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Zimmerman ME, Hart LJ, Medrano P, Piccone C, Ramirez DM, Huggins LK, Sotres-Alvarez D, Fish LJ, Østbye T, Holliday KM. COVID-19 in the Community: Changes to Women's Mental Health, Financial Security, and Physical Activity. AJPM Focus 2023; 2:100095. [PMID: 37234692 PMCID: PMC10039779 DOI: 10.1016/j.focus.2023.100095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/28/2023]
Abstract
Introduction This study describes changes in the mental health, financial security, and physical activity levels of women in North Carolina during the COVID-19 pandemic. Methods Data were collected from women aged 20-40 years receiving primary care at 2 health centers in North Carolina during 2020-2022. Surveys (N=127) evaluated changes in mental health, financial security, and physical activity during the COVID-19 pandemic. These outcomes were analyzed both descriptively and for association with sociodemographic factors using logistic regression. A subset of participants (n=46) participated in semistructured interviews. Interview transcripts were reviewed and evaluated for recurring themes by primary and secondary coders using a rapid-coding technique. Analysis was conducted in 2022. Results Women surveyed were 28.4% non-Hispanic White, 38.6% non-Hispanic Black, and 33.1% Hispanic/Latina. Compared with reports before the pandemic, participants reported increased frustration or boredom (69.1%), loneliness (51.6%), anxiety (64.3%), depression (52.4%), and changed sleep patterns (68.3%). Increased alcohol and other recreational substance use were associated with race and ethnicity (p<0.05) after adjustment for other sociodemographic factors. Participants reported difficulty in paying for basic expenses (44.0%). Financial difficulties during COVID-19 were associated with non-Hispanic Black race and ethnicity, less education, and lower prepandemic household income. Data showed pandemic-associated reductions in mild (32.8%), moderate (39.5%), and strenuous (43.3%) exercise, with a correlation between increased depression and reduced mild exercise. Interviews identified themes including reduced activity while working remotely, lack of gym access, and reduced motivation for exercise. Conclusions This mixed-methods study is one of the first to evaluate the mental health, financial security, and physical activity challenges women aged between 20 and 40 years in the southern U.S. faced during the COVID-19 pandemic.
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Affiliation(s)
| | - Lauren J. Hart
- Department of Family Medicine & Community Health, Duke University School of Medicine, Durham, North Carolina
| | - Perla Medrano
- Duke Global Health Institute, Duke University, Durham, North Carolina
| | - Caitlin Piccone
- Department of Family Medicine & Community Health, Duke University School of Medicine, Durham, North Carolina
| | - Diana M. Ramirez
- Sanford School of Public Policy, Duke University, Durham, North Carolina
| | - Lenique K.L. Huggins
- Duke Global Health Institute, Duke University, Durham, North Carolina
- Department of Biology, Trinity College of Arts and Sciences, Duke University, Durham, North Carolina
| | - Daniela Sotres-Alvarez
- Department of Biostatistics, Gillings School of Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Laura J. Fish
- Department of Family Medicine & Community Health, Duke University School of Medicine, Durham, North Carolina
| | - Truls Østbye
- Department of Family Medicine & Community Health, Duke University School of Medicine, Durham, North Carolina
- Duke Global Health Institute, Duke University, Durham, North Carolina
| | - Katelyn M. Holliday
- Department of Family Medicine & Community Health, Duke University School of Medicine, Durham, North Carolina
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Lin K, White MJ, Holliday KM, Parnell LS, Parente VM. Protective and Unequal? Caregiver Presence During Pediatric Hospitalizations. Hosp Pediatr 2023; 13:e1-e5. [PMID: 36482776 PMCID: PMC9881426 DOI: 10.1542/hpeds.2022-006590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
OBJECTIVES Describe the association between caregiver presence on hospital day 1 and outcomes related to readmissions, pain, and adverse events (AE). METHODS Caregiver presence during general pediatrics rounds on hospital day 1 was recorded, along with demographic data and clinical outcomes via chart review. AE data were obtained from the safety reporting system. χ2 tests compared demographic characteristics between present and absent caregivers. Background elimination determined significant predictors of caregiver presence and their association with outcomes. RESULTS A total of 324 families were assessed (34.9% non-Hispanic white, 41.4% Black, 17% Hispanic or Latinx, 6.8% other race or ethnicity). Adolescents (aged ≥14 years) had increased odds of not having a caregiver present compared with 6- to 13-year-olds (36.2% vs 10%; adjusted odds ratio [aOR] 5.11 [95% confidence interval (CI) 1.88-13.87]). Publicly insured children were more likely to not have a caregiver present versus privately insured children (25.1% vs 12.4%; aOR 2.38 [95% CI 1.19-4.73]). Compared with having a caregiver present, children without caregivers were more likely to be readmitted at 7 days (aOR 3.6 [95% CI 1.0-12.2]), receive opiates for moderate/severe pain control (aOR 11.5 [95% CI 1.7-75.7]), and have an AE reported (aOR 4.0 [95% CI 1.0-15.1]). CONCLUSIONS Adolescents and children with public insurance were less likely to have a caregiver present. Not having a caregiver present was associated with increased readmission, opiate prescription, and AE reporting. Further research is needed to delineate whether associations with clinical outcomes reflect differences in quality of care and decrease barriers to caregiver presence.
