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Zeki Al Hazzouri A, Jawadekar N, Kezios K, Caunca MR, Elfassy T, Calonico S, Kershaw KN, Yaffe K, Launer L, Elbejjani M, Grasset L, Manly J, Odden MC, Glymour MM. Racial Residential Segregation in Young Adulthood and Brain Integrity in Middle Age: Can We Learn From Small Samples? Am J Epidemiol 2022; 191:591-598. [PMID: 35020781 DOI: 10.1093/aje/kwab297] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Revised: 12/15/2021] [Accepted: 12/28/2021] [Indexed: 12/15/2022] Open
Abstract
Racial residential segregation is associated with multiple adverse health outcomes in Black individuals. Yet, the influence of structural racism and racial residential segregation on brain aging is less understood. In this study, we investigated the association between cumulative exposure to racial residential segregation over 25 years (1985-2010) in young adulthood, as measured by the Getis-Ord Gi* statistic, and year 25 measures of brain volume (cerebral, gray matter, white matter, and hippocampal volumes) in midlife. We studied 290 Black participants with available brain imaging data who were enrolled in the Coronary Artery Risk Development in Young Adults (CARDIA) Study, a prospective cohort study. CARDIA investigators originally recruited 2,637 Black participants aged 18-30 years from 4 field centers across the United States. We conducted analyses using marginal structural models, incorporating inverse probability of treatment weighting and inverse probability of censoring weighting. We found that compared with low/medium segregation, greater cumulative exposure to a high level of racial residential segregation throughout young adulthood was associated with smaller brain volumes in general (e.g., for cerebral volume, β = -0.08, 95% confidence interval: -0.15, -0.02) and with a more pronounced reduction in hippocampal volume, though results were not statistically significant. Our findings suggest that exposure to segregated neighborhoods may be associated with worse brain aging.
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An NP's guide to current physical activity recommendations. Nurse Pract 2020; 45:24-31. [PMID: 32826536 DOI: 10.1097/01.npr.0000694708.74213.53] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Physical inactivity is a public health crisis that contributes to many of the chronic diseases that affect Americans. This review emphasizes the beneficial health implications of physical activity along with the dangers of sedentary lifestyles. It also provides advice tailored to NPs to help their patients become more physically active.
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Brayton SH, Bosch TA, Bantle AE, Hodges JS, Dengel DR, Chow LS. The impact of high BMI on acute changes in body composition following 90 minutes of running. COGENT MEDICINE 2018; 5:1502960. [PMID: 31380465 PMCID: PMC6677399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023] Open
Abstract
OBJECTIVES Although physical activity ameliorates the metabolic impact of high body mass index (BMI), runners with BMI≥25 kg/m2 are relatively understudied.This study had two goals: 1) Identify differences in body composition, as measured by dual X-ray absorptiometry (DXA), between overweight (BMI≥25 kg/m2) runners (OWR) and normal weight (BMI<25 kg/m2) runners (NWR) and 2) Examine whether an 90 minute run alters total or regional fat mass, as measured by DXA, in OWR and NWR. We hypothesized that OWR would have higher total body fat than NWR and OWR with greater changes in visceral fat after a prolonged run. DESIGN Body composition analysis before and after a supervised run. METHODS We recruited NWR (n=16,F:n=7,28.1±1.4 years, BMI 22.0±0.4 kg/m2, results as mean±SE) and OWR (n=11,F:n=7,32.0±1.6 years, BMI 30.5±1.4kg/m2) participants. DXA based body composition was measured before and after a supervised, 90 minute run at 60% heart rate reserve. RESULTS OWR had higher body fat than NWR in all measured regions.. Both groups did not significantly reduce fat mass at any measured fat depots after the running exposure. CONCLUSIONS OWR had higher body fat in all measured regions than NWR. DXA could not demonstrate any acute fat mass changes after a prolonged run.
