Longitudinal analysis of sibling correlation on blood pressure using mixed modeling

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Longitudinal analysis of sibling correlation on blood pressure using mixed modeling. / Tan, Qihua; Duan, Hongmei; Wang, Ancong; Zhu, Dongyi; Li, Shuxia.

In: Annals of Epidemiology, Vol. 33, 2019, p. 49-53.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Tan, Q, Duan, H, Wang, A, Zhu, D & Li, S 2019, 'Longitudinal analysis of sibling correlation on blood pressure using mixed modeling', Annals of Epidemiology, vol. 33, pp. 49-53. https://doi.org/10.1016/j.annepidem.2019.02.006

APA

Tan, Q., Duan, H., Wang, A., Zhu, D., & Li, S. (2019). Longitudinal analysis of sibling correlation on blood pressure using mixed modeling. Annals of Epidemiology, 33, 49-53. https://doi.org/10.1016/j.annepidem.2019.02.006

Vancouver

Tan Q, Duan H, Wang A, Zhu D, Li S. Longitudinal analysis of sibling correlation on blood pressure using mixed modeling. Annals of Epidemiology. 2019;33:49-53. https://doi.org/10.1016/j.annepidem.2019.02.006

Author

Tan, Qihua ; Duan, Hongmei ; Wang, Ancong ; Zhu, Dongyi ; Li, Shuxia. / Longitudinal analysis of sibling correlation on blood pressure using mixed modeling. In: Annals of Epidemiology. 2019 ; Vol. 33. pp. 49-53.

Bibtex

@article{e05b2291d15e492494d361d32854e5a3,
title = "Longitudinal analysis of sibling correlation on blood pressure using mixed modeling",
abstract = "Purpose: Although moderate to high genetic contribution to blood pressure variation have been estimated in numerous studies, the genetic control over the longitudinal change in blood pressure has been less frequently investigated because of the requirement of longitudinal design. Methods: Based on blood pressure data from a large-scale family-based longitudinal survey, we introduced hierarchical modeling of longitudinal family data in combination with fractional polynomials for fitting nonlinear age patterns of blood pressure and the mixed-effect models for estimating sibling correlation on blood pressure to assess the genetic and shared environmental effects on blood pressure level as well as on the rate of change in blood pressure over ages. Results: Significant sibling correlations were estimated on the levels of systolic blood pressure (0.2, 95% CI: 0.10–0.30) and diastolic blood pressure (0.28, 95% CI: 0.18–0.38), whereas for the longitudinal change or the rate of change, significant correlation was estimated only for diastolic blood pressure (0.13, 95% CI: 0.04–0.23). In the sex-specific analysis, similar pattern is observed, but statistical significance was only reached in female siblings with correlation estimates higher than the overall sample. Conclusion: The rate of change in blood pressure is mainly influenced by individual's unique environment; and the genetic and common family environment may play a role in regulating the longitudinal change of diastolic but not systolic blood pressure.",
keywords = "Blood pressure, Fractional polynomials, Longitudinal, Mixed-effects model, Sibling correlation",
author = "Qihua Tan and Hongmei Duan and Ancong Wang and Dongyi Zhu and Shuxia Li",
year = "2019",
doi = "10.1016/j.annepidem.2019.02.006",
language = "English",
volume = "33",
pages = "49--53",
journal = "Annals of Epidemiology",
issn = "1047-2797",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Longitudinal analysis of sibling correlation on blood pressure using mixed modeling

AU - Tan, Qihua

AU - Duan, Hongmei

AU - Wang, Ancong

AU - Zhu, Dongyi

AU - Li, Shuxia

PY - 2019

Y1 - 2019

N2 - Purpose: Although moderate to high genetic contribution to blood pressure variation have been estimated in numerous studies, the genetic control over the longitudinal change in blood pressure has been less frequently investigated because of the requirement of longitudinal design. Methods: Based on blood pressure data from a large-scale family-based longitudinal survey, we introduced hierarchical modeling of longitudinal family data in combination with fractional polynomials for fitting nonlinear age patterns of blood pressure and the mixed-effect models for estimating sibling correlation on blood pressure to assess the genetic and shared environmental effects on blood pressure level as well as on the rate of change in blood pressure over ages. Results: Significant sibling correlations were estimated on the levels of systolic blood pressure (0.2, 95% CI: 0.10–0.30) and diastolic blood pressure (0.28, 95% CI: 0.18–0.38), whereas for the longitudinal change or the rate of change, significant correlation was estimated only for diastolic blood pressure (0.13, 95% CI: 0.04–0.23). In the sex-specific analysis, similar pattern is observed, but statistical significance was only reached in female siblings with correlation estimates higher than the overall sample. Conclusion: The rate of change in blood pressure is mainly influenced by individual's unique environment; and the genetic and common family environment may play a role in regulating the longitudinal change of diastolic but not systolic blood pressure.

AB - Purpose: Although moderate to high genetic contribution to blood pressure variation have been estimated in numerous studies, the genetic control over the longitudinal change in blood pressure has been less frequently investigated because of the requirement of longitudinal design. Methods: Based on blood pressure data from a large-scale family-based longitudinal survey, we introduced hierarchical modeling of longitudinal family data in combination with fractional polynomials for fitting nonlinear age patterns of blood pressure and the mixed-effect models for estimating sibling correlation on blood pressure to assess the genetic and shared environmental effects on blood pressure level as well as on the rate of change in blood pressure over ages. Results: Significant sibling correlations were estimated on the levels of systolic blood pressure (0.2, 95% CI: 0.10–0.30) and diastolic blood pressure (0.28, 95% CI: 0.18–0.38), whereas for the longitudinal change or the rate of change, significant correlation was estimated only for diastolic blood pressure (0.13, 95% CI: 0.04–0.23). In the sex-specific analysis, similar pattern is observed, but statistical significance was only reached in female siblings with correlation estimates higher than the overall sample. Conclusion: The rate of change in blood pressure is mainly influenced by individual's unique environment; and the genetic and common family environment may play a role in regulating the longitudinal change of diastolic but not systolic blood pressure.

KW - Blood pressure

KW - Fractional polynomials

KW - Longitudinal

KW - Mixed-effects model

KW - Sibling correlation

U2 - 10.1016/j.annepidem.2019.02.006

DO - 10.1016/j.annepidem.2019.02.006

M3 - Journal article

C2 - 30904389

AN - SCOPUS:85062940376

VL - 33

SP - 49

EP - 53

JO - Annals of Epidemiology

JF - Annals of Epidemiology

SN - 1047-2797

ER -

ID: 223569576