2019
DOI: 10.3389/fpsyg.2019.02446
|View full text |Cite
|
Sign up to set email alerts
|

Lowered Plasma Steady-State Levels of Progesterone Combined With Declining Progesterone Levels During the Luteal Phase Predict Peri-Menstrual Syndrome and Its Major Subdomains

Abstract: BackgroundIt is unknown whether lowered steady state levels of sex hormones coupled with changes in those hormones during the menstrual cycle are associated with premenstrual syndrome (PMS).ObjectiveTo examine associations between levels of progesterone and oestradiol during the menstrual cycle and PMS considering different diagnostic criteria for PMS.MethodsForty-one women aged 18–45 years with a regular menstrual cycle completed the Daily Record of Severity of Problems (DRSP) for all 28 consecutive days of t… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4
1

Citation Types

1
35
0

Year Published

2019
2019
2024
2024

Publication Types

Select...
5
1

Relationship

1
5

Authors

Journals

citations
Cited by 21 publications
(36 citation statements)
references
References 78 publications
1
35
0
Order By: Relevance
“…Furthermore, we verified that the diagnosis of PMS according to Biggs and Demuth (2011) as well as the diagnoses of PeriMS and MCAS, but not the ACOGbased PMS diagnosis, were externally validated by levels of the sex hormones oestradiol and progesterone (Roomruangwong et al, 2019). In addition, a diagnosis of PMS according to Biggs and Demuth (2011) was only predicted by lower steady-state levels of progesterone in the luteal phase (Biggs & Demuth, 2011), while the PeriMS and MCAS diagnoses were significantly related to both sex hormones (Roomruangwong et al, 2019). Lower steady-state levels of progesterone averaged over the luteal phase coupled with decreasing progesterone levels during the luteal phase also predicted changes in severity of the DRSP as well as alterations in severity of its four subdomains, namely a) depressive symptoms; b) fatigue and physio-somatic symptoms; c) increased appetite and craving combined with breast tenderness and swelling; and d) anxiety (Roomruangwong et al, 2019).…”
Section: Introductionmentioning
confidence: 66%
See 4 more Smart Citations
“…Furthermore, we verified that the diagnosis of PMS according to Biggs and Demuth (2011) as well as the diagnoses of PeriMS and MCAS, but not the ACOGbased PMS diagnosis, were externally validated by levels of the sex hormones oestradiol and progesterone (Roomruangwong et al, 2019). In addition, a diagnosis of PMS according to Biggs and Demuth (2011) was only predicted by lower steady-state levels of progesterone in the luteal phase (Biggs & Demuth, 2011), while the PeriMS and MCAS diagnoses were significantly related to both sex hormones (Roomruangwong et al, 2019). Lower steady-state levels of progesterone averaged over the luteal phase coupled with decreasing progesterone levels during the luteal phase also predicted changes in severity of the DRSP as well as alterations in severity of its four subdomains, namely a) depressive symptoms; b) fatigue and physio-somatic symptoms; c) increased appetite and craving combined with breast tenderness and swelling; and d) anxiety (Roomruangwong et al, 2019).…”
Section: Introductionmentioning
confidence: 66%
“…The presence of PMS was considered when the total DRSP score was ≥70 on day −5 to −1 of menses and when there was a 30% difference between premenstrual (day −5 to −1) and postmenstrual (day 6-10) scores (Endicott et al, 2006;Biggs & Demuth, 2011;Qiao et al, 2012). In addition, participants were also categorised in those who had PeriMS with increased DRSP ratings during the perimenstrual period (day 1+ day 2 þ day 24-28) and MCAS (Roomruangwong et al, 2019). We also computed scores of the four subdomains of the DRSP, namely a) depressive dimension; b) physio-somatic component; c) increased appetite and craving combined with breast tenderness and swelling; and d) anxiety dimension (Roomruangwong et al, 2019).…”
Section: Clinical Assessmentsmentioning
confidence: 99%
See 3 more Smart Citations