The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Associations of Combined Genetic and Lifestyle Risks With Incident Cardiovascular Disease and Diabetes in the UK Biobank Study
Open accessAbstract
Importance: Genetic and lifestyle factors both contribute to the risk of developing cardiovascular disease, but whether poor health behaviors are associated with similar increases in risk among individuals with low, intermediate, or high genetic risk is unknown. Objective: To investigate the association of combined health behaviors and factors within genetic risk groups with coronary artery disease, atrial fibrillation, stroke, hypertension, and type 2 diabetes as well as to investigate the interactions between genetic risk and lifestyle. Design, Setting, and Participants: The UK Biobank cohort study includes more than 500 000 participants aged 40 to 70 years who were recruited from 22 assessment centers across the United Kingdom from 2006 to 2010. A total of 339 003 unrelated individuals of white British descent with available genotype and matching genetic data and reported sex were included in this study from the UK Biobank population-based sample. Individuals were included in the analyses of 1 or more new-onset diseases. Data were analyzed from April 2006 to March 2015. Main Outcomes and Measures: Risks of new-onset cardiovascular disease and diabetes associated with genetic risk and combined health behaviors and factors. Genetic risk was categorized as low (quintile 1), intermediate (quintiles 2-4), or high (quintile 5). Within each genetic risk group, the risks of incident events associated with ideal, intermediate, or poor combined health behaviors and factors were investigated and compared with low genetic risk and ideal lifestyle. Results: Of 339 003 individuals, 181 702 (53.6%) were female, and the mean (SD) age was 56.86 (7.99) years. During follow-up, 9771 of 325 133 participants (3.0%) developed coronary artery disease, 7095 of 333 637 (2.1%) developed atrial fibrillation, 3145 of 332 971 (0.9%) developed stroke, 11 358 of 234 651 (4.8%) developed hypertension, and 4379 of 322 014 (1.4%) developed diabetes. Genetic risk and lifestyle were independent predictors of incident events, and there were no interactions for any outcome. Compared with ideal lifestyle in the low genetic risk group, poor lifestyle was associated with a hazard ratio of up to 4.54 (95% CI, 3.72-5.54) for coronary artery disease, 5.41 (95% CI, 4.29-6.81) for atrial fibrillation, 4.68 (95% CI, 3.85-5.69) for hypertension, 2.26 (95% CI, 1.63-3.14) for stroke, and 15.46 (95% CI, 10.82-22.08) for diabetes in the high genetic risk group. Conclusions and Relevance: In this large contemporary population, genetic composition and combined health behaviors and factors had a log-additive effect on the risk of developing cardiovascular disease. The relative effects of poor lifestyle were comparable between genetic risk groups. Behavioral lifestyle changes should be encouraged for all through comprehensive, multifactorial approaches, although high-risk individuals may be selected based on the genetic risk.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Sudlow, C., Gallacher, J., Allen, N., Beral, V., Burton, P., Danesh, J., Downey, P., Elliott, P., Green, J., Landray, M., et al. (2015) · PLOS Medicine · doi:10.1371/journal.pmed.1001779 · Cited by 12,728
Lloyd-Jones, D. M., Hong, Y., Labarthe, D., Mozaffarian, D., Appel, L. J., Van Horn, L., Greenlund, K., Daniels, S., Nichol, G., Tomaselli, G. F., et al. (2010) · Circulation · doi:10.1161/circulationaha.109.192703 · Cited by 4,750
Diet, lifestyle, and the risk of type 2 diabetes mellitus in women.
