https://orcid.org/0000-0001-9313-9981
Figures
Abstract
Previous studies showed that physical activity (PA) is concerned with hypertension (HTN). However, the mediation and interaction role of the obesity index: body mass index (BMI), waist-hip ratio (WHR), body fat rate (BFR) and visceral fat index (VFI) between PA and HTN has never been studied. Therefore, the purpose of this study was to assess the mediation and interaction of the obesity index between moderate-vigorous recreational physical activity (MVRPA) and HTN. We conducted a cross-sectional study of 4710 individuals aged 41 or older in Torch Development Zone, Zhongshan City. The mediation and interaction of the obesity index were evaluated by a four-way decomposition. 48.07% of participants had HTN among these groups. In the adjusted linear regression model, MVRPA was significantly correlated with WHR (β±SE = -0.005±0.002; P<0.05). Compared to sufficient MVRPA (odds ratio (OR) = 1.35), 95% (confidence interval (CI) = 1.17–1.56), insufficient MVRPA increased the risk of developing HTN. Furthermore, there were associations between BMI, WHR, BFR, VFI and HTN where the adjusted ORs and 95% CIs were 1.11 (1.09–1.13), 6.23 (2.61–14.90), 1.04 (1.03–1.06), 1.07 (1.06–1.09), respectively. The mediation analyses suggested that the impact of MVRPA on HTN risk may partly be explained by changes in obesity index, with a pure indirect mediation of WHR between MVRPA and HTN (P<0.05). Therefore, weight control, especially reducing abdominal obesity and maintaining adequate MVRPA, may lead to more proper control of HTN.
Citation: Du B, Li Y, Xia Y, Wu S, Wei Y, Wang Z, et al. (2023) The mediation and interaction of the obesity index between moderate-vigorous recreational physical activity and hypertension. PLoS ONE 18(12): e0296333. https://doi.org/10.1371/journal.pone.0296333
Editor: Jeong-Ah Ahn, Ajou University, REPUBLIC OF KOREA
Received: September 4, 2023; Accepted: December 8, 2023; Published: December 28, 2023
Copyright: © 2023 Du et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.
Funding: This work was supported by Key Project of National Natural Science Foundation of China (81830113) (JG); National key R & D plan of China "Research on modernization of traditional Chinese medicine" (2018YFC1704200) (JG) and Guangzhou Basic and Applied Basic Research General Project (202201010545) (TS). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
1. Introduction
One quarter of adults worldwide are affected by hypertension (HTN), which is the main cause of all-cause mortality and a serious global public health problem [1, 2]. A survey in China showed that the incidence rate of HTN is very high, and about 44.7% of adults have HTN [3, 4]. The older adults in China is constantly increasing, and the government and healthcare institutions have conducted extensive research and intervention efforts to prevent the prevalence of HTN. However, the control of HTN is still not optimistic [5, 6]. Factors cannot be ignored are: the age of HTN patients is decreasing, and the use of convenient interventions is not realistic [7].
In recent decades, the mechanism by which conventional physical activity (PA) has a protective effect on HTN has been extensively studied [8–10]. A systematic review also pointed out that people who participate in a large amount of leisure-time PA have a lower HTN risk than those who participate in a low amount of leisure-time PA [11]. A possible mechanism is to change the obesity status of individual [12]. Obesity is usually simply defined as abnormal or excessive accumulation in adipose tissue [13]. Body mass index (BMI) can be used to estimate the prevalence and associated risks of obesity in the population, and it is the simplest obesity measurement method. However, BMI does not take into account the wide variation in the distribution of body fat, and obesity or its associated health risks do not necessarily correspond across individuals and groups. Significant changes in abdominal fat mass within a narrow range of systemic fat or BMI. In addition, it is also possible to identify the increased risk from obesity-related diseases due to abdominal fat accumulation by measuring waist-hip ratio (WHR), body fat rate (BFR) and visceral fat index (VFI). The 2010 Global Burden of Disease Study estimated that approximately 3.4 million people may die from overweight and obesity [14]. A study has found a nearly linear correlation between BMI and blood pressure (BP) [15]. The increase in VFI in obese individuals may also lead to an increase in BP levels [16]. These studies confirm the connection between PA and obesity index. However, there is limited research on the combined effects of PA and obesity index on HTN. The mediation and interaction effects of obesity indices such as BMI, WHR, BFR, and VFI between moderate-vigorous recreational physical activity (MVRPA) and HTN, as well as their combined effects, are still unclear. Therefore, it is necessary to conduct this study to understand the link between PA and HTN risks in response to the high prevalence of HTN.
