The relationship between urban sprawl and coronary heart disease in women

The association of neighborhood walkability and food environment with incident cardiovascular disease in The Maastricht Study

Built environmental determinants can drive lifestyle behaviors and potentially reduce chronic disease prevalence. Few studies exist that have examined the association of obesogenic environment exposures with cardiovascular disease (CVD) outcomes. We aim to specifically examine the association between neighborhood walkability, food environment and CVD. Data from 6117 Dutch participants of The Maastricht Study, between the ages of 40 and 75 years in the Netherlands were examined. Home addresses were linked to geographic information systems data from the Geoscience and Health Cohort Consortium to create neighborhood exposures of walkability and food environment. Perceived walkability was obtained from the Abbreviated Neighborhood Environment Walkability Scale. An 11-year incidence of CVD was defined by self-reported non-fatal or fatal event (as registered by Statistics Netherlands). Cox regression models examined the association of environment exposures with incident CVD adjusted for demographic and socioeconomic variables. There was lower incidence of CVD using the perceived walkability questionnaire in those living in the most walkable neighborhood (Quartile 4 HR: .77; 95% CI = .62, .97) but not using the objective walkability index (Quartile 4 HR: 1.10; 95% CI = .89, 1.38). There was no association between the food environment and incident CVD (Quartile 4 HR: .82; 95% CI = .65, 1.04). The discordant findings between walkability measures suggest integrating residential feedback and accounting for lived experiences should be prioritized by policymakers when designing equitable neighborhoods to prevent CVD.

Association of urban environments with Atherosclerotic cardiovascular disease: A prospective cohort study in the UK Biobank

Urban environments and cardiovascular health are closely linked, yet only a few specific exposures have been explored in isolation and mostly adopting cross-sectional design. The influence of socioeconomic status and genetic predisposition also remains unclear. Hence, leveraging the UK Biobank data (n = 206,681), we conducted a prospective analysis of 213 urban environmental variables and their association with atherosclerotic cardiovascular disease (ASCVD). The ExWAS and regularized Cox models analyses highlighted air pollution, industrial sites, and complex street networks as primary environmental risk factors. Instead, land-use density of leisure, public services, infrastructure and residential, and drinking water hardness showed a negative association with ASCVD risk. By integrating sparse canonical correlation and mediation analyses, we found distinct urban environment patterns through diverse pathways influence ASCVD. The environment characterized by pollution and complex streets impact ASCVD through adverse mental health (mediation proportion:30.7 %, 95 % CI:22.4 %-44.0 %), while highly-developed community and high-water hardness environment via cardiometabolic status (22.6 %, 95 % CI:19.7 %-26.0 %). Further, we found low socioeconomic status amplifies disadvantaged urban environment effects on ASCVD, yet there were no similar findings for ASCVD genetic predisposition. This research deepened our understanding of city-cardiovascular health links and the role of socioeconomic status, with implications for urban planning and public health interventions.

Correlation analysis of the urban community environment and health promotion among adults aged ≥ 55 years: the mediating role of physical activity

BACKGROUND

Physical health (PH), including muscle strength, endurance, and the ability to perform daily physical tasks, gradually declines with increasing age, leading to disability and an increased disease burden. Both the urban community environment (UCE) and physical activity (PA) were linked to PH.

METHODS

A total of 625 participants aged 55 years and older from Haidian and Chaoyang Districts in Beijing, China, were included in the study from September to December 2023.PH was assessed by a combined score of four tests, including BMI, chronic disease, depression and self-rated health.The Neighborhood Environment Walkability Scale-Abbreviated (NEWS-A), Center for Epidemiological Survey-Depression Scale (CES-D), Physical Activity Scale for Elderly (PASE) and Social Support Rate Score (SSRS) were collected. The analysis was carried out with SPSS v.20 and Amos 24, and the results were validated via structural equation modeling (SEM).

RESULTS

The urban community environment was positively associated with the health level of older adults. Specifically, the standardized path coefficients indicate that the influence of the built environment (0.72-0.88) was greater than that of the social environment (0.43-0.55) and personal attributes (0.22-0.37) on older adults' health. Physical activity demonstrated both a mediating effect and an indirect effect, highlighting its significant value as a mediating variable.

CONCLUSIONS

The urban community environment has a positive impact on promoting the physical health of older adults, with the influence of the built environment being greater than that of the social environment and personal attributes on their physical health. Physical activity acts as a mediator between the urban community environment and the physical health of older adults.

Intergenerational Occurrence of Premature Birth and Reproductive Health in Prematurely-Born Women in the Women's Health Initiative

OBJECTIVE

To compare reproductive history and postmenopausal health by birth status (preterm vs. full term) in a U.S. longitudinal study of postmenopausal women. Birth status was examined according to region of residence, household, and neighborhood socioeconomic status (SES).

METHODS

In the Women's Health Initiative Observational Study, 2271 women were born prematurely (< 37 weeks). ANOVA and Chi-square determined birth status differences of reproductive history, pregnancy, and postmenopausal health. Odds ratios were calculated using either binary logistic or multinomial logistic regression. SES and U.S. region of residence were examined as potential effect modifiers.

RESULTS

Preterm-born women compared to term-born women had higher risk of delivering a premature infant (aOR 1.68, 95% CI [1.46, 1.93]), higher odds of later-age first pregnancy (aOR 1.27 95% CI [1.02, 1.58]), longer duration to become pregnant (> 1 year to pregnancy) (aOR 1.10 95% CI [1.01, 1.21]), more miscarriages (aOR 1.23 95% CI [1.11, 1.37]), and more pregnancy complications including hypertension (aOR 1.58 95% CI (1.13, 2.21)], preeclampsia (aOR 1.64 95% CI [1.24, 2.16]), and gestational diabetes (aOR 1.68 95% CI [1.11, 2.53]). Preterm-born women had higher odds of menopause before age 50 (aOR 1.09 95% CI [1.05, 1.14]). Post-menopause, they had higher rates of diabetes (p = .01), hypertension (p = .01), hysterectomy (p = .045), and higher Charlson Comorbidity Index scores (p = .01).

CONCLUSIONS

Preterm-born women had higher reproductive and pregnancy risks which when coupled with early menopause, may indicate a shorter childbearing period than term-born women. Guidelines for integration of preterm history in women's health care across the life course are needed to identify and manage their higher risk.

Associations between urban exposome and recurrence risk among survivors of acute myocardial infarction in Beijing, China

Few previous studies have investigated the impacts of coexposure to multiple urban environmental factors on the prognosis of acute myocardial infarction (AMI) events. This study aimed to evaluate the associations between the urban exposome and AMI recurrence. We used data from 88,509 AMI patients from a large cohort obtained from the Beijing Cardiovascular Disease Surveillance System between 2013 and 2019. Twenty-six types of urban exposures were assessed within 300-m, 500-m, and 1000-m buffers of patients' home addresses in the baseline and cumulative average levels. We used the Cox proportional hazard model along with the Elastic Net (ENET) algorithm to estimate the hazard ratios (HRs) of recurrent AMI per interquartile range increase in each selected urban exposure. The increased risk of AMI recurrence was significantly associated with lower urban function diversity in the 500-m buffer, longer distance to subway stations and higher PM2.5 for both baseline and cumulative average exposure. The cumulative averages of two urban factors, including the distance to parks, and the density of fruit and vegetable shops in the 1000-m buffer, were also identified as significant factors affecting the risk of AMI recurrence. These findings can help improve the urban design for promoting human cardiovascular health.

