{"id":{"repo_id":"south-carolina","oai_identifier":"oai:scholarcommons.sc.edu:etd-1549"},"canonical_url":"https://search.dev.ndltd.org/etd/south-carolina/oai:scholarcommons.sc.edu:etd-1549","repository":{"repo_id":"south-carolina","name":"University of South Carolina","base_url":"https://scholarcommons.sc.edu/do/oai/"},"display":{"title":"Percentiles of Traditional and New Measures of Physical Activity Based On Accelerometry","abstract":"<p>This paper looks at sex- and age-specific percentiles curves for several measures of physical activity by gender and age group. Accelerometer data from healthy participants in the National Health and Nutrition Examination Survey study, a program of studies designed to assess the health and nutritional status of adults and children in the United States has been utilized here. Two popular measures of physical activity, time spent in moderate-to-vigorous physical activity and sedentary time, along with new measures that summarize daily cumulative physical activity and its spread over minutes in a day and over days in a week are considered. We derive percentiles charts that are analogous to growth charts and that can be used, for example, to assess individual activity levels, to evaluate intervention programs, or to track individual changes over time.</p>","abstract_html":"&lt;p&gt;This paper looks at sex- and age-specific percentiles curves for several measures of physical activity by gender and age group. Accelerometer data from healthy participants in the National Health and Nutrition Examination Survey study, a program of studies designed to assess the health and nutritional status of adults and children in the United States has been utilized here. Two popular measures of physical activity, time spent in moderate-to-vigorous physical activity and sedentary time, along with new measures that summarize daily cumulative physical activity and its spread over minutes in a day and over days in a week are considered. We derive percentiles charts that are analogous to growth charts and that can be used, for example, to assess individual activity levels, to evaluate intervention programs, or to track individual changes over time.&lt;/p&gt;","abstract_has_math":false,"creators":["Hassan, Rahnuma Muneer"],"institution":null,"degree_name":"M.S.P.H.","degree_level":"Campus Access Thesis","degree_discipline":"Epidemiology and Biostatistics","degree_department":null,"school":null,"contributors":["Matteo Bottai"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011-01-01T08:00:00Z","date_published":"2011-01-01T08:00:00Z","updated_at":"2026-07-24T04:37:49Z","subjects":["Biostatistics","Physical Sciences and Mathematics","Statistics and Probability","Growth Charts","MVPA","Quantiles Regression","Survey Data"],"languages":[],"rights":["© 2011, Rahnuma Muneer Hassan"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarcommons.sc.edu/etd/548","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Matteo Bottai"]},{"key":"dc:creator","label":"Author","values":["Hassan, Rahnuma Muneer"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Epidemiology and Biostatistics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Campus Access Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S.P.H."]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Biostatistics","Physical Sciences and Mathematics","Statistics and Probability","Growth Charts","MVPA","Quantiles Regression","Survey Data"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["© 2011, Rahnuma Muneer Hassan"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarcommons.sc.edu/etd/548"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["<p>This paper looks at sex- and age-specific percentiles curves for several measures of physical activity by gender and age group. Accelerometer data from healthy participants in the National Health and Nutrition Examination Survey study, a program of studies designed to assess the health and nutritional status of adults and children in the United States has been utilized here. Two popular measures of physical activity, time spent in moderate-to-vigorous physical activity and sedentary time, along with new measures that summarize daily cumulative physical activity and its spread over minutes in a day and over days in a week are considered. We derive percentiles charts that are analogous to growth charts and that can be used, for example, to assess individual activity levels, to evaluate intervention programs, or to track individual changes over time.</p>"]},{"key":"dc:title","label":"Title","values":["Percentiles of Traditional and New Measures of Physical Activity Based On Accelerometry"]}]}],"canonical_facts":{"dc:contributor":["Matteo Bottai"],"dc:creator":["Hassan, Rahnuma Muneer"],"dc:description.abstract":["<p>This paper looks at sex- and age-specific percentiles curves for several measures of physical activity by gender and age group. Accelerometer data from healthy participants in the National Health and Nutrition Examination Survey study, a program of studies designed to assess the health and nutritional status of adults and children in the United States has been utilized here. Two popular measures of physical activity, time spent in moderate-to-vigorous physical activity and sedentary time, along with new measures that summarize daily cumulative physical activity and its spread over minutes in a day and over days in a week are considered. We derive percentiles charts that are analogous to growth charts and that can be used, for example, to assess individual activity levels, to evaluate intervention programs, or to track individual changes over time.</p>"],"dc:identifier":["https://scholarcommons.sc.edu/etd/548"],"dc:rights":["© 2011, Rahnuma Muneer Hassan"],"dc:subject":["Biostatistics","Physical Sciences and Mathematics","Statistics and Probability","Growth Charts","MVPA","Quantiles Regression","Survey Data"],"dc:title":["Percentiles of Traditional and New Measures of Physical Activity Based On Accelerometry"],"thesis:degree_discipline":["Epidemiology and Biostatistics"],"thesis:degree_level":["Campus Access Thesis"],"thesis:degree_name":["M.S.P.H."]},"updated_at":"2026-07-24T04:37:49Z"}