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Tammi R, Kaartinen NE, Harald K, Maukonen M, Tapanainen H, Smith-Warner SA, Albanes D, Eriksson JG, Jousilahti P, Koskinen S, Laaksonen MA, Heikkinen S, Pitkäniemi J, Pajari AM, Männistö S. Partial substitution of red meat or processed meat with plant-based foods and the risk of colorectal cancer. Eur J Epidemiol 2024:10.1007/s10654-024-01096-7. [PMID: 38253935 DOI: 10.1007/s10654-024-01096-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 01/02/2024] [Indexed: 01/24/2024]
Abstract
OBJECTIVES Shifting from animal-based to plant-based diets could reduce colorectal cancer (CRC) incidence. Currently, the impacts of these dietary shifts on CRC risk are ill-defined. Therefore, we examined partial substitutions of red or processed meat with whole grains, vegetables, fruits or a combination of these in relation to CRC risk in Finnish adults. METHODS We pooled five Finnish cohorts, resulting in 43 788 participants aged ≥ 25 years (79% men). Diet was assessed by validated food frequency questionnaires at study enrolment. We modelled partial substitutions of red (100 g/week) or processed meat (50 g/week) with corresponding amounts of plant-based foods. Cohort-specific hazard ratios (HR) for CRC were calculated using Cox proportional hazards models and pooled together using random-effects models. Adjustments included age, sex, energy intake and other relevant confounders. RESULTS During the median follow-up of 28.8 years, 1124 CRCs were diagnosed. We observed small risk reductions when red meat was substituted with vegetables (HR 0.97, 95% CI 0.95 - 0.99), fruits (0.97, 0.94 - 0.99), or whole grains, vegetables and fruits combined (0.97, 0.95 - 0.99). For processed meat, these substitutions yielded 1% risk reductions. Substituting red or processed meat with whole grains was associated with a decreased CRC risk only in participants with < median whole grain intake (0.92, 0.86 - 0.98; 0.96, 0.93 - 0.99, respectively; pinteraction=0.001). CONCLUSIONS Even small, easily implemented substitutions of red or processed meat with whole grains, vegetables or fruits could lower CRC risk in a population with high meat consumption. These findings broaden our insight into dietary modifications that could foster CRC primary prevention.
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Affiliation(s)
- Rilla Tammi
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare (THL), P.O. Box 30, Helsinki, 00271, Finland.
| | - Niina E Kaartinen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare (THL), P.O. Box 30, Helsinki, 00271, Finland
| | - Kennet Harald
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare (THL), P.O. Box 30, Helsinki, 00271, Finland
| | - Mirkka Maukonen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare (THL), P.O. Box 30, Helsinki, 00271, Finland
| | - Heli Tapanainen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare (THL), P.O. Box 30, Helsinki, 00271, Finland
| | - Stephanie A Smith-Warner
- Departments of Nutrition and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health (NIH), Bethesda, MD, USA
| | - Johan G Eriksson
- Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Folkhälsan Research Center, University of Helsinki, Helsinki, Finland
- Department of Obstetrics and Gynaecology and Human Potential Translational Research programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Agency for Science, Technology and Research, Singapore Institute for Clinical Sciences (SICS), A*STAR, Singapore, Singapore
| | - Pekka Jousilahti
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare (THL), P.O. Box 30, Helsinki, 00271, Finland
| | - Seppo Koskinen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare (THL), P.O. Box 30, Helsinki, 00271, Finland
| | - Maarit A Laaksonen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare (THL), P.O. Box 30, Helsinki, 00271, Finland
- School of Public Health, Faculty of Medicine, University of Sydney, Sydney, NSW, Australia
| | - Sanna Heikkinen
- Finnish Cancer Registry, Institute for Statistical and Epidemiological Cancer Research, Helsinki, Finland
| | - Janne Pitkäniemi
- Finnish Cancer Registry, Institute for Statistical and Epidemiological Cancer Research, Helsinki, Finland
- Health Sciences Unit, Faculty of Social Sciences, Tampere University, Tampere, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Anne-Maria Pajari
- Department of Food and Nutrition, University of Helsinki, Helsinki, Finland
| | - Satu Männistö
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare (THL), P.O. Box 30, Helsinki, 00271, Finland
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Kaptoge S, Seshasai SRK, Sun L, Walker M, Bolton T, Spackman S, Ataklte F, Willeit P, Bell S, Burgess S, Pennells L, Altay S, Assmann G, Ben-Shlomo Y, Best LG, Björkelund C, Blazer DG, Brenner H, Brunner EJ, Dagenais GR, Cooper JA, Cooper C, Crespo CJ, Cushman M, D'Agostino RB, Daimon M, Daniels LB, Danker R, Davidson KW, de Jongh RT, Donfrancesco C, Ducimetiere P, Elders PJM, Engström G, Ford I, Gallacher I, Bakker SJL, Goldbourt U, de La Cámara G, Grimsgaard S, Gudnason V, Hansson PO, Imano H, Jukema JW, Kabrhel C, Kauhanen J, Kavousi M, Kiechl S, Knuiman MW, Kromhout D, Krumholz HM, Kuller LH, Laatikainen T, Lowler DA, Meyer HE, Mukamal K, Nietert PJ, Ninomiya T, Nitsch D, Nordestgaard BG, Palmieri L, Price JF, Ridker PM, Sun Q, Rosengren A, Roussel R, Sakurai M, Salomaa V, Schöttker B, Shaw JE, Strandberg TE, Sundström J, Tolonen H, Tverdal A, Verschuren WMM, Völzke H, Wagenknecht L, Wallace RB, Wannamethee SG, Wareham NJ, Wassertheil-Smoller S, Yamagishi K, Yeap BB, Harrison S, Inouye M, Griffin S, Butterworth AS, Wood AM, Thompson SG, Sattar N, Danesh J, Di Angelantonio E, Tipping RW, Russell S, Johansen M, Bancks MP, Mongraw-Chaffin M, Magliano D, Barr ELM, Zimmet PZ, Knuiman MW, Whincup PH, Willeit J, Willeit P, Leitner C, Lawlor DA, Ben-Shlomo Y, Elwood P, Sutherland SE, Hunt KJ, Cushman M, Selmer RM, Haheim LL, Ariansen I, Tybjaer-Hansen A, Frikkle-Schmidt R, Langsted A, Donfrancesco C, Lo Noce C, Balkau B, Bonnet F, Fumeron F, Pablos DL, Ferro CR, Morales TG, Mclachlan S, Guralnik J, Khaw KT, Brenner H, Holleczek B, Stocker H, Nissinen A, Palmieri L, Vartiainen E, Jousilahti P, Harald K, Massaro JM, Pencina M, Lyass A, Susa S, Oizumi T, Kayama T, Chetrit A, Roth J, Orenstein L, Welin L, Svärdsudd K, Lissner L, Hange D, Mehlig K, Salomaa V, Tilvis RS, Dennison E, Cooper C, Westbury L, Norman PE, Almeida OP, Hankey GJ, Hata J, Shibata M, Furuta Y, Bom MT, Rutters F, Muilwijk M, Kraft P, Lindstrom S, Turman C, Kiyama M, Kitamura A, Yamagishi K, Gerber Y, Laatikainen T, Salonen JT, van Schoor LN, van Zutphen EM, Verschuren WMM, Engström G, Melander O, Psaty BM, Blaha M, de Boer IH, Kronmal RA, Sattar N, Rosengren A, Nitsch D, Grandits G, Tverdal A, Shin HC, Albertorio JR, Gillum RF, Hu FB, Cooper JA, Humphries S, Hill- Briggs F, Vrany E, Butler M, Schwartz JE, Kiyama M, Kitamura A, Iso H, Amouyel P, Arveiler D, Ferrieres J, Gansevoort RT, de Boer R, Kieneker L, Crespo CJ, Assmann G, Trompet S, Kearney P, Cantin B, Després JP, Lamarche B, Laughlin G, McEvoy L, Aspelund T, Thorsson B, Sigurdsson G, Tilly M, Ikram MA, Dorr M, Schipf S, Völzke H, Fretts AM, Umans JG, Ali T, Shara N, Davey-Smith G, Can G, Yüksel H, Özkan U, Nakagawa H, Morikawa Y, Ishizaki M, Njølstad I, Wilsgaard T, Mathiesen E, Sundström J, Buring J, Cook N, Arndt V, Rothenbacher D, Manson J, Tinker L, Shipley M, Tabak AG, Kivimaki M, Packard C, Robertson M, Feskens E, Geleijnse M, Kromhout D. Life expectancy associated with different ages at diagnosis of type 2 diabetes in high-income countries: 23 million person-years of observation. Lancet Diabetes Endocrinol 2023; 11:731-742. [PMID: 37708900 PMCID: PMC7615299 DOI: 10.1016/s2213-8587(23)00223-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 07/14/2023] [Accepted: 07/14/2023] [Indexed: 09/16/2023]
Abstract
BACKGROUND The prevalence of type 2 diabetes is increasing rapidly, particularly among younger age groups. Estimates suggest that people with diabetes die, on average, 6 years earlier than people without diabetes. We aimed to provide reliable estimates of the associations between age at diagnosis of diabetes and all-cause mortality, cause-specific mortality, and reductions in life expectancy. METHODS For this observational study, we conducted a combined analysis of individual-participant data from 19 high-income countries using two large-scale data sources: the Emerging Risk Factors Collaboration (96 cohorts, median baseline years 1961-2007, median latest follow-up years 1980-2013) and the UK Biobank (median baseline year 2006, median latest follow-up year 2020). We calculated age-adjusted and sex-adjusted hazard ratios (HRs) for all-cause mortality according to age at diagnosis of diabetes using data from 1 515 718 participants, in whom deaths were recorded during 23·1 million person-years of follow-up. We estimated cumulative survival by applying age-specific HRs to age-specific death rates from 2015 for the USA and the EU. FINDINGS For participants with diabetes, we observed a linear dose-response association between earlier age at diagnosis and higher risk of all-cause mortality compared with participants without diabetes. HRs were 2·69 (95% CI 2·43-2·97) when diagnosed at 30-39 years, 2·26 (2·08-2·45) at 40-49 years, 1·84 (1·72-1·97) at 50-59 years, 1·57 (1·47-1·67) at 60-69 years, and 1·39 (1·29-1·51) at 70 years and older. HRs per decade of earlier diagnosis were similar for men and women. Using death rates from the USA, a 50-year-old individual with diabetes died on average 14 years earlier when diagnosed aged 30 years, 10 years earlier when diagnosed aged 40 years, or 6 years earlier when diagnosed aged 50 years than an individual without diabetes. Using EU death rates, the corresponding estimates were 13, 9, or 5 years earlier. INTERPRETATION Every decade of earlier diagnosis of diabetes was associated with about 3-4 years of lower life expectancy, highlighting the need to develop and implement interventions that prevent or delay the onset of diabetes and to intensify the treatment of risk factors among young adults diagnosed with diabetes. FUNDING British Heart Foundation, Medical Research Council, National Institute for Health and Care Research, and Health Data Research UK.
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Tammi R, Männistö S, Harald K, Maukonen M, Eriksson JG, Jousilahti P, Koskinen S, Kaartinen NE. Different carbohydrate exposures and weight gain-results from a pooled analysis of three population-based studies. Int J Obes (Lond) 2023:10.1038/s41366-023-01323-3. [PMID: 37149710 PMCID: PMC10359185 DOI: 10.1038/s41366-023-01323-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 04/25/2023] [Accepted: 04/27/2023] [Indexed: 05/08/2023]
Abstract
BACKGROUND The role of carbohydrate quantity and quality in weight gain remains unsolved, and research on carbohydrate subcategories is scarce. We examined total carbohydrates, dietary fiber, total sugar, and sucrose intake in relation to the risk of weight gain in Finnish adults. METHODS Our data comprised 8327 adults aged 25-70 years in three population-based prospective cohorts. Diet was assessed by a validated food frequency questionnaire and nutrient intakes were calculated utilizing the Finnish Food Composition Database. Anthropometric measurements were collected according to standard protocols. Two-staged pooling was applied to derive relative risks across cohorts for weight gain of at least 5% by exposure variable intake quintiles in a 7-year follow-up. Linear trends were examined based on a Wald test. RESULTS No association was observed between intakes of total carbohydrate, dietary fiber, total sugar or sucrose and the risk of weight gain of at least 5%. Yet, total sugar intake had a borderline protective association with the risk of weight gain in participants with obesity (RR 0.63; 95% CI 0.40-1.00 for highest vs. lowest quintile) and sucrose intake in participants with ≥10% decrease in carbohydrate intake during the follow-up (RR 0.78; 95% CI 0.61-1.00) after adjustments for sex, age, baseline weight, education, smoking, physical activity, and energy intake. Further adjustment for fruit consumption strengthened the associations. CONCLUSIONS Our findings do not support an association between carbohydrate intake and weight gain. However, the results suggested that concurrent changes in carbohydrate intake might be an important determinant of weight change and should be further examined in future studies.
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Affiliation(s)
- Rilla Tammi
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare (THL), Helsinki, Finland.
| | - Satu Männistö
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Kennet Harald
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Mirkka Maukonen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Johan G Eriksson
- Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Folkhälsan Research Center, University of Helsinki, Helsinki, Finland
- Department of Obstetrics and Gynecology and Human Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research, (A*STAR), Singapore, Singapore
| | - Pekka Jousilahti
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Seppo Koskinen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Niina E Kaartinen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare (THL), Helsinki, Finland
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Maukonen M, Harald K, Kaartinen NE, Tapanainen H, Albanes D, Eriksson J, Härkänen T, Jousilahti P, Koskinen S, Päivärinta E, Suikki T, Tolonen H, Pajari AM, Männistö S. Partial substitution of red or processed meat with plant-based foods and the risk of type 2 diabetes. Sci Rep 2023; 13:5874. [PMID: 37041301 PMCID: PMC10090151 DOI: 10.1038/s41598-023-32859-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 04/04/2023] [Indexed: 04/13/2023] Open
Abstract
High consumption of red and processed meat has been associated with increased type 2 diabetes (T2D) risk. These kinds of diets are also environmentally unsustainable. We examined a modeled association between a partial substitution of red meat or processed meat with plant-based foods (legumes, vegetables, fruit, cereals, or a combination of these) and T2D risk among Finnish adults. We used pooled data from five Finnish cohorts (n = 41,662, 22% women, aged ≥ 25 years, 10.9 years median follow-up with 1750 incident T2D cases). Diet was assessed by a validated food frequency questionnaire. In the substitution models, 100 g/week of red meat or 50 g/week of processed meat were substituted with similar amounts of plant-based substitutes. Cohort-specific hazard ratios (HRs) were estimated by Cox proportional hazards multivariable model and pooled using a two-staged random-effects model. We observed small, but statistically significant, reductions in T2D risk in men when red or processed meat were partially substituted with fruits (red meat: HR 0.98, 95% CI 0.97-1.00, P = 0.049, processed meat: 0.99, 0.98-1.00, P = 0.005), cereals (red meat: 0.97, 0.95-0.99, P = 0.005, processed meat: 0.99, 0.98-1.00, P = 0.004) or combination of plant-based foods (only processed meat: 0.99, 0.98-1.00, P = 0.004) but not with legumes or vegetables. The findings of women were similar but not statistically significant. Our findings suggest that even small, easily implemented, shifts towards more sustainable diets may reduce T2D risk particularly in men.