Spatial scale analysis for the relationships between the built environment and cardiovascular disease based on multi-source data

To examine what built environment characteristics improve the health outcomes of human beings is always a hot issue. While a growing literature has analyzed the link between the built environment and health, few studies have investigated this relationship across different spatial scales. In this study, eighteen variables were selected from multi-source data and reduced to eight built environment attributes using principal component analysis. These attributes included socioeconomic deprivation, urban density, street walkability, land-use diversity, blue-green space, transportation convenience, ageing, and street insecurity. Multiscale geographically weighted regression was then employed to clarify how these attributes relate to cardiovascular disease at different scales. The results indicated that: (1) multiscale geographically weighted regression showed a better fit of the association between the built environment and cardiovascular diseases than other models (e.g., ordinary least squares and geographically weighted regression), and is thus an effective approach for multiscale analysis of the built environment and health associations; (2) built environment variables related to cardiovascular diseases can be divided into global variables with large scales (e.g., socioeconomic deprivation, street walkability, land-use diversity, blue-green space, transportation convenience, and ageing) and local variables with small scales (e.g., urban density and street insecurity); and (3) at specific spatial scales, global variables had trivial spatial variation across the area, while local variables showed significant gradients. These findings provide greater insight into the association between the built environment and lifestyle-related diseases in densely populated cities, emphasizing the significance of hierarchical and place-specific policy formation in health interventions.

Associations of Urban Built Environment with Cardiovascular Risks and Mortality: a Systematic Review

With rapid urbanization, built environment has emerged as a set of modifiable factors of cardiovascular disease (CVD) risks. We conducted a systematic review to synthesize evidence on the associations of attributes of urban built environment (e.g. residential density, land use mix, greenness and walkability) with cardiovascular risk factors (e.g. hypertension and arterial stiffness) and major CVD events including mortality. A total of 63 studies, including 31 of cross-sectional design and 32 of longitudinal design conducted across 21 geographical locations and published between 2012 and 2023 were extracted for review. Overall, we report moderately consistent evidence of protective associations of greenness with cardiovascular risks and major CVD events (cross-sectional studies: 12 of 15 on hypertension/blood pressure (BP) and 2 of 3 on arterial stiffness; and longitudinal studies: 6 of 8 on hypertension/BP, 7 of 8 on CVD mortality, 3 of 3 on ischemic heart disease mortality and 5 of 8 studies on stroke hospitalization or mortality reporting significant inverse associations). Consistently, walkability was associated with lower risks of hypertension, arterial stiffness and major CVD events (cross-sectional studies: 11 of 12 on hypertension/BP and 1 of 1 on arterial stiffness; and longitudinal studies: 3 of 6 on hypertension/BP and 1 of 2 studies on CVD events being protective). Sixty-seven percent of the studies were rated as "probably high" risk of confounding bias because of inability to adjust for underlying comorbidities/family history of diseases in their statistical models. Forty-six percent and 14% of the studies were rated as "probably high" risk of bias for exposure and outcome measurements, respectively. Future studies with robust design will further help elucidate the linkages between urban built environment and cardiovascular health, thereby informing planning policies for creating healthy cities.

Associations of maternal preterm birth with subsequent risk for type 2 diabetes in women from the women's health initiative

Preterm birth has been associated with insulin resistance and beta-cell dysfunction, a hallmark characteristic of type 2 diabetes. However, studies investigating the relationship between a personal history of being born preterm and type 2 diabetes are sparse. We sought to investigate the potential association between a personal history of being born preterm and risk for type 2 diabetes in a racially and ethnically diverse population. Baseline and incident data (>16 years of follow-up) from the Women's Health Initiative (n = 85,356) were used to examine the association between personal history of being born preterm (born 1910-1940s) and prevalent (baseline enrollment; cross-sectional) or incident (prospective cohort) cases of type 2 diabetes. Logistic and Cox proportional hazards regression models were used to estimate odds and hazards ratios. Being born preterm was significantly, positively associated with odds for prevalent type 2 diabetes at enrollment (adjOR = 1.79, 95% CI 1.43-2.24; P < 0.0001). Stratified regression models suggested the positive associations at baseline were consistent across race and ethnicity groups. However, being born preterm was not significantly associated with risk for incident type 2 diabetes. Regression models stratified by age at enrollment suggest the relationship between being born preterm and type 2 diabetes persists only among younger age groups. Preterm birth was associated with higher risk of type 2 diabetes but only in those diagnosed with type 2 diabetes prior to study enrollment, suggesting the association between preterm birth and type 2 diabetes may exist at earlier age of diagnosis but wane over time.

Measuring the effects of Compactness/Sprawl on COVID 19 spread patterns at the neighborhood level

This study analyzes the compactness/sprawl index and its effects on the spread of COVID-19 in the neighborhoods of Ahvaz, Iran. Multiple Criteria Decision Making and GIS techniques were used to develop the index. Also, the effects of compactness/sprawl on COVID-19 were investigated using a regression model. It was found that when considering the number of COVID-19 cases per 1000 people, the compactness/sprawl index did not affect the spread of the disease. However, it had a low but significant effect if the raw number of cases was considered. Results also showed that the compactness index significantly affected the raw number of cases, with a coefficient of 0.291, indicating that more compact neighborhoods had more COVID-19 cases. This is unsurprising as more people live in compact areas and, therefore, the raw number of cases is also likely to be higher. In the absence of proper control measures, this could result in further contact between people, thereby, increasing the risk of virus spread. Overall, we found that compactness had a dual effect on the spread of COVID-19 in Ahvaz. We conclude that proper development and implementation of control measures in well-designed compact neighborhoods are essential for enhancing pandemic resilience.

A Semiparametric Approach to Model-Based Sensitivity Analysis in Observational Studies

When drawing causal inference from observational data, there is almost always concern about unmeasured confounding. One way to tackle this is to conduct a sensitivity analysis. One widely-used sensitivity analysis framework hypothesizes the existence of a scalar unmeasured confounder U and asks how the causal conclusion would change were U measured and included in the primary analysis. Work along this line often makes various parametric assumptions on U, for the sake of mathematical and computational convenience. In this article, we further this line of research by developing a valid sensitivity analysis that leaves the distribution of U unrestricted. Compared to many existing methods in the literature, our method allows for a larger and more flexible family of models, mitigates observable implications (Franks et al., 2019), and works seamlessly with any primary analysis that models the outcome regression parametrically. We construct both pointwise confidence intervals and confidence bands that are uniformly valid over a given sensitivity parameter space, thus formally accounting for unknown sensitivity parameters. We apply our proposed method on an influential yet controversial study of the causal relationship between war experiences and political activeness using observational data from Uganda.

Health and Environmental Co-Benefits of City Urban Form in Latin America: An Ecological Study

We investigated the association of urban landscape profiles with health and environmental outcomes, and whether those profiles are linked to environmental and health co-benefits. In this ecological study, we used data from 208 cities in 8 Latin American countries of the SALud URBana en América Latina (SALURBAL) project. Four urban landscape profiles were defined with metrics for the fragmentation, isolation, and shape of patches (contiguous area of urban development). Four environmental measures (lack of greenness, PM_2.5, NO₂, and carbon footprint), two cause-specific mortality rates (non-communicable diseases and unintentional injury mortality), and prevalence of three risk factors (hypertension, diabetes, and obesity) for adults were used as the main outcomes. We used linear regression models to evaluate the association of urban landscape profiles with environmental and health outcomes. In addition, we used finite mixture modeling to create co-benefit classes. Cities with the scattered pixels profile (low fragmentation, high isolation, and compact shaped patches) were most likely to have positive co-benefits. Profiles described as proximate stones (moderate fragmentation, moderate isolation, and irregular shape) and proximate inkblots (moderate-high fragmentation, moderate isolation, and complex shape) were most likely to have negative co-benefits. The contiguous large inkblots profile (low fragmentation, low isolation, and complex shape) was most likely to have mixed benefits.

