Biogerontology DOI 10.1007/s10522-015-9582-z
RESEARCH ARTICLE
Nonlinear relationship between waist to hip ratio, weight and strength in elders: is gender the key? ´ ngeles de la Torre . Solange Amor . Carmen Castillo . Jose´ A. Carnicero . Mari A Amelia Guadalupe-Grau . Leocadio Rodrı´guez-Man˜as . Francisco J. Garcı´a-Garcı´a
Received: 11 January 2015 / Accepted: 7 May 2015 Springer Science+Business Media Dordrecht 2015
Abstract Visceral fat has a high metabolic activity with deleterious effects on health contributing to the risk for the frailty syndrome. We studied the association between waist to hip ratio (an indirect measure of visceral fat stores) on upper and lower extremities strength. 1741 individuals aged C65 participated in this study. The data was obtained from the Toledo Study for Healthy Aging. For each gender, we studied the relationship between the waist-to-hip ratio (WHR), body mass index (BMI) and regional muscle strength (grip, shoulder, knee and hip) using multivariate linear regression and kernel regression statistical models. WHR was higher in men than in women (0.98 ± 0.07 vs. 0.91 ± 0.08, respectively, P \ 0.05). In women with high WHR, we observed a decrease in strength especially in those with a normal BMI. As the WHR lowered, the strength increased regardless of the BMI. In men, lower strength was generally related to the lowest and highest WHR’s. Maximum strength in men corresponded at a WHR around 1 and the highest BMI. Muscle strength depends on the joined distribution of WHR and BMI according to gender. In consequence, ´ . de la Torre C. Castillo J. A. Carnicero M. A S. Amor A. Guadalupe-Grau (&) F. J. Garcı´a-Garcı´a Geriatrics Department, Hospital Virgen del Valle, Toledo, Spain e-mail: [email protected] L. Rodrı´guez-Man˜as Geriatrics Department, Hospital Universitario de Getafe, 45071 Madrid, Spain
sex, WHR and BMI should be analyzed conjointly to study the relationship among fat distribution, weight and muscle strength. Keywords Body composition Sarcopenia Abdominal obesity Frailty Strength
Introduction Frailty syndrome is known as a wasting syndrome related to hormonal and inflammatory changes in ageing. This is a critical age-related disorder within the older population (Garcı´a-Garcı´a et al. 2011) precursor of disability and susceptible to treatment (Boockvar and Meier 2006). Since the frailty syndrome has adverse consequences, such as higher morbidity, mortality and lower quality of life, there has been extensive research trying to understand the mechanisms undergoing this condition. According to the definition developed by Fried et al. (2001), sarcopenia, which is defined as the loss of muscle mass and strength that occurs with aging plays a major role in frailty. On the other hand, obesity is a matter of concern all over the world, and its prevalence is still increasing in the old population (Gomez-Cabello et al. 2011). In the last years, obesity and in particular visceral fat accumulation have been associated with the development of frailty syndrome and sarcopenia. Visceral fat
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accumulation causes deregulation of adipocyte function (Wisse 2004; Greenberg and Obin 2006; Matsuzawa 2006) leading to a pro-inflammatory state that increases the risk for the development of sarcopenia and frailty (Pou et al. 2007; Phillips and Prins 2008). The body mass index (BMI) is the most widely used measurement for obesity in all age groups; therefore, since the concept of the ‘‘fat frail’’ was established, studies have used BMI to assess the relationship between frailty and obesity. However, the ageing process is accompanied by an increase and redistribution of body fat, and this distribution is different in men and women (Prentice and Jebb 2001). Therefore, it seems necessary to explore other useful techniques, such as the waist circumference, in order to identify individuals with high visceral adiposity in this specific population. In fact, individuals with high waist circumference and the same BMI are more likely to be frail (Hubbard et al. 2010). However, there are studies that emphasize the importance of body fat distribution, rather than BMI or waist circumference alone, to determine the cardiovascular risk, which is closely related to frailty. In these studies the waist-to-hip ratio (WHR) is used, because as the abdominal fat increases, the waist circumference increases relative to the hip girth (Larsson et al. 1984). Several studies show that simple anthropometric measurements such as waist circumference or WHR can be used as indirect measurements of visceral fat accumulation and body fat distribution, if more accurate techniques such as MRI, CT scan or DXA are not available (Van Der Kooy and Seidell 1993; Turcato et al. 2000; Despre´s et al. 1991; Van Der Kooy et al. 1992). It is known that an increase in visceral fat may affect the skeletal muscle by multiple pathways (hormonal changes, inflammatory state, local deposits of fat) (Zamboni et al. 2008), causing sarcopenia; so visceral fat could be an important cause of frailty. Men tend to have central obesity (visceral fat) and women gynoid obesity (subcutaneous fat). This difference in body fat distribution might affect the muscle and, therefore, the muscle strength in different ways, since it is the visceral fat, and not the subcutaneous fat accumulation, the one more strongly associated to the inflammation with deleterious effects on health (Zamboni et al. 2005). Therefore, the aim of this study was to test the influence of the WHR (as a surrogate measurement of body fat distribution) on upper and lower extremity muscle strength studying men and women separately.
