A MEASUREMENT ERROR APPROACH TO ESTIMATING USUAL DAILY PHYSICAL ACTIVITY DISTRIBU
Greg J Welk
Iowa State University, 1138 Pearson Hall, Ames, Ia 50011-2207
Grant 5R01HL091024-03 from National Heart, Lung, And Blood Institute
Abstract: Measurement error in physical activity assessment has made it difficult to answer important questions about the prevalence of physical activity and associations with various health-related outcomes. The objective in the present application is to develop and evaluate statistical procedures to model, quantify and adjust for measurement error in a commonly used and accepted physical activity recall instrument (24 hour physical activity recall 24hPAR). To develop appropriate statistical models, we will conduct a Physical Activity Measurement Survey (PAMS) to obtain recall and objective physical activity data from a representative sample of 1200 adults (19- 70 yrs) who reside in rural and urban environments in Iowa. Participants will complete two days of physical activity monitoring with the BodyMedia Sensewear Pro III (SP3), a multi-channel pattern recognition device that provides accurate estimates of PA and energy expenditure. After each monitoring day, participants will complete a telephone-administered 24hPAR assessment. After replicate measures of the SP3 and 24hPAR are obtained, self-reported physical activity propensity data will be obtained to provide auxiliary information for estimating models and distributions of usual physical activity. The sequential series of Specific Aims will address unique questions about measurement error in physical activity and lead to the development of procedures and methodologies to facilitate the application of these methods in future research. In Aim 1, we will develop a self- administered physical activity propensity questionnaire (PAPQ) and a 24 hr PA recall (24hPAR) telephone interview that can be administered in a large-scale survey setting. In Aim 2, measurement error models will be estimated for the recall and reference measures in order to estimate the bias and random measurement error structure of measurements. A unique aspect of the proposed modeling is that we will utilize new propensity-based approaches to address the fact that many adults in the population report no physical activity. In Aim 3, the 24PAR will be calibrated against the temporally matched SP3 data so that the measurements essentially behave as if they had been collected using a reference instrument. In Aim 4, the measurement error model and calibration procedures will be used to estimate usual daily physical activity of individuals in subpopulations. The approach in this research is innovative, because it utilizes state of the art monitors and will lead to the development of new statistical techniques to model and correct physical activity measurement error. The proposed research is significant, because it will directly address a complex and long-standing measurement problem in the physical activity field (i.e. obtaining accurate indicators of usual physical activity). This information will help to improve physical activity epidemiology research and facilitate the development of more effective public health surveillance research. The resulting physical activity measurement model from this study will also facilitate future research aimed at jointly modeling error in energy intake and energy expenditure. The project is guided by a strong research team with expertise in all necessary facets of the study (physical activity assessment, survey design and administration, and measurement error modeling). The proposed study will develop and evaluate statistical procedures to model, quantify and adjust for measurement error in a commonly used and accepted physical activity recall instrument (24 hour physical activity recall). Data for the study will be obtained through a multi-component activity monitoring protocol (Physical Activity Measurement Survey) that will collect recall and objective physical activity data from a representative sample of 1200 adults (21-70 yrs) who reside in 3 ethnically diverse Iowa counties. Data analyses will involve the development and evaluation of statistical procedures that calibrate the self-report measure against objective physical data to obtain accurate estimates of "usual" physical activity in the population
Keywords: 21+ years old; Accounting; Address; Adult; African American; Afro American; Afroamerican; Age; Analysis, Data; Area; Arts; Behavior; Black Populations; Black or African American; Calibration; Caloric Intake; Characteristics; Cognitive; Complex; County; Data; Data Analyses; Development; Devices; Diagnostic Sensitivity; Diet; Dietary Assessment; Dietary History; Dietary intake; Eating; Energy Expenditure; Energy Intake; Energy Metabolism; Environment; Epidemic; Epidemiologic Research; Epidemiologic Studies; Epidemiological Studies; Epidemiology Research; Ethnic Origin; Ethnicity; Ethnicity aspects; Evaluation; Expenditure; Food; Food Intake; Foundations; Frequencies (time pattern); Frequency; Future; Gender; Goals; Health; Hispanic Populations; Hispanics; Hispanics or Latinos; Hour; Household; Human, Adult; Individual; Intake; Interest Group; Interview; Investigation; Investigators; Iowa; Latino Population; Lead; Light; Literature; Measurement; Measures; Method LOINC Axis 6; Methodology; Methods; Methods