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Milne RL, Fletcher AS, MacInnis RJ, Hodge AM, Hopkins AH, Bassett JK, Bruinsma FJ, Lynch BM, Dugué PA, Jayasekara H, Brinkman MT, Popowski LV, Baglietto L, Severi G, O'Dea K, Hopper JL, Southey MC, English DR, Giles GG. Cohort Profile: The Melbourne Collaborative Cohort Study (Health 2020). Int J Epidemiol 2018. [PMID: 28641380 DOI: 10.1093/ije/dyx085] [Citation(s) in RCA: 107] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Affiliation(s)
- R L Milne
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.,Centre for Epidemiology and Biostatistics, University of Melbourne, Parkville, VIC, Australia
| | - A S Fletcher
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
| | - R J MacInnis
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.,Centre for Epidemiology and Biostatistics, University of Melbourne, Parkville, VIC, Australia
| | - A M Hodge
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
| | - A H Hopkins
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
| | - J K Bassett
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
| | - F J Bruinsma
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
| | - B M Lynch
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.,Centre for Epidemiology and Biostatistics, University of Melbourne, Parkville, VIC, Australia.,Physical Activity Laboratory, Baker IDI Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - P A Dugué
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.,Centre for Epidemiology and Biostatistics, University of Melbourne, Parkville, VIC, Australia
| | - H Jayasekara
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.,Centre for Epidemiology and Biostatistics, University of Melbourne, Parkville, VIC, Australia
| | - M T Brinkman
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
| | - L V Popowski
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
| | - L Baglietto
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.,Centre for Epidemiology and Biostatistics, University of Melbourne, Parkville, VIC, Australia.,Centre de Recherche en Épidémiologie et Santé des Populations, Université Paris-Saclay, Villejuif, France.,Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - G Severi
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.,Centre for Epidemiology and Biostatistics, University of Melbourne, Parkville, VIC, Australia.,Centre de Recherche en Épidémiologie et Santé des Populations, Université Paris-Saclay, Villejuif, France.,Human Genetics Foundation (HuGeF), Turin, Italy
| | - K O'Dea
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.,Centre of Population Health Research, University of South Australia, Adelaide, SA, Australia
| | - J L Hopper
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.,Centre for Epidemiology and Biostatistics, University of Melbourne, Parkville, VIC, Australia
| | - M C Southey
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.,Genetic Epidemiology Laboratory, University of Melbourne, Parkville, VIC, Australia
| | - D R English
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.,Centre for Epidemiology and Biostatistics, University of Melbourne, Parkville, VIC, Australia
| | - G G Giles
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.,Centre for Epidemiology and Biostatistics, University of Melbourne, Parkville, VIC, Australia
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Brinkman MT, Kellen E, Zeegers MP, van Dongen MCJMS, Dagnelie PC, Muls E, Buntinx F. Validation of the IMMIDIET food frequency questionnaire in an adult Belgian population: a report from the Belgian case-control study on bladder cancer risk. Acta Clin Belg 2011; 66:18-25. [PMID: 21485759 DOI: 10.2143/acb.66.1.2062509] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
We evaluated the performance of the IMMIDIET food frequency questionnaire (FFQ) used to collect dietary data for the Belgian case-control study on bladder cancer. Thirty-seven men and women aged 50 years and older were recruited from the University Hospital in Leuven, Belgium. Participants completed the IMMIDIET FFQ, a 7-day diet diary and a 24-hour diet recall. Median intakes and inter-quartile ranges were calculated for 27 foods and nutrients from each dietary assessment method. All dietary factors were log-transformed and adjusted for energy using the nutrient density method. Pearson correlation coefficients were used to compare the different dietary assessment methods. Bland-Altman plots were also used to assess levels of agreement between the dietary methods. Energy, fruit and vegetable intake estimates were higher from the IMMIDIET FFQ compared with the two reference methods.The highest deattenuated correlations between the FFQ and 7-day diary were meat (0.58), bread (0.44), fruit (0.38) and fish (0.38). The highest deattenuated correlations between the FFQ and 24-hour recall were for fruit (0.72), fat (0.48), alcohol (0.44), cholesterol (0.42), monounsaturated fatty acid (0.42) and polyunsaturated fatty acid (0.41). Generally, correlation was lower for the micro-nutrients except for phosphorus (0.42), vitamin C (0.41) and calcium (0.40). The IMMIDIET FFQ is an appropriate instrument to measure usual dietary intake for the Belgian case-control study on bladder cancer risk. Further investigation of nutritional assessment methods is necessary.
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Affiliation(s)
- M T Brinkman
- Department of General Practice, Katholieke Universiteit Leuven-Comprehensive Cancer Institute, Limburg, Belgium
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Brinkman MT, Baglietto L, Krishnan K, English DR, Severi G, Morris HA, Hopper JL, Giles GG. Consumption of animal products, their nutrient components and postmenopausal circulating steroid hormone concentrations. Eur J Clin Nutr 2009; 64:176-83. [PMID: 19904296 DOI: 10.1038/ejcn.2009.129] [Citation(s) in RCA: 39] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
BACKGROUND/OBJECTIVES Little is known about nutritional factors that influence circulating concentrations of steroid hormones, which are consistently associated with risk of breast cancer for postmenopausal women. We aimed to investigate the association between consumption of animal products and the plasma concentrations of steroid hormones and sex hormone-binding globulin (SHBG). SUBJECTS/METHODS Cross-sectional analysis was conducted on plasma from 766 naturally postmenopausal women. We measured plasma concentrations of steroid hormones and SHBG, and estimated dietary intakes using a 121-item food frequency questionnaire. Log-transformed values of hormone concentrations were regressed on quartiles of intake of meat and dairy products among food items, and fats, proteins and cholesterol among nutrient intake. RESULTS Total red and fresh red meat consumption was negatively associated with SHBG levels (P for trend=0.04 and <0.01, respectively). Mean SHBG concentrations were approximately 8% and 13% lower for women in the highest quartile compared with the lowest quartile of total red and fresh red meat consumption, respectively. Positive associations were observed between dairy product consumption and total and free estradiol concentrations (P for trend=0.02 and 0.03, respectively). Mean concentrations of total and free estradiol were 15 and 14% higher for women in the highest quartile of dairy product consumption than for those in the lowest quartile, respectively. No associations were observed with consumption of processed meat, chicken, fish, eggs, cholesterol, fats or protein. CONCLUSIONS Our study suggests that greater consumption of total red and fresh red meat and dairy products might influence circulating concentrations of SHBG and estradiol, respectively. Confirmation and further investigation is required.
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Affiliation(s)
- M T Brinkman
- Cancer Epidemiology Centre, The Cancer Council Victoria, Melbourne, Australia.
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