The relationship between exposure and outcome can be explained through the concepts of mediation and interaction, which can help explain the impact of a reason on the "how" and "for whom" of a result [17]. In this study, the mediation hypothesis is that individuals with insufficient MVRPA may increase the risk of unhealthy obesity index, which in turn may increase the risk of HTN. According to the interaction hypothesis, the unhealthy obesity index may have a stronger correlation with the risk of HTN in individuals with insufficient MVRPA. But there may be both mediation and interaction. In this context, traditional mediation analysis cannot be effectively conducted and interpreted due to the inability to take into account or distinguish different factors. In our study, we use J VanderWeele’s four-way decomposition method performs mediation/interaction analysis, which divides mediation and interaction effects into four components: (i) the effect of the exposure in the absence of the mediator, (ii) the interactive effect when the mediator is left to what it would be in the absence of exposure, (iii) a mediated interaction (INTmed), and (iv) a pure indirect effect (PIE) [18]. Compared to analyzing mediation and interaction effects separately, the four-way decomposition method can better reflect the correlation between exposure effects, mediation effects, and outcomes [19, 20].
The purpose of this study is to evaluate the mediation and interaction of the obesity index between MVRPA and HTN by applying a four-way decomposition method, so as to provide reference for the prevention and treatment of HTN.
2. Materials and methods
2.1 Study population
Our study was a cross-sectional survey used the baseline data from the Health Questionnaire of People with glucolipid metabolic disorder in Zhongshan City which is a predominantly development zone, and this study was based on the National Basic Public Health Service project. From May to October 2020, 11003 participants (aged≥41 years) enrolled at Zhongshan Torch Development Zone Hospital, Zhongshan City, Guangdong Province through local advertisements, invitation letters, health talks, or referrals from the local community. Individuals without severe infectious diseases, end-stage tumors, recent major surgeries, and external injuries who lived in the local area for more than 6 months were eligible to participate. Participants’ eligibility was verified by investigators in Zhongshan City. All eligible participants completed a self-administered questionnaire and participated in a physical examination which including health checkup (height, weight, waist circumference, hipline, BP, etc.), blood tests (fasting blood glucose (FBG), triglycerides). A standardized questionnaire and residents’ health records was used to assess demographic, anxiety, depression, and HTN. This study was conducted in accordance with the principles of the Declaration of Helsinki. This study has been approved by the Guangdong Pharmaceutical University Review Boards (Medical Ethics (2019) No.109). Paper informed consent was obtained from each participant, and the records were kept at Guangdong Pharmaceutical University.
As shown in the flow chart (Fig 1), of the total 11003 participants, 5429 participants had participated in and fill out PA part of questionnaire. we excluded 28 individuals aged≤40 years, and 691 individuals with missing data of covariates or mediators (age, weight, height, waist circumference, hipline, family income, occupation, BFR and VFI). This left a total of 4710 participants (1173 men and 2937 women) for the final analyses.
