Browsing by Author "Mohan, V"

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    DISTRIBUTION OF 10-YEAR AND LIFETIME PREDICTED RISK FOR CARDIOVASCULAR DISEASE IN THE INDIAN SENTINEL SURVEILLANCE STUDY POPULATION
    (JOURNAL OF EPIDEMIOLOGY AND COMMUNITY HEALTH, 2011) Jeemon, P; Prabhakaran, D; Huffman, M; Goenka, S; Ramakrishnan, L; Thankappan, KR; Mohan, V; Joshi, PP; Lloyd-Jones, DM; Reddy, KS
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    Distribution of 10-year and lifetime predicted risk for cardiovascular disease in the Indian Sentinel Surveillance Study population (cross-sectional survey results)
    (BMJ OPEN, 2011) Jeemon, P; Prabhakaran, D; Huffman, MD; Ramakrishnan, L; Goenka, S; Thankappan, KR; Mohan, V; Joshi, PP; Mohan, BVM; Ahmed, F; Ramanathan, M; Ahuja, R; Chaturvedi, V; Lloyd-Jones, DM; Reddy, KS
    Introduction: Cardiovascular disease (CVD) prevention guidelines recommend lifetime risk stratification for primary prevention of CVD, but no such risk stratification has been performed in India to date. Methods: The authors estimated short-term and lifetime predicted CVD risk among 10 054 disease-free, adult Indians in the 20-69-year age group who participated in a nationwide risk factor surveillance study. The study population was then stratified into high short-term (>= 10% 10-year risk or diabetes), low short-term (<10%)/high lifetime and low short-term/low lifetime CVD risk groups. Results: The mean age (SD) of the study population (men=63%) was 40.8 +/- 10.9 years. High short-term risk for coronary heart disease was prevalent in more than one-fifth of the population (23.5%, 95% CI 22.7 to 24.4). Nearly half of individuals with low short-term predicted risk (48.2%, 95% CI 47.1 to 49.3) had a high predicted lifetime risk for CVD. While the proportion of individuals with all optimal risk factors was 15.3% (95% CI 14.6% to 16.0%), it was 20.6% (95% CI 18.7% to 22.6%) and 8.8% (95% CI 7.7% to 10.5%) in the highest and lowest educational groups, respectively. Conclusion: Approximately one in two men and three in four women in India had low short-term predicted risks for CVD in this national study, based on aggregate risk factor burden. However, two in three men and one in two women had high lifetime predicted risks for CVD, highlighting a key limitation of short-term risk stratification.
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    Distribution of 10-year lifetime predicted risk for cardiovascular disease in the Indian Sentinel Surveillance Study population (Cross –sectional survey results).
    (BMJ Open, 2011) Jeemon, P; Prabhakaran, D; Huffman, MD; Ramakrishnan, L; Goenka, S; Thankappan, KR; Mohan, V; Joshi, PP; Mohan, BVM; Ahmed, F; Ramanathan, M; Ajuja, R; Chaturvedi, V; Lloyd-Jones, D; Reddy, KS
    Introduction:Cardiovascular disease (CVD) prevention guidelines recommend lifetime risk stratification for primary prevention of CVD, but no such risk stratification has been performed in India to date.METHODS:The authors estimated short-term and lifetime predicted CVD risk among 10,054 disease-free, adult Indians in the 20-69-year age group who participated in a nationwide risk factor surveillance study. The study population was then stratified into high short-term (? 10% 10-year risk or diabetes), low short-term (<10%)/high lifetime and low short-term/low lifetime CVD risk groups.RESULTS: The mean age (SD) of the study population (men=63%) was 40.8 ± 10.9 years. High short-term risk for coronary heart disease was prevalent in more than one-fifth of the population (23.5%, 95% CI 22.7 to 24.4). Nearly half of individuals with low short-term predicted risk (48.2%, 95% CI 47.1 to 49.3) had a high predicted lifetime risk for CVD. While the proportion of individuals with all optimal risk factors was 15.3% (95% CI 14.6% to 16.0%), it was 20.6% (95% CI 18.7% to 22.6%) and 8.8% (95% CI 7.7% to 10.5%) in the highest and lowest educational groups, respectively.CONCLUSION: Approximately one in two men and three in four women in India had low short-term predicted risks for CVD in this national study, based on aggregate risk factor burden. However, two in three men and one in two women had high lifetime predicted risks for CVD, highlighting a key limitation of short-term risk stratification.