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Affiliation(s)
- Mirkka Maukonen
- Finnish Institute for Health and Welfare (THL), Mannerheimintie 166, PL 30, 00271, Helsinki, Finland.
| | - Kennet Harald
- Finnish Institute for Health and Welfare (THL), Mannerheimintie 166, PL 30, 00271, Helsinki, Finland
| | - Niina E Kaartinen
- Finnish Institute for Health and Welfare (THL), Mannerheimintie 166, PL 30, 00271, Helsinki, Finland
| | - Heli Tapanainen
- Finnish Institute for Health and Welfare (THL), Mannerheimintie 166, PL 30, 00271, Helsinki, Finland
| | | | - Johan Eriksson
- Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, 00014, Helsinki, Finland
- Folkhälsan Research Center, University of Helsinki, 00014, Helsinki, Finland
- Department of Obstetrics and Gynecology and Human Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research, (A*STAR), Singapore, Singapore
| | - Tommi Härkänen
- Finnish Institute for Health and Welfare (THL), Mannerheimintie 166, PL 30, 00271, Helsinki, Finland
| | - Pekka Jousilahti
- Finnish Institute for Health and Welfare (THL), Mannerheimintie 166, PL 30, 00271, Helsinki, Finland
| | - Seppo Koskinen
- Finnish Institute for Health and Welfare (THL), Mannerheimintie 166, PL 30, 00271, Helsinki, Finland
| | | | - Tiina Suikki
- Finnish Institute for Health and Welfare (THL), Mannerheimintie 166, PL 30, 00271, Helsinki, Finland
| | - Hanna Tolonen
- Finnish Institute for Health and Welfare (THL), Mannerheimintie 166, PL 30, 00271, Helsinki, Finland
| | | | - Satu Männistö
- Finnish Institute for Health and Welfare (THL), Mannerheimintie 166, PL 30, 00271, Helsinki, Finland
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Mäki P, Harald K, Lindström J, Männistö S, Laatikainen T. Association of adiposity with morbidity in Finnish adults: A register-based follow-up study. Scand J Public Health 2023:14034948221148053. [PMID: 36916274 DOI: 10.1177/14034948221148053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/16/2023]
Abstract
AIMS The aims of this study were to update risk estimates of obesity related co-morbidities and to provide evidence of the importance of obesity prevention to decision makers. METHODS The study included 25- to 74-year-old participants (N=22,977) of the National FINRISK Studies in 1997, 2002 and 2007. Body mass index was calculated from measured weight and height at baseline. Data on morbidity were ascertained via linkage to the National Hospital Discharge Register, the Cancer Register and the records of the Social Insurance Institution of Finland until the end of year 2018. The Cox proportional hazards model was used to estimate associations between weight status and the risk of the end-point diseases during follow-up, with adjustment for age and smoking. RESULTS At baseline, 31% of participants had at least one of the investigated diseases. Overweight, obesity and severe obesity were associated with type 2 diabetes, gout, gallbladder diseases and knee and hip osteoarthritis during the follow-up in both men and women. The risk of coronary heart disease was increased in men who were overweight, obese and severely obese and in women who were obese and severely obese. Risk of asthma was increased only among women who were obese and severely obese. No associations were found between obesity and breast, prostate or colorectal cancer. CONCLUSIONS
The study showed a strong relationship between excess body weight and the prevalence and incidence of several diseases. Obesity prevention is essential to reduce disease burden in the future.
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Affiliation(s)
- Päivi Mäki
- Finnish Institute for Health and Welfare, Finland
| | | | | | | | - Tiina Laatikainen
- Finnish Institute for Health and Welfare, Finland.,Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Finland.,Joint Municipal Authority for North Karelia Social and Health Services (Siun sote), Finland
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Abstract
AIMS The objective was to evaluate whether sodium intake, assessed with the gold standard 24-h urinary collections, was related to long-term incidence of death, cardiovascular disease (CVD) and diabetes mellitus (DM). METHODS A cohort of 4630 individuals aged 25-64 years collected 24-h urine samples in 1979-2002 and were followed up to 14 years for the incidence of any CVD, coronary heart disease (CHD), stroke, heart failure (HF) and DM event, and death. Cox proportional hazards models were used to estimate the association between the baseline salt intake and incident events and adjusted for baseline age, body mass index, serum cholesterol, prevalent DM, and stratified by sex and cohort baseline year. RESULTS During the follow-up, we observed 423 deaths, 424 CVD events (288 CHD events, 142 strokes, 139 HF events) and 161 DM events. Compared with the highest quartile of salt intake, persons in the lowest quartile had a lower incidence of CVD (hazard ratio [HR] 0.70; 95% confidence interval [CI], 0.51-0.95, p = .02), CHD (HR 0.63 [95% CI 0.42-0.94], p = .02) and DM (HR 0.52 [95% CI 0.31-0.87], p = .01). The results were non-significant for mortality, HF, and stroke. CONCLUSION High sodium intake is associated with an increased incidence of CVD and DM.
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Affiliation(s)
- Matti A Vuori
- Division of Medicine, University of Turku and Turku University Hospital, Turku, Finland.,Department of Public Health Solutions, Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Kennet Harald
- Department of Public Health Solutions, Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Antti Jula
- Department of Public Health Solutions, Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Liisa Valsta
- Department of Public Health Solutions, Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Tiina Laatikainen
- Department of Public Health Solutions, Finnish Institute for Health and Welfare (THL), Helsinki, Finland.,Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland.,Joint Municipal Authority for North Karelia Social and Health Services (Siun sote), Joensuu, Finland
| | - Veikko Salomaa
- Department of Public Health Solutions, Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Jaakko Tuomilehto
- Department of Public Health Solutions, Finnish Institute for Health and Welfare (THL), Helsinki, Finland.,Department of Public Health, University of Helsinki, Helsinki, Finland.,Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Pekka Jousilahti
- Department of Public Health Solutions, Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Teemu J Niiranen
- Division of Medicine, University of Turku and Turku University Hospital, Turku, Finland.,Department of Public Health Solutions, Finnish Institute for Health and Welfare (THL), Helsinki, Finland
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Jousilahti P, Laatikainen T, Harkanen T, Borodulin K, Harald K, Koskinen S, Mannisto S, Peltonen M, Sundvall J, Valsta L, Vartiainen E. P6222Changes in main CVD risk factors in Finland 1992–2017. Eur Heart J 2019. [DOI: 10.1093/eurheartj/ehz746.0826] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background
Systematic monitoring of cardiovascular disease (CVD) risk factors started in eastern Finland already in the 1970s as part of the North Karelia Project. Later on risk factor monitoring was extended to other parts of the country.
Purpose
In this study we report the trends of main CVD risk factors in Finland from 1992 to 2017.
Methods
Study population consists of a population-based random sample of 31 402 men and women aged 25–64 years who participated in the FINRISK Studies from 1992 to 2012, and in the FinHealth Study in 2017. Data collection was done every five years. Participation rate decreased from 76% in 1992 to 56% in 2017. Study protocol included self-reported questionnaire data on smoking and other health behavior, measurements of height, weight and blood pressure, and venous blood sample for laboratory analysis. Blood pressure was measured two times, and the average of the measurements was calculated, total serum cholesterol was analyzed using enzymatic method, and LDL cholesterol was calculated using Friedewald formula.
Results
Smoking prevalence, mean blood pressure and total and LDL cholesterol levels declined markedly during the 25 year follow up but BMI, waist circumference and prevalence of obesity increased (table).
CVD risk factor change from 1992 to 2017 Risk factor Men 1992 Men 2017 p value Women 1992 Women 2017 p value Smoking (%) 36.7 20.6 <0.001 25.9 16.5 <0.001 SBP (mmHg) 136.6 131.2 <0.001 130.3 124.5 <0.001 DBP (mmHg) 82.7 81.6 <0.001 78.6 77.8 <0.001 Chol (mmol/L) 5.66 5.17 <0.001 5.42 5.18 <0.001 LDL chol (mmol/L) 3.54 3.16 <0.001 3.26 3.03 <0.001 BMI (kg/m2) 26.2 27.2 <0.001 25.1 26.4 <0.001 WC (cm) 92.8 96.1 <0.001 79.2 86.2 <0.001 Obesity (%) 15.7 23.2 <0.001 14.8 22.7 <0.001
Conclusions
The levels of main traditional CVD risk factors have markedly decreased among the Finnish population during the last 25 years but in the same time, obesity has become a major public health challenge.
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Affiliation(s)
- P Jousilahti
- National Institute for Health and Welfare-THL, Helsinki, Finland
| | - T Laatikainen
- National Institute for Health and Welfare-THL, Helsinki, Finland
| | - T Harkanen
- National Institute for Health and Welfare-THL, Helsinki, Finland
| | - K Borodulin
- National Institute for Health and Welfare-THL, Helsinki, Finland
| | - K Harald
- National Institute for Health and Welfare-THL, Helsinki, Finland
| | - S Koskinen
- National Institute for Health and Welfare-THL, Helsinki, Finland
| | - S Mannisto
- National Institute for Health and Welfare-THL, Helsinki, Finland
| | - M Peltonen
- National Institute for Health and Welfare-THL, Helsinki, Finland
| | - J Sundvall
- National Institute for Health and Welfare-THL, Helsinki, Finland
| | - L Valsta
- National Institute for Health and Welfare-THL, Helsinki, Finland
| | - E Vartiainen
- National Institute for Health and Welfare-THL, Helsinki, Finland
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8
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Barengo NC, Antikainen R, Harald K, Jousilahti P. Smoking and cancer, cardiovascular and total mortality among older adults: The Finrisk Study. Prev Med Rep 2019; 14:100875. [PMID: 31061784 PMCID: PMC6488533 DOI: 10.1016/j.pmedr.2019.100875] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2018] [Revised: 04/17/2019] [Accepted: 04/22/2019] [Indexed: 12/03/2022] Open
Abstract
Little information is available about the deleterious effect of smoking in older adults The objective of this study was to assess the relationship of smoking habits with cancer, CVD and all-cause mortality in late middle-age (45–64 years) and older (65–74) people. This cohort study of 6516 men and 6514 women studied the relationship of smoking habits with cancer, cardiovascular disease (CVD) and all-cause mortality among middle-aged and older Finnish men and women during 1997–2013. The study cohort was followed up until the end of 2013 (median follow-up time was 11.8 years). Mortality data were obtained from the National Causes of Death Register and data on incident stroke events from the National Hospital Discharge Register. Adjusted Hazard ratios (HR) for total mortality were 2.61 (95% Confidence interval 2.15–3.18) among 45–64 years-old men and 2.59 (2.03–3.29) in 65–74 years-old men. The corresponding HRs for women 45–64 years-of-age were 3.21 (2.47–4.19) and 3.12 (2.09–4.68) for those 65–74 years-old, respectively. Adjusted HRs for CVD mortality in the 45–64 years-old and 65–74 years-old groups were 2.67 (1.92–2.67) and 1.95 (1.33–2.86) in men, and 4.28 (2.29–7.99) and 2.67 (1.28–5.58) in women, respectively. Among men, the risk difference between never and current smokers was 108/100.000 in the age-group 45–64 years, and 324/100.000 in the age group 65–74 years. Among women the differences were 52/100.000 and 196/100.000, respectively. In conclusion, absolute risk difference between never and current smokers are larger among the older age group. Smoking cessation counseling should routinely target also older adults in primary health-care.
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Affiliation(s)
- Noël C. Barengo
- Department of Medical and Population Health Sciences Research, Herbert Wertheim College of Medicine, Florida International University, Miami 33199, USA
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Corresponding author at: Department of Medical and Population Health Sciences Research, Herbert Wertheim College of Medicine, Florida International University, Miami, USA.
| | - Riitta Antikainen
- Center for Life Course Health Research/Geriatrics, Faculty of Medicine, University of Oulu, Oulu, Finland
- Medical Research Center Oulu, Oulu University Hospital, Oulu, Finland
- Oulu City Hospital, Oulu, Finland
| | - Kennet Harald
- Public Health Solutions Department, National Institute for Health and Welfare (THL)
| | - Pekka Jousilahti
- Public Health Solutions Department, National Institute for Health and Welfare (THL)
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9
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Mozaffarian D, Dashti HS, Wojczynski MK, Chu AY, Nettleton JA, Männistö S, Kristiansson K, Reedik M, Lahti J, Houston DK, Cornelis MC, van Rooij FJA, Dimitriou M, Kanoni S, Mikkilä V, Steffen LM, de Oliveira Otto MC, Qi L, Psaty B, Djousse L, Rotter JI, Harald K, Perola M, Rissanen H, Jula A, Krista F, Mihailov E, Feitosa MF, Ngwa JS, Xue L, Jacques PF, Perälä MM, Palotie A, Liu Y, Nalls NA, Ferrucci L, Hernandez D, Manichaikul A, Tsai MY, Kiefte-de Jong JC, Hofman A, Uitterlinden AG, Rallidis L, Ridker PM, Rose LM, Buring JE, Lehtimäki T, Kähönen M, Viikari J, Lemaitre R, Salomaa V, Knekt P, Metspalu A, Borecki IB, Cupples LA, Eriksson JG, Kritchevsky SB, Bandinelli S, Siscovick D, Franco OH, Deloukas P, Dedoussis G, Chasman DI, Raitakari O, Tanaka T. Genome-wide association meta-analysis of fish and EPA+DHA consumption in 17 US and European cohorts. PLoS One 2017; 12:e0186456. [PMID: 29236708 PMCID: PMC5728559 DOI: 10.1371/journal.pone.0186456] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2015] [Accepted: 09/14/2017] [Indexed: 01/17/2023] Open
Abstract
BACKGROUND Regular fish and omega-3 consumption may have several health benefits and are recommended by major dietary guidelines. Yet, their intakes remain remarkably variable both within and across populations, which could partly owe to genetic influences. OBJECTIVE To identify common genetic variants that influence fish and dietary eicosapentaenoic acid plus docosahexaenoic acid (EPA+DHA) consumption. DESIGN We conducted genome-wide association (GWA) meta-analysis of fish (n = 86,467) and EPA+DHA (n = 62,265) consumption in 17 cohorts of European descent from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium Nutrition Working Group. Results from cohort-specific GWA analyses (additive model) for fish and EPA+DHA consumption were adjusted for age, sex, energy intake, and population stratification, and meta-analyzed separately using fixed-effect meta-analysis with inverse variance weights (METAL software). Additionally, heritability was estimated in 2 cohorts. RESULTS Heritability estimates for fish and EPA+DHA consumption ranged from 0.13-0.24 and 0.12-0.22, respectively. A significant GWA for fish intake was observed for rs9502823 on chromosome 6: each copy of the minor allele (FreqA = 0.015) was associated with 0.029 servings/day (~1 serving/month) lower fish consumption (P = 1.96x10-8). No significant association was observed for EPA+DHA, although rs7206790 in the obesity-associated FTO gene was among top hits (P = 8.18x10-7). Post-hoc calculations demonstrated 95% statistical power to detect a genetic variant associated with effect size of 0.05% for fish and 0.08% for EPA+DHA. CONCLUSIONS These novel findings suggest that non-genetic personal and environmental factors are principal determinants of the remarkable variation in fish consumption, representing modifiable targets for increasing intakes among all individuals. Genes underlying the signal at rs72838923 and mechanisms for the association warrant further investigation.