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Affiliation(s)
- Karen Lin
- Department of Graduate Medical Education, Duke University Health System, Durham, North Carolina
| | - Michelle J. White
- Department of Pediatrics, Duke University Health System, Durham, North Carolina
| | - Katelyn M. Holliday
- Family Medicine and Community Health at Duke University Health System, Durham, North Carolina
| | - Lisa S. Parnell
- Department of Pediatrics, Duke University Health System, Durham, North Carolina
| | - Victoria M. Parente
- Department of Pediatrics, Duke University Health System, Durham, North Carolina
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Holliday KM, Gondalia R, Baldassari A, Justice AE, Stewart JD, Liao D, Yanosky JD, Jordahl KM, Bhatti P, Assimes TL, Pankow JS, Guan W, Fornage M, Bressler J, North KE, Conneely KN, Li Y, Hou L, Vokonas PS, Ward-Caviness CK, Wilson R, Wolf K, Waldenberger M, Cyrys J, Peters A, Boezen HM, Vonk JM, Sayols-Baixeras S, Lee M, Baccarelli AA, Whitsel EA. Gaseous air pollutants and DNA methylation in a methylome-wide association study of an ethnically and environmentally diverse population of U.S. adults. Environ Res 2022; 212:113360. [PMID: 35500859 PMCID: PMC9354583 DOI: 10.1016/j.envres.2022.113360] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 04/18/2022] [Accepted: 04/20/2022] [Indexed: 06/03/2023]
Abstract
Epigenetic mechanisms may underlie air pollution-health outcome associations. We estimated gaseous air pollutant-DNA methylation (DNAm) associations using twelve subpopulations within Women's Health Initiative (WHI) and Atherosclerosis Risk in Communities (ARIC) cohorts (n = 8397; mean age 61.3 years; 83% female; 46% African-American, 46% European-American, 8% Hispanic/Latino). We used geocoded participant address-specific mean ambient carbon monoxide (CO), nitrogen oxides (NO2; NOx), ozone (O3), and sulfur dioxide (SO2) concentrations estimated over the 2-, 7-, 28-, and 365-day periods before collection of blood samples used to generate Illumina 450 k array leukocyte DNAm measurements. We estimated methylome-wide, subpopulation- and race/ethnicity-stratified pollutant-DNAm associations in multi-level, linear mixed-effects models adjusted for sociodemographic, behavioral, meteorological, and technical covariates. We combined stratum-specific estimates in inverse variance-weighted meta-analyses and characterized significant associations (false discovery rate; FDR<0.05) at Cytosine-phosphate-Guanine (CpG) sites without among-strata heterogeneity (PCochran's Q > 0.05). We attempted replication in the Cooperative Health Research in Region of Augsburg (KORA) study and Normative Aging Study (NAS). We observed a -0.3 (95% CI: -0.4, -0.2) unit decrease in percent DNAm per interquartile range (IQR, 7.3 ppb) increase in 28-day mean NO2 concentration at cg01885635 (chromosome 3; regulatory region 290 bp upstream from ZNF621; FDR = 0.03). At intragenic sites cg21849932 (chromosome 20; LIME1; intron 3) and cg05353869 (chromosome 11; KLHL35; exon 2), we observed a -0.3 (95% CI: -0.4, -0.2) unit decrease (FDR = 0.04) and a 1.2 (95% CI: 0.7, 1.7) unit increase (FDR = 0.04), respectively, in percent DNAm per IQR (17.6 ppb) increase in 7-day mean ozone concentration. Results were not fully replicated in KORA and NAS. We identified three CpG sites potentially susceptible to gaseous air pollution-induced DNAm changes near genes relevant for cardiovascular and lung disease. Further harmonized investigations with a range of gaseous pollutants and averaging durations are needed to determine the effect of gaseous air pollutants on DNA methylation and ultimately gene expression.
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Affiliation(s)
- Katelyn M Holliday
- Department of Family Medicine and Community Health, School of Medicine, Duke University, Durham, NC, USA; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.
| | - Rahul Gondalia
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Antoine Baldassari
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | | | - James D Stewart
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Duanping Liao
- Division of Epidemiology, Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Jeff D Yanosky
- Division of Epidemiology, Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Kristina M Jordahl
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
| | - Parveen Bhatti
- Cancer Control Research, BC Cancer, Vancouver, BC, Canada
| | | | - James S Pankow
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA
| | - Weihua Guan
- Division of Biostatistics, University of Minnesota, Minneapolis, MN, USA
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA; Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Jan Bressler
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Karen N Conneely
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Yun Li
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA; Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA; Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University Chicago, Evanston, IL, USA; Center for Population Epigenetics, Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University Chicago, Evanston, IL, USA
| | - Pantel S Vokonas
- VA Normative Aging Study, VA Boston Healthcare System, Schools of Medicine and Public Health, Boston University, Boston, MA, USA
| | - Cavin K Ward-Caviness
- Environmental Public Health Division, National Health and Environmental Effects Research Laboratory, 104 Mason Farm Rd, Chapel Hill, NC, 27514, USA
| | - Rory Wilson
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany; Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Kathrin Wolf
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany; Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Josef Cyrys
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany; Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig Maximilians University, Munich, Germany
| | - H Marike Boezen
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, the Netherlands; University of Groningen, University Medical Center Groningen, GRIAC Research Institute, the Netherlands
| | - Judith M Vonk
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, the Netherlands; University of Groningen, University Medical Center Groningen, GRIAC Research Institute, the Netherlands
| | - Sergi Sayols-Baixeras
- Cardiovascular Epidemiology and Genetics Research Group, Hospital Del Mar Medical Research Institute (IMIM), Campus Del Mar, Universitat Pompeu Fabra, Barcelona, Spain; Consorcio CIBER, M.P. Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain; Molecular Epidemiology and Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Mikyeong Lee
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Andrea A Baccarelli
- Laboratory of Environmental Epigenetics, Departments of Environmental Health Sciences and Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Eric A Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA; Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
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White MJ, Holliday KM, Hoover S, Robinson-Ezekwe N, Corbie-Smith G, Williams A, Bess K, Frerichs L. The significant places of African American adults and their perceived influence on cardiovascular disease risk behaviors. BMC Public Health 2021; 21:2018. [PMID: 34740336 PMCID: PMC8570769 DOI: 10.1186/s12889-021-12022-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Accepted: 10/13/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND AA living in rural areas of the southeastern U.S. experience a disproportionate burden of cardiovascular disease (CVD) morbidity and mortality. Neighborhood environmental factors contribute to this disparity and may decrease the effectiveness of lifestyle interventions aimed at preventing CVD. Furthermore, the influence of neighborhood factors on AA CVD risk behaviors (i.e. physical activity) may be obscured by the use of researcher-defined neighborhoods and researcher-defined healthy and unhealthy places. The objective of this study was to elucidate the effects of neighborhood environments on AA CVD risk behaviors among AA adults who recently completed a lifestyle intervention. We specifically sought to identify AA adults' self-perceived places of significance and their perceptions of how these places impact CVD risk behaviors including diet, physical activity and smoking. METHODS We conducted semi-structured interviews with AA adults (N = 26) living in two rural North Carolina counties (Edgecombe and Nash, North Carolina, USA). Participants were recruited from a community-based behavioral CVD risk reduction intervention. All had at least one risk factor for CVD. Participants identified significant places including where they spent the most time, meaningful places, and healthy and unhealthy places on local maps. Using these maps as a reference, participants described the impact of each location on their CVD risk behaviors. Data were transcribed verbatim and coded using NVivo 12. RESULTS The average age of participants was 63 (SD = 10) and 92% were female. Places participants defined as meaningful and places where they spent the most time included churches and relatives' homes. Healthy places included gyms and parks. Unhealthy places included fast food restaurants and relatives' homes where unhealthy food was served. Place influenced CVD risk behaviors in multiple ways including through degree of perceived control over the environment, emotional attachment and loneliness, caretaking responsibilities, social pressures and social support. CONCLUSIONS As we seek to improve cardiovascular interventions for rural AA in the American South, it will be important to further assess the effect of significant places beyond place of residence. Strategies which leverage or modify behavioral influences within person-defined significant places may improve the reach and effectiveness of behavioral lifestyle interventions.
