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Srour B, Hüsing A, Gonzales Maldonado S, Kühn T, Kaaks R. Theoretical prediction of life expectancy using lifestyle factors in the EPIC-Heidelberg cohort. Eur J Public Health 2020. [DOI: 10.1093/eurpub/ckaa165.054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Background
The past few decades have witnessed a substantial increase in life expectancy in Western countries, leading to an increase in the prevalence of age-related chronic diseases. Several lifestyle risk factors (i.e. smoking, adiposity, unhealthy diet, heavy alcohol drinking and lack of physical activity) have been responsible for a large proportion of premature deaths, as they can affect the incidence of age-related chronic diseases. Our objective was to predict the loss of residual life expectancy (RLE) associated with these lifestyle factors, using data from the EPIC-Heidelberg cohort, linked to an up-to-date mortality registry.
Methods
A total of 23,324 German adults, aged 40 years and above were included (1994-1998) and followed until June 2019. A multi-adjusted parametric proportional hazard model (Gompertz hazard distribution), used to predict survival probabilities, followed by a life table approach was used.
Results
At age 40, being a heavy smoker (> 10 cigarettes/day) was associated with 10.5 y loss of RLE in men and 8.3 in women. Low body mass index (< 22.5 kg/m2) was associated with a RLE loss of 3.7 y in men and 1.4 y in women, while obesity was associated with 4.4 y in men and 3.8 y in women. Heavy alcohol drinking (> 4 drinks/day) was associated with a loss of 4.5 y in men, and high red/processed meat consumption (≥ 120 g/day) was associated with a loss of 1.1y in men and 2.1 y in women. Compared with an overall healthy lifestyle, combined unhealthy behaviors were associated with a loss of RLE of 21.4 y in men and 15.5 y in women.
Conclusions
Prevention strategies encouraging the adoption of an overall healthy lifestyle, particularly by avoiding smoking, heavy alcohol drinking, excess body fatness and reducing red/processed meat consumption, help reducing premature deaths. An extension of this project using blood biomarkers measures is ongoing.
Key messages
Adopting a healthy lifestyle by avoiding or reducing the exposure to risk factors might contribute to a longer life expectancy. Tobacco use, adiposity, and alcohol are probably the main modifiable lifestyle factors affecting life expectancy.
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Affiliation(s)
- B Srour
- Division of Cancer Epidemiology, German Cancer Research Center DKFZ, Heidelberg, Germany
| | - A Hüsing
- Division of Cancer Epidemiology, German Cancer Research Center DKFZ, Heidelberg, Germany
| | - S Gonzales Maldonado
- Division of Cancer Epidemiology, German Cancer Research Center DKFZ, Heidelberg, Germany
| | - T Kühn
- Division of Cancer Epidemiology, German Cancer Research Center DKFZ, Heidelberg, Germany
| | - R Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center DKFZ, Heidelberg, Germany
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Li K, Hüsing A, Fortner RT, Tjønneland A, Hansen L, Dossus L, Chang-Claude J, Bergmann M, Steffen A, Bamia C, Trichopoulos D, Trichopoulou A, Palli D, Mattiello A, Agnoli C, Tumino R, Onland-Moret NC, Peeters PH, Bueno-de-Mesquita HB, Gram IT, Weiderpass E, Sánchez-Cantalejo E, Chirlaque MD, Duell EJ, Ardanaz E, Idahl A, Lundin E, Khaw KT, Travis RC, Merritt MA, Gunter MJ, Riboli E, Ferrari P, Terry K, Cramer D, Kaaks R. An epidemiologic risk prediction model for ovarian cancer in Europe: the EPIC study. Br J Cancer 2015; 112:1257-65. [PMID: 25742479 PMCID: PMC4385951 DOI: 10.1038/bjc.2015.22] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2014] [Revised: 12/22/2014] [Accepted: 12/29/2014] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Ovarian cancer has a high case-fatality ratio, largely due to late diagnosis. Epidemiologic risk prediction models could help identify women at increased risk who may benefit from targeted prevention measures, such as screening or chemopreventive agents. METHODS We built an ovarian cancer risk prediction model with epidemiologic risk factors from 202,206 women in the European Prospective Investigation into Cancer and Nutrition study. RESULTS Older age at menopause, longer duration of hormone replacement therapy, and higher body mass index were included as increasing ovarian cancer risk, whereas unilateral ovariectomy, longer duration of oral contraceptive use, and higher number of full-term pregnancies were decreasing risk. The discriminatory power (overall concordance index) of this model, as examined with five-fold cross-validation, was 0.64 (95% confidence interval (CI): 0.57, 0.70). The ratio of the expected to observed number of ovarian cancer cases occurring in the first 5 years of follow-up was 0.90 (293 out of 324, 95% CI: 0.81-1.01), in general there was no evidence for miscalibration. CONCLUSION Our ovarian cancer risk model containing only epidemiological data showed modest discriminatory power for a Western European population. Future studies should consider adding informative biomarkers to possibly improve the predictive ability of the model.
