage may contribute to aggressive NSCLC biology, but the pathways linking biology to disadvantage are likely operating through socioeconomic-related stress.

Accounting for space, time, and behavior using GPS derived dynamic measures of environmental exposure.

Time-weighted spatial averaging approaches (TWSA) are an increasingly utilized method for calculating exposure using global positioning system (GPS) mobility data for health-related research. They can provide a time-weighted measure of exposure, or dose, to various environments or health hazards. However, little work has been done to compare existing methodologies, nor to assess how sensitive these methods are to mobility data inputs (e.g., walking vs driving), the type of environmental data being assessed as the exposure (e.g., continuous surfaces vs points of interest), and underlying point-pattern clustering of participants (e.g., if a person is highly mobile vs predominantly stationary). Here we contrast three TWSA approaches that have been previously used or recently introduced in the literature: Kernel Density Estimation (KDE), Density Ranking (DR), and Point Overlay (PO). We feed GPS and accelerometer data from 602 participants through each method to derive time-weighted activity spaces, comparing four mobility behaviors: all movement, stationary time, walking time, and in-vehicle time. We then calculate exposure values derived from the various TWSA activity spaces with four environmental layer data types (point, line, area, surface). Similarities and differences across TWSA derived exposures for the sample and between individuals are explored, and we discuss interpretation of TWSA outputs providing recommendations for researchers seeking to apply these methods to health-related studies.

A RIEMANN MANIFOLD MODEL FRAMEWORK FOR LONGITUDINAL CHANGES IN PHYSICAL ACTIVITY PATTERNS.

Physical activity (PA) is significantly associated with many health outcomes. The wide usage of wearable accelerometer-based activity trackers in recent years has provided a unique opportunity for in-depth research on PA and its relations with health outcomes and interventions. Past analysis of activity tracker data relies heavily on aggregating minute-level PA records into day-level summary statistics in which important information of PA temporal/diurnal patterns is lost. In this paper we propose a novel functional data analysis approach based on Riemann manifolds for modeling PA and its longitudinal changes. We model smoothed minute-level PA of a day as one-dimensional Riemann manifolds and longitudinal changes in PA in different visits as deformations between manifolds. The variability in changes of PA among a cohort of subjects is characterized via variability in the deformation. Functional principal component analysis is further adopted to model the deformations, and PC scores are used as a proxy in modeling the relation between changes in PA and health outcomes and/or interventions. We conduct comprehensive analyses on data from two clinical trials: Reach for Health (RfH) and Metabolism, Exercise and Nutrition at UCSD (MENU), focusing on the effect of interventions on longitudinal changes in PA patterns and how different modes of changes in PA influence weight loss, respectively. The proposed approach reveals unique modes of changes, including overall enhanced PA, boosted morning PA, and shifts of active hours specific to each study cohort. The results bring new insights into the study of longitudinal changes in PA and health and have the potential to facilitate designing of effective health interventions and guidelines.