Susceptibility of hypertensive individuals to acute blood pressure increases in response to personal-level environmental temperature decrease.

BACKGROUND: Environmental temperature is negatively associated with blood pressure (BP), and hypertension may exacerbate this association. The aim of this study is to investigate whether hypertensive individuals are more susceptible to acute BP increases following temperature decrease than non-hypertensive individuals. METHODS: The study panel consisted of 126 hypertensive and 125 non-hypertensive (n = 251) elderly participants who completed 940 clinical visits during the winter of 2016 and summer of 2017 in Beijing, China. Personal-level environmental temperature (PET) was continuously monitored for each participant with a portable sensor platform. We associated systolic BP (SBP) and diastolic BP (DBP) with the average PET over 24 h before clinical visits using linear mixed-effects models and explored hourly lag patterns for the associations using distributed lag models. RESULTS: We found that per 1 °C decrease in PET, hypertensive individuals showed an average (95 % confidence interval) increase of 0.96 (0.72, 1.19) and 0.28 (0.13, 0.42) mmHg for SBP and DBP, respectively; and non-hypertensive participants showed significantly smaller increases of 0.28 (0.03, 0.53) mmHg SBP and 0.14 (-0.01, 0.30) mmHg DBP. A lag pattern analysis showed that for hypertensive individuals, the increases in SBP and DBP were greatest following lag 1 h PET decrease and gradually attenuated up to lag 10 h exposure. No significant BP change was observed in non-hypertensive individuals associated with lag 1-24 h PET exposure. The enhanced increase in PET-associated BP in hypertensive participants (i.e., susceptibility) was more significant in winter than in summer. CONCLUSIONS: We found that a decrease in environmental temperature was associated with acute BP increases and these associations diminished over time, disappearing after approximately 10 hours. This implies that any intervention measures to prevent BP increases due to temperature drop should be implemented as soon as possible. Such timely interventions are particularly needed for hypertensive individuals especially during the cold season due to their increased susceptibility.

Understanding the patterns and health impact of indoor air pollutant exposures in Bradford, UK: a study protocol.

INTRODUCTION: Relative to outdoor air pollution, there is little evidence examining the composition and concentrations of indoor air pollution and its associated health impacts. The INGENIOUS project aims to provide the comprehensive understanding of indoor air pollution in UK homes. METHODS AND ANALYSIS: 'Real Home Assessment' is a cross-sectional, multimethod study within INGENIOUS. This study monitors indoor air pollutants over 2 weeks using low-cost sensors placed in three rooms in 300 Born in Bradford (BiB) households. Building audits are completed by researchers, and participants are asked to complete a home survey and a health and behaviour questionnaire, in addition to recording household activities and health symptoms on at least 1 weekday and 1 weekend day. A subsample of 150 households will receive more intensive measurements of volatile organic compound and particulate matter for 3 days. Qualitative interviews conducted with 30 participants will identify key barriers and enablers of effective ventilation practices. Outdoor air pollution is measured in 14 locations across Bradford to explore relationships between indoor and outdoor air quality. Data will be analysed to explore total concentrations of indoor air pollutants, how these vary with building characteristics, and whether they are related to health symptoms. Interviews will be analysed through content and thematic analysis. ETHICS AND DISSEMINATION: Ethical approval has been obtained from the NHS Health Research Authority Yorkshire and the Humber (Bradford Leeds) Research Ethics Committee (22/YH/0288). We will disseminate findings using our websites, social media, publications and conferences. Data will be open access through the BiB, the Open Science Framework and the UK Data Service.

Early detection of COPD patients' symptoms with personal environmental sensors: a remote sensing framework using probabilistic latent component analysis with linear dynamic systems.

