Residential exposure to traffic noise and risk of incident atrial fibrillation: A cohort study

BackgroundStudies have found long-term exposure to traffic noise to be associated with higher risk for hypertension, ischemic heart disease and stroke. We aimed to investigate the novel hypothesis that traffic noise increases the risk of atrial fibrillation (A-fib).MethodsIn a population-based cohort of 57,053 people aged 50–64 years at enrolment in 1993–1997, we identified 2692 cases of first-ever hospital admission of A-fib from enrolment to end of follow-up in 2011 using a nationwide registry. The mean follow-up time was 14.7 years. Present and historical residential addresses were identified for all cohort members from 1987 to 2011. For all addresses, exposure to road traffic and railway noise was estimated using the Nordic prediction method and exposure to air pollution was estimated using a validated dispersion model. We used Cox proportional hazard model for the analyses with adjustment for lifestyle, socioeconomic position and air pollution.ResultsA 10 dB higher 5-year time-weighted mean exposure to road traffic noise was associated with a 6% higher risk of A-fib (incidence rate ratio (IRR): 1.06; 95% confidence interval (95% CI): 1.00–1.12) in models adjusted for factors related to lifestyle and socioeconomic position. The association followed a monotonic exposure–response relationship. In analyses with adjustment for air pollution, NO_x or NO₂, there were no statistically significant associations between exposure to road traffic noise and risk of A-fib; IRR: 1.04; (95% CI: 0.96–1.11) and IRR: 1.01; (95% CI: 0.94–1.09), respectively. Exposure to railway noise was not associated with A-fib.ConclusionExposure to residential road traffic noise may be associated with higher risk of A-fib, though associations were difficult to separate from exposure to air pollution.     

Exposure to long-term air pollution and road traffic noise in relation to cholesterol: A cross-sectional study

BackgroundExposure to traffic noise and air pollution have both been associated with cardiovascular disease, though the mechanisms behind are not yet clear.ObjectivesWe aimed to investigate whether the two exposures were associated with levels of cholesterol in a cross-sectional design.MethodsIn 1993–1997, 39,863 participants aged 50–64 year and living in the Greater Copenhagen area were enrolled in a population-based cohort study. For each participant, non-fasting total cholesterol was determined in whole blood samples on the day of enrolment. Residential addresses 5-years preceding enrolment were identified in a national register and road traffic noise (L_den) were modeled for all addresses. For air pollution, nitrogen dioxide (NO₂) was modeled at all addresses using a dispersion model and PM_2.5 was modeled at all enrolment addresses using a land-use regression model. Analyses were done using linear regression with adjustment for potential confounders as well as mutual adjustment for the three exposures.ResultsBaseline residential exposure to the interquartile range of road traffic noise, NO₂ and PM_2.5 was associated with a 0.58 mg/dl (95% confidence interval: − 0.09; 1.25), a 0.68 mg/dl (0.22; 1.16) and a 0.78 mg/dl (0.22; 1.34) higher level of total cholesterol in single pollutant models, respectively. In two pollutant models with adjustment for noise in air pollution models and vice versa, the association between air pollution and cholesterol remained for both air pollution variables (NO₂: 0.72 (0.11; 1.34); PM_2.5: 0.70 (0.12; 1.28) mg/dl), whereas there was no association for noise (− 0.08 mg/dl). In three-pollutant models (NO₂, PM_2.5 and road traffic noise), estimates for NO₂ and PM_2.5 were slightly diminished (NO₂: 0.58 (− 0.05; 1.22); PM_2.5: 0.57 (− 0.02; 1.17) mg/dl).ConclusionsAir pollution and possibly also road traffic noise may be associated with slightly higher levels of cholesterol, though associations for the two exposures were difficult to separate.     

Increased catecholamine levels in urine in subjects exposed to road traffic noise: the role of stress hormones in noise research

The nocturnal excretion of catecholamines in urine was studied in 30-45-year-old women whose bedroom and/or living room were facing streets of varying traffic volume. The traffic volume of the streets was used as an indicator of noise exposure; adrenaline and noradrenaline concentrations were assessed as indicators of the outcome of the physiological stress. Significant associations between traffic volume and noradrenaline concentrations in urine were found with regard to the exposure of the bedroom (not the living room), indicating a higher chronic physiological arousal in noise-exposed subjects as compared to less exposed. Subjective measures of disturbance due to traffic noise were positively correlated with the noradrenaline level. However, this was only found in subjects where closing the window could not reduce the perceived disturbance, which points to the effectiveness of individual coping mechanisms. Stress hormones are useful indicators to study associations, mechanisms, and interactions between noise, health outcomes, and effect modifiers in epidemiological noise research.     