Built Environments and Cardiovascular Health: REVIEW AND IMPLICATIONS

PURPOSE

This review presents a general overview of the state of evidence on the relationships between neighborhood built environments and cardiovascular health outcomes among adults. We also summarize relevant literature on the associations of built environments with active living behaviors (physical activity [PA] and sedentary behavior), as they are considered as key behavioral pathways.

REVIEW METHODS

We identified recently published systematic reviews assessing associations of built environment attributes with cardiovascular health outcomes or active living behaviors. We summarized findings of the key systematic reviews and presented findings of pertinent empirical studies, where appropriate.

SUMMARY

Increasing evidence suggests that living in a place supportive of engaging in PA for transportation (eg, walkability features) and recreation (eg, parks) can be protective against cardiovascular disease (CVD) risk. Places conducive to higher levels of sedentary travel (ie, prolonged sitting in cars) may have adverse effects on cardiovascular health. The built environment of where people live can affect how active they are and subsequently their cardiovascular health. Clinical professionals are encouraged to consider the built environment features of where their patients live in counseling, as this may assist them to understand potential opportunities or barriers to active living and to propose a suitable CVD prevention strategy.

Multiple pathways and mediation effects of built environment on kidney disease rate via mitigation of atmospheric threats

Air pollution and high temperatures can increase kidney disease rate, especially under climate change. A well-designed urban environment has mediating effects on atmospheric environmental threats and promoting human health, but previous studies have overlooked these effects. This study used partial least squares modeling and urban-scale data from Taiwan to identify the crucial effects (i.e., direct, indirect, and total effects) and pathways of urban form (i.e., urban development intensity, land-use mix, and urban sprawl), urban greening (i.e., green coverage), urban industrial status (e.g., industrial level), atmospheric environment (i.e., high temperature and air pollution), and socioeconomic status (i.e., elderly ratio, medical resources, and economic status) on kidney disease rate. Maximizing land-use mix and green coverage and minimizing urban development intensity, urban sprawl, and industrial levels could help reduce kidney disease rate. Air pollution and high temperature had a mediation effect of built environment on kidney disease rate; with the mediation effect of air pollution was greater than that of high temperature. Furthermore, air pollution, high temperature, and elderly ratio increased kidney disease rate, whereas medical resources decreased kidney disease rate. This study is the first to consider the impact (i.e., direct, indirect, and total effects) and pathways of built environment characteristics on kidney disease rate. The findings revealed that an appropriate urban policy might be a practical strategy and lower kidney disease rate for a healthy city development. Moreover, this study provides a new approach for clarifying complex relationships and identifying crucial factors.

Does living near hospital obscure the association between active living environments and hospitalization?

Hospitals tend to be among the destinations that make densely populated, well-connected neighbourhoods more conducive to active living. In this study, we determined whether living near a hospital distorts the association between living in favourable ALEs and hospitalization for physical inactivity-related cardiometabolic diseases. We used a record linkage of 442,345 respondents of the Canadian Community Health Survey and their hospitalization records for cardiometabolic disease. We then assessed respondents' neighbourhoods using the Canadian Active Living Environments measure (Can-ALE), a measure based on ≥3-way intersection density, residential density, and points of interest. We then calculated the distance in kilometers between the centroids of respondents' assigned dissemination areas and the nearest user-contributed location for hospitals from OpenStreetMap. We monitored changes in estimates for the association between ALEs and odds of cardiometabolic disease hospitalization using a series of logistic regressions with indicator variables for distances to hospital of 500 meters to 10 kilometers. We found that living between 500 meters and six kilometers of a hospital and was associated with modestly higher odds of cardiometabolic hospitalization (OR 1.10, 95% CI 1.02 to 1.18 for 500 meters; OR 1.05, 95% CI 1.01 to 1.09 for six kilometers). Living in more favourable ALEs was associated with lower odds of hospitalization (OR 0.79, 95% CI 0.68 to 0.91; comparing the most favourable to least favourable ALEs). Effect estimates between more favourable ALEs and lower odds of hospitalization were marginally strengthened when living within 2-6 kilometers to a hospital was accounted for. This study demonstrates the importance of disentangling interrelated geographic factors and underlines the potential for built environments to elicit reductions in health care.

Joint associations between neighborhood walkability, greenness, and particulate air pollution on cardiovascular mortality among adults with a history of stroke or acute myocardial infarction

Fine particulate matter (PM_2.5) is a known risk factor for cardiovascular disease (CVD). Neighborhood walkability and greenness may also be associated with CVD, but there is limited evidence on their joint or interacting effects with PM_2.5.

Neighbourhood walkability and mortality: Findings from a 15-year follow-up of a nationally representative cohort of Canadian adults in urban areas

BACKGROUND

Using a nationally representative cohort of Canadian adults, we assessed associations between neighbourhood walkability and cause-specific mortality and investigated whether they differed by socioeconomic status.

METHODS

The study population was drawn from the 2001 Canadian Census Health and Environment Cohort, which contains individual-level data from a random sample of 20% of Canadian households mandated to complete the long-form census. We included those aged ≥ 25 years at baseline who lived in urban and suburban areas. The national death registry was used to ascertain annual vital status. Linkages to annual income tax data provided place of residence. The Canadian Active Living Environments, a national index that summarizes walkability across Canadian neighbourhoods, was assigned to individuals' residential history. The Cox proportional hazards model was used to assess associations between walkability and cause-specific mortality.

RESULTS

A total of 1.8 million participants (52.5% female) accrued 27.3 million person-years and 265 710 deaths during the 15-year follow-up. The adjusted hazard ratio (HR) for living in a highly walkable neighbourhood relative to living in the least walkable neighbourhoods was associated with a 9% (HR: 0.91 [0.88, 0.95]) and 3% (HR: 0.97 [0.94, 0.99]) reduced risk of cardiovascular and all non-accidental mortality, respectively. The strongest benefits of walkability were found among individuals within the lowest education and household income categories, and who lived in the most deprived neighbourhoods. There were no significant associations (most [class 5] versus least [class 1] walkable HR: 0.84 [0.61-1.16]) seen for accidental traffic mortality.

CONCLUSIONS

Canadian adults who live in walkable neighbourhoods have lower rates of cardiovascular and non-accidental mortality, with the greatest benefits seen in those from the lowest socioeconomic groups.

Associations of Urban Environment Features with Hypertension and Blood Pressure across 230 Latin American Cities

BACKGROUND

Features of the urban physical environment may be linked to the development of high blood pressure, a leading risk factor for global burden of disease.

OBJECTIVES

We examined associations of urban physical environment features with hypertension and blood pressure measures in adults across 230 Latin American cities.

METHODS

In this cross-sectional study we used health, social, and built environment data from the SALud URBana en América Latina (SALURBAL) project. The individual-level outcomes were hypertension and levels of systolic and diastolic blood pressure. The exposures were city and subcity built environment features, mass transit infrastructure, and green space. Odds ratios (ORs) and mean differences and 95% confidence intervals (CIs) were estimated using multilevel logistic and linear regression models, with single- and multiple-exposure models adjusted for individual-level age, sex, education, and subcity educational attainment.