2.2 Assessment of MVRPA
The PA section of the questionnaire is based on an abbreviated version of International Physical Activity Questionnaire (IPAQ) [21]. In this study, the types of MVRPA included moderate recreational physical activity (MRPA) and vigorous recreational physical activity (VRPA). Information on MVRPA was collected at enrollment. We define fitness or recreational activities that last for at least 10 minutes and result in a small increase in breathing or heart rate as MRPA (such as brisk walking, slow jogging, yoga, practising Tai Chi, cycling, climbing stairs and dancing). We define fitness or recreational activities that last for at least 10 minutes and result in a large increase in breathing or heart rate as VRPA (such as long-distance running, playing football, playing basketball, playing badminton, doing rope skipping and swimming). Sufficient MVRPA was defined as adults should undertake not less than 150 minutes of MRPA or 75 minutes of VRPA or an equivalent combination of MRPA and VRPA (1min of VRPA is equivalent to 2min of MRPA) per week according to WHO 2020 guidelines on PA and sedentary behaviour [22].
2.3 Assessment of HTN
For each participant, we measured BP three times on different days on their right upper arm after five min of rest in a seated position using an electronic sphygmomanometer (Omron HBP-1300, Omron Corporation, Dalian, China). HTN was defined by an average of three BP measurements with combining systolic BP (SBP)≥140 mmHg and/or diastolic BP (DBP)≥90 mmHg, or a self-reported diagnosis of HTN, or current use of antihypertensive medications [23].
2.4 Assessment of mediators
The height was measured by metal column height meter (TZG, Shkodak Medical, Shanghai, China), the unit of height is centimeter (cm), accurate to 0.1 cm. Weight, BMI, BFR, VFI were reported by body composition analyzer (Omron HBF-371, Omron Corporation, Beijing, China), the maximum weighing range is 140 kg, and the recorded results are accurate to 100 g. And all participants remained fasting for at least 8 hours before measurement. Waist circumference and hip circumference were measured by tape measure, and the figure is accurate to 0.1 cm. WHR was computed as waist circumference (cm) divided by hipline (cm) [24].
2.5 Assessment of other factors
Sociodemographic information included age (continuous), sex (male and female), nation (the Han nationality or others), education level (elementary education, junior high education, secondary general or vocational education, higher vocational education or university), occupation (civil servants and employees of firms and enterprises, professional and technical personnel, service works, workers and peasants or others), family income (≤¥4000, ¥4001-¥10000, >¥10000 or not quite clear), marital status (single people, married people, divorced people or widowed people), smoking habits (never smokers, ex-smokers or current smoker) and alcohol consumption (never drinkers, ex-drinkers or current drinkers). Depression was measured using the score from the Patient Health Questionnaire-9 (PHQ-9) [25]. Judgment score of standards for identifying possible depression is 5 or above [26]. Anxiety was measured using the score from the Generalized Anxiety Disorder Scale-7 (GAD-7). Judgment score of standards for identifying possible anxiety is 5 or above [27].
2.6 Statistical analyses
Baseline characteristics were calculated and displayed as median values (upper or lower quartile) for continuous variables and ratios for categorical variables. The comparison of categorical variables is conducted using chi-square test. Comparison of continuous variables using analysis of ANOVA analysis. Linear regression analyses were performed to assess the relationships between BMI, WHR, BFR, VFI and MVRPA. Logistic regression analyses were performed to identify (1) independent variables (MVRPA was treated as categorical variables) associated with HTN; (2) independent variables (BMI, WHR, BFR and VFI were treated as continuous variables) associated with HTN. 95% CI was obtained by Wald method. The covariates of the model were determined through literature review and correlation analysis with single factor analysis. Meanwhile, the continuous variable triglyceride and FBG with more information are included in the model rather than the disease. All models were adjusted for the following potential confounding factors: age, sex, nation, education level, occupation, family income, marital status, drinking, smoking, anxiety, depression, triglyceride and FBG.
To further analyze the role of obesity index in MVRPA and HTN, we use J VanderWeele’s four-way decomposition method performs mediation/interaction analysis, which divides mediation and interaction effects into four components: controlled direct effect (CDE), reference interaction (INTref), INTmed, and PIE [18]. The following four potential contributors are defined in this article:
- CDE: The effect of MVRPA has a direct effect on HTN.
- INTref: This represents the impact on HTN that is due to the interaction between MVRPA and obesity index only.