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Affiliation(s)
- Michelle J White
- Department of Pediatrics, Duke University School of Medicine, DUMC 102376, 2301 Erwin Rd, Durham, NC, 27705, USA.
| | - Katelyn M Holliday
- Department of Family Medicine and Community Health, Duke University School of Medicine, DUMC 2914, Durham, NC, 27710, USA
| | - Stephanie Hoover
- Center for Health Equity Research, Department of Social Medicine, University of North Carolina at Chapel Hill, 323 MacNider Hall, CB #7240, Chapel Hill, NC, 27599-7240, USA
| | - Nicole Robinson-Ezekwe
- Center for Health Equity Research, Department of Social Medicine, University of North Carolina at Chapel Hill, 323 MacNider Hall, CB #7240, Chapel Hill, NC, 27599-7240, USA
| | - Giselle Corbie-Smith
- Center for Health Equity Research, Department of Social Medicine, University of North Carolina at Chapel Hill, 323 MacNider Hall, CB #7240, Chapel Hill, NC, 27599-7240, USA
| | - Anissa Williams
- Center for Health Equity Research, Department of Social Medicine, University of North Carolina at Chapel Hill, 323 MacNider Hall, CB #7240, Chapel Hill, NC, 27599-7240, USA
| | - Kiana Bess
- Department of Health Behavior and Health Education, University of Michigan School of Public Health, 1415 Washington Heights, Ann Arbor, MI, 48109-2029, USA
| | - Leah Frerichs
- Center for Health Equity Research, Department of Social Medicine, University of North Carolina at Chapel Hill, 323 MacNider Hall, CB #7240, Chapel Hill, NC, 27599-7240, USA
- Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 170 Roseneau Hall, CB #7400, Chapel Hill, NC, 27599-7400, USA
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5
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Gondalia R, Baldassari A, Holliday KM, Justice AE, Stewart JD, Liao D, Yanosky JD, Engel SM, Sheps D, Jordahl KM, Bhatti P, Horvath S, Assimes TL, Demerath EW, Guan W, Fornage M, Bressler J, North KE, Conneely KN, Li Y, Hou L, Baccarelli AA, Whitsel EA. Epigenetically mediated electrocardiographic manifestations of sub-chronic exposures to ambient particulate matter air pollution in the Women's Health Initiative and Atherosclerosis Risk in Communities Study. Environ Res 2021; 198:111211. [PMID: 33895111 PMCID: PMC8179344 DOI: 10.1016/j.envres.2021.111211] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 03/10/2021] [Accepted: 04/19/2021] [Indexed: 06/03/2023]
Abstract
BACKGROUND Short-duration exposure to ambient particulate matter (PM) air pollution is associated with cardiac autonomic dysfunction and prolonged ventricular repolarization. However, associations with sub-chronic exposures to coarser particulates are relatively poorly characterized as are molecular mechanisms underlying their potential relationships with cardiovascular disease. MATERIALS AND METHODS We estimated associations between monthly mean concentrations of PM < 10 μm and 2.5-10 μm in diameter (PM10; PM2.5-10) with time-domain measures of heart rate variability (HRV) and QT interval duration (QT) among U.S. women and men in the Women's Health Initiative and Atherosclerosis Risk in Communities Study (nHRV = 82,107; nQT = 76,711). Then we examined mediation of the PM-HRV and PM-QT associations by DNA methylation (DNAm) at three Cytosine-phosphate-Guanine (CpG) sites (cg19004594, cg24102420, cg12124767) with known sensitivity to monthly mean PM concentrations in a subset of the participants (nHRV = 7,169; nQT = 6,895). After multiply imputing missing PM, electrocardiographic and covariable data, we estimated associations using attrition-weighted, linear, mixed, longitudinal models adjusting for sociodemographic, behavioral, meteorological, and clinical characteristics. We assessed mediation by estimating the proportions of PM-HRV and PM-QT associations mediated by DNAm. RESULTS We found little evidence of PM-HRV association, PM-QT association, or mediation by DNAm. CONCLUSIONS The findings suggest that among racially/ethnically and environmentally diverse U.S. populations, sub-chronic exposures to coarser particulates may not exert appreciable, epigenetically mediated effects on cardiac autonomic function or ventricular repolarization. Further investigation in better-powered studies is warranted, with additional focus on shorter duration exposures to finer particulates and non-electrocardiographic outcomes among relatively susceptible populations.
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Affiliation(s)
- Rahul Gondalia
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.
| | - Antoine Baldassari
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Katelyn M Holliday
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA; Department of Community and Family Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Anne E Justice
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA; Geisinger Health System, Danville, PA, USA
| | - James D Stewart
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Duanping Liao
- Division of Epidemiology, Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Jeff D Yanosky
- Division of Epidemiology, Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Stephanie M Engel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - David Sheps
- Department of Epidemiology, University of Florida, Gainesville, FL, USA
| | - Kristina M Jordahl
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
| | - Parveen Bhatti
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
| | - Steve Horvath
- Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA; Biostatistics, School of Public Health, University of California Los Angeles, Los Angeles, USA
| | | | - Ellen W Demerath
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA
| | - Weihua Guan
- Division of Biostatistics, University of Minnesota, Minneapolis, MN, USA
| | - Myriam Fornage
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Jan Bressler
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA; Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC, USA
| | - Karen N Conneely
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Yun Li
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA; Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA; Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University Chicago, Evanston, IL, USA; Center for Population Epigenetics, Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Andrea A Baccarelli
- Laboratory of Environmental Epigenetics, Departments of Environmental Health Sciences and Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Eric A Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA; Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
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6
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Gondalia R, Holliday KM, Baldassari A, Justice AE, Stewart JD, Liao D, Yanosky JD, Engel SM, Jordahl KM, Bhatti P, Horvath S, Assimes TL, Pankow JS, Demerath EW, Guan W, Fornage M, Bressler J, North KE, Conneely KN, Li Y, Hou L, Baccarelli AA, Whitsel EA. Leukocyte Traits and Exposure to Ambient Particulate Matter Air Pollution in the Women's Health Initiative and Atherosclerosis Risk in Communities Study. Environ Health Perspect 2020; 128:17004. [PMID: 31903802 PMCID: PMC7015624 DOI: 10.1289/ehp5360] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Revised: 09/25/2019] [Accepted: 12/03/2019] [Indexed: 05/20/2023]
Abstract
BACKGROUND Inflammatory effects of ambient particulate matter (PM) air pollution exposures may underlie PM-related increases in cardiovascular disease risk and mortality, although evidence of PM-associated leukocytosis is inconsistent and largely based on small, cross-sectional, and/or unrepresentative study populations. OBJECTIVES Our objective was to estimate PM-leukocyte associations among U.S. women and men in the Women's Health Initiative and Atherosclerosis Risk in Communities study (n = 165,675 ). METHODS We based the PM-leukocyte estimations on up to four study visits per participant, at which peripheral blood leukocytes and geocoded address-specific concentrations of PM ≤ 10 , ≤ 2.5 , and 2.5 - 10 μ m in diameter (PM 10 , PM 2.5 , and PM 2.5 - 10 , respectively) were available. We multiply imputed missing data using chained equations and estimated PM-leukocyte count associations over daily to yearly PM exposure averaging periods using center-specific, linear, mixed, longitudinal models weighted for attrition and adjusted for sociodemographic, behavioral, meteorological, and geographic covariates. In a subset of participants with available data (n = 8,457 ), we also estimated PM-leukocyte proportion associations in compositional data analyses. RESULTS We found a 12 cells / μ L (95% confidence interval: - 9 , 33) higher leukocyte count, a 1.2% (0.6%, 1.8%) higher granulocyte proportion, and a - 1.1 % (- 1.9 % , - 0.3 % ) lower CD 8 + T-cell proportion per 10 - μ g / m 3 increase in 1-month mean PM 2.5 . However, shorter-duration PM 10 exposures were inversely and only modestly associated with leukocyte count. DISCUSSION The PM 2.5 -leukocyte estimates, albeit imprecise, suggest that among racially, ethnically, and environmentally diverse U.S. populations, sustained, ambient exposure to fine PM may induce subclinical, but epidemiologically important, inflammatory effects. https://doi.org/10.1289/EHP5360.