RESULTS

A total of 109,176 participants from 230 cities and eight countries were included in the hypertension analyses and 50,228 participants from 194 cities and seven countries were included in the blood pressure measures analyses. Participants were 18-97 years of age. In multiple-exposure models, higher city fragmentation was associated with higher odds of having hypertension (OR per standard deviation (SD) increase=1.11; 95% CI: 1.01, 1.21); presence (vs. no presence) of mass transit in the city was associated with higher odds of having hypertension (OR=1.30; 95% CI: 1.09, 1.54); higher subcity population density was associated with lower odds of having hypertension (OR per SD increase=0.90; 95% CI: 0.85, 0.94); and higher subcity intersection density was associated with higher odds of having hypertension [OR per SD increase=1.09; 95% CI: 1.04, 1.15). The presence of mass transit was also associated with slightly higher systolic and diastolic blood pressure in multiple-exposure models adjusted for treatment. Except for the association between intersection density and hypertension, associations were attenuated after adjustment for country. An inverse association of greenness with continuous blood pressure emerged after country adjustment.

DISCUSSION

Our results suggest that urban physical environment features-such as fragmentation, mass transit, population density, and intersection density-may be related to hypertension in Latin American cities. Reducing chronic disease risks in the growing urban areas of Latin America may require attention to integrated management of urban design and transport planning. https://doi.org/10.1289/EHP7870.

Associations of Urban Environment Features with Hypertension and Blood Pressure across 230 Latin American Cities

BACKGROUND

Features of the urban physical environment may be linked to the development of high blood pressure, a leading risk factor for global burden of disease.

OBJECTIVES

We examined associations of urban physical environment features with hypertension and blood pressure measures in adults across 230 Latin American cities.

METHODS

In this cross-sectional study we used health, social, and built environment data from the SALud URBana en América Latina (SALURBAL) project. The individual-level outcomes were hypertension and levels of systolic and diastolic blood pressure. The exposures were city and subcity built environment features, mass transit infrastructure, and green space. Odds ratios (ORs) and mean differences and 95% confidence intervals (CIs) were estimated using multilevel logistic and linear regression models, with single- and multiple-exposure models adjusted for individual-level age, sex, education, and subcity educational attainment.

RESULTS

A total of 109,176 participants from 230 cities and eight countries were included in the hypertension analyses and 50,228 participants from 194 cities and seven countries were included in the blood pressure measures analyses. Participants were 18-97 years of age. In multiple-exposure models, higher city fragmentation was associated with higher odds of having hypertension (OR per standard deviation (SD) increase=1.11; 95% CI: 1.01, 1.21); presence (vs. no presence) of mass transit in the city was associated with higher odds of having hypertension (OR=1.30; 95% CI: 1.09, 1.54); higher subcity population density was associated with lower odds of having hypertension (OR per SD increase=0.90; 95% CI: 0.85, 0.94); and higher subcity intersection density was associated with higher odds of having hypertension [OR per SD increase=1.09; 95% CI: 1.04, 1.15). The presence of mass transit was also associated with slightly higher systolic and diastolic blood pressure in multiple-exposure models adjusted for treatment. Except for the association between intersection density and hypertension, associations were attenuated after adjustment for country. An inverse association of greenness with continuous blood pressure emerged after country adjustment.

DISCUSSION

Our results suggest that urban physical environment features-such as fragmentation, mass transit, population density, and intersection density-may be related to hypertension in Latin American cities. Reducing chronic disease risks in the growing urban areas of Latin America may require attention to integrated management of urban design and transport planning. https://doi.org/10.1289/EHP7870.

Exploring multiple pathways and mediation effects of urban environmental factors for suicide prevention

Public health is threatened by air pollution and high temperature, especially in urban areas and areas impacted by climate change. Well-designed urban forms have co-benefits on promoting human health and mediating atmospheric environment-related threats (e.g., high temperature and air pollution). Previous studies overlooked these mediating effects of urban form on suicide mortality. This study used partial least squares modeling and countywide data in Taiwan to identify the crucial influences and pathways of urban environment, socioeconomic status, and diseases on suicide mortality. The model considered the impact of the characteristics of urban form (i.e., urban development intensity, land mix, and urban sprawl), urban industrial status (i.e., industrial level), urban greening (i.e., green coverage), disease (i.e., important diseases morbidity of human immunodeficiency virus [HIV], cerebrovascular disease [CVD], chronic liver disease and cirrhosis [CLDC], nephritis, nephrotic syndrome and nephrosis [NNSN], malignant tumor [MT]), socioeconomic status (i.e., income level and aging population rate), and the atmospheric environment (i.e., air pollution and high temperature) on suicide mortality. Optimizing land mix and minimizing urban development intensity and urban sprawl have been found to reduce suicide mortality. The mediating effect of urban form on suicide mortality originated from air pollution and high temperature, and mediating air pollution was greater than high temperature. Furthermore, industrial level, important diseases (HIV, CVD, CLDC, NNSN, and MT) morbidity, an aging population rate, air pollution, and high temperature were associated with an increase in suicide mortality, whereas green coverage and income level were associated with a reduction in suicide rates. The findings demonstrate that appropriate urban policy and urban planning may lower suicide mortality, be useful strategies for suicide prevention, and be a foundation for building a healthy city. Moreover, this study provides clarity on the complex relationship of suicide and the urban environment while identifying crucial factors.

Estimating 24-Hour Urinary Excretion of Sodium and Potassium Is More Reliable from 24-Hour Urine Than Spot Urine Sample in a Feeding Study of US Older Postmenopausal Women

BACKGROUND

Assessing estimated sodium (Na) and potassium (K) intakes derived from 24-h urinary excretions compared with a spot urine sample, if comparable, could reduce participant burden in epidemiologic and clinical studies.

OBJECTIVES

In a 2-week controlled-feeding study, Na and K excretions from a 24-h urine collection were compared with a first-void spot urine sample, applying established algorithms and enhanced models to estimate 24-h excretion. Actual and estimated 24-h excretions were evaluated relative to mean daily Na and K intakes in the feeding study.

METHODS

A total of 153 older postmenopausal women ages 75.4 ± 3.5 y participated in a 2-wk controlled-feeding study with a 4-d repeating menu cycle based on their usual intake (ClinicalTrials.gov Identifier: NCT00000611). Of the 150 participants who provided both a first-void spot urine sample and a 24-h urine collection on the penultimate study day, statistical methods included Pearson correlations for Na and K between intake, 24-h collections, and the 24-h estimated excretions using 4 established algorithms: enhanced biomarker models by regressing ln-transformed intakes on ln-transformed 24-h excretions or ln-transformed 24-h estimated excretions plus participant characteristics and sensitivity analyses for factors potentially influencing Na or K excretion (e.g., possible kidney disease estimated glomerular filtration rate <60 mL/min/1.73 m2 ).

RESULTS

Pearson correlation coefficients between Na and K intakes and actual 24-h excretions were 0.57 and 0.38-0.44 for estimated 24-h excretions, depending on electrolyte and algorithm used. Enhanced biomarker model cross-validated R 2 (CVR2) for 24-h excretions were 38.5% (Na), 40.2% (K), and 42.0% (Na/K). After excluding participants with possible kidney disease, the CVR2 values were 43.2% (Na), 40.2% (K), and 38.1% (Na/K).

CONCLUSIONS

Twenty-four-hour urine excretion measurement performs better than estimated 24-h excretion from a spot urine as a biomarker for Na and K intake among a sample of primarily White postmenopausal women.

How Does Urban Sprawl Affect Public Health? Evidence from Panel Survey Data in Urbanizing China

This study takes urbanizing China as the research object, employs data from three follow-up surveys conducted by the Harmonized China Health and Retirement Longitudinal Study, and examines the effects of urban sprawl on public health from physical and mental health perspectives. Although urban sprawl does not necessarily increase the risk of each specific type of disease or psychological feeling, it has a significant impact on overall physical and mental health. Further analysis reveals significant heterogeneity in the effects of urban sprawl on the physical and mental health of different groups. Specifically, urban sprawl is detrimental to the physical health of males and females, but only has negative impact on the mental health of females. Younger groups are more vulnerable to physical and mental health damage from urban sprawl relative to middle-aged and older groups. In addition, urban sprawl has a significant negative impact on the health of the low-education group but a very limited impact on the health of the high-education counterpart. From an income perspective, however, the preference for suburban housing among middle- and high-income groups makes their health more vulnerable to the negative effects of urban sprawl than low-income groups living in urban centers.