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Methods and procedures Study design and participants Data were taken from the baseline assessment of the Toledo Study for Healthy Aging (TSHA), a population-based longitudinal study of institutionalized and community dwelling Caucasian individuals aged 65 years and older, residing in the province of Toledo (Spain) whose method has been reported elsewhere (Garcı´a-Garcı´a et al. 2001). The TSHA is approved by the local ethics committee (CEIC). The selection of the study participants, and the data collection at baseline, were conducted from June 2006 to September 2009. All participants signed a written informed consent before the start of study. The data was collected in three stages. The first one, was an interview; the second stage, a clinical and physical performance examination; and the third stage, a blood sample taken while fasting. Measurements Muscle strength Upper- (grip and shoulder abduction) and lower-limbs (knee extensors and hip flexors) maximal voluntary isometric strength was measured in kg in all subjects using a hydraulic hand dynamometer (Jamar Preston, Jackson, MI, USA) and a manual muscle test system (Lafayette, Ind, USA), being the error of measurement 0.1 kg and 0.2 kg respectively for each systems. All measurements were gathered using international standard procedures (Ottenbacher et al. 2002). The subjects could do three repetitions all the results were noted, but only the best result was registered. • •
•
Grip With subject in a sitting position, he/she pressed the dynamometer with the dominant hand. Shoulder abduction With the subject in a sitting and the interviewer behind the subject, the interviewer placed the dynamometer on the external side of the subject´s arm. Then the subject was told to raise the arm. Hip flexion With the subject in a sitting position, knees at 90, the interviewer was kneeling next to the subject and placed the dynamometer on the anterior side of the thigh right above the knee, then the subject had to push up the thigh.
Biogerontology
•
Knee extension With the subject in the sitting position, the interviewer kneeling next to the subject. The subject had one knee flexed at 908, and the one that is going to be explored flexed at an angle right below 1808. The interviewer placed the dynamometer in the anterior side of the leg just above the ankle and asked the subject to extend the knee to 1808.
Anthropometrics Waist and hip circumferences were measured in centimeters with a metric band to the nearest millimeter. The metric band was placed horizontally just below the 12th rib and over the iliac crest. The hip circumference measurement was taken at the point yielding the maximum circumference over the buttocks, with the tape held in a horizontal plane. Waist-hip ratio was calculated by dividing waist circumference (cm) by hip circumference (cm). Height was measured using a stadiometer (Medizintechnik seit 1890, KaWe, Germany) and weight was measured with a SECA precision scale (SECA 884 floor scale, Germany). BMI was calculated as weight (kg) divided by height2 (m2). Comorbidity Comorbidity data was collected from medical diagnoses and the information given by the participant. We considered ischemic heart disease, peripheral vascular disease, syncopal episodes, hypertension, diabetes, high cholesterol, chronic obstructive pulmonary disease-COPD, peptic ulcer disease, fractures, osteoporosis, osteoarthritis, dementia, Parkinson disease, and thyroid disease between others. Statistical analysis Descriptive data are presented as mean values (SD). Baseline characteristics between men and women were compared using t student tests. Normality of data was checked using the Kolmogorov–Smirnov test. When the data did not meet parametric criteria, the comparisons were made using non-parametric tests (Mann–Whitney). The associations of shoulder, grip, hip and knee strength with waist to hip ratio and BMI were assessed using multivariate linear regression models, including age as possible confounder. In order to model the nonlinear behavior and identified critical
changes in the curves slopes, two or three cutoff points for the WHR and the interactions of the WHR variables with BMI were included within the model (May and Bigelow 2006). Additionally, a nonparametric kernel regression model with the same variables (age, WHR and BMI) was assessed in order to both generalize the parametric model and describe the results in an easier way. All analyses were carried for men and women, separately. Analyses were made with the Statistical Package R for windows (Vienna, Austria) (http://www.r-project.org), version 2.15.2. P value was set at level \ 0.05.
