Abstract
Background. The present study sought to examine the association between physical exercise as a lifestyle habit with anthropometric parameters and body composition and aging in men.
Methods. Intensity of exercise was scored as metabolic equivalent-min/week (MET-min/week) from data of the questionnaire, while anthropometric parameters and body composition were carried out by standard measuring instruments and dual-energy X-ray absorptiometry scanner, respectively.
Results. Age was associated with decreases in bodyweight, height, total lean mass and bone mass, but an increase in fat mass. The negative association of lean mass with age was predominantly due to the negative association of lean masses in the legs and arm, while the positive association of fat mass with age was primarily due to the positive association of fat masses in the trunk and abdomen. Exercise of intensity greater than 1000 MET-min/week was significantly associated with higher lean and bone masses and lower fat mass. The increase in lean mass was predominantly in the legs, while the decreases in fat mass were in the trunk and abdomen.
Conclusion. The study showed that the high intensity of physical exercise, equivalent to greater than 1000 MET-min/week, is required to effect beneficial changes in the body composition. Hence, results from the study support the importance of promoting a lifestyle habit of exercise of sufficient intensity in order to mitigate the increase risks of sarcopenia and obesity and their attendant ill effects on health in men as they age.
Introduction
Aging is associated with changes in body composition and in one study, it was reported that body fat increased from 18 to 36% in men and 33 to 44% in women from age 18 to 85 years; and concurrent with the increase in fat mass was a decrease in muscle mass [Citation1–3 ]. Age-related accumulation of fat deposits and the loss of muscle mass have been shown to increase the risk of developing a wide range of chronic disorders, including hypercholesterolemia, atherosclerosis, hyperinsulinemia, insulin resistance, non-insulin-dependent diabetes and hypertension [Citation4,Citation5].
Changes in body composition are related, to a certain extent, to diet and the level of physical exercise that an individual is engaged in. Participation in regular physical exercise may help reduce the incidence of frailty in the elderly by increasing muscle mass and strength and consequently improves the capacity to perform physical activity [Citation6–9 ]. Furthermore, it may reduce the incidence of overweight and obesity and therefore, other diseases including type 2 diabetes mellitus, coronary heart disease, osteoporosis, in addition to possible improvement in cognition and a reduction in the risk of disability later on in life [Citation10–13 ].
It has been shown that aging affects multiple compartments and is associated with many factors including ethnic, cultural and socio-economic factors [Citation14,Citation15]. It is important to conduct research in different population groups to evaluate how physical exercise and aging are associated with changes in body composition. There are relatively few studies on the associations between physical exercise and changes in body composition in Asian populations [Citation16–18 ]. The major difference of these earlier reports was the use of MET-min/week score for the intensity of the physical exercise and the evaluation of relationships of the intensity of exercise with anthropometric parameters and the general and regional body composition in the present study.
There is evidence that the protective potential of exercise may be related to the frequency and intensity of the exercise [Citation19]. Therefore, the present study sought to better understand how different levels of intensity of physical exercise, as a lifestyle habit, in men living in the community, are associated with the whole body and regional changes in bone, lean and fat masses in a cohort of Asian men. A better understanding of the inter-relationship between physical exercise and age-associated changes in body composition in men may help in the formulation of strategies for the management of aging men and help mitigate the ill effects of age-related illnesses.
Subjects, materials and methods
Subjects
This study was approved by the Institutional Review Board of the National University Hospital and each volunteer had given his written informed consent. The method was previously reported [Citation20]. Five hundred thirty-one Singaporean Chinese men, aged between 29 years and 72 years were included in the analyses. As the primary objective of the study was to evaluate the determinants of the natural aging process, only subjects with no known existing or history of major medical illnesses such as cancer, hypertension, thyroid dysfunction, diabetes, osteoporotic fracture and cardiovascular events as well as major sleep disorders including sleep apnoea requiring chronic treatment were included in the study. None of the subjects had a history of erectile dysfunction requiring treatment. On physical examination, none had genital abnormalities. Subjects were not paid for participation. They represented the diverse spectrum of people in Singapore, ranging from those with low to high levels of education, working and non-working men (retirees), and those in various types of vocations [Citation21]. Their profiles were typical in Singapore, which is a highly urbanised city–state with no rural population. Each subject answered a self-administered and investigator-guided questionnaire. Questions asked covered their medical, dietary, social, sex and family histories and other relevant histories regarding consumption of hormones, supplements and medication, types of beverages, smoking, alcohol consumption and engagement in physical exercise.
