35 results on '"Ugel E."'
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2. ISOCAM survey and dust models of 3CR radio galaxies and quasars
- Author
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Siebenmorgen, R., Freudling, W., Kr"ugel, E., and Haas, M.
- Subjects
Astrophysics - Abstract
We present a survey of all 3CR sources imaged with ISOCAM onboard the Infrared Space Observatory (ISO). For the source, we present spatially integrated mid--infrared (MIR, 5 - 18mic.) fluxes measured from newly calibrated ISOCAM images. In total, we detected 68 AGN of the 3CR catalogue, at redshifts z < 2.5. The one with the highest redshift is 4C+72.26 at z = 3.53. ISOCAM data are combined with other photometric measurements to construct the spectral energy distribution (SED) from optical to radio wavelengths. In order to describe dust emission we apply new radiative transfer models. By varying three parameters, luminosity, effective size and extinction, we obtain a fit to the SED for our objects. In the MIR the hot dust component is mainly due to small grains and PAHs. In the models, a type 1 AGN is represented by a compact dust distribution, the dust is therefore very warm and emission of PAHs is weak because of photo--destruction. In AGNs of type 2, the dust is relatively colder but PAH bands are strong., Comment: Accepted by A&A, 30pages, 10 Figures, available at: http://www.eso.org/~rsiebenm/FTP/3CRisocam.pdf
- Published
- 2004
- Full Text
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3. Mid-infrared emission of galactic nuclei: TIMMI2 versus ISO observations and models
- Author
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Siebenmorgen, R., Kr"ugel, E., and Spoon, H. W. W.
- Subjects
Astrophysics - Abstract
We investigate the mid-infrared radiation of galaxies that are powered by a starburst or by an AGN. For this end, we compare the spectra obtained at different spatial scales in a sample of infrared bright galaxies. ISO observations which include emission of the nucleus as well as most of the host galaxy are compared with TIMMI2 spectra of the nuclear region. We find that ISO spectra are generally dominated by strong PAH bands. However, this is no longer true when inspecting the mid-infrared emission of the pure nucleus. Here PAH emission is detected in starbursts whereas it is significantly reduced or completely absent in AGNs. A physical explanation of these new observational results is presented by examining the temperature fluctuation of a PAH after interaction with a photon. It turns out that the hardness of the radiation field is a key parameter for quantifying the photo-destruction of small grains. Our theoretical study predicts PAH evaporation in soft X-ray environments. Radiative transfer calculations of clumpy starbursts and AGN corroborate the observational fact that PAH emission is connected to starburst activity whereas PAHs are destroyed near an AGN. The radiative transfer models predict for starbursts a much larger mid-infrared size than for AGN. This is confirmed by our TIMMI2 acquisition images: We find that the mid-infrared emission of Seyferts is dominated by a compact core while most of the starbursts are spatially resolved., Comment: 19 pages, 22 Figures, accepted by A&A
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- 2003
- Full Text
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4. The Infrared Continuum Radiation of NGC1808 : A PAH and Polarisation Study
- Author
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Siebenmorgen, R., Kr"ugel, E., and Laureijs, R. J.
- Subjects
Astrophysics - Abstract
The paper is devoted to the understanding of the infrared emission of nuclear regions in galaxies. a) ISO data of NGC1808 are presented: spectro--photometry from 5.1 to 16.4 mic., a 25"x25" map at 6 mic. and 170mic. photometry. b) The data are complemented by a polarization measurement at 170 mic. (2.5+/-0.4% at position angle 94+/-5deg) and a map at 6 mic. In the map, the degree of polarisation goes up to 20% in the outer regions. We argue that the polarisation is produced by emission of big grains and exclude very small grains and PAHs or scattering and extinction. c) The mid infrared spectrum shows, beside the main emission bands, a so far unknown plateau of PAH features in the >13 mic.region. d) The total spectrum can be fit under the assumption of optically thin emission. However, such a model fails to reproduce the 25mic. point and implies that the mid infrared is due to very small grains and PAHs. These particles would then also have to be responsible for the 6 mic. polarisation, which is unlikely. e) To avoid these difficulties, we successfully turn to a radiative transfer model whose major feature is the existence of (hot spots) produced by the dust clouds around OB stars. We demonstrate the decisive influence on the mid infrared spectrum of both the PAHs and the hot spots., Comment: 11 pages, 6 figures, accepted by A&A
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- 2001
- Full Text
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5. Sociodemographic Determinants of Lung Cancer: How Race and Income Affect Survival
- Author
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Duval, A.J., primary, Shaikh, A.M., additional, Ugel, E., additional, Tiwari, M., additional, and Berman, A., additional
- Published
- 2023
- Full Text
- View/download PDF
6. Worldwide trends in hypertension prevalence and progress in treatment and control from 1990 to 2019: a pooled analysis of 1201 population-representative studies with 104 million participants
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Zhou, B, Carrillo-Larco, Rm, Danaei, G, Riley, Lm, Paciorek, Cj, Stevens, Ga, Gregg, Ew, Bennett, Je, Solomon, B, Singleton, Rk, Sophiea, Mk, Iurilli, Mlc, Lhoste, Vpf, Cowan, Mj, Savin, S, Woodward, M, Balanova, Y, Cifkova, R, Damasceno, A, Elliott, P, Farzadfar, F, He, J, Ikeda, N, Kengne, Ap, Khang, Yh, Kim, Hc, Laxmaiah, A, Lin, Hh, Maira, Pm, Miranda, Jj, Neuhauser, H, Sundstrom, J, Varghese, C, Widyahening, Is, Zdrojewski, T, Ezzati, M, Abarca-Gomez, L, Abdeen, Za, Rahim, Hfa, Abu-Rmeileh, Nm, Acosta-Cazares, B, Adams, Rj, Aekplakorn, W, Afsana, K, Afzal, S, Agdeppa, Ia, Aghazadeh-Attari, J, Aguilar-Salinas, Ca, Agyemang, C, Ahmad, Na, Ahmadi, A, Ahmadi, N, Ahmadizar, F, Ahmed, Sh, Ahrens, W, Ajlouni, K, Al-Raddadi, R, Alarouj, M, Albuhairan, F, Aldhukair, S, Ali, Mm, Alkandari, A, Alkerwi, A, Allin, K, Aly, E, Amarapurkar, Dn, Amougou, N, Amouyel, P, Andersen, Lb, Anderssen, Sa, Anjana, Rm, Ansari-Moghaddam, A, Ansong, D, Aounallah-Skhiri, H, Araujo, J, Ariansen, I, Aris, T, Arku, Re, Arlappa, N, Aryal, Kk, Aspelund, T, Assah, Fk, Assuncao, Mcf, Auvinen, J, Avdicova, M, Azevedo, A, Azimi-Nezhad, M, Azizi, F, Azmin, M, Babu, Bv, Bahijri, S, Balakrishna, N, Bamoshmoosh, M, Banach, M, Banadinovic, M, Bandosz, P, Banegas, Jr, Baran, J, Barbagallo, Cm, Barcelo, A, Barkat, A, Barreto, M, Barros, Ajd, Barros, Mvg, Bartosiewicz, A, Basit, A, Bastos, Jld, Bata, I, Batieha, Am, Batyrbek, A, Baur, La, Beaglehole, R, Belavendra, A, Ben Romdhane, H, Benet, M, Benson, Ls, Berkinbayev, S, Bernabe-Ortiz, A, Bettiol, H, Bezerra, J, Bhagyalaxmi, A, Bhargava, Sk, Bia, D, Biasch, K, Lele, Ecb, Bikbov, Mm, Bista, B, Bjerregaard, P, Bjertness, E, Bjertness, Mb, Bjorkelund, C, Bloch, Kv, Blokstra, A, Bo, S, Bobak, M, Boeing, H, Boggia, Jg, Boissonnet, Cp, Bojesen, Se, Bongard, V, Bonilla-Vargas, A, Bopp, M, Borghs, H, Bovet, P, Boyer, Cb, Braeckman, L, Brajkovich, I, Branca, F, Breckenkamp, J, Brenner, H, Brewster, Lm, Briceno, Y, Brito, M, Bruno, G, Bueno-de-Mesquita, Hb, Bueno, G, Bugge, A, Burns, C, Bursztyn, M, de Leon, Ac, Cacciottolo, J, Cameron, C, Can, G, Candido, Apc, Capanzana, Mv, Capkova, N, Capuano, E, Capuano, V, Cardoso, Vc, Carlsson, Ac, Carvalho, J, Casanueva, Ff, Censi, L, Cervantes-Loaiza, M, Chadjigeorgiou, Ca, Chamukuttan, S, Chan, Aw, Chan, Q, Chaturvedi, Hk, Chaturvedi, N, Chee, Ml, Chen, Cj, Chen, Ff, Chen, Hs, Chen, Sh, Chen, Zm, Cheng, Cy, Cheraghian, B, Dekkaki, Ic, Chetrit, A, Chien, Kl, Chiolero, A, Chiou, St, Chirita-Emandi, A, Chirlaque, Md, Cho, B, Christensen, K, Christofaro, Dg, Chudek, J, Cinteza, E, Claessens, F, Clarke, J, Clays, E, Cohen, E, Concin, H, Cooper, C, Coppinger, Tc, Costanzo, S, Cottel, D, Cowell, C, Craig, Cl, Crampin, Ac, Crujeiras, Ab, Cruz, Jj, Csilla, S, Cui, Lf, Cureau, Fv, Cuschieri, S, D'Arrigo, G, D'Orsi, E, Dallongeville, J, Dankner, R, Dantoft, Tm, Dauchet, L, Davletov, K, De Backer, G, De Bacquer, D, De Curtis, A, de Gaetano, G, De Henauw, S, de Oliveira, Pd, De Ridder, D, De Smedt, D, Deepa, M, Deev, Ad, Degennaro, V, Delisle, H, Demarest, S, Dennison, E, Deschamps, V, Dhimal, M, Di Castelnuovo, Af, Dias-da-Costa, Js, Diaz, A, Dickerson, Tt, Dika, Z, Djalalinia, S, Htp, Do, Dobson, Aj, Donfrancesco, C, Donoso, Sp, Doring, A, Dorobantu, M, Dorr, M, Doua, K, Dragano, N, Drygas, W, Duante, Ca, Duboz, P, Duda, Rb, Dulskiene, V, Dushpanova, A, Dzakula, A, Dzerve, V, Dziankowska-Zaborszczyk, E, Eddie, R, Eftekhar, E, Eggertsen, R, Eghtesad, S, Eiben, G, Ekelund, U, El-Khateeb, M, El Ati, J, Eldemire-Shearer, D, Eliasen, M, Elosua, R, Erasmus, Rt, Erbel, R, Erem, C, Eriksen, L, Eriksson, Jg, Escobedo-de la Pena, J, Eslami, S, Esmaeili, A, Evans, A, Faeh, D, Fakhretdinova, Aa, Fall, Ch, Faramarzi, E, Farjam, M, Fattahi, Mr, Fawwad, A, Felix-Redondo, Fj, Felix, Sb, Ferguson, Ts, Fernandes, Ra, Fernandez-Berges, D, Ferrante, D, Ferrao, T, Ferrari, M, Ferrario, Mm, Ferreccio, C, Ferreira, Hs, Ferrer, E, Ferrieres, J, Figueiro, Th, Fink, G, Fischer, K, Foo, Lh, Forsner, M, Fouad, Hm, Francis, Dk, Grego, Franco, Frikke-Schmidt, R, Frontera, G, Fuchs, Fd, Fuchs, Sc, Fujita, Y, Fumihiko, M, Furdela, V, Furer, A, Furusawa, T, Gaciong, Z, Galbarczyk, A, Galenkamp, H, Galvano, F, Gao, Jl, Gao, P, Garcia-de-la-Hera, M, Garcia, P, Gareta, D, Garnett, Sp, Gaspoz, Jm, Gasull, M, Gazzinelli, A, Gehring, U, Geleijnse, Jm, George, R, Ghanbari, A, Ghasemi, E, Gheorghe-Fronea, Of, Ghimire, A, Gialluisi, A, Giampaoli, S, Gieger, C, Gill, Tk, Giovannelli, J, Gironella, G, Giwercman, A, Gkiouras, K, Goldberg, M, Goldsmith, Ra, Gomez, Lf, Gomula, A, da Silva, Bgc, Goncalves, H, Goncalves, M, Gonzalez-Chica, Da, Gonzalez-Gross, M, Gonzalez-Rivas, Jp, Gonzalez-Villalpando, C, Gonzalez-Villalpando, Me, Gonzalez, Ar, Gorbea, Mb, Gottrand, F, Graff-Iversen, S, Grafnetter, D, Grajda, A, Grammatikopoulou, Mg, Gregor, Rd, Grodzicki, T, Grosso, G, Gruden, G, Df, Gu, Guan, Op, Gudmundsson, Ef, Gudnason, V, Guerrero, R, Guessous, I, Guimaraes, Al, Gulliford, Mc, Gunnlaugsdottir, J, Gunter, Mj, Gupta, Pc, Gupta, R, Gureje, O, Gurzkowska, B, Gutierrez, L, Gutzwiller, F, Ha, S, Hadaegh, F, Haghshenas, R, Hakimi, H, Halkjaer, J, Hambleton, Ir, Hamzeh, B, Hange, D, Hanif, Aam, Hantunen, S, Hao, J, Hardman, Cm, Kumar, Rh, Hashemi-Shahri, Sm, Hata, J, Haugsgjerd, T, Hayes, Aj, Yn, He, Heier, M, Hendriks, Me, Henrique, Rd, Henriques, A, Cadena, Lh, Herrala, S, Heshmat, R, Hill, Ag, Sy, Ho, Sc, Ho, Hobbs, M, Holdsworth, M, Homayounfar, R, Dinc, Gh, Horimoto, Arvr, Hormiga, Cm, Horta, Bl, Houti, L, Howitt, C, Htay, Tt, Htet, As, Htike, Mmt, Yh, Hu, Huerta, Jm, Huhtaniemi, It, Huiart, L, Huisman, M, Husseini, As, Huybrechts, I, Hwalla, N, Iacoviello, L, Iannone, Ag, Ibrahim, Mm, Wong, Ni, Ikram, Ma, Iotova, V, Irazola, Ve, Ishida, T, Isiguzo, Gc, Islam, M, Islam, Sms, Iwasaki, M, Jackson, Rt, Jacobs, Jm, Jaddou, Hy, Jafar, T, James, K, Jamrozik, K, Janszky, I, Janus, E, Jarvelin, Mr, Jasienska, G, Jelakovic, A, Jelakovic, B, Jennings, G, Jha, Ak, Jiang, Cq, Jimenez, Ro, Jockel, Kh, Joffres, M, Johansson, M, Jokelainen, Jj, Jonas, Jb, Jorgensen, T, Joshi, P, Joukar, F, Jozwiak, J, Juolevi, A, Jurak, G, Juresa, V, Kaaks, R, Kafatos, A, Kajantie, Eo, Kalmatayeva, Z, Kalpourtzi, N, Kalter-Leibovici, O, Kampmann, Fb, Kannan, S, Karaglani, E, Karhus, Ll, Karki, Kb, Katibeh, M, Katz, J, Kauhanen, J, Kaur, P, Kavousi, M, Kazakbaeva, Gm, Keil, U, Boker, Lk, Keinanen-Kiukaanniemi, S, Kelishadi, R, Kemper, Hcg, Keramati, M, Kerimkulova, A, Kersting, M, Key, T, Khader, Ys, Khalili, D, Khaw, Kt, Kheiri, B, Kheradmand, M, Khosravi, A, Kiechl-Kohlendorfer, U, Kiechl, S, Killewo, J, Kim, Dw, Kim, J, Klakk, H, Klimek, M, Klumbiene, J, Knoflach, M, Kolle, E, Kolsteren, P, Kontto, Jp, Korpelainen, R, Korrovits, P, Kos, J, Koskinen, S, Kouda, K, Kowlessur, S, Koziel, S, Kratenova, J, Kriaucioniene, V, Kristensen, Pl, Krokstad, S, Kromhout, D, Kruger, Hs, Kubinova, R, Kuciene, R, Kujala, Um, Kulaga, Z, Kumar, Rk, Kurjata, P, Kusuma, Ys, Kutsenko, V, Kuulasmaa, K, Kyobutungi, C, Laatikainen, T, Lachat, C, Laid, Y, Lam, Th, Landrove, O, Lanska, V, Lappas, G, Larijani, B, Latt, Ts, Le