In order to determine which clinical, anthropometric, dietary, and biochemical variables are independent predictors of total and regional bone mineral density (BMD) in normal postmenopausal women, a cross-sectional study of 140 normal postmenopausal women has been carried out. Subjects were white, aged 45-71 yr (mean 58 yr), and had no history of disorders or medication use likely to influence bone or calcium metabolism. Multiple regression analysis was used to derive models for total and regional BMD in terms of the other variables measured. The analysis indicated that total body BMD was positively related to fat mass (P less than 0.0001), serum estrone (P = 0.0095) and age at menopause (P = 0.0165), and negatively related to age (P less than 0.0001), 24-h urine calcium (P = 0.0002), sex hormone-binding globulin (P = 0.0003), and serum alkaline phosphatase activity (P = 0.0029) (R2 = 0.61). Similar relationships were found in the subregions of the total body scans and in the lumbar spine and proximal femur, with insulin-like growth factor-1, parity, and age at menarche also being related to BMD at at least two of these sites. Lean body mass was not an independent correlate of BMD at any site once fat mass was taken into account. Muscle strength, physical activity, alcohol intake, and dietary intakes of calcium, sodium and protein did not emerge as significant predictors of BMD in this homogeneous group of postmenopausal women. We conclude that total body fat is the most significant predictor of BMD throughout the skeleton and this relationship is not explicable in terms of either estrone production in fat tissue or the dependence of skeletal load-bearing on fat mass. The mechanism underlying this relationship is an important question to be addressed in bone biology.

Determinants of Total Body and Regional Bone Mineral Density in Normal Postmenopausal Women—A Key Role for Fat Mass

Obesity has become a major public health problem. Given the current increase in life expectancy, the prevalence of obesity also raises steadily among older age groups. The increase in life expectancy is often accompanied with additional years of susceptibility to chronic ill health associated with obesity in the elderly. Both obesity and ageing are conditions leading to serious health problems and increased risk for disease and death. Ageing is associated with an increase in abdominal obesity, a major contributor to insulin resistance and the metabolic syndrome. Obesity in the elderly is thus a serious concern and comprehension of the key mechanisms of ageing and age-related diseases has become a necessary matter. Here, we aimed to identify similarities underlying mechanisms related to both obesity and ageing. We bring together evidence that age-related changes in body fat distribution and metabolism might be key factors of a vicious cycle that can accelerate the ageing process and onset of age-related diseases.

/pdf/obesity-and-related-consequences-to-ageing-14w8o0umes.pdf

Obesity and related consequences to ageing.

Background
The aim of this study was to describe the age-dependent changes in the parameters of physical performance and body composition in Japanese older adults who are independently dwelling in the community. We also examined whether the age-dependent changes differ among physical performance and body composition parameters.

Methods
Cross-sectional data from 10 092 community-dwelling older adults (mean age 73.6 years; 5296 women) were analyzed. The measures of physical performance included hand-grip strength, the five-times-sit-to-stand test, and walking speed. Body composition parameters (body weight, fat mass, and appendicular skeletal muscle mass) were measured with a bioelectrical impedance analyser. Correlations between age and the physical performance and body composition parameters were tested. The T-scores of physical performance and body composition measurements were calculated and presented according to 5-year age groups to examine the differences in age-dependent changes in physical performance and body composition parameters.

Results
All physical performance measures significantly decreased with aging. The cumulative mean T-scores according to age group showed different age-dependent changes between body mass index (BMI) and appendicular skeletal muscle mass index (ASMI) (cumulative mean T-score change of BMI and ASMI of −5.7 to −2.9 and −12.7 to −12.1, respectively). The slope declines in age-associated changes were greater in grip strength (β = −0.77, 95% confidence interval = −0.82 to −0.76) for men and in walking speed (β = −0.95, 95% confidence interval = −0.99 to −0.90) for women.

Conclusions
The patterns of age-dependent decreases in physical performance measures differed among parameters and between sexes. There is a possibility of a difference in the age-related slope patterns among parameters; decreases in grip strength in men and walking speed in women may be more prominent with advancing age. Furthermore, the decrease in ASMI with age is more striking than that of BMI.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jcsm.12197

Age-dependent changes in physical performance and body composition in community-dwelling Japanese older adults.

Ageing is a natural process. Everyone must undergo this phase of life at his or her own time and pace. In the broader sense, ageing reflects all the changes taking place over the course of life. These changes start from birth—one grows, develops and attains maturity. To the young, ageing is exciting. Middle age is the time when people notice the age-related changes like greying of hair, wrinkled skin and a fair amount of physical decline. Even the healthiest, aesthetically fit cannot escape these changes. Slow and steady physical impairment and functional disability are noticed resulting in increased dependency in the period of old age. According to World Health Organization, ageing is a course of biological reality which starts at conception and ends with death. It has its own dynamics, much beyond human control. However, this process of ageing is also subject to the constructions by which each society makes sense of old age. In most of the developed countries, the age of 60 is considered equivalent to retirement age and it is said to be the beginning of old age. In this chapter, you understand the details of ageing processes and associated physiological changes.

/pdf/ageing-process-and-physiological-changes-2phenirynn.pdf

Ageing Process and Physiological Changes

Concentration and distribution of parabens, triclosan, and triclocarban in pregnant woman serum in China.

