Age-standardized and cumulative incidence rates (three-digit ... - IARC
Age-standardized and cumulative incidence rates (three-digit ... - IARC
Age-standardized and cumulative incidence rates (three-digit ... - IARC
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<strong>Age</strong>-<strong>st<strong>and</strong>ardized</strong> (world) <strong>incidence</strong> (per 100,000) <strong>and</strong><br />
<strong>cumulative</strong> (0-74) <strong>incidence</strong> (percent)<br />
<strong>rates</strong> <strong>and</strong> st<strong>and</strong>ard errors<br />
Mesothelioma (C45) (contd)<br />
MALE<br />
Cases ASR(W) CUM 0-74<br />
FEMALE<br />
Cases ASR(W) CUM 0-74<br />
Asia (contd)<br />
*India, Ahmedabad 4 0.1 0.04 0.01 0.01 2 0.0 0.02 0.00 0.00<br />
*India, Bangalore 7 0.1 0.03 0.01 0.01 0 - - - -<br />
India, Chennai (Madras) 6 0.1 0.03 0.01 0.01 1 0.0 0.01 0.00 0.00<br />
*India, Delhi 6 0.0 0.02 0.01 0.00 1 0.0 0.00 0.00 0.00<br />
*India, Karunagappally 0 - - - - 0 - - - -<br />
India, Mumbai (Bombay) 23 0.1 0.03 0.02 0.00 9 0.1 0.02 0.01 0.00<br />
*India, Nagpur 0 - - - - 0 - - - -<br />
*India, Poona 1 0.0 0.02 0.00 0.00 1 0.0 0.03 0.01 0.01<br />
*India, Triv<strong>and</strong>rum 0 - - - - 0 - - - -<br />
Israel: Jews 76 0.6 0.07 0.07 0.01 32 0.2 0.04 0.02 0.00<br />
Israel: Jews born in Israel 12 0.5 0.20 0.05 0.02 6 0.1 0.05 0.01 0.01<br />
Israel: Jews born in Europe or America 46 0.7 0.13 0.09 0.02 15 0.2 0.07 0.02 0.01<br />
Israel: Jews born in Africa or Asia 18 0.5 0.12 0.06 0.01 11 0.3 0.10 0.03 0.01<br />
Israel: Non-Jews 3 0.2 0.10 0.02 0.01 1 0.1 0.07 - -<br />
Japan, Hiroshima 22 0.6 0.12 0.05 0.02 8 0.2 0.08 0.03 0.01<br />
*Japan, Miyagi Prefecture 19 0.2 0.05 0.03 0.01 9 0.1 0.03 0.01 0.00<br />
*Japan, Nagasaki Prefecture 45 0.7 0.10 0.07 0.01 15 0.2 0.05 0.02 0.01<br />
*Japan, Osaka Prefecture 211 0.7 0.05 0.08 0.01 73 0.2 0.02 0.02 0.00<br />
*Japan, Saga Prefecture 10 0.3 0.10 0.03 0.01 6 0.1 0.07 0.01 0.01<br />
*Japan, Yamagata Prefecture 9 0.2 0.06 0.02 0.01 3 0.0 0.02 0.00 0.00<br />
*Korea, Busan 8 0.3 0.11 0.04 0.02 5 0.1 0.05 0.02 0.01<br />
*Korea, Daegu 1 0.1 0.06 0.01 0.01 1 0.0 0.05 0.01 0.01<br />
*Korea, Kangwha County 2 0.9 0.62 0.10 0.07 0 - - - -<br />
*Korea, Seoul 34 0.2 0.03 0.02 0.00 22 0.1 0.02 0.01 0.00<br />
*Kuwait: Kuwaitis 1 0.2 0.17 - - 0 - - - -<br />
*Kuwait: Non-Kuwaitis 5 0.1 0.05 0.01 0.00 0 - - - -<br />
*Oman: Omani 1 0.0 0.04 - - 0 - - - -<br />
*Pakistan, South Karachi 2 0.1 0.08 0.01 0.01 0 - - - -<br />
*Philippines, Manila 5 0.1 0.04 0.01 0.01 8 0.1 0.04 0.01 0.00<br />
*Philippines, Rizal 4 0.1 0.04 0.01 0.01 2 0.0 0.02 0.00 0.00<br />
Singapore: Chinese 23 0.5 0.10 0.06 0.01 8 0.1 0.04 0.01 0.00<br />
