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Background: Evidence suggests that exposure to particulate matter with aerodynamic diameter less than 10 μm (PM10) is associated with reduced birth weight, but information is limited on the sources of PM10 and exposure misclassification from assigning exposures to place of residence at birth.Methods: Trimester and source-specific PM10 exposures (PM10 from road source, local non-road source, and total source) in pregnancy were estimated using dispersion models and a full maternal residential history for 12,020 births from the Avon longitudinal study of parents and children (ALSPAC) cohort in 1990-1992 in the Bristol area. Information on birth outcomes were obtained from birth records. Maternal sociodemographic and lifestyle factors were obtained from questionnaires. We used linear regression models for continuous outcomes (birth weight, head circumference (HC), and birth length (BL) and logistic regression models for binary outcomes (preterm birth (PTB), term low birth weight (TLBW) and small for gestational age (SGA)). Sensitivity analysis was performed using multiple imputation for missing covariate data.Results: After adjustment, interquartile range increases in source specific PM10 from traffic were associated with 17 to 18% increased odds of TLBW in all pregnancy periods. We also found odds of TLBW increased by 40% (OR: 1.40, 95%CI: 1.12, 1.75) and odds of SGA increased by 18% (OR: 1.18, 95%CI: 1.05, 1.32) per IQR (6.54 μg/m3) increase of total PM10 exposure in the third trimester.Conclusion: This study adds to evidence that maternal PM10 exposures affect birth weight, with particular concern in relation to exposures to PM10 from road transport sources; results for total PM10 suggest greatest effect in the third trimester. Effect size estimates relate to exposures in the 1990s and are higher than those for recent studies - this may relate to reduced exposure misclassification through use of full residential history information, changes in air pollution toxicity over time and/or residual confounding. [ABSTRACT FROM AUTHOR]

The Rapid Inquiry Facility 4.0 (RIF) is a new user-friendly and open-access tool, developed by the UK Small Area Health Statistics Unit (SAHSU), to facilitate environment public health tracking (EPHT) or surveillance (EPHS). The RIF is designed to help public health professionals and academics to rapidly perform exploratory investigations of health and environmental data at the small-area level (e.g. postcode or detailed census areas) in order to identify unusual signals, such as disease clusters and potential environmental hazards, whether localized (e.g. industrial site) or widespread (e.g. air and noise pollution). The RIF allows the use of advanced disease mapping methods, including Bayesian small-area smoothing and complex risk analysis functionalities, while accounting for confounders. The RIF could be particularly useful to monitor spatio-temporal trends in mortality and morbidity associated with cardiovascular diseases, cancers, diabetes and chronic lung diseases, or to conduct local or national studies on air pollution, flooding, low-magnetic fields or nuclear power plants. [ABSTRACT FROM AUTHOR]

Small area ecological studies are commonly used in epidemiology to assess the impact of area level risk factors on health outcomes when data are only available in an aggregated form. However, the resulting estimates are often biased due to unmeasured confounders, which typically are not available from the standard administrative registries used for these studies. Extra information on confounders can be provided through external data sets such as surveys or cohorts, where the data are available at the individual level rather than at the area level; however, such data typically lack the geographical coverage of administrative registries. We develop a framework of analysis which combines ecological and individual level data from different sources to provide an adjusted estimate of area level risk factors which is less biased. Our method (i) summarizes all available individual level confounders into an area level scalar variable, which we call ecological propensity score (EPS), (ii) implements a hierarchical structured approach to impute the values of EPS whenever they are missing, and (iii) includes the estimated and imputed EPS into the ecological regression linking the risk factors to the health outcome. Through a simulation study, we show that integrating individual level data into small area analyses via EPS is a promising method to reduce the bias intrinsic in ecological studies due to unmeasured confounders; we also apply the method to a real case study to evaluate the effect of air pollution on coronary heart disease hospital admissions in Greater London. [ABSTRACT FROM AUTHOR]

