Citywide Averages Research Articles

Geochemical status of non-reclaimed ash dumps subjected to long-term self-overgrowing: Evidence from the Tyumen, Russia

Establishing the geochemical state of ash dumps of solid fuel thermal power plants in the absence of reclamation is extremely important in urban conditions. The current study was performed to assess the level, spatial distribution, soil pollution and risk of potentially toxic elements (PTEs) and polycyclic aromatic hydrocarbons (PAHs) in soils of abandoned ash dumps from the city of Tyumen, Russia. In general, the soils of as dumps had elevated levels of PTEs and PAHs compared to the crustal abundance and global soil background. A number of metals, namely Sr, Ni, Cu, Cr, Zn, and V, were concentrated in the soils of ash dumps (2–6 times), while As, Co, and Pb slightly exceeded the citywide average (up to 1.5 times). Naphthalene (NAP) was the only representative of the studied PAHs, the concentrations of which in the soils of ash dumps significantly exceeded the median content in urban soils of Tyumen. Elevated levels of NAP are likely a consequence of frequent fires occurring in grassy areas. Spatial patterns of pollutants are mainly controlled by the initial heterogeneity of technogenic substrates, rather than the post-depositional processes including vegetation and soil cover development. Low and moderate pollution and human health risks of PTEs and PAHs were revealed in topsoils of the studied sites. Although elevated levels of pollutants in coal ash dump soils are due to peat combustion, they pose less of an environmental risk than the more common coal ash dumps and are potentially suitable for a wider variety of management practices.

School exposure to air pollution in the UK and Ireland: Indoor-Outdoor air quality assessment

Abstract Background Globally, 93% of children under the age of 15 (1.8 billion) are exposed to fine particulate matter (PM2.5) levels that might cause respiratory/cardiovascular disorders, impaired neuro/cognitive development, and cancer. Air pollution causes 1/10 deaths in children under the age of 5. Methods The purpose of this observational study was to collect data on indoor and outdoor air quality in 24 schools over 10 school days and compare it with city-wide average air quality levels reported in rural/urban areas in the UK and Northern Ireland. Nitrogen dioxide, volatile organic compounds (VOCs) and PM10,2.5,1 were monitored inside the classrooms and school surroundings with personal pollution monitors. City-wide averages were taken from local reference air quality and ground-source monitoring stations. Data was expressed using the Plume Labs Air Quality Index (PAQI) thresholds [low (0-20), moderate (21-50), high (51-100), very high (101+) pollution level] aligned with WHO's exposure recommendations. Results Despite both AQIs being in the moderate threshold, the school's average indoor AQI was ∼44% higher than the city-wide average. Only 27% of schools’ indoor air quality indexes matched the city-wide average, 59% were higher and 14% were lower. Rural schools had a marginally higher average indoor AQI than urban schools. The primary classroom pollutants observed were VOCs, followed by PM10. The average walk-exposure AQI of 33% of total schools was higher than the city's average. The school reporting the highest average walk AQI was seven times higher than the lowest. Conclusions Poor indoor air quality and higher levels of pollutants were found inside the majority of the schools across the regions. There is a need for mitigation strategies to identify responsible factors for indoor air pollution. A regulatory framework for school ventilation and behavior interventions like nasal washes may reduce pollution exposure and its impact on children's health outcomes and mortality. Key messages • Poor indoor air quality (∼44% higher than the city-wide average) and higher levels of pollutants (volatile organic compounds and PM10) were found inside the majority of the schools across the regions. • A regulatory framework for school ventilation and behavior interventions like nasal washes may reduce air pollution exposure and its impact on children’s health outcomes and mortality.