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Affiliation(s)
- Dariush Mozaffarian
- Friedman School of Nutrition Science & Policy, Tufts University, Boston, MA, United States of America
- * E-mail:
| | - Hassan S Dashti
- Friedman School of Nutrition Science & Policy, Tufts University, Boston, MA, United States of America
- Nutrition and Genomics Laboratory, Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA, United States of America
| | - Mary K Wojczynski
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States of America
| | - Audrey Y Chu
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, United States of America
| | - Jennifer A Nettleton
- Division of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, TX, United States of America
| | - Satu Männistö
- National Institute for Health and Welfare, Helsinki, Finland
| | | | - Mägi Reedik
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Jari Lahti
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
- Folkhälsan Research Centre, Helsinki, Finland
| | - Denise K Houston
- Sticht Center on Aging, Wake Forest School of Medicine, Winston Salem, NC, United States of America
| | - Marilyn C Cornelis
- Department of Nutrition, Harvard School of Public Health, Boston, MA, United States of America
| | - Frank J. A van Rooij
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Netherlands Genomics Initiative-sponsored Netherlands Consortium for Healthy Aging, Leiden, The Netherlands
| | - Maria Dimitriou
- Department of Dietetics and Nutrition, Harokopio University, Athens, Greece
| | - Stavroula Kanoni
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Vera Mikkilä
- Department of Food and Environmental Sciences, University of Helsinki, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Lyn M Steffen
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN, United States of America
| | - Marcia C de Oliveira Otto
- Division of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, TX, United States of America
| | - Lu Qi
- Netherlands Genomics Initiative-sponsored Netherlands Consortium for Healthy Aging, Leiden, The Netherlands
| | - Bruce Psaty
- Department of Medicine, Epidemiology and Health Services, University of Washington, Seattle, WA, United States of America
| | - Luc Djousse
- Department of Medicine, Harvard Medical School, and Division of Aging Brigham and Women's Hospital, Boston, MA, United States of America
| | - Jerome I Rotter
- Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Los Angeles, CA, United States of America
| | - Kennet Harald
- National Institute for Health and Welfare, Helsinki, Finland
| | - Markus Perola
- National Institute for Health and Welfare, Helsinki, Finland
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- University of Tartu, Estonian Genome Center, Tartu, Estonia
| | - Harri Rissanen
- National Institute for Health and Welfare, Helsinki, Finland
| | - Antti Jula
- National Institute for Health and Welfare, Helsinki, Finland
| | - Fischer Krista
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | | | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States of America
| | - Julius S Ngwa
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States of America
- Division of Cardiovascular Medicine, Howard University College of Medicine, Washington DC, United States of America
| | - Luting Xue
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States of America
| | - Paul F Jacques
- Friedman School of Nutrition Science & Policy, Tufts University, Boston, MA, United States of America
- Nutritional Epidemiology Program, USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA, United States of America
| | - Mia-Maria Perälä
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Medical Genetics, University of Helsinki and University Central Hospital, Helsinki, Finland
| | - Yongmei Liu
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston Salem, NC, United States of America
| | - Nike A Nalls
- Laboratory of Neurogenetics, National Institute of Aging, Bethesda, MD, United States of America
| | - Luigi Ferrucci
- Clinical Research Branch, National Institute on Aging, Baltimore, MD, United States of America
| | - Dena Hernandez
- Laboratory of Neurogenetics, National Institute of Aging, Bethesda, MD, United States of America
| | - Ani Manichaikul
- Center for Public Health Genomics and Division of Biostatistics and Epidemiology, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, United States of America
| | - Michael Y Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, United States of America
| | - Jessica C Kiefte-de Jong
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Leiden University College, The Hague, The Netherlands
| | - Albert Hofman
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Netherlands Genomics Initiative-sponsored Netherlands Consortium for Healthy Aging, Leiden, The Netherlands
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - André G Uitterlinden
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Netherlands Genomics Initiative-sponsored Netherlands Consortium for Healthy Aging, Leiden, The Netherlands
| | - Loukianos Rallidis
- Second Department of Cardiology, University General Hospital Attikon, Athens, Greece
| | - Paul M Ridker
- National Institute for Health and Welfare, Helsinki, Finland
- Harvard Medical School, Boston MA, United States of America
| | - Lynda M Rose
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, United States of America
| | - Julie E Buring
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, United States of America
- Harvard Medical School, Boston MA, United States of America
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, University of Tampere School of Medicine, Tampere, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, University of Tampere and Tampere University Hospital, Tampere, Finland
| | - Jorma Viikari
- Department of Medicine, University of Turku and Turku University Hospital, Turku, Finland
| | - Rozenn Lemaitre
- Department of Medicine, University of Washington, Seattle, WA, United States of America
| | - Veikko Salomaa
- National Institute for Health and Welfare, Helsinki, Finland
| | - Paul Knekt
- National Institute for Health and Welfare, Helsinki, Finland
| | | | - Ingrid B Borecki
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States of America
| | - L. Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States of America
- NHLBI Framingham Heart Study, Framingham, MA, United States of America
| | - Johan G Eriksson
- National Institute for Health and Welfare, Helsinki, Finland
- Department of General Practice and Primary health Care, University of Helsinki, Helsinki, Finland
- Helsinki University Central Hospital, Unit of General Practice, Helsinki, Finland
| | - Stephen B Kritchevsky
- Sticht Center on Aging, Wake Forest School of Medicine, Winston Salem, NC, United States of America
| | | | - David Siscovick
- New York Academy of Medicine, New York, NY, United States of America
| | - Oscar H Franco
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Netherlands Genomics Initiative-sponsored Netherlands Consortium for Healthy Aging, Leiden, The Netherlands
| | - Panos Deloukas
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
- Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorder, King Abdulaziz University, Jeddah, Saudi Arabia
| | - George Dedoussis
- Department of Dietetics and Nutrition, Harokopio University, Athens, Greece
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, United States of America
- Harvard Medical School, Boston MA, United States of America
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Toshiko Tanaka
- Clinical Research Branch, National Institute on Aging, Baltimore, MD, United States of America
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10
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Jousilahti P, Harald K, Jula A, Laatikainen T, Mannisto S, Peltonen M, Perola M, Puska P, Salomaa V, Tuomilehto J, Valsta L, Vartiainen E. 1192Salt intake and the risk of heart failure. Eur Heart J 2017. [DOI: 10.1093/eurheartj/ehx502.1192] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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11
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Graff M, Scott RA, Justice AE, Young KL, Feitosa MF, Barata L, Winkler TW, Chu AY, Mahajan A, Hadley D, Xue L, Workalemahu T, Heard-Costa NL, den Hoed M, Ahluwalia TS, Qi Q, Ngwa JS, Renström F, Quaye L, Eicher JD, Hayes JE, Cornelis M, Kutalik Z, Lim E, Luan J, Huffman JE, Zhang W, Zhao W, Griffin PJ, Haller T, Ahmad S, Marques-Vidal PM, Bien S, Yengo L, Teumer A, Smith AV, Kumari M, Harder MN, Justesen JM, Kleber ME, Hollensted M, Lohman K, Rivera NV, Whitfield JB, Zhao JH, Stringham HM, Lyytikäinen LP, Huppertz C, Willemsen G, Peyrot WJ, Wu Y, Kristiansson K, Demirkan A, Fornage M, Hassinen M, Bielak LF, Cadby G, Tanaka T, Mägi R, van der Most PJ, Jackson AU, Bragg-Gresham JL, Vitart V, Marten J, Navarro P, Bellis C, Pasko D, Johansson Å, Snitker S, Cheng YC, Eriksson J, Lim U, Aadahl M, Adair LS, Amin N, Balkau B, Auvinen J, Beilby J, Bergman RN, Bergmann S, Bertoni AG, Blangero J, Bonnefond A, Bonnycastle LL, Borja JB, Brage S, Busonero F, Buyske S, Campbell H, Chines PS, Collins FS, Corre T, Smith GD, Delgado GE, Dueker N, Dörr M, Ebeling T, Eiriksdottir G, Esko T, Faul JD, Fu M, Færch K, Gieger C, Gläser S, Gong J, Gordon-Larsen P, Grallert H, Grammer TB, Grarup N, van Grootheest G, Harald K, Hastie ND, Havulinna AS, Hernandez D, Hindorff L, Hocking LJ, Holmens OL, Holzapfel C, Hottenga JJ, Huang J, Huang T, Hui J, Huth C, Hutri-Kähönen N, James AL, Jansson JO, Jhun MA, Juonala M, Kinnunen L, Koistinen HA, Kolcic I, Komulainen P, Kuusisto J, Kvaløy K, Kähönen M, Lakka TA, Launer LJ, Lehne B, Lindgren CM, Lorentzon M, Luben R, Marre M, Milaneschi Y, Monda KL, Montgomery GW, De Moor MHM, Mulas A, Müller-Nurasyid M, Musk AW, Männikkö R, Männistö S, Narisu N, Nauck M, Nettleton JA, Nolte IM, Oldehinkel AJ, Olden M, Ong KK, Padmanabhan S, Paternoster L, Perez J, Perola M, Peters A, Peters U, Peyser PA, Prokopenko I, Puolijoki H, Raitakari OT, Rankinen T, Rasmussen-Torvik LJ, Rawal R, Ridker PM, Rose LM, Rudan I, Sarti C, Sarzynski MA, Savonen K, Scott WR, Sanna S, Shuldiner AR, Sidney S, Silbernagel G, Smith BH, Smith JA, Snieder H, Stančáková A, Sternfeld B, Swift AJ, Tammelin T, Tan ST, Thorand B, Thuillier D, Vandenput L, Vestergaard H, van Vliet-Ostaptchouk JV, Vohl MC, Völker U, Waeber G, Walker M, Wild S, Wong A, Wright AF, Zillikens MC, Zubair N, Haiman CA, Lemarchand L, Gyllensten U, Ohlsson C, Hofman A, Rivadeneira F, Uitterlinden AG, Pérusse L, Wilson JF, Hayward C, Polasek O, Cucca F, Hveem K, Hartman CA, Tönjes A, Bandinelli S, Palmer LJ, Kardia SLR, Rauramaa R, Sørensen TIA, Tuomilehto J, Salomaa V, Penninx BWJH, de Geus EJC, Boomsma DI, Lehtimäki T, Mangino M, Laakso M, Bouchard C, Martin NG, Kuh D, Liu Y, Linneberg A, März W, Strauch K, Kivimäki M, Harris TB, Gudnason V, Völzke H, Qi L, Järvelin MR, Chambers JC, Kooner JS, Froguel P, Kooperberg C, Vollenweider P, Hallmans G, Hansen T, Pedersen O, Metspalu A, Wareham NJ, Langenberg C, Weir DR, Porteous DJ, Boerwinkle E, Chasman DI, Abecasis GR, Barroso I, McCarthy MI, Frayling TM, O’Connell JR, van Duijn CM, Boehnke M, Heid IM, Mohlke KL, Strachan DP, Fox CS, Liu CT, Hirschhorn JN, Klein RJ, Johnson AD, Borecki IB, Franks PW, North KE, Cupples LA, Loos RJF, Kilpeläinen TO. Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults. PLoS Genet 2017; 13:e1006528. [PMID: 28448500 PMCID: PMC5407576 DOI: 10.1371/journal.pgen.1006528] [Citation(s) in RCA: 119] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2016] [Accepted: 12/07/2016] [Indexed: 11/23/2022] Open
Abstract
Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.