Road traffic noise, sensitivity, annoyance and self-reported health--a structural equation model exercise

The proposed effect of road traffic noise on hypertension and ischemic heart disease finds mixed empirical support. One problem with many studies is that the directions of the causal relationships are not identified. This is often the case when cross-sectional data and multivariate regression models are utilised. The aim of the study was to explore the relationship between road traffic noise and health. More specifically the relationships between noise complaints, noise sensitivity and subjectively reported hypertension and heart problems were investigated. 1842 respondents in Oslo, Norway were interviewed about their experience of the local environment and their subjective health complaints. The interviews were conducted as part of two surveys. Individual measures of air pollution (NO(2)) and noise (Lden) were calculated. The data were analysed using Structural Equation Models. Only sensitivity to noise is related to hypertension and chest pain. No relationships between noise exposure and health complaints were identified. Rather than noise being the causal agent leading to health problems, the results suggest that the noise-health relationships in these studies may be spurious. It is conceivable that individual vulnerability is reflected both in ill health and in being sensitive to noise. The benefit of including more contextual variables in a model of noise-health relationships is supported.     

Urban road-traffic noise and blood pressure and heart rate in preschool children

Night time noise exposure has very rarely been used in previous studies on the relationship between community noise and children's blood pressure, although children spend a larger part of their night time sleeping at home than adults. For this reason, we focused on night time noise exposure at children's residences and daytime noise at kindergartens. The aim of this study was to investigate the effects of urban road-traffic noise on children's blood pressure and heart rate. A cross-sectional study was performed on 328 preschool children (174 boys and 154 girls) aged 3-7 years, who attended 10 public kindergartens in Belgrade. Equivalent noise levels (Leq) were measured during night in front of children's residences and during day in front of kindergartens. A residence was regarded noisy if Leq exceeded 45 dB (A) during night and quiet if the Leq was < or =45 dB (A). Noisy and quiet kindergartens were those with daily Leq>60 dB (A) and < or =60 dB (A), respectively. Children's blood pressure was measured with mercury sphygmomanometer. Heart rate was counted by radial artery palpitation for 1 min. The prevalence of children with hypertensive values of blood pressure was 3.96% (13 children, including 8 boys and 5 girls) with higher prevalence in children from noisy residences (5.70%), compared to children from quiet residences (1.48%). The difference was borderline significant (p=0.054). Systolic pressure was significantly higher (5 mm Hg on average) among children from noisy residences and kindergartens, compared to children from both quiet environments (p<0.01). Heart rate was significantly higher (2 beats/min on average) in children from noisy residences, compared to children from quiet residences (p<0.05). Multiple regression, after allowing for possible confounders, showed a significant correlation between noise exposure and children's systolic pressure (B=1.056; p=0.009).     

Neighbour noise annoyance and psychiatric diseases

Data from a national sample survey (interview data) were used to test for possible correlations between different measures of noise annoyance and measures of psychiatric problems/diseases. The test was accomplished by crosstab programme for correlation between variables. The main variables were noise annoyance from different sources and psychiatric problems/diseases. Age and sex were used as covariables. A correlation was shown between neighbour noise annoyance and various indicators of self-reported psychiatric problems/diseases in the middle age groups, more prevalent and stronger for women than for men. The results, in accordance with research in other countries, indicate that people with psychiatric problems/diseases are more sensitive towards neighbour noise than the rest of the population. The same survey and the same method showed only low or no correlation between other sources of noise annoyance and psychiatric diseases.     

Parameters of well-being and subjective health and their relationship with residential traffic noise exposure--a representative evaluation in Switzerland

In the present paper, the associations between residential traffic noise exposure from the noise sources--road, rail and aircraft--and self-reported indicators of health and well-being are investigated in a representative sample of the Swiss population. The study is based on record linkage of the Swiss GIS Noise Database (SonBase) and the Swiss Household Panel (SHP), a large panel survey with more than 10,000 respondents all over the country. A range of exposure-effect relationships of noise exposure and parameters of health and well-being such as self-reported health status, satisfaction with health, sleep disturbances, the intensity of the wish to move from the current residence as well as the awareness of "noise problems" at the place of living were investigated. Both unadjusted as well as models that controlled for age, sex, socioeconomic status, degree of urbanization at the place of residence, and personal living conditions were developed. A contribution of residential noise exposure as regards subjective estimates of health cannot been ruled out, but must be put into perspective as the effects of exposure measures were of rather small magnitude, especially compared to well-established determinants of health. Against the background of the explanatory power of classic health predictors, the present analyses allow one to gage the contribution of residential noise exposure on subjective health outcomes from a more general, integral point of view.     

