Skip to main content

Cost-effectiveness and potential budget impact of non-pharmacological interventions for early management in prehypertensive people: an economic evaluation for China

Abstract

Background

Non-pharmacological interventions (NPIs) could be considered in the early management of prehypertensive population. This study aimed to evaluate the potential cost-effectiveness of NPIs and the budget impact of implementing NPIs on prehypertensive population in China and provide evidence of chronic disease management innovation for decision-makers.

Methods

Five NPIs including usual care, lifestyle, strengthen exercise, relaxation, and diet therapy were selected based on the practice of hypertension management in China. A nine-state Markov model was constructed to evaluate the lifetime costs and health outcomes of five NPIs and a non-intervention group from the perspective of Chinese healthcare system. The effectiveness of NPIs was obtained from a published study. Parameters including transition probabilities, costs and utilities were extracted or calculated from published literature and open-access databases. Sensitivity analyses were conducted to test the uncertainty of all parameters. The impact of duration of intervention was considered in scenario analyses. A budget impact analysis (BIA) was conducted to evaluate the total cost and the medical cost saving of a hypothetical nationwide implementation of potential cost-effective NPI in prehypertensive people. Management strategies including focusing on patients with specific ages or different CVE risk levels, and different duration of implementation were taken into consideration.

Results

Strengthen exercise was the most cost-effective intervention with a probability of 78.1% under the given WTP threshold. Our results were sensitive to the cost of interventions, and the utility of prehypertension and hypertension. The duration of implementation had limited impact on the results. BIA results showed that the program cost was hefty and far more than the medical cost saving with the course of simulation time. Applying management strategies which focused on individual characteristics could largely reduce the program cost despite it remained higher than medical cost saving.

Conclusions

Strengthen exercise was a potential NPI that can be considered in priority for early management in prehypertensive population. Although early management can acquire medical cost saving, the related program cost can be quite hefty. Precise strategies which may help reduce the cost of early management should be taken into consideration in program design.

Peer Review reports

Background

Prehypertension, a blood pressure (BP) category which refers to the intermediate stage between hypertension and normal BP [1], was defined as a BP range of 120–139/80–89 mmHg. However, according to the 2017 guidelines of the American College of Cardiology (ACC), BP exceeding 130/80 mmHg has been diagnosed as grade 1 hypertension [2]. Reduction of diagnostic threshold in ACC guidelines led to corresponding adjustment of hypertension management in United States. However, for countries that still use 140/90mmHg as diagnostic criteria, it indicates that BP management should be advanced to the prehypertension state. Prehypertension has a large prevalence which affects 25–50% of adults worldwide [3]. Compared with normal BP, prehypertension confers a higher risk of progression to hypertension and cardiovascular events (CVE) with a 5-year progression rate of 40% [4,5,6]. Therefore, adopting early management for prehypertensive population holds great value for long-term health outcomes.

Non-pharmacological interventions (NPIs) have been proven to have short-term efficacy for BP control in previous research [5, 7,8,9,10,11]. Meanwhile, NPIs are recommended by recent guidelines, which can be considered a priority in preventing hypertension [10, 12]. In China, more than 100 million hypertensive patients have already been covered in routine health management such as regular follow-up and physical examination [13]. Besides, NPIs such as dietary therapy, aerobic exercise, and relaxation are provided in the Primary Public Health Services for hypertension management. However, NPIs which rely on health education or behavioral changes, are highly dependent on the supervision from well-trained service providers [14,15,16,17]. As of 2021, the Chinese government had invested nearly $400 million in chronic disease management [18]. If NPIs were implemented in prehypertension in advance, there will be a huge and non-negligible expense for governmental management.

In a previously published meta-analysis, the short-term efficacy of NPIs in prehypertensive population has been proven. Combined with the meta-analysis, whether we should apply NPIs to the prehypertensive population and which NPIs are potentially cost-effective should be evaluated. Considering the scarce health resources and rising demand, it is also necessary to explore affordable service strategies under the specific NPI with cost-effectiveness. This study aimed to evaluate the potential cost-effectiveness of five representative NPIs in prehypertensive population and evaluate the input and output of implementing the potential cost-effective NPIs for early management of prehypertension in China.

Methods

A cost-effectiveness analysis and a budget impact analysis (BIA) were conducted to accomplish the main purpose of this study. Sensitivity analyses and scenario analyses were conducted to test the robustness of the results and evaluated the impact of the duration of intervention on results in cost-effectiveness analysis. This research was reported to follow the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) [19]. The protocol of this research could be found elsewhere [20].

Interventions

According to the previously published network meta-analysis [10], we considered five NPIs: usual care, lifestyle, strengthen exercise, relaxation, and diet therapy [10]. Definitions, contents and intensities of NPIs in this study were consistent with that network meta-analysis. These NPIs were in line with the practice of BP management in China and have the potential to be applied to prehypertensive population [21]. A non-intervention group, which was also set up for comparison, was assumed to not affect BP change and have no cost. Definitions and BP reduction of these five NPIs can be found in Table 1. Detailed information on these interventions is shown in Supplementary Table 1.