In this study, we present a cohort study involving 106 COPD patients using portable environmental sensor nodes with attached air pollution sensors and activity-related sensors, as well as daily symptom records and peak flow measurements to monitor patients' activity and personal exposure to air pollution. This is the first study which attempts to predict COPD symptoms based on personal air pollution exposure. We developed a system that can detect COPD patients' symptoms one day in advance of symptoms appearing. We proposed using the Probabilistic Latent Component Analysis (PLCA) model based on 3-dimensional and 4-dimensional spectral dictionary tensors for personalised and population monitoring, respectively. The model is combined with Linear Dynamic Systems (LDS) to track the patients' symptoms. We compared the performance of PLCA and PLCA-LDS models against Random Forest models in the identification of COPD patients' symptoms, since tree-based classifiers were used for remote monitoring of COPD patients in the literature. We found that there was a significant difference between the classifiers, symptoms and the personalised versus population factors. Our results show that the proposed PLCA-LDS-3D model outperformed the PLCA and the RF models between 4 and 20% on average. When we used only air pollutants as input, the PLCA-LDS-3D forecasting results in personalised and population models were 48.67 and 36.33% accuracy for worsening of lung capacity and 38.67 and 19% accuracy for exacerbation of COPD patients' symptoms, respectively. We have shown that indicators of the quality of an individual's environment, specifically air pollutants, are as good predictors of the worsening of respiratory symptoms in COPD patients as a direct measurement.

Associations of air pollution mixtures with ambulatory blood pressure: The MobiliSense sensor-based study.

Air pollution is acknowledged as a determinant of blood pressure (BP), supporting the hypothesis that air pollution, via hypertension and other mechanisms, has detrimental effects on human health. Previous studies evaluating the associations between air pollution exposure and BP did not consider the effect that air pollutant mixtures may have on BP. We investigated the effect of exposure to single species or their synergistic effects as air pollution mixture on ambulatory BP. Using portable sensors, we measured personal concentrations of black carbon (BC), nitrogen dioxide (NO2), nitrogen monoxide (NO), carbon monoxide (CO), ozone (O3), and particles with aerodynamic diameters below 2.5 µm (PM2.5). We simultaneously collected ambulatory BP measurements (30-min intervals, N = 3319) of 221 participants over one day of their lives. Air pollution concentrations were averaged over 5 min to 1 h before each BP measurement, and inhaled doses were estimated across the same exposure windows using estimated ventilation rates. Fixed-effect linear models as well as quantile G-computation techniques were applied to associate air pollutants' individual and combined effects with BP, adjusting for potential confounders. In mixture models, a quartile increase in air pollutant concentrations (BC, NO2, NO, CO, and O3) in the previous 5 min was associated with a 1.92 mmHg (95% CI: 0.63, 3.20) higher systolic BP (SBP), while 30-min and 1-h exposures were not associated with SBP. However, the effects on diastolic BP (DBP) were inconsistent across exposure windows. Unlike concentration mixtures, inhalation mixtures in the previous 5 min to 1 h were associated with increased SBP. Out-of-home BC and O3 concentrations were more strongly associated with ambulatory BP outcomes than in-home concentrations. In contrast, only the in-home concentration of CO reduced DBP in stratified analyses. This study shows that exposure to a mixture of air pollutants (concentration and inhalation) was associated with elevated SBP.

Automated classification of time-activity-location patterns for improved estimation of personal exposure to air pollution.

BACKGROUND: Air pollution epidemiology has primarily relied on measurements from fixed outdoor air quality monitoring stations to derive population-scale exposure. Characterisation of individual time-activity-location patterns is critical for accurate estimations of personal exposure and dose because pollutant concentrations and inhalation rates vary significantly by location and activity. METHODS: We developed and evaluated an automated model to classify major exposure-related microenvironments (home, work, other static, in-transit) and separated them into indoor and outdoor locations, sleeping activity and five modes of transport (walking, cycling, car, bus, metro/train) with multidisciplinary methods from the fields of movement ecology and artificial intelligence. As input parameters, we used GPS coordinates, accelerometry, and noise, collected at 1 min intervals with a validated Personal Air quality Monitor (PAM) carried by 35 volunteers for one week each. The model classifications were then evaluated against manual time-activity logs kept by participants. RESULTS: Overall, the model performed reliably in classifying home, work, and other indoor microenvironments (F1-score>0.70) but only moderately well for sleeping and visits to outdoor microenvironments (F1-score=0.57 and 0.3 respectively). Random forest approaches performed very well in classifying modes of transport (F1-score>0.91). We found that the performance of the automated methods significantly surpassed those of manual logs. CONCLUSIONS: Automated models for time-activity classification can markedly improve exposure metrics. Such models can be developed in many programming languages, and if well formulated can have general applicability in large-scale health studies, providing a comprehensive picture of environmental health risks during daily life with readily gathered parameters from smartphone technologies.

