Supplementary appendix

Transcription

1 Supplementary appendix This appendix formed part of the original submission and has been peer reviewed. We post it as supplied by the authors. Supplement to: Anjana RM, Deepa M, Pradeepa R, et al, for the ICMR INDIAB Collaborative Study Group. Prevalence of diabetes and prediabetes in 15 states of India: results from the ICMR INDIAB population-based cross-sectional study. Lancet Diabetes Endocrinol 2017; published online June 7. S (17)

2 ICMR INDIAB Collaborative Study Group Authors Ranjit Mohan Anjana 1 Mohan Deepa 1 Rajendra Pradeepa 1 Jagadish Mahanta 2 Kanwar Narain 2 Hiranya Kumar Das 2 Prabha Adhikari 3 Paturi Vishnupriya Rao 4 Banshi Saboo 5 Ajay Kumar 6 Anil Bhansali 7 Mary John 8 Rosang Luaia 9 Taranga Reang 10 Somorjit Ningombam 11 Lobsang Jampa 12 Richard O Budnah 13 Nirmal Elangovan 1 Radhakrishnan Subashini 1 Ulagamathesan Venkatesan 1 Ranjit Unnikrishnan 1 Ashok Kumar Das 14 Sri Venkata Madhu 15 Mohammed K Ali 1 Arvind Pandey 16 R S Dhaliwal 17 Tanvir Kaur 17 Soumya Swaminathan 17 Viswanathan Mohan 1 Contributors Vasudevan Sudha 1 Somasundaram Jaya Parvathi 1 Ramamoorthy Jayashri 1 Kaliaperumal Velmurugan 1 Prasanta Kumar Borah 2 Sathish B Rao 3 Jayendrasinh M. Padhiyar 5 Smita Sharma 6 Pachuau Lalramenga 9 Swapan Kumar Das 10 Th Bhubhonchandra Singh 11 Tao Kaki 12 Manoj Risbud Basaiawmoit 13 Deepak Kumar Shukla 17 Modugu Nageswara Rao 18 Prashant P Joshi 19 Vinay Kumar Dhandania 20 Shashank R Joshi 21 Chittaranjan Sakerlal Yajnik 22 1

3 Affiliations 1 Madras Diabetes Research Foundation & Dr.Mohan s Diabetes Specialities Centre, WHO Collaborating Centre for Noncommunicable Diseases Prevention and Control & ICMR Centre for Advanced Research on Diabetes, Chennai, Tamil Nadu, India 2 Regional Medical Research Centre, Dibrugarh, Assam, India 3 Kasturba Medical College, Mangalore, Karnataka, India 4 Diabetes Research Society, Hyderabad, Telungana, India 5 Dia Care Diabetes Care & Hormone Clinic, Ahmedabad, Gujarat, India 6 Diabetes Care & Research Centre, Patna, Bihar, India 7 Postgraduate Institute of Medical Education and Research, Chandigarh, India 8 Christian Medical College, Ludhiana, Punjab, India 9 Civil Hospital, Aizawl, Mizoram, India 10 Agartala Government Medical College, Agartala, Tripura, India 11 Directorate of Health Services, Imphal, Manipur, India 12 Directorate of Health Services, Naharlagun, Arunachal Pradesh, India 13 Directorate of Health Services, Shillong, Meghalaya, India 14 Pondicherry Institute of Medical Sciences, Puducherry, India 15 University College of Medical Sciences and GTB Hospital, New Delhi, India 16 National Institute of Medical Statistics, New Delhi 17 Indian Council of Medical Research, New Delhi, India 18 Nizam s Institute of Medical Sciences, Hyderabad 19 Government Medical College, Nagpur 20 Diabetes Care Center, Ranchi 21 Lilavati Hospital, Mumbai 22 King Edward Memorial Hospital & Research Centre, Pune 2

