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Harada S, Iida M, Miyagawa N, Hirata A, Kuwabara K, Matsumoto M, Okamura T, Edagawa S, Kawada Y, Miyake A, Toki R, Akiyama M, Kawai A, Sugiyama D, Sato Y, Takemura R, Fukai K, Ishibashi Y, Kato S, Kurihara A, Sata M, Shibuki T, Takeuchi A, Kohsaka S, Sawano M, Shoji S, Izawa Y, Katsumata M, Oki K, Takahashi S, Takizawa T, Maruya H, Nishiwaki Y, Kawasaki R, Hirayama A, Ishikawa T, Saito R, Sato A, Soga T, Sugimoto M, Tomita M, Komaki S, Ohmomo H, Ono K, Otsuka-Yamasaki Y, Shimizu A, Sutoh Y, Hozawa A, Kinoshita K, Koshiba S, Kumada K, Ogishima S, Sakurai-Yageta M, Tamiya G, Takebayashi T. Study Profile of the Tsuruoka Metabolomics Cohort Study (TMCS). J Epidemiol 2024; 34:393-401. [PMID: 38191178 PMCID: PMC11230875 DOI: 10.2188/jea.je20230192] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 11/17/2023] [Indexed: 01/10/2024] Open
Abstract
The Tsuruoka Metabolomics Cohort Study (TMCS) is an ongoing population-based cohort study being conducted in the rural area of Yamagata Prefecture, Japan. This study aimed to enhance the precision prevention of multi-factorial, complex diseases, including non-communicable and aging-associated diseases, by improving risk stratification and prediction measures. At baseline, 11,002 participants aged 35-74 years were recruited in Tsuruoka City, Yamagata Prefecture, Japan, between 2012 and 2015, with an ongoing follow-up survey. Participants underwent various measurements, examinations, tests, and questionnaires on their health, lifestyle, and social factors. This study uses an integrative approach with deep molecular profiling to identify potential biomarkers linked to phenotypes that underpin disease pathophysiology and provide better mechanistic insights into social health determinants. The TMCS incorporates multi-omics data, including genetic and metabolomic analyses of 10,933 participants, and comprehensive data collection ranging from physical, psychological, behavioral, and social to biological data. The metabolome is used as a phenotypic probe because it is sensitive to changes in physiological and external conditions. The TMCS focuses on collecting outcomes for cardiovascular disease, cancer incidence and mortality, disability and functional decline due to aging and disease sequelae, and the variation in health status within the body represented by omics analysis that lies between exposure and disease. It contains several sub-studies on aging, heated tobacco products, and women's health. This study is notable for its robust design, high participation rate (89%), and long-term repeated surveys. Moreover, it contributes to precision prevention in Japan and East Asia as a well-established multi-omics platform.
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Affiliation(s)
- Sei Harada
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan
- Institute for Advanced Biosciences, Keio University, Yamagata, Japan
| | - Miho Iida
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan
- Institute for Advanced Biosciences, Keio University, Yamagata, Japan
| | - Naoko Miyagawa
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan
| | - Aya Hirata
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan
| | - Kazuyo Kuwabara
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan
| | - Minako Matsumoto
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan
| | - Tomonori Okamura
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan
| | - Shun Edagawa
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan
| | - Yoko Kawada
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan
| | - Atsuko Miyake
- Department of Obstetrics and Gynecology, Keio University School of Medicine, Tokyo, Japan
| | - Ryota Toki
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan
| | - Miki Akiyama
- Institute for Advanced Biosciences, Keio University, Yamagata, Japan
- Faculty of Environment and Information Studies, Keio University, Kanagawa, Japan
| | - Atsuki Kawai
- Institute for Advanced Biosciences, Keio University, Yamagata, Japan
| | - Daisuke Sugiyama
- Faculty of Nursing and Medical Care and Graduate School of Health Management, Keio University, Kanagawa, Japan
| | - Yasunori Sato
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan
- Biostatistics Unit, Clinical and Translational Research Center, Keio University Hospital, Tokyo, Japan
| | - Ryo Takemura
- Biostatistics Unit, Clinical and Translational Research Center, Keio University Hospital, Tokyo, Japan
| | - Kota Fukai
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan
| | - Yoshiki Ishibashi
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan
| | - Suzuka Kato
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan
| | - Ayako Kurihara
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan
| | - Mizuki Sata
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan
| | - Takuma Shibuki
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan
| | - Ayano Takeuchi
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan
| | - Shun Kohsaka
- Department of Cardiology, Keio University School of Medicine, Tokyo, Japan
| | - Mitsuaki Sawano
- Department of Cardiology, Keio University School of Medicine, Tokyo, Japan
| | - Satoshi Shoji
- Department of Cardiology, Keio University School of Medicine, Tokyo, Japan
- Duke Clinical Research Institute, Durham, NC, USA
| | - Yoshikane Izawa
- Department of Neurology, Keio University School of Medicine, Tokyo, Japan
| | - Masahiro Katsumata
- Department of Neurology, Keio University School of Medicine, Tokyo, Japan
| | - Koichi Oki
- Department of Neurology, Keio University School of Medicine, Tokyo, Japan
- Department of Neurology, Tokyo Saiseikai Central Hospital, Tokyo, Japan
| | - Shinichi Takahashi
- Department of Neurology, Keio University School of Medicine, Tokyo, Japan
- Department of Neurology and Stroke, Saitama Medical University International Medical Center, Saitama, Japan
| | - Tsubasa Takizawa
- Department of Neurology, Keio University School of Medicine, Tokyo, Japan
| | | | - Yuji Nishiwaki
- Department of Environmental and Occupational Health, School of Medicine, Toho University, Tokyo, Japan
| | - Ryo Kawasaki
- Division of Public Health, Department of Social Medicine, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Akiyoshi Hirayama
- Institute for Advanced Biosciences, Keio University, Yamagata, Japan
| | - Takamasa Ishikawa
- Institute for Advanced Biosciences, Keio University, Yamagata, Japan
| | - Rintaro Saito
- Institute for Advanced Biosciences, Keio University, Yamagata, Japan
| | - Asako Sato
- Institute for Advanced Biosciences, Keio University, Yamagata, Japan
| | - Tomoyoshi Soga
- Institute for Advanced Biosciences, Keio University, Yamagata, Japan
| | - Masahiro Sugimoto
- Institute for Advanced Biosciences, Keio University, Yamagata, Japan
| | - Masaru Tomita
- Institute for Advanced Biosciences, Keio University, Yamagata, Japan
| | - Shohei Komaki
- Division of Biomedical Information Analysis, Institute for Biomedical Sciences of Iwate Medical University, Iwate, Japan
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Iwate, Japan
| | - Hideki Ohmomo
- Division of Biomedical Information Analysis, Institute for Biomedical Sciences of Iwate Medical University, Iwate, Japan
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Iwate, Japan
| | - Kanako Ono
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Iwate, Japan
| | - Yayoi Otsuka-Yamasaki
- Division of Biomedical Information Analysis, Institute for Biomedical Sciences of Iwate Medical University, Iwate, Japan
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Iwate, Japan
| | - Atsushi Shimizu
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan
- Division of Biomedical Information Analysis, Institute for Biomedical Sciences of Iwate Medical University, Iwate, Japan
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Iwate, Japan
| | - Yoichi Sutoh
