Residential black carbon exposure and circulating markers of systemic inflammation in elderly males: the Normative Aging Study.BACKGROUND: Traffic-related particles (TRPs) are associated with adverse cardiovascular events. 'The exact mechanisms are unclear, but systemic inflammatory responses likely play a role.
OBJECTIVES: We conducted a repeated measures study among male participants of the Normative Aging Study in the greater Boston, Massachusetts “Boston” redirects here. For other uses, see Boston (disambiguation).
Boston is the capital and most populous city of Massachusetts. The largest city in New England, Boston is considered the unofficial economic and cultural center of the entire New , area to determine whether individual-level residential black carbon (BC), a marker of TRPs, is associated with systemic inflammation and whether coronary heart disease coronary heart disease: see coronary artery disease.
coronary heart disease
or ischemic heart disease
Progressive reduction of blood supply to the heart muscle due to narrowing or blocking of a coronary artery (see atherosclerosis). (CHD CHD coronary heart disease.
Latin Chirurgiae Doctor (Doctor of Surgery)
n.pr See disease, coronary heart.
canine hip dysplasia. ), diabetes, and obesity modify associations.
METHODS: We quantified markers of inflammation in 1,163 serum samples from 580 men. Exposure to BC up to 4 weeks prior was predicted from a validated spatiotemporal spa·ti·o·tem·po·ral
1. Of, relating to, or existing in both space and time.
2. Of or relating to space-time.
[Latin spatium, space + temporal1. land-use regression model. Linear mixed effects models estimated the effects of BC on each marker while adjusting for potential confounders.
RESULTS: Associations between BC and blood markers were not observed in main effects models or when stratified stratified /strat·i·fied/ (strat´i-fid) formed or arranged in layers.
Arranged in the form of layers or strata. by obesity status. However, BC was positively associated with markers of inflammation in men with CHD (particularly vascular endothelial growth factor Vascular endothelial growth factor (VEGF) is an important signaling protein involved in both vasculogenesis (the de novo formation of the embryonic circulatory system) and angiogenesis (the growth of blood vessels from pre-existing vasculature). ) and in men with diabetes (particularly interlettkin-1[beta] and tumor necrosis tumor necrosis Death of tumor tissue, a common event in aggressive CAs in which the tumor rapidly outgrows its blood supply, resulting in tumor cell death. Cf Apoptosis. factor-[alpha]). Significant exposure time windows varied by marker, although in general the strongest associations were observed with moving averages of 2-7 days after a lag of several days.
CONCLUSIONS: In an elderly male population, estimated BC exposures were positively associated with markers of systemic inflammation but only in men with CHD or diabetes.
KEY WORDS: air pollution, black carbon, cardiovascular disease Cardiovascular disease
Disease that affects the heart and blood vessels.
Mentioned in: Lipoproteins Test
cardiovascular disease , coronary heart disease, diabetes, inflammation, land-use regression model, particulate matter particulate matter
n. Abbr. PM
Material suspended in the air in the form of minute solid particles or liquid droplets, especially when considered as an atmospheric pollutant.
Noun 1. , susceptible, traffic. Environ Health Perspect 120:674-680 (2012). http://dx.doi.org/10.1289/ehp.1103982 [Online 15 February 2012]
Particulate matter (PM) air pollution, especially from combustion sources, is associated with adverse cardiovascular outcomes (Brook 2008; Mills et al. 2009). Identifying source-specific PM health effects is of practical concern for prevention efforts, and traffic-related particles (TRPs) have been of special interest. Short-term transient exposure to TRPs has been associated with increased daily mortality (Laden et al. 2000), acute myocardial infarction acute myocardial infarction (·kyōōtˑ mī·ō·karˑ·dē· (Lanki et al. 2006; Peters et al. 2004; Zanobetti and Schwartz 2006), and high blood pressure (Delfino et al. 2010). Several of these studies suggest greater toxicity associated with TRP Trp tryptophan.
tryptophan. exposure than with other sources of PM (Laden et al. 2000; Peters et al. 2004; Zanobetti and Schwartz 2006). Furthermore, studies of intermediate cardiovascular health effects also suggest greater toxicity associated with TRPs, as indicated by stronger inflammatory, coagulatory, and cardiac autonomic nervous system autonomic nervous system: see nervous system.
autonomic nervous system
Part of the nervous system that is not under conscious control and that regulates the internal organs. It includes the sympathetic, parasympathetic, and enteric nervous systems. responses (Park et al. 2008; Schwartz et al. 2005; Zeka et al. 2006).
Although the exact biological mechanisms by which TRPs exert effects on the cardio-vascular system are still unclear, there is strong evidence that inflammation is involved in the pathophysiological responses to PM inhalation (Brook et al. 2003; Donaldson et al. 2001; Pope and Dockery 2006). In studies of TRP exposures, associations with inflammatory markers have been observed in the elderly (Zeka et al. 2006), individuals with diabetes (O'Neill et al. 2007), young healthy male highway patrol highway patrol
A state law enforcement organization whose police officers patrol the public highways. troopers (Riediker et al. 2004), and elderly individuals with coronary artery disease coronary artery disease, condition that results when the coronary arteries are narrowed or occluded, most commonly by atherosclerotic deposits of fibrous and fatty tissue. (Delfino et al. 2009). Furthermore, studies suggest that individuals with diabetes and coronary heart disease (CHD), diseases associated with systemic inflammation, are likely to be more susceptible to systemic inflammation in response to PM exposure (Delfino et al. 2008; Dubowsky et al. 2006; Rioux et al. 2010).
TRPs are generally a mixture of tailpipe tail·pipe
The pipe through which exhaust gases from an engine are discharged. Also called exhaust pipe.
a pipe from which exhaust gases are discharged, esp. emissions of combustion PM, tire-and break-wear PM, and mineral PM from road pavement abrasion. Black carbon (BC), a specific component of [PM.sub.2.5] (PM with aerodynamic diameter Drug particles for pulmonary delivery are typically characterized by aerodynamic diameter rather than geometric diameter. The velocity at which the drug settles is proportional to the aerodynamic diameter, da. [less than or equal to] 2.5 [micro]m) resulting from incomplete combustion, is a widely used surrogate of TRPs (Janssen et al. 2011). Although other sources may contribute to BC, few sources other than traffic contribute to BC in the Boston area where this study was conducted (Gryparis et al. 2007).
The present study was designed to investigate the relationship between short-term exposure to modeled residential concentrations of BC and markers of systemic inflammation in a group of elderly males with and without chronic health conditions and to determine whether CHD, diabetes, and obesity modify associations between BC and markers of inflammation. Exposure to BC was estimated from a validated land-use regression model that incorporated temporal effects and space-time interactions and was assigned at the individual level (Gryparis et al. 2007). Circulating markers of systemic inflammation were the pro-inflammatory cytokines interleukin interleukin
Any of a class of naturally occurring proteins important in regulation of lymphocyte function. Several known types are recognized as crucial constituents of the body's immune system (see immunity). (IL)-1[beta], IL-6, IL-8, tumor necrosis factor-[alpha] (TNF-[alpha]), and vascular endothelial growth factor (VEGF VEGF vascular endothelial growth factor. ), as well as the soluble TNF TNF
tumor necrosis factor
n an abbreviation for tumor
f receptor-2 (sTNF-RII) and the acute-phase protein C-reactive protein (CRP C-reactive protein (CRP)
A protein present in blood serum in various abnormal states, like inflammation.