Methodologies
Exercise scores (MET-min/week).
In contract to our earlier studies [Citation20,Citation22] which scored the physical exercise based on the types, duration and frequency, exercise scoring was based on metabolic equivalents (METs) and the cut offs for light (<3 METS), moderate (3–6 METS) and vigorous (>6 METS) in accordance to the guidelines for Americans [Citation23]. According to the data derived from the self-administered questionnaire, each exercise type is given an exercise score computed as MET-min/week. For example, running and brisk walking were given MET scores of 10 and 4.5, respectively. An individual who ran three times a week and each time for 30 min will have a total MET-min/week of 10 × 3 × 30 = 900. While a person who brisk walked for 30 min and six times per week will have a total MET-min/week of 4.5 × 30 × 6 = 810. Those who did not exercise routinely were given an arbitrary MET-min/week of 0. The exercise intensities were categorised into four MET groups: METGp1 (no habitual exercise MET-min/week, 0), METGp2 (MET-min/week, <500), METGp3 (MET-min/week, 500–1000) and METGp4 (MET-min/week, >1000).
Anthropometric measurements
The bodyweight (Bwt) was measured without shoes using an electronic measuring scale, and height (Ht) to the nearest cm was taken. The body mass index (BMI) was calculated as Bwt in kilogram (kg) divided by the Ht in meter squared. Waist circumference (W) was measured midway between the lower costal margin and iliac crest during the end-expiratory phase [Citation24]. Hip circumference (H) was measured in centimetres. In addition, the waist/hip (W/H) and waist/Ht (W/Ht) ratios were computed as indices of body fat. The comparative usefulness of these anthropometric measures as indices for body fat in an Asian population has been reported by an earlier study [Citation21].
Body composition.
Dual-energy X-ray absorptiometry (DXA) was used for the estimation of the percent body fat (%FM), which has been found by earlier studies to correlate well with other methods including hydrodensitometry and Jackson and Pollock (seven-site) skinfold prediction [Citation25]. Each subject underwent a whole body scan, a spinal scan at the L2–L4, and a scan of the hip using DXA (DPX-L, Lunar Radiation, Madison, WI, USA; software version 1.3z). Percent body fat (%FM) was computed automatically by the DXA scanner using Siri formula-calculation [Citation26]. The average spine at the L2–L4 areal bone mineral density (SaBMD), hip (the proximal femur) areal BMD (HaBMD), and the average (AaBMD), mean of the SaBMD and HaBMD, total bone mineral content (TBMC), total lean mass (TLM), total fat mass (TFM), percent lean mass (%LM), and percent bone mass (%BMC) were computed. Regional distributions of lean and fat masses for the trunk, abdomen, legs and arms were computed from data obtained from the whole body scan.
Handgrip dynamometer.
A handgrip dynamometer was used to for the handgrip strength (Grip) test. The purpose of this test was to measure the maximum isometric strength of the hand and forearm muscles. Handgrip strength is important for any sport in which the hands are used for catching, throwing or lifting. Also, as a general rule, people with strong hands tend to be strong elsewhere, so this test is often used as a general test of strength. Each subject holds the dynamometer in the dominant hand to be tested, with the arm at right angles and the elbow by the side of the body. The handle of the dynamometer was adjusted if required – the base should rest on first metacarpal (heel of palm), while the handle should rest on middle of four fingers. When ready the subject squeezed the dynamometer with maximum isometric effort, which was maintained for about 5 s. No other body movement was allowed. The subject was strongly encouraged to give a maximum effort. Each subject performed the handgrip test three times and the maximum score among the three was used for the analyses. The handgrip strength (Grip) was expressed in kilogram.
