Risk factors associated with asthma among adults in Khuzestan, southwest Iran

Assessing the impact of meteorological factors and air pollution on respiratory disease mortality rates: a random forest model analysis (2017-2021)

Air pollution poses a significant threat to the health of all living beings on our planet. It has been scientifically established as a crucial factor affecting mortality rates, respiratory illnesses, mental well-being, and overall health. This study aimed to investigate the impact of air pollution and meteorological factors on respiratory disease mortality rates in Mashhad in 2017-2021 using a Random Forest (RF) model. At first, the daily statistics of meteorological parameters (pressure, humidity, temperature, solar radiation) during 2017-2021 were collected. The information related to pollutants pollutants such as PM2.5 (which is defined as particulate matter with less than 2.5 micrometer diameter and potentially harmful to humans), PM10 (Particles with a diameter of 10 micrometers or less that can negatively impact both human health and environmental conditions.), sulfur dioxide (SO2), nitrogen dioxide (NO2), and carbon monoxide (CO) was collected. the mortality statistics from respiratory diseases were collected from the Health system registaration (Sina). Then we used the RF regression model in Excel and Python software to investigate the interaction between the mentioned variables. The escalating trend of air pollution in Mashhad has led to an expected increase in respiratory-related hospitalizations. This necessitates urgent air pollution control measures. Concurrently, the study of pollutants and climatic elements, as substantiated by global epidemiological studies, is crucial. In Mashhad, the second most polluted city in Iran, climatic factors like humidity, sunshine duration, temperature, pressure, and sunlight intensity exacerbate atmospheric pollution levels, impacting human health and ecosystems. The R2, RSME, and MAE of RF model are 0.73, 2.52, and 2 which indicate that the model has successfully identified the relationship between input variables and the target variable, and it will exhibit high accuracy in predictions. In this study, the most influential factor was identified when the Variance Inflation (VI) factor reached a value of 0.548. This indicates a strong correlation between this factor and the death rate of patients during the specified period. Furthermore, we analyzed by excluding the day and month plans from our model. The results showed that the factor with the highest coefficient in the executive model was related to pressure, with a VI value of 0.049. This suggests that pressure plays a significant role in our model and has a substantial effect on the death rate of patients. In the study of various pollutants, it was found that PM10 had the most significant impact on the mortality rate of patients with respiratory conditions, with a VI of 0.039. Following PM10, the pollutants with the next highest coefficients of importance were NO2 (VI = 0.034), SO2 (VI = 0.033), PM2.5 (VI = 0.029), and CO (VI = 0.025), respectively. Furthermore, the study observed a notable increase in the mortality rate of respiratory patients over time. Specifically, for every five days, the death rate increased by 35.5%. Indeed, climate change and air pollution significantly contribute to the mortality rate from respiratory diseases. Therefore, it is crucial for individuals, particularly those with respiratory conditions, to heed meteorological warnings.

The frequency of asthma and its related factors: results of the enrolment phase of Tabari cohort study

INTRODUCTION

A large portion of the world's population has asthma. This study aimed to ascertain asthma prevalence and related factors in the Tabari cohort study (TCS).

METHODS

The TCS included 10,255 35-70-year-olds from urban and mountainous Sari (northern Iran) between June 2015 and November 2017. Education, occupation, domicile, socioeconomic position, history of psychiatric disorders, smoking (including hookah smoking), opium usage, and daily physical activity level were determined.

RESULTS

The final analysis included 9939 individuals. The asthma rate was 7.4%. Multiple factors increased asthma risk, according to statistical analysis. These factors included being female (OR, 1.337; 95% CI, 1.142-1.565), retired (OR, 1.553; 95% CI, 1.205-2.002), living in the city (OR, 1.268; 95% CI, 1.083-1.484), using opioids (OR, 1.689; 95% CI, 1.299-2.197), having lower socioeconomic status (SES) (OR, 0.723; 95% CI, 0.579-0.903), history of psychiatric disorders (OR, 2.313; 95% CI, 1.826-2.930), and aged 60-70 (OR, 2.325; 95% CI, 1.765-3.064), and BMI above 30 kg/m2 (OR, 1.499; 95% CI, 1.220-1.841). Several factors increased asthma probability in multivariate regression analysis. These factors include being female (OR = 1.389, p = 0.015), ages between 60 and 70 (OR = 2.034, p < 0.001), using opioids (OR = 1.940, p < 0.001), lower SES (OR = 0.738, p = 0.012), history of psychiatric disorders (OR = 2.035, p < 0.001), BMI above 30 kg/m2 (OR = 1.518, p < 0.001), and being a smoker (OR = 1.337, p = 0.056).

CONCLUSION

This study has identified that the prevalence of asthma in the Tabari cohort group is high. In addition, it was demonstrated that various factors are related to asthma.

Association between exposure to greenness and atopic march in children and adults-A systematic review and meta-analysis

Introduction

Allergic diseases are a global public health problem. Food allergy, atopic dermatitis (AD), allergic rhinoconjunctivitis, allergic rhinitis (AR) and asthma represent the natural course of allergic diseases, also known as the "atopic march". In recent years, a large number of studies have been published on the association between greenness exposure and allergic diseases. However, systematic reviews on the association between greenness exposure and multiple allergic diseases or atopic march are lacking.

Methods

In this study, PubMed, EMBASE, ISI Web of Science, and Scopus were systematically searched. Meta-analyses were performed if at least three studies reported risk estimates for the same outcome and exposure measures.

Results

Of 2355 records, 48 studies were included for qualitative review. Five birth cohort studies, five cross-sectional studies, and one case-control study were included for asthma meta-analysis, respectively. Four birth cohort studies were included for AR meta-analysis. Our results support that exposure to a greener environment at birth reduces the risk of asthma and AR in childhood. In addition, higher greenness exposure was associated with decreased odds of current asthma in children.

Discussion

There was a large heterogeneity among the included studies and most of them did not specify the vegetation type and causative allergens. Therefore the study results need to be further validated. In addition, a small number of studies evaluated the association between greenness and food allergy, AD and allergic rhinoconjunctivitis. More research is needed to strengthen our understanding of the association between greenness and allergic diseases.

Association between Green Space Structure and the Prevalence of Asthma: A Case Study of Toronto

Asthma is a chronic inflammatory disease that can be caused by various factors, such as asthma-related genes, lifestyle, and air pollution, and it can result in adverse impacts on asthmatics' mental health and quality of life. Hence, asthma issues have been widely studied, mainly from demographic, socioeconomic, and genetic perspectives. Although it is becoming increasingly clear that asthma is likely influenced by green spaces, the underlying mechanisms are still unclear and inconsistent. Moreover, green space influences the prevalence of asthma concurrently in multiple ways, but most existing studies have explored only one pathway or a partial pathway, rather than the multi-pathways. Compared to greenness (measured by Normalized Difference Vegetation Index, tree density, etc.), green space structure-which has the potential to impact the concentration of air pollution and microbial diversity-is still less investigated in studies on the influence of green space on asthma. Given this research gap, this research took Toronto, Canada, as a case study to explore the two pathways between green space structure and the prevalence of asthma based on controlling the related covariates. Using regression analysis, it was found that green space structure can protect those aged 0-19 years from a high risk of developing asthma, and this direct protective effect can be enhanced by high tree diversity. For adults, green space structure does not influence the prevalence of asthma unless moderated by tree diversity (a measurement of the richness and diversity of trees). However, this impact was not found in adult females. Moreover, the hypothesis that green space structure influences the prevalence of asthma by reducing air pollution was not confirmed in this study, which can be attributed to a variety of causes.