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Affiliation(s)
- Rahul Gondalia
- Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, North Carolina
| | - Katelyn M. Holliday
- Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, North Carolina
- Department of Community and Family Medicine, Duke University School of Medicine, Durham, North Carolina
| | - Antoine Baldassari
- Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, North Carolina
| | - Anne E. Justice
- Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, North Carolina
- Geisinger Health System, Danville, Pennsylvania
| | - James D. Stewart
- Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, North Carolina
| | - Duanping Liao
- Division of Epidemiology, Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, Pennsylvania
| | - Jeff D. Yanosky
- Division of Epidemiology, Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, Pennsylvania
| | - Stephanie M. Engel
- Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, North Carolina
| | - Kristina M. Jordahl
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington
| | - Parveen Bhatti
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington
| | - Steve Horvath
- Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
- Department of Biostatistics, School of Public Health, University of California, Los Angeles, Los Angeles, California
| | | | - James S. Pankow
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota
| | - Ellen W. Demerath
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota
| | - Weihua Guan
- Division of Biostatistics, University of Minnesota, Minneapolis, Minnesota
| | - Myriam Fornage
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, Texas
| | - Jan Bressler
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas
| | - Kari E. North
- Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, North Carolina
- Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Karen N. Conneely
- Department of Human Genetics, Emory University School of Medicine, Atlanta, Georgia
| | - Yun Li
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
- Department of Biostatistics, University of North Carolina Gillings School of Global Public Health, Chapel Hill, North Carolina
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
- Center for Population Epigenetics, Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Andrea A. Baccarelli
- Laboratory of Environmental Epigenetics, Departments of Environmental Health Sciences and Epidemiology, Columbia University Mailman School of Public Health, New York, New York
| | - Eric A. Whitsel
- Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, North Carolina
- Department of Medicine, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
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7
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Gondalia R, Baldassari A, Holliday KM, Justice AE, Méndez-Giráldez R, Stewart JD, Liao D, Yanosky JD, Brennan KJM, Engel SM, Jordahl KM, Kennedy E, Ward-Caviness CK, Wolf K, Waldenberger M, Cyrys J, Peters A, Bhatti P, Horvath S, Assimes TL, Pankow JS, Demerath EW, Guan W, Fornage M, Bressler J, North KE, Conneely KN, Li Y, Hou L, Baccarelli AA, Whitsel EA. Methylome-wide association study provides evidence of particulate matter air pollution-associated DNA methylation. Environ Int 2019; 132:104723. [PMID: 31208937 PMCID: PMC6754789 DOI: 10.1016/j.envint.2019.03.071] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2018] [Revised: 03/28/2019] [Accepted: 03/29/2019] [Indexed: 05/17/2023]
Abstract
BACKGROUND DNA methylation (DNAm) may contribute to processes that underlie associations between air pollution and poor health. Therefore, our objective was to evaluate associations between DNAm and ambient concentrations of particulate matter (PM) ≤2.5, ≤10, and 2.5-10 μm in diameter (PM2.5; PM10; PM2.5-10). METHODS We conducted a methylome-wide association study among twelve cohort- and race/ethnicity-stratified subpopulations from the Women's Health Initiative and the Atherosclerosis Risk in Communities study (n = 8397; mean age: 61.5 years; 83% female; 45% African American; 9% Hispanic/Latino American). We averaged geocoded address-specific estimates of daily and monthly mean PM concentrations over 2, 7, 28, and 365 days and 1 and 12 months before exams at which we measured leukocyte DNAm in whole blood. We estimated subpopulation-specific, DNAm-PM associations at approximately 485,000 Cytosine-phosphate-Guanine (CpG) sites in multi-level, linear, mixed-effects models. We combined subpopulation- and site-specific estimates in fixed-effects, inverse variance-weighted meta-analyses, then for associations that exceeded methylome-wide significance and were not heterogeneous across subpopulations (P < 1.0 × 10-7; PCochran's Q > 0.10), we characterized associations using publicly accessible genomic databases and attempted replication in the Cooperative Health Research in the Region of Augsburg (KORA) study. RESULTS Analyses identified significant DNAm-PM associations at three CpG sites. Twenty-eight-day mean PM10 was positively associated with DNAm at cg19004594 (chromosome 20; MATN4; P = 3.33 × 10-8). One-month mean PM10 and PM2.5-10 were positively associated with DNAm at cg24102420 (chromosome 10; ARPP21; P = 5.84 × 10-8) and inversely associated with DNAm at cg12124767 (chromosome 7; CFTR; P = 9.86 × 10-8). The PM-sensitive CpG sites mapped to neurological, pulmonary, endocrine, and cardiovascular disease-related genes, but DNAm at those sites was not associated with gene expression in blood cells and did not replicate in KORA. CONCLUSIONS Ambient PM concentrations were associated with DNAm at genomic regions potentially related to poor health among racially, ethnically and environmentally diverse populations of U.S. women and men. Further investigation is warranted to uncover mechanisms through which PM-induced epigenomic changes may cause disease.
