Skip to main content
Download PDF

The mediating effect of sleep disturbance on the association between hypertension and depression: a national data analysis

Clinical Hypertension volume 30, Article number: 5 (2024) Cite this article

Abstract

Background

Sleep disturbance is a common among people with hypertension. However, the mediating role of sleep disturbance in the association between hypertension and depression remains unclear. This study aims to investigate the mediating role of sleep disturbance in the association between hypertension and depression.

Materials and methods

This was cross-sectional study. The data were derived from the Indonesian Family Life Survey Fifth Wave (2014–2015). We include a total of 19,138 adults’ participants with age range from 18 to 65 years old who completed response on the variable of hypertension, sleep disturbance, and depression. The mediating model analysis was processed using the PROCESS macro ins SPSS from Hayes model.

Results

Depression was reported by 22% of total respondents. The group with hypertension showed a substantially higher prevalence of depression than non-hypertension group (P < 0.001). Hypertension had a significant overall effect on depression (β = 0.682; 95%CI 0.489 to 0.875, P < 0.001). The direct effect of hypertension on depression was significant (β = 0.418; 95%CI 0.244 to 0.592, P < 0.001) and the indirect effect that mediated by sleep disturbance was also significant (β = 0.264, 95%CI 0.174 to 0.356, P < 0.001). It is worth noting that sleep disturbance partially mediated the association between hypertension and depression.

Conclusion

The findings of this study indicated that sleep disturbance contributed to the etiology of depression and hypertension in adult populations. Nurses should be involved in managing sleep disturbances, such as using behavioral therapy, as it may serve as both a treatment and primary prevention measure for depression and hypertension.

Graphical Abstract

Background

Hypertension is a common chronic condition with global prevalence ranging from 31 to 56% [1, 2]. In Indonesia, about 8.4% of adults have been diagnosed with hypertension by a medical doctor [3]. Hypertension has been linked to elevated risk of cardiovascular comorbidities including stroke [4] and chronic kidney diseases [5, 6]. Other evidence suggests that people with hypertension are more likely to experience depression [7, 8].

Several studies have reported prevalence rates ranging from 22 to 32% [7, 9]. Previous studies suggest a bidirectional association between hypertension and depression [9, 10]. Depression may increase the risk of hypertension by activating the body’s stress responses and increasing autonomic nervous system activation [11]. On the other hand, hypertension may increase the risk for depression by causing cerebrovascular pathologies [12] and increasing the sense of hopelessness related to living with a chronic condition [13]. People who suffer from both depression and hypertension often report low quality of life [14]. In addition, they often experience sleep disturbances [15]. While, the underlying mechanism of the hypertension-depression relationship remain complex, sleep disturbance has been identified as a potential mediator [15].

Sleep disturbance has been linked to physical and mental health including cardiovascular disease and mood disorders [16]. People with sleep problem have high risk to develop hypertension [17] and depression [18]. However, there is a lack of study investigating the mediating role of sleep disturbance in the association between hypertension and depression. Hence, in this study we aim to investigate the mediating role of sleep disturbance in the association between hypertension and depression using nationally representative data from Indonesia.

Materials and methods

Data source and participants

The data was derived from Indonesian Family Life Survey (IFLS) fifth Wave (IFLS-5), which is a cross-sectional study, fielded in September 2014 to April 2015. The IFLS sample represents approximately 83% of the Indonesian population living in 13 of the country’s 26 provinces, covering 16,204 households and 50,148 individuals [19]. The IFLS has been conducted 5 times, in 1993, 1997, 2000, 2007, and 2014. The details of study design of the IFLS-5 have been previously described [19]. In this study, we include a total of 19,138 adults’ participants with age range from 18 to 65 years old who have completed response on the variable of hypertension, sleep disturbance, and depression.

Ethical approval

The IFLS data are accessible to the general public. Institutional review boards at the University of Gajah Mada in Indonesia and the RAND Corporation in the United States have examined and approved the survey’s methods with the ethical clearance No.s0064-06-01-CR01 [19]. Before data collection began, all participants provided their written, informed consent.

Measurements

Depression

Depression was measured using the short form Centres for Epidemiologic Studies Depression Scale (CES-D-10) [20]. CES-D-10 consist of 10 items rated on a 4-point Likert scale ranging from 0 (rarely or none of the time) to 3 (all of the time) with higher score indicating more depressive symptoms. A total score of 10 or higher is indicative of having depression. Previous study revealed that this scale has acceptable validity and reliability [19].

Hypertension

Previous studies using IFLS data indicate that hypertension, as measured by blood pressure, covers approximately 40% of participants [21, 22], while hypertension using self-reported measurements covers around 80% of participants [21]. Therefore, in this study, hypertension was assessed using self-report, measured with the question, “Has a doctor, paramedic, or nurse ever told you that you had hypertension?”.

Sleep disturbance

Sleep disturbance was measured using the combination of five items of Patient-Reported Outcomes Measurement Information System (PROMIS) sleep disturbance measure [23] and five items of PROMIS sleep impairment measure [24]. Previous study reported that the scale has good Cronbach’s alpha of 0.82 [25]. Higher scores on the scales indicate more sleep disturbance with a cut-off point 11 or higher indicating of having sleep disturbance [25].

Lifestyle and comorbidity condition

Smoking status was measured and classified into three groups (never, quitters and current tobacco users) [19]. Physical activity was measured using the short version of International Physical Activity Questionnaire (IPAQ) for the last 7 days (IPAQ-S7S) [26]. It is divided into three level of low, moderate, and high intensity physical activity. Additionally, for the outpatient care were assessed using single item questionnaire [19].

For comorbidity conditions (diabetes mellitus, tuberculosis, asthma, lung condition, heart attack, liver disease, stroke, cancer, high cholesterol, kidney disease, stomach or other digestive disease, and psychiatric problem). It was measured using single item question such as ‘Has a doctor/paramedic/nurse/midwife ever told you that you had…? to which participants answered “yes” or “no” [19].

Demographic

In addition, demographic variable including age, gender, marital status, attending school, and education level were added in this study [19].

Statistical analyses

At the beginning, we used STATA software for all data processing. In the second stage, we used SPSS software version 29.0 to perform all statistical analyses (IBM, Armonk, NY, USA). A two-tailed of P < 0.05 was considered as a statistically significant level. To analyse the differences in the baseline characteristics between the 2 groups, we used the chi-squared or Fisher’s exact test for categorical variables and independent t-tests for continuous variables. The correlation between main variable (hypertension, sleep disturbance, and depression) were measured using Pearson and Spearman correlation. Univariate and multivariate linear regression analyses were also performed. Finally, the mediating model analysis was processed using the PROCESS macro ins SPSS from Hayes model [27].

Result

Study characteristic

Figure 1 depicted the participants’ flow diagram. In total, there were 25,824 adult participants were screened for eligibility. Of these, a total of 6,686 participants were excluded, with 779 not responding to questionnaires and 5,907 having missing data. This included missing data in the ‘hypertension’ variable (n = 4,932), ‘depression’ variable (n = 966), and ‘sleep disturbance’ variable (n = 9). Finally, a total of 19,138 participants were included in the main analysis. Hypertension was confirmed for 2,736 (14.3%) individuals.

Fig. 1
figure 1

Participant flow chart. n = number of participants

Full size image

Demographic comparisons between patients with hypertension (n = 2,736) and without hypertension (n = 16,402) were presented in Table 1. The prevalence of hypertension varies across age groups, with rates of 6.5% for the 18–34 age group, 13.1% for the 35–49 age group, and 25.9% for the 50–65 age group. Most of the participants were married (84%) and 96% of them have attended the school.

Table 1 Demographic comparison of participants
Full size table

The comparison of lifestyle and comorbidity conditions were presented in Table 2. In total 37% of included participants were smoker. The hypertension group had higher sleep disturbance compared to the non-hypertension group. There is a significant difference between the two groups in terms of physical activity (vigorous and low activity levels) (P < 0.001 and P = 0.001, respectively). Other details of the variable can be seen in Table 2.

Table 2 Lifestyle and comorbid comparison of participants
Full size table

Depression

The depression was reported in 22% of the total sample. The group with hypertension had a significantly higher depression prevalence compared to the non-hypertension group (see Table 2, P < 0.001). Supplementary Table S1 presented the response of participants who endorse each of the depression questionnaires.

Association between the hypertension, sleep disturbance, and depression

Supplementary Table S2 shows the association between the hypertension, sleep disturbance, and depression. The hypertension variable had a significant positive correlation with depression (r = 0.05, P < 0.001). The hypertension variable also has a significant positive correlation with sleep disturbance (r = 0.05, P < 0.001). Similarly sleep disturbance variable also has a significant positive correlation with depression (r = 0.44, P < 0.001).

The bivariate and multiple linear regression results are displayed in Table 3. In the unadjusted model, all predictors show a significant positive association with the target variable. When hypertension and sleep disturbance are combined as predictors in Model 1, the association remains significantly positive. In Model 2, all predictors also exhibit a significant positive association with the outcome variables.

Table 3 Associations from multiple linear regression models of hypertension with sleep disturbance, and depression
Full size table

Mediating effect of sleep disturbance on the association between hypertension and depression

The simple mediating analysis indicated that sleep disturbance partially mediated the association between hypertension and depression. As shown in Fig. 2 and supplementary Table 3, hypertension was positively associated with sleep disturbance (a = 0.725), and sleep disturbance was positively associated with depression (b = 0.364). Based on 5,000 bootstrap resamples, the bootstrap confidence interval for the indirect effect (ab = 0.264) was entirely above zero, ranging from 0.174 to 0.356. The total effect of hypertension on depression was significant (β = 0.682; 95% CI 0.489 to 0.875, P < 0.001), comprising a direct effect (β = 0.418; 95% CI 0.244 to 0.592, P < 0.001) and an indirect effect (β = 0.264; 95% CI 0.174 to 0.356, P < 0.001).

Fig. 2
figure 2

Mediation Analysis Results. The data were presented in Beta coefficient (standard error)

Full size image

Discussion

To the best of our knowledge, this is the first study investigating the mediating effect of sleep disturbance in the association between hypertension and depression. This study highlights that sleep disturbance becomes partial mediation in the association between hypertension and depression. Because the methodology is rigorous and we use a big sample size, hence our study should be considered.

Although the pathological mechanism of sleep disturbance after hypertension was complex. However, it can develop as a result of hypertension due to factors such as persistent physiological stress [28], increased sympathetic nervous system activity causing alertness [29, 30], disrupted nighttime blood pressure patterns [31], potential sleep-affecting medication side effects [32], psychological impact from hypertension management [33], and endothelial dysfunction [34, 35], all of which contribute to sleep disruptions. Effective hypertension treatment, lifestyle changes [36], and stress reduction measures are critical for sleep disturbance [37]. If sleep problems persist, it is critical to consult a healthcare practitioner, as treating hypertension may improve sleep quality [37,38,39].

In this study, sleep disturbance is observed in approximately 17% of the hypertension group and 13.7% of the non-hypertension group. Consistent with previous studies, sleep disturbances such as obstructive sleep apnea (OSA) and insomnia are prevalent following hypertension [32, 40, 41]. Evidence suggests that OSA becomes a significant risk factor for hypertension [42]. Numerous pathways, including endothelial impairment [43, 44], oxidative stress [45, 46], inflammation [47, 48], and sympathetic activation [49, 50], are generally acknowledged as ways in which OSA leads to the development of hypertension. Of note, this study reveals that sleep disturbance partially mediates the association between hypertension and depression. It indicates that targeting depression treatment after hypertension should also consider sleep disturbance.

We found that the prevalence of depression following hypertension in our study is 25% which is higher than in the non-hypertension group (21%, see Table 2). In line with previous studies, the prevalence of depression was ranging from 22 to 32% following hypertension [7, 9] and 13–17% in the general population [51, 52]. Because the presence of depression affects the health-related quality of life [14]. Hence, it is important for clinicians and researchers to implement the best treatment approach for depression.

Strengths and limitations

To the best of our knowledge, this study possesses several strengths. First, this study was national representativeness of the data since the study population was taken from participants across Indonesia. Second, all interviewers for the IFLS were trained to understand the methodology and the content of the questionnaire.

This study highlights several limitations. First, the data related severity of hypertension, subtype, and type of medication is not available. Second, potential confounders could not obtain such use hypnotic used, dietary factors, and environmental factors, which may threaten the internal validity. Third, the data related to blood pressure and medication for hypertension is unable to be provided. Fourth, the data related to hypertension was self-reported, which may cause information bias.

Conclusion

The result of this study suggested that sleep disturbance plays a role in the etiology of hypertension and depression in adult populations. The management of sleep disturbance could potentially serve as treatment and primary prevention for depression in these populations. Behavioral therapy could be implemented to reduce sleep disturbance.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

IFLS:

Indonesian Family Life Survey

CES-D-10:

Centers for Epidemiologic Studies Depression Scale

PROMIS:

Patient-Reported Outcomes Measurement Information System

IPAQ:

International Physical Activity Questionnaire

OSA:

Obstructive sleep apnea

References

  1. Bloch MJ. Worldwide prevalence of hypertension exceeds 1.3 billion. J Am Soc Hypertens. 2016;10(10):753–4.

  2. Kearney PM, Whelton M, Reynolds K, Whelton PK, He J. Worldwide prevalence of hypertension: a systematic review. J Hypertens. 2004;22(1):11–9.

    Article  CAS  PubMed  Google Scholar 

  3. Kemenkes RI. Laporan Nasional Riset Kesehatan Dasar. Kementerian Kesehatan RI. 2018. p. 203.

  4. Wajngarten M, Silva GS. Hypertension and stroke: update on treatment. Eur Cardiol Rev. 2019;14(2):111.

    Article  Google Scholar 

  5. Faraco G, Iadecola C. Hypertension: a harbinger of stroke and dementia. Hypertension. 2013;62(5):810–7.

    Article  CAS  PubMed  Google Scholar 

  6. Lauder L, Mahfoud F, Azizi M, Bhatt DL, Ewen S, Kario K, et al. Hypertension management in patients with cardiovascular comorbidities. Eur Heart J. 2023;44(23):2066–77.

    Article  CAS  PubMed  Google Scholar 

  7. Li Z, Li Y, Chen L, Chen P, Hu Y. Prevalence of depression in patients with hypertension: a systematic review and meta-analysis. Medicine. 2015;94:31.

    Article  Google Scholar 

  8. Villarreal-Zegarra D, Bernabe‐Ortiz A. Association between arterial hypertension and depressive symptoms: results from population‐based surveys in Peru. Asia‐Pacific Psychiatry. 2020;12(2):e12385.

    Article  PubMed  Google Scholar 

  9. Mai AS, Lim OZH, Ho YJ, Kong G, Lim GEH, Ng CH, et al. Prevalence, risk factors and intervention for depression and anxiety in pulmonary hypertension: a systematic review and meta-analysis. Front Med. 2022;9: 765461.

    Article  Google Scholar 

  10. Meng L, Chen D, Yang Y, Zheng Y, Hui R. Depression increases the risk of hypertension incidence: a meta-analysis of prospective cohort studies. J Hypertens. 2012;30(5):842–51.

    Article  CAS  PubMed  Google Scholar 

  11. Scalco AZ, Scalco MZ, Azul JBS, Neto FL. Hypertension and depression. Clinics. 2005;60(3):241–50.

    Article  PubMed  Google Scholar 

  12. Turana Y, Tengkawan J, Chia YC, Shin J, Chen CH, Park S, et al. Mental health problems and hypertension in the elderly: review from the HOPE Asia Network. J Clin Hypertens. 2021;23(3):504–12.

    Article  Google Scholar 

  13. Ang CW, Tan MM, Bärnighausen T, Reininghaus U, Reidpath D, Su TT. Mental distress along the cascade of care in managing hypertension. Sci Rep. 2022;12(1):15910.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Zhang Y, Zhou Z, Gao J, Wang D, Zhang Q, Zhou Z, et al. Health-related quality of life and its influencing factors for patients with hypertension: evidence from the urban and rural areas of Shaanxi Province, China. BMC Health Serv Res. 2016;16:1–9.

    Article  Google Scholar 

  15. Cai Y, Chen M, Zhai W, Wang C. Interaction between trouble sleeping and depression on hypertension in the NHANES 2005–2018. BMC Public Health. 2022;22(1):1–11.

    Article  Google Scholar 

  16. Seow LSE, Tan XW, Chong SA, Vaingankar JA, Abdin E, Shafie S, et al. Independent and combined associations of sleep duration and sleep quality with common physical and mental disorders: results from a multi-ethnic population-based study. PLoS One. 2020;15(7): e0235816.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Vgontzas AN, Liao D, Bixler EO, Chrousos GP, Vela-Bueno A. Insomnia with objective short sleep duration is associated with a high risk for hypertension. Sleep. 2009;32(4):491–7.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Kudlow P, Cha D, Lam R, McIntyre R. Sleep architecture variation: a mediator of metabolic disturbance in individuals with major depressive disorder. Sleep Med. 2013;14(10):943–9.

    Article  CAS  PubMed  Google Scholar 

  19. Strauss J, Witoelar F, Sikoki B. The fifth wave of the Indonesia family life survey: overview and field report, Vol. 1. Santa Monica: Rand; 2016. p. 1–94.

  20. Knight RG, Williams S, McGee R, Olaman S. Psychometric properties of the centre for epidemiologic studies depression scale (CES-D) in a sample of women in middle life. Behav Res Ther. 1997;35(4):373–80.

    Article  CAS  PubMed  Google Scholar 

  21. Mahwati Y, Nurrika D, Latief K. The determinants of undiagnosed hypertension among Indonesian adults: a cross-sectional study based on the 2014–2015 Indonesia family life survey. J Prev Med Public Health. 2022;55(1):60.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Latief K, Nurrika D, Tsai M-K, Gao W. Body mass index asian populations category and stroke and heart disease in the adult population: a longitudinal study of the Indonesia Family Life Survey (IFLS) 2007 and 2014. BMC Public Health. 2023;23(1):2221.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Yu L, Buysse DJ, Germain A, Moul DE, Stover A, Dodds NE, et al. Development of short forms from the PROMIS™ sleep disturbance and sleep-related impairment item banks. Behav Sleep Med. 2012;10(1):6–24.

    Article  Google Scholar 

  24. Buysse DJ, Yu L, Moul DE, Germain A, Stover A, Dodds NE, et al. Development and validation of patient-reported outcome measures for sleep disturbance and sleep-related impairments. Sleep. 2010;33(6):781–92.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Peltzer K, Pengpid S. Prevalence, social and health correlates of insomnia among persons 15 years and older in Indonesia. Psychol Health Med. 2019;24(6):757–68.

    Article  PubMed  Google Scholar 

  26. Craig CL, Marshall AL, Sjöström M, Bauman AE, Booth ML, Ainsworth BE, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003;35(8):1381–95.

    Article  PubMed  Google Scholar 

  27. Hayes AF. Mediation, moderation, and conditional process analysis. Introduction to mediation, moderation, and conditional process analysis: A regression-based approach, Vol. 1. 2013. p. 20.

  28. Kalmbach DA, Cuamatzi-Castelan AS, Tonnu CV, Tran KM, Anderson JR, Roth T, et al. Hyperarousal and sleep reactivity in insomnia: current insights. Nat Sci Sleep. 2018;10:193–201.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Maes J, Verbraecken J, Willemen M, De Volder I, Van Gastel A, Michiels N, et al. Sleep misperception, EEG characteristics and autonomic nervous system activity in primary insomnia: a retrospective study on polysomnographic data. Int J Psychophysiol. 2014;91(3):163–71.

    Article  CAS  PubMed  Google Scholar 

  30. Bonnet MH, Arand DL. Hyperarousal and insomnia: state of the science. Sleep Med Rev. 2010;14(1):9–15.

    Article  PubMed  Google Scholar 

  31. Maiolino G, Bisogni V, Soranna D, Pengo MF, Pucci G, Vettor R, et al. Effects of insomnia and restless legs syndrome on sleep arterial blood pressure: a systematic review and meta-analysis. Sleep Med Rev. 2021;59: 101497.

    Article  PubMed  Google Scholar 

  32. Jarrin DC, Alvaro PK, Bouchard M-A, Jarrin SD, Drake CL, Morin CM. Insomnia and hypertension: a systematic review. Sleep Med Rev. 2018;41:3–38.

    Article  PubMed  Google Scholar 

  33. Pickering TG, Hall JE, Appel LJ, Falkner BE, Graves J, Hill MN, Jones DW, Kurtz T, Sheps SG, Roccella EJ. Recommendations for blood pressure measurement in humans and experimental animals: part 1: blood pressure measurement in humans: a statement for professionals from the Subcommittee of Professional and Public Education of the American Heart Association Council on High Blood Pressure Research. Circulation. 2005;111(5):697–716.

  34. Portaluppi F, Tiseo R, Smolensky MH, Hermida RC, Ayala DE, Fabbian F. Circadian rhythms and cardiovascular health. Sleep Med Rev. 2012;16(2):151–66.

    Article  PubMed  Google Scholar 

  35. Chen L, Yang G. Recent advances in circadian rhythms in cardiovascular system. Front Pharmacol. 2015;6:71.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Williams B, Poulter N, Brown M, Davis M, McInnes G, Potter J, et al. Guidelines for management of hypertension: report of the fourth working party of the British hypertension society, 2004—BHS IV. J Hum Hypertens. 2004;18(3):139–85.

    Article  CAS  PubMed  Google Scholar 

  37. Lytle J, Mwatha C, Davis KK. Effect of lavender aromatherapy on vital signs and perceived quality of sleep in the intermediate care unit: a pilot study. Am J Crit Care. 2014;23(1):24–9.

    Article  PubMed  Google Scholar 

  38. Carnethon MR, Johnson DA. Sleep and resistant hypertension. Curr Hypertens Rep. 2019;21:1–6.

    Article  Google Scholar 

  39. Cho M-C. Clinical significance and therapeutic implication of nocturnal hypertension: relationship between nighttime blood pressure and quality of sleep. Korean Circ J. 2019;49(9):818–28.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Thomas SJ, Calhoun D. Sleep, insomnia, and hypertension: current findings and future directions. J Am Soc Hypertens. 2017;11(2):122–9.

    Article  PubMed  Google Scholar 

  41. Pepin J-L, Borel A-L, Tamisier R, Baguet J-P, Levy P, Dauvilliers Y. Hypertension and sleep: overview of a tight relationship. Sleep Med Rev. 2014;18(6):509–19.

    Article  PubMed  Google Scholar 

  42. Kareem O, Tanvir M, Naqash A, Bader GN. Obstructive sleep Apnoea: a risk factor for hypertension. J Cardiol Cardiovasc Sci. 2018;2(2):20–8.

  43. Hirata Y, Nagata D, Suzuki E, Nishimatsu H, Suzuki J-i, Nagai R. Diagnosis and treatment of endothelial dysfunction in cardiovascular disease a review. Int Heart J. 2010;51(1):1–6.

    Article  CAS  PubMed  Google Scholar 

  44. Jafari B, Mohsenin V. Endothelial dysfunction and hypertension in obstructive sleep apnea–Is it due to intermittent hypoxia? J Cardiovasc Disease Res. 2013;4(2):87–91.

    Article  Google Scholar 

  45. Lavie L. Oxidative stress in obstructive sleep apnea and intermittent hypoxia–revisited–the bad ugly and good: implications to the heart and brain. Sleep Med Rev. 2015;20:27–45.

    Article  PubMed  Google Scholar 

  46. Eisele HJ, Markart P, Schulz R. Obstructive sleep apnea, oxidative stress, and cardiovascular disease: evidence from human studies. Oxid Med Cell Longev. 2015;2015.

  47. Unnikrishnan D, Jun J, Polotsky V. Inflammation in sleep apnea: an update. Rev Endocr Metab Disord. 2015;16:25–34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Chul Sung K, Suh JY, Kim BS, Kang JH, Kim H, Lee MH, et al. High sensitivity C-reactive protein as an independent risk factor for essential hypertension. Am J Hypertens. 2003;16(6):429–33.

    Article  Google Scholar 

  49. Parati G, Lombardi C, Hedner J, Bonsignore MR, Grote L, Tkacova R, et al. Position paper on the management of patients with obstructive sleep apnea and hypertension: joint recommendations by the European Society of Hypertension, by the European Respiratory Society and by the members of European COST (COoperation in Scientific and Technological research) ACTION B26 on obstructive sleep apnea. J Hypertens. 2012;30(4):633–46.

    Article  CAS  PubMed  Google Scholar 

  50. Freet CS, Stoner JF, Tang X. Baroreflex and chemoreflex controls of sympathetic activity following intermittent hypoxia. Auton Neurosci. 2013;174(1–2):8–14.

    Article  CAS  PubMed  Google Scholar 

  51. Lim GY, Tam WW, Lu Y, Ho CS, Zhang MW, Ho RC. Prevalence of depression in the community from 30 countries between 1994 and 2014. Sci Rep. 2018;8(1):2861.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Alamri HS, Algarni A, Shehata SF, Al Bshabshe A, Alshehri NN, ALAsiri AM, et al. Prevalence of depression, anxiety, and stress among the general population in Saudi Arabia during Covid-19 pandemic. Int J Environ Res Public Health. 2020;17(24): 9183.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

Not applicable.

Author information

Authors and Affiliations

  1. Global Health and Health Security, College of Public Health, Taipei Medical University, Taipei, Taiwan

    Kamaluddin Latief

  2. Centre for Family Welfare, Faculty of Public Health, Universitas Indonesia, Depok, Indonesia

    Kamaluddin Latief

  3. Yale School of Nursing, Yale University, New Haven, CT, USA

    Samuel Akyirem

  4. Department of Fundamental Nursing, Faculty of Nursing, Mahidol University, Bangkok, Thailand

    Siriluk Sithichoksakulchai

  5. College of Nursing, Kaohsiung Medical University, Kaohsiung, Taiwan

    Siriluk Sithichoksakulchai

  6. Public Health Study Program, Banten School of Health Science, South Tangerang, Indonesia

    Dieta Nurrika

  7. Culture, Research, and Technology, The Ministry of Education, Higher Education Service Institutions (LL-DIKTI) Region IV, Bandung, Indonesia

    Dieta Nurrika

  8. Faculty of Nursing, Universitas Jember, Jember, Indonesia

    Mokh. Sujarwadi

  9. Faculty of Nursing, Chulalongkorn University, Boromarajonani Srisataphat Building, 12th Floor Rama1 Road, Wang Mai, Pathum Wan, Bangkok, 10330, Thailand

    Faizul Hasan

Authors
  1. Kamaluddin Latief
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Samuel Akyirem
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Siriluk Sithichoksakulchai
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Dieta Nurrika
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mokh. Sujarwadi
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Faizul Hasan
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

FH and KL acquired data, performed the statistical analyses, interpreted data, and drafted and revised the manuscript for important intellectual content and approved the final version. SA, SS, DN, and MS interpreted data, reviewed the analyses, and approved the final version.

Corresponding author

Correspondence to Faizul Hasan.

Ethics declarations

Ethics approval and consent to participate

This study was approved by the Institutional review boards at the University of Gajah Mada in Indonesia and the RAND Corporation in the United States with the ethical clearance No. s0064-06-01-CR01.

Consent for publication

Not applicable.

Competing interests

The authors declare no potential conflicts of interest.

Additional information

Publisher’s Note

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

Supplementary Information

Additional file 1: Supplementary Table S1.

Depression items: the percentages of participants who endorse each response (N = 19138).

Additional file 2: Supplementary Table S2.

The correlation between main variables (N = 19138).

Additional file 3: Supplementary Table S3.

Mediating analysis.

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

Latief, K., Akyirem, S., Sithichoksakulchai, S. et al. The mediating effect of sleep disturbance on the association between hypertension and depression: a national data analysis. Clin Hypertens 30, 5 (2024). https://doi.org/10.1186/s40885-024-00263-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s40885-024-00263-y

Keywords

Clinical Hypertension

ISSN: 2056-5909

Contact us