Dr. Kevin  Lane  Od image

Dr. Kevin Lane Od

2390 E Florida Ave #207
Hemet CA 92544
951 526-6100
Medical School: Other - Unknown
Accepts Medicare: No
Participates In eRX: No
Participates In PQRS: No
Participates In EHR: No
License #: 10632
NPI: 1548210453
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Effect of time-activity adjustment on exposure assessment for traffic-related ultrafine particles. - Journal of exposure science & environmental epidemiology
Exposures to ultrafine particles (<100 nm, estimated as particle number concentration, PNC) differ from ambient concentrations because of the spatial and temporal variability of both PNC and people. Our goal was to evaluate the influence of time-activity adjustment on exposure assignment and associations with blood biomarkers for a near-highway population. A regression model based on mobile monitoring and spatial and temporal variables was used to generate hourly ambient residential PNC for a full year for a subset of participants (n=140) in the Community Assessment of Freeway Exposure and Health study. We modified the ambient estimates for each hour using personal estimates of hourly time spent in five micro-environments (inside home, outside home, at work, commuting, other) as well as particle infiltration. Time-activity adjusted (TAA)-PNC values differed from residential ambient annual average (RAA)-PNC, with lower exposures predicted for participants who spent more time away from home. Employment status and distance to highway had a differential effect on TAA-PNC. We found associations of RAA-PNC with high sensitivity C-reactive protein and Interleukin-6, although exposure-response functions were non-monotonic. TAA-PNC associations had larger effect estimates and linear exposure-response functions. Our findings suggest that time-activity adjustment improves exposure assessment for air pollutants that vary greatly in space and time.
Highway proximity associated with cardiovascular disease risk: the influence of individual-level confounders and exposure misclassification. - Environmental health : a global access science source
Elevated cardiovascular disease risk has been reported with proximity to highways or busy roadways, but proximity measures can be challenging to interpret given potential confounders and exposure error.We conducted a cross sectional analysis of plasma levels of C-Reactive Protein (hsCRP), Interleukin-6 (IL-6), Tumor Necrosis Factor alpha receptor II (TNF-RII) and fibrinogen with distance of residence to a highway in and around Boston, Massachusetts. Distance was assigned using ortho-photo corrected parcel matching, as well as less precise approaches such as simple parcel matching and geocoding addresses to street networks. We used a combined random and convenience sample of 260 adults >40 years old. We screened a large number of individual-level variables including some infrequently collected for assessment of highway proximity, and included a subset in our final regression models. We monitored ultrafine particle (UFP) levels in the study areas to help interpret proximity measures.Using the orthophoto corrected geocoding, in a fully adjusted model, hsCRP and IL-6 differed by distance category relative to urban background: 43% (-16%,141%) and 49% (6%,110%) increase for 0-50 m; 7% (-39%,45%) and 41% (6%,86%) for 50-150 m; 54% (-2%,142%) and 18% (-11%,57%) for 150-250 m, and 49% (-4%, 131%) and 42% (6%, 89%) for 250-450 m. There was little evidence for association for TNF-RII or fibrinogen. Ortho-photo corrected geocoding resulted in stronger associations than traditional methods which introduced differential misclassification. Restricted analysis found the effect of proximity on biomarkers was mostly downwind from the highway or upwind where there was considerable local street traffic, consistent with patterns of monitored UFP levels.We found associations between highway proximity and both hsCRP and IL-6, with non-monotonic patterns explained partly by individual-level factors and differences between proximity and UFP concentrations. Our analyses emphasize the importance of controlling for the risk of differential exposure misclassification from geocoding error.
Mapping the vertical distribution of population and particulate air pollution in a near-highway urban neighborhood: implications for exposure assessment. - Journal of exposure science & environmental epidemiology
Owing to data collection challenges, the vertical variation in population in cities and particulate air pollution are typically not accounted for in exposure assessments, which may lead to misclassification of exposures based on elevation of residency. To better assess this misclassification, the vertical distribution of the potentially highly exposed population (PHEP), defined as all residents within the 100-m buffer zone of above-ground highways or the 200-m buffer zone of a highway-tunnel exit, was estimated for four floor categories in Boston's Chinatown (MA, USA) using the three-dimensional digital geography methodology. Vertical profiles of particle number concentration (7-3000 nm; PNC) and particulate matter (PM2.5) mass concentration were measured by hoisting instruments up the vertical face of an 11-story (35-m) building near the study area throughout the day on multiple days. The concentrations from all the profiles (n=23) were averaged together for each floor category. As measurement elevation increased from 0 to 35 m PNC decreased by 7.7%, compared with 3.6% for PM2.5. PHEP was multiplied by the average PNC for each floor category to assess exposures for near-highway populations. The results show that adding temporally-averaged vertical air pollution data had a small effect on residential ambient exposures for our study population; however, greater effects were observed when individual days were considered (e.g., winds were off the highways).
