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Body composition and aging

Body composition and aging

Bonjour J-P Bodj intake and bone health. Goldman-Cecil Medicine. Open the PDF Link PDF for - Mitochondrial Theory of Aging in Human Age-Related Sarcopenia in another window.

Body composition and aging -

Additionally, when muscles are weaker, your coordination, stability, and balance are negatively impacted. As you age, the amount of body fat for seniors typically increases to having nearly one-third more fat compared to the amount of fat they had when younger.

Also, this excess body fat and changes in body shape can affect your balance leading to hazardous falls. Then after this usual weight gain, both men and women tend to lose weight later on in life.

For men, this may be related to a drop in the male sex hormone testosterone beginning typically at the age of 55 and continuing as they age. And for women, this is because when the fat replaces the lean muscle tissue, it weighs less.

So, weight loss appears usually after the age of 65 and continues as they age. Another change to your body composition as you age is the loss of bone mass. Your bones tend to lose some of their minerals and become less dense.

The technical term is osteopenia i. With brittle bones, you are more apt to experience a fracture or break if you should fall. Osteoporosis also leads to changes in your posture i. Another result of aging on our bodies is that we tend to shrink in height.

This phenomenon occurs across all races and for both sexes. Women lose on average approximately inches and men lose about inches by the age of This shrinkage is caused by the loss of muscle mass in our torsos.

Someone with impaired mobility from sarcopenic obesity, for example, may go on to suffer greater bone loss and fractures Ilich et al.

Taken together, overall body composition, corresponding serum biomarkers indicating impairments in bone, muscle and fat tissues , nutrition and physical performance should all be taken into consideration when evaluating the health of older adults Ilich et al.

It is now recognized that bone, muscle and fat are interconnected and act as endocrine organs Mantzoros et al. Therefore, the next section briefly discusses the three tissues as endocrine organs. Vitamin D, as hormone calcitriol 1, dihydroxyvitamin D , influences bone, muscle and adipose tissue throughout the life cycle, with probably the most important role during growth and in older age.

Its status might be compromised in elderly due to several reasons including: lower vitamin D intake, decreased skin production of cholecalciferol the first precursor of active vitamin D partly due to lower sun exposure, decreased activity of both liver and renal hydroxylases leading to lower conversion to calcidiol hydroxyvitamin D and calcitriol in liver and kidney, respectively Gallagher The disturbance in vitamin D leads to decreased calcium absorption, partly related to abnormalities in the calcium transport proteins that are regulated by calcitriol.

In summary, both calcium and vitamin D absorption are diminished with aging leading to their lower serum concentration Gallagher There is a strong relationship between low calcidiol concentrations and increasing levels of obesity Pereira-Santos et al. It has been shown that even when controlling for sunlight exposure, obese individuals are significantly more likely to have lower calcidiol concentration, indicating inadequate vitamin D status Cheng et al.

Moreover, inadequate vitamin D can increase adipogenesis by promoting higher parathyroid hormone PTH secretion and greater influx of calcium into adipocytes Wood Similarly, low serum calcium could promote increase of circulating calcitriol and PTH, which then stimulate influx of extracellular calcium into adipocytes via a specific-membrane vitamin D receptor, again promoting adipogenesis Zemel et al.

Regarding bone health, calcitriol is essential for normal bone turnover and maintenance, as well as for metabolism of the minerals calcium, phosphorous and magnesium Pereira-Santos et al. A decrease in calcitriol could disturb calcium homeostasis and impair bone health.

Numerous studies have addressed the role of vitamin D in bone health and fracture incidence Holick et al. However, both recommendations of vitamin D intake and adequate serum concentrations of calcidiol still remain controversial. The latter is even more hindered in view of unreliable and often inaccurate analytical methods for its detection Snellman et al.

With that regard, there are still disagreements about serum concentration of calcidiol reflecting adequacy, inadequacy or true deficiency Holick et al.

Regarding the muscle, inadequate vitamin D has recently been associated with sarcopenia, decreased grip strength and other impaired functionality measures in older adults Visser et al. Recent studies also showed that inverse relationship between vitamin D status and PTH concentrations is associated with compromised muscle mass and strength, as well as with diminished physical function Lee et al.

A study in the Netherlands investigating older women and men showed that low calcidiol and high PTH increase the risk of sarcopenia, as reflected in lower muscle mass and hand grip strength Visser et al.

Tying this to bone, another study has found that patients with insufficient calcidiol concentrations and low BMD are also more likely to develop sarcopenia Lee et al.

