Lung Cancer and Air Quality in a Large Urban County in the United States.

Lung cancer is the leading cancer-related killer in the United States. The incidence varies geographically and may be affected by environmental pollutants. Our goal was to determine associations within time series for specific air pollutants and lung cancer cases over a 33-year period in Wayne County, Michigan, controlling for population change. Lung cancer data for Wayne County were queried from the Michigan Cancer Registry from 1985 to 2018. Air pollutant data were obtained from the United States Environmental Protection Agency from 1980 to 2018. Autoregressive distributed lag (ARDL) models were estimated to investigate time lags in years between specific air pollution levels and lung cancer development. A total of 58,866 cases of lung cancer were identified. The mean age was 67.8 years. Females accounted for 53 percent of all cases in 2018 compared to 44 percent in 1985. Three major clusters of lung cancer incidence were detected with the most intense clusters in downtown Detroit and the heavily industrialized downriver area. Sulfur dioxide (SO2) had the strongest statistically significant relationship with lung cancer, showing both short- and long-term effects (lag range, 1-15 years). Particulate matter (PM2.5) (lag range, 1-3 years) and nitrogen dioxide (NO2) (lag range, 2-4 years) had more immediate effects on lung cancer development compared to carbon monoxide (CO) (lag range, 5-6 years), hazardous air pollutants (HAPs) (lag range, 9 years) and lead (Pb) (lag range, 10-12 years), which had more long-term effects on lung cancer development. Areas with poor air quality may benefit from targeted interventions for lung cancer screening and reductions in environmental pollution.

Regional trends in diagnosis of advanced lung cancer in Michigan over 33 years.

Background: Lung cancer is the most common cancer killer worldwide. Nearly 80 percent of lung cancers are diagnosed at advanced stages. Lack of access to medical care and undwerutilized lung cancer screening are key reasons for advanced diagnoses. We sought to understand the regional differences in presentation of lung cancer across Michigan. Utilizing a comprehensive cancer registry over 33 years, our goal was to examine associations between sociodemographic patient factors and diagnoses at advanced stages. Methods: The Michigan Cancer Registry was queried from 1985 to 2018 to include all new diagnoses of non-small cell lung cancer (NSCLC) using International Classification of Diseases for Oncology (ICD-O) version 3 codes. NSCLC was categorized as early, regional and distant disease. Advanced disease was considered to be any disease that was regional or distant. NSCLC rates were calculated and mapped at the zip code level using the 2010 population as the denominator and spatial empirical Bayes methodology. Regional hospital service areas were constructed using travel time to treatment from the patient's zip code centroid. Logistic regression models were estimated to investigate the significance of rural vs. urban and travel time on level of disease at presentation. Kaplan-Meier and multivariate survival analysis was performed to evaluate the association between distance from the nearest medical center and length of survival controlling for known risk factors for lung cancer. Results: From 1985 to 2018, there were 141,977 patients in Michigan diagnosed with NSCLC. In 1985, men were 2.2 times more likely than women to be diagnosed but by 2018 women and men developed disease at equal rates. Mean age was 67.8 years. Among all patients with known stage of disease, 72.5% of patients were diagnosed with advanced disease. Regional and distant NSCLC rates were both higher in the northern parts of the state. Longer drive times in rural regions also significantly increased the likelihood of advanced NSCLC diagnoses, in particular regional lung cancer. Patients with longer drive times also experienced overall worse survival after controlling for other factors. Conclusions: Regional disparities exist in Michigan for diagnoses of NSCLC at advanced stages. Factors such as lack of screening in urban regions and distances to treating institutions in rural areas likely contribute to the increased likelihood of advanced NSCLC. Future interventions should target the specific needs of residents to detect disease at earlier stages and improve overall outcomes.

Spatial and spatio-temporal clusters of lung cancer incidence by stage of disease in Michigan, United States 1985-2018.