Coroller, G, Bao, Kln, Le, THUY DUNG, Lee, J, Lehmann, N, Lehtimaki, T, Lemogoum, D, Levitt, Ns, Yp, Li, Lilly, Cl, Lim, Wy, Lima-Costa, Mf, Lin, X, Lin, Yt, Lind, L, Lingam, V, Linneberg, A, Lissner, L, Litwin, M, Wc, Lo, Loit, Hm, Lopez-Garcia, E, Lopez, T, Lotufo, Pa, Lozano, Je, Lovrencic, Il, Lukrafka, Jl, Luksiene, D, Lundqvist, A, Lundqvist, R, Lunet, N, Lustigova, M, Luszczki, E, Gs, Ma, Ma, J, Machado-Coelho, Gll, Machado-Rodrigues, Am, Macia, E, Macieira, Lm, Madar, Aa, Maggi, S, Magliano, Dj, Magriplis, E, Mahasampath, G, Maire, B, Majer, M, Makdisse, M, Malekzadeh, F, Malekzadeh, R, Malhotra, R, Mallikharjuna, K, Malyutina, Sk, Maniego, Lv, Manios, Y, Mann, Ji, Mansour-Ghanaei, F, Manzato, E, Marcil, A, Margozzini, P, Marild, Sb, Glavic, Mm, Marques-Vidal, P, Marques, Lp, Marrugat, J, Martorell, R, Mascarenhas, Lp, Matasin, M, Mathiesen, Eb, Mathur, P, Matijasevich, A, Matlosz, P, Matsha, Te, Mavrogianni, C, Mbanya, Jcn, Posso, Ajm, Mcfarlane, Sr, Mcgarvey, St, Mclachlan, S, Mclean, Rm, Mclean, Sb, Mcnulty, Ba, Benchekor, Sm, Medzioniene, J, Mehdipour, P, Mehlig, K, Mehrparvar, Ah, Meirhaeghe, A, Meisinger, C, Montano, Cm, Menezes, Amb, Menon, Gr, Mereke, A, Meshram, Ii, Metspalu, A, Meyer, He, Mi, J, Michels, N, Mikkel, K, Milkowska, K, Miller, Jc, Minderico, Cs, Mini, Gk, Mirjalili, Mr, Mirrakhimov, E, Misigoj-Durakovic, M, Modesti, Pa, Moghaddam, Ss, Mohajer, B, Mohamed, Mk, Mohamed, Sf, Mohammad, K, Mohammadi, Mr, Mohammadi, Z, Mohammadifard, N, Mohammadpourhodki, R, Mohan, V, Mohanna, S, Yusoff, Mfm, Mohebbi, I, Mohebi, F, Moitry, M, Mollehave, Lt, Molnar, D, Momenan, A, Mondo, Ck, Monterrubio-Flores, E, Monyeki, Kdk, Moon, Js, Moosazadeh, M, Moreira, Lb, Morejon, A, Moreno, La, Morgan, K, Moschonis, G, Mossakowska, M, Mostafa, A, Mostafavi, Sa, Mota, J, Motlagh, Me, Motta, J, Moura-dos-Santos, Ma, Mridha, Mk, Msyamboza, Kp, Tt, Mu, Muhihi, Aj, Muiesan, Ml, Muller-Nurasyid, M, Murphy, N, Mursu, J, Musa, Ki, Milanovic, Sm, Musil, V, Mustafa, N, Nabipour, I, Naderimagham, S, Nagel, G, Naidu, Bm, Najafi, F, Nakamura, H, Namesna, J, Nang, Eek, Nangia, Vb, Narake, S, Ndiaye, Nc, Neal, Wa, Nejatizadeh, A, Nenko, I, Neovius, M, Neuhauser, Hk, Nguyen, Ct, Nguyen, Nd, Nguyen, Qv, Nguyen, Qn, Nieto-Martinez, Re, Niiranen, Tj, Nikitin, Yp, Ninomiya, T, Nishtar, S, Njelekela, Ma, Noale, M, Noboa, Oa, Noorbala, Aa, Norat, T, Nordendahl, M, Nordestgaard, Bg, Noto, D, Nowak-Szczepanska, N, Al Nsour, M, Nunes, B, O'Neill, Tw, O'Reilly, D, Ochimana, C, Oda, E, Odili, An, Oh, K, Ohara, K, Ohtsuka, R, Olie, V, Olinto, Mta, Oliveira, Io, Omar, Ma, Onat, A, Ong, Sk, Ono, Lm, Ordunez, P, Ornelas, R, Ortiz, Pj, Osmond, C, Ostojic, Sm, Ostovar, A, Otero, Ja, Overvad, K, Owusu-Dabo, E, Paccaud, Fm, Padez, C, Pahomova, E, de Paiva, Km, Pajak, A, Palli, D, Palmieri, L, Pan, Wh, Panda-Jonas, S, Panza, F, Paoli, M, Papandreou, D, Park, Sw, Park, S, Parnell, Wr, Parsaeian, M, Pasquet, P, Patel, Nd, Pavlyshyn, H, Pecin, I, Pednekar, Ms, Pedro, Jm, Peer, N, Peixoto, Sv, Peltonen, M, Pereira, Ac, Peres, Kgda, Peres, Ma, Peters, A, Petkeviciene, J, Peykari, N, Pham, St, Pichardo, Rn, Pigeot, I, Pikhart, H, Pilav, A, Pilotto, L, Pitakaka, F, Piwonska, A, Pizarro, An, Plans-Rubio, P, Polasek, O, Porta, M, Poudyal, A, Pourfarzi, F, Pourshams, A, Poustchi, H, Pradeepa, R, Price, Aj, Price, Jf, Providencia, R, Puhakka, Se, Puiu, M, Punab, M, Qasrawi, Rf, Qorbani, M, Queiroz, D, Bao, Tq, Radic, I, Radisauskas, R, Rahimikazerooni, S, Rahman, M, Raitakari, O, Raj, M, Rakhimova, Em, Rao, Sr, Ramachandran, A, Ramos, E, Rampal, L, Rampal, S, Reina, Dar, Rarra, V, Rech, Cr, Redon, J, Reganit, Pfm, Regecova, V, Revilla, L, Rezaianzadeh, A, Ribeiro, R, Riboli, E, Richter, A, Rigo, F, de Wit, Tfr, Ritti-Dias, Rm, Robitaille, C, Rodriguez-Artalejo, F, Rodriguez-Perez, Md, Rodriguez-Villamizar, La, Roggenbuck, U, Rojas-Martinez, R, Romaguera, D, Romeo, El, Rosengren, A, Roy, Jgr, Rubinstein, A, Ruidavets, Jb, Ruiz-Betancourt, Bs, Ruiz-Castell, M, Rusakova, Ia, Russo, P, Rutkowski, M, Sabanayagam, C, Sabbaghi, H, Sachdev, Hs, Sadjadi, A, Safarpour, Ar, Safi, S, Safiri, S, Saidi, O, Sakarya, S, Saki, N, Salanave, B, Martinez, Es, Salmeron, D, Salomaa, V, Salonen, Jt, Salvetti, M, Sanchez-Abanto, J, Sans, S, Santos, Da, Santos, Is, Santos, Lc, Santos, Mp, Santos, R, Saramies, Jl, Sardinha, Lb, Sarganas, G, Sarrafzadegan, N, Sathish, T, Saum, Ku, Savva, S, Sawada, N, Sbaraini, M, Scazufca, M, Schaan, Bd, Schargrodsky, H, Schipf, S, Schmidt, Co, Schnohr, P, Schottker, B, Schramm, S, Schultsz, C, Schutte, Ae, Sebert, S, Sein, Aa, Sen, A, Senbanjo, Io, Sepanlou, Sg, Servais, J, Shalnova, Sa, Shamah-Levy, T, Shamshirgaran, M, Shanthirani, Cs, Sharafkhah, M, Sharma, Sk, Shaw, Je, Shayanrad, A, Shayesteh, Aa, Shi, Zm, Shibuya, K, Shimizu-Furusawa, H, Shin, Dw, Shirani, M, Shiri, R, Shrestha, N, Si-Ramlee, K, Siani, A, Siantar, R, Sibai, Am, Silva, Crd, Silva, Das, Simon, M, Simons, J, Simons, La, Sjostrom, M, Slowikowska-Hilczer, J, Slusarczyk, P, Smeeth, L, Hk, So, Soares, Fc, Sobngwi, E, Soderberg, S, Soemantri, A, Sofat, R, Solfrizzi, V, Somi, Mh, Sonestedt, E, Song, Y, Sorensen, Tia, Sorgjerd, Ep, Soric, M, Jerome, Cs, Soumare, A, Sparboe-Nilsen, B, Sparrenberger, K, Staessen, Ja, Starc, G, Stavreski, B, Steene-Johannessen, J, Stehle, P, Stein, Ad, Stergiou, Gs, Stessman, J, Stieber, J, Stockl, D, Stocks, T, Stokwiszewski, J, Stronks, K, Strufaldi, Mw, Suka, M, Sun, Ca, Sung, Yt, Suriyawongpaisal, P, Rg, Sy, Syddall, He, Sylva, Rc, Szklo, M, Tai, Es, Tammesoo, Ml, Tamosiunas, A, Tan, Ej, Tang, X, Tanser, F, Tao, Y, Tarawneh, Mr, Tarqui-Mamani, Cb, Taylor, A, Taylor, J, Tebar, Wr, Tell, Gs, Tello, T, Tham, Yc, Thankappan, Kr, Theobald, H, Theodoridis, X, Thijs, L, Thinggaard, M, Thomas, N, Thorand, B, Thuesen, Bh, Timmermans, Ej, Tjandrarini, Dh, Tjonneland, A, Toft, U, Tolonen, Hk, Tolstrup, Js, Topbas, M, Topor-Madry, R, Tormo, Mj, Tornaritis, Mj, Torrent, M, Torres-Collado, L, Touloumi, G, Traissac, P, Triantafyllou, A, Trichopoulos, D, Trichopoulou, A, Trinh, Oth, Trivedi, A, Tshepo, L, Tsugane, S, Tuliakova, Am, Tulloch-Reid, Mk, Tullu, F, Tuomainen, Tp, Tuomilehto, J, Turley, Ml, Twig, G, Tynelius, P, Tzourio, C, Ueda, P, Ugel, E, Ulmer, H, Uusitalo, Hmt, Valdivia, G, Valvi, D, van Dam, Rm, van den Born, Bj, Van der Heyden, J, van der Schouw, Yt, Van Herck, K, Minh, Hv, Van Schoor, Nm, van Valkengoed, Igm, van Zutphen, Em, Vanderschueren, D, Vanuzzo, D, Varbo, A, Vasan, Sk, Vega, T, Veidebaum, T, Velasquez-Melendez, G, Veronesi, G, Verschuren, Wmm, Verstraeten, R, Victora, Cg, Viet, L, Villalpando, S, Vineis, P, Vioque, J, Virtanen, Jk, Visvikis-Siest, S, Viswanathan, B, Vlasoff, T, Vollenweider, P, Voutilainen, A, Wade, An, Walton, J, Wambiya, Eoa, Bebakar, Wmw, Mohamud, Wnw, Wanderley, Rd, Wang, Md, Wang, Nl, Wang, Q, Wang, Xj, Wang, Yx, Wang, Yw, Wannamethee, Sg, Wareham, N, Wei, 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Csilla, Liufu Cui, Felipe V Cureau, Sarah Cuschieri, Graziella D'Arrigo, Eleonora d'Orsi, Jean Dallongeville, Rachel Dankner, Thomas M Dantoft, Luc Dauchet, Kairat Davletov, Guy De Backer, Dirk De Bacquer, Amalia De Curtis, Giovanni de Gaetano, Stefaan De Henauw, Paula Duarte de Oliveira, David De Ridder, Delphine De Smedt, Mohan Deepa, Alexander D Deev, Vincent Jr DeGennaro, Hélène Delisle, Stefaan Demarest, Elaine Dennison, Valérie Deschamps, Meghnath Dhimal, Augusto F Di Castelnuovo, Juvenal Soares Dias-da-Costa, Alejandro Diaz, Ty T Dickerson, Zivka Dika, Shirin Djalalinia, Ha Tp Do, Annette J Dobson, Chiara Donfrancesco, Silvana P Donoso, Angela Döring, Maria Dorobantu, Marcus Dörr, Kouamelan Doua, Nico Dragano, Wojciech Drygas, Charmaine A Duante, Priscilla Duboz, Rosemary B Duda, Virginija Dulskiene, Anar Dushpanova, Aleksandar Džakula, Vilnis Dzerve, Elzbieta Dziankowska-Zaborszczyk, Ricky Eddie, Ebrahim Eftekhar, Robert Eggertsen, Sareh Eghtesad, Gabriele Eiben, Ulf Ekelund, 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Andre L Guimaraes, Martin C Gulliford, Johanna Gunnlaugsdottir, Marc J Gunter, Prakash C Gupta, Rajeev Gupta, Oye Gureje, Beata Gurzkowska, Laura Gutierrez, Felix Gutzwiller, Seongjun Ha, Farzad Hadaegh, Rosa Haghshenas, Hamid Hakimi, Jytte Halkjær, Ian R Hambleton, Behrooz Hamzeh, Dominique Hange, Abu Am Hanif, Sari Hantunen, Jie Hao, Carla Menêses Hardman, Rachakulla Hari Kumar, Seyed Mohammad Hashemi-Shahri, Jun Hata, Teresa Haugsgjerd, Alison J Hayes, Yuna He, Margit Heier, Marleen Elisabeth Hendriks, Rafael Dos Santos Henrique, Ana Henriques, Leticia Hernandez Cadena, Herqutanto, Sauli Herrala, Ramin Heshmat, Allan G Hill, Sai Yin Ho, Suzanne C Ho, Michael Hobbs, Michelle Holdsworth, Reza Homayounfar, Gonul Horasan Dinc, Andrea Rvr Horimoto, Claudia M Hormiga, Bernardo L Horta, Leila Houti, Christina Howitt, Thein Thein Htay, Aung Soe Htet, Maung Maung Than Htike, Yonghua Hu, José María Huerta, Ilpo Tapani Huhtaniemi, Laetitia Huiart, Martijn Huisman, Abdullatif S Husseini, Inge Huybrechts, Nahla Hwalla, Licia Iacoviello, Anna G Iannone, Mohsen M Ibrahim, Norazizah Ibrahim Wong, M Arfan Ikram, Violeta Iotova, Vilma E Irazola, Takafumi Ishida, Godsent C Isiguzo, Muhammad Islam, Sheikh Mohammed Shariful Islam, Masanori Iwasaki, Rod T Jackson, Jeremy M Jacobs, Hashem Y Jaddou, Tazeen Jafar, Kenneth James, Konrad Jamrozik, Imre Janszky, Edward Janus, Marjo-Riitta Jarvelin, Grazyna Jasienska, Ana Jelaković, Bojan Jelaković, Garry Jennings, Anjani Kumar Jha, Chao Qiang Jiang, Ramon O Jimenez, Karl-Heinz Jöckel, Michel Joffres, Mattias Johansson, Jari J Jokelainen, Jost B Jonas, Torben Jørgensen, Pradeep Joshi, Farahnaz Joukar, Jacek Jóżwiak, Anne Juolevi, Gregor Jurak, Vesna Jureša, Rudolf Kaaks, Anthony Kafatos, Eero O Kajantie, Zhanna Kalmatayeva, Natasa Kalpourtzi, Ofra Kalter-Leibovici, Freja B Kampmann, Srinivasan Kannan, Eva Karaglani, Line L Kårhus, Khem B Karki, Marzieh Katibeh, Joanne Katz, Jussi Kauhanen, Prabhdeep Kaur, Maryam Kavousi, Gyulli M Kazakbaeva, Ulrich Keil, Lital Keinan Boker, Sirkka Keinänen-Kiukaanniemi, Roya Kelishadi, Han Cg Kemper, Maryam Keramati, Alina Kerimkulova, Mathilde Kersting, Timothy Key, Yousef Saleh Khader, Davood Khalili, Kay-Tee Khaw, Bahareh Kheiri, Motahareh Kheradmand, Alireza Khosravi, Ursula Kiechl-Kohlendorfer, Stefan Kiechl, Japhet Killewo, Dong Wook Kim, Jeongseon Kim, Heidi Klakk, Magdalena Klimek, Jurate Klumbiene, Michael Knoflach, Elin Kolle, Patrick Kolsteren, Jukka P Kontto, Raija Korpelainen, Paul Korrovits, Jelena Kos, Seppo Koskinen, Katsuyasu Kouda, Sudhir Kowlessur, Slawomir Koziel, Jana Kratenova, Vilma Kriaucioniene, Peter Lund Kristensen, Steiner Krokstad, Daan Kromhout, Herculina S Kruger, Ruzena Kubinova, Renata Kuciene, Urho M Kujala, Zbigniew Kulaga, R Krishna Kumar, Pawel Kurjata, Yadlapalli S Kusuma, Vladimir Kutsenko, Kari Kuulasmaa, Catherine Kyobutungi, Tiina Laatikainen, Carl Lachat, Youcef Laid, Tai Hing Lam, Orlando Landrove, Vera Lanska, Georg Lappas, Bagher 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Mansour-Ghanaei, Enzo Manzato, Anie Marcil, Staffan B Mårild, Mihalea Marinović Glavić, Pedro Marques-Vidal, Larissa Pruner Marques, Jaume Marrugat, Reynaldo Martorell, Luis P Mascarenhas, Marija Matasin, Ellisiv B Mathiesen, Prashant Mathur, Alicia Matijasevich, Piotr Matlosz, Tandi E Matsha, Christina Mavrogianni, Jean Claude N Mbanya, Anselmo J Mc Donald Posso, Shelly R McFarlane, Stephen T McGarvey, Stela McLachlan, Rachael M McLean, Scott B McLean, Breige A McNulty, Sounnia Mediene Benchekor, Jurate Medzioniene, Parinaz Mehdipour, Kirsten Mehlig, Amir Houshang Mehrparvar, Aline Meirhaeghe, Christa Meisinger, Carlos Mendoza Montano, Ana Maria B Menezes, Geetha R Menon, Alibek Mereke, Indrapal I Meshram, Andres Metspalu, Haakon E Meyer, Jie Mi, Nathalie Michels, Kairit Mikkel, Karolina Milkowska, Jody C Miller, Cláudia S Minderico, G K Mini, Mohammad Reza Mirjalili, Erkin Mirrakhimov, Marjeta Mišigoj-Duraković, Pietro A Modesti, Sahar Saeedi Moghaddam, Bahram Mohajer, Mostafa K 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D. A., Peres, Marco A., Peters, Annette, Petkeviciene, Janina, Peykari, Niloofar, Son Thai Pham, Pichardo, Rafael N., Pigeot, Iris, Pikhart, Hynek, Pilav, Aida, Pilotto, Lorenza, Pitakaka, Freda, Piwonska, Aleksandra, Pizarro, Andreia N., Plans-Rubio, Pedro, Polasek, Ozren, Porta, Miquel, Poudyal, Anil, Pourfarzi, Farhad, Pourshams, Akram, Poustchi, Hossein, Pradeepa, Rajendra, Price, Alison J., Price, Jacqueline F., Providencia, Rui, Puhakka, Soile E., Puiu, Maria, Punab, Margus, Qasrawi, Radwan F., Qorbani, Mostafa, Queiroz, Daniel, Tran Quoc Bao, Radic, Ivana, Radisauskas, Ricardas, Rahimikazerooni, Salar, Rahman, Mahfuzar, Raitakari, Olli, Raj, Manu, Rakhimova, Ellina M., Rao, Sudha Ramachandra, Ramachandran, Ambady, Ramos, Elisabete, Rampal, Lekhraj, Rampal, Sanjay, Rangel Reina, Daniel A., Rarra, Vayia, Rech, Cassiano Ricardo, Redon, Josep, Reganit, Paul Ferdinand M., Regecova, Valeria, Revilla, Luis, Rezaianzadeh, Abbas, Ribeiro, Robespierre, Riboli, Elio, Richter, Adrian, Rigo, Fernando, de Wit, Tobias F. 