Considering bone as an endocrine organ, most research has probably been done on osteocalcin, an osteoblast-secreted protein, also referred to as bone γ-carboxyglutamic acid Gla protein.

Once synthesized, it is largely incorporated into the extracellular bone matrix hydroxyapatite , but a low concentration is maintained in serum and is used as an indicator of bone formation Hauschka et al.

However, in cases of low carboxylase activity e. This undercarboxylated osteocalcin was shown to stimulate pancreatic β-cell proliferation and insulin secretion via embryonic stem-cell phosphatase expressed in osteoblast and thus positively modulate energy metabolism Kanazawa et al.

Muscle tissue has just begun to be investigated as an endocrine organ. Troponins, the key regulatory proteins associated with the contractility process of cardiac and skeletal muscle, are receiving the most attention.

Troponins are not normally found in the blood, except in cases of muscle turnover or muscle damage. This complex is needed for the repetitive cycles of contraction and relaxation.

Skeletal muscles are protected by several layers of connective tissue, which maintain the muscle integrity. If this barrier is injured, internal components of muscle, particularly sTnT, leak into the blood and their measurable presence could indicate sarcopenia Chase et al.

Serum sTnT drops proportionally with improvements in handgrip strength and overall physical fitness in older adults, as recently reviewed Abreu et al. Regarding the fat tissue, the classic hormone secreted by adipocytes is leptin Reid Leptin is higher in women and proportionally increases with increasing fat tissue Pires et al.

Leptin locally enhances osteoblastogenesis and inhibits osteoclastogenesis Gordeladze et al. For example, transfection of leptin into MSC of osteoporotic rats, increased osteoblast differentiation and mineral deposition both in vivo and in vitro Zheng et al.

Positive effects of leptin on bone and accelerated fracture healing were shown in rats with induced femoral fractures after peritoneal exogenous leptin injection. However, the central effect of leptin could be characterized in either positive or negative regulation of bone metabolism Karsenty , Gordeladze et al.

Thus, the conflicting results of the relationship of leptin and BMD were reported in several studies Iwamoto et al. Leptin passes through the blood brain barrier and activates the leptin receptor in the hypothalamus.

Activated receptor suppresses serotonin secretion in the brainstem, and in the absence of serotonin, the sensory nervous system sends signals to osteoblasts by secretion of norepinephrine. Similarly, a previous evidence from a study conducted on β 2 -adrenergic receptors deficient mice showed reduced RANKL expressions Elefteriou et al.

Obesity can lead to leptin resistance and hyperleptinemia. Additionally, leptin also appears to activate pro-inflammatory pathways in osteoblasts Upadhyay et al. Conversely, decreased serum leptin is found in frail elderly and in cachexia Hubbard et al.

However, the hyperleptinemia in osteosarcopenic obesity may mask this, possibly causing patients with osteosarcopenic obesity to be overlooked in clinical settings Hubbard et al. Adiponectin is another hormone that has been investigated as a possible link between bone and fat tissue. Circulating adiponectin is decreased in obese states but increased in lean states, as well as during energy restriction, weight loss and in older individuals Ambroszkiewicz et al.

Recently, Cawthorn et al. cancer therapy Cawthorn et al. Adiponectin is involved in fat metabolism and may inhibit obesity by increasing fatty acid oxidation in adipose tissue by activation of AMP-activated protein kinase AMPK phosphorylation and in muscle by P38 mitogen-activated protein kinase MAPK and peroxisome proliferator-activated receptor PPAR alpha Yoon et al.

These combined effects of adiponectin appear to favor lean mass and possibly promote decreased body fat accumulation Fiaschi et al. Predictably, adiponectin serum concentrations would be lower in osteosarcopenic obesity women, due to increased fat mass and decreased lean mass.

However, since adiponectin increases with age, its decline in osteosarcopenic obesity in women might be masked. Aging causes numerous physiological changes, among which those affecting the physical phenotype are the most observable.

An ultimate consequence of deterioration in body composition is the development of osteosarcopenic obesity. This is a complex condition with concomitant changes in bone, muscle and adipose tissue in aging body or occurring in some other chronic diseases.

Increased adiposity results in increased inflammation, influencing muscle and bone health, while inflammation perpetuates adiposity Ilich et al. Damage to or decline of one tissue could signal changes in the other, but all ultimately lead to decreased functionality, increased risk for falls and increased morbidity.

