Weather and air pollutants have an impact on patients with respiratory diseases and breathing difficulties in Munich, Germany

Methods to Advance Climate Science in Respiratory Health: Satellite-Based Environmental Modeling for Temperature Exposure Assessment in Epidemiological Studies

Climate change is a major concern with significant impacts on human health including respiratory outcomes, particularly through changes in air temperature. The rise in global temperature has led to an increase in heat waves and extreme weather events, which pose serious risks to respiratory health. Accurately assessing the effects of air temperature on respiratory health requires a comprehensive approach that incorporates fine-scale exposure assessment to characterize the geospatial environment impacting population health. Recent advances in open-source earth observation data have allowed for improved exposure assessment through temperature modeling.

Climate and human health: a review of publication trends in the International Journal of Biometeorology

The climate-health nexus is well documented in the field of biometeorology. Since its inception, Biometeorology has in many ways become the umbrella under which much of this collaborative research has been conducted. Whilst a range of review papers have considered the development of biometeorological research and its coverage in this journal, and a few have reviewed the literature on specific diseases, none have focused on the sub-field of climate and health as a whole. Since its first issue in 1957, the International Journal of Biometeorology has published a total of 2183 papers that broadly consider human health and its relationship with climate. In this review, we identify a total of 180 (8.3%, n = 2183) of these papers that specifically focus on the intersection between meteorological variables and specific, named diagnosable diseases, and explore the publication trends thereof. The number of publications on climate and health in the journal increases considerably since 2011. The largest number of publications on the topic was in 2017 (18) followed by 2021 (17). Of the 180 studies conducted, respiratory diseases accounted for 37.2% of the publications, cardiovascular disease 17%, and cerebrovascular disease 11.1%. The literature on climate and health in the journal is dominated by studies from the global North, with a particular focus on Asia and Europe. Only 2.2% and 8.3% of these studies explore empirical evidence from the African continent and South America respectively. These findings highlight the importance of continued research on climate and human health, especially in low- and lower-middle-income countries, the populations of which are more vulnerable to climate-sensitive illnesses.

The relationship of weather with daily physical activity and the time spent out of home in older adults from Germany – the ActiFE study

Background

There is a need for a comprehensive evaluation of the associations between varieties of weather conditions on the time spent out-of-home (TOH) and on walking duration (WD) among older adults. We aim to investigate the extent to which various weather parameters (temperature, solar radiation, sunshine duration, humidity, windspeed, and rain) determine daily WD the TOH in older adults.

Methods

The ActiFE (Activity and Function in Older People in Ulm) study is a prospective study of participants aged 65 years or older who wore an accelerometer and kept a movement diary in up to three temporally separated waves from 2009 to 2018 for a duration up to seven days per wave (up to three weeks in summary). We used weather data from a weather station near the participants‘ homes. Age-adjusted and gender-stratified generalized mixed models were used to predict WD and TOH (with 95% confidence interval (CI)) within and between weather categories. Generalized additive models were computed for the single predictions at the weather quartile boundaries. Cubic splines (with 95% pointwise confidence bands (CB)) visualized the continuous course of the weather values.

Results

Higher temperatures, solar radiation and more hours of sunshine, led to an increase in WD and TOH, while higher precipitation, humidities and windspeeds led to a decrease. Women had in general higher WD and TOH times than men.

Conclusions

Our data suggest that weather parameters have a considerable influence on PA and TOH. Future analyses and interpretation of PA data should therefore account for weather parameters.

Supplementary Information

The online version contains supplementary material available at 10.1186/s11556-022-00286-0.

A Machine Learning-Based Study of the Effects of Air Pollution and Weather in Respiratory Disease Patients Visiting Emergency Departments

Background. To date, investigating respiratory disease patients visiting the emergency departments related with fined dust is limited. This study aimed to analyze the effects of two variable-weather and air pollution on respiratory disease patients who visited emergency departments. Methods. This study utilized the National Emergency Department Information System (NEDIS) database. The meteorological data were obtained from the National Climate Data Service. Each weather factor reflected the accumulated data of 4 days: a patient’s visit day and 3 days before the visit day. We utilized the RandomForestRegressor of scikit-learn for data analysis. Result. The study included 525,579 participants. This study found that multiple variables of weather and air pollution influenced the respiratory diseases of patients who visited emergency departments. Most of the respiratory disease patients had acute upper respiratory infections [J00–J06], influenza [J09–J11], and pneumonia [J12–J18], on which PM10 following temperature and steam pressure was the most influential. As the top three leading causes of admission to the emergency department, pneumonia [J12–J18], acute upper respiratory infections [J00–J06], and chronic lower respiratory diseases [J40–J47] were highly influenced by PM10. Conclusion. Most of the respiratory patients visiting EDs were diagnosed with acute upper respiratory infections, influenza, and pneumonia. Following temperature, steam pressure and PM10 had influential relations with these diseases. It is expected that the number of respiratory disease patients visiting the emergency departments will increase by day 3 when the steam pressure and temperature values are low, and the variables of air pollution are high. The number of respiratory disease patients visiting the emergency departments will increase by day 3 when the steam pressure and temperature values are low, and the variables of air pollution are high.