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Goya, Wareham, Nicholas, Wei, Wenbin, Weres, Aneta, Werner, Bo, Whincup, Peter H., Widhalm, Kurt, Wiecek, Andrzej, Wilks, Rainford J., Willeit, Johann, Willeit, Peter, Williams, Emmanuel A., Wilsgaard, Tom, Wojtyniak, Bogdan, Wong-McClure, Roy A., Wong, Andrew, Wong, Tien Yin, Woo, Jean, Wu, Frederick C., Wu, Shouling, Wyszynska, Justyna, Xu, Haiquan, Xu, Liang, Yaacob, Nor Azwany, Yan, Weili, Yang, Ling, Yang, Xiaoguang, Yang, Yang, Yasuharu, Tabara, Ye, Xingwang, Yiallouros, Panayiotis K., Yoosefi, Moein, Yoshihara, Akihiro, You, San-Lin, Younger-Coleman, Novie O., Yusoff, Ahmad Faudzi, Zainuddin, Ahmad A., Zakavi, Seyed Rasoul, Zamani, Farhad, Zambon, Sabina, Zampelas, Antonis, Elisa Zapata, Maria, Zaw, Ko Ko, Zejglicova, Kristyna, Vrkic, Tajana Zeljkovic, Zeng, Yi, Zhang, Luxia, Zhao, Dong, Zhao, Ming-Hui, Zhen, Shiqi, Zheng, Yingfeng, Zholdin, Bekbolat, Zhu, Dan, Zins, Marie, Zitt, Emanuel, Zocalo, Yanina, Zoghlami, Nada, Zuniga Cisneros, Julio., School of Medicine, ACS - Diabetes & metabolism, APH - Global Health, Pulmonology, Medical Informatics, Adult Psychiatry, Global Health, APH - Quality of Care, APH - Methodology, Vascular Medicine, ACS - Atherosclerosis & ischemic syndromes, Anesthesiology, Graduate School, and ACS - Heart failure & arrhythmias
- Subjects
Male ,Latin Americans ,Nutrition and Disease ,Epidemiology ,[SDV]Life Sciences [q-bio] ,Medizin ,BLOOD-PRESSURE ,030204 cardiovascular system & hematology ,Worldwide trends in hypertension prevalence and progress in treatment and control from 1990 to 2019: a pooled analysis of 1201 population-representative studies with 104 million participants ,Hypertension ,Prevalence ,Control ,Tretament ,GUIDELINES ,Global Health ,Worldwide trends ,0302 clinical medicine ,Hypertension prevalence ,Voeding en Ziekte ,Medicine and Health Sciences ,kohonnut verenpaine ,Medicine ,030212 general & internal medicine ,Prevention and Control ,11 Medical and Health Sciences ,ComputingMilieux_MISCELLANEOUS ,education.field_of_study ,food and beverages ,Public Health, Global Health, Social Medicine and Epidemiology ,General Medicine ,Noncommunicable diseases ,Period prevalence ,Middle Aged ,kansainvälinen vertailu ,3142 Public health care science, environmental and occupational health ,3. Good health ,MIDDLE-INCOME ,Pooled analysis ,SYSTEMATIC ANALYSIS ,INCOME COUNTRIES ,ADULTS ,PREVENTION ,MANAGEMENT ,ADHERENCE ,DIAGNOSIS ,Western europe ,[SDE]Environmental Sciences ,Hypertension/diagnosis ,NCD Risk Factor Collaboration (NCD-RisC) ,Female ,B990 Subjects Allied to Medicine not elsewhere classified ,Life Sciences & Biomedicine ,Adult ,health-care ,esiintyvyys ,Central asia ,Population ,Nursing ,3121 Internal medicine ,03 medical and health sciences ,Medicine, General & Internal ,Drug Therapy ,General & Internal Medicine ,Life Science ,Humans ,ddc:610 ,education ,Antihypertensive Agents ,VLAG ,Aged ,Science & Technology ,Antihypertensive Agents/therapeutic use ,business.industry ,Omvårdnad ,fungi ,General and internal medicine ,Estados de Saúde e de Doença ,Taking medication ,Treatment ,Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi ,Blood pressure ,Faculdade de Ciências Sociais ,3121 General medicine, internal medicine and other clinical medicine ,lääkehoito ,1182 Biochemistry, cell and molecular biology ,business ,Demography - Abstract
Background: hypertension can be detected at the primary health-care level and low-cost treatments can effectively control hypertension. We aimed to measure the prevalence of hypertension and progress in its detection, treatment, and control from 1990 to 2019 for 200 countries and territories. Methods: we used data from 1990 to 2019 on people aged 30-79 years from population-representative studies with measurement of blood pressure and data on blood pressure treatment. We defined hypertension as having systolic blood pressure 140 mm Hg or greater, diastolic blood pressure 90 mm Hg or greater, or taking medication for hypertension. We applied a Bayesian hierarchical model to estimate the prevalence of hypertension and the proportion of people with hypertension who had a previous diagnosis (detection), who were taking medication for hypertension (treatment), and whose hypertension was controlled to below 140/90 mm Hg (control). The model allowed for trends over time to be non-linear and to vary by age. Findings: the number of people aged 30-79 years with hypertension doubled from 1990 to 2019, from 331 (95% credible interval 306-359) million women and 317 (292-344) million men in 1990 to 626 (584-668) million women and 652 (604-698) million men in 2019, despite stable global age-standardised prevalence. In 2019, age-standardised hypertension prevalence was lowest in Canada and Peru for both men and women; in Taiwan, South Korea, Japan, and some countries in western Europe including Switzerland, Spain, and the UK for women; and in several low-income and middle-income countries such as Eritrea, Bangladesh, Ethiopia, and Solomon Islands for men. Hypertension prevalence surpassed 50% for women in two countries and men in nine countries, in central and eastern Europe, central Asia, Oceania, and Latin America. Globally, 59% (55-62) of women and 49% (46-52) of men with hypertension reported a previous diagnosis of hypertension in 2019, and 47% (43-51) of women and 38% (35-41) of men were treated. Control rates among people with hypertension in 2019 were 23% (20-27) for women and 18% (16-21) for men. In 2019, treatment and control rates were highest in South Korea, Canada, and Iceland (treatment >70%; control >50%), followed by the USA, Costa Rica, Germany, Portugal, and Taiwan. Treatment rates were less than 25% for women and less than 20% for men in Nepal, Indonesia, and some countries in sub-Saharan Africa and Oceania. Control rates were below 10% for women and men in these countries and for men in some countries in north Africa, central and south Asia, and eastern Europe. Treatment and control rates have improved in most countries since 1990, but we found little change in most countries in sub-Saharan Africa and Oceania. Improvements were largest in high-income countries, central Europe, and some upper-middle-income and recently high-income countries including Costa Rica, Taiwan, Kazakhstan, South Africa, Brazil, Chile, Turkey, and Iran. Interpretation Improvements in the detection, treatment, and control of hypertension have varied substantially across countries, with some middle-income countries now outperforming most high-income nations. The dual approach of reducing hypertension prevalence through primary prevention and enhancing its treatment and control is achievable not only in high-income countries but also in low-income and middle-income settings., British Heart Foundation Centre of Research Excellence Grant; World Health Organization (WHO); Abdul Latif Jameel Institute for Disease and Emergency Analytics Fellowship
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- 2021
7. Heterogeneous contributions of change in population distribution of body mass index to change in obesity and underweight
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Iurilli, M.L.C. Zhou, B. Bennett, J.E. Carrillo-Larco, R.M. Sophiea, M.K. Rodriguez-Martinez, A. Bixby, H. Solomon, B.D. Taddei, C. Danaei, G. Di Cesare, M. Stevens, G.A. Riley, L.M. Savin, S. Cowan, M.J. Bovet, P. Damasceno, A. Chirita-Emandi, A. Hayes, A.J. Ikeda, N. Jackson, R.T. Khang, Y.-H. Laxmaiah, A. Liu, J. Miranda, J.J. Saidi, O. Sebert, S. Sorić, M. Starc, G. Gregg, E.W. Abarca-Gómez, L. Abdeen, Z.A. Abdrakhmanova, S. Ghaffar, S.A. Rahim, H.F.A. Abu-Rmeileh, N.M. Garba, J.A. Acosta-Cazares, B. Adams, R.J. Aekplakorn, W. Afsana, K. Afzal, S. Agdeppa, I.A. Aghazadeh-Attari, J. Aguilar-Salinas, C.A. Agyemang, C. Ahmad, M.H. Ahmad, N.A. Ahmadi, A. Ahmadi, N. Ahmed, S.H. Ahrens, W. Aitmurzaeva, G. Ajlouni, K. Al-Hazzaa, H.M. Al-Lahou, B. Al-Raddadi, R. Alarouj, M. AlBuhairan, F. AlDhukair, S. Ali, M.M. Alkandari, A. Alkerwi, A. Allin, K. Alvarez-Pedrerol, M. Aly, E. Amarapurkar, D.N. Amiri, P. Amougou, N. Amouyel, P. Andersen, L.B. Anderssen, S.A. Ängquist, L. Anjana, R.M. Ansari-Moghaddam, A. Aounallah-Skhiri, H. Araújo, J. Ariansen, I. Aris, T. Arku, R.E. Arlappa, N. Aryal, K.K. Aspelund, T. Assah, F.K. Assunção, M.C.F. Aung, M.S. Auvinen, J. Mária Avdicová Avi, S. Azevedo, A. Azimi-Nezhad, M. Azizi, F. Azmin, M. Babu, B.V. Bæksgaard Jørgensen, M. Baharudin, A. Bahijri, S. Baker, J.L. Balakrishna, N. Bamoshmoosh, M. Banach, M. Bandosz, P. Banegas, J.R. Baran, J. Barbagallo, C.M. Barceló, A. Barkat, A. Barros, A.J.D. Barros, M.V.G. Basit, A. Bastos, J.L.D. Bata, I. Batieha, A.M. Batista, R.L. Battakova, Z. Batyrbek, A. Baur, L.A. Beaglehole, R. Bel-Serrat, S. Belavendra, A. Romdhane, H.B. Benedics, J. Benet, M. Bergh, I.H. Berkinbayev, S. Bernabe-Ortiz, A. Bernotiene, G. Bettiol, H. Bezerra, J. Bhagyalaxmi, A. Bharadwaj, S. Bhargava, S.K. Bhutta, Z.A. Bi, H. Bi, Y. Bia, D. Lele, E.C.B. Bikbov, M.M. Bista, B. Bjelica, D.J. Bjerregaard, P. Bjertness, E. Bjertness, M.B. Björkelund, C. Bloch, K.V. Blokstra, A. Bo, S. Bobak, M. Boddy, L.M. Boehm, B.O. 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Cilia, M. Cinteza, E. Claessens, F. Clarke, J. Clays, E. Cohen, E. Concin, H. Confortin, S.C. Cooper, C. Coppinger, T.C. Corpeleijn, E. Costanzo, S. Cottel, D. Cowell, C. Craig, C.L. Crampin, A.C. Crujeiras, A.B. Csilla, S. Cucu, A.M. Cui, L. Cureau, F.V. Czenczek-Lewandowska, E. D’Arrigo, G. d’Orsi, E. Dacica, L. Dal Re Saavedra, M.A. Dallongeville, J. Damsgaard, C.T. Dankner, R. Dantoft, T.M. Dasgupta, P. Dastgiri, S. Dauchet, L. Davletov, K. De Backer, G. De Bacquer, D. de Gaetano, G. De Henauw, S. de Oliveira, P.D. De Ridder, D. De Ridder, K. de Rooij, S.R. De Smedt, D. Deepa, M. Deev, A.D. DeGennaro, V., Jr Dehghan, A. Delisle, H. Delpeuch, F. Demarest, S. Dennison, E. Dereń, K. Deschamps, V. Dhimal, M. Di Castelnuovo, A.F. Dias-da-Costa, J.S. Díaz-Sánchez, M.E. Diaz, A. Dika, Z. Djalalinia, S. Djordjic, V. Do, H.T.P. Dobson, A.J. Donati, M.B. Donfrancesco, C. Donoso, S.P. Döring, A. Dorobantu, M. Dorosty, A.R. Doua, K. Dragano, N. Drygas, W. Duan, J.L. Duante, C.A. Duboz, P. Duda, R.B. Duleva, V. Dulskiene, V. Dumith, S.C. Dushpanova, A. Dzerve, V. Dziankowska-Zaborszczyk, E. Eddie, R. Eftekhar, E. Egbagbe, E.E. Eggertsen, R. Eghtesad, S. Eiben, G. Ekelund, U. El-Khateeb, M. Ati, J.E. Eldemire-Shearer, D. Eliasen, M. Elliott, P. Engle-Stone, R. Enguerran, M. Erasmus, R.T. Erbel, R. Erem, C. Eriksen, L. Eriksson, J.G. Escobedo-de la Peña, J. Eslami, S. Esmaeili, A. Evans, A. Faeh, D. Fakhretdinova, A.A. Fall, C.H. Faramarzi, E. Farjam, M. Sant’Angelo, V.F. Farzadfar, F. Fattahi, M.R. Fawwad, A. Felix-Redondo, F.J. Ferguson, T.S. Fernandes, R.A. Fernández-Bergés, D. Ferrante, D. Ferrao, T. Ferrari, M. Ferrario, M.M. Ferreccio, C. Ferrer, E. Ferrieres, J. Figueiró, T.H. Fijalkowska, A. Fink, G. Fischer, K. Foo, L.H. Forsner, M. Fouad, H.M. Francis, D.K. Maria do Carmo Franco Frikke-Schmidt, R. Frontera, G. Fuchs, F.D. Fuchs, S.C. Fujiati, I.I. Fujita, Y. Fumihiko, M. Furusawa, T. Gaciong, Z. Gafencu, M. Galbarczyk, A. Galenkamp, H. Galeone, D. Galfo, M. 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Gurzkowska, B. Gutiérrez-González, E. Gutierrez, L. Gutzwiller, F. Ha, S. Hadaegh, F. Hadjigeorgiou, C.A. Haghshenas, R. Hakimi, H. Halkjær, J. Hambleton, I.R. Hamzeh, B. Hange, D. Hanif, A.A.M. Hantunen, S. Hao, J. Kumar, R.H. Hashemi-Shahri, S.M. Hassapidou, M. Hata, J. Haugsgjerd, T. He, J. He, Y. He, Y. Heidinger-Felso, R. Heinen, M. Hejgaard, T. Hendriks, M.E. dos Santos Henrique, R. Henriques, A. Cadena, L.H. Herrala, S. Herrera, V.M. Herter-Aeberli, I. Heshmat, R. Hill, A.G. Ho, S.Y. Ho, S.C. Hobbs, M. Holdsworth, M. Homayounfar, R. Homs, C. Hopman, W.M. Horimoto, A.R.V.R. Hormiga, C.M. Horta, B.L. Houti, L. Howitt, C. Htay, T.T. Htet, A.S. Htike, M.M.T. Hu, Y. Huerta, J.M. Huhtaniemi, I.T. Huiart, L. Petrescu, C.H. Huisman, M. Husseini, A. Huu, C.N. Huybrechts, I. Hwalla, N. Hyska, J. Iacoviello, L. Ibarluzea, J.M. Ibrahim, M.M. Wong, N.I. Ikram, M.A. Iotova, V. Irazola, V.E. Ishida, T. Islam, M. Islam, S.M.S. Iwasaki, M. Jacobs, J.M. Jaddou, H.Y. Jafar, T. James, K. 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Zargar, A.H. Zaw, K.K. Zdrojewski, T. Zejglicova, K. Vrkic, T.Z. Zeng, Y. Zhang, L. Zhang, Z.-Y. Zhao, D. Zhao, M.-H. Zhao, W. Zhen, S. Zheng, W. Zheng, Y. Zholdin, B. Zhou, M. Zhu, D. Zins, M. Zitt, E. Zocalo, Y. Cisneros, J.Z. Zuziak, M. Ezzati, M. Filippi, S. NCD Risk Factor Collaboration (NCD-RisC)
