Methods: Six osteoporosis risk assessments tools (the Simple Calculated Osteoporosis Risk Estimation [SCORE], the Osteoporosis Risk Assessment Instrument, the Age Bulk One or Never Estrogen, the body weight, the Malaysian Osteoporosis Screening Tool, and the Osteoporosis Self-Assessment Tool for Asians) were used to screen postmenopausal women who had not been previously diagnosed with osteoporosis/osteopenia. These women also underwent a dual-energy X-ray absorptiometry (DXA) scan to confirm the absence or presence of osteoporosis.
Results: A total of 164/224 participants were recruited (response rate, 73.2%), of which only 150/164 (91.5%) completed their DXA scan. Sixteen participants (10.7%) were found to have osteoporosis, whilst 65/150 (43.3%) were found to have osteopenia. Using precision-recall curves, the recall of the tools ranged from 0.50 to 1.00, whilst precision ranged from 0.04 to 0.14. The area under the curve (AUC) ranged from 0.027 to 0.161. The SCORE had the best balance between recall (1.00), precision (0.04-0.12), and AUC (0.072-0.161).
Conclusions: We found that the SCORE had the best balance between recall, precision, and AUC among the 6 screening tools that were compared among Malaysian postmenopausal women.
METHODS: This cross-sectional study recruited 203 postmenopausal women (age ranged from 51 to 85 years old) in community settings. The dietary intakes of the participants were assessed using a validated interviewer-administered semi-quantitative food frequency questionnaire (FFQ), while dietary acid load (DAL) was estimated using net endogenous acid production (NEAP). Agena® MassARRAY genotyping analysis and serum collagen type 1 cross-linked C-telopeptide (CTX1) were used to identify the IL6 genotype and as a bone resorption marker, respectively. The interactions between diet and single-nucleotide polymorphisms (SNPs) were assessed using linear regressions.
RESULTS: A total of 203 healthy postmenopausal women aged between 51 and 85 years participated in this study. The mean BMI of the participants was 24.3 kg/m2. In IL6 -174 G/C, all the participants carried the GG genotype, while the C allele was absent. Approximately 40% of the participants had a high dietary acid load. Dietary acid load (B = 0.15, p = 0.031) and the IL6 -572 CC genotype group (B = 0.14, p = 0.044) were positively associated with a higher bone resorption. However, there was no moderating effect of the IL6 genetic polymorphism on the relationship between and acid ash diet and bone resorption markers among the postmenopausal women (p = 0.79).
CONCLUSION: High consumption of an acid ash diet and the IL6 -572 C allele seem to attribute to high bone resorption among postmenopausal women. However, our finding does not support the interaction effect of dietary acidity and IL6 (-174G/C and -572G/C) polymorphisms on the rate of bone resorption. Taken together, these results have given scientific research other candidate genes to focus on which may interact with DAL on bone resorption, to enhance planning for preventing or delaying the onset of osteoporosis among postmenopausal women.
Materials and Methods: Sixty postmenopausal female patients aged 51-68 years were included in the study to assess the relationship between tooth loss and the level of blood pressure. The information including sociodemographics, last menstruation period, hypertension history, and the duration of having tooth loss was recorded. Blood pressure was measured using sphygmomanometer and the number of tooth loss was determined.
Results: The results showed a more significant tooth loss in hypertension (median: 23 + 4; interquartile range [IQR]: 6) compared to the normotension postmenopausal women (median: 18 + 6; IQR: 12; P < 0.05). Furthermore, obese patients had more tooth loss (median: 23 + 5; IQR: 8) than the overweight patients (median: 19 + 8; IQR: 8).
Conclusion: Tooth loss is associated with the increase of hypertension in postmenopausal women which may have a role in the development of vascular diseases.
METHOD: A historical cohort of 986 premenopausal, and 1123 postmenopausal, parous breast cancer patients diagnosed from 2001 to 2012 in University Malaya Medical Centre were included in the analyses. Time since LCB was categorized into quintiles. Multivariable Cox regression was used to determine whether time since LCB was associated with survival following breast cancer, adjusting for demographic, tumor, and treatment characteristics.
RESULTS: Premenopausal breast cancer patients with the most recent childbirth (LCB quintile 1) were younger, more likely to present with unfavorable prognostic profiles and had the lowest 5-year overall survival (OS) (66.9; 95% CI 60.2-73.6%), compared to women with longer duration since LCB (quintile 2 thru 5). In univariable analysis, time since LCB was inversely associated with risk of mortality and the hazard ratio for LCB quintile 2, 3, 4, and 5 versus quintile 1 were 0.53 (95% CI 0.36-0.77), 0.49 (95% CI 0.33-0.75), 0.61 (95% CI 0.43-0.85), and 0.64 (95% CI 0.44-0.93), respectively; P trend = 0.016. However, this association was attenuated substantially following adjustment for age at diagnosis and other prognostic factors. Similarly, postmenopausal breast cancer patients with the most recent childbirth were also more likely to present with unfavorable disease profiles. Compared to postmenopausal breast cancer patients in LCB quintile 1, patients in quintile 5 had a higher risk of mortality. This association was not significant following multivariable adjustment.
CONCLUSION: Time since LCB is not independently associated with survival in premenopausal or postmenopausal breast cancers. The apparent increase in risks of mortality in premenopausal breast cancer patients with a recent childbirth, and postmenopausal patients with longer duration since LCB, appear to be largely explained by their age at diagnosis.
DESIGN: Prospective cohort study.
SETTING: England, Wales and Scotland.
PARTICIPANTS: 17 781 postmenopausal women from the UK Women's Cohort Study.
PRIMARY OUTCOME MEASURE: Incident cases of malignant breast cancers (International Classification of Diseases (ICD) 9 code 174 and ICD 10 code C50).
RESULTS: From 282 277 person-years follow-up, there were 946 incident breast cancer cases with an incidence rate of 3.35 per 1000 women. Body mass index (HR: 1.04; 95% CI: 1.02 to 1.07), blouse size (HR: 1.10; 1.03 to 1.18), waist circumference (HR: 1.07; 1.01 to 1.14) and skirt size (HR: 1.14;1.06 to 1.22) had positive associations with postmenopausal breast cancer after adjustment for potential confounders. Increased weight over adulthood (HR: 1.02; 1.01 to 1.03) was also associated with increased risk for postmenopausal breast cancer.
CONCLUSIONS: Blouse and skirt sizes can be used as adipose indicators in predicting postmenopausal breast cancer. Maintaining healthy body weight over adulthood is an effective measure in the prevention of postmenopausal breast cancer.