- Division of Biomedical Information Analysis, Institute for Biomedical Sciences of Iwate Medical University, Iwate, Japan
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Iwate, Japan
| | - Atsushi Hozawa
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Kengo Kinoshita
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Graduate School of Information Sciences, Tohoku University, Sendai, Japan
- Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, Sendai, Japan
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Seizo Koshiba
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Kazuki Kumada
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Soichi Ogishima
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | | | - Gen Tamiya
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Graduate School of Medicine, Tohoku University, Sendai, Japan
- Center for Advanced Intelligence Project, RIKEN, Tokyo, Japan
| | - Toru Takebayashi
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan
- Institute for Advanced Biosciences, Keio University, Yamagata, Japan
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Noda A, Obara T, Shirota M, Ueno F, Matsuzaki F, Hatanaka R, Obara R, Morishita K, Shinoda G, Orui M, Murakami K, Ishikuro M, Kuriyama S. Medication use before and during pregnancy in Japan: the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study. Eur J Clin Pharmacol 2024; 80:1171-1180. [PMID: 38630193 PMCID: PMC11226522 DOI: 10.1007/s00228-024-03685-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 04/02/2024] [Indexed: 07/06/2024]
Abstract
PURPOSE To elucidate the status of medication use among pregnant women in Japan, by means of a multigenerational genome and birth cohort study: the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study (TMM BirThree Cohort Study). METHODS Questionnaires were distributed to pregnant women participating in the TMM BirThree Cohort Study (from July 2013 to March 2017) around 12 weeks (early pregnancy) and 26 weeks (middle pregnancy). We analysed medication use over three periods: (1) 12 months prior to pregnancy diagnosis, (2) the period between pregnancy diagnosis and around week 12 of pregnancy, and (3) post around week 12 of pregnancy. RESULTS In total, 19,297 women were included in the analysis. The proportion of pregnant women using medications was 49.0% prior to pregnancy diagnosis, 52.1% from diagnosis to week 12, and 58.4% post week 12 of pregnancy. The most frequently prescribed medications were loxoprofen sodium hydrate (5.5%) prior to pregnancy diagnosis, magnesium oxide (5.9%) from diagnosis to week 12, and ritodrine hydrochloride (10.5%) post week 12 of pregnancy. The number of women who used suspected teratogenic medications during early pregnancy was 96 prior to pregnancy diagnosis, 48 from diagnosis to week 12, and 54 post week 12 of pregnancy. CONCLUSION We found that ~ 50% of the pregnant women used medications before and during pregnancy and some took potential teratogenic medications during pregnancy. In birth genomic cohort study, it is expected that investigations into the safety and effectiveness of medications used during pregnancy will advance.
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Affiliation(s)
- Aoi Noda
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryou-Cho, Aoba-Ku, Sendai, Miyagi, 980-8573, Japan
- Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan
- Department of Pharmaceutical Sciences, Tohoku University Hospital, Sendai, Miyagi, Japan
| | - Taku Obara
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryou-Cho, Aoba-Ku, Sendai, Miyagi, 980-8573, Japan.
- Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan.
- Department of Pharmaceutical Sciences, Tohoku University Hospital, Sendai, Miyagi, Japan.
| | - Matsuyuki Shirota
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryou-Cho, Aoba-Ku, Sendai, Miyagi, 980-8573, Japan
- Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan
| | - Fumihiko Ueno
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryou-Cho, Aoba-Ku, Sendai, Miyagi, 980-8573, Japan
| | - Fumiko Matsuzaki
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryou-Cho, Aoba-Ku, Sendai, Miyagi, 980-8573, Japan
| | - Rieko Hatanaka
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryou-Cho, Aoba-Ku, Sendai, Miyagi, 980-8573, Japan
- Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan
| | - Ryo Obara
- Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan
| | - Kei Morishita
- Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan
- Department of Pharmaceutical Sciences, Tohoku University Hospital, Sendai, Miyagi, Japan
| | - Genki Shinoda
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryou-Cho, Aoba-Ku, Sendai, Miyagi, 980-8573, Japan
- Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan
| | - Masatsugu Orui
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryou-Cho, Aoba-Ku, Sendai, Miyagi, 980-8573, Japan
- Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan
| | - Keiko Murakami
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryou-Cho, Aoba-Ku, Sendai, Miyagi, 980-8573, Japan
| | - Mami Ishikuro
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryou-Cho, Aoba-Ku, Sendai, Miyagi, 980-8573, Japan
- Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan
| | - Shinichi Kuriyama
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryou-Cho, Aoba-Ku, Sendai, Miyagi, 980-8573, Japan
- Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan
- International Research Institute of Disaster Science, Tohoku University, Sendai, Miyagi, Japan
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Santo K, Santos RD, Girotto AN, Nieri J, Monfardini F, Raupp P, Pereira PM, Berwanger O, Machline-Carrion MJ. Statins use for primary prevention of cardiovascular disease: A population-based digitally enabled real-world evidence cross-sectional study in primary care in Brazil. J Clin Lipidol 2024; 18:e384-e393. [PMID: 38431498 DOI: 10.1016/j.jacl.2024.02.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 12/20/2023] [Accepted: 02/14/2024] [Indexed: 03/05/2024]
Abstract
BACKGROUND Statins are the main strategy to reduce dyslipidemia-related cardiovascular risk. Nevertheless, there is scarce evidence on the real-world statins use in primary care settings in low-middle-income countries. OBJECTIVE We conducted a cross-sectional retrospective study using anonymized data routinely collected by community health workers in Brazil aimed to evaluate statin use and associated factors in a primary prevention population with cardiovascular risk enhancers. METHODS Study population consisted of adults with hypertension, diabetes, and/or dyslipidemia. The primary and secondary outcomes were the proportion of individuals self-reporting statins use on any dose and high-dose statins/high-intensity lipid-lowering therapy (LLT), respectively. RESULTS Of the 2,133,900 adult individuals in the database, 415,766 (19.5%) were included in the study cohort. From this cohort, 89.1% had hypertension, 28.9% diabetes, and 5.5% dyslipidemia. The mean age was 61.5 (standard deviation 14.5) years, 63.4% were female, and 61.0% were of mixed-race. Only 2.6% and 0.1% of individuals self-reported the use of statins and high-dose statins/high-intensity LLT, respectively. Older age (odds ratio [OR] 1.96; 95% confidence interval [CI] 1.88, 2.05, p < 0.001), living in the South region of Brazil (OR 4.39; 95% CI 3.97, 4.85, p < 0.001), heart failure (OR 2.60; 95% CI 2.33, 2.89, p < 0.001), chronic kidney disease (OR 1.49; 95% CI 1.35, 1.64, p < 0.001), and anti-hypertensive medications use (OR 4.38; 95% CI 4.07, 4.71, p < 0.001) were independently associated with statin use. CONCLUSION In a real-world evidence study analyzing data routinely collected in a digitized primary care setting, we observed a very low use of statins in a primary prevention population with cardiovascular risk enhancers in Brazil. Socio-demographic factors and co-morbidities were associated with higher statins use rates.
