The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform
Kathrin Wolf - One of the best experts on this subject based on the ideXlab platform.
-
OP X – 1 Long-term exposure to ultrafine particles and type 2 diabetes prevalence in a Longitudinal Setting
Occupational and Environmental Medicine, 2018Co-Authors: Kathrin Wolf, Alexandra Schneider, Susanne Breitner, Josef Cyrys, Wolfgang Rathmann, Wolfgang Koenig, Cornelia Huth, Christa Meisinger, Barbara Thorand, Annette PetersAbstract:Background/aim Recent studies suggested an association between long-term air pollution and type 2 diabetes (T2D). However, evidence is limited, especially for ultrafine particles (UFP, diameter Methods We conducted a Longitudinal analysis based on data of the baseline survey (1999–2001), first (2006–2008) and second follow-up (2013–2014) of the KORA S4 cohort in the Augsburg region, Germany. Long-term exposure to particle number concentration (PNC) as indicator for UFP, ozone, particulate matter with diameters Results We analysed 9450 observations of 4217 participants aged 25 to 75 years at baseline. T2D prevalence increased from 4.4% at baseline to 9.9% at the second follow-up. Our results indicated an increased T2D prevalence in association with all air pollutants. Significant effect estimates were seen for PNC [odds ratio: 1.14 (95%-confidence interval: 1.03; 1.25) per 1958 particles/cm3 (interquartile range) increase], PMcoarse [1.15 (1.03; 1.29) per 1.4 µg/m³ increase] and NOx [1.14 (1.02; 1.27) per 8.6 µg/m³ increase]. Effect estimates were higher for smokers, residents of the rural counties and participants with high CRP, whereas age, sex, obesity, physical activity, education, and a history of cardiovascular disease did not modify the estimates significantly. Conclusion As one of the first studies investigating chronic exposure to ultrafine particles and T2D in a Longitudinal Setting, our results point towards a positive association highlighting the role of ultrafine particles within the complex mixture of ambient air pollution.
-
OP X – 5 Long-term exposure to air pollution and biomarkers of inflammation and insulin resistance in a Longitudinal Setting
Occupational and Environmental Medicine, 2018Co-Authors: Sarah Mwiberi, Kathrin Wolf, Susanne Breitner, Wolfgang Rathmann, Wolfgang Koenig, Cornelia Huth, Regina Ruckerl, Christian Herder, Michael Roden, Josef CyrysAbstract:Background/aim Exposure to outdoor air pollution has been associated with systemic inflammation but results have been inconsistent. Evidence for deleterious effects on glucose metabolism and insulin resistance is still limited. We investigated the association of long-term air pollution exposure on biomarkers of systemic inflammation, glycaemia, and insulin resistance measured up to three times. Methods We used baseline survey (1999–2001), first follow-up (2006–2008) and second follow-up (2013–2014) from the KORA study in Augsburg, Southern Germany. At each examination, we measured plasma high-sensitivity C-reactive protein (hsCRP), glycosylated haemoglobin (HbA1c) and homeostatic model assessment of insulin resistance (HOMA-IR) calculated from fasting glucose and insulin. We estimated residential long-term exposure to ultrafine particles (UFP), different size fractions of particulate matter, soot, nitrogen oxides and ozone by land use regression. Associations between annual pollutants and biomarkers were modelled using generalised estimating equations adjusting for socio-demographic, lifestyle and clinical covariates. Potential effect-modifiers were examined by use of interaction terms. Results We included 9590 observations from 4255 participants aged 25 to 75 years at baseline in the analyses. Air pollutant concentrations at the participants’ residences were well below the EU guidelines for regulated pollutants. Except for ozone, all pollutants were positively associated with at least one of the biomarkers. For UFP, the highest effect was seen for hsCRP with an increase of 3% (95% CI: 0.4 to 5.6) per 1900 particles/cm 3 increase. Particulate matter between 2.5 and 10 µg/m³, soot and nitrogen dioxides were significantly associated with HbA1c and HOMA-IR. For the latter, effect estimates tended to be higher for males and elderly participants while this was not the case for the other two biomarkers. Conclusion The findings of this Longitudinal study add to a scarce body of literature on cardiometabolic health effects in association with chronic exposure to air pollution and help to fill the existing research gap, especially with regard to the effects of ultrafine particles.