Hu, F. B., Manson, J. E., Stampfer, M. J., Colditz, G., Liu, S., Solomon, C. G., & Willett, W. C. (2001) · New England Journal of Medicine · doi:10.1056/nejmoa010492 · Cited by 2,901
Redefine statistical significance
Benjamin, D. J., Berger, J. O., Johannesson, M., Nosek, B. A., Wagenmakers, E.-J., Berk, R., Bollen, K. A., Brembs, B., Brown, L., Camerer, C., et al. (2017) · Nature Human Behaviour · doi:10.1038/s41562-017-0189-z · Cited by 2,772
A comprehensive 1000 Genomes–based genome-wide association meta-analysis of coronary artery disease
the CARDIoGRAMplusC4D Consortium (2015) · Nature Genetics · doi:10.1038/ng.3396 · Cited by 2,447
Mozaffarian, D. (2016) · Circulation · doi:10.1161/circulationaha.115.018585 · Cited by 2,216 · cited 1×
“recentdefinitionof ideal intakeofdietary components for cardiovascular health.(31) The eMethods in the Supplement includes the definitions of smoking, BMI, and physical activity, and eTable 6 in the Supplement includes the definitions and variables used for diet components.”
the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Morris, A. P., Voight, B. F., Teslovich, T. M., Ferreira, T., Segrè, A. V., Steinthorsdottir, V., Strawbridge, R. J., Khan, H., Grallert, H., et al. (2012) · Nature Genetics · doi:10.1038/ng.2383 · Cited by 1,912
Genetic Risk, Adherence to a Healthy Lifestyle, and Coronary Disease
Khera, A. V., Emdin, C. A., Drake, I., Natarajan, P., Bick, A. G., Cook, N. R., Chasman, D. I., Baber, U., Mehran, R., Rader, D. J., et al. (2016) · New England Journal of Medicine · doi:10.1056/nejmoa1605086 · Cited by 1,460
Genome-wide association study identifies 74 loci associated with educational attainment
Okbay, A., Beauchamp, J. P., Fontana, M. A., Lee, J. J., Pers, T. H., Rietveld, C. A., Turley, P., Chen, G.-B., Emilsson, V., Meddens, S. F. W., et al. (2016) · Nature · doi:10.1038/nature17671 · Cited by 1,297
Self-citationTownsend, P. (1987) · Journal of Social Policy · doi:10.1017/s0047279400020341 · Cited by 1,294
Cited by
Heart Disease and Stroke Statistics—2020 Update: A Report From the American Heart Association
Virani, S. S., Alonso, A., Benjamin, E. J., Bittencourt, M. S., Callaway, C. W., Carson, A. P., Chamberlain, A. M., Chang, A. R., Cheng, S., Delling, F. N., et al. (2020) · Circulation · doi:10.1161/cir.0000000000000757 · Cited by 9,175
Heart Disease and Stroke Statistics—2019 Update: A Report From the American Heart Association
Benjamin, E. J., Muntner, P., Alonso, A., Bittencourt, M. S., Callaway, C. W., Carson, A. P., Chamberlain, A. M., Chang, A. R., Cheng, S., Das, S. R., et al. (2019) · Circulation · doi:10.1161/cir.0000000000000659 · Cited by 9,036
Heart Disease and Stroke Statistics—2023 Update: A Report From the American Heart Association
Tsao, C. W., Aday, A. W., Almarzooq, Z. I., Anderson, C. A. M., Arora, P., Avery, C. L., Baker-Smith, C. M., Beaton, A. Z., Boehme, A. K., Buxton, A. E., et al. (2023) · Circulation · doi:10.1161/cir.0000000000001123 · Cited by 8,300
Heart Disease and Stroke Statistics—2022 Update: A Report From the American Heart Association
Tsao, C. W., Aday, A. W., Almarzooq, Z. I., Alonso, A., Beaton, A. Z., Bittencourt, M. S., Boehme, A. K., Buxton, A. E., Carson, A. P., Commodore-Mensah, Y., et al. (2022) · Circulation · doi:10.1161/cir.0000000000001052 · Cited by 5,987