Weather-related subjective well-being in patients with coronary artery disease

One of the particularly vulnerable groups for adverse weather conditions is people with heart disease. Most of the studies analyzed the association between certain weather conditions and increased mortality, morbidity, hospital admissions, calls, or visits to the emergency department and used as statistical data. This study evaluated associations between daily weather conditions and daily weather-related well-being in patients with coronary artery disease (CAD). From June 2008 to October 2012, a total of 865 consecutive patients with CAD (mean age 60 years; 30% of women) were recruited from the cardiac rehabilitation program at the Hospital Palanga Clinic, Lithuania. To evaluate the well-being, all patients filled in Palanga self-assessment diary for weather sensitivity every day from 8 to 21 days (average 15 ± 3 days) about their well-being (psychological, cardiac, and physical symptoms) on the last day. The weather data was recorded in the database eight times every day with a 3-hour interval using the weather station "Vantage Pro2 Plus" which was located in the same Clinic. The daily averages of the eight time records for weather parameters were calculated and were linked to the same-day diary data. We found that the well-being of patients with CAD was associated with weather parameters; specifically, general well-being was better within the temperature range 9-15 °C and worse on both sides of this range. Worsened general well-being was also associated with higher relative humidity and lower atmospheric pressure. Weather parameters can explain from 3 to 8% of the variance of well-being in patients with CAD.

Association of air pollution with outpatient visits for respiratory diseases of children in an ex-heavily polluted Northwestern city, China

BACKGROUND

A great number of studies have confirmed that children are a particularly vulnerable population to air pollution.

METHODS

In the present study, 332,337 outpatient visits of 15 hospitals for respiratory diseases among children (0-13 years), as well as the simultaneous meteorological and air pollution data, were obtained from 2014 to 2016 in Lanzhou, China. The generalized additive model was used to examine the effects of air pollutants on children's respiratory outpatient visits, including the stratified analysis of age, gender and season.

RESULTS

We found that PM_2.5, NO₂ and SO₂ were significantly associated with the increased total respiratory outpatient visits. The increments of total respiratory outpatient visits were the highest in lag 05 for NO₂ and SO₂, a 10 μg/m³ increase in NO₂ and SO₂ was associated with a 2.50% (95% CI: 1.54, 3.48%) and 3.50% (95% CI: 1.51, 5.53%) increase in total respiratory outpatient visits, respectively. Those associations remained stable in two-pollutant models. Through stratification analysis, all air pollutants other than PM₁₀ were significantly positive associated with the outpatients of bronchitis and upper respiratory tract infection. Besides, both NO₂ and SO₂ were positively related to the pneumonia outpatient visits. PM_2.5 and SO₂ were significantly related to the outpatient visits of other respiratory diseases, while only NO₂ was positively associated with the asthma outpatients. We found these associations were stronger in girls than in boys, particularly in younger (0-3 years) children. Interestingly, season stratification analysis indicated that these associations were stronger in the cold season than in the transition or the hot season for PM₁₀, PM_2.5 and SO₂.

CONCLUSIONS

Our results indicate that the air pollution exposure may account for the increased risk of outpatient visits for respiratory diseases among children in Lanzhou, particularly for younger children and in the cold season.

A time for everything and everything in its time - exploring the mechanisms underlying seasonality of COPD exacerbations

Across Europe, COPD affects 23 million people leading to annual health care costs of ~€25.1 billion. This burden is particularly severe during winter months in association with the peak incidence of exacerbation events. Seasonal variation in the health status of patients with COPD places additional and often critical pressure on already strained health care resources. COPD exacerbations are characterized by worsening day-to-day symptoms of an individual and often triggered by respiratory infections, but the process by which this occurs in a seasonal fashion is likely to be multifactorial. In this review, we discuss recent population studies that highlight the impact of seasonality in COPD and review the proposed biological mechanisms underlying this. An appraisal of the role of the host susceptibility and response, environmental triggers and the biology of respiratory pathogens is detailed. The impact of each aspect is considered, and an integrated model of the context for the whole individual and society in general is explored.

Past, present and future of the climate and human health commission

The following paper presents the history of the Climate and Human Health Commission at the International Society of Biometeorology after more than one decade since its creation. A brief history of the origins of the human biometeorology is revealed through some of the main research topics and publications of the founders of the society in this field. Secondly, it is presented as a brief review of the activities of the commission in the last 10 years, based on the reports that have periodically been submitted by members of the commission to the Bulletin of the society. A summary of the topics of interest on human biometeorology and the most frequent research topics are also described. Thirdly, the need of adapting human biometeorology contents, methods and techniques to a changing world is articulated according to some of the new environmental threats in the XXI century. Finally, a list of future actions and research lines collected through a form from members of the commission is presented. The paper concludes with the existence of great challenge for human biometeorology in order to transform biometeorological knowledge into specific services to improve the wellbeing of human beings.

