Science of the Total Environment 443 (2013) 397–402
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Long-term exposure to trafﬁc-related air pollution and the risk of death from hemorrhagic stroke and lung cancer in Shizuoka, Japan Takashi Yorifuji a,⁎, Saori Kashima b, Toshihide Tsuda a, Kazuko Ishikawa-Takata c, Toshiki Ohta d, Ken-ichi Tsuruta e, Hiroyuki Doi f a
Department of Human Ecology, Okayama University Graduate School of Environmental and Life Science, 1-1-1 Tsushima-naka, Kita-ku, Okayama 700-8530, Japan Department of Public Health and Health Policy, Hiroshima University, Institute of Biomedical & Health Sciences, 1-2-3 Kasumi, Minami-ku, Hiroshima 734-8551, Japan Department of Nutritional Education, National Institute of Health and Nutrition, 1-23-1 Toyama, Shinjuku-ku, Tokyo 162-836, Japan d Geriatric Health Services Facility Sakuranosato, 2-25 Nakaokazaki-cho, Okazaki, Aichi 444-0921, Japan e Director of Medical Policy, Shizuoka Prefecture, 9-6 Ohtemachi, Aoi-ku, Shizuoka 462-8601, Japan f Department of Epidemiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, 2-5-1 Shikata-cho, Kita-ku, Okayama 700-8558, Japan b c
H I G H L I G H T S ► We evaluated the effect of long-term exposure to air pollution and mortality. ► Air pollution increased the risk of cardiopulmonary and lung cancer mortality. ► Air pollution had adverse effects on intracerebral hemorrhage and ischemic stroke.
a r t i c l e
i n f o
Article history: Received 17 March 2012 Received in revised form 28 June 2012 Accepted 24 October 2012 Available online 30 November 2012 Keywords: Air pollution Environmental exposure Lung neoplasms Nitrogen dioxide Stroke
a b s t r a c t A number of studies have linked exposure to long-term outdoor air pollution with cardiopulmonary disease; however, the evidence for stroke is limited. Furthermore, evidence with the risk for lung cancer (LC) is still inconsistent. We, therefore, evaluated the association between long-term exposure to trafﬁc-related air pollution and cause-speciﬁc mortality. Individual data were extracted from participants of an ongoing cohort study in Shizuoka, Japan. A total of 14,001 elderly residents completed questionnaires and were followed from December 1999 to January 2009. Annual individual nitrogen dioxide (NO2) exposure data, as an index for trafﬁc-related exposure, were modeled using a Land Use Regression model and assigned to the participants. We then estimated the adjusted hazard ratios (HRs) and their conﬁdence intervals (CIs) associated with a 10 μg/m3 elevation in NO2 for all-cause or cause-speciﬁc mortality using time-varying Cox proportional hazards models. We found positive associations of NO2 levels with all-cause (HR=1.12, 95% CI: 1.07–1.18), cardiopulmonary disease (HR=1.22, 95% CI: 1.15– 1.30), and LC mortality (HR=1.20, 95% CI: 1.03–1.40). Among cardiopulmonary disease mortality, not only the risk for ischemic heart disease (HR=1.27, 95% CI: 1.11–1.47) but also the risks for stroke were elevated: intracerebral hemorrhage (HR=1.28, 95% CI: 1.05–1.57) and ischemic stroke (HR=1.20, 95% CI: 1.04–1.39). The present study supports the existing evidence that long-term exposure to trafﬁc-related air pollution increases the risk of cardiopulmonary as well as LC mortality, and provides additional evidence for adverse effects on intracerebral hemorrhage as well as ischemic stroke. © 2012 Elsevier B.V. All rights reserved.