-
op x 1 long term exposure to ultrafine particles and type 2 diabetes prevalence in a Longitudinal Setting
Occupational and Environmental Medicine, 2018Co-Authors: Kathrin Wolf, Alexandra Schneider, Susanne Breitner, Josef Cyrys, Wolfgang Rathmann, Wolfgang Koenig, Cornelia Huth, Christa Meisinger, Barbara Thorand, Annette PetersAbstract:Background/aim Recent studies suggested an association between long-term air pollution and type 2 diabetes (T2D). However, evidence is limited, especially for ultrafine particles (UFP, diameter Methods We conducted a Longitudinal analysis based on data of the baseline survey (1999–2001), first (2006–2008) and second follow-up (2013–2014) of the KORA S4 cohort in the Augsburg region, Germany. Long-term exposure to particle number concentration (PNC) as indicator for UFP, ozone, particulate matter with diameters Results We analysed 9450 observations of 4217 participants aged 25 to 75 years at baseline. T2D prevalence increased from 4.4% at baseline to 9.9% at the second follow-up. Our results indicated an increased T2D prevalence in association with all air pollutants. Significant effect estimates were seen for PNC [odds ratio: 1.14 (95%-confidence interval: 1.03; 1.25) per 1958 particles/cm3 (interquartile range) increase], PMcoarse [1.15 (1.03; 1.29) per 1.4 µg/m³ increase] and NOx [1.14 (1.02; 1.27) per 8.6 µg/m³ increase]. Effect estimates were higher for smokers, residents of the rural counties and participants with high CRP, whereas age, sex, obesity, physical activity, education, and a history of cardiovascular disease did not modify the estimates significantly. Conclusion As one of the first studies investigating chronic exposure to ultrafine particles and T2D in a Longitudinal Setting, our results point towards a positive association highlighting the role of ultrafine particles within the complex mixture of ambient air pollution.
-
op x 5 long term exposure to air pollution and biomarkers of inflammation and insulin resistance in a Longitudinal Setting
Occupational and Environmental Medicine, 2018Co-Authors: Sarah Mwiberi, Kathrin Wolf, Susanne Breitner, Wolfgang Rathmann, Wolfgang Koenig, Cornelia Huth, Regina Ruckerl, Christian Herder, Michael Roden, Josef CyrysAbstract:Background/aim Exposure to outdoor air pollution has been associated with systemic inflammation but results have been inconsistent. Evidence for deleterious effects on glucose metabolism and insulin resistance is still limited. We investigated the association of long-term air pollution exposure on biomarkers of systemic inflammation, glycaemia, and insulin resistance measured up to three times. Methods We used baseline survey (1999–2001), first follow-up (2006–2008) and second follow-up (2013–2014) from the KORA study in Augsburg, Southern Germany. At each examination, we measured plasma high-sensitivity C-reactive protein (hsCRP), glycosylated haemoglobin (HbA1c) and homeostatic model assessment of insulin resistance (HOMA-IR) calculated from fasting glucose and insulin. We estimated residential long-term exposure to ultrafine particles (UFP), different size fractions of particulate matter, soot, nitrogen oxides and ozone by land use regression. Associations between annual pollutants and biomarkers were modelled using generalised estimating equations adjusting for socio-demographic, lifestyle and clinical covariates. Potential effect-modifiers were examined by use of interaction terms. Results We included 9590 observations from 4255 participants aged 25 to 75 years at baseline in the analyses. Air pollutant concentrations at the participants’ residences were well below the EU guidelines for regulated pollutants. Except for ozone, all pollutants were positively associated with at least one of the biomarkers. For UFP, the highest effect was seen for hsCRP with an increase of 3% (95% CI: 0.4 to 5.6) per 1900 particles/cm 3 increase. Particulate matter between 2.5 and 10 µg/m³, soot and nitrogen dioxides were significantly associated with HbA1c and HOMA-IR. For the latter, effect estimates tended to be higher for males and elderly participants while this was not the case for the other two biomarkers. Conclusion The findings of this Longitudinal study add to a scarce body of literature on cardiometabolic health effects in association with chronic exposure to air pollution and help to fill the existing research gap, especially with regard to the effects of ultrafine particles.
Jennifer A Smith - One of the best experts on this subject based on the ideXlab platform.
