The impact of exposure to air pollution on cognitive performance

This paper examines the effect of both cumulative and transitory exposures to air pollution for the same individuals over time on cognitive performance by matching a nationally representative longitudinal survey and air quality data in China according to the exact time and geographic locations of the cognitive tests. We find that long-term exposure to air pollution impedes cognitive performance in verbal and math tests. We provide evidence that the effect of air pollution on verbal tests becomes more pronounced as people age, especially for men and the less educated. The damage on the aging brain by air pollution likely imposes substantial health and economic costs, considering that cognitive functioning is critical for the elderly for both running daily errands and making high-stake decisions.

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Analyzing Individual-Level Secondary Data with Instrumental Variable Methods Is Useful for Studying the Effects of Air Pollution on Dementia

Journal of Alzheimer s Disease ◽

10.3233/jad-200497 ◽

2021 ◽

Vol 79 (1) ◽

pp. 15-23

Author(s):

Kelly C. Bishop ◽

Sehba Husain-Krautter ◽

Jonathan D. Ketcham ◽

Nicolai V. Kuminoff ◽

Corbett Schimming

Keyword(s):

Air Pollution ◽

Instrumental Variable ◽

Secondary Data ◽

Quality Data ◽

Long Term Effects ◽

Individual Level ◽

Medicare Claims Data ◽

Advance Knowledge ◽

Air Quality Data

We hypothesize that analyzing individual-level secondary data with instrumental variable (IV) methods can advance knowledge of the long-term effects of air pollution on dementia. We discuss issues in measurement using secondary data and how IV estimation can overcome biases due to measurement error and unmeasured variables. We link air-quality data from the Environmental Protection Agency’s monitors with Medicare claims data to illustrate the use of secondary data to document associations. Additionally, we describe results from a previous study that uses an IV for pollution and finds that PM2.5’s effects on dementia are larger than non-causal associations.

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Analyzing Individual-Level Secondary Data with Instrumental Variable Methods Is Useful for Studying the Effects of Air Pollution on Dementia

Advances in Alzheimer’s Disease - Alzheimer’s Disease and Air Pollution ◽

10.3233/aiad210044 ◽

2021 ◽

Author(s):

Kelly C. Bishop ◽

Sehba Husain-Krautter ◽

Jonathan D. Ketcham ◽

Nicolai V. Kuminoff ◽

Corbett Schimming

Keyword(s):

Air Pollution ◽

Instrumental Variable ◽

Secondary Data ◽

Quality Data ◽

Long Term Effects ◽

Individual Level ◽

Medicare Claims Data ◽

Advance Knowledge ◽

Air Quality Data

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Health risk assessment and countermeasure analysis of the elderly population exposed to PM2.5 microenvironment

Work ◽

10.3233/wor-205361 ◽

2021 ◽

pp. 1-11

Author(s):

Yan Xu ◽

Wantian Cui

Keyword(s):

Mental Health ◽

Health Risk ◽

Elderly Population ◽

Mental Health Problems ◽

Negative Impact ◽

The Elderly ◽

Exposure Concentration ◽

Physical Diseases ◽

The Impact

BACKGROUND: China’s atmospheric PM2.5 pollution is serious, and PM2.5 exerts a negative impact on the human respiratory system, cardiovascular, and mental health, and even more serious health risk for the elderly with weak immunity. OBJECTIVE: This work aims to analyse the impacts of PM2.5 microenvironment exposure on the health of the elderly and provide corresponding countermeasures. METHODS: The survey subjects are 118 retired elderly people in the community. PM2.5 exposure concentrations are monitored in summer (June 10 ∼ July 10, 2019) and winter (November 25 ∼ December 25, 2019). RESULTS: The exposure concentration in winter is higher than that in summer, with statistical difference (P < 0.05). Under the impact of PM2.5 microenvironment exposure, smoking in the elderly can increase the concentration of PM2.5, and long-term exposure to PM2.5 in the elderly can cause mental health problems. CONCLUSION: Long-term exposure of the elderly to the PM2.5 microenvironment leads to physical diseases and even psychological problems, which requires attention.

