Symptom Structure of Depression in Older Adults on the Qinghai-Tibet Plateau: A Network Analysis

Overview

Journal Int J Environ Res Public Health

Publisher MDPI

Specialties Environmental Health
Public Health

Date 2022 Nov 11

PMID 36360690

Authors

Buzohre Eli

Yueyue Zhou

Yaru Chen

Xin Huang

Zhengkui Liu

Affiliations

Soon will be listed here.

Abstract

Previous studies have confirmed that depression among residents in high-altitude areas is more severe, and that depression may be more persistent and disabling in older adults. This study aims to identify the symptom structure of depression among older adults on the Qinghai-Tibet Plateau (the highest plateau in the world) from a network perspective. This cross-sectional study enrolled 507 older adults (ages 60-80 years old) from the Yushu Prefecture, which is on the Qinghai-Tibet Plateau, China. Depressive symptoms were self-reported using the shortened Center for Epidemiological Studies-Depression Scale (CES-D-10). Then, a Gaussian graphical model (GGM) of depression was developed. Poor sleep, fear, and hopelessness about the future exhibited high centrality in the network. The strongest edge connections emerged between unhappiness and hopelessness about the future, followed by hopelessness about the future and fear; hopelessness about the future and poor sleep; fear and unhappiness; and then poor sleep and unhappiness in the network. The findings of this current study add to the small body of literature on the network structure and complex relationships between depressive symptoms in older adults in high-altitude areas.

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References

Wang J, Zhou Y, Liang Y, Liu Z . A Large Sample Survey of Tibetan People on the Qinghai-Tibet Plateau: Current Situation of Depression and Risk Factors. Int J Environ Res Public Health. 2020; 17(1). PMC: 6981986. DOI: 10.3390/ijerph17010289. View

Fried E, Eidhof M, Palic S, Costantini G, Huisman-van Dijk H, Bockting C . Replicability and Generalizability of Posttraumatic Stress Disorder (PTSD) Networks: A Cross-Cultural Multisite Study of PTSD Symptoms in Four Trauma Patient Samples. Clin Psychol Sci. 2018; 6(3):335-351. PMC: 5974702. DOI: 10.1177/2167702617745092. View

Heeren A, Jones P, McNally R . Mapping network connectivity among symptoms of social anxiety and comorbid depression in people with social anxiety disorder. J Affect Disord. 2017; 228:75-82. DOI: 10.1016/j.jad.2017.12.003. View

Ishikawa M, Yamanaka G, Yamamoto N, Nakaoka T, Okumiya K, Matsubayashi K . Depression and Altitude: Cross-Sectional Community-Based Study Among Elderly High-Altitude Residents in the Himalayan Regions. Cult Med Psychiatry. 2015; 40(1):1-11. DOI: 10.1007/s11013-015-9462-7. View

Brandao D, Fontenelle L, da Silva S, Rossi Menezes P, Pastor-Valero M . Depression and excess mortality in the elderly living in low- and middle-income countries: Systematic review and meta-analysis. Int J Geriatr Psychiatry. 2018; 34(1):22-30. DOI: 10.1002/gps.5008. View

Chen X, Liu J, Wang J, Xin Z, Zhang Q, Zhang W . Altered resting-state networks may explain the executive impairment in young health immigrants into high-altitude area. Brain Imaging Behav. 2020; 15(1):147-156. DOI: 10.1007/s11682-019-00241-1. View

Epskamp S, Borsboom D, Fried E . Estimating psychological networks and their accuracy: A tutorial paper. Behav Res Methods. 2017; 50(1):195-212. PMC: 5809547. DOI: 10.3758/s13428-017-0862-1. View

Schraegle W, Titus J . Executive function and health-related quality of life in pediatric epilepsy. Epilepsy Behav. 2016; 62:20-6. DOI: 10.1016/j.yebeh.2016.06.006. View

Bringmann L, Elmer T, Epskamp S, Krause R, Schoch D, Wichers M . What do centrality measures measure in psychological networks?. J Abnorm Psychol. 2019; 128(8):892-903. DOI: 10.1037/abn0000446. View

10.

Stafford M, Bendayan R, Tymoszuk U, Kuh D . Social support from the closest person and sleep quality in later life: Evidence from a British birth cohort study. J Psychosom Res. 2017; 98:1-9. PMC: 5478069. DOI: 10.1016/j.jpsychores.2017.04.014. View

11.

Eli B, Zhou Y, Liang Y, Fu L, Zheng H, Liu Z . A profile analysis of post-traumatic stress disorder and depressive symptoms among Chinese Shidu parents. Eur J Psychotraumatol. 2020; 11(1):1766770. PMC: 7472999. DOI: 10.1080/20008198.2020.1766770. View

12.

Hallquist M, Wright A, Molenaar P . Problems with Centrality Measures in Psychopathology Symptom Networks: Why Network Psychometrics Cannot Escape Psychometric Theory. Multivariate Behav Res. 2019; 56(2):199-223. PMC: 7012663. DOI: 10.1080/00273171.2019.1640103. View

13.

Fried E, Epskamp S, Nesse R, Tuerlinckx F, Borsboom D . What are 'good' depression symptoms? Comparing the centrality of DSM and non-DSM symptoms of depression in a network analysis. J Affect Disord. 2015; 189:314-20. DOI: 10.1016/j.jad.2015.09.005. View

14.

Luppa M, Sikorski C, Luck T, Ehreke L, Konnopka A, Wiese B . Age- and gender-specific prevalence of depression in latest-life--systematic review and meta-analysis. J Affect Disord. 2011; 136(3):212-21. DOI: 10.1016/j.jad.2010.11.033. View

15.

Ray K, Dutta A, Panjwani U, Thakur L, Anand J, Kumar S . Hypobaric hypoxia modulates brain biogenic amines and disturbs sleep architecture. Neurochem Int. 2010; 58(1):112-8. DOI: 10.1016/j.neuint.2010.11.003. View

16.

Ni Mhaolain A, Fan C, Romero-Ortuno R, Cogan L, Cunningham C, Lawlor B . Depression: a modifiable factor in fearful older fallers transitioning to frailty?. Int J Geriatr Psychiatry. 2012; 27(7):727-33. DOI: 10.1002/gps.2780. View

17.

Synowiec-Pilat M, Palega A . Fear of cancer and older people's beliefs about cancer treatment in Poland. J Psychosoc Oncol. 2017; 36(1):97-112. DOI: 10.1080/07347332.2017.1357665. View

18.

Krsteska R, Pejoska V . The association of poor economic condition and family relations in childhood with late-life depression. Psychiatr Danub. 2013; 25(3):241-7. View

19.

Hartung T, Fried E, Mehnert A, Hinz A, Vehling S . Frequency and network analysis of depressive symptoms in patients with cancer compared to the general population. J Affect Disord. 2019; 256:295-301. DOI: 10.1016/j.jad.2019.06.009. View

20.

Rubin M, Bicki A, Papini S, Smits J, Telch M, Gray J . Distinct trajectories of depression symptoms in early and middle adolescence: Preliminary evidence from longitudinal network analysis. J Psychiatr Res. 2021; 142:198-203. DOI: 10.1016/j.jpsychires.2021.07.053. View