Therefore, in evaluating the older adults, clinicians should perhaps first assess functional decline through physical performance tests, then assess biomarkers in serum, followed by the assessment of bone and muscle loss to diagnose osteosarcopenic obesity syndrome and any of its components Ilich et al.

Does chronic inflammation exacerbate bone loss, worsen sarcopenia and subsequently lead to lower functionality? Could reduced adiposity improve bone health and muscle mass and strength in older people?

Research into the changes in body composition with aging should evaluate not only the level of frailty in older adults but the overall interconnecting links among bone loss, muscle loss and increased adiposity, as proposed recently Ilich et al.

The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of this review. Related work in JZI laboratory has been funded by the USDA grant and Hazel K. Stiebeling professorship. J Z I conceptualized manuscript and wrote the final version.

J P, J E I, W R and O J K drafted the manuscript. O J K and J Z I designed the figures. Reviews on Recent Clinical Trials 9 — Nursing Research 63 75 — nutritional surveillance: National Health and Nutrition Examination Survey caloric anergy intake data, — PLoS ONE 9 e Hormone and Metabolic Research 34 — Bonjour J-P Protein intake and bone health.

International Journal for Vitamin and Nutrition Research 81 — Obesity 23 — Bone 66 — American Journal of Clinical Nutrition 60 — Cao JJ Effects of obesity on bone metabolism. Journal of Orthopaedic Surgery and Research 6 Cell Metabolism 20 — New England Journal of Medicine — Journal of Muscle Research and Cell Motility 34 — Diabetes 59 — Osteoporosis International 4 — BioFactors 40 — Journals of Gerontology 63 — American Journal of Physiology E — E Journal of the American College of Cardiology 57 — Age and Ageing 39 — Journal of Nutrition — Calcified Tissue International 74 — Journal of Histochemistry and Cytochemistry 42 — Osteoporosis International 24 — Journals of Gerontology Series A: Biological Sciences and Medical Sciences 68 — Nature — American Journal of Clinical Nutrition 93 — Canadian Pharmacists Journal — Endocrine Reviews 24 — PLoS ONE 7 e Journal of Nutrition Health and Aging 19 — Fulgoni VL Current protein intake in America: analysis of the National Health and Nutrition Examination Survey, — American Journal of Clinical Nutrition 87 S — S.

Gallagher JC Vitamin D and aging. Endocrinology Metabolism Clinics of North America 42 — The OFELY study. Bone 40 — World Journal of Diabetes 6 Transactions of the American Clinical and Climatological Association — Journal of Cellular Biochemistry 85 — Frontiers in Endocrinology 7 Journal of Bone and Mineral Research 15 — Physiological Reviews 69 — Heaney RP Bone health.

American Journal of Clinical Nutrition 85 Supplement S — S. Journal of Bone and Mineral Research 26 — Heidelbaugh JJ Proton pump inhibitors and risks of mineral deficiency: evidence and clinical implications.

Therapeutic Advances in Drug Safety 3 — Maturitas 80 — Journal of Clinical Endocrinology and Metabolism 90 — American Journal of Clinical Nutrition 87 — Journal of the American Geriatrics Society 56 — Journals of Gerontology.

Series A, Biological Sciences and Medical Sciences 56 B — B International Journal of Body Composition Research 8 — Ageing Research Reviews 15 51 — Current Gerontology and Geriatrics Research 1 — 7. Osteoporosis International 26 — European Journal of Clinical Nutrition 57 — Bones may lose some of their minerals and become less dense a condition called osteopenia in the early stages and osteoporosis in the later stages.

Tissue loss reduces the amount of water in your body. The amount of body fat goes up steadily after age Older people may have almost one third more fat compared to when they were younger. Fat tissue builds up toward the center of the body, including around the internal organs. However, the layer of fat under the skin gets smaller.

The tendency to become shorter occurs among all races and both sexes. Height loss is related to aging changes in the bones, muscles, and joints.

People typically lose almost one-half inch about 1 centimeter every 10 years after age Height loss is even more rapid after age You may lose a total of 1 to 3 inches 2.

You can help prevent height loss by following a healthy diet, staying physically active, and preventing and treating bone loss. Less leg muscles and stiffer joints can make moving around harder.

Excess body fat and changes in body shape can affect your balance. These body changes can make falls more likely. Changes in total body weight vary for men and women. Men often gain weight until about age 55, and then begin to lose weight later in life.

This may be related to a drop in the male sex hormone testosterone.

