It has been suggested that air pollution may increase the risk of type 2 diabetes but data on particulate matter with diameter <2.5μm (PM2.5) are inconsistent. We examined the association between ...long-term exposure to PM2.5 and diabetes incidence.
We used the Danish Nurse Cohort with 28,731 female nurses who at recruitment in 1993 or 1999 reported information on diabetes prevalence and risk factors, and obtained data on incidence of diabetes from National Diabetes Register until 2013. We estimated annual mean concentrations of PM2.5, particulate matter with diameter <10μm (PM10), nitrogen oxides (NOx) and nitrogen dioxide (NO2) at their residence since 1990 using a dispersion model and examined the association between the 5-year running mean of pollutants and diabetes incidence using a time-varying Cox regression.
Of 24,174 nurses 1137 (4.7%) developed diabetes. We detected a significant positive association between PM2.5 and diabetes incidence (hazard ratio; 95% confidence interval: 1.11; 1.02–1.22 per interquartile range of 3.1μg/m3), and weaker associations for PM10 (1.06; 0.98–1.14 per 2.8μg/m3), NO2 (1.05; 0.99–1.12 per 7.5μg/m3), and NOx (1.01; 0.98–1.05 per 10.2μg/m3) in fully adjusted models. Associations with PM2.5 persisted in two-pollutant models. Associations with PM2.5 were significantly enhanced in never smokers (1.24; 1.09–1.42), and augmented in obese (1.25; 1.06–1.47) and subjects with myocardial infarction (1.32; 0.86–2.02), but without significant interaction.
Fine particulate matter may the most relevant pollutant for diabetes development among women, and non-smokers, obese women, and heart disease patients may be most susceptible.
•Evidence on association of PM2.5 with diabetes is inconsistent.•We linked residential PM2.5 to diabetes incidence in Danish Nurse Cohort.•We found 39% (4–86%) increased risk of diabetes per 10μg/m3 increase in PM2.5.•PM2.5 may be the most relevant pollutant for diabetes development.•Non-smokers, obese, and heart disease patients may be most susceptible.
•Early-life exposure to air pollution may increase asthma risk in young children.•Children living in low socio-economy areas may be more susceptible.•Air pollution have adverse health effects even at ...low concentrations.
Asthma is a complex, heterogeneous disease and one of the most common chronic diseases among children. Exposure to ambient air pollution in early life and childhood may influence asthma aetiology, but it is uncertain which specific components of air pollution and exposure windows are of importance. The role of socio-economic status (SES) is also unclear. The aims of the present study are, therefore, to investigate how various exposure windows of different pollutants affect risk-induced asthma in early life and to explore the possible effect SES has on that relationship.
The study population was constructed using register data on all singleton births in the greater Stockholm area between 2006 and 2013. Exposure to ambient black carbon (BC), fine particulate matter (PM2.5), primary organic carbon (pOC) secondary organic aerosols (SOA), secondary inorganic aerosols, and oxidative potential at the residential address was modelled as mean values for the entire pregnancy period, the first year of life and the first three years of life. Swedish national registers were used to define the outcome: asthma diagnosis assessed at hospital during the first six years of life. Hazard ratios (HRs) and their 95% confidence intervals (CIs) were modelled with Cox proportional hazards model with age as the underlying time-scale, adjusting for relevant potential confounding variables.
An increased risk for developing childhood asthma was observed in association with exposure to PM2.5, pOC and SOA during the first three years of life. With an interquartile range increase in exposure, the HRs were 1.06 (95% CI: 1.01–1.10), 1.05 (95% CI: 1.02–1.09) and 1.02 (95% CI: 1.00–1.04), for PM2.5, pOC and SOA, respectively, in the fully adjusted models. Exposure during foetal life or the first year of life was not associated with asthma risk, and the other pollutants were not statistically significantly associated with increased risk. Furthermore, the increase in risk associated with PM2.5 and the components BC, pOC and SOA were stronger in areas with lower SES.
Our results suggest that exposure to air pollution during the first three years of life may increase the risk for asthma in early childhood. The findings further imply a possible increased vulnerability to air pollution-attributed asthma among low SES children.
Air pollution exposure has been linked to coronary heart disease, although evidence on
and myocardial infarction (MI) incidence is mixed.
This prospective cohort study aimed to investigate ...associations between long-term exposure to air pollution and MI incidence, adjusting for road traffic noise.
We used data from the nationwide Danish Nurse Cohort on 22,882 female nurses (
of age) who, at recruitment in 1993 or 1999, reported information on cardiovascular disease risk factors. Data on MI incidence was collected from the Danish National Patient Register until the end of 2014. Annual mean concentrations of particulate matter (PM) with a diameter
(
),
, nitrogen dioxide (
), and nitrogen oxides (
) at the nurses' residences since 1990 (
and
) or 1970 (
and
) were estimated using the Danish Eulerian Hemispheric Model/Urban Background Model/AirGIS (DEHM/UBM/AirGIS) dispersion model. We used time-varying Cox regression models to examine the association between 1- and 3-y running means of these pollutants, as well as 23-y running means of
and
, with both overall and fatal incident MI. Associations were explored in three progressively adjusted models: Model 1, adjusted for age and baseline year; Model 2, with further adjustment for potential confounding by lifestyle and cardiovascular disease risk factors; and Model 3, with further adjustment for road traffic noise, modeled as the annual mean of a weighted 24-h average (
).
