1.561113 贵阳,贵州医科大学公共卫生与健康学院环境污染与疾病监控教育部重点实验室
2.400038 重庆,陆军军医大学(第三军医大学)军事预防医学系军队流行病学教研室
3.400032 重庆,沙坪坝区双碑社区卫生服务中心
4.400039 重庆,九龙坡区疾病预防控制中心
5.401120 重庆,重庆医科大学附属第三医院心血管疾病中心
Received:20 September 2023,
Revised:2023-10-18,
Published:30 June 2024
移动端阅览
Meng NIE, Na WU, Huiyan JIAO, et al. Trajectory of systolic blood pressure fluctuation and its influencing factors in community-dwelling patients with hypertension[J]. Journal of Army Medical University, 2024, 46(12): 1457-封3.
Meng NIE, Na WU, Huiyan JIAO, et al. Trajectory of systolic blood pressure fluctuation and its influencing factors in community-dwelling patients with hypertension[J]. Journal of Army Medical University, 2024, 46(12): 1457-封3. DOI: 10.16016/j.2097-0927.202309112.
目的
2
分析和构建社区高血压人群收缩压(systolic blood pressure
SBP)变化的轨迹模型,并分析不同SBP轨迹的影响因素。
方法
2
本研究基于社区回顾性队列,运用潜类别轨迹模型(latent class trajectory modelling,LCTM)分析社区高血压人群SBP的变化模式,识别、构建SBP的纵向变化轨迹;运用无序多分类logistic回归分析不同SBP轨迹的影响因素,根据先验知识使用“有向无环图”识别和调整不同的混杂因素。
结果
2
共793名高血压患者被纳入分析,LCTM拟合的社区高血压患者SBP轨迹最优分组为3组,分别为低水平平稳组(
n
=561,70.74%)、下降组(
n
=170,21.44%)和上升组(
n
=62,7.82%);年龄、锻炼频率、随访方式、摄盐情况、遵医行为、有无转诊在不同SBP轨迹亚组中分布存在统计学差异(
P
<
0.05);无序多分类logistic回归分析结果显示,以低水平平稳组为对照,“男性”、“门诊随访”的患者被分类到下降组的可能性较高,
OR
及95%
CI
分别为1.436(1.016~2.030)、1.702(1.202~2.410);而“年龄≥65岁”,“不锻炼或偶尔锻炼”,摄盐情况为“中”和“重”度的人群,被分类到上升组的可能性更高,
OR
及95%
CI
依次为1.949(1.145~3.317)、2.284(1.305~3.998)、2.433(1.272~4.654)、4.540 (1.291~15.963)。
结论
2
社区高血压人群收缩压变化轨迹可分为3组,即“低水平平稳组”、“下降组”和“上升组”;性别、年龄、摄盐情况、锻炼频率、随访方式可能是收缩压轨迹的影响因素。
Objective
2
To analyze and construct systolic blood pressure (SBP) fluctuation trajectory in a community population with hypertension and to analyze the factors influencing different trajectories.
Methods
2
This is a community-based retrospective cohort study. A latent class trajectory model was used to identify and construct longitudinal trajectories of blood pressure change. Multinomial logistic regression analysis was performed to identify the associated factors of blood pressure trajectories by adjusting for different confounders. Potential confounding factors were identified using a directed acyclic graph based on a priori knowledge.
Results
2
A total of 793 patients with hyperten
sion were enrolled in the analysis. They were divided into 3 groups by LCTM-fitted systolic blood pressure trajectories
namely stable low-level group (
n
=561
70.74%)
declining group (
n
=170
21.44%) and rising group (
n
=62
7.82%). Significant differences were observed among the 3 trajectories groups in terms of age
frequency of exercise
ways of follow-up
salt intake
compliance behavior
and referral (
P
<
0.05). Compared to the stable low-level group and adjusting for corresponding confounding factors
the male patients and the patients with "outpatient follow-up" were more likely to be classified into "declining group"
with
OR
and 95%
CI
of 1.436 (1.016~2.030) and 1.702 (1.202~2.410)
respectively. The participants aged ≥65 years
who did not exercise or occasionally exercised
and had moderate and severe salt intake
were more likely to be classified into the "rising group"(
OR
=1.949
2.284
2.433
4.540
95%
CI
: 1.145~3.317
1.305~3.998
1.272~4.654
1.291~15.963).
Conclusion
2
SBP trajectories in community-dwelling hypertensive population can be divided into stable low-level
declining and rising groups. Gender
age
salt intake
exercise frequency
and follow-up methods may be influencing factors for SBP blood pressure trajectory.
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