A Comprehensive Review of Drain Water Pollution Potential and Environmental Control Strategies in Khulna, Bangladesh

The main issues with drain water in Khulna, Bangladesh, include contamination, a lack of infrastructure, and sensitivity to seasonal changes. This review paper discusses the different causes of drain water pollution, such as inadequate drainage systems and poor waste disposal procedures, as well as the effects of this pollution on the environment, such as waterlogging and ecosystem contamination. The length of the current drainage systems in Khulna is roughly 528.120 km, with primary drains covering 175.43 km (33.22%), secondary drains spanning 150.45 km (28.49%), and tertiary drains spanning 202.24 km (38.29%). 291.230 km (55.14%) of these are pucca, or well-constructed drains, 51.790 km (9.81%) are semi-pucca, and 185.10 km (35.05%) are kutcha, or earthen drains. However, research on drainage density in 31 wards revealed that wards 23 and 31 had the highest and lowest drainage densities, respectively, of 33.88 km/km2 and 3.06 km/km2, with a citywide average of 11.79 km/km2. 51 primary outflow sites make up the drainage system in Khulna City, which is drained by the Bhairab, Rupsha, Mayur, and Gallamari rivers. Additionally, according to recent research by the Khulna Development Authority (KDA), just 33% of city residents have access to some type of drainage facility close to their homes, leaving roughly 67% without designed drainage systems. The drainage systems at KCC have been discovered to need further upkeep and cleaning. This paper intends to offer useful insights for policymakers, researchers, and environmentalists working toward a sustainable and healthy urban environment in Khulna by illuminating the amount of drain water pollution and outlining numerous alternatives.

Can urban polycentricity improve air quality? Evidence from Chinese cities

This study utilizes high-resolution population grid data from 2004 to 2018 to assess the extent of urban polycentricity in 284 Chinese prefecture-level cities. A new method for measuring urban polycentricity is devised using the Clauset-Newman-Moore grey modularity maximization algorithm. Additionally, the Spatial Durbin Model is applied to investigate the effect of urban polycentricity on the mean and spatial variation of PM2.5 concentrations. Our statistical results show that the increased distance between urban centers and the increased size disparity between the large and small centers effectively reduces air pollution within the city. On the other hand, in cities with a strong clustering of urban centers and significant size disparity between main and sub-centers, the polycentric urban structure cannot help reduce air pollution but merely shift it to other urban centers within the city. Hence, interpreting the severity of urban air pollution solely on the basis of the citywide average of air pollution may be insufficient. It is necessary to consider the possible relocation of air-polluting activities associated with polycentric urban structures. Policymakers should take into account the potential spatial inequality of air pollution driven by urban polycentricity.

CONSTRUCTION PROCESS AND SERVICE LEVEL OF SCHOOLCHILD CARE FACILITIES BY ELEMENTARY SCHOOL UNIT IN LOCAL CITIES

This study aims to clarify the supply process in the status of each elementary school district with schoolchild care facilities, in the Ube and Matsue Cities. Since the latter half of the 1970s, Ube City has been advancing the facility supply, and Matsue City has been doing so since the early 1990s, reaching a facility establishment rate of 200% per elementary school district by around 2010. The facilities of the two cities satisfy the criteria for the number of people and area as a city-wide average, however, the improvement of some overcrowded facilities is an issue.

Dual public health crises: the overlap of drug overdose and firearm injury in Indianapolis, Indiana, 2018–2020

BackgroundDrug overdose and firearm injury are two of the United States (US) most unrelenting public health crises, both of which have been compounded by the COVID-19 pandemic. Programs and policies typically focus on each epidemic, alone, which may produce less efficient interventions if overlap does exist. The objective is to examine whether drug overdose correlates with and is associated with firearm injury at the census tract level while controlling for neighborhood characteristics.MethodsAn ecological study of census tracts in Indianapolis, Indiana from 2018 to 2020. Population rates per 100,000 and census tracts with the highest overlap of overdose and firearm injury were identified based on spatial clusters. Bivariate association between census tract characteristic and drug overdose and firearm violence rate within spatial clusters. Zero-inflated negative binominal regression was used to estimate if the drug overdose activity is associated with higher future firearm injury.ResultsIn high overdose—high firearm injury census tracts, rates of firearm injury and drug overdose are two times higher compared to city wide rates. Indicators of structural disadvantage and structural racism are higher in high overdose—high firearm injury census tracts compared to city-wide averages. Drug overdoses are associated with higher rates of firearm injury in the following year (IRR: 1.004, 95% CI 1.001, 1.007, p < 0.05), adjusting for census tract characteristics and spatial dependence.ConclusionsDrug overdose and firearm injury co-spatially concentrate within census tracts. Moreover, drug overdoses are associated with future firearm injury. Interventions to reduce firearm injuries and drug overdoses should be a co-response in high drug overdose—high firearm injury communities.