1. Introduction A number of studies have linked exposure to acute or chronic outdoor air pollution with cardiopulmonary disease (Brook et al., 2010; Abbreviations: BMI, Body mass index; CI, conﬁdence interval; COPD, chronic obstructive pulmonary disease; GIS, Geographic Information System; HR, hazard ratio; ICD, International Classiﬁcation of Disease; IHD, ischemic heart disease; LC, lung cancer; LUR, Land Use Regression; NO2, nitrogen dioxide. ⁎ Corresponding author at: Department of Human Ecology, Okayama University Graduate School of Environmental and Life Science, 3-1-1 Tsushima-naka, Kita-ku, Okayama 700-8530, Japan. Tel./fax: +81 86 251 8925. E-mail address: [email protected]
(T. Yorifuji). 0048-9697/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.scitotenv.2012.10.088
Pope and Dockery, 2006). In particular, the existing evidence is strong for the effect on ischemic heart disease (IHD) (Brook et al., 2010; Pope and Dockery, 2006). Meanwhile, some studies have also linked levels of air pollutants with ischemic stroke; however, the ﬁndings for hemorrhagic stroke remain inconsistent. Indeed, several studies examined the effects of exposure to outdoor air pollution on stroke morbidity as well as mortality (Andersen et al., 2012; Andersen et al., 2010; Chan et al., 2006; Henrotin et al., 2007; Hong et al., 2002; Lipsett et al., 2011; Maheswaran and Elliott, 2003; Maheswaran et al., 2005; Maheswaran et al., 2012; Villeneuve et al., 2006; Wellenius et al., 2005; Yamazaki et al., 2007; Yorifuji et al., 2011). Most of the studies which examined the effect of acute exposure
T. Yorifuji et al. / Science of the Total Environment 443 (2013) 397–402
found only associations with ischemic but not hemorrhagic stroke (Andersen et al., 2010; Chan et al., 2006; Henrotin et al., 2007; Hong et al., 2002; Wellenius et al., 2005). A small number of studies which suggested an association with hemorrhagic stroke were conducted only in Asian countries (Tsai et al., 2003; Yamazaki et al., 2007; Yorifuji et al., 2011). In addition, several cohort studies suggested potential adverse effects on stroke or ischemic stroke (Andersen et al., 2012; Lipsett et al., 2011; Miller et al., 2007), although none of the studies provided ﬁndings on the associations with hemorrhagic one. Considering that air pollution may lead to endothelial dysfunction or vasoconstriction (hypertension) (Brook et al., 2010; Pope and Dockery, 2006), chronic exposure to air pollution may also raise the risk of hemorrhagic stroke and the effect could be detected in Asian countries, where incidence of this type of stroke is high (Kitamura et al., 2006). In addition, recent cohort studies demonstrated potential adverse effects on lung cancer (LC) (Krewski et al., 2009; Lepeule et al., 2012; Raaschou-Nielsen et al., 2011; Turner et al., 2011). However, evidence linking exposure to outdoor air pollution with the risk for LC is still limited, in particular in Asian countries. In our previous study, we suggested the risk only in non-smokers but not in current or former smokers, possibly due to the short follow-up (1999–2006) of the study (Yorifuji et al., 2010). In the present study, therefore, we extended the follow-up period through 2009 (total of nine years) and evaluated the association between long-term exposure to trafﬁc-related air pollution, indexed by nitrogen dioxide (NO2) levels, and cause-speciﬁc mortality, especially focusing on stroke and LC.
2. Materials and methods 2.1. Study area and participants Individual data were extracted from participants of an ongoing cohort study: the Shizuoka elderly cohort (Kubota et al., 2005). The Shizuoka prefecture is located in the approximate center of Japan and has an area of 7780 km2. It has a southern coastline facing the Paciﬁc Ocean and there are mountains exceeding 3000 m in altitude in the north (Kashima et al., 2009). In December 1999, 22,200 residents were randomly chosen from all 74 municipalities in Shizuoka, by stratifying both sex and age groups (65 to 74; 75 to 84). Then, questionnaires were distributed to the participants, resulting in responses from 14,001 residents (response rate: 63%). The self-completed questionnaire included age, sex, smoking habit (non-; ex-; and current smoker), body weight, height, current medical history (hypertension, diabetes mellitus, and so on), ﬁnancial capability, and other characteristics. Socioeconomic status was assessed by asking whether participants considered themselves to be ﬁnancially capable, with the possible answers being non-capable or capable. Participants were followed-up in December 2002, March 2006, and January 2009 using the same questionnaire. In the previous air pollution study (Yorifuji et al., 2010), we utilized the information until the third follow-up (in March 2006); in the present study, we then extended the follow-up period until January 2009. Because we modeled trafﬁc-related air pollution, indexed by NO2, using the participants' baseline residential information, we excluded 271 participants whose residential information was not available and 318 participants who moved during the study period. Therefore, we targeted 13,412 participants. As shown in Fig. 1, 1407 participants were lost to follow-up during December 1999 to 2002, 2345 participants were lost to follow-up during 2002 to March 2006, and 3888 participants were lost to follow-up during 2006 to January 2009. Finally, 1800 deaths were identiﬁed up to January 2009. In the analyses, we treated those who were lost to follow-up during 2002 to March 2006 (n =2345) as censored at December 2002 and those who were lost to follow-up during 2006 to January 2009 (n=3888) as censored at March 2006. Survivors at January 2009 were treated as being censored at the end of the study.