Lung cancer is the most common cause of cancer-related death in Michigan. Most patients are diagnosed at advanced stages of the disease. There is a need to detect clusters of lung cancer incidence over time, to generate new hypotheses about causation and identify high-risk areas for screening and treatment. The Michigan Cancer Surveillance database of individual lung cancer cases, 1985 to 2018 was used for this study. Spatial and spatiotemporal clusters of lung cancer and level of disease (localized, regional and distant) were detected using discrete Poisson spatial scan statistics at the zip code level over the study time period. The approach detected cancer clusters in cities such as Battle Creek, Sterling Heights and St. Clair County that occurred prior to year 2000 but not afterwards. In the northern area of the lower peninsula and the upper peninsula clusters of late-stage lung cancer emerged after year 2000. In Otter Lake Township and southwest Detroit, late-stage lung cancer clusters persisted. Public and patient education about lung cancer screening programs must remain a health priority in order to optimize lung cancer surveillance. Interventions should also involve programs such as telemedicine to reduce advanced stage disease in remote areas. In cities such as Detroit, residents often live near industry that emits air pollutants. Future research should therefore, continue to focus on the geography of lung cancer to uncover place-based risks and in response, the need for screening and health care services.

Spaces of Segregation and Health: Complex Associations for Black Immigrant and US-Born Mothers in New York City.

Black immigrants are a growing proportion of the Black population in the USA, and despite the fact that they now comprise nearly a quarter of Black urban residents, few studies address the relationships between racial segregation and maternal and birth outcomes among Black immigrants. In this study of birth outcomes among US-born and immigrant Black mothers in New York City between 2010 and 2014, we applied multilevel models, assessing the association between segregation (measured through a novel kernel-based measure of local segregation) and adverse birth outcomes (preterm birth (PTB) and low birth weight (LBW; < 2500 g)) among African-born, Caribbean-born, and US-born Black mothers. We found that African-born and Caribbean/Latin American-born Black mothers had a significantly lower incidence of PTB compared with US-born Black mothers (7.0 and 10.1, respectively, compared with 11.2 for US-born mothers). We also found disparities in the incidence of infant LBW by nativity, with the highest incidence among infants born to US-born mothers (10.9), compared with African-born (6.9) and Caribbean-born mothers (9.0). After adjusting for maternal (maternal age; higher rates of reported drug use and smoking) and contextual characteristics (neighborhood SES; green space access), we found that maternal residence in an area with high Black segregation increases the likelihood of PTB and LBW among US-born and Caribbean-born Black mothers. In contrast, the association between segregation and birth outcomes was insignificant for African-born mothers. Associations between tract-level socioeconomic disadvantage and birth outcomes also varied across groups, with only US-born Black mothers showing the expected positive association with risk of PTB and LBW.

Lead Emissions and Population Vulnerability in the Detroit Metropolitan Area, 2006-2013: Impact of Pollution, Housing Age and Neighborhood Racial Isolation and Poverty on Blood Lead in Children.

This research investigates the relationships between airborne and depositional industrial lead emission concentrations modeled using Environmental Protection Agency's (EPA's) American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) and childhood blood lead levels (BLL) in the Detroit Metropolitan Area (DMA) 2006-2013. Linear and mediation interaction regression models estimated the effects of older housing and airborne and depositional lead emission concentrations on black and white childhood BLLs, controlling for neighborhood levels of racial isolation and poverty-important social structures in the DMA. The results showed a direct relationship between airborne and depositional lead emissions and higher childhood BLL, after controlling for median housing age. Lead emissions also exacerbated the effect of older housing on black and white children's BLLs (indirect relationship), after controlling for social structures. Findings from this research indicate that black and white children exposed to lead-based paint/pipes in older housing are further impacted by industrial lead pollution that may lead to permanent neurological damage.

Outbreaks of foodborne Salmonella enteritidis in the United States between 1990 and 2015: An analysis of epidemiological and spatial-temporal trends.