Statistical analysis
Statistical analyses were performed using SPSS for windows version 16.0. Multi-regression analyses of age with adjustment for cofounders such as MET-min/week and Bwt with all anthropometric and body composition parameters were carried out. Comparison of means using the Univariate analyses of the General Linear Model coupled with the Least Significant Difference (LSD) as the post hoc test for multiple means were used on continuous measurements with the four MET-groups and where appropriate. Age and Bwt were used as covariates in these analyses.
Results
shows both positive and negative associations between age and various parameters of body composition in the present cohort of healthy Chinese men aged between 29 years and 72 years.
Table I. Linear regression of age with the various anthropometric and body composition parameters.
Bwt and Ht were significantly and negatively associated with age (). The negative association of Ht with age was, in part, contributed by the significant negative association with TBMC and TLM (β = 0.257 and 0.329, respectively), and to a lesser extent by the positive association with TFM (β = 0.096) with p-values of <0.01. In addition, after adjusting for age, Bwt was not significantly associated with the level of physical activities (MET-min/week).
Hip circumference (H) was negatively, while W/H and W/Ht ratios were positively associated with age (). It is interesting to note that while W/H and W/Ht were significantly and positively associated with age, BMI was not ().
Bwt was a covariate in the analyses of the association of age groups with bone, lean and fat masses. Since, participation in regular exercise might be a determinant of body composition, analyses of associations of body composition with age were adjusted for exercise scores (MET-min/week). Bone, lean and fat masses, whether expressed as total or percent mass showed similar association with age. TBMC, %BMC, TLM, %LM were negatively, while TFM and %FM were positively associated with age ().
However, the associations of these lean, bone and fat masses with age do not reveal the association at the regional level. The data showed that SaBMD and AaBMD were not, but HaBMD was significantly and negatively associated with age ().
While TLM showed a negative association with age, the different regional lean masses showed both positive and negative associations with age. Percent trunk lean mass (%TrunkLM) and percent abdominal lean mass (%AbdLM) were positively, while percent arm (%ArmLM) and percent leg (%LegLM) lean mass were negatively associated with age ().
A similar situation existed for fat mass. While TFM was positively associated with age, %TrunkFM and %AbdFM were positively, %LegFM was negatively, while %ArmFM was not associated with age ().
Among the 531 Chinese men in the study, 29.2% did not have a regular exercise regime (METGp1, MET-min/week = 0), 29.2% had light intensity (METGp2, MET-min/week <500), 19.4% had moderate intensity (METGp3, MET-min/week = 500-1000) and 22.2% had vigorous intensity (METGp4, MET-min/week >1000), as a lifestyle habit (). Interestingly, the analyses showed that older men tended to exercise more vigorously than younger men; men in METGp4 were significantly older than those in the other three MET-groups (METGp1-METGp3; ). Chinese men in Singapore who were ≤40 years old (AgeGp1), on an average, exercised the least intense among the four age groups, and exercised less than half as intense as older men >60 years old (). showed that significantly more men in the >60 years age group (AgeGp4) were in the vigorously intense exercise group (METGp4) than all the three younger age groups (AgeGp1–AgeGp3). In addition, significantly more men in the youngest age group (AgeGp1) did not have a regular exercise regime as compared to men >60 years old (AgeGp4) ().
Table II. Univariate analyses of various parameters with the four MET-groups and four age groups.
Table III. Chi-squared analyses of number of men in the four age groups in the four MET-groups.
Regular engagement in physical exercise of sufficient intensity was favourably associated with some anthropometric parameters in the cohort of Chinese men. Hip circumference (H) was significantly bigger in METGp4 as compared to METGp2 and therefore W/H ratios were significantly smaller than those who exercised less intensely or not at all (METGp1 and METGp2) ().