Results The TSHA sample consisted of 2488 individuals aged 65 years and older. All of them participated in the interview corresponding to the first stage of the study and 1972 participated in the physical examination. For the purpose of this study, we included those subjects who participated in the first and second stage who had BMI, waist and hip circumferences and upper and lower extremities strength. We excluded individuals with severe liver and renal disease, severe dementia, rheumatologic diseases and subjects who used corticosteroids chronically. After applying our exclusion and inclusion criteria, from the 1972 individuals who participated in the interview and physical exam, we ended up with 1741 individuals (56.1 % women) with a mean age of 75.2 ± 6.1 (Table 1). Men had higher WHR and lower BMI than women (P \ 0.05). Men also had higher strengths than women (P \ 0.05) (Table 1). Tables 2 and 3 show the results for the multivariate linear regression models for men and women, respectively. We obtained several cut off points for WHR and analyzed the interaction with BMI. We found that the overall interaction between BMI and WHR was not significant, whereas the interaction between BMI and WHR in each cut off point was significant indicating relevant changes (proportional to BMI) in the curves slopes at the cut off points. The changes were critical in men in whom we observed shifts in the slopes, while in women they were more smoothed. The explanation for this was that the relationship between strength, WHR and BMI was not linear; therefore we performed a kernel regression model in order to analyze the joined effect of both variables (BMI and WHR) on the muscle
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Biogerontology Table 1 Descriptive characteristics of the participants stratified by sex
Men (n = 764) Mean ± SD Age (years)
75.1 ± 5.8
75.2 ± 6.1
Height (cm)
164.1 ± 6.9
151.9 ± 6.4
76.1 ± 11.9 28.2 ± 3.9
69.3 ± 12.3 30.0 ± 5.0
Waist circumference (cm)
102.4 ± 10.3
99.0 ± 12.0
Hip circumference (cm)
105.0 ± 8.3
109.5 ± 10.9
Weight (kg) BMI (kg/m2)
WHR
0.98 ± 0.07
0.91 ± 0.08
Shoulder strength (kg)
19.1 ± 10.5
11.3 ± 6.2
Grip strength (kg)
28.8 ± 8.9
16.7 ± 5.9
Leg strength (kg)
22.8 ± 12.3
16.3 ± 9.5
Knee strength (kg)
15.4 ± 7.8
11.7 ± 6.6
PASE
69.3 ± 53.7
68.5 ± 40.8
MMSE
24.5 ± 4.1
23.5 ± 4.5
GDS
1.8 ± 2.1
3.1 ± 3.2
Charlson Index
1.1 ± 1.5
1.2 ± 1.7
%
* P value \ 0.05, value \ 0.001
P
BMI body mass index; WHR wais-hip ratio; MMSE mini mental state examination; PASE physical activity scale for the elderly; DGS geriatric depression scale; DM diabetes mellitus; ADL activities of daily living; IADL instrumental activities of daily living
%
DM
20.8
19.7
Hypertension
42.9
54.3
Myocardial infarction
8.9
4.0
Cardiac insufficiency
4.4
4.6
Angina pectoris
6.0
5.7
Cerebrovascular disease
5.2
3.3
Cancer
1.9
2.3
Robust
48.2
46.6
Pre-frail Frail
43.9 7.9
43.0 10.4
ADL dependency
12.7
23.4
IADL dependency
69.0
47.5
Frailty status
Educational level None
63.51
66.94*
Primary school
16.36
19.18*
Cprimary
20.13
13.88*
strength. Figures 1 and 2 show the kernel regression estimates as both a smoother generalization and a more interpretable model than the parametric one for men and women respectively. In men, the distribution of strength, BMI and WHR together shows different shapes. On one hand, hip, shoulder and knee strength have a bell shape distribution, sharp for the shoulder and hip and flattened for the knee. On the other hand, grip strength shows a more uniform distribution (Fig. 1). In general, we see an increase in strength as
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Women (n = 977) Mean ± SD
the BMI goes up, especially with the WHR around 1 (0.95–1.10). Lower strength was obtained with WHR [ 1.2 and BMI [ 30 kg/m2, as well as in subjects with WHR \ 0.9 and BMI \ 30 kg/m2. In women, the distribution of the strength, WHR and BMI behaves in a different way compared to men. In particular, as the WHR went down, the strength of every test increased regardless of the BMI. Maximum strength was found with WHR \ 0.9 and BMI between 25 and 35 kg/m2. In women with WHR [ 1.05 we
Biogerontology Table 2 Multivariate regression model estimates in men Muscle Strength Variable
Shoulder Cutoff point
Grip Beta
Hip
P value
Cutoff point
Beta
P value
Cutoff point
Knee Beta
P value
Cutoff point
Beta
P value
0.002
BMI–WHR-cutoff1
1.019
-48.8
0.033
0.948
-201.6
0.026
1.054
94.9
0.007
0.909
-256.4
BMI–WHR-cutoff2
1.042
141.7
0.005
0.952
212.0
0.023
1.073
-142.1
0.005
0.917
353.5
0.002
BMI–WHR-cutoff3
1.061
-126.4
0.002
1.007
-20.4
0.042
1.186
-188.6
0.262
0.933
-104.1
0.006
2.9
0.191
3.7
0.319
-2.2
0.302
6.7
0.315
BMI–WHR
The three cutoff points shown for the WHR–BMI interaction correspond to critical changes in the curves slopes in the interaction between WHR, BMI and strength
Table 3 Multivariate regression model estimates in women Muscle strength Variable
Shoulder
BMI–WHR-cutoff1
0.794
43.1
BMI–WHR-cutoff2
0.825
-22.4 -21.7
0.161
BMI–WHR
Cutoff point
Grip Beta
P value
Hip
Knee
Cutoff point
Beta
P value
Cutoff point
Beta
P value
Cutoff point
Beta
P value
0.050
0.890
-8.3
0.028
0.798
63.4
0.009
0.938
8.3
0.021
0.829
-34.8
0.053
0.838
-37.4
0.037
0.012
0.851
31.1
2.5
0.103
-29.7
0.169
0.037
7.2
0.127
The three cutoff points shown for the WHR–BMI interaction correspond to critical changes in the curves slopes in the interaction between WHR, BMI and strength
observed a decrease in strength especially in those with a BMI \ 30 kg/m2 (Fig. 2).
