| Literature DB >> 24993766 |
Pietro Ferrari1, Idlir Licaj1, David C Muller1, Per Kragh Andersen2, Mattias Johansson1, Heiner Boeing3, Elisabete Weiderpass4, Laure Dossus5, Laureen Dartois5, Guy Fagherazzi5, Kathryn E Bradbury6, Kay-Tee Khaw7, Nick Wareham8, Eric J Duell9, Aurelio Barricarte10, Esther Molina-Montes11, Carmen Navarro Sanchez12, Larraitz Arriola13, Peter Wallström14, Anne Tjønneland15, Anja Olsen15, Antonia Trichopoulou16, Vasiliki Benetou17, Dimitrios Trichopoulos18, Rosario Tumino19, Claudia Agnoli20, Carlotta Sacerdote21, Domenico Palli22, Kuanrong Li23, Rudolf Kaaks23, Petra Peeters24, Joline Wj Beulens24, Luciana Nunes25, Marc Gunter26, Teresa Norat26, Kim Overvad27, Paul Brennan1, Elio Riboli26, Isabelle Romieu1.
Abstract
OBJECTIVES: To investigate the role of factors that modulate the association between alcohol and mortality, and to provide estimates of absolute risk of death.Entities:
Keywords: Cardiology; Nutrition & Dietetics
Mesh:
Year: 2014 PMID: 24993766 PMCID: PMC4091394 DOI: 10.1136/bmjopen-2014-005245
Source DB: PubMed Journal: BMJ Open ISSN: 2044-6055 Impact factor: 2.692
Country-specific and sex-specific number of participants (N), person-years (PY), cause-specific and overall number of deaths
| N | PY | CHD* | CVD† | Cancers | Other cancers¶ | Violent and injuries** | Resp†† | Other causes‡‡ | Total | |||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Country | Breast | UADT‡ | Liver | Colon-rectum | Total§ | |||||||||
| Women | ||||||||||||||
| France | 65 127 | 971 127 | 45 | 202 | 62 | 8 | 4 | 27 | 101 | 678 | 115 | 73 | 1619 | 2833 |
| Italy | 24 956 | 306 244 | 26 | 87 | 71 | 6 | 12 | 53 | 142 | 293 | 30 | 12 | 120 | 710 |
| Spain | 23 616 | 323 027 | 41 | 50 | 51 | 6 | 9 | 47 | 113 | 243 | 46 | 9 | 119 | 621 |
| UK | 50 251 | 651 640 | 387 | 320 | 160 | 30 | 15 | 127 | 332 | 716 | 85 | 161 | 1091 | 3092 |
| The Netherlands | 14 583 | 189 531 | 110 | 137 | 58 | 14 | 7 | 78 | 157 | 370 | 20 | 65 | 209 | 1068 |
| Greece | 14 391 | 143 150 | 139 | 100 | 41 | 2 | 10 | 18 | 71 | 146 | 26 | 27 | 94 | 603 |
| Germany | 27 098 | 307 380 | 56 | 74 | 64 | 12 | 14 | 44 | 134 | 256 | 35 | 25 | 114 | 694 |
| Denmark | 27 773 | 328 375 | 84 | 143 | 128 | 23 | 17 | 110 | 278 | 648 | 51 | 116 | 548 | 1868 |
| All | 247 795 | 3 220 474 | 888 | 1113 | 635 | 101 | 88 | 504 | 1328 | 3335 | 408 | 488 | 3848 | 11 489 |
| Men | ||||||||||||||
| France | – | – | – | – | – | – | – | – | – | – | – | – | – | – |
| Italy | 13 471 | 168 992 | 53 | 59 | – | 8 | 10 | 39 | 57 | 240 | 35 | 13 | 131 | 588 |
| Spain | 14 089 | 189 942 | 136 | 88 | – | 34 | 14 | 62 | 110 | 351 | 81 | 42 | 151 | 959 |
| UK | 20 452 | 262 720 | 438 | 229 | – | 41 | 11 | 68 | 120 | 567 | 88 | 171 | 1040 | 2653 |
| The Netherlands | – | – | – | – | – | – | – | – | – | – | – | – | – | – |
| Greece | 9726 | 90 989 | 193 | 141 | – | 12 | 20 | 31 | 63 | 279 | 49 | 54 | 99 | 878 |
| Germany | 19 743 | 221 724 | 167 | 138 | – | 37 | 25 | 65 | 127 | 437 | 84 | 35 | 264 | 1253 |
| Denmark | 24 454 | 282 622 | 273 | 271 | – | 91 | 31 | 126 | 248 | 838 | 111 | 95 | 794 | 2633 |
| All | 101 935 | 1 216 988 | 1260 | 926 | – | 223 | 111 | 391 | 725 | 2712 | 448 | 410 | 2479 | 8964 |
*CHD, coronary heart disease (I20–I25) deaths.