4 SAMPLING AND WEIGHTAGE ANALYSIS THE ICMR-INDIAB STUDY A. SAMPLING: i. Sample size calculation: The sample size was calculated separately for urban and rural areas [Table S1], as previous studies have shown large variations in urban and rural prevalence of type 2 diabetes mellitus. Assuming a prevalence of 10% in urban areas and 4% in rural areas, allowing for a precision of 20%, a non response rate of 20% and an error of 5%, the sample size was estimated to be 1200 in urban areas and 2800 in rural areas in each of the states studied, with a total of 4,000 individuals / state. Sample size calculation ICMR- INDIAB Table S1: Sample size calculation for Phase II of the ICMR- INDIAB study Prevalence (p) Rural Diabetes = 4 % Urban Diabetes = 10 % q = (1-p) Relative error (d) = 20% of p n = Z 2 (p) (q) d 2 96% 0.8 % n= (1.96) 2 (4) (96) (0.8) 2 = = % 2% (1.96) 2 (10) (90) (2) 2 = = 865 Sample Size per state (n) Accounting for Nonresponders [20%] n = 20 X 2305 = = 2766 n = 20 X 865 = = 1038 Approx 2,800 1,200 Formula: Sample size (n) = Z 2 (p) (q) d 2 Z= Z statistic for a level of confidence. For the level of confidence of 95%, the conventional Z value is 1.96 {2 SD} p= prevalence or proportion of the aspect being studied in the population. q= (1-p) d= relative error of the estimated prevalence. ii. Sampling design: A stratified multi-stage sampling design, [similar to the one employed in the National Family Health Survey - 3 (NFHS - 3)] was adopted for this study [Figure S1]. A two-stage design [Village-Household] was used in rural areas, while a three-stage design [Wards Census Enumeration Blocks (CEBs)-Household] was adopted in urban areas. In both urban and rural areas, three-level stratification was done based on geographical distribution, population size and female literacy rate ( as a surrogate of socio-economic status) so as to provide a sample of individuals that was truly representative of the population of the state under study. The first level of stratification was based on geographic distribution with each state/ut being divided into contiguous districts. This was based on the NFHS-3 sampling methodology. The second level of stratification was based on population size to ensure that there was no bias in the study and that all villages/wards, big and small, were represented in the sample studied proportionate to their contribution to the total rural/urban population of a state. The Probability Proportional to Population size (PPS) method was used to achieve this. The third level of stratification was based on the rural/urban female literacy rate, which was used as a surrogate of socio-economic status, to ensure that the sample of villages / wards selected was truly 3

5 representative of the state studied. The primary sampling units (PSUs) were villages in rural areas and Census Enumeration Blocks (CEBs) in urban areas. The ultimate stage units were households in both areas. Households were selected by systematic sampling with a random start. From each urban and rural PSU, 24 and 56 households were selected respectively. In both rural and urban areas, only one individual was selected within each household using the WHO Kish method [STEPwise approach to surveillance (STEPS; Figure S1: ICMR-INDIAB Sampling strategy ICMR INDIAB STUDY SAMPLING STRATEGY Stratified multistage design Rural (2 stage design) Urban ( 3 stage design) (3 level stratification) (3 level stratification) Villages Urban wards Census Enumeration Block Household Household Source: Anjana RM, Pradeepa R, Deepa M, et al. The Indian Council of Medical Research-India Diabetes (ICMR INDIAB) study: methodological details. J Diabetes Sci Technol. 2011; 5:

6 iii. Example of sample selection in rural areas: In rural areas, the 2001 Census list of villages served as the sampling frame. To ensure that the villages included in the study were representative of the rural population of the state under study, three levels of stratification were used in each state. The first level of stratification was geographic, with the state being divided into contiguous regions. This stratification was adopted from NFHS-3. Table S2 shows the stratification of regions for Tamil Nadu state. Regions Table S2: Stratification I Regions and districts in Tamil Nadu (Based on the NFHS-3 methodology) Districts 1 Coimbatore, Dindigul, Madurai, Theni, Erode, Nilgiri 2 Vellore, Dharmapuri, Krishnagiri, Thiruvannamalai, Salem, Namakkal, Tiruchirappalli, Karur, Perambalur, Ariyalur 3 Kanniyakumari 4 Kanchipuram, Tiruvallur, Cuddalore, Villupuram, Thanjavur, Nagappattinam, Tiruvarur, Chennai 5 Pudukkottai, Sivaganga, Virudhunagar, Ramanathapuram, Thootukudi, Tirunelveli The second level of stratification was based on the village population size [Table S3]. This variable was included to ensure that there was no bias in the study & that all villages, big and small, were represented in the sample studied proportionate to their contribution to the total rural population. Arbitrary cut offs were chosen as shown in Table S3. Table S3: Stratification II Based on the Village population size Stratification II (Village population size) < >3000 The third and final level of stratification was done based on female literacy rate [Table S4]. This variable was chosen as a crude predictor of the socio-economic status of the state. The female literacy rate for each state will be studied and then median cut offs will be made to ensure equal and even stratification. Table S4: Stratification III Based on the Female literacy rate Stratification III (Female literacy) Below Median Above Median 5

