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The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 57:M37-M44 (2002)
© 2002 The Gerontological Society of America

Motor Performance in Relation to Age, Anthropometric Characteristics, and Serum Lipids in Women

Xinxin Guoa, Michael Matouseka, Valter Sundha and Bertil Steena

a Department of Geriatric Medicine, Göteborg University, Sweden

Xinxin Guo, Department of Geriatric Medicine, Vasa Hospital, Göteborg University, SE 411 33 Göteborg, Sweden E-mail: xinxin.guo{at}geriatrik.gu.se.

Decision Editor: John E. Morley, MB, BCh


   Abstract
Top
 Abstract
Methods
 Results
 Discussion
 References
 
Background. The relationships between motor performance and age, anthropometric characteristics, and serum lipids were studied in a population-based sample of women (N = 865).

Methods. Motor performance was measured by a precise laboratory test, the Postural-Locomotion-Manual test, using an optoelectronic technique. Anthropometric measurements included body mass index (BMI) and waist-to-hip ratio. Blood samples were drawn for the measurement of total cholesterol, high-density lipoprotein (HDL) cholesterol, and triglyceride concentrations.

Results. Motor performance deteriorated with age in a curvilinear way. High BMI, high waist-to-hip ratio, high triglycerides and low HDL cholesterol were all correlated to poor motor performance after adjustment for age, vascular disease, hypertension, diabetes, smoking, physical exercise, and some chronic diseases. Stepwise regression analyses showed that age, waist-to-hip ratio, triglycerides, HDL cholesterol, physical exercise, and vascular diseases were independent predictors of motor performance.

Conclusions. High age, high waist-to-hip ratio, high triglycerides, and low HDL cholesterol were associated with poor motor performance in women. Monitoring abdominal adiposity and serum lipids in clinical work might help us to identify people with early motor impairment and to prevent more severe mobility disability.

MOTOR impairment is a common problem in the elderly population