Discussion In this study we aimed to investigate the relationship between WHR, BMI and upper and lower extremities muscle strength. The main findings are: (1) there is a non-linear relationship between BMI, WHR and muscle strength; (2) This relationship shows dramatic differences between sexes; (3) Muscle strength depends on the joined distribution of BMI and WHR and should not be interpreted separately. We used simple anthropometric measurements as surrogates of body fat distribution and accumulation (Turcato et al. 2000; Despre´s et al. 1991; Van Der Kooy et al. 1992). Maximum strength in men was present with WHR around 1 and BMI above 30 kg/m2. This represented an obese population with fat distributed homogenously over their body. The explanation for this finding may be that this group of men had an enhancement in fat free mass (FFM) as the BMI increased, with a subsequent improvement in muscle mass and isotonic
strength (backpack effect) (Lafortuna et al. 2005, 2004). Decreased strength in men was seen with high WHR in obese men, and low WHR in overweight and obese men. These findings showed a possible deleterious effect on strength when fat accumulated in both the abdomen and the hips in obese and overweight men. Visceral fat has been shown to lead to sarcopenia and frailty and this explains why men with more central obesity have less strength (Pou et al. 2007, Phillips and Prins 2008). Obese and overweight men with gynoid obesity have less strength. Although we do not include blood analysis results in this study or body physiognomy analysis, we hypothesize that this finding could be due to hypogonadism (Dhindsa et al. 2007). Maximum strength in women was found with low WHR and high BMI, which represents a population with gynoid obesity, which may have a protective effect in obese women (Fan and Farrell 2008, Rodrı´guez et al. 2007, Vega et al. 2007). Decreased strength was seen in overweight women with high WHR, therefore they were overweight females with fat accumulated in the abdomen. At some point, the peripheral subcutaneous fat storage capacity is maximized and the fat starts to accumulate in the abdomen
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Fig. 1 Kernel regression estimates in men. Three dimensional axis represent strength (kg), WHR, and BMI (kg/m2)
Fig. 2 Kernel regression estimates in women. Three dimensional axis represent strength (kg), WHR, and BMI (kg/m2)
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and other locations such as muscle, pancreas, liver (Despre´s et al. 2008, Krssak et al. 1999, Britton and Fox 2011), with worse consequences for women (Ibrahim 2010, Fox et al. 2007, Cornier et al. 2011). As we mentioned above, these differences between genders may be partially explained by the differences in the body fat distribution, but there may be also a hormonal and genetic explanation. (Llopis et al. 1998; Rissanen et al. 1999; Roelen et al. 1996; Fryburg and Barret 1993; Fox et al. 2012; Zillikenset al. 2008). This study may help future research in assessing patient at risk for frailty, since obese individuals are at higher risk for frailty (Blaum et al. 2005). But the BMI is not the best measurement for obesity in the elderly due to the change in body composition they go through. (Prentice and Jebb 2001). It is necessary to use other measurements of fat distribution such as WHR. We show that in the elderly both the BMI and the WHR (as an indirect measurement of fat distribution) should be assessed together, in order to evaluate muscle strength or sarcopenia, and therefore, frailty. This study may be clinically relevant for future research focused on finding simple way to evaluate the risk of frailty in clinical practice, and consequently, initiate prevention such as diet and exercise (Villareal et al. 2006). There are several limitations in this study that may affect the inferences derived from these data. First, because the results are cross-sectional, a cause-and-effect relationship between strength, BMI and WHR can only be suggested. Second, since the subjects of our study were Caucasians, living in Toledo and with high BMI, these results cannot be generalized to other populations or other races or ethnic groups. Another limitation is that we used indirect techniques to assess body fat distribution such as anthropometric measurements. The main strength of this investigation is the sample size, which allows us to have very accurate results. Another strength is the fact that we measured the strength in all the extremities, which let us see the different behavior between upper and lower extremities, combined with several body composition measurements to assess weight and body fat distribution. In conclusion, the relationship between strength and body composition parameters is more complex than we thought. BMI, body fat distribution and gender have to be evaluated together (Chaston and Dixon 2008).
Acknowledgments All authors have contributed equally to the work and have read and agree to the submission of the paper. This study was funded by Grants PI031558, PI07/90637, PI07/ 90306, RD 06/0013, and RD12/0043 from the Instituto de Salud Carlos III (Ministerio de Economı´a y Competitividad), 03031-00 from Instituto de Ciencias de la Salud (Consejerı´a de Sanidad de Castilla la Mancha), Spain, and FP7-305483-2 from the FP7-Health-2012-Innovation of the European Union. Conflict of interest The authors declare that they have no conflict of interest.