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Affiliation(s)
- K Li
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - A Hüsing
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - R T Fortner
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - A Tjønneland
- The Danish Cancer Society Research Center, Copenhagen, Denmark
| | - L Hansen
- The Danish Cancer Society Research Center, Copenhagen, Denmark
| | - L Dossus
- Inserm, Centre for research in Epidemiology and Population Health (CESP), U1018, Nutrition, Hormones and Women's Health team, F-94805 Villejuif, France
- University Paris Sud, UMRS 1018, F-94805 Villejuif, France
| | - J Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - M Bergmann
- German Institute of Human Nutrition in Potsdam-Rehbruecke, Potsdam, Germany
| | - A Steffen
- German Institute of Human Nutrition in Potsdam-Rehbruecke, Potsdam, Germany
| | - C Bamia
- Department of Hygiene, Epidemiology and Medical Statistics, University of Athens Medical School, Athens, Greece
| | - D Trichopoulos
- Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA
- Bureau of Epidemiologic Research, Academy of Athens, Athens, Greece
- Hellenic Health Foundation, Athens, Greece
| | - A Trichopoulou
- Bureau of Epidemiologic Research, Academy of Athens, Athens, Greece
- Hellenic Health Foundation, Athens, Greece
| | - D Palli
- Molecular and Nutritional Epidemiology Unit, Cancer Research and Prevention Institute—ISPO, Florence, Italy
| | - A Mattiello
- Dipartimento di Medicina Clinica e Chirurgia, University of Naples Federico II, Naples, Italy
| | - C Agnoli
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - R Tumino
- Cancer Registry and Histopathology Unit, ‘Civic—M.P. Arezzo' Hospital, Ragusa, Italy
| | - N C Onland-Moret
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - P H Peeters
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - H B(as) Bueno-de-Mesquita
- Department for Determinants of Chronic Diseases (DCD), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - I T Gram
- Department of Community Medicine, Faculty of Health Sciences, The Arctic University of Norway, Tromsø, Norway
| | - E Weiderpass
- Department of Community Medicine, Faculty of Health Sciences, The Arctic University of Norway, Tromsø, Norway
- Department of Research, Cancer Registry of Norway, Oslo, Norway
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - E Sánchez-Cantalejo
- Escuela Andaluza de Salud Pública, Instituto de Investigación Biosanitaria de Granada (Granada.ibs), Granada, Spain
- CIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - M-D Chirlaque
- CIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Department of Epidemiology, Murcia Regional Health Authority, Murcia, Spain
| | - E J Duell
- Unit of Nutrition, Environment and Cancer Epidemiology Research Program, Bellvitge Biomedical Research Institute (IDIBELL), Catalan Institute of Oncology (ICO), Barcelona, Spain
| | - E Ardanaz
- CIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Navarre Public Health Institute, Pamplona, Spain
| | - A Idahl
- Department of Clinical Sciences, Obstetrics and Gynecology and Department of Public Health and Clinical Medicine, Nutritional Research Umeå University, Umeå, Sweden
| | - E Lundin
- Department of Medical Biosciences, Pathology Umeå University, Umeå, Sweden
| | - K-T Khaw
- University of Cambridge, School of Clinical Medicine, Cambridge, UK
| | - R C Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health University of Oxford, Oxford, UK
| | - M A Merritt
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, London, UK
| | - M J Gunter
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, London, UK
| | - E Riboli
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, London, UK
| | - P Ferrari
- International Agency for Research on Cancer, Lyon, France
| | - K Terry
- Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA
- Obstetrics and Gynecology Epidemiology Center, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - D Cramer
- Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA
- Obstetrics and Gynecology Epidemiology Center, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - R Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