†CVD, cardiovascular disease (I00–I99 except I20–I25) deaths.
‡UADT deaths from upper aerodigestive cancers (including cancer of the mouth (C01–C10 without C08=salivary gland)), larynx (C21), pharynx (C11–C14), oesophagus (C15)).
§Total frequency of alcohol-related cancers.
¶Other cancers: deaths from all other cancers.
**Violent deaths and injuries, including injury, poisoning and certain other consequences of external causes (S00–T98), and external causes of morbidity and mortality (V01–Y98).
††Resp=respiratory diseases (J00–J99).
‡‡All other causes of death.
Characteristics of the study population at recruitment, according to amount and type of alcohol intake (g/day) in the EPIC study*
| Characteristics | Unit | Never drinkers | Lifetime drinkers | Total‡ | Wine consumers§ | Beer consumers‡ | ||||
|---|---|---|---|---|---|---|---|---|---|---|
| 0.1–4.9 | 5–14.9 | 15–29.9 | 30–59.9† | >60† | ||||||
| Women | ||||||||||
| Number of participants | n | 25 146 | 112 281 | 77 147 | 27 179 | 6042 | – | 247 795 | 85 965 | 8748 |
| Person-years | – | 330 854 | 1 460 315 | 998 547 | 352 220 | 78 538 | – | 3 220 474 | 1 124 546 | 110 761 |
| Age at recruitment | Years | 52 (9) | 52 (10) | 51 (10) | 49 (11) | 47 (11) | – | 51 (38–63) | 52 (9) | 46 (12) |
| Lifetime alcohol intake | g/day | 0 (–) | 2 (2) | 9 (3) | 20 (4) | 43 (21) | – | 7 (0–17) | 12 (9) | 11 (9) |
| Educational attainment¶ | % | 14 | 22 | 27 | 33 | 37 | – | 25 | 28 | 28 |
| Current smokers | % | 13 | 14 | 18 | 24 | 31 | – | 17 | 17 | 28 |
| Body mass index | kg/m2 | 27 (5) | 25 (5) | 25 (4) | 24 (4) | 24 (4) | – | 25 (20–31) | 24 (4) | 25 (4) |
| Height | cm | 158 (6) | 161 (6) | 162 (6) | 163 (7) | 164 (6) | – | 162 (153–170) | 162 (6) | 163 (7) |
| (Moderately) active | % | 26 | 39 | 44 | 44 | 43 | – | 40 | 42 | 42 |
| Ever use of HRT** | % | 16 | 25 | 29 | 28 | 25 | – | 25 | 50 | 34 |
| Postmenopausal status†† | % | 50 | 49 | 49 | 44 | 38 | – | 48 | 29 | 20 |
| Energy intake | kcal/day | 1848 (537) | 1943 (537) | 2015 (536) | 2090 (552) | 2195 (602) | – | 1978 (542) | 2046 (544) | 1976 (545) |
| Men | ||||||||||
| Number of participants | n | 1600 | 14 287 | 28 875 | 28 049 | 20 788 | 8336 | 101 935 | 26 137 | 22 136 |
| Person-years | – | 19 114 | 171 739 | 345 899 | 333 784 | 247 612 | 98 841 | 1 216 989 | 317 937 | 259 934 |
| Age at recruitment | Years | 53 (11) | 53 (11) | 53 (9) | 52 (9) | 52 (9) | 52 (9) | 53 (41–64) | 53 (9) | 52 (10) |
| Lifetime alcohol intake | g/day | 0 (–) | 2 (2) | 10 (3) | 22 (4) | 42 (8) | 94 (45) | 25 (3–45) | 30 (27) | 22 (25) |
| Educational attainment¶ | % | 21 | 30 | 31 | 32 | 26 | 14 | 29 | 22 | 27 |
| Current smokers | % | 28 | 22 | 25 | 30 | 36 | 49 | 30 | 31 | 33 |
| Body mass index | kg/m2 | 27 (4) | 26 (4) | 26 (3) | 27 (3) | 27 (4) | 28 (4) | 27 (22–31) | 27 (4) | 27 (4) |
| Height | cm | 171 (7) | 174 (7) | 175 (7) | 175 (7) | 174 (7) | 172 (7) | 174 (165–183) | 172 (7) | 175 (7) |
| (Moderately) active | % | 42 | 46 | 50 | 52 | 52 | 50 | 50 | 48 | 52 |
| Energy intake | kcal/day | 2284 (675) | 2267 (650) | 2315 (618) | 2417 (622) | 2569 (646) | 2789 (716) | 2427 (656) | 2487 (652) | 2369 (651) |
*Means±SDs are presented for continuous variables, frequencies for categorical variables.