Table 1 Definitions and BP reduction of included NPIs

Cost-effectiveness analysis

Study population

The initial simulated cohort was 10,000 individuals with prehypertension, of which baseline characteristics were extracted from China Health and Nutrition Surveys (CHNS). Detailed information is shown in Supplementary Table 6. CHNS is a comprehensive, long-term survey which is one of the most representative nationwide data in China [22, 23]. CHNS is created to address key public health risk factors, health outcomes, and demographic and socioeconomic aspects at individual, household, and community levels. The CHNS sought to investigate the impact of socioeconomic evolution on public health over time.

Model conceptualization and construction

We conducted a Markov model-based cost-effectiveness analysis from the perspective of Chinese healthcare system [24, 25]. The healthcare system perspective considered the consumption of healthcare resources and the benefits to patients within the healthcare sector resulting from a particular intervention [25]. Figure 1 reflects the state-transition pathway of Markov model. The initial state was prehypertension, followed by the state of hypertension. A total of three complication states as well as their post-states (myocardial infarction, heart failure, and stroke) were considered [24]. The simulated cohort could only stay in the three complication states for one year, and would automatically progress to their post-states in the following year [24, 26]. The model used a lifetime time horizon with the cycle length set as one year to simulate the life-long disease progression of prehypertensive individuals under each NPI. The discount rate was set as 5% according to the recommendation of the “Chinese Guidelines for Pharmacoeconomics Evaluation 2020 edition“ [25]. The transition probability of prehypertension to hypertension and hypertension to each CVE state would be calculated based on risk prediction models which input the cohort characteristics such as age, gender, body mass index, etc [27,28,29,30]. Detailed information was shown in Supplementary Tables 26. The mortality rate of prehypertension and hypertension without CVE was considered as natural mortality rate [31]. The natural mortality was time-dependent which was derived from the Sixth National Population Census in China conducted in 2010 [31]. The transition probabilities between other health states were obtained based on existing clinical studies or mature economic models [31,32,33,34,35,36].

Fig. 1
figure 1

Markov model. MI: myocardial infarction; HF: heart failure

Model assumptions for this study could be found as follow: (1) The NPIs could effectively reduce the BP of the subjects in the first year and the effect from the second year was to maintain the BP; (2) NPIs were only applied on the prehypertension and were stopped when they leave that state; (3) All patients could only have CVE once in their lives and they could not return after entering a post-state.

We used ICER as the decision indicator, and regarded one time 2021 GDP per capita ($12,728) as the willingness to pay (WTP) threshold [37]. The financial support for NPIs, might not come from medical insurance, but the local public health funding. Therefore, a higher threshold would also be set in the sensitivity analyses (for example, three times the GDP per capita in China ($38,184)).

Model parameters

Effectiveness

Since current published studies were all short-term follow-up studies, long-term outcomes including CVE could not be obtained. Therefore, we introduced BP reduction from a meta-analysis as effectiveness input [10] (Detailed BP reduction could be found in Table 1 and Supplementary Table 7). Then, age-dependent transition probabilities (from prehypertension or hypertension to CVE) were calculated through published risk prediction models [27,28,29,30]. Transition probabilities of CVE to post CVE, CVE to death, and post CVE to death were obtained from published articles.

Cost and utility

The cost of NPIs was calculated by decomposing them into detailed items. These items were in line with the description extracted from the published network meta-analysis [10]. For a service item that has a set price, its cost was calculated by the frequency and the unit price. We use the human capital method combined with the wages of related employees were used to calculate unpriced service items. For other items such as temporary personnel training costs, and fixed asset acquisition, the calculation method was to sum up the wages of related employees and then shared by the initial input population. The cost of each detailed item can be found in Table 2. The detailed calculation process of the cost of interventions can be found in Supplementary Tables 9, 10. Costs were updated to 2021 through Consumer Price Index [38].

For people entering the hypertension state, we considered the cost of hypertension management (Detailed items can be found in Supplementary Table 9). The cost of each CVE state was extracted from China-based studies [39, 40]. We also considered the end-of-life cost in this study, and we extracted the value from a Chinese study that targeted acute coronary syndrome [41].

Utilities of prehypertension and hypertension were extracted from a quasi-experiment in China [42]. The utilities of each CVE state were derived from other published China-based studies [43]. The detailed content of included parameters is shown in Supplementary Table 8. Quality-adjusted life-years (QALYs) were calculated by multiplying the length of time spent in a certain health state by the utility associated with that health state [26].

Sensitivity analyses and scenario analyses

In DSA, we used the 95% confidence intervals (CI) of single effect size as the fluctuation interval. A fluctuation of 20% (considering the great uncertainty of the cost and utilities) was assumed for parameters without 95% CI. The discount rate was set to fluctuate between 0% and 8%. The results of the DSA were displayed in tornado diagrams.