Are Cooling Centers Optimally Placed to Serve Vulnerable Populations? An analysis of 77 US Cities

BACKGROUND AND AIM: Although extreme heat can affect anyone, some people are more exposed and/or more susceptible than others. In urban settings, cooling centers are frequently used to mitigate the negative health effects of extreme heat. However, how well cooling centers serve those at greatest risk remains unknown. We compared the distribution of cooling centers versus perceived need based on markers of urban heat island and population vulnerability in multiple cities across the US. METHODS: We identified the location of 935 cooling centers across 77 populous US cities from publicly available sources. Within each city, we estimated average land surface temperature (LST) from MODIS and the CDC’s Social Vulnerability Index (SVI) within a 1-mile walking network of each cooling center and compared those values to average values across the corresponding city. We then meta-analyzed results across cities overall and grouped by National Climate Assessment (NCA4) regions to evaluate climate-relevant regional differences. RESULTS:Nationally, LST around cooling centers was 3.3°F cooler than the city-wide average. The largest differences were seen in the Northwest and Southwest where LST near cooling centers was on average 5℉ cooler than the city average. In contrast, the average SVI of populations living near cooling centers was greater than the city average (0.61 versus 0.55), suggesting that, nationally, cooling centers are preferentially located somewhat closer to vulnerable populations. Regionally, cooling centers were located closest to more vulnerable populations in the Northern Great Plains and in the Southeast. CONCLUSIONS:These results suggest that there may be room for improvement in the placement of cooling centers closer to those subgroups of the population most likely to be adversely impacted by days of extreme heat. KEYWORDS: Temperature Extremes, Environmental Disparities, Spatial Statistics, Environmental Justice

Neighborhood Social Cohesion and Inequalities in COVID-19 Diagnosis Rates by Area-Level Black/African American Racial Composition.

Geographic inequalities in COVID-19 diagnosis are now well documented. However, we do not sufficiently know whether inequalities are related to social characteristics of communities, such as collective engagement. We tested whether neighborhood social cohesion is associated with inequalities in COVID-19 diagnosis rate and the extent the association varies across neighborhood racial composition. We calculated COVID-19 diagnosis rates in Philadelphia, PA, per 10,000 general population across 46 ZIP codes, as of April 2020. Social cohesion measures were from the Southeastern Pennsylvania Household Health Survey, 2018. We estimated Poisson regressions to quantify associations between social cohesion and COVID-19 diagnosis rate, testing a multiplicative interaction with Black racial composition in the neighborhood, which we operationalize via a binary indicator of ZIP codes above vs. below the city-wide average (41%) Black population. Two social cohesion indicators were significantly associated with COVID-19 diagnosis. Associations varied across Black neighborhood racial composition (p <0.05 for the interaction test). In ZIP codes with ≥41% of Black people, higher collective engagement was associated with an 18% higher COVID-19 diagnosis rate (IRR=1.18, 95%CI=1.11, 1.26). In contrast, areas with <41% of Black people, higher engagement was associated with a 26% lower diagnosis rate (IRR=0.74, 95%CI=0.67, 0.82). Neighborhood social cohesion is associated with both higher and lower COVID-19 diagnosis rates, and the extent of associations varies across Black neighborhood racial composition. We recommend some strategies for reducing inequalities based on the segmentation model within the social cohesion and public health intervention framework.