Figure 1. Ht, H and W/H in the four MET-groups.
The average Ht in men who exercised vigorously (METGp4) was significantly higher than those who exercise only lightly (METGp2) (). In addition, multi-regression analyses with age as a covariate, Ht was independently and positively associated with Bwt, TLM, TBMC and TFM and their respective standardised coefficients were 0.52, 0.34, 0.24 and 0.097 (p < 0.02).
It is interesting to note that only men who had vigorous physical exercise (METGp4) were associated with significantly higher TBMC, TLM, SaBMD, HaBMD and AaBMD, but significantly lower TFM than those in the three other exercise groups, METGp1–METGp3 ( and ). Similar trends were noted when body composition were expressed as %BMC, %LM and %FM ().
Figure 2. BMC, TLM and TFM in the four MET-groups.
Figure 3. Mean (±SD) of SaBMD, HaBMD and AaBMD according in the four MET groups.
Figure 4. %BMC, %LM and %FM in the four MET-groups.
Physical exercise was also associated with different trends in regional distribution of body composition. Analyses of regional distribution showed that men in METGp4 were associated with higher TrunkLM, ArmLM and LegLM by 2.3–4.2%, with LegLM being highest, by 4.2% as compared to men who did not exercise routinely (METGp1) (). In addition, men in METGp3, those with moderately intense exercise, were associated with higher LegLM when compared to men in the METGp1 ().
Figure 5. TrunkLM, ArmLM and LegLM in the four MET-groups.
Men in the vigorous exercise group (METGp4) were associated with lower fat masses in the arms, legs, trunk and abdomen, respectively by 10.5, 8.4, 12.7 and 14.4%, when compared to men in METGp1. In addition men in METGp4 were associated with significantly lower TrunkFM and AbdFM than men in both METGp2 and METGp3 (). However, when expressed as percent, exercise was significantly and negatively associated only with %TtrunkFM and %AbdFM. The difference in %TrunkFM and %AbdFM in the METGp4 versus METGp1 was, respectively 0.88% and 0.72% ().
Figure 6. TrunkFM, AbdFM, ArmFM and LegFM in the four MET-groups.
Figure 7. %TrunkFM, %AbdFM in the four MET-groups.
Body composition was significantly associated with handgrip strength (Grip). Since handgrip strength is probably different for different population groups, a normal distribution of the handgrip strength of the cohort of Chinese men in the present study showed that the 25th, 50th and 75th percentiles, respectively, were 33.55, 37.55 and 41.85 kg. Handgrip strength was negatively associated with age and %FM, but was positively associated with %LM, and at the regional level only with %ArmLM ().
Table IV. Regression analyses of handgrip strength (Grip) with body composition parameters with age, Bwt and MET-min/week as covariates.
Discussion
The present study showed that aging in a cohort of Asian Chinese men is both positively and negatively associated with body composition and some anthropometric parameters, confirming what have been shown by other investigators for Caucasians [Citation1–3 ]. In addition, the regional distribution of body composition may be reflective of ill-effects resulting from changes in body composition as men age. While TLM and %LM were negatively associated with age, a different pattern of association was noted at the regional level. Percent TrunkLM and %AbdLM were positively, while %ArmLM and %LegLM were negatively associated with age. In other words, the negative association of TLM and %LM with age was contributed predominantly by the negative association of %ArmLM and %LegLM but not by %TrunkLM and %AbdLM. It would appear that age is associated with lower lean masses in the limbs than other parts of the body. This may be an important observation as frailty and risk of fall relate to strength in the arms and legs. It has been shown in the present study that handgrip strength was positively associated with TLM and %LM, but negatively with TFM and %FM. However, at the regional level, handgrip strength was significantly and positively associated only with %ArmLM. Although no measurement of leg strength was carried out in the present study, handgrip strength may be indicative of general strength of the individual and may represent a more dynamic measurement of muscle function, therefore, be a useful predictor of functional capacity in the elderly. Hence, the observed negative association of LegLM with age, might, in part, contribute to the increase risk of frailty as men age. It would therefore be expedient to include in the management of aging a modality to help build up lean mass and strength training for the limbs and help minimise the risk of frailty as men age.