Singapore: Indian 1 0.1 0.13 0.01 0.01 2 0.6 0.42 0.03 0.03<br />
Singapore: Malay 2 0.2 0.14 0.01 0.01 0 - - - -<br />
*Thail<strong>and</strong>, Bangkok 4 0.0 0.02 0.00 0.00 1 0.0 0.01 0.00 0.00<br />
*Thail<strong>and</strong>, Chiang Mai 3 0.1 0.05 0.01 0.01 0 - - - -<br />
*Thail<strong>and</strong>, Khon Kaen 0 - - - - 0 - - - -<br />
*Thail<strong>and</strong>, Lampang 3 0.1 0.07 0.01 0.01 4 0.2 0.08 0.02 0.02<br />
*Thail<strong>and</strong>, Songkhla 0 - - - - 0 - - - -<br />
*Viet Nam, Hanoi 9 0.2 0.08 - - 6 0.1 0.05 - -<br />
*Viet Nam, Ho Chi Minh City 2 0.0 0.03 0.00 0.00 0 - - - -<br />
Europe<br />
Austria, Tyrol 13 0.6 0.18 0.09 0.03 5 0.2 0.09 0.04 0.02<br />
Austria, Vorarlberg 3 0.3 0.18 0.07 0.04 4 0.2 0.12 0.03 0.02<br />
+*Belarus 98 0.3 0.03 0.05 0.00 101 0.3 0.03 0.03 0.00<br />
*Belgium, Fl<strong>and</strong>ers, (excl. Limburg) 150 1.8 0.15 0.22 0.02 39 0.4 0.08 0.05 0.01<br />
*Belgium, Limburg 13 1.1 0.31 0.13 0.04 8 0.5 0.19 0.05 0.02<br />
*Croatia 168 1.1 0.09 0.14 0.01 54 0.3 0.04 0.03 0.01<br />
Czech Republic 150 0.5 0.04 0.06 0.01 112 0.3 0.03 0.03 0.00<br />
Denmark 322 1.6 0.09 0.21 0.01 71 0.3 0.04 0.04 0.01<br />
Estonia 13 0.3 0.09 0.04 0.01 14 0.2 0.06 0.03 0.01<br />
Finl<strong>and</strong> 196 1.1 0.08 0.15 0.01 62 0.2 0.03 0.03 0.00<br />
France, Bas-Rhin 38 1.2 0.20 0.16 0.03 9 0.2 0.08 0.04 0.01<br />
*France, Calvados 31 1.4 0.26 0.20 0.04 13 0.5 0.15 0.06 0.02<br />
France, Cote d’Or<br />
France, Doubs 25 1.4 0.30 0.17 0.04 6 0.3 0.12 0.02 0.01<br />
France, Haut-Rhin 18 0.8 0.19 0.09 0.03 4 0.1 0.07 0.02 0.01<br />
*France, Herault 15 0.4 0.11 0.06 0.02 7 0.2 0.07 0.02 0.01<br />
France, Isere 56 1.6 0.22 0.20 0.03 17 0.3 0.09 0.04 0.01<br />
*France, Manche 19 1.4 0.33 0.15 0.04 5 0.3 0.15 0.04 0.02<br />
*France, Somme 26 1.4 0.29 0.18 0.04 11 0.5 0.17 0.06 0.02<br />
France, Tarn 13 0.9 0.27 0.10 0.03 3 0.1 0.08 0.02 0.01<br />
Germany, Saarl<strong>and</strong> 26 0.6 0.12 0.08 0.02 5 0.1 0.04 0.01 0.01<br />
Icel<strong>and</strong> 7 0.9 0.35 0.13 0.05 2 0.2 0.13 0.02 0.02<br />
Irel<strong>and</strong> 58 0.7 0.09 0.09 0.01 7 0.1 0.04 0.01 0.00<br />
Italy, Biella Province 10 1.9 0.62 0.19 0.07 3 0.4 0.28 0.05 0.03<br />
Italy, Ferrara Province 28 1.5 0.31 0.18 0.04 13 0.5 0.17 0.08 0.02<br />
*Italy, Florence 36 0.6 0.11 0.08 0.02 19 0.2 0.06 0.03 0.01<br />
Italy, Genoa Province 206 5.4 0.40 0.67 0.05 60 1.2 0.20 0.14 0.02<br />
Italy, Liguria 167 4.5 0.38 0.57 0.05 39 0.8 0.15 0.09 0.02<br />
Italy, Macerata Province 13 0.9 0.27 0.11 0.04 4 0.2 0.14 0.03 0.02<br />
Italy, Modena Province 18 0.8 0.19 0.09 0.02 4 0.2 0.08 0.02 0.01<br />
Italy, North East 133 2.4 0.22 0.29 0.03 34 0.5 0.09 0.05 0.01<br />
+* Important-See notes on population page<br />
595