-
Interaction between Social/Psychosocial Factors and Genetic Variants on Body Mass Index: A Gene-Environment Interaction Analysis in a Longitudinal Setting.
International Journal of Environmental Research and Public Health, 2017Co-Authors: Wei Zhao, Sharon L R Kardia, Erin B Ware, Zihuai He, Jessica D Faul, Jennifer A SmithAbstract:Obesity, which develops over time, is one of the leading causes of chronic diseases such as cardiovascular disease. However, hundreds of BMI (body mass index)-associated genetic loci identified through large-scale genome-wide association studies (GWAS) only explain about 2.7% of BMI variation. Most common human traits are believed to be influenced by both genetic and environmental factors. Past studies suggest a variety of environmental features that are associated with obesity, including socioeconomic status and psychosocial factors. This study combines both gene/regions and environmental factors to explore whether social/psychosocial factors (childhood and adult socioeconomic status, social support, anger, chronic burden, stressful life events, and depressive symptoms) modify the effect of sets of genetic variants on BMI in European American and African American participants in the Health and Retirement Study (HRS). In order to incorporate Longitudinal phenotype data collected in the HRS and investigate entire sets of single nucleotide polymorphisms (SNPs) within gene/region simultaneously, we applied a novel set-based test for gene-environment interaction in Longitudinal studies (LGEWIS). Childhood socioeconomic status (parental education) was found to modify the genetic effect in the gene/region around SNP rs9540493 on BMI in European Americans in the HRS. The most significant SNP (rs9540488) by childhood socioeconomic status interaction within the rs9540493 gene/region was suggestively replicated in the Multi-Ethnic Study of Atherosclerosis (MESA) (p = 0.07).
-
interaction between social psychosocial factors and genetic variants on body mass index a gene environment interaction analysis in a Longitudinal Setting
International Journal of Environmental Research and Public Health, 2017Co-Authors: Wei Zhao, Sharon L R Kardia, Erin B Ware, Zihuai He, Jessica D Faul, Jennifer A SmithAbstract:Obesity, which develops over time, is one of the leading causes of chronic diseases such as cardiovascular disease. However, hundreds of BMI (body mass index)-associated genetic loci identified through large-scale genome-wide association studies (GWAS) only explain about 2.7% of BMI variation. Most common human traits are believed to be influenced by both genetic and environmental factors. Past studies suggest a variety of environmental features that are associated with obesity, including socioeconomic status and psychosocial factors. This study combines both gene/regions and environmental factors to explore whether social/psychosocial factors (childhood and adult socioeconomic status, social support, anger, chronic burden, stressful life events, and depressive symptoms) modify the effect of sets of genetic variants on BMI in European American and African American participants in the Health and Retirement Study (HRS). In order to incorporate Longitudinal phenotype data collected in the HRS and investigate entire sets of single nucleotide polymorphisms (SNPs) within gene/region simultaneously, we applied a novel set-based test for gene-environment interaction in Longitudinal studies (LGEWIS). Childhood socioeconomic status (parental education) was found to modify the genetic effect in the gene/region around SNP rs9540493 on BMI in European Americans in the HRS. The most significant SNP (rs9540488) by childhood socioeconomic status interaction within the rs9540493 gene/region was suggestively replicated in the Multi-Ethnic Study of Atherosclerosis (MESA) (p = 0.07).
-
testing departure from additivity in tukey s model using shrinkage application to a Longitudinal Setting
Statistics in Medicine, 2014Co-Authors: Yian Ko, Bhramar Mukherjee, Jennifer A Smith, Sung Kyun Park, Sharon L R Kardia, Matthew A Allison, Pantel S Vokonas, Jinbo Chen, Ana V DiezrouxAbstract:While there has been extensive research developing gene-environment interaction (GEI) methods in case-control studies, little attention has been given to sparse and efficient modeling of GEI in Longitudinal studies. In a two-way table for GEI with rows and columns as categorical variables, a conventional saturated interaction model involves estimation of a specific parameter for each cell, with constraints ensuring identifiability. The estimates are unbiased but are potentially inefficient because the number of parameters to be estimated can grow quickly with increasing categories of row/column factors. On the other hand, Tukey’s one degree of freedom (df) model for non-additivity treats the interaction term as a scaled product of row and column main effects. Due to the parsimonious form of interaction, the interaction estimate leads to enhanced efficiency and the corresponding test could lead to increased power. Unfortunately, Tukey’s model gives biased estimates and low power if the model is misspecified. When screening multiple GEIs where each genetic and environmental marker may exhibit a distinct interaction pattern, a robust estimator for interaction is important for GEI detection. We propose a shrinkage estimator for interaction effects that combines estimates from both Tukey’s and saturated interaction models and use the corresponding Wald test for testing interaction in a Longitudinal Setting. The proposed estimator is robust to misspecification of interaction structure. We illustrate the proposed methods using two Longitudinal studies — the Normative Aging Study and the Multi-Ethnic Study of Atherosclerosis.