Conversely, TFM was positively associated with age. As with lean mass, a different pattern of association was noted at the regional level. Percent trunk fat (%TrunkFM) and %AbdFM were positively, while %LegFM was negatively associated with age. It therefore, appears that the positive association of TFM and %FM with age was predominantly due to the positive association in TrunkFM and AbdFM with age. Increase in abdominal fat is known to contribute to the increase risk of a wide range of chronic disorders, including hypercholesterolemia, atherosclerosis, hyperinsulinemia, insulin resistance, non-insulin-dependent diabetes and hypertension [Citation4,Citation5]. On the other hand, the loss of lean mass and fat mass in arms and legs may explain the observation of wrinkling in arms and legs in the elderly.
Total BMC, %BMC and only HaBMD were significantly and negatively associated with age. In fact, the rate of osteopenia of the proximal femur in this cohort of Chinese men was relatively high, >20% (unpublished). It is still unclear why this is so. It might be related to the relatively sedentary lifestyle that the average Singaporean men had. The observation that vigorous physical exercise, men in METGp4, was positively associated with TBMC, % BMC, SaBMD, HaBMD and AaBMD gives credence to this suggestion.
Results of the present study also showed a negative association of Bwt with age. It has been shown that changes in Bwt may also lead to physical dysfunction in older persons, both high and low body weight had been associated with functional difficulties and disability in old age [Citation27–30 ]. While weight gain in older persons is a major risk factor for several diseases and conditions, including diabetes mellitus and coronary artery disease, weight loss in the elderly may be indicative of poor or declining health and is a risk factor for mortality [Citation31]. Therefore, having modalities that proactively address the issue of changes in Bwt and body composition must be an integral component of any aging management programme.
Engagement in regular physical exercise was not common among the cohort of Asian Chinese men in the study. About 58% were either not or engaged in low intensity of physical exercise. In addition, 19.4% had moderately intense, while 22.2% had vigorous physical exercise as a lifestyle habit. As reported in an earlier study [Citation21], Chinese men in the >60 years age group exercise more intensely than younger men. Significantly more men >60 years old were in the METGp4 (vigorous exercise group) than all other age groups below 60 years. In contrast to the 80% of European men above 65 years who were not engaged in strenuous physical exercise [Citation32], about 53.1% of the Chinese men above 60 years old were engaged in moderately to vigorously intense physical exercise. It would appear that older men in Singapore tended to exercise more intensely and regularly than the elderly in the European group. Whether this observation that older men were exercising more vigorously than younger men is true in other Chinese population groups in Asia is not known. This might be a unique feature to the Chinese men in Singapore, as it is a highly urbanised and competitive society where younger men are very focused on career development and raising of a family. Therefore, any extrapolation to other Chinese population groups in Asia must be viewed with caution.
Similar to other studies in Caucasian populations, weight change was independently and inversely predicted by age. In contrast to these studies, however, the present study showed that Bwt was not associated with the level of regular physical exercise [Citation33,Citation34].
The present study showed that regardless of age, regular engagement in physical exercise was associated with beneficial changes in body composition, and could reverse the trend set in by aging. As was recommended by the American College of Sports Medicine and the American Heart Association [Citation19], the present study showed that the intensity level of the physical exercise matters. It appears that most of the favourable associations in body composition were noted in men who exercised vigorously, equivalent to more then 1000 MET-min/week, an observation similar to an earlier study [Citation35]. In several body composition parameters, the favourable associations were noted even against those who were in the METGp2 and METGp3, in other words, maximal benefits were seen in the vigorous exercise group. Therefore, a higher threshold of exercise intensity may be required to trigger the favourable association for most body composition parameters.