7 All the variables used for stratification have been used in NFHS-3 design as well. For purpose of simplicity, we have chosen only 1 state (Tamil Nadu), to illustrate the details of the methodology used in the study. After the first level of stratification, Tamil Nadu state was divided into five regions (as shown in Table S2). Table S5 shows the rural population in each region of Tamil Nadu and the number of villages in each of these regions. Thus in Tamil Nadu, the number of villages in each region was calculated as shown in Table S5. Table S5: Region wise selection of number of villages in the state Region Rural population (a) No. of villages Villages selected for the present study 1 60,32, ,18,64, ,82, ,02,20, ,22, Total 3,49,21,681 (b) No. of villages to be selected for the study = 100 per state a / b x Total no. of villages to be selected per state (i.e n=100) Table S6 shows stratification II and III done for Region 1 in rural Tamil Nadu for selecting the nine villages. Table S7 shows the list of villages selected in region 1 along with their district codes. Figure S2 shows the sampling framework in rural areas.. Table S6: Stratification II and III for Region 1 in rural Tamil Nadu Population size <1000 Female literacy rate Population No. of villages % total population % of villages No. of villages to be selected < Population size < Population size >3000 < Total 9 6

8 Table S7: Number of villages selected for the study (Region 1) Population Size (n) Female Literacy (%) Total population No. of villages No. of villages selected Village name District code Subdistrict Code <1000 < Sirupattii Idayanathan < Sengattampatti Sellappampalayam >3000 < Kadamalaikundu Thullukkuttinayakkanur Cherangode T. Meenakshipuram Kandiankoil Figure S2: ICMR-INDIAB sampling framework in rural areas ICMR-INDIAB STUDY SAMPLING DESIGN IN RURAL AREAS State/UT Rural Area Stratified into regions containing contiguous districts In each region, sub-stratification based on village population size & female literacy rate In each stratum, villages selected by PPS method (50 villages selected/state) In each village 56 Households selected by systematic sampling (sample size in rural area 2800 ; 2800/50=56) In each household 1 individual selected using KISH table Source: Anjana RM, Pradeepa R, Deepa M, et al. The Indian Council of Medical Research-India Diabetes (ICMR INDIAB) study: methodological details. J Diabetes Sci Technol. 2011; 5:

9 iv. Example of sample selection in urban areas: For stratification I, the Tamil Nadu state was divided into regions similar to the rural areas as shown in Table S2. In the next level of stratification, all urban towns in the given region were stratified accordingly to population size. Table S8 shows the second level of stratification used for urban areas. Table S8: Stratification II Based on the town population size Stratification III (Town population size) <20,000 20,000 1,00,000 >1,00,000 The third level of stratification was done using female literacy rate. Just as in the rural areas, median of literacy were used for the stratification. Table S9 shows stratification III in urban areas. Table S9: Stratification III Based on the Female literacy rate Stratification III (Female literacy) Below Median Above Median Table S10 shows the region-wise selection of wards in urban Tamil Nadu. Just as for villages in rural areas, it was decided to study 50 wards in each state. Table S10: Region wise selection of number of wards in Tamil Nadu State Region Urban population (a) No. of wards Wards selected for the present study Total (b) No. of wards to be selected for the study = 50 per state a / b x Total no. of wards to be selected per state (i.e n=50) 8