OBJECTIVES: To evaluate the role of eggs and other food vehicles as risk factors associated with Salmonella enteritidis (SE) outbreaks in order to address the endemicity of SE infections in the USA. METHODS: We retrieved and analyzed data relating to all SE outbreaks reported to the Centers for Disease Control and Prevention (CDC) between 1990 and 2015. We then used descriptive and analytical statistical methods, including negative binomial regression models for the estimation of rate-ratios, to analyze the data. RESULTS: Analyses showed that egg-based dishes were the most common food vehicle associated with outbreaks of SE in the USA (273 cases [24%]); this was followed by several other food items, including meat (130 cases [11%]), vegetables (96 cases [8%]), chicken items (95 cases [8%]), dairy products (55 cases [5%]), and bakery items (8 cases [1%]). Compared to egg-based dishes, other food items such as meat (exp(ß) = 0.51, 95% CI 0.37, 0.69), chicken (exp(ß) = 0.42, 95% CI 0.30, 0.58), vegetables (exp(ß) = 0.41, 95% CI 0.29, 0.55), and dairy items (exp(ß) = 0.27, 95% CI 0.18, 0.40) were significantly associated with outbreaks of SE in the USA. Of 1144 SE outbreaks, 402 (35%) occurred in the Northeast region of the USA, followed by the South (253 [22%]), West (250 [22%]), and Midwestern regions (239 [21%]). CONCLUSIONS: Epidemiological and spatiotemporal trends analyses demonstrated that a significant proportions of Salmonella enteritidis outbreaks in the USA are attributed to food vehicles other than eggs. Our findings can be used to plan effective strategies to mitigate the increasing occurrence of foodborne SE outbreaks.

Use of a spatiotemporal approach for understanding preschoolers' playground activity.

This study used spatiotemporal hot-spot analysis to characterize physical activity on the childcare center playground. Preschool-aged children (N = 34) wore a GPS and accelerometer during 2-3 outdoor periods on one day. A spatiotemporal weights matrix was generated so that points within a specified distance in meters (space) and 3 min (time) were considered neighbors. The Getis-Ord G* statistic was calculated to detect locations of significant hot/cold spots in vector magnitude counts/15­sec. Hot/cold spots changed within a single outdoor period and between outdoor periods, highlighting the importance of time. This approach can be used to identify points of intervention during provided outdoor time.

Explained and unexplained racial and regional inequality in obesity prevalence in the United States.

Objective: There are substantial racial and regional disparities in obesity prevalence in the United States. This study partitioned the mean Body Mass Index (BMI) and obesity prevalence rate gaps between non-Hispanic blacks and non-Hispanic whites into the portion attributable to observable obesity risk factors and the remaining portion attributable to unobservable factors at the national and the state levels in the United States (U.S.) in 2010. Design: This study used a simulated micro-population dataset combining common information from the Behavioral Risk Factor Surveillance System and the U.S. Census data to obtain a reliable, large sample representing the adult populations at the national and state levels. It then applied a reweighting decomposition method to decompose the black-white mean BMI and obesity prevalence disparities at the national and state levels into the portion attributable to the differences in distribution of observable obesity risk factors and the remaining portion unexplainable with risk factors. Results: We found that the observable differences in distribution of known obesity risk factors explain 18.5% of the mean BMI difference and 20.6% of obesity prevalence disparities between non-Hispanic blacks and non-Hispanic whites. There were substantial variations in how much the differences in distribution of known obesity risk factors can explain black-white gaps in mean BMI (-67.7% to 833.6%) and obesity prevalence (-278.5% to 340.3%) at the state level. Conclusion: The results from this study demonstrate that known obesity risk factors explain a small proportion of the racial, ethnic and between-state disparities in obesity prevalence in the United States. Future etiologic studies are required to further understand the causal factors underlying obesity and racial, ethnic and geographic disparities.

Mapping Multi-Disease Risk during El Niño: An Ecosyndemic Approach.

El Niño is a quasi-periodic pattern of climate variability and extremes often associated with hazards and disease. While El Niño links to individual diseases have been examined, less is known about the cluster of multi-disease risk referred to as an ecosyndemic, which emerges during extreme events. The objective of this study was to explore a mapping approach to represent the spatial distribution of ecosyndemics in Piura, Peru at the district-level during the first few months of 1998. Using geographic information systems and multivariate analysis, descriptive and analytical methodologies were employed to map disease overlap of 7 climate-sensitive diseases and construct an ecosyndemic index, which was then mapped and applied to another El Niño period as proof of concept. The main findings showed that many districts across Piura faced multi-disease risk over several weeks in the austral summer of 1998. The distribution of ecosyndemics were spatially clustered in western Piura among 11 districts. Furthermore, the ecosydemic index in 1998 when compared to 1983 showed a strong positive correlation, demonstrating the potential utility of the index. The study supports PAHO efforts to develop multi-disease based and interprogrammatic approaches to control and prevention, particularly for climate and poverty-related infections in Latin America and the Caribbean.