Particulate matter exposure, dietary inflammatory index and preterm birth in Mexico city, Mexico

BackgroundParticulate matter ≤10 μm in aerodynamic diameter (PM10) and diet quality are risk factors for systemic inflammation, which is associated with preterm birth (PTB). PM10 and a pro-inflammatory diet (assessed by the Dietary Inflammatory Index [DII®]) have been individually evaluated as causes of PTB and differences by offspring sex have been reported for the DII. However, additional studies are needed to evaluate joint effects of these associations to inform intervention efforts. ObjectivesTo evaluate the independent and joint effects of PM10 and energy-adjusted DII (E-DII) on PTB risks. MethodsPM10 estimates were generated from daily citywide averages for 1216 pregnant women from three subcohorts of the Early Life Exposures in Mexico to Environmental Toxicants study using data from the Mexico City Outdoor Air Monitoring Network. Among a subset of participants (N = 620), E-DII scores were calculated using a validated food frequency questionnaire. Cox Proportional Hazards models were run for select periods during pregnancy and entire pregnancy averages for E-DII and PM10. We assessed for potential non-linear associations using natural splines. ResultsIn adjusted models, PM10 exposure was associated with increased risks of PTB for a range of values (58–72 μg/m3) during the second trimester, while negative associations were seen during the second (≥74 μg/m3) and third trimesters (55–65 μg/m3). Analyses conducted using distributed lag models for periods closer to delivery (max lag = 90) did not show negative associations between PM10 exposure and preterm birth, and indeed positive significant associations were observed (estimates and figures). E-DII was not associated with PTB and there was no evidence of effect modification by infant sex. There was no evidence of interaction between PM10 and E-DII and the risk of preterm birth. DiscussionAssociations between PM10 and PTB in Mexico City varied over time and across levels of PM10. Our findings of negative associations in the second and third trimesters, which are contrary to the hypothesized relationship between PM10 and PTB, may be due to a number of factors, including live birth bias and the exposure period evaluated. Differences in results for the periods evaluated suggest that PM10 from shorter exposure windows may play a more proximal role in initiating preterm labor.

The environmental neighborhoods of cities and their spatial extent

We define the new concept of an environmental neighborhood as the surrounding area influencing the environmental quality at a given point in a city, and propose a novel methodology to measure its spatial extent. We compute the spatial correlation of air quality and urban parameters from high spatial resolution datasets for New York City, where the urban characteristics are averaged over variable urban footprint sizes, ranging from 25 m × 5 m to 5000 m × 5000 m. The scale at which these correlations peak indicates the extent of the neighboring area that influences pollutant concentrations deviations from the city-wide average. The results indicate that the scale of these environmental neighborhoods ranges from ∼1000 m (for attributes such as road area or building footmark) down to ∼200 m (for building use or green area). Selecting this optimal neighborhood scale is thus critical for identifying the urban fabric and activity attributes that have the largest influence on air quality; smaller footprints do not contain all the pertinent urban surface information while larger footprints contain irrelevant, potentially misleading information. The quantification of this scale of influence therefore enables more effective and localized policies and interventions to improve urban environmental quality and reduce urban health disparities. More broadly, the findings indicate that, in a wide range of environmental and ecological applications where surface heterogeneity is a primary driver, the scale of analysis is not an external parameter to be chosen, but rather an internal parameter dictated by the problem physics.

Monitoring Neighborhood Concentrations of PM2.5 and Black Carbon: When Using Citywide Averages Underestimates Impacts in a Community with Environmental Justice Issues

Monitoring networks are commonly designed to measure the air quality of regional air sheds and may not be representative of neighborhood air quality. This study presents data collected in a neighbo...

