Is Particle Pollution in Outdoor Air Associated with Metabolic Control in Type 2 Diabetes?
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{"title"=>"Is particle pollution in outdoor air associated with metabolic control in type 2 diabetes?", "type"=>"journal", "authors"=>[{"first_name"=>"Teresa", "last_name"=>"Tamayo", "scopus_author_id"=>"36134914500"}, {"first_name"=>"Wolfgang", "last_name"=>"Rathmann", "scopus_author_id"=>"55800240200"}, {"first_name"=>"Ursula", "last_name"=>"Krämer", "scopus_author_id"=>"7102010419"}, {"first_name"=>"Dorothea", "last_name"=>"Sugiri", "scopus_author_id"=>"6602274684"}, {"first_name"=>"Matthias", "last_name"=>"Grabert", "scopus_author_id"=>"6603386673"}, {"first_name"=>"Reinhard W.", "last_name"=>"Holl", "scopus_author_id"=>"7005983446"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"pmid"=>"24619127", "doi"=>"10.1371/journal.pone.0091639", "sgr"=>"84897502073", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "scopus"=>"2-s2.0-84897502073", "issn"=>"19326203", "pui"=>"372764701"}, "id"=>"6bbaea23-bb0d-37aa-a1d7-cbd90f07cd2d", "abstract"=>"BACKGROUND: There is growing evidence that air pollutants are associated with the risk of type 2 diabetes. Subclinical inflammation may be a mechanism linking air pollution with diabetes. Information is lacking whether air pollution also contributes to worse metabolic control in newly diagnosed type 2 diabetes. We examined the hypothesis that residential particulate matter (PM10) is associated with HbA1c concentration in newly diagnosed type 2 diabetes.\\n\\nMETHODS: Nationwide regional levels of particulate matter with a diameter of ≤ 10 µm (PM10) were obtained in 2009 from background monitoring stations in Germany (Federal Environmental Agency) and assigned to place of residency of 9,102 newly diagnosed diabetes patients registered in the DPV database throughout Germany (age 65.5 ± 13.5 yrs; males: 52.1%). Mean HbA1c (%) levels stratified for air pollution quartiles (PM10 in µg/m(3)) were estimated using linear regression models adjusting for age, sex, BMI, diabetes duration, geographic region, year of ascertainment, and social indicators.\\n\\nFINDINGS: In both men and women, adjusted HbA1c was significantly lower in the lowest quartile of PM10 exposure in comparison to quartiles Q2-Q4. Largest differences in adjusted HbA1c (95% CI) were seen comparing lowest quartiles of exposure with highest quartiles (men %: -0.42 (-0.62; -0.23)/mmol/mol: -28.11 (-30.30; -26.04), women, %: -0.28 (-0.47; -0.09)/mmol/mol: -0.28 (-0.47; -0.09)).\\n\\nINTERPRETATION: Air pollution may be associated with higher HbA1c levels in newly diagnosed type 2 diabetes patients. Further studies are warranted to examine this association.", "link"=>"http://www.mendeley.com/research/particle-pollution-outdoor-air-associated-metabolic-control-type-2-diabetes", "reader_count"=>19, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>1, "Researcher"=>3, "Student > Ph. D. Student"=>4, "Student > Postgraduate"=>2, "Student > Master"=>5, "Other"=>1, "Student > Bachelor"=>2, "Lecturer"=>1}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>1, "Researcher"=>3, "Student > Ph. D. Student"=>4, "Student > Postgraduate"=>2, "Student > Master"=>5, "Other"=>1, "Student > Bachelor"=>2, "Lecturer"=>1}, "reader_count_by_subject_area"=>{"Engineering"=>1, "Environmental Science"=>4, "Nursing and Health Professions"=>4, "Medicine and Dentistry"=>6, "Agricultural and Biological Sciences"=>1, "Social Sciences"=>1, "Computer Science"=>1, "Earth and Planetary Sciences"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>6}, "Social Sciences"=>{"Social Sciences"=>1}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>1}, "Computer Science"=>{"Computer Science"=>1}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>4}, "Environmental Science"=>{"Environmental Science"=>4}}, "reader_count_by_country"=>{"Canada"=>1, "United States"=>1}, "group_count"=>0}