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Affiliation(s)
- Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Robert A. Scott
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - Anne E. Justice
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Kristin L. Young
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Mary F. Feitosa
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Llilda Barata
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Thomas W. Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Audrey Y. Chu
- National Heart, Lung, and Blood Institute, Framingham Heart Study, Framingham, Massachusetts, United States of America
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
| | - Anubha Mahajan
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - David Hadley
- Division of Population Health Sciences and Education, St. George's, University of London, London, United Kingdom
| | - Luting Xue
- National Heart, Lung, and Blood Institute, Framingham Heart Study, Framingham, Massachusetts, United States of America
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Tsegaselassie Workalemahu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Nancy L. Heard-Costa
- National Heart, Lung, and Blood Institute, Framingham Heart Study, Framingham, Massachusetts, United States of America
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts, United States of America
| | - Marcel den Hoed
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
- Department of Immunology, Genetics and Pathology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Tarunveer S. Ahluwalia
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Steno Diabetes Center, Gentofte, Denmark
| | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, United States of America
| | - Julius S. Ngwa
- Howard University, Department of Internal Medicine, Washington DC, United States of America
| | - Frida Renström
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden
- Department of Biobank Research, Umeå University, Umeå, Sweden
| | - Lydia Quaye
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - John D. Eicher
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, The Framingham Heart Study, Framingham, Massachusetts, United States of America
| | - James E. Hayes
- Cell and Developmental Biology Graduate Program, Weill Cornell Graduate School of Medical Sciences, Cornell University, New York, New York, United States of America
- Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Marilyn Cornelis
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Zoltan Kutalik
- Institute of Social and Preventive Medicine, Lausanne University Hospital, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Elise Lim
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Jian’an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - Jennifer E. Huffman
- National Heart, Lung, and Blood Institute, Framingham Heart Study, Framingham, Massachusetts, United States of America
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
- Department of Cardiology, Ealing Hospital HNS Trust, Middlesex, United Kingdom
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Paula J. Griffin
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Toomas Haller
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Shafqat Ahmad
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden
| | - Pedro M. Marques-Vidal
- Department of Internal Medicine, Internal Medicine, Lausanne University Hospital, Lausanne, Switzerland
| | - Stephanie Bien
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Loic Yengo
- University of Lille, CNRS, Institut Pasteur de Lille, UMR 8199 - EGID, Lille, France
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Albert Vernon Smith
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Meena Kumari
- ISER, University of Essex, Colchester, Essex, United Kingdom
| | - Marie Neergaard Harder
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Johanne Marie Justesen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Marcus E. Kleber
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Institute of Nutrition, Friedrich Schiller University Jena, Jena, Germany
| | - Mette Hollensted
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Kurt Lohman
- Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Natalia V. Rivera
- Karolinska Institutet, Respiratory Unit, Department of Medicine Solna, Stockholm, Sweden
| | - John B. Whitfield
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Jing Hua Zhao
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - Heather M. Stringham
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, University of Tampere School of Medicine, Tampere, Finland
| | - Charlotte Huppertz
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
- EMGO+ Institute, Vrije Universiteit & VU University Medical Center, Amsterdam, The Netherlands
- Department of Public and Occupational Health, VU University Medical Center, Amsterdam, The Netherlands
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
- EMGO+ Institute, Vrije Universiteit & VU University Medical Center, Amsterdam, The Netherlands
| | - Wouter J. Peyrot
- Department of Psychiatry, EMGO Institute for Health and Care Research and Neuroscience Campus Amsterdam, VU University Medical Center/GGZ InGeest, Amsterdam, The Netherlands
| | - Ying Wu
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Kati Kristiansson
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Ayse Demirkan
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Myriam Fornage
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, Texas, United States of America
- Division of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Maija Hassinen
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Lawrence F. Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Gemma Cadby
- Centre for Genetic Origins of Health and Disease, University of Western Australia, Crawley, Western Australia, Australia
| | - Toshiko Tanaka
- Translational Gerontology Branch, National Institute on Aging, Baltimore, Maryland, United States of America
| | - Reedik Mägi
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Peter J. van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Anne U. Jackson
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Jennifer L. Bragg-Gresham
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Veronique Vitart
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Jonathan Marten
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Pau Navarro
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Claire Bellis
- Human Genetics, Genome Institute of Singapore, Agency for Science, Technology and Research of Singapore, Singapore
- Genomics Research Centre, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Dorota Pasko
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, United Kingdom
| | - Åsa Johansson
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Søren Snitker
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Yu-Ching Cheng
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
- Veterans Affairs Maryland Health Care System, University of Maryland, Baltimore, Maryland, United States of America
| | - Joel Eriksson
- Centre for Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Unhee Lim
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii, United States of America
| | - Mette Aadahl
- Research Centre for Prevention and Health, Glostrup University Hospital, Glostrup, Denmark
- Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Linda S. Adair
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Najaf Amin
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - Beverley Balkau
- INSERM U-1018, CESP, Renal and Cardiovascular Epidemiology, UVSQ-UPS, Villejuif, France
| | - Juha Auvinen
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Unit of Primary Care, Oulu University Hospital, Oulu, Finland
| | - John Beilby
- Busselton Population Medical Research Institute, Nedlands, Western Australia, Australia
- PathWest Laboratory Medicine of WA, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- School of Pathology and Laboratory Medicine, The University of Western Australia, Crawley, Western Australia, Australia
| | - Richard N. Bergman
- Diabetes and Obesity Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
| | - Sven Bergmann
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
| | - Alain G. Bertoni
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - John Blangero
- Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Amélie Bonnefond
- University of Lille, CNRS, Institut Pasteur de Lille, UMR 8199 - EGID, Lille, France
| | - Lori L. Bonnycastle
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland, United States of America
| | - Judith B. Borja
- USC-Office of Population Studies Foundation, Inc., University of San Carlos, Cebu City, Philippines
- Department of Nutrition and Dietetics, University of San Carlos, Cebu City, Philippines
| | - Søren Brage
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - Fabio Busonero
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale Delle Ricerche (CNR), Cittadella Universitaria di Monserrato, Monserrato, Italy
| | - Steve Buyske
- Department of Genetics, Rutgers University, Piscataway, New Jersey, United States of America
- Department of Statistics and Biostatistics, Rutgers University, Piscataway, New Jersey, United States of America
| | - Harry Campbell
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, Edinburgh, Scotland
| | - Peter S. Chines
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland, United States of America
| | - Francis S. Collins
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland, United States of America
| | - Tanguy Corre
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
| | - George Davey Smith
- MRC Integrative Epidemiology Unit & School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Graciela E. Delgado
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Nicole Dueker
- University of Maryland School of Medicine, Department of Epidemiology & Public Health, Baltimore, Maryland, United States of America
| | - Marcus Dörr
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Tapani Ebeling
- Department of Medicine, Oulu University Hospital, Oulu, Finland
- Institute of Clinical Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland
| | | | - Tõnu Esko
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Division of Endocrinology, Boston Children's Hospital, Boston, Massachusetts, United States of America
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts, United States of America
| | - Jessica D. Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Mao Fu
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | | | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Sven Gläser
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Jian Gong
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Penny Gordon-Larsen
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Harald Grallert
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Tanja B. Grammer
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Gerard van Grootheest
- Department of Psychiatry, EMGO Institute for Health and Care Research and Neuroscience Campus Amsterdam, VU University Medical Center/GGZ InGeest, Amsterdam, The Netherlands
| | - Kennet Harald
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
| | - Nicholas D. Hastie
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Aki S. Havulinna
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
| | - Dena Hernandez
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, Maryland, United States of America
| | - Lucia Hindorff
- Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Lynne J. Hocking
- Musculoskeletal Research Programme, Division of Applied Medicine, University of Aberdeen, Foresterhill, Aberdeen, United Kingdom
- Generation Scotland, Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | | | - Christina Holzapfel
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Nutritional Medicine, Klinikum Rechts der Isar, Technische Universität München, Munich, Germany
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
- NCA Institute, VU University & VU Medical Center, Amsterdam, The Netherlands
| | - Jie Huang
- Department of Human Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
| | - Tao Huang
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Jennie Hui
- Busselton Population Medical Research Institute, Nedlands, Western Australia, Australia
- PathWest Laboratory Medicine of WA, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- School of Population Health, The University of Western Australia, Crawley, Western Australia, Australia
| | - Cornelia Huth
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Nina Hutri-Kähönen
- Department of Pediatrics, Tampere University Hospital, Tampere, Finland
- Department of Pediatrics, University of Tampere School of Medicine, Tampere, Finland
| | - Alan L. James
- Busselton Population Medical Research Institute, Nedlands, Western Australia, Australia
- Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- School of Medicine and Pharmacology, The University of Western Australia, Crawley, Western Australia, Australia
| | - John-Olov Jansson
- Department of Physiology, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Min A. Jhun
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Markus Juonala
- Department of Medicine, University of Turku, Turku, Finland
- Division of Medicine, Turku University Hospital, Turku, Finland
| | - Leena Kinnunen
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
| | - Heikki A. Koistinen
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
- Department of Medicine and Abdominal Center: Endocrinology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland
- Minerva Foundation Institute for Medical Research, Helsinki, Finland
| | - Ivana Kolcic
- Department of Public Health, Faculty of Medicine, University of Split, Split, Croatia
| | | | - Johanna Kuusisto
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Kirsti Kvaløy
- HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, Levanger, Norway
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland
- Department of Clinical Physiology, University of Tampere School of Medicine, Tampere, Finland
| | - Timo A. Lakka
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Institute of Biomedicine, Physiology, University of Eastern Finland, Kuopio Campus, Finland
| | - Lenore J. Launer
- Neuroepidemiology Section, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Benjamin Lehne
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Cecilia M. Lindgren
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America
- The Big Data Institute, University of Oxford, Oxford, United Kingdom
| | - Mattias Lorentzon
- Centre for Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Geriatric Medicine, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Robert Luben
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Michel Marre
- INSERM U-1138, Équipe 2: Pathophysiology and Therapeutics of Vascular and Renal diseases Related to Diabetes, Centre de Recherche des Cordeliers, Paris, France
- Department of Endocrinology, Diabetology, Nutrition, and Metabolic Diseases, Bichat Claude Bernard Hospital, Paris, France
| | - Yuri Milaneschi
- Department of Psychiatry, EMGO Institute for Health and Care Research and Neuroscience Campus Amsterdam, VU University Medical Center/GGZ InGeest, Amsterdam, The Netherlands
| | - Keri L. Monda
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Center for Observational Research, Amgen Inc., Thousand Oaks, California, United States of America
| | - Grant W. Montgomery
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Marleen H. M. De Moor
- EMGO+ Institute, Vrije Universiteit & VU University Medical Center, Amsterdam, The Netherlands
- Section of Clinical Child and Family Studies, Department of Educational and Family Studies, Vrije Universiteit, Amsterdam, The Netherlands
| | - Antonella Mulas
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale Delle Ricerche (CNR), Cittadella Universitaria di Monserrato, Monserrato, Italy
- Dipartimento di Scienze Biomediche, Università degli Studi di Sassari, Sassari, Italy
| | - Martina Müller-Nurasyid
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Department of Medicine I, Ludwig-Maximilians-Universität, Munich, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany
| | - A. W. Musk
- Busselton Population Medical Research Institute, Nedlands, Western Australia, Australia
- School of Population Health, The University of Western Australia, Crawley, Western Australia, Australia
- Department of Respiratory Medicine, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
| | - Reija Männikkö
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Satu Männistö
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
| | - Narisu Narisu
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland, United States of America
| | - Matthias Nauck
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Jennifer A. Nettleton
- Division of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Ilja M. Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Albertine J. Oldehinkel
- Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Matthias Olden
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Ken K. Ong
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - Sandosh Padmanabhan
- Generation Scotland, Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
- Institute of Cardiovascular and Medical Sciences, BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, United Kingdom
| | - Lavinia Paternoster
- MRC Integrative Epidemiology Unit & School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Jeremiah Perez
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Markus Perola
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- University of Tartu, Estonian Genome Centre, Tartu, Estonia
| | - Annette Peters
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Patricia A. Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Inga Prokopenko
- Genomics of Common Disease, Imperial College London, London, United Kingdom
| | | | - Olli T. Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Tuomo Rankinen
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, Louisiana, United States of America
| | - Laura J. Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
| | - Rajesh Rawal
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Paul M. Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Lynda M. Rose
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
| | - Igor Rudan
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, Edinburgh, Scotland
| | - Cinzia Sarti
- Social Services and Health Care Department, City of Helsinki, Helsinki, Finland
| | - Mark A. Sarzynski
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, Louisiana, United States of America
| | - Kai Savonen
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - William R. Scott
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Serena Sanna
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale Delle Ricerche (CNR), Cittadella Universitaria di Monserrato, Monserrato, Italy
| | - Alan R. Shuldiner
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
- Veterans Affairs Maryland Health Care System, University of Maryland, Baltimore, Maryland, United States of America
| | - Steve Sidney
- Division of Research, Kaiser Permanente Northern California, Oakland, California, United States of America
| | - Günther Silbernagel
- Division of Angiology, Department of Internal Medicine, Medical University Graz, Austria
| | - Blair H. Smith
- Generation Scotland, Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
- School of Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee, Scotland
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Alena Stančáková
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Barbara Sternfeld
- Division of Research, Kaiser Permanente Northern California, Oakland, California, United States of America
| | - Amy J. Swift
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland, United States of America
| | - Tuija Tammelin
- LIKES Research Center for Sport and Health Sciences, Jyväskylä, Finland
| | - Sian-Tsung Tan
- National Heart and Lung Institute, Imperial College London, United Kingdom
| | - Barbara Thorand
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Dorothée Thuillier
- University of Lille, CNRS, Institut Pasteur de Lille, UMR 8199 - EGID, Lille, France
| | - Liesbeth Vandenput
- Centre for Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Henrik Vestergaard
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Steno Diabetes Center, Gentofte, Denmark
| | - Jana V. van Vliet-Ostaptchouk
- Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Marie-Claude Vohl
- Institute of Nutrition and Functional Foods, Quebec, Canada
- School of Nutrition, Laval University, Quebec, Canada
| | - Uwe Völker
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Germany
| | - Gérard Waeber
- Department of Internal Medicine, Internal Medicine, Lausanne University Hospital, Lausanne, Switzerland
| | - Mark Walker
- Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Sarah Wild
- Centre for Population Health Sciences, Usher Institute for Population Health Sciences and Informatics, Teviot Place, Edinburgh, Scotland
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, London, United Kingdom
| | - Alan F. Wright
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | | | - Niha Zubair
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Christopher A. Haiman
- Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Loic Lemarchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii, United States of America
| | - Ulf Gyllensten
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Claes Ohlsson
- Centre for Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Albert Hofman
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Aging, Leiden University Medical Center, Leiden, The Netherlands
| | - Fernando Rivadeneira
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Aging, Leiden University Medical Center, Leiden, The Netherlands
| | - André G. Uitterlinden
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - Louis Pérusse
- Institute of Nutrition and Functional Foods, Quebec, Canada
- Department of Kinesiology, Laval University, Quebec, Canada
| | - James F. Wilson
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, Edinburgh, Scotland
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Ozren Polasek
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, Edinburgh, Scotland
- Department of Public Health, Faculty of Medicine, University of Split, Split, Croatia
| | - Francesco Cucca
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale Delle Ricerche (CNR), Cittadella Universitaria di Monserrato, Monserrato, Italy
- Dipartimento di Scienze Biomediche, Università degli Studi di Sassari, Sassari, Italy
| | - Kristian Hveem
- HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, Levanger, Norway
| | - Catharina A. Hartman
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Anke Tönjes
- University of Leipzig, Medical Department, Leipzig, Germany
| | | | - Lyle J. Palmer
- School of Public Health, University of Adelaide, Adelaide, South Australia, Australia
| | - Sharon L. R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Rainer Rauramaa
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Thorkild I. A. Sørensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- MRC Integrative Epidemiology Unit & School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
- Department of Clinical Epidemiology, Bispebjerg and Frederiksberg Hospitals, The Capital Region, Copenhagen, Denmark
| | - Jaakko Tuomilehto
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
- Centre for Vascular Prevention, Danube-University Krems, Krems, Austria
- Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Veikko Salomaa
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
| | - Brenda W. J. H. Penninx
- Department of Psychiatry, EMGO Institute for Health and Care Research and Neuroscience Campus Amsterdam, VU University Medical Center/GGZ InGeest, Amsterdam, The Netherlands
| | - Eco J. C. de Geus
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
- EMGO+ Institute, Vrije Universiteit & VU University Medical Center, Amsterdam, The Netherlands
| | - Dorret I. Boomsma
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
- NCA Institute, VU University & VU Medical Center, Amsterdam, The Netherlands
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, University of Tampere School of Medicine, Tampere, Finland
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
- National Institute for Health Research Biomedical Research Centre at Guy's and St. Thomas' Foundation Trust, London, United Kingdom
| | - Markku Laakso
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Claude Bouchard
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, Louisiana, United States of America
| | - Nicholas G. Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing at UCL, London, United Kingdom
| | - Yongmei Liu
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Allan Linneberg
- Research Centre for Prevention and Health, Glostrup University Hospital, Glostrup, Denmark
- Department of Clinical Experimental Research, Rigshospitalet, Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Winfried März
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Synlab Academy, Synlab Services LLC, Mannheim, Germany
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany
| | - Mika Kivimäki
- Department of Epidemiology and Public Health, University College London, London, United Kingdom
| | - Tamara B. Harris
- Laboratory of Epidemiology and Population Science, National Institute on Aging, Bethesda, Maryland, United States of America
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Lu Qi
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Marjo-Riitta Järvelin
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Unit of Primary Care, Oulu University Hospital, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
- MRC-PHE Centre for Environment and Health, Imperial College London, London, United Kingdom
| | - John C. Chambers
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
- Department of Cardiology, Ealing Hospital HNS Trust, Middlesex, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Jaspal S. Kooner
- Department of Cardiology, Ealing Hospital HNS Trust, Middlesex, United Kingdom
- National Heart and Lung Institute, Imperial College London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Philippe Froguel
- University of Lille, CNRS, Institut Pasteur de Lille, UMR 8199 - EGID, Lille, France
- Hammersmith Hospital, London, United Kingdom
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Peter Vollenweider
- Department of Internal Medicine, Internal Medicine, Lausanne University Hospital, Lausanne, Switzerland
| | - Göran Hallmans
- Department of Biobank Research, Umeå University, Umeå, Sweden
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Nicholas J. Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - David R. Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, United States of America
| | - David J. Porteous
- Generation Scotland, Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Eric Boerwinkle
- Division of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Daniel I. Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | | | | | | | - Gonçalo R. Abecasis
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Inês Barroso
- Wellcome Trust Sanger Institute, Hinxton, United Kingdom
- NIHR Cambridge Biomedical Research Centre, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, United Kingdom
- The University of Cambridge Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, Cambridge, United Kingdom
| | - Mark I. McCarthy
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, United Kingdom
- Oxford NIHR Biomedical Research Centre, Oxford, United Kingdom
| | - Timothy M. Frayling
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, United Kingdom
| | - Jeffrey R. O’Connell
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Cornelia M. van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Aging, Leiden University Medical Center, Leiden, The Netherlands
- Center of Medical Systems Biology, Leiden, The Netherlands
| | - Michael Boehnke
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Iris M. Heid
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Karen L. Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - David P. Strachan
- Population Health Research Institute, St. George's University of London, London, United Kingdom
| | - Caroline S. Fox
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, The Framingham Heart Study, Framingham, Massachusetts, United States of America
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Joel N. Hirschhorn
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts, United States of America
- Divisions of Endocrinology and Genetics and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, Massachusetts, United States of America
| | - Robert J. Klein
- Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Andrew D. Johnson
- National Heart, Lung, and Blood Institute, Framingham Heart Study, Framingham, Massachusetts, United States of America
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, The Framingham Heart Study, Framingham, Massachusetts, United States of America
| | - Ingrid B. Borecki
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Paul W. Franks
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden
- Department of Public Health & Clinical Medicine, Umeå University, Umeå, Sweden
| | - Kari E. North
- Carolina Center for Genome Sciences, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - L. Adrienne Cupples
- National Heart, Lung, and Blood Institute, Framingham Heart Study, Framingham, Massachusetts, United States of America
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Ruth J. F. Loos
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
- Genetics of Obesity and Related Metabolic Traits Program, Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- The Department of Preventive Medicine, The Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Tuomas O. Kilpeläinen
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Department of Preventive Medicine, The Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
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Kaartinen NE, Similä ME, Kanerva N, Valsta LM, Harald K, Männistö S. Naturally occurring and added sugar in relation to macronutrient intake and food consumption: results from a population-based study in adults. J Nutr Sci 2017; 6:e7. [PMID: 28620482 PMCID: PMC5465852 DOI: 10.1017/jns.2017.3] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2016] [Accepted: 01/16/2017] [Indexed: 01/16/2023] Open
Abstract
Associations between sugar intake and the remaining diet are poorly described in modern food environments. We aimed at exploring associations of high naturally occurring and added sugar intakes with sociodemographic characteristics, intake of macronutrients, fibre and selected food groups. Our data comprised 4842 Finnish adults aged 25-74 years, who participated in the population-based DIetary, Lifestyle and Genetic determinants of Obesity and Metabolic syndrome (DILGOM) study. Diet was assessed by a validated 131-item FFQ. The food item disaggregation approach was used to estimate sucrose and fructose intakes from natural sources (naturally occurring sugar) and all other sources (added sugar). Sex-specific trends in macronutrient, fibre and food group intakes across sugar type quartiles were determined with general linear modelling adjusting for age, energy intake, leisure-time physical activity, smoking, education and BMI. Overall, results were similar across sexes. Young age was found to be a determinant of higher added sugar and lower naturally occurring sugar intakes (P < 0·0001). High added sugar intake was associated with low fibre intake (P < 0·0001) accompanied with lower fruit (P < 0·0001 women; P = 0·022 men) and vegetable consumption (P < 0·0001) and higher wheat consumption (P = 0·0003 women; P < 0·0001 men). Opposite results were found for naturally occurring sugar. Butter consumption increased by 28-32 % (P < 0·0001) when shifting from the lowest to the highest added sugar intake quartile, while a decrease of 26-38 % (P < 0·0001) was found for naturally occurring sugar. Therefore, the associations of sugar types with dietary carbohydrate and fat quality seem opposing. Proper adjustments with dietary variables are needed when studying independent relationships between sugar and health.