While engagement in vigorous exercise has definite positive association with body composition, the converse is probably true. Men who were not engaged in or engaged in low intensity of exercise may be associated with lower lean and higher fat masses, and this scenario is considered a major risk factor for the development of many age-related chronic diseases [Citation36]. In contrast to an earlier study which purported that gain in fat mass is more of a function of a lack of rigorous exercise rather than of age itself [Citation37], the present study showed that higher fat mass, whether, it is whole body fat or abdominal fat, was associated with age and independent of physical exercise. Higher lean masses, TLM, %LM and especially LegLM were associated with regular and intense physical exercise. Higher lean mass coupled with exercise can increase strength in the arms and legs and thereby, may help to reduce the incidence of frailty and prevent fall and fractures which tend to be higher in older men [Citation38–40 ]. Furthermore, physical exercise-associated increase in lean mass in the legs may help to combat wrinkling in the limbs as men age.
This study supports the importance of physical exercise in the prevention of weight gain and unfavourable age-related changes in body fat, especially those in the abdomen, loss of lean mass in the limbs and loss of bone masses in men [Citation41,Citation42] as well as lower mortality [Citation43].
In summary, age is unfavourably associated with Bwt and pattern of body composition. In particular, age is associated with lower lean mass, particularly in the limbs, higher fat mass in the trunk and abdomen. Bone mass as well as areal BMD, especially HaBMD were negatively associated with age. A lifestyle habit of engagement in regular physical exercise of sufficient intensity, above 1000MET-min/week, may be able to negate the age-related negative changes in body composition.
Therefore, we propose that a systematically planned programme for the promotion of engagement in regular physical exercise must be integrated into any management modality of the aging population as was also suggested by earlier investigators [Citation43,Citation44]. The preventive physical exercise programmes should be tailored to the appropriate age groups and the physical exercise must be of sufficient frequency, intensity and duration in order to benefit from the positive effect of physical exercise. However, in order for any preventive programme to work, active education of the public should target in getting the individuals taking ownership of their own well being. Only a strong commitment to stay the course on the exercise programme as a lifestyle habit can the benefits be realised [Citation20].
Acknowledgements
The authors express their sincere thanks to Ms. Helen Mok, Mrs. Baharudin Said, Ms. Eng Sok Kheng and Ms. Poon Peng Cheng for their expert technical input into this study. This study was supported, in part, by fund from the Academic Research Fund of the National University of Singapore. Dr. Victor Goh position in the General Clinical Research Centre at Harbor UCLA Medical Center was supported by the NIH grant (M01-RR0425).
References
- CohnSH., VartskyD, YasumuraS, SawitskyA, ZanziI, VaswaniA, EllisKJ. Compartmental body composition based on total-body, potassium, and calcium. Am J Physiol 1980;239:E524–E530.
- BorkanGA, HultzDE, GerzofSG, RobbinsAH, SilbertCK. Age changes in body composition revealed by computed tomography. Gerontology 1983;38:673–677.
- NovakLP. Aging, total body potassium, fat-free mass, and cell mass in males and females between ages 18 and 85 years. J Gerontol 1972;24:438–459.
- StenholmS, KosterA, AlleyDE, HoustonDK, KanayaA, LeeJS, NewmanAB, SatterfieldS, SimonsickEM, VisserM, et al. Joint association of obesity and metabolic syndrome with incident mobility limitation in older men and women – results from the Health, Aging, and Body Composition Study. J Gerontol A Biol Sci Med Sci 2009;65:84–92.
- YeoSE, HaysNP, DennisRA, KortebeinPM, SullivanDH, EvansWJ, CokerRH. Fat distribution and glucose metabolism in older, obese men and women. J Gerontol A Biol Sci Med Sci 2007;62:1393–1401.
- Di FrancescoV, ZamboniM, ZoicoE, BortolaniA, MaggiS, BissoliL, ZivelonghiA, GuarientoS, BoselloO. Relationships between leisure-time physical activity, obesity and disability in elderly men. Aging Clin Exp Res 2005;17:201–206.