We used Monte Carlo simulation with 10,000 iterations performed to do the PSA. The prior distribution of parameters was applied, such as a beta distribution for transition probability and utility, and a gamma distribution for cost. Here we also considered the uncertainty of effectiveness parameters, and a normal distribution was applied. We used scatter plots and cost-effectiveness acceptability curves (CEAC) to present the cost-effectiveness for each regimen with various WTP thresholds.

To evaluate the impact of the duration of NPIs intervention on base-case analysis results, we further considered several scenario analyses, in which the years of NPIs implementation varied from one year to the lifetime time horizon.

Budget impact analysis

A BIA model was constructed to estimate the program cost and the medical cost saving of national implementation of potential cost-effective NPI for prehypertensive population from the perspective of Chinese healthcare system. The program cost was calculated by multiplying the implementation cost with the Chinese demographic characteristics [44]. Medical cost saving was considered as the reduction expenditure in the medical costs of health states followed by prehypertension compared to non-intervention. The simulation time was set as 15 years. We also included scenarios of different early management strategies, which considered three factors: (1) the beginning age of early management (Four age groups were considered: “45–49”, “50–54”, “55–59”, “60–64”); (2) whether to include only patients with high risk of CVE into early management; (3) duration of implementation varied from one year to simulation horizon. In addition, compliance to NPIs including 100%, 80%, 60%, 40%, 20% was also considered in this model. Details of key model assumptions, methodologies, and parameters input are shown in the Supplementary material p18-21.

Table 2 Cost table of detail items

Results

Cost-effectiveness analysis

Results of base-case analysis are shown in Table 3. It showed that relaxation and diet therapy had greater costs but fewer QALYs gained, which were strongly dominated by other interventions. Usual care and lifestyle were extended dominated by strengthen exercise. Details were shown in the cost-effectiveness plane(Supplementary Fig. 3). After ruling out all dominated interventions, strengthen exercise was cost-effective compared to non-intervention, given that the ICER was lower than the WTP threshold of $12,728 per QALY.

According to the breakdown results of the base-case analysis (shown in Supplementary Tables 11, 12), the differences in costs and QALYs gained in prehypertension and hypertension state might contribute more to the differences between the results. We also found that strengthen exercise had the longest average time for people from prehypertension transition to hypertension, followed by relaxation and lifestyle, which was in line with the effectiveness indicators.

Table 3 Results of base-case analysis

The results of scenario analyses are shown in Fig. 2. Relaxation and diet therapy were excluded from the scenario analyses since they were strongly dominated by other interventions in the base-case analysis. With the years of implementation increasing to seven, the ICERs between all groups dropped consistently from their highest point. After years of implementation increasing to ten, the ICERs between all groups became steady. The ICERs between usual care and non-intervention were higher than in other comparisons. Although ICER between usual care and non-intervention with one year of implementation reached $12,615, which was the highest among all scenarios, it was still lower than the WTP threshold($12,728).

Fig. 2
figure 2

Results of scenario analyses

Sensitivity analyses

Results of DSA and PSA are shown in Supplementary Fig. 4a and b. We included totally four comparisons in DSA. The results were sensitive to utilities of prehypertension and hypertension in all comparisons. Cost of interventions for prehypertension and discount rate also influenced the results. Note that the fluctuation in the utility of hypertension could even lead to the change in the conclusions of all four comparisons. This was further discussed in the discussion.

The cost-effectiveness acceptability curve is shown in Fig. 3. Non-intervention had the highest probability to be cost-effective when WTP ranged from 0$ to $4,700. At a WTP threshold of $12,728 per QALY, strengthen exercise had a probability of over 78.1% being cost-effective. This probability rose to 77.1% when WTP threshold reached $38,184 per QALY.

Fig. 3
figure 3

Probabilistic Sensitivity analyses: cost-effectiveness acceptability curve (10,000 iterations). WTP: willingness-to-pay; CEAC: cost-effectiveness acceptability curve

Budget impact analysis

According to the base-case results, we only considered strengthen exercise in the budget impact analysis. Results of budget impact analysis of which the duration of implementation is 15 years are shown in Fig. 4. The medical cost saving, which increased with the course of simulation time,was far less than the hefty program cost. Through considering some specific strategies including decreasing the duration of intervention, starting intervention in older population, and only managing population with high risk of CVE, we could found that the previous conclusion was unchanged. However, we found that through these strategies, the program costs could be reduced. In addition, according to Fig. 4, changing a strategy might lead to little change in cost saving, but huge reduction in program costs could be observed. (Detailed results can be found in the Supplementary Fig. 5a, b, c and d).

Fig. 4
figure 4

Results of Budget impact analysis results

Discussion

According to the results of base-case analysis, strengthen exercise might be the most cost-effective intervention at the WTP threshold of one-time GDP per capita in China. DSA results showed that our results were sensitive to the utility of prehypertension and hypertension, discount rate, and the costs of interventions. PSA results showed that when the WTP was set to one-time GDP per capita, strengthen exercise had the highest probability to be cost-effective. The other interventions were not associated with a probability of greater than 50% being cost-effective. Implementation of NPIs within seven years had great impact on the results. However, results become stable when years of implementation over ten. BIA showed that the program implementing strengthen exercise for early intervention in prehypertensive individuals could bring medical cost saving. However, the program cost was hefty and far more than the medical cost saving. Focusing on patients with specific characteristics or shortening years of implementation can help reduce the program cost.

