{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,27]],"date-time":"2026-10-27T08:42:47Z","timestamp":1793090567679,"version":"4.5.0"},"reference-count":52,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"10","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["JAHA"],"published-print":{"date-parts":[[2017,10,11]]},"abstract":"<jats:sec xml:lang=\"en\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p xml:lang=\"en\">\n                      The relationship between light intensity physical activity (\n                      <jats:styled-content style=\"fixed-case\">PA<\/jats:styled-content>\n                      ), which is common in older adults, and cardiovascular disease (\n                      <jats:styled-content style=\"fixed-case\">CVD<\/jats:styled-content>\n                      ) risk factors is unclear. This study examined associations of accelerometer\u2010measured\n                      <jats:styled-content style=\"fixed-case\">PA<\/jats:styled-content>\n                      intensity with\n                      <jats:styled-content style=\"fixed-case\">CVD<\/jats:styled-content>\n                      risk factors in older women of different race\u2010ethnicities.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec xml:lang=\"en\">\n                    <jats:title>Methods and Results<\/jats:title>\n                    <jats:p xml:lang=\"en\">\n                      Cross\u2010sectional analyses were conducted in 4832 women (mean age 78.9\u00a0years; 52.5% white, 30.5% black, 17.1% Hispanic) who were without known\n                      <jats:styled-content style=\"fixed-case\">CVD<\/jats:styled-content>\n                      and wore triaxial accelerometers a minimum of 4 of 7\u00a0days with \u226510\u00a0hours\/d awake wear\u2010time. Vector magnitude counts per 15\u2010s epoch were used to define time spent in low light (19\u2013225 counts\/15 s), high light (226\u2013518), and moderate\u2010to\u2010vigorous; \u2265519) intensity\n                      <jats:styled-content style=\"fixed-case\">PA<\/jats:styled-content>\n                      . Fasting\n                      <jats:styled-content style=\"fixed-case\">CVD<\/jats:styled-content>\n                      biomarkers, resting blood pressure, waist girth, body mass index, and 10\u2010year predicted\n                      <jats:styled-content style=\"fixed-case\">CVD<\/jats:styled-content>\n                      risk (Reynolds Risk Score) were measured. After adjusting for age, wear time, race\u2010ethnicity, and potential confounders, each\n                      <jats:styled-content style=\"fixed-case\">PA<\/jats:styled-content>\n                      measure was favorably associated with mean high\u2010density lipoprotein, triglyceride, glucose, C\u2010reactive protein, body mass index, waist girth, and Reynolds Risk Score (\n                      <jats:italic>P<\/jats:italic>\n                      &lt;0.05, all). Associations with mean blood pressure, insulin, and total and low\u2010density lipoprotein cholesterol were variable. A 30\u2010minute\/d increment in\n                      <jats:styled-content style=\"fixed-case\">PA<\/jats:styled-content>\n                      was associated, on average, with odds ratios for high predicted\n                      <jats:styled-content style=\"fixed-case\">CVD<\/jats:styled-content>\n                      risk (Reynolds Risk Score \u226520) of 0.96 (95% confidence interval, 0.92, 1.00), 0.88 (0.83, 0.94), and 0.85 (0.79, 0.91) for low light, high light, and moderate\u2010to\u2010vigorous, respectively, and remained significant with further mutual control for\n                      <jats:styled-content style=\"fixed-case\">PA<\/jats:styled-content>\n                      intensity.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec xml:lang=\"en\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p xml:lang=\"en\">\n                      <jats:styled-content style=\"fixed-case\">PA<\/jats:styled-content>\n                      measured by accelerometry, including light intensity\n                      <jats:styled-content style=\"fixed-case\">PA<\/jats:styled-content>\n                      , was associated with lower\n                      <jats:styled-content style=\"fixed-case\">CVD<\/jats:styled-content>\n                      risk factor levels in race\u2010ethnically diverse older women.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1161\/jaha.117.007064","type":"journal-article","created":{"date-parts":[[2017,10,17]],"date-time":"2017-10-17T20:10:20Z","timestamp":1508271020000},"update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":84,"title":["Both Light Intensity and Moderate\u2010to\u2010Vigorous Physical Activity Measured by Accelerometry Are Favorably Associated With Cardiometabolic Risk Factors in Older Women: The Objective Physical Activity and Cardiovascular Health (OPACH) Study"],"prefix":"10.1161","volume":"6","author":[{"given":"Michael J.","family":"LaMonte","sequence":"first","affiliation":[{"name":"School of Public Health and Health Professions University at Buffalo\u2014SUNY, Buffalo, NY"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cora E.","family":"Lewis","sequence":"additional","affiliation":[{"name":"School of Medicine, University of Alabama\u2010Birmingham, AL"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David M.","family":"Buchner","sequence":"additional","affiliation":[{"name":"University of Illinois, Urbana Champaign, IL"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kelly R.","family":"Evenson","sequence":"additional","affiliation":[{"name":"Gillings School of Public Health, University of North Carolina, Chapel Hill, 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