and Techniques; Methods, Other; Modeling; Models, Statistical; Monitor; NHANES; National Health and Nutrition Examination Survey; Nature; Nutrient; Nutrition; Nutritional Science; Obesity; Occupational; Outcome; Outcome Measure; Participant; Patient Self-Report; Pattern; Pattern Recognition; Pattern Recognition/Display/Analysis; Pb element; Persons; Phone; Photoradiation; Physical activity; Pilot Projects; Population; Population Surveillance; Prevalence; Probabilistic Models; Procedures; Process; Property; Property, LOINC Axis 2; Protocol; Protocols documentation; Public Health; Public Health Surveillance; Qualifying; Questionnaires; Race; Racial Group; Recruitment Activity; Reporting; Research; Research Personnel; Researchers; Rural; Sampling; Science of nutrition; Self-Administered; Self-Report; Series; Social Desirabilities; Social Desirability; Solutions; Spanish Origin; Statistical Models; Stocks, Racial; Structure; Study models; Survey Instrument; Surveys; Techniques; Telephone; Telephone Interviews; Testing; Time; Work; adiposity; adult human (21+); base; black American; caloric dietary content; corpulence; corpulency; corpulentia; cost; cost effective; data modeling; design; designing; experience; food consumption; heavy metal Pb; heavy metal lead; hispanic community; improved; innovate; innovation; innovative; instrument; nutrition; obese; obese people; obese person; obese population; pilot study; public health medicine (field); public health priorities; public health relevance; recruit; response; tool
Project start date: 2008-09-15
Project end date: 2012-05-31
Budget start date: 1-JUN-2010
Budget end date: 31-MAY-2011
PFA/PA: PAR-07-259
5R01HL091024-03 (2010): $793604
Sponsored Links Excellgen http://Excellgen.com
A MEASUREMENT ERROR APPROACH TO ESTIMATING USUAL DAILY PHYSICAL ACTIVITY DISTRIBU
Greg J Welk, Associate Professor
Iowa State University, 1138 Pearson Hall, Ames, Ia 50011-2207
Grant 5R01HL091024-02 from National Heart, Lung, And Blood Institute
Abstract: Measurement error in physical activity assessment has made it difficult to answer important questions about the prevalence of physical activity and associations with various health-related outcomes. The objective in the present application is to develop and evaluate statistical procedures to model, quantify and adjust for measurement error in a commonly used and accepted physical activity recall instrument (24 hour physical activity recall 24hPAR). To develop appropriate statistical models, we will conduct a Physical Activity Measurement Survey (PAMS) to obtain recall and objective physical activity data from a representative sample of 1200 adults (19- 70 yrs) who reside in rural and urban environments in Iowa. Participants will complete two days of physical activity monitoring with the BodyMedia Sensewear Pro III (SP3), a multi-channel pattern recognition device that provides accurate estimates of PA and energy expenditure. After each monitoring day, participants will complete a telephone-administered 24hPAR assessment. After replicate measures of the SP3 and 24hPAR are obtained, self-reported physical activity propensity data will be obtained to provide auxiliary information for estimating models and distributions of usual physical activity. The sequential series of Specific Aims will address unique questions about measurement error in physical activity and lead to the development of procedures and methodologies to facilitate the application of these methods in future research. In Aim 1, we will develop a self- administered physical activity propensity questionnaire (PAPQ) and a 24 hr PA recall (24hPAR) telephone interview that can be administered in a large-scale survey setting. In Aim 2, measurement error models will be estimated for the recall and reference measures in order to estimate the bias and random measurement error structure of measurements. A unique aspect of the proposed modeling is that we will utilize new propensity-based approaches to address the fact that many adults in the population report no physical activity. In Aim 3, the 24PAR will be calibrated against the temporally matched SP3 data so that the measurements essentially behave as if they had been collected using a reference instrument. In Aim 4, the measurement error model and calibration procedures will be used to estimate usual daily physical activity of individuals in subpopulations. The approach in this research is innovative, because it utilizes state of the art monitors and will lead to the development of new statistical techniques to model and correct physical activity measurement error. The proposed research is significant, because it will directly address a complex and long-standing measurement problem in the physical activity field (i.e. obtaining accurate indicators of usual physical activity). This information will help to improve physical activity epidemiology research and facilitate the development of more effective public health surveillance research. The resulting physical activity measurement model from this study will also facilitate future research aimed at jointly modeling error in energy intake and energy expenditure. The project is guided by a strong research team with expertise in all necessary facets of the study (physical activity assessment, survey design and administration, and measurement error modeling). The proposed study will develop and evaluate statistical procedures to model, quantify and adjust for measurement error in a commonly used and accepted physical activity recall instrument (24 hour physical activity recall). Data for the study will be obtained through a multi-component activity monitoring protocol (Physical Activity Measurement Survey) that will collect recall and objective physical activity data from a representative sample of 1200 adults (21-70 yrs) who reside in 3 ethnically diverse Iowa counties. Data analyses will involve the development and evaluation of statistical procedures that calibrate the self-report measure against objective physical data to obtain accurate estimates of "usual" physical activity in the population