10 Table S11 shows stratification II and III done in urban Tamil Nadu and Table S12 shows the list of wards that were selected in region 1. Figure S3 shows the sampling framework in urban areas. Table S11: Stratification II and III for region I in urban Tamil Nadu Female literacy rate Population No. of Towns No. of wards % of wards No. of wards to be selected Population size <20,000 < Population size 20,000-1,00,000 < Population size >1,00,000 < Total 13 Total no of wards selected in region 1 = 13 Table S12: List of wards selected for the study (Region 1) Population Size (n) Female Literacy (%) Total population No. of towns No. of wards selected Town (Ward No) District code <20,000 < Andipalayam (CT) - Ward No Subdistrict code 20,000 < O' Valley (TP) - Ward No ,00, Theni Allinagaram (M) - Ward No.27 Theni Allinagaram (M) - Ward No.23 Kotagiri (TP) - Ward No.7 Periyanaicken-palayam (TP) - Ward No.13 >1,00,000 < Coimbatore (M.Corp.)- Ward No.54 Coimbatore (M.Corp. - Ward No.19 Coimbatore (M.Corp.)- Ward No.53 Madurai (M Corp.) - Ward No.25 Coimbatore (M.Corp.)- Ward No.32 Erode (M) - Ward No

11 Figure S3: ICMR-INDIAB sampling framework in urban areas ICMR-INDIAB STUDY SAMPLING DESIGN IN URBAN AREAS State/UT Urban Area Stratified into regions containing contiguous districts In each region, sub-stratification done based on town population size & female literacy rate In each stratum, wards selected by PPS method (50 wards selected/state) In each ward All Census Enumeration Blocks (CEBs) listed 1 CEB selected from each ward by random selection In each CEB All households listed 24 households selected by systematic sampling (sample size in urban areas 1200: 1200/50=24) 1 individual selected from each household using KISH table Source: Anjana RM, Pradeepa R, Deepa M, et al. The Indian Council of Medical Research-India Diabetes (ICMR INDIAB) study: methodological details. J Diabetes Sci Technol. 2011; 5: B. ESTIMATION PROCEDURE ADOPTED TO ARRIVE AT THE WEIGHTED ESTIMATES OF PREVALENCE RATES OF DIABETES Weights: The weighting was done at the domain level, which are urban and rural areas of each state. This means that all individuals in the same domain will share a common weight. The weighting process for the ICMR-INDIAB study involved three steps: Step 1 - The base weight or design weight (The inverse of the probability of selection of an individual respondent is the base weight). Step 2 - An adjustment for non-response by sample individuals eligible for the survey (Non-response adjustment is required at individual level for diabetes screening. In each state/ut household level nonresponse is considered separately in urban and rural areas, and each geographical region within rural/urban area). Step 3 - A post-stratification adjustment (calibration) of sample totals to the population totals on survey period (Similar to non-response adjustment, the post-stratification calibration is done in urban and rural area of each state/ut). Ultimately, the final weight (W) for an individual respondent was computed as the product of the base weights, the non-response adjustment and post-stratification calibration adjustment. The final weights 10

12 were used in all analyses to produce estimates of population parameters. An example for weight calculation for the state of Tamil Nadu is provided in Tables S Table S13: Example of weight calculation for Tamil Nadu state Tamil Nadu State Details Urban (C ) Rural (D) Total (E) Cell number 1 2 Population Total Population 27,483,998 34,921,681 62,405,679 3 Sample size Total Sample size 1,248 2,968 4,216 4 Probability of selection (fi) C4 / C Number screened 1,029 2,480 3,509 6 Response Rate C6 / C Design Weight (Ratio of Probability of selection and probability of selection in the Domain) E5/ C weight adjusted for Response Rate (Design Wt/ RR) C8 / C Normalisation of weight C9 * C C9 * (E4/C10 Final Weight +D10) Weighted Number of cases C6 * C Table S14: Example of weight calculation for Tamil Nadu state Rural Rural Tamil Nadu Reg1 Reg2 Reg3 Reg4 Reg5 Total Population 6,032,618 11,864, ,107 10,220,031 6,222,897 34,921,681 Sample ,968 Actual tests ,480 Response Rate Probability of selection E E E E E-05 Design weight Weight adjusted for response rate Number of cases Normalised weight Number of cases Final Weights

13 Table S15: Example of weight calculation for Tamil Nadu state Urban Urban-Tamil Nadu Reg1 Reg2 Reg3 Reg4 Reg5 Total Population 7,178,044 5,708,744 1,093,927 9,876,057 3,627,226 27,483,998 Sample ,248 Actual tests ,029 Response Rate Probability of selection E E E E E E-05 Design weight Weight adjusted for response rate Number of cases Normalised weight Number of cases Final weights