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Affiliation(s)
- Karla Santo
- Hospital Israelita Albert Einstein, 755 Comendador Elias Jafet Street, room 408/409, Floor L4, Morumbi, São Paulo, SP, Postal Code 05653-000, Brazil (Santo, Santos, Nieri, Monfardini and Berwanger).
| | - Raul D Santos
- Hospital Israelita Albert Einstein, 755 Comendador Elias Jafet Street, room 408/409, Floor L4, Morumbi, São Paulo, SP, Postal Code 05653-000, Brazil (Santo, Santos, Nieri, Monfardini and Berwanger); Heart Institute (InCor), University of Sao Paulo Medical School, 44 Dr Enéas Carvalho de Aguiar Avenue, Cerqueira César, São Paulo, SP, Postal Code 05403-900, Brazil (Santos)
| | - Alysson Nathan Girotto
- epHealth Primary Care Solutions, 3339 Dr. Antônio Luiz Moura Gonzaga Road, Room 107 Block A, Rio Tavares, Florianópolis, SC, Postal Code 88048-300, Brazil (Girotto and Pereira)
| | - Josue Nieri
- Hospital Israelita Albert Einstein, 755 Comendador Elias Jafet Street, room 408/409, Floor L4, Morumbi, São Paulo, SP, Postal Code 05653-000, Brazil (Santo, Santos, Nieri, Monfardini and Berwanger)
| | - Frederico Monfardini
- Hospital Israelita Albert Einstein, 755 Comendador Elias Jafet Street, room 408/409, Floor L4, Morumbi, São Paulo, SP, Postal Code 05653-000, Brazil (Santo, Santos, Nieri, Monfardini and Berwanger)
| | - Priscila Raupp
- Novartis Biociências Brazil, 90 Professor Vicente Rao Avenue, Cidade Monções, São Paulo, SP, Postal Code 04706-900, Brazil (Raupp)
| | - Pedro Marton Pereira
- epHealth Primary Care Solutions, 3339 Dr. Antônio Luiz Moura Gonzaga Road, Room 107 Block A, Rio Tavares, Florianópolis, SC, Postal Code 88048-300, Brazil (Girotto and Pereira); epHealth UK, C/O Taylor Vinters, Floor 33 Tower 42, 25 Old Broad Street, London, EC2N 1HQ, United Kingdom (Pereira); Instituto epHealth, 2302 Consolação Street, CJ 21, Room 104, Consolação, Sao Paulo, SP, Postal Code 01302-001, Brazil (Pereira)
| | - Otavio Berwanger
- Hospital Israelita Albert Einstein, 755 Comendador Elias Jafet Street, room 408/409, Floor L4, Morumbi, São Paulo, SP, Postal Code 05653-000, Brazil (Santo, Santos, Nieri, Monfardini and Berwanger); The George Institute for Global Health, 4 Wood Ln, London, NW9 7PA, United Kingdom (Berwanger); Imperial College London, 80 Wood Ln, London, W12 7TA, United Kingdom (Berwanger)
| | - M Julia Machline-Carrion
- epHealth UK, C/O Taylor Vinters, Floor 33 Tower 42, 25 Old Broad Street, London, EC2N 1HQ, United Kingdom (Pereira); Instituto epHealth, 2302 Consolação Street, CJ 21, Room 104, Consolação, Sao Paulo, SP, Postal Code 01302-001, Brazil (Pereira)
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Kihara T, Yamagishi K, Imatoh T, Ihira H, Goto A, Iso H, Sawada N, Tsugane S, Inoue M. Validity of self-reported Helicobacter pylori eradication treatment from questionnaire and interview surveys of the JPHC-NEXT study: comparison with prescription history from insurance claims data. J Epidemiol 2024:JE20230168. [PMID: 38191180 DOI: 10.2188/jea.je20230168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2024] Open
Abstract
BACKGROUND We aimed to evaluate the validity of self-administered questionnaire surveys and face-to-face interview surveys for the detection of Helicobacter pylori eradication therapy. METHODS Participants were a cohort, aged 40-74 years, living in three different locations of Japan, who took part in the baseline survey (2011-2012) of the Japan Public Health Center-based Prospective Study for the Next Generation (JPHC-NEXT). Five years after the baseline survey, a questionnaire and interview survey were independently conducted to determine the history of Helicobacter pylori eradication treatment over the 5-year period. Prescription of Helicobacter pylori eradication medications in national insurance claims data from the baseline survey to the 5-year survey was used as a reference standard. RESULTS In total, 15,760 questionnaire surveys and 8,006 interview surveys were included in the analysis. There were 3,471 respondents to the questionnaire and 2,398 respondents to the interview who reported having received Helicobacter pylori eradication treatment within the past five years. Comparison of the questionnaire survey to national insurance claims data showed a sensitivity of 95.1% (2213/2328), specificity of 90.6% (12174/13432), positive predictive value of 63.8% (2213/3471), negative predictive value of 99.1% (12174/12289), and Cohen's Kappa value of 0.71. Respective values of the interview survey were 94.4% (1694/1795), 88.7% (5507/6211), 70.6% (1694/2398), 98.2% (5507/5608), and 0.74. CONCLUSION Both the questionnaire and the interview showed high sensitivity, high specificity, and good agreement with the insurance claim prescriptions data. Some participants may have received eradication treatment without going through the public insurance claim database, resulting in a low positive predictive value.