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    Double burden of underweight and overweight among children (10-19 years of age) of employees working in Indian industrial units
    (The National Medical Journal of India, 2009) Jeemon, P; Prabhakaran, D; Mohan, V; Thankappan, KR; Joshi, PP; Ahmed, F; Chaturvedi, V; Reddy, KS
    BACKGROUND: Along with the existing problem of underweight, overweight in children is increasing in the developing world. However, there is little information on its magnitude and pattern in the Indian context. We aimed to study the pattern and correlates of overweight in Indian children and adolescents.METHODS: A total of 3750 children in the age group of 10-19 years, who were family members of randomly selected employees from 10 different industrial sites in India, were surveyed using an interviewer-administered questionnaire. RESULTS: The prevalence of underweight was highest in peri-urban areas (30.2% and 53.2% according to Indian and international criteria, respectively). In urban and highly urban areas, the prevalence of underweight was 14.1% and 9.8%, respectively, according to the Indian criteria, and 27.1% and 19.2%, respectively, according to international criteria. The proportion of overweight children was highest in the highly urban category (19.1% and 13.4% according to Indian and international criteria, respectively). The level of urbanization (OR 3.1 and 4.7 for overweight in urban and highly urban areas, respectively, compared with peri-urban areas, p < 0.001), physical activity (OR 0.4, p < 0.001, in children with physical activity score > or = 75th percentile compared with a score < or = 75th percentile) and frequency of meals outside the home (OR 12, p < 0.001, if > 25% weekly meals taken outside the home compared with < 25% of weekly meals outside home) were significant predictors of overweight. CONCLUSION: There is a double burden of underweight and overweight among Indian children and adolescents.
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    Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015: a systematic analysis for the Global Burden of Disease Study 2015
    (LANCET) Wang, HD; Naghavi, M; Allen, C; Barber, RM; Bhutta, ZA; Carter, A; Casey, DC; Charlson, FJ; Chen, AZ; Coates, MM; Coggeshall, M; Dandona, L; Dicker, DJ; Erskine, HE; Ferrari, AJ; Fitzmaurice, C; Foreman, K; Forouzanfar, MH; Fraser, MS; Pullman, N; Gething, PW; Goldberg, EM; Graetz, N; Haagsma, JA; Hay, SI; Huynh, C; Johnson, C; Kassebaum, NJ; Kinfu, Y; Kulikoff, XR; Kutz, M; Kyu, HH; Larson, HJ; Leung, J; Liang, XF; Lim, SS; Lind, M; Lozano, R; Marquez, N; Mensah, GA; Mikesell, J; Mokdad, AH; Mooney, MD; Nguyen, G; Nsoesie, E; Pigott, DM; Pinho, C; Roth, GA; Salomon, JA