89 research outputs found

    Walking the Talk: Doing Science with Perimenopausal Women and their Health Care Providers

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    Perimenopausal high estrogen levels amplify the social stress of changing reproductive status in a culture that places value on women’s youth and beauty. As it was realized that progesterone physiologically counterbalances the effects of estrogen, it would be better to use progesterone, rather than estrogen for appropriate therapy of perimenopause. Based on this new knowledge was designed a three-arm study project comparing the recommended therapy, low dose OC (oral contraceptives) against progesterone therapy. In the pilot project cooperated Health Care Providers (HCP), by whose help was assembled eleven domains, which perimenopausal women find the most problematic. These HCP were also providing consultations for women with these problems, what gave to the women a good chance of self-analyses of their experience, and to HCP knowledge that the participation with their patients can bring something new into their practice

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    Estradiol (E 2 ) and progesterone (P 4 ) collaborate within bone remodelling on resorption (E 2 ) and formation (P 4 ). We integrate evidence that P 4 may prevent and, with antiresorptives, treat women's osteoporosis. P 4 stimulates osteoblast differentiation in vitro. Menarche (E 2 ) and onset of ovulation (P 4 ) both contribute to peak BMD. Meta-analysis of 5 studies confirms that regularly cycling premenopausal women lose bone mineral density (BMD) related to subclinical ovulatory disturbances (SODs). Cyclic progestin prevents bone loss in healthy premenopausal women with amenorrhea or SOD. BMD loss is more rapid in perimenopause than postmenopause-decreased bone formation due to P 4 deficiency contributes. In 4 placebo-controlled RCTs, BMD loss is not prevented by P 4 in postmenopausal women with increased bone turnover. However, 5 studies of E 2 -MPA co-therapy show greater BMD increases versus E 2 alone. P 4 fracture data are lacking. P 4 prevents bone loss in pre-and possibly perimenopausal women; progesterone co-therapy with antiresorptives may increase bone formation and BMD

    Patterns and predictors of sitting time over ten years in a large population-based Canadian sample: findings from the Canadian Multicentre Osteoporosis Study (CaMos)

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    Our objective was to describe patterns and predictors of sedentary behavior (sitting time) over 10 years among a large Canadian cohort. Data are from the Canadian Multicentre Osteoporosis Study, a prospective study of women and men randomly selected from the general population. Respondents reported socio-demographics, lifestyle behaviors and health outcomes in interviewer-administered questionnaires; weight and height were measured. Baseline data were collected between 1995 and 1997 (n = 9418; participation rate = 42%), and at 5- (n = 7648) and 10-year follow-ups (n = 5567). Total sitting time was summed across domain-specific questions at three time points and dichotomized into “low” (≤ 7 h/day) and “high” ( > 7 h/day), based on recent meta-analytic evidence on time sitting and all-cause mortality. Ten-year sitting patterns were classified as “consistently high”, “consistently low”, “increased”, “decreased”, and “mixed”. Predictors of sedentary behavior patterns were explored using chi-square tests, ANOVA and logistic regression. At baseline (mean age = 62.1 years � 13.4) average sitting was 6.9 h/day; it was 7.0 at 5- and 10-year follow-ups (p for trend = 0.12). Overall 23% reported consistently high sitting time, 22% consistently low sitting, 14% decreased sitting, 17% increased sitting with 24% mixed patterns. Consistently high sitters were more likely to be men, university educated, full-time employed, obese, and to report consistently low physical activity levels. This is one of the first population-based studies to explore patterns of sedentary behavior (multi-domain sitting) within men and women over years. Risk classification of sitting among many adults changed during follow-up. Thus, studies of sitting and health would benefit from multiple measures of sitting over time

    Reduced bone loss is associated with reduced mortality risk in subjects exposed to nitrogen bisphosphonates: A mediation analysis

