Multi-trajectory modeling of home blood pressure telemonitoring utilization among hypertensive patients in China: A latent class growth analysis
Introduction
It was reported by WHO that chronic diseases were accounted for 68% of all deaths global wide and 79% of mortality in China [1]. Of all the chronic diseases in China, the burden of hypertension has been increasing in recent years with an age-standardized prevalence elevation by 1.4% per year from 2002 to 2012 [2]. Burden of Hypertension Survey indicated that 27.8% of Chinese adults are hypertensive [3]. However, the level of hypertension awareness as well as the proportion of effective treatment and BP control have remained low [4]. It was reported from the China Kadoorie Biobank Study that only 4.2% of the hypertensive patients had their blood pressure (BP) under control (BP < 140/90 mm Hg) [5].
BP control has been proved to be effective through a systematical approach, including clinical intervention, lifestyle modification and self-management [6]. Telemonitoring, such as education through telephone, texting and SMS and computer or smartphone based software, has potential to facilitate behavior change in BP patients, resulting in improved access to healthcare, better health outcomes and cost saving [[7], [8], [9], [10]]. Similar evidence was also demonstrated in China [11,12]. It was reported by a meta-analysis that telemonitoring could significantly lower systolic blood pressure (SBP) (mean 3.74 mmHg; 95% CI 2.19–2.58 mmHg) and diastolic blood pressure (DBP) (mean 2.37 mmHg; 95% CI 0.40–4.35 mmHg) [13]. Moreover, Morton et al. proposed that patients with chronic diseases who use digital devices to conduct self-management tend to feel supported [14]. However, adherence as well as effectiveness remains uncertain in the long run [8,10].
The majority of the published literature on HBPT assessment has been cross-sectional which provides little information on the developmental trajectories or use pattern of telemonitoring devices over time. In contrary to the traditional approach grouping subjects cross-sectionally, the latent class growth analysis (LCGA) is able to identify latent groups who share similar developmental trajectories over time [15,16]. LCGA has been widely used in the evaluation of mental health [17,18] and life course epidemiology etc. [[19], [20], [21]]. Goh et al. successfully identified three trajectories among patients utilizing telemonitoring with type 2 diabetes in Singapore with LCGA analysis, including minimal, intermittent-waning and consistent users [22]. However, the relationship between the developmental trajectories of the telemonitoring utilization frequency and clinical indicators (e.g., BP and plasma glucose levels) has not been studied yet.
HBPT has great potential in China with increasing numbers of smartphone users. It is important to understand the developmental trajectories or use pattern of HBPT over time for achieving long-term effectiveness and high adherence. We hence conducted a prospective cohort study of HBPT with hypertensive patients using to identify trajectories and reveal patterns of HBPT utilization. We firstly identify the longitudinal trajectories of HBPT utilization during 5-month follow-up period. We then explored the relationship between trajectories and patient’s characteristics such as socio-demographic, clinical indicators and HBPT use factors. Lastly, we assessed the correlation between longitudinal trajectories of HBPT utilization pattern and BP control outcome.
Section snippets
Study design, site, and population
The study was conducted in Yichang, Hubei Province, China. Patients who met the following criteria were enrolled from Xiling, Huayan, Baisha and Xueyuan community health centers in Yichang from March 2016 to November 2016: (1) diagnosed with hypertension based on World Health Organization criteria [23] for more than one year before entering this program, (2) has a smartphone in which the WeChat app is available in order to register an account, and (3) who is able to use of the smartphone and
Baseline characteristics of hypertensive patients in association with telehealth devices use trajectories
A total of 122 hypertensive patients were recruited to the study. Baseline characteristics such as socio-demographics, clinical-related variables and telehealth devices use status were presented in Table 1. The average age of the participants was 58.31 years (SD = 11.66) (45.08% female), among which 64.75% were married. The average baseline mean SBP was normal and the mean DBP was slightly higher than standard (90 mmHg). Among all hypertensive patients, 50.82% had their BP controlled well at
Principle results
Our study, as the first one, investigated the correlation between the longitudinal HBPT use patterns and individuals’ BP control status overtime. We identified the longitudinal use trajectories of HBPT among adults with hypertension. The five distinct trajectories were persistently low (Trajectory 1), moderate with decreasing (Trajectory 2), sharply decreasing (Trajectory 3), high with decreasing (Trajectory 4) and persistently high with increasing (Trajectory 5). The differences in age,
Conclusions
The application of LCGA in HBPT utilization identified 5 distinct latent trajectories: persistently low, moderate with decreasing, sharply decreasing, high with decreasing, persistently high with increasing. Although no statistical significant difference in age, marital status, BP (both SBP and DBP) and BP control status in the first period between the 5 trajectories were found, we demonstrated that regular monitoring had positive correlation with improved BP control in some extent. Our study
Funding
This project wasfunded by National Natural Science Foundation of China. (71403092).
Conflict of interests
The authors declare that they have no competing interests.
Authors' contributions
Conceived and designed this study: Ting Ye, Boyang Li, Pei Zhang, Liang Zhang.
Performed the study: Pei Zhang, Chengzhong Xu, Jiajuan Yang, Zijing Pan, Zhouzhi Wu, Ting Ye.
Analyzed the data: Ting Ye, Zijing Pan.
Wrote the paper: Ting Ye, Boyang Li, Zhaolian Ouyang and Zijing Pan.
All authors read and approved the final manuscript.
Acknowledgements
This project proceeded under the help of Yichang Centre for Disease Control and Prevention and Yichang Health Management Data Analysis Center.
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