Associations between maternal exposure to air pollution and traffic noise and newborn's size at birth: A cohort study

BackgroundMaternal exposure to air pollution and traffic noise has been suggested to impair fetal growth, but studies have reported inconsistent findings.ObjectiveTo investigate associations between residential air pollution and traffic noise during pregnancy and newborn's size at birth.MethodsFrom a national birth cohort we identified 75,166 live-born singletons born at term with information on the children's size at birth. Residential address history from conception until birth was collected and air pollution (NO₂ and NO_x) and road traffic noise was modeled at all addresses. Associations between exposures and indicators of newborn's size at birth: birth weight, placental weight and head and abdominal circumference were analyzed by linear and logistic regression, and adjusted for potential confounders.ResultsIn mutually adjusted models we found a 10 μg/m³ higher time-weighted mean exposure to NO₂ during pregnancy to be associated with a 0.35 mm smaller head circumference (95% confidence interval (CI): 95% CI: − 0.57; − 0.12); a 0.50 mm smaller abdominal circumference (95% CI: − 0.80; − 0.20) and a 5.02 g higher placental weight (95% CI: 2.93; 7.11). No associations were found between air pollution and birth weight. Exposure to residential road traffic noise was weakly associated with reduced head circumference, whereas none of the other newborn's size indicators were associated with noise, neither before nor after adjustment for air pollution.ConclusionsThis study indicates that air pollution may result in a small reduction in offspring's birth head and abdominal circumference, but not birth weight, whereas traffic noise seems not to affect newborn's size at birth.     

Road-traffic noise and factors influencing noise annoyance in an urban population

Noise annoyance is influenced by sound-related factors: type of noise, noise level and frequency, and person-related factors—physiological, psychological, and social factors. Prior to implementation of the Directive 2002/49/EC of the European Parliament and of the Council in Serbia, there was a need for the first comprehensive study on noise annoyance in Serbian urban population. The aim of this study was to determine principal factors for high noise annoyance in an adult urban population and to assess their predictive value. A cross-sectional study was performed on 3097 adult residents of a downtown municipality in Belgrade (1217 men and 1880 women), aged 18–96 years. Equivalent noise levels [Leq (dBA)] were measured during day, evening and night in all streets of the municipality. Noise annoyance was estimated using self-reported annoyance scale. Noise annoyance showed strong correlation with noise levels, personal characteristics and some housing conditions. Dose–response relationship was found between the percentage of highly annoyed residents and Lden. Logistic regression model identified increased risk for a high level of noise annoyance with regard to: orientation of living room/bedroom toward the street (Odds Ratio = 2.60; 95% Confidence Interval = 2.04–3.31), duration of stay at apartment during the day [OR = 1.04, 95%CI = 1.02–1.06 (per hour)], noise sensitivity [OR = 1.04, 95%CI = 1.03–1.04 (per scale unit)], and nighttime road-traffic noise level [OR = 1.03, 95%CI = 1.02–1.04 (per decibel)].     

Epidemiological research on non-auditory effects of occupational noise exposure

Epidemiological studies about non-auditory effects of noise have been reviewed. For methodological reasons, only occupational studies are compared with each other. Most studies were directed, as before, to the relation between noise and arterial blood pressure. In about half of the studies, a positive relation could be demonstrated, in the other studies, however, no relation was found. Methodological comments are given. Definite conclusions are still not possible. In three investigations the effects of noise on pregnancy were studied. A negative effect on birth weight is presented in one of these studies. More research is needed. Task components probably interact with noise exposure producing annoyance and stress symptoms. The use of epidemiological methods in research of non-auditory effects of noise is still very limited.     