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RESEARCH ARTICLE
Nonlinear relationship between waist to hip ratio, weight and strength in elders: is gender the key? ´ ngeles de la Torre . Solange Amor . Carmen Castillo . Jose´ A. Carnicero . Mari A Amelia Guadalupe-Grau . Leocadio Rodrı´guez-Man˜as . Francisco J. Garcı´a-Garcı´a
Received: 11 January 2015 / Accepted: 7 May 2015 Springer Science+Business Media Dordrecht 2015
Abstract Visceral fat has a high metabolic activity with deleterious effects on health contributing to the risk for the frailty syndrome. We studied the association between waist to hip ratio (an indirect measure of visceral fat stores) on upper and lower extremities strength. 1741 individuals aged C65 participated in this study. The data was obtained from the Toledo Study for Healthy Aging. For each gender, we studied the relationship between the waist-to-hip ratio (WHR), body mass index (BMI) and regional muscle strength (grip, shoulder, knee and hip) using multivariate linear regression and kernel regression statistical models. WHR was higher in men than in women (0.98 ± 0.07 vs. 0.91 ± 0.08, respectively, P \ 0.05). In women with high WHR, we observed a decrease in strength especially in those with a normal BMI. As the WHR lowered, the strength increased regardless of the BMI. In men, lower strength was generally related to the lowest and highest WHR’s. Maximum strength in men corresponded at a WHR around 1 and the highest BMI. Muscle strength depends on the joined distribution of WHR and BMI according to gender. In consequence, ´ . de la Torre C. Castillo J. A. Carnicero M. A S. Amor A. Guadalupe-Grau (&) F. J. Garcı´a-Garcı´a Geriatrics Department, Hospital Virgen del Valle, Toledo, Spain e-mail: [email protected] L. Rodrı´guez-Man˜as Geriatrics Department, Hospital Universitario de Getafe, 45071 Madrid, Spain
sex, WHR and BMI should be analyzed conjointly to study the relationship among fat distribution, weight and muscle strength. Keywords Body composition Sarcopenia Abdominal obesity Frailty Strength
Introduction Frailty syndrome is known as a wasting syndrome related to hormonal and inflammatory changes in ageing. This is a critical age-related disorder within the older population (Garcı´a-Garcı´a et al. 2011) precursor of disability and susceptible to treatment (Boockvar and Meier 2006). Since the frailty syndrome has adverse consequences, such as higher morbidity, mortality and lower quality of life, there has been extensive research trying to understand the mechanisms undergoing this condition. According to the definition developed by Fried et al. (2001), sarcopenia, which is defined as the loss of muscle mass and strength that occurs with aging plays a major role in frailty. On the other hand, obesity is a matter of concern all over the world, and its prevalence is still increasing in the old population (Gomez-Cabello et al. 2011). In the last years, obesity and in particular visceral fat accumulation have been associated with the development of frailty syndrome and sarcopenia. Visceral fat
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accumulation causes deregulation of adipocyte function (Wisse 2004; Greenberg and Obin 2006; Matsuzawa 2006) leading to a pro-inflammatory state that increases the risk for the development of sarcopenia and frailty (Pou et al. 2007; Phillips and Prins 2008). The body mass index (BMI) is the most widely used measurement for obesity in all age groups; therefore, since the concept of the ‘‘fat frail’’ was established, studies have used BMI to assess the relationship between frailty and obesity. However, the ageing process is accompanied by an increase and redistribution of body fat, and this distribution is different in men and women (Prentice and Jebb 2001). Therefore, it seems necessary to explore other useful techniques, such as the waist circumference, in order to identify individuals with high visceral adiposity in this specific population. In fact, individuals with high waist circumference and the same BMI are more likely to be frail (Hubbard et al. 2010). However, there are studies that emphasize the importance of body fat distribution, rather than BMI or waist circumference alone, to determine the cardiovascular risk, which is closely related to frailty. In these studies the waist-to-hip ratio (WHR) is used, because as the abdominal fat increases, the waist circumference increases relative to the hip girth (Larsson et al. 1984). Several studies show that simple anthropometric measurements such as waist circumference or WHR can be used as indirect measurements of visceral fat accumulation and body fat distribution, if more accurate techniques such as MRI, CT scan or DXA are not available (Van Der Kooy and Seidell 1993; Turcato et al. 2000; Despre´s et al. 1991; Van Der Kooy et al. 1992). It is known that an increase in visceral fat may affect the skeletal muscle by multiple pathways (hormonal changes, inflammatory state, local deposits of fat) (Zamboni et al. 2008), causing sarcopenia; so visceral fat could be an important cause of frailty. Men tend to have central obesity (visceral fat) and women gynoid obesity (subcutaneous fat). This difference in body fat distribution might affect the muscle and, therefore, the muscle strength in different ways, since it is the visceral fat, and not the subcutaneous fat accumulation, the one more strongly associated to the inflammation with deleterious effects on health (Zamboni et al. 2005). Therefore, the aim of this study was to test the influence of the WHR (as a surrogate measurement of body fat distribution) on upper and lower extremity muscle strength studying men and women separately.