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Affiliation(s)
- Tomomi Kihara
- Department of Public Health Medicine, Institute of Medicine, and Health Service Research and Development Center, University of Tsukuba
| | - Kazumasa Yamagishi
- Department of Public Health Medicine, Institute of Medicine, and Health Service Research and Development Center, University of Tsukuba
- Ibaraki Western Medical Center
| | - Takuya Imatoh
- Division of Cohort Research, Institute for Cancer Control, National Cancer Center
| | - Hikaru Ihira
- Division of Cohort Research, Institute for Cancer Control, National Cancer Center
| | - Atsushi Goto
- Department of Health Data Science, Graduate School of Data Science, Yokohama City University
| | - Hiroyasu Iso
- Department of Public Health Medicine, Institute of Medicine, and Health Service Research and Development Center, University of Tsukuba
- Bureau of International Health Cooperation, National Center for Global Health and Medicine
| | - Norie Sawada
- Division of Cohort Research, Institute for Cancer Control, National Cancer Center
| | - Shoichiro Tsugane
- Division of Cohort Research, Institute for Cancer Control, National Cancer Center
- National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition
| | - Manami Inoue
- Division of Cohort Research, Institute for Cancer Control, National Cancer Center
- Division of Prevention, Institute for Cancer Control, National Cancer Center
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Zhao T, Yan Q, Wang C, Zeng J, Zhang R, Wang H, Pu L, Dai X, Liu H, Han L. Identification of Serum Biomarkers of Ischemic Stroke in a Hypertensive Population Based on Metabolomics and Lipidomics. Neuroscience 2023; 533:22-35. [PMID: 37806545 DOI: 10.1016/j.neuroscience.2023.09.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 09/21/2023] [Accepted: 09/25/2023] [Indexed: 10/10/2023]
Abstract
Hypertensive individuals are at a high risk of stroke, and thus, prevention of stroke in hypertensive patients is essential. Metabolomics and lipidomics can be used to identify diagnostic biomarkers and conduct early assessments of stroke risk in hypertensive populations. In this study, serum samples were collected from 30 hypertensive ischemic stroke (IS), 30 matched hypertensive and 30 matched healthy participants. Metabolomics and lipidomics analyses were conducted via liquid chromatography-tandem mass spectrometry, and the data were analyzed using multivariate and univariate statistical methods. A random forest algorithm and binary logistic regression were used to screen the biomarkers and establish diagnostic model. We detected 21 differential metabolites and 38 differential lipids between the hypertensive IS and healthy group. Moreover, we found 18 differential metabolites and 31 differential lipids between the hypertensive IS and hypertension group. In particular, the following seven metabolites or lipids distinguished the hypertensive IS from the healthy group: 4-hydroxyphenylpyruvic acid, cafestol, phosphatidylethanolamine (PE) (18:0p/18:2), PE (16:0e/20:4), (O-acyI)-1-hydroxy fatty acid (36:3), PE (16:0p/20:3) and PE (18:1p/18:2) (rep). The following seven biomarkers distinguished the hypertensive IS from the hypertension group: diglyceride (DG) (20:1/18:2), PE (18:0p/18:2), PE (16:0e/22:5), phosphatidylcholine (40:7), dimethylphosphatidylethanolamine (50:3), DG (18:1/18:2), and 4-hydroxyphenylpyruvic acid. The aforementioned panels had good diagnostic and predictive ability for hypertensive IS. Our study determines the metabolomic and lipidomic profiles of hypertensive IS patients and thereby identifies potential biomarkers of the presence of IS in hypertensive populations.
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Affiliation(s)
- Tian Zhao
- Key Laboratory of Diagnosis and Treatment of Digestive System Tumors of Zhejiang Province, Ningbo No. 2 Hospital, Ningbo 315000, China; Center for Cardiovascular and Cerebrovascular Epidemiology and Translational Medicine, Guoke Ningbo Life Science and Health Industry Research Institute, Ningbo 315000, China.
| | - Qianqian Yan
- Center for Cardiovascular and Cerebrovascular Epidemiology and Translational Medicine, Guoke Ningbo Life Science and Health Industry Research Institute, Ningbo 315000, China.
| | - Changyi Wang
- Department of Non-Communicable Disease Prevention and Control, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen 518000, China.
| | - Jingjing Zeng
- Key Laboratory of Diagnosis and Treatment of Digestive System Tumors of Zhejiang Province, Ningbo No. 2 Hospital, Ningbo 315000, China; Center for Cardiovascular and Cerebrovascular Epidemiology and Translational Medicine, Guoke Ningbo Life Science and Health Industry Research Institute, Ningbo 315000, China.
| | - Ruijie Zhang
- Key Laboratory of Diagnosis and Treatment of Digestive System Tumors of Zhejiang Province, Ningbo No. 2 Hospital, Ningbo 315000, China; Center for Cardiovascular and Cerebrovascular Epidemiology and Translational Medicine, Guoke Ningbo Life Science and Health Industry Research Institute, Ningbo 315000, China.
| | - Han Wang
- Key Laboratory of Diagnosis and Treatment of Digestive System Tumors of Zhejiang Province, Ningbo No. 2 Hospital, Ningbo 315000, China; Center for Cardiovascular and Cerebrovascular Epidemiology and Translational Medicine, Guoke Ningbo Life Science and Health Industry Research Institute, Ningbo 315000, China.
| | - Liyuan Pu
- Key Laboratory of Diagnosis and Treatment of Digestive System Tumors of Zhejiang Province, Ningbo No. 2 Hospital, Ningbo 315000, China; Center for Cardiovascular and Cerebrovascular Epidemiology and Translational Medicine, Guoke Ningbo Life Science and Health Industry Research Institute, Ningbo 315000, China.
| | - Xiaoyu Dai
- Department of Anus & Intestine Surgery, Ningbo No. 2 Hospital, Ningbo 315000, China.
| | - Huina Liu
- Key Laboratory of Diagnosis and Treatment of Digestive System Tumors of Zhejiang Province, Ningbo No. 2 Hospital, Ningbo 315000, China; Center for Cardiovascular and Cerebrovascular Epidemiology and Translational Medicine, Guoke Ningbo Life Science and Health Industry Research Institute, Ningbo 315000, China.
| | - Liyuan Han
- Key Laboratory of Diagnosis and Treatment of Digestive System Tumors of Zhejiang Province, Ningbo No. 2 Hospital, Ningbo 315000, China; Center for Cardiovascular and Cerebrovascular Epidemiology and Translational Medicine, Guoke Ningbo Life Science and Health Industry Research Institute, Ningbo 315000, China.
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6
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Sakima A, Yamazato M, Kohagura K, Ishida A, Matayoshi T, Tana T, Nakamura Y, Ohya Y. Achievement rate of target blood pressure in patients with hypertension treated by hypertension specialists and non-specialists in a real-world setting. Hypertens Res 2023; 46:2460-2469. [PMID: 37414873 DOI: 10.1038/s41440-023-01362-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 06/13/2023] [Accepted: 06/15/2023] [Indexed: 07/08/2023]
Abstract
Hypertension remains a major global healthcare issue. Considering that most Japanese patients with hypertension are managed by general practitioners, hypertension specialists should be involved in actual clinical practice. We investigated the blood pressure (BP), guidelines recommended for achievement rate of the target BP, and clinical variables of patients with hypertension treated by hypertension specialists and those treated by non-specialists in a real-world setting. Factors associated with the target BP achievement in this population were also investigated. Outpatients with hypertension from 12 medical facilities in Okinawa Prefecture were enrolled (n = 1469 [specialist group, 794; non-specialist group, 675]; mean age, 64.2 years; females, 45.8%). For all patients, BP and rate of the target BP achievement were 129.0 ± 15.5/74.6 ± 10.6 mmHg, and 51.8%, respectively. BP and the rate of target of BP achievement were 128.0 ± 15.1/73.4 ± 10.4 mmHg and 56.7% in the specialist group, and they were 130.1 ± 15.9/76.0 ± 10.8 mmHg and 46.1% in the non-specialist group. The urinary salt excretion and obesity rates were comparable between the specialist and non-specialist groups. Multivariable logistic analyses indicated that hypertension specialists and good medication adherence were positive factors, whereas obesity, chronic kidney disease, diabetes mellitus, and urinary salt excretion were inverse factors associated with target BP achievement in this population. Initiatives for salt reduction, medication adherence, and proper obesity management are crucial to improving BP management in patients with hypertension. Hypertension specialists are expected to play an essential role in them. For all patients, the target blood pressure (BP) achievement rate were 51.8%. Hypertension specialists and good medication adherence were positive factors in achieving target BP; conversely, obesity, diabetes mellitus, chronic kidney disease, and high urinary salt excretion were inverse factors in achieving target BP among patients with hypertension.