14 QUALITY CONTROL THE ICMR INDIAB STUDY Quality control refers to the efforts undertaken during the study, to monitor the quality of data at identified points of data collection and processing. Quality control in the field was achieved through multiple tiers of checks in pre-field, field and post field activities. Quality Control in Pre-field Activities Quality control at the pre-field level involved regular calibration (after completing every 20 subjects and at the start and end of every primary sampling unit) and checking of all instruments and equipment used in the study. Measurements from weighing machines, stadiometers, electronic BP apparatus, and glucose meters were checked against accurate standards (e.g. known pre-weighted sand bags) to determine if there were any errors. The automated blood pressure machines were calibrated against each other. Glucose meters were calibrated by comparing the control solution against the reference value provided in the kit. Regular examination of study tools was done to ensure that the instrument functioning was not compromised by damage and/or failing batteries. Quality Control during Field Activities Quality control in the field was achieved through multiple tiers of checks. In the first tier of quality control, the Quality Supervisors performed daily checks on all questionnaires, anthropometric measurements, and biological samples collected and/or recorded by the field personnel. The second tier of quality control was carried out by Quality Managers who randomly chose ten PSUs in each state for monitoring of data collection. These occasions were also utilised for on-site training, refreshers and/or collecting repeat samples for validation. The State Principal Investigators provided a third tier of quality control via regular field visits to supervise field activities. Finally, an external quality monitoring team from the Indian Council of Medical Research (ICMR) made site visits to check the quality of data and onsite procedures with the help of a National Monitoring Committee. All field work and pre-field activities were documented using quality logbooks. To date, 39 quality logs have been utilised in this study and have helped ensure high standards of quality. Quality control in Post-field Activities Data: All data collected was couriered to the central coordinating centre (MDRF). At MDRF, the data was cleaned and entered using a 100% double entry technique. Blood samples: All the analyses for the study were performed at the National Accreditation Board for Testing and Calibration Laboratories (NABL) and College of American Pathologists (CAP) accredited central laboratory at Dr Mohan s Diabetes Specialities Centre [DMDSC] at Chennai. Two percent of the fasting plasma samples were analysed for quality control. The laboratory was blinded to the results of the capillary test. Accurate coding system was followed to ensure anonymity of samples and also facilitated tracking of specific samples if the need arose. 13

15 ICMR-INDIAB STUDY EQUIPMENT CALIBRATION LOG - STADIOMETER 14

16 ICMR-INDIAB STUDY EQUIPMENT CALIBRATION LOG -WEIGHING MACHINE 15

17 ICMR-INDIAB STUDY EQUIPMENT CALIBRATION LOG - MEASURING TAPE 16

18 ICMR-INDIAB STUDY EQUIPMENT CALIBRATION LOG - BP APPRATUS 17

19 0ICMR-INDIAB STUDY EQUIPMENT CALIBRATION LOG - GLUCOMETER 18

20 Table S16: Comparison of responders versus non-responders for blood sample in the ICMR-INDIAB study, by state Respondent Non Respondent Age (years) Chandigarh a Jharkhand a PHASE I Maharasht ra a Tamil Nadu a MAINLAND Andhra Pradesh b PHASE II Bihar b Gujarat b Karnataka b Punjab b Arunach al Pradesh c Assam c NORTH EAST Responder 35.8 ± ± ± ± ± ± ± ± ± ± ±4.2 44± ± ± ±14.5 Non-responder 35.2 ± ± ± ± ± ± ± ± ± ± ±4.4 41± ± ± ±14.7 P value Weight (kg) Responder 58.8 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±10.7 Non-responder 58.5 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±0.3 P value Height (cm) Responder ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±.7 Non-responder ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±9.0 P value Body mass index (kg/m 2 ) Responder 23.1 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±3.8 Non-responder 23.1 ± ± ± ± ±4.5 21±3.9 22± ± ± ± ± ±3.5 22± ± ±3.9 P value Waist circumference(c m) Responder 80.8± ± ± ± ± ± ± ± ± ± ± ± ± ± ±10.9 Non-responder 81.4± ± ± ± ± ± ± ± ± ± ± ± ± ± ±11 P value Systolic BP (mmhg) Responder 126 ± ±19 127±18 129±19 128±18 128± ± ±25 136±18 130±18 130±20 129±18 124±18 126±17 128±19 Non-responder 127 ± ±19 127±20 129±17 130± ± ± ±25 135±17 126±18 128±19 128±18 123±18 124±15 129±17 P value Values are presented as mean±sd or numbers [percentage] as appropriate; a Phase I; b Phase II; c Northeastern phase; none of the data provided here are published elsewhere Manipur c Meghala ya c Mizoram c Tripur a c