Mentioned in: Pelvic Inflammatory Disease
n.pr See C-reactive protein. ). These markers, associated with CHD and other inflammatory-related diseases to varying degrees, are commonly assessed in air pollution studies and were chosen to reflect both early and later acute phase systemic inflammatory responses, providing a more comprehensive understanding of the exposure-elicited biological mechanisms. We investigated changes in these markers with respect to exposure from 1 day up to 4 weeks.
Materials and Methods
Study population. The study population consisted of a subset of participants from the Normative Aging Study, a community-based longitudinal study longitudinal study
a chronological study in epidemiology which attempts to establish a relationship between an antecedent cause and a subsequent effect. See also cohort study. of aging among 2,280 men from the greater Boston, Massachusetts, area (21-81 years of age at study entry) that was initiated in 1963 by the U.S Veterans Affairs Veterans Affairs is a term of the business that deals with the relation between a government and its veteran communities, usually administered by the designated government agency. Outpatient Clinic in Boston (Bell et al. 1966). Participants were free of known medical conditions See carpal tunnel syndrome, computer vision syndrome, dry eyes and deep vein thrombosis. at enrollment and were asked to visit the clinic every 3-5 years for a detailed examination, including a routine physical examination, laboratory tests, collection of medical history and social status information, and administration of questionnaires on medication use, smoking history, alcohol consumption, food intake, and other factors that may influence health. Participants visited the study center in the morning after an overnight fast and abstinence from smoking. Men were classified as having CHD based on a physician diagnosis of nonfatal myocardial infarction myocardial infarction: see under infarction. or angina pectoris [International Classification of Diseases, 8th revision (World Health Organization 1967) codes 410-414] and were classified as having diabetes based on a physician's diagnosis of diabetes mellitus diabetes mellitus
Disorder of insufficient production of or reduced sensitivity to insulin. Insulin, synthesized in the islets of Langerhans (see Langerhans, islets of), is necessary to metabolize glucose. In diabetes, blood sugar levels increase (hyperglycemia). and/or fasting blood glucose blood glucose Diabetology The principal sugar produced by the body from food–especially carbohydrates, but also from proteins and fats; glucose is the body's major source of energy, is transported to cells via the circulation and used by cells in the presence levels > 126 mg/dL. Obesity was defined as body mass index (BMI BMI body mass index.
body mass index
Body mass index (BMI)
A measurement that has replaced weight as the preferred determinant of obesity. ) [greater than or equal to]30 kg/[m.sup.2]. Follow-up has been excellent, with loss of c 1% of subjects per year, primarily because of death (n = 728) or moving out of the region. A total of 580 Massachusetts residents with archived serum samples collected between 2000 and 2008 were included in the present study. All participants provided written informed consent before study procedures. The present study protocol was approved by the Institutional Review Board of the Harvard School of Public Health The Harvard School of Public Health is (colloquially, HSPH) is one of the professional graduate schools of Harvard University. Located in Longwood Area of the Boston, Massachusetts neighborhood of Mission Hill, next to Harvard Medical School and Cambridge, Massachusetts, .
Exposure assessment. Individual-level estimates of residential BC concentrations were predicted from a validated spatiotemporal land-use regression model. Details of this model are presented elsewhere (Gryparis et al. 2007; Suglia et al. 2008). In brief, BC was measured using an aethalometer at more than 80 locations in the greater Boston area, of which three-quarters were residential; the rest were commercial or government facilities. These measurements were used to calibrate To adjust or bring into balance. Scanners, CRTs and similar peripherals may require periodic adjustment. Unlike digital devices, the electronic components within these analog devices may change from their original specification. See color calibration and tweak. a model predicting concentrations based on BC measurements at a central location (to capture regional day effects), land-use terms (e.g., traffic density, open space) at each of the calibration monitors, weather parameters, height of the planetary boundary layer The planetary boundary layer (PBL), also known as the atmospheric boundary layer (ABL) or peplosphere, is the lowest part of the atmosphere and its behavior is directly influenced by its contact with a planetary surface. , and interactions of these parameters. Penalized splines were used to capture nonlinearities in dependence, and thin plate splines of latitude and longitude latitude and longitude
Coordinate system by which the position or location of any place on the Earth's surface can be determined and described. Latitude is a measurement of location north or south of the Equator. were used to capture remaining spatial variability. The exposure model predicted 24-hr measures of BC. Daily BC measurements, presented as micrograms per cubic meter, were lagged up to 1 week and averaged up to 4 weeks before the visit date.
Collection and analysis of blood samples. Study staff collected blood samples by venous puncture in the morning after over-night fast at each study visit. We quantified serum marker levels in-house using multiplexing technology (MILLIPLEX[TM]MAP) with commercially available MILLIPLE[TM] MAP kits (EMD EMD Electromechanical dissociation, see there Millipore, Billerica, MA, USA). In brief, the technology uses color-coded microspheres (beads) that are each coated with a specific capture antibody. A small amount of serum sample (25 [micro]L) is added, and the analyte is captured onto the bead. Circulating cytokines IL-[beta], TNF-[alpha], IL-8, VEGF, and sTNF-RII were assayed from serum (MILLIPLEX Human Cytokine/Chemokine; EMD Millipore) and quantified using the Luminex[R] 200[TM] System multiplex detection system (Luminex Corporation, Austin, TX, USA). We monitored the performance of the assays with standard quality control procedures, including analysis of blinded pooled samples. Values for which the percent recovery of the standards was < 70% or > 130% were excluded from analysis. This led to the exclusion of 260 (22%) VEGF values. All data were normalized for interbatch variation.
Serum high-sensitivity CRP was measured at the reference laboratory at Children's Hospital, Boston, using the immunoturbidimetric assay on the Hitachi 917 analyzer (Roche Diagnostics, Indianapolis, IN, USA) with reagents and calibrators from DenkaSeiken (Niigata, Japan). To control for acute inflammation acute inflammation
Inflammation having a rapid onset and coming to a crisis relatively quickly, with a clear and distinct termination. or infection, any observations for which CRP was [greater than or equal to] 10 mg/L were excluded from analysis (n = 54) (Pearson et al. 2003).
Statistical analysis. Linear mixed effects models with random intercepts, which account for the correlation of repeated measures, were used to estimate the association between exposure to BC and the biomarkers of interest. Outcome data were natural log transformed to improve the normality of the residuals. For each biomarker, associations with daily BC in the 24 hr preceding the blood draw--lagged up to 7 days and averaged over periods ranging from 1 day to 4 weeks--were investigated in separate models. Based on associations with individual lags, we also assessed associations with lagged moving averages. An unstructured covariance matrix was chosen as the working covariance Covariance
A measure of the degree to which returns on two risky assets move in tandem. A positive covariance means that asset returns move together. A negative covariance means returns vary inversely. structure because it provided the lowest Alcaike information criterion. A priori-selected potential confounders (classified at each visit) included in the models were the continuous variables of age, pack-years of cigarettes smoked, fasting blood glucose level blood glucose level,
n level of glu-cose in the bloodstream, normally about 70 to 115 mg/dL after fasting overnight. Higher levels may indicate diseases such as diabetes mellitus. , BMI, and apparent temperature for the 24 hr before the clinic visit (measured at Logan Airport) and the categorical variables of alcohol consumption (> 2 vs. < 2 drinks/day), calendar year, season, and medication use (antihypertensives, statins, and/or nonsteroidal anti-inflammatory drugs Nonsteroidal Anti-Inflammatory Drugs Definition
Nonsteroidal anti-inflammatory drugs are medicines that relieve pain, swelling, stiffness, and inflammation. ). We estimated the percent change and 95% confidence intervals (Cls) in each blood marker for an increase in the exposure equal to the average interquartile range (IQR IQR Interquartile Range (statistics)
IQR Internet Quick Reference
IQR Individual Qualification Record
IQR Internal Quality Review ) of the BC exposure window concentrations (0.36 [micro]g/[m.sup.3]). To assess potential differences between those with repeat visits and only one visit, we conducted a sensitivity analysis restricting the main effects models to those with repeated observations only.