Introduction: Birth weight is a strong predictor of infant mortality, morbidity and later disease risk. Previous work from the 1980s indicated a shift in the UK towards heavier births; this descriptive analysis looks at more recent trends.Methods: Office for National Statistics (ONS) registration data on 17.2 million live, single births from 1986 to 2012 were investigated for temporal trends in mean birth weight, potential years of birth weight change and changes in the proportions of very low (<1500 g), low (<2500 g) and high (≥4000 g) birth weight. Analysis used multiple linear and logistic regression adjusted for maternal age, marital status, area-level deprivation and ethnicity. Additional analyses used the ONS NHS Numbers for Babies data set for 2006-2012, which has information on individual ethnicity and gestational age.Results: Over 27 years there was an increase in birth weight of 43 g (95% CI 42 to 44) in females and 44 g (95% CI 43 to 45) in males, driven by birth weight increases between 1986-1990 and 2007-2012. There was a concurrent decreased risk of having low birth weight but an 8% increased risk in males and 10% increased risk in females of having high birth weight. For 2006-2012 the birth weight increase was greater in preterm as compared with term births.Conclusions: Since 1986 the birth weight distribution of live, single births in England and Wales has shifted towards heavier births, partly explained by increases in maternal age and non-white ethnicity, as well as changes in deprivation levels. Other potential influences include increases in maternal obesity and reductions in smoking prevalence particularly following the introduction of legislation restricting smoking in public places in 2007. [ABSTRACT FROM AUTHOR]

Background: In England there are four national routinely collected data sets on births: Office for National Statistics (ONS) births based on birth registrations; Hospital Episode Statistics (HES) deliveries (mothers' information); HES births (babies' information); and NHS Numbers for Babies (NN4B) based on ONS births plus gestational age and ethnicity information. This study describes and compares these data, with the aim of recommending the most appropriate data set(s) for use in epidemiological research and surveillance.Methods: We assessed the completeness and quality of the data sets in relation to use in epidemiological research and surveillance and produced detailed descriptive statistics on common reproductive outcomes for each data set including temporal and spatial trends.Results: ONS births is a high quality complete data set but lacks interpretive and clinical information. HES deliveries showed good agreement with ONS births but HES births showed larger amounts of missing or unavailable data. Both HES data sets had improved quality from 2003 onwards, but showed some local spatial variability. NN4B showed excellent agreement with ONS and HES deliveries for the years available (2006-2010). Annual number of births increased by 17.6% comparing 2002 with 2010 (ONS births). Approximately 6% of births were of low birth weight (2.6% term low birth weight) and 0.5% were stillbirths.Conclusions: Routinely collected data on births provide a valuable resource for researchers. ONS and NN4B offer the most complete and accurate record of births. Where more detailed clinical information is required, HES deliveries offers a high quality data set that captures the majority of English births. [ABSTRACT FROM AUTHOR]

Road traffic gives rise to noise and air pollution exposures, both of which are associated with adverse health effects especially for cardiovascular disease, but mechanisms may differ. Understanding the variability in correlations between these pollutants is essential to understand better their separate and joint effects on human health. We explored associations between modelled noise and air pollutants using different spatial units and area characteristics in London in 2003–2010. We modelled annual average exposures to road traffic noise (L Aeq,24 h , L den , L Aeq,16 h , L night ) for ~ 190,000 postcode centroids in London using the UK Calculation of Road Traffic Noise (CRTN) method. We used a dispersion model (KCLurban) to model nitrogen dioxide, nitrogen oxide, ozone, total and the traffic-only component of particulate matter ≤ 2.5 μm and ≤ 10 μm. We analysed noise and air pollution correlations at the postcode level (~ 50 people), postcodes stratified by London Boroughs (~ 240,000 people), neighbourhoods (Lower layer Super Output Areas) (~ 1600 people), 1 km grid squares, air pollution tertiles, 50 m, 100 m and 200 m in distance from major roads and by deprivation tertiles. Across all London postcodes, we observed overall moderate correlations between modelled noise and air pollution that were stable over time (Spearman's rho range: | 0.34–0.55 |). Correlations, however, varied considerably depending on the spatial unit: largest ranges were seen in neighbourhoods and 1 km grid squares (both Spearman's rho range: | 0.01–0.87 |) and was less for Boroughs (Spearman's rho range: | 0.21–0.78 |). There was little difference in correlations between exposure tertiles, distance from road or deprivation tertiles. Associations between noise and air pollution at the relevant geographical unit of analysis need to be carefully considered in any epidemiological analysis, in particular in complex urban areas. Low correlations near roads, however, suggest that independent effects of road noise and traffic-related air pollution can be reliably determined within London. [ABSTRACT FROM AUTHOR]