Positional error and time-activity patterns in near-highway proximity studies: an exposure misclassification analysis. - Environmental health : a global access science source
The growing interest in research on the health effects of near-highway air pollutants requires an assessment of potential sources of error in exposure assignment techniques that rely on residential proximity to roadways.We compared the amount of positional error in the geocoding process for three different data sources (parcels, TIGER and StreetMap USA) to a "gold standard" residential geocoding process that used ortho-photos, large multi-building parcel layouts or large multi-unit building floor plans. The potential effect of positional error for each geocoding method was assessed as part of a proximity to highway epidemiological study in the Boston area, using all participants with complete address information (N = 703). Hourly time-activity data for the most recent workday/weekday and non-workday/weekend were collected to examine time spent in five different micro-environments (inside of home, outside of home, school/work, travel on highway, and other). Analysis included examination of whether time-activity patterns were differentially distributed either by proximity to highway or across demographic groups.Median positional error was significantly higher in street network geocoding (StreetMap USA = 23 m; TIGER = 22 m) than parcel geocoding (8 m). When restricted to multi-building parcels and large multi-unit building parcels, all three geocoding methods had substantial positional error (parcels = 24 m; StreetMap USA = 28 m; TIGER = 37 m). Street network geocoding also differentially introduced greater amounts of positional error in the proximity to highway study in the 0-50 m proximity category. Time spent inside home on workdays/weekdays differed significantly by demographic variables (age, employment status, educational attainment, income and race). Time-activity patterns were also significantly different when stratified by proximity to highway, with those participants residing in the 0-50 m proximity category reporting significantly more time in the school/work micro-environment on workdays/weekdays than all other distance groups.These findings indicate the potential for both differential and non-differential exposure misclassification due to geocoding error and time-activity patterns in studies of highway proximity. We also propose a multi-stage manual correction process to minimize positional error. Additional research is needed in other populations and geographic settings.
A community participatory study of cardiovascular health and exposure to near-highway air pollution: study design and methods. - Reviews on environmental health
Current literature is insufficient to make causal inferences or establish dose-response relationships for traffic-related ultrafine particles (UFPs) and cardiovascular (CV) health. The Community Assessment of Freeway Exposure and Health (CAFEH) is a cross-sectional study of the relationship between UFP and biomarkers of CV risk. CAFEH uses a community-based participatory research framework that partners university researchers with community groups and residents. Our central hypothesis is that chronic exposure to UFP is associated with changes in biomarkers. The study enrolled more than 700 residents from three near-highway neighborhoods in the Boston metropolitan area in Massachusetts, USA. All participants completed an in-home questionnaire and a subset (440+) completed an additional supplemental questionnaire and provided biomarkers. Air pollution monitoring was conducted by a mobile laboratory equipped with fast-response instruments, at fixed sites, and inside the homes of selected study participants. We seek to develop improved estimates of UFP exposure by combining spatiotemporal models of ambient UFP with data on participant time-activity and housing characteristics. Exposure estimates will then be compared with biomarker levels to ascertain associations. This article describes our study design and methods and presents preliminary findings from east Somerville, one of the three study communities.
Highway proximity associations with blood markers of inflammation: evidence for a role for IL-1β. - Journal of toxicology and environmental health. Part A
Cardiovascular disease is known to be associated with proximity to major roadways and highways. Thus, blood samples from 20 near highway and 20 urban background residents were analyzed for presence of cytokines and other biomarkers. Near-highway participants displayed significantly lower socioeconomic status (SES) and significantly higher occupational vehicle exhaust exposure and higher low-density lipoprotein (LDL) levels. Controlling for exposure to vehicle exhaust on the job, interleukin-6 (IL-6) was numerically higher in near highway participants. Using logistic regression analyses, IL-1β was significantly elevated near highway. It is interesting that elevations were found in IL-1β, a key cytokine linked to inflammation from particulate matter (PM). More studies are needed with larger sample sizes to assess the possible role of IL-1β.
