Person: Laden, Francine
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Laden
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Francine
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Laden, Francine
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Publication Spatial clustering of physical activity and obesity in relation to built environment factors among older women in three U.S. states(BioMed Central, 2014) Tamura, Kosuke; Puett, Robin C; Hart, Jaime; Starnes, Heather A; Laden, Francine; Troped, Philip JBackground: Identifying spatial clusters of chronic diseases has been conducted over the past several decades. More recently these approaches have been applied to physical activity and obesity. However, few studies have investigated built environment characteristics in relation to these spatial clusters. This study’s aims were to detect spatial clusters of physical activity and obesity, examine whether the geographic distribution of covariates affects clusters, and compare built environment characteristics inside and outside clusters. Methods: In 2004, Nurses’ Health Study participants from California, Massachusetts, and Pennsylvania completed survey items on physical activity (N = 22,599) and weight-status (N = 19,448). The spatial scan statistic was utilized to detect spatial clustering of higher and lower likelihood of obesity and meeting physical activity recommendations via walking. Clustering analyses and tests that adjusted for socio-demographic and health-related variables were conducted. Neighborhood built environment characteristics for participants inside and outside spatial clusters were compared. Results: Seven clusters of physical activity were identified in California and Massachusetts. Two clusters of obesity were identified in Pennsylvania. Overall, adjusting for socio-demographic and health-related covariates had little effect on the size or location of clusters in the three states with a few exceptions. For instance, adjusting for husband’s education fully accounted for physical activity clusters in California. In California and Massachusetts, population density, intersection density, and diversity and density of facilities in two higher physical activity clusters were significantly greater than in neighborhoods outside of clusters. In contrast, in two other higher physical activity clusters in California and Massachusetts, population density, diversity of facilities, and density of facilities were significantly lower than in areas outside of clusters. In Pennsylvania, population density, intersection density, diversity of facilities, and certain types of facility density inside obesity clusters were significantly lower compared to areas outside the clusters. Conclusions: Spatial clustering techniques can identify high and low risk areas for physical activity and obesity. Although covariates significantly differed inside and outside the clusters, patterns of differences were mostly inconsistent. The findings from these spatial analyses could eventually facilitate the design and implementation of more resource-efficient, geographically targeted interventions for both physical activity and obesity.Publication Autism Spectrum Disorder and Particulate Matter Air Pollution before, during, and after Pregnancy: A Nested Case–Control Analysis within the Nurses’ Health Study II Cohort(NLM-Export, 2014) Raz, Raanan; Roberts, Andrea L.; Lyall, Kristen; Hart, Jaime; Just, Allan C.; Laden, Francine; Weisskopf, MarcBackground: Autism spectrum disorder (ASD) is a developmental disorder with increasing prevalence worldwide, yet has unclear etiology. Objective: We explored the association between maternal exposure to particulate matter (PM) air pollution and odds of ASD in her child. Methods: We conducted a nested case–control study of participants in the Nurses’ Health Study II (NHS II), a prospective cohort of 116,430 U.S. female nurses recruited in 1989, followed by biennial mailed questionnaires. Subjects were NHS II participants’ children born 1990–2002 with ASD (n = 245), and children without ASD (n = 1,522) randomly selected using frequency matching for birth years. Diagnosis of ASD was based on maternal report, which was validated against the Autism Diagnostic Interview-Revised in a subset. Monthly averages of PM with diameters ≤ 2.5 μm (PM2.5) and 2.5–10 μm (PM10–2.5) were predicted from a spatiotemporal model for the continental United States and linked to residential addresses. Results: PM2.5 exposure during pregnancy was associated with increased odds of ASD, with an adjusted odds ratio (OR) for ASD per interquartile range (IQR) higher PM2.5 (4.42 μg/m3) of 1.57 (95% CI: 1.22, 2.03) among women with the same address before and after pregnancy (160 cases, 986 controls). Associations with PM2.5 exposure 9 months before or after the pregnancy were weaker in independent models and null when all three time periods were included, whereas the association with the 9 months of pregnancy remained (OR = 1.63; 95% CI: 1.08, 2.47). The association between ASD and PM2.5 was stronger for exposure during the third trimester (OR = 1.42 per IQR increase in PM2.5; 95% CI: 1.09, 1.86) than during the first two trimesters (ORs = 1.06 and 1.00) when mutually adjusted. There was little association between PM10–2.5 and ASD. Conclusions: Higher maternal exposure to PM2.5 during pregnancy, particularly the third trimester, was associated with greater odds of a child having ASD. Citation Raz R, Roberts AL, Lyall K, Hart JE, Just AC, Laden F, Weisskopf MG. 2015. Autism spectrum disorder and particulate matter air pollution before, during, and after pregnancy: a nested case–control analysis within the Nurses’ Health Study II cohort. Environ Health Perspect 123:264–270; http://dx.doi.org/10.1289/ehp.1408133Publication The relations between sleep, time of physical activity, and time outdoors among adult women(Public Library of Science, 2017) Murray, Kate; Godbole, Suneeta; Natarajan, Loki; Full, Kelsie; Hipp, J. Aaron; Glanz, Karen; Mitchell, Jonathan; Laden, Francine; James, Peter; Quante, Mirja; Kerr, JacquelinePhysical activity and time spent outdoors may be important non-pharmacological approaches to improve sleep quality and duration (or sleep patterns) but there is little empirical research evaluating the two simultaneously. The current study assesses the role of physical activity and time outdoors in predicting sleep health by using objective measurement of the three variables. A convenience sample of 360 adult women (mean age = 55.38 ±9.89 years; mean body mass index = 27.74 ±6.12) was recruited from different regions of the U.S. Participants wore a Global Positioning System device and ActiGraph GT3X+ accelerometers on the hip for 7 days and on the wrist for 7 days and 7 nights to assess total time and time of day spent outdoors, total minutes in moderate-to-vigorous physical activity per day, and 4 measures of sleep health, respectively. A generalized mixed-effects model was used to assess temporal associations between moderate-to-vigorous physical activity, outdoor time, and sleep at the daily level (days = 1931) within individuals. There was a significant interaction (p = 0.04) between moderate-to-vigorous physical activity and time spent outdoors in predicting total sleep time but not for predicting sleep efficiency. Increasing time outdoors in the afternoon (versus morning) predicted lower sleep efficiency, but had no effect on total sleep time. Time spent outdoors and the time of day spent outdoors may be important moderators in assessing the relation between physical activity and sleep. More research is needed in larger populations using experimental designs.Publication The relation between past exposure to fine particulate air pollution and prevalent anxiety: observational cohort study(BMJ Publishing Group Ltd., 2015) Power, Melinda C; Kioumourtzoglou, Marianthi-Anna; Hart, Jaime; Okereke, Olivia; Laden, Francine; Weisskopf, MarcObjective: To determine whether higher past exposure to particulate air pollution is associated with prevalent high symptoms of anxiety. Design: Observational cohort study. Setting: Nurses’ Health Study. Participants: 71 271 women enrolled in the Nurses’ Health Study residing throughout the contiguous United States who had valid estimates on exposure to particulate matter for at least one exposure period of interest and data on anxiety symptoms. Main outcome measures Meaningfully high symptoms of anxiety, defined as a score of 6 points or greater on the phobic anxiety subscale of the Crown-Crisp index, administered in 2004. Results: The 71 271 eligible women were aged between 57 and 85 