- Subjects
nutritional and metabolic diseases ,sense organs ,skin and connective tissue diseases - Abstract
From 1985 to 2016, the prevalence of underweight decreased, and that of obesity and severe obesity increased, in most regions, with significant variation in the magnitude of these changes across regions. We investigated how much change in mean body mass index (BMI) explains changes in the prevalence of underweight, obesity, and severe obesity in different regions using data from 2896 population-based studies with 187 million participants. Changes in the prevalence of underweight and total obesity, and to a lesser extent severe obesity, are largely driven by shifts in the distribution of BMI, with smaller contributions from changes in the shape of the distribution. In East and Southeast Asia and sub-Saharan Africa, the underweight tail of the BMI distribution was left behind as the distribution shifted. There is a need for policies that address all forms of malnutrition by making healthy foods accessible and affordable, while restricting unhealthy foods through fiscal and regulatory restrictions. © Copyright.
- Published
- 2021
8. Worldwide trends in blood pressure from 1975 to 2015: a pooled analysis of 1479 population-based measurement studies with 19·1 million participants
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Goya, Wareham, Nicholas, Wederkopp, N., Weerasekera, Deepa, Whincup, Peter H., Widhalm, Kurt, Widyahening, Indah S., Wiecek, Andrzej, Wijga, Alet H., Wilks, Rainford J., Willeit, Johann, Willeit, P., Williams, E. A., Wilsgaard, Tom, Wojtyniak, Bogdan, Wong, Tien Yin, Wong-McClure, R. A., Woo, Jean, Wu, A. G., Wu, Frederick C., Wu, Shou Ling, Xu, Haiquan, Yan, Weili, Yang, Xiaoguang, Ye, Xingwang, Yiallouros, Panayiotis K., Yoshihara, Akihiro, Younger-Coleman, Novie O., Yusoff, Ahmad F., Yusoff, Muhammad Fadhli Mohd, Zambon, Sabina, Zdrojewski, Tomasz, Zeng, Yi, Zhao, Dong, Zhao, Wenhua, Zheng, Yingfeng, Zhu, Dan, Zimmermann, Esther, Cisneros, Julio Zuniga, NCD Risk Factor Collaboration (NCD-RisC), Interactions Gène-Environnement en Physiopathologie Cardio-Vasculaire (IGE-PCV), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), and Yiallouros, Panayiotis K. [0000-0002-8339-9285]
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Worldwide trends ,Faculdade de Ciências Sociais ,Medicine (all) ,[SDV]Life Sciences [q-bio] ,Blood pressure ,ComputingMilieux_MISCELLANEOUS - Abstract
Background Raised blood pressure is an important risk factor for cardiovascular diseases and chronic kidney disease. We estimated worldwide trends in mean systolic and mean diastolic blood pressure, and the prevalence of, and number of people with, raised blood pressure, defined as systolic blood pressure of 140 mm Hg or higher or diastolic blood pressure of 90 mm Hg or higher. Methods For this analysis, we pooled national, subnational, or community population-based studies that had measured blood pressure in adults aged 18 years and older. We used a Bayesian hierarchical model to estimate trends from 1975 to 2015 in mean systolic and mean diastolic blood pressure, and the prevalence of raised blood pressure for 200 countries. We calculated the contributions of changes in prevalence versus population growth and ageing to the increase in the number of adults with raised blood pressure. Findings We pooled 1479 studies that had measured the blood pressures of 19·1 million adults. Global age-standardised mean systolic blood pressure in 2015 was 127·0 mm Hg (95% credible interval 125·7–128·3) in men and 122·3 mm Hg (121·0–123·6) in women; age-standardised mean diastolic blood pressure was 78·7 mm Hg (77·9–79·5) for men and 76·7 mm Hg (75·9–77·6) for women. Global age-standardised prevalence of raised blood pressure was 24·1% (21·4–27·1) in men and 20·1% (17·8–22·5) in women in 2015. Mean systolic and mean diastolic blood pressure decreased substantially from 1975 to 2015 in high-income western and Asia Pacific countries, moving these countries from having some of the highest worldwide blood pressure in 1975 to the lowest in 2015. Mean blood pressure also decreased in women in central and eastern Europe, Latin America and the Caribbean, and, more recently, central Asia, Middle East, and north Africa, but the estimated trends in these super-regions had larger uncertainty than in high-income super-regions. By contrast, mean blood pressure might have increased in east and southeast Asia, south Asia, Oceania, and sub-Saharan Africa. In 2015, central and eastern Europe, sub-Saharan Africa, and south Asia had the highest blood pressure levels. Prevalence of raised blood pressure decreased in high-income and some middle-income countries; it remained unchanged elsewhere. The number of adults with raised blood pressure increased from 594 million in 1975 to 1·13 billion in 2015, with the increase largely in low-income and middle-income countries. The global increase in the number of adults with raised blood pressure is a net effect of increase due to population growth and ageing, and decrease due to declining age-specific prevalence. Interpretation During the past four decades, the highest worldwide blood pressure levels have shifted from high-income countries to low-income countries in south Asia and sub-Saharan Africa due to opposite trends, while blood pressure has been persistently high in central and eastern Europe. Funding Wellcome Trust. © 2017 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY license 389 10064 37 55
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9. Worldwide trends in blood pressure from 1975 to 2015: a pooled analysis of 1479 population-based measurement studies with 19·1 million participants
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and Cisneros, J.Z. and Zhu, D. and Eggertsen, R. and NCD Risk Factor Collaboration (NCD-RisC), Imperial College London, United Kingdom, Middlesex University, United Kingdom, World Health Organization, Switzerland, University of California, Berkeley, United States, Tufts University, United States, Universidad Peruana Cayetano Heredia, Peru, Tehran University of Medical Sciences, Iran, Brandeis University, United States, Mulago Hospital, Uganda, Yale University, United States, University of Lausanne, Switzerland, Ministry of Health, Seychelles, National Center for Cardiovascular Diseases, China, National Institute of Health and Nutrition, Japan, University of Auckland, New Zealand, Simon Fraser University, Canada, South African Medical Research Council, South Africa, National Institute for Health and Welfare, Finland, University of Hong Kong, Hong Kong, National Institute of Nutrition, India, Capital Medical University Beijing An Zhen Hospital, China, Robert Koch Institute, Germany, 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Research, Malaysia, Xinjiang Medical University, China, Beijing Tongren Hospital, China, St George's, University of London, United Kingdom, Medical University of Vienna, Austria, Institute of Food and Nutrition Development of Ministry of Agriculture, China, Children's Hospital of Fudan University, China, Chinese Center for Disease Control and Prevention, China, University of Cyprus, Cyprus, Ministry of Health, Malaysia, and Inner Mongolia Medical University, China
- Abstract
Background Raised blood pressure is an important risk factor for cardiovascular diseases and chronic kidney disease. We estimated worldwide trends in mean systolic and mean diastolic blood pressure, and the prevalence of, and number of people with, raised blood pressure, defined as systolic blood pressure of 140 mm Hg or higher or diastolic blood pressure of 90 mm Hg or higher. Methods For this analysis, we pooled national, subnational, or community population-based studies that had measured blood pressure in adults aged 18 years and older. We used a Bayesian hierarchical model to estimate trends from 1975 to 2015 in mean systolic and mean diastolic blood pressure, and the prevalence of raised blood pressure for 200 countries. We calculated the contributions of changes in prevalence versus population growth and ageing to the increase in the number of adults with raised blood pressure. Findings We pooled 1479 studies that had measured the blood pressures of 19·1 million adults. Global age-standardised mean systolic blood pressure in 2015 was 127·0 mm Hg (95% credible interval 125·7–128·3) in men and 122·3 mm Hg (121·0–123·6) in women; age-standardised mean diastolic blood pressure was 78·7 mm Hg (77·9–79·5) for men and 76·7 mm Hg (75·9–77·6) for women. Global age-standardised prevalence of raised blood pressure was 24·1% (21·4–27·1) in men and 20·1% (17·8–22·5) in women in 2015. Mean systolic and mean diastolic blood pressure decreased substantially from 1975 to 2015 in high-income western and Asia Pacific countries, moving these countries from having some of the highest worldwide blood pressure in 1975 to the lowest in 2015. Mean blood pressure also decreased in women in central and eastern Europe, Latin America and the Caribbean, and, more recently, central Asia, Middle East, and north Africa, but the estimated trends in these super-regions had larger uncertainty than in high-income super-regions. By contrast, mean blood pressure might have increased in east and southeast Asia, south Asia, Oceania, and sub-Saharan Africa. In 2015, central and eastern Europe, sub-Saharan Africa, and south Asia had the highest blood pressure levels. Prevalence of raised blood pressure decreased in high-income and some middle-income countries; it remained unchanged elsewhere. The number of adults with raised blood pressure increased from 594 million in 1975 to 1·13 billion in 2015, with the increase largely in low-income and middle-income countries. The global increase in the number of adults with raised blood pressure is a net effect of increase due to population growth and ageing, and decrease due to declining age-specific prevalence. Interpretation During the past four decades, the highest worldwide blood pressure levels have shifted from high-income countries to low-income countries in south Asia and sub-Saharan Africa due to opposite trends, while blood pressure has been persistently high in central and eastern Europe. Funding Wellcome Trust. © 2017 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY license
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- 2017
10. Nanostructured LaCoO3 powders: influence of the preparation method on the CO oxidation
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Ugel, E., Natile, M. M., and ANTONELLA GLISENTI
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- 2004
11. EFFECTS OF AGROCHEMICALS ON THE MECHANICAL PROPERTIES OF PLASTIC FILMS FOR GREENHOUSE COVERING
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Vox, G., primary, Schettini, E., additional, Stefani, L., additional, Modesti, M., additional, and Ugel, E., additional
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- 2008
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12. REDUCTION OF THE ENVIRONMENTAL IMPACT OF PLASTIC FILMS FOR GREENHOUSE COVERING BY USING FLUOROPOLYMERIC MATERIALS
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Stefani, L., primary, Zanon, M., additional, Modesti, M., additional, Ugel, E., additional, Vox, G., additional, and Schettini, E., additional
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- 2008
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13. ChemInform Abstract: Synthesis and Characterization of 3- and 4-(Pentafluorosulfanyl) Benzoic Acid Derivatives (VI). X-Ray Structure of 3—SF5—C6H4—COOH.