Of the 22,882 women, 641 developed MI during a mean follow-up of 18.6 y, 121 (18.9%) of which were fatal. Reported hazard ratios (HRs) were based on interquartile range increases of 5.3, 5.5, 8.1, and
for
,
,
, and
, respectively. In Model 1, we observed a positive association between a 3-y running mean of
and an overall incident MI with an
1.20 (95% CI: 1.07, 1.35), which attenuated to
1.06 (95% CI: 0.92, 1.23) in Model 2. In Model 1 for incident fatal MI, we observed a strong association with a 3-y running mean of
, with an
1.69 (95% CI: 1.33, 2.13), which attenuated to
1.35 (95% CI: 1.01, 1.81) in Model 2. Similar associations were seen for
, with 3-y, Model 2 estimates for overall and fatal incident MI of
1.06 (95% CI: 0.91, 1.23) and
1.35 (95% CI: 1.01, 1.81), respectively. No evidence of an association was observed for
or
. For all pollutants, associations in Model 2 were robust to further adjustment for road traffic noise in Model 3 and were similar for a 1-y running mean exposure.
We found no association between long-term exposure to
,
,
, or
and overall MI incidence, but we observed positive associations for
and
with fatal MI. We present novel findings that the association between PM and MI incidence is robust to adjustment for road traffic noise. https://doi.org/10.1289/EHP5818.
Background
The provision of different types of mortality metrics (e.g., mortality rate ratios MRRs and life expectancy) allows the research community to access a more informative set of health ...metrics. The aim of this study was to provide a panel of mortality metrics associated with a comprehensive range of disorders and to design a web page to visualize all results.
Methods and findings
In a population-based cohort of all 7,378,598 persons living in Denmark at some point between 2000 and 2018, we identified individuals diagnosed at hospitals with 1,803 specific categories of disorders through the International Classification of Diseases-10th Revision (ICD-10) in the National Patient Register. Information on date and cause of death was obtained from the Registry of Causes of Death. For each of the disorders, a panel of epidemiological and mortality metrics was estimated, including incidence rates, age-of-onset distributions, MRRs, and differences in life expectancy (estimated as life years lost LYLs). Additionally, we examined models that adjusted for measures of air pollution to explore potential associations with MRRs. We focus on 39 general medical conditions to simplify the presentation of results, which cover 10 broad categories: circulatory, endocrine, pulmonary, gastrointestinal, urogenital, musculoskeletal, hematologic, mental, and neurologic conditions and cancer. A total of 3,676,694 males and 3,701,904 females were followed up for 101.7 million person-years. During the 19-year follow-up period, 1,034,273 persons (14.0%) died. For 37 of the 39 selected medical conditions, mortality rates were larger and life expectancy shorter compared to the Danish general population. For these 37 disorders, MRRs ranged from 1.09 (95% confidence interval CI: 1.09 to 1.10) for vision problems to 7.85 (7.77 to 7.93) for chronic liver disease, while LYLs ranged from 0.31 (0.14 to 0.47) years (approximately 16 weeks) for allergy to 17.05 (16.95 to 17.15) years for chronic liver disease. Adjustment for air pollution had very little impact on the estimates; however, a limitation of the study is the possibility that the association between the different disorders and mortality could be explained by other underlying factors associated with both the disorder and mortality.
Conclusions
In this study, we show estimates of incidence, age of onset, age of death, and mortality metrics (both MRRs and LYLs) for a comprehensive range of disorders. The interactive data visualization site (
https://nbepi.com/atlas
) allows more fine-grained analysis of the link between a range of disorders and key mortality estimates.
Display omitted
•We examined the 9th-grade exit exams of 785,312 children in Denmark.•Children’s GPA was associated with lifetime exposure to air pollution.•An increase of 5 µg/m3 in PM2.5 was linked ...to a one-point decrease in GPA.•The negative associations were noticeable in the mathematics and natural sciences.•Girls and children with non-Danish mothers were susceptible to the association.
