The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Hypertension, Blood Pressure, and Heart Rate Variability: The Atherosclerosis Risk in Communities (ARIC) Study
Abstract
Dysregulation of the autonomic nervous system has been implicated in the development of hypertension. Heart rate variability is a noninvasive tool to quantitatively estimate cardiac autonomic activity and has been used to document decreased cardiac autonomic activity in hypertension. The ability of decreased heart rate variability to predict incident hypertension has not been well studied, and there are no studies of whether hypertension leads to changes in heart rate variability. We investigated the temporal sequence linking hypertension, blood pressure, and heart rate variability in a population-based cohort of 11 061 individuals aged 45 to 54 years at baseline. Individuals with hypertension had decreased heart rate variability at baseline, and this association was present across the full blood pressure range. Among 7099 individuals without hypertension at baseline, low heart rate variability predicted greater risk of incident hypertension over 9 years of follow-up. The hazard ratio (95% confidence interval [CI]) for the lowest compared with the highest quartile of the standard deviation of normal-to-normal R-R intervals was 1.24 (95% CI, 1.10–1.40), for the root mean square of successive differences in normal-to-normal R-R intervals was 1.36 (95% CI, 1.21–1.54), and for R-R interval was 1.44 (95% CI, 1.27–1.63). Over 9 years, there was no measurable difference in the rate of change in heart rate variability among those with and without hypertension, although the differences in heart rate variability at follow-up were smaller than those at baseline. These findings thus support the thesis that the autonomic nervous system is involved in the development of hypertension, yet suggest that differences in the autonomic profile of hypertensives and normotensives do not increase with time.
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
Heart rate variability: Standards of measurement, physiological interpretation, and clinical use
Malik, M., Bigger, J. T., Camm, A. J., Kleiger, R. E., Malliani, A., Moss, A. J., & Schwartz, P. J. (1996) · European Heart Journal · doi:10.1093/oxfordjournals.eurheartj.a014868 · Cited by 15,289
Reaven, G. M., Lithell, H., & Landsberg, L. (1996) · New England Journal of Medicine · doi:10.1056/nejm199602083340607 · Cited by 1,435
Sympathetic overactivity in hypertension. A moving target
JULIUS, S., & NESBITT, S. (1996) · American Journal of Hypertension · doi:10.1016/0895-7061(96)00287-7 · Cited by 237
Glucose tolerance and other determinants of cardiovascular autonomic function: the Hoorn Study
Gerritsen, J., Dekker, J. M., TenVoorde, B. J., Bertelsmann, F. W., Kostense, P. J., Stehouwer, C. D. A., Heine, R. J., Nijpels, G., Heethaar, R. M., & Bouter, L. M. (2000) · Diabetologia · doi:10.1007/s001250051344 · Cited by 121
Cited by
Laborde, S., Mosley, E., & Thayer, J. F. (2017) · Frontiers in Psychology · doi:10.3389/fpsyg.2017.00213 · Cited by 2,336
Thayer, J. F., Yamamoto, S. S., & Brosschot, J. F. (2010) · International Journal of Cardiology · doi:10.1016/j.ijcard.2009.09.543 · Cited by 2,276
Shaffer, F., McCraty, R., & Zerr, C. L. (2014) · Frontiers in Psychology · doi:10.3389/fpsyg.2014.01040 · Cited by 1,866
The role of vagal function in the risk for cardiovascular disease and mortality
Thayer, J. F., & Lane, R. D. (2007) · Biological Psychology · doi:10.1016/j.biopsycho.2005.11.013 · Cited by 1,033
Kemp, A. H., & Quintana, D. S. (2013) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2013.06.018 · Cited by 538
Heart rate variability in type 2 diabetes mellitus: A systematic review and meta–analysis
Benichou, T., Pereira, B., Mermillod, M., Tauveron, I., Pfabigan, D., Maqdasy, S., & Dutheil, F. (2018) · PLOS ONE · doi:10.1371/journal.pone.0195166 · Cited by 419
Considerations in the assessment of heart rate variability in biobehavioral research
Quintana, D. S., & Heathers, J. A. J. (2014) · Frontiers in Psychology · doi:10.3389/fpsyg.2014.00805 · Cited by 395
Breath of Life: The Respiratory Vagal Stimulation Model of Contemplative Activity
Gerritsen, R. J. S., & Band, G. P. H. (2018) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2018.00397 · Cited by 342
Diabetes, Glucose, Insulin, and Heart Rate Variability
Schroeder, E. B., Chambless, L. E., Liao, D., Prineas, R. J., Evans, G. W., Rosamond, W. D., & Heiss, G. (2005) · Diabetes Care · doi:10.2337/diacare.28.3.668 · Cited by 302
Self-citationMicro- and nanoplastics: A new cardiovascular risk factor?