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Impact of Frailty on Medical and Long-Term Care Expenditures for the Elderly Age 75 or Over in Japan

Innovation in Aging ◽

10.1093/geroni/igaa057.569 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

pp. 176-176

Author(s):

Hiroto Yoshida ◽

Yuriko Kihara

Keyword(s):

Long Term Care ◽

The Elderly ◽

Elderly Age ◽

Term Care ◽

Intentional Weight Loss ◽

Long Term Care Insurance ◽

And Gender ◽

The Impact

Abstract This study examined the impact of frailty on medical and long-term care expenditures in an older Japanese population. The subjects were those aged 75 years and over who responded to the survey (March 2018) in Bibai, Hokkaido, Japan (n=1,203) and have never received certification of long-term care insurance at the survey. We followed up 867 individuals (72.1%) until the end of December 2018 (10 month-period). We defined frailty as a state in performing 4 items and over of 15 items which were composed of un-intentional weight loss, history of falls, etc. Among 867 subjects, 233 subjects (26.9%) were judged to be frailty group, and 634 subjects (73.1%) non-frailty group. We compared period to the new certification of long-term care insurance (LTCI), accumulated medical and long-term care expenditures adjusted for age and gender between the two groups during the follow-up period. Cox proportional hazard models were used to examine the association between baseline frailty and the new certification of LTCI. The relative hazard ratio (HR) was higher in frailty group than non-frailty group (HR=3.51, 95% CI：1.30-9.45, P=.013). The adjusted mean accumulated medical and long-term care expenditures per capita during the follow-up were significantly (P=.002) larger for those in the frailty group (629,699 yen), while those in the non-frailty group were 450,995 yen. We confirmed strong economic impact of frailty in the elderly aged 75 or over in Japan.

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Modeling Building Stock Development

Sustainability ◽

10.3390/su13020723 ◽

2021 ◽

Vol 13 (2) ◽

pp. 723

Author(s):

Antti Kurvinen ◽

Arto Saari ◽

Juhani Heljo ◽

Eero Nippala

Keyword(s):

Model Development ◽

Housing Demand ◽

Quality Data ◽

Building Stock ◽

Test Arena ◽

Climate Targets ◽

Wide Range ◽

Key Variables ◽

The Impact

It is widely agreed that dynamics of building stocks are relatively poorly known even if it is recognized to be an important research topic. Better understanding of building stock dynamics and future development is crucial, e.g., for sustainable management of the built environment as various analyses require long-term projections of building stock development. Recognizing the uncertainty in relation to long-term modeling, we propose a transparent calculation-based QuantiSTOCK model for modeling building stock development. Our approach not only provides a tangible tool for understanding development when selected assumptions are valid but also, most importantly, allows for studying the sensitivity of results to alternative developments of the key variables. Therefore, this relatively simple modeling approach provides fruitful grounds for understanding the impact of different key variables, which is needed to facilitate meaningful debate on different housing, land use, and environment-related policies. The QuantiSTOCK model may be extended in numerous ways and lays the groundwork for modeling the future developments of building stocks. The presented model may be used in a wide range of analyses ranging from assessing housing demand at the regional level to providing input for defining sustainable pathways towards climate targets. Due to the availability of high-quality data, the Finnish building stock provided a great test arena for the model development.

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Scalable kernel-based SVM classification algorithm on imbalance air quality data for proficient healthcare

Complex & Intelligent Systems ◽

10.1007/s40747-021-00435-5 ◽

2021 ◽

Author(s):

Shwet Ketu ◽

Pramod Kumar Mishra

Keyword(s):

