Interaction between Long-Term Exposure to Fine Particulate Matter and Physical Activity, and Risk of Cardiovascular Disease and Overall Mortality in U.S. Women
2020; National Institute of Environmental Health Sciences; Volume: 128; Issue: 12 Linguagem: Inglês
10.1289/ehp7402
ISSN1552-9924
AutoresElise G. Elliott, Francine Laden, Peter James, Eric B. Rimm, Kathryn M. Rexrode, Jaime E. Hart,
Tópico(s)Air Quality Monitoring and Forecasting
ResumoVol. 128, No. 12 ResearchOpen AccessInteraction between Long-Term Exposure to Fine Particulate Matter and Physical Activity, and Risk of Cardiovascular Disease and Overall Mortality in U.S. Women Elise G. Elliott, Francine Laden, Peter James, Eric B. Rimm, Kathryn M. Rexrode, and Jaime E. Hart Elise G. Elliott Address correspondence to Elise G. Elliott, 401 Park Dr., 3rd Fl. West, Boston, MA 02215 USA. Telephone: (617) 525-4206, Fax: (617) 525-2578. Email: E-mail Address: [email protected] Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA , Francine Laden Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA , Peter James Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA , Eric B. Rimm Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA , Kathryn M. Rexrode Division of Women's Health, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA , and Jaime E. Hart Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA Published:23 December 2020CID: 127012https://doi.org/10.1289/EHP7402Cited by:1AboutSectionsPDF Supplemental Materials ToolsDownload CitationsTrack CitationsCopy LTI LinkHTMLAbstractPDF ShareShare onFacebookTwitterLinked InRedditEmail AbstractBackground:Increased respiration during physical activity may increase air pollution dose, which may attenuate the benefits of physical activity on cardiovascular disease (CVD) risk and overall mortality.Objectives:We aimed to examine the multiplicative interaction between long-term ambient residential exposure to fine particulate matter <2.5 microns (PM2.5) and physical activity in the association with CVD risk and overall mortality.Methods:We followed 104,990 female participants of the U.S.-based prospective Nurses' Health Study from 1988 to 2008. We used Cox proportional hazards models to assess the independent associations of 24-months moving average residential PM2.5 exposure and physical activity updated every 4 y and the multiplicative interaction of the two on CVD (myocardial infarction and stroke) risk and overall mortality, after adjusting for demographics and CVD risk factors.Results:During 20 years of follow-up, we documented 6,074 incident CVD cases and 9,827 deaths. In fully adjusted models, PM2.5 exposure was associated with modest increased risks of CVD [hazard ratio (HR) for fifth quintile ≥16.5 μg/m3 compared to first quintile <10.7 μg/m3: 1.09, 95% confidence interval (CI): 0.99, 1.20; ptrend=0.05] and overall mortality (HR fifth compared to first quintile: 1.10, 95% CI: 1.02, 1.19; ptrend=0.07). Higher overall physical activity was associated with substantially lower risk of CVD [HR fourth quartile, which was ≥24.4 metabolic equivalent of task (MET)-h/wk, compared to first quartile (<3.7MET-h/wk): 0.61, 95% CI: 0.57, 0.66; ptrend<0.0001] and overall mortality (HR fourth compared to first quartile: 0.40, 95% CI: 0.37, 0.42; ptrend<0.0001). We observed no statistically significant interactions between PM2.5 exposure and physical activity (overall, walking, vigorous activity) in association with CVD risk and overall mortality.Discussion:In this study of U.S. women, we observed no multiplicative interaction between long-term PM2.5 exposure and physical activity; higher physical activity was strongly associated with lower CVD risk and overall mortality at all levels of PM2.5 exposure. https://doi.org/10.1289/EHP7402IntroductionCardiovascular disease (CVD), including coronary heart disease (CHD) and stroke, is the leading cause of death in the United States (Benjamin et al. 2019) and the leading cause of noncommunicable disease-related mortality and morbidity worldwide (Joseph et al. 2017). Two well-established factors associated with incidence of CVD and death are the adverse effects of air