; Sandar, L; Silpakit, N; Sligar, A; Sorensen, RJD; Stanaway, J; Steiner, C; Teeple, S; Thomas, BA; Troeger, C; VanderZanden, A; Vollset, SE; Wanga, V; Whiteford, HA; Wolock, T; Zoeckler, L; Abate, KH; Abbafati, C; Abbas, KM; Abd-Allah, F; Abera, SF; Abreu, DMX; Abu-Raddad, LJ; Abyu, GY; Achoki, T; Adelekan, AL; Ademi, Z; Adou, AK; Adsuar, JC; Afanvi, KA; Afshin, A; Agardh, EE; Agarwal, A; Agrawal, A; Kiadaliri, AA; Ajala, ON; Akanda, AS; Akinyemi, RO; Akinyemiju, TF; Akseer, N; Al Lami, FH; Alabed, S; Al-Aly, Z; Alam, K; Alam, NKM; Alasfoor, D; Aldhahri, SF; Aldridge, RW; Alegretti, MA; Aleman, AV; Alemu, ZA; Alexander, LT; Alhabib, S; Ali, R; Alkerwi, A; Alla, F; Allebeck, P; Al-Raddadi, R; Alsharif, U; Altirkawi, KA; Martin, EA; Alvis-Guzman, N; Amare, AT; Amegah, AK; Ameh, EA; Amini, H; Ammar, W; Amrock, SM; Andersen, HH; Anderson, B; Anderson, GM; Antonio, CAT; Aregay, AF; Arnlov, J; Arsenijevic, VSA; Al Artaman; Asayesh, H; Asghar, RJ; Atique, S; Avokpaho, EFGA; Awasthi, A; Azzopardi, P; Bacha, U; Badawi, A; Bahit, MC; Balakrishnan, K; Banerjee, A; Barac, A; Barker-Collo, SL; Barnighausen, T; Barregard, L; Barrero, LH; Basu, A; Basu, S; Bayou, YT; Bazargan-Hejazi, S; Beardsley, J; Bedi, N; Beghi, E; Belay, HA; Bell, B; Bell, ML; Bello, AK; Bennett, DA; Bensenor, IM; Berhane, A; Bernabe, E; Betsu, BD; Beyene, AS; Bhala, N; Bhalla, A; Biadgilign, S; Bikbov, B; Bin Abdulhak, AA; Biroscak, BJ; Biryukov, S; Bjertness, E; Blore, JD; Blosser, CD; Bohensky, MA; Borschmann, R; Bose, D; Bourne, RRA; Brainin, M; Brayne, CEG; Brazinova, A; Breitborde, NJK; Brenner, H; Brewer, JD; Brown, A; Brown, J; Brugha, TS; Buckle, GC; Butt, ZA; Calabria, B; Campos-Novato, IR; Campuzano, JC; Carapetis, JR; Cardenas, R; Carpenter, D; Carrero, JJ; Castaneda-Oquela, CA; Rivas, JC; Catala-Lopez, F; Cavalleri, F; Cercy, K; Cerda, J; Chen, WQ; Chew, A; Chiang, PPC; Chibalabala, M; Chibueze, CE; Chimed-Ochir, O; Chisumpa, VH; Choi, JYJ; Chowdhury, R; Christensen, H; Christopher, DJ; Ciobanu, LG; Cirillo, M; Cohen, AJ; Colistro, V; Colomar, M; Colquhoun, SM; Cooper, C; Cooper, LT; Cortinovis, M; Cowie, BC; Crump, JA; Damsere-Derry, J; Danawi, H; Dandona, R; Daoud, F; Darby, SC; Dargan, PI; das Neves, J; Davey, G; Davis, AC; Davitoiu, DV; de Castro, EF; de Jager, P; De Leo, D; Degenhardt, L; Dellavalle, RP; Deribe, K; Deribew, A; Dharmaratne, SD; Dhillon, PK; Diaz-Torne, C; Ding, EL; dos