Josef Cyrys - One of the best experts on this subject based on the ideXlab platform.
-
OP X – 1 Long-term exposure to ultrafine particles and type 2 diabetes prevalence in a Longitudinal Setting
Occupational and Environmental Medicine, 2018Co-Authors: Kathrin Wolf, Alexandra Schneider, Susanne Breitner, Josef Cyrys, Wolfgang Rathmann, Wolfgang Koenig, Cornelia Huth, Christa Meisinger, Barbara Thorand, Annette PetersAbstract:Background/aim Recent studies suggested an association between long-term air pollution and type 2 diabetes (T2D). However, evidence is limited, especially for ultrafine particles (UFP, diameter Methods We conducted a Longitudinal analysis based on data of the baseline survey (1999–2001), first (2006–2008) and second follow-up (2013–2014) of the KORA S4 cohort in the Augsburg region, Germany. Long-term exposure to particle number concentration (PNC) as indicator for UFP, ozone, particulate matter with diameters Results We analysed 9450 observations of 4217 participants aged 25 to 75 years at baseline. T2D prevalence increased from 4.4% at baseline to 9.9% at the second follow-up. Our results indicated an increased T2D prevalence in association with all air pollutants. Significant effect estimates were seen for PNC [odds ratio: 1.14 (95%-confidence interval: 1.03; 1.25) per 1958 particles/cm3 (interquartile range) increase], PMcoarse [1.15 (1.03; 1.29) per 1.4 µg/m³ increase] and NOx [1.14 (1.02; 1.27) per 8.6 µg/m³ increase]. Effect estimates were higher for smokers, residents of the rural counties and participants with high CRP, whereas age, sex, obesity, physical activity, education, and a history of cardiovascular disease did not modify the estimates significantly. Conclusion As one of the first studies investigating chronic exposure to ultrafine particles and T2D in a Longitudinal Setting, our results point towards a positive association highlighting the role of ultrafine particles within the complex mixture of ambient air pollution.
-
OP X – 5 Long-term exposure to air pollution and biomarkers of inflammation and insulin resistance in a Longitudinal Setting
Occupational and Environmental Medicine, 2018Co-Authors: Sarah Mwiberi, Kathrin Wolf, Susanne Breitner, Wolfgang Rathmann, Wolfgang Koenig, Cornelia Huth, Regina Ruckerl, Christian Herder, Michael Roden, Josef CyrysAbstract:Background/aim Exposure to outdoor air pollution has been associated with systemic inflammation but results have been inconsistent. Evidence for deleterious effects on glucose metabolism and insulin resistance is still limited. We investigated the association of long-term air pollution exposure on biomarkers of systemic inflammation, glycaemia, and insulin resistance measured up to three times. Methods We used baseline survey (1999–2001), first follow-up (2006–2008) and second follow-up (2013–2014) from the KORA study in Augsburg, Southern Germany. At each examination, we measured plasma high-sensitivity C-reactive protein (hsCRP), glycosylated haemoglobin (HbA1c) and homeostatic model assessment of insulin resistance (HOMA-IR) calculated from fasting glucose and insulin. We estimated residential long-term exposure to ultrafine particles (UFP), different size fractions of particulate matter, soot, nitrogen oxides and ozone by land use regression. Associations between annual pollutants and biomarkers were modelled using generalised estimating equations adjusting for socio-demographic, lifestyle and clinical covariates. Potential effect-modifiers were examined by use of interaction terms. Results We included 9590 observations from 4255 participants aged 25 to 75 years at baseline in the analyses. Air pollutant concentrations at the participants’ residences were well below the EU guidelines for regulated pollutants. Except for ozone, all pollutants were positively associated with at least one of the biomarkers. For UFP, the highest effect was seen for hsCRP with an increase of 3% (95% CI: 0.4 to 5.6) per 1900 particles/cm 3 increase. Particulate matter between 2.5 and 10 µg/m³, soot and nitrogen dioxides were significantly associated with HbA1c and HOMA-IR. For the latter, effect estimates tended to be higher for males and elderly participants while this was not the case for the other two biomarkers. Conclusion The findings of this Longitudinal study add to a scarce body of literature on cardiometabolic health effects in association with chronic exposure to air pollution and help to fill the existing research gap, especially with regard to the effects of ultrafine particles.