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Affiliation(s)
- Seth H Brayton
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, University of Minnesota, MMC 101, 420 Delaware St. SE, Minneapolis, MN 55455, 612-624-5150,
| | - Tyler A Bosch
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, University of Minnesota, MMC 101, 420 Delaware St. SE, Minneapolis, MN 55455, 612-624-5150,
| | - Anne E Bantle
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, University of Minnesota, MMC 101, 420 Delaware St. SE, Minneapolis, MN 55455, 612-624-5150,
| | - James S Hodges
- Division of Biostatistics, School of Public Health, University of Minnesota University of Minnesota, Room 200 University Office Plaza, 2702A, 2221 University Ave SE, Minneapolis, MN 55414, 612-624-5150,
| | - Donald R Dengel
- School of Kinesiology, College of Education and Human Development, University of Minnesota, Room 141B Mariucci Arena, 1901 4th St SE, Minneapolis, 55414, 612-624-5150,
| | - Lisa S Chow
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, University of Minnesota, MMC 101, 420 Delaware St. SE, Minneapolis, MN 55455, 612-624-5150,
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Brayton SH, Bosch TA, Bantle AE, Hodges JS, Dengel DR, Chow LS. The impact of high BMI on acute changes in body composition following 90 min of running. COGENT MEDICINE 2018. [DOI: 10.1080/2331205x.2018.1502960] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022] Open
Affiliation(s)
- Seth H. Brayton
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Tyler A. Bosch
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Anne E Bantle
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, University of Minnesota, Minneapolis, MN, 55455, USA
| | - James S. Hodges
- Division of Biostatistics, School of Public Health, University of Minnesota University of Minnesota, Minneapolis, MN, 55414, USA
| | - Donald R. Dengel
- School of Kinesiology, College of Education and Human Development, University of Minnesota, Minneapolis, 55414, USA
| | - Lisa S. Chow
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, University of Minnesota, Minneapolis, MN, 55455, USA
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Spartano NL, Lyass A, Larson MG, Lewis GD, Vasan RS. Submaximal Exercise Systolic Blood Pressure and Heart Rate at 20 Years of Follow-up: Correlates in the Framingham Heart Study. J Am Heart Assoc 2016; 5:e002821. [PMID: 27233297 PMCID: PMC4937245 DOI: 10.1161/jaha.115.002821] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2016] [Accepted: 04/19/2016] [Indexed: 11/16/2022]
Abstract
BACKGROUND Beyond their resting values, exercise responses in blood pressure (BP) and heart rate (HR) may add prognostic information for cardiovascular disease (CVD). In cross-sectional studies, exercise BP and HR responses correlate with CVD risk factors; however, it is unclear which factors influence longitudinal changes in exercise responses over time, which is important for our understanding of the development of CVD. METHODS AND RESULTS We assessed BP and HR responses to low-level exercise tests (6-minute Bruce protocol) in 1231 Framingham Offspring participants (55% women) who underwent a routine treadmill test in 1979-1983 (baseline; mean age 39±8 years) that was repeated in 1998-2001 (follow-up; mean age 58±8 years). Adjusting for baseline exercise responses, we related the follow-up exercise responses to baseline CVD risk factors and to their changes between examinations. Compared with men, women had greater rise in exercise systolic (S)BP and HR at 20-year follow-up (both P<0.005). Baseline blood lipid levels, resting SBP and HR, and smoking status were associated with greater exercise SBP at follow-up (all P<0.05). Weight gain across examinations was associated with higher exercise SBP and HR at follow-up (both P<0.0001). Smoking cessation was associated with a 53% reduced risk of attaining the highest quartile of exercise SBP (≥180 mm Hg) at follow-up (P<0.05). CONCLUSION An adverse CVD risk factor profile in young adults and its worsening over time were associated with higher SBP and HR responses to low-level exercise in midlife. Maintaining or adopting a healthy risk factor profile may favorably impact the exercise responses over time.
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Affiliation(s)
- Nicole L Spartano
- Sections of Preventative Medicine and Epidemiology, and Cardiology, Department of Medicine, Boston University School of Medicine, Boston, MA The Whitaker Cardiovascular Institute, Boston University School of Medicine, Boston, MA
| | - Asya Lyass
- Framingham Heart Study, Framingham, MA Department of Mathematics and Statistics, Boston University, Boston, MA
| | - Martin G Larson
- Framingham Heart Study, Framingham, MA Department of Mathematics and Statistics, Boston University, Boston, MA Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Gregory D Lewis
- Cardiology Division, Massachusetts General Hospital, Harvard Medical School, Cambridge, MA Pulmonary and Critical Care Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA Broad Institute of MIT and Harvard, Cambridge, MA
| | - Ramachandran S Vasan
- Sections of Preventative Medicine and Epidemiology, and Cardiology, Department of Medicine, Boston University School of Medicine, Boston, MA Framingham Heart Study, Framingham, MA Department of Epidemiology, Boston University School of Public Health, Boston, MA
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