To evaluate effect modification effect modification Epidemiology An interaction among multiple possible cause-and-effect relationships, where the estimate of the effect of one factor on a disease process depends on other factors in the study by CHD, diabetes, and obesity, separate models were constructed including interaction terms between each condition and the BC exposure metric. The general form of the model was
where, for the ith individual at the jth measurement occasion, BC is the continuous moving average or daily lag, CHD = 1 for presence of CHD and 0 otherwise, BC x CHD is the cross-product between exposure and CHD status, Z is a vector of covariates, and [b.sub.oi] is a random intercept for the ith individual.
Residual plots and the distributions of error terms were assessed to check the normality of the residuals and adequacy of model fits. Statistical significance for all testing was considered at the a = 0.05 level. Analyses were performed with. SAS (1) (SAS Institute Inc., Cary, NC, www.sas.com) A software company that specializes in data warehousing and decision support software based on the SAS System. Founded in 1976, SAS is one of the world's largest privately held software companies. See SAS System. (version 9.2; SAS Institute Inc., Cary, NC, USA).
total of 580 males were included in the analysis (Table 1). At the first study visit starting in 2000, the average age was 73 years (range, 57-100 years); 4% were current smokers, and 67% were former smokers. Blood samples were collected one to four times for each participant (median = 2) for a total of 1,163 measurements. At first visit, 175 participants (30%) had CHD, 107 (18%) had diabetes, and 153 (26%) were obese. Over the course of the study, an additional 38 developed CHD, 31 developed diabetes, and 26 became obese. The median estimated 24-hr residential BC concentration before the baseline clinic visit was 0.39 [micro]g/[m.sup.3] (range, 0.01-3.84 [micro]g/[m.sup.3]). Spearman spear·man
A man, especially a soldier, armed with a spear. rank correlation coefficients ([r.sub.S]) showed weak (rs c 0.30) to moderate ([r.sub.S] = 0.30-0.70) correlations among the blood markers, with the exception of IL-6 and IL-8 ([r.sub.S]= 0.71), VEGF and 1L-8 ([r.sub.S]= 0.77), and VEGF and IL-6 ([r.sub.S]= 0.74; Table 2). CRP was weakly correlated with all blood markers. Similar correlation patterns were observed across subpopulations by health condition (data not shown), although correlations were slightly stronger between some markers among men with diabetes (TNF-[alpha] and IL-1[beta], [r.sub.S]=0.53; TNF-[alpha] and IL-6, [r.sub.S]=0.62; VEGF and IL-1[beta], [r.sub.S]=0.50) and obesity (VEGF and IL--[beta], [r.sub.S]=0.57).
Results from univariate and multivariable main effects models were similar, and thus only selected. results from multivariable models are presented (Table 3). In the main effects models, we did not observe consistent patterns of association between the blood markers and estimated daily BC averaged over periods of up to 4 weeks [see Supplemental Material, Table 1 (http://dx.doi.org/10.1289/ehp.110.982)] or single-day BC lagged up to 7 days (Table 3). In general, effect estimates were close to the null without consistent direction, and CIs widely overlapped zero. In a sensitivity analysis, we restricted. the main effects models to those with repeated observations (n = 425), finding that overall patterns and magnitudes of the effect estimates were similar (data not shown),
Table 1. Characteristics of male study participants at first study visit (n=580) Characteristic Value Race White 557(96.0) Black 13(2.2) Hispanic white 2(0.3) Unknown 8(1.4) Smoking status Current 23(4.0) Former 391(67.4) Never 166(28.6) Alcohol consumption (>2 drinks/day) 102(17.6) Physician-diagnosed medical conditions CHD 175(30.2) Diabetes or fasting blood glucose>126 mg/dL 107(18.4) Medication use Antihypertensive medications 361(62.2) Statins 240(41.4) Nonsteroidal anti-inflammatory drugs 346(59.7) Age (years) [(mean (range)] 73(57-100) RMI (kg/[m.sup.2]) (mean[+or-]SD) 28.3[+or-]4.2 Obese ([greater than or equal 153(26.4) to]30kg/[m.sup.2] Not obese (<30kg/[m.sup.2]) 427(73.6) Pack-years among ever smokers [median 29.9(<1-131) (range)] Intiammaton, marker levels median (25th-75th percentile)] IL-1[beta](pg/mL) 2.6(1.2-13.8) IL-6 (pg/mL) 31.3(5.3-169.4) IL-8 (pg/mL) 45.7(23.8-94.8) VEGF (pg/mL; n=451) 836.0(267.5-1376.1) TNF-[alpha](pg/mL) 15.2(7.2-39.9) sTNF-RII (ng/mL) 5.6(4.4-7.0) CRP (mg/L; n=536) 1.6(0.8-3 2) Values are n (%) unless otherwise specified. Table 2. Spearman rank correlations between inflammatory makers at baseline [[r.sub.s](p-value)]. Marker IL-6 IL-8 TNF-[alpha] IL-1[beta] 0.55(<0.0001) 0.53(<0.0001) 0.44(<0.0001) IL-6 0.71(<0.0001) 0.54(<0.0001) IL-8 0.52(<0.0001) TNF-[alpha] VEGF sTNF-RII Marker VEGF sTNF-RII CRP IL-1[beta] 0.46(<0.0001) 0.07(0.11) 0.02(0.69) IL-6 0.74(<0.0001) 0.14(0.001) 0.03(0.51) IL-8 0.77(<0.0001) 0.20(<0.0001) 0.04(0.41) TNF-[alpha] 0.48(<0.0001) 0.17(<0.0001) 0.09(0.04) VEGF 0.18(<0.0001) -0.02(0.73) sTNF-RII 0.19(<0.0001) Table 3. Percent change in blood marker per IQR (0.36 [micro]g/[m.sup.3]) increase in BC. Marker/single-day exposure lag Change [% (95% C1)] p-Value IL-1[beta] Lag 0 -2.2(-8.2, 4.2) 0.48 Lag 1 -3.0(-9.5, 4.0) 0.40 Lag 3 -7.2(-15.6, 2.1) 0.12 Lag 4 -2.4(-9.5, 5.3) 0.53 Lag 5 -3.5(-10.3, 3.8) 0.34 IL-6 Lag 0 -1.0(-9.1. 7.8) 0.82 Lag 1 -3.8(-11.7, 4.7) 0.37 Lag 3 6.8(-4.4, 18.5) 0.25 Lag 4 1.8(-6.1, 10.4) 0.66 Lag 5 -0.1(-7.5, 7.9) 0.97 IL-8 Lag 0 1.0(-3.3, 5.4) 0.66 Lag 1 -1.0(-4.8, 3.0) 0.62 Lag 3 -2.0(-7.4, 3.6) 0.47 Lag 4 -0.1(-4.1, 4.1) 0.97 Lag 5 1.0(-2.7, 4.9) 0.59 VEGF Lag 0 3.3(-2.7, 9.6) 0.29 Lag 1 -0.1(-6.1, 6.2) 0.96 Lag 3 0.4(-6.2, 7.5) 0 90 Lag 4 0.8(-4.5, 6.4) 0.78 Lag 5 2.6(-2.4. 7.9) 0.32 TNF-[alpha] Lag 0 -0.9(-5.4, 3.8) 0.70 Lag 1 -1.2(-5.8, 3.7) 0.63 Lag 3 -0.4(-7.0, 6.7) 0.91 Lag 4 1.9(-3.0, 7.0) 0.46 Lag 5 0.9(-3.5, 5.6) 0.68 sTNF-RII Lag 0 0.2(-1.8, 2.3) 0.82 Lag 1 -0.3(-2.5, 1.9) 0.76 Lag 3 -0.1(-2.7, 2.7) 0.97 Lag 4 0.8(-1.4, 3.0) 0.50 Lag 5 0.9(-1.2, 3.0) 0.39 CRP Lag 0 -0.4(-5.3, 4.7) 0.87 Lag 1 4.8(-0.7, 10.6) 0.09 Lag 3 -1.2(-7.8, 6.0) 0.74 Lag 4 -2.7(-8.1, 3.1) 0.35 Lag 5 -3.1(-7.5, 1.5) 0.18 Models were adjusted for age, BMI, calendar year, pack-years, medication use, season, fasting glucose level, alcohol consumption, and apparent temperature.