Drug interventions were not considered in this cost-effectiveness analysis, since there were already two high-quality studies discussed the use of antihypertensives in the Chinese prehypertensive people. Zhou et al. developed a microsimulation model to compare costs and effectiveness of drug treatment and NPIs for prehypertensive people over a lifetime horizon from a government affordability perspective [17]. Their results showed that at a WTP threshold of one time GDP per capita in 2017, drug interventions only had a 1.8% probability of being cost-effective compared with NPIs. Therefore, they suggested that drug treatment was not cost-effective compared with NPIs for target population. Chen et al. built a Markov state-transition model to simulate a hypothetical cohort of Chinese adults with high-range prehypertension but without CVE [24]. They found that compared with placebo, drug treatment had great benefits in delaying the development of hypertension but was far from cost-effective at a WTP threshold of one time GDP per capita in 2014. Therefore, considering the current existed evidence, we did not included the drug interventions in our study. However, there were lack of current studies which targeted on the cost-effectiveness of NPIs for prehypertensive people. Thus, our study results could make up for this deficiency.

According to DSA results, for all four comparisons, the utility of prehypertension and hypertension, and cost of interventions had great impacts on our results. This could also be identified from the breakdown of base-case analysis. Costs and QALYs gained in prehypertension and hypertension states differed greatly between groups. It is also notable that the fluctuation of the utility of hypertension could even lead to the change in conclusion when WTP was set as $12,728. However, when WTP was set as $38,184, our conclusion was stable. Utility of prehypertension and hypertension used in this study, which was based on Guo’s study [42], is 0.931 and 0.8 respectively. Guo conducted a quasi-experiment in China to investigate the effectiveness of a non-pharmacological intervention on the prehypertensive population, and the utility of different states of BP conversion process was measured. Therefore, we considered that these two values could be used in our China based study. Some similar study which focused on prehypertensive people made an assumption that utility of prehypertension and utility of hypertension were the same [17, 24]. However, we did not believe that this assumption was reliable. Spruill’s study found that people with prehypertension had nearly the same quality of life as normal people [56], while Wang’ s study found that people with hypertension had significantly different quality of life from normal people [57]. These two indirect evidence showed that the utility of prehypertension and hypertension states can be different. Therefore, in our study, we considered different utility values for these two states. Nevertheless, due to the high uncertainty of these two utility values in our study, future studies targeted on the the utilities of prehypertensive and hypertensive people that are representative of China are needed to resolve this parameter uncertainty. For costs of interventions, which were calculated from included studies, might be subjective. However, this uncertainty was hard to handle since it was difficult to find an authoritative reference. Thus, a national guideline to instruct management staff to implement NPIs was needed to improve the calculation of related costs.

Some NPIs were proven to be cost-effective in CEA, however, the results of BIA show the affordability of the implementation program was concerning. According to hypertension guidelines from each country, there seems a radical approach to including people with prehypertension in management. Although 2017 ACC guidelines have made this attempt, the implementation of early management in low- and middle-income countries still needs further consideration. Because according to our BIA results, the program cost could be a huge expense and greatly exceeded the medical cost saving in this BIA. However, the medical cost saving was underestimated because not only individuals with prehypertension can benefit from the program. Our research only focuses on the CVE related to hypertension, therefore, other chronic diseases related to comorbidity which may produce extra medical costs were not involved. For example, some previous research proved that NPIs have potential effectiveness in diseases such as prediabetes [58, 59]. This suggested people with prehypertension or prediabetes might benefit from health service innovation like integrated care. In addition, in this BIA, we explored several potential management strategies to give more precise interventions. These strategies including setting the beginning age of early management, including only patients with high risk of CVE, and reducing the duration of implementation, can all help to reduce the program cost through managing people more accurately. Although the program cost remained high, it could be largely reduced if the interventions based on individual characteristics were applied, which could only lead to little change in cost saving. This can be an inspiration to future research which focused on precise chronic disease prevention. The changes of input and output of different strategies may provide decision-makers with more information to choose the optimal management strategy.