- EbrahimS, WannametheeSG, WhincupP, WalkerM, ShaperAG. Locomotor disability in a cohort of British men: the impact of lifestyle and disease. Int J Epidemiol 2000;29:478–486.
- LandiF, OnderG, CarpenterI, CesariM, SoldatoM, BernabeiR. Physical activity prevented functional decline among frail community-living elderly subjects in an international observational study. J Clin Epidemiol 2007;60:518–524.
- Van den BrinkCL, PicavetH, Van den BosGA, GiampaoliS, NissinenA, KromhoutD. Duration and intensity of physical activity and disability among European elderly men. Disabil Rehabil 2005;27:341–347.
- BerlinJA, ColditzGA. A meta-analysis of physical activity in the prevention of coronary heart disease. Am J Epidemiol 1990;132:612–628.
- ColcombeS, KramerAF. Fitness effects on the cognitive function of older adults: a meta-analytic study. Psychol Sci 2003;14:125–130.
- StampferMJ, HuFB, MansonJE, RimmEB, WillettWC. Primary prevention of coronary heart disease in women through diet and lifestyle. N Engl J Med 2000;343:16–22.
- HuFB, MansonJE, StampferMJ, ColditzG, LiuS, SolomonCG, WillettWC. Diet, lifestyle, and the risk of type 2 diabetes mellitus in women. N Engl J Med 2001;345:790–797.
- SeemanTE, CrimminsE, HuangM-H, SingerB, BucurA, GruenewaldT, BerkmanLF, ReubenDB. Cumulative biological risk and socio-economic differences in mortality: MacArthur Studies of Successful Aging. Soc Sc Med 2004;58:1985–1997.
- ThumbooJ, FongK-Y, MachinD, ChanS-P, SohC-H, LeongK-H, FengP-H, ThioS-T, BoeyM-L. Quality of life in an urban Asian population: the impact of ethnicity and socio-economic status. Soc Sc Med 2003;56:1761–1772.
- KesavachandranC, BihariV, MathurN. Can physical activity maintain normal grades of body mass index and body fat percentage?Int J Yoga 2009;2:26–29. Available from: http://www.ijoy.org.in/text.asp?2009/2/1/26/53839 . Last accessed 13 November 2009.
- FooLH, ZhangQ, ZhuK, MaG, GreenfieldH, FraserDR. Influence of body composition, muscle strength, diet and physical activity on total body and forearm bone mass in Chinese adolescent girls. Br J Nutr 2007;98:1281–1287.
- LeeMM, Wu-WilliamsA, WhittemoreAS, ZhengS, GallagherR, TehC-Z, ZhouL, WangX, ChenK, LingC, et al. Comparison of dietary habits, physical activity and body size among Chinese in North America and China. Int J Epidemiol 1994;23:984–990.
- NelsonME, RejeskiWJ, BlairSN, DuncanPW, JudgeJO, KingAC, MaceraCA, Castaneda-SceppaC. Physical activity and public health in older adults: Recommendation from the American College of Sports Medicine and the American Heart Association. Med Sci Sports Exerc 2007;8:1435–1445.
- GohVHH, TongTYY, MokHPP, SaidB. Interactions among age, adiposity, bodyweight, lifestyle factors and sex steroid hormones in healthy Singaporean Chinese men. Asian J Androl 2007;9:611–621.
- GohVH, TainCF, TongTY, MokHP, WongMT. Are BMI and other anthropometric measures appropriate as indices for obesity? A study in an Asian population. J Lipid Res 2004; 45:1892–1898.
- GohVHH, TongTYY. The association of exercise with sleep, sex steroids, sexual activities and aging in Asian men. J Men's Health 2009;6:317–324.
- Guidelines for physical activities for American. Department of Health and Human Services. et al. http:://www.health.gov/PAguidelines/guidelines/appendix1.aspx . Last accessed 5 November 2009.
- World Health Organization. Physical Status: the use and interpretation of anthropometry. World Health Organ Tech Rep Ser 1995;854:1–452.