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Affiliation(s)
- Rahul Gondalia
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.
| | - Antoine Baldassari
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Katelyn M Holliday
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA; Department of Community and Family Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Anne E Justice
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA; Geisinger Health System, Danville, PA, USA
| | - Raúl Méndez-Giráldez
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - James D Stewart
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Duanping Liao
- Division of Epidemiology, Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Jeff D Yanosky
- Division of Epidemiology, Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Kasey J M Brennan
- Laboratory of Environmental Epigenetics, Departments of Environmental Health Sciences and Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Stephanie M Engel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Kristina M Jordahl
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
| | - Elizabeth Kennedy
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Cavin K Ward-Caviness
- Environmental Public Health Division, National Health and Environmental Effects Research Laboratory, 104 Mason Farm Rd, Chapel Hill, NC, USA
| | - Kathrin Wolf
- Institute of Epidemiology, Helmholtz Zentrum München, Ingolstaedter Landstrasse 1, Neuherberg, Germany
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Ingolstaedter Landstrasse 1, Neuherberg, Germany
| | - Josef Cyrys
- Institute of Epidemiology, Helmholtz Zentrum München, Ingolstaedter Landstrasse 1, Neuherberg, Germany; Environmental Science Center, University of Augsburg, Augsburg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, Ingolstaedter Landstrasse 1, Neuherberg, Germany
| | - Parveen Bhatti
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
| | - Steve Horvath
- Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA; Biostatistics, School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
| | | | - James S Pankow
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA
| | - Ellen W Demerath
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA
| | - Weihua Guan
- Division of Biostatistics, University of Minnesota, Minneapolis, MN, USA
| | - Myriam Fornage
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Jan Bressler
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA; Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC, USA
| | - Karen N Conneely
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Yun Li
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA; Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA; Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University Chicago, Evanston, IL, USA; Center for Population Epigenetics, Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University Chicago, Evanston, IL, USA
| | - Andrea A Baccarelli
- Laboratory of Environmental Epigenetics, Departments of Environmental Health Sciences and Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Eric A Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA; Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
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Porter AK, Schilsky S, Evenson KR, Florido R, Palta P, Holliday KM, Folsom AR. The Association of Sport and Exercise Activities With Cardiovascular Disease Risk: The Atherosclerosis Risk in Communities (ARIC) Study. J Phys Act Health 2019; 16:698-705. [PMID: 31369998 PMCID: PMC6994359 DOI: 10.1123/jpah.2018-0671] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Revised: 03/25/2019] [Accepted: 06/03/2019] [Indexed: 11/18/2022]
Abstract
BACKGROUND This study assessed the independent associations between participation in self-reported sport and exercise activities and incident cardiovascular disease (CVD). METHODS Data were from 13,204 participants in the Atherosclerosis Risk in Communities Study cohort (1987-2015). Baseline sport and exercise activities were assessed via the modified Baecke questionnaire. Incident CVD included coronary heart disease, heart failure, or stroke. Multivariable-adjusted Cox proportional hazard models assessed the association of participation in specific sport and exercise activities at enrollment with risk of CVD. RESULTS During a median follow-up time of 25.2 years, 30% of the analytic sample (n = 3966) was diagnosed with incident CVD. In fully adjusted models, participation in racquet sports (hazard ratio [HR] 0.75; 95% confidence interval [CI], 0.61-0.93), aerobics (HR 0.75; 95% CI, 0.63-0.88), running (HR 0.68; 95% CI, 0.54-0.85), and walking (HR 0.89; 95% CI, 0.83-0.95) was significantly associated with a lower risk of CVD. There were no significant associations for bicycling, softball/baseball, gymnastics, swimming, basketball, calisthenics exercises, golfing with cart, golfing with walking, bowling, or weight training. CONCLUSIONS Participation in specific sport and exercises may substantially reduce the risk for CVD.
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9
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Engeda JC, Holliday KM, Hardy ST, Chakladar S, Lin DY, Talavera GA, Howard BV, Daviglus ML, Pirzada A, Schreiner PJ, Zeng D, Avery CL. Transitions from Ideal to Intermediate Cholesterol Levels may vary by Cholesterol Metric. Sci Rep 2018; 8:2782. [PMID: 29426885 PMCID: PMC5807429 DOI: 10.1038/s41598-018-20660-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2017] [Accepted: 01/09/2018] [Indexed: 11/08/2022] Open
Abstract
To examine the ability of total cholesterol (TC), a low-density lipoprotein cholesterol (LDL-C) proxy widely used in public health initiatives, to capture important population-level shifts away from ideal and intermediate LDL-C throughout adulthood. We estimated age (≥20 years)-, race/ethnic (Caucasian, African American, and Hispanic/Latino)-, and sex- specific net transition probabilities between ideal, intermediate, and poor TC and LDL-C using National Health and Nutrition Examination Survey (2007-2014; N = 13,584) and Hispanic Community Health Study/Study of Latinos (2008-2011; N = 15,612) data in 2016 and validated and calibrated novel Markov-type models designed for cross-sectional data. At age 20, >80% of participants had ideal TC, whereas the race/ethnic- and sex-specific prevalence of ideal LDL-C ranged from 39.2%-59.6%. Net transition estimates suggested that the largest one-year net shifts away from ideal and intermediate LDL-C occurred approximately two decades earlier than peak net population shifts away from ideal and intermediate TC. Public health and clinical initiatives focused on monitoring TC in middle-adulthood may miss important shifts away from ideal and intermediate LDL-C, potentially increasing the duration, perhaps by decades, that large segments of the population are exposed to suboptimal LDL-C.
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Affiliation(s)
- Joseph C Engeda
- Departments of Epidemiology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | - Katelyn M Holliday
- Departments of Epidemiology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Shakia T Hardy
- Departments of Epidemiology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Sujatro Chakladar
- Departments of Biostatistics, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Dan-Yu Lin
- Departments of Biostatistics, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Gregory A Talavera
- Division of Health Promotion and Behavioral Science, San Diego State University, San Diego, CA, USA
| | - Barbara V Howard
- MedStar Health Research Institute and Georgetown/Howard Universities Center for Clinical and Translational Sciences, Hyattsville, MD, USA
| | - Martha L Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL, USA
| | - Amber Pirzada
- Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL, USA
| | - Pamela J Schreiner
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA
| | - Donglin Zeng
- Departments of Biostatistics, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Christy L Avery
- Departments of Epidemiology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Population Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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10
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Holliday KM, Howard AG, Emch M, Rodríguez DA, Rosamond WD, Evenson KR. Deriving a GPS Monitoring Time Recommendation for Physical Activity Studies of Adults. Med Sci Sports Exerc 2017; 49:939-947. [PMID: 28009791 DOI: 10.1249/mss.0000000000001190] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
INTRODUCTION Determining locations of physical activity (PA) is important for surveillance and intervention development, yet recommendations for using location recording tools like global positioning system (GPS) units are lacking. Specifically, no recommendation exists for the number of days study participants should wear a GPS to reliably estimate PA time spent in locations. METHODS This study used data from participants (N = 224, age = 18-85 yr) in five states who concurrently wore an ActiGraph GT1M accelerometer and a Qstarz BT-Q1000X GPS for three consecutive weeks to construct monitoring day recommendations through variance partitioning methods. PA bouts ≥10 min were constructed from accelerometer counts, and the location of GPS points was determined using a hand-coding protocol. RESULTS Monitoring day recommendations varied by the type of location (e.g., participant homes vs parks) and the intensity of PA bouts considered (low and medium cut point moderate to vigorous PA [MVPA] bouts or high cut point vigorous PA [VPA] bouts). In general, minutes of all PA intensities spent in a given location could be measured with ≥80% reliability using 1-3 d of GPS monitoring for fitness facilities, schools, and footpaths. MVPA bout minutes in parks and roads required longer monitoring periods of 5-12 d. PA in homes and commercial areas required >19 d of monitoring. CONCLUSIONS Twelve days of monitoring was found to reliably estimate minutes in both low and medium threshold MVPA as well as VPA bouts for many important built environment locations that can be targeted to increase PA at the population level. Minutes of PA in the home environment and commercial locations may be best assessed through other means given the lengthy estimated monitoring time required.