Air Pollution ◽

Air Quality ◽

Class Imbalance ◽

Imbalanced Data ◽

Classification Algorithm ◽

Quality Data ◽

Pollution Level ◽

Classification Problems ◽

Chi Square ◽

The Impact

AbstractIn the last decade, we have seen drastic changes in the air pollution level, which has become a critical environmental issue. It should be handled carefully towards making the solutions for proficient healthcare. Reducing the impact of air pollution on human health is possible only if the data is correctly classified. In numerous classification problems, we are facing the class imbalance issue. Learning from imbalanced data is always a challenging task for researchers, and from time to time, possible solutions have been developed by researchers. In this paper, we are focused on dealing with the imbalanced class distribution in a way that the classification algorithm will not compromise its performance. The proposed algorithm is based on the concept of the adjusting kernel scaling (AKS) method to deal with the multi-class imbalanced dataset. The kernel function's selection has been evaluated with the help of weighting criteria and the chi-square test. All the experimental evaluation has been performed on sensor-based Indian Central Pollution Control Board (CPCB) dataset. The proposed algorithm with the highest accuracy of 99.66% wins the race among all the classification algorithms i.e. Adaboost (59.72%), Multi-Layer Perceptron (95.71%), GaussianNB (80.87%), and SVM (96.92). The results of the proposed algorithm are also better than the existing literature methods. It is also clear from these results that our proposed algorithm is efficient for dealing with class imbalance problems along with enhanced performance. Thus, accurate classification of air quality through our proposed algorithm will be useful for improving the existing preventive policies and will also help in enhancing the capabilities of effective emergency response in the worst pollution situation.

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Quantifying the impact of air pollution on the urban population of Brazil

Cadernos de Saúde Pública ◽

10.1590/s0102-311x2007001600013 ◽

2007 ◽

Vol 23 (suppl 4) ◽

pp. S529-S536 ◽

Cited By ~ 15

Author(s):

Izabel Marcilio ◽

Nelson Gouveia

Keyword(s):

Air Pollution ◽

Urban Population ◽

Hospital Admissions ◽

Age Groups ◽

The Elderly ◽

Impact Factors ◽

Pollution Levels ◽

Time Series Studies ◽

The Impact ◽

Respiratory Causes

This study aimed to quantify air pollution impact on morbidity and mortality in the Brazilian urban population using locally generated impact factors. Concentration-response coefficients were used to estimate the number of hospitalizations and deaths attributable to air pollution in seven Brazilian cities. Poisson regression coefficients (beta) were obtained from time-series studies conducted in Brazil. The study included individuals 65 years old and over and children under five. More than 600 deaths a year from respiratory causes in the elderly and 47 in children were attributable to mean air pollution levels, corresponding to 4.9% and 5.5% of all deaths from respiratory causes in these age groups. More than 4,000 hospital admissions for respiratory conditions were also attributable to air pollution. These results quantitatively demonstrate the currently observed contribution of air pollution to mortality and hospitalizations in Brazilian cities. Such assessment is thought to help support the planning of surveillance and control activities for air pollution in these and similar areas.

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Air Pollution and Human Sperm Sex Ratio

American Journal of Men s Health ◽

10.1177/1557988317752608 ◽

2018 ◽

Vol 12 (4) ◽

pp. 907-912 ◽

Cited By ~ 3

Author(s):

Michał Radwan ◽

Emila Dziewirska ◽

Paweł Radwan ◽

Lucjusz Jakubowski ◽

Wojciech Hanke ◽

...

Keyword(s):

Air Pollution ◽

Particulate Matter ◽

Sex Ratio ◽

Human Sperm ◽

Quality Data ◽

Aerodynamic Diameter ◽

Limited Data ◽

Study Population ◽

Air Quality Data

The present study was designed to address the hypothesis that exposure to specific air pollutants may impact human sperm Y:X chromosome ratio. The study population consisted of 195 men who were attending an infertility clinic for diagnostic purposes and who had normal semen concentration of 15–300 mln/ml (WHO, 2010). Participants represented a subset of men in a multicenter parent study conducted in Poland to evaluate environmental factors and male fertility. Participants were interviewed and provided a semen sample. The Y:X ratio was assessed by fluorescent in situ hybridization (FISH). Air quality data were obtained from the AirBase database. In multivariate analysis the significant reduction was observed in the proportion of Y/X chromosome bearing sperm and exposure to particulate matter >10 μm in aerodynamic diameter PM10 ( p = .009) and particulate matter <10 μm in aerodynamic diameter PM2.5 ( p = .023). The observed effects of a lower Y:X sperm chromosome ratio among men exposed to air pollution support the evidence that the trend of declining sex ratio in several societies over past decades has been due to exposure to air pollution; however due to limited data on this issue, the obtained results should be confirmed in longitudinal studies.