A Systematic Review Protocol of Opportunities for Noncommunicable Disease Prevention via Public Space Initiatives in African Cities.

Public spaces have the potential to produce equitable improvements in population health. This mixed-methods systematic review aims to understand the components of, determinants, risks, and outcomes associated with public space initiatives in African cities. This study will include quantitative and qualitative study designs that describe public space initiatives in African cities with implications for promoting health and wellbeing, particularly through the prevention of noncommunicable diseases. Only studies published after 1990 and that contain primary or secondary data will be included in the review. Literature search strategies will be developed with a medical librarian. We will search PubMed, using both text words and medical subject headings. We will adapt this search to Scopus, Global Health, and Web of Science. This systematic review will adopt a mixed methods analytical approach. Mixing will occur in extracting both qualitative and quantitative findings; in synthesizing findings; and in the analysis where we will integrate the qualitative and quantitative strands. The learnings from this study will contribute to advancing knowledge on noncommunicable disease prevention through public space initiatives in African cities.

Personal exposure to air pollution and respiratory health of COPD patients in London.

Previous studies have investigated the effects of air pollution on chronic obstructive pulmonary disease (COPD) patients using either fixed-site measurements or a limited number of personal measurements, usually for one pollutant and a short time period. These limitations may introduce bias and distort the epidemiological associations as they do not account for all the potential sources or the temporal variability of pollution.We used detailed information on individuals' exposure to various pollutants measured at fine spatiotemporal scale to obtain more reliable effect estimates. A panel of 115 patients was followed up for an average continuous period of 128 days carrying a personal monitor specifically designed for this project that measured temperature, nitrogen dioxide (NO2), ozone (O3), nitric oxide (NO), carbon monoxide (CO), and particulate matter with aerodynamic diameter <2.5 and <10 µm at 1-min time resolution. Each patient recorded daily information on respiratory symptoms and measured peak expiratory flow (PEF). A pulmonologist combined related data to define a binary variable denoting an "exacerbation". The exposure-response associations were assessed with mixed effects models.We found that gaseous pollutants were associated with a deterioration in patients' health. We observed an increase of 16.4% (95% CI 8.6-24.6%), 9.4% (95% CI 5.4-13.6%) and 7.6% (95% CI 3.0-12.4%) in the odds of exacerbation for an interquartile range increase in NO2, NO and CO, respectively. Similar results were obtained for cough and sputum. O3 was found to have adverse associations with PEF and breathlessness. No association was observed between particulate matter and any outcome.Our findings suggest that, when considering total personal exposure to air pollutants, mainly the gaseous pollutants affect COPD patients' health.

Difference in ambient-personal exposure to PM2.5 and its inflammatory effect in local residents in urban and peri-urban Beijing, China: results of the AIRLESS project.

Measurement of ambient fine particulate matter (PM2.5) is often used as a proxy of personal exposure in epidemiological studies. However, the difference between personal and ambient exposure, and whether it biases the estimates of health effects remain unknown. Based on an epidemiological study (AIRLESS) and simultaneously launched intensive monitoring campaigns (APHH), we quantified and compared the personal and ambient exposure to PM2.5 and the related health impact among residents in Beijing, China. In total, 123 urban and 128 peri-urban non-smoking participants were recruited from two well-established cohorts in Beijing. During winter 2016 and summer 2017, each participant was instructed to carry a validated personal air monitor (PAM) to measure PM2.5 concentration at high spatiotemporal resolution for seven consecutive days in each season. Multiple inflammatory biomarkers were measured, including exhaled NO, blood monocytes counts and C-reactive protein. Linear mixed-effect models were used for the associations between exposure and health outcomes with adjustment for confounders. The average level of daily personal exposure to PM2.5 was consistently lower than using corresponding ambient concentration, and the difference is greater during the winter. The personal to ambient (P/A) ratio of exposure to PM2.5 exhibited an exponentially declining trend, and showed larger variations when ambient PM2.5 levels < 25 µg m-3. Personal exposure to PM2.5 was significantly associated with the increase in respiratory and systemic inflammatory biomarkers; however, the associations were weaker or became insignificant when ambient concentrations were used. Exposure to ambient PM2.5 might not be a good proxy to estimate the health effect of exposure to personal PM2.5.