However, there are several limitations in the study. Firstly, NPIs included in this study were all extracted from current published studies and guidelines. Since the costs were calculated subjectively, some currently unsolvable biases might be introduced to our results. Secondly, effectiveness parameters were obtained from a network meta-analysis which based on global population, their generalization of to the Chinese context needed further assessment. Thirdly, utility values of CVE related states used in this study were extracted from different sources. There might exist biases that the utility gap between health states was not fully attributed to changes in utility due to changes in health status. Thus, we considered a 20% upper and lower range of fluctuations in DSA, and the results showed that the conclusions were stable. Fourth, the transition probabilities between CVE related states in our model could be quite similar among different NPIs and had no direct relationship with NPIs. Besides, our model assumed that only in the first year could the NPIs effectively reduce the BP of the subjects and the effect from the second year was to maintain the BP. These two could be strong assumptions without evidence support. However, since follow-up of current NPIs studies mainly did not exceed one year, long-term BP benefits could not be obtained from current evidence. Therefore, this limitation may be handled by further high-quality long follow-up studies. Fifth, we used the static cohort in BIA rather than the dynamic cohort, which might lead to imprecise estimation. Therefore, we only dropped the qualitative conclusions instead of providing quantitative outcomes.

Conclusion

Implementing NPIs in prehypertensive population is a recommended management scheme. According to our research, strengthen exercise was potentially cost effective which can be considered in priority for early management in prehypertensive population. Although early management can acquire medical cost saving, the related program cost can be quite hefty. Precise strategies which may help reduce the cost of early management should be taken into consideration in program design.

Availability of data and materials

All data generated or analyzed during this study are included in this published article and supplementary files. The unpublished network meta-analysis is available from the corresponding author with reasonable request.

Code availability

R codes for this study are available on GitHub

( https://github.com/TaihangShao/prehypertension_CEA_model ).

References

  1. Zhonghua Xin Xue Guan Bing Za Zhi. National guideline for hypertension management in China (2019). 2020;48(1):10–46. https://doi.org/10.3760/cma.j.issn.0253-3758.2020.01.004.

  2. Whelton PK, Carey RM, Aronow WS, Casey DE, Collins KJ, Dennison Himmelfarb C, DePalma SM, Gidding S, Jamerson KA, Jones DW, et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA guideline for the prevention, detection, evaluation, and management of high blood pressure in adults: a report of the american college of cardiology/american heart association task force on clinical practice guidelines. Hypertension. 2018;71(6):1269–324.

    Article  CAS  PubMed  Google Scholar 

  3. Li X, Gao Y, Wu M, Wei D, Xiong X, Yang Y, Jiang Y, Pan X, Zhao R, Yang F, et al. Effect of Tai Chi versus aerobic exercise on blood pressure in prehypertension patients (TCOBPP): a study protocol for a 12-month single-blind randomized controlled trial. Trials. 2022;23(1):1001.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Materson BJ, Garcia-Estrada M, Degraff SB, Preston RA. Prehypertension is real and can be associated with target organ damage. J Am Soc Hypertens. 2017;11(11):704–8.

    Article  PubMed  Google Scholar 

  5. Egan BM, Stevens-Fabry S. Prehypertension–prevalence, health risks, and management strategies. Nat Rev Cardiol. 2015;12(5):289–300.

    Article  PubMed  Google Scholar 

  6. Kanegae H, Oikawa T, Kario K. Should pre-hypertension be treated? Curr Hypertens Rep. 2017;19(11):91.

    Article  PubMed  Google Scholar 

  7. Patnode CD, Evans CV, Senger CA, Redmond N, Lin JS. Behavioral counseling to promote a healthful diet and physical activity for cardiovascular disease prevention in adults without known cardiovascular disease risk factors. JAMA-J AM Med Assoc. 2017;318(2):175.

    Article  Google Scholar 

  8. Park S, Han KS. Blood pressure response to meditation and yoga: a systematic review and meta-analysis. The journal of alternative and complementary medicine (New York, NY). 2017;23(9):685–95.

    Article  PubMed  Google Scholar 

  9. Herrod P, Doleman B, Blackwell J, O’Boyle F, Williams JP, Lund JN, Phillips BE. Exercise and other nonpharmacological strategies to reduce blood pressure in older adults: a systematic review and meta-analysis. J Am Soc Hypertens. 2018;12(4):248–67.

    Article  PubMed  Google Scholar 

  10. Shao T, Liang L, Zhou C, Tang Y, Gao W, Tu Y, Yin Y, Malone DC, Tang W. Short-term efficacy of non-pharmacological interventions for global population with elevated blood pressure: a network meta-analysis. Front Public Health. 2022;10:1051581.

    Article  PubMed  Google Scholar 

  11. Williamson W, Foster C, Reid H, Kelly P, Lewandowski AJ, Boardman H, Roberts N, McCartney D, Huckstep O, Newton J, et al. Will Exercise advice be sufficient for treatment of young adults with prehypertension and hypertension? A systematic review and meta-analysis. Hypertension. 2016;68(1):78–87.

    Article  CAS  PubMed  Google Scholar 

  12. Foldes C, Fisher JW. Hypertension. Ann Intern Med. 2019;171(7):525.

    Article  PubMed  Google Scholar 

  13. Ministry of Health of the People’s Republic of China. 2021 China’s health and health care development statistics bulletin; 2021. http://www.gov.cn/xinwen/2022-07/12/content_5700670.htm. Accessed 22 Dec 2022.