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Affiliation(s)
- Atsushi Sakima
- Health Administration Center, University of the Ryukyus, Okinawa, Japan.
| | - Masanobu Yamazato
- Department of Cardiovascular Medicine, Nephrology and Neurology, Graduate School of Medicine, University of the Ryukyus, Okinawa, Japan
| | - Kentaro Kohagura
- Dialysis Unit, University Hospital of the Ryukyus, Okinawa, Japan
| | - Akio Ishida
- Department of Cardiovascular Medicine, Nephrology and Neurology, Graduate School of Medicine, University of the Ryukyus, Okinawa, Japan
| | - Tetsutaro Matayoshi
- Department of Cardiovascular Medicine, Nephrology and Neurology, Graduate School of Medicine, University of the Ryukyus, Okinawa, Japan
| | | | | | - Yusuke Ohya
- Department of Cardiovascular Medicine, Nephrology and Neurology, Graduate School of Medicine, University of the Ryukyus, Okinawa, Japan
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7
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Chen Y, Xu W, Zhang W, Tong R, Yuan A, Li Z, Jiang H, Hu L, Huang L, Xu Y, Zhang Z, Sun M, Yan X, Chen AF, Qian K, Pu J. Plasma metabolic fingerprints for large-scale screening and personalized risk stratification of metabolic syndrome. Cell Rep Med 2023; 4:101109. [PMID: 37467725 PMCID: PMC10394172 DOI: 10.1016/j.xcrm.2023.101109] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 04/01/2023] [Accepted: 06/16/2023] [Indexed: 07/21/2023]
Abstract
Direct diagnosis and accurate assessment of metabolic syndrome (MetS) allow for prompt clinical interventions. However, traditional diagnostic strategies overlook the complex heterogeneity of MetS. Here, we perform metabolomic analysis in 13,554 participants from the natural cohort and identify 26 hub plasma metabolic fingerprints (PMFs) associated with MetS and its early identification (pre-MetS). By leveraging machine-learning algorithms, we develop robust diagnostic models for pre-MetS and MetS with convincing performance through independent validation. We utilize these PMFs to assess the relative contributions of the four major MetS risk factors in the general population, ranked as follows: hyperglycemia, hypertension, dyslipidemia, and obesity. Furthermore, we devise a personalized three-dimensional plasma metabolic risk (PMR) stratification, revealing three distinct risk patterns. In summary, our study offers effective screening tools for identifying pre-MetS and MetS patients in the general community, while defining the heterogeneous risk stratification of metabolic phenotypes in real-world settings.
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Affiliation(s)
- Yifan Chen
- Division of Cardiology, State Key Laboratory of Systems Medicine for Cancer, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Road, Shanghai 200127, China
| | - Wei Xu
- Division of Cardiology, State Key Laboratory of Systems Medicine for Cancer, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Road, Shanghai 200127, China
| | - Wei Zhang
- Division of Cardiology, State Key Laboratory of Systems Medicine for Cancer, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Road, Shanghai 200127, China
| | - Renyang Tong
- Division of Cardiology, State Key Laboratory of Systems Medicine for Cancer, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Road, Shanghai 200127, China
| | - Ancai Yuan
- Division of Cardiology, State Key Laboratory of Systems Medicine for Cancer, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Road, Shanghai 200127, China
| | - Zheng Li
- Division of Cardiology, State Key Laboratory of Systems Medicine for Cancer, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Road, Shanghai 200127, China
| | - Huiru Jiang
- Division of Cardiology, State Key Laboratory of Systems Medicine for Cancer, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Road, Shanghai 200127, China
| | - Liuhua Hu
- Division of Cardiology, State Key Laboratory of Systems Medicine for Cancer, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Road, Shanghai 200127, China
| | - Lin Huang
- Country Department of Clinical Laboratory Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Yudian Xu
- School of Biomedical Engineering, Institute of Medical Robotics and Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Ziyue Zhang
- School of Biomedical Engineering, Institute of Medical Robotics and Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Mingze Sun
- Division of Cardiology, State Key Laboratory of Systems Medicine for Cancer, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Road, Shanghai 200127, China
| | - Xiaoxiang Yan
- Department of Cardiovascular Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Alex F Chen
- Institute for Developmental and Regenerative Cardiovascular Medicine, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200092, China.
| | - Kun Qian
- Division of Cardiology, State Key Laboratory of Systems Medicine for Cancer, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Road, Shanghai 200127, China; School of Biomedical Engineering, Institute of Medical Robotics and Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai 200030, China.
| | - Jun Pu
- Division of Cardiology, State Key Laboratory of Systems Medicine for Cancer, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Road, Shanghai 200127, China.
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8
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Vasquez MS, Mertens E, Berete F, Van der Heyden J, Peñalvo JL, Vandevijvere S. Comparing self-reported health interview survey and pharmacy billing data in determining the prevalence of diabetes, hypertension, and hypercholesterolemia in Belgium. Arch Public Health 2023; 81:121. [PMID: 37391854 DOI: 10.1186/s13690-023-01134-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Accepted: 06/15/2023] [Indexed: 07/02/2023] Open
Abstract
BACKGROUND Administrative and health surveys are used in monitoring key health indicators in a population. This study investigated the agreement between self-reported disease status from the Belgian Health Interview Survey (BHIS) and pharmaceutical insurance claims extracted from the Belgian Compulsory Health Insurance (BCHI) in ascertaining the prevalence of diabetes, hypertension, and hypercholesterolemia. METHODS Linkage was made between the BHIS 2018 and the BCHI 2018, from which chronic condition was ascertained using the Anatomical Therapeutic Chemical (ATC) classification and defined daily dose. The data sources were compared using estimates of disease prevalence and various measures of agreement and validity. Multivariable logistic regression was performed for each chronic condition to identify the factors associated to the agreement between the two data sources. RESULTS The prevalence estimates computed from the BCHI and the self-reported disease definition in BHIS, respectively, are 5.8% and 5.9% diabetes cases, 24.6% and 17.6% hypertension cases, and 16.2% and 18.1% of hypercholesterolemia cases. The overall agreement and kappa coefficient between the BCHI and the self-reported disease status is highest for diabetes and is equivalent to 97.6% and 0.80, respectively. The disagreement between the two data sources in ascertaining diabetes is associated with multimorbidity and older age categories. CONCLUSION This study demonstrated the capability of pharmacy billing data in ascertaining and monitoring diabetes in the Belgian population. More studies are needed to assess the applicability of pharmacy claims in ascertaining other chronic conditions and to evaluate the performance of other administrative data such as hospital records containing diagnostic codes.
