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PURE – India Overview. Dubai – Jan 2006. PURE-India: Investigators and sites. Chandigarh Prof. Rajesh Kumar. Jaipur : Prof. Rajeev Gupta. Bangalore Mario Vaz Anura V Kurpad. Chennai Prof V Mohan. Trivandrum Prof. Soman. TIME LINE OF PURE-India. Dec2005 ~ 22,000. Dec 2002 ~5000
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PURE – IndiaOverview Dubai – Jan 2006
PURE-India: Investigators and sites Chandigarh Prof. Rajesh Kumar Jaipur: Prof. Rajeev Gupta Bangalore Mario Vaz Anura V Kurpad Chennai Prof V Mohan Trivandrum Prof. Soman
TIME LINE OF PURE-India Dec2005 ~ 22,000 Dec 2002 ~5000 Other centres start data Dec 2001 ~ 2500 subjects Jan 2001 Data starts-B’lore PURE-India Mtg Identification of Other centres (3) July 2000 Conceptualisation Chandigarh As 5th centre
The PURE-India Study is carried out in states with very diverse characteristics s N
The PURE-India Study is carried out in states with very diverse characteristics
Household income (Rs/month) by location ~ $ 235 ~ $ 45
Education level below high school (%): Urban-Rural - females
Daily dietary intakes in urban and rural populations: Bangalore centre
Hypertension: known, treated and controlled(%): - by location
Daily dietary intakes in urban slums relative to other urban and rural populations a Age and gender adjusted means,
Anthropometric profiles in urban and rural populations a Age and gender adjusted
Prevalence: diabetes and hypertension in urban slums relative to other urban and rural areas
Summary • There is considerable heterogeneity in the variables that we have studied and in disease outcomes, across locations (urban-rural-urban slum), gender and region (centre) • Urban-rural risk transitions generally follow patterns of development. In Kerala, there is evidence of a reversal of the transition with the rural population. • Dietary data needs to analysed in most centres – this when available will help us understand some of the changes that we have observed across centres and locations • Non responder data and issues of response bias are being analysed
CHALLENGES / ISSUES OF THE STUDY • Subjects in rural areas / slums unwilling to participate due to loss of daily wages • Responder burden due to the length of questionnaires • Working men unavailable during the day / particular seasons. • No perceived benefits in some groups slums / urban areas. • Takes 45 mins to enter one subjects data in the data entry system.