Assessing the Influence of Socioeconomic Status and Air Pollution Levels on the Public Perception of Local Air Quality in a Mexico-US Border City

Association Between the Incidence of Hospitalizations for Acute Cardiovascular Events, Weather, and Air Pollution

Background

The incidence of hospitalizations for cardiovascular events has been associated with specific weather conditions and air pollution. A comprehensive model including the interactions between various environmental factors remains to be developed.

Objectives

The purpose of this study was to develop a comprehensive model of the association between weather patterns and the incidence of cardiovascular events and use this model to forecast near-term spatiotemporal risk.

Methods

We present a spatiotemporal analysis of the association between atmospheric data and the incidence rate of hospital admissions related to heart failure (922,132 episodes), myocardial infarction (521,988 episodes), and ischemic stroke (263,529 episodes) in ∼24 million people in Canada between 2007 and 2017. Our hierarchical Bayesian model captured the spatiotemporal distribution of hospitalizations and identified weather and air pollution-related factors that could partially explain fluctuations in incidence.

Results

Models that included weather and air pollution variables outperformed models without those covariates for most event types. Our results suggest that environmental factors may interact in complex ways on human physiology. The impact of environmental factors was magnified with increasing age. The weather and air pollution variables included in our models were predictive of the future incidence of heart failure, myocardial infarction, and ischemic strokes.

Conclusions

The increasing importance of environmental factors on cardiovascular events with increasing age raises the need for the development of educational materials for older patients to recognize environmental conditions where exacerbations are more likely. This model could be the basis of a forecasting system used for local, short-term clinical resource planning based on the anticipated incidence of events.

Machine learning based efficient prediction of positive cases of waterborne diseases

BACKGROUND

Water quality has been compromised and endangered by different contaminants due to Pakistan's rapid population development, which has resulted in a dramatic rise in waterborne infections and afflicted many regions of Pakistan. Because of this, modeling and predicting waterborne diseases has become a hot topic for researchers and is very important for controlling waterborne disease pollution.

METHODS

In our study, first, we collected typhoid and malaria patient data for the years 2017-2020 from Ayub Medical Hospital. The collected data set has seven important input features. In the current study, different ML models were first trained and tested on the current study dataset using the tenfold cross-validation method. Second, we investigated the importance of input features in waterborne disease-positive case detection. The experiment results showed that Random Forest correctly predicted malaria-positive cases 60% of the time and typhoid-positive cases 77% of the time, which is better than other machine-learning models. In this research, we have also investigated the input features that are more important in the prediction and will help analyze positive cases of waterborne disease. The random forest feature selection technique has been used, and experimental results have shown that age, history, and test results play an important role in predicting waterborne disease-positive cases. In the end, we concluded that this interesting study could help health departments in different areas reduce the number of people who get sick from the water.

Air Pollution and Environmental Justice in Latin America: Where Are We and How Can We Move Forward?

PURPOSE OF REVIEW

Air pollution in Latin America is a major environmental threat, yet few studies have focused on aspects of environmental justice with regard to air pollution in the region. We examined the scientific literature and described whether and how this issue has been addressed, identify possible gaps in knowledge, and offer suggestions for future research to contribute to policies that seek greater equity concerning air pollution impacts in Latin America.

RECENT FINDINGS

There is a limited literature that has addressed issues of environmental justice or environmental health inequalities about air pollution in Latin America, with studies concentrated in Brazil, Mexico, and Chile. Studies that examined disparities in exposure to air pollution found a clear pattern of higher exposure in socially deprived areas. Studies that examined disparities in health impacts associated with air pollution have mixed results, but many found a clear modification of effect with those in the lower socioeconomic groups presenting greater effects. Despite Latin America's colonial and slavery history, no studies have considered ethnicity or minority populations. The literature shows that health risks (exposure and susceptibility) associated with air pollution are unevenly distributed among Latin American populations. Methodological approaches varied and can be improved in future studies, especially for exposure assessment to air pollution, as well as for assigning socioeconomic position to individuals. Using smaller geographic units and spatial regression techniques will allow a reduction in measurement error. Attempts should be made to include both individual and contextual socioeconomic indicators in the analysis. Better quality information will help understand these differential exposures and effects and provide inputs to policies to tackle these inequalities.