- INTmed: This represents the impact on HTN that is due to both mediation and interaction between MVRPA and obesity index.
- PIE: The effect of MVRPA on HTN which purely goes through WHR.
Fig 2 shows a causal graphing representing the association of MVRPA with risk of HTN mediated by BMI, WHR, BFR and VFI. In SAS9.4, through the combination of four paths, all the effects and proportion attributes of the four combinations can be output. All analyses were performed with SAS version 9.4 software (SAS Institute Inc, Cary, NC, USA). Two-tailed P-values of <0.05 were considered statistically significant.
(A) CDE due to neither mediation nor interaction (in the current study: the effect of MVRPA has a direct effect on HTN), (B) INTref due to interaction alone, (C) INTmed due to both mediation and interaction, (D) PIE due to mediation alone (in the current study: the effect of MVRPA on HTN which purely goes through WHR).
3. Results
Table 1 shows the baseline characteristics of the study population by sufficient MVRPA and insufficient MVRPA. Of the 4710 subjects, 2937 (62.4%) were female, 3578 (76.0%) had insufficient MVRPA. Compared with participants in the insufficient MVRPA group, those in the sufficient MVRPA group were less likely to be low education,smokers, depression, anxiety and HTN.
Table 2 shows the baseline characteristics of the study population by non-HTN and HTN. Of the 4710 subjects, 2264 (48.1%) participants had HTN. Compared with participants in the non-HTN group, those in the HTN group were more likely to be low education, without spouses.
The linear regression revealed that MVRPA was associated with WHR and VFI before adjusted (β±SE = -0.010±0.002, -0.412±0.166, respectively; P <0.05) (Table 3). After adjustment for age, sex, nation, education, occupation, family income, marital status, drinking, smoking, and anxiety and depression, MVRPA still strongly associated with WHR (β±SE = -0.005±0.002; P <0.05). We did not observe the relation between MVRPA and BMI, BFR.
Table 4 shows that HTN was significantly associated with MVRPA before and after adjusting for potential confounders (crude OR = 1.44, 95%CI = 1.26–1.65; adjusted OR = 1.35, 95%CI = 1.17–1.56). Furthermore, there were associations between BMI, WHR, BFR, VFI and HTN where the multivariable-adjusted ORs and 95%CIs were 1.11 (1.09–1.13), 6.23 (2.61–14.90), 1.04 (1.03–1.06), 1.07 (1.06–1.09), respectively.
The results of the four-way decomposition are shown in Table 5. In the model accounting for the presence of a total effect between MVRPA and obesity index (BMI, WHR, BFR and VFI) (P<0.001), insufficient MVRPA increases the risk of HTN: 1.39 (1.18–1.60), 1.35 (1.16–1.55), 1.38 (1.19–1.58), 1.33 (1.12–1.54), respectively. With BMI, BFR and VFI as being the mediator, we didn’t observe the mediation and / or interaction, the excess relative risk (ERR) and 95% CIs of CDE were 0.34 (0.16–0.53), 0.36(0.17–0.55), 0.33(0.15–0.51), respectively. A mediate effect of WHR between MVRPA and HTN was observed. Specifically, the ERR of the PIE generated by WHR is 0.02 (95% CI: 0.00–0.03), and 5% of the ERR of insufficient MVRPA on HTN compared to sufficient MVRPA is attributable to PIE. And the overall proportion mediated (PIE plus the INTmed) by WHR was 4%.
4. Discussion
The results of the four-way decomposition analysis indicated that the effect of MVRPA on the risk of HTN may partly be explained by changes in obesity index, where there is PIE of WHR between MVRPA and HTN. The present study supplements the current literature regarding MVRPA and HTN among the elder population, and indicates WHR can more largely affect the association between MVRPA and the risk of HTN than BMI, BFR, and VFI.