Adult obesity prevalence at the county level in the United States, 2000-2010: Downscaling public health survey data using a spatial microsimulation approach.

Obesity is a growing public health concern in the United States. There is a need to monitor obesity prevalence at the local level to intervene in place-specific ways. However, national public health surveys suppress the local geographic information of respondents due to small sample sizes and the protection of confidentiality. This study therefore, uses a spatial microsimulation approach to estimate obesity prevalence rates at the county level across the United States to visualize temporal, spatial and spatio-temporal changes from 2000 to 2010 for use in the monitoring of obesity prevalence. This method iteratively replicates the demographic characteristics of public health survey respondents with census data for those areas. Following, Local Moran's I was used to identify clusters of high and low obesity prevalence. The findings showed that obesity prevalence rose dramatically over the last decade with substantial variation across counties and states. Counties in Southern states, especially along the Mississippi River and Appalachian Mountains and counties containing or in proximity to Native American reservation sites showed elevated obesity prevalence rates across the decade. Counties in Midwestern states had higher obesity prevalence rates compared to counties in Western and Northeastern states. This study demonstrated the use of spatial microsimulation modeling as an alternative method to obtain reliable obesity prevalence rates at the local-level using existing health survey and census data.

Physical activity and chronic diseases among older people in a mid-size city in China: a longitudinal investigation of bipolar effects.

BACKGROUND: While previous studies have shown that regular physical activity can delay the onset of certain chronic diseases; less is known about the changes in physical activity practices following chronic disease diagnoses. China is experiencing a rapid aging transition, with physical activity an important routine in many older people's lives. This study utilizes the Health Belief Model to better understand the bidirectional relationships and bipolar effects between physical activity and chronic disease burden in Huainan City, a mid-sized city in China. METHODS: Longitudinal health survey data (2010-2015) from annual clinic visits for 3198 older people were obtained from a local hospital, representing 97% of the older population in three contiguous neighborhoods in Huainan City. The chronic diseases studied included obesity, hypertension, diabetes, hyperlipidemia, cardiovascular diseases, liver and biliary system diseases, and poor kidney function. Multilevel logistic regression was used to examine differences in physical activity levels across socio-demographic groups. Cox proportional hazards models were used to examine the impacts of physical activity practice levels on chronic disease onsets. Logistic regression was used to estimate the effects of chronic disease diagnosis on physical activity practice levels. RESULTS: The prevalence of chronic diseases increased with increasing age, among men, and those with a lower education. Older people who were physically active experienced a later onset of chronic disease compared to their sedentary counterparts, particularly for obesity and diabetes. Following diagnosis of a chronic disease, physically active older people were more likely to increase their physical activity levels, while sedentary older people were less likely to initiate physical activity, demonstrating bipolar health trajectory effects. CONCLUSIONS: Health disparities among older people may widen as the sedentary experience earlier onsets of chronic diseases and worse health trajectories, compared to physically active people. Future health education communication and programmatic interventions should focus on sedentary and less healthy older populations to encourage healthy aging. These lessons from China may be applied to other countries also experiencing an increasing aging population.

Impacts of Federally Funded State Obesity Programs on Adult Obesity Prevalence in the United States, 1998-2010.

OBJECTIVES: From 2000 to 2010, the Division of Nutrition, Physical Activity, and Obesity (DNPAO) at the Centers for Disease Control and Prevention (CDC) funded 37 state health departments to address the obesity epidemic in their states through various interventions. The objective of this study was to investigate the overall impacts of CDC-DNPAO statewide intervention programs on adult obesity prevalence in the United States. METHODS: We used a set of an individual-level, interrupted time-series regression and a quasi-experimental analysis to evaluate the overall effect of CDC-DNPAO intervention programs before (1998-1999) and after (2010) their implementation by using data from CDC's Behavioral Risk Factor Surveillance System. RESULTS: States that implemented the CDC-DNPAO program had a 2.4% to 3.8% reduction in the odds of obesity during 2000-2010 compared with states without the program. The effect of the CDC-DNPAO program varied by length of program implementation. A quasi-experimental analysis found that states with longer program implementation did not necessarily have lower odds of obesity than states with shorter program implementation. CONCLUSIONS: Statewide obesity interventions can contribute to reduced odds of obesity in the United States. Future research should evaluate the CDC-DNPAO programs in relation to their goals, objectives, and other environmental obesity risk factors to inform future interventions.