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Zarantonello, C., primary, Guerrato, A., additional, Ugel, E., additional, Bertani, R., additional, Benetollo, F., additional, Milani, R., additional, Venzo, A., additional, and Zaggia, A., additional
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- 2008
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14. Synthesis and characterisation of 3- and 4-(pentafluorosulfanyl)benzoic acid derivatives
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Zarantonello, C., primary, Guerrato, A., additional, Ugel, E., additional, Bertani, R., additional, Benetollo, F., additional, Milani, R., additional, Venzo, A., additional, and Zaggia, A., additional
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- 2007
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15. Reduction of the environmental impact of plastic films for greenhouse covering by using fluoropolymeric materials
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Stefani, L., Zanon, M., Modesti, M., Ugel, E., Giuliano Vox, and Schettini, E.
16. ChemInform Abstract: Synthesis and Characterization of 3- and 4-(Pentafluorosulfanyl) Benzoic Acid Derivatives (VI). X-Ray Structure of 3-SF5-C6H4-COOH.
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Zarantonello, C., Guerrato, A., Ugel, E., Bertani, R., Benetollo, F., Milani, R., Venzo, A., and Zaggia, A.
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- 2008
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17. Height and body-mass index trajectories of school-aged children and adolescents from 1985 to 2019 in 200 countries and territories: a pooled analysis of 2181 population-based studies with 65 million participants
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Ming-Dong, Wang, Ningli, Wang, Qian, Wang, Xiangjun, Wang, Ya Xing, Wang, Ying-Wei, Wannamethee, S Goya, Wareham, Nicholas, Weber, Adelheid, Wedderkopp, Niels, Weerasekera, Deepa, Weghuber, Daniel, Wei, Wenbin, Weres, Aneta, Werner, Bo, Whincup, Peter H, Widhalm, Kurt, Widyahening, Indah S, Wiecek, Andrzej, Wilks, Rainford J, Willeit, Johann, Willeit, Peter, Williams, Julianne, Wilsgaard, Tom, Wojtyniak, Bogdan, Wong-McClure, Roy A, Wong, Andrew, Wong, Jyh Eiin, Wong, Tien Yin, Woo, Jean, Woodward, Mark, Wu, Frederick C, Wu, Jianfeng, Wu, Li Juan, Wu, Shouling, Xu, Haiquan, Xu, Liang, Yaacob, Nor Azwany, Yamborisut, Uruwan, Yan, Weili, Yang, Ling, Yang, Xiaoguang, Yang, Yang, Yardim, Nazan, Yaseri, Mehdi, Yasuharu, Tabara, Ye, Xingwang, Yiallouros, Panayiotis K, Yoosefi, Moein, Yoshihara, Akihiro, You, Qi Sheng, You, San-Lin, Younger-Coleman, Novie O, Yusof, Safiah Md, Yusoff, Ahmad Faudzi, Zaccagni, Luciana, Zafiropulos, Vassilis, Zakavi, Seyed Rasoul, Zamani, Farhad, Zambon, Sabina, Zampelas, Antonis, Zamrazilova, Hana, Zapata, Maria Elisa, Zargar, Abdul Hamid, Zaw, Ko Ko, Zdrojewski, Tomasz, Vrkic, Tajana Zeljkovic, Zeng, Yi, Zhang, Luxia, Zhang, Zhen-Yu, Zhao, Dong, Zhao, Ming-Hui, Zhao, Wenhua, Zhen, Shiqi, Zheng, Wei, Zheng, Yingfeng, Zholdin, Bekbolat, Zhou, Maigeng, Zhu, Dan, Zocalo, Yanina, Cisneros, Julio Zuniga, Zuziak, Monika, Faculdade de Ciências da Nutrição e Alimentação, Instituto de Saúde Pública da Universidade do Porto, Interactions Gène-Environnement en Physiopathologie Cardio-Vasculaire (IGE-PCV), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Environnement, Santé, Sociétés (ESS), Centre National de la Recherche Scientifique (CNRS), European Project: 774548, Reproductive Origins of Adult Health and Disease (ROAHD), Rodriguez-Martinez A, Zhou B, Sophiea MK, Bentham J, Paciorek CJ, Iurilli ML, Carrillo-Larco RM, Bennett JE, Di Cesare M, Taddei C, Bixby H, Stevens GA, Riley LM, Cowan MJ, Savin S, 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Mansour-Ghanaei F., Manzato E., Margozzini P., Markaki A., Markey O., Markidou Ioannidou E., Marques-Vidal P., Marques L.P., Marrugat J., Martin-Prevel Y., Martin R., Martorell R., Martos E., Marventano S., Mascarenhas L.P., Masoodi S.R., Mathiesen E.B., Mathur P., Matijasevich A., Matsha T.E., Mavrogianni C., Mazur A., Mbanya J.C.N., McFarlane S.R., McGarvey S.T., McKee M., McLachlan S., McLean R.M., McLean S.B., McNulty B.A., Mediene-Benchekor S., Medzioniene J., Mehdipour P., Mehlig K., Mehrparvar A.H., Meirhaeghe A., Meisfjord J., Meisinger C., Menezes A.M.B., Menon G.R., Mensink G.B., Menzano M.T., Mereke A., Meshram I.I., Metspalu A., Mi J., Michaelsen K.F., Michels N., Mikkel K., Milkowska K., Miller J.C., Minderico C.S., Mini G.K., Miquel J.F., Mirjalili M.R., Mirkopoulou D., Mirrakhimov E., Misigoj-Durakovic M., Mistretta A., Mocanu V., Modesti P.A., Moghaddam S.S., Mohajer B., Mohamed M.K., Mohamed S.F., Mohammad K., Mohammadi Z., Mohammadifard N., Mohammadpourhodki R., Mohan V., Mohanna S., Mohd Yusoff M.F., Mohebbi I., Mohebi F., Moitry M., Molbo D., Mollehave L.T., Moller N.C., Molnar D., Momenan A., Mondo C.K., Monroy-Valle M., Monterrubio-Flores E., Monyeki K.D.K., Moosazadeh M., Moreira L.B., Morejon A., Moreno L.A., Morgan K., Morin S.N., Mortensen E.L., Moschonis G., Mossakowska M., Mostafa A., Mota-Pinto A., Mota J., Motlagh M.E., Motta J., Moura-dos-Santos M.A., Mridha M.K., Msyamboza K.P., Mu T.T., Muc M., Mugosa B., Muiesan M.L., Mukhtorova P., Muller-Nurasyid M., Murphy N., Mursu J., Murtagh E.M., Musa K.I., Music Milanovic S., Musil V., Mustafa N., Nabipour I., Naderimagham S., Nagel G., Naidu B.M., Najafi F., Nakamura H., Namesna J., Nang E.E.K., Nangia V.B., Nankap M., Narake S., Nardone P., Nauck M., Neal W.A., Nejatizadeh A., Nelis K., Nelis L., Nenko I., Neovius M., Nervi F., Nguyen C.T., Nguyen D., Nguyen Q.N., Nieto-Martinez R.E., Nikitin Y.P., Ning G., Ninomiya T., Nishtar S., Noale M., Noboa O.A., Nogueira H., Norat T., Nordendahl M., Nordestgaard B.G., Noto D., Nowak-Szczepanska N., Nsour M.A., Nuhoglu I., Nurk E., O'Neill T.W., O'Reilly D., Obreja G., Ochimana C., Ochoa-Aviles A.M., Oda E., Oh K., Ohara K., Ohlsson C., Ohtsuka R., Olafsson O., Olinto M.T.A., Oliveira I.O., Omar M.A., Onat A., Ong S.K., Ono L.M., Ordunez P., Ornelas R., Ortiz A.P., Ortiz P.J., Osler M., Osmond C., Ostojic S.M., Ostovar A., Otero J.A., Overvad K., Owusu-Dabo E., Paccaud F.M., Padez C., Pagkalos I., Pahomova E., Paiva K.M.D., Pajak A., Palli D., Palloni A., Palmieri L., Pan W.-H., Panda-Jonas S., Pandey A., Panza F., Papandreou D., Park S.-W., Park S., Parnell W.R., Parsaeian M., Pascanu I.M., Pasquet P., Patel N.D., Pednekar M.S., Peer N., Peixoto S.V., Peltonen M., Pereira A.C., Peres M.A., Perez-Farinos N., Perez C.M., Peterkova V., Peters A., Petersmann A., Petkeviciene J., Petrauskiene A., Pettenuzzo E., Peykari N., Pham S.T., Pichardo R.N., Pierannunzio D., Pigeot I., Pikhart H., Pilav A., Pilotto L., Pistelli F., Pitakaka F., Piwonska A., Pizarro A.N., Plans-Rubio P., Poh B.K., Pohlabeln H., Pop R.M., Porta M., Posch G., Poudyal A., Poulimeneas D., Pouraram H., Pourfarzi F., Pourshams A., Poustchi H., Pradeepa R., Price A.J., Price J.F., Providencia R., Puder J.J., Pudule I., Puhakka S.E., Puiu M., Punab M., Qasrawi R.F., Qorbani M., Quoc Bao T., Radic I., Radisauskas R., Rahimikazerooni S., Rahman M., Raitakari O., Raj M., Rakhimova E., Rakhmatulloev S., Rakovac I., Ramachandra Rao S., Ramachandran A., Ramke J., Ramos E., Ramos R., Rampal L., Rampal S., Rarra V., Rascon-Pacheco R.A., Rasmussen M., Rech C.R., Redon J., Reganit P.F.M., Regecova V., Revilla L., Rezaianzadeh A., Ribas-Barba L., Ribeiro R., Riboli E., Richter A., Rigo F., Rinaldo N., Rinke de Wit T.F., Rito A., Ritti-Dias R.M., Rivera J.A., Robitaille C., Roccaldo R., Rodrigues D., Rodriguez-Artalejo F., Rodriguez-Perez M.D.C., Rodriguez-Villamizar L.A., Roggenbuck U., Rojas-Martinez R., Rojroongwasinkul N., Romaguera D., Romeo E.L., Rosario R.V., Rosengren A., Rouse I., Roy J.G., Rubinstein A., Ruhli F.J., Ruidavets J.-B., Ruiz-Betancourt B.S., Ruiz Moreno E., Rusakova I.A., Russell Jonsson K., Russo P., Rust P., Rutkowski M., Sabanayagam C., Sacchini E., Sachdev H.S., Sadjadi A., Safarpour A.R., Safi S., Safiri S., Saidi O., Saki N., Salanave B., Salazar Martinez E., Salmeron D., Salomaa V., Salonen J.T., Salvetti M., Samoutian M., Sanchez-Abanto J., Sandjaja, Sans S., Santa Marina L., Santos D.A., Santos I.S., Santos L.C., Santos M.P., Santos O., Santos R., Santos Sanz S., Saramies J.L., Sardinha L.B., Sarrafzadegan N., Sathish T., Saum K.-U., Savva S., Savy M., Sawada N., Sbaraini M., Scazufca M., Schaan B.D., Schaffrath Rosario A., Schargrodsky H., Schienkiewitz A., Schindler K., Schipf S., Schmidt C.O., Schmidt I.M., Schnohr P., Schottker B., Schramm S., Schroder H., Schultsz C., Schutte A.E., Sebert S., Sein A.A., Selamat R., Sember V., Sen A., Senbanjo I.O., Sepanlou S.G., Sequera V., Serra-Majem L., Servais J., Sevcikova L., Shalnova S.A., Shamah-Levy T., Shamshirgaran M., Shanthirani C.S., Sharafkhah M., Sharma S.K., Shaw J.E., Shayanrad A., Shayesteh A.A., Shengelia L., Shi Z., Shibuya K., Shimizu-Furusawa H., Shin D.W., Shin Y., Shirani M., Shiri R., Shrestha N., Si-Ramlee K., Siani A., Siantar R., Sibai A.M., Silva A.M., Silva D.A.S., Simon M., Simons J., Simons L.A., Sjoberg A., Sjostrom M., Skodje G., Slowikowska-Hilczer J., Slusarczyk P., Smeeth L., So H.-K., Soares F.C., Sobek G., Sobngwi E., Sodemann M., Soderberg S., Soekatri M.Y., Soemantri A., Sofat R., Solfrizzi V., Somi M.H., Sonestedt E., Song Y., Sorgjerd E.P., Sossa Jerome C., Soto-Rojas V.E., Soumare A., Sovic S., Sparboe-Nilsen B., Sparrenberger K., Spinelli A., Spiroski I., Staessen J.A., Stamm H., Stathopoulou M.G., Staub K., Stavreski B., Steene-Johannessen J., Stehle P., Stein A.D., Stergiou G.S., Stessman J., Stevanovic R., Stieber J., Stockl D., Stocks T., Stokwiszewski J., Stoyanova E., Stratton G., Stronks K., Strufaldi M.W., Sturua L., Suarez-Medina R., Suka M., Sun C.-A., Sundstrom J., Sung Y.-T., Sunyer J., Suriyawongpaisal P., Swinburn B.A., Sy R.G., Syddall H.E., Sylva R.C., Szklo M., Szponar L., Tai E.S., Tammesoo M.-L., Tamosiunas A., Tan E.J., Tang X., Tanser F., Tao Y., Tarawneh M.R., Tarp J., Tarqui-Mamani C.B., Taxova Braunerova R., Taylor A., Taylor J., Tchibindat F., Tebar W.R., Tell G.S., Tello T., Thankappan K.R., Theobald H., Theodoridis X., Thijs L., Thomas N., Thuesen B.H., Ticha L., Timmermans E.J., Tjonneland A., Tolonen H.K., Tolstrup J.S., Topbas M., Topor-Madry R., Torheim L.E., Tormo M.J., Tornaritis M.J., Torrent M., Torres-Collado L., Toselli S., Traissac P., Tran T.T.-H., Trichopoulos D., Trichopoulou A., Trinh O.T., Trivedi A., Tshepo L., Tsigga M., Tsugane S., Tuliakova A.M., Tulloch-Reid M.K., Tullu F., Tuomainen T.-P., Tuomilehto J., Turley M.L., Tynelius P., Tzotzas T., Tzourio C., Ueda P., Ugel E., Ukoli F.A., Ulmer H., Unal B., Usupova Z., Uusitalo H.M., Uysal N., Vaitkeviciute J., Valdivia G., Vale S., Valvi D., van Dam R.M., Van der Heyden J., van der Schouw Y.T., Van Herck K., Van Minh H., van Valkengoed I.G., Vanderschueren D., Vanuzzo D., Varbo A., Varela-Moreiras G., Varona-Perez P., Vasan S.K., Vega T., Veidebaum T., Velasquez-Melendez G., Velika B., Veronesi G., Verschuren W.M., Victora C.G., Viegi G., Viet L., Villalpando S., Vineis P., Vioque J., Virtanen J.K., Visser M., Visvikis-Siest S., Viswanathan B., Vladulescu M., Vlasoff T., Vocanec D., Volzke H., Voutilainen A., Voutilainen S., Vrijheid M., Vrijkotte T.G., Wade A.N., Wagner A., Waldhor T., Walton J., Wambiya E.O., Wan Bebakar W.M., Wan Mohamud W.N., Wanderley Junior R.D.S., Wang M.-D., Wang N., Wang Q., Wang X., Wang Y.X., Wang Y.-W., Wannamethee S.G., Wareham N., Weber A., Wedderkopp N., Weerasekera D., Weghuber D., Wei W., Weres A., Werner B., Whincup P.H., Widhalm K., Widyahening I.S., Wiecek A., Wilks R.J., Willeit J., Willeit P., Williams J., Wilsgaard T., Wojtyniak B., Wong-McClure R.A., Wong A., Wong J.E., Wong T.Y., Woo J., Woodward M., Wu F.C., Wu J., Wu L.J., Wu S., Xu H., Xu L., Yaacob N.A., Yamborisut U., Yan W., Yang L., Yang X., Yang Y., Yardim N., Yaseri M., Yasuharu T., Ye X., Yiallouros P.K., Yoosefi M., Yoshihara A., You Q.S., You S.-L., Younger-Coleman N.O., Yusof S.M., Yusoff A.F., Zaccagni L., Zafiropulos V., Zakavi S.R., Zamani F., Zambon S., Zampelas A., Zamrazilova H., Zapata M.E., Zargar A.H., Zaw K.K., Zdrojewski T., Zeljkovic Vrkic T., Zeng Y., Zhang L., Zhang Z.-Y., Zhao D., Zhao M.-H., Zhao W., Zhen S., Zheng W., Zheng Y., Zholdin B., Zhou M., Zhu D., Zocalo Y., Zuniga Cisneros J., Zuziak M., and Ezzati M.