-
op x 1 long term exposure to ultrafine particles and type 2 diabetes prevalence in a Longitudinal Setting
Occupational and Environmental Medicine, 2018Co-Authors: Kathrin Wolf, Alexandra Schneider, Susanne Breitner, Josef Cyrys, Wolfgang Rathmann, Wolfgang Koenig, Cornelia Huth, Christa Meisinger, Barbara Thorand, Annette PetersAbstract:Background/aim Recent studies suggested an association between long-term air pollution and type 2 diabetes (T2D). However, evidence is limited, especially for ultrafine particles (UFP, diameter Methods We conducted a Longitudinal analysis based on data of the baseline survey (1999–2001), first (2006–2008) and second follow-up (2013–2014) of the KORA S4 cohort in the Augsburg region, Germany. Long-term exposure to particle number concentration (PNC) as indicator for UFP, ozone, particulate matter with diameters Results We analysed 9450 observations of 4217 participants aged 25 to 75 years at baseline. T2D prevalence increased from 4.4% at baseline to 9.9% at the second follow-up. Our results indicated an increased T2D prevalence in association with all air pollutants. Significant effect estimates were seen for PNC [odds ratio: 1.14 (95%-confidence interval: 1.03; 1.25) per 1958 particles/cm3 (interquartile range) increase], PMcoarse [1.15 (1.03; 1.29) per 1.4 µg/m³ increase] and NOx [1.14 (1.02; 1.27) per 8.6 µg/m³ increase]. Effect estimates were higher for smokers, residents of the rural counties and participants with high CRP, whereas age, sex, obesity, physical activity, education, and a history of cardiovascular disease did not modify the estimates significantly. Conclusion As one of the first studies investigating chronic exposure to ultrafine particles and T2D in a Longitudinal Setting, our results point towards a positive association highlighting the role of ultrafine particles within the complex mixture of ambient air pollution.
-
op x 5 long term exposure to air pollution and biomarkers of inflammation and insulin resistance in a Longitudinal Setting
Occupational and Environmental Medicine, 2018Co-Authors: Sarah Mwiberi, Kathrin Wolf, Susanne Breitner, Wolfgang Rathmann, Wolfgang Koenig, Cornelia Huth, Regina Ruckerl, Christian Herder, Michael Roden, Josef CyrysAbstract:Background/aim Exposure to outdoor air pollution has been associated with systemic inflammation but results have been inconsistent. Evidence for deleterious effects on glucose metabolism and insulin resistance is still limited. We investigated the association of long-term air pollution exposure on biomarkers of systemic inflammation, glycaemia, and insulin resistance measured up to three times. Methods We used baseline survey (1999–2001), first follow-up (2006–2008) and second follow-up (2013–2014) from the KORA study in Augsburg, Southern Germany. At each examination, we measured plasma high-sensitivity C-reactive protein (hsCRP), glycosylated haemoglobin (HbA1c) and homeostatic model assessment of insulin resistance (HOMA-IR) calculated from fasting glucose and insulin. We estimated residential long-term exposure to ultrafine particles (UFP), different size fractions of particulate matter, soot, nitrogen oxides and ozone by land use regression. Associations between annual pollutants and biomarkers were modelled using generalised estimating equations adjusting for socio-demographic, lifestyle and clinical covariates. Potential effect-modifiers were examined by use of interaction terms. Results We included 9590 observations from 4255 participants aged 25 to 75 years at baseline in the analyses. Air pollutant concentrations at the participants’ residences were well below the EU guidelines for regulated pollutants. Except for ozone, all pollutants were positively associated with at least one of the biomarkers. For UFP, the highest effect was seen for hsCRP with an increase of 3% (95% CI: 0.4 to 5.6) per 1900 particles/cm 3 increase. Particulate matter between 2.5 and 10 µg/m³, soot and nitrogen dioxides were significantly associated with HbA1c and HOMA-IR. For the latter, effect estimates tended to be higher for males and elderly participants while this was not the case for the other two biomarkers. Conclusion The findings of this Longitudinal study add to a scarce body of literature on cardiometabolic health effects in association with chronic exposure to air pollution and help to fill the existing research gap, especially with regard to the effects of ultrafine particles.