years (mean 70 years) at the time of assessment of anxiety symptoms, with a prevalence of high anxiety symptoms of 15%. Exposure to particulate matter was characterized using estimated average exposure to particulate matter <2.5 μm in diameter (PM2.5) and 2.5 to 10 μm in diameter (PM2.5-10) in the one month, three months, six months, one year, and 15 years prior to assessment of anxiety symptoms, and residential distance to the nearest major road two years prior to assessment. Significantly increased odds of high anxiety symptoms were observed with higher exposure to PM2.5 for multiple averaging periods (for example, odds ratio per 10 µg/m3 increase in prior one month average PM2.5: 1.12, 95% confidence interval 1.06 to 1.19; in prior 12 month average PM2.5: 1.15, 1.06 to 1.26). Models including multiple exposure windows suggested short term averaging periods were more relevant than long term averaging periods. There was no association between anxiety and exposure to PM2.5-10. Residential proximity to major roads was not related to anxiety symptoms in a dose dependent manner. Conclusions: Exposure to fine particulate matter (PM2.5) was associated with high symptoms of anxiety, with more recent exposures potentially more relevant than more distant exposures. Research evaluating whether reductions in exposure to ambient PM2.5 would reduce the population level burden of clinically relevant symptoms of anxiety is warranted.Publication Residential Greenness and Birthweight in the State of Massachusetts, USA(MDPI AG, 2018-06-12) Fong, Kelvin; Coull, Brent; Koutrakis, Petros; Laden, Francine; Schwartz, Joel; James, PeterPublication Environmental radon exposure and breast cancer risk in the Nurses’ Health Study II(BioMed Central, 2017) VoPham, Trang; DuPré, Natalie; Tamimi, Rulla; James, Peter; Bertrand, Kimberly A.; Vieira, Veronica; Laden, Francine; Hart, JaimeBackground: Radon and its decay products, a source of ionizing radiation, are primarily inhaled and can deliver a radiation dose to breast tissue, where they may continue to decay and emit DNA damage-inducing particles. Few studies have examined the relationship between radon and breast cancer. Methods: The Nurses’ Health Study II (NHSII) includes U.S. female registered nurses who completed biennial questionnaires since 1989. Self-reported breast cancer was confirmed from medical records. County-level radon exposures were linked with geocoded residential addresses updated throughout follow-up. Time-varying Cox regression models adjusted for established breast cancer risk factors were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). Results: From 1989 to 2013, 3966 invasive breast cancer cases occurred among 112,639 participants. Increasing radon exposure was not associated with breast cancer risk overall (adjusted HR comparing highest to lowest quintile = 1.06, 95% CI: 0.94, 1.21, p for trend = 0.30). However, women in the highest quintile of exposure (≥74.9 Bq/m3) had a suggested elevated risk of ER−/PR- breast cancer compared to women in the lowest quintile (<27.0 Bq/m3) (adjusted HR = 1.38, 95% CI: 0.97, 1.96, p for trend = 0.05). No association was observed for ER+/PR+ breast cancer. Conclusions: Although we did not find an association between radon exposure and risk of overall or ER+/PR+ breast cancer, we observed a suggestive association with risk of ER−/PR- breast cancer. Electronic supplementary material The online version of this article (10.1186/s12940-017-0305-6) contains supplementary material, which is available to authorized users.Publication Residential particulate matter and distance to roadways in relation to mammographic density: results from the Nurses’ Health Studies(BioMed Central, 2017) DuPre, Natalie; Hart, Jaime; Bertrand, Kimberly A.; Kraft, Phillip; Laden, Francine; Tamimi, RullaBackground: High mammographic density is a strong, well-established breast cancer risk factor. Three studies conducted in various smaller geographic settings reported inconsistent findings between air pollution and mammographic density. We assessed whether particulate matter (PM) exposures (PM2.5, PM2.5–10, and PM10) and distance to roadways were associated with mammographic density among women residing across the United States. Methods: The Nurses’ Health Studies are prospective cohorts for whom a subset has