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Affiliation(s)
- Niina E. Kaartinen
- Department of Health, National Institute for Health and Welfare, PO Box 30, FI-00271 Helsinki, Finland
| | - Minna E. Similä
- Department of Health, National Institute for Health and Welfare, PO Box 30, FI-00271 Helsinki, Finland
| | - Noora Kanerva
- Department of Health, National Institute for Health and Welfare, PO Box 30, FI-00271 Helsinki, Finland
| | - Liisa M. Valsta
- Department of Health, National Institute for Health and Welfare, PO Box 30, FI-00271 Helsinki, Finland
| | - Kennet Harald
- Department of Health, National Institute for Health and Welfare, PO Box 30, FI-00271 Helsinki, Finland
| | - Satu Männistö
- Department of Health, National Institute for Health and Welfare, PO Box 30, FI-00271 Helsinki, Finland
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Barengo NC, Antikainen R, Borodulin K, Harald K, Jousilahti P. Leisure-Time Physical Activity Reduces Total and Cardiovascular Mortality and Cardiovascular Disease Incidence in Older Adults. J Am Geriatr Soc 2016; 65:504-510. [PMID: 28024086 DOI: 10.1111/jgs.14694] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
OBJECTIVES To determine whether leisure-time physical activity (LTPA) is independently associated with all-cause and cardiovascular mortality and with incidence of cardiovascular disease (CVD) and stroke in older adults. DESIGN Population-based cohort study (median follow-up 11.8 years). SETTING Community, five Finnish provinces. PARTICIPANTS Men and women aged 65 to 74 who participated in a baseline risk factor survey between 1997 and 2007 in Finland (N = 2,456). MEASUREMENTS The study protocol included a self-administered questionnaire, health examination at the study site, and blood sample for laboratory analysis. LTPA was classified into three levels: low, moderate, high. Mortality data were obtained from the National Causes of Death Register and data on incident CVD (coronary heart disease, stroke) events from the National Hospital Discharge Register. RESULTS Multifactorial-adjusted (age, area, study year, sex, smoking, body mass index, systolic blood pressure, serum cholesterol, education, marital status) risks of total mortality (moderate: hazard ratio (HR) = 0.61, 95% confidence interval (CI) = 0.50-0.74; high: HR = 0.47, 95% CI = 0.34-0.63, P for trend <.001), CVD mortality (moderate: HR = 0.46, 95% CI = 0.33-0.64; high: HR = 0.34, 95% CI = 0.20-0.59, P for trend <.001), and an incident CVD event (moderate HR = 0.69, 95% CI = 0.54-0.88; high: HR = 0.55, 95% CI = 0.38-0.79, P for trend <.001) were lower for those with moderate or high LTPA levels than for those with low LTPA levels. Further adjustment for self-reported inability to perform LTPA did not change the associations remarkably. CONCLUSIONS Baseline LTPA reduces the risk of total and CVD mortality and incident CVD events in older adults independently of the major known CVD risk factors. The protective effect of LTPA is dose dependent.
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Affiliation(s)
- Noël C Barengo
- Department of Medical and Population Health Sciences Research, Herbert Wertheim College of Medicine, Florida International University, Miami, Florida.,Clinicum, Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Riitta Antikainen
- Center for Life Course Health Research/Geriatrics, Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center Oulu, Oulu University Hospital, Oulu, Finland.,Oulu City Hospital, Oulu, Finland
| | - Katja Borodulin
- Department of Health, National Institute for Health and Welfare, Helsinki, Finland
| | - Kennet Harald
- Department of Health, National Institute for Health and Welfare, Helsinki, Finland
| | - Pekka Jousilahti
- Department of Health, National Institute for Health and Welfare, Helsinki, Finland
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14
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Jousilahti P, Laatikainen T, Peltonen M, Borodulin K, Männistö S, Jula A, Salomaa V, Harald K, Puska P, Vartiainen E. Primary prevention and risk factor reduction in coronary heart disease mortality among working aged men and women in eastern Finland over 40 years: population based observational study. BMJ 2016; 352:i721. [PMID: 26932978 PMCID: PMC4772739 DOI: 10.1136/bmj.i721] [Citation(s) in RCA: 70] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/26/2015] [Indexed: 12/22/2022]
Abstract
OBJECTIVE To estimate how much changes in the main risk factors of cardiovascular disease (smoking prevalence, serum cholesterol, and systolic blood pressure) can explain the reduction in coronary heart disease mortality observed among working aged men and women in eastern Finland. DESIGN Population based observational study. SETTING Eastern Finland. PARTICIPANTS 34,525 men and women aged 30-59 years who participated in the national FINRISK studies between 1972 and 2012. INTERVENTIONS Change in main cardiovascular risk factors through population based primary prevention. MAIN OUTCOME MEASURES Predicted and observed age standardised mortality due to coronary heart disease. Predicted change was estimated with a logistic regression model using risk factor data collected in nine consecutive, population based, risk factor surveys conducted every five years since 1972. Data on observed mortality were obtained from the National Causes of Death Register. RESULTS During the 40 year study period, levels of the three major cardiovascular risk factors decreased except for a small increase in serum cholesterol levels between 2007 and 2012. From years 1969-1972 to 2012, coronary heart disease mortality decreased by 82% (from 643 to 118 deaths per 100,000 people) and 84% (114 to 17) among men and women aged 35-64 years, respectively. During the first 10 years of the study, changes in these three target risk factors contributed to nearly all of the observed mortality reduction. Since the mid-1980s, the observed reduction in mortality has been larger than predicted. In the last 10 years of the study, about two thirds (69% in men and 66% in women) of the reduction could be explained by changes in the three main risk factors, and the remaining third by other factors. CONCLUSION Reductions in disease burden and mortality due to coronary heart disease can be achieved through the use of population based primary prevention programmes. Secondary prevention among high risk individuals and treatment of acute events of coronary heart disease could confer additional benefit.
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Affiliation(s)
- Pekka Jousilahti
- National Institute for Health and Welfare, Department of Health, PO Box 30, 00271 Helsinki, Finland
| | - Tiina Laatikainen
- University of Eastern Finland, Institute of Public Health and Clinical Nutrition, Kuopio, Finland
| | - Markku Peltonen
- National Institute for Health and Welfare, Department of Health, PO Box 30, 00271 Helsinki, Finland
| | - Katja Borodulin
- National Institute for Health and Welfare, Department of Health, PO Box 30, 00271 Helsinki, Finland
| | - Satu Männistö
- National Institute for Health and Welfare, Department of Health, PO Box 30, 00271 Helsinki, Finland
| | - Antti Jula
- National Institute for Health and Welfare, Department of Health, PO Box 30, 00271 Helsinki, Finland
| | - Veikko Salomaa
- National Institute for Health and Welfare, Department of Health, PO Box 30, 00271 Helsinki, Finland
| | - Kennet Harald
- National Institute for Health and Welfare, Department of Health, PO Box 30, 00271 Helsinki, Finland
| | - Pekka Puska
- National Institute for Health and Welfare, Department of Health, PO Box 30, 00271 Helsinki, Finland
| | - Erkki Vartiainen
- National Institute for Health and Welfare, Department of Health, PO Box 30, 00271 Helsinki, Finland
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15
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Männistö S, Harald K, Kanerva N, Borodulin K, Kaartinen N, Jousilahti P. Who are Obese? Prevalence and Lifestyle Characteristics Associated with Normal-Weight Obesity in the National FINRISK 2012 Study (Finland). Int J Epidemiol 2015. [DOI: 10.1093/ije/dyv096.401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
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Nettleton JA, Follis JL, Ngwa JS, Smith CE, Ahmad S, Tanaka T, Wojczynski MK, Voortman T, Lemaitre RN, Kristiansson K, Nuotio ML, Houston DK, Perälä MM, Qi Q, Sonestedt E, Manichaikul A, Kanoni S, Ganna A, Mikkilä V, North KE, Siscovick DS, Harald K, Mckeown NM, Johansson I, Rissanen H, Liu Y, Lahti J, Hu FB, Bandinelli S, Rukh G, Rich S, Booij L, Dmitriou M, Ax E, Raitakari O, Mukamal K, Männistö S, Hallmans G, Jula A, Ericson U, Jacobs DR, Van Rooij FJA, Deloukas P, Sjögren P, Kähönen M, Djousse L, Perola M, Barroso I, Hofman A, Stirrups K, Viikari J, Uitterlinden AG, Kalafati IP, Franco OH, Mozaffarian D, Salomaa V, Borecki IB, Knekt P, Kritchevsky SB, Eriksson JG, Dedoussis GV, Qi L, Ferrucci L, Orho-Melander M, Zillikens MC, Ingelsson E, Lehtimäki T, Renström F, Cupples LA, Loos RJF, Franks PW. Gene × dietary pattern interactions in obesity: analysis of up to 68 317 adults of European ancestry. Hum Mol Genet 2015; 24:4728-38. [PMID: 25994509 PMCID: PMC4512626 DOI: 10.1093/hmg/ddv186] [Citation(s) in RCA: 78] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2015] [Accepted: 05/17/2015] [Indexed: 11/14/2022] Open
Abstract
Obesity is highly heritable. Genetic variants showing robust associations with obesity traits have been identified through genome-wide association studies. We investigated whether a composite score representing healthy diet modifies associations of these variants with obesity traits. Totally, 32 body mass index (BMI)- and 14 waist-hip ratio (WHR)-associated single nucleotide polymorphisms were genotyped, and genetic risk scores (GRS) were calculated in 18 cohorts of European ancestry (n = 68 317). Diet score was calculated based on self-reported intakes of whole grains, fish, fruits, vegetables, nuts/seeds (favorable) and red/processed meats, sweets, sugar-sweetened beverages and fried potatoes (unfavorable). Multivariable adjusted, linear regression within each cohort followed by inverse variance-weighted, fixed-effects meta-analysis was used to characterize: (a) associations of each GRS with BMI and BMI-adjusted WHR and (b) diet score modification of genetic associations with BMI and BMI-adjusted WHR. Nominally significant interactions (P = 0.006-0.04) were observed between the diet score and WHR-GRS (but not BMI-GRS), two WHR loci (GRB14 rs10195252; LYPLAL1 rs4846567) and two BMI loci (LRRN6C rs10968576; MTIF3 rs4771122), for the respective BMI-adjusted WHR or BMI outcomes. Although the magnitudes of these select interactions were small, our data indicated that associations between genetic predisposition and obesity traits were stronger with a healthier diet. Our findings generate interesting hypotheses; however, experimental and functional studies are needed to determine their clinical relevance.