Background Accidental non-fire-related (ANFR) carbon monoxide (CO) poisoning is a cause of fatalities and hospital admissions. This is the first study that describes the characteristics of ANFR CO hospital admissions in England. Methods Hospital Episode Statistics (HES) inpatient data for England between 2001 and 2010 were used. ANFR CO poisoning admissions were defined as any mention of ICD-10 code T58: toxic effect of CO andX47: accidental poisoning by gases or vapours, excluding ICD-10 codes potentially related to fires (X00-X09, T20-T32 and Y26). Results There were 2463 ANFR CO admissions over the 10-year period (annual rate: 0.49/100 000); these comprised just under half (48.7%) of all non-fire-related (accidental and non-accidental) CO admissions. There was seasonal variability, with more admissions in colderwinter months. Higher admission rates were observed in the north of England. Just over half (53%) of ANFR admissions were male, and the highest rates of ANFR admissions were in those aged >80 years. Conclusion The burden of ANFR CO poisoning is preventable. The results of this study suggest an appreciable burden of CO and highlight differences that may aid targeting of public health interventions. [ABSTRACT FROM AUTHOR]

Aims Road traffic noise has been associated with hypertension but evidence for the long-term effects on hospital admissions and mortality is limited. We examined the effects of long-term exposure to road traffic noise on hospital admissions and mortality in the general population. Methods The study population consisted of 8.6 million inhabitants of London, one of Europe's largest cities. We assessed small and results area-level associations of day- (7:00-22:59) and nighttime (23:00-06:59) road traffic noise with cardiovascular hospital admissions and all-cause and cardiovascular mortality in all adults (≥25 years) and elderly (≥75 years) through Poisson regression models. We adjusted models for age, sex, area-level socioeconomic deprivation, ethnicity, smoking, air pollution, and neighbourhood spatial structure. Median daytime exposure to road traffic noise was 55.6 dB. Daytime road traffic noise increased the risk of hospital admission for stroke with relative risk (RR) 1.05 [95% confidence interval (CI): 1.02-1.09] in adults, and 1.09 (95% CI: 1.04-1.14) in the elderly in areas .60 vs.,55 dB. Nighttime noise was associated with stroke admissions only among the elderly. Daytime noise was significantly associated with all-cause mortality in adults [RR 1.04 (95% CI: 1.00-1.07) in areas .60 vs.,55 dB]. Positive but non-significant associations were seen with mortality for cardiovascular and ischaemic heart disease, and stroke. Results were similar for the elderly. Conclusions Long-term exposure to road traffic noise was associated with small increased risks of all-cause mortality and cardiovascular mortality and morbidity in the general population, particularly for stroke in the elderly. [ABSTRACT FROM AUTHOR]

Background: Evidence for an association between traffic-related air pollution and allergic disease is inconsistent, possibly because the adverse effects may be limited to susceptible subgroups and these have not been identified. This study examined children in the Childhood Asthma Prevention Study (CAPS), potentially susceptible to air pollution effects because of a family history of asthma. Methods: We examined cross-sectional associations at age eight years between road density within 75 m and 50 m of home address weighted by road type (traffic density), as a proxy for traffic-related air pollution, on the following allergic and respiratory outcomes: skin prick tests (SPTs), total and specific serum IgE, pre- and post-bronchodilator lung function, airway hyperresponsiveness, exhaled NO, and reported asthma and rhinitis. Results: Weighted road density was positively associated with allergic sensitisation and allergic rhinitis. Adjusted relative risk (RR) for house dust mite (HDM) positive SPT was 1.25 (95% CI: 1.06–1.48), for detectable house dust mite-specific IgE was 1.19 (95% CI: 1.01–1.41) and for allergic rhinitis was 1.30 (95% CI: 1.03–1.63) per 100 m local road or 33.3 m motorway within 50 m of home. Associations were also seen with small decrements of peak and mid-expiratory flows and increased risk of asthma, current wheeze and rhinitis in atopic children. Conclusion: Associations between road density and allergic disease were found in a potentially susceptible subgroup of children at high risk of developing atopy and asthma. [ABSTRACT FROM AUTHOR]