Effect modification by CHD, diabetes mellitus, and obesity. In models investigating modification by CHD status (interaction p-value, < 0.01 to 0.99), stratum-specific effect estimates were generally null for those without CHD, whereas among those with CHD over the study period (total n = 213), IL-6, VEGF, and TNF-[alpha] increased with BC at later lags [e.g., IL-6 increased 25.6% at lag 4 (95% CI: 7.2, 47.1; interaction p-value < 0.01), VEGF increased 10.2% at lag 5 (95% CI: 0.2, 21.8; interaction p-value = 0.12), and TNF-[alpha] increased 13.2% at lag 4 (95% CI: 1.9, 25.8; interaction p-value = 0.02)] but not with earlier lags (Table 4). No associations were observed with the unlagged moving averages [see Supplemental Material, Table 2 (http://dx.dokorg/10.1289/ehp.1103982)]. Associations with lagged exposures continued to be observed when exposures were averaged over a period of up to 1 week for IL-6 (lag 4, 7-day moving average; 24.9%; 95% CI: 2.3, 52.6; interaction p-value = 0.04) and VEGF (lag 5, 6-day moving average; 22.6%; 95% CI: 8.0, 39.2; interaction p-value = 0.02) but not for TNF-[alpha]. (Figure 1; see also Supplemental Material, Table 4). Restricting analyses to those with CHD only (i.e., without diabetes, total n = 155) resulted in attenuated effect estimates (Figure 1).
When stratified by diabetes status (interaction p-value, < 0.001 to 0.99), associations for those without diabetes were also generally null, with the exception of significant inverse associations with nearly all exposure windows for IL-[beta](Table 5). Among those with diabetes over the study period (total n = 138), significant positive associations were observed with nearly all exposure windows for IL-1[beta] and with later daily lags for 1L-6, IL-8, and TNE-[alpha] [e.g., IL-6 increased 55.1% at lag 3 (95% CI 16.7, 106.3; interaction p-value < 0.01), and IL-8 increased 19.9% at lag 4 (95% CI: 5.3, 36.4; interaction p-value < 0.01), and TNF-[alpha] increased 17.7% at lag 3 (95% CI: 0.3, 38.1; interaction p-value = 0.14)]. IL-6 was also associated with unlagged moving average exposures starting at 5 days [see Supplemental Material, Table 3 (http://dx.doi.org/10.1289/ehp.1103982)]. We also observed a consistent pattern of positive associations with these markers for longer exposure windows for lag 3 (IL-6, TNF-[alpha]) and lag 4 (IL-8; Figure 2). After excluding those with CHD (n = 71), a smaller range of exposure windows were significantly associated with IL-1[beta], although point estimates were similar. For IL-6, estimated effects were attenuated (Figure 2; see also Supplemental Material, Table 5). Effect estimates remained similar for IL-8 and TNF-[alpha].
We also estimated associations among those with both CHD and diabetes (n = 76), finding that for IL-6 and IL-8, associations with BC were stronger than those for either condition alone (Figure 2). We did not assess the effect of obesity in addition to CHD and diabetes because few observations (< 3%) were characterized by the presence of all three conditions.
Using individual-level exposure estimates of BC in a relatively large panel of elderly males with repeated measurements, the results of this study suggest that estimated BC exposures are associated with increases in markers of systemic inflammation, but only in individuals with CHD, diabetes, or both CHD and diabetes. Our findings also suggest that the effects of exposure may occur after a lag period of days and may be observed with daily exposures averaged up to 7 days. We did not observe associations in the cohort as a whole.
Table 4. Percent change in blood marker per IQR (0.36 [micro]g/[m.sup.3]) increase in daily BC by CHD status. Marker/single-day Without CHD exposure lag Change [% (95% CI)] p-value IL-1[beta] Lag 0 -4.1(-11.8, 4.3) 0.33 Lag 1 -7.0(-15.1, 1.9) 0.12 Lag 3 -8.2(-18.1, 3.0) 0.14 Lag 4 -4.0(-11.5, 4.2) 0.33 Lag 5 -5.3(-12.1, 1.9) 0.15 IL-6 Lag 0 1.1(-8.2, 11.4) 0.83 Lag 1 -5.9(-16.3, 5.8) 0.31 Lag 3 2.1(-9.9, 15.7) 0.74 Lag 4 -4.2(-12.5, 4.9) 0.36 Lag 5 -3.4(-11.3, 5.3) 0.43 IL-8 Lag 0 2.7(-2.0, 7.7) 0.27 Lag 1 -1.7(-6.4, 3.2) 0.49 Lag 3 -2.0(-7.6, 4.1) 0.51 Lag 4 -1.4(-5.4, 2.9) 0.53 Lag 5 -0.3(-4.3, 3.8) 0.88 VEGF Lag 0 4.1(-2.9, 11.6) 0.26 Lag 1 0.4(-7.1, 8.6) 0.91 Lag 3 1.2(-6.5, 9.6) 0.76 Lag 4 -0.5(-6.2, 5.5) 0.86 Lag 5 0.8(-4.7, 6.7) 0.77 TNF-[alpha] Lag 0 0.7(-5.0, 6.7) 0.82 Lag 1 -1.5(-7.5, 4.8) 0.63 Lag 3 -0.7(-8.7, 8.1) 0.87 Lag 4 -1.3(-6.2. 3.8) 0.60 Lag 5 -1.6(-5.9, 3.0) 0.50 s-INF-RII Lag 0 1.2(-1.2, 3.6) 0.32 Lag 1 0.5(-2.1, 3.1) 0.72 Lag 3 0.5(-2.7, 3.7) 0.77 Lag 4 1.3(-1.2, 3.9) 0.32 Lag 5 1.7(-0.6, 4.0) 0.15 CRP Lag 0 -1.5(-7.3, 4.6) 0.62 Lag 1 3.5(-3.5, 10.9) 0.34 Lag 3 -0.9(-8.7. 7.5) 0.82 Lag 4 -4.2(-10.5, 2.7) 0.22 Lag 5 -2.8(-7.9, 2.5) 0.30 Marker/single-day With CHD Interaction exposure lag Change [%(95% CI)] p-Value p-value IL-1[beta] Lag 0 1.5(-6.6, 10.3) 0.73 0.34 Lag 1 3.1(-7.3, 14.7) 0.58 0.14 Lag 3 -4.9(-17.8, 10.0) 0.50 0.70 Lag 4 3.9(-11.7, 22.3) 0.64 0.39 Lag 5 3.6(-10.9, 20.4) 0.65 0 28 IL-6 Lag 0 -4.9(-18.1, 10.3) 0.50 0.48 Lag 1 -1.0(-11.9, 11.3) 0.87 0.54 Lag 3 16.3(-2.3, 38.5) 0.09 0.22 Lag 4 25.6(7.2, 47.1) <0.01 <0.01 Lag 5 12.7(-4.0. 32.4) 0.14 0.09 IL-8 Lag 0 -2.3 (-9.1, 4.9) 0.52 0.23 Lag 1 0.1(-5.8, 6.3) 0.98 0.64 Lag 3 -2.3 (-12.9, 9.6) 0.69 0.96 Lag 4 4.0(-6.2, 15.3) 0.45 0 34 Lag 5 6.1(-2.2, 15.0) 0.15 0.16 VEGF Lag 0 1.6(-8.4, 12.7) 0.76 0.70 Lag 1 -1.0(-9.9, 8.8) 0.83 0.81 Lag 3 -0.8(-12.9, 12.9) 0.90 0.79 Lag 4 5.2(-7.1, 19.1) 0.42 0.42 Lag 5 10.2(-0.2, 21.8) 0.05 0.12 TNF-[alpha] Lag 0 -4.0(-10.6, 3.2) 0.27 0.31 Lag 1 -0.7(-7.9, 7.1) 0.86 0.87 Lag 3 0.2(-10.2, 11.8) 0.97 0.90 Lag 4 13.2(1.9, 25.8) 0.02 0.02 Lag 5 10.9(1.0, 21.7) 0.03 0.02 s-INF-RII Lag 0 -1.5(-4.8, 1.9) 0.38 0.20 Lag 1 -1.4(-4.9, 2.2) 0.45 0.40 Lag 3 -1.2(-5.5, 3.3) 0.60 0.54 Lag 4 -0.8(-4.8, 3.4) 0.72 0.40 Lag 5 -1.5(-4.9, 2.1) 0.42 0.14 CRP Lag 0 1.5(-6.7, 10.4) 0.73 0.56 Lag 1 6.4(-2.0, 15.6) 0.14 0.60 Lag 3 -1.9(-13.8, 11.7) 0.78 0.90 Lag 4 2.1(-7.9, 13.2) 0.69 0.30 Lag 5 -4.3(-12.1, 4.2) 0.31 0.76 Models were adjusted for age, BMI, calendar year, pack-years, medication use, season, fasting glucose level, alcohol consumption, an dapparent temperature.