pollution exposure and the beneficial effects of physical activity. Air pollution exposure is a major environmental risk factor for overall mortality and CVD risk (Benjamin et al. 2019; Burnett et al. 2018; Laden et al. 2006; Pope et al. 2020, 2015; Yusuf et al. 2020). An estimated 4.2 million premature deaths worldwide (Landrigan et al. 2018) and 5%–10% of annual premature mortality in the contiguous United States (Dedoussi et al. 2020) are associated with ambient air pollution, as well as 29% of incident stroke (Benjamin et al. 2019) and stroke burden, as measured in disability-adjusted life-years (DALY) (Feigin et al. 2016). Physical activity is one of the strongest modifiable factors associated with CVD risk (Benjamin et al. 2019; Joseph et al. 2017), and regular physical activity has been consistently associated with decreased risk of acute myocardial infarction (MI) (Yusuf et al. 2004), decreased risk of coronary heart disease (Chomistek et al. 2016), and decreased risk of stroke (Feigin et al. 2016; O'Donnell et al. 2016). Among women in the Nurses' Health Study (NHS), a prospective cohort of U.S. women, chronic exposure to particulate matter (PM) air pollution has previously been associated with increased risk of MI, coronary heart disease, and overall and cause-specific mortality (DuPré et al. 2019; Hart et al. 2015a, 2015b; Puett et al. 2008, 2009). Also in this cohort, moderate- and moderate-to-vigorous–intensity physical activity have been associated with a decreased risk of CHD (Li et al. 2006; Stampfer et al. 2000) and stroke (Chiuve et al. 2008; Hu et al. 2000).Although a large body of evidence has observed associations between air pollution exposure and CVD risk and overall mortality and between physical activity and CVD risk and mortality, the interaction between long-term air pollution exposure and physical activity on CVD risk and mortality is not yet fully understood. Physical activity increases deeper respiration and may increase internal air pollution dose at a given concentration, which might attenuate the benefits of physical activity on CVD risk and mortality (Pasqua et al. 2018). Evidence from some, but not all, studies of short-term exposures suggest that air pollution exposure during physical activity may be associated with acute adverse physiological responses in markers of CVD health (Cole-Hunter et al. 2016; Corlin et al. 2018; Giles et al. 2018; Sinharay et al. 2018). Only three studies have investigated the interaction between long-term exposure to air pollutants and physical activity in relation to CVD incidence or mortality. Two studies have examined this interaction for long-term nitrogen dioxide (NO2) exposure and physical activity in association with mortality and MI risk and did not observe interactions (Andersen et al. 2015; Kubesch et al. 2018). One study has examined the interaction between long-term exposure to PM air pollution and physical activity in association with mortality and did not observe interactions (Sun et al. 2020). However, no study has examined the interaction between long-term exposure to PM air pollution and long-term physical activity in association with MI, stroke, and overall mortality risk.Our objective was to confirm previous associations with physical activity and long-term exposure to PM less than 2.5 microns in diameter (PM2.5) and assess the multiplicative interaction between them on CVD risk and overall nonaccidental mortality in the NHS prospective cohort.MethodsStudy PopulationThe NHS is an ongoing nationwide prospective cohort study of 121,701 U.S. female registered nurses (30–55 y old) enrolled at study inception in 1976. Women were initially enrolled from 11 selected states, though participants now live throughout the contiguous United States. NHS participants complete self-administered questionnaires biennially, providing information on incident disease, medical history, and lifestyle factors. Response rates for most follow-up cycles have been ≥90% (Bao et al. 2016; Morabia 2016). In the current analysis, we followed NHS participants from 1988 to 2008 and included participants if at the beginning of these analyses in 1988 