According to our knowledge, there are few previous studies examining the interrelationships between MVPRA, obesity index and HTN, especially using the four-way decomposition method. Given that MVPRA is related to obesity index [28], our results indicated that the effects of MVPRA on HTN might be mediated by obesity index. Studies have shown that high levels of PA can reduce the risk of HTN by improving cardiovascular function and lowering levels of inflammatory factors [29, 30]. Furthermore, SBP, DBP and glycated hemoglobin (HbA1c) levels in people with high amounts of recreational sports and aerobic training were lower than non-exercising control group in middle-aged and older adults [31]. Our results are consistent with those findings. Similarly, a randomized controlled trial in older adults (66–80 years old) reported that home SBP (maximum between-group difference = 7.7 mmHg, P = 0.003) and home DBP (maximum between-group difference = 4.2 mmHg, P = 0.001) values of the exercise group is significantly lower than that of the non exercise group [32]. Recent WHO suggested that adults (18–64 years) and older adults (65 years and above) should, throughout the week, accumulate 150–300 minutes of moderate-intensity aerobic PA or 75–150 minutes of vigorous-intensity aerobic PA or an equivalent combination of moderate and vigorous PA [22]. Some studies also found that PA and all cause (CVD) cardiovascular disease mortality, cancer and diabetes incidence have a curvilinear dose-response relationship [22]. A China Health and Nutrition Survey 1991–2015 showed that the incidence rate of HTN increased from 10.86% in 1991 to 20.34% in 2015, while the median PA decreased from 408 MET·h/week to 104 MET·h/week at the same time. It is also pointed out that a high level of PA could to some extent alleviate the adverse effect of obesity index on HTN [33]. Moreover, a large national cohort study indicated that high BMI and low aerobic capacity in late adolescence were associated with higher risk of HTN in adulthood, and had a negative additive and multiplicative interaction [15]. However, we did not find a statistically significant interaction between PA and markers of obesity in present study. Decreasing PA and increasing BMI were associated with increased risk of HTN. Our findings consistent with Jackson’s study and suggest that both PA and maintenance of a healthy body weight are associated with lower risk of HTN [15], and there is a pure indirect mediation of WHR between MVRPA and HTN.
Participates with insufficient MVRPA have higher risk of HTN than those with sufficient MVRPA. In our study, only WHR as mediator has statistically significance PIE (4%, 0%-9%). This may due to WHR can reveal an unfavorable increase in abdominal fat much better than BMI, BFR and VFI [34]. Previous studies have shown that the deposition of abdominal fat organs is closely related to the occurrence of HTN [35, 36]. Previous research reports showed that abdominal obesity increases the likelihood of insulin resistance and elevated levels of non sterile fatty acid water, thereby increasing the risk of cardiovascular disease [37]. However, the mechanism by which determine fat distribution are not yet clear, and current data cannot explain why different behaviors are related to fat deposition at different locations. It has been suggested that visceral fat is particularly susceptible to adrenal-driven lipolysis during PA, which is why visceral fat is preferentially reduced in people with high PA levels [38]. Some potential biological mechanisms may explain how the impact of MVPRA on HTN is partially attributed to obesity index [39]. The findings showed that the reduction in PA-induced HTN was associated with post-exercise blood viscosity and aggregation of red blood cells [40]. At the same time, it can reduce sympathetic nerve tension, as to reduce the release of catecholamines, which reduce systemic vascular resistance [41, 42]. Indirectly, catecholamines act through β-adrenergic receptors in adipocytes, inducing an increase in cyclic adenosine monophosphate (cAMP) levels, which activates prekallikrein activator (PKA) and ultimately enhances lipolysis [43]. Adipose tissue is responsible for secreting leptin, a cytokine that boosts the activity of the sympathetic nervous system. So, lipolysis may lead to lower sympathetic nerve tension, relax peripheral artery, and lower BP [44].