21 Non-responders vs responders: Of the 60,918 individuals approached, 57,117 individuals participated (93.8%). Of the 6.2% (3,801/60,918) who did not participate, 3.7% did not respond even after repeated requests, 1.4% were not available after a minimum of three visits including one weekend visit, and 1.1% had houses locked. However, as we have already accounted for a 20% non response rate in the sample size calculation, we do not think this will significantly affect the results. The other 5%, were those who participated in the study but did not provide blood samples. These individuals were not included for estimating the prevalence of diabetes (due to non-availability of blood samples). Responders and non-responders for blood sample in each state were compared and it was found that there were no significant differences in the general characteristics with respect to age, weight, height, BMI, waist circumference and systolic blood pressure. 20

22 Chandigar h a Jharkhand a PHASE I Table S17: General characteristics of the study population, by state (urban areas) MAINLAND Maharasht ra a Tamil Nadu a Andhra Pradesh b PHASE II Bihar b Gujarat b Karnataka b Punjab b Arunacha l Pradesh c Assam c NORTH EAST n Age [years] 39 5(12 8) 39 6(14 0) 40 0 (14 0) 40 6(14 0) 41 2(14 5) 41 5(14 4) 43 1 ( 14 4) 40 3 (14 1) 42 6 ( 15 2) Male [%] 38 6 (11 9) Manipur c Meghalay a c Mizoram c Tripura c 41 7( 14 3) 43 9 ( 15 1) 40 2 ( 14 4) 42 8 ( 15 5) 42 8(13 9) 447 (49%) 482 (51%) 630 (50%) 520 (48%) 512 (44%) 528 (45%) 504 (43%) 408 (35%) 495 (44%) 583 (50%) 420 (37%) 527 (44%) 443 (40%) 479 (40%) 460 (40%) Female [%] 464 (51%) 463 (49%) 624 (50%) 556 (52%) 643 (56%) 638 (55%) 676 (57%) 755 (65%) 630 (56%) 594 (50%) 703 (63%) 675 (56%) 655 (60%) 704 (60%) 691 (60%) BMI [kg/m 2 ] 24 4 ( 4 6) 22 7(4 6) 22 2 (4 3) 23 6( 4 9) 24 1 ( 4 9) 22 8 ( 4 5) 23 5 ( 4 6) 23 7 ( 4 9) 25 0 ( 4 6) 23 4 (3 4) 22 6 ( 4 2) 24 0 ( 4 0) 22 6 ( 4 0) 23 7 ( 3 9) 22 2 (4 0) Waist [cm] Male 86 5 ( 11 6) 84 3 (13 6) 81 2 (11 9) 83 4 (11 9) 85 2 ( 12 2) 85 0 ( 12 8) 83 1 ( 11 0) 85 1 ( 12 2) 89 1 ( 12 