  14. Morgan F, Battersby A, Weightman AL, Searchfield L, Turley R, Morgan H, Jagroo J, Ellis S. Adherence to exercise referral schemes by participants - what do providers and commissioners need to know? A systematic review of barriers and facilitators. BMC Public Health. 2016;16:227.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Dhungana RR, Pedisic Z, de Courten M. Implementation of non-pharmacological interventions for the treatment of hypertension in primary care: a narrative review of effectiveness, cost-effectiveness, barriers, and facilitators. BMC Prim Care. 2022;23(1):298.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Anderson P, Bendtsen P, Spak F, Reynolds J, Drummond C, Segura L, Keurhorst MN, Palacio-Vieira J, Wojnar M, Parkinson K, et al. Improving the delivery of brief interventions for heavy drinking in primary health care: outcome results of the optimizing delivery of health care intervention (ODHIN) five-country cluster randomized factorial trial. Addiction. 2016;111(11):1935–45.

    Article  PubMed  Google Scholar 

  17. Zhou YF, Liu N, Wang P, Jeong YJ, Song XY, Pan XF, Zhang X, He M, Li H, Gao YT, et al. Cost-effectiveness of drug treatment for chinese patients with stage I hypertension according to the 2017 hypertension clinical practice guidelines. Hypertension. 2020;76(3):750–8.

    Article  CAS  PubMed  Google Scholar 

  18. Primary Department of National Health and Family Planning Commission. Relevant work and requirements of the national basic public health service project in 2017. ; 2017. http://www.nbphsp.org.cn/jbgw/jswd/20171017/1004.html. Accessed 4 Nov 2020.

  19. Husereau D, Drummond M, Augustovski F, de Bekker-Grob E, Briggs AH, Carswell C, Caulley L, Chaiyakunapruk N, Greenberg D, Loder E, et al. Consolidated health economic evaluation reporting standards 2022 (CHEERS 2022) statement: updated reporting guidance for health economic evaluations. Value Health. 2022;25(1):3–9.

    Article  PubMed  Google Scholar 

  20. Shao T, Li X, Zhou C, Zang X, Malone DC, Zhang L, Zhou J, Tang W. Effectiveness and efficiency of non-drug therapy among Community-Dwelling adults with hypertension in China: a protocol for network meta-analysis and cost-effectiveness analysis. Front Med-Lausanne. 2021;8:651559.

    Article  PubMed  PubMed Central  Google Scholar 

  21. National Health Commission of the People’s Republic of China. National Basic Public Health Service Projects. in 2017; 2017. http://www.nhc.gov.cn/jws/s3577/201709/fb16b2e306bd469ab84e0c42173bc52d.shtml. Accessed 21 December 2021.

  22. Popkin BM, Du S, Zhai F, Zhang B. Cohort Profile: the China health and nutrition survey–monitoring and understanding socio-economic and health change in China, 1989–2011. Int J Epidemiol. 2010;39(6):1435–40.

    Article  PubMed  Google Scholar 

  23. Zhang B, Zhai FY, Du SF, Popkin BM. The China health and nutrition survey, 1989–2011. Obes Rev. 2014;15(Suppl 1):2–7.

    Article  PubMed  Google Scholar 

  24. Chen T, Yu D, Cornelius V, Qin R, Cai Y, Jiang Z, Zhao Z. Potential health impact and cost-effectiveness of drug therapy for prehypertension. Int J Cardiol. 2017;240:403–8.

    Article  PubMed  Google Scholar 

  25. Liu G. Chinese guidelines for pharmacoeconomics evaluation 2020. China Market Press; 2020.

  26. Smith SM, Campbell JD. Cost-effectiveness of renin-guided treatment of hypertension. AM J HYPERTENS. 2013;26(11):1303–10.

    Article  PubMed  Google Scholar 

  27. Chien KL, Hsu HC, Su TC, Chang WT, Sung FC, Chen MF, Lee YT. Prediction models for the risk of new-onset hypertension in ethnic chinese in Taiwan. J Hum Hypertens. 2011;25(5):294–303.

    Article  PubMed  Google Scholar 

  28. Kannel WB, D’Agostino RB, Silbershatz H, Belanger AJ, Wilson PW, Levy D. Profile for estimating risk of heart failure. Arch Intern Med. 1999;159(11):1197–204.

    Article  CAS  PubMed  Google Scholar 

  29. Chien K, Su T, Hsu H, Chang W, Chen P, Sung F, Chen M, Lee Y. Constructing the prediction model for the risk of stroke in a Chinese population. Stroke. 2010;41(9):1858–64.

    Article  Google Scholar 

  30. Zhang X, Attia J, D’Este C, Yu X, Wu X. A risk score predicted coronary heart disease and stroke in a chinese cohort. J Clin Epidemiol. 2005;58(9):951–8.

    Article  PubMed  Google Scholar 

  31. National Bureau of Statistics. The sixth national census. ; 2010. http://www.stats.gov.cn/tjsj/pcsj/rkpc/6rp/indexch.htm. Accessed 16 Aug 2022.

