Literature DB >> 15356407

Predicting participation in prospective studies of ovarian aging.

Deborah B Nelson1, Mary D Sammel, Ellen W Freeman, Li Liu, Elizabeth Langan, Clarisa R Gracia.   

Abstract

OBJECTIVE: Identifying clinical markers and characteristics of the transition to menopause is an important woman's health issue, and recent long-term, prospective, cohort studies are just beginning to offer insight into methods of predicting the transition to menopause. One of the major challenges of conducting prospective cohort studies is the problem of attrition-both the retention of study participants and the influence of dropouts on the final study results. We conducted this systematic analysis to: 1) identify baseline predictors of subsequent long-term participation, and 2) determine the demographic, psychosocial, and hormonal differences between participants and dropouts among a group of premenopausal women enrolled in a longitudinal study of ovarian aging.
DESIGN: Using data from the Penn Ovarian Aging study, premenopausal women aged 35 to 47 enrolled in the study were classified as either Active (full participants), Skipped, or Dropped participants based on their visit pattern during a 4-year study interval.
RESULTS: Most of the demographic and psychosocial variables did not significantly differ between the Active, Skipped, or Dropped groups. There was no racial difference in study participation. The Dropouts were more likely to have a high school education and were less likely to report menopause symptoms compared with the Actives (P < 0.01). The Skipped group reported more anxiety (P < 0.05), and members were more likely to have less than a high school education compared with the Actives (P < 0.03). Hormone levels (estradiol, follicle-stimulating hormone, luteinizing hormone, dehydroepiandrosterone, testosterone) at enrollment were within the premenopausal range and did not significantly differ among the three study groups. These findings remained after adjustment for covariates and hormone levels in multivariate analyses.
CONCLUSIONS: Education, anxiety levels and menopause symptoms at baseline differed marginally between the women participating fully and those who dropped out or skipped multiple assessments. These findings are important and indicate that long-term study participation rates do not differ substantially by racial group or any of the other demographic or hormonal characteristics examined.

Entities:  

Mesh:

Substances:

Year:  2004        PMID: 15356407     DOI: 10.1097/01.gme.0000139770.14675.40

Source DB:  PubMed          Journal:  Menopause        ISSN: 1072-3714            Impact factor:   2.953


  6 in total

1.  Anxiety as a risk factor for menopausal hot flashes: evidence from the Penn Ovarian Aging cohort.

Authors:  Ellen W Freeman; Mary D Sammel
Journal:  Menopause       Date:  2016-09       Impact factor: 2.953

2.  Obesity and reproductive hormone levels in the transition to menopause.

Authors:  Ellen W Freeman; Mary D Sammel; Hui Lin; Clarisa R Gracia
Journal:  Menopause       Date:  2010-07       Impact factor: 2.953

3.  Factors that influence entry into stages of the menopausal transition.

Authors:  Mary D Sammel; Ellen W Freeman; Ziyue Liu; Hui Lin; Wensheng Guo
Journal:  Menopause       Date:  2009 Nov-Dec       Impact factor: 2.953

4.  Association of change in estradiol to lower urinary tract symptoms during the menopausal transition.

Authors:  Manish Gopal; Mary D Sammel; Lily A Arya; Ellen W Freeman; Hui Lin; Clarisa Gracia
Journal:  Obstet Gynecol       Date:  2008-11       Impact factor: 7.661

5.  Modeling Short- and Long-Term Characteristics of Follicle Stimulating Hormone as Predictors of Severe Hot Flashes in Penn Ovarian Aging Study.

Authors:  Bei Jiang; Naisyin Wang; Mary D Sammel; Michael R Elliott
Journal:  J R Stat Soc Ser C Appl Stat       Date:  2015-03-26       Impact factor: 1.864

6.  Methods in a longitudinal cohort study of late reproductive age women: the Penn Ovarian Aging Study (POAS).

Authors:  Ellen W Freeman; Mary D Sammel
Journal:  Womens Midlife Health       Date:  2016-01-27
  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.