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Affiliation(s)
- Maria Salve Vasquez
- Department of Epidemiology and Public Health, Service of Health Information, Sciensano, Brussels, Belgium.
| | - Elly Mertens
- Unit of Non-Communicable Diseases, Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgium
| | - Finaba Berete
- Department of Epidemiology and Public Health, Service of Health Information, Sciensano, Brussels, Belgium
| | - Johan Van der Heyden
- Department of Epidemiology and Public Health, Service of Health Information, Sciensano, Brussels, Belgium
| | - José L Peñalvo
- Unit of Non-Communicable Diseases, Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgium
| | - Stefanie Vandevijvere
- Department of Epidemiology and Public Health, Service of Health Information, Sciensano, Brussels, Belgium
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9
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Mulligan MD, Murphy R, Reddin C, Judge C, Ferguson J, Alvarez-Iglesias A, McGrath ER, O’Donnell MJ. Population attributable fraction of hypertension for dementia: global, regional, and national estimates for 186 countries. EClinicalMedicine 2023; 60:102012. [PMID: 37261323 PMCID: PMC10227413 DOI: 10.1016/j.eclinm.2023.102012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 04/30/2023] [Accepted: 05/02/2023] [Indexed: 06/02/2023] Open
Abstract
Background Quantifying the proportion of dementia attributable to highly prevalent modifiable risk factors, such as hypertension, is important in informing effective dementia prevention strategies. We aim to quantify the population attributable fraction (PAF) of hypertension for dementia (the proportion of dementia cases that would not occur if hypertension was eliminated) at global, regional, and national levels. Methods In this study, we searched international and governmental websites for global, regional, and national data reporting population hypertension (according to 10-year age categories) and dementia prevalence. MEDLINE was searched for studies reporting the risk of dementia from age at hypertension diagnosis from database inception to December 31, 2022. Longitudinal observational studies with >500 participants reporting hazard ratios by age at hypertension diagnosis for risk of future all-cause dementia were eligible for inclusion. Studies excluded had cross-sectional methodology, specific vascular dementia or 'cognitive impairment' outcomes, and no age-specific metrics of association reported. The PAF of hypertension for dementia was calculated globally and for each country and region worldwide. Findings Data from the Global Burden of Disease, United Nations Population Prospectus, NCD Risk Factor Collaboration, UK Biobank, and Atherosclerosis Risk in Communities Study were obtained. 186 countries reported dementia and hypertension prevalence data. The global PAF of hypertension for dementia was 15.8% [95% Credible Interval (CI), 8.8%-22.7%]. Latin America and the Caribbean (18.0% [95% CI, 9.4%-26.6%]), and Europe (17.2% [95% CI, 9.6%-24.7%]) had the highest PAF of hypertension for dementia. Hypertension diagnosed between the ages of 30-44 had the highest age-specific global attributable fraction for dementia (8.4% [95% CI, 3.4%-13.5%]), followed by ages 45-54 (2.92% [ 95% CI, 0.96%-4.88%]), 55-64 (2.59% [95% CI, 1.15%-4.03%]) and 65-74 (1.82% [95% CI, -2.31%-5.96%]). Interpretation The population attributable risk of hypertension for dementia is 15.8%, suggesting that optimal detection and treatment, particularly at midlife, has the potential to markedly reduce the global burden of dementia. Funding Wellcome Trust; Health Research Board of Ireland; Alzheimer's Association.
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Affiliation(s)
- Martin D. Mulligan
- School of Medicine, University of Galway, University Road, Galway, H91TK33, Ireland
- HRB Clinical Research Facility, University of Galway, University Road, Galway, H91TK33, Ireland
| | - Robert Murphy
- School of Medicine, University of Galway, University Road, Galway, H91TK33, Ireland
- HRB Clinical Research Facility, University of Galway, University Road, Galway, H91TK33, Ireland
| | - Catriona Reddin
- School of Medicine, University of Galway, University Road, Galway, H91TK33, Ireland
- HRB Clinical Research Facility, University of Galway, University Road, Galway, H91TK33, Ireland
| | - Conor Judge
- School of Medicine, University of Galway, University Road, Galway, H91TK33, Ireland
- HRB Clinical Research Facility, University of Galway, University Road, Galway, H91TK33, Ireland
| | - John Ferguson
- HRB Clinical Research Facility, University of Galway, University Road, Galway, H91TK33, Ireland
| | - Alberto Alvarez-Iglesias
- School of Medicine, University of Galway, University Road, Galway, H91TK33, Ireland
- HRB Clinical Research Facility, University of Galway, University Road, Galway, H91TK33, Ireland
| | - Emer R. McGrath
- School of Medicine, University of Galway, University Road, Galway, H91TK33, Ireland
- HRB Clinical Research Facility, University of Galway, University Road, Galway, H91TK33, Ireland
| | - Martin J. O’Donnell
- School of Medicine, University of Galway, University Road, Galway, H91TK33, Ireland
- HRB Clinical Research Facility, University of Galway, University Road, Galway, H91TK33, Ireland
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10
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Heikkinen J, Honkanen RJ, Williams LJ, Quirk S, Kröger H, Koivumaa-Honkanen H. Comparing self-reports to national register data in the detection of disabling mental and musculoskeletal disorders among ageing women. Maturitas 2022; 164:46-51. [DOI: 10.1016/j.maturitas.2022.06.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Revised: 04/10/2022] [Accepted: 06/14/2022] [Indexed: 10/17/2022]
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11
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Metabolic Syndrome and Prostate Cancer Risk in Mexican Men: A Population Case-control Study. Arch Med Res 2022; 53:594-602. [DOI: 10.1016/j.arcmed.2022.07.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 07/06/2022] [Accepted: 07/15/2022] [Indexed: 11/20/2022]
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12
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Sasaki M, Miyagawa N, Harada S, Tsubota K, Takebayashi T, Nishiwaki Y, Kawasaki R. Dietary Patterns and Their Associations with Intermediate Age-Related Macular Degeneration in a Japanese Population. J Clin Med 2022; 11:jcm11061617. [PMID: 35329943 PMCID: PMC8955354 DOI: 10.3390/jcm11061617] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 03/09/2022] [Accepted: 03/11/2022] [Indexed: 11/22/2022] Open
Abstract
This population-based cross-sectional study investigated the influence of dietary patterns on age-related macular degeneration (AMD) in a Japanese population. The Tsuruoka Metabolomics Cohort Study enrolled a general population aged 35–74 years from among participants in annual health check-up programs in Tsuruoka City, Japan. Eating habits were assessed using a food frequency questionnaire. Principal component analysis was used to identify dietary patterns among food items. The association between quartiles of scores for each dietary pattern and intermediate AMD was assessed using multivariate logistic regression models. Of 3433 participants, 415 had intermediate AMD. We identified four principal components comprising the Vegetable-rich pattern, Varied staple food pattern, Animal-rich pattern, and Seafood-rich pattern. After adjusting for potential confounders, higher Varied staple food diet scores were associated with a lower prevalence of intermediate AMD (fourth vs. first quartile) (OR, 0.63; 95% confidence interval [CI], 0.46–0.86). A significant trend of decreasing ORs for intermediate AMD associated with increasing Varied staple food diet scores was noted (p for trend = 0.002). There was no significant association between the other dietary patterns and intermediate AMD. In a Japanese population, individuals with a dietary pattern score high in the Varied staple food pattern had a lower prevalence of intermediate AMD.