Keywords: 21+ years old; Accounting; Address; Adult; African American; Afro American; Afroamerican; Age; Analysis, Data; Area; Arts; Behavior; Black Populations; Black or African American; Calibration; Caloric Intake; Characteristics; Classification; Cognitive; Complex; County; Data; Data Analyses; Development; Devices; Diagnostic Sensitivity; Diet; Dietary Assessment; Dietary History; Dietary intake; Eating; Energy Expenditure; Energy Intake; Energy Metabolism; Environment; Epidemic; Epidemiologic Research; Epidemiologic Studies; Epidemiological Studies; Epidemiology Research; Ethnic Origin; Ethnicity; Ethnicity aspects; Evaluation; Expenditure; Food; Food Intake; Foundations; Frequencies (time pattern); Frequency; Future; Gender; Goals; Health; Hispanic Populations; Hispanics; Hispanics or Latinos; Hour; Household; Human, Adult; Individual; Intake; Interest Group; Interview; Investigation; Investigators; Iowa; Latino Population; Lead; Light; Literature; Measurement; Measures; Method LOINC Axis 6; Methodology; Methods; Methods and Techniques; Methods, Other; Modeling; Models, Statistical; Monitor; NHANES; National Health and Nutrition Examination Survey; Nature; Nutrient; Nutrition; Nutritional Science; Obesity; Occupational; Outcome; Outcome Measure; Participant; Patient Self-Report; Pattern; Pattern Recognition; Pattern Recognition/Display/Analysis; Pb element; Persons; Phone; Photoradiation; Physical activity; Pilot Projects; Population; Population Surveillance; Prevalence; Probabilistic Models; Procedures; Process; Property; Property, LOINC Axis 2; Protocol; Protocols documentation; Public Health; Public Health Surveillance; Qualifying; Questionnaires; Race; Racial Group; Recruitment Activity; Reporting; Research; Research Personnel; Researchers; Rural; Sampling; Science of nutrition; Self-Administered; Self-Report; Series; Social Desirabilities; Social Desirability; Solutions; Spanish Origin; Statistical Models; Stocks, Racial; Structure; Study models; Survey Instrument; Surveys; Systematics; Techniques; Telephone; Telephone Interviews; Testing; Time; Work; adiposity; adult human (21+); base; black American; caloric dietary content; corpulence; corpulency; corpulentia; cost; cost effective; data modeling; design; designing; experience; food consumption; heavy metal Pb; heavy metal lead; hispanic community; improved; innovate; innovation; innovative; instrument; nutrition; obese; obese people; obese person; obese population; pilot study; public health medicine (field); public health priorities; public health relevance; recruit; response; tool
Project start date: 2008-09-15
Project end date: 2012-05-31
Budget start date: 1-JUN-2009
Budget end date: 31-MAY-2010
PFA/PA: PAR-07-259
5R01HL091024-02 (2009): $810859
Grants awarded to Greg J Welk
A MEASUREMENT ERROR APPROACH TO ESTIMATING USUAL DAILY PHYSICAL ACTIVITY DISTRIBU
Greg J Welk, Associate Professor
Iowa State University, 1138 Pearson Hall, Ames, Ia 50011-2207
Grant 3R01HL091024-02S2 from Office Of The Director, National Institutes Of Health
Abstract: Measurement error in physical activity assessment has made it difficult to answer important questions about the prevalence of physical activity and associations with various health-related outcomes. The objective in the present application is to develop and evaluate statistical procedures to model, quantify and adjust for measurement error in a commonly used and accepted physical activity recall instrument (24 hour physical activity recall 24hPAR). To develop appropriate statistical models, we will conduct a Physical Activity Measurement Survey (PAMS) to obtain recall and objective physical activity data from a representative sample of 1200 adults (19- 70 yrs) who reside in rural and urban environments in Iowa. Participants will complete two days of physical activity monitoring with the BodyMedia Sensewear Pro III (SP3), a multi-channel pattern recognition device that provides accurate estimates of PA and energy expenditure. After each monitoring day, participants will complete a telephone-administered 24hPAR assessment. After replicate measures of the SP3 and 24hPAR are obtained, self-reported physical activity propensity data will be obtained to provide auxiliary information for estimating models and distributions of usual physical activity. The sequential series of Specific Aims will address unique questions about measurement error in physical activity and lead to the development of procedures and methodologies to facilitate the application of these methods in future research. In Aim 1, we will develop