Particulate Matter, Dietary Inflammatory Index and Preterm Birth in Mexico City

TPS 741: Adverse birth outcomes 2, Exhibition Hall, Ground floor, August 28, 2019, 3:00 PM - 4:30 PM Background: Particulate matter ≤10 μm (PM10) and diet quality are both risk factors for systemic inflammation, which has been implicated in the etiology of preterm birth (PTB). Although PM10 and a pro-inflammatory diet (assessed by the Dietary Inflammatory Index [DII®]) have been individually evaluated as determinants of PTB and differences by offspring sex have been reported for the DII, additional studies on both independent and joint effects of these two risk factors are needed to inform future intervention strategies. Methods: PM10 estimates were generated from daily citywide averages for 1216 pregnant women from three subcohorts of the Early Life Exposures in Mexico to ENvironmental Toxicants study using data from the Mexico City Monitoring Network. Among a subset of participants (N=620), DII scores were calculated using data from a validated food frequency questionnaire. Trimester-specific and overall pregnancy average data for the DII and PM10 were used. Sex and period-specific Cox Proportional Hazards models were used to estimate hazard ratios (HR) and 95% CIs of PTB with respect to quartiles of PM10 and the DII (Q1 = referent), adjusting for age, education, parity, delivery type and cohort. Results: Results varied by sex for PM10 and the DII. For example, adjusted HRs, (95% CIs) for second trimester PM10 for boys were: 1.25 (0.59, 2.62), 0.58 (0.17, 2.00), 0.45 (0.11, 1.84) and for girls: 0.47 (0.20, 1.08), 0.13 (0.03, 0.57), 0.16 (0.04, 0.73), for Q2, Q3 and Q4 respectively relative to Q1. For the DII, first trimester differences by sex were also evident, e.g., 0.88 (0.33, 2.37) for boys and 0.30 (0.09, 0.99) for girls for Q4 vs. Q1. We did not find evidence of a joint PM10-DII effect. Conclusions: PM10 and DII were differentially associated with preterm birth. Sex differences and apparently protective diet-related and air pollution associations need further evaluation.

Maximizing Colonoscopy Completion Rates and Quality: Effect of Direct Primary Care Provider versus Gastroenterology Referral in Colorectal Cancer Screening and Surveillance

Introduction: Colorectal cancer (CRC) is the 2nd leading cause of cancer death in the US and the 4th worldwide. In the US, incidence has declined as a result of screening strategies, since early diagnosis is the most important prognostic factor. CRC screening with colonoscopy provides visualization of precancerous polyps and the opportunity for immediate removal. The effect in CRC mortality is stronger when colonoscopies are of good quality. A good bowel preparation increases diagnostic accuracy and therapeutic safety. Methods: A retrospective review of CRC screening rates in our inner-city community health clinic identified our screening rate was 37%, significantly below the citywide average of 70%. To improve our screening rate, direct colonoscopy referral by Primary Care Provider (PCP) was added to our EMR's order set. We aimed to determine if referral origin, PCP vs Gastroenterologist (GI), impacts completion rates and quality of bowel preparation. We reviewed all referral orders for screening or surveillance colonoscopy at our facility from June 2015 to September 2016. Patients >50 years old were included and those on which colonoscopies were performed for diagnostic purposes were excluded. Results: We identified 313 patients referred for CRC screening or surveillance colonoscopy. Of these, 50.5% were referred by GI and 49.5% by PCP. Baseline characteristics were compared among groups (Table 1). Older patients and those with diabetes or liver disease were more likely to be referred by GI (Table 2). 60% of our patients (N=188) completed their colonoscopy. Patients referred by GI were more likely to complete their colonoscopy compared to those with direct PCP referral, 72.8% vs 47.1% respectively (p < 0.0001). Also, the GI referral group was more likely to have better bowel preparation compared to the direct PCP referral group (p=0.0017).Table: Table. Patient baseline characteristics and characteristics per referral typeTable: Table. Odds of GI referral for colonoscopy evaluation per patients' factorsConclusion: This study is part of the quality improvement endeavors undertaken at our clinic to improve our 37% CRC screening rate. Despite providing direct PCP referrals for colonoscopy, patients referred by GI were more likely to complete their colonoscopy and to have better bowel preparation. We theorize that multiple factors contributed to our findings, including PCP's knowledge of procedure's details and confidence answering questions. Hence, the approach of our PCPs towards CRC screening and surveillance should be explored. Further studies are needed to evaluate interventions as ours and their impact in improving CRC screening rates.