This study has the following strengths: for the first time, the four-way decomposition method was used to explore the association between MVRPA and hypertension, but it has not been widely used in clinical research. Moreover, our study used a large, high compliance, baseline data of cohort population. Our study also has several limitations. First, we used a cross-sectional data, but the four-way decomposition may be more suitable for prospective cohort studies [19]. However, in our study, the causal sequence is basically reasonable given that HTN was regarded as chronic diseases, obesity index about BMI, WHR, BFR and VFI were all collected in hospital’s physical examination or residents’ health records. Second, the data of MVRPA are obtained from questionnaires, and it is inevitable that there will be errors when compared with the objective measurement results using accelerometers. Noticeably, the measure of MVRPA was based on the IPAQ with sufficient reliability and validity. Last, although we adjusted for study covariates in the analyses, there may be some unmeasured confounding factors in our study, such as participants’ eating habit, which is likely to impact PA behaviors and obesity index. Therefore, future studies are needed.
In conclusion, we found that in the predisposing factor of HTN, the effect of MVRPA on the risk of HTN may partly be explained by changes in WHR, where there is PIE of WHR between MVRPA and HTN. Therefore, weight control, especially reducing abdominal obesity and maintaining adequate MVRPA, may lead to more proper control of HTN. And our study may provide insights into the predisposing factor of clinical outcomes by causal mediation analysis in clinical research.
References
- 1. Xu X, Byles J, Shi Z, McElduff P, Hall J. Dietary pattern transitions, and the associations with BMI, waist circumference, weight and hypertension in a 7-year follow-up among the older Chinese population: a longitudinal study. BMC Public Health. 2016;16:743–754. pmid:27502827
- 2. Manosroi W, Williams GH. Genetics of Human Primary Hypertension: Focus on Hormonal Mechanisms. Endocr Rev. 2019;40:825–856. pmid:30590482
- 3. Wang Z, Chen Z, Zhang L, Wang X, Hao G, Zhang Z, et al. Status of Hypertension in China: Results From the China Hypertension Survey, 2012–2015. Circulation. 2018;137:2344–2356. pmid:29449338
- 4. Xu Z, Yang J, Hu J, Song Y, He W, Luo T, et al. Primary Aldosteronism in Patients in China With Recently Detected Hypertension. J Am Coll Cardiol. 2020;75:1913–1922. pmid:32327102
- 5. Li D, Lv J, Liu F, Liu P, Yang X, Feng Y, et al. Hypertension burden and control in mainland China: Analysis of nationwide data 2003–2012. Int J Cardiol. 2015;184:637–644. pmid:25771229
- 6. Li W, Gu H, Teo KK, Bo J, Wang Y, Yang J, et al. Hypertension prevalence, awareness, treatment, and control in 115 rural and urban communities involving 47 000 people from China. J Hypertens. 2016;34:39–46. pmid:26630211
- 7. Lu J, Lu Y, Wang X, Li X, Linderman GC, Wu C, et al. Prevalence, awareness, treatment, and control of hypertension in China: data from 1·7 million adults in a population-based screening study (China PEACE Million Persons Project). Lancet. 2017;390:2549–2558. pmid:29102084
- 8. Börjesson M, One-ups A, Lundqvist S, Dahlöf B. Physical activity and exercise lower blood pressure in individuals with hypertension: narrative review of 27 RCTs. Br J Sports Med. 2016;50:356–61. pmid:26787705
- 9. Liu X, Zhang D, Liu Y, Sun X, Han C, Wang B, et al. Dose-Response Association Between Physical Activity and Incident Hypertension: A Systematic Review and Meta-Analysis of Cohort Studies. Hypertension. 2017;69:813–820. pmid:28348016
- 10. Diaz KM, Booth JN 3rd, Seals SR, Abdalla M, Dubbert PM, Sims M, et al. Physical Activity and Incident Hypertension in African Americans: The Jackson Heart Study. Hypertension. 2017;69:421–427. pmid:28137988
- 11. Pescatello LS, Buchner DM, Jakicic JM, Powell KE, Kraus WE, Bloodgood B, et al. Physical Activity to Prevent and Treat Hypertension: A Systematic Review. Med Sci Sports Exerc. 2019;51:1314–1323. pmid:31095088
- 12. Kenchaiah S, Sesso HD, Gaziano JM. Body mass index and vigorous physical activity and the risk of heart failure among men. Circulation. 2009;119:44–52. pmid:19103991
- 13. Obesity: preventing and managing the global epidemic. Report of a WHO consultation. World Health Organ Tech Rep Ser. 2000;894:1–253.
- 14. Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H, et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380:2224–60. pmid:23245609
- 15. Jackson C, Herber-Gast GC, Brown W. Joint effects of physical activity and BMI on risk of hypertension in women: a longitudinal study. J Obes. 2014;2014:2715–32. pmid:24669312
- 16. Seravalle G, Grassi G. Obesity and hypertension. Pharmacol Res. 2017;122:1–7. pmid:28532816
- 17.
VanderWeele TJ. Explanation in causal inference: methods for mediation and interaction. New York, NY: Oxford University Press; 2015. https://doi.org/10.1080/17470218.2015.1115884 pmid:28190383
- 18. VanderWeele TJ. A unification of mediation and interaction: a 4-way decomposition. Epidemiology. 2014;25:749–61. pmid:25000145
- 19. Wang G, Sun Q, Liang L, Clash C, Zhang C, Hong X, et al. Inter-generational link of obesity in term and preterm births: role of maternal plasma acylcarnitines. Int J Obes (Lond). 2019;43:1967–1977. pmid:31332276
- 20. Mutlu U, Swanson SA, Klaver CCW, Hofman A, Koudstaal PJ, Ikram MA, et al. The mediating role of the venules between smoking and ischemic stroke. Eur J Epidemiol. 2018;33:1219–1228. pmid:30182323
- 21. Cleland C, Ferguson S, Ellis G, Hunter RF. Validity of the International Physical Activity Questionnaire (IPAQ) for assessing moderate-to-vigorous physical activity and sedentary behaviour of older adults in the United Kingdom. BMC Med Res Methodol. 2018;18:176–188. pmid:30577770
- 22. Bull FC, Al-Ansari SS, Biddle S, Borodulin K, Buman MP, Cardon G, et al. World Health Organization 2020 guidelines on physical activity and sedentary behaviour. Br J Sports Med. 2020;54:1451–1462. pmid:33239350
- 23. National Health Commission, The National Bureau of Disease Control and Prevention, National Center for Cardiovascular Diseases, Fuwai hospital, Chinese Academy of Medical Sciences, et al. National guideline for hypertension management in China (2019). Chinese Journal of Cardiology. 2020, 48(01): 10–46. pmid:32008294
- 24. Zhou BF; Cooperative Meta-Analysis Group of the Working Group on Obesity in China. Predictive values of body mass index and waist circumference for risk factors of certain related diseases in Chinese adults—study on optimal cut-off points of body mass index and waist circumference in Chinese adults. Biomed Environ Sci. 2002;15:83–96.
- 25. Levis B, Benedetti A, Thombs BD. Accuracy of Patient Health Questionnaire-9 (PHQ-9) for screening to detect major depression: individual participant data meta-analysis. BMJ. 2019;365:1476–1487. pmid:30967483
- 26. Gilbody S, Richards D, Brealey S, Hewitt C. Screening for depression in medical settings with the Patient Health Questionnaire (PHQ): a diagnostic meta-analysis. J Gen Intern Med. 2007;22:1596–602. pmid:17874169
- 27. Toussaint A, Hüsing P, Gumz A, Wingenfeld K, Härter M, Schramm E, et al. Sensitivity to change and minimal clinically important difference of the 7-item Generalized Anxiety Disorder Questionnaire (GAD-7). J Affect Disord. 2020;265:395–401. pmid:32090765
- 28. Wang R, Feng Z, Xue D, Liu Y, Wu R. Exploring the links between population density, lifestyle, and being overweight: secondary data analyses of middle-aged and older Chinese adults. Health Qual Life Outcomes. 2019;17:100–110. pmid:31186044
- 29. Lieb W, Vasan RS. Prevention strategies for hypertension: who should be targeted? Future Cardiol. 2008;4:211–3. pmid:19804325
- 30. Vancampfort D, Koyanagi A, Ward PB, Rosenbaum S, Schuch FB, Mugisha J, et al. Chronic physical conditions, multimorbidity and physical activity across 46 low- and middle-income countries. Int J Behav Nutr Phys Act. 2017;14:6–19. pmid:28100238
- 31. Schneider VM, Frank P, Fuchs SC, Ferrari R. Effects of recreational sports and combined training on blood pressure and glycated hemoglobin in middle-aged and older adults: A systematic review with meta-analysis. Exp Gerontol. 2021;154:1115–49. pmid:34509590
- 32. Miura H, Takahashi Y, Maki Y, Sugino M. Effects of exercise training on arterial stiffness in older hypertensive females. Eur J Appl Physiol. 2015;115:1847–54. pmid:25869875
- 33. Zou Q, Wang H, Su C, Du W, Ouyang Y, Jia X, et al. Longitudinal association between physical activity and blood pressure, risk of hypertension among Chinese adults: China Health and Nutrition Survey 1991–2015. Eur J Clin Nutr. 2021;75:274–282. pmid:32404900
- 34. Freigang R, Geier AK, Schmid GL, Frese T, Klement A, Unverzagt S. Misclassification of Self-Reported Body Mass Index Categories. Dtsch Arztebl Int. 2020;117:253–260. pmid:32449888
- 35. Eastwood SV, Tillin T, Wright A, Mayet J, Godsland I, Forouhi NG, et al. Thigh fat and muscle each contribute to excess cardiometabolic risk in South Asians, independent of visceral adipose tissue. Obesity. 2014;22:2071–2079. pmid:24862429
- 36. Sullivan CA, Kahn SE, Fujimoto WY, Hayashi T, Leonetti DL & Boyko EJ. Change in intra-abdominal fat predicts the risk of hypertension in Japanese Americans. Hypertension 2015;66:134–140. pmid:26063668
- 37. Van Gaal LF, Mertens IL, De Block CE. Mechanisms linking obesity with cardiovascular disease. Nature. 2006;444:875–80. pmid:17167476
- 38. Murphy JC, McDaniel JL, Mora K, Villareal DT, Fontana L, Weiss EP. Preferential reductions in intermuscular and visceral adipose tissue with exercise-induced weight loss compared with calorie restriction. J Appl Physiol. 2012;112:79–85. pmid:22016371
- 39. El-Ashker S, Pednekar MS, Narake SS, Albaker W, Al-Hariri M. Blood Pressure and Cardio-Metabolic Risk Profile in Young Saudi Males in a University Setting. Medicina (Kaunas). 2021;57:755–764. pmid:34440961
- 40. Stembridge M, Ainslie PN, Boulet LM, Anholm J, Subedi P, Tymko MM, et al. The independent effects of hypovolaemia and pulmonary vasoconstriction on ventricular function and exercise capacity during acclimatisation to 3800 m. J Physiol. 2019;597:1059–1072. pmid:29808473
- 41. Beevers G, Lip GY, O’Brien E. ABC of hypertension: The pathophysiology of hypertension. BMJ. 2001;322:912–6. pmid:11302910
- 42. Devereux RB, Case DB, Alderman MH, Pickering TG, Chien S, Laragh JH. Possible role of increased blood viscosity in the hemodynamics of systemic hypertension. Am J Cardiol. 2000;85:1265–8. pmid:10802017
- 43. Kolnes KJ, Petersen MH, Lien-Iversen T, Højlund K, Jensen J. Effect of Exercise Training on Fat Loss-Energetic Perspectives and the Role of Improved Adipose Tissue Function and Body Fat Distribution. Front Physiol. 2021;12:7377–09. pmid:34630157
- 44. Stenehjem JS, Hjerkind KV, Nilsen TIL. Adiposity, physical activity, and risk of hypertension: prospective data from the population-based HUNT Study, Norway. J Hum Hypertens. 2018 Apr;32(4):278–286. pmid:29483587