Cargando…

States Transitions Inference of Postpartum Depression Based on Multi-State Markov Model

Background: Postpartum depression (PPD) has been recognized as a severe public health problem worldwide due to its high incidence and the detrimental consequences not only for the mother but for the infant and the family. However, the pattern of natural transition trajectories of PPD has rarely been...

Descripción completa

Detalles Bibliográficos
Autores principales: Xiong, Juan, Fang, Qiyu, Chen, Jialing, Li, Yingxin, Li, Huiyi, Li, Wenjie, Zheng, Xujuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8304364/
https://www.ncbi.nlm.nih.gov/pubmed/34299899
http://dx.doi.org/10.3390/ijerph18147449
_version_ 1783727317003010048
author Xiong, Juan
Fang, Qiyu
Chen, Jialing
Li, Yingxin
Li, Huiyi
Li, Wenjie
Zheng, Xujuan
author_facet Xiong, Juan
Fang, Qiyu
Chen, Jialing
Li, Yingxin
Li, Huiyi
Li, Wenjie
Zheng, Xujuan
author_sort Xiong, Juan
collection PubMed
description Background: Postpartum depression (PPD) has been recognized as a severe public health problem worldwide due to its high incidence and the detrimental consequences not only for the mother but for the infant and the family. However, the pattern of natural transition trajectories of PPD has rarely been explored. Methods: In this research, a quantitative longitudinal study was conducted to explore the PPD progression process, providing information on the transition probability, hazard ratio, and the mean sojourn time in the three postnatal mental states, namely normal state, mild PPD, and severe PPD. The multi-state Markov model was built based on 912 depression status assessments in 304 Chinese primiparous women over multiple time points of six weeks postpartum, three months postpartum, and six months postpartum. Results: Among the 608 PPD status transitions from one visit to the next visit, 6.2% (38/608) showed deterioration of mental status from the level at the previous visit; while 40.0% (243/608) showed improvement at the next visit. A subject in normal state who does transition then has a probability of 49.8% of worsening to mild PPD, and 50.2% to severe PPD. A subject with mild PPD who does transition has a 20.0% chance of worsening to severe PPD. A subject with severe PPD is more likely to improve to mild PPD than developing to the normal state. On average, the sojourn time in the normal state, mild PPD, and severe PPD was 64.12, 6.29, and 9.37 weeks, respectively. Women in normal state had 6.0%, 8.5%, 8.7%, and 8.8% chances of progress to severe PPD within three months, nine months, one year, and three years, respectively. Increased all kinds of supports were associated with decreased risk of deterioration from normal state to severe PPD (hazard ratio, HR: 0.42–0.65); and increased informational supports, evaluation of support, and maternal age were associated with alleviation from severe PPD to normal state (HR: 1.46–2.27). Conclusions: The PPD state transition probabilities caused more attention and awareness about the regular PPD screening for postnatal women and the timely intervention for women with mild or severe PPD. The preventive actions on PPD should be conducted at the early stages, and three yearly; at least one yearly screening is strongly recommended. Emotional support, material support, informational support, and evaluation of support had significant positive associations with the prevention of PPD progression transitions. The derived transition probabilities and sojourn time can serve as an importance reference for health professionals to make proactive plans and target interventions for PPD.
format Online
Article
Text
id pubmed-8304364
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-83043642021-07-25 States Transitions Inference of Postpartum Depression Based on Multi-State Markov Model Xiong, Juan Fang, Qiyu Chen, Jialing Li, Yingxin Li, Huiyi Li, Wenjie Zheng, Xujuan Int J Environ Res Public Health Article Background: Postpartum depression (PPD) has been recognized as a severe public health problem worldwide due to its high incidence and the detrimental consequences not only for the mother but for the infant and the family. However, the pattern of natural transition trajectories of PPD has rarely been explored. Methods: In this research, a quantitative longitudinal study was conducted to explore the PPD progression process, providing information on the transition probability, hazard ratio, and the mean sojourn time in the three postnatal mental states, namely normal state, mild PPD, and severe PPD. The multi-state Markov model was built based on 912 depression status assessments in 304 Chinese primiparous women over multiple time points of six weeks postpartum, three months postpartum, and six months postpartum. Results: Among the 608 PPD status transitions from one visit to the next visit, 6.2% (38/608) showed deterioration of mental status from the level at the previous visit; while 40.0% (243/608) showed improvement at the next visit. A subject in normal state who does transition then has a probability of 49.8% of worsening to mild PPD, and 50.2% to severe PPD. A subject with mild PPD who does transition has a 20.0% chance of worsening to severe PPD. A subject with severe PPD is more likely to improve to mild PPD than developing to the normal state. On average, the sojourn time in the normal state, mild PPD, and severe PPD was 64.12, 6.29, and 9.37 weeks, respectively. Women in normal state had 6.0%, 8.5%, 8.7%, and 8.8% chances of progress to severe PPD within three months, nine months, one year, and three years, respectively. Increased all kinds of supports were associated with decreased risk of deterioration from normal state to severe PPD (hazard ratio, HR: 0.42–0.65); and increased informational supports, evaluation of support, and maternal age were associated with alleviation from severe PPD to normal state (HR: 1.46–2.27). Conclusions: The PPD state transition probabilities caused more attention and awareness about the regular PPD screening for postnatal women and the timely intervention for women with mild or severe PPD. The preventive actions on PPD should be conducted at the early stages, and three yearly; at least one yearly screening is strongly recommended. Emotional support, material support, informational support, and evaluation of support had significant positive associations with the prevention of PPD progression transitions. The derived transition probabilities and sojourn time can serve as an importance reference for health professionals to make proactive plans and target interventions for PPD. MDPI 2021-07-13 /pmc/articles/PMC8304364/ /pubmed/34299899 http://dx.doi.org/10.3390/ijerph18147449 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Xiong, Juan
Fang, Qiyu
Chen, Jialing
Li, Yingxin
Li, Huiyi
Li, Wenjie
Zheng, Xujuan
States Transitions Inference of Postpartum Depression Based on Multi-State Markov Model
title States Transitions Inference of Postpartum Depression Based on Multi-State Markov Model
title_full States Transitions Inference of Postpartum Depression Based on Multi-State Markov Model
title_fullStr States Transitions Inference of Postpartum Depression Based on Multi-State Markov Model
title_full_unstemmed States Transitions Inference of Postpartum Depression Based on Multi-State Markov Model
title_short States Transitions Inference of Postpartum Depression Based on Multi-State Markov Model
title_sort states transitions inference of postpartum depression based on multi-state markov model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8304364/
https://www.ncbi.nlm.nih.gov/pubmed/34299899
http://dx.doi.org/10.3390/ijerph18147449
work_keys_str_mv AT xiongjuan statestransitionsinferenceofpostpartumdepressionbasedonmultistatemarkovmodel
AT fangqiyu statestransitionsinferenceofpostpartumdepressionbasedonmultistatemarkovmodel
AT chenjialing statestransitionsinferenceofpostpartumdepressionbasedonmultistatemarkovmodel
AT liyingxin statestransitionsinferenceofpostpartumdepressionbasedonmultistatemarkovmodel
AT lihuiyi statestransitionsinferenceofpostpartumdepressionbasedonmultistatemarkovmodel
AT liwenjie statestransitionsinferenceofpostpartumdepressionbasedonmultistatemarkovmodel
AT zhengxujuan statestransitionsinferenceofpostpartumdepressionbasedonmultistatemarkovmodel