a self- administered physical activity propensity questionnaire (PAPQ) and a 24 hr PA recall (24hPAR) telephone interview that can be administered in a large-scale survey setting. In Aim 2, measurement error models will be estimated for the recall and reference measures in order to estimate the bias and random measurement error structure of measurements. A unique aspect of the proposed modeling is that we will utilize new propensity-based approaches to address the fact that many adults in the population report no physical activity. In Aim 3, the 24PAR will be calibrated against the temporally matched SP3 data so that the measurements essentially behave as if they had been collected using a reference instrument. In Aim 4, the measurement error model and calibration procedures will be used to estimate usual daily physical activity of individuals in subpopulations. The approach in this research is innovative, because it utilizes state of the art monitors and will lead to the development of new statistical techniques to model and correct physical activity measurement error. The proposed research is significant, because it will directly address a complex and long-standing measurement problem in the physical activity field (i.e. obtaining accurate indicators of usual physical activity). This information will help to improve physical activity epidemiology research and facilitate the development of more effective public health surveillance research. The resulting physical activity measurement model from this study will also facilitate future research aimed at jointly modeling error in energy intake and energy expenditure. The project is guided by a strong research team with expertise in all necessary facets of the study (physical activity assessment, survey design and administration, and measurement error modeling)
Keywords: 21+ years old; Accounting; Address; Adult; African American; Afro American; Afroamerican; Age; Analysis, Data; Area; Arts; Behavior; Black Populations; Black or African American; Calibration; Caloric Intake; Characteristics; Cognitive; Complex; County; Data; Data Analyses; Development; Devices; Diagnostic Sensitivity; Diet; Dietary Assessment; Dietary History; Dietary intake; Eating; Energy Expenditure; Energy Intake; Energy Metabolism; Environment; Epidemic; Epidemiologic Research; Epidemiologic Studies; Epidemiological Studies; Epidemiology Research; Ethnic Origin; Ethnicity; Ethnicity aspects; Evaluation; Expenditure; Food; Food Intake; Foundations; Frequencies (time pattern); Frequency; Future; Gender; Goals; Health; Hispanic Populations; Hispanics; Hispanics or Latinos; Hour; Household; Human, Adult; Individual; Intake; Interest Group; Interview; Investigation; Investigators; Iowa; Latino Population; Lead; Light; Literature; Measurement; Measures; Method LOINC Axis 6; Methodology; Methods; Methods and Techniques; Methods, Other; Modeling; Models, Statistical; Monitor; NHANES; National Health and Nutrition Examination Survey; Nature; Nutrient; Nutrition; Nutritional Science; Obesity; Occupational; Outcome; Outcome Measure; Participant; Patient Self-Report; Pattern; Pattern Recognition; Pattern Recognition/Display/Analysis; Pb element; Persons; Phone; Photoradiation; Physical activity; Pilot Projects; Population; Population Surveillance; Prevalence; Probabilistic Models; Procedures; Process; Property; Property, LOINC Axis 2; Protocol; Protocols documentation; Public Health; Public Health Surveillance; Qualifying; Questionnaires; Race; Racial Group; Recruitment Activity; Reporting; Research; Research Personnel; Researchers; Rural; Sampling; Science of nutrition; Self-Administered; Self-Report; Series; Social Desirabilities; Social Desirability; Solutions; Spanish Origin; Statistical Models; Stocks, Racial; Structure; Study models; Survey Instrument; Surveys; Techniques; Telephone; Telephone Interviews; Testing; Time; Work; adiposity; adult human (21+); base; black American; caloric dietary content; corpulence; corpulency; corpulentia; cost; cost effective; data modeling; design; designing; experience; food consumption; heavy metal Pb; heavy metal lead; hispanic community; improved; innovate; innovation; innovative; instrument; nutrition; obese; obese people; obese person; obese population; pilot study; public health medicine (field); public health priorities; public health relevance; recruit; response; tool
Relevance: The proposed study will develop and evaluate statistical procedures to model, quantify and adjust for measurement error in a commonly used and accepted physical activity recall instrument (24 hour physical activity recall). Data for the study will be obtained through a multi-component activity monitoring protocol (Physical Activity Measurement Survey) that will collect recall and objective physical activity data from a representative sample of 1200 adults (21-70 yrs) who reside in 3 ethnically diverse Iowa counties. Data analyses will involve the development and evaluation of statistical procedures that calibrate the self-report measure against objective physical data to obtain accurate estimates of "usual" physical activity in the population
Project start date: 2008-09-15
Project end date: 2012-05-31
Budget start date: 6-MAY-2010
Budget end date: 31-MAY-2010
PFA/PA: PAR-07-259
3R01HL091024-02S2 (2010): $8500
3R01HL091024-02S1 (2009): $75929