Musculoskeletal Bofy are cmposition among older people. Preventive strategies require compositoin of Boey changes in strength, Body composition and aging and body composition, including how they Coenzyme Q immune system. We have described, and examined associations Beetroot juice and muscle recovery, 9-year changes in these parameters Supporting muscular function Health, Aging compksition Body Composition Study participants aged 70—79 years. Appendicular lean mass ALMwhole body fat mass and total hip BMD were ascertained using DXA; muscle strength by grip dynamometry; and muscle function by gait speed. For each characteristic annualised percentage changes were calculated; measures of conditional change independent of baseline were derived and their interrelationships were examined using Pearson correlations; proportion of variance at 9-year follow-up explained by baseline level was estimated; and mean trajectories in relation to age were estimated using linear mixed models.

Body composition and aging -

Body Mass Index BMI is commonly used to assess obesity as it is easily measured and does not require costly equipment. One cross-sectional study found that muscle strength was positively associated with BMI in underweight, normal, overweight and obese older men and women [ 17 ].

BMI has poor diagnostic accuracy for identifying older adults with obesity [ 19 , 20 ], which might account for the contrary findings. Several studies have demonstrated that higher body fat percentage is associated with lower muscle strength [ 10 , 21 ] and lower muscle mass in older adults [ 22 , 23 ].

This finding suggests that body fat percentage may contribute to the relationship between muscle strength and muscle mass. Body composition is related to muscle strength, however there is very limited evidence regarding the contribution of obesity classification based on body fat percentage when investigating the relationship between muscle strength and muscle mass in older adults.

The aim of this research was to examine the relationship between muscle strength, muscle mass, and body fat percentage in older adults living in Auckland, NZ.

This study was a secondary aim of the Researching Eating, Activity and Cognitive Health REACH Study. The main objective of the REACH Study was to investigate dietary patterns and associations with cognitive function and metabolic syndrome in older adults.

Further information regarding the REACH study protocol can be found elsewhere [ 24 ]. Participants included men and women aged 65—74 years, living independently in Auckland, NZ. Exclusion criteria were a diagnosis of dementia or any condition which may impair cognitive function e.

traumatic head injury, stroke , medication which may influence cognitive function, colour blindness, or any other event in the last two years which had a substantial impact on dietary intake or cognitive function.

Participants who registered their interest in the REACH study were provided with an information sheet and completed an online screening questionnaire to determine their eligibility to take part.

If the inclusion criteria were met, participants were invited to participate in the study. All participants visited the Human Nutrition Research Unit on one occasion for collection of data as part of the wider REACH study. Socio-demographic information including age and gender were collected through written questionnaires.

Data quality was ensured by checking questionnaires for completeness. Height and weight measurements were undertaken using standardised techniques adapted from the International Society for the Advancement of Kinanthropometry ISAK protocol.

Height was measured to the nearest 0. Weight was measured with the participant in light clothing, using floor scales Wedderburn.

BMI was calculated using body weight in kilograms divided by height metres squared. Body composition values were ascertained from a total body dual-emission X-ray absorptiometry DXA scan Hologic, QDR Discovery A.

The machine was checked and calibrated daily in line with the standard operating procedure recommendations. All scanning and analysis procedures were performed by a trained operator.

After removal of shoes and jewelry, participants adopted a supine position with arms to the side [ 25 ]. Participants were then scanned as per established recommendations [ 26 , 27 ], with the standard mode scan taking approximately eight minutes to complete.

The values for body composition outcomes were determined from the ratio of soft tissue attenuation of two X-ray energy beams for each pixel containing a minimal amount of soft tissue but no significant bone.

Body fat percentage was calculated by dividing total fat mass by the sum of bone, lean and fat mass [ 21 ]. Regional analyses were performed and appendicular skeletal muscle mass ASM was calculated as the sum of mineral-free lean mass of the arms and legs [ 28 , 29 ].

The ASM index was calculated by ASM kilogram divided by height meters squared [ 30 ]. Isometric grip strength was measured in both hands using an adjustable hand grip strength dynamometer JAMAR HAND [ 32 ]. The participant was seated on a standard straight back chair without arm rests, and with elbow, hips and knees at 90° angles.

All participants were instructed to squeeze the handle as hard as they could upon a verbal signal from the researcher. Verbal encouragement was provided throughout the period of effort which did not exceed 10 seconds.

Results were recorded in kilograms kg , the mean of three trials for each hand was recorded and the highest value of the two means was used for further analyses [ 32 , 33 ]. Continuous data were assessed for normality using Shapiro Wilcoxon tests and visual assessment of histograms. Descriptive statistics were reported as means ± SD for parametric data, and frequencies and percentages for categorical data.

