Do psycho-social factors contribute more to symptom reporting by middle-aged women than hormonal status?

O’Connor, Vivienne; Mar, Chris B Del; Sheehan, Mary; Siskind, Victor; Fox-Young, Stephanie; Cragg, Carole

doi:10.1016/0378-5122(94)90001-9

Cited by 60 publications

(21 citation statements)

References 20 publications

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“…The hysterectomy rate in this study was comparable to that reported from other Australian data. Our rate for 45-to 55-year-old women (25%) was between that reported for a randomly ascertained sample of Melbourne women (22%) 33 and a randomly selected sample of Brisbane women (31%), 34 both in the same age group. For women aged 50 to 59 years our sample's prevalence (32.6%) was similar to that (34.2%) from a community survey of women in a region of New South Wales.…”

Section: Commentmentioning

confidence: 63%

Predictors of hysterectomy: An Australian study

Treloar¹,

Anh²,

O’Connor³

et al. 1999

American Journal of Obstetrics and Gynecology

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OBJECTIVE:We evaluated the relative importance of predictors of hysterectomy. STUDY DESIGN: A questionnaire survey of an Australia-wide sample of adult female twins was conducted; self-report data were validated against reports from treating physicians. RESULTS: A total of 3096 women (94%) and 366 physicians (87%) responded. The sensitivity of patient report of hysterectomy was 98.2%. Best predictors of hysterectomy were endometriosis (odds ratio 4.85, 95% confidence interval 3.17-7.43), medical consultation for menorrhagia (odds ratio 3.55, 95% confidence interval 2.47-5.12), joint effects of fibroids with medical consultation for chronic or persisting pelvic pain (odds ratio 3.34, 95% confidence interval 1.42 to 7.87), having smoked >40 cigarettes per day (odds ratio 3.24, 95% confidence interval 1.10-9.55), joint effects of fibroids with consultation for menstrual problems (odds ratio 2.61, 95% confidence interval 1.36-5.01), and tubal ligation (odds ratio 1.77, 95% confidence interval 1.31-2.39). Less-important predictors were age and higher education level (protective). CONCLUSION: Consulting a physician about pelvic pain and menstrual problems, especially heavy bleeding, are recognized steps toward hysterectomy. Of particular interest for future genetic analyses are the high odds of hysterectomy for women with endometriosis, fibroids, or menorrhagia. (Am J Obstet Gynecol 1999;180:945-54.) Key words: Hysterectomy, validation, predictors, risk factors Studies investigating pathways to hysterectomy performed for benign and nonemergency conditions have been rare. Clinical reviews have focused on the impact of new or changing techniques available to surgical practice and on developments in medical and pharmaceutical treatments. A health policy agenda concerning appropriate use of health care resources has influenced many other reviews of rates and indications. The first phase of the current study, with use of a genetic epidemiologic approach, attempted to identify predictors of hysterectomy and their causal role with use of data on Australian twins. 1 To our surprise, we found strong evidence for genetic factors influencing liability to hysterectomy, accounting for 66% of the total variance. Furthermore, these genetic influences were stable across birth cohorts in spite of differences in incidence resulting from aging and other factors such as secular changes in surgical practice and health service financing. 1 We therefore hypothesized that the high heritability of hysterectomy reflects genetic influences on gynecologic factors that are commonly indications for elective hysterectomy. Here we describe a survey implemented to collect data to test this hypothesis. In this study we focus on the relative importance of risk factors for hysterectomy and the phenotypic relationships between them. Genetic analyses making full use of the twin structure of the sample will be the subject of a further study. Given this epidemiologic focus, we also aimed to test the validity of retrospective self-reported data against d...

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Section: Commentmentioning

confidence: 63%

Predictors of hysterectomy: An Australian study

Treloar¹,

Anh²,

O’Connor³

et al. 1999

American Journal of Obstetrics and Gynecology

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“…Our data, then, are supportive of what has been reported before by similar research. While women acknowledge the importance of psychosocial aspects of their life while they experience the menopausal transition (O'Connor et al 1995, Legare et al 2000, Quine and Rubin 1997, they are primarily concerned with short-term symptoms (Hampson and Hibbard 1996) that could impair their functional abilities. Moreover, symptoms, as described in the physicians' explanatory model of menopause, have often been cited as being more severe than is thought by women themselves (Delorey 1989).…”