Objectives: To investigate associations between respiratory disease and occupational exposures in a New Zealand urban population, the Wellington Respiratory Survey. Methods: Multiple regression analyses in a population sample of 1017 individuals aged 25 to 74 years with spirometry and questionnaire information, including a lifetime occupational history. Results: Chronic bronchitis symptoms were associated with self-reported exposure to hairdressing, paint manufacturing, insecticides, welding, detergents and with ALOHA Job Exposure Matrix-assessed gases/fumes exposure. The strongest association was for hairdressing (odds ratio 6.91; 95% confidence interval: 2.02 to 23.70). Cumulative exposure to mineral dust and gases/fumes was associated with higher FEV] % (forced expiratory volume in the first second of expiration) predicted. Analyses were limited by relatively small numbers of cases. Conclusions: Increased risks of objectively defined respiratory disease, which have been previously documented, were not seen. Nevertheless, the study suggested increased risk of respiratory symptoms with various occupational exposures as well as likely healthy worker effect. [ABSTRACT FROM AUTHOR]

Background: Association of childhood respiratory illness with traffic air pollution has been investigated largely in developed but not in developing countries, where pollution levels are often very high. Objectives: In this study we investigated associations between respiratory health and outdoor and indoor air pollution in schoolchildren 7-14 years of age in low socioeconomic status areas in the Niger Delta. Methods: A cross-sectional survey was carried out among 1,397 schoolchildren. Exposure to home outdoor and indoor air pollution was assessed by self-report questionnaire. School air pollution exposures were assessed using traffic counts, distance of schools to major streets, and particulate matter and carbon monoxide measurements, combined using principal components analysis. Hierarchical logistic regression was used to examine associations with reported respiratory health, adjusting for potential confounders. Results: Traffic disturbance at home (i.e., traffic noise and/or fumes evident inside the home vs. none) was associated with wheeze [odds ratio (OR) = 2.16; 95% confidence interval (CI), 1.28-3.64], night cough (OR = 1.37; 95% CI, 1.03-1.82), phlegm (OR = 1.49; 95% CI, 1.09-2.04), and nose symptoms (OR = 1.40; 95% CI, 1.03-1.90), whereas school exposure to a component variable indicating exposure to fine particles was associated with increased phlegm (OR = 1.38; 95% CI, 1.09-1.75). Nonsignificant positive associations were found between cooking with wood/coal (OR = 2.99; 95% CI, 0.88-10.18) or kerosene (OR = 2.83; 95% CI, 0.85-9.44) and phlegm compared with cooking with gas. Conclusion: Traffic pollution is associated with respiratory symptoms in schoolchildren in a deprived area of western Africa. Associations may have been underestimated because of nondifferential misclassification resulting from limitations in exposure measurement. [ABSTRACT FROM AUTHOR]

Aim: To identify age- and gender-specific prevalence rates for physician-diagnosed asthma, allergic rhinitis (AR) and eczema across a whole lifespan. Method: Presentations of asthma, allergic rhinitis and eczema were identified in individuals aged 0 to 65 who consulted their general practitioner at least once in 1998-99 from a population sample of 266,733 in Scotland, and in 1991-95 for asthma and allergic rhinitis in 6,836,063 person years at risk in England and Wales. Results: In both sexes asthma presentations peak at 4-6 years whilst eczema peaks in infancy. A second asthma peak occurs during adolescence, earlier in females, at a time when a female predominance for all three atopic diseases is established. Female predominance of eczema presentations are limited to the reproductive period of 15-49 years. Conclusion: The patterns of presentations for asthma, allergic rhinitis and eczema by age and gender suggest important gender-specific differences in disease predisposition and diagnosis. [ABSTRACT FROM AUTHOR]

This article presents information on a study which determines the quantity and quality of medical events in COPD and asthma patients from the general population. COPD produces a substantial and growing disease burden worldwide. Most COPD patients are aging individuals, often with several comorbidities and multiple drug treatments. Similarly, asthma is also associated with a substantial and growing disease burden worldwide. Asthma is the most common chronic disease in Western children, and asthma diagnosis can happen at all ages, including the elderly. It is recognized that the epidemiology of both conditions, although asthma slightly better than COPD, is still behind achievements of cardiovascular or cancer epidemiology.