Bringing Fresh Produce to Corner Stores in Declining Neighborhoods: Reflections from Detroit FRESH

The paper reports and reflects on an action research project to increase availability and sales of fresh produce in 26 neighborhood corner stores in Detroit, Michigan. Through analysis of neighbor­hood, store-related, and supply-chain character­istics, I identify factors in successful operations as well as challenges confronted by stores between 2009 and 2012, when many Detroit neighborhoods lost population due to tax foreclosure and aban­donment. Neighborhood distress was reflected in challenges experienced by a majority of stores, including those that dropped out of the project prematurely (five out of seven), or participated only inconsistently (seven out of 10). Nine stores supplied fresh produce consistently. Operators with high levels of performance tended to be in zip codes experiencing population losses at a lower rate than the citywide average, be more committed to their store-neighborhood, have more experience with fresh produce sales, and be more willing to test alternatives. This paper reflects on the chal­lenges of implementing corner store strategies in rapidly depopulating neighborhoods without ongoing subsidy. It also demonstrates the lessons in implementing them as action research projects including with students and community partners.

The material practices of quantification: Measuring ‘deprivation’ in the Amsterdam Neighbourhood Policy

The use of indicators and indexes in social policy, as part of evidence-based policy, is understood by governmentality scholars as ‘techniques of governance’. However, we know very little about how the process of quantification is enacted in the material practices that constitute social policy itself. In this article we focus on a particular quantified object: the ‘Normal Amsterdam Level’ (NAP), used in an Amsterdam Neighbourhood Policy programme. We follow the NAP from its birth, to its life and its afterlife. We show that the qualification ‘deprived’ calls forth a whole set of problematic arrangements which are lost in a process of quantification. We understand the NAP as a generative device that actively assembles and arranges the world. These assemblages are rendered ‘hard’ through semiotic, statistical and visual techniques that produce facts about targeted neighbourhoods in relation to a city-wide average, thus serving as evidence and legitimisation for policy interventions.

An assessment of air pollutant exposure methods in Mexico City, Mexico

Geostatistical interpolation methods to estimate individual exposure to outdoor air pollutants can be used in pregnancy cohorts where personal exposure data are not collected. Our objectives were to a) develop four assessment methods (citywide average (CWA); nearest monitor (NM); inverse distance weighting (IDW); and ordinary Kriging (OK)), and b) compare daily metrics and cross-validations of interpolation models. We obtained 2008 hourly data from Mexico City’s outdoor air monitoring network for PM10, PM2.5, O3, CO, NO2, and SO2 and constructed daily exposure metrics for 1,000 simulated individual locations across five populated geographic zones. Descriptive statistics from all methods were calculated for dry and wet seasons, and by zone. We also evaluated IDW and OK methods’ ability to predict measured concentrations at monitors using cross validation and a coefficient of variation (COV). All methods were performed using SAS 9.3, except ordinary Kriging which was modeled using R’s gstat package. Overall, mean concentrations and standard deviations were similar among the different methods for each pollutant. Correlations between methods were generally high (r = 0.77 to 0.99). However, ranges of estimated concentrations determined by NM, IDW, and OK were wider than the ranges for CWA. Root mean square errors for OK were consistently equal to or lower than for the IDW method. OK standard errors varied considerably between pollutants and the computed COVs ranged from 0.46 (least error) for SO2 and PM10 to 3.91 (most error) for PM2.5. OK predicted concentrations measured at the monitors better than IDW and NM. Given the similarity in results for the exposure methods, OK is preferred because this method alone provides predicted standard errors which can be incorporated in statistical models. The daily estimated exposures calculated using these different exposure methods provide flexibility to evaluate multiple windows of exposure during pregnancy, not just trimester or pregnancy-long exposures.Implications: Many studies evaluating associations between outdoor air pollution and adverse pregnancy outcomes rely on outdoor air pollution monitoring data linked to information gathered from large birth registries, and often lack residence location information needed to estimate individual exposure. This study simulated 1,000 residential locations to evaluate four air pollution exposure assessment methods, and describes possible exposure misclassification from using spatial averaging versus geostatistical interpolation models. An implication of this work is that policies to reduce air pollution and exposure among pregnant women based on epidemiologic literature should take into account possible error in estimates of effect when spatial averages alone are evaluated.