Modeling of road traffic noise and estimated human exposure in Fulton County, Georgia, USA

Environmental noise is a major source of public complaints. Noise in the community causes physical and socio-economic effects and has been shown to be related to adverse health impacts. Noise, however, has not been actively researched in the United States compared with the European Union countries in recent years. In this research, we aimed at modeling road traffic noise and analyzing human exposure in Fulton County, Georgia, United States. We modeled road traffic noise levels using the United States Department of Transportation Federal Highway Administration Traffic Noise Model implemented in SoundPLAN?. After analyzing noise levels with raster, vector and fa?ade maps, we estimated human exposure to high noise levels. Accurate digital elevation models and building heights were derived from Light Detection And Ranging survey datasets and building footprint boundaries. Traffic datasets were collected from the Georgia Department of Transportation and the Atlanta Regional Commission. Noise level simulation was performed with 62 computers in a distributed computing environment. Finally, the noise-exposed population was calculated using geographic information system techniques. Results show that 48% of the total county population [N=870,166 residents] is potentially exposed to 55 dB(A) or higher noise levels during daytime. About 9% of the population is potentially exposed to 67 dB(A) or higher noises. At nighttime, 32% of the population is expected to be exposed to noise levels higher than 50 dB(A). This research shows that large-scale traffic noise estimation is possible with the help of various organizations. We believe that this research is a significant stepping stone for analyzing community health associated with noise exposures in the United States.     

Disturbance caused by various fluctuating single noises and combined community noises

Three experiments were conducted to investigate factors influencing the (rated) disturbance caused by various noises to subjects when they were reading: (a) comparison of disturbances from various noises at 70 dB(A) L_eq; (b) comparison of exposure-response relationships between road traffic, aircraft, and train noises; and (c) the effect of road traffic background noise on the total disturbance caused by combined noise (aircraft or train noise combined with road traffic noise). From the three experiments, the following conclusions were drawn: (1) High-level components such as peak level contributed to the disturbance, since the noise was more disturbing with the increase of peak level. (2) Although the general pattern of the exposure-response relationships for aircraft and train noises was similar, the disturbance due to road traffic noise increased with L_eq level more rapidly than for aircraft and train noise. Considering that the peak level of aircraft or train noise was always higher than that of road traffic noise at equal L_eq levels, the contribution of the high-level components to the disturbance appeared to be level-dependent. (3) The background noise level did not affect the total disturbance. Because the high-level components of combined noises were almost the same, this finding was consistent with conclusions drawn in (1) and (2).     

Estimating human exposure to transport noise in central Dublin, Ireland

This paper reports on research conducted to determine estimates of the extent of environmental noise exposure from road transport on residents and workers in central Dublin, Ireland. The Harmonoise calculation method is used to calculate noise values for the study area while a Geographical Information System (GIS) is utilised as a platform upon which levels of noise exposure are estimated. Residential exposure is determined for L(den) and L(night) while worker exposure is determined for L(den). In order to analyse the potential of traffic management as a noise abatement measure, traffic was redirected from the main residential areas to alternative road links and the revised exposure levels were determined. The results show that the extent of noise exposure in Dublin is considerable, and in relative terms, it is worse for the night-time period. In addition, the results suggest also that traffic management measures have the potential to lead to significant reductions in the level of noise exposure provided that careful consideration is given to the impact of traffic flows on residential populations.     

Modeling of road traffic noise and estimated human exposure in Fulton County,Georgia, USA

Environmental noise is a major source of public complaints. Noise in the community causes physical and socio-economic effects and has been shown to be related to adverse health impacts. Noise, however, has not been actively researched in the United States compared with the European Union countries in recent years. In this research, we aimed at modeling road traffic noise and analyzing human exposure in Fulton County, Georgia, United States. We modeled road traffic noise levels using the United States Department of Transportation Federal Highway Administration Traffic Noise Model implemented in SoundPLAN®. After analyzing noise levels with raster, vector and façade maps, we estimated human exposure to high noise levels. Accurate digital elevation models and building heights were derived from Light Detection And Ranging survey datasets and building footprint boundaries. Traffic datasets were collected from the Georgia Department of Transportation and the Atlanta Regional Commission. Noise level simulation was performed with 62 computers in a distributed computing environment. Finally, the noise-exposed population was calculated using geographic information system techniques. Results show that 48% of the total county population [N = 870,166 residents] is potentially exposed to 55 dB(A) or higher noise levels during daytime. About 9% of the population is potentially exposed to 67 dB(A) or higher noises. At nighttime, 32% of the population is expected to be exposed to noise levels higher than 50 dB(A). This research shows that large-scale traffic noise estimation is possible with the help of various organizations. We believe that this research is a significant stepping stone for analyzing community health associated with noise exposures in the United States.     