†In women the last alcohol category is ≥30 g/day.
‡For continuous variables (with exception of energy intake), mean (10–90th centile) values are reported.
§Study participants consuming more than 10 g/day of wine (or beer), and consuming less than 3 g/day of beer (or wine).
¶Participants with a university degree or more.
**HRT=hormonal replacement therapy.
††Postmenopausal women plus women who underwent an ovariectomy.
Figure 1Number of deaths, person-years (PY) and multivariable HRs (Models were stratified by centre. Systematic adjustment was undertaken for age at recruitment, body mass index and height, former drinking, time since alcohol quitting, smoking status, duration of smoking, age at start smoking, educational attainment and energy intake. In women adjustment was undertaken for menopausal status, ever use of replacement hormones and number of full-term pregnancies.) with 95% CIs and p value of the Wald test for statistical significance for overall and cause-specific mortality by categories of lifetime alcohol use, in women and men.
Sex-specific number of deaths, HR* and 95% CI for overall mortality by categories of lifetime alcohol use (g/day), by smoking status (never and current smokers), and type of alcoholic beverage
| Overall | Women | pheterog‡ | Overall | Men | pheterog‡ | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Never smokers | Current smokers | Never smokers | Current smokers | ||||||||||||
| Deaths | HR† | (95% CI) | Deaths | HR† | (95% CI) | Deaths | HR† | (95% CI) | Deaths | HR† | (95% CI) | ||||
| Never | 1009 | 1.34 | (1.24 to 1.45) | 154 | 1.72 | (1.32 to 2.23) | Never | 84 | 1.50 | (1.19 to 1.21) | 58 | 2.09 | (1.26 to 3.47) | ||
| 0.1–4.9 | 3046 | 1 | Ref | 1021 | 1.53 | (1.23 to 1.90) | 0.1–4.9 | 457 | 1 | Ref | 367 | 1.62 | (1.04 to 2.53) | ||
| 5–14.9 | 1550 | 1.04 | (0.98 to 1.11) | 874 | 1.51 | (1.21 to 1.88) | 5–14.9 | 538 | 0.93 | (0.82 to 1.06) | 799 | 1.45 | (0.93 to 2.25) | ||
| 15–29.9 | 397 | 1.04 | (0.94 to 1.16) | 435 | 1.74 | (1.38 to 2.19) | 15–29.9 | 369 | 1.00 | (0.87 to 1.16) | 927 | 1.66 | (1.06 to 2.58) | ||
| ≥ 30 | 82 | 1.29 | (1.03 to 1.61) | 140 | 2.08 | (1.59 to 2.73) | 30–59.9 | 254 | 1.22 | (1.23 to 1.43) | 857 | 1.83 | (1.17 to 2.84) | ||
| pWald§ | <0.001 | <0.001 | 0.150 | ≥ 60 | 107 | 1.56 | (1.25 to 1.95) | 590 | 2.43 | (1.55 to 3.80) | |||||
| pWald§ | <0.001 | <0.001 | 0.864 | ||||||||||||
|
|
| ||||||||||||||
| Never | 2156 | 1.15 | (1.09 to 1.22) | 5041 | 1.06 | (1.02 to 1.12) | Never | 1064 | 1.21 | (1.12 to 1.30) | 975 | 1.07 | (0.98 to 1.16) | ||
| 0.1–2.9 | 5109 | 1 | Ref | 5477 | 1 | Ref | 0.1–2.9 | 3266 | 1 | Ref | 2959 | 1 | Ref | ||
| 3–9.9 | 2813 | 0.96 | (0.92 to 1.01) | 787 | 1.15 | (1.07 to 1.24) | 3–9.9 | 2139 | 0.92 | (0.87 to 0.97) | 2486 | 1.04 | (0.98 to 1.10) | ||
| 10–19.9 | 1057 | 1.00 | (0.93 to 1.07) | 147 | 1.50 | (1.27 to 1.77) | 10–19.9 | 1040 | 0.96 | (0.89 to 1.03) | 1248 | 1.12 | (1.04 to 1.20) | ||
| ≥ 20 | 354 | 1.14 | (1.02 to 1.27) | 37 | 1.47 | (1.06 to 2.04) | 20–39.9 | 814 | 1.03 | (0.95 to 1.13) | 877 | 1.41 | (1.30 to 1.54) | ||
| pWald§ | <0.001 | <0.001 | <0.001 | ≥40 | 641 | 1.22 | (1.10 to 1.35) | 419 | 1.86 | (1.66 to 2.09) | |||||
| pWald§ | <0.001 | <0.001 | <0.001 | ||||||||||||
*Models were stratified by centre. Systematic adjustment was undertaken for age at recruitment, BMI and height, former drinking, time since alcohol quitting, smoking status, duration of smoking, age at start smoking, educational attainment and energy intake. In women adjustment was undertaken for menopausal status, ever use of replacement hormones and number of full-term pregnancies.