Santos, KPB; Dossou, E; Driscoll, TR; Duan, LL; Dubey, M; Bartholow, B; Ellenbogen, RG; Lycke, C; Elyazar, I; Endries, AY; Ermakov, SP; Eshrati, B; Esteghamati, A; Estep, K; Faghmous, IDA; Fahimi, S; Jose, E; Farid, TA; Farinha, CSES; Faro, A; Farvid, MS; Farzadfar, F; Feigin, VL; Fereshtehnejad, SM; Fernandes, JG; Fernandes, JC; Fischer, F; Fitchett, JRA; Flaxman, A; Foigt, N; Fowkes, FGR; Franca, EB; Franklin, RC; Friedman, J; Frostad, J; Hirst, T; Futran, ND; Gall, SL; Gambashidze, K; Gamkrelidze, A; Ganguly, P; Gankpe, FG; Gebre, T; Gebrehiwot, TT; Gebremedhin, AT; Gebru, AA; Geleijnse, JM; Gessner, BD; Ghoshal, AG; Gibney, KB; Gillum, RF; Gilmour, S; Giref, AZ; Giroud, M; Gishu, MD; Giussani, G; Glaser, E; Godwin, WW; Gomez-Dantes, H; Gona, P; Goodridge, A; Gopalani, SV; Gosselin, RA; Gotay, CC; Goto, A; Gouda, HN; Greaves, F; Gugnani, HC; Gupta, R; Gupta, R; Gupta, V; Gutierrez, RA; Hafezi-Nejad, N; Haile, D; Hailu, AD; Hailu, GB; Halasa, YA; Hamadeh, RR; Hamidi, S; Hancock, J; Handal, AJ; Hankey, GJ; Hao, YT; Harb, HL; Harikrishnan, S; Haro, JM; Havmoeller, R; Heckbert, SR; Heredia-Pi, IB; Heydarpour, P; Hilderink, HBM; Hoek, HW; Hogg, RS; Horino, M; Horita, N; Hosgood, HD; Hotez, PJ; Hoy, DG; Hsairi, M; Htet, AS; Htike, MMT; Hu, GQ; Huang, C; Huang, H; Huiart, L; Husseini, A; Huybrechts, I; Huynh, G; Iburg, KM; Innos, K; Inoue, M; Iyer, VJ; Jacobs, TA; Jacobsen, KH; Jahanmehr, N; Jakovljevic, MB; James, P; Javanbakht, M; Jayaraman, SP; Jayatilleke, AU; Jeemon, P; Jensen, PN; Jha, V; Jiang, G; Jiang, Y; Jibat, T; Jimenez-Corona, A; Jonas, JB; Joshi, TK; Kabir, Z; Karnak, R; Kan, HD; Kant, S; Karch, A; Karema, CK; Karimkhani, C; Karletsos, D; Karthikeyan, G; Kasaeian, A; Katibeh, M; Kaul, A; Kawakami, N; Kayibanda, JF; Keiyoro, PN; Kemmer, L; Kemp, AH; Kengne, AP; Keren, A; Kereselidze, M; Kesavachandran, CN; Khader, YS; Khalil, IA; Khan, AR; Khan, EA; Khang, YH; Khera, S; Khoja, TAM; Kieling, C; Kim, D; Kim, YJ; Kissela, BM; Kissoon, N; Knibbs, LD; Knudsen, AK; Kokubo, Y; Kolte, D; Kopec, JA; Kosen, S; Koul, PA; Koyanagi, A; Krog, NH; Defo, BK; Bicer, BK; Kudom, AA; Kuipers, EJ; Kulkarni, VS; Kumar, GA; Kwan, GF; Lal, A; Lal, DK; Lalloo, R; Lam, H; Lam, JO; Langan, SM; Lansingh, VC; Larsson, A; Laryea, DO; Latif, AA; Lawrynowicz, AEB; Leigh, J; Levi, M; Li, Y; Lindsay, MP; Lipshultz, SE; Liu, PY; Liu, S; Liu, Y; Lo, LT; Logroscino, G; Lotufo, PA; Lucas, RM; Lunevicius, R; Lyons, RA; Ma, S; Machado, VMP; Mackay, MT; MacLachlan, JH; El Razek, HMA; El Razek, MMA; Majdan, M; Majeed, A; Malekzadeh, R; Manamo, WAA; Mandisarisa, J; Mangalam, S; Mapoma, CC; Marcenes, W; Margolis, DJ; Martin, GR; Martinez-Raga, J; Marzan, MB; Masiye, F; -Jones, AJM; Massano, J; Matzopoulos, R; Mayosi, BM; McGarvey, ST; McGrath, JJ; Mckee, M; McMahon, BJ; Meaney, PA; Mehari, A; Mehndiratta, MM; Mena-Rodriguez, F; Mekonnen, AB; Melaku, YA; Memiah, P; Memish, ZA; Mendoza, W; Meretoja, A; Meretoja, TJ; Mhimbira, FA; Micha, R; Miller, TR; Mirarefin, M; Misganaw, A; Mock, CN; Mohammad, KA; Mohammadi, A; Mohammed, S; Mohan, V; Mola, GLD; Monasta, L; Hernandez, JCM; Montero, P; Montico, M; Montine, TJ; Moradi-Lakeh, M; Morawska, L; Morgan, K; Mori, R; Mozaffarian, D; Mueller, U; Murthy, GVS; Murthy, S; Musa, KI; Nachega, JB; Nagel, G; Naidoo, KS; Naik, N; Naldi, L; Nangia, V; Nash, D; Nejjari, C; Neupane, S; Newton, CR; Newton, JN; Ng, M; Ngalesoni, FN; Ngirabega, JD; Le