Health impact assessment (HIA) aims to make the health consequences of decisions explicit. Decision‐makers need to know that the conclusions of HIA are robust. Quantified estimates of potential health impacts may be more influential but there are a number of concerns. First, not everything that can be quantified is important. Second, not everything that is being quantified at present should be, if this cannot be done robustly. Finally, not everything that is important can be quantified: rigorous qualitative HIA will still be needed for a thorough assessment. This paper presents the first published attempt to provide practical guidance on what is required to perform robust, quantitative HIA. Initial steps include profiling the affected populations, obtaining evidence for postulated impacts, and determining how differences in subgroups' exposures and susceptibilities affect impacts. Using epidemiological evidence for HIA is different from carrying out a new study. Key steps in quantifying impacts are mapping the causal pathway, selecting appropriate outcome measures and selecting or developing a statistical model. Evidence from different sources is needed. For many health impacts, evidence of an effect may be scarce and estimates of the size and nature of the relationship may be inadequate. Assumptions and uncertainties must therefore be explicit. Modelled data can sometimes be tested against empirical data but sensitivity analyses are crucial. When scientific problems occur, discontinuing the study is not an option, as HIA is usually intended to inform real decisions. Both qualitative and quantitative elements of HIA must be performed robustly to be of value. [ABSTRACT FROM PUBLISHER]

Background Road traffic noise has been linked to increased risk of stroke, for which hypertension and carotid intima-media thickness (cIMT) are risk factors. A link between traffic noise and hypertension has been established, but there are few studies on blood pressure and no studies on cIMT. Objectives To examine cross-sectional associations for long-term exposure to night-time noise with cIMT, systolic blood pressure (SBP), diastolic blood pressure (DBP) and hypertension. Methods The study population consisted of 2592 adults from the Whitehall II and SABRE cohort studies living within Greater London who had cIMT, SBP and DBP measured. Exposure to night-time road traffic noise (A-weighted dB, referred to as dBA) was estimated at each participant's residential postcode centroid. Results Mean night-time road noise levels were 52 dBA (SD = 4). In the pooled analysis adjusted for cohort, sex, age, ethnicity, marital status, smoking, area-level deprivation and NOx there was a 9.1 μm (95% CI: − 7.1, 25.2) increase in cIMT in association with 10 dBA increase in night-time noise. Analyses by noise categories of 55–60 dBA (16.2 μm, 95% CI: − 8.7, 41.2), and > 60 dBA (21.2 μm, 95% CI: − 2.5, 44.9) vs. < 55 dBA were also positive but non-significant, expect among those not using antihypertensive medication and exposed to > 60 dBA vs. < 55 dBA (32.6 μm, 95% CI: 6.2, 59.0). Associations for SBP, DPB and hypertension were close to null. Conclusions After adjustments, including for air pollution, the association between night-time road traffic noise and cIMT was only observed among non-medication users but associations with blood pressure and hypertension were largely null. [ABSTRACT FROM AUTHOR]

Aircraft noise causes annoyance and sleep disturbance and there is some evidence of associations between long-term exposures and cardiovascular disease (CVD). We investigated short-term associations between previous day aircraft noise and cardiovascular events in a population of 6.3 million residing near Heathrow Airport using a case-crossover design and exposure data for different times of day and night. We included all recorded hospitalisations (n = 442,442) and deaths (n = 49,443) in 2014–2018 due to CVD. Conditional logistic regression was used to estimate the ORs and adjusted for NO 2 concentration, temperature, and holidays. We estimated an increase in risk for 10 dB increment in noise during the previous evening (L eve OR = 1.007, 95% CI 0.999–1.015), particularly from 22:00–23:00 h (OR = 1.007, 95% CI 1.000–1.013), and the early morning hours 04:30–06:00 h (OR = 1.012, 95% CI 1.002–1.021) for all CVD admissions, but no significant associations with day-time noise. There was effect modification by age-sex, ethnicity, deprivation, and season, and some suggestion that high noise variability at night was associated with higher risks. Our findings are consistent with proposed mechanisms for short-term impacts of aircraft noise at night on CVD from experimental studies, including sleep disturbance, increases in blood pressure and stress hormone levels and impaired endothelial function. [ABSTRACT FROM AUTHOR]