  32. Kulchaitanaroaj P, Brooks JM, Chaiyakunapruk N, Goedken AM, Chrischilles EA, Carter BL. Cost-utility analysis of physician-pharmacist collaborative intervention for treating hypertension compared with usual care. J Hypertens. 2017;35(1):178–87.

    Article  CAS  PubMed  Google Scholar 

  33. Tangri N, Ferguson TW, Whitlock RH, Rigatto C, Jassal DS, Kass M, Toleva O, Komenda P. Long term health outcomes in patients with a history of myocardial infarction: a population based cohort study. PLoS ONE. 2017;12(7):e180010.

    Article  Google Scholar 

  34. Chiang FT, Shyu KG, Wu CJ, Mar GY, Hou CJ, Li AH, Wen MS, Lai WT, Lin SJ, Kuo CT, et al. Predictors of 1-year outcomes in the Taiwan acute coronary syndrome full spectrum registry. J Formos Med Assoc. 2014;113(11):794–802.

    Article  PubMed  Google Scholar 

  35. Lulu S, Rong L, Tao L, Shiming J, Xiaofeng K, Jinyu G, Jian Z. Prognosis Status with its influencing factors in heart failure patients during 1 year of discharged period. Chin Circulation J. 2013;28(02):125–8.

    Google Scholar 

  36. Chang KC, Lee HC, Tseng MC, Huang YC. Three-year survival after first-ever ischemic stroke is predicted by initial stroke severity: a hospital-based study. Clin Neurol Neurosur. 2010;112(4):296–301.

    Article  Google Scholar 

  37. National Bureau of Statistics. China’s GDP per capita in 2021. ; 2022. https://data.stats.gov.cn/easyquery.htm?cn=C01. Accessed 16 Aug 2022.

  38. Conti RM, Padula WV, Becker RV, Salamone S. The cost-effectiveness of therapeutic drug monitoring for the prescription drug-based treatment of chronic myeloid leukemia. J Manag Care SPEC PH. 2021;27(8):1077–85.

    Google Scholar 

  39. Ministry of Health of the People’s Republic of China. 2020 China Health Statistics Yearbook; 2021. https://www.yearbookchina.com/navibooklist-n3020013080-1.html?from=singlemessage. Accessed 21 Dec 2021.

  40. Wu Y, Zhou Q, Xuan J, Li M, Zelt S, Huang Y, Yin H, Huang M. A cost-effectiveness analysis between Amlodipine and Angiotensin II receptor blockers in stroke and myocardial infarction Prevention among Hypertension Patients in China. Value Health Reg ISS. 2013;2(1):75–80.

    Article  Google Scholar 

  41. Zhang L, Lin Z, Yin H, Liu J, Xuan J. Clopidogrel Versus aspirin for the treatment of acute coronary syndrome after a 12-month dual antiplatelet therapy: a cost-effectiveness analysis from China payer’s perspective. Clin Ther. 2018;40(12):2125–37.

    Article  CAS  PubMed  Google Scholar 

  42. Guo H, Wang X, Xu J, Mao T, Chen J. Prevention of hypertension in patients with prehypertension in the rural areas of China: a community-based quasi-experiment. The Lancet. 2018;392:82.

    Article  Google Scholar 

  43. Ren M, Xuan D, Lu Y, Fu Y, Xuan J. Economic evaluation of olmesartan/amlodipine fixed-dose combination for hypertension treatment in China. J Med Econ. 2020;23(4):394–400.

    Article  PubMed  Google Scholar 

  44. The CHNS research team. China Health and Nutrition Survey. ; 2021. https://www.cpc.unc.edu/projects/china/. Accessed 21 December 2021.

  45. Li D. Research on the Application of Activity-based Costing in Public Hospital Cost Accounting——Taking Y Public Hospital as an Example. Yunnan University of Finance and Economics; 2021. Available at: https://kns.cnki.net/kcms2/article/abstract?v=ECJfaSgxqGd8lsxGY4nOKHJSLq-oKShzksE_AbiOpMP92AROCGWPOpUHHWjvZFByBKl53X4QA_dxbNepF16qqMeU8Mi60He4yOHbmDJG7DiIo7rOlghkbw==&uniplatform=NZKPT&language=CHS.

  46. Luo L, Wang Z, Fang X, Xu H, Zhong H, Kang X. China’s online sporting goods consumption status and influencing factors——An empirical analysis based on big data on Tmall platform. J Shanghai Sport Univ. 2021;45(06):35–49.

    Google Scholar 

  47. Zhang Z, Research on the Design of Home Fitness Equipment Based on Consumer Behavior. Yanshan University; 2014. Available at: https://kns.cnki.net/kcms/detail/detail.aspx?FileName=1015009364.nh&DbName=CMFD2015.

  48. Xian X, Research on Marketing Strategy of JH Vocational Training Company. Guangxi Normal University. ; 2016. Available at: https://kns.cnki.net/kcms2/article/abstract?v=ECJfaSgxqGdirFmQ2UX7846BoYidP1RuAe2VoAUY1Rfg-_c-6VcIla6mfnJj1HzihKgRR98RuEiGlz98CBR4W2LdmNDHIg8qDb4-c-TVCRpOMOfM4l0MzQ==&uniplatform=NZKPT&language=CHS.