Particulate matter components and subclinical atherosclerosis: common approaches to estimating exposure in a Multi-Ethnic Study of Atherosclerosis cross-sectional study

BackgroundConcentrations of outdoor fine particulate matter (PM2.5) have been associated with cardiovascular disease. PM2.5 chemical composition may be responsible for effects of exposure to PM2.5.MethodsUsing data from the Multi-Ethnic Study of Atherosclerosis (MESA) collected in 2000–2002 on 6,256 US adults without clinical cardiovascular disease in six U.S. metropolitan areas, we investigated cross-sectional associations of estimated long-term exposure to total PM2.5 mass and PM2.5 components (elemental carbon [EC], organic carbon [OC], silicon and sulfur) with measures of subclinical atherosclerosis (coronary artery calcium [CAC] and right common carotid intima-media thickness [CIMT]). Community monitors deployed for this study from 2007 to 2008 were used to estimate exposures at baseline addresses using three commonly-used approaches: (1) nearest monitor (the primary approach), (2) inverse-distance monitor weighting and (3) city-wide average.ResultsUsing the exposure estimate based on nearest monitor, in single-pollutant models, increased OC (effect estimate [95% CI] per IQR: 35.1 μm [26.8, 43.3]), EC (9.6 μm [3.6,15.7]), sulfur (22.7 μm [15.0,30.4]) and total PM2.5 (14.7 μm [9.0,20.5]) but not silicon (5.2 μm [−9.8,20.1]), were associated with increased CIMT; in two-pollutant models, only the association with OC was robust to control for the other pollutants. Findings were generally consistent across the three exposure estimation approaches. None of the PM measures were positively associated with either the presence or extent of CAC. In sensitivity analyses, effect estimates for OC and silicon were particularly sensitive to control for metropolitan area.ConclusionEmploying commonly-used exposure estimation approaches, all of the PM2.5 components considered, except silicon, were associated with increased CIMT, with the evidence being strongest for OC; no component was associated with increased CAC. PM2.5 chemical components, or other features of the sources that produced them, may be important in determining the effect of PM exposure on atherosclerosis. These cross-sectional findings await confirmation in future work employing longitudinal outcome measures and using more sophisticated approaches to estimating exposure.

Does living in slums or non-slums influence women's nutritional status? Evidence from Indian mega-cities

This article examines the intra-city distribution of women's nutritional status across eight Indian mega-cities with a specific focus on slum–non-slum divide. The analysis is based on the National Family Health Survey (2005–06) of India and highlights the dual burden of malnutrition among urban women. The results show that one in every two women in mega-cities is malnourished (either undernourished or overnourished), but a biased, analytical focus on citywide averages conceals the nature of the problem. Overnutrition among women is notably higher in non-slum areas whereas underweight persists as a key concern among slum dwellers. Cities located in the Central India (Nagpur and Indore) have the highest proportion of underweight women whereas the cities in South India (Chennai and Hyderabad) show a high prevalence of overweight women across both slum and non-slum areas. The intensity of income-related inequalities in underweight outcome is much greater for non-slum areas, whereas inequalities in overweight outcomes are higher among slums. Furthermore, regression analysis indicates that place of residence as such has no significant impact on women's nutritional status and that this elementary association is primarily a ramification mediated through other key socioeconomic correlates. Results suggest that, it would be rational to develop a comprehensive urban nutritional plan that focuses on dietary planning and behaviour change to address both type of malnutrition at the same time.