Zhu, X., Wang, C., Duan, X., Liang, B., Genbo Xu, E., & Huang, Z. (2023) · Environment International · doi:10.1016/j.envint.2022.107662 · Cited by 273
RR Interval Variability Is Inversely Related to Inflammatory Markers: The CARDIA Study
Sloan, R. P., McCreath, H., Tracey, K. J., Sidney, S., Liu, K., & Seeman, T. (2007) · Molecular Medicine · doi:10.2119/2006-00112.sloan · Cited by 264
Does inadequate sleep play a role in vulnerability to obesity?
Knutson, K. L. (2012) · American Journal of Human Biology · doi:10.1002/ajhb.22219 · Cited by 241
Li, K., Cardoso, C., Moctezuma-Ramirez, A., Elgalad, A., & Perin, E. (2023) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph20247146 · Cited by 160
DeepHeart: Semi-Supervised Sequence Learning for Cardiovascular Risk Prediction
Ballinger, B., Hsieh, J., Singh, A., Sohoni, N., Wang, J., Tison, G., Marcus, G., Sanchez, J., Maguire, C., Olgin, J., et al. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v32i1.11891 · Cited by 156
Possibilities and limitations of the polar RS800 in measuring heart rate variability at rest
Wallén, M. B., Hasson, D., Theorell, T., Canlon, B., & Osika, W. (2012) · European Journal of Applied Physiology · doi:10.1007/s00421-011-2079-9 · Cited by 135
Picard, M., Tauveron, I., Magdasy, S., Benichou, T., Bagheri, R., Ugbolue, U. C., Navel, V., & Dutheil, F. (2021) · PLoS ONE · doi:10.1371/journal.pone.0251863 · Cited by 130
Tang, Y., Shah, H., Bueno Junior, C. R., Sun, X., Mitri, J., Sambataro, M., Sambado, L., Gerstein, H. C., Fonseca, V., Doria, A., et al. (2021) · Diabetes Care · doi:10.2337/dc20-1842 · Cited by 60
Effects of exercise during pregnancy on maternal heart rate and heart rate variability
May, L. E., Knowlton, J., Hanson, J., Suminski, R., Paynter, C., Fang, X., & Gustafson, K. M. (2016) · PM&R · doi:10.1016/j.pmrj.2015.11.006 · Cited by 49
Salles, G. F., Ribeiro, F. M., Guimarães, G. M., Muxfeldt, E. S., & Cardoso, C. R. L. (2014) · Journal of Hypertension · doi:10.1097/hjh.0000000000000068 · Cited by 34
Tak, L. M., Janssens, K. A. M., Dietrich, A., Slaets, J. P. J., & Rosmalen, J. G. M. (2010) · Psychotherapy and Psychosomatics · doi:10.1159/000296136 · Cited by 27
Grübler, M. R., Kienreich, K., Gaksch, M., Verheyen, N., Hartaigh, B. Ó., Fahrleitner-Pammer, A., März, W., Schmid, J., Oberreither, E.-M., Wetzel, J., et al. (2016) · Medicine · doi:10.1097/md.0000000000002794 · Cited by 13
Metadata
- Authors
- Schroeder, E. B., Liao, D., Chambless, L. E., Prineas, R. J., Evans, G. W., & Heiss, G.
- Venue
- Hypertension
- Published
- 2003-12
- Volume
- 42
- Issue
- 6
- Pages
- 1106-1111
- ISSN
- 0194-911X (ISSN-L)
- 1524-4563
- OpenAlex
- W2113269449
- Cited by
- 452
- References
- 4
- FWCI
- 2.93
- Type
- journal article
- Language
- en
- Open access
- closed
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.