Among individuals with CHD, BC was associated with IL-6, VEGF, and TNF-[alpha]. However, VEGF, a growth factor related to angiogenesis angiogenesis /an·gio·gen·e·sis/ (-jen´e-sis) vasculogenesis; development of blood vessels either in the embryo or in the form of neovascularization or revascularization.
n. , was most consistently associated with BC after restricting analyses to those with CHD only (i.e., without diabetes) and using different lagged averaging periods. Exclusion of individuals with diabetes resulted in attenuated effect estimates for IL-6, VEGF, and TNF-[alpha], suggesting that some of the effects were attributable to individuals with diabetes. Specifically, 27% of those with CHD also had diabetes. IL-6 and VEGF are elevated in CHD and have been shown to predict CHD events (Cesari et al. 2003; Danesh et al. 2008; Eaton et al. 2008). Among men with CHD, these markers were increased in association with exposure after a 4-or 5-day lag, (i.e., exposure occurred 5 and 6 days before the date of visit), suggesting a delay in the production or release of these markers into the circulatory system circulatory system, group of organs that transport blood and the substances it carries to and from all parts of the body. The circulatory system can be considered as composed of two parts: the systemic circulation, which serves the body as a whole except for the . Alternatively, there may be a slow rise in the concentrations of these markers in the circulatory system beginning with early exposure and reaching the greatest concentration several days later. Although we do not know of previous investigations between BC and VEGF, previous studies have investigated associations between residential BC and IL-6 (Delfino et al. 2008, 2009). In these small panel studies of elderly Los Angeles area residents with CHD followed for 12 weeks, increases in IL-6 were observed with BC concentrations averaged over 24 hr and over 3 days. Further experimental and observational studies with extended measurements are needed to investigate the timing of responses.
Inflammatory markers were also associated with BC exposure among individuals with, diabetes in this study but over a wider range of exposure windows. Specifically, IL-1[beta], IL-6, IL-8, and TNF-[alpha] were associated with BC. Both IL-1[beta] and TNF-[alpha] appear to be regulators of PM-induced production and release of IL-6 and IL-8 (Herseth et al. 2008; Ishii et al. 2004; Jimenez et al. 2002), which suggests that associations for IL-1[beta] and TNF-[alpha] would precede those. This may help to explain why we observed associations between IL-1[beta] and BC averages starting on the same day and associations between BC and IL-8 and IL-6 starting at later lags, but this does not explain the apparent lag in the association with TNF-[alpha]. With the exclusion of those individuals with CHD, point estimates for IL-1[beta] and TNF-[alpha] were similar in the restricted and unrestricted analyses, suggesting that individuals with CHD did not account for these associations. Both IL-8 and TNF-[alpha] are elevated in individuals with diabetes and may be involved in its risk arid development (Duncan et al. 2003; Herder et al. 2005; P.lomgaard et al. 2007; Pradhan et al. 2001; Spranger et at. 2003). IL-1[beta] is produced by pancreatic [beta] cells, and it is thought that high glucose levels lead to the production of 13 cells, which in turn leads to the production and release of IL-1[beta] (Larsen et at 2007). Thus, for those with diabetes, exposure to BC may especially affect IL-1[beta], which in turn may play a role in the elaboration of additional cytokines. We also found inverse associations between IL-1[beta] and BC among individuals without diabetes, and it is unclear why increasing exposure would lead to decreasing IL-1[beta]. Further, we also found that the presence of both CHD and diabetes conferred the greatest sensitivity to BC-associated changes in IL-6 and IL-8. Further studies are needed to investigate the effects of multiple comorbidities on pollution-related health effects.