Section: Determination Of the Patient's Illnessmentioning

confidence: 99%

The limitations of a negotiation model for perimenopausal women

Massé

Côté

Dodin

2001

Sociology Health & Illness

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The clinical negotiation model proposed by Katon and Kleinman (1981) puts culture at the very heart of the patientdoctor relationship. As opposed to the asymmetric model that stresses an unequal power relationship between a dominant physician and a powerless patient, this transactional model suggests that we view the clinical encounter as the locus of a negotiation that takes place between two kinds of knowledge (lay and professional), and between two agendas: the doctor's and the patient's. According to such a model, the doctor is taught to listen to the patient's own explanatory model of disease.Using an in-depth analysis of clinical encounters between perimenopausal women and female physicians, and of separate interviews with individual doctors and patients concerning their respective explanatory models, this pilot study puts emphasis on both the limitations of a transactional model and on the strategies deployed by doctors for enhancing the credibility of hormonal replacement therapy.Keywords: menopause, clinical encounter, negotiation model, transactional model, practice patterns IntroductionThe difficulties in the doctor-patient relationship in Western medicine have been treated as emblematic of its profit-oriented, dehumanising system of health care and as mirroring, in the local setting of the clinical encounter, asymmetric power structures in the wider society. Through a rich diversity of hermeneutic, constructivist, case-study or discourse-analysis methodologies, social scientists have tried to identify the factors that make these doctor-patient relationships problematic (Roter et al. 1988, Cosnier et al. 1993, Roter and Frankel 1992. As an alternative to functionalist and critical asymmetric models of the doctor-patient relationship which emphasise the cultural dimensions of the medical encounter, some medical anthropologists and sociologists have suggested focusing on more symmetric`negotiation' models. As early as the 1950s, as illustrated by Tuckett (1978), and drawing on the literature on negotiated order in the realm of health care (Strauss 1979), a number of medical sociology studies suggest that beyond the activity-passivity and guidance co-operation models of a doctor-patient interaction there has emerged a mutual participation model that stresses the active role of the patient and a mutual negotiation process. While recognising that`the basic consideration in situations of bargaining and negotiation is where the power lies' (Tuckett 1978: 206), research now focuses on the conditions (local, interactionist or structural) that influence this negotiation. One interesting variant of this negotiation model, developed from a cultural-interpretativist approach, is the cognitive-interpretative`transactional model' developed by Katon and Kleinman (1981). This model stresses the negotiation process between two divergent explanatory models of illness: the medical-clinical model and the patient-popular model. Tensions and ineffectiveness in clinical encounters are thus explained by communication...

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“…First, the representativeness of many of the samples is not known, although only three were strictly clinical. Sampling strategies included random sampling of telephone numbers (Dennerstein et al, 1993;Feldman et al, 1985;Grisso et al, 1999), random sampling from population registers (Hagstad and Janson, 1986;Holte, 1991;O'Connor et al, 1995), entire communities sent a questionnaire (Berg et al, 1988), a multistage stratified cluster sampling from clinical records (Rizk et al, 1998), patients drawn from general practice (Thompson et al, 1973) or a menopause center (Carda et al, 1998), and a sampling of women in outpatient waiting areas (Moore and Kombe, 1991;Punyahotra et al, 1997;Staropoli et al, 1998). For only two studies was sampling not described (Boulet et al, 1994).…”

Section: Discussionmentioning

confidence: 99%

Geographical distribution of hot flash frequencies: Considering climatic influences

Sievert¹,

Flanagan²

2005

Am. J. Phys. Anthropol.

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Laboratory studies suggest that hot flashes are triggered by small elevations in core body temperature acting within a reduced thermoneutral zone, i.e., the temperature range in which a woman neither shivers nor sweats. In the present study, it was hypothesized that women in different populations develop climate-specific thermoneutral zones, and ultimately, population-specific frequencies of hot flashes at menopause. Correlations were predicted between hot flash frequencies and latitude, elevation, and annual temperatures. Data on hot flash frequencies were drawn from 54 studies. Pearson correlation analyses and simple linear regressions were applied, first using all studies, and second using a subset of studies that included participants only to age 60 (n = 36). Regressions were repeated with all studies, controlling for method of hot flash assessment. When analyses were restricted to studies that included women up to age 60, average temperature of the coldest month was a significant predictor of hot flash frequency (P < 0.01), explaining 29.2% of the variation in hot flash frequency. In a separate equation, the difference between hottest and coldest temperatures was also a significant predictor (P < 0.01), explaining 26.4% of the variation in hot flash frequency. When regressions used all studies but controlled for method of hot flash assessment, average temperature of the coldest month, difference between hottest and coldest temperatures, and mean annual temperature were significant predictors of hot flash frequency. Women reported fewer hot flashes in warmer temperatures, and more hot flashes with increasing seasonality. These results suggest that acclimatization to coldest temperatures or sensitivity to seasonality may explain part of the population variation in hot flash frequency.

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Do psycho-social factors contribute more to symptom reporting by middle-aged women than hormonal status?

Cited by 60 publications

References 20 publications

Predictors of hysterectomy: An Australian study

Predictors of hysterectomy: An Australian study

The limitations of a negotiation model for perimenopausal women

Geographical distribution of hot flash frequencies: Considering climatic influences

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