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Male ,body-mass index ,ADULTHOOD ,Adolescents ,pituuskasvu ,Pediatrics ,Body Mass Index ,0302 clinical medicine ,Child Development ,nuoret ,Public health surveillance ,Medicine ,Health Status Indicators ,10. No inequality ,Child ,11 Medical and Health Sciences ,Body mass index ,ComputingMilieux_MISCELLANEOUS ,education.field_of_study ,VDP::Medisinske Fag: 700::Helsefag: 800::Samfunnsmedisin, sosialmedisin: 801 ,General Medicine ,Body mass indexes ,kansainvälinen vertailu ,3. Good health ,Geography ,Health ,030220 oncology & carcinogenesis ,Child, Preschool ,Medical and Health sciences ,purl.org/becyt/ford/3 [https] ,medicine.medical_specialty ,School-aged adolescents ,Socio-culturale ,lapset (ikäryhmät) ,Nursing ,territories ,ravinto ,purl.org/becyt/ford/3.3 [https] ,03 medical and health sciences ,School Children ,SDG 3 - Good Health and Well-being ,SYSTEMATIC ANALYSIS ,Humans ,school-aged children and adolescents ,Montenegro ,education ,Science & Technology ,Omvårdnad ,Health sciences, Medical and Health sciences ,Ciências médicas e da saúde ,Bayes Theorem ,Anthropometry ,Adolescent Development ,medicine.disease ,TRENDS ,Height and Body-mass Index ,Faculdade de Ciências Sociais ,UNDERNUTRITION ,Height index trajectories ,Height, body mass index, children , epidemiology ,risk factors, growth ,Stature ,Demography ,Settore MED/09 - Medicina Interna ,Internationality ,[SDV]Life Sciences [q-bio] ,030204 cardiovascular system & hematology ,Body-mass index trajectories ,Epidemiology ,Medicine and Health Sciences ,risk factors ,countries ,EPIDEMIOLOGY ,height ,children ,adolescents ,BMI ,030212 general & internal medicine ,painoindeksi ,Child development ,2. Zero hunger ,Medicine(all) ,School age child ,obestity children cardiovascular ,Population Health ,1. No poverty ,Pediatrik ,Public Health, Global Health, Social Medicine and Epidemiology ,3142 Public health care science, environmental and occupational health ,Pooled analysis ,NUTRITION ,Female ,medicine.symptom ,pooled analysis ,Life Sciences & Biomedicine ,terveys ,height, BMI, nutrition, health, children, adolescents ,Adolescent ,growth ,Population ,body-mass ,Population based ,Body-mass index ,Young Adult ,Medicine, General & Internal ,Meta-Analysis as Topic ,General & Internal Medicine ,parasitic diseases ,Weight gain ,School-aged childrens ,Age trajectories ,business.industry ,Height ,Weight ,Body Height ,Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi ,Malnutrition ,ONSET ,Ciências da Saúde, Ciências médicas e da saúde ,School-aged children ,VDP::Medical disciplines: 700::Health sciences: 800::Community medicine, Social medicine: 801 ,business ,terveysriskit ,Estilos de Vida e Impacto na Saúde - Abstract
BACKGROUND: Comparable global data on health and nutrition of school-aged children and adolescents are scarce. We aimed to estimate age trajectories and time trends in mean height and mean body-mass index (BMI), which measures weight gain beyond what is expected from height gain, for school-aged children and adolescents., METHODS: For this pooled analysis, we used a database of cardiometabolic risk factors collated by the Non-Communicable Disease Risk Factor Collaboration. We applied a Bayesian hierarchical model to estimate trends from 1985 to 2019 in mean height and mean BMI in 1-year age groups for ages 5–19 years. The model allowed for non-linear changes over time in mean height and mean BMI and for non-linear changes with age of children and adolescents, including periods of rapid growth during adolescence., FINDINGS: We pooled data from 2181 population-based studies, with measurements of height and weight in 65 million participants in 200 countries and territories. In 2019, we estimated a difference of 20 cm or higher in mean height of 19-year-old adolescents between countries with the tallest populations (the Netherlands, Montenegro, Estonia, and Bosnia and Herzegovina for boys; and the Netherlands, Montenegro, Denmark, and Iceland for girls) and those with the shortest populations (Timor-Leste, Laos, Solomon Islands, and Papua New Guinea for boys; and Guatemala, Bangladesh, Nepal, and Timor-Leste for girls). In the same year, the difference between the highest mean BMI (in Pacific island countries, Kuwait, Bahrain, The Bahamas, Chile, the USA, and New Zealand for both boys and girls and in South Africa for girls) and lowest mean BMI (in India, Bangladesh, Timor-Leste, Ethiopia, and Chad for boys and girls; and in Japan and Romania for girls) was approximately 9–10 kg/m2. In some countries, children aged 5 years started with healthier height or BMI than the global median and, in some cases, as healthy as the best performing countries, but they became progressively less healthy compared with their comparators as they grew older by not growing as tall (eg, boys in Austria and Barbados, and girls in Belgium and Puerto Rico) or gaining too much weight for their height (eg, girls and boys in Kuwait, Bahrain, Fiji, Jamaica, and Mexico; and girls in South Africa and New Zealand). In other countries, growing children overtook the height of their comparators (eg, Latvia, Czech Republic, Morocco, and Iran) or curbed their weight gain (eg, Italy, France, and Croatia) in late childhood and adolescence. When changes in both height and BMI were considered, girls in South Korea, Vietnam, Saudi Arabia, Turkey, and some central Asian countries (eg, Armenia and Azerbaijan), and boys in central and western Europe (eg, Portugal, Denmark, Poland, and Montenegro) had the healthiest changes in anthropometric status over the past 3·5 decades because, compared with children and adolescents in other countries, they had a much larger gain in height than they did in BMI. The unhealthiest changes—gaining too little height, too much weight for their height compared with children in other countries, or both—occurred in many countries in sub-Saharan Africa, New Zealand, and the USA for boys and girls; in Malaysia and some Pacific island nations for boys; and in Mexico for girls., INTERPRETATION: The height and BMI trajectories over age and time of school-aged children and adolescents are highly variable across countries, which indicates heterogeneous nutritional quality and lifelong health advantages and risks., Wellcome Trust, AstraZeneca Young Health Programme, EU., peer-reviewed
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- 2020
18. Synthesis and characterisation of 3- and 4-(pentafluorosulfanyl)benzoic acid derivatives: X-ray structure of 3–SF5–C6H4–COOH
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Zarantonello, C., Guerrato, A., Ugel, E., Bertani, R., Benetollo, F., Milani, R., Venzo, A., and Zaggia, A.
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X-rays , *BENZOIC acid , *BROMIDES , *ANILINE - Abstract
Abstract: The high yield synthesis of 3- and 4-(pentafluorosulfanyl)benzoic acid derivatives is described starting from the NO2-derivatives, which are reduced to the corresponding anilines. Then the NH2– group is converted to bromide and subsequently to the HC The benzaldeydes are then oxidised to the corresponding benzoic acids. The X-ray structure of 3–SF5–C6H4–COOH is also reported. [Copyright &y& Elsevier]
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- 2007
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19. [Evaluation of Implementation of the HEARTS Initiative in a Rural Community in Venezuela, 2023Avaliação da implementação da iniciativa HEARTS em uma comunidade rural da Venezuela, 2023].
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Durán M, Ugel E, Ojeda-Cáceres H, Bonelli A, Saglimbeni M, Rodríguez Araque E, González Galasso C, Yñiguez A, González C, Ramos D, and Rivera E
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Objective: To evaluate the implementation of HEARTS strategies in a community in the Bolivarian Republic of Venezuela., Methods: Quasi-experimental study evaluating the cascade of care, driving factors, and maturity and performance indicators four months after implementation of the HEARTS initiative in 52 patients with high blood pressure (BP) in the community of La Marroquina. The data were processed using SPSS
® Statistics, version 25.0. Student's t-distribution and chi-square tests were applied to determine statistical significance., Results: Fifty patients, 63.5% of them with a low educational level and low or very low socioeconomic status, completed the four-month monitoring period. At baseline, 11.5% had controlled BP and 40.4% initiated monotherapy. By the fourth month, 100% of patients with high BP had been diagnosed, 92% had received treatment, and 52% had achieved control of their BP. Seventy-two percent were receiving combined therapy. Seventy percent of the hypertensive individuals maintained blood pressure levels <140/90 mmHg. The maturity index score was 4 of 5, and the performance index was classified as incipient., Conclusion: This work shows that, in a short time, a good maturity index was achieved through the implementation, by medical and supervised non-medical personnel, of a standardized protocol for diagnosis, treatment, and monitoring of high blood pressure in a rural population. Rates of diagnosis, treatment, and BP control improved, with incipient performance results. Sustaining this initiative will have a major impact on the health of this population. Its implementation as a national public health policy is recommended., Competing Interests: Conflicto de intereses. Ninguno declarado por los autores.- Published
- 2024
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20. Relative Body Mass Index Improves the BMI Percentile Performance for Detection and Monitoring of Excess Adiposity in Adolescents.
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Velasquez-Mieyer PA, Nieto-Martinez R, Neira CP, De Oliveira-Gomes D, Velasquez Rodriguez AE, Ugel E, and Cowan PA
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- Male, Female, Adolescent, Humans, Body Mass Index, Obesity metabolism, Adipose Tissue metabolism, Absorptiometry, Photon, Body Composition, Adiposity, Overweight metabolism
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Obesity is defined as excess adipose tissue; however, commonly used methods may under-detect adiposity in adolescents. This study compared the performance of body mass index percentile (BMI%) and relative body mass index (RBMI) in identifying excess body fat percentage (BF%) and estimated RBMI cut points to better stratify severity of adiposity. In 567 adolescents ages 11-19 year, BF% measured by DXA was used to compare BMI% and RBMI performance at different degrees of adiposity. RBMI cut points for adiposity detection were derived via ROC curve analysis. BF% was strongly correlated with BMI% (r = 0.889, p < 0.001) and RBMI (r = 0.901, p < 0.001). However, RBMI exhibited less dispersion and better discriminated the relationship with BF% independent of age, race, and gender. Both BMI% and RBMI performed similarly for detecting high BF% (≥25 BF% in males; ≥30 BF% in females). Nonetheless, the relationship of BMI% with BF% was diminished among leaner adolescents. RBMI detected overweight in 21.3% more females and 14.2% more males. RBMI improved the detection of excess adiposity in individuals otherwise classified as having normal weight or overweight by BMI%. RBMI is a valuable and accessible tool for earlier detection, intervention, and effective follow-up of excess adiposity in youth at higher risk for complications.
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- 2024
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21. The diabetes care continuum in Venezuela: Cross-sectional and longitudinal analyses to evaluate engagement and retention in care.
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Goodman-Palmer D, González-Rivas JP, Jaacks LM, Duran M, Marulanda MI, Ugel E, Chavarro JE, Danaei G, and Nieto-Martinez R
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The impact of the humanitarian crisis in Venezuela on care for noncommunicable diseases (NCDs) such as diabetes is unknown. This study aims to document health system performance for diabetes management in Venezuela during the humanitarian crisis. This longitudinal study on NCDs is nationally representative at baseline (2014-2017) and has follow-up (2018-2020) data on 35% of participants. Separate analyses of the baseline population with diabetes (n = 585) and the longitudinal population with diabetes (n = 210) were conducted. Baseline analyses constructed a weighted care continuum: all diabetes; diagnosed; treated; achieved glycaemic control; achieved blood pressure, cholesterol, and glycaemic control; and achieved aforementioned control plus non-smoking. Weighted multinomial regression models controlling for region were used to estimate the association between socio-demographic characteristics and care continuum stage. Longitudinal analyses constructed an unweighted care continuum: all diabetes; diagnosed; treated; and achieved glycaemic control. Unweighted multinomial regression models controlling for region were used to estimate the association between socio-demographic characteristics and changes in care continuum stage. Among 585 participants with diabetes at baseline, 71% were diagnosed, 51% were on treatment, and 32% had achieved glycaemic control. Among 210 participants with diabetes in the longitudinal population, 50 (24%) participants' diabetes management worsened, while 40 (19%) participants improved. Specifically, the proportion of those treated decreased (60% in 2014-2017 to 51% in 2018-2020), while the proportion of participants achieving glycaemic control did not change. Although treatment rates have declined substantially among people with diabetes in Venezuela, management changed less than expected during the crisis., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: Dr. Goodman-Palmer provides scientific consultations through Epidemiologic Research & Methods, LLC (ERM); none of her consulting through ERM is related to the topic of the current study. All authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)
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- 2024
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22. Revised Case Finding Protocol for Dysglycemia in Chile: A Call for Action in Other Populations.