Abstract 18927: Geographic Variation of AHA's ‰Life's Simple Seven in Women

Background: Evidence shows that individuals achieving AHA’s “Life’s Simple 7” cardiovascular health metrics have significantly reduced risk of CVD incidence and mortality. Geographic variation in CVD risk factors has been previously described. We sought to determine whether CV risk as defined by optimal CV health metrics varied geographically among women. Methods: In 2009, Sister to Sister provided free cardiovascular screenings to 9,442 women in 12 cities, including Atlanta, Baltimore, Boston, Chicago, Dallas, Detroit, Jacksonville, Los Angeles, Miami, St. Louis, Tampa, and Washington, DC. Using biometric data collected from screenings supplemented by surveys on CVD risk, we analyzed variance in the “Simple 7” cardiovascular metrics by city. These metrics were defined as being physically active, having normal blood pressure, weight and blood glucose and total cholesterol levels, and eating a healthy diet. We used 6 of these 7 metrics, excluding diet, to assign each city with a risk score. Results: Few cities were at optimal health. On average, cities achieved 3.8 out of 6 cardiovascular metrics. From a regional perspective, Atlanta, Dallas and Detroit were significantly lower, and Boston and St. Louis were significantly higher than the city-wide average (see figure 1). Conclusion: Significant geographic variation exists in proportion of individuals achieving “ideal CV health” as measured by the AHA’s “Life’s Simple 7”. Given this, solutions to improve community based CV risk will need to be tailored by region.

AIR POLLUTION AND REPEATED ULTRASOUND MEASURES OF FETAL GROWTH IN MEXICO CITY

Background and Aims: Fetal growth may be affected by maternal air pollution exposure. Among a cohort of pregnant women in Mexico City, we obtained repeated fetal biometry ultrasound data to examine associations between maternal air pollution exposure in early pregnancy and changes in fetal growth. Methods: Information on factors known to impair fetal growth was collected by physical exams and questionnaires in 2010. Repeated ultrasound scans during gestation were performed to measure biometric parameters of the developing fetus [head circumference (HC), abdominal circumference (AC), femur length (FL), and biparietal diameter (BPD)]. Gestational age was estimated from these ultrasound measurements. Using 2009-2010 air pollution data from the city’s atmospheric monitoring network, first trimester citywide averages of PM2.5 were calculated for each individual. We applied linear regression to calculate individual-specific slopes for the four growth parameters. These slopes were used as the outcome in four multivariate linear models with predictors being individual-specific first trimester concentrations of PM2.5; mother’s age and education, and fetal sex. Results: Data were analyzed for 42 women. The average (SD) rates of increase (centimeters/gestational week (cm/wk) for fetal parameters (HC, AC, FL, and BPD) were: 1.01 (0.08), 1.04 (.12), 0.25 (0.02), and 0.28 (0.03) respectively. Point estimates for the association were positive for both HC (.083 cm/wk, p = 0.17, per 10 µg/m3 increment in exposure) and FL (.014 cm/wk, p = 0.43) . Reductions of -.005 cm/wk for BPD (p = 0.82) and -.170 cm/wk for AC (p = .06) per 10 µg/m3 were observed. Conclusions: Fetal parameters may respond to maternal air pollution exposures uniquely, and this response may vary by pollutant and timing of gestational exposure. This analysis of repeated ultrasound measures and first trimester PM2.5 concentrations supports the need for further work examining changes in fetal parameters associated withother pollutant exposures.