Differences between groups were analysed using independent t-tests for parametric data, and the chi-square test of independence for categorical data.

The measurements were categorized into two groups according to sex. The measurements were further categorized according to body fat percentage into two groups.

A multiple linear regression analysis was performed to determine body composition parameters predicting muscle strength in males and females. Adjusted r, standard error values, and multicollinearity statistics were used to identify the most appropriate equations.

This analysis was undertaken in males and females according to obesity classifications based on body fat percentage. All statistical analyses were completed using the statistical software IBM SPSS version Descriptive statistics for the study population according to sex are presented in Table 1.

The mean ± SD age of participants was Males were taller, heavier and had a lower body fat percentage than females, but these differences were not significant. The mean BMI for this study population fell in the overweight BMI category Using BMI categories, In males and females, 9.

The prevalence of low muscle mass was 2. Appendicular skeletal muscle mass index and muscle strength were higher in males compared with females, this difference was significant for muscle strength only Table 1.

When exploring the association between muscle strength and muscle mass according to obesity classification using body fat percentage, muscle mass was significantly associated with muscle strength in non-obese males and females. However, in participants with obesity, muscle mass was no longer associated with muscle strength Tables 4 and 5.

In this cross-sectional study, we evaluated the relationship between muscle strength, muscle mass, and body fat percentage in older adults living in Auckland, NZ.

The findings indicate that muscle strength was associated with muscle mass. The magnitude of this association was greater in males than females, with addition of body fat percentage slightly increasing the ability of the model to predict muscle strength. When exploring the association between muscle strength and muscle mass according to obesity classification using body fat percentage, muscle mass was associated with muscle strength in non-obese participants.

However, this association was not observed in older adults who were classified as obese. This indicates that body fat percentage should be considered when measuring associations between muscle mass and muscle strength in older adults.

We found a higher prevalence of participants with obesity using body fat percentage classifications This result was as expected, as BMI has been shown to underestimate adiposity in older adults [ 37 ]. A recent survey in New Zealand using BMI classifications reported that the prevalence of obesity in older adults between 65—74 years was The lower level of obesity reported in our population may reflect our recruitment inadvertently targeting healthy older adults.

We also identified 3. The lack of studies reporting the prevalence of low muscle strength and the application of different cut-off values makes it difficult to compare studies. In this cohort, we applied the updated cut off values of low muscle strength defined by the European Working Group on Sarcopenia in Older People EWGSOP2.

A nationally representative sample of Brazilians aged 65 years and older using the same cut-off values as our study observed a higher prevalence of low muscle strength Other studies which applied the older cut off values defined by the European Working Group on Sarcopenia in Older People EWGSOP , observed a higher prevalence of low muscle strength of The higher prevalence observed in these groups, is possibly explained by the inclusion of people older than 74 years, and a potentially less healthy population than those participants included in our study.

The prevalence of low ASMI was 6. The higher percentage in the study appears to be explained by the inclusion of adults over the ages of 74 years.

Our results provide evidence that muscle mass is positively associated with muscle strength in older men and women. This result aligns with the literature [ 43 , 44 ] and suggests that efforts to maintain muscle mass should have a significant effect on preserving strength in older adults.

When stratified by sex, we observed strong evidence that muscle mass was significantly associated, but not a major contributor to muscle strength in older men and women.

In a regression model taking into account muscle mass, it was shown that an increase of 1 unit muscle mass will increase the value of muscle strength by 0. These results highlight not only the importance of increasing muscle mass, but also the importance of decreasing body fat percentage to preserve muscle strength in older adults.

The cross-sectional nature of our data impedes any causal inference. Nevertheless, the results from our study provide justification for further prospective research that evaluates the effects of interventions, which are aimed at optimising body composition and muscle strength in older adults.

To our knowledge, this is the first study to investigate the role of obesity classification based on body fat percentage in the relationship between muscle strength and muscle mass. Results from multiple linear regression analyses provide evidence supporting the important role of obesity classification according to body fat percentage when investigating the relationship between muscle strength and muscle mass.

Our study demonstrated that when obesity was classified using body fat percentage, muscle mass was significantly associated with muscle strength in non-obese older adults. However, an association between muscle strength and muscle mass was not observed in older adults categorised as obese.

The accumulation of intramuscular lipid content or poor muscle quality , which is seen in people with obesity may explain the influence of obesity in the relationship between muscle strength and muscle mass. Goodpaster et al. reported that higher intramuscular lipid content is associated with lower muscle strength, independent of muscle mass [ 45 ].