Mediation analysis of racial disparities in triple-negative breast cancer incidence among postmenopausal women

BACKGROUND

Triple-negative breast cancer (TNBC) is disproportionately higher in Black women relative to White women. The objective of this study was to examine to what extent the association between race/ethnicity and risk of TNBC is mediated by potentially modifiable factors.

METHODS

A total of 128,623 Black and White women aged 50-79 years from the Women's Health Initiative were followed for a mean of 15.8 years. 643 incident TNBC cases (92 Black women and 551 White women) were confirmed by medical record review. Mediation analyses were conducted using an approach under a counterfactual framework.

RESULTS

Black women had approximately twofold higher risk of TNBC compared with white women (HR = 1.93, 95% CI 1.52-2.45). We observed that 48% of the racial disparity was mediated by metabolic dysfunction defined by having 3 or more cardiometabolic risk factors including elevated waist circumference, having history of diabetes, high cholesterol and hypertension. The racial disparity was not significantly mediated by other factors studied, including socioeconomic, lifestyle or reproductive factors.

CONCLUSION

Our study observed that approximately half of the racial disparity between postmenopausal Black and White women in TNBC incidence was driven by metabolic dysfunction.

Biomarkers of phthalates and inflammation: Findings from a subgroup of Women's Health Initiative participants

BACKGROUND

Recent experimental work has shown that phthalates may increase inflammation. Prior research has not examined the role of exposure to phthalates in relation to inflammatory status among postmenopausal women who are at higher risk of developing inflammation-related chronic disorders.

OBJECTIVES

We aimed to examine the associations of urinary phthalate biomarker concentrations with circulating levels of c-reactive protein [CRP] and interleukin-6 [IL-6] among 443 postmenopausal women selected into a breast cancer case-control study nested within the Women's Health Initiative (WHI).

METHODS

A total of 13 phthalate metabolites were measured in urine samples provided at WHI enrollment from 1993 to 1998. We also measured baseline levels of CRP and IL-6 in these women's serum or plasma samples. Multivariable linear models were used to investigate the role of each phthalate biomarker in relation to CRP and IL-6, adjusting for potential confounding factors and specifically evaluating the role of BMI.

RESULTS

In adjusted models we observed positive associations of monocarboxynonyl phthalate (MCNP) with CRP (β = 0.092; 95% CI 0.026, 0.158) and IL-6 (β = 0.108; 95% CI 0.013, 0.204). These positive associations were attenuated and non-significant, however, after further adjustment for body mass index (BMI). In contrast, we observed inverse associations of monoethyl phthalate (MEP) (β = -0.019; 95% CI -0.036, -0.001) and monobenzyl phthalate (MBzP) (β = -0.034; 95% CI -0.058, -0.010) with CRP levels only after adjustment for BMI. Other phthalate biomarkers examined were not significantly associated with either CRP or IL-6 levels.

CONCLUSIONS

Overall, these results do not suggest an important role for phthalates in promoting an inflammatory response. Future prospective studies are warranted to improve understanding of these associations, particularly in clarifying the role of BMI.

Socioeconomic status as an effect modifier of the association between built environment and mortality in elderly Hong Kong Chinese: A latent profile analysis

BACKGROUND

Previous studies have focused on associations between individual built environment (BE) characteristics and mortality, and found the BE-mortality associations differed by socioeconomic status (SES). Different individual BE characteristics may have different impacts on health and thus could interact. Combinations of BE characteristics may be a better approach to explore the BE-mortality associations.

OBJECTIVES

This study aimed to investigate the associations of BE pattern with mortality in a prospective cohort of elderly Hong Kong Chinese (Mr. OS and Ms. OS Study), and assess whether the BE-mortality association differed by SES.

METHODS

Between 2001 and 2003, 3944 participants aged 65-98 years at baseline were included in the present analysis. BE characteristics were assessed via Geographic Information System. Data on all-cause and cause-specific mortality were obtained from the Hong Kong Government Death Registry. Latent profile analysis was used to derive BE class, and the Cox proportional hazards model was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs).

RESULTS

Three BE classes were identified. During a total of 53276 person-years of follow-up, 1632 deaths were observed. There were no significant associations of BE class with all-cause and cause-specific mortality. However, we found the associations of BE class with all-cause mortality were modified by SES. In comparison with Class 3 (characterized by greater green space), HRs (95%CIs) were 0.72 (0.54, 0.97) for Class 1 (characterized by greater commercial land use) and 0.77 (0.64, 0.94) for Class 2 (characterized by greater residential land use) among low-SES participants. The associations were stronger among high-SES participants, with 0.55 (0.33, 0.89) for Class 1 and 0.68 (0.48, 0.97) for Class 2. In contrast, Class 2 (HR 1.18, 95%CI 1.01-1.39) had a higher mortality risk compared with Class 3 among middle-SES participants.

CONCLUSIONS

Our findings provide new evidence on the role of SES as an effect modifier of BE pattern and mortality. BE pattern has a varied effect on mortality risk for different SES groups.

Active living environments, physical activity and premature cardiometabolic mortality in Canada: a nationwide cohort study

OBJECTIVE

To evaluate sex-specific and age-specific associations of active living environments (ALEs) with premature cardiometabolic mortality.

DESIGN

Population-based retrospective cohort study.

SETTING

Residential neighbourhoods (1000-metre circular buffers from the centroids of dissemination areas) across Canada for which the Canadian ALE Measure was derived, based on intersection density, points of interest and dwelling density.

PARTICIPANTS

249 420 survey respondents from an individual-level record linkage between the Canadian Community Health Survey (2000-2010) and the Canadian Mortality Database until 2011, comprised of older women (65-85 years), older men (65-81 years), middle-aged women (45-64 years) and middle-aged men (45-64 years).

PRIMARY OUTCOME MEASURES

Premature cardiometabolic mortality and average daily energy expenditure attributable to walking. Multivariable proportional hazards regression models were adjusted for age, educational attainment, dissemination area-level median income, smoking status, obesity, the presence of chronic conditions, season of survey response and survey cycle.

RESULTS

Survey respondents contributed a total of 1 451 913 person-years. Greater walking was observed in more favourable ALEs. Walking was associated with lower cardiometabolic death in all groups except for middle-aged men. Favourable ALEs conferred a 22% reduction in death from cardiometabolic causes (HR 0.78, 95% CI 0.63 to 0.97) for older women.

CONCLUSIONS

On average, people walk more in favourable ALEs, regardless of sex and age. With the exception of middle-aged men, walking is associated with lower premature cardiometabolic death. Older women living in neighbourhoods that favour active living live longer.

Multiple impacts and pathways of urban form and environmental factors on cardiovascular mortality

Air pollution and heat are significant threats to public health, especially in urban areas with intensive human activities under the trend of climate change. However, the mediation effects of urban form on health via air pollution and heat have been overlooked in previous investigations. This study explored the potential impacts and pathways of urban form on cardiovascular mortality through air pollutants and heat by using partial least squares model with data from Taiwan. The measurable characteristics of urban form include city size, urban sprawl, and mixed land use. Other factors that influence cardiovascular mortality, such as urban industrial level, economic status, aging population, and medical resource, were also considered in the model. Results revealed that maximizing mixed land use and minimizing city size and urban sprawl can help reduce cardiovascular mortality, and the minimizing city size was the most important one. Urban industrial level, economic status, aging population, and medical resource were also influential factors. This is the first study to consider the pathways and impacts of urban form on cardiovascular mortality, and our results indicate that proper urban planning and policy could reduce cardiovascular mortality.