Heart Disease and Stroke Statistics—2021 Update: A Report From the American Heart Association
Virani, S. S., Alonso, A., Aparicio, H. J., Benjamin, E. J., Bittencourt, M. S., Callaway, C. W., Carson, A. P., Chamberlain, A. M., Cheng, S., Delling, F. N., et al. (2021) · Circulation · doi:10.1161/cir.0000000000000950 · Cited by 5,784
Martin, S. S., Aday, A. W., Almarzooq, Z. I., Anderson, C. A. M., Arora, P., Avery, C. L., Baker-Smith, C. M., Barone Gibbs, B., Beaton, A. Z., Boehme, A. K., et al. (2024) · Circulation · doi:10.1161/cir.0000000000001209 · Cited by 2,800
Association of Lifestyle and Genetic Risk With Incidence of Dementia
Lourida, I., Hannon, E., Littlejohns, T. J., Langa, K. M., Hyppönen, E., Kuzma, E., & Llewellyn, D. J. (2019) · JAMA · doi:10.1001/jama.2019.9879 · Cited by 881
Yun, J.-S., & Ko, S.-H. (2021) · Metabolism · doi:10.1016/j.metabol.2021.154838 · Cited by 292
Han, H., Cao, Y., Feng, C., Zheng, Y., Dhana, K., Zhu, S., Shang, C., Yuan, C., & Zong, G. (2022) · Diabetes Care · doi:10.2337/dc21-1512 · Cited by 290
Obesity, unfavourable lifestyle and genetic risk of type 2 diabetes: a case-cohort study
Schnurr, T. M., Jakupović, H., Carrasquilla, G. D., Ängquist, L., Grarup, N., Sørensen, T. I. A., Tjønneland, A., Overvad, K., Pedersen, O., Hansen, T., et al. (2020) · Diabetologia · doi:10.1007/s00125-020-05140-5 · Cited by 231
Geng, T., Zhu, K., Lu, Q., Wan, Z., Chen, X., Liu, L., Pan, A., & Liu, G. (2023) · PLOS Medicine · doi:10.1371/journal.pmed.1004135 · Cited by 205
Stamatakis, E., Owen, K. B., Shepherd, L., Drayton, B., Hamer, M., & Bauman, A. E. (2021) · Epidemiology · doi:10.1097/ede.0000000000001316 · Cited by 192
Clinical utility of polygenic risk scores for coronary artery disease
Klarin, D., & Natarajan, P. (2022) · Nature Reviews Cardiology · doi:10.1038/s41569-021-00638-w · Cited by 152
The Need for a Human Pangenome Reference Sequence
Miga, K. H., & Wang, T. (2021) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-120120-081921 · Cited by 137
Muse, E. D., & Topol, E. J. (2024) · Cell Metabolism · doi:10.1016/j.cmet.2024.02.002 · Cited by 50
How Will Genetics Inform the Clinical Care of Atrial Fibrillation?
Shoemaker, M. B., Shah, R. L., Roden, D. M., & Perez, M. V. (2020) · Circulation Research · doi:10.1161/circresaha.120.316365 · Cited by 27
Karvela, M., Golden, C. T., Bell, N., Martin-Li, S., Bedzo-Nutakor, J., Bosnic, N., DeBeaudrap, P., de Mateo-Lopez, S., Alajrami, A., Qin, Y., et al. (2024) · Scientific Reports · doi:10.1038/s41598-024-55105-6 · Cited by 23
Behera, S., Belyeu, J. R., Chen, X., Paulin, L. F., Nguyen, N. Q. H., Newman, E., Mahmoud, M., Menon, V. K., Qi, Q., Joshi, P., et al. (2023) · doi:10.1101/2023.04.24.538128 · Cited by 21
Zhang, Y., Zhang, Y., Ye, Z., Yang, S., Liu, M., Wu, Q., Zhou, C., He, P., Gan, X., & Qin, X. (2024) · Cancer Epidemiology, Biomarkers & Prevention · doi:10.1158/1055-9965.epi-23-0766 · Cited by 14
Metadata
- Authors
- Said, M. A., Verweij, N., & van der Harst, P.
- Venue
- JAMA Cardiology
- Publisher
- American Medical Association (AMA)
- Published
- 2018-08-01
- Volume
- 3
- Issue
- 8
- Pages
- 693
- ISSN
- 2380-6583 (ISSN-L)
- OpenAlex
- W2810806985
- Cited by
- 641
- References
- 17
- FWCI
- 14.02
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
