PPT-Determining Household Obesity Status Using Scanner Data

Elina T Page Sabrina K Young Megan Sweitzer Abigail Okrent Economic Research Service November 2 2021 2021 FCSM Research and Policy Conference The findings and conclusions in this presentation are those of the authors and should not be construed to represent any official USDA or US Government determination or policy The . Scanner ModelGroupScanner ModelGroupContex XD2490BEpson GT 1500Contex SD4410CEpson GT-2500 AContex SD4430CEpson GT-S50AContex SD4450CEpson GT-S80AContex SD4490CEpson GT-20000 AEpson GT-30000CAEpson DS DCLG . 2011-based projections. Tim Lyne, Experian. The DCLG household projections – . summary of the approach. What the . data . available . at . the time of producing the projections told us about household formation. First steps.. Anna Bobel, Retail Prices Section, CSO of Poland, Warsaw. A.Bobel@stat.gov.pl. Tomasz Pietras, Price Statistics Centre of the Statistical Office in Opole. T.Pietras@stat.gov.pl. THE CENTRAL STATISTICAL OFFICE OF POLAND. experience. . with. scanner data. From sampling . to. index . calculation. Paulina Jonéus. COICOP. COICOP divisions where we use mainly scanner data. 01 . (daily necessities excl. perishable fruits, vegetables and meat sold in department stores, supermarkets and hypermarkets) . DCLG . 2011-based projections. Tim Lyne, Experian. The DCLG household projections – . summary of the approach. What the . data . available . at . the time of producing the projections told us about household formation. Olivier . Dupriez. World Bank, Development Data Group. odupriez@worldbank.org. 6 June 2013. Initial objective. Calculate poverty PPPs. Had price data at basic heading level from the ICP ; needed consumption shares “at the poverty line” for the same breakdown to be used as weights.. This Training Tool has been prepared by the LIHEAP Clearinghouse under contract with the U.S. Department of Health and Human Services, Division of Energy Assistance. The content of this publication does not necessarily reflect the views or policies of the . . . Adults by Race/Ethnicity, State and Territory, . BRFSS, . 2015-2017. Definitions. Obesity: Body Mass Index (BMI) of . 30 kg/m. 2. . or higher.. Body Mass Index (BMI): A measure of . an adult’s . Speaker: . Qingtao. . Meng. . MD. West China hospital, . Chendu. , China . Background. Diabetes Mellitus is a major global public health challenge. Background. As an . important risk factor for DM, Obesity is rising throughout the world. and . cesarean section . . Birth by the Numbers. Gene Declercq. March, 2016. Long Standing Concern with Maternal Obesity. Contemporary . Categorization . of Obesity. BirthByTheNumbers.org. BMI & Obesity Categories. and . Family Characteristics. : . Issues and Recommendations for the 2020 Round. Group of Experts on Population and Housing . Censuses. Geneva, 30 . September – 3 . October . 2013. Task Force Members. 5210 . & Motivational Interviewing to . the Rescue!. Jamie Jeffrey, MD, FAAP. Medical Director, Children’s Medicine Center & . HealthyKids Pediatric Weight Management Program. Clinical Associate Professor, WVU-Charleston. 04 May 2015. . M.Oyuntsetseg. Statistician. Population and Social Statistics Department. Contents. Article 6. System of official statistical indicators and the basis for its production. 2) population and social statistics; . Big . Data in Official Statistics: . the . C. ase of . S. canner Data . in . Istat. Gianluca D’Amato, Annunziata Fiore, Domenico Infante, Antonella Simone, Giorgio Vinci, . Antonino Virgillito. Istat.