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Methods and procedures Study design and participants Data were taken from the baseline assessment of the Toledo Study for Healthy Aging (TSHA), a population-based longitudinal study of institutionalized and community dwelling Caucasian individuals aged 65 years and older, residing in the province of Toledo (Spain) whose method has been reported elsewhere (Garcı´a-Garcı´a et al. 2001). The TSHA is approved by the local ethics committee (CEIC). The selection of the study participants, and the data collection at baseline, were conducted from June 2006 to September 2009. All participants signed a written informed consent before the start of study. The data was collected in three stages. The first one, was an interview; the second stage, a clinical and physical performance examination; and the third stage, a blood sample taken while fasting. Measurements Muscle strength Upper- (grip and shoulder abduction) and lower-limbs (knee extensors and hip flexors) maximal voluntary isometric strength was measured in kg in all subjects using a hydraulic hand dynamometer (Jamar Preston, Jackson, MI, USA) and a manual muscle test system (Lafayette, Ind, USA), being the error of measurement 0.1 kg and 0.2 kg respectively for each systems. All measurements were gathered using international standard procedures (Ottenbacher et al. 2002). The subjects could do three repetitions all the results were noted, but only the best result was registered. • •
•
Grip With subject in a sitting position, he/she pressed the dynamometer with the dominant hand. Shoulder abduction With the subject in a sitting and the interviewer behind the subject, the interviewer placed the dynamometer on the external side of the subject´s arm. Then the subject was told to raise the arm. Hip flexion With the subject in a sitting position, knees at 90, the interviewer was kneeling next to the subject and placed the dynamometer on the anterior side of the thigh right above the knee, then the subject had to push up the thigh.
Biogerontology
•
Knee extension With the subject in the sitting position, the interviewer kneeling next to the subject. The subject had one knee flexed at 908, and the one that is going to be explored flexed at an angle right below 1808. The interviewer placed the dynamometer in the anterior side of the leg just above the ankle and asked the subject to extend the knee to 1808.
Anthropometrics Waist and hip circumferences were measured in centimeters with a metric band to the nearest millimeter. The metric band was placed horizontally just below the 12th rib and over the iliac crest. The hip circumference measurement was taken at the point yielding the maximum circumference over the buttocks, with the tape held in a horizontal plane. Waist-hip ratio was calculated by dividing waist circumference (cm) by hip circumference (cm). Height was measured using a stadiometer (Medizintechnik seit 1890, KaWe, Germany) and weight was measured with a SECA precision scale (SECA 884 floor scale, Germany). BMI was calculated as weight (kg) divided by height2 (m2). Comorbidity Comorbidity data was collected from medical diagnoses and the information given by the participant. We considered ischemic heart disease, peripheral vascular disease, syncopal episodes, hypertension, diabetes, high cholesterol, chronic obstructive pulmonary disease-COPD, peptic ulcer disease, fractures, osteoporosis, osteoarthritis, dementia, Parkinson disease, and thyroid disease between others. Statistical analysis Descriptive data are presented as mean values (SD). Baseline characteristics between men and women were compared using t student tests. Normality of data was checked using the Kolmogorov–Smirnov test. When the data did not meet parametric criteria, the comparisons were made using non-parametric tests (Mann–Whitney). The associations of shoulder, grip, hip and knee strength with waist to hip ratio and BMI were assessed using multivariate linear regression models, including age as possible confounder. In order to model the nonlinear behavior and identified critical
changes in the curves slopes, two or three cutoff points for the WHR and the interactions of the WHR variables with BMI were included within the model (May and Bigelow 2006). Additionally, a nonparametric kernel regression model with the same variables (age, WHR and BMI) was assessed in order to both generalize the parametric model and describe the results in an easier way. All analyses were carried for men and women, separately. Analyses were made with the Statistical Package R for windows (Vienna, Austria) (http://www.r-project.org), version 2.15.2. P value was set at level \ 0.05.