Annette Peters - One of the best experts on this subject based on the ideXlab platform.
-
OP X – 1 Long-term exposure to ultrafine particles and type 2 diabetes prevalence in a Longitudinal Setting
Occupational and Environmental Medicine, 2018Co-Authors: Kathrin Wolf, Alexandra Schneider, Susanne Breitner, Josef Cyrys, Wolfgang Rathmann, Wolfgang Koenig, Cornelia Huth, Christa Meisinger, Barbara Thorand, Annette PetersAbstract:Background/aim Recent studies suggested an association between long-term air pollution and type 2 diabetes (T2D). However, evidence is limited, especially for ultrafine particles (UFP, diameter Methods We conducted a Longitudinal analysis based on data of the baseline survey (1999–2001), first (2006–2008) and second follow-up (2013–2014) of the KORA S4 cohort in the Augsburg region, Germany. Long-term exposure to particle number concentration (PNC) as indicator for UFP, ozone, particulate matter with diameters Results We analysed 9450 observations of 4217 participants aged 25 to 75 years at baseline. T2D prevalence increased from 4.4% at baseline to 9.9% at the second follow-up. Our results indicated an increased T2D prevalence in association with all air pollutants. Significant effect estimates were seen for PNC [odds ratio: 1.14 (95%-confidence interval: 1.03; 1.25) per 1958 particles/cm3 (interquartile range) increase], PMcoarse [1.15 (1.03; 1.29) per 1.4 µg/m³ increase] and NOx [1.14 (1.02; 1.27) per 8.6 µg/m³ increase]. Effect estimates were higher for smokers, residents of the rural counties and participants with high CRP, whereas age, sex, obesity, physical activity, education, and a history of cardiovascular disease did not modify the estimates significantly. Conclusion As one of the first studies investigating chronic exposure to ultrafine particles and T2D in a Longitudinal Setting, our results point towards a positive association highlighting the role of ultrafine particles within the complex mixture of ambient air pollution.
-
op x 1 long term exposure to ultrafine particles and type 2 diabetes prevalence in a Longitudinal Setting
Occupational and Environmental Medicine, 2018Co-Authors: Kathrin Wolf, Alexandra Schneider, Susanne Breitner, Josef Cyrys, Wolfgang Rathmann, Wolfgang Koenig, Cornelia Huth, Christa Meisinger, Barbara Thorand, Annette PetersAbstract:Background/aim Recent studies suggested an association between long-term air pollution and type 2 diabetes (T2D). However, evidence is limited, especially for ultrafine particles (UFP, diameter Methods We conducted a Longitudinal analysis based on data of the baseline survey (1999–2001), first (2006–2008) and second follow-up (2013–2014) of the KORA S4 cohort in the Augsburg region, Germany. Long-term exposure to particle number concentration (PNC) as indicator for UFP, ozone, particulate matter with diameters Results We analysed 9450 observations of 4217 participants aged 25 to 75 years at baseline. T2D prevalence increased from 4.4% at baseline to 9.9% at the second follow-up. Our results indicated an increased T2D prevalence in association with all air pollutants. Significant effect estimates were seen for PNC [odds ratio: 1.14 (95%-confidence interval: 1.03; 1.25) per 1958 particles/cm3 (interquartile range) increase], PMcoarse [1.15 (1.03; 1.29) per 1.4 µg/m³ increase] and NOx [1.14 (1.02; 1.27) per 8.6 µg/m³ increase]. Effect estimates were higher for smokers, residents of the rural counties and participants with high CRP, whereas age, sex, obesity, physical activity, education, and a history of cardiovascular disease did not modify the estimates significantly. Conclusion As one of the first studies investigating chronic exposure to ultrafine particles and T2D in a Longitudinal Setting, our results point towards a positive association highlighting the role of ultrafine particles within the complex mixture of ambient air pollution.