Objectives 
Aging, body composition, and body mass index (BMI) are important factors in bone mineral density (BMD). Although several studies have investigated the various parameters and factors that differentially influence BMD, the results have been inconsistent. Thus, the primary goal of the present study was to further characterize the relationships of aging, body composition parameters, and BMI with BMD in Chinese Han males older than 50 years.


Methods 
The present study was a retrospective analysis of the body composition, BMI, and BMD of 358 Chinese male outpatients between 50 and 89 years of age that were recruited from our hospital between 2009 and 2011. Qualified subjects were stratified according to age and BMI as follows: 50–59 (n = 35), 60–69 (n = 123), 70–79 (n = 93), and 80–89 (n = 107) years of age and low weight (BMI: < 20 kg/m2; n = 21), medium weight (20 ≤ BMI < 24 kg/m2; n = 118), overweight (24 ≤ BMI < 28 kg/m2; n = 178), and obese (BMI ≥ 28 kg/m2; n = 41). Dual-energy X-ray absorptiometry (DEXA) was used to assess bone mineral content (BMC), lean mass (LM), fat mass (FM), fat-free mass (FFM), lumbar spine (L1-L4) BMD, femoral neck BMD, and total hip BMD. Additionally, the FM index (FMI; FM/height2), LM index (LMI; LM/height2), FFM index (FFMI; [BMC+LM]/height2), percentage of BMC (%BMC; BMC/[BMC+FM+LM] × 100%), percentage of FM (%FM; FM/[BMC+FM+LM] × 100%), and percentage of LM (%LM; LM/(BMC+FM+LM) × 100%) were calculated. Osteopenia or osteoporosis was identified using the criteria and T-score of the World Health Organization.


Results 
Although there were no significant differences in BMI among the age groups, there was a significant decline in height and weight according to age (p < 0.0001 and p = 0.0002, respectively). The LMI and FFMI also declined with age (both p < 0.0001) whereas the FMI exhibited a significant increase that peaked in the 80-89-years group (p = 0.0145). Although the absolute values of BMC and LM declined with age (p = 0.0031 and p < 0.0001, respectively), there was no significant difference in FM. In terms of body composition, there were no significant differences in %BMC but there was an increase in %FM (p < 0.0001) and a decrease in %LM (p < 0.0001) with age. The femoral neck and total hip BMD significantly declined with age (p < 0.0001 and p = 0.0027, respectively) but there were no differences in L1-L4. BMD increased at all sites (all p < 0.01) as BMI increased but there were declines in the detection rates of osteoporosis and osteopenia (both p < 0.001). A logistic regression revealed that when the medium weight group was given a BMI value of 1, a decline in BMI was an independent risk factor of osteoporosis or osteopenia, while an increase in BMI was a protective factor for BMD. At the same time, BMD in L1-L4 exhibited a significant positive association with FMI (p = 0.0003) and the femoral neck and total hip BMDs had significant positive associations with FFMI and LMI, respectively (both p < 0.0001).


Conclusions 
These data indicate that LMI and FFMI exhibited significant negative associations with aging in Chinese Han males older than 50 years, whereas FMI had a positive association. BMD in the femoral neck and total hip declined with age but an increased BMI was protective for BMD. LMI and FFMI were protective for BMD in the femoral neck and total hip.

/pdf/aged-related-changes-in-body-composition-and-association-1q2gq14ajw.pdf

Aged-Related Changes in Body Composition and Association between Body Composition with Bone Mass Density by Body Mass Index in Chinese Han Men over 50-year-old

Objectives The causal direction and magnitude of the association between total body bone mineral density (TB-BMD) and osteoarthritis (OA) risk is uncertain owing to the susceptibility of observational studies to confounding and reverse causation. The study aimed to explore the relationships between TB-BMD concentration and OA using Mendelian randomization (MR). Methods In this study, we used two-sample MR to obtain unconfounded estimates of the effect of TB-BMD on hip and knee OA. Single nucleotide polymorphisms (SNPs) strongly associated with TB-BMD in a large genome-wide association study (GWAS) were identified and selected as instrumental variables (IVs). In addition to the main analysis using inverse-variance weighted (IVW) method, we applied 2 additional methods to control for pleiotropy(MR-Egger regression, weighted median estimator) and compared the respective MR estimates. Results MR analyses suggested that genetically predicted higher TB-BMD is associated with risks of hip OA (For IVW: OR=1.199, 95%CI: 1.02-1.42, P=0.032; for WM: OR=1.257, 95%CI: 1.09-1.45, P=0.002). There was no evidence that the observed causal effect between TB-BMD and the risk of hip OA was affected by genetic pleiotropy(P=0.618). Additionally, our study didn’t support causal effects of a genetically increased TB-BMD risk on knee OA risk(OR=1.121, 95%CI: 0.99-1.28, P=0.084 using IVW; OR=1.132, 95%CI: 0.99-1.29, P=0.068 using WM; OR=1.274, 95%CI: 0.88-1.85, P=0.217 using MR-Egger). Conclusions Our findings support a causal effect that a genetic predisposition to systematically higher TB-BMD was associated with the risk of OA. And, TB-BMD likely exerts an effect on the risk of hip OA not knee OA.

/pdf/the-causal-association-between-bone-mineral-density-and-risk-vrzsptgs.pdf

Ying Jiang

Papers

Aged-Related Changes in Body Composition and Association between Body Composition with Bone Mass Density by Body Mass Index in Chinese Han Men over 50-year-old

The causal association between bone mineral density and risk of osteoarthritis: A Mendelian randomization study