Robust estimation of the causal effect of time-varying neighborhood factors on health outcomes

The fundamental difficulty of establishing causal relationships between an exposure and an outcome in observational data involves disentangling causality from confounding factors. This problem underlies much of neighborhoods research, which abounds with studies that consider associations between neighborhood characteristics and health outcomes in longitudinal data. Such analyses are confounded by selection issues; individuals with above average health outcomes (or associated characteristics) may self-select into advantaged neighborhoods. Techniques commonly used to assess causal inferences in observational longitudinal data, such as inverse probability of treatment weighting (IPTW), may be inappropriate in neighborhoods data due to unique characteristics of such data. We advance the IPTW toolkit by introducing a procedure based on a multivariate kernel density function which is more appropriate for neighborhoods data. The proposed weighting method is applied in conjunction with a marginal structural model. Our empirical analyses use longitudinal data from the Health and Retirement Study; our exposure of interest is an index of neighborhood socioeconomic status (NSES), and we examine its influence on cognitive function. Our findings illustrate the importance of the choice of method for IPTW-the comparison weighting methods provide poor balance across the set of covariates (which is not the case for our preferred procedure) and yield misleading results when applied in the outcomes models. The utility of the multivariate kernel is also validated via simulation. In addition, our findings emphasize the importance of IPTW-controlling for covariates within a regression without IPTW indicates that NSES affects cognition, whereas IPTW-weighted models fail to show a statistically significant effect.

Socio-Demographic Determinants of Mortality from Chronic Noncommunicable Diseases in Women of Reproductive Age in the Republic of Georgia: Evidence from the National Reproductive Age Mortality Study (2014)

Purpose

Worldwide, noncommunicable diseases (NCDs) are the leading cause of premature death of women, taking the highest toll in developing countries. This study aimed to identify key socio-demographic determinants of NCD mortality in reproductive-aged women (15-49 years) in Georgia.

Materials and Methods

The study employed the verbal autopsy data from the second National Reproductive Age Mortality Survey 2014. Univariate and multivariate logistic regression models were fitted to explore the association between each risk factor and NCD mortality, measured by crude and adjusted odds ratio (AOR) with respective 95% confidence intervals (95% CI).

Results

In the final sample of 843 women, 586 (69.5%) deaths were attributed to NCDs, the majority of which occurred outside a hospital (72.7%) and among women aged 45-49 years (46.8%), ethnic Georgians (85.2%), urban residents (60.1%), those being married (60.6%), unemployed (75.1%) or having secondary and higher education (69.5%), but with nearly equal distribution across the wealth quintiles. After multivariate adjustment, the odds of dying from NCDs were significantly higher in women aged 45-49 years (AOR=17.69, 95% CI= 9.35 to 33.50), those being least educated (AOR=1.55, 95% CI= 1.01 to 2.37) and unemployed (AOR=1.47, 95% CI= 1.01 to 2.14) compared, respectively, to their youngest (15-24 years), more educated and employed counterparts. Strikingly, the adjusted odds were significantly lower in "other" ethnic minorities (AOR=0.29, 95% CI= 0.14 to 0.61) relative to ethnic Georgians. Contrariwise, there were no significant associations between NCD mortality and women's marital or wealth status, place of residence (rural/urban) or place of death.

Conclusion

Age, ethnicity, education, and employment were found to be strong independent predictors of young women's NCD mortality in Georgia. Further research on root causes of inequalities in mortality across the socioeconomic spectrum is warranted to inform equity- and life course-based multisectoral, integrated policy responses that would be conducive to enhancing women's survival during and beyond reproduction.

Urban Densification and 12-Year Changes in Cardiovascular Risk Markers

Background

Population densities of many cities are increasing rapidly, with the potential for impacts on cardiovascular health. This longitudinal study examined the potential impact of population‐density increases in urban areas (urban densification) on cardiovascular risk markers among Australian adults.

Methods and Results

Data were from the Australian Diabetes, Obesity and Lifestyle Study, in which adult participants’ cardiovascular risk markers were collected in 3 waves (in 1999–2000, 2004–2005, and 2011–2012). We included 2354 participants with a mean age of 51 years at baseline who did not change their residence during the study period. Outcomes were 12‐year changes in waist circumference, weight, systolic and diastolic blood pressure, fasting and 2‐hour postload plasma glucose, high‐density lipoprotein cholesterol, and triglycerides. The exposure was neighborhood population densification, defined as 12‐year change in population density within a 1‐km radius buffer around the participant’s home. Multilevel linear growth models, adjusting for potential confounders, were used to examine the relationships. Each 1% annual increase in population density was related with smaller increases in waist circumference (b=−0.043 cm/y; 95% CI, −0.065 to −0.021 [P<0.001]), weight (b=−0.019 kg/y; 95% CI, −0.039 to 0.001 [P=0.07]), and high‐density lipoprotein cholesterol (b=−0.035 mg/dL per year; 95% CI, −0.067 to −0.002 [P=0.04]), and greater increases in diastolic blood pressure (b=0.032 mm Hg/y; 95% CI, −0.004 to 0.069 [P=0.08]).

Conclusions

Our findings suggest that, at least in the context of Australia, urban densification may be protective against obesity risk but may have adverse effects on blood lipids and blood pressure. Further research is needed to understand the mechanisms through which urban densification influences cardiovascular health.

Urban Sprawl and Health Outcome Associations in Sicily

Urban sprawl has several negative impacts on the environment, the economy, and human health. The main objective of this work was to formulate and validate a sprawl/compactness index for Sicilian municipalities and evaluate its association with health outcomes. An ecological study was conducted with 110 municipalities in Sicily, Italy. Principal component analysis was adopted to create the sprawl/compactness Sicilian index, and linear regression analysis was used to evaluate the association between the sprawl index and health outcomes. More variance of the new sprawl index was explained by the working factor, followed by density, surface extension, and land use mix. When validating the index, we found that public transportation had an inverse relation with sprawl increase (p < 0.001), and private transportation was directly related to the increase in sprawl (p < 0.001). After controlling for the Sicilian socio-economic deprivation index and overall mortality, cardiovascular mortality was the only outcome directly associated with the increase in the sprawl index (odds ratio = 0.0068, p < 0.001). Urban sprawl has to be monitored in Sicily over time to understand the evolution of the urbanization phenomenon and its relationship with health outcomes such as cardiovascular mortality. The use of the sprawl index should help policymakers define the necessary strategic aspects and actions to improve human health and quality of life in cities through a multi-sectorial approach.

Predictors of urinary phthalate biomarker concentrations in postmenopausal women

BACKGROUND

Phthalates are ubiquitous endocrine disrupting chemicals present in a wide variety of consumer products. However, the personal characteristics associated with phthalate exposure are unclear.

OBJECTIVES

We sought to describe personal, behavioral, and reproductive characteristics associated with phthalate metabolite concentrations in an ongoing study nested within the Women's Health Initiative (WHI).

MATERIALS AND METHODS

We measured thirteen phthalate metabolites in two or three archived urine samples collected in 1993-2001 from each of 1257 WHI participants (2991 observations). We fit multivariable generalized estimating equation models to predict urinary biomarker concentrations from personal, behavioral, and reproductive characteristics.