screening mammograms from the 1990s (interquartile range 1990–1999). PM was estimated using spatio-temporal models linked to residential addresses. Among 3258 women (average age at mammogram 52.7 years), we performed multivariable linear regression to assess associations between square-root-transformed mammographic density and PM within 1 and 3 years before the mammogram. For linear regression estimates of PM in relation to untransformed mammographic density outcomes, bootstrapped robust standard errors are used to calculate 95% confidence intervals (CIs). Analyses were stratified by menopausal status and region of residence. Results: Recent PM and distance to roadways were not associated with mammographic density in premenopausal women (PM2.5 within 3 years before mammogram β = 0.05, 95% CI –0.16, 0.27; PM2.5–10 β = 0, 95%, CI –0.15, 0.16; PM10 β = 0.02, 95% CI –0.10, 0.13) and postmenopausal women (PM2.5 within 3 years before mammogram β = –0.05, 95% CI –0.27, 0.17; PM2.5–10 β = –0.01, 95% CI –0.16, 0.14; PM10 β = –0.02, 95% CI –0.13, 0.09). Largely null associations were observed within regions. Suggestive associations were observed among postmenopausal women in the Northeast (n = 745), where a 10-μg/m3 increase in PM2.5 within 3 years before the mammogram was associated with 3.4 percentage points higher percent mammographic density (95% CI –0.5, 7.3). Conclusions: These findings do not support that recent PM or roadway exposures influence mammographic density. Although PM was largely not associated with mammographic density, we cannot rule out the role of PM during earlier exposure time windows and possible associations among northeastern postmenopausal women. Electronic supplementary material The online version of this article (doi:10.1186/s13058-017-0915-5) contains supplementary material, which is available to authorized users.Publication Genome-wide Association Study Identifies Multiple Risk Loci for Chronic Lymphocytic Leukemia(2013) Berndt, Sonja I.; Skibola, Christine F.; Joseph, Vijai; Camp, Nicola J.; Nieters, Alexandra; Wang, Zhaoming; Cozen, Wendy; Monnereau, Alain; Wang, Sophia S.; Kelly, Rachel S.; Lan, Qing; Teras, Lauren R.; Chatterjee, Nilanjan; Chung, Charles C.; Yeager, Meredith; Brooks-Wilson, Angela R.; Hartge, Patricia; Purdue, Mark P.; Birmann, Brenda; Armstrong, Bruce K.; Cocco, Pierluigi; Zhang, Yawei; Severi, Gianluca; Zeleniuch-Jacquotte, Anne; Lawrence, Charles; Burdette, Laurie; Yuenger, Jeffrey; Hutchinson, Amy; Jacobs, Kevin B.; Call, Timothy G.; Shanafelt, Tait D.; Novak, Anne J.; Kay, Neil E.; Liebow, Mark; Wang, Alice H.; Smedby, Karin E; Adami, Hans-Olov; Melbye, Mads; Glimelius, Bengt; Chang, Ellen T.; Glenn, Martha; Curtin, Karen; Cannon-Albright, Lisa A.; Jones, Brandt; Diver, W. Ryan; Link, Brian K.; Weiner, George J.; Conde, Lucia; Bracci, Paige M.; Riby, Jacques; Holly, Elizabeth A.; Smith, Martyn T.; Jackson, Rebecca D.; Tinker, Lesley F.; Benavente, Yolanda; Becker, Nikolaus; Boffetta, Paolo; Brennan, Paul; Foretova, Lenka; Maynadie, Marc; McKay, James; Staines, Anthony; Rabe, Kari G.; Achenbach, Sara J.; Vachon, Celine M.; Goldin, Lynn R; Strom, Sara S.; Lanasa, Mark C.; Spector, Logan G.; Leis, Jose F.; Cunningham, Julie M.; Weinberg, J. Brice; Morrison, Vicki A.; Caporaso, Neil E.; Norman, Aaron D.; Linet, Martha S.; De Roos, Anneclaire J.; Morton, Lindsay M.; Severson, Richard K.; Riboli, Elio; Vineis, Paolo; Kaaks, Rudolph; Trichopoulos, Dimitrios; Masala, Giovanna; Weiderpass, Elisabete; Chirlaque, María-Dolores; Vermeulen, Roel C H; Travis, Ruth C.; Giles, Graham G.; Albanes, Demetrius; Virtamo, Jarmo; Weinstein, Stephanie; Clavel, Jacqueline; Zheng, Tongzhang; Holford, Theodore R; Offit, Kenneth; Zelenetz, Andrew; Klein, Robert J.; Spinelli, John J.; Bertrand, Kimberly; Laden, Francine; Giovannucci, Edward; Kraft, Phillip; Kricker, Anne; Turner, Jenny; Vajdic, Claire M.; Ennas, Maria Grazia; Ferri, Giovanni M.; Miligi, Lucia; Liang, Liming; Sampson, Joshua; Crouch, Simon; Park, Ju-hyun; North, Kari E.; Cox, Angela; Snowden, John A.; Wright, Josh; Carracedo, Angel; Lopez-Otin, Carlos; Bea, Silvia; Salaverria, Itziar; Martin, David; Campo, Elias; Fraumeni, Joseph F.; de Sanjose, Silvia; Hjalgrim, Henrik; Cerhan, James R.; Chanock, Stephen J.; Rothman, Nathaniel; Slager, Susan L.Publication Exposure measurement error