Using low-cost sensor technologies and advanced computational methods to improve dose estimations in health panel studies: results of the AIRLESS project.

BACKGROUND: Air pollution epidemiology has primarily relied on fixed outdoor air quality monitoring networks and static populations. METHODS: Taking advantage of recent advancements in sensor technologies and computational techniques, this paper presents a novel methodological approach that improves dose estimations of multiple air pollutants in large-scale health studies. We show the results of an intensive field campaign that measured personal exposures to gaseous pollutants and particulate matter of a health panel of 251 participants residing in urban and peri-urban Beijing with 60 personal air quality monitors (PAMs). Outdoor air pollution measurements were collected in monitoring stations close to the participants' residential addresses. Based on parameters collected with the PAMs, we developed an advanced computational model that automatically classified time-activity-location patterns of each individual during daily life at high spatial and temporal resolution. RESULTS: Applying this methodological approach in two established cohorts, we found substantial differences between doses estimated from outdoor and personal air quality measurements. The PAM measurements also significantly reduced the correlation between pollutant species often observed in static outdoor measurements, reducing confounding effects. CONCLUSIONS: Future work will utilise these improved dose estimations to investigate the underlying mechanisms of air pollution on cardio-pulmonary health outcomes using detailed medical biomarkers in a way that has not been possible before.

Characterising low-cost sensors in highly portable platforms to quantify personal exposure in diverse environments.

The inaccurate quantification of personal exposure to air pollution introduces error and bias in health estimations, severely limiting causal inference in epidemiological research worldwide. Rapid advancements in affordable, miniaturised air pollution sensor technologies offer the potential to address this limitation by capturing the high variability of personal exposure during daily life in large-scale studies with unprecedented spatial and temporal resolution. However, concerns remain regarding the suitability of novel sensing technologies for scientific and policy purposes. In this paper we characterise the performance of a portable personal air quality monitor (PAM) that integrates multiple miniaturised sensors for nitrogen oxides (NO x ), carbon monoxide (CO), ozone (O3) and particulate matter (PM) measurements along with temperature, relative humidity, acceleration, noise and GPS sensors. Overall, the air pollution sensors showed high reproducibility (mean R ¯ 2 = 0.93, min-max: 0.80-1.00) and excellent agreement with standard instrumentation (mean R ¯ 2 = 0.82, min-max: 0.54-0.99) in outdoor, indoor and commuting microenvironments across seasons and different geographical settings. An important outcome of this study is that the error of the PAM is significantly smaller than the error introduced when estimating personal exposure based on sparsely distributed outdoor fixed monitoring stations. Hence, novel sensing technologies such as the ones demonstrated here can revolutionise health studies by providing highly resolved reliable exposure metrics at a large scale to investigate the underlying mechanisms of the effects of air pollution on health.

Recruitment of patients with Chronic Obstructive Pulmonary Disease (COPD) from the Clinical Practice Research Datalink (CPRD) for research.

Databases of electronic health records (EHR) are not only a valuable source of data for health research but have also recently been used as a medium through which potential study participants can be screened, located and approached to take part in research. The aim was to assess whether it is feasible and practical to screen, locate and approach patients to take part in research through the Clinical Practice Research Datalink (CPRD). This is a cohort study in primary care. The CPRD anonymised EHR database was searched to screen patients with Chronic Obstructive Pulmonary Disease (COPD) to take part in a research study. The potential participants were contacted via their General Practitioner (GP) who confirmed their eligibility. Eighty two practices across Greater London were invited to the study. Twenty-six (31.7%) practices consented to participate resulting in a pre-screened list of 988 patients. Of these, 632 (63.7%) were confirmed as eligible following the GP review. Two hundred twenty seven (36%) response forms were received by the study team; 79 (34.8%) responded 'yes' (i.e., they wanted to be contacted by the research assistant for more information and to talk about enrolling in the study), and 148 (65.2%) declined participation. This study has shown that it is possible to use EHR databases such as CPRD to screen, locate and recruit participants for research. This method provides access to a cohort of patients while minimising input needed by GPs and allows researchers to examine healthcare usage and disease burden in more detail and in real-life settings.