†Models included interaction terms between lifetime alcohol use and a smoking indicator (0=never smokers; 1=current smokers), keeping the reference category the group of moderate alcohol users (0.1–4.9 g/day) among never smokers, whereas former smokers and participants with unknown smoking status were excluded.
‡Pheterogeneity: difference in HRs assessed comparing the log-likelihood of models with and without interaction terms between alcohol and smoking status to a four and five degrees of freedom (dof) χ2 distribution, in women and men, respectively.
§pWald: determined using a Wald test for contrasts according to a χ2 distribution with four and five degrees of freedom, in women and men, respectively.
¶Models on wine and beer uses were mutually adjusted, and also included spirits/liquors use.
**pdifference expresses the difference of associations between wine and beer use, determined evaluating the significance of the parameter estimate γ2 in a model that included, other than the list of confounders, the terms γ1(X1+X2)/2+γ2(X1 − X2)/2, with X1=log(wine use+1) and X2=log(beer use+1).
Figure 2Sex-specific plots displaying cumulative probabilities of death due to overall mortality, for heavy (=30 g/day in women and=60 g/day in men, continuous line) and moderate lifetime use (0.1–4.9 g/day) (dotted line), in smokers (black line) and never smokers (grey line), for study participants aged 60 years.
Figure 3In competing risks analyses, sex-specific plots displaying cumulative probabilities of death due to CVD/CHD (red), alcohol-related cancers (blue) and violent death and injuries (green), for study participants aged 60 years according to heavy (=30 g/day in women and=60 g/day in men, continuous line) and moderate (0.1–4.9 g/day, dotted lines) lifetime alcohol use in current and never smokers in the EPIC study.
Sex-specific estimates of rate advancement period (RAP) and associated 95% CI for overall and mortality due to ARCs, CVD/CHD and injuries and violent deaths, related to two scenarios of lifetime alcohol use. RAP estimates express the impact of a given exposure on the risk of death, by determining the time (in years) by which the risk of death is anticipated for study participants exposed, for example, all drinkers more than the threshold (5 or 15 g/day in Scenarios I and II, respectively), compared to non-exposed, that is, individuals drinking between 0.1 g/day and the threshold*
| Scenario I | Scenario II | |||
|---|---|---|---|---|
| Threshold 5 g/day | Threshold 15 g/day | |||
| RAP (years) | 95% CI | RAP (years) | 95% CI | |
| Women | ||||
| Overall | 0.36 | −0.05 to 0.76 | 0.83 | 0.26 to 1.39 |
| CVD/CHD | 0.23 | −0.46 to 0.92 | 0.08 | −0.96 to 1.14 |
| Alcohol-related cancers | 1.28 | −0.86 to 3.41 | 1.90 | −1.00 to 4.81 |
| Injuries and violent deaths | −2.69 | −6.85 to 1.47 | −0.20 | −5.85 to 5.46 |
| Men | ||||
| Overall | 0.15 | −0.48 to 0.76 | 1.42 | 0.96 to 1.89 |
| CVD/CHD | −0.53 | −1.57 to 0.50 | −0.01 | −0.82 to 0.81 |
| Alcohol-related cancers | 2.59 | −0.30 to 5.49 | 5.03 | 3.07 to 7.00 |
| Injuries and violent deaths | 7.59 | −2.82 to 18.02 | 11.83 | 3.92 to 18.17 |
*Never lifetime alcohol users did not enter into the estimation process.
CVD/CHD, cardiovascular diseases coronary heart disease; RAP, rate advancement period.