Indoor and outdoor measurements of particle number concentration in near-highway homes. - Journal of exposure science & environmental epidemiology
Exposure to high levels of traffic-generated particles may pose risks to human health; however, limited measurement has been conducted at homes near highways. The purpose of this study was to characterize differences between indoor and outdoor particle number concentration (PNC) in homes near to and distant from a highway and to identify factors that may affect infiltration. We monitored indoor and outdoor PNC (6-3000 nm) for 1-3 weeks at 18 homes located <1500 m from Interstate-93 (I-93) in Somerville, MA (USA). Median hourly indoor and outdoor PNC pooled over all homes were 5.2 × 10(3) and 5.9 × 10(3) particles/cm(3), respectively; the median ratio of indoor-to-outdoor PNC was 0.95 (5(th)/95th percentile: 0.42/1.75). Homes <100 m from I-93 (n=4) had higher indoor and outdoor PNC compared with homes >1000 m away (n=3). In regression models, a 10% increase in outdoor PNC was associated with an approximately equal (10.8%) increase in indoor PNC. Wind speed and direction, temperature, time of day and weekday were also associated with indoor PNC. Average mean indoor PNC was lower for homes with air conditioners compared with homes without air conditioning. These results may have significance for estimating indoor, personal exposures to traffic-related air pollution.
Exposure of trucking company workers to particulate matter during the winter. - Chemosphere
This study analyzed the workplace area concentrations and the personal exposure concentrations to fine particulate (PM2.5), elemental carbon (EC), and organic carbon (OC) measured during the winter period in trucking companies. The averaged personal exposure concentrations at breathing zones of workers are much greater than those of the microenvironment concentrations. The highest difference between the area (microenvironment) and personal exposure concentrations was in the PM2.5 concentrations followed by the OC concentrations. The area concentrations of PM2.5, EC, and OC at a large terminal were higher than those at a small one. The highest area concentrations of PM2.5, EC, and OC were observed in the shop areas followed by pick-up and delivery (P&D) areas. The area concentrations and personal exposure to PM2.5, EC, and OC in the shop and P&D areas which are highly affected by diesel engine exhaust emissions were much higher than those in the docks which are significantly affected by liquefied petroleum gas (LPG) engine exhaust emissions. The highest EC fraction to the total carbon (EC + OC) concentrations was observed in the shops, while the lowest one was identified in the offices. The personal exposure of the smoking workers to PM2.5 and OC was much higher than that of the non-smoking workers. However, the smoking might not significantly contribute to the personal exposure to EC. There were significant correlations between the PM2.5 and OC concentrations in both the area and personal exposure concentrations. However, significant correlations between the PM2.5 and EC concentrations and between the OC and EC concentrations were not identified.
Association of modeled long-term personal exposure to ultrafine particles with inflammatory and coagulation biomarkers. - Environment international
Long-term exposure to fine particulate matter has been linked to cardiovascular disease and systemic inflammatory responses; however, evidence is limited regarding the effects of long-term exposure to ultrafine particulate matter (UFP, <100nm). We used a cross-sectional study design to examine the association of long-term exposure to near-highway UFP with measures of systemic inflammation and coagulation.We analyzed blood samples from 408 individuals aged 40-91years living in three near-highway and three urban background areas in and near Boston, Massachusetts. We conducted mobile monitoring of particle number concentration (PNC) in each area, and used the data to develop and validate highly resolved spatiotemporal (hourly, 20m) PNC regression models. These models were linked with participant time-activity data to determine individual time-activity adjusted (TAA) annual average PNC exposures. Multivariable regression modeling and stratification were used to assess the association between TAA-PNC and single peripheral blood measures of high-sensitivity C-reactive protein (hsCRP), interleukin-6 (IL-6), tumor-necrosis factor alpha receptor II (TNFRII) and fibrinogen.After adjusting for age, sex, education, body mass index, smoking and race/ethnicity, an interquartile-range (10,000particles/cm(3)) increase in TAA-PNC had a positive non-significant association with a 14.0% (95% CI: -4.6%, 36.2%) positive difference in hsCRP, an 8.9% (95% CI: -0.4%, 10.9%) positive difference in IL-6, and a 5.1% (95% CI: -0.4%, 10.9%) positive difference in TNFRII. Stratification by race/ethnicity revealed that TAA-PNC had larger effect estimates for all three inflammatory markers and was significantly associated with hsCRP and TNFRII in white non-Hispanic, but not East Asian participants. Fibrinogen had a negative non-significant association with TAA-PNC.Our findings suggest an association between annual average near-highway TAA-PNC and subclinical inflammatory markers of CVD risk.Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

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