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Beckmann L, Hüsing A, Setiawan VW, Amiano P, Clavel-Chapelon F, Chanock SJ, Cox DG, Diver R, Dossus L, Feigelson HS, Haiman C, Hallmans G, Hayes RB, Henderson BE, Hoover RN, Hunter DJ, Khaw K, Kolonel LN, Kraft P, Lund E, Le Marchand L, Peeters PHM, Riboli E, Stram D, Thomas G, Thun MJ, Tumino R, Trichopoulos D, Vogel U, Willett WC, Yeager M, Ziegler R, Hankinson SE, Kaaks R. Comprehensive analysis of hormone and genetic variation in 36 genes related to steroid hormone metabolism in pre- and postmenopausal women from the breast and prostate cancer cohort consortium (BPC3). J Clin Endocrinol Metab 2011; 96:E360-7. [PMID: 21177793 PMCID: PMC3048330 DOI: 10.1210/jc.2010-0912] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
CONTEXT Sex steroids play a central role in breast cancer development. OBJECTIVE This study aimed to relate polymorphic variants in 36 candidate genes in the sex steroid pathway to serum concentrations of sex steroid hormones and SHBG. DESIGN Data on 700 genetic polymorphisms were combined with existing hormone assays and data on breast cancer incidence, within the European Prospective Investigation into Cancer and Nutrition (EPIC) and the Nurses' Health Study (NHS) cohorts; significant findings were reanalyzed in the Multiethnic Cohort (MEC). SETTING AND PARTICIPANTS We analyzed data from a pooled sample of 3852 pre- and postmenopausal Caucasian women from EPIC and NHS and 454 postmenopausal women from MEC. MAIN OUTCOME MEASURES Outcome measures were SHBG, testosterone, dehydroepiandrosterone (DHEAS), androstenedione, estrone (E1), and estradiol (E2) as well as breast cancer risk. RESULTS Globally significant associations were found among pre- and postmenopausal women combined between levels of SHBG and the SHBG gene and between DHEAS and the FSHR and AKR1C3 genes. Among postmenopausal women, serum E1 and E2 were significantly associated with the genes CYP19 and FSHR, and E1 was associated with ESR1. None of the variants related to serum hormone levels showed any significant association with breast cancer risk. CONCLUSIONS We confirmed associations between serum levels of SHBG and the SHBG gene and of E1 and E2 and the CYP19 and ESR1 genes. Novel associations were observed between FSHR and DHEAS, E1, and E2 and between AKR1C3 and DHEAS.
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Affiliation(s)
- L Beckmann
- Division of Cancer Epidemiology, German Cancer Research Center, Im Neuenheimer Feld 581, 69120 Heidelberg, Germany
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Weiland SK, von Mutius E, Hirsch T, Duhme H, Fritzsch C, Werner B, Hüsing A, Stender M, Renz H, Leupold W, Keil U. Prevalence of respiratory and atopic disorders among children in the East and West of Germany five years after unification. Eur Respir J 1999; 14:862-70. [PMID: 10573234 DOI: 10.1034/j.1399-3003.1999.14d23.x] [Citation(s) in RCA: 194] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Living conditions in eastern Germany have changed rapidly since unification in 1990 and little is known about how these changes affect the prevalence of atopic diseases. This study describes methods and prevalences of a large epidemiological project investigating determinants of childhood asthma and allergies in eastern (Dresden and Leipzig) and western (Munich) Germany in 1995/1996. Community based random samples of 9-11 yr old children in Dresden (n=3,017) and Munich (n=2,612), and of 5-7 yr old children in Dresden (n=3,300), Leipzig (n=3,167) and Munich (n=2,165) were studied by parental questionnaires, bronchial challenges with hypertonic saline, skin examination, skin-prick tests, and measurements of specific and total serum immunoglobulin (Ig)E using Phase II modules of the International Study of Asthma and Allergies in Childhood (ISAAC). In 9-11 yr old children, the prevalence of physician diagnosed asthma (7.9% versus 10.3%; p<0.01) and bronchial hyperresponsiveness (15.7% versus 19.9%; p<0.05) was lower in Dresden than in Munich. No difference between Munich and Dresden was observed in the prevalence of diagnosed hay fever, skin test reactivity to > or = 1 allergen, and increased levels (>0.35 kU x L(-1)) of specific IgE against inhalant and food allergens. Symptoms and visible signs of atopic eczema tended to be more prevalent in Dresden. Similar East-West differences between the three study areas were seen in the younger age group. These findings are in line with recently observed increases in the prevalence of hay fever and atopic sensitization, but not of asthma and bronchial hyperresponsiveness, among 9-11 yr old children in Leipzig.
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Affiliation(s)
- S K Weiland
- Institute of Epidemiology and Social Medicine, University of Münster, Germany
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