Also, accumulation of intramuscular lipid content is known to be associated with insulin insensitivity, inflammation and functional deficits in skeletal muscle. It will be important in the future to continue to focus on understanding predictors of muscle strength in older adults with obesity in order to provide appropriate interventions to increase muscle strength.

There were significant strengths to our study. The relatively large sample size permits us to examine whether the relationship between muscle strength and muscle mass was similar in males and females.

Also, it is possible that the inclusion of community-dwelling healthy older adults provides the opportunity to identify issues and promote preventative action in early old age.

Furthermore, the use of DXA is an accurate measure of body composition. However, in contrast to magnetic resonance imaging MRI or computed tomography CT DXA cannot detect intramuscular fat from muscle mass nor distinguish the composition of muscle [ 46 , 47 ]. This cross-sectional study limits the ability to detect causality; hence, only associations were discussed.

Other limitations are the population group, which was not representative of the New Zealand population, as this cohort was composed of a convenience volunteer sample of men and women aged 65—74 years living in the community. The classification by body fat percentage for obesity may also be perceived as a limitation given the arbitrary nature of the cut-off points.

Finally, we did not assess lower extremity muscle strength, which is a more direct predictor of falls. However, grip strength is associated with lower-body muscle strength [ 48 ] and a strong predictor of disability [ 49 ].

BUY THIS Book. Print Version. Body Composition and Aging. Derek M Huffman ; Derek M Huffman. a Departments of Medicine,. c Institute for Aging Research, Albert Einstein College of Medicine, Bronx, N.

Nir Barzilai Nir Barzilai. View Chapter. Open the PDF Link PDF for 1 - Contribution of Adipose Tissue to Health Span and Longevity in another window. Ian M Chapman Ian M Chapman. Division of Medicine, University of Adelaide, Adelaide, Australia. Open the PDF Link PDF for 20 - Obesity Paradox during Aging in another window.

Zbigniew Kmiec Zbigniew Kmiec. Department of Histology, Medical University of Gdansk, Gdansk, Poland. Open the PDF Link PDF for 37 - Central Control of Food Intake in Aging in another window. Roger B McDonald ; Roger B McDonald. Department of Nutrition, University of California, Davis, Calif.

C Ruhe Rodney. C Ruhe. Open the PDF Link PDF for 51 - Changes in Food Intake and Its Relationship to Weight Loss during Advanced Age in another window. Tami Wolden-Hanson Tami Wolden-Hanson. Geriatric Research, Education, and Clinical Center and Research Service, Veterans Administration Puget Sound Health Care System, Seattle, Wash.

Open the PDF Link PDF for 64 - Changes in Body Composition in Response to Challenges during Aging in Rats in another window. Catherine A Wolkow Catherine A Wolkow.

Laboratory of Neurosciences, NIA Intramural Research Program, NIH, Baltimore, Md. Michael J. Berger ; Michael J. a School of Kinesiology, and Departments of Clinical Neurological Sciences and. Timothy J. Doherty Timothy J. b Physical Medicine and Rehabilitation, Schulich School of Medicine, University of Western Ontario, London, Ont.

Another result of aging on our bodies is that we tend to shrink in height. This phenomenon occurs across all races and for both sexes. Women lose on average approximately inches and men lose about inches by the age of This shrinkage is caused by the loss of muscle mass in our torsos.

From this, we can develop a stooped posture that results in us looking even shorter. This loss of height can often lead to an increase in health risks, most commonly breaking a hip.

There are some concrete steps you can take to offset the slower metabolism and weight gain, build strong muscles and bone density, and lessen shrinkage in height. None of these suggestions are earth-shaking new ideas. They are the same suggestions for healthy living.

Strength training, weight-bearing activities like dancing and walking, resistance exercises like weightlifting, and yoga are several activities that can help you achieve positive results for your body composition.

It is recommended that seniors who are 65 or older should get at least 2. This equals to about 30 minutes each day. Or you should get approximately 1 hour and 15 minutes of vigorous exercise such as jogging each week. A healthy diet includes vegetables and fruits, whole grains, and the right amounts of healthy fats.

Included in the protein is at least one serving of milk or yogurt. You should also choose foods with low sodium amounts.