Recent research suggests a link between air pollution and cognitive development in children, and studies on air pollution and academic achievement are emerging. We conducted a nationwide cohort study in Denmark to explore the associations between lifetime exposure to air pollution and academic performance in 9th grade. The study encompassed 785,312 children born in Denmark between 1989 and 2005, all of whom completed 9th-grade exit examinations. Using linear mixed models with a random intercept for each school, we assessed the relationship between 16 years of exposure to PM2.5, PM10, and gaseous pollutants and Grade Point Averages (GPA) in exit examinations, covering subjects such as Danish literature, Danish writing, English, mathematics, and natural sciences. The study revealed that a 5 µg/m3 increase in PM2.5 and PM10 was associated with a decrease of 0.99 (95 % Confidence Intervals: −1.05, −0.92) and 0.46 (−0.50, −0.41) in GPA, respectively. Notably, these negative associations were more pronounced in mathematics and natural sciences compared to language-related subjects. Additionally, girls and children with non-Danish mothers were found to be particularly susceptible to the adverse effects of air pollution exposure. These results underscore the potential long-term consequences of air pollution on academic achievement, emphasizing the significance of interventions that foster healthier environments for children's cognitive development.
Air pollutants such as NO2 and PM2.5 have consistently been linked to mortality, but only few previous studies have addressed associations with long-term exposure to black carbon (BC) and ozone (O3).
...We investigated the association between PM2.5, PM10, BC, NO2, and O3 and mortality in a Danish cohort of 49,564 individuals who were followed up from enrollment in 1993–1997 through 2015. Residential address history from 1979 onwards was combined with air pollution exposure obtained by the state-of-the-art, validated, THOR/AirGIS air pollution modelling system, and information on residential traffic noise exposure, lifestyle and socio-demography.
We observed higher risks of all-cause as well as cardiovascular disease (CVD) mortality with higher long-term exposure to PM2.5, PM10, BC, and NO2. For PM2.5 and CVD mortality, a hazard ratio (HR) of 1.29 (95% CI: 1.13–1.47) per 5 μg/m3 was observed, and correspondingly HRs of 1.16 (95% CI: 1.05–1.27) and 1.11 (95% CI: 1.04–1.17) were observed for BC (per 1 μg/m3) and NO2 (per 10 μg/m3), respectively. Adjustment for noise gave slightly lower estimates for the air pollutants and CVD mortality. Inverse relationships were observed for O3. None of the investigated air pollutants were related to risk of respiratory mortality. Stratified analyses suggested that the elevated risks of CVD and all-cause mortality in relation to long-term PM, NO2 and BC exposure were restricted to males.
This study supports a role of PM, BC, and NO2 in all-cause and CVD mortality independent of road traffic noise exposure.
•Higher exposure to PM2.5, PM10, NO2 and black carbon was associated with mortality.•Associations of air pollutants and CVD mortality were independent of noise exposure.•O3 exposure was not associated with increased mortality risk.
The search for the genetic factors underlying complex neuropsychiatric disorders has proceeded apace in the past decade. Despite some advances in identifying genetic variants associated with ...psychiatric disorders, most variants have small individual contributions to risk. By contrast, disease risk increase appears to be less subtle for disease-predisposing environmental insults. In this study, we sought to identify associations between environmental pollution and risk of neuropsychiatric disorders. We present exploratory analyses of 2 independent, very large datasets: 151 million unique individuals, represented in a United States insurance claims dataset, and 1.4 million unique individuals documented in Danish national treatment registers. Environmental Protection Agency (EPA) county-level environmental quality indices (EQIs) in the US and individual-level exposure to air pollution in Denmark were used to assess the association between pollution exposure and the risk of neuropsychiatric disorders. These results show that air pollution is significantly associated with increased risk of psychiatric disorders. We hypothesize that pollutants affect the human brain via neuroinflammatory pathways that have also been shown to cause depression-like phenotypes in animal studies.
Particulate matter air pollution is widely considered as the leading environmental cause of premature mortality. However, there are substantial differences in the estimated health burden between the ...assessments. The aim of this work is to quantify the deaths attributable to ambient air pollution in Nordic countries applying selected assessment tools and approaches, and to identify the main disparities. We quantified and compared the estimated deaths from three health risk assessment tools and from a set of different concentration-response functions. A separate analysis was conducted for the impacts of spatial resolution of the exposure model on the estimated deaths. We found that the death rate (deaths per million) attributable to PM2.5 and O3 were the highest in Denmark and the lowest in Iceland. In the five Nordic countries, the results between the three tools ranged from 8500 to 11,400 for PM2.5 related deaths, and for ozone from 230 to 260 deaths in 2015. Substantially larger differences were found between five concentration-response functions. The shape of concentration-response functions, and applied theoretical thresholds led to substantial differences in the estimated deaths. Nordic countries are especially sensitive to theoretical thresholds due to low exposures. Sensitivity analysis demonstrated that when using spatial exposure assessment methods, high spatial resolution is necessary to avoid underestimation of exposures and health effects.
•Structural equations are a useful tool to model environment and health pathways.•Multiple stressors (noise, odor, smoke) and physical/emotional health were assessed.•Stress and well-being latent ...variables were estimated via many observed variables.•Environmental stress responses have a direct effect on physical well-being.•Self-rated health mediated the pathway between physical and emotional well-being.
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