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Combining risk factors and demographic surveillance: Potentials of WHO STEPS and INDEPTH methodologies for assessing epidemiological transition

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Combining risk factors and demographic surveillance: Potentials of WHO STEPS and INDEPTH methodologies for assessing epidemiological transition
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    Combining risk factors and demographic surveillance:Potentials of WHO STEPS and INDEPTHmethodologies for assessing epidemiologicaltransition    Ng N., Van Minh H., Tesfaye F., Bonita R., Byass P., Stenlund H.,Weinehall L., Wall S.  Department of Public Health, Faculty of Medicine, Gadjah Mada University, Farmako St. North Sekip,Jogjakarta 55281, Indonesia; Faculty of Public Health, Hanoi Medical University, Hanoi, Viet Nam;Department of Community Health, Faculty of Medicine, Addis Ababa University, Addis Ababa, Ethiopia;Evidence for Information and Policy (EIP), World Health Organization, Geneva, Switzerland; UmeåInternational School of Public Health, Epidemiology and Public Health Sciences, Department of PublicHealth and Clinical Medicine, Umeå University, Umeå, Sweden Abstract: Aims: Demographic surveillance systems (DSSs) create platforms to monitor populationdynamics. This paper discusses the potential of combining the WHO STEPwise approach to Surveillance(STEPS) within ongoing DSSs, to assess changes in non-communicable disease (NCD) risk factors.Methods: Three DSSs in Ethiopia, Vietnam, and Indonesia have collected NCD risk factors using WHOSTEPS, focusing on self-reported lifestyle risk factors (Step 1) and measurement of blood pressure andanthropometric parameters (Step 2). Results: DSSs provide sampling frames for NCD risk factor surveillance, which reveals the distribution of risk factors and their dynamics at the population level. TheWHO STEPS approach with its add-on modules is feasible and adaptable in DSS settings. Availablemortality data in the DSSs enable mortality assessment by cause of death using verbal autopsy, which isrelevant in estimating the impact of NCDs. DSSs as well as risk factor surveillance data may potentially be alever for hypothesis-driven research to address specific a priori hypotheses or research questions.Conclusion: Combining DSSs with the WHO STEPS approach can potentially address basicepidemiological questions on NCDs, which can be used as a powerful advocacy tool in public healthdecision-making for NCD prevention. © 2006 Taylor & Francis. Author Keywords: Demographic surveillance systems; Hypothesis-driven research; Non-communicablediseases; Risk factor surveillance; WHO STEPS Index Keywords: adult; anthropometry; article; autopsy; blood pressure measurement; cause of death;communicable disease; demography; Ethiopia; female; human; Indonesia; lifestyle; male; methodology;mortality; priority journal; risk factor; self report; Viet Nam; world health organization; Adult; ChronicDisease; Developing Countries; Ethiopia; Female; Humans; Indonesia; Life Style; Male; Middle Aged;Population Surveillance; Risk Factors; Vietnam; World Health Year: 2006 Source title: Scandinavian Journal of Public Health Volume: 34 Issue: 2  1.2.3.4.5.6.7.8.1.2.3.4.5.6.7.8. Page : 199-208 Cited by: 12 Link: Scorpus Link  Correspondence Address: Ng, N.; Department of Public Health, Faculty of Medicine, Gadjah MadaUniversity, Farmako St North Sekip, Jogjakarta 55281, Indonesia; email: nawi_ng@yahoo.com ISSN: 14034948 CODEN: SJPHA DOI: 10.1080/14034940500204506 PubMed ID: 16581713 Language of Original Document: English Abbreviated Source Title: Scandinavian Journal of Public Health Document Type: Article Source: Scopus Authors with affiliations:  Ng, N., Department of Public Health, Faculty of Medicine, Gadjah Mada University, Farmako St. North Sekip, Jogjakarta55281, Indonesia Van Minh, H., Faculty of Public Health, Hanoi Medical University, Hanoi, Viet Nam Tesfaye, F., Department of Community Health, Faculty of Medicine, Addis Ababa University, Addis Ababa, Ethiopia Bonita, R., Evidence for Information and Policy (EIP), World Health Organization, Geneva, Switzerland Byass, P., Umeå International School of Public Health, Epidemiology and Public Health Sciences, Department of PublicHealth and Clinical Medicine, Umeå University, Umeå, Sweden Stenlund, H., Umeå International School of Public Health, Epidemiology and Public Health Sciences, Department of PublicHealth and Clinical Medicine, Umeå University, Umeå, Sweden Weinehall, L., Umeå International School of Public Health, Epidemiology and Public Health Sciences, Department of PublicHealth and Clinical Medicine, Umeå University, Umeå, Sweden Wall, S., Umeå International School of Public Health, Epidemiology and Public Health Sciences, Department of Public Healthand Clinical Medicine, Umeå University, Umeå, Sweden References: Omran, A.R., The epidemiologic transition: A theory of the epidemiology of population change (1971) Milbank Mem FundQ, 49, pp. 509-538 Wall, S., Epidemiology in transition (1999) Int J Epidemiol, 28, pp. S1000-S1004 Caselli, G., The key phases of the European health transition (1995) Pol Popul Rev, 7, pp. 73-102 Munoz Pradas, F., Nos, R.N., Transitions in mortality and health: Theory, comparison and historical evidence (1995) PolPopul Rev, 7, pp. 53-71 Beaglehole, R., (2003) Global Health - A New Era, , Oxford: Oxford University Press Reddy, K.S., Yusuf, S., Emerging epidemic of cardiovascular disease in developing countries (1998) Circulation, 97, pp.596-601 World health report 2003: Shaping the future (2003), World Health Organisation. 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