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Affiliation(s)
- Jennifer A Nettleton
- Division of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas, Health Science Center, Houston, TX, USA
| | - Jack L Follis
- Department of Mathematics, University of St. Thomas, Houston, TX, USA
| | - Julius S Ngwa
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Caren E Smith
- Jean Mayer USDA Human Nutrition Research Center on Aging, Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
| | - Shafqat Ahmad
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit
| | - Toshiko Tanaka
- Clinical Research Branch, National Institute on Aging, Baltimore, MD, USA
| | - Mary K Wojczynski
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Trudy Voortman
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands, Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands
| | | | | | - Marja-Liisa Nuotio
- Unit of Public Health Genomics, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Tukholmankatu 8, Helsinki 00290, Finland
| | | | - Mia-Maria Perälä
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Haartmaninkatu 8, Helsinki 00290, Finland
| | - Qibin Qi
- Department of Nutrition, Harvard Chan School of Public Health, Boston, MA, USA, Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Emily Sonestedt
- Department of Clinical Sciences-Malmö, Lund University, Malmö, Sweden
| | - Ani Manichaikul
- Center for Public Health Genomics, Department of Public Health Sciences, Division of Biostatistics and Epidemiology, University of Virginia, Charlottesville, VA, USA
| | - Stavroula Kanoni
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Andrea Ganna
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Vera Mikkilä
- Department of Food and Environmental Sciences, Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Kari E North
- Department of Epidemiology and Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC, USA
| | | | - Kennet Harald
- THL-National Institute for Health and Welfare, Mannerheimintie 166, Helsinki 00300, Finland
| | - Nicola M Mckeown
- Jean Mayer USDA Human Nutrition Research Center on Aging, Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
| | | | - Harri Rissanen
- THL-National Institute for Health and Welfare, Mannerheimintie 166, Helsinki 00300, Finland
| | - Yongmei Liu
- Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston Salem, NC, USA
| | - Jari Lahti
- Institute of Behavioral Sciences, Folkhälsan Research Centre, Helsinki, Finland
| | - Frank B Hu
- Department of Nutrition, Harvard Chan School of Public Health, Boston, MA, USA
| | | | - Gull Rukh
- Department of Clinical Sciences-Malmö, Lund University, Malmö, Sweden
| | | | - Lisanne Booij
- Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Maria Dmitriou
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece
| | - Erika Ax
- Department of Public Health and Caring Sciences, Clinical Nutrition and Metabolism
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland, Department of Clinical Physiology and Nuclear Medicine
| | - Kenneth Mukamal
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Satu Männistö
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Haartmaninkatu 8, Helsinki 00290, Finland
| | - Göran Hallmans
- Department of Public Health and Clinical Medicine, Nutritional Research
| | - Antti Jula
- THL-National Institute for Health and Welfare, Mannerheimintie 166, Helsinki 00300, Finland
| | - Ulrika Ericson
- Department of Clinical Sciences-Malmö, Lund University, Malmö, Sweden
| | - David R Jacobs
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Frank J A Van Rooij
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands, Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands
| | - Panos Deloukas
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
| | - Per Sjögren
- Department of Public Health and Caring Sciences, Clinical Nutrition and Metabolism
| | - Mika Kähönen
- Department of Clinical Physiology, University of Tampere and Tampere University Hospital, Tampere, Finland
| | - Luc Djousse
- Division of Aging, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA, Harvard Medical School and Boston VA Healthcare System, Boston, MA, USA
| | - Markus Perola
- Unit of Public Health Genomics, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Tukholmankatu 8, Helsinki 00290, Finland, University of Tartu, Estonian Genome Center, Ülikooli 18, Tartu 50090, Estonia
| | - Inês Barroso
- Metabolic Disease Group, Wellcome Trust Sanger Institute, Hinxton, UK, University of Cambridge Metabolic Research Labs, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
| | - Albert Hofman
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands, Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands
| | - Kathleen Stirrups
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Jorma Viikari
- Department of Medicine, University of Turku and Division of Medicine, Turku University Hospital, Turku, Finland
| | - André G Uitterlinden
- Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Ioanna P Kalafati
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece
| | - Oscar H Franco
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands, Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands
| | - Dariush Mozaffarian
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
| | - Veikko Salomaa
- THL-National Institute for Health and Welfare, Mannerheimintie 166, Helsinki 00300, Finland
| | - Ingrid B Borecki
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Paul Knekt
- THL-National Institute for Health and Welfare, Mannerheimintie 166, Helsinki 00300, Finland
| | | | - Johan G Eriksson
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Haartmaninkatu 8, Helsinki 00290, Finland, Folkhälsan Research Centre, Helsinki, Finland, Department of General Practice and Primary Health Care, Institute of Clinical Medicine, University of Helsinki, Helsinki, Finland, Unit of General Practice, Helsinki University Central Hospital, Helsinki, Finland
| | - George V Dedoussis
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece
| | - Lu Qi
- Department of Nutrition, Harvard Chan School of Public Health, Boston, MA, USA
| | - Luigi Ferrucci
- Clinical Research Branch, National Institute on Aging, Baltimore, MD, USA
| | | | - M Carola Zillikens
- Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Erik Ingelsson
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and School of Medicine, University of Tampere, Tampere, Finland
| | - Frida Renström
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Department of Biobank Research
| | - L Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Ruth J F Loos
- The Genetics of Obesity and Related Metabolic Traits Program, The Charles Bronfman Institute for Personalized Medicine and The Mindich Child Health and Development Institute, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Paul W Franks
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Department of Nutrition, Harvard Chan School of Public Health, Boston, MA, USA, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden,
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Wikström K, Lindström J, Harald K, Peltonen M, Laatikainen T. Clinical and lifestyle-related risk factors for incident multimorbidity: 10-year follow-up of Finnish population-based cohorts 1982-2012. Eur J Intern Med 2015; 26:211-6. [PMID: 25747490 DOI: 10.1016/j.ejim.2015.02.012] [Citation(s) in RCA: 81] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/30/2014] [Revised: 02/06/2015] [Accepted: 02/10/2015] [Indexed: 12/11/2022]
Abstract
BACKGROUND Multimorbidity is a huge burden to individuals and societies and more attention should be paid on its risk factors and prevention possibilities. The aim of this study was to investigate which clinical and lifestyle characteristics predict the development of multimorbidity both among initially disease-free people and among people who have diabetes or CVD. METHODS Data comprised 25-64 year old, randomly selected men and women (n=32,972) who participated in one of the five national FINRISK surveys between 1982 and 2002 in Finland. The surveys included anthropometric measurements, blood samples and structured questionnaire. Data on incident diagnoses of the five most common chronic diseases during 10 years were received from the national registers on mortality, hospitalizations, and reimbursement rights. RESULTS Predisposing factors for multimorbidity among disease-free population were smoking, physical inactivity, and BMI. Among men also systolic blood pressure and low education predicted multimorbidity. Among men with DM at baseline, high blood pressure, physical inactivity, and smoking increased the likelihood of incident multimorbidity. Among women, significant predictors of multimorbidity were high BMI and smoking. Among men and women with CVD, the only baseline factor that was significantly associated with the development of multimorbidity in the multivariate prediction model was low fruit and vegetable consumption. CONCLUSION Several modifiable clinical and lifestyle risk factors were found to predict incident multimorbidity. Better recognition and management of these risk factors could potentially have a large impact on the development of multimorbidity, and consequently, premature mortality and costs of care among the aging populations.
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Affiliation(s)
- Katja Wikström
- National Institute for Health and Welfare, Department of Chronic Disease Prevention, PO Box 30, 00271 Helsinki, Finland.
| | - Jaana Lindström
- National Institute for Health and Welfare, Department of Chronic Disease Prevention, PO Box 30, 00271 Helsinki, Finland
| | - Kennet Harald
- National Institute for Health and Welfare, Department of Chronic Disease Prevention, PO Box 30, 00271 Helsinki, Finland
| | - Markku Peltonen
- National Institute for Health and Welfare, Department of Chronic Disease Prevention, PO Box 30, 00271 Helsinki, Finland
| | - Tiina Laatikainen
- National Institute for Health and Welfare, Department of Chronic Disease Prevention, PO Box 30, 00271 Helsinki, Finland; Institute of Public Health and Clinical Nutrition, University of Eastern Finland, PO Box 1627, Kuopio, Finland; Hospital District of North Karelia, Tikkamäentie 16, Joensuu, Finland
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Borodulin K, Harald K, Jousilahti P, Laatikainen T, Männistö S, Vartiainen E. Time trends in physical activity from 1982 to 2012 in Finland. Scand J Med Sci Sports 2015; 26:93-100. [DOI: 10.1111/sms.12401] [Citation(s) in RCA: 53] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/04/2014] [Indexed: 11/28/2022]
Affiliation(s)
- K. Borodulin
- National Institute for Health and Welfare; Helsinki Finland
| | - K. Harald
- National Institute for Health and Welfare; Helsinki Finland
| | - P. Jousilahti
- National Institute for Health and Welfare; Helsinki Finland
| | - T. Laatikainen
- National Institute for Health and Welfare; Helsinki Finland
- Institute of Public Health and Clinical Nutrition; University of Eastern Finland; Joensuu Finland
- Hospital District of North Karelia; Joensuu Finland
| | - S. Männistö
- National Institute for Health and Welfare; Helsinki Finland
| | - E. Vartiainen
- National Institute for Health and Welfare; Helsinki Finland
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19
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Valkeinen H, Harald K, Borodulin K, Mäkinen TE, Heliövaara M, Leino-Arjas P, Sainio P, Kestilä L, Kunst A, Rahkonen O, Tammelin T, Härkänen T, Prättälä R. Educational differences in estimated and measured physical fitness. Eur J Public Health 2013; 23:998-1002. [PMID: 23729485 DOI: 10.1093/eurpub/ckt049] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Available information about the association between education and physical fitness (PF) is scarce. The purpose of this study was to examine educational differences in PF in the working age population using different methods to assess PF. METHODS The Health 2000 Survey was carried out for adults aged ≥ 30 years (n = 8028) in Finland. For this study, 30-54-year-old men and women with data on PF and physical activity (PA) were selected (n = 3724). PF was assessed by self-estimated overall physical fitness and running ability, a physician's estimation of a participant's working capacity, the trunk extensors' endurance and hand grip strength tests. The highest educational qualification taken by the participant was used as a measure of education. The analyses were adjusted for age, PA, BMI, smoking and chronic diseases. RESULTS PF was best in the high-educated men and women. The educational differences were minor in self-estimated overall PF. Adjusting for the covariates, the differences in self-estimated running ability and working capacity decreased. The educational differences in the trunk extensors' endurance test were independent of covariates. PA and other health behaviours contributed most to the differences. CONCLUSION People with high education had better PF irrespective of the method used to assess PF. A large amount of the educational differences could be explained by PA and other health behaviours. More research is needed to understand the determinants of educational differences in PF.
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Affiliation(s)
- Heli Valkeinen
- 1 Department of Health, Functional Capacity and Welfare, National Institute for Health and Welfare (THL), Helsinki, Finland
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20
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Mähönen M, Jula A, Harald K, Antikainen R, Tuomilehto J, Zeller T, Blankenberg S, Salomaa V. The validity of heart failure diagnoses obtained from administrative registers. Eur J Prev Cardiol 2012; 20:254-9. [PMID: 22345696 DOI: 10.1177/2047487312438979] [Citation(s) in RCA: 43] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Population-based administrative registers could be used for identifying heart failure (HF) cases. However, the validity of the classification obtained from administrative registers is not known. DESIGN The validity of HF diagnoses obtained by record linkage of administrative databases in Finland was assessed against classification by three independent physicians. METHODS Data from the nationwide registers in Finland - the Hospital Discharge Register, Causes of Death Register, Drug Reimbursement Register, and pharmacy prescription data - were linked with the FINRISK 1997 survey data. Cases with hospitalizations before the survey date with HF as one of the discharge diagnoses, cases with special reimbursement for HF drugs before the survey date and cases with the use of furosemide before the survey date were classified as HF in the registers. All these cases, cases with baseline brain natriuretic peptide > 100 pg/ml, and cases with use of digoxin were independently assessed by two physicians as HF/no HF. Discrepant cases were solved by a third physician. This classification was considered as the gold standard, against which the registers were assessed. RESULTS The specificity of the registers was 99.7% (95% CI 99.5-99.8%), positive predictive value 85.9% (95% CI 79.7-90.5%), negative predictive value 97.9% (95% CI 97.6-98.2%), and sensitivity 48.5% (95% CI 42.9-54.2%). CONCLUSIONS Classification obtained from administrative registers has high specificity and can be used in follow-up studies with HF as an end point. Sensitivity is modest and administrative data should be used with caution for surveillance.
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Affiliation(s)
- Markku Mähönen
- Department of Public Health, University of Helsinki, Helsinki, Finland.
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Lahti-Koski M, Harald K, Saarni SE, Peltonen M, Männistö S. Changes in body mass index and measures of abdominal obesity in Finnish adults between 1992 and 2007, the National FINRISK Study. Clin Obes 2012; 2:57-63. [PMID: 25586048 DOI: 10.1111/j.1758-8111.2012.00035.x] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
UNLABELLED What is already known about this subject • Recent obesity trends across the world in adults are mixed, varying from showing signs of levelling off to a continuously increasing prevalence. • Secular trends in body mass index (BMI) and waist circumference may vary by sex and age. • Relying exclusively on BMI data may lead to underestimate the obesity epidemic. What this study adds • Adverse trends in obesity indicators have continued in Finland in the 2000s. • In older men, BMI remained quite stable and in older women BMI has decreased since 1997. • Steep upward trends in abdominal obesity (waist circumference and waist-to-height ratio, WHtR) have taken place in both men and women and in all age groups, especially during the past 10 years. • The impact of BMI adjustment on trends in abdominal obesity varied by age such that increases in BMI-adjusted waist circumference and WHtR were more prominent in older age groups. SUMMARY Signs that obesity trends will level off at the turn of the 21st century have been reported. In these studies, however, the definition of obesity has been based only on body mass index (BMI). We investigated obesity trends among Finnish adults over recent years by using BMI, waist circumference and waist-to-height ratio as indicators for obesity. Data were derived from the national FINRISK surveys, which are cross-sectional population surveys conducted at 5-year intervals between 1992 and 2007. Altogether, 20 551 randomly selected men and women aged 25-64 years participated in health examinations, where weight, height, and waist and hip circumferences were measured by trained nurses. Mean BMI increased in younger men and women (aged 25-44 years) between 1992 and 2007, whereas in older men, BMI remained quite stable and in older women BMI has decreased since 1997. Nevertheless, mean waist circumference and waist-to-height ratio increased in both men and women over the 15-year period. The upward trends took place in all age groups, especially during the past 10 years. Adverse trends in obesity indicators have continued in Finland in the 2000s. In particular, concerns are related to steep upward trends in abdominal obesity.
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Affiliation(s)
- M Lahti-Koski
- Finnish Heart Association, Helsinki, FinlandNational Institute for Health and Welfare (THL), Helsinki, FinlandDepartment of Psychiatry, Health Center, City of Helsinki, Helsinki, Finland
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Kucharska-Newton AM, Harald K, Rosamond WD, Rose KM, Rea TD, Salomaa V. Socioeconomic indicators and the risk of acute coronary heart disease events: comparison of population-based data from the United States and Finland. Ann Epidemiol 2011; 21:572-9. [PMID: 21737046 DOI: 10.1016/j.annepidem.2011.04.006] [Citation(s) in RCA: 79] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2010] [Revised: 04/13/2011] [Accepted: 04/18/2011] [Indexed: 10/18/2022]
Abstract
PURPOSE We wished to determine whether a gradient of association of low socioeconomic status with incidence of coronary heart disease was present in two population-based cohorts, one from United States and the other from Finland. METHODS Using data from the Atherosclerosis Risk in Communities (ARIC) cohort and the Finnish FINRISK cohort, we estimated, with Cox proportional hazard regression models, incidence of sudden cardiac death (SCD), non-sudden cardiac death (NSCD), and non-fatal myocardial infarction (NFMI) for strata of income and education (follow-up: 1987-2001). In both cohorts, incidence rates of the three outcomes increased across all socioeconomic status exposure categories. RESULTS Low education was associated with increased hazard of NFMI in both cohorts and with increased risk of SCD among ARIC women. Low income was significantly associated with increased hazard of all three outcomes among ARIC women and with increased hazard of cardiac death among ARIC men. In FINRISK, low income was significantly associated with increased risk of SCD only. Risk of SCD in the low income categories was similar for both cohorts. Smoking, alcohol consumption, and race (ARIC only) did not appreciably alter effect estimates in either cohort. CONCLUSIONS Indices of low SES show similar associations with increased risk of cardiac events in Finland and in United States.