Introduction Exposure to road traffic noise may increase blood pressure and heart rate. It is unclear to what extent exposure to air pollution may influence this relationship. We investigated associations between noise, blood pressure and heart rate, with harmonized data from three European cohorts, while taking into account exposure to air pollution. Methods Road traffic noise exposure was assessed using a European noise model based on the Common Noise Assessment Methods in Europe framework (CNOSSOS-EU). Exposure to air pollution was estimated using a European-wide land use regression model. Blood pressure and heart rate were obtained by trained clinical professionals. Pooled cross-sectional analyses of harmonized data were conducted at the individual level and with random-effects meta-analyses. Results We analyzed data from 88,336 participants, across the three participating cohorts (mean age 47.0 (±13.9) years). Each 10 dB(A) increase in noise was associated with a 0.93 (95% CI 0.76;1.11) bpm increase in heart rate, but with a decrease in blood pressure of 0.01 (95% CI −0.24;0.23) mmHg for systolic and 0.38 (95% CI −0.53; −0.24) mmHg for diastolic blood pressure. Adjustments for PM 10 or NO 2 attenuated the associations, but remained significant for DBP and HR. Results for BP differed by cohort, with negative associations with noise in LifeLines, no significant associations in EPIC-Oxford, and positive associations with noise >60 dB(A) in HUNT3. Conclusions Our study suggests that road traffic noise may be related to increased heart rate. No consistent evidence for a relation between noise and blood pressure was found. [ABSTRACT FROM AUTHOR]

Summary Genetic epidemiology is a rapidly expanding research field, but the implications of findings from such studies for individual or population health are unclear. The use of molecular genetic screening currently has some legitimacy in certain monogenic conditions, but no established value with respect to common complex diseases. Personalised medical care based on molecular genetic testing is also as yet undeveloped for common diseases. Genetic epidemiology can contribute to establishing the causal nature of environmentally modifiable risk factors, throught the application of mendelian randomisation approaches and thus contribute to appropriate preventive strategies. Technological and other advances will allow the potential of genetic epidemiology to be revealed over the next few years, and the establishment of large population-based resources for such studies (biobanks) should contribute to this endeavour. [ABSTRACT FROM AUTHOR]

Unintentional non-fire related (UNFR) carbon monoxide (CO) poisoning is a preventable cause of morbidity and mortality. Epidemiological data on UNFR CO poisoning can help monitor changes in the magnitude of this burden, particularly through comparisons of multiple countries, and to identify vulnerable sub-groups of the population which may be more at risk. Here, we collected data on age- and sex- specific number of hospital admissions with a primary diagnosis of UNFR CO poisoning in England (2002-2016), aggregated to small areas, alongside area-level characteristics (i.e. deprivation, rurality and ethnicity). We analysed temporal trends using piecewise log-linear models and compared them to analogous data obtained for Canada, France, Spain and the US. We estimated age-standardized rates per 100,000 inhabitants by area-level characteristics using the WHO standard population (2000-2025). We then fitted the Besag York Mollie (BYM) model, a Bayesian hierarchical spatial model, to assess the independent effect of each area-level characteristic on the standardized risk of hospitalization. Temporal trends showed significant decreases after 2010. Decreasing trends were also observed across all countries studied, yet France had a 5-fold higher risk. Based on 3399 UNFR CO poisoning hospitalizations, we found an increased risk in areas classified as rural (0.69, 95% CrI: 0.67; 0.80), highly deprived (1.77, 95% CrI: 1.66; 2.10) or with the largest proportion of Asian (1.15, 95% CrI: 1.03; 1.49) or Black population (1.35, 95% CrI: 1.20; 1.80). Our multivariate approach provides strong evidence for the identification of vulnerable populations which can inform prevention policies and targeted interventions. [ABSTRACT FROM AUTHOR]