Using city-wide mobile noise assessments to estimate bicycle trip annual exposure to Black Carbon

Several studies have shown that a significant amount of daily air pollution exposure, in particular Black Carbon (BC), is inhaled during bicycle trips. Previously, the instantaneous BC exposure of cyclists was modeled as the sum of a background concentration and a local traffic related component based on a local assessment of traffic noise. We present a fast and low cost methodology to achieve a city-wide assessment of yearly average BC exposure of cyclists along their trips, based on a city-wide mobile noise sensing campaign.The methodology requires participatory sensing measurements of noise, partially combined with BC and/or other air pollutants sensitive to local traffic variations. The combined measurements cover the spatial and meteorological variability and provide the data for an instantaneous exposure model. The mobile noise-only measurements map the full city; and yearly meteorology statistics are used to extrapolate the instantaneous exposure model to a yearly average map of in-traffic air pollution exposure. Less than four passages at each segment along the network with mobile noise equipment are necessary to reach a standard error of 500 ng/m³ for the yearly average BC exposure.A strong seasonal effect due to the BC background concentration is detected. The background contributes only 25% to the total trip exposure during spring and summer. During winter the background component increases to 50–60%. Engine related traffic noise along the bicyclist's route is a valid indicator of the BC exposure along the route, independent of the seasonal background. Low exposure route selection results in an exposure reduction of 35% in winter and 60% in summer, sensitive to the weather conditions, specific trip attributes and the available alternatives.The methodology is relevant for further research into the local effects of air pollution on health. Mobile noise mapping adds local traffic data including traffic dynamics into the air pollution exposure assessments. Local policy makers and urban planners can use the results to support the implementation of low exposure infrastructure, create awareness through route planners and achieve behavioral changes toward active travel modes.     

A multi-objective design optimisation of eco-friendly aircraft: the impact of noise fees on airplanes sustainable development

The current work deals with multi-objective optimisations including financial merit factors in the multi-disciplinary conceptual design of a commercial aircraft with a specific focus on noise social cost. The results of optimisations using financial and performance-oriented objective functions have been analysed and combined in a multi-objective optimisation problem using a three-dimensional objective vector. The main novelty of the present work is the analysis of social cost noise fees effectiveness integrated in financial models embracing a wider group of stakeholders’ interests. The foundations of this research lie on the air traffic increase envisaged in the next decades and the contextual growth of the urban areas nearby airport facilities. This scenario requires the aeronautical industry to handle the environment challenge taking into account all the social and economic effects. Indeed, the consolidated technology has approached a saturation point, therefore breakthrough concepts and configurations are mandatory. This matter is addressed as a highly multi-disciplinary problem within conceptual design framework. The financial model proposed is shown to highlight the need of appropriate noise fees as instruments to push all stakeholders towards a technology radical renewal and encourage the aeronautical industry towards a shared strategy in the development of an eco-friendly commercial aviation system.     

Noise Impact and Improvement on Indoors Acoustic Comfort for the Building Adjacent to Heavy Traffic Road

A good acoustic environment is absolutely essential to maintaining a high level satisfaction and moral health among residents. Noise and other boresome sounds come from both in- door and outdoor sources. For the residential buildings adjacent to heavy traffic roads, outdoors traffic noise is the main source that affects indoor acoustic quality and health. Ventilation and outdoor noise prevention become a pair of contradictions for the residents in China nowadays for those buildings adjacent to heavy traffic roads. It is investigated that traffic noise emission is mainly con- stituted by the motors of trucks, buses and motorcycles as well as brake. In this paper, two methods of traffic noise reduction on the indoor sound environment and comfort are carried out to study and compare the residential buildings adjacent to heavy traffic roadway in a city. One is to install noise barriers on the two sides of the roadway, which consist of sound-proof glass and plas- tic materials. The effect of sound-insulation of this method is heavily dependent on the relative distance between the noise bar- rier and indoors. A reduction of sound with an average pressure level of 2–15dB is achieved on the places behind and under the noise barrier. However, for the equivalent of noise barrier height, the noise reduction effect is little. As for the places of higher than the noise barrier, the traffic noise will be even strengthened by 3–7dB. Noise increment can be seen at the points of distance farther than 15m and height more than noise barrier; the noise reduction effect is not satisfactory or even worsened. In addition, not every location is appropriate to install the noise barrier along the heavy traffic roads. The other method of noise reduction for the buildings adjacent to heavy traffic is to install the airproof and soundproof windows, which is the conversion from natural venti- lation to mechanical ventilation. A reduction of sound with an average pressure level of 5dB to 17dB can be achieved compared with common glass windows, if adopting sound proof glass win- dows. These two methods are helpful to isolate high frequency noise but not for low frequency noise. For those frequency noises, installing thick and cotton curtain and porous carpet can only decrease 2.4–4.5dB, which hardly contributes to indoor sound comfort, so further study is demanded to cut down traffic noise, especially to cut down the low frequency noise.     