Nguyen, Q; Nisar, MI; Pete, PMN; Nomura, M; Norheim, OF; Norman, PE; Norrving, B; Nyakarahuka, L; Ogbo, FA; Ohkubo, T; Ojelabi, FA; Olivares, PR; Olusanya, BO; Olusanya, JO; Opio, JN; Oren, E; Ortiz, A; Osman, M; Ota, E; Ozdemir, R; Pa, M; Pandian, JD; Pant, PR; Papachristou, C; Park, EK; Park, JH; Parry, CD; Parsaeian, M; Caicedo, AJP; Patten, SB; Patton, GC; Paul, VK; Pearce, N; Pedro, JM; Stokic, LP; Pereira, DM; Perico, N; Pesudovs, K; Petzold, M; Phillips, MR; Piel, FB; Pillay, JD; Plass, D; Platts-Mills, JA; Polinder, S; Pope, CA; Popova, S; Poulton, RG; Pourmalek, F; Prabhakaran, D; Qorbani, M; Quame-Amaglo, J; Quistberg, DA; 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Werdecker, A; Westerman, R; White, RA; Wijeratne, T; Wilkinson, JD; Williams, HC; Wiysonge, CS; Woldeyohannes, SM; Wolfe, CDA; Won, SH; Wong, JQ; Woolf, AD; Xavier, D; Xiao, QY; Xu, GL; Yakob, B; Yalew, AZ; Yan, LL; Yano, YC; Yaseri, M; Ye, P; Yebyo, HG; Yip, P; Yirsaw, BD; Yonemoto, N; Yonga, G; Younis, MZ; Yu, SC; Zaidi, Z; Zaki, MES; Zannad, F; Zavala, DE; Zeeb, H; Zeleke, BM; Zhang, H; Zodpey, S; Zonies, D; Zuhlke, LJ; Vos, T; Lopez, AD; Murray, CJL
    Background Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures. Methods We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography-year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, life expectancy from birth increased from 61.7 years (95% uncertainty interval 61.4-61.9) in 1980 to 71.8 years (71.5-72.2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11.3 years (3.7-17.4), to 62.6 years (56.5-70.2). Total deaths increased by 4.1% (2.6-5.6) from 2005 to 2015, rising to 55.8 million (54.9 million to 56.6 million) in 2015, but age-standardised death rates fell by 17.0% (15.8-18.1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14.1% (12.6-16.0) to 39.8 million (39.2 million to 40.5 million) in 2015, whereas age-standardised rates decreased by 13.1% (11.9-14.3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42.1%, 39.1-44.6), malaria (43.1%, 34.7-51.8), neonatal preterm birth complications (29.8%, 24.8-34.9), and maternal disorders (29.1%, 19.3-37.1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000-183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000-532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death. Interpretation At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems. Copyright (C) The Author(s). Published by Elsevier Ltd.