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Nieto-Martinez R, Mechanick JI, González-Rivas JP, Ugel E, Iglesias R, Clyne M, and Grekin C
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- Adult, Adolescent, Humans, Blood Glucose, Overweight epidemiology, Retrospective Studies, Cross-Sectional Studies, Chile epidemiology, Obesity epidemiology, Obesity complications, Prediabetic State epidemiology, Diabetes Mellitus, Type 2 complications
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Objective: Guidelines recommend case finding for dysglycemia (prediabetes and type 2 diabetes [T2D]) in adults or youth older than 10 years with overweight/obesity, but increased adiposity has not been associated with dysglycemia in some Hispanic populations. This study aims to determine the prevalence of dysglycemia in this population using simplified criteria independent of body mass index and age to request an oral glucose tolerance test (OGTT)., Methods: Cross-sectional retrospective analysis of medical records from a clinical center in Chile (2000-2007). OGTT was obtained from any patient with 1 cardiometabolic risk factor (CMRF) independent of age and body mass index., Results: In total, 4969 adults (mean age ± SD) 45.7 ± 15.9 years and 509 youths 16.6 ± 3.0 years were included. The prevalence (%, 95% CI) of prediabetes doubled that of T2D in youths (14.1%, 1.4-17.4 vs 6.3%, 4.5-8.7) and tripled it in adults (36.0%, 34.7-37.4 vs 10.7%, 9.8-11.5). In underweight and normal-weight adults, 22% (12.0-36.7) and 29.2% (26.4-32.1) had prediabetes, whereas 4.9% (1.3-16.1) and 8.8% (7.2-10.7) had T2D, respectively. In normal weight youths, 10.5% (6.7-15.9) and 2.9% (1.2-6.6) had prediabetes and T2D, respectively. In adults, but not in youths, most dysglycemia categories were related to overweight/obesity., Conclusion: This study supports a public health policy to identify more people at risk for cardiovascular disease by implementing a revised case finding protocol for dysglycemia using OGTT in even normal weight patients over 6 years of age when there is at least 1 CMRF. Reanalysis of case finding protocols for cardiometabolic risk in other populations is warranted., Competing Interests: Disclosure The authors have no multiplicity of interest to disclose., (Copyright © 2023 AACE. Published by Elsevier Inc. All rights reserved.)
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- 2023
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23. Cardiometabolic risk factors in Venezuela. The EVESCAM study: a national cross-sectional survey in adults.
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Nieto-Martínez R, González-Rivas JP, Ugel E, Duran M, Dávila E, Constantino R, García A, Mechanick JI, and Marulanda MI
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- Adult, Cross-Sectional Studies, Female, Humans, Male, Middle Aged, Obesity diagnosis, Obesity epidemiology, Prevalence, Risk Factors, Venezuela epidemiology, Cardiometabolic Risk Factors, Cardiovascular Diseases diagnosis, Cardiovascular Diseases epidemiology
- Abstract
Background: No previous study in Venezuela and few in the Region of the Americas have reported national cardiometabolic health data., Objectives: To determine the prevalence and distribution of cardiometabolic risk factors (CMRF) in adults of Venezuela., Methods: A population-based, cross-sectional, and randomized cluster sampling national study was designed to recruit 4454 adults with 20 years or older from the eight regions of the country from July 2014 to January 2017. Sociodemographic, clinical, physical activity, nutritional, and psychological questionnaires; anthropometrics, blood pressure, and biochemical measurements were obtained. The results were weighted by gender, age, and regions., Results: Data from 3414 participants (77% of recruited), 52.2% female, mean age of 41.2 ± 15.8 years, were analyzed. CMRF adjusted-prevalence were: diabetes (12.3%), prediabetes (34.9%), hypertension (34.1%), obesity (24.6%), overweight (34.4%), abdominal obesity (47.6%), underweight (4.4%), hypercholesterolemia (19.8%), hypertriglyceridemia (22.7%), low HDL-cholesterol (63.2%), high LDL-c (20.5%), daily consumption of fruits (20.9%) and vegetables (30.0%), insufficient physical activity (35.2%), anxiety (14.6%) and depression (3.2%) symptoms, current smoker (11.7%), and high (≥ 20%) 10-year fatal cardiovascular risk (14.0%). CMRF prevalence varied according to gender, age and region of residence., Conclusions: Cardiometabolic risk factors are highly prevalent in Venezuelan adults. This situation can be affected by the severe socio-economic crisis in the country. The joint action of different stakeholders to implement public health strategies for the prevention and treatment of these risk factors in Venezuela is urgently needed., (Copyright © 2020 Primary Care Diabetes Europe. Published by Elsevier Ltd. All rights reserved.)
- Published
- 2021
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24. Optimal waist circumference cutoff values to predict cardiometabolic alterations in a Venezuela national representative sample. The EVESCAM study.
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González-Rivas JP, Mechanick JI, Iglesias-Fortes R, De-Oliveira-Gomes D, Silva J, Valencia J, Figueroa E, Duran M, Ugel E, Infante-García MM, Marulanda MI, and Nieto-Martínez R
- Abstract
Background: Waist circumference (WC) value reflects abdominal adiposity, but the amount abdominal fat that is associated to cardiometabolic risk factors varies among ethnicities. Determination of metabolic abnormalities has not undergone a WC adaptation process in Venezuela., Aims: The aim of the study was (1) to determine the optimal WC cutoff value associated with ≥2 cardiometabolic alterations and (2) incorporating this new WC cutoff, to determine the prevalence of abdominal obesity and cardiometabolic risk factors related in Venezuela., Methods: The study was national population-based, cross-sectional, and randomized sample, from 2014 to 2017. To assess performance of WC for identifying cardiometabolic alterations, receiver operating characteristics curves, area under the curve (AUC), sensitivity, specificity, and positive likelihood ratios were calculated., Results: Three thousand three hundred eighty-seven adults were evaluated with mean age of 41.2 ± 15.8 years. Using the best tradeoff between sensitivity and specificity, WC cutoffs of 90 cm in men (sensitivity = 72.4% and specificity = 66.1%) and 86 cm in women (sensitivity = 76.2% and specificity = 61.4%) were optimal for aggregation of ≥2 cardiometabolic alterations. AUC was 0.75 in men and 0.73 in women using these new cutoffs. Prevalence of abdominal obesity and metabolic syndrome was 59.6% (95 CI; 57.5-61.7) and 47.6% (95 CI; 45.2-50.0), respectively. Cardiometabolic risk factors were associated with being men, higher age, adiposity, and living in northern or western regions., Conclusion: The optimal WC values associated with cardiometabolic alterations were 90 cm in men and 86 cm in women. More than half of the Venezuelan population had abdominal obesity incorporating this new WC cutoff.
- Published
- 2020
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25. Dietary intake and cardiometabolic risk factors among Venezuelan adults: a nationally representative analysis.
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Goodman D, González-Rivas JP, Jaacks LM, Duran M, Marulanda MI, Ugel E, Mattei J, Chavarro JE, and Nieto-Martinez R
- Abstract
Background: Increasing trends in global obesity have been attributed to a nutrition transition where healthy foods are replaced by ultra-processed foods. It remains unknown if this nutrition transition has occurred in Venezuela, a country undergoing a socio-political crisis with widespread food shortages., Methods: We described dietary intake of Venezuelans from a nationally representative study conducted between 2014 and 2017. We conducted a cross-sectional analysis of dietary, sociodemographic, and clinical data from Venezuelans ≥20 years of age ( n = 3420). Dietary intake was assessed using a semi-quantitative food frequency questionnaire. Standardized clinical and anthropometric measurements estimated obesity, type 2 diabetes, and hypertension. A Dietary Diversity Score (DDS) was calculated using an amended Minimum Dietary Diversity for Women score where the range was 0 to 8 food groups, with 8 being the most diverse. Analyses accounted for complex survey design by estimating weighted frequencies of dietary intake and DDS across sociodemographic and cardiometabolic risk-based subgroups., Results: The prevalence of obesity was 24.6% (95% CI: 21.6-27.7), type 2 diabetes was 13.3% (11.2-15.7), and hypertension was 30.8% (27.7-34.0). Western foods were consumed infrequently. Most frequently consumed foods included coffee, arepas (a salted corn flour cake), and cheese. Mean DDS was 2.3 food groups (Range: 0-8, Standard Error: 0.07) and this score did not vary among subgroups. Men, younger individuals, and those with higher socioeconomic status were more likely to consume red meat and soft drinks once or more weekly. Women and those with higher socioeconomic status were more likely to consume vegetables and cheese once or more daily. Participants with obesity, type 2 diabetes, and hypertension had lower daily intake of red meat and arepas compared to participants without these risk factors., Conclusions: Despite high prevalence of cardiometabolic risk factors, adults in Venezuela have not gone through a nutrition transition similar to that observed elsewhere in Latin America. Dietary diversity is low and widely consumed food groups that are considered unhealthy are part of the traditional diet. Future studies are needed in Venezuela using more comprehensive measurements of dietary intake to understand the effect of the socio-political crisis on dietary patterns and cardiometabolic risk factors., Competing Interests: Competing interestsThe authors declare that they have no competing interests., (© The Author(s) 2020.)
- Published
- 2020
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26. External validation of the Finnish diabetes risk score in Venezuela using a national sample: The EVESCAM.
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Nieto-Martínez R, González-Rivas JP, Ugel E, Marulanda MI, Durán M, Mechanick JI, and Aschner P
- Subjects
- Adult, Cross-Sectional Studies, Diabetes Mellitus blood, Diabetes Mellitus epidemiology, Female, Glucose Tolerance Test methods, Humans, Male, Morbidity trends, Retrospective Studies, Risk Factors, Venezuela epidemiology, Blood Glucose metabolism, Diabetes Mellitus diagnosis, Population Surveillance, Propensity Score
- Abstract
Aims: To evaluate the performance of the Latin American Finnish Diabetes Risk Score (LA-FINDRISC) compared with the original O-FINDRISC in general population. To establish the best cut-off to detect unknown type 2 diabetes (uT2D) and prediabetes., Methods: The EVESCAM was a national population-based, cross-sectional, randomized cluster sampling study, which assessed 3454 adults from July 2014 to January 2017. Those with self-report of diabetes were excluded; a total of 3061 subjects were analyzed. Waist circumference adapted for Latin America was the difference between the LA-FINDRISC and the O-FINDRISC. The area under the curve (AUC), sensitivity, and specificity were calculated., Results: The prevalence of uT2D and prediabetes were 3.3% and 38.5%. The AUC with the LA-FINDRISC vs. the O-FINDRISC were: for uT2D, 0.722 vs. 0.729 in men (p=0.854) and 0.724 vs. 0.732 in women (p=0.896); for prediabetes (impaired fasting glucose [IFG] + impaired glucose tolerance [IGT], 0.590 vs. 0.587 in men (p=0.887) and 0.621 vs. 0.627 in women (p=0.777); for IFG, 0.582 vs. 0.580 in men (p=0.924) and 0.607 vs. 0.617 in women (p=0.690); for IGT, 0.691 vs. 0.692 in men (p=0.971) and 0.672 vs. 0.671 in women (p=0.974). Using the LA-FINDRISC, the best cut-offs to detect uT2D were 9 in men and 10 in women and to detect IGT was 9 in both genders., Conclusion: LA-FINDRISC has similar performance than O-FINDRISC in Venezuelan adults and showed a good performance to detect uT2D and IGT, but not IFG. The best cut-offs to detect glucose alterations were established., (Copyright © 2019 Primary Care Diabetes Europe. Published by Elsevier Ltd. All rights reserved.)
- Published
- 2019
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27. Diabetes and depression were not associated in Venezuelan adults: The EVESCAM study, a national cross-sectional sample.
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González-Rivas JP, Polonsky W, Infante-García MM, Duran M, Ugel E, Marulanda MI, Mechanick JI, and Nieto-Martínez R
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- Adult, Aged, Blood Glucose metabolism, Cross-Sectional Studies, Diabetes Mellitus, Type 2 blood, Female, Humans, Male, Middle Aged, Prevalence, Retrospective Studies, Risk Factors, Venezuela epidemiology, Young Adult, Depression epidemiology, Diabetes Mellitus, Type 2 epidemiology, Population Surveillance methods, Psychometrics methods, Risk Assessment methods
- Abstract
Background: Evidence suggests that depression is more common in patients with diabetes than in the general population. However, contradictory results expose controversy in this association., Objective: To evaluate the relationship between diabetes and depression in a national sample of Venezuelan adults., Methods: The EVESCAM was a national population-based, cross-sectional, randomized cluster sampling study, which assessed 3,454 adults from July 2014 to January 2017 (response rate of 77.3%). Diabetes was defined using fasting blood glucose and a 2-hour oral glucose tolerance test. Depressive symptoms were determined using the Hospital Anxiety and Depression Scale., Results: 3255 subjects were assessed. Depressive symptom score was different between genders and among age groups (p<0.001), and similar in those subjects with or without diabetes (p=0.899). Depressive symptoms prevalence was higher in women than in men and increased with age (p<0.05), but was similar in those with and without diabetes (p=0.215). Using a multivariate regression analysis model, the association of depressive symptoms and diabetes remains non-significant after adjusting for age and gender (Odds ratio=0.98; 95% Confidence Intervals 0.95 - 1.02, p=0.504)., Conclusion: Diabetes and depression were not associated in a large sample of Venezuelan adults., (Copyright © 2019 Primary Care Diabetes Europe. Published by Elsevier Ltd. All rights reserved.)
- Published
- 2019
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28. Cardiovascular Health in a National Sample of Venezuelan Subjects Assessed According to the AHA Score: The EVESCAM.
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González-Rivas JP, Mechanick JI, Ugel E, Marulanda MI, Duran M, and Nieto-Martínez R
- Subjects
- Adult, Age Distribution, Aged, Cluster Analysis, Educational Status, Female, Healthy Lifestyle, Humans, Male, Middle Aged, Prevalence, Risk Factors, Sex Distribution, Venezuela epidemiology, Young Adult, Cardiovascular Diseases epidemiology, Health Status
- Abstract
Background: Cardiovascular health status of the Venezuelan population has not been evaluated. The American Heart Association recommends the Cardiovascular Health Score (CHS) to assess cardiovascular health., Objectives: This study sought to determine the prevalence of CHS categories in a nationally representative sample of Venezuelan adults., Methods: EVESCAM (Venezuelan Study of Cardio-Metabolic Health) was a national population-based, cross-sectional, randomized cluster sampling study performed from July 1, 2014 to January 31, 2017, which assessed 3,454 adults, age ≥20 years, with a response rate of 77.3%. The American Heart Association's CHS evaluates 4 behaviors (smoking, body mass index, physical activity, and diet) and 3 risk factors (total cholesterol, blood pressure, and blood glucose), assigning 1 point to those meting an ideal behavior or factor or 0 points if are not. Subjects were categorized as having ideal (5 to 7 points), intermediate (3 to 4), or poor (<3) cardiovascular health. Weighted prevalence by age, sex, and regions are presented., Results: A total of 2,992 participants completed the data. Mean age and CHS were 41.4 ± 15.8 years and 4.3 ± 1.1 points, respectively. The prevalence of ideal CHS was 37.9% (95% confidence interval: 35.0 to 40.7); two-thirds presented with intermediate to poor CHS. Ideal CHS was most prevalent in women, in the youngest participants, and in those with higher education degree and living in a rural area. The prevalence of 7 components was 0.13%. Subjects evaluated since mid-2016 had a higher prevalence of ideal CHS (≈47%) than those evaluated before it (≈32%) (p < 0.001)., Conclusions: A high prevalence of ideal CHS was observed in Venezuelan adults compared with other reports; however, a large proportion remain with high risk for cardiovascular disease., (Copyright © 2019 World Heart Federation (Geneva). Published by Elsevier B.V. All rights reserved.)