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Glucose variability and the risks of stroke, myocardial infarction, and all-cause mortality in individuals with diabetes: retrospective cohort study

Cardiovascular Diabetology ◽

10.1186/s12933-020-01134-0 ◽

2020 ◽

Vol 19 (1) ◽

Cited By ~ 1

Author(s):

Da Young Lee ◽

Kyungdo Han ◽

Sanghyun Park ◽

Ji Hee Yu ◽

Ji A. Seo ◽

...

Keyword(s):

Myocardial Infarction ◽

Cohort Study ◽

Retrospective Cohort Study ◽

Retrospective Cohort ◽

The Elderly ◽

Glucose Variability ◽

All Cause Mortality ◽

Nationwide Observational Study ◽

The Impact

Abstract Background Previous research regarding long-term glucose variability over several years which is an emerging indicator of glycemic control in diabetes showed several limitations. We investigated whether variability in long-term fasting plasma glucose (FG) can predict the development of stroke, myocardial infarction (MI), and all-cause mortality in patients with diabetes. Methods This is a retrospective cohort study using the data provided by the Korean National Health Insurance Corporation. A total of 624,237 Koreans ≥ 20 years old with diabetes who had undergone health examinations at least twice from 2005 to 2008 and simultaneously more than once from 2009 to 2010 (baseline) without previous histories of stroke or MI. As a parameter of variability of FG, variability independent of mean (VIM) was calculated using FG levels measured at least three times during the 5 years until the baseline. Study endpoints were incident stroke, MI, and all-cause mortality through December 31, 2017. Results During follow-up, 25,038 cases of stroke, 15,832 cases of MI, and 44,716 deaths were identified. As the quartile of FG VIM increased, the risk of clinical outcomes serially increased after adjustment for confounding factors including duration and medications of diabetes and the mean FG. Adjusted hazard ratios (95% confidence intervals) of FG VIM quartile 4 compared with quartile 1 were 1.20 (1.16–1.24), 1.20 (1.15–1.25), and 1.32 (1.29–1.36) for stroke, MI and all-cause mortality, respectively. The impact of FG variability was higher in the elderly and those with a longer duration of diabetes and lower FG levels. Conclusions In diabetes, long-term glucose variability showed a dose–response relationship with the risk of stroke, MI, and all-cause mortality in this nationwide observational study.

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A Preliminary Attempt at the Identification and Financial Estimation of the Negative Health Effects of Urban and Industrial Air Pollution Based on the Agglomeration of Gdańsk

Sustainability ◽

10.3390/su12010042 ◽

2019 ◽

Vol 12 (1) ◽

pp. 42 ◽

Cited By ~ 3

Author(s):

Piotr O. Czechowski ◽

Piotr Dąbrowiecki ◽

Aneta Oniszczuk-Jastrząbek ◽

Michalina Bielawska ◽

Ernest Czermański ◽

...

Keyword(s):

Air Pollution ◽

Health Effects ◽

Causal Relation ◽

Financial Burden ◽

Incidence Rates ◽

Industrial Air Pollution ◽

Urban Populations ◽

General Regression ◽

The Impact

This article marks the first attempt on Polish and European scale to identify the relationship between urban and industrial air pollution and the health conditions of urban populations, while also estimating the financial burden of incidence rates among urban populations for diseases selected in the course of this study as having a causal relation with such incidence. This paper presents the findings of a pilot study based on general regression models, intended to explore air pollutants with a statistically relevant impact on the incidence of selected diseases within the Agglomeration of Gdańsk in the years 2010–2018. In discussing the city’s industrial functions, the study takes into consideration the existence within its limits of a large port that services thousands of ships every year, contributing substantially to the volume of emissions (mainly NOx and PM) to the air. The causes considered include the impact of air pollution, seasonality, land- and sea-based emissions, as well as their mutual interactions. All of the factors and their interactions have a significant impact (p ≤ 0.05) on the incidence of selected diseases in the long term (9 years). The source data were obtained from the Polish National Health Fund (NFZ), the Agency for Regional Monitoring of Atmosphere in the Agglomeration of Gdańsk (ARMAAG), the Chief Inspectorate of Environmental Protection (GIOŚ), and the Port of Gdańsk Harbourmaster. The study used 60 variables representing the diseases, classified into 19 groups. The resulting findings were used to formulate a methodology for estimating the financial burden of the negative health effects of air pollution for the agglomeration, and will be utilized as a reference point for further research in selected regions of Poland.

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