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Affiliation(s)
- Katelyn M Holliday
- 1Department of Epidemiology, University of North Carolina, Chapel Hill, NC; 2Department of Biostatistics, University of North Carolina, Chapel Hill, NC; 3Department of Geography, University of North Carolina, Chapel Hill, NC; and 4Department of City and Regional Planning, University of California, Berkeley, CA
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11
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Abstract
Increasing physical activity (PA) at the population level requires appropriately targeting intervention development. Identifying the locations in which participants with various sociodemographic, body weight, and geographic characteristics tend to engage in varying intensities of PA as well as locations these populations underutilize for PA may facilitate this process. A visual location-coding protocol was developed and implemented in Google Fusion Tables and Maps using data from participants (N = 223, age 18-85) in five states. Participants concurrently wore ActiGraph GT1M accelerometers and Qstarz BT-Q1000X GPS units for 3 weeks to identify locations of moderate-to-vigorous (MVPA) or vigorous (VPA) bouts. Cochran-Mantel-Haenzel general association tests examined usage differences by participant characteristics (sex, age, race/ethnicity, education, body mass index (BMI), and recruitment city). Homes and roads encompassed >40% of bout-based PA minutes regardless of PA intensity. Fitness facilities and schools were important for VPA (19 and 12% of bout minutes). Parks were used for 13% of MVPA bout minutes but only 4% of VPA bout minutes. Hispanics, those without a college degree, and overweight/obese participants frequently completed MVPA bouts at home. Older adults often used roads for MVPA bouts. Hispanics, those with ≤high school education, and healthy/overweight participants frequently had MVPA bouts in parks. Applying a new location-coding protocol in a diverse population showed that adult PA locations varied by PA intensity, sociodemographic characteristics, BMI, and geographic location. Although homes, roads, and parks remain important locations for demographically targeted PA interventions, observed usage patterns by participant characteristics may facilitate development of more appropriately targeted interventions.
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Affiliation(s)
- Katelyn M Holliday
- Department of Epidemiology, University of North Carolina, 137 E. Franklin Street, Suite 306, Chapel Hill, NC, 27514, USA.
| | - Annie Green Howard
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA
| | - Michael Emch
- Department of Epidemiology, University of North Carolina, 137 E. Franklin Street, Suite 306, Chapel Hill, NC, 27514, USA
- Department of Geography, University of North Carolina, Chapel Hill, NC, USA
| | - Daniel A Rodríguez
- Department of City and Regional Planning, University of California, Berkeley, CA, USA
| | - Wayne D Rosamond
- Department of Epidemiology, University of North Carolina, 137 E. Franklin Street, Suite 306, Chapel Hill, NC, 27514, USA
| | - Kelly R Evenson
- Department of Epidemiology, University of North Carolina, 137 E. Franklin Street, Suite 306, Chapel Hill, NC, 27514, USA
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12
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Hardy ST, Holliday KM, Chakladar S, Engeda JC, Allen NB, Heiss G, Lloyd-Jones DM, Schreiner PJ, Shay CM, Lin D, Zeng D, Avery CL. Heterogeneity in Blood Pressure Transitions Over the Life Course: Age-Specific Emergence of Racial/Ethnic and Sex Disparities in the United States. JAMA Cardiol 2017; 2:653-661. [PMID: 28423153 PMCID: PMC5634332 DOI: 10.1001/jamacardio.2017.0652] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Importance Many studies have assessed racial/ethnic and sex disparities in the prevalence of elevated blood pressure (BP) from childhood to adulthood, yet few have examined differences in age-specific transitions between categories of BP over the life course in contemporary, multiracial/multiethnic populations. Objective To estimate age, racial/ethnic, and sex-specific annual net transition probabilities between categories of BP using Markov modeling of cross-sectional data from the National Health and Nutrition Examination Survey. Design, Setting, and Participants National probability sample (National Health and Nutrition Examination Survey in 2007-2008, 2009-2010, and 2011-2012) of 17 747 African American, white American, and Mexican American participants aged 8 to 80 years. The data were analyzed from September 2014 to November 2015. Main Outcomes and Measures Age-specific American Heart Association-defined BP categories. Results Three National Health and Nutrition Examination Survey cross-sectional samples were used to characterize the ages at which self-reported African American (n = 4973), white American (n = 8886), and Mexican American (n = 3888) populations transitioned between ideal BP, prehypertension, and hypertension across the life course. At age 8 years, disparities in the prevalence of ideal BP were observed, with the prevalence being lower among boys (86.6%-88.8%) compared with girls (93.0%-96.3%). From ages 8 to 30 years, annual net transition probabilities from ideal to prehypertension among male individuals were more than 2 times the net transition probabilities of their female counterparts. The largest net transition probabilities for ages 8 to 30 years occurred in African American young men, among whom a net 2.9% (95% CI, 2.3%-3.4%) of those with ideal BP transitioned to prehypertension 1 year later. Mexican American young women aged 8 to 30 years experienced the lowest ideal to prehypertension net transition probabilities (0.6%; 95% CI, 0.3%-0.8%). After age 40 years, ideal to prehypertension net transition probabilities stabilized or decreased (range, 3.0%-4.5%) for men, whereas net transition probabilities for women increased rapidly (range, 2.6%-13.0%). Mexican American women exhibited the largest ideal to prehypertension net transition probabilities after age 60 years. The largest prehypertension to hypertension net transition probabilities occurred at young ages in boys of white race/ethnicity and African Americans, approximately age 8 years and age 25 years, respectively, while net transition probabilities for white women and Mexican Americans increased over the life course. Conclusions and Relevance Heterogeneity in net transition probabilities from ideal BP emerge during childhood, with associated rapid declines in ideal BP observed in boys and African Americans, thus introducing disparities. Primordial prevention beginning in childhood and into early adulthood is necessary to preempt the development of prehypertension and hypertension, as well as associated racial/ethnic and sex disparities.