Predicting Flow in the Pediatric Emergency Department: Are Holidays Lighter?

OBJECTIVE

The aim of this study was to determine whether patient volume in an urban pediatric emergency department (ED) can be predicted based on holidays and thus aid in staffing and resource allocation.

METHODS

Log-in dates and times were obtained for all patients seen in an urban pediatric ED between July 1, 2006, and June 30, 2013. Visits were coded for the day of the week, tour (ie, shift), and season and whether they occurred on a holiday or nonholiday. Comparisons between the median number of patient visits on holidays versus nonholidays by day of the week, tour, and season were performed. Additional comparisons on 5 Monday holidays as well as New Year's Day, Thanksgiving, and Christmas Day were also performed. Data were presented as medians with interquartile ranges. Group comparisons were performed via using Mann-Whitney U tests and Kruskal-Wallis tests (α = 0.05, 2 tailed).

RESULTS

There were 223,677 total patient visits, with a mean yearly census of 31,954. The median daily volume was 85, peaking on Mondays (median, 99). The summer season demonstrated the fewest number of patient visits (median, 74) relative to the other seasons (medians, 89-91). Compared with nonholidays, there were fewer patient visits on Thanksgiving and Christmas Day and in the late afternoon and evening on other individual holidays.

CONCLUSIONS

Fewer patient visits on Thanksgiving and Christmas Days, as well as during the late afternoon/evening on several other holidays, point to the possibility of small adjustments to staffing in ways that can more efficiently balance demand with available resources.

Neighborhood-Level Factors Related to Asthma in Children Living in Urban Areas

Asthma disproportionately affects children who are non-White and of low socioeconomic status. One innovative approach to address these health disparities is to investigate the child's neighborhood environment and factors influencing asthma symptoms. The purpose of this integrative review is to critique research investigating the relationships between neighborhood-level factors and asthma morbidity in urban children. Three literature databases were searched using the terms "asthma," "child," "neighborhood," and "urban." The articles included were organized into six themes within the larger domains of prevalence, physical, and social factors. Literature tables provide in-depth analysis of each article and demonstrate a need for strengthening analysis methods. The current research points to the necessity for a multilevel study to analyze neighborhood-level factors that are associated with increased asthma morbidity in urban children. School nurse clinicians, working within children's neighborhoods, are uniquely positioned to assess modifiable neighborhood-level determinants of health in caring for children with asthma.

Humidity: A review and primer on atmospheric moisture and human health

Research examining associations between weather and human health frequently includes the effects of atmospheric humidity. A large number of humidity variables have been developed for numerous purposes, but little guidance is available to health researchers regarding appropriate variable selection. We examine a suite of commonly used humidity variables and summarize both the medical and biometeorological literature on associations between humidity and human health. As an example of the importance of humidity variable selection, we correlate numerous hourly humidity variables to daily respiratory syncytial virus isolates in Singapore from 1992 to 1994. Most water-vapor mass based variables (specific humidity, absolute humidity, mixing ratio, dewpoint temperature, vapor pressure) exhibit comparable correlations. Variables that include a thermal component (relative humidity, dewpoint depression, saturation vapor pressure) exhibit strong diurnality and seasonality. Humidity variable selection must be dictated by the underlying research question. Despite being the most commonly used humidity variable, relative humidity should be used sparingly and avoided in cases when the proximity to saturation is not medically relevant. Care must be taken in averaging certain humidity variables daily or seasonally to avoid statistical biasing associated with variables that are inherently diurnal through their relationship to temperature.

Modeling and predicting hemorrhagic fever with renal syndrome trends based on meteorological factors in Hu County, China

Background

Hu County is a serious hemorrhagic fever with renal syndrome (HFRS) epidemic area, with notable fluctuation of the HFRS epidemic in recent years. This study aimed to explore the optimal model for HFRS epidemic prediction in Hu.

Methods

Three models were constructed and compared, including a generalized linear model (GLM), a generalized additive model (GAM), and a principal components regression model (PCRM). The fitting and predictive adjusted R² of each model were calculated. Ljung-Box Q tests for fitted and predicted residuals of each model were conducted. The study period was stratified into before (1971–1993) and after (1994–2012) vaccine implementation epochs to avoid the confounding factor of vaccination.

Results

The autocorrelation of fitted and predicted residuals of the GAM in the two epochs were not significant (Ljung-Box Q test, P>.05). The adjusted R² for the predictive abilities of the GLM, GAM, and PCRM were 0.752, 0.799, and 0.665 in the early epoch, and 0.669, 0.756, and 0.574 in the recent epoch. The adjusted R² values of the three models were lower in the early epoch than in the recent epoch.

Conclusions

GAM is superior to GLM and PCRM for monthly HFRS case number prediction in Hu County. A shift in model reliability coincident with vaccination implementation demonstrates the importance of vaccination in HFRS control and prevention.