- Published
- 2019
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29. Re-Classifying Hypertension in the Venezuelan EVESCAM Database Using 2017 AHA/ACC Criteria: High Prevalence, Poor Control, and Urgent Call for Action.
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González-Rivas J, Mechanick J, Duran M, Ugel E, Marulanda M, and Nieto-Martínez R
- Subjects
- Adult, Aged, American Heart Association, Blood Pressure Determination instrumentation, Cluster Analysis, Cross-Sectional Studies, Databases, Factual, Female, Humans, Male, Middle Aged, Practice Guidelines as Topic, Prevalence, United States, Venezuela epidemiology, Hypertension classification, Hypertension epidemiology
- Abstract
Background: In 2017 the American Heart Association (AHA)/American College of Cardiology (ACC) changed the criteria to define hypertension (HTN)., Objective: To re-analyze Venezuelan data to update HTN prevalence rates and estimate the number of adults with uncontrolled blood pressure (BP) using AHA/ACC criteria., Methods: The EVESCAM was a national population-based, cross-sectional, randomized cluster sampling study, which assessed 3,420 adults from July 2014 to January 2017, with a response rate of 77.3%. The mean of two BP measurements was obtained using a standard oscillometric device protocol. HTN was defined using both 2017 AHA/ACC guideline (BP ≥ 130/80 mmHg) and JNC7 (BP ≥ 140/90 mmHg) criteria., Findings: The crude prevalence of HTN using 2017 AHA/ACC guideline criteria was 60.4%, 13% higher than with the JNC7 criteria. The age-standardized prevalence was 55.4% in men and 49.0% in women (p < 0.001), 17.5% and 12.7% higher, respectively, compared with the JNC7 criteria. In subjects without self-reported HTN, the age-standardized prevalence of HTN was 43.4% in men and 32.3% in women, of whom, 22.9% and 19.2% were between 130-139/80-89 mmHg, respectively. In those with self-reported HTN, the prevalence of uncontrolled BP (≥130/80 mmHg) on antihypertensive medication was 66.8% in men and 65.8% in women. The total estimated number of subjects with HTN in Venezuela increased to 11 million, and only about 1.8 million are controlled., Conclusion: Using the new 2017 AHA/ACC guideline, the prevalence of HTN in Venezuela is approximately half of the adult population and associated with relatively poor BP control., Competing Interests: The authors have no competing interests to declare., (© 2019 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/.)
- Published
- 2019
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30. Prevalence of diabetes in three regions of Venezuela. The VEMSOLS study results.
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Nieto-Martínez R, Mechanick JI, Brajkovich I, Ugel E, Risques A, Florez H, and González-Rivas JP
- Subjects
- Adult, Age Distribution, Cross-Sectional Studies, Diabetes Mellitus diagnosis, Diabetes Mellitus psychology, Diabetes Mellitus therapy, Female, Health Knowledge, Attitudes, Practice, Health Promotion, Humans, Male, Middle Aged, Patient Education as Topic, Prediabetic State epidemiology, Prevalence, Risk Factors, Sex Distribution, Time Factors, Venezuela epidemiology, Young Adult, Diabetes Mellitus epidemiology
- Abstract
Objective: The prevalence of diabetes in multiple regions of Venezuela is unknown. To determine the prevalence of diabetes in five populations from three regions of Venezuela., Methods: During 2006-2010, 1334 subjects ≥20years were selected by multistage stratified random sampling from all households from 3 regions of Venezuela. Anthropometric measurements and biochemical analysis were obtained. Statistical methods were calculated using SPSS 20 software., Findings: Mean (SE) age was 44.8 years (0.39) and 68.5% were females. The prevalence of diabetes was 8.3% (95% CI, 6.9%-10.0%), higher in men than women (11.2% and 7.0% respectively; p=0.01). The prevalence adjusted by age and gender was 8.0% (95% CI, 6.9%-9.9%). This figure increased with age, with the lowest prevalence in the 20-29year old group (1.8% [95% CI, 0.6%-4.8%]) and the highest in the oldest group (26.8% [95% CI, 16.2%-40.5%]). Subjects with overweight or obesity had no increased risk of diabetes compared with those with normal weight. However, in women, the presence of abdominal obesity was associated with an increase of the risk of diabetes by 77% (OR 1.77 [95% CI, 1.1%-2.9%]). The prevalence of prediabetes was 14.6% (95% CI, 12.8%-16.7%), and only 48.2% were aware of their diabetes condition., Conclusion: In this study, 8.3% of the subjects had diabetes and 14.6% prediabetes. Less than half of the subjects with diabetes were aware of their condition. These results point to a major public health problem, requiring the implementation of diabetes prevention programs., (Copyright © 2017 Primary Care Diabetes Europe. Published by Elsevier Ltd. All rights reserved.)
- Published
- 2018
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31. Prevalence of Dyslipidemias in Three Regions in Venezuela: The VEMSOLS Study Results.
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González-Rivas JP, Nieto-Martínez R, Brajkovich I, Ugel E, and Rísquez A
- Subjects
- Adult, Cross-Sectional Studies, Female, Humans, Life Style, Male, Prevalence, Risk Factors, Spatial Analysis, Venezuela epidemiology, Dyslipidemias epidemiology
- Abstract
Background: The prevalence of dyslipidemia in multiple regions of Venezuela is unknown. The Venezuelan Metabolic Syndrome, Obesity and Lifestyle Study (VEMSOLS) was undertaken to evaluate cardiometabolic risk factors in Venezuela., Objective: To determine the prevalence of dyslipidemia in five populations from three regions of Venezuela., Methods: During the years 2006 to 2010, 1320 subjects aged 20 years or older were selected by multistage stratified random sampling from all households in five municipalities from 3 regions of Venezuela: Lara State (Western region), Merida State (Andean region), and Capital District (Capital region). Anthropometric measurements and biochemical analysis were obtained from each participant. Dyslipidemia was defined according to the NCEP/ATPIII definitions., Results: Mean age was 44.8 ± 0.39 years and 68.5% were females. The prevalence of lipids abnormalities related to the metabolic syndrome (low HDL-c [58.6%; 95% CI 54.9 - 62.1] and elevated triglycerides [39.7%; 36.1 - 43.2]) were the most prevalent lipid alterations, followed by atherogenic dyslipidemia (25.9%; 22.7 - 29.1), elevated LDL-c (23.3%; 20.2 - 26.4), hypercholesterolemia (22.2%; 19.2 - 25.2), and mix dyslipidemia (8.9%; 6.8 - 11.0). Dyslipidemia was more prevalent with increasing body mass index., Conclusion: Dyslipidemias are prevalent cardiometabolic risk factors in Venezuela. Among these, a higher prevalence of low HDL is a condition also consistently reported in Latin America.
- Published
- 2018
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32. APPLICATION OF THE AACE/ACE ADVANCED FRAMEWORK FOR THE DIAGNOSIS OF OBESITY AND CARDIOMETABOLIC DISEASE STAGING IN A GENERAL POPULATION FROM 3 REGIONS OF VENEZUELA: THE VEMSOLS STUDY RESULTS.
- Author
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Nieto-Martínez R, González-Rivas JP, Ugel E, Brajkovich I, Risquez A, Garvey WT, and Mechanick JI
- Subjects
- Adult, Blood Glucose metabolism, Blood Pressure, Body Mass Index, Cardiovascular Diseases metabolism, Cholesterol, HDL metabolism, Diabetes Mellitus, Type 2 metabolism, Endocrinology, Female, Glucose Intolerance metabolism, Humans, Hypertension epidemiology, Male, Metabolic Syndrome metabolism, Middle Aged, Obesity metabolism, Overweight epidemiology, Overweight metabolism, Prevalence, Severity of Illness Index, Societies, Medical, Triglycerides metabolism, United States, Venezuela epidemiology, Waist Circumference, World Health Organization, Cardiovascular Diseases epidemiology, Diabetes Mellitus, Type 2 epidemiology, Glucose Intolerance epidemiology, Metabolic Syndrome epidemiology, Obesity epidemiology
- Abstract
Objective: To determine the prevalence of obesity according to the American Association of Clinical Endocrinologists/American College of Endocrinology (AACE/ACE) framework based on a complications-centric model with further application of the Cardiometabolic Disease Staging (CMDS) system in a Venezuelan population., Methods: A total of 1,320 adults were randomly selected from 3 regions. The AACE/ACE framework definitions were as follows: overweight, body mass index (BMI) 25 to 29.9 kg/m
2 and no obesity-related complications (ORC); obesity stage 0, BMI ≥30 and no ORC; stage 1, BMI ≥25 and 1 or more mild-to-moderate ORC; and stage 2, BMI ≥25 and 1 or more severe ORC. CMDS definitions were as follows: stage 0, no metabolic syndrome (MS) components; stage 1, 1 to 2 MS components without impaired fasting glucose (IFG); stage 2, IFG or ≥3 MS components but without IFG; stage 3, IFG and MS; and stage 4, type 2 diabetes (T2D) or cardiovascular disease., Results: The mean age was 44.8 ± 0.4 years, and 68.5% were female. The prevalence of obesity according to the AACE/ACE framework was 63.1%: overweight 3.0% (95% confidence interval [CI]: 2.1-3.9); obesity stage 0: 0.1% (0.07-0.27); obesity stage 1: 26.6% (24.2-29.0); and obesity stage 2: 36.4% (33.8-39.0). Most subjects with a BMI <25 were CMDS 0 or 1. In those with BMI ≥ 25, only 4.6% were CMDS 0. The prevalence of obesity according to the World Health Organization (WHO, BMI ≥30) was 29.3% (24.7-33.7)., Conclusion: In a general population study, applying the AACE/ACE framework for obesity and CMDS increased the detection of ORC and therefore higher risk subjects compared to classic anthropometric measurements., Abbreviations: AACE = American Association of Clinical Endocrinologists; ACE = American College of Endocrinology; BMI = body mass index; CMDS = Cardiometabolic Disease Staging; DALY = disability-adjusted life years; LA = Latin America; MS = metabolic syndrome; ORC = obesity-related complications; WC = waist circumference; WHO = World Health Organization.- Published
- 2018
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33. Cardio-Metabolic Health Venezuelan Study (EVESCAM): Design and Implementation.
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Nieto-Martínez R, Inés Marulanda M, González-Rivas JP, Ugel E, Durán M, Barengo N, Aschner P, Patiño M, López Gómez L, Monsalve P, Marcano H, and Florez H
- Subjects
- Adult, Cross-Sectional Studies, Female, Humans, Male, Prevalence, Risk Factors, Venezuela epidemiology, Young Adult, Metabolic Syndrome epidemiology
- Abstract
The EVESCAM (EstudioVenezolano de Salud Cardio-Metabólica) is the first national, population survey in Venezuela, designed to examine the prevalence of diabetes and cardio-metabolic risk factors and its relationship with lifestyle. It is a cross-sectional, cluster sampling study, which recruited 4454 participants aged ≥ 20 years. The data were collected in community health-care centers by trained health professionals and medical students. The data collected from each subject included, after informed consent, structured questionnaires (clinical, demographic, physical activity, nutritional and psychological), anthropometric measurements (weight, height and waist circumference), body fat by bioelectrical impedance, hand grip, blood pressure, electrocardiogram, and biochemical measurements (standard 75 g oral glucose tolerance test, total cholesterol, HDL-cholesterol, LDL-cholesterol and triglycerides). The data will be used to estimate the prevalence of overweight, obesity, prediabetes, diabetes, hypertension, dyslipidemias, sarcopenia and metabolic syndrome; and to examine their relationships with lifestyle factors. The risk of coronary heart disease and impaired glucose regulation will be estimated using the Framingham Coronary Heart Disease Risk Score and the Latin America adaptation of the Finnish Diabetes Risk Score (LA-FINDRISC), respectively. These results will guide national cardiovascular and diabetes prevention strategies, and will be available for government agencies to help in the implementation of public health policies.
- Published
- 2017
34. High prevalence and poor control of hypertension in five venezuelan populations: the VEMSOLS study.
- Author
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González-Rivas JP, José García Santiago R, Ugel E, Brajkovich I, Risquez A, and Nieto-Martínez R
- Subjects
- Adult, Aged, Female, Humans, Hypertension prevention & control, Male, Middle Aged, Venezuela epidemiology, Young Adult, Hypertension epidemiology
- Abstract
The prevalence of hypertension in multiple regions of Venezuela is unknown. The objective of this study was to estimate the prevalence of hypertension in five populations from three regions. During 2006 to 2010, 1392 subjects aged 20 or older were selected by multistage stratified random sampling from all households in five municipalities from: Lara State (Western region), Merida State (Andean region), and Capital District (Capital region). Anthropometric measurements, blood pressure, and biochemical analysis were obtained from each participant. Mean age was 45.2 ± 0.4 years and 68% were females. The overall prevalence of hypertension was 31.3% (CI 95% 28.9 – 33.8), it was higher in men than women (38.1% [33.5 – 42.8] vs. 28.2% [25.4 – 31.2], respectively; p <0.001). The hypertensive participants were older, with higher body mass index (BMI), glucose, total cholesterol, LDL-c, and triglycerides; and lower values of HDL-c, than pre-hypertensive and normotensive participants (p < 0.05). In women, hypertension prevalence increased linearly for every decade of life and by category of BMI; whereas in men it increased until the fifth decade of life, and was similar in patients with overweight and obesity. The risk of hypertension increased with age, the presence of obesity, diabetes, overweight and family history of hypertension. Only 17.7% of the hypertensive subjects were both treated and controlled. In conclusion, about one third of the subjects evaluated had hypertension and about one fifth of them had their hypertension under control. In Venezuela, hypertension is a serious public health problem exacerbated by age and overweight.
- Published
- 2016
35. [Dental caries amongst mentally retarded people and those suffering from Down's syndrome].
- Author
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Dávila ME, Gil M, Daza D, Bullones X, and Ugel E
- Subjects
- Adolescent, Adult, Age Factors, Child, Dental Caries therapy, Dental Health Services statistics & numerical data, Down Syndrome diagnosis, Female, Humans, Intellectual Disability diagnosis, Male, Prevalence, Sex Factors, Venezuela epidemiology, Dental Caries epidemiology, Down Syndrome complications, Intellectual Disability complications
- Abstract
Objective: A descriptive investigation was conducted for determining the prevalence of dental caries amongst mentally retarded (MR) people and those suffering from Down's syndrome (DS)., Methods: A special school located in Morán county in the State of Lara was visited. The inclusion criteria involved dental examination of 60 students and their parents/or the person responsible for them being interviewed., Results: Participants' mean age was 14.5 +/- 8.17; 48.3% were from a blue collar level. Regarding oral health, 53.0% had dental caries, 51.7% being in the molars. Moderately MR people had the highest proportion of dental caries (75%). About 53% of the females and 46.2% of males, 644% and 31.9% of RM and DS participants had caries. 28.3% needed non-urgent dental treatment and 45% were using public dental health services., Conclusions: People suffering from MR and DS have precarious oral health; it is thus recommended that health programmes be created which are specifically directed towards these people.
- Published
- 2006
- Full Text
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