Lead Emissions and Population Vulnerability in the Detroit (Michigan, USA) Metropolitan Area, 2006-2013: A Spatial and Temporal Analysis.

Objective: The purpose of this research is to geographically model airborne lead emission concentrations and total lead deposition in the Detroit Metropolitan Area (DMA) from 2006 to 2013. Further, this study characterizes the racial and socioeconomic composition of recipient neighborhoods and estimates the potential for IQ (Intelligence Quotient) loss of children residing there. Methods: Lead emissions were modeled from emitting facilities in the DMA using AERMOD (American Meteorological Society/Environmental Protection Agency Regulatory Model). Multilevel modeling was used to estimate local racial residential segregation, controlling for poverty. Global Moran's I bivariate spatial autocorrelation statistics were used to assess modeled emissions with increasing segregation. Results: Lead emitting facilities were primarily located in, and moving to, highly black segregated neighborhoods regardless of poverty levels-a phenomenon known as environmental injustice. The findings from this research showed three years of elevated airborne emission concentrations in these neighborhoods to equate to a predicted 1.0 to 3.0 reduction in IQ points for children living there. Across the DMA there are many areas where annual lead deposition was substantially higher than recommended for aquatic (rivers, lakes, etc.) and terrestrial (forests, dunes, etc.) ecosystems. These lead levels result in decreased reproductive and growth rates in plants and animals, and neurological deficits in vertebrates. Conclusions: This lead-hazard and neighborhood context assessment will inform future childhood lead exposure studies and potential health consequences in the DMA.

How the built environment affects change in older people's physical activity: A mixed- methods approach using longitudinal health survey data in urban China.

Although the general population in China is physically active, only 45% of older adults meet the World Health Organization's recommendation for weekly moderate-to-vigorous exercise, to achieve health benefits. This percentage is even lower (9.8%) in urban China. It is, therefore, important to understand the pathways by which physical activity behaviors are impacted by the built environment. This study utilized a mixed methods approach-interviews (n = 42) and longitudinal (2010-2015) health survey data (n = 3094) for older people residing in three neighborhoods in Huainan, a mid-sized city in Anhui Province, central eastern China. First, a content analysis of interview data was used to identify individual and built environment factors (motivators and barriers) that impacted physical activity within older people's activity spaces. Second, a multilevel path analysis was conducted using the health survey data to demonstrate the pathways by which these motivators and barriers contributed to the initiation, regulation, and maintenance of physical activity. This study found (a) that the liveliness of an apartment building and its proximity to functional spaces (fast-food stores, farmer's markets, supermarkets, pharmacies, schools, hospitals, PA facilities and natural and man-made water bodies) were important factors in attracting sedentary older people to initiate physical activity; (b) the social networks of apartment neighbors helped to initiate, regulate, and maintain physical activity; and housing closeness to functional spaces was important in maintaining physical activity, particularly for those older people with chronic diseases. To increase older people's overall physical activity, future interventions should focus on residential form and access to functional spaces, prior to investing in large-scale urban design interventions.

Neonatal mortality in East Africa and West Africa: a geographic analysis of district-level demographic and health survey data.

Under-five child mortality declined 47% since 2000 following the implementation of the United Nation's (UN) Millennium Development Goals. To further reduce under-five child mortality, the UN's Sustainable Development Goals (SDGs) will focus on interventions to address neonatal mortality, a major contributor of under-five mortality. The African region has the highest neonatal mortality rate (28.0 per 1000 live births), followed by that of the Eastern Mediterranean (26.6) and South-East Asia (24.3). This study used the Demographic and Health Survey Birth Recode data (http://dhsprogram.com/data/File-Types-and-Names.cfm) to identify high-risk districts and countries for neonatal mortality in two sub-regions of Africa - East Africa and West Africa. Geographically weighted Poisson regression models were estimated to capture the spatially varying relationships between neonatal mortality and dimensions of potential need i) care around the time of delivery, ii) maternal education, and iii) women's empowerment. In East Africa, neonatal mortality was significantly associated with home births, mothers without an education and mothers whose husbands decided on contraceptive practices, controlling for rural residency. In West Africa, neonatal mortality was also significantly associated with home births, mothers with a primary education and mothers who did not want or plan their last child. Importantly, neonatal mortality associated with home deliveries were explained by maternal exposure to unprotected water sources in East Africa and older maternal age and female sex of infants in West Africa. Future SDG-interventions may target these dimensions of need in priority high-risk districts and countries, to further reduce the burden of neonatal mortality in Africa.