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Affiliation(s)
- Mariko Sasaki
- Department of Ophthalmology, Keio University School of Medicine, Tokyo 160-8582, Japan;
- Department of Ophthalmology, Tachikawa Hospital, Tokyo 190-8531, Japan
- National Institute of Sensory Organs, National Tokyo Medical Center, Tokyo 152-8902, Japan
- Correspondence:
| | - Naoko Miyagawa
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo 160-8582, Japan; (N.M.); (S.H.); (T.T.)
| | - Sei Harada
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo 160-8582, Japan; (N.M.); (S.H.); (T.T.)
| | - Kazuo Tsubota
- Department of Ophthalmology, Keio University School of Medicine, Tokyo 160-8582, Japan;
| | - Toru Takebayashi
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo 160-8582, Japan; (N.M.); (S.H.); (T.T.)
| | - Yuji Nishiwaki
- Department of Environmental and Occupational Health, Toho University, Tokyo 143-8540, Japan;
| | - Ryo Kawasaki
- Department of Vision Informatics (Topcon), Osaka University Graduate School of Medicine, Osaka 565-0871, Japan;
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13
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Hara A, Hirata T, Okamura T, Kimura S, Urushihara H. Lifestyle behaviors associated with the initiation of renal replacement therapy in Japanese patients with chronic kidney disease: a retrospective cohort study using a claims database linked with specific health checkup results. Environ Health Prev Med 2021; 26:102. [PMID: 34627137 PMCID: PMC8502396 DOI: 10.1186/s12199-021-01022-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 09/24/2021] [Indexed: 11/10/2022] Open
Abstract
Background Chronic kidney disease (CKD) is an independent risk factor for progression to an end-stage renal disease requiring dialysis or kidney transplantation. We investigated the association of lifestyle behaviors with the initiation of renal replacement therapy (RRT) among CKD patients using an employment-based health insurance claims database linked with specific health checkup (SHC) data. Methods This retrospective cohort study included 149,620 CKD patients aged 40–74 years who underwent a SHC between April 2008 and March 2016. CKD patients were identified using ICD-10 diagnostic codes and SHC results. We investigated lifestyle behaviors recorded at SHC. Initiation of RRT was defined by medical procedure claims. Lifestyle behaviors related to the initiation of RRT were identified using a Cox proportional hazards regression model with recency-weighted cumulative exposure as a time-dependent covariate. Results During 384,042 patient-years of follow-up by the end of March 2016, 295 dialysis and no kidney transplantation cases were identified. Current smoking (hazard ratio: 1.87, 95% confidence interval, 1.04─3.36), skipping breakfast (4.80, 1.98─11.62), and taking sufficient rest along with sleep (2.09, 1.14─3.85) were associated with the initiation of RRT. Conclusions Among CKD patients, the lifestyle behaviors of smoking, skipping breakfast, and sufficient rest along with sleep were independently associated with the initiation of RRT. Our study strengthens the importance of monitoring lifestyle behaviors to delay the progression of mild CKD to RRT in the Japanese working generation. A substantial portion of subjects had missing data for eGFR and drinking frequency, warranting verification of these results in prospective studies. Supplementary Information The online version contains supplementary material available at 10.1186/s12199-021-01022-3.
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Affiliation(s)
- Azusa Hara
- Division of Drug Development and Regulatory Science, Faculty of Pharmacy, Keio University, 1-5-30, Shibakoen, Minato-ku, Tokyo, 105-8512, Japan
| | - Takumi Hirata
- Department of Public Health, Hokkaido University Faculty of Medicine, Sapporo, Japan
| | - Tomonori Okamura
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan
| | | | - Hisashi Urushihara
- Division of Drug Development and Regulatory Science, Faculty of Pharmacy, Keio University, 1-5-30, Shibakoen, Minato-ku, Tokyo, 105-8512, Japan.
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14
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Worldwide trends in hypertension prevalence and progress in treatment and control from 1990 to 2019: a pooled analysis of 1201 population-representative studies with 104 million participants. Lancet 2021; 398:957-980. [PMID: 34450083 PMCID: PMC8446938 DOI: 10.1016/s0140-6736(21)01330-1] [Citation(s) in RCA: 1076] [Impact Index Per Article: 358.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 06/01/2021] [Accepted: 06/03/2021] [Indexed: 02/05/2023]
Abstract
BACKGROUND Hypertension can be detected at the primary health-care level and low-cost treatments can effectively control hypertension. We aimed to measure the prevalence of hypertension and progress in its detection, treatment, and control from 1990 to 2019 for 200 countries and territories. METHODS We used data from 1990 to 2019 on people aged 30-79 years from population-representative studies with measurement of blood pressure and data on blood pressure treatment. We defined hypertension as having systolic blood pressure 140 mm Hg or greater, diastolic blood pressure 90 mm Hg or greater, or taking medication for hypertension. We applied a Bayesian hierarchical model to estimate the prevalence of hypertension and the proportion of people with hypertension who had a previous diagnosis (detection), who were taking medication for hypertension (treatment), and whose hypertension was controlled to below 140/90 mm Hg (control). The model allowed for trends over time to be non-linear and to vary by age. FINDINGS The number of people aged 30-79 years with hypertension doubled from 1990 to 2019, from 331 (95% credible interval 306-359) million women and 317 (292-344) million men in 1990 to 626 (584-668) million women and 652 (604-698) million men in 2019, despite stable global age-standardised prevalence. In 2019, age-standardised hypertension prevalence was lowest in Canada and Peru for both men and women; in Taiwan, South Korea, Japan, and some countries in western Europe including Switzerland, Spain, and the UK for women; and in several low-income and middle-income countries such as Eritrea, Bangladesh, Ethiopia, and Solomon Islands for men. Hypertension prevalence surpassed 50% for women in two countries and men in nine countries, in central and eastern Europe, central Asia, Oceania, and Latin America. Globally, 59% (55-62) of women and 49% (46-52) of men with hypertension reported a previous diagnosis of hypertension in 2019, and 47% (43-51) of women and 38% (35-41) of men were treated. Control rates among people with hypertension in 2019 were 23% (20-27) for women and 18% (16-21) for men. In 2019, treatment and control rates were highest in South Korea, Canada, and Iceland (treatment >70%; control >50%), followed by the USA, Costa Rica, Germany, Portugal, and Taiwan. Treatment rates were less than 25% for women and less than 20% for men in Nepal, Indonesia, and some countries in sub-Saharan Africa and Oceania. Control rates were below 10% for women and men in these countries and for men in some countries in north Africa, central and south Asia, and eastern Europe. Treatment and control rates have improved in most countries since 1990, but we found little change in most countries in sub-Saharan Africa and Oceania. Improvements were largest in high-income countries, central Europe, and some upper-middle-income and recently high-income countries including Costa Rica, Taiwan, Kazakhstan, South Africa, Brazil, Chile, Turkey, and Iran. INTERPRETATION Improvements in the detection, treatment, and control of hypertension have varied substantially across countries, with some middle-income countries now outperforming most high-income nations. The dual approach of reducing hypertension prevalence through primary prevention and enhancing its treatment and control is achievable not only in high-income countries but also in low-income and middle-income settings. FUNDING WHO.