Scopus | Further Information

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  • {"files"=>["https://ndownloader.figshare.com/files/1414706"], "description"=>"<p>Results are numbers (N), frequencies in % or means (SD). Abbreviation of Nielsen areas: 1 (N) = Hamburg, Bremen, Schleswig-Holstein, Lower Saxony (North); 2 (W) = North Rhine-Westfalia (West); 3 (SW) = Hesse, Rhineland-Palatinate, Saarland, Baden-Württemberg (Southwest); 4 (S) = Bavaria (South); 5 (B) = Berlin (Northeast); 6 (NE) = Mecklenburg-Vorpommern, Brandenburg, Saxony-Anhalt (Northeast); 7 (E) = Thuringia, Saxony (East). HbA1c levels in % (NGSP) can be converted to mmol/mol (IFCC) by application of the following formula: IFCC = (10.93*NGSP)−23.50.</p>", "links"=>[], "tags"=>["Atmospheric science", "atmospheric chemistry", "Air quality", "Environmental sciences", "Environmental engineering", "pollution", "statistics", "Confidence intervals", "Statistical methods", "Endocrinology", "Diabetic endocrinology", "Diabetes mellitus type 2", "epidemiology", "Metabolic disorders", "Public health", "geographic"], "article_id"=>957637, "categories"=>["Mathematics", "Medicine"], "users"=>["Teresa Tamayo", "Wolfgang Rathmann", "Ursula Krämer", "Dorothea Sugiri", "Matthias Grabert", "Reinhard W. Holl"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0091639.t002", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Characteristics_of_participants_with_type_2_diabetes_per_geographic_region_Nielsen_area_/957637", "title"=>"Characteristics of participants with type 2 diabetes per geographic region (Nielsen area).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-03-11 02:44:08"}
  • {"files"=>["https://ndownloader.figshare.com/files/1414707"], "description"=>"<p>*Results are adjusted means for HbA<sub>1c</sub> in % calculated from generalized linear regression models. Models were fitted adjusting for age, sex, body mass index, duration of diabetes, geographic region, year of treatment, and social indicators (low education, immigration background). Furthermore, difference in HbA<sub>1c</sub> levels in % (95% CI) comparing quartiles of PM<sub>10</sub> exposure also derived from linear regression models are presented. Group differences are considered as significant (highlighted in bold) if corresponding 95% confidence intervals do not include 0. HbA1c levels in % (NGSP) can be converted to mmol/mol (IFCC) by application of the following formula: IFCC = (10.93*NGSP)−23.50.</p>", "links"=>[], "tags"=>["Atmospheric science", "atmospheric chemistry", "Air quality", "Environmental sciences", "Environmental engineering", "pollution", "statistics", "Confidence intervals", "Statistical methods", "Endocrinology", "Diabetic endocrinology", "Diabetes mellitus type 2", "epidemiology", "Metabolic disorders", "Public health", "comparing", "quartiles", "particulate"], "article_id"=>957638, "categories"=>["Mathematics", "Medicine"], "users"=>["Teresa Tamayo", "Wolfgang Rathmann", "Ursula Krämer", "Dorothea Sugiri", "Matthias Grabert", "Reinhard W. Holl"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0091639.t003", "stats"=>{"downloads"=>1, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Adjusted_mean_HbA_1c_and_difference_in_HbA_1c_comparing_quartiles_of_particulate_matter_PM_10_exposure_in_type_2_diabetes_patients_/957638", "title"=>"Adjusted mean HbA<sub>1c</sub> and difference in HbA<sub>1c</sub> comparing quartiles of particulate matter (PM<sub>10</sub>) exposure in type 2 diabetes patients<sup>*</sup>.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-03-11 02:44:08"}
  • {"files"=>["https://ndownloader.figshare.com/files/1414705"], "description"=>"<p>*Results are numbers (N), frequencies in % or means (SD). HbA1c levels in % (NGSP) can be converted to mmol/mol (IFCC) by application of the following formula: IFCC = (10.93*NGSP)−23.50.</p>", "links"=>[], "tags"=>["Atmospheric science", "atmospheric chemistry", "Air quality", "Environmental sciences", "Environmental engineering", "pollution", "statistics", "Confidence intervals", "Statistical methods", "Endocrinology", "Diabetic endocrinology", "Diabetes mellitus type 2", "epidemiology", "Metabolic disorders", "Public health"], "article_id"=>957636, "categories"=>["Mathematics", "Medicine"], "users"=>["Teresa Tamayo", "Wolfgang Rathmann", "Ursula Krämer", "Dorothea Sugiri", "Matthias Grabert", "Reinhard W. Holl"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0091639.t001", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Characteristics_of_participants_with_type_2_diabetes_/957636", "title"=>"Characteristics of participants with type 2 diabetes<sup>*</sup>.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-03-11 02:44:08"}

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Relative Metric

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