Wolfgang Rathmann - One of the best experts on this subject based on the ideXlab platform.
-
OP X – 1 Long-term exposure to ultrafine particles and type 2 diabetes prevalence in a Longitudinal Setting
Occupational and Environmental Medicine, 2018Co-Authors: Kathrin Wolf, Alexandra Schneider, Susanne Breitner, Josef Cyrys, Wolfgang Rathmann, Wolfgang Koenig, Cornelia Huth, Christa Meisinger, Barbara Thorand, Annette PetersAbstract:Background/aim Recent studies suggested an association between long-term air pollution and type 2 diabetes (T2D). However, evidence is limited, especially for ultrafine particles (UFP, diameter Methods We conducted a Longitudinal analysis based on data of the baseline survey (1999–2001), first (2006–2008) and second follow-up (2013–2014) of the KORA S4 cohort in the Augsburg region, Germany. Long-term exposure to particle number concentration (PNC) as indicator for UFP, ozone, particulate matter with diameters Results We analysed 9450 observations of 4217 participants aged 25 to 75 years at baseline. T2D prevalence increased from 4.4% at baseline to 9.9% at the second follow-up. Our results indicated an increased T2D prevalence in association with all air pollutants. Significant effect estimates were seen for PNC [odds ratio: 1.14 (95%-confidence interval: 1.03; 1.25) per 1958 particles/cm3 (interquartile range) increase], PMcoarse [1.15 (1.03; 1.29) per 1.4 µg/m³ increase] and NOx [1.14 (1.02; 1.27) per 8.6 µg/m³ increase]. Effect estimates were higher for smokers, residents of the rural counties and participants with high CRP, whereas age, sex, obesity, physical activity, education, and a history of cardiovascular disease did not modify the estimates significantly. Conclusion As one of the first studies investigating chronic exposure to ultrafine particles and T2D in a Longitudinal Setting, our results point towards a positive association highlighting the role of ultrafine particles within the complex mixture of ambient air pollution.
-
OP X – 5 Long-term exposure to air pollution and biomarkers of inflammation and insulin resistance in a Longitudinal Setting
Occupational and Environmental Medicine, 2018Co-Authors: Sarah Mwiberi, Kathrin Wolf, Susanne Breitner, Wolfgang Rathmann, Wolfgang Koenig, Cornelia Huth, Regina Ruckerl, Christian Herder, Michael Roden, Josef CyrysAbstract:Background/aim Exposure to outdoor air pollution has been associated with systemic inflammation but results have been inconsistent. Evidence for deleterious effects on glucose metabolism and insulin resistance is still limited. We investigated the association of long-term air pollution exposure on biomarkers of systemic inflammation, glycaemia, and insulin resistance measured up to three times. Methods We used baseline survey (1999–2001), first follow-up (2006–2008) and second follow-up (2013–2014) from the KORA study in Augsburg, Southern Germany. At each examination, we measured plasma high-sensitivity C-reactive protein (hsCRP), glycosylated haemoglobin (HbA1c) and homeostatic model assessment of insulin resistance (HOMA-IR) calculated from fasting glucose and insulin. We estimated residential long-term exposure to ultrafine particles (UFP), different size fractions of particulate matter, soot, nitrogen oxides and ozone by land use regression. Associations between annual pollutants and biomarkers were modelled using generalised estimating equations adjusting for socio-demographic, lifestyle and clinical covariates. Potential effect-modifiers were examined by use of interaction terms. Results We included 9590 observations from 4255 participants aged 25 to 75 years at baseline in the analyses. Air pollutant concentrations at the participants’ residences were well below the EU guidelines for regulated pollutants. Except for ozone, all pollutants were positively associated with at least one of the biomarkers. For UFP, the highest effect was seen for hsCRP with an increase of 3% (95% CI: 0.4 to 5.6) per 1900 particles/cm 3 increase. Particulate matter between 2.5 and 10 µg/m³, soot and nitrogen dioxides were significantly associated with HbA1c and HOMA-IR. For the latter, effect estimates tended to be higher for males and elderly participants while this was not the case for the other two biomarkers. Conclusion The findings of this Longitudinal study add to a scarce body of literature on cardiometabolic health effects in association with chronic exposure to air pollution and help to fill the existing research gap, especially with regard to the effects of ultrafine particles.