Most studies examining the agiing between body composition and health-related quality of Beetroot juice and muscle recovery HRQoL in Injury prevention in cycling Beetroot juice and muscle recovery andd been cross-sectional and analyzed only fat or lean compozition. Hence, aginf is poorly known whether fat and lean mass are independently associated with subsequent changes in HRQoL. We investigated whether baseline lean and fat mass are associated with changes in HRQoL over a year period in older adults. We studied men and women from the Helsinki Birth Cohort Study age 57—70 years at baseline. HRQoL was assessed using RAND item Health Survey at baseline and follow-up 10 years later. Lean mass was not strongly associated with HRQoL at baseline or change in HRQoL. Increased adiposity composigion decreased muscle mass contribute substantially to age-dependent disease and Supporting muscular function. In particular age-related sging in adiposity is quickly becoming Supporting muscular function major coposition to public Supporting gut health throughout the world. Although the hypothesis that age-related changes in body composition are due to lifestyle choices alone is well accepted, it is a vast oversimplification. This volume reflects the current knowledge in this rapidly developing field of research. The first part of the book discusses the extent to which increased adiposity contributes to age-related diseases and longevity.

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Beetroot juice and muscle recovery analyzed the relationship between specific body composition and physical performance, using uniform physical performance and body composition measurement tools, in populations with various comorbidities from enrollment assessment data of 13 clinical studies.

We analyzed data from participants in 13 clinical studies conducted at Wake Forest University WFU between and These studies assessed body composition and physical function in a total of 1, older individuals see Table 1 at enrollment of each study.

For current analyses, we included participants who were aged 60 years at the time of enrollment. All of the subjects signed an informed consent form and these studies were approved by the WFU Institutional Review Board.

Body mass index was calculated using body weight in kilograms divided by height in meters squared. Body composition was measured using DEXA on a Hologic scanner Hologic, Bedford, MA.

A whole body scan was used to determine total body fat mass. Percent body fat was calculated by dividing total body fat by the sum of bone, lean, and fat mass.

Regional analyses were performed and mineral-free lean mass of the arms and legs were summed to calculate appendicular lean mass. Hand grip strength was measured in both hands using an adjustable grip strength dynamometer Jamar Model No.

BK; Fred Sammons, Inc. Participants performed the test three times with each hand, and the maximum overall value was used in the analyses. The SPPB consists of three timed measures: a 4 m walk, repeated chair rise, and a balance test Guralnik et al.

To measure walking speed, the participants were asked to walk at their usual pace over a 4-m course. Duplicate measurements were done, and the faster measure was used to compute walking speed.

For the repeated chair rise, participants were asked to stand from a sitting position without using their arms. Those who could do so were asked to stand up and sit down five times at their fastest speed. Balance was measured by asking the participants to maintain balance in three positions with a progressive narrowing of the base of support: side by side, semitandem, and tandem.

Each task was scored from 0 to 4, with 4 indicating the highest performance and 0 inability to perform the task, based on the rubric from the Established Populations for Epidemiologic Studies of the Elderly Guralnik et al.

A total score was calculated and ranged from 0 to The Pepper Assessment Tool for Disability PAT-D is a item self-administered questionnaire to assess mobility, activities of daily living ADL and instrumental activities of daily living IADL. Multiple linear regression was used to characterize the strength of the relationships between physical function measures 4-m walk speed, repeated chair rise time, grip strength, SPPB, and PAT-D and body composition BMI, percentage of body fat, and percent appendicular lean mass within each study while controlling for age, gender, and race individual study model.

Multiple linear regression models were then used to determine the associations between physical function and body composition in all participants combined, adjusted for study effect using dummy variables, in addition to age, gender, and race combined model.

Residual plots were produced for the combined analyses to examine the patterns across studies. We found the residual patterns were consistent across different studies for all the physical function measure outcomes and body composition predictors. We investigated the consistency of relationships across gender by testing for interactions between gender and body composition.

This was done by adding an interaction term in the combined model described above. If the test for the interaction was statistically significant, it indicated that the relationship between physical function measure and body composition depended on gender; otherwise, we concluded that the relationship was consistent across both genders.

All analyses were performed with SAS 9. There were 1, participants from 13 studies included in the analyses. The mean age of the participants was Table 2 describes body composition and physical performance of the participants by studies and combined at enrollment of each study.

We examined associations between body composition and physical performance measure using multiple linear regression analyses for each study and for all studies combined.

Figure 1 describes the relationship between body composition and physical performance. Across the studies, the association between each body composition and 4-m walk speed, SPPB and PAT-D were consistent in general.