Results The TSHA sample consisted of 2488 individuals aged 65 years and older. All of them participated in the interview corresponding to the first stage of the study and 1972 participated in the physical examination. For the purpose of this study, we included those subjects who participated in the first and second stage who had BMI, waist and hip circumferences and upper and lower extremities strength. We excluded individuals with severe liver and renal disease, severe dementia, rheumatologic diseases and subjects who used corticosteroids chronically. After applying our exclusion and inclusion criteria, from the 1972 individuals who participated in the interview and physical exam, we ended up with 1741 individuals (56.1 % women) with a mean age of 75.2 ± 6.1 (Table 1). Men had higher WHR and lower BMI than women (P \ 0.05). Men also had higher strengths than women (P \ 0.05) (Table 1). Tables 2 and 3 show the results for the multivariate linear regression models for men and women, respectively. We obtained several cut off points for WHR and analyzed the interaction with BMI. We found that the overall interaction between BMI and WHR was not significant, whereas the interaction between BMI and WHR in each cut off point was significant indicating relevant changes (proportional to BMI) in the curves slopes at the cut off points. The changes were critical in men in whom we observed shifts in the slopes, while in women they were more smoothed. The explanation for this was that the relationship between strength, WHR and BMI was not linear; therefore we performed a kernel regression model in order to analyze the joined effect of both variables (BMI and WHR) on the muscle
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Biogerontology Table 1 Descriptive characteristics of the participants stratified by sex
Men (n = 764) Mean ± SD Age (years)
75.1 ± 5.8
75.2 ± 6.1
Height (cm)
164.1 ± 6.9
151.9 ± 6.4
76.1 ± 11.9 28.2 ± 3.9
69.3 ± 12.3 30.0 ± 5.0
Waist circumference (cm)
102.4 ± 10.3
99.0 ± 12.0
Hip circumference (cm)
105.0 ± 8.3
109.5 ± 10.9
Weight (kg) BMI (kg/m2)
WHR
0.98 ± 0.07
0.91 ± 0.08
Shoulder strength (kg)
19.1 ± 10.5
11.3 ± 6.2
Grip strength (kg)
28.8 ± 8.9
16.7 ± 5.9
Leg strength (kg)
22.8 ± 12.3
16.3 ± 9.5
Knee strength (kg)
15.4 ± 7.8
11.7 ± 6.6
PASE
69.3 ± 53.7
68.5 ± 40.8
MMSE
24.5 ± 4.1
23.5 ± 4.5
GDS
1.8 ± 2.1
3.1 ± 3.2
Charlson Index
1.1 ± 1.5
1.2 ± 1.7
%
* P value \ 0.05, value \ 0.001
P
BMI body mass index; WHR wais-hip ratio; MMSE mini mental state examination; PASE physical activity scale for the elderly; DGS geriatric depression scale; DM diabetes mellitus; ADL activities of daily living; IADL instrumental activities of daily living
%
DM
20.8
19.7
Hypertension
42.9
54.3
Myocardial infarction
8.9
4.0
Cardiac insufficiency
4.4
4.6
Angina pectoris
6.0
5.7
Cerebrovascular disease
5.2
3.3
Cancer
1.9
2.3
Robust
48.2
46.6
Pre-frail Frail
43.9 7.9
43.0 10.4
ADL dependency
12.7
23.4
IADL dependency
69.0
47.5
Frailty status
Educational level None
63.51
66.94*
Primary school
16.36
19.18*
Cprimary
20.13
13.88*
strength. Figures 1 and 2 show the kernel regression estimates as both a smoother generalization and a more interpretable model than the parametric one for men and women respectively. In men, the distribution of strength, BMI and WHR together shows different shapes. On one hand, hip, shoulder and knee strength have a bell shape distribution, sharp for the shoulder and hip and flattened for the knee. On the other hand, grip strength shows a more uniform distribution (Fig. 1). In general, we see an increase in strength as
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Women (n = 977) Mean ± SD
the BMI goes up, especially with the WHR around 1 (0.95–1.10). Lower strength was obtained with WHR [ 1.2 and BMI [ 30 kg/m2, as well as in subjects with WHR \ 0.9 and BMI \ 30 kg/m2. In women, the distribution of the strength, WHR and BMI behaves in a different way compared to men. In particular, as the WHR went down, the strength of every test increased regardless of the BMI. Maximum strength was found with WHR \ 0.9 and BMI between 25 and 35 kg/m2. In women with WHR [ 1.05 we
Biogerontology Table 2 Multivariate regression model estimates in men Muscle Strength Variable
Shoulder Cutoff point
Grip Beta
Hip
P value
Cutoff point
Beta
P value
Cutoff point
Knee Beta
P value
Cutoff point
Beta
P value
0.002
BMI–WHR-cutoff1
1.019
-48.8
0.033
0.948
-201.6
0.026
1.054
94.9
0.007
0.909
-256.4
BMI–WHR-cutoff2
1.042
141.7
0.005
0.952
212.0
0.023
1.073
-142.1
0.005
0.917
353.5
0.002
BMI–WHR-cutoff3
1.061
-126.4
0.002
1.007
-20.4
0.042
1.186
-188.6
0.262
0.933
-104.1
0.006
2.9
0.191
3.7
0.319
-2.2
0.302
6.7
0.315
BMI–WHR
The three cutoff points shown for the WHR–BMI interaction correspond to critical changes in the curves slopes in the interaction between WHR, BMI and strength
Table 3 Multivariate regression model estimates in women Muscle strength Variable
Shoulder
BMI–WHR-cutoff1
0.794
43.1
BMI–WHR-cutoff2
0.825
-22.4 -21.7
0.161
BMI–WHR
Cutoff point
Grip Beta
P value
Hip
Knee
Cutoff point
Beta
P value
Cutoff point
Beta
P value
Cutoff point
Beta
P value
0.050
0.890
-8.3
0.028
0.798
63.4
0.009
0.938
8.3
0.021
0.829
-34.8
0.053
0.838
-37.4
0.037
0.012
0.851
31.1
2.5
0.103
-29.7
0.169
0.037
7.2
0.127
The three cutoff points shown for the WHR–BMI interaction correspond to critical changes in the curves slopes in the interaction between WHR, BMI and strength
observed a decrease in strength especially in those with a BMI \ 30 kg/m2 (Fig. 2).
