Kathleen L Strong1, Ruth Bonita. 1. Surveillance for Information and Policy Team, Chronic Disease and Health Promotion Department, Noncommunicable diseases and Mental Health Cluster, World Health Organization, Geneva.
Abstract
OBJECTIVES: The WHO Global InfoBase assembles country-level chronic disease risk factor prevalence data from WHO's member states. METHODS: The focus of this report is recent, nationally representative data. The risk factors of choice are those that make the greatest contribution to mortality and morbidity from chronic disease, can be changed through primary intervention and are easily measured in populations. RESULTS: Eight risk factors fit these criteria. They are: tobacco and alcohol use, patterns of physical inactivity, low fruit/vegetable intake, obesity, blood pressure, cholesterol and diabetes. Important to the data collection is the need to display prevalence data for these eight risk factors by age group(s) and sex and with some measure of the uncertainty of the estimate. CONCLUSIONS: This tool can be used by countries to evaluate the quality of the data that they have for chronic disease surveillance. The aim is to improve risk factor data quality and to standardize data, either through common survey instruments or by using existing country data to model risk factor estimates. These "harmonized" estimates will allow for comparisons over time and between countries.
OBJECTIVES: The WHO Global InfoBase assembles country-level chronic disease risk factor prevalence data from WHO's member states. METHODS: The focus of this report is recent, nationally representative data. The risk factors of choice are those that make the greatest contribution to mortality and morbidity from chronic disease, can be changed through primary intervention and are easily measured in populations. RESULTS: Eight risk factors fit these criteria. They are: tobacco and alcohol use, patterns of physical inactivity, low fruit/vegetable intake, obesity, blood pressure, cholesterol and diabetes. Important to the data collection is the need to display prevalence data for these eight risk factors by age group(s) and sex and with some measure of the uncertainty of the estimate. CONCLUSIONS: This tool can be used by countries to evaluate the quality of the data that they have for chronic disease surveillance. The aim is to improve risk factor data quality and to standardize data, either through common survey instruments or by using existing country data to model risk factor estimates. These "harmonized" estimates will allow for comparisons over time and between countries.
Authors: Gerald S Bloomfield; Ann Mwangi; Patrick Chege; Chrispinus J Simiyu; Daniel F Aswa; David Odhiambo; Andrew A Obala; Paul Ayuo; Barasa O Khwa-Otsyula Journal: Heart Date: 2013-07-19 Impact factor: 5.994