in PM2.5 health effects studies: A pooled analysis of eight personal exposure validation studies(BioMed Central, 2014) Kioumourtzoglou, Marianthi-Anna; Spiegelman, Donna; Szpiro, Adam A; Sheppard, Lianne; Kaufman, Joel D; Yanosky, Jeff D; Williams, Ronald; Laden, Francine; Hong, Biling; Suh, HelenBackground: Exposure measurement error is a concern in long-term PM2.5 health studies using ambient concentrations as exposures. We assessed error magnitude by estimating calibration coefficients as the association between personal PM2.5 exposures from validation studies and typically available surrogate exposures. Methods: Daily personal and ambient PM2.5, and when available sulfate, measurements were compiled from nine cities, over 2 to 12 days. True exposure was defined as personal exposure to PM2.5 of ambient origin. Since PM2.5 of ambient origin could only be determined for five cities, personal exposure to total PM2.5 was also considered. Surrogate exposures were estimated as ambient PM2.5 at the nearest monitor or predicted outside subjects’ homes. We estimated calibration coefficients by regressing true on surrogate exposures in random effects models. Results: When monthly-averaged personal PM2.5 of ambient origin was used as the true exposure, calibration coefficients equaled 0.31 (95% CI:0.14, 0.47) for nearest monitor and 0.54 (95% CI:0.42, 0.65) for outdoor home predictions. Between-city heterogeneity was not found for outdoor home PM2.5 for either true exposure. Heterogeneity was significant for nearest monitor PM2.5, for both true exposures, but not after adjusting for city-average motor vehicle number for total personal PM2.5. Conclusions: Calibration coefficients were <1, consistent with previously reported chronic health risks using nearest monitor exposures being under-estimated when ambient concentrations are the exposure of interest. Calibration coefficients were closer to 1 for outdoor home predictions, likely reflecting less spatial error. Further research is needed to determine how our findings can be incorporated in future health studies.Publication Perinatal Air Pollutant Exposures and Autism Spectrum Disorder in the Children of Nurses’ Health Study II Participants(National Institute of Environmental Health Sciences, 2013) Roberts, Andrea L.; Lyall, Kristen; Hart, Jaime; Laden, Francine; Just, Allan C.; Bobb, Jennifer; Koenen, Karestan C.; Ascherio, Alberto; Weisskopf, Marc G.Objective: Air pollution contains many toxicants known to affect neurological function and to have effects on the fetus in utero. Recent studies have reported associations between perinatal exposure to air pollutants and autism spectrum disorder (ASD) in children. We tested the hypothesis that perinatal exposure to air pollutants is associated with ASD, focusing on pollutants associated with ASD in prior studies. Methods: We estimated associations between U.S. Environmental Protection Agency–modeled levels of hazardous air pollutants at the time and place of birth and ASD in the children of participants in the Nurses’ Health Study II (325 cases, 22,101 controls). Our analyses focused on pollutants associated with ASD in prior research. We accounted for possible confounding and ascertainment bias by adjusting for family-level socioeconomic status (maternal grandparents’ education) and census tract–level socioeconomic measures (e.g., tract median income and percent college educated), as well as maternal age at birth and year of birth. We also examined possible differences in the relationship between ASD and pollutant exposures by child’s sex. Results: Perinatal exposures to the highest versus lowest quintile of diesel, lead, manganese, mercury, methylene chloride, and an overall measure of metals were significantly associated with ASD, with odds ratios ranging from 1.5 (for overall metals measure) to 2.0 (for diesel and mercury). In addition, linear trends were positive and statistically significant for these exposures (p < .05 for each). For most pollutants, associations were stronger for boys (279 cases) than for girls (46 cases) and significantly different according to sex. Conclusions: Perinatal exposure to air pollutants may increase risk for ASD. Additionally, future studies should consider sex-specific biological pathways connecting perinatal exposure to pollutants with ASD.