RESULTS

Older age was predictive of lower concentrations of monobenzyl phthalate (MBzP), mono-carboxyoctyl phthalate (MCOP), mono-3-carboxypropyl phthalate (MCPP), and the sum of di-n-butyl phthalate metabolites (ΣDBP). Phthalate metabolite concentrations varied by race/region, with generally higher concentrations observed among non-Whites and women from the West region. Higher neighborhood socioeconomic status predicted lower MBzP concentrations, and higher education predicted lower monoethyl phthalate (MEP) and higher concentrations of the sum of metabolites of di-isobutyl phthalate (ΣDiBP). Overweight/obesity predicted higher MBzP, MCOP, monocarboxynonyl phthalate (MCNP), MCPP, and the sum of metabolites of di(2-ethylhexyl) phthalate (ΣDEHP) and lower MEP concentrations. Alcohol consumption predicted higher concentrations of MEP and ΣDBP, while current smokers had higher ΣDBP concentrations. Better diet quality as assessed by Healthy Eating Index 2005 scores predicted lower concentrations of MBzP, ΣDiBP, and ΣDEHP.

CONCLUSION

Factors predictive of lower biomarker concentrations included increased age and healthy behaviors (e.g. lower alcohol intake, lower body mass index, not smoking, higher quality diet, and moderate physical activity). Racial group (generally higher among non-Whites) and geographic regions (generally higher in Northeast and West compared to South regions) also were predictive of phthalate biomarker concentrations.

Urinary Phthalate Biomarker Concentrations and Postmenopausal Breast Cancer Risk

BACKGROUND

Growing laboratory and animal model evidence supports the potentially carcinogenic effects of some phthalates, chemicals used as plasticizers in a wide variety of consumer products, including cosmetics, medications, and vinyl flooring. However, prospective data on whether phthalates are associated with human breast cancer risk are lacking.

METHODS

We conducted a nested case-control study within the Women's Health Initiative (WHI) prospective cohort (n = 419 invasive case subjects and 838 control subjects). Control subjects were matched 2:1 to case subjects on age, enrollment date, follow-up time, and WHI study group. We quantified 13 phthalate metabolites and creatinine in two or three urine samples per participant over one to three years. Multivariable conditional logistic regression analysis was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for breast cancer risk associated with each phthalate biomarker up to 19 years of follow-up.

RESULTS

Overall, we did not observe statistically significant positive associations between phthalate biomarkers and breast cancer risk in multivariable analyses (eg, 4th vs 1st quartile of diethylhexyl phthalate, OR = 1.03, 95% CI = 0.91 to 1.17). Results were generally similar in analyses restricted to disease subtypes, to nonusers of postmenopausal hormone therapy, stratified by body mass index, or to case subjects diagnosed within three, five, or ten years.

CONCLUSIONS

In the first prospective analysis of phthalates and postmenopausal breast cancer, phthalate biomarker concentrations did not result in an increased risk of developing invasive breast cancer.

Built environment and cardio-metabolic health: systematic review and meta-analysis of longitudinal studies

Built environment attributes may be related to cardio-metabolic diseases (e.g. type 2 diabetes, heart disease and stroke) and their risk factors, potentially by influencing residents' physical activity. However, existing literature reviews on the built environment and health for the most part focus on obesity as the outcome and rely on cross-sectional studies. This systematic review synthesized current evidence on longitudinal relationships between built environment attributes and cardio-metabolic health outcomes among adults and on the potential mediating role of physical inactivity. By searching eight databases for peer-reviewed journal articles published in the English language between January 2000 and July 2016, the review identified 36 articles. A meta-analysis method, weighted Z-test, was used to quantify the strength of evidence by incorporating the methodological quality of the studies. We found strong evidence for longitudinal relationships of walkability with obesity, type 2 diabetes and hypertension outcomes in the expected direction. There was strong evidence for the impact of urban sprawl on obesity outcomes. The evidence on potential mediation by physical activity was inconclusive. Further longitudinal studies are warranted to examine which specific built environment attributes influence residents' cardio-metabolic health outcomes and how physical inactivity may be involved in these relationships.

Particulate Air Pollutants, Brain Structure, and Neurocognitive Disorders in Older Women

Introduction

An increasing number of studies have suggested that exposure to particulate matter (PM) may represent a novel - and potentially amendable - environmental determinant of brain aging. The current longitudinal environmental epidemiological study addressed some important knowledge gaps in this emerging field, which combines the study of air pollution and neuroepidemiology. The investigators hypothesized that long-term PM exposure adversely influences global brain volume and brain regions (e.g., frontal lobe or hippocampus) that are critical to memory and complex cognitive processing or that are affected by neuropathological changes in dementia. It was also hypothesized that long-term PM exposure results in neurovascular damage and may increase the risk of mild cognitive impairment (MCI) and -dementia.

Methods

The investigators selected a well-characterized and geographically diverse population of older women (N = 7,479; average age = 71.0 ± 3.8 years at baseline) in the Women's Health Initiative (WHI) Memory Study (WHIMS) cohort (1996-2007), which included a subcohort (n = 1,403) enrolled in the WHIMS-Magnetic Resonance Imaging (WHIMS-MRI) study (2005-2006). Residence-specific yearly exposures to PM ≤ 2.5 µm in aerodynamic diameter (PM₂.₅) were estimated using a Bayesian maximum entropy spatiotemporal model of annual monitoring data (1999-2007) recorded in the U.S. Environmental Protection Agency (U.S. EPA) Air Quality System (AQS). Annual exposures (1996-2005) to diesel PM (DPM) were assigned to each residential census tract in a nationwide spatiotemporal mapping, based on a generalized additive model (GAM), to conduct census tract-specific temporal interpolation of DPM on-road estimates given by the U.S. EPA National-Scale Air Toxics Assessment Program. Multiple linear regression and multicovariate-adjusted Cox models were used to examine the associations, with statistical adjustment for multiple potential confounders.

Results

The investigators found that participants had smaller brain volumes, especially in the normal-appearing white matter (WM), if they lived in locations with higher levels of cumulative exposure (1999-2006) to PM ₂.₅ before the brain MRI scans were performed. The associations were not explained by sociodemographic factors, socioeconomic status, lifestyle factors, or other clinical characteristics. Analyses showed that the adverse effect on brain structure in the participants was driven primarily by the smaller WM volumes associated with cumulative PM₂.₅ exposures, which were present in the WM divisions of the association brain area (frontal, parietal, and temporal lobes) and corpus callosum. Increased DPM exposures were associated with larger ventricular volume, suggesting an overall atrophic effect on the aging brains. The participants tended to have smaller gray matter (GM) volumes if they lived in areas with the highest (i.e., fourth quartile) estimated cumulative DPM exposure in the 10 years before the brain MRI scans, compared with women in the first to third quartiles. This observed association was present in the total brain GM and in the association brain cortices. The associations with normal-appearing WM varied by DPM exposure range. For women with estimated cumulative exposure below that of the fourth quartile, increased DPM estimates were associated with smaller WM volumes. However, for women with increased cumulative DPM exposures estimates in the fourth quartile, WM volumes were larger. This pattern of association was found consistently in the association brain area; no measurable difference was found in the volume of the corpus callosum. These observed adverse effects of cumulative exposure to PM₂.₅ (linking exposure with smaller WM volumes) and to DPM (linking exposure in the highest quartile with smaller GM volumes) were not significantly modified by existing cardiovascular diseases, diabetes mellitus, obesity, or measured white blood cell (WBC) count. MRI measurements of the structural brain showed no differences in small-vessel ischemic diseases (SVID) in participants with varying levels of cumulative exposure to PM₂.₅ (1999-2006) or DPM (1996-2005), and no associations between PM exposures and SVID volumes were noted for total brain, association brain area, GM, or WM. For neurocognitive outcomes followed until 2007, the investigators found no evidence for increased risk of MCI/dementia associated with long-term PM exposures. Although exploratory secondary analyses showed different patterns of associations linking PM exposures separately with MCI and dementia, none of the -results was statistically significant. A similar lack of associations between PM exposures and MCI/dementia was found across the subgroups, with no strong indications for effect modification by cardiovascular diseases, diabetes mellitus, obesity, or WBC count.

