PURE – India Overview Dubai – Jan 2006

PURE-India: Investigators and sites Bangalore Mario Vaz Anura V Kurpad Jaipur: Prof. Rajeev Gupta Chennai Prof V Mohan Trivandrum Prof. Soman Chandigarh Prof. Rajesh Kumar

TIME LINE OF PURE-India July 2000 Conceptualisation Jan 2001 Data starts-B’lore Dec 2001 ~ 2500 subjects PURE-India Mtg Identification of Other centres (3) Dec 2002 ~5000 Other centres start data Chandigarh As 5 th centre Dec2005 ~ 22,000

ALL CENTRES Chandig arh JaipurBangalo re ChennaiTrivan drum Households surveyed Eligible households Eligible individuals Participants Response Rate (%) Recruitment Status – PURE India Centers

UrbanRural Response rate (%)5256 Participants Completed measurements (%) 9391 Provided blood sample (%) 9083 PURE – INDIA Recruitment Status

The PURE-India Study is carried out in states with very diverse characteristics CENTREStatesBirth Rate /1000 Infant Mortality Rate / 1000 Life expectancy at birth Literacy rate (%) Population density / sq. km Bangalore Karnataka Andhra Pradesh Chennai Tamil Nadu Trivandrum Kerala Jaipur Rajasthan Chandigarh Haryana s N

Present analysis: numbers TotalUrbanRural Bangalore Chennai Trivandrum Jaipur Chandigarh All centres

The PURE-India Study is carried out in states with very diverse characteristics CENTREStatesRelative Human Development Rank Bangalore Karnataka3 Andhra Pradesh4 Chennai Tamil Nadu2 Trivandrum Kerala1 Jaipur Rajasthan5 Chandigarh - Haryana-

Household income (Rs/month) by location ~ $ 235 ~ $ 45

Education level below high school (%): Urban-Rural - males

Education level below high school (%): Urban-Rural - females

TV ownership (%) by location

2-wheeler ownership (%) by location

Kitchen mixer ownership (%) by location

Current tobacco use (%): Urban-Rural - males

Current tobacco use (%): Urban-Rural - females

Current alcohol use (%): Urban-Rural - males

% of males who are sedentary by location

% of females who are sedentary by location

Daily dietary intakes in urban and rural populations: Bangalore centre RuralUrban Energy (kcal) Carbohydrate intake (g) Fat intake (g) Sugar (g) Salt (g) Total vegetables (g)50158 Total fruits (g)49166

% of males who are overweight/obese (BMI ≥ 25) by location

% females who are overweight/obese (BMI ≥ 25) by location

Mean Waist-hip ratio: Males by location

Mean Waist-hip ratio: Females by location

Serum total cholesterol (mg/dl): Males - by location

Serum total cholesterol (mg/dl): Females - by location

Prevalence of hypertension (%): Males - by location

Prevalence of hypertension (%): Females - by location

Hypertension: known, treated and controlled(%): - by location

Prevalence of diabetes (%): Males - by location

Prevalence of diabetes (%): Females - by location

Prevalence of CHD (%): Males - by location

Prevalence of CHD (%): Females - by location

Daily dietary intakes in urban slums relative to other urban and rural populations RuralSlumsUrban Energy (kcal) Carbohydrate intake (g) Fat intake (g) Sugar (g) Salt (g) Vegetable intake (g) a Age and gender adjusted means,

Anthropometric profiles in urban and rural populations RuralSlumUrban Weight (kg) a BMI (kg/m 2 ) a % overweight (BMI ≥ 25<30 kg/m 2 ) Men Women % obese Men Women a Age and gender adjusted

Prevalence: diabetes and hypertension in urban slums relative to other urban and rural areas RuralSlumUrban Diabetes (Hx + FBS ≥ 126 mg/dl) Men Women Hypertension (Hx + BP ≥ 140/90 mmHg) Men Women

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.

% use of wood as cooking fuel by location

% use of LPG (gas) as cooking fuel by location

Mean Waist circ (cm) : Males by location

Mean Waist circ (cm) : Females by location