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Lammintausta A, Immonen-Räihä P, Lehtonen A, Räihä I, Harald K, Torppa J, Airaksinen JKE, Salomaa V. Myocardial infarction events and cardiovascular risk factor levels in Finnish- and Swedish-speaking populations of Finland. Ann Med 2011; 43:562-9. [PMID: 20964582 DOI: 10.3109/07853890.2010.526136] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND. The Swedish-speaking minority of Finland is unique, because it has a higher socioeconomic status (SES) and longer life expectancy than the Finnish-speaking majority. We hypothesized that this minority may have a lower attack rate of coronary events and analysed whether this could be explained by their higher SES. METHODS. The population-based myocardial infarction (MI) registers recorded 4,845 MI events in Turku during 1988-1998. Individual-level indicators of SES were obtained from Statistics Finland. The population-based FINRISK surveys recorded cardiovascular risk factors and native languages of 10,432 people in 1987, 1997, and 2002. RESULTS. The age-standardized attack rate of MI was lower among the 35-64-year-old Swedish-speaking men than among Finnish-speaking men (rate ratio 0.66; 95% confidence interval 0.47-0.85) and the difference remained significant after adjustment for SES. The Swedish-speaking inhabitants had higher age-, sex-, and SES-adjusted high-density lipoprotein cholesterol, and lower triglycerides, body mass index, and diastolic blood pressure. Conclusion. The Swedish-speaking inhabitants of Turku had lower MI morbidity and coronary mortality than the Finnish-speaking inhabitants. After controlling for SES, these differences remained significant among men, suggesting that other factors, such as differences in the risk factor profiles may also play a role.
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Do R, Xie C, Zhang X, Männistö S, Harald K, Islam S, Bailey SD, Rangarajan S, McQueen MJ, Diaz R, Lisheng L, Wang X, Silander K, Peltonen L, Yusuf S, Salomaa V, Engert JC, Anand SS. The effect of chromosome 9p21 variants on cardiovascular disease may be modified by dietary intake: evidence from a case/control and a prospective study. PLoS Med 2011; 8:e1001106. [PMID: 22022235 PMCID: PMC3191151 DOI: 10.1371/journal.pmed.1001106] [Citation(s) in RCA: 72] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2011] [Accepted: 08/30/2011] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND One of the most robust genetic associations for cardiovascular disease (CVD) is the Chromosome 9p21 region. However, the interaction of this locus with environmental factors has not been extensively explored. We investigated the association of 9p21 with myocardial infarction (MI) in individuals of different ethnicities, and tested for an interaction with environmental factors. METHODS AND FINDINGS We genotyped four 9p21 SNPs in 8,114 individuals from the global INTERHEART study. All four variants were associated with MI, with odds ratios (ORs) of 1.18 to 1.20 (1.85×10(-8)≤p≤5.21×10(-7)). A significant interaction (p = 4.0×10(-4)) was observed between rs2383206 and a factor-analysis-derived "prudent" diet pattern score, for which a major component was raw vegetables. An effect of 9p21 on MI was observed in the group with a low prudent diet score (OR = 1.32, p = 6.82×10(-7)), but the effect was diminished in a step-wise fashion in the medium (OR = 1.17, p = 4.9×10(-3)) and high prudent diet scoring groups (OR = 1.02, p = 0.68) (p = 0.014 for difference). We also analyzed data from 19,129 individuals (including 1,014 incident cases of CVD) from the prospective FINRISK study, which used a closely related dietary variable. In this analysis, the 9p21 risk allele demonstrated a larger effect on CVD risk in the groups with diets low or average for fresh vegetables, fruits, and berries (hazard ratio [HR] = 1.22, p = 3.0×10(-4), and HR = 1.35, p = 4.1×10(-3), respectively) compared to the group with high consumption of these foods (HR = 0.96, p = 0.73) (p = 0.0011 for difference). The combination of the least prudent diet and two copies of the risk allele was associated with a 2-fold increase in risk for MI (OR = 1.98, p = 2.11×10(-9)) in the INTERHEART study and a 1.66-fold increase in risk for CVD in the FINRISK study (HR = 1.66, p = 0.0026). CONCLUSIONS The risk of MI and CVD conferred by Chromosome 9p21 SNPs appears to be modified by a prudent diet high in raw vegetables and fruits. Please see later in the article for the Editors' Summary.
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Affiliation(s)
- Ron Do
- Department of Human Genetics, McGill University, Montréal, Quebec, Canada
| | - Changchun Xie
- Population Health Research Institute, Hamilton Health Sciences, and McMaster University, Hamilton, Ontario, Canada
- Departments of Medicine and Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada
| | - Xiaohe Zhang
- Population Health Research Institute, Hamilton Health Sciences, and McMaster University, Hamilton, Ontario, Canada
| | - Satu Männistö
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
| | - Kennet Harald
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
| | - Shofiqul Islam
- Population Health Research Institute, Hamilton Health Sciences, and McMaster University, Hamilton, Ontario, Canada
- Departments of Medicine and Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada
| | - Swneke D. Bailey
- Department of Human Genetics, McGill University, Montréal, Quebec, Canada
| | - Sumathy Rangarajan
- Population Health Research Institute, Hamilton Health Sciences, and McMaster University, Hamilton, Ontario, Canada
| | - Matthew J. McQueen
- Population Health Research Institute, Hamilton Health Sciences, and McMaster University, Hamilton, Ontario, Canada
| | - Rafael Diaz
- Estudios Cardiologicos Latinoamerica, Rosario, Argentina
| | - Liu Lisheng
- Cardiovascular Institute and Fu Wai Hospital, Chinese Hypertension League Institute, Beijing, China
| | - Xingyu Wang
- Laboratory of Human Genetics, Beijing Hypertension League Institute, Beijing, China
| | - Kaisa Silander
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
- Human Genomics Unit, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Leena Peltonen
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
- Human Genomics Unit, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Salim Yusuf
- Population Health Research Institute, Hamilton Health Sciences, and McMaster University, Hamilton, Ontario, Canada
| | - Veikko Salomaa
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
| | - James C. Engert
- Department of Human Genetics, McGill University, Montréal, Quebec, Canada
- Department of Medicine, McGill University, Montréal, Quebec, Canada
- The Research Institute of the McGill University Health Centre, Montréal, Quebec, Canada
- * E-mail: (JCE); (SSA)
| | - Sonia S. Anand
- Population Health Research Institute, Hamilton Health Sciences, and McMaster University, Hamilton, Ontario, Canada
- Departments of Medicine and Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada
- * E-mail: (JCE); (SSA)
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Noseworthy PA, Tikkanen JT, Porthan K, Oikarinen L, Pietilä A, Harald K, Peloso GM, Merchant FM, Jula A, Väänänen H, Hwang SJ, O'Donnell CJ, Salomaa V, Newton-Cheh C, Huikuri HV. The early repolarization pattern in the general population: clinical correlates and heritability. J Am Coll Cardiol 2011; 57:2284-9. [PMID: 21600720 DOI: 10.1016/j.jacc.2011.04.003] [Citation(s) in RCA: 163] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2010] [Revised: 03/04/2011] [Accepted: 04/12/2011] [Indexed: 11/26/2022]
Abstract
OBJECTIVES This study sought to describe the clinical correlates and heritability of the early repolarization pattern (ERP) in 2 large, population-based cohorts. BACKGROUND There is growing recognition that ERP is associated with adverse outcomes. METHODS Participants of the Framingham Heart Study (FHS) (N = 3,995) and the Health 2000 Survey (H2K) (N = 5,489) were included. ERP was defined as a J-point elevation ≥0.1 mV in ≥2 leads in either the inferior (II, III, aVF) or lateral (I, aVL, V(4-6)) territory or both. We tested the association between clinical characteristics and ERP, and estimated sibling recurrence risk. RESULTS ERP was present in 243 of 3,955 (6.1%) of FHS and 180 of 5,489 (3.3%) of H2K subjects. Male sex, younger age, lower systolic blood pressure, higher Sokolow-Lyon index, and lower Cornell voltage were independently associated with the presence of ERP. In the FHS sample, siblings of individuals with ERP had an ERP prevalence of 11.6% (recurrence risk ratio of 1.89). Siblings of individuals with ERP had an increased unadjusted odds of ERP (odds ratio: 2.22, 95% confidence interval: 1.01 to 4.85, p = 0.047). CONCLUSIONS ERP has strong association with clinical factors and has evidence for a heritable basis in the general population. Further assessment of the genetic determinants of ERP is warranted.
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Affiliation(s)
- Peter A Noseworthy
- Cardiovascular Research Center and Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA
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Pajunen P, Jousilahti P, Borodulin K, Harald K, Tuomilehto J, Salomaa V. Body fat measured by a near-infrared interactance device as a predictor of cardiovascular events: the FINRISK'92 cohort. Obesity (Silver Spring) 2011; 19:848-52. [PMID: 20966903 DOI: 10.1038/oby.2010.236] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
We evaluated how body fat percentage, measured by a portable near-infrared interactance (NIR) device predicts cardiovascular (CVD), coronary heart disease (CHD), and ischemic stroke events in a prospective population-based survey. The study population consisted of 2,842 men and 3,196 women, who participated in the FINRISK'92 survey. Obesity was assessed with BMI, waist circumference, and waist-to-hip ratio (WHR) and body fat percentage measured with an NIR. Mean length of follow-up was 9 years and 3 months. In Cox proportional hazards regression analyses for men, BMI, waist circumference, and WHR as well as body fat percentage were predictors of a CVD event when adjusted for age and for major risk factors. Hazard ratio (HR) per 1 s.d. was 1.27 (95% confidence interval: 1.10-1.48) for body fat percentage, 1.30 (1.16-1.46) for BMI, and 1.31 (1.16-1.50) for waist circumference. Among women, the body fat lost its predictive power in a fully adjusted model. Body fat percentage, BMI, waist circumference, and WHR were predictors of a CHD event both among men and women, whereas body fat percentage did not predict ischemic stroke among either gender. We observed that body fat percentage measured by an NIR device was a significant predictor of CVD and CHD events among men and women, but in our population-based survey, it did not provide any additional predictive power over and above the simpler measures, such as BMI or WHR.
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Affiliation(s)
- Pia Pajunen
- Diabetes Prevention Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland.
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Jackson D, White I, Kostis JB, Wilson AC, Folsom AR, Wu K, Chambless L, Benderly M, Goldbourt U, Willeit J, Kiechl S, Yarnell JWG, Sweetnam PM, Elwood PC, Cushman M, Psaty BM, Tracy RP, Tybjaerg-Hansen A, Haverkate F, de Maat MPM, Thompson SG, Fowkes FGR, Lee AJ, Smith FB, Salomaa V, Harald K, Rasi V, Vahtera E, Jousilahti P, D'Agostino R, Kannel WB, Wilson PWF, Tofler G, Levy D, Marchioli R, Valagussa F, Rosengren A, Wilhelmsen L, Lappas G, Eriksson H, Cremer P, Nagel D, Curb JD, Rodriguez B, Yano K, Salonen JT, Nyyssönen K, Tuomainen TP, Hedblad B, Engström G, Berglund G, Loewel H, Koenig W, Hense HW, Meade TW, Cooper JA, De Stavola B, Knottenbelt C, Miller GJ, Cooper JA, Bauer KA, Rosenberg RD, Sato S, Kitamura A, Naito Y, Iso H, Salomaa V, Harald K, Rasi V, Vahtera E, Jousilahti P, Palosuo T, Ducimetiere P, Amouyel P, Arveiler D, Evans AE, Ferrieres J, Juhan-Vague I, Bingham A, Schulte H, Assmann G, Cantin B, Lamarche B, Despres JP, Dagenais GR, Tunstall-Pedoe H, Lowe GDO, Woodward M, Ben-Shlomo Y, Davey Smith G, Palmieri V, Yeh JL, Meade TW, Rudnicka A, Brennan P, Knottenbelt C, Cooper JA, Ridker P, Rodeghiero F, Tosetto A, Shepherd J, Lowe GDO, Ford I, Robertson M, Brunner E, Shipley M, Feskens EJM, Di Angelantonio E, Kaptoge S, Lewington S, Lowe GDO, Sarwar N, Thompson SG, Walker M, Watson S, White IR, Wood AM, Danesh J. Systematically missing confounders in individual participant data meta-analysis of observational cohort studies. Stat Med 2009; 28:1218-37. [PMID: 19222087 PMCID: PMC2922684 DOI: 10.1002/sim.3540] [Citation(s) in RCA: 39] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
One difficulty in performing meta-analyses of observational cohort studies is that the availability of confounders may vary between cohorts, so that some cohorts provide fully adjusted analyses while others only provide partially adjusted analyses. Commonly, analyses of the association between an exposure and disease either are restricted to cohorts with full confounder information, or use all cohorts but do not fully adjust for confounding. We propose using a bivariate random-effects meta-analysis model to use information from all available cohorts while still adjusting for all the potential confounders. Our method uses both the fully adjusted and the partially adjusted estimated effects in the cohorts with full confounder information, together with an estimate of their within-cohort correlation. The method is applied to estimate the association between fibrinogen level and coronary heart disease incidence using data from 154 012 participants in 31 cohorts.† Copyright © 2009 John Wiley & Sons, Ltd.
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Harald K, Koskinen S, Jousilahti P, Torppa J, Vartiainen E, Salomaa V. Changes in traditional risk factors no longer explain time trends in cardiovascular mortality and its socioeconomic differences. J Epidemiol Community Health 2008; 62:251-7. [PMID: 18272741 DOI: 10.1136/jech.2007.060707] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
AIM To investigate to what extent the changes in traditional risk factors (total cholesterol, smoking, hypertension) explain the changes in socioeconomic (defined by occupational class and household income) differences in cardiovascular mortality in Finland during the past 20 years. DESIGN Study population comprised 14,642 men and women aged 35-64 years who were selected from population-based FINRISK surveys in 1987, 1992, 1997 or 2002 in three areas of Finland. The 1982 and 1987 FINRISK cohorts were used to determine a model for the probability of cardiovascular death based on risk factor values at the baseline for each socioeconomic group. These predicted changes in cardiovascular mortality were then contrasted with observed mortality rates in different socioeconomic groups to determine the contribution of the changes in risk factors to changes in actual mortality. RESULTS We found that among men during 1987-97, when risk factor levels were improving in all socioeconomic groups, the model explained 29-44% of the observed mortality decline. The risk factors explained a larger part of the decline among lower socioeconomic groups. During the period 1997-2002 the risk factor levels stopped improving in all socioeconomic groups but observed mortality rates kept declining. The predicted mortality rates were 16-34% of the observed rates during the period 1987-2002. CONCLUSIONS Changes in traditional risk factors no longer provide a good explanation of the changes in cardiovascular mortality and its socioeconomic differences. However, risk factors did explain the cardiovascular mortality decline among lower socioeconomic groups.