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    Impact of alcohol on coronary heart disease in Indian men
    (Atherosclerosis, 2010) Roy, A; Prabhakaran, D; Jeemon, P; Thankappan, KR; Mohan, V; Ramakrishnan, L; Joshi, P; Ahmed, F; Mohan, BV; Saran, RK; Sinha, N; Reddy, KS
    BACKGROUND: Moderate alcohol consumption is known to be protective against coronary heart disease (CHD). However, the INTERHEART study, a case-control study of acute myocardial infarction (MI) patients, revealed that alcohol consumption in South Asians was not protective against CHD. We therefore planned to study cardiovascular risk factor and CHD prevalence among male alcohol users as compared to age matched lifetime abstainers. METHODS: The subjects for this study were recruited from a cross-sectional survey carried out among employees and their family members aged 20-69 years in 10 medium-to-large industries from diverse sites in India, using a stratified random sampling technique. Information on education, behavioral, clinical and biochemical risk factors of CHD and alcohol use was obtained through standardized instruments. CHD diagnosis was based on Rose Questionnaire or a prior physician diagnosed CHD. RESULTS: A total of 4465 subjects were present or past alcohol users. The mean age of alcohol users and lifetime abstainers was 42.8+/-11.0 years and 42.8+/-11.1 years, respectively (p=0.90). Systolic blood pressure and diastolic blood pressure were significantly higher in alcohol users (128.7+/-17.6 mmHg/80.1+/-11.3 mmHg) as compared to lifetime abstainers (126.9+/-15.9 mmHg/79.5+/-10.3 mmHg, p<0.01). Fasting blood sugar in alcohol users (98.7+/-30.5 mg%) was also significantly higher than lifetime abstainers (96.6+/-26.0 mg%, p<0.01). Total cholesterol was lower in alcohol users (179.1+/-41.1 mg%) as compared to lifetime abstainers (182.7+/-38.2 mg%, p<0.01). HDL cholesterol was higher in alcohol users (42.9+/-10.8 mg%) as compared to lifetime abstainers (41.3+/-10.0 mg%, p<0.01). Body mass index (BMI) was lower in alcohol users as compared to lifetime abstainers (22.7+/-4.1 kg/m2 vs. 24.0+/-3.3 kg/m2, p<0.001). Tobacco use was significantly higher in alcohol users (63.1% vs. 20.7%). The odds ratio (OR) of having CHD after adjusting for tobacco use, BMI and education was 1.4 (95%CI 1.0-1.9) in alcohol users as compared to controls. The OR was 1.2 (95%CI 0.8-1.6) in occasional alcohol users, 1.6 (95%CI 1.0-2.2) in regular alcohol users and 2.1 (95% CI 1.1-3.0) in past alcohol users as compared to controls.CONCLUSION:We did not observe an inverse (protective) association between alcohol intake and the prevalence of CHD. In contrast, our study indicated an association in the reverse direction, suggesting possible harm of alcohol for coronary risk in Indian men. This relationship needs to be further examined in large, prospective study.
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    Measurement of cholesterol and triglycerides from a dried blood spot in an Indian Council of Medical Research-World Health Organization multicentric survey on risk factors for noncommunicable diseases in India
    (Journal of Clinical Lipidology, 2012) Lakshmy, R; Mathur, P; Gupta, R; Shah, B; Anand, K; Mohan, V; Desai, NG; Mahanta, J; Joshi, PP; Thankappan, KR
    Dried blood may be a convenient method of sample collection in epidemiological studies; however, the method needs evaluation in a field settings. In the present study, feasibility of using dried blood for measurement of cholesterol and triglycerides was evaluated in multicenter surveillance study for noncommunicable disease (NCD).