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15
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Matsumoto M, Harada S, Iida M, Kato S, Sata M, Hirata A, Kuwabara K, Takeuchi A, Sugiyama D, Okamura T, Takebayashi T. Erratum to "Validity Assessment of Self-reported Medication Use for Hypertension, Diabetes, and Dyslipidemia in a Pharmacoepidemiologic Study by Comparison With Health Insurance Claims" [J Epidemiol 31 (9) (2021) 495-502]. J Epidemiol 2021; 31:520-521. [PMID: 34305074 PMCID: PMC8328859 DOI: 10.2188/jea.je20210109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Affiliation(s)
- Minako Matsumoto
- Department of Preventive Medicine and Public Health, School of Medicine, Keio University
| | - Sei Harada
- Department of Preventive Medicine and Public Health, School of Medicine, Keio University
| | - Miho Iida
- Department of Preventive Medicine and Public Health, School of Medicine, Keio University
| | - Suzuka Kato
- Department of Preventive Medicine and Public Health, School of Medicine, Keio University
| | - Mizuki Sata
- Department of Preventive Medicine and Public Health, School of Medicine, Keio University
| | - Aya Hirata
- Department of Preventive Medicine and Public Health, School of Medicine, Keio University
| | - Kazuyo Kuwabara
- Department of Preventive Medicine and Public Health, School of Medicine, Keio University
| | - Ayano Takeuchi
- Department of Preventive Medicine and Public Health, School of Medicine, Keio University
| | - Daisuke Sugiyama
- Department of Preventive Medicine and Public Health, School of Medicine, Keio University
| | - Tomonori Okamura
- Department of Preventive Medicine and Public Health, School of Medicine, Keio University
| | - Toru Takebayashi
- Department of Preventive Medicine and Public Health, School of Medicine, Keio University
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16
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Lindbohm JV, Sipilä PN, Mars N, Knüppel A, Pentti J, Nyberg ST, Frank P, Ahmadi-Abhari S, Brunner EJ, Shipley MJ, Singh-Manoux A, Tabak AG, Batty GD, Kivimäki M. Association between change in cardiovascular risk scores and future cardiovascular disease: analyses of data from the Whitehall II longitudinal, prospective cohort study. Lancet Digit Health 2021; 3:e434-e444. [PMID: 34167764 PMCID: PMC8474012 DOI: 10.1016/s2589-7500(21)00079-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 03/28/2021] [Accepted: 04/22/2021] [Indexed: 01/09/2023]
Abstract
BACKGROUND Evaluation of cardiovascular disease risk in primary care, which is recommended every 5 years in middle-aged and older adults (typical age range 40-75 years), is based on risk scores, such as the European Society of Cardiology Systematic Coronary Risk Evaluation (SCORE) and American College of Cardiology/American Heart Association Atherosclerotic Cardiovascular Disease (ASCVD) algorithms. This evaluation currently uses only the most recent risk factor assessment. We aimed to examine whether 5-year changes in SCORE and ASCVD risk scores are associated with future cardiovascular disease risk. METHODS We analysed data from the Whitehall II longitudinal, prospective cohort study for individuals with no history of stroke, myocardial infarction, coronary artery bypass graft, percutaneous coronary intervention, definite angina, heart failure, or peripheral artery disease. Participants underwent clinical examinations in 5-year intervals between Aug 7, 1991, and Dec 6, 2016, and were followed up for incident cardiovascular disease until Oct 2, 2019. Levels of, and 5-year changes in, cardiovascular disease risk were assessed using the SCORE and ASCVD risk scores and were analysed as predictors of cardiovascular disease. Harrell's C index, continuous net reclassification improvement, the Akaike information criterion, and calibration analysis were used to assess whether incorporating change in risk scores into a model including only a single risk score assessment improved the predictive performance. We assessed the levels of, and 5-year changes in, SCORE and ASCVD risk scores as predictors of cardiovascular disease and disease-free life-years using Cox proportional hazards and flexible parametric survival models. FINDINGS 7574 participants (5233 [69·1%] men, 2341 [30·9%] women) aged 40-75 years were included in analyses of risk score change between April 24, 1997, and Oct 2, 2019. During a mean follow-up of 18·7 years (SD 5·5), 1441 (19·0%; 1042 [72·3%] men and 399 [27·7%] women) participants developed cardiovascular disease. Adding 5-year change in risk score to a model that included only a single risk score assessment improved model performance according to Harrell's C index (from 0·685 to 0·690, change 0·004 [95% CI 0·000 to 0·008] for SCORE; from 0·699 to 0·700, change 0·001 [0·000 to 0·003] for ASCVD), the Akaike information criterion (from 17 255 to 17 200, change -57 [95% CI -97 to -13] for SCORE; from 14 739 to 14 729, change -10 [-28 to 7] for ASCVD), and the continuous net reclassification index (0·353 [95% CI 0·234 to 0·447] for SCORE; 0·232 [0·030 to 0·344] for ASCVD). Both favourable and unfavourable changes in SCORE and ASCVD were associated with cardiovascular disease risk and disease-free life-years. The associations were seen in both sexes and all age groups up to the age of 75 years. At the age of 45 years, each 2-unit improvement in risk scores was associated with an additional 1·3 life-years (95% CI 0·4 to 2·2) free of cardiovascular disease for SCORE and an additional 0·9 life-years (95% CI 0·5 to 1·3) for ASCVD. At age 65 years, this same improvement was associated with an additional 0·4 life-years (95% CI 0·0 to 0·7) free of cardiovascular disease for SCORE and 0·3 life-years (95% CI 0·1 to 0·5) for ASCVD. These models were developed into an interactive calculator, which enables estimation of the number of cardiovascular disease-free life-years for an individual as a function of two risk score measurements. INTERPRETATION Changes in the SCORE and ASCVD risk scores over time inform cardiovascular disease risk prediction beyond a single risk score assessment. Repeat data might allow more accurate cardiovascular risk stratification and strengthen the evidence base for decisions on preventive interventions. FUNDING UK Medical Research Council, British Heart Foundation, Wellcome Trust, and US National Institute on Aging.
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Affiliation(s)
- Joni V Lindbohm
- Clinicum, Department of Public Health, University of Helsinki, Helsinki, Finland; Department of Epidemiology and Public Health, University College London, London, UK.
| | - Pyry N Sipilä
- Clinicum, Department of Public Health, University of Helsinki, Helsinki, Finland; Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Nina Mars
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Anika Knüppel
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Jaana Pentti
- Clinicum, Department of Public Health, University of Helsinki, Helsinki, Finland; Department of Public Health, University of Turku, Turku, Finland
| | - Solja T Nyberg
- Clinicum, Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Philipp Frank
- Department of Epidemiology and Public Health, University College London, London, UK
| | | | - Eric J Brunner
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Martin J Shipley
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Archana Singh-Manoux
- Department of Epidemiology and Public Health, University College London, London, UK; Université de Paris, Inserm U1153, Epidemiology of Ageing and Neurodegenerative diseases, Paris, France
| | - Adam G Tabak
- Department of Epidemiology and Public Health, University College London, London, UK; 1st Department of Medicine, Semmelweis University Faculty of Medicine, Budapest, Hungary
| | - G David Batty
- Department of Epidemiology and Public Health, University College London, London, UK; School of Biological and Population Health Sciences, Oregon State University, Corvallis, OR, USA
| | - Mika Kivimäki
- Clinicum, Department of Public Health, University of Helsinki, Helsinki, Finland; Department of Epidemiology and Public Health, University College London, London, UK
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