  49. National Cardiovascular Disease Center Office. National basic hypertension prevention and management guidelines 2020 edition. China Recycling Magazine. 2021;36(3):209–20.

    Google Scholar 

  50. National Bureau of Statistics. 2020 China Statistical Yearbook. ; 2021. http://www.stats.gov.cn/tjsj/ndsj/2020/indexch.htm. Accessed 21 December 2021.

  51. Li M. Empirical Research on Yoga Movement in Xi’an Area——Taking Profitable Institutions as an Example. Xi’an Institute of Physical Education; 2013. Available at: https://kns.cnki.net/kcms2/article/abstract?v=ECJfaSgxqGfKwFuTS8pWjXkcWXh9SEFGajin2zENmWk8BDCF1m0YYrXSAc37iUFr5wQpUpfOuZDu5Xih4gR2eNvbYF5E5y1Ydj8dG8OPPHEZYs6QPr8duw==&uniplatform=NZKPT&language=CHS.

  52. Chen C, Research on Perfecting the Cost Accounting Method of Traditional Chinese Medicine Medical Service in Jiangsu Province from the Perspective of Knowledge Management. Nanjing University of Chinese Medicine; 2012. Available at: https://kns.cnki.net/kcms2/article/abstract?v=ECJfaSgxqGeSIgr-GIaRWQoE6qpEey3ELerPnMJuxe6astnS82bapZRLI3i8nhCbeuuWtCSB1Agx7lcRJdcN1Wih4-jyf0YLu3lF5YEE9oC555DeMez5WQ==&uniplatform=NZKPT&language=CHS.

  53. People’s Government of Xuanwu District, Nanjing City. Announcement of the price of medical service items in primary medical and health institutions in Xuanwu District (diagnosis and treatment of Chinese medicine and ethnic medicine). ; 2020. http://www.xwzf.gov.cn/xwqrmzf/202001/t20200107_1766775.html. Accessed 21 Dec 2021.

  54. People’s Government of Xuanwu District, Nanjing City. Announcement of the price of medical service items of primary medical and health institutions in Xuanwu District (Physiotherapy and Rehabilitation). ; 2020. http://www.xwzf.gov.cn/xwqrmzf/202001/t20200107_1766768.html. Accessed 21 Dec 2021.

  55. Perez-Aranda A, D’Amico F, Feliu-Soler A, McCracken LM, Penarrubia-Maria MT, Andres-Rodriguez L, Angarita-Osorio N, Knapp M, Garcia-Campayo J, Luciano JV. Cost-utility of mindfulness-based stress reduction for fibromyalgia versus a multicomponent intervention and usual care: a 12-month randomized controlled trial (EUDAIMON Study). J Clin Med. 2019;8(7):1068.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Spruill TM, Feltheimer SD, Harlapur M, Schwartz JE, Ogedegbe G, Park Y, Gerin W. Are there consequences of labeling patients with prehypertension? An experimental study of effects on blood pressure and quality of life. J Psychosom Res. 2013;74(5):433–8.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Wang R, Zhao Y, He X, Ma X, Yan X, Sun Y, Liu W, Gu Z, Zhao J, He J. Impact of hypertension on health-related quality of life in a population-based study in Shanghai, China. Public Health. 2009;123(8):534–9.

    Article  CAS  PubMed  Google Scholar 

  58. Coomans DBA, Scoubeau C, Musuaya AE, Costa-Junior JM, Castela A, Carpentier J, Faoro V, Klass M, Cnop M, Eizirik DL. Exercise as a non-pharmacological intervention to protect pancreatic beta cells in individuals with type 1 and type 2 diabetes. Diabetologia. 2023;66(3):450–60.

    Article  Google Scholar 

  59. Yin Y, Tu Y, Zhao M, Tang W. Effectiveness and cost-effectiveness of non-pharmacological interventions among chinese adults with prediabetes: a protocol for network meta-analysis and CHIME-modeled cost-effectiveness analysis. Int J Env Res Pub He. 2022;19(3):1622.

    Article  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

General Program of National Natural Science Foundation of China (72174207).

Author information

Authors and Affiliations

Authors

Contributions

Conceptualization: All authors; Methodology: LL and TS; Formal analysis and investigation: HL and LL; Writing - original draft preparation: LL, TS and HL; Writing - review and editing: WT and MZ; Funding acquisition: WT; Resources: WT; Supervision: WT.

Corresponding author

Correspondence to Wenxi Tang.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liang, L., Shao, T., Li, H. et al. Cost-effectiveness and potential budget impact of non-pharmacological interventions for early management in prehypertensive people: an economic evaluation for China. BMC Public Health 23, 1531 (2023). https://doi.org/10.1186/s12889-023-16458-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12889-023-16458-1

Keywords