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    Paradoxical impact of alcohol consumption on coronary heart disease
    (EUROPEAN HEART JOURNAL, 2009) Roy, A; Prabhakaran, D; Jeemon, P; Thankappan, KR; Mohan, V; Ramakrishnan, L; Joshi, P; Ahmed, FU; Mohan, BVM; Reddy, KS
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    Prevalence and determinants of diabetes mellitus in the Indian industrial population
    (Diabetic Medicine, 2008) Ajay, VS; Prabhakaran, D; Jeemon, P; Thankappan, KR; Mohan, V; Ramakrishnan, L; Joshi, P; Ahmed, FU; Mohan, BVM; Chaturvedi, R; Mukherjee, R; Reddy, KS
    AIM: To highlight the regional difference in the prevalence of diabetes mellitus (DM) and to explore determinants in variability in the Indian industrial population. METHODS: A cross-sectional survey was carried out among the employees and their family members (10 930 individuals, mean age 39.6 years, 6764 male) of eleven medium-to-large industries from diverse sites in India, using a stratified random sampling technique. Information on behavioural, clinical and biochemical risk factors of DM was obtained, through standardized instruments. DM was diagnosed when fasting blood glucose was > or = 7.0 mmol/l and/or individuals took drug treatment for DM. Multiple logistic regression analysis was carried out to identify the potential predictors of DM. RESULT: In the 20 to 69-year-old age group, the crude prevalence of DM and impaired fasting glucose was 10.1 and 5.3%, respectively. Urban sites had a higher prevalence and awareness of DM status. Individuals in the lower education group had a high prevalence of DM (11.6%). In diabetic subjects, 38.4% were unaware that they had diabetes. Waist-circumference-to-height ratio had a higher DM predictive power than waist circumference and body mass index. The risk factors associated with overall prevalence of DM were: age, sex, low-education level, family history of DM, hypertension and overweight/obesity. Interaction of risk factors was observed only in urban high-prevalence sites. CONCLUSION: There are wide regional variations in the prevalence of DM in India. The high burden of undetected diabetes, even in settings with universal access to on-site health care, highlights the need for innovative prevention and control strategies.
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    Urban rural differences in prevalence of self-reported diabetes in India - The WHO-ICMR Indian NCD risk factor surveillance
    (DIABETES RESEARCH AND CLINICAL PRACTICE, 2008) Mohan, V; Mathur, P; Deepa, R; Deepa, M; Shukla, DK; Menon, GR; Anand, K; Desai, NG; Joshi, PP; Mahanta, J; Thankappan, KR; Shah, B
    Recent reports show strikingly high prevalence of diabetes among urban Asian Indians; however, there are very few studies comparing urban, peri-urban and rural prevalence rates of diabetes and their risk factors at the national level. This study is a part of the national non-communicable diseases (NCD) risk factor surveillance conducted in different geographical locations (North, South, East, West/central) in India between April 2003 and March 2005. A total of 44,523 individuals (age: 15-64 years) inclusive of IS,239 from urban, 15,760 from peri-urban/slum and 13,524 from rural areas were recruited. Major risk factors were studied using modified WHO STEPS approach. Diabetes was diagnosed based on self-reported diabetes diagnosed by a physician. The lowest prevalence of self-reported diabetes was recorded in rural (3.1%) followed by peri-urban/slum (3.2%) and the highest in urban areas (7.3%, odds ratio (OR) for urban areas: 2.48, 95% confidence interval (Cl): 2.21-2.79, p < 0.001). Urban residents with abdominal obesity and sedentary activity had the highest prevalence of self-reported diabetes (11.3%) while rural residents without abdominal obesity performing vigorous activity had the lowest prevalence (0.7%). In conclusion, this nation-wide NCD risk factor surveillance study shows that the prevalence of self-reported diabetes is higher in urban, intermediate in peri-urban and lowest in rural areas. Urban residence, abdominal obesity and physical inactivity are the risk factors associated with diabetes in this study. (c) 2007 Elsevier Ireland Ltd. All rights reserved.