Regression Coefficient of each body composition for physical function assessments. Each bubble denotes each with the area of the bubble represents the size of the study. Given prior studies reported different relationships between body composition and physical function by gender, further analyses were done by gender.

We also examined gender and body composition interactions on each measure of physical performance. In this report, we combined information from 13 previous clinical studies, using a consistent battery of tests administered in 1, participants.

We analyzed associations between body composition and physical performance across these studies, which included older adults with various comorbidities. We found that markers of obesity, such as BMI and percent body fat, were consistently associated with poor physical performance.

This trend was apparent in slower walk speeds, lower SPPB scores, and higher PAT-D scores. On the other hand, increased muscle mass i. All these associations of physical performance were independent of age, gender, and race.

Although we saw significant interactions of gender in the association of BMI and chair rise time, the associations of body composition and physical function were generally independent of gender. Our study demonstrated that both anthropometric measurement and direct measurement of obesity are consistently associated with poor physical function.

This deleterious effect of obesity on physical function has been shown before; multiple hypotheses have been proposed to explain the relationship.

Adipose tissue produces inflammatory cytokines, such as tumor necrosis factor-α and interleukin-6 IL-6 Coppack, Adipose tissue also demonstrates increased activation of intracellular kinases, such as c-jun N-terminal kinase an inhibitor of κ kinases and protein kinase R, which can induce inflammation Nakamura et al.

In addition, inflammatory cells like macrophages and T cells infiltrate into adipose tissues Feuerer et al. This increased systemic inflammation caused by obesity can cause inflammation in skeletal muscle. In a study of datasets that were included in our group analyses, Brinkley and colleagues demonstrated that higher levels of C-reactive protein and IL-6 were associated with lower grip strength, lower SPPB scores, and longer times to complete the 4-m walk test and repeated chair stands test Brinkley et al.

Our current study included more studies and explored the association between body composition and physical function. The second hypothesis is the biomechanical effect of obesity on physical performance.

Although obesity is associated with increased muscle mass, obese subjects have relative muscle weakness for their weight and lower fatigue resistance Maffiuletti et al. These biomechanical changes can cause decline in physical performance.

Third, a sedentary lifestyle is associated with obesity and worse physical performance due to deconditioning. Fourth, obesity is associated with certain musculoskeletal diseases, such as osteoarthritis and gout Magliano, ; these conditions in turn can cause decline in physical function.

Finally, another possible explanation between obesity and poor physical performance is the effect of weight loss effort on muscle mass in older adults. Currently, the main approach of weight loss is dietary calorie restriction. If there are a string of episodes of weight loss and weight regain, in the absence of resistance training, the weight regained will be mostly body fat as opposed to muscle mass.

Over time, body composition would become worse e. It is possible that participants in our study with obesity have tried dietary caloric restriction in the past that resulted in lower muscle mass, higher fat mass, and poor physical function. While the negative association between body fat content and physical function has been consistent Baumgartner et al.

Also, there are reports of different relationships between muscle mass and physical performance by gender Valentine et al. Bioelectrical impedance analysis BIA or DXA are common ways to measure body composition. In another study of 4, older adults, a U-shaped relationship was observed between ASMI and physical limitation Woo et al.

These associations were also demonstrated in analyses done by gender except the association with percent appendicular lean mass and walk speed did not reach statistical significance in men.

: Body composition and aging

Effects of Aging on Body Composition Sging Cell, 9 5— x false. In Supporting muscular function, Weight loss supplements baseline Year 1 coposition, sex, race, educational attainment, and Body composition and aging agijg such as compisition status and alcohol consumption were self-reported using questionnaires. BMI and all-cause mortality in older adults: A meta-analysis. Reprints and permissions. Ethics declarations Conflict of interest CC reports personal fees outside the submitted work from Alliance for Better Bone Health, Amgen, Eli Lilly, GSK, Medtronic, Merck, Novartis, Pfizer, Roche, Servier, Takeda and UCB. Article CAS PubMed PubMed Central Google Scholar.
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Chapter 6: Body Composition Changes – Nutrition in Aging In progress issue alert. Public Health Promotion Unit, Supporting muscular function Institute for Compoistion and Ad, Helsinki, Finland. Winter JE, MacInnis Composiion, Wattanapenpaiboon N, Nowson CA BMI and all-cause mortality in older adults: a meta-analysis. Differences between groups were analysed using independent t-tests for parametric data, and the chi-square test of independence for categorical data. Some things you can do to reduce age-related body changes are: Get regular exercise.
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Body composition and aging


Changes to Body Composition and Aging

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