Table 5. Percent change in blood marker per IQR (0.36 [micro]g/[m.sup.3]) increase in darily BC by diabetes status. Marker/single-day Without diabetes exposure lag Change [% (95% CI)] p-Value IL-1[beta] Lag 0 -4.3(-10.4, 2.3) 0.20 Lag 1 -5.3(-11.6, 1.5) 0.12 Lag 3 -12.2(-20.3, -3.3) 0.01 Lag 4 -7.4(-13.9, -0.6) 0.03 Lag 5 -6.3(12 7, 0 6) 0.07 IL-6 Lag 0 -1.8(-10.2, 7.4) 0.69 Lag 1 -4.7(-12.9, 4.1) 0.28 Lag 3 -0.8(-11.4, 11.0) 0.88 Lag 4 -2.6(-10.1, 5.6) 0.52 Lag 5 -1.9(-9.6, 6.4) 0.64 IL-8 Lag 0 0.8(-3.5, 5.2) 0.73 Lag 1 -1.4(-5.1, 2.5) 0.48 lag 3 -4.7(-10.1, 1.0) 0.10 Lag 4 -2.7(-6.9, 1.7) 0.22 Lag 5 -0.1(-3.9, 3.8) 0.95 VEGF Lag 0 5.0(-1.2, 11.5) 0.12 Lag 1 1.5(-4.8, 8.1) 0.65 Lag 3 -2.1(-9.0, 5.3) 0.56 Lag 4 -0.6 (-6,1, 51) 0.82 Lag 5 2.4(-2.7, 1,7) 0.36 TNF-[alpha] Lag 0 -0.2(-4.9, 4.7) 0.93 Lag 1 -1.1(-6.0, 4.0) 0.66 Lag 3 -3.8(-10.5, 3.4) 0.30 Lag 4 -1.6(-6.1, 3.1) 0.49 Lag 5 0.4 -4.8 41) 0.87 sTNF-RII Lag 0 0.8(-1.3, 2.9) 0.47 Lag 1 0.4(-1.9, 2.8) 0.74 Lau 3 0.2(-2.7, 3.2) 0.88 Lag 4 0.7(-1.7, 3.2) 0.56 Lag 5 1.1(-1.1, 3.3) 0.34 CRP Lag 0 -1.0(-6.2, 4.5) 0.72 Lag 1 4.6(-1.3, 10.8) 0.13 Lag 3 -1.3(-8.5, 6.5) 0.74 Lag 4 1.8(-7 4, 4.2) 0.55 Lag 5 -3.4(-8.0, 1.3.0) 0.16 Marker/single-day With diabetes Interaction exposure lag Change [% (95% CI)] p-Value p-Value IL-1[beta] Lag 0 13.4(-5.5, 36.0) 0.18 0.08 Lag 1 17.0(1.0, 35,5) 0 04 0.01 Lag 3 27.4(0.9, 60.8) 0.04 <0.01 Lag 4 46.1(18.8. 79.6) <0.001 <0.001 Lag 5 25.1(6.4, 46.9) 0.01 <0.001 IL-6 Lag 0 6,9(-11.9, 29.8) 0.50 0.41 Lag 1 6.5(-12.8, 30.0) 0.54 0.31 Lag 3 55.1(16.1, 106.3) <0.01 <0.01 Lag 4 37.4(2.0. 85.0) 0.04 0.02 Lag 5 16.0(-6.9, 44.5) 0.19 0.15 IL-8 Lag 0 2.5(-9.4, 15.9) 0.70 0.79 Lag 1 2.3(-10.1, 16.5) 0.73 0.58 lag 3 13.4(-4.0, 34.1) 0.14 0.05 Lag 4 19.9(5.3, 36.4) 0.01 <0.01 Lag 5 11.4 (-0.3, 24.4) 0.06 0.06 VEGF Lag 0 -6.9(-18.9, 6.8) 0.30 0.53 Lag 1 -10.4(-24.1, 5.9) 0.20 0.69 Lag 3 15.3(-6.7, 42.6) 0.19 0.02 Lag 4 12.5 (-7.2, 36.5) 0.23 <0.001 Lag 5 4.1(-12.2, 23.5) 0.64 0.04 TNF-[alpha] Lag 0 -39(-14.2,76) 0.49 0.10 Lag 1 1.4(-9.9, 14.1) 0.82 016 Lag 3 17.7(0.3, 38.1) 0.05 0.14 Lag 4 27.8(10.0, 48.4) <0.01 0.22 Lag 5 12.4)04, 25.8 0.04 0.85 sTNF-RII Lag 0 -2.7(-6.9, 1.8) 0.23 0.15 Lag 1 -4.3(-9.3, 1.0) 0.11 0.10 Lau 3 -2.3(-7.6, 3.3) 0.42 0.42 Lag 4 0.7(-4.0, 5.6) 0.78 0 99 Lag 5 -0.3(-5.3, 5.0) 0.92 0.63 CRP Lag 0 3.0(-8.6, 16.2) 0.63 0 55 Lag 1 6.2(-6.0, 20.0) 0.34 0.82 Lag 3 -0.1(-15.3, 17.8) 0.99 0.90 Lag 4 -9.0(-21.9, 6.1) 0.23 0.36 Lag 5 -0.4(-14.5, 15.0) 0 96 0.70 Models were adjusted for age, BMI, calendar year, pack-years, medication use, season, fasting glucose level, alcohol consumption, an dapparent temperature.
Although studies have noted evidence of increased vulnerability of individuals with diabetes to various cardiac and systemic effects of PM air pollution, few studies have specifically reported associations between inflammatory markers and BC. In a study of individuals with diabetes in the Boston area, BC averaged over the previous 24 hr up to 6 days was found to be most strongly associated with increased levels of adhesion molecules involved in inflammation and endothelial endothelial /en·do·the·li·al/ (-the´le-al) pertaining to or made up of endothelium.
A layer of cells that lines the inside of certain body cavities, for example, blood vessels. function (soluble intercellular adhesion molecule-1 (sICAM-1) and soluble vascular adhesion molecule-1 (sVCAM-1)] (O'Neill et al. 2007), whereas null associations were observed with sulfate sulfate, chemical compound containing the sulfate (SO4) radical. Sulfates are salts or esters of sulfuric acid, H2SO4, formed by replacing one or both of the hydrogens with a metal (e.g., sodium) or a radical (e.g., ammonium or ethyl). PM, and weaker associations were found with [PM.sub.2.5]. Although our study did not investigate adhesion molecules, our present findings are consistent with these previous findings. In another study conducted in the Midwest among nonsmoking non·smok·ing
1. Not engaging in the smoking of tobacco: nonsmoking passengers.
2. Designated or reserved for nonsmokers: the nonsmoking section of a restaurant. elderly individuals with comorhidities including diabetes, IL-6 increased, although not significantly, with increasing 5-day average BC (Dubowsky et al. 2006), consistent with our findings for IL-6. However, contrary to our findings, CRP was positively associated with 5-day average BC in the Dubowsky et al. (2006) study. In our study, point estimates for CRP were in both directions and widely overlapped the null. Differences in the study population may explain these different findings because the Dubowsky et al. (2006) study population was primarily female, whereas ours was entirely male.
There are a number of strengths to this study. One is the use of individual-level predictions of BC concentrations from a validated spatiotemporal land-use regression model, which we considered to be a surrogate for primary traffic PM. Specifically, the spatial variability of BC on a given day reflected the-variability of traffic in the region and was the basis of the BC model developed and used for this study. Although nonresidential exposure to BC not captured in the prediction model may have introduced some exposure measurement error, we believe that this error is small compared with exposure misclassifica-tion introduced from the use of fixed ambient monitoring data, which is the traditional exposure assessment method in large air pollution studies. An additional strength of this study is the well-characterized study population and our ability to adjust for a number of potentially important between-and within-person confounders in our statistical models.
As with any epidemiological study, however, ours is not without limitations. One limitation of concern is the lack of information on copollutants. We did not examine other pollutants such as total [PM.sub.2.5] or [PM.sub.2.5] components other than BC in this study. Because the BC model is based largely on the daily spatial variation exhibited by BC, it is unlikely that total [PM.sub.2.5] or any other copollutant was responsible for the effects we observed for BC. Other components of [PM.sub.2.5] such as sulfates and organic PM, are more homogeneous over the study region. Further, although we cannot completely rule out confounding by a copollutant, the correlations between BC and PM2,5, carbon monoxide carbon monoxide, chemical compound, CO, a colorless, odorless, tasteless, extremely poisonous gas that is less dense than air under ordinary conditions. It is very slightly soluble in water and burns in air with a characteristic blue flame, producing carbon dioxide; , and nitrogen dioxide, which are related to traffic pollution, have been shown to be strong (Delfino et al. 2008; Ren et al. 2011), whereas the correlation between BC and sulfate, which is associated with coal-burning power plants, is weaker (Ren et al. 2011). Thus, even though some of the observed associations may be confounded by correlated exposures, it is likely that the potential confounding copollutants are traffic related as opposed to nonmobile. Further, we acknowledge that although BC was used as a surrogate of TRPs, the most toxic component of TRPs is still unknown, so BC may not fully represent the most toxic aspect of TRP exposure. It is also possible that some other sources have contributed to BC measurements in the area, but we expect this would add only a small amount of exposure misclassification. Finally, the findings from this study may not be generalizable to females, younger individuals, and nonwhite non·white
A person who is not white.
nonwhite adj. populations if the biological responses to BC differ in these populations.