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Affiliation(s)
- Shakia T Hardy
- Department of Epidemiology, The University of North Carolina at Chapel Hill
| | - Katelyn M Holliday
- Department of Epidemiology, The University of North Carolina at Chapel Hill
| | - Sujatro Chakladar
- Department of Biostatistics, The University of North Carolina at Chapel Hill
| | - Joseph C Engeda
- Department of Epidemiology, The University of North Carolina at Chapel Hill
| | - Norrina B Allen
- Department of Preventive Medicine, Northwestern University, Chicago, Illinois
| | - Gerardo Heiss
- Department of Epidemiology, The University of North Carolina at Chapel Hill
| | | | - Pamela J Schreiner
- Division of Epidemiology & Community Health, School of Public Health, University of Minnesota, Minneapolis
| | - Christina M Shay
- Department of Nutrition, The University of North Carolina at Chapel Hill
| | - Danyu Lin
- Department of Biostatistics, The University of North Carolina at Chapel Hill
| | - Donglin Zeng
- Department of Biostatistics, The University of North Carolina at Chapel Hill
| | - Christy L Avery
- Department of Epidemiology, The University of North Carolina at Chapel Hill
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13
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Holliday KM, Lin DY, Chakladar S, Castañeda SF, Daviglus ML, Evenson KR, Marquez DX, Qi Q, Shay CM, Sotres-Alvarez D, Vidot DC, Zeng D, Avery CL. Targeting physical activity interventions for adults: When should intervention occur? Prev Med 2017; 97:13-18. [PMID: 28024863 PMCID: PMC5337155 DOI: 10.1016/j.ypmed.2016.12.036] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2016] [Revised: 11/29/2016] [Accepted: 12/21/2016] [Indexed: 11/25/2022]
Abstract
Understanding demographic differences in transitions across physical activity (PA) levels is important for informing PA-promoting interventions, yet few studies have examined these transitions in contemporary multi-ethnic adult populations. We estimated age-, race/ethnicity-, and sex-specific 1-year net transition probabilities (NTPs) for National Health and Nutrition Examination Survey (2007-2012, n=11,556) and Hispanic Community Health Study/Study of Latinos (2008-2011, n=15,585) adult participants using novel Markov-type state transition models developed for cross-sectional data. Among populations with ideal PA (≥150min/week; ranging from 56% (non-Hispanic black females) to 88% (non-Hispanic white males) at age 20), NTPs to intermediate PA (>0-<149min/week) generally increased with age, particularly for non-Hispanic black females for whom a net 0.0% (95% confidence interval (CI): 0.0, 0.2) transitioned from ideal to intermediate PA at age 20; by age 70, the NTP rose to 3.6% (95% CI: 2.3, 4.8). Heterogeneity in intermediate to poor (0min/week) PA NTPs also was observed, with NTPs peaking at age 20 for Hispanic/Latino males and females [age 20 NTP=3.7% (95% CI: 2.0, 5.5) for females and 5.0% (1.2, 8.7) for males], but increasing throughout adulthood for non-Hispanic blacks and whites [e.g. age 70 NTP=7.8% (95% CI: 6.1, 9.6%) for black females and 8.1% (4.7, 11.6) for black males]. Demographic differences in PA net transitions across adulthood justify further development of tailored interventions. However, innovative efforts may be required for populations in which large proportions have already transitioned from ideal PA by early adulthood.
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Affiliation(s)
- Katelyn M Holliday
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 137 E. Franklin Street Suite 306, Chapel Hill, NC 27514, USA.
| | - Dan Yu Lin
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive, 3101 McGavran-Greenburg Hall, Chapel Hill, NC 27514, USA.
| | - Sujatro Chakladar
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive, 3101 McGavran-Greenburg Hall, Chapel Hill, NC 27514, USA.
| | - Sheila F Castañeda
- Graduate School of Public Health, San Diego State University, 5500 Campanile Dr., San Diego, CA 92182, USA.
| | - Martha L Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, 1819 W. Polk Street, Suite 246, Chicago, IL 60612, USA.
| | - Kelly R Evenson
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 137 E. Franklin Street Suite 306, Chapel Hill, NC 27514, USA.
| | - David X Marquez
- Department of Kinesiology and Nutrition, University of Illinois at Chicago, 1919 W. Taylor Street, Room 625, MC 994, Chicago, IL 60612, USA.
| | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Belfer 1306A, Bronx, NY 10461, USA.
| | - Christina M Shay
- Department of Nutrition, University of North Carolina at Chapel Hill, 2201 McGavran- Greenberg Hall, Chapel Hill, NC 27599, USA.
| | - Daniela Sotres-Alvarez
- Collaborative Studies Coordinating Center, Department of Biostatistics, University of North Carolina at Chapel Hill, 137 E. Franklin Street, Suite 203, Chapel Hill, NC 27514, USA.
| | - Denise C Vidot
- University of Miami, Miller School of Medicine, Clinical Research Building, 1120 NW 14th Street, Suite 1515, Miami, FL 33136, USA.
| | - Donglin Zeng
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive, 3101 McGavran-Greenburg Hall, Chapel Hill, NC 27514, USA.
| | - Christy L Avery
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 137 E. Franklin Street Suite 306, Chapel Hill, NC 27514, USA.
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14
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Avery CL, Holliday KM, Chakladar S, Engeda JC, Hardy ST, Reis JP, Schreiner PJ, Shay CM, Daviglus ML, Heiss G, Lin DY, Zeng D. Disparities in Early Transitions to Obesity in Contemporary Multi-Ethnic U.S. Populations. PLoS One 2016; 11:e0158025. [PMID: 27348868 PMCID: PMC4922630 DOI: 10.1371/journal.pone.0158025] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2016] [Accepted: 05/24/2016] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND Few studies have examined weight transitions in contemporary multi-ethnic populations spanning early childhood through adulthood despite the ability of such research to inform obesity prevention, control, and disparities reduction. METHODS AND RESULTS We characterized the ages at which African American, Caucasian, and Mexican American populations transitioned to overweight and obesity using contemporary and nationally representative cross-sectional National Health and Nutrition Examination Survey data (n = 21,220; aged 2-80 years). Age-, sex-, and race/ethnic-specific one-year net transition probabilities between body mass index-classified normal weight, overweight, and obesity were estimated using calibrated and validated Markov-type models that accommodated complex sampling. At age two, the obesity prevalence ranged from 7.3% in Caucasian males to 16.1% in Mexican American males. For all populations, estimated one-year overweight to obesity net transition probabilities peaked at age two and were highest for Mexican American males and African American females, for whom a net 12.3% (95% CI: 7.6%-17.0%) and 11.9% (95% CI: 8.5%-15.3%) of the overweight populations transitioned to obesity by age three, respectively. However, extrapolation to the 2010 U.S. population demonstrated that Mexican American males were the only population for whom net increases in obesity peaked during early childhood; age-specific net increases in obesity were approximately constant through the second decade of life for African Americans and Mexican American females and peaked at age 20 for Caucasians. CONCLUSIONS African American and Mexican American populations shoulder elevated rates of many obesity-associated chronic diseases and disparities in early transitions to obesity could further increase these inequalities if left unaddressed.