7) Female 81 2 ( 12 3) 77 3(12 7) 73 4 (11 6) 78 5 ( 12 0) 81 2 (13 0) 80 1 ( 13 6) 81 3 ( 12 0) 80 4 (12 2) 87 1 ( 11 9) Overall Systolic BP [mmhg] Diastolic BP [mmhg] Current smokers n[%] 81 8 (10 2) 80 3 (10 3) 83.9 (12.5) 80.8 (13.6) 77.3 (12.4) 80.9 (12.2) 84.2 (12.5) 82.4 (13.5) 82 (11.6) 82.1 (12.4) 88 (12.3) 81 (10.3) 83 3 ( 11 3) 85 1 ( 11 0) 81 5 ( 10 8) 84 1( 13 3) 82 0 (10 7) 80 3 ( 12 8) 84 0 ( 11 5) 81 1 ( 11 4) 81 9 ( 11 5) 80 7( 11 1) 130 ( 18) 130 (19) 128 (19) 130 ( 19) 129 (18) 129 ( 19) 120 ( 24) 120 (27) 136 ( 18) 130 (18) 132 ( 21) 130 ( 18) 125 (20) 127(18) 131( 20) 79(11) 78 (11) 80 (11) 81 (11) 79 (11) 78 (10) 73 (14) 73 (16) 81 (10) 83 (11) 79 (11) 84 (10) 80 ( 11) 80 ( 11) 80 (11) Male 107 (24%) 87 (18%) 107 (17%) 163 (31%) 105 (21%) 48 (9%) 70 (14%) 86 (21%) 23 (5%) 135 (23%) 107 (26%) 119 (23%) 203 (46%) 277 (58%) 202 (44%) Female 3 (<1%) 6 (1%) 11 (2%) 3 (<1%) 5 (<1%) 9 (1%) 2 (<1%) (1%) 2 (<1%) 13 (2%) 5 (0 8) 142 (20 2) 2 (0 3) Current alcohol n[%] Male 135 (30%) 118 (25%) 130 (21%) 170 (33%) 142 (28%) 88 (17%) 23 (5%) 83 (20%) 152 (31%) 256 (44%) 101 (21%) 185 (35%) 114 (25 7) 177 (37 0) 81 (17 6) Female 0 10 (2%) 1 (<1%) 2 (<1%) 1 (<1%) 2 (<1%) 0 2 (<1%) (17%) 8 (1%) 0 2 (<1%) 15 (2%) 2 (<1%) Socioeconomic status (SES) Low [%] Middle [%] 87 (10%) 194 (21%) 161 (13%) 172 (16%) 214 (19%) 210 (18%) 140 (12%) 158 (14%) 101 (9%) 153 (13%) 107 (10%) 23 (2%) 125 (11%) 127 (11%) 96 (8%) 284 (31%) 453 (49%) 510 (42%) 405 (39%) 595 (52%) 606 (52%) 550 (47%) 618 (53%) 548 (49%) 415 (35%) 558 (50%) 412 (34%) 387 (35%) 408 (35%) 631 (55%) High [%] 533 (59%) 283 (30%) 554 (45%) 471 (45%) 346 (30%) 350 (30%) 490 (42%) 387 (33%) 476 (42%) 609 (52%) 458 (41%) 767 (64%) 586 (53%) 648 (55%) 424 (37%) Values are presented as mean(sd or numbers [percentage] as appropriate; a Phase I (November 17, 2008, and April 16, 2010); b Phase II(September 24, 2012, and July 26, 2013); c North East Phase (January 5, 2012, and July 3, 2015); none of the data provided here are published elsewhere 81.4 (12.3) 84.5 (11.3) 81.2 (11.2) 82.8 (12.3) 81.2 (10.9) 21