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    Bisphosphonates, potent anti-resorptive agents, have been found to be associated with mortality reduction. Accelerated bone loss is, in itself, an independent predictor of mortality risk, but the relationship between bisphosphonates, bone loss, and mortality is unknown. This study aimed to determine whether the association between bisphosphonates and mortality is mediated by a reduction in the rate of bone loss. Participants from the population‐based Canadian Multicentre Osteoporosis Study were followed prospectively between1996 and 2011. Comorbidities and lifestyle factors were collected at baseline and bone mineral density (BMD) at baseline and at years 3 (for those aged 40 to 60 years), 5, and 10. Rate of bone loss was calculated using linear regression. Information on medication use was obtained yearly. Bisphosphonate users grouped into nitrogen bisphosphonates (nBP; alendronate or risedronate) and etidronate and non‐users (NoRx) were matched by propensity score, including all baseline factors as well as time of treatment. Cox’s proportional hazards models, unadjusted and adjusted for annual rate of bone loss, were used to determine the association between nBP and etidronate versus NoRx. For the treatment groups with significant mortality risk reduction, the percent of mortality reduction mediated by a reduction in the rate of bone loss was estimated using a causal mediation analysis. There were 271 pairs of nBP and matched NoRx and 327 pairs of etidronate and matched NoRx. nBP but not etidronate use was associated with significant mortality risk reduction (hazard ratios [HR]=0.61 [95% confidenceinterval0.39–0.96]and1.35[95%CI0.86–2.11] for nBP and etidronate, respectively). Rapid bone loss was associated with more than2‐fold increased mortality risk compared with no loss. Mediation analysis indicated that39% (95%CI7%–84%) of the nBP association with mortality was related to a reduction in the rate of bone loss. This finding provides an insight into the mechanism of the relationship between nBP and survival benefit in osteoporotic patients

    A Risk Assessment Tool for Predicting Fragility Fractures and Mortality in the Elderly

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    Existing fracture risk assessment tools are not designed to predict fracture-associated consequences, possibly contributing to the current undermanagement of fragility fractures worldwide. We aimed to develop a risk assessment tool for predicting the conceptual risk of fragility fractures and its consequences. The study involved 8965 people aged >= 60 years from the Dubbo Osteoporosis Epidemiology Study and the Canadian Multicentre Osteoporosis Study. Incident fracture was identified from X-ray reports and questionnaires, and death was ascertained though contact with a family member or obituary review. We used a multistate model to quantify the effects of the predictors on the transition risks to an initial and subsequent incident fracture and mortality, accounting for their complex interrelationships, confounding effects, and death as a competing risk. There were 2364 initial fractures, 755 subsequent fractures, and 3300 deaths during a median follow-up of 13 years (interquartile range [IQR] 7-15). The prediction model included sex, age, bone mineral density, history of falls within 12 previous months, prior fracture after the age of 50 years, cardiovascular diseases, diabetes mellitus, chronic pulmonary diseases, hypertension, and cancer. The model accurately predicted fragility fractures up to 11 years of follow-up and post-fracture mortality up to 9 years, ranging from 7 years after hip fractures to 15 years after non-hip fractures. For example, a 70-year-old woman with aT-score of -1.5 and without other risk factors would have 10% chance of sustaining a fracture and an 8% risk of dying in 5 years. However, after an initial fracture, her risk of sustaining another fracture or dying doubles to 33%, ranging from 26% after a distal to 42% post hip fracture. A robust statistical technique was used to develop a prediction model for individualization of progression to fracture and its consequences, facilitating informed decision making about risk and thus treatment for individuals with different risk profiles. (c) 2020 American Society for Bone and Mineral Research

    Does Molimina Indicate Ovulation? Prospective Data in a Hormonally Documented Single-Cycle in Spontaneously Menstruating Women

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    Approximately 33% of normal-length (21–35 days) cycles have subclinical ovulatory disturbances and lack sufficient progesterone, although their normal length ensures enough estrogen. Subclinical ovulatory disturbances are related to significant premenopausal spine bone loss (−0.86%/year). Molimina, non-distressing premenstrual experiences, may detect ovulation within normal-length cycles. This prospective study assessed the relationship between molimina and ovulation. After 1-cycle of daily diary and first morning urine collections, women answered the Molimina Question (MQ): “Can you tell by the way you feel that your period is coming?” and were invited to share (a) predictive premenstrual experience(s). A 3-fold increase in follicular-luteal pregnanediol levels confirmed ovulation. In 610 spontaneously menstruating women (not on hormonal contraception, mean age 31.5 ± 5.3, menarche age 12.7 ± 1.5, cycle length [CL] 29 days, MQ positive in 89%), reported premenstrual experiences which included negative moods (62%), cramps (48%), bloating (39%), and front (26%) or axillary (25%) breast tenderness. Of 432 women with pregnanediol-documented cycles, 398 (92%) were ovulatory (CL: 29 ± 5) and 34 (8%) had ovulatory disturbances (CL: 32 ± 14). Women with/without ovulatory cycles were similar in parity, body mass index, smoking, dietary restraint and the MQ; ovulatory-disturbed cycles were longer. Molimina did not confirm ovulation. A non-invasive, inexpensive ovulation indicator is needed to prevent osteoporosis

    Osteoporosis: What a Clinician Expects to Learn from a Patient’s Bone Density Examination

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