they were alive, had no history of CVD, were still responding to questionnaires, had at least one residential address during follow-up where air pollution predictions were available, and provided information on physical activity on at least one questionnaire. This study protocol was approved by the Institutional Review Board of Brigham and Women's Hospital, Boston, Massachusetts, and consent was implied through the return of the questionnaires.Outcome AssessmentMethods to confirm incident CVD have been published in detail elsewhere (Hart et al. 2015b; Shan et al. 2020; Yu et al. 2016). Incident CVD was determined as the first occurrence of either fatal and nonfatal acute MI (ICD-9 code 410) or stroke (ICD-9 codes 430 to 437). Participants were asked to report all occurrences of physician-diagnosed incident CVD (MI or stroke) on the baseline, and all subsequent biennial questionnaires and participants (or next-of-kin for fatal cases) provided consent to review all medical records pertaining to their reported diagnosis. Cases of nonfatal CVD were confirmed through medical record review or through interview or a letter confirming hospitalization for the MI or stroke. Cases of fatal CVD were confirmed through hospital record review, autopsy, report of CVD as the underlying cause on the death certificate, a history of CVD and CVD was the most plausible cause of death, or supporting information provided by a family member.We included deaths from all nonaccidental causes for assessment of overall mortality. Deaths were either reported by next-of-kin or through searches of the National Death Index for nonrespondents. Identification of deaths in the NHS cohort has been validated previously (Rich-Edwards et al. 1994). Primary cause of death was determined through physician review of death certificates and medical records according to the International Classification of Diseases, Ninth Revision (ICD-9).Exposure AssessmentAssessment of Ambient Residential PM2.5 ExposureResidential addresses were updated every 2 y with each questionnaire cycle and geocoded to obtain latitude and longitude. We calculated exposure to PM2.5 at each residential address using spatiotemporal prediction models available in the contiguous United States for each month between January 1988 and December 2007 (Yanosky et al. 2014). The generalized additive mixed models used monthly average PM2.5 and/or PM10 monitoring data from the U.S. Environmental Protection Agency's Air Quality System and other publicly available networks (Yanosky et al. 2014). Additionally, the models incorporated geospatial predictors (road network data, residential and urban land use, density of PM2.5 and PM10 point-sources, and elevation data) and monthly average meteorological data (wind speed, temperature, precipitation) (Yanosky et al. 2014). Predictions models were evaluated using 10-fold cross-validation (CV) and predictive accuracy for PM2.5 across the contiguous United States was high (CV R2=0.77) (Yanosky et al. 2014). Previously, we investigated different lag periods of PM2.5 in relation to CVD and mortality in the NHS and found that a longer lag period did not modify associations in comparison with 24-month moving average PM2.5 (Hart et al. 2015b). We therefore calculated 24-month moving averages for each questionnaire cycle as a measure of long-term exposures. If 24-month average PM2.5 during follow-up was missing, we excluded participants for the corresponding questionnaire cycle in the analyses.Assessment of Physical ActivityLeisure-time physical activity was assessed using information from the biennial questionnaires. Physical activity was first reported in 1986 and updated every 2 or 4 y (depending on available space on the biennial questionnaire). On each questionnaire assessing physical activity, participants reported the average time per week spent participating in specific leisure-time activities, including walking, jogging, running, bicycling, lap swimming, tennis, squash or racquetball, and calisthenics and other aerobic activities. Over time, activities reported through the questionnaires were expanded to include other low and high intensity