-
op x 1 long term exposure to ultrafine particles and type 2 diabetes prevalence in a Longitudinal Setting
Occupational and Environmental Medicine, 2018Co-Authors: Kathrin Wolf, Alexandra Schneider, Susanne Breitner, Josef Cyrys, Wolfgang Rathmann, Wolfgang Koenig, Cornelia Huth, Christa Meisinger, Barbara Thorand, Annette PetersAbstract:Background/aim Recent studies suggested an association between long-term air pollution and type 2 diabetes (T2D). However, evidence is limited, especially for ultrafine particles (UFP, diameter Methods We conducted a Longitudinal analysis based on data of the baseline survey (1999–2001), first (2006–2008) and second follow-up (2013–2014) of the KORA S4 cohort in the Augsburg region, Germany. Long-term exposure to particle number concentration (PNC) as indicator for UFP, ozone, particulate matter with diameters Results We analysed 9450 observations of 4217 participants aged 25 to 75 years at baseline. T2D prevalence increased from 4.4% at baseline to 9.9% at the second follow-up. Our results indicated an increased T2D prevalence in association with all air pollutants. Significant effect estimates were seen for PNC [odds ratio: 1.14 (95%-confidence interval: 1.03; 1.25) per 1958 particles/cm3 (interquartile range) increase], PMcoarse [1.15 (1.03; 1.29) per 1.4 µg/m³ increase] and NOx [1.14 (1.02; 1.27) per 8.6 µg/m³ increase]. Effect estimates were higher for smokers, residents of the rural counties and participants with high CRP, whereas age, sex, obesity, physical activity, education, and a history of cardiovascular disease did not modify the estimates significantly. Conclusion As one of the first studies investigating chronic exposure to ultrafine particles and T2D in a Longitudinal Setting, our results point towards a positive association highlighting the role of ultrafine particles within the complex mixture of ambient air pollution.
-
op x 5 long term exposure to air pollution and biomarkers of inflammation and insulin resistance in a Longitudinal Setting
Occupational and Environmental Medicine, 2018Co-Authors: Sarah Mwiberi, Kathrin Wolf, Susanne Breitner, Wolfgang Rathmann, Wolfgang Koenig, Cornelia Huth, Regina Ruckerl, Christian Herder, Michael Roden, Josef CyrysAbstract:Background/aim Exposure to outdoor air pollution has been associated with systemic inflammation but results have been inconsistent. Evidence for deleterious effects on glucose metabolism and insulin resistance is still limited. We investigated the association of long-term air pollution exposure on biomarkers of systemic inflammation, glycaemia, and insulin resistance measured up to three times. Methods We used baseline survey (1999–2001), first follow-up (2006–2008) and second follow-up (2013–2014) from the KORA study in Augsburg, Southern Germany. At each examination, we measured plasma high-sensitivity C-reactive protein (hsCRP), glycosylated haemoglobin (HbA1c) and homeostatic model assessment of insulin resistance (HOMA-IR) calculated from fasting glucose and insulin. We estimated residential long-term exposure to ultrafine particles (UFP), different size fractions of particulate matter, soot, nitrogen oxides and ozone by land use regression. Associations between annual pollutants and biomarkers were modelled using generalised estimating equations adjusting for socio-demographic, lifestyle and clinical covariates. Potential effect-modifiers were examined by use of interaction terms. Results We included 9590 observations from 4255 participants aged 25 to 75 years at baseline in the analyses. Air pollutant concentrations at the participants’ residences were well below the EU guidelines for regulated pollutants. Except for ozone, all pollutants were positively associated with at least one of the biomarkers. For UFP, the highest effect was seen for hsCRP with an increase of 3% (95% CI: 0.4 to 5.6) per 1900 particles/cm 3 increase. Particulate matter between 2.5 and 10 µg/m³, soot and nitrogen dioxides were significantly associated with HbA1c and HOMA-IR. For the latter, effect estimates tended to be higher for males and elderly participants while this was not the case for the other two biomarkers. Conclusion The findings of this Longitudinal study add to a scarce body of literature on cardiometabolic health effects in association with chronic exposure to air pollution and help to fill the existing research gap, especially with regard to the effects of ultrafine particles.