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Affiliation(s)
- K Harald
- National Public Health Institute, Mannerheimintie 160, FIN-00300, Helsinki, Finland.
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Danesh J, Erqou S, Walker M, Thompson SG, Tipping R, Ford C, Pressel S, Walldius G, Jungner I, Folsom AR, Chambless LE, Knuiman M, Whincup PH, Wannamethee SG, Morris RW, Willeit J, Kiechl S, Santer P, Mayr A, Wald N, Ebrahim S, Lawlor DA, Yarnell JWG, Gallacher J, Casiglia E, Tikhonoff V, Nietert PJ, Sutherland SE, Bachman DL, Keil JE, Cushman M, Psaty BM, Tracy RP, Tybjaerg-Hansen A, Nordestgaard BG, Frikke-Schmidt R, Giampaoli S, Palmieri L, Panico S, Vanuzzo D, Pilotto L, Simons L, McCallum J, Friedlander Y, Fowkes FGR, Lee AJ, Smith FB, Taylor J, Guralnik J, Phillips C, Wallace R, Blazer D, Khaw KT, Jansson JH, Donfrancesco C, Salomaa V, Harald K, Jousilahti P, Vartiainen E, Woodward M, D'Agostino RB, Wolf PA, Vasan RS, Pencina MJ, Bladbjerg EM, Jorgensen T, Moller L, Jespersen J, Dankner R, Chetrit A, Lubin F, Rosengren A, Wilhelmsen L, Lappas G, Eriksson H, Bjorkelund C, Cremer P, Nagel D, Tilvis R, Strandberg T, Rodriguez B, Bouter LM, Heine RJ, Dekker JM, Nijpels G, Stehouwer CDA, Rimm E, Pai J, Sato S, Iso H, Kitamura A, Noda H, Goldbourt U, Salomaa V, Salonen JT, Nyyssönen K, Tuomainen TP, Deeg D, Poppelaars JL, Meade T, Cooper J, Hedblad B, Berglund G, Engstrom G, Döring A, Koenig W, Meisinger C, Mraz W, Kuller L, Selmer R, Tverdal A, Nystad W, Gillum R, Mussolino M, Hankinson S, Manson J, De Stavola B, Knottenbelt C, Cooper JA, Bauer KA, Rosenberg RD, Sato S, Naito Y, Holme I, Nakagawa H, Miura H, Ducimetiere P, Jouven X, Crespo C, Garcia-Palmieri M, Amouyel P, Arveiler D, Evans A, Ferrieres J, Schulte H, Assmann G, Shepherd J, Packard C, Sattar N, Cantin B, Lamarche B, Després JP, Dagenais GR, Barrett-Connor E, Wingard D, Bettencourt R, Gudnason V, Aspelund T, Sigurdsson G, Thorsson B, Trevisan M, Witteman J, Kardys I, Breteler M, Hofman A, Tunstall-Pedoe H, Tavendale R, Lowe GDO, Ben-Shlomo Y, Howard BV, Zhang Y, Best L, Umans J, Onat A, Meade TW, Njolstad I, Mathiesen E, Lochen ML, Wilsgaard T, Gaziano JM, Stampfer M, Ridker P, Ulmer H, Diem G, Concin H, Rodeghiero F, Tosetto A, Brunner E, Shipley M, Buring J, Cobbe SM, Ford I, Robertson M, He Y, Ibanez AM, Feskens EJM, Kromhout D, Collins R, Di Angelantonio E, Kaptoge S, Lewington S, Orfei L, Pennells L, Perry P, Ray K, Sarwar N, Scherman M, Thompson A, Watson S, Wensley F, White IR, Wood AM. The Emerging Risk Factors Collaboration: analysis of individual data on lipid, inflammatory and other markers in over 1.1 million participants in 104 prospective studies of cardiovascular diseases. Eur J Epidemiol 2007; 22:839-69. [PMID: 17876711 DOI: 10.1007/s10654-007-9165-7] [Citation(s) in RCA: 132] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2007] [Accepted: 07/02/2007] [Indexed: 01/22/2023]
Abstract
Many long-term prospective studies have reported on associations of cardiovascular diseases with circulating lipid markers and/or inflammatory markers. Studies have not, however, generally been designed to provide reliable estimates under different circumstances and to correct for within-person variability. The Emerging Risk Factors Collaboration has established a central database on over 1.1 million participants from 104 prospective population-based studies, in which subsets have information on lipid and inflammatory markers, other characteristics, as well as major cardiovascular morbidity and cause-specific mortality. Information on repeat measurements on relevant characteristics has been collected in approximately 340,000 participants to enable estimation of and correction for within-person variability. Re-analysis of individual data will yield up to approximately 69,000 incident fatal or nonfatal first ever major cardiovascular outcomes recorded during about 11.7 million person years at risk. The primary analyses will involve age-specific regression models in people without known baseline cardiovascular disease in relation to fatal or nonfatal first ever coronary heart disease outcomes. This initiative will characterize more precisely and in greater detail than has previously been possible the shape and strength of the age- and sex-specific associations of several lipid and inflammatory markers with incident coronary heart disease outcomes (and, secondarily, with other incident cardiovascular outcomes) under a wide range of circumstances. It will, therefore, help to determine to what extent such associations are independent from possible confounding factors and to what extent such markers (separately and in combination) provide incremental predictive value.
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Lahti-Koski M, Harald K, Männistö S, Laatikainen T, Jousilahti P. Fifteen-year changes in body mass index and waist circumference in Finnish adults. ACTA ACUST UNITED AC 2007; 14:398-404. [PMID: 17568239 DOI: 10.1097/hjr.0b013e32800fef1f] [Citation(s) in RCA: 53] [Impact Index Per Article: 3.1] [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: 11/26/2022]
Abstract
BACKGROUND Obesity is an increasing health problem. Data on long-term obesity trends are most often based on the measurement of body mass index (BMI). Abdominal obesity, assessed by waist circumference may, however, be more closely related to health risks than overall obesity. The aim of this study was to investigate 15-year changes in general and abdominal obesity among adults in Finland, and furthermore, to assess whether obesity trends differ between educational groups. DESIGN Four cross-sectional population surveys conducted at 5-year intervals between 1987 and 2002. METHODS Altogether, 9025 men and 9950 women aged 25-64 years participated in these surveys. The weight, height, and waist circumferences of the participants were measured using a standardized protocol. RESULTS Mean waist circumference increased by 2.7 cm in men and 4.3 cm in women in 15 years. Whereas the distribution of BMI values did not change much, a remarkable shift towards higher waist circumference values was observed in 15 years. In both sexes, mean and high values of waist circumference increased in all educational groups. However, the values remained highest among the subjects with the lowest education. CONCLUSIONS These results indicate that adverse changes in body shape have taken place from the late 1980s to the early 2000s. Given that one in five Finnish adults is defined as obese based on BMI, there is an even larger group of individuals at risk of obesity-related metabolic disorders because of abdominal obesity, particularly among low-educated individuals.
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Affiliation(s)
- Marjaana Lahti-Koski
- National Public Health Institute, Department of Health Promotion and Chronic Disease Prevention, Helsinki, Finland.
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Harald K, Pajunen P, Jousilahti P, Koskinen S, Vartiainen E, Salomaa V. Modifiable risk factors have an impact on socio-economic differences in coronary heart disease events. SCAND CARDIOVASC J 2007; 40:87-95. [PMID: 16608778 DOI: 10.1080/14017430500519872] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
OBJECTIVES To investigate the association of socio-economic status, defined by occupational class, income and education, with coronary heart disease (CHD) morbidity and mortality, and further to analyse to which extent modifiable risk factors may explain socio-economic differences in CHD risk. DESIGN A population-based prospective cohort study including 9,061 men and 10,211 women aged 35-64 at baseline who participated in a cardiovascular risk factor survey in 1982, 1987, 1992 or 1997 in Finland. The subjects were followed for CHD events up till the end of 2001. Cox's proportional hazards model was used in the analysis. RESULTS Male manual workers had a double risk of CHD death compared with upper-level employees (HR=2.00, 95% CI 1.35-2.97). This excess risk was reduced by 31% when adjusted for traditional cardiovascular risk factors and most of this reduction was due to smoking. CONCLUSIONS Modifiable risk factors explained about a third of the excess CHD mortality between manual workers and upper-level employees in men. Among women the differences between socio-economic groups were not statistically significant.
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Affiliation(s)
- Kennet Harald
- National Public Health Institute, Helsinki, Finland.
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Harald K, Salomaa V, Jousilahti P, Koskinen S, Vartiainen E. Non-participation and mortality in different socioeconomic groups: the FINRISK population surveys in 1972-92. J Epidemiol Community Health 2007; 61:449-54. [PMID: 17435214 PMCID: PMC2465683 DOI: 10.1136/jech.2006.049908] [Citation(s) in RCA: 81] [Impact Index Per Article: 4.8] [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: 11/03/2022]
Abstract
BACKGROUND Declining response rates pose a serious threat to the validity of estimates derived from epidemiological studies. If respondents and non-respondents differ systematically from each other, there can be a bias in the results of the study. A population-based cohort study was conducted to investigate disparities in socioeconomic structure between respondents and non-respondents and the contribution of these disparities to socioeconomic differences in total and cardiovascular mortality. DESIGN Data comprised 32,354 male and female participants and 4890 non-participants aged 35-74 years who belonged to the sample in one of the five FINRISK surveys in 1972, 1977, 1982, 1987 or 1992 in Finland. They were followed up for 9 years and 6 months. RESULTS It was found that the lower socioeconomic groups were over-represented among non-respondents both in men and women. When comparing the relative risk of death using the highest socioeconomic group of the participants as the reference group, it was found that although the socioeconomic gradient was similar for participants and non-participants-that is, lower groups had a higher risk of death-the risk was at a higher level among non-respondents. CONCLUSIONS Basing analysis on participants does not distort the relative risk of death associated with socioeconomic position. However, it does underestimate the absolute risk.
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Affiliation(s)
- Kennet Harald
- National Public Health Institute, Mannerheimintie 160, FIN-00300, Helsinki, Finland.
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Danesh J, Lewington S, Thompson SG, Lowe GDO, Collins R, Kostis JB, Wilson AC, Folsom AR, Wu K, Benderly M, Goldbourt U, Willeit J, Kiechl S, Yarnell JWG, Sweetnam PM, Elwood PC, Cushman M, Psaty BM, Tracy RP, Tybjaerg-Hansen A, Haverkate F, de Maat MPM, Fowkes FGR, Lee AJ, Smith FB, Salomaa V, Harald K, Rasi R, Vahtera E, Jousilahti P, Pekkanen J, D'Agostino R, Kannel WB, Wilson PWF, Tofler G, Arocha-Piñango CL, Rodriguez-Larralde A, Nagy E, Mijares M, Espinosa R, Rodriquez-Roa E, Ryder E, Diez-Ewald MP, Campos G, Fernandez V, Torres E, Marchioli R, Valagussa F, Rosengren A, Wilhelmsen L, Lappas G, Eriksson H, Cremer P, Nagel D, Curb JD, Rodriguez B, Yano K, Salonen JT, Nyyssönen K, Tuomainen TP, Hedblad B, Lind P, Loewel H, Koenig W, Meade TW, Cooper JA, De Stavola B, Knottenbelt C, Miller GJ, Cooper JA, Bauer KA, Rosenberg RD, Sato S, Kitamura A, Naito Y, Palosuo T, Ducimetiere P, Amouyel P, Arveiler D, Evans AE, Ferrieres J, Juhan-Vague I, Bingham A, Schulte H, Assmann G, Cantin B, Lamarche B, Després JP, Dagenais GR, Tunstall-Pedoe H, Woodward M, Ben-Shlomo Y, Davey Smith G, Palmieri V, Yeh JL, Rudnicka A, Ridker P, Rodeghiero F, Tosetto A, Shepherd J, Ford I, Robertson M, Brunner E, Shipley M, Feskens EJM, Kromhout D, Dickinson A, Ireland B, Juzwishin K, Kaptoge S, Lewington S, Memon A, Sarwar N, Walker M, Wheeler J, White I, Wood A. Plasma fibrinogen level and the risk of major cardiovascular diseases and nonvascular mortality: an individual participant meta-analysis. JAMA 2005; 294:1799-809. [PMID: 16219884 DOI: 10.1001/jama.294.14.1799] [Citation(s) in RCA: 460] [Impact Index Per Article: 24.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
CONTEXT Plasma fibrinogen levels may be associated with the risk of coronary heart disease (CHD) and stroke. OBJECTIVE To assess the relationships of fibrinogen levels with risk of major vascular and with risk of nonvascular outcomes based on individual participant data. DATA SOURCES Relevant studies were identified by computer-assisted searches, hand searches of reference lists, and personal communication with relevant investigators. STUDY SELECTION All identified prospective studies were included with information available on baseline fibrinogen levels and details of subsequent major vascular morbidity and/or cause-specific mortality during at least 1 year of follow-up. Studies were excluded if they recruited participants on the basis of having had a previous history of cardiovascular disease; participants with known preexisting CHD or stroke were excluded. DATA EXTRACTION Individual records were provided on each of 154,211 participants in 31 prospective studies. During 1.38 million person-years of follow-up, there were 6944 first nonfatal myocardial infarctions or stroke events and 13,210 deaths. Cause-specific mortality was generally available. Analyses involved proportional hazards modeling with adjustment for confounding by known cardiovascular risk factors and for regression dilution bias. DATA SYNTHESIS Within each age group considered (40-59, 60-69, and > or =70 years), there was an approximately log-linear association with usual fibrinogen level for the risk of any CHD, any stroke, other vascular (eg, non-CHD, nonstroke) mortality, and nonvascular mortality. There was no evidence of a threshold within the range of usual fibrinogen level studied at any age. The age- and sex- adjusted hazard ratio per 1-g/L increase in usual fibrinogen level for CHD was 2.42 (95% confidence interval [CI], 2.24-2.60); stroke, 2.06 (95% CI, 1.83-2.33); other vascular mortality, 2.76 (95% CI, 2.28-3.35); and nonvascular mortality, 2.03 (95% CI, 1.90-2.18). The hazard ratios for CHD and stroke were reduced to about 1.8 after further adjustment for measured values of several established vascular risk factors. In a subset of 7011 participants with available C-reactive protein values, the findings for CHD were essentially unchanged following additional adjustment for C-reactive protein. The associations of fibrinogen level with CHD or stroke did not differ substantially according to sex, smoking, blood pressure, blood lipid levels, or several features of study design. CONCLUSIONS In this large individual participant meta-analysis, moderately strong associations were found between usual plasma fibrinogen level and the risks of CHD, stroke, other vascular mortality, and nonvascular mortality in a wide range of circumstances in healthy middle-aged adults. Assessment of any causal relevance of elevated fibrinogen levels to disease requires additional research.
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