Conclusions

The investigators concluded that their study findings support the hypothesized brain-structure neurotoxicity associated with PM exposures, a result that is in line with emerging neurotoxicological data. However, the investigators found no evidence of increased risk of MCI/dementia associated with long-term PM exposures.

To better test the neurovascular effect hypothesis in PM-associated neurotoxic effects on the aging brain, the investigators recommend that future studies pay greater attention to selecting optimal populations with repeated measurements of cerebrovascular damage and address the possibility of selection biases accordingly. To further investigate the long-term consequence of brain-structure neurotoxicity on pathological brain aging, future researchers should take the pathobiologically heterogeneous neurocognitive outcomes into account and design adequately powered prospective cohort studies with improved exposure estimation and valid outcome ascertainment to assess whether PM-associated neurotoxicity increases the risks of pathological brain aging, including MCI and dementia.

Landmark estimation of survival and treatment effects in observational studies

Clinical studies aimed at identifying effective treatments to reduce the risk of disease or death often require long term follow-up of participants in order to observe a sufficient number of events to precisely estimate the treatment effect. In such studies, observing the outcome of interest during follow-up may be difficult and high rates of censoring may be observed which often leads to reduced power when applying straightforward statistical methods developed for time-to-event data. Alternative methods have been proposed to take advantage of auxiliary information that may potentially improve efficiency when estimating marginal survival and improve power when testing for a treatment effect. Recently, Parast et al. (J Am Stat Assoc 109(505):384-394, 2014) proposed a landmark estimation procedure for the estimation of survival and treatment effects in a randomized clinical trial setting and demonstrated that significant gains in efficiency and power could be obtained by incorporating intermediate event information as well as baseline covariates. However, the procedure requires the assumption that the potential outcomes for each individual under treatment and control are independent of treatment group assignment which is unlikely to hold in an observational study setting. In this paper we develop the landmark estimation procedure for use in an observational setting. In particular, we incorporate inverse probability of treatment weights (IPTW) in the landmark estimation procedure to account for selection bias on observed baseline (pretreatment) covariates. We demonstrate that consistent estimates of survival and treatment effects can be obtained by using IPTW and that there is improved efficiency by using auxiliary intermediate event and baseline information. We compare our proposed estimates to those obtained using the Kaplan-Meier estimator, the original landmark estimation procedure, and the IPTW Kaplan-Meier estimator. We illustrate our resulting reduction in bias and gains in efficiency through a simulation study and apply our procedure to an AIDS dataset to examine the effect of previous antiretroviral therapy on survival.

Optimizing Variance-Bias Trade-off in the TWANG Package for Estimation of Propensity Scores

While propensity score weighting has been shown to reduce bias in treatment effect estimation when selection bias is present, it has also been shown that such weighting can perform poorly if the estimated propensity score weights are highly variable. Various approaches have been proposed which can reduce the variability of the weights and the risk of poor performance, particularly those based on machine learning methods. In this study, we closely examine approaches to fine-tune one machine learning technique (generalized boosted models [GBM]) to select propensity scores that seek to optimize the variance-bias trade-off that is inherent in most propensity score analyses. Specifically, we propose and evaluate three approaches for selecting the optimal number of trees for the GBM in the twang package in R. Normally, the twang package in R iteratively selects the optimal number of trees as that which maximizes balance between the treatment groups being considered. Because the selected number of trees may lead to highly variable propensity score weights, we examine alternative ways to tune the number of trees used in the estimation of propensity score weights such that we sacrifice some balance on the pre-treatment covariates in exchange for less variable weights. We use simulation studies to illustrate these methods and to describe the potential advantages and disadvantages of each method. We apply these methods to two case studies: one examining the effect of dog ownership on the owner's general health using data from a large, population-based survey in California, and a second investigating the relationship between abstinence and a long-term economic outcome among a sample of high-risk youth.

Change in Neighborhood Characteristics and Change in Coronary Artery Calcium: A Longitudinal Investigation in the MESA (Multi-Ethnic Study of Atherosclerosis) Cohort

BACKGROUND

Although some evidence shows that neighborhood deprivation is associated with greater subclinical atherosclerosis, prior studies have not identified what aspects of deprived neighborhoods were driving the association.

METHODS

We investigated whether social and physical neighborhood characteristics are related to the progression of subclinical atherosclerosis in 5950 adult participants of the MESA (Multi-Ethnic Study of Atherosclerosis) during a 12-year follow-up period. We assessed subclinical disease using coronary artery calcium (CAC). Neighborhood features examined included density of recreational facilities, density of healthy food stores, and survey-based measures of availability of healthy foods, walking environment, and social environment. We used econometric fixed-effects models to investigate how change in a given neighborhood exposure is related to simultaneous change in subclinical atherosclerosis.

RESULTS

Increases in density of neighborhood healthy food stores were associated with decreases in CAC (mean changes in CAC Agatston units per 1-SD increase in neighborhood exposures, -19.99; 95% confidence interval, -35.21 to -4.78) after adjustment for time-varying demographic confounders and computed tomography scanner type. This association remained similar in magnitude after additional adjustment for time-varying behavioral risk factors and depression. The addition of time-varying biomedical factors attenuated associations with CAC slightly (mean changes in CAC per 1-SD increase in neighborhood exposures, -17.60; 95% confidence interval, -32.71 to -2.49). Changes across time in other neighborhood measures were not significantly associated with within-person change in CAC.

CONCLUSIONS

Results from this longitudinal study provide suggestive evidence that greater access to neighborhood healthy food resources may slow the development of coronary atherosclerosis in middle-aged and older adults.

Urban sprawl, obesity, and cancer mortality in the United States: cross-sectional analysis and methodological challenges

BACKGROUND

Urban sprawl has the potential to influence cancer mortality via direct and indirect effects on obesity, access to health services, physical activity, transportation choices and other correlates of sprawl and urbanization.

METHODS

This paper presents a cross-sectional analysis of associations between urban sprawl and cancer mortality in urban and suburban counties of the United States. This ecological analysis was designed to examine whether urban sprawl is associated with total and obesity-related cancer mortality and to what extent these associations differed in different regions of the US. A major focus of our analyses was to adequately account for spatial heterogeneity in mortality. Therefore, we fit a series of regression models, stratified by gender, successively testing for the presence of spatial heterogeneity. Our resulting models included county level variables related to race, smoking, obesity, access to health services, insurance status, socioeconomic position, and broad geographic region as well as a measure of urban sprawl and several interactions. Our most complex models also included random effects to account for any county-level spatial autocorrelation that remained unexplained by these variables.

RESULTS

Total cancer mortality rates were higher in less sprawling areas and contrary to our initial hypothesis; this was also true of obesity related cancers in six of seven U.S. regions (census divisions) where there were statistically significant associations between the sprawl index and mortality. We also found significant interactions (p < 0.05) between region and urban sprawl for total and obesity related cancer mortality in both sexes. Thus, the association between urban sprawl and cancer mortality differs in different regions of the US.

CONCLUSIONS

Despite higher levels of obesity in more sprawling counties in the US, mortality from obesity related cancer was not greater in such counties. Identification of disparities in cancer mortality within and between geographic regions is an ongoing public health challenge and an opportunity for further analytical work identifying potential causes of these disparities. Future analyses of urban sprawl and health outcomes should consider exploring regional and international variation in associations between sprawl and health.