23 Chandigar h a Jharkhand a Table S18: General characteristics of the study population, by state (rural areas) PHASE I Maharasht ra a Tamil Nadu a MAINLAND Andhra Pradesh b PHASE II Bihar b Gujarat b Karnataka b Punjab b Arunachal Pradesh c Assam c NORTH EAST n Age (years) 34 4(11 7) 39 5(14 3) 41 8(14 8) 42 9(14 7) 43 4(15 5) 41 5(14 7) 43 3(14 8) 43 0(15 2) Male (%) 1253 (51%) 1204 (50%) 1323 (50%) 1251 (48%) 1174 (44%) 1122 (41%)* 1337 (49%) 1038 (38%) Female(%) 1192 (49%) 1188 (50%) 1343 (50%) 1337 (52%) 1496(56%) 1610(59%) 1399(51%) 1707(62%) Manipur c 42 4(15 2 ) 39 8(13 2)* 40 8(14 1) 43 9(15 1) (43%) 1362 (48%) 1115 (40%) (46%) 1495(57% (52%) 1653(60%) ) (54%) Meghalay a c 40 0(14 4 ) 1188 (45%)* 1481(55% ) Mizoram c 41 9(14 7 ) 1393 (48%) 1504(52% ) BMI (kg/m 2 ) 22 8(4 5) 19 2(3 0) 20 5(3 8) 21 7(3 9) 21 6(4 3) 20 3(3 4) 21 6(4 1) 21 3(4 0) 24 0(4 5) 22 5(3 5) 20 4(3 5) 23 0(3 7) 21 0(3 2) 22 1(3 4) Waist (cm) Male 81 6(11 6) 74 1(9 3) 77 3(11 0) 79 2(11 1) 79 6 (12 7) 78 0(10 0) 78 3(10 4) 79 7(10 9) Female 77 7(13 0) 68 4(8 8) 68 0(10 4) 73 2(10 8) 71 6(11 4) 73 4(10 4) 75 4(11 1) 74 5(11 1) Overall Systolic BP (mmhg) Diastolic BP (mmhg) Current smokers n(%) 79.7 (12.5) 71.3 (9.6) 72.7 (11.7) 76.1 (11.4) 78 (12.9) 75.3 (10.5) 76.8 (10.9) 76.5 (11.3) 87 2(11 0 )* 81 3(9 6) 76 1(10 1) 81 2(9 9) 75 3(8 8) 78 0(9 9) 86 4(11 6 ) 79 2(11 0)* 72 5(9 9) 81 1(11 2) 75 3(9 9) 75 6(10 1) (11.4) 80.2 (10.4) 74 (10.1) 81.2 (10.6) 75.3 (9.4) (10.1) 124(16) 127(19 127(18)* 129(19)* 128(18) 127(18)* 130(16) 125(24) 136(17) 130( 18) 129(20) 128(18) 124(17) 125(17)* 128(18) 78(11) 76(11) 78(11) 78(11) 78(10) 76(10) 80(10) 76(13) 82(10) 82(11) 73(11) 83(11) 78(11) 79(10) 78(11) Male 373 (30%) 212 (18%) 202 (15%) 421 (34%) 323 (28%)* 153 (14%)* 327 (25%) 231 (22%) 52 (5%) 336 (26%) 290 (26%) 447 (35%) 793 (67%) 895(65%) * Female 12 (1%) 50 (4%) 23 (2%) 5 (4%) 27 (2%) 38 (2%) 12 (1%) 1 (<1%) 2 (<1%) 75 (5%) 16 (1%)* 78 (5%) 87 (6%) 432 (29%) Current alcohol n(%) Male 361 (29%) 553 (46%) 229 (17%)* 456 (36%) 371 (32%) 204 (18%) 95 (7%)* 179 (17%) 320 (28%) 631 (46%) 397 (36%) 503 (40%) 303 (26%) Tripura c 40 5(14 7) 1215 (46%)* 1440(54 %) 20 7(3 7) 77 5(10 2) 75 5(10 7) 76.4 (10.5) 525 (43%) 103 (7%) 323 (23%) 251 (21%) Female 1 (<1%) 180 (15%) 1 (<1%) 5 (<1%) 44 (3%) 2 (<1%) 2 (<1%) 32 (2%) 2 (<1%) 340 (23%) 137 (8%) 10 (<1%)* 10(<1%) 17 (1%) 37 (3%) Socioeconomic status (SES) 818 (31%) 1359 (50%) 662 Low (%) 283 (12%) 537 (22%) 629 (24%) 419 (16%) 369 (14%) 611 (22%) 97 (4%) 683 (24%) 865 (31%) 238 (9%) (25%) (41%) 1104 (40%) 747 (28%) 1558 (55%) Middle (%) 775 (32%) 1206 (50%) 1142 (43%) (53%) (52%) 1470 (54%) 1351 (49%) (62%) (63%) 471 (18%) (30%) 332 High (%) 1387 (57%) 649 (27%)* 895 (34%) 801 (31%) 268 (10%) (46%)* 664 (24%) (68%) 613 (22%) 552 (20%) (12%) Values are presented as mean±sd or numbers [percentage] as appropriate; * p<0 05, p< compared urban participants as shown in Supplementary Table S1; a Phase I (November 17, 2008, and April 16, 2010); b Phase II(September 24, 2012, and July 26, 2013); c North East Phase (January 5, 2012, and July 3, 2015); none of the data provided here are published elsewhere 846 (29%) 1146 (40%) * 905 (31%) 991 (37%) 1425 (54%) 239 (9%) 22