Analysis of transportation carbon emissions and its potential for reduction in China

The transportation industry is an essential sector for carbon emissions mitigation.This paper firstly used the LMDI(Logarithmic Mean Divisia Index)decomposition method to establish factors decomposition model on China’s transportation carbon emission.Then,a quantitative analysis was performed to study the factors influencing China’s transportation carbon emissions from 1991 to 2008,which are identified as transportation energy efficiency,transportation structure and transportation development.The results showed that:(1)The impact of transportation development on transportation carbon emissions showed pulling function.Its contribution value to carbon emissions remained at high growth since 1991 and showed an exponential growth trend.(2)The impact of transportation structure on transportation carbon emissions showed promoting function in general,but its role in promoting carbon emissions decreased year by year.And with the continuous optimization of transportation structure,the promoting effect decreased gradually and showed the inversed"U"trend.(3)The impact of transportation energy efficiency on transportation carbon emissions showed a function of inhibition before pulling.In order to predict the potential of carbon emission reduction,three scenarios were set.Analysis of the scenarios showed that if greater intensity emission reduction measures are taken,the carbon emissions will reduce by 31.01 million tons by 2015 and by 48.81 million tons by 2020.     

Annoyance due to aircraft noise has increased over the years—Results of the HYENA study

In the HYENA study (HYpertension and Exposure to Noise near Airports) noise annoyances due to aircraft and road traffic noise were assessed in subjects that lived in the vicinity of 6 major European airports using the 11-point ICBEN scale (International Commission on Biological Effects of Noise). A distinction was made between the annoyance during the day and during the night. L_den and L_night were considered as indicators of noise exposure. Pooled data analyses showed clear exposure–response relationships between the noise level and the noise annoyance for both exposures. The exposure–response curves for road noise were congruent with the EU standard curves used for predicting the number of highly noise annoyed subjects in European communities. Annoyance ratings due to aircraft noise, however, were higher than predicted by the EU standard curves. The data supports other findings suggesting that the people's attitude towards aircraft noise has changed over the years, and that the EU standard curve for aircraft noise should be modified.     

Relative effects of educational level and occupational social class on body concentrations of persistent organic pollutants in a representative sample of the general population of Catalonia,Spain

Scant evidence is available worldwide on the relative influence of occupational social class and educational level on body concentrations of persistent organic pollutants (POPs) in the general population. The objective was to analyse such influence in a representative sample of the general population of Catalonia, Spain. Participants in the Catalan Health Interview Survey aged 18–74 were interviewed face-to-face, gave blood, and underwent a physical exam. The role of age, body mass index (BMI), and parity was analysed with General Linear Models, and adjusted geometric means (GMs) were obtained. Crude (unadjusted) concentrations were higher in women and men with lower education, and in women, but not men, in the less affluent social class. After adjusting for age, in women there were no associations between POP levels and social class or education. After adjusting for age and BMI, men in the less affluent class had higher p,p′-DDE concentrations than men in class I (p-value = 0.016), while men in class IV had lower HCB than men in the upper class (p-value < 0.03). Also in contrast with some expectations, positive associations between education and POP levels were observed after adjusting for age and BMI in men; e.g., men with university studies had higher HCB concentrations than men with first stage of primary schooling (adjusted GM 153.9 and 80.5 ng/g, respectively) (p-value < 0.001). When education and social class were co-adjusted for, some positive associations with education in men remained statistically significant, whereas class remained associated only with p,p′-DDE. Educational level influenced blood concentrations of POPs more than occupational social class, especially in men. In women, POP concentrations were mainly explained by age/birth cohort, parity and BMI. In men, while concentrations were also mainly explained by age/birth cohort and BMI, both social class and education showed positive associations. Important characteristics of socioeconomic groups as age and BMI may largely explain crude differences among such groups in internal contamination by POPs. The absence of clear patterns of relationships between blood concentrations of POPs and indicators of socioeconomic position may fundamentally be due to the widespread, lifelong, and generally invisible contamination of human food webs. Decreasing historical trends would also partly explain crude socioeconomic differences apparently due to birth cohort effects.