We observed positive associations between markers of inflammation and residential BC among older men with CHD and diabetes. Such associations were not observed when observations from the entire cohort were included in the model. Whether exposure to BC is causally related to the development of CHD and diabetes is unclear. However, the results of this study support the conclusion that systemic inflammatory responses occur subsequent to BC exposure among those with CHD and diabetes.
Address correspondence to S.C. Fang, 665 Huntington Ave., Building 1, Room 1411, Boston, MA 02115 USA. Telephone: (617) 432-6460. Fax: (617) 432-6981. E-mail: email@example.com
Supplemental Material is available online (http://dx.doi.org/10.1289/ehp.1103982).
We thank K. Feng, M. Wang, E. Dibbs, T. Kotlov, and H. Guan guan: see curassow. .
This research was supported by National Institutes of Health grant 1R01 ES014663-01A2 and Harvard-National Institute for Occupational Safety and Health Education and Research Center Pilot Project grant T42 OH008416-04. The VA Normative Aging Study is supported by the Cooperative Studies Program/Epidemiology Research and Information Center (ERIC) of the Department of Veterans Affairs and is a component of the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC MAVERIC Marshall Aerospace Vehicle Representation In C (NASA)
MAVERIC Multilocation Audio/Visual Ethernet Relay Interface Computer ). S.C. Fang was supported by an award from the American Heart Association.
The authors declare they have no actual or potential competing financial interests.
Received 24 May 2011; accepted 15 February 2012.
Bell B, Rose CL, Damon A. 1966. The Veterans Administration longitudinal study of healthy aging. Gerontologist ger·on·tol·o·gy
The scientific study of the biological, psychological, and sociological phenomena associated with old age and aging.
Brook RD. 2008. Cardiovascular effects of air pollution. Clin Sci (Lond) 115(6):175-187.
Brook RD, Brook JR, Rajagopalan S. 2003. Air pollution: the "heart" of the problem. Curr Hypertens Rep 5(1):32-39.
Cesari M, Penninx BW, Newman AB, Kritchevsky SB, Nicklas BJ, Sutton-Tyrrell K, et al. 2003. Inflammatory markers and onset of cardiovascular events: results from the Health ABC study. Circulation 108(19):2317-2322.
Danesh J, Kaptoge S, Mann AG, Sarwar N, Wood A, Angleman SB, et al. 2008. Long-term interleukin-6 levels and subsequent risk of coronary heart disease: two new prospective studies and a systematic review. PLoS Med 5(4):e78; 10.1371/ journal.pmed.0050078 [Online 8 April 2008].
Delfino RJ, Staimer N, Tjoa T, Gillen DL, Polidori A, Arhami M, et al. 2009. Air pollution exposures and circulating biomarkers of effect in a susceptible population: clues to potential causal component mixtures and mechanisms. Environ Health Perspect 117:1232-1238.
Delfino RJ, Staimer N, Tjoa T, Polidori A, Arhami M, Gillen DL, et al, 2008. Circulating biomarkers of inflammation, antioxidant antioxidant, substance that prevents or slows the breakdown of another substance by oxygen. Synthetic and natural antioxidants are used to slow the deterioration of gasoline and rubber, and such antioxidants as vitamin C (ascorbic acid), butylated hydroxytoluene activity, and platelet activation are associated with primary combustion aerosols in subjects with coronary artery disease. Environ Health Perspect 116:898-906.
Delfino RJ, Tjoa T, Gillen DL, Staimer N, Polidori A, Arhami M, et al. 2010. Traffic-related air pollution and blood pressure in elderly subjects with coronary artery disease. Epidemiology 21(3):396-404.
Donaldson K, Stone V, Seaton A, MacNee W. 2001. Ambient particle inhalation and the cardiovascular system cardiovascular system: see circulatory system.
System of vessels that convey blood to and from tissues throughout the body, bringing nutrients and oxygen and removing wastes and carbon dioxide. : potential mechanisms. Environ Health Perspect 109(suppl 4):523-527.
Dubowsky SD, Suh H, Schwartz J, Coull BA, Gold DR. 2006. Diabetes, obesity, and hypertension may enhance associations between air pollution and markers of systemic inflammation. Environ Health Perspect 114:992-998.
Duncan BB, Schmidt MI, Pankow JS, Ballantyne CM, Cooper 0, Vigo A, et al. 2003. Low-grade systemic inflammation and the development of type 2 diabetes type 2 diabetes
See diabetes mellitus. : the atherosclerosis risk in communities study. Diabetes 52(7):1799-1805.
Eaton CB, Gramling Ft, Parker DR, Roberts MB, Lu B, Ridker PM. 2008. Prospective association of vascular endothelial growth factor-A (VEGF-A) with coronary heart disease mortality in southeastern New England. Atherosclerosis 200(1):221-227.
Gryparis A, Coull B, Schwartz J, Suh H. 2007. Semiparametric latent variable regression models for spatiotemporal modelling of mobile source particles in the greater Boston area. J R Stat Soc Ser C Appl Stat 56(2):183-209.
Herder C, Haastert B, Muller-Scholze S, Koenig W, Thorand B, Holle R, et al. 2005. Association of systemic chemokine chemokine /che·mo·kine/ (ke´mo-kin) any of a group of low molecular weight cytokines identified on the basis of their ability to induce chemotaxis or chemokinesis in leukocytes (or in particular populations of leukocytes) in inflammation. concentrations with impaired glucose tolerance Impaired Glucose Tolerance (IGT) is a pre-diabetic state of dysglycemia, that is associated with insulin resistance and increased risk of cardiovascular pathology. IGT may precede type 2 diabetes mellitus by many years. IGT is also a risk factor for mortality. and type 2 diabetes: results from the Cooperative Health Research in the Region of Augsburg Survey S4 (KORA S4). Diabetes 54(suppl 2): S11 S17.
Herseth J, Refsnes M, Lag M, Hetland G, Schwarze P. 2008. IL-1 beta as a determinant in silica-induced cytokine Cytokine
Any of a group of soluble proteins that are released by a cell to send messages which are delivered to the same cell (autocrine), an adjacent cell (paracrine), or a distant cell (endocrine). responses in monocyte-endothelial cell co-cultures. Hum Exp Toxicol 27(5):387-399.
Ishii H, Fujii T, Hogg JC, Hayashi S, Mukae H, Vincent Ft, et al. 2004. Contribution of IL-113 and TNF-ct to the initiation of the peripheral lung response to atmospheric particulates (PM10). Am J Physiol Lung Cell Mol Physiol 287(1):L176 L183.
Janssen NA, Hoek G, Simic-Lawson M, Fischer P, van Bree L, ten Brink H, et al. 2011. Black carbon as an additional indicator of the adverse health effects of airborne particles compared to PM10 and PM2s. Environ Health Perspect 119:1691-1699.
Jimenez LA, Drost EM, Gilmour PS, Rahman I, Antonicelli F, Ritchie H, et al. 2002. [PM.sub.10]-exposed macrophages stimulate a proinflammatory response in lung epithelial cells Epithelial cells
Cells that form a thin surface coating on the outside of a body structure.
Mentioned in: Corneal Transplantation via INF-[alpha]. Am J Physiol Lung Cell Mol Physiol 282(2):L237 L248.
Laden F, Neas LM, Dockery DW, Schwartz J. 2000. Association of fine particulate matter from different sources with daily mortality in six U.S. cities. Environ Health Perspect 108:941-947.
Lanki T, Pekkanen J, Aalto P, Elosua R, Berglind N, D'Ippoliti D, et al. 2006. Associations of traffic related air pollutants with hospitalisation for first acute myocardial infarction: the HEAPSS study. Occup Environ Med 63(12):844-851.