activities, such as weight training, yoga, and lawn mowing. Participants reported the average time per week spent participating in each of these leisure-time activities in seven provided categories, ranging from 0 min to ≥11h/wk. Location (indoors vs. outdoors) of physical activity was not assessed. Time per week spent participating in each activity was multiplied by each activity's metabolic equivalent of task (MET) score to obtain MET-hours per week, which incorporates frequency, duration, and intensity of activity (Ainsworth et al. 2011). We calculated overall physical activity in MET-hours per week by summing the MET-hours per week across all activities. Additionally, we considered MET-hours per week from walking alone, MET-hours per week from vigorous-intensity activities (≥6 METs/hour: jogging, running, biking, swimming, and tennis), MET-hours per week from low- or moderate-intensity activities (<6 METs/hour) (Lee et al. 2019; U.S. Department of Health and Human Services 2019), and MET-hours per week for physical activities likely to be performed outdoors (e.g., walking, running, biking, lawn mowing), created by excluding activities more likely to be performed indoors (squash, racquet ball, arm weight training, leg weight training) from total MET-hours. If physical activity information (MET-hours per week) during follow-up was missing, we excluded participants for the corresponding questionnaire cycle in the analyses.Potential Confounders and Effect ModifiersWe obtained information on potential confounders and effect modifiers from the biennial questionnaires. Covariates are updated every 2 y, with the exception of diet, which is queried every 4 y, race (assessed in 2004), family history of MI (assessed in 1984), occupation of the participant's father and mother (assessed in 1976), educational attainment of the participant's husband (assessed in 1992), and participant's educational attainment (assessed in 1992). Additionally, the geocoded addresses were linked to data from the 2000 U.S. Census to obtain information on neighborhood-level socioeconomic status (SES) ( www.census.gov). Covariates were selected a priori based on previous research in the NHS cohort and wider literature indicating that covariates may be either risk factors for the outcomes or potential confounders of the associations of interest (Anand et al. 2008; Beelen et al. 2014; Cesaroni et al. 2014; Hart et al. 2015b; Hoek et al. 2013; Puett et al. 2008, 2009; Weichenthal et al. 2014). We included age and race in all models. In fully adjusted models, we additionally adjusted for incident cancer, family history of MI, smoking status, pack-years, overall diet quality using the Alternate Healthy Eating Index score (McCullough and Willett 2006), alcohol consumption, multivitamin use, individual-level SES (occupation of the participant's father and mother, educational attainment of the participant's husband, participant's educational attainment, marital status, employment status), and neighborhood-level SES (census tract median income and census tract median home value). If information on time-varying covariates was missing during follow-up, we used information reported on the preceding questionnaire, assuming no changes, to impute missing data. For remaining missing covariate data, we imputed missing data with "0" and accounted for missing covariate data using missing indicators in Cox proportional hazards models.Statistical AnalysisPerson-time was assessed as months of follow-up from the return date of the 1988 questionnaire until incident CVD, death, or the end of follow-up (31 May 31 2008), whichever came first. We used time-varying Cox proportional hazards models to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations between 24-month average ambient PM2.5 exposure [per 10 μg/m3 increase (Hart et al. 2015b; Puett et al. 2009) or by quintiles of PM2.5 exposure], physical activity [per 9 MET-h/wk for overall physical activity, based on weekly physical activity recommendations (Lee et al. 2019; U.S. Department of Health and Human Services 2019) or by quartiles of overall physical activity, walking, and vigorous