2.2. Exposure data To evaluate the health effects of trafﬁc-related exposure, indexed by NO2, we modeled annual individual NO2 exposure during April 1996 to March 2009 using a Land Use Regression (LUR) model. LUR models have been developed and utilized to model trafﬁc pollutants within the framework of a Geographic Information System (GIS) (Ryan and LeMasters, 2007). The details are described elsewhere (Kashima et al., 2009); however, we brieﬂy describe the modeling approach adopted. We constructed models which best predicted the monitored levels of annual NO2 using geographical variables. Annual exposure data (NO2) during April 1996 to March 2009 were available from the Environmental Database, managed by the National Institute for Environmental Studies in Japan. A ﬁscal year in Japan starts from April and the data availability depends on the ﬁscal year, we thus utilized the ﬁscal year as an annual basis. During the period, 67 sampling sites for NO2 were available. The observed annual-mean NO2 concentration across all 67 sites was 35.11 μg/m 3 (standard deviation of 12.10) and ranged from 9.40 to 77.08 μg/m 3. Geographic variables of interest were listed as follows: road type [distance from major road, number of major roads within circular buffers]; trafﬁc intensity [road density of large roads (≥13 m) and of medium roads (5.5–13 m) within circular buffers, trafﬁc counts (of cars, buses, trucks, big trucks, sum of all vehicles) on weekdays and on weekends within circular buffers]; land use [building, farm, forest, water area within circular buffers]; and physical component [population and housing density within circular buffers, elevation data, and distance from coastline]. All geographical variables were collected by the GIS-software ArcGIS (ESRI Japan Inc., version 10.0). After the most appropriate models were constructed for each year (during April 1996 to March 2009), each participant was assigned geographical information of the selected variables according to their geocoded residence. Then, individual annual NO2 exposure was estimated using geographical information as prediction variables. As observed in the previous study (Yorifuji et al., 2010), there is a possibility that some participants would be assigned negative NO2 exposure concentrations since some geographic variables had negative slopes in the models, in particular distance from the coastline. In the present study, however, it should be noted that individual NO2 exposure data was used as an index for trafﬁc-related exposure; thus such negative values could be acceptable.
2.3. Outcome data Vital statistics for determining the causes of death of participants were obtained from the database of the Ministry of Health, Labour and Welfare of Japan. We linked the deceased participants and the causes of death using birthday, sex, and residential area. The underlying causes of death were coded according to the 10th International Classiﬁcation of Disease (ICD-10). The numbers of deaths from all causes, cardiopulmonary disease (ICD 10 code: I10-70/J00-J99), LC (ICD 10 code: C33–C34), and other causes (deaths excluding cardiopulmonary and LC deaths) were determined. Furthermore, regarding cardiopulmonary disease mortality, we more ﬁnely classiﬁed the causes of death as follows: circulatory disease (I10–70), ischemic heart disease (IHD) (I20–I25), other cardiac diseases (such as dysrhythmias, heart failure and cardiac arrest) (I26–51), cerebrovascular disease (I60–69), subarachnoid hemorrhage (I60, I69.0), intracerebral hemorrhage (I61, I69.1), ischemic stroke (I63, I69.3), other circulatory diseases (causes of deaths excluding those speciﬁed in I10– 70), pulmonary disease (J00–J99), pneumonia and inﬂuenza (J10–29), chronic obstructive pulmonary disease (COPD) and allied conditions (J40–47), and other pulmonary disease (causes of deaths excluding those speciﬁed in J00–J99).
T. Yorifuji et al. / Science of the Total Environment 443 (2013) 397–402
Randomly selected participants n=22,040
Questionnaire returned n=14,001 (Shizuoka cohort) Exclusion -Inadequate residential information (n=271) -Move out during study period (n=318)
Study participants n=13,412
Lost to follow up (n=1,407)
Survived and returned questionnaire (n=11,226) Death (n=779)
Lost to follow up (n=2,345)
Survived and returned questionnaire (n=8,333) Death (n=548)
Lost to follow up (n=3,888)
Survived and returned questionnaire (n=3,972) Death (n=473) Fig. 1. Follow-up ﬂow diagram of participants from 1999 to 2009.
2.4. Statistical analysis Time-varying Cox proportional hazards models were used to assess the association between NO2 exposure and all-cause or cause-speciﬁc mortality. The participants were assigned estimated NO2 exposure in the ﬁscal year of the outcome because a previous study showed that the deaths associated with air pollution occur within a year or two of exposure (Schwartz et al., 2008). For each study participant, person-years were counted from the baseline to the date of death or to the date of censorship, whichever occurred ﬁrst. Then, the adjusted hazard ratios (HRs) associated with a 10 μg/m3 elevation in NO2 levels for all-cause or cause-speciﬁc mortality were estimated. We ﬁrst adjusted for age and sex. We then adjusted for smoking (non-; ex-; and current smoker), BMI, hypertension, diabetes, ﬁnancial capability, and area mean taxable income. These potential confounders were decided a priori. BMI was deﬁned as body weight (kg) divided by height squared (m2). The area mean income was derived from dividing total taxable gain of each municipality in 1998 by the number of taxpayers in the municipality in 1998. The data were obtained from the Statistics Bureau, Japan (Statistics Bureau, 2002). We entered age and area mean income as linear terms into the models; BMI as linear and quadratic terms. In sensitivity analyses, we used other windows of exposure, i.e. the preceding one (12 months), two (24 months), or three (36 months) ﬁscal year(s) of the outcome. We also used average concentration from the ﬁscal year 1999 to the ﬁscal year of the outcome of each participant, e.g. average concentration during 1999 to 2005 for participants who were deceased in the ﬁscal year 2005. Some participants lived far from the sampling sites (e.g. around 50 km), possibly resulting in extrapolation too far outside the NO2 measurement area. Therefore, we restricted the participants to those who lived within 25 km or 10 km from the sampling sites and examined the associations between NO2 exposure and mortality. Moreover, to make person-time at risk comparable between the subjects who died and the subjects who censored, we treated those who were lost to follow-up during 2002 to March 2006 (n= 2345) and those who were lost to follow-up during 2006 to January 2009 (n= 3888) as censored at the mid-point of each period. All conﬁdence intervals (CIs) were estimated at the 95% level. PASW software version 18.0 was used for the analysis.