Larsen CM, Fa ulenbach M, Vaag A, Volund A, Ehses JA, Seifert B, et al. 2007. Interleukin-l receptor antagonist in type 2 diabetes mellitus Type 2 diabetes mellitus
One of the two major types of diabetes mellitus, characterized by late age of onset (30 years or older), insulin resistance, high levels of blood sugar, and little or no need for supple-mental insulin. . N Engl J Med 356(15)1517-1526.
Mills NL, Donaldson K, Hadoke PW, Boon NA, MacNee W, Cassee FR, et al. 2009. Adverse cardiovascular effects of air pollution. Nat Clin Pract Cardiovasc Med 6(1):36-44.
O'Neill MS, Veves A, Sarnat JA, Zanobetti A, Gold DR, Economides PA, et al. 2007. Air pollution and inflammation in type 2 diabetes: a mechanism for susceptibility. Occup Environ Med 64(6):373-379.
Park SK, O'Neill MS, Vokonas PS, Sparrow D, Spiro A III, Tucker KL, et al. 2008. Traffic-related particles are associated with elevated homocysteine Homocysteine Definition
Homocysteine is a naturally occurring amino acid found in blood plasma. High levels of homocysteine in the blood are believed to increase the chance of heart disease, stroke, Alzheimer's disease, and osteoporosis. : the VA normative aging study. Am J Resp Crit Care Med 178(3):283-289.
Pearson TA, Mensah GA, Alexander RW, Anderson JL, Cannon RO III, Criqui M, et al. 2003. Markers of inflammation and cardiovascular disease: application to clinical and public health practice: a statement for healthcare professionals from the Centers for Disease Control and Prevention Centers for Disease Control and Prevention (CDC), agency of the U.S. Public Health Service since 1973, with headquarters in Atlanta; it was established in 1946 as the Communicable Disease Center. and the American Heart Association. Circulation 107(3):499-511.
Peters A, von Klot S, Heier M, Trentinaglia I, Hermann A, Wichmann HE, et al. 2004. Exposure to traffic and the onset of myocardial infarction. N Engl J Med 351(17):1721-1730.
Plomgaard P, Nielsen AR, Fischer CP, Mortensen OH, Broholm C, Penkowa M, et al. 2007. Associations between insulin resistance Insulin Resistance Definition
Insulin resistance is not a disease as such but rather a state or condition in which a person's body tissues have a lowered level of response to insulin, a hormone secreted by the pancreas that helps to regulate the level and TNF-[alpha] in plasma, skeletal muscle and adipose tissue adipose tissue (ăd`əpōs'): see connective tissue.
or fatty tissue
Connective tissue consisting mainly of fat cells, specialized to synthesize and contain large globules of fat, within a in humans with and without type 2 diabetes. Diabetologia 50(12):2562-2571.
Pope CA Ill, Dockery DW. 2006. Health effects of fine particulate air pollution: lines that connect. J Air Waste Manag Assoc 56(6):709-742.
Pradhan AD, Manson JE, Rifai N, Suring JE, Ridker PM. 2001. C-reactive protein, interleukin 6, and risk of developing type 2 diabetes mellitus. JAMA 286(3):327-334.
Ren C, Fang S, Wright RO, Suh H, Schwartz J. 2011. Urinary 8-hydroxy-2'-deoxyguanosine as a biomarker of oxidative DNA DNA: see nucleic acid.
or deoxyribonucleic acid
One of two types of nucleic acid (the other is RNA); a complex organic compound found in all living cells and many viruses. It is the chemical substance of genes. damage induced by ambient pollution in the Normative Aging Study. Occup Environ Med 68:562-569.
Riediker M, Cascio WE, Griggs TR, Herbst MC, Bromberg PA, Neas L, et al. 2004. Particulate matter exposure in cars is associated with cardiovascular effects in healthy young men, Am J Resp Crit Care Med 169(8):934-940.
Rioux CL, Tucker KL, Mwamburi M, Cute DM, Cohen cohen
(Hebrew: “priest”) Jewish priest descended from Zadok (a descendant of Aaron), priest at the First Temple of Jerusalem. The biblical priesthood was hereditary and male. SA, Brugge D. 2010. Residential traffic exposure, pulse pressure pulse pressure
The variation in blood pressure occurring in an artery during the cardiac cycle; the difference between systolic and diastolic pressures. , and C-reactive protein: consistency and contrast among exposure characterization methods. Environ Health Perspect 118:803-811.
Schwartz J, Litonjua A, Suh H, Verrier M, Zanobetti A, Syring M, et al. 2005. Traffic related pollution and heart rate variability Heart rate variability (HRV) is a measure of variations in the heart rate. It is usually calculated by analysing the time series of beat-to-beat intervals from ECG or arterial pressure tracings. in a panel of elderly subjects. Thorax thorax, body division found in certain animals. In humans and other mammals it lies between the neck and abdomen and is also called the chest. The skeletal frame of the thorax is formed by the sternum (breastbone) and ribs in front and the dorsal vertebrae in back. 60(6):455-461.
Spranger J, Kroke A, Mohlig M, Hoffmann K, Bergmann MM, Ristow M, et al. 2003. Inflammatory cytokines and the risk to develop type 2 diabetes: results of the prospective population-based European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Study. Diabetes 52(3):812-817.
Suglia SF, Gryparis A, Wright RO, Schwartz J, Wright RJ. 2008. Association of black carbon with cognition among children in a prospective birth cohort study. Am J Epidemiol 167(31:280-286.
World Health Organization. 1967. ICD ICD International Classification of Diseases (of the World Health Organization); intrauterine contraceptive device.
abbr. 8th Revision, WHO Manual of the International Statistical Classification of Diseases. Geneva Geneva, canton and city, Switzerland
Geneva (jənē`və), Fr. Genève, canton (1990 pop. 373,019), 109 sq mi (282 sq km), SW Switzerland, surrounding the southwest tip of the Lake of Geneva. :World Health Organization.
Zanobetti A, Schwartz J. 2006. Air pollution and emergency admissions in Boston, MA. J Epidemiol Community Health 60(1 0):890-895.
Zeka A, Sullivan JR, Vokonas PS, Sparrow D, Schwartz J. 2006. Inflammatory markers and particulate air pollution: characterizing the pathway to disease. Int J Epidemiol 35(51:1347-1354.
Shona C. Fang, (1) Amar J Mehta, (1), (2), (3) Stacey E. Alexeeff, (1) Alexandros Gryparis, (4) Brent Coul1, (5) Pantel Vokonas, (6), (7) David C. Christiani,(1), (8) and Joel Schwartz (1)
(1.) Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts, USA; (2.) Chronic Disease Epidemiology Unit, Swiss Tropical and Public Health Institute, Basel, Switzerland; (3.) Department of Public Health, University of Basel The University of Basel (German: Universität Basel) is located at Basel, Switzerland. History
Founded in 1459, it is Switzerland's oldest university. , Basel, Switzerland; (4.) Department of Applied Mathematics, University of Crete The University was established in 1973 and started functioning in the academic year 1977-78. As a higher education institution, it is a legal person of public law, i.e. it operates under the supervision of the State. The seat of the University is in Rethymnon. , Crete, Greece; (5.) Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA; (6.) VA Normative Aging Study, Veterans Affairs Boston Healthcare System, Boston, Massachusetts, USA; (7.) Department of Medicine, Boston University School of Medicine Boston University School of Medicine (BUSM) is one of the graduate schools of Boston University. It is an American medical school located in the South End neighborhood of Boston, Massachusetts. , Boston, Massachusetts, USA; (8.) Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA