Secular trends in the incidence of major depressive disorder and dysthymia in China from 1990 to 2019.
Age–period–cohort analysis
China
Depressive disorders
Dysthymia
Incidence
Joinpoint regression
Journal
BMC public health
ISSN: 1471-2458
Titre abrégé: BMC Public Health
Pays: England
ID NLM: 100968562
Informations de publication
Date de publication:
06 11 2023
06 11 2023
Historique:
received:
14
03
2023
accepted:
19
10
2023
medline:
7
11
2023
pubmed:
6
11
2023
entrez:
5
11
2023
Statut:
epublish
Résumé
Depression is increasingly recognized as a worldwide serious, public health concern. A better understanding of depression is important for advancing its management and learning the difference between major depressive disorder (MDD) and dysthymia. Our aim is to conduct a concurrent analysis of the trends of both MDD and dysthymia in China. The data on depression from 1990 to 2019 were collected from the Global Burden of Disease Study 2019 (GBD 2019). To determine the average annual percent changes (AAPC) and relative risks (RRs), joinpoint regression and the age-period-cohort models were employed, respectively. The incidence number of MDD and dysthymia continuously increased in China from 1990 to 2019, however, the age-standardized rates (ASR) had a decreasing trend in both men and women. The results from joinpoint regression showed that a declining trend was presented in young people (< 50 years) but an increased trend in the elderly (≥ 50 years) both in men and women, during 1990-2019. Age is the most influential factor for MDD and dysthymia. Age RRs for MDD incidence had an overall increasing trend with age. Period RR in MDD presented a U-shaped pattern, while Cohort RRs presented an inverted U-shaped pattern. On the other hand, RRs in dysthymia for period and cohort effects had no statistical significance, only the age effect presented an inverted U-shaped pattern. The disparities in trends observed between MDD and dysthymia during the period of 1990-2019 indicated the significance of distinguishing between these two disorders. The age, period and cohort effects all had a greater impact on MDD than on dysthymia, and age effects presented different influential patterns in these two. To alleviate the burden of depressive disorders in China, proactive measures need to be implemented, with particular attention to the elderly population.
Sections du résumé
BACKGROUND
Depression is increasingly recognized as a worldwide serious, public health concern. A better understanding of depression is important for advancing its management and learning the difference between major depressive disorder (MDD) and dysthymia. Our aim is to conduct a concurrent analysis of the trends of both MDD and dysthymia in China.
METHODS
The data on depression from 1990 to 2019 were collected from the Global Burden of Disease Study 2019 (GBD 2019). To determine the average annual percent changes (AAPC) and relative risks (RRs), joinpoint regression and the age-period-cohort models were employed, respectively.
RESULTS
The incidence number of MDD and dysthymia continuously increased in China from 1990 to 2019, however, the age-standardized rates (ASR) had a decreasing trend in both men and women. The results from joinpoint regression showed that a declining trend was presented in young people (< 50 years) but an increased trend in the elderly (≥ 50 years) both in men and women, during 1990-2019. Age is the most influential factor for MDD and dysthymia. Age RRs for MDD incidence had an overall increasing trend with age. Period RR in MDD presented a U-shaped pattern, while Cohort RRs presented an inverted U-shaped pattern. On the other hand, RRs in dysthymia for period and cohort effects had no statistical significance, only the age effect presented an inverted U-shaped pattern.
CONCLUSIONS
The disparities in trends observed between MDD and dysthymia during the period of 1990-2019 indicated the significance of distinguishing between these two disorders. The age, period and cohort effects all had a greater impact on MDD than on dysthymia, and age effects presented different influential patterns in these two. To alleviate the burden of depressive disorders in China, proactive measures need to be implemented, with particular attention to the elderly population.
Identifiants
pubmed: 37926849
doi: 10.1186/s12889-023-17025-4
pii: 10.1186/s12889-023-17025-4
pmc: PMC10626640
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
2162Informations de copyright
© 2023. The Author(s).
Références
Lancet. 2018 Oct 27;392(10157):1553-1598
pubmed: 30314863
J Affect Disord. 2022 Jan 1;296:169-174
pubmed: 34601304
Demography. 2008 May;45(2):387-416
pubmed: 18613487
J Psychiatr Res. 2020 Jul;126:134-140
pubmed: 31439359
Lancet. 2019 Sep 28;394(10204):1145-1158
pubmed: 31248666
JAMA Psychiatry. 2014 May;71(5):573-81
pubmed: 24806211
Psychiatry Res. 2019 Aug;278:213-217
pubmed: 31226547
Lancet. 2020 Oct 17;396(10258):1160-1203
pubmed: 33069325
Lancet Psychiatry. 2020 Sep;7(9):801-812
pubmed: 32828168
Br J Psychiatry. 2000 Dec;177:486-92
pubmed: 11102321
J Affect Disord. 2022 Jan 1;296:241-243
pubmed: 34619450
Front Psychiatry. 2021 Oct 25;12:589687
pubmed: 34759845
Lancet. 2020 Oct 17;396(10258):1204-1222
pubmed: 33069326
J Affect Disord. 2020 May 1;268:95-101
pubmed: 32158012
Lancet Psychiatry. 2019 Mar;6(3):211-224
pubmed: 30792114
Soc Psychiatry Psychiatr Epidemiol. 2019 Jan;54(1):99-110
pubmed: 30171272
Soc Sci Res. 2015 Jan;49:53-69
pubmed: 25432603
Lancet. 2020 Oct 17;396(10258):1223-1249
pubmed: 33069327
Demography. 2013 Dec;50(6):1945-67
pubmed: 24072610
Annu Rev Public Health. 1991;12:425-57
pubmed: 2049144
Lancet Psychiatry. 2022 Feb;9(2):137-150
pubmed: 35026139
Drug Alcohol Depend. 2013 Sep 1;132(1-2):140-8
pubmed: 23433898
World Psychiatry. 2011 Oct;10(3):210-6
pubmed: 21991281
Int J Epidemiol. 2017 Aug 1;46(4):1157-1170
pubmed: 28338900
Lancet Psychiatry. 2021 Nov;8(11):981-990
pubmed: 34559991
Glob Health Action. 2020;13(1):1712147
pubmed: 31937206
Psychol Med. 2012 Feb;42(2):409-17
pubmed: 21835095
Epidemiology. 2012 Jul;23(4):583-93
pubmed: 22407139
Curr Neuropharmacol. 2021;19(6):766-786
pubmed: 32888272
Child Psychiatry Hum Dev. 2022 Jun 28;:
pubmed: 35763175
Soc Psychiatry Psychiatr Epidemiol. 2017 Jan;52(1):105-116
pubmed: 27761600
Lancet. 2016 Apr 16;387(10028):1672-85
pubmed: 26454360
Prog Neurobiol. 2019 May;176:86-102
pubmed: 30721749
Soc Sci Med. 2019 Jan;220:387-395
pubmed: 30529490
Shanghai Arch Psychiatry. 2012 Jun;24(3):172-4
pubmed: 25324622
BMC Med. 2020 Jan 27;18(1):21
pubmed: 31983345
Depress Anxiety. 2014 Jun;31(6):459-71
pubmed: 24272961
Aging Ment Health. 2014 Jul;18(5):570-8
pubmed: 23998249
Stat Med. 2022 Jul 20;41(16):3102-3130
pubmed: 35522060
Stat Med. 2009 Dec 20;28(29):3670-82
pubmed: 19856324
J Affect Disord. 2020 Feb 15;263:609-620
pubmed: 31744739
Epidemiol Psychiatr Sci. 2019 Apr;28(2):199-209
pubmed: 28805174
J Korean Med Sci. 2018 Apr 26;33(19):e149
pubmed: 29736162
Epidemiol Health. 2017 Dec 5;39:e2017056
pubmed: 29309721
J Abnorm Psychol. 2008 Aug;117(3):552-60
pubmed: 18729608