Search

In environmental epidemiology, time series analyses represent a widely used statistical tool. However, though being commonly used, there is soften confusion regarding the specific requirements, such as which link function might be most appropriate, when or how to control for seasonality or how to account for lags. The present overview draws from experiences in other disciplines and discusses the proper execution of time series analyses based on considerations that are relevant in environmental epidemiology. Time series analysis in environmental epidemiology focuses on acute events caused by short-term changes in exposure. These exposures should be fairly wide-spread affecting a large number of persons, usually all inhabitants of a political entity. Pollutants in air or drinking water as well as meteorological factors serve as typical examples. Despite the many time series analyses performed world-wide, some health effects that would lend themselves to that approach are still under-explored. This would include also some neurological and psychiatric endpoints. Int J Occup Med Environ Health. 2023;36(6):704–16

A pumped storage power plant produces significant noise such that adjacent areas were deemed uninhabitable for the local population. In recent years, the population in the area has increased, and the noise levels are now causing significant distress to the local population. The company operating the power plant and a citizens’ initiative have both commissioned noise measurements. The measurements showed that the continuous pump noise was audible over many kilometers. The A-weighted sound-pressure level of 50 dBA at the next residential area underestimates the perceived noise, given the clear tonal nature in the low frequency range. Interviews of the exposed population, together with detailed “annoyance diaries” by a sample of the residents, proved their high level of annoyance. Their reported observations on distress and sleep disturbances coincide with the time course of the pumping operation. The pumping noise leads to annoyance in a large area, and to considerable nuisance in a smaller one. For the most exposed homes, long-term exposure might be considered a health hazard due to stress and disturbances in sleep quality. Therefore, the operator committed to developing a technical noise control plan. This case shows that a scientific approach within a complex environmental noise problem can foster an agreement about noise protection measures. However, this can only be successful if all involved parties participate in the process. Pilot studies are underway to test the impact of damping material layers on the pipes, the housing of the pipes, and the kind of air vessel solutions between the pumps and the pipes. Int J Occup Med Environ Health. 2019;32(3):401–11

Objectives: The World Health Organization (WHO) provides data on national indices of health, environment and economy. When we were asked, why air pollution is negatively correlated with cancer mortality, our first response (presumably the mortality data are not age-adjusted) was not sufficient to explain the paradox. Material and Methods: A table including all-cause, cancer and childhood mortality, life expectancy, gross national product per person, smoking prevalence, physician density and particulate matter (PM10) per country (N = 193) was developed. For explorative purposes weighted cross-sectional multiple linear regressions models were built. Results: Air pollution is positively correlated with infant and overall mortality and negatively with life expectancy. This might not only depict a true causal effect of PM10 because air quality is also an indicator of a country’s prosperity and general state of environment. Cancer mortality is negatively correlated with PM10. However, this association turns positive when economic or health system indicators are controlled. Conclusions: The World Health Organization’s world-wide data sets demonstrate the large disparity of our world. A careful and professional approach is needed as interpretation is difficult, especially for lay persons. Therefore, with publicly available data WHO should also provide interpretation and guidance.

Objectives: WHO's Children's Environment and Health Action Plan for Europe (CEHAPE) focuses on improvements of indoor environments where children spend most of their time. To investigate the relationship between school indoor air pollutants and cognitive performance in elementary school children, a multidisciplinary study was planned in all-day schools in Austria. Materials and Methods: In a cross-sectional study (LuKi study: Air and Children) indoor air pollutants were monitored in nine elementary all-day schools in urban and rural regions of Austria. In addition, school dust and suspended particulates (PM10, PM2.5) were measured, focusing on semivolatile compounds (e.g. phthalates, phosphororganic compounds [POC]). Health status and environmental conditions were determined by parents' questionnaire, cognitive function was measured by Standard Progressive Matrices (SPM). Results: Overall, 596 children (6-8 years of age) were eligible for the study. Cognitive tests were performed in 436 children. Analysis showed significant correlations of tris(2-chlorethyl)-phosphate (TCEP) in PM10 and PM2.5 and school dust samples with cognitive performance. Cognitive performance decreased with increasing concentrations of TCEP. Furthermore, cognitive function decreased significantly with increasing CO2 levels. Conclusions: POC are widely used as plasticizers, flame retardants and floor sealing. This is the first report of a correlation between TCEP in indoor air samples and impairment of cognitive performance in school children. As a precautionary measure, it is recommended to prohibit the use of toxic chemicals and those suspected of a toxic potential in children's environments such as schools.