activity], and the multiplicative interaction of the two on risk of MI, stroke, MI or stroke combined, and overall mortality. We accounted for missing covariate data using missing indicators. Analyses were stratified by age at follow-up (months) and calendar period to control for age and temporal effects. In categorical analyses, we used the median value of each category to conduct tests for trend. We modeled multiplicative interactions between quintiles of 24-month average PM2.5 exposure and quartiles of physical activity using stratified Cox proportional hazards models and tested for statistical significance (α=0.05) using likelihood ratio tests comparing models with and without interaction terms.We conducted sensitivity analyses to assess the robustness of our findings on physical activity as well as interactions between PM2.5 exposure and physical activity in association with CVD and overall mortality. We estimated MET-hours per week for physical activities likely to be performed outdoors (e.g., walking, running, biking, lawn mowing), created by excluding activities more likely to be performed indoors (squash, racquet ball, arm weight training, leg weight training) from total MET-hours. All analyses were conducted in SAS (version 9.4; SAS Institute Inc.).ResultsAmong 104,990 eligible participants, we observed 6,074 incident cases of CVD (MI or stroke), 3,304 incident cases of MI, 2,848 incident cases of stroke, and 9,827 deaths over follow-up. Over the course of follow-up from 1988 to 2008 and standardized to the age-distribution of the study population, participants were on average 63.1 (standard deviation: 8.9) y old (not age-adjusted), had 24-month average PM2.5 levels of 13.7 mg/m3 [standard deviation (SD): 3.5], reported overall physical activity participation of 18.3 MET-h/wk (SD: 23.1), were primarily White, never or past smokers, and married (Table 1; Table S1). Those with the highest levels of 24-month average ambient PM2.5 exposure were on average younger, slightly less physically active, were less likely to have high cholesterol, had poorer overall diet quality, and were less likely to use multivitamins. Those with highest levels of physical activity on average lived in areas with higher neighborhood SES, were more likely to be of normal weight, were less likely to have hypertension, were less likely to have diabetes, had better overall diet quality, were more likely to use multivitamins, and had husbands with higher levels of education. Over time, average PM2.5 levels decreased from 17.0 μg/m3 in 1988 to 11.3 μg/m3 in 2006, whereas reported participation in overall physical activity increased from 15.4 MET-h/wk in 1988 to 20.9 MET-h/wk in 2006 (Table S1).Table 1 Age-standardized characteristics of Nurses' Health Study participants throughout follow-up (1988–2008), overall, by quintile of 24-month average ambient PM2.5 exposure, and by quartile of total physical activity (N=104,990).Table 1, in two main columns, lists Characteristics begin superscript lowercase b end superscript and Mean plus or minus standard deviation or percentage begin superscript lowercase a end superscript. The column Mean plus or minus standard deviation or percentage begin superscript lowercase a end superscript column is sub divided into four columns, namely, overall, particulate matter less than 2.5 microns, particulate matter less than 2.5 microns, Physical activity, and Physical activity. Each of these sub columns are further sub divided into one column, namely, Quintile 1. Quintile 5, Quintile 1, and Quintile 4.Mean±SD or %aPM2.5PM2.5Physical activityPhysical activityCharacteristicbOverallQuintile 1Quintile 5Quartile 1Quartile 4Age (y)c63.1±8.966.6±8.358.7±8.263.7±9.363.0±8.424-month average ambient PM2.5 (μg/m3)13.7±3.59.1±1.318.8±2.013.9±3.513.4±3.5Physical activity (MET-h/wk) Overall physical activity18.3±23.120.3±24.816.8±21.31.5±1.147.6±28.9 Walking7.2±10.67.2±9.78.0±12.41.4±4.315.5±14.8 Jogging0.3±2.70.3±2.70.2±2.70.0±0.60.9±5.1 Running0.2±3.60.3±4.00.2±3.30.0±0.70.8±7.0 Biking1.9±6.42.0±6.61.9±6.50.1±1.34.9±11.2 Vigorous activity3.8±11.64.2±12.33.6±11.30.2±2.811.0±20.3 Outdoor physical