Approval for this study was obtained from the Institutional Review Board of Okayama Graduate School of Medicine, Dentistry and Pharmaceutical Sciences on January 28th, 2011 (No. 448). 3. Results The baseline characteristics of all participants (n=13,412) are shown in Table 1. As expected, there were 989 participants who were assigned negative concentrations. Table 1 also shows the baseline characteristics of participants according to the endpoint. Those who were deceased tended to be older, male, current smoker, and having diabetes. Those who were lost to follow-up during 1999 to 2002 tended to be older, current smoker, and ﬁnancially non-capable compared to survivors. Table 2 shows the adjusted HR associated with a 10 μg/m 3 elevation in NO2 levels (in the ﬁscal year of the outcome) for all-cause and cause-speciﬁc mortality. We could not link 137 deaths with a cause of death, thus we excluded them from the subsequent analyses. We found positive associations of NO2 levels with all-cause (HR = 1.12, 95% CI: 1.07–1.18), cardiopulmonary disease (HR = 1.22, 95% CI: 1.15–1.30), and LC mortality (HR = 1.20, 95% CI: 1.03–1.40). On the other hand, other causes of mortality (deaths excluding cardiopulmonary and LC deaths) were not associated with NO2 exposure. With regard to LC mortality, the effect estimate among non-smokers (HR = 1.30, 95% CI: 0.98–1.71) was higher compared to ex- and current smokers (HR = 1.18, 95% CI: 0.98–1.43). Among cardiopulmonary mortality (Table 3), NO2 levels were positively associated with both circulatory and pulmonary disease mortalities. The strong association for increased risk was observed for not only cardiac disease, such as IHD (HR= 1.27, 95% CI: 1.11–1.47), but also for cerebrovascular disease mortality, i.e. NO2 exposure was associated with both intracerebral hemorrhage (HR =1.28, 95% CI: 1.05– 1.57) and ischemic stroke (HR = 1.20, 95% CI: 1.04–1.39). However, the association with subarachnoid hemorrhage was not apparent. When we used other windows of exposure [preceding one (12 months), two (24 months), or three (36 months) ﬁscal year(s) of the outcome] (Table 4), all of the positive associations between NO2 exposure and selected mortality remained. Adopting average concentration from the ﬁscal year 1999 to the ﬁscal year of the outcome of each participant did not alter HRs substantially. When we restricted
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Table 1 Baseline characteristics of participants: overall and according to the endpoint. Participants were men and women aged 65 years or over living in the study areas in December 1999.
Mean age (year) (SD) Sex (% female)a Mean body mass index (SD)b Smoking categorya Never-smoker Ex-smoker Current smoker Unknown Hypertension (%) Diabetes (%) Financial capabilitya Capable Non-capable Unknown Mean taxable income of each municipality (million yen) (SD)c Mean NO2 concentration (μg/m3) (SD)d
Overall (n = 13,412)
Survivors (n = 3972)
74 (5.4) 6560 (48.9) 22 (3.1)
72 (5.1) 2022 (50.9) 22 (2.9)
9109 1535 2174 594 4131 1040
(67.9) (11.4) (16.2) (4.4) (30.8) (7.8)
2837 474 563 98 1257 238
(71.4) (11.9) (14.2) (2.5) (31.6) (6)
7313 4063 2036 3.3
(54.5) (30.3) (15.2) (0.2)
2455 1105 412 3.3
(61.8) (27.8) (10.4) (0.2)
Deaths (n = 1800)
Censored during 1999–2002 (n = 1407)
Censored during 2002–2006 (n = 2345)
Censored during 2006–2009 (n = 3888)
75 (5.4) 1221 (52.1) 22 (3.2)
74 (5.3) 2016 (51.9) 22 (2.9)
75 (5.4) 709 (50.4) 22 (3.5)
(59.1) (15.3) (20.1) (5.6) (29.4) (11.2)
1604 (68.4) 262 (11.2) 386 (16.5) 93 (4) 740 (31.6) 202 (8.6)
2710 392 587 199 1223 266
(69.7) (10.1) (15.1) (5.1) (31.5) (6.8)
895 132 277 103 382 133
(63.6) (9.4) (19.7) (7.3) (27.1) (9.5)
963 (53.5) 519 (28.8) 318 (17.7) 3.3 (0.2)
1150 (49) 780 (33.3) 415 (17.7) 3.3 (0.2)
2111 1151 626 3.3
(54.3) (29.6) (16.1) (0.2)
634 508 265 3.3
(45.1) (36.1) (18.8) (0.2)
77 (5.1) 592 (32.9) 21 (3.2) 1063 275 361 101 529 201
SD; standard deviation, NO2; nitrogen dioxide. a No. (%) of participants is shown. Percentages may not sum to 100% due to rounding. b Body mass index is calculated as body weight (kg) divided by height squared (m2). c Million yen equals about 13,125 US dollars (Feb 2012). d Annual NO2 concentration when the event occurred.
participants to those living within 25 km or 10 km of sampling sites, the number of participants was reduced to 10,708 and 8593, respectively. In the latter scenario, only 20 participants were assigned negative values. The positive associations between NO2 exposure and mortality were still observed. Even when we treated those who were lost to follow-up during 2002 to March 2006 and those who were lost to follow-up during 2006 to January 2009 as censored at the mid-point of each period, the results did not change substantially.