Three modes of power operation: Understanding doctor-patient conflicts in China's hospital therapeutic landscapes.

Doctor-patient conflicts in contemporary China are increasing in numbers and severity. This health geographic study shows how hospitals as a type of therapeutic landscape can shape doctor-patient relationships. First, the comprehensive nature of therapeutic landscapes with an emphasis on power operation within symbolic environments is provided as a framework for this study. Second, the results from participant observation and interviews with patients and doctors previously involved in conflicts are reported from Internal Medicine and Surgery Departments, within four hospitals in Anhui Province, Eastern China. The study finds that the spatial and temporal arrangements of spaces, the inside decorations and the different modes of discourses can build or ruin harmonious doctor-patient relations. The research concludes that adaptations to current hospital therapeutic landscapes can improve trust between patients and doctors, resulting in fewer conflicts and better health outcomes in China.

El Niño, Climate, and Cholera Associations in Piura, Peru, 1991-2001: A Wavelet Analysis.

In Peru, it was hypothesized that epidemic cholera in 1991 was linked to El Niño, the warm phase of El Niño-Southern Oscillation. While previous studies demonstrated an association in 1997-1998, using cross-sectional data, they did not assess the consistency of this relationship across the decade. Thus, how strong or variable an El Niño-cholera relationship was in Peru or whether El Niño triggered epidemic cholera early in the decade remains unknown. In this study, wavelet and mediation analyses were used to characterize temporal patterns among El Niño, local climate variables (rainfall, river discharge, and air temperature), and cholera incidence in Piura, Peru from 1991 to 2001 and to estimate the mediating effects of local climate on El Niño-cholera relationships. The study hypothesis is that El Niño-related connections with cholera in Piura were transient and interconnected via local climate pathways. Overall, our findings provide evidence that a strong El Niño-cholera link, mediated by local hydrology, existed in the latter part of the 1990s but found no evidence of an El Niño association in the earlier part of the decade, suggesting that El Niño may not have precipitated cholera emergence in Piura. Further examinations of cholera epicenters in Peru are recommended to support these results in Piura. For public health planning, the results may improve existing efforts that utilize El Niño monitoring for preparedness during future climate-related extremes in the region.

Do more hospital beds lead to higher hospitalization rates? a spatial examination of Roemer's Law.

BACKGROUND: Roemer's Law, a widely cited principle in health care policy, states that hospital beds that are built tend to be used. This simple but powerful expression has been invoked to justify Certificate of Need regulation of hospital beds in an effort to contain health care costs. Despite its influence, a surprisingly small body of empirical evidence supports its content. Furthermore, known geographic factors influencing health services use and the spatial structure of the relationship between hospital bed availability and hospitalization rates have not been sufficiently explored in past examinations of Roemer's Law. We pose the question, "Accounting for space in health care access and use, is there an observable association between the availability of hospital beds and hospital utilization?" METHODS: We employ an ecological research design based upon the Anderson behavioral model of health care utilization. This conceptual model is implemented in an explicitly spatial context. The effect of hospital bed availability on the utilization of hospital services is evaluated, accounting for spatial structure and controlling for other known determinants of hospital utilization. The stability of this relationship is explored by testing across numerous geographic scales of analysis. The case study comprises an entire state system of hospitals and population, evaluating over one million inpatient admissions. RESULTS: We find compelling evidence that a positive, statistically significant relationship exists between hospital bed availability and inpatient hospitalization rates. Additionally, the observed relationship is invariant with changes in the geographic scale of analysis. CONCLUSIONS: This study provides evidence for the effects of Roemer's Law, thus suggesting that variations in hospitalization rates have origins in the availability of hospital beds. This relationship is found to be robust across geographic scales of analysis. These findings suggest continued regulation of hospital bed supply to assist in controlling hospital utilization is justified.