activityd17.8±22.419.5±23.816.6±21.11.5±1.146.1±28.2 Pack-years of smoking13.1±19.512.7±19.013.2±19.916.1±22.511.4±17.3 Census tract median income (per 1,000 USD)64.0±25.060.4±23.961.9±24.362.2±23.566.0±26.9 Census tract median home value (per 1,000 USD)172.3±128.9174.8±142.6169.5±129.7161.8±114.5185.2±144.5Race and ethnicity White9495929394 Black11221 Other/more than one race54655 Hispanic1211124-month average PM2.5 quintiles (μg/m3) Quintile 1: <10.72010001823 Quintile 2: 10.7 to <12.520002020 Quintile 3: 12.5 to <14.420002020 Quintile 4: 14.4 to <16.520002119 Quintile 5: ≥16.52001002118Total physical activity quartiles (MET-h/wk) Quartile 1: <3.72523271000 Quartile 2: 3.7 to <10.925232600 Quartile 3: 10.9 to <24.425252500 Quartile 4: ≥24.42528220100 Any vigorous physical activity reported3335331254Body mass index (kg/m2) <254748503857 25 to <303332323230 ≥302020193012 High blood pressure4344414938 High cholesterol5355475450 Diabetes777115 Family history of myocardial infarction3735393837Smoking status Never smoker4444474244 Past smoker4346394146 Current smoker121014169Alcohol consumption (grams/day) 05554586350 0.1 to <52321232023 5 to <151415121117 15 to <3056446 ≥3034333AHEI diet score quartile Quartile 1: <42.92522283518 Quartile 2: 42.9 to <51.82523252821 Quartile 3: 51.8 to <60.42525242226 Quartile 4: ≥60.42530221536Multivitamin use4750414251Mother's occupation housewife6462686464Father's occupation professional/manager2628242428Husband's highest level of education more than high school4244413748Registered nursing degree in 19728685888587Married - ever7576737376Retired - ever4446414246Note: AHEI, Alternate Healthy Eating Index; MET, metabolic equivalent of task; PM2.5, particulate matter <2.5 microns; SD, standard deviation.aValues are means±SD or percentages and are standardized to the age distribution of the study population and represent the average values over the course of follow-up from 1988 to 2008, accounting for changes in time-varying characteristics.bCharacteristics are updated every 2 y, with the exception of diet, which is queried every 4 y, race (assessed in 2004), family history of MI (assessed in 1984), occupation of the participant's father and mother (assessed in 1976), educational attainment of the participant's husband (assessed in 1992), and participant's educational attainment (assessed in 1992).cNot age standardized.dOutdoor physical activity excludes types of assessed physical activity that are more likely to be engaged in indoors for some or all of the time (squash, racquet ball, arm weight training, leg weight training).Analyses of the associations between 24-month average ambient PM2.5 exposure and risk of MI, stroke, and overall mortality showed a modest but consistent increased risk of MI or stroke and overall mortality associated with increasing exposure (Table 2). In fully adjusted models, those in the highest quintile of 24-month average ambient PM2.5 exposure (≥16.5 μg/m3) had 1.09 times the risk of MI or stroke (95% CI: 0.99, 1.20; ptrend=0.05) and 1.10 times the risk of death (95% CI: 1.02, 1.19; ptrend=0.07) in comparison with those in the lowest quintile of exposure (<10.7 μg/m3). Continuous analyses per 10 μg/m3 greater 24-month average ambient PM2.5 exposure were consistent, with 1.09 times the risk of MI or stroke (95% CI: 1.00, 1.19) and 1.07 times the risk of death (95% CI: 1.00, 1.15). Models were robust to adjustment for confounders.Table 2 Associations between 24-month average PM2.5 exposure and incident myocardial infarction, stroke, and overall mortality among Nurses' Health Study participants 1988–2008 (N=104,990)Table 2 has five columns, namely, Outcome, Cases (lowercase italic n), Person-years (lowercase italic n), Basic begin superscript lowercase a end superscript hazard ratio (95 percent confidence intervals), and Fully adjusted begin superscript lowercase b end superscript hazard ratio (95 percent confidence intervals).OutcomeCases (n)Person-years (n)Basica HR (95% CI)Fully adjustedb HR (95% CI)PM2.5 (μg/m3) MI or stroke Q1: <10.71,324323,283RefRef Q2: 10.7–12.41,324326,5701.08 (1.00, 1.17)1.07 (0.99, 1.16) Q3: 12.5–14.31,277326,7271.11 (1.02, 1.20)1.10 (1.02, 1.19) Q4: 14.4–16.41,188328,3811.12 (1.03, 1.21)1.09 (1.01, 1.19) Q5: ≥16.5961327,0521.11 (1.02, 1.22)1.09 (0.99, 1.20) p for trendc0.010.05 Continuous (10 μg/m3)6,0741,632,0121.12 (1.03, 1.21)1.09 (1.00, 1.19) MI Q1: <10.7697323,763RefRef Q2: 10.7–12.4693327,0581.06 (0.95, 1.18)1.05 (0.95, 1.17) Q3: 12.5–14.3686327,1781.11 (0.99, 1.23)1.10 (0.99, 1.22) Q4: 14.4–16.4674328,8161.16 (1.04, 1.30)1.13 (1.01, 1.26) Q5: ≥16.5554327,4001.13 (0.99, 1.27)1.09 (0.96, 1.24) p for trendc0.020.07 Continuous (10 μg/m3)3,3041,634,2151.16 (1.03, 1.30)1.13 (1.01, 1.26) Stroke Q1: <10.7645323,721RefRef Q2: 10.7–12.4648327,0091.10 (0.98, 1.23)1.09 (0.98, 1.22) Q3: 12.5–14.3609327,1861.10 (0.98, 1.23)1.10 (0.98, 1.23) Q4: 14.4–16.4527328,8171.06 (0.94, 1.19)1.04 (0.92, 1.17) Q5: ≥16.5419327,4351.08 (0.94, 1.24)1.07 (0.93, 1.23) p for trendc0.340.49 Continuous (10 μg/m3)2,8481,634,1681.05 (0.93, 1.19)1.04 (0.92, 1.18) Overall mortality Q1: <10.72,553324,401RefRef Q2: 10.7–12.42,352327,6521.11 (1.04, 1.17)1.08 (1.02, 1.15) Q3: 12.5–14.32,111327,7811.08 (1.01, 1.14)1.07 (1.01, 1.13) Q4: 14.4–16.41,670329,3601.05 (0.99, 1.12)1.03 (0.97, 1.10) Q5: ≥16.51,141327,8391.12 (1.04, 1.21)1.10 (1.02, 1.19) p for trendc0.020.07 Continuous (10 μg/m3)9,8271,637,0331.09 (1.02, 1.17)1.07 (1.00, 1.15)Note: CI, confidence interval; HR, hazard ratio; MI, myocardial infarction; PM2.5, particulate matter <2.5 microns; Q, quintile; Ref, referent.aBasic model: adjusted for age and race (White yes/no).bFully adjusted model: additionally adjusted for incident cancer (yes/no), family history of myocardial infarction (yes/no), smoking status (never, past, current), pack-years, Alternate Healthy Eating Index score quartiles, alcohol consumption (0.0, <5.0, 5.0–9.9, 10.0–19.9, or ≥20.0g/d), multivitamin use (yes/no), census tract median income (USD), census tract median home value (USD), occupation father (professional or other), occupation mother (housewife or other), husband's level of education more than high school (yes/no), registered nursing degree in 1992 (yes/no), marital status (married or not married), retirement status (retired or not retired).cp for trend based on median quintile values.There was a consistent decreased risk of MI and/or stroke and overall mortality associated with higher overall physical activity (Table 3; Figures 1–3). In fully adjusted models, those in the highest quartile of physical activity (≥24.4MET-h/wk) had 0.61 times the risk of MI or stroke (95% CI: 0.57, 0.66; ptrend<0.0001), 0.64 times the risk of MI (95% CI: 0.58, 0.71; ptrend<0.0001), 0.58 times the risk of stroke (95% CI: 0.52, 0.65; ptrend<0.0001), and 0.40 times the risk of death (95% CI: 0.37, 0.42; ptrend<0.0001) in comparison with those in the lowest quartile of overall physical activity (<3.7MET-h/wk). Continuous analyses based on a 9 MET-h/wk greater overall physical activity were consistent, with 0.98 times the risk of MI or stroke (95% CI: 0.97, 0.98), 0.98 times the risk of MI (95% CI: 0.97, 0.98), 0.97 times the risk of stroke (95% CI: 0.97, 0.98), and 0.95 times the risk of death (95% CI: 0.94, 0.95). Results from analyses for walking and participation in any vigorous physical activity were consistent with those for overall physical activity. Among those who reported participating in any vigorous physical activity (jogging, running, biking, swimming, or tennis) (33% of the study population), higher vigorous physical activity was associated with lower risk for overall CVD, MI, stroke, and overall mortality.Table 3 Associations between physical activity and incident myocardial infarction, stroke, and overall mortality among Nurses' Health Study participants 1988–2008 (N=104,990).Table 3 has five columns, namely, Outcome, Cases (lowercase italic n), Person-years (lowercase italic n), Basic begin superscript lowercase a end superscript hazard ratio (95 percent confidence intervals), and Fully adjusted begin superscript lowercase b end superscript hazard ratio (95 percent confidence intervals).OutcomeCases (n)Person-years (n)Basica HR (95% CI)Fully adjustedb HR (95% CI)Overall physical
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