Exposure to long-range transported particulate matter and modeling age-related particle deposition

Exposure to particulate matter (PM) is known to cause cardiovascular disease and increase mortality and morbidity. Asian dust (AD) is a meteorological phenomenon which affects much of East Asia year-round but especially during the spring months. Here, we have characterized concentrations of PM₁₀ and classified synoptic air flow trajectories using HYSPLIT model for Asian dust events (from March to April) in Jeju island, Korea. The ADE is a phenomenon in which sand and dust in the deserts of China or Mongolia rise mainly in spring and are blown away by western winds and gradually subside. The calculated inhaled PM₁₀ doses from specific microenvironments (home, work or school, and transportation) were from 5.28 to 101.48 μg depending on age group and different microenvironments while the calculated PM₁₀ inhaled doses for ADE ranged within 67.92 -769.27 μg. Also, we have evaluated the contribution of specific microenvironments to the exposure for different age groups using time-activity patterns and calculated inhaled PM₁₀ doses and deposited mass/mass flux so as to estimate exposure using multiple-path particle dosimetry (MPPD) model. The monthly average outdoor PM₁₀ concentration range was 29.3-65.4 μg/m³, whereas the monthly PM₁₀ concentration for ADE was 127.0-342.0 μg/m³. Air masses from clusters 1 and 2 were 24% and 29% (in 2017), clusters 2 and 3 were 24% and 32% (in 2018), and clusters 1 and 3 were 28% and 26% (in 2019) for ADE. In the aerosol deposition based on MPPD model, the corresponding values for daily particle deposited mass for two age groups ranged from 8.64 ×10^-5 μg (age 8) to 8.64 ×10^-4 μg (age 21). We assessed the PM_2.5 exposure considering time-activity patterns, age groups, and ADE exposure evaluation caused by long-range transport airflow; this could be helpful for assessing PM₁₀ exposure-related health evaluation.

Development of a Health-Based Index to Identify the Association between Air Pollution and Health Effects in Mexico City

Health risks from air pollution continue to be a major concern for residents in Mexico City. These health burdens could be partially alleviated through individual avoidance behavior if accurate information regarding the daily health risks of multiple pollutants became available. A split sample approach was used in this study to create and validate a multi-pollutant, health-based air quality index. Poisson generalized linear models were used to assess the impacts of ambient air pollution (i.e., fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ground-level ozone (O3)) on a total of 610,982 daily emergency department (ED) visits for respiratory disease obtained from 40 facilities in the metropolitan area of Mexico City from 2010 to 2015. Increased risk of respiratory ED visits was observed for interquartile increases in the 4-day average concentrations of PM2.5 (Risk Ratio (RR) 1.03, 95% CI 1.01–1.04), O3 (RR 1.03, 95% CI 1.01–1.05), and to a lesser extent NO2 (RR 1.01, 95% CI 0.99–1.02). An additive, multi-pollutant index was created using coefficients for these three pollutants. Positive associations of index values with daily respiratory ED visits was observed among children (ages 2–17) and adults (ages 18+). The use of previously unavailable daily health records enabled an assessment of short-term ambient air pollution concentrations on respiratory morbidity in Mexico City and the creation of a health-based air quality index, which is now currently in use in Mexico City.

Differences in Psychosocial Factors and Experimental Pain Sensitivity between Hispanics and non-Hispanic Whites from the U.S.-Mexico Border

PURPOSE

Research suggests that ethnicity is a predictor of pain-related outcomes; however, studies comparing the differences in experimental pain sensitivity between Hispanics and non-Hispanic Whites (NHW) are scarce. This study investigated these differences between Hispanics and NHW from the U.S- Mexico border.

METHODS

Fifty-eight healthy subjects completed the survey packet, which included a demographic and a psychosocial factors questionnaire. Participants underwent quantitative sensory testing which included heat pain threshold, heat pain tolerance, Suprathreshold Heat Pain Response (SHPR), and Conditioned Pain Modulation (CPM). SHPR was induced by repeated thermal stimuli in both thenar eminences. CPM was assessed using SHPR as the experimental stimulus, and cold pressor task as the conditioning stimulus.

RESULTS

Analyses showed significant differences in experimental pain measures believed to be representative of facilitatory pain processing including SHPR, and heat pain threshold, where Hispanics reported significantly higher pain ratings than NHW. Hispanics also reported higher levels of ethnic identity and acculturation. However, these factors were not significantly associated with experimental pain sensitivity.

CONCLUSION

The experimental pain sensitivity and psychosocial factors included in this study differed by ethnic group, where Hispanics reported significantly higher pain ratings, when compared to NHW. However, ethnic identity and acculturation were not associated with these pain-related outcomes. Overall, enhanced understanding by clinicians of pain sensitivity and disparities in the pain experience between ethnic groups allows for increased cultural sensitivity and can be used to optimize pain treatment on an individual-by-individual basis.