Linking e-health records, patient-reported symptoms and environmental exposure data to characterise and model COPD exacerbations: protocol for the COPE study.

INTRODUCTION: Relationships between exacerbations of chronic obstructive pulmonary disease (COPD) and environmental factors such as temperature, humidity and air pollution are not well characterised, due in part to oversimplification in the assignment of exposure estimates to individuals and populations. New developments in miniature environmental sensors mean that patients can now carry a personal air quality monitor for long periods of time as they go about their daily lives. This creates the potential for capturing a direct link between individual activities, environmental exposures and the health of patients with COPD. Direct associations then have the potential to be scaled up to population levels and tested using advanced human exposure models linked to electronic health records. METHODS AND ANALYSIS: This study has 5 stages: (1) development and deployment of personal air monitors; (2) recruitment and monitoring of a cohort of 160 patients with COPD for up to 6 months with recruitment of participants through the Clinical Practice Research Datalink (CPRD); (3) statistical associations between personal exposure with COPD-related health outcomes; (4) validation of a time-activity exposure model and (5) development of a COPD prediction model for London. ETHICS AND DISSEMINATION: The Research Ethics Committee for Camden and Islington has provided ethical approval for the conduct of the study. Approval has also been granted by National Health Service (NHS) Research and Development and the Independent Scientific Advisory Committee. The results of the study will be disseminated through appropriate conference presentations and peer-reviewed journals.

The economic benefits of reducing the levels of nitrogen dioxide (NO2) near primary schools: The case of London.

Providing a healthy school environment is a priority for child health. The aim of this study is to develop a methodology that allows quantification of the potential economic benefit of reducing indoor exposure to nitrogen dioxide (NO2) in children attending primary schools. Using environmental and health data collected in primary schools in London, this study estimates that, on average, 82 asthma exacerbations per school can be averted each year by reducing outdoor NO2 concentrations. The study expands upon previous analyses in two ways: first it assesses the health benefits of reducing children's exposure to indoor NO2 while at school, second it considers the children's perspective in the economic evaluation. Using a willingness to pay approach, the study quantifies that the monetary benefits of reducing children's indoor NO2 exposure while at school would range between £2.5 k per school if a child's perspective based on child's budget is adopted up to £60 k if a parent's perspective is considered. This study highlights that designers, engineers, policymakers and stakeholders need to consider the reduction of outdoor pollution, and particularly NO2 levels, near primary schools as there may be substantial health and monetary benefits.

Global Associations between Air Pollutants and Chronic Obstructive Pulmonary Disease Hospitalizations. A Systematic Review.

RATIONALE: Exacerbations are key events in chronic obstructive pulmonary disease (COPD), affecting lung function decline and quality of life. The effect of exposure to different air pollutants on COPD exacerbations is not clear. OBJECTIVES: To carry out a systematic review, examining associations between air pollutants and hospital admissions for COPD exacerbations. METHODS: MEDLINE, Embase, BIOSIS, Science Citation Index, and the Air Pollution Epidemiology Database were searched for publications published between 1980 and September 2015. Inclusion criteria were focused on studies presenting solely a COPD outcome defined by hospital admissions and a measure of gaseous air pollutants and particle fractions. The association between each pollutant and COPD admissions was investigated in metaanalyses using random effects models. Analyses were stratified by geographical clusters for investigation of the consistency of the evidence worldwide. MEASUREMENTS AND MAIN RESULTS: Forty-six studies were included, and results for all the pollutants under investigation showed marginal positive associations; however, the number of included studies was small, the studies had high heterogeneity, and there was evidence of small-study bias. Geographical clustering of the effects of pollution on COPD hospital admissions was evident and reduced heterogeneity significantly. CONCLUSIONS: The most consistent association was between a 1-mg/m3 increase in carbon monoxide level and COPD-related admissions (odds ratio, 1.02; 95% confidence interval, 1.01-1.03). The heterogeneity was moderate, and there was a consistent positive association in both Europe and North America, although levels were clearly below World Health Organization guideline values. There is mixed evidence on the effects of environmental pollution on COPD exacerbations. Limitations of previous studies included the low spatiotemporal resolution of pollutants, inadequate control for confounding factors, and the use of aggregated health data that ignored personal characteristics. The need for more targeted exposure estimates in a large number of geographical locations is evident.