- KohrtWM. Preliminary evidence that DEXA provides an accurate assessment of body composition. J Appl Physiol 1998;84:372–377.
- SiriWE. Body composition from fluid spaces and density: analysis of methods. Nutrition 1993;9:480–491.
- EnsrudKE, NevittMC, YunisC, CauleyJA, SeeleyDG, FoxKM, CummingsSR. Correlates of impaired function in older women. J Am Geriatr Soc 1994;42:481–489.
- GalanosAN, PieperCF, Cornoni-HuntleyJC, BalesCW, FillenbaumGG. Nutrition and function: Is there a relationship between body mass index and the functional capabilities of community-dwelling elderly?J Am Geriatr Soc 1994;42:368–373.
- HarrisT, KovarMG, SuzmanR, KleinmanJC, FeldmenJJ. Longitudinal study of physical ability in the oldest-old. Am J Public Health 1989;79:698–702.
- LaunerLJ, HarrisT, RumpelC, MadansJ. Body mass index, weight change, and risk of mobility disability in middle-aged and older women. The epidemiologic follow-up study of NHANES I. JAMA 1994;271:1093–1098.
- FischerJ, JohnsonMA. Low body weight and weight loss in the aged. J Am Diet Assoc 1990;90:1697–1706.
- SchuitAJ. Physical activity, body composition and healthy ageing. Sci Sports 2006;21:209–213.
- HughesVA, FronteraWR, RoubenoffR, EvansWJ, SinghMA. Longitudinal changes in body composition in older men and women: role of body weight change and physical activity. Am J Clin Nutr 2002;76:473–481.
- NooyensAC, VisscherTL, SchuitAJ, van RossumCT, VerschurenWM, van MechelenW, SeidellJC. Effects of retirement on lifestyle in relation to change in weight and waist circumference in Dutch men: a prospective study. Public Health Nutr 2005;8:1266–1274.
- CokerRH, WilliamsRH, KortebeinPM, SullivanDH, EvansWJ. Influence of exercise intensity on abdominal fat and adiponectin in elderly adults. Metab Syndr Relat Disord 2009;7:363–368.
- Bortz WM 2nd. The disuse syndrome. West J Med 1984;141:691–694.
- MeredithCN, ZackinMJ, FronteraWR, EvansWJ. Body composition and aerobic capacity in young and middle-aged endurance-trained men. Med Sci Sports Exerc 1987;19:557–563.
- CampbellWW, CrimMC, YoungVR, EvansWJ. Increased energy requirements and body composition changes with resistance training in older adults. Am J Clin Nutr 1994;60:167–175.
- CampbellWW, CrimMC, YoungVR, JosephLJ, EvansWJ. Effects of resistance training and dietary protein intake on protein metabolism in older adults. Am J Physiol Endocrinol Metab 1995;31:E1143–E1153.
- CampbellWW, JosephLJ, DaveySL, Cyr-CampbellD, AndersonRA, EvansWJ. Effects of resistance training and chromium picolinate on body composition and skeletal muscle in older men. J Appl Physiol 1999;86:29–39.
- EkelundU, BrageS, FranksPW, HenningsS, EmmsS, WongMY, WarehamNJ. Physical activity energy expenditure predicts changes in body composition in middle-aged healthy whites: effect modification by age. Am J Clin Nutr 2005;81:964–969.
- BocaliniDS, SerraAJ, dos SantosL, MuradN, LevyRF. Strength training preserves the bone mineral density of postmenopausal women without hormone replacement therapy. J Aging Health 2009;21:519–527.
- KahnEB, RamseyLT, BrownsonRC, HealthGW, HowzeEH, PowellKE, StoneEJ, RajabMW, CorsoP. The effectiveness of interventions to increase physical activity. A systematic review. Am J Prev Med 2002;22:73–107.
- EvansWJ, Cyr-CampbellD. Nutrition, exercise and healthy aging. J Am Diet Assoc 1997;97:632–638.