Peter D. Hart, Nestor Asiamah, Getu Teferi, Ivan Uher
{"title":"利用基于州的流行率估算得出的体育锻炼与其他健康相关指标之间的关系","authors":"Peter D. Hart, Nestor Asiamah, Getu Teferi, Ivan Uher","doi":"10.34172/hpp.2023.36","DOIUrl":null,"url":null,"abstract":"Background: Both physical activity and muscle-strengthening activity have known relationships with other health-related variables such as alcohol and tobacco use, diet, and health-related quality of life (HRQOL). The purpose of this study was to explore and quantify the associations between physical activity measures and health-related variables at the higher state level. Methods: This cross-sectional study used data from the 2017 and 2019 Behavioral Risk Factor Surveillance System surveys. State-based prevalence (%) estimates were computed for meeting physical activity guidelines (PA), meeting muscle-strengthening activity guidelines (MS), both PA and MS (MB), drinking alcohol (D1), heavy alcohol drinking (HD), fruit consumption (F1), vegetable consumption (V1), good self-rated health (GH), overweight (OW), obesity (OB), current smoking (SN), and smokeless tobacco use (SL). Descriptive statistics, correlation coefficients, and data visualization methods were employed. Results: Strongest associations were seen between PA and F1 (2017: r=0.717 & 2019: r=0.695), MS and OB (2017: r=-0.781 & 2019: r=-0.599), PA and GH (2017: r=0.631 & 2019: r=0.649), PA and OB (2017: r=-0.645 & 2019: r=-0.763), and MB and SN (2017: r=-0.713 & 2019: r=-0.645). V1 was associated only with PA (2017: r=0.335 & 2019: r=0.357) whereas OW was not associated only with PA. Canonical correlation analysis showed the physical activity variables were directly related (r c=0.884, P<0.001) to the health variables. Conclusion: This study used high-level data to support the many known relationships between PA measures and health-related variables.","PeriodicalId":46588,"journal":{"name":"Health Promotion Perspectives","volume":"53 49","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2023-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Relationships between physical activity and other health-related measures using state-based prevalence estimates\",\"authors\":\"Peter D. Hart, Nestor Asiamah, Getu Teferi, Ivan Uher\",\"doi\":\"10.34172/hpp.2023.36\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background: Both physical activity and muscle-strengthening activity have known relationships with other health-related variables such as alcohol and tobacco use, diet, and health-related quality of life (HRQOL). The purpose of this study was to explore and quantify the associations between physical activity measures and health-related variables at the higher state level. Methods: This cross-sectional study used data from the 2017 and 2019 Behavioral Risk Factor Surveillance System surveys. State-based prevalence (%) estimates were computed for meeting physical activity guidelines (PA), meeting muscle-strengthening activity guidelines (MS), both PA and MS (MB), drinking alcohol (D1), heavy alcohol drinking (HD), fruit consumption (F1), vegetable consumption (V1), good self-rated health (GH), overweight (OW), obesity (OB), current smoking (SN), and smokeless tobacco use (SL). Descriptive statistics, correlation coefficients, and data visualization methods were employed. Results: Strongest associations were seen between PA and F1 (2017: r=0.717 & 2019: r=0.695), MS and OB (2017: r=-0.781 & 2019: r=-0.599), PA and GH (2017: r=0.631 & 2019: r=0.649), PA and OB (2017: r=-0.645 & 2019: r=-0.763), and MB and SN (2017: r=-0.713 & 2019: r=-0.645). V1 was associated only with PA (2017: r=0.335 & 2019: r=0.357) whereas OW was not associated only with PA. Canonical correlation analysis showed the physical activity variables were directly related (r c=0.884, P<0.001) to the health variables. Conclusion: This study used high-level data to support the many known relationships between PA measures and health-related variables.\",\"PeriodicalId\":46588,\"journal\":{\"name\":\"Health Promotion Perspectives\",\"volume\":\"53 49\",\"pages\":\"\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2023-12-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Health Promotion Perspectives\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.34172/hpp.2023.36\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Health Promotion Perspectives","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.34172/hpp.2023.36","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
Relationships between physical activity and other health-related measures using state-based prevalence estimates
Background: Both physical activity and muscle-strengthening activity have known relationships with other health-related variables such as alcohol and tobacco use, diet, and health-related quality of life (HRQOL). The purpose of this study was to explore and quantify the associations between physical activity measures and health-related variables at the higher state level. Methods: This cross-sectional study used data from the 2017 and 2019 Behavioral Risk Factor Surveillance System surveys. State-based prevalence (%) estimates were computed for meeting physical activity guidelines (PA), meeting muscle-strengthening activity guidelines (MS), both PA and MS (MB), drinking alcohol (D1), heavy alcohol drinking (HD), fruit consumption (F1), vegetable consumption (V1), good self-rated health (GH), overweight (OW), obesity (OB), current smoking (SN), and smokeless tobacco use (SL). Descriptive statistics, correlation coefficients, and data visualization methods were employed. Results: Strongest associations were seen between PA and F1 (2017: r=0.717 & 2019: r=0.695), MS and OB (2017: r=-0.781 & 2019: r=-0.599), PA and GH (2017: r=0.631 & 2019: r=0.649), PA and OB (2017: r=-0.645 & 2019: r=-0.763), and MB and SN (2017: r=-0.713 & 2019: r=-0.645). V1 was associated only with PA (2017: r=0.335 & 2019: r=0.357) whereas OW was not associated only with PA. Canonical correlation analysis showed the physical activity variables were directly related (r c=0.884, P<0.001) to the health variables. Conclusion: This study used high-level data to support the many known relationships between PA measures and health-related variables.