Discussion In this study we aimed to investigate the relationship between WHR, BMI and upper and lower extremities muscle strength. The main findings are: (1) there is a non-linear relationship between BMI, WHR and muscle strength; (2) This relationship shows dramatic differences between sexes; (3) Muscle strength depends on the joined distribution of BMI and WHR and should not be interpreted separately. We used simple anthropometric measurements as surrogates of body fat distribution and accumulation (Turcato et al. 2000; Despre´s et al. 1991; Van Der Kooy et al. 1992). Maximum strength in men was present with WHR around 1 and BMI above 30 kg/m2. This represented an obese population with fat distributed homogenously over their body. The explanation for this finding may be that this group of men had an enhancement in fat free mass (FFM) as the BMI increased, with a subsequent improvement in muscle mass and isotonic
strength (backpack effect) (Lafortuna et al. 2005, 2004). Decreased strength in men was seen with high WHR in obese men, and low WHR in overweight and obese men. These findings showed a possible deleterious effect on strength when fat accumulated in both the abdomen and the hips in obese and overweight men. Visceral fat has been shown to lead to sarcopenia and frailty and this explains why men with more central obesity have less strength (Pou et al. 2007, Phillips and Prins 2008). Obese and overweight men with gynoid obesity have less strength. Although we do not include blood analysis results in this study or body physiognomy analysis, we hypothesize that this finding could be due to hypogonadism (Dhindsa et al. 2007). Maximum strength in women was found with low WHR and high BMI, which represents a population with gynoid obesity, which may have a protective effect in obese women (Fan and Farrell 2008, Rodrı´guez et al. 2007, Vega et al. 2007). Decreased strength was seen in overweight women with high WHR, therefore they were overweight females with fat accumulated in the abdomen. At some point, the peripheral subcutaneous fat storage capacity is maximized and the fat starts to accumulate in the abdomen
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Fig. 1 Kernel regression estimates in men. Three dimensional axis represent strength (kg), WHR, and BMI (kg/m2)
Fig. 2 Kernel regression estimates in women. Three dimensional axis represent strength (kg), WHR, and BMI (kg/m2)
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and other locations such as muscle, pancreas, liver (Despre´s et al. 2008, Krssak et al. 1999, Britton and Fox 2011), with worse consequences for women (Ibrahim 2010, Fox et al. 2007, Cornier et al. 2011). As we mentioned above, these differences between genders may be partially explained by the differences in the body fat distribution, but there may be also a hormonal and genetic explanation. (Llopis et al. 1998; Rissanen et al. 1999; Roelen et al. 1996; Fryburg and Barret 1993; Fox et al. 2012; Zillikenset al. 2008). This study may help future research in assessing patient at risk for frailty, since obese individuals are at higher risk for frailty (Blaum et al. 2005). But the BMI is not the best measurement for obesity in the elderly due to the change in body composition they go through. (Prentice and Jebb 2001). It is necessary to use other measurements of fat distribution such as WHR. We show that in the elderly both the BMI and the WHR (as an indirect measurement of fat distribution) should be assessed together, in order to evaluate muscle strength or sarcopenia, and therefore, frailty. This study may be clinically relevant for future research focused on finding simple way to evaluate the risk of frailty in clinical practice, and consequently, initiate prevention such as diet and exercise (Villareal et al. 2006). There are several limitations in this study that may affect the inferences derived from these data. First, because the results are cross-sectional, a cause-and-effect relationship between strength, BMI and WHR can only be suggested. Second, since the subjects of our study were Caucasians, living in Toledo and with high BMI, these results cannot be generalized to other populations or other races or ethnic groups. Another limitation is that we used indirect techniques to assess body fat distribution such as anthropometric measurements. The main strength of this investigation is the sample size, which allows us to have very accurate results. Another strength is the fact that we measured the strength in all the extremities, which let us see the different behavior between upper and lower extremities, combined with several body composition measurements to assess weight and body fat distribution. In conclusion, the relationship between strength and body composition parameters is more complex than we thought. BMI, body fat distribution and gender have to be evaluated together (Chaston and Dixon 2008).
Acknowledgments All authors have contributed equally to the work and have read and agree to the submission of the paper. This study was funded by Grants PI031558, PI07/90637, PI07/ 90306, RD 06/0013, and RD12/0043 from the Instituto de Salud Carlos III (Ministerio de Economı´a y Competitividad), 03031-00 from Instituto de Ciencias de la Salud (Consejerı´a de Sanidad de Castilla la Mancha), Spain, and FP7-305483-2 from the FP7-Health-2012-Innovation of the European Union. Conflict of interest The authors declare that they have no conflict of interest.
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