PubMed · 15966640
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Michael Glick. 2005. A concern that cannot weight.. https://doi.org/10.14219/jada.archive.2005.0214
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INTRODUCTION: Previous studies suggesting different effects of diet on post-menopausal bone loss may have given conflicting results because they sometimes failed to exclude confounding conditions or used imprecise methodology. DESIGN: To identify dietary determinants of bone loss from the lumbar spine after menopause in women not taking hormone replacement who developed no evidence of spondylotic or sclerotic degenerative disease, forty-three women were followed with repeated (mean = 12) measurements of bone mineral density (BMD) at L2-4 for 11-14 years. Eleven developed evidence suggestive of degenerative disease and were excluded. Diet was assessed at the beginning of the study and 2.5 years later using 3-day and 7-day periods of weighed intakes. Nutrients estimated were: carbohydrate, fat, protein, fibre, calcium, magnesium, iron, phosphorus, copper, zinc and six vitamins. We tested the ability of diet to predict post-menopausal bone loss using stepwise regression. RESULTS: Each woman's BMD change was described by a single coefficient after log transformation of the BMD data. The best model for BMD loss including dietary factors alone had two significant determinants: daily energy or protein (p=0.0003) intake was adverse, while dietary iron (p=0.002) was predictive of bone maintenance, an effect that persisted if iron was expressed as a ratio to energy intake. Adding body mass index to the model increased the goodness of fit (R (2)adj rose from 0.33 to 0.42) without affecting the statistical significance of the dietary determinants. CONCLUSIONS: Diet may influence bone loss after menopause, with dietary iron (or an associated factor) possibly having a protective effect on bone at the spine.
OBJECTIVES: To measure health-related quality of life (HRQoL) in a clinical sample of obese children by child self-report and parent-proxy report; to compare quality of life assessments provided by obese children and their parents; to assess differences in quality of life between the obese clinical sample and healthy control children. DESIGN: Pairwise comparison of obese children matched for age, gender and socio-economic status with non-obese controls. SUBJECTS: One hundred and twenty-six obese children (body mass index (BMI) >/=98th centile) and 71 lean control children (BMI <85th centile). Controls were matched with 71 children from the obese clinical group (mean age 8.6, standard deviation (s.d.) 1.9 years; 33 M/38 F). MEASUREMENT: The Paediatric Quality of Life Inventory (UK) version 4 was self-administered to parents and to children aged 8-12 years and interview was administered to children aged 5-7 years. This questionnaire assessed physical, social, emotional and school functioning from which total, physical and psychosocial health summary scores were derived. RESULTS: In the obese clinical group (n=126), parent proxy-reported quality of life was low for all domains. In the obese clinical group, parent-reported scores were significantly lower than child self-reported scores in all domains except physical health and school functioning. Parent-proxy reports were significantly higher for healthy controls than obese children in all domains (median total score 85.2 vs 64.7; 95% confidence interval (CI) 15.6, 24.1). For child self-reports, only physical health was significantly higher for healthy controls than obese children (median score 81.3 vs 75.0; 95% CI 3.1, 12.5). CONCLUSIONS: HRQoL is impaired in clinical samples of obese children compared to lean children, but the degree of impairment is likely to be greatest when assessed using the parent perspective rather than the child perspective.
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