4. Discussion We extended the follow-up period of an ongoing cohort study to evaluate the association between long-term exposure to trafﬁc-related air pollution, indexed by NO2, and cause-speciﬁc mortality, especially focusing on stroke and LC in Shizuoka, Japan. As hypothesized, we found an adverse effect of trafﬁc-related air pollution on all-cause and cardiopulmonary disease mortality. Among cardiopulmonary disease mortality, exposure was associated with both intracerebral hemorrhage and ischemic stroke. Furthermore, NO2 exposure index was positively related with LC mortality. One point should be noted to interpret the study ﬁnding. As noted, individual NO2 exposure data was used as an index for trafﬁc-related exposure; thus, negative concentrations were acceptable. It should be Table 2 Adjusted HR following a 10 μg/m3 elevation in estimated NO2 and 95% conﬁdence intervals for all-cause and cause-speciﬁc mortality. Mortality HR (95% CI)a (n) All-cause mortality 1663 Cause-speciﬁc mortality Cardiopulmonary (I10–70/J00– 801 J99) Lung cancer (C33–C34) 116 Other causesc 746
HR (95% CI)b
1.08 (1.04–1.12) 1.12 (1.07–1.18) 1.14 (1.09–1.20) 1.22 (1.15–1.30) 1.15 (1.00–1.31) 1.20 (1.03–1.40) 0.99 (0.94–1.04) 1.01 (0.95–1.09)
NO2, nitrogen dioxide; HR, hazard ratio; CI, conﬁdence interval. a Adjusted for age and sex. b Adjusted for age, sex, smoking category, BMI (linear and quadratic), hypertension, diabetes, ﬁnancial capability, and area mean income. c Mortality from other causes is deﬁned as deaths due to causes other than cardiopulmonary disease or lung cancer.
cautious when we compare the effect estimates of the present study with those from air pollution studies which use (general) NO2 exposure. In the present study, long-term air pollution was shown to increase the risk of cardiopulmonary mortality, which reinforced the ﬁnding of our previous study (Yorifuji et al., 2010). In particular, consistent with the existing evidence (Brook et al., 2010; Lipsett et al., 2011; Ostro et al., 2010; Pope and Dockery, 2006), the effect was strong for IHD. The different ﬁndings from the cohort studies in Western countries were that on cerebrovascular disease and its type. Indeed, among cohort studies, increases in nonfatal stroke and fatal cerebrovascular disease were observed in the Women's Health Initiative Observational Study in the U.S. (Miller et al., 2007). In contrast, no association between outdoor air pollution and cerebrovascular disease was found in the American Cancer Society study (Pope et al., 2004). In addition, a study in Denmark suggested a possible association with ischemic stroke but not with hemorrhagic one (Andersen et al., 2012). These different ﬁndings between the previous studies in Western countries and the present one would be attributable to the high frequency of cerebrovascular disease as well as stroke of hemorrhagic type in Japan (Elkind and Sacco, 2010; Ministry of Health Labour and Welfare in Japan, 2010), probably making it possible to detect health effects. Table 3 Adjusted HR following a 10 μg/m3 elevation in estimated NO2 and 95% conﬁdence intervals for cardiopulmonary mortality.