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Affiliation(s)
- Christy L. Avery
- Department of Epidemiology, the University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Katelyn M. Holliday
- Department of Epidemiology, the University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Sujatro Chakladar
- Department of Biostatistics, the University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Joseph C. Engeda
- Department of Epidemiology, the University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Shakia T. Hardy
- Department of Epidemiology, the University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Jared P. Reis
- Epidemiology Branch, Population and Prevention Sciences Program, Division of Cardiovascular Sciences, National Heart, Lung and Blood Institute, Bethesda, Maryland, United States of America
| | - Pamela J. Schreiner
- Division of Epidemiology & Community Health, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Christina M. Shay
- Department of Nutrition, the University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Martha L. Daviglus
- Department of Medicine Institute for Minority Health Research, University of Illinois at Chicago, Chicago, Illinois, United States of America
| | - Gerardo Heiss
- Department of Epidemiology, the University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Dan Yu Lin
- Department of Biostatistics, the University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Donglin Zeng
- Department of Biostatistics, the University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
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15
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Evenson KR, Jones SA, Holliday KM, Cohen DA, McKenzie TL. Park characteristics, use, and physical activity: A review of studies using SOPARC (System for Observing Play and Recreation in Communities). Prev Med 2016; 86:153-66. [PMID: 26946365 PMCID: PMC4837088 DOI: 10.1016/j.ypmed.2016.02.029] [Citation(s) in RCA: 120] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2015] [Revised: 01/18/2016] [Accepted: 02/18/2016] [Indexed: 11/28/2022]
Abstract
The System for Observing Play and Recreation in Communities (SOPARC) can obtain information on park users and their physical activity using momentary time sampling. We conducted a literature review of studies using the SOPARC tool to describe the observational methods of each study, and to extract public park use overall and by demographics and physical activity levels. We searched PubMed, Embase, and SPORTDiscus for full-length observational studies published in English in peer-reviewed journals through 2014. Twenty-four studies from 34 articles were included. The number of parks observed per study ranged from 3 to 50. Most studies observed parks during one season. The number of days parks were observed ranged from 1 to 16, with 16 studies observing 5 or more days. All studies included at least one weekday and all but two included at least one weekend day. Parks were observed from 1 to 14times/day, with most studies observing at least 4 times/day. All studies included both morning and afternoon observations, with one exception. There was a wide range of park users (mean 1.0 to 152.6 people/park/observation period), with typically more males than females visiting parks and older adults less than other age groups. Park user physical activity levels varied greatly across studies, with youths generally more active than adults and younger children more active than adolescents. SOPARC was adapted to numerous settings and these review results can be used to improve future studies using the tool, demonstrate ways to compare park data, and inform park promotions and programming.
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Affiliation(s)
- Kelly R Evenson
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina - Chapel Hill, 137 East Franklin Street, Suite 306, Chapel Hill, NC 27514, United States.
| | - Sydney A Jones
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina - Chapel Hill, 137 East Franklin Street, Suite 306, Chapel Hill, NC 27514, United States.
| | - Katelyn M Holliday
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina - Chapel Hill, 137 East Franklin Street, Suite 306, Chapel Hill, NC 27514, United States.
| | - Deborah A Cohen
- RAND Corporation, 1776 Main Street, Santa Monica, CA 90407, United States.
| | - Thomas L McKenzie
- School of Exercise and Nutritional Sciences, San Diego State University, 5127 Walsh Way, San Diego, CA 92115, United States.
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16
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Holliday KM, Avery CL, Poole C, McGraw K, Williams R, Liao D, Smith RL, Whitsel EA. Estimating personal exposures from ambient air pollution measures: using meta-analysis to assess measurement error. Epidemiology 2014; 25:35-43. [PMID: 24220191 PMCID: PMC3973436 DOI: 10.1097/ede.0000000000000006] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
BACKGROUND Although ambient concentrations of particulate matter ≤10 μm (PM10) are often used as proxies for total personal exposure, correlation (r) between ambient and personal PM10 concentrations varies. Factors underlying this variation and its effect on health outcome-PM exposure relationships remain poorly understood. METHODS We conducted a random-effects meta-analysis to estimate effects of study, participant, and environmental factors on r; used the estimates to impute personal exposure from ambient PM10 concentrations among 4,012 nonsmoking, participants with diabetes in the Women's Health Initiative clinical trial; and then estimated the associations of ambient and imputed personal PM10 concentrations with electrocardiographic measures, such as heart rate variability. RESULTS We identified 15 studies (in years 1990-2009) of 342 participants in five countries. The median r was 0.46 (range = 0.13 to 0.72). There was little evidence of funnel plot asymmetry but substantial heterogeneity of r, which increased 0.05 (95% confidence interval = 0.01 to 0.09) per 10 µg/m increase in mean ambient PM10 concentration. Substituting imputed personal exposure for ambient PM10 concentrations shifted mean percent changes in electrocardiographic measures per 10 µg/m increase in exposure away from the null and decreased their precision, for example, -2.0% (-4.6% to 0.7%) versus -7.9% (-15.9% to 0.9%), for the standard deviation of normal-to-normal RR interval duration. CONCLUSIONS Analogous distributions and heterogeneity of r in extant meta-analyses of ambient and personal PM2.5 concentrations suggest that observed shifts in mean percent change and decreases in precision may be generalizable across particle size.
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Affiliation(s)
- Katelyn M Holliday
- From the aDepartment of Epidemiology, University of North Carolina, Chapel Hill, NC; bHealth Sciences Library, University of North Carolina, Chapel Hill, NC; cUnited States Environmental Protection Agency, Research Triangle Park, Durham, NC; dDepartment of Public Health Sciences, Pennsylvania State University, Hershey, PA; eStatistical and Mathematical Sciences Institute, Research Triangle Park, Durham, NC; fDepartment of Statistics and Operations Research, University of North Carolina, Chapel Hill, NC; and gDepartment of Medicine, University of North Carolina, Chapel Hill, NC
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