This study inspects the impact of environmental deterioration and income on longevity and fertility in Asian countries, specifically the nations that are highly vulnerable to extreme weather. The study examines the data, covering two decades from 2000 to 2019. The empirical conclusions of the panel ARDL-PMG and the CS-ARDL econometric models indicate that environmental degradation leads to a decline in birth rate and life expectancy, while a rising income has a significant influence over longevity. However, increasing per capita income alone cannot solve the problem of population crisis in climatically susceptible countries. Therefore, the sample countries must prioritize climate action and formulate climate-resilient policies to add more years to the lives of their citizens. Similarly, for increasing childbirth the sample nations need to make peace with nature. The outcomes of this study are strong enough, as both the models support each other's findings, producing similar significant outcomes.
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http://dx.doi.org/10.1016/j.heliyon.2023.e22637 | DOI Listing |
Psychol Addict Behav
January 2025
Department of Psychiatry, Center for Behavior Genetics of Aging, University of California, San Diego.
Objective: Alcohol use is common in older adults and linked to poor health and aging outcomes. Studies have demonstrated genetic and environmental contributions to the quantity of alcohol consumption in mid-to-late life, but less is known about whether these influences are moderated by sociodemographic factors such as age, sex, and educational attainment. This study sought to better understand sociodemographic trends in alcohol consumption across the second half of the life course and their underlying genetic and environmental influences.
View Article and Find Full Text PDFHealth Justice
January 2025
Center for Opioid Epidemiology and Policy, Department of Population Health, NYU Grossman School of Medicine, 190 Madison Ave, New York, NY, 10016, USA.
Background: Medicaid expansion via the Affordable Care Act, more recent legislation and Medicaid 1115 waivers offer opportunity to increase health care access among individuals involved in the carceral system. Effective enrollment of new beneficiaries and temporary suspension and reactivation of existing Medicaid benefits upon release is key to the success of these efforts. This study aims to characterize how jails, prisons and Medicaid agencies are implementing Medicaid suspension and enrollment programs and identifies barriers and facilitators to implementation.
View Article and Find Full Text PDFEnviron Sci Pollut Res Int
January 2025
Department of Chemical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, 15875-4413, Iran.
This study presents a novel, eco-friendly method for removing methyldiethanolamine (MDEA) from wastewater, addressing its environmental impact and elevated chemical oxygen demand (COD) from gas refineries. We employed two wetland plants, Phragmites australis and Typha latifolia, utilizing a hydroponics approach to assess MDEA removal efficiency. Wastewater samples from the Ilam gas refinery in Iran were tested at varying initial concentrations (50 to 1600 ppm) over three consecutive 7-day periods, with a 1-day rest interval.
View Article and Find Full Text PDFEnviron Sci Pollut Res Int
January 2025
Institute for Bioanalysis, University of Applied Sciences Coburg, Coburg, Germany.
Biocides, applied in building materials as antimicrobial protectants, can be leached out by rain, presenting substantial environmental risks as confirmed by studies on aquatic environments. However, these biocides are consistently released throughout the year in a diluted form, posing unique challenges for the prediction of transport, transformation, and ecotoxicity assessment in soil. To address this challenge, we combined COMLEAM, which predicts leaching from facades into the soil, with the FOCUS PELMO pesticide model to predict biocide distribution in soil.
View Article and Find Full Text PDFEnviron Geochem Health
January 2025
School of Environmental Science and Engineering, Shandong University, Qingdao, 266237, China.
Groundwater arsenic (As), contamination is a significant issue worldwide including China and Pakistan, particularly in canal command areas. In this study, 131 groundwater samples were collected, and three machine learning models [Random Forest (RF), Logistic Regression (LR), and Artificial Neural Network (ANN)] were employed to predict As concentration. Descriptive statistics helped to conclude that all of the samples were inside the permitted limit of WHO for pH, Ca, Mg, Turbidity, Cl, K, Na, SO, NO, F and beyond limit of WHO for EC, HCO, TDS, and As.
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