Cardiopulmonary (I10–70/J00–J99) Circulatory disease (I10–70) Ischemic heart disease (I20–I25) Other cardiac disease (I26–51) Cerebrovascular disease (I60–69) Subarachnoid hemorrhage (I60, I69.0) Intracerebral hemorrhage (I61, I69.1) Ischemic stroke (I63, I69.3) Other circulatory disease Pulmonary disease (J00–J99) Pneumonia and inﬂuenza (J10–29) COPD and allied conditions (J40–47) Other pulmonary disease
HR (95% CI)*
801 520 110 156 248 23 61 160 6 281 159 50 72
1.22 1.24 1.29 1.27 1.19 0.91 1.28 1.20 1.32 1.19 1.15 0.98 1.38
(1.15–1.30) (1.15–1.33) (1.12–1.48) (1.15–1.46) (1.06–1.34) (0.65–1.27) (1.05–1.57) (1.04–1.39) (0.70–2.49) (1.06–1.34) (0.99–1.35) (0.75–1.29) (1.17–1.63)
* Adjusted for age, sex, smoking category, BMI (linear and quadratic), hypertension, diabetes, ﬁnancial capability, and area mean income. NO2, nitrogen dioxide; COPD, chronic obstructive pulmonary disease; HR, hazard ratio; CI, conﬁdence interval.
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Table 4 Sensitivity analyses. Adjusted HR* following a 10 μg/m3 elevation in estimated NO2 and 95% conﬁdence intervals for both cardiopulmonary disease and lung cancer mortalities.
Alternative exposure periods Preceding 1 ﬁscal year of the event Preceding 2 ﬁscal years of the event Preceding 3 ﬁscal years of the event Average concentration from 1999 until the ﬁscal year of the event Restriction of participants Living within 25 km from the sampling sites Living within 10 km from the sampling sites
1.17 1.25 1.24 1.17
1.15 1.23 1.21 1.14
1.23 1.29 1.31 1.24
1.18 1.28 1.33 1.16
1.20 1.33 1.23 1.16
(1.09–1.25) (1.17–1.35) (1.15–1.33) (1.08–1.25)
1.24 (1.15–1.32) 1.23 (1.14–1.33)
(1.02–1.31) (1.08–1.40) (1.06–1.38) (1.00–1.30)
1.22 (1.07–1.38) 1.17 (1.00–1.38)
(0.96–1.59) (1.01–1.65) (1.10–1.57) (0.96–1.60)
1.28 (1.02–1.61) 1.27 (0.97–1.66)
(1.00–1.39) (1.08–1.51) (1.02–1.72) (0.97–1.38)
1.20 (1.01–1.41) 1.12 (0.91–1.40)
(1.01–1.43) (1.13–1.56) (1.03–1.46) (0.97–1.39)
1.19 (0.99–1.42) 1.27 (1.07–1.50)
* Adjusted for age, sex, smoking category, BMI (linear and quadratic), hypertension, diabetes, ﬁnancial capability, and area mean income. NO2, nitrogen dioxide; CI, conﬁdence interval; HR, hazard ratio.
Air pollution is hypothesized to raise the risk of ischemic stroke through increased plasma viscosity (Hong et al., 2002). In contrast, the potential mechanisms linking air pollution to hemorrhagic stroke may include: First, direct ischemic damage to blood vessels induced by air pollution may lead to brain hemorrhage (Dickinson, 2001). Second, air pollution has been associated with acute endothelial dysfunction (atherosclerosis) (Brook et al., 2010; Pope and Dockery, 2006), which may lead to the brain vessels' vulnerability to rupture (Suwa et al., 2002). Third, air pollution may trigger vasoconstriction or hypertension (Brook et al., 2010; Pope and Dockery, 2006), which might also lead to hemorrhagic stroke. No observed association with subarachnoid hemorrhage, in contrast with the time-series study in Japan (Yorifuji et al., 2011), may be explained by small number of cases in the present study or different mechanisms between acute and chronic exposure. Although our previous study did not ﬁnd an adverse effect of air pollution on LC mortality among the total participants (Yorifuji et al., 2010), this extended study provided additional ﬁnding to the existing evidence (Filleul et al., 2005; Krewski et al., 2009; Laden et al., 2006; Lepeule et al., 2012; Nafstad et al., 2003; Pope et al., 2002; Raaschou-Nielsen et al., 2011; Turner et al., 2011). The different ﬁnding could be due to the short follow-up of the previous study (Yorifuji et al., 2010). Consistent with our previous (Yorifuji et al., 2010) as well as other studies (Beelen et al., 2008; Pope et al., 2002; Raaschou-Nielsen et al., 2011), a stronger association between air pollution and LC mortality was suggested among non-smokers compared to ex- and current smokers. This ﬁnding may reﬂect vulnerability of non-smokers to air pollution. A major limitation of the present study was that there was considerable loss to follow-up during the study period (Fig. 1). The loss was more frequently observed among older participants, smokers, and participants with more ﬁnancial stress. Therefore, the assumption of the Cox proportional hazards model (i.e., non-informative censoring (Collett, 2003)) may be violated, possibly inducing selection bias (Hernan et al., 2004). For example, almost 10% of the participants (1407 out of 13,412 participants) were lost to follow-up during 1999–2002 and did not contribute to person-years. According to Table 1, participants who were lost to follow-up during that period were older, likely to smoke, likely to be ﬁnancially non-capable, and they tended to live in more polluted areas compared to survivors, which might have caused underestimation of the effect estimates. In the present study, LUR modeling was used to assess individual exposure; the R2 of 0.54 of the original LUR modeling was moderate and lower compared to other studies (Kashima et al., 2009). However, LUR modeling induces primarily Berkson error, and hence should mostly reduce power and not bias the effect estimates (Nieuwenhuijsen, 2003). In addition, there were 989 participants who were assigned negative concentrations probably due to extrapolation far outside the NO2 measurement area and selected geographical variables. However, as noted, we analyzed all participants since we considered the estimated concentration as an index for trafﬁc-related air pollution as well as a relative indicator. When we restricted participants to those living within 25 km or 10 km of the sampling sites, which could substantially reduce
the participants who were assigned negative values, we obtained similar effect estimates. Another limitation of the present study was the inability to obtain the detailed information about smoking (e.g., smoking pack-years (one pack year is deﬁned as one pack smoked per day for one year)). However, in the stratiﬁed analysis by smoking status, the effect estimate for LC mortality in non-smokers was also elevated, which suggested potential residual confounding would be minimal. When we linked deceased participants and the causes of death using birthday, sex, and residential area, we could not link 137 deaths. This could be due to participants moving away or to coding error. However, it would probably be non-differential disease misclassiﬁcation, leading effect estimates toward the null. Finally, although air pollution has been found to be associated with reduced survival after stroke (Maheswaran et al., 2010), our mortality study cannot distinguish between effects of air pollution on incidence and effects of air pollution on survival after stroke. In conclusion, the present study supports the existing evidence that long-term exposure to trafﬁc-related air pollution increases the risk of cardiopulmonary as well as LC mortality, and provides additional evidence for adverse effects on intracerebral hemorrhage as well as ischemic stroke. Financial support This work was supported by a Health and Labour Sciences Research Grant for Comprehensive Research on Aging and Health. Competing interests None disclosed. Acknowledgments We appreciate the staff of the Shizuoka Health Institute for maintaining the Shizuoka elderly cohort. We also thank Etsuji Suzuki, Sachiko Inoue, and three anonymous reviewers. References Andersen ZJ, Olsen TS, Andersen KK, Loft S, Ketzel M, Raaschou-Nielsen O. Association between short-term exposure to ultraﬁne particles and hospital admissions for stroke in Copenhagen, Denmark. Eur Heart J 2010;31:2034–40. Andersen ZJ, Kristiansen LC, Andersen KK, Olsen TS, Hvidberg M, Jensen SS, et al. Stroke and long-term exposure to outdoor air pollution from nitrogen dioxide: a cohort study. Stroke 2012;43:320–5. Beelen R, Hoek G, van den Brandt PA, Goldbohm RA, Fischer P, Schouten LJ, et al. Long-term effects of trafﬁc-related air pollution on mortality in a Dutch cohort (NLCS-AIR study). Environ Health Perspect 2008;116:196–202. Brook RD, Rajagopalan S, Pope III CA, Brook JR, Bhatnagar A, Diez-Roux AV, et al. Particulate matter air pollution and cardiovascular disease: an update to the scientiﬁc statement from the American Heart Association. Circulation 2010;121:2331–78. Chan CC, Chuang KJ, Chien LC, Chen WJ, Chang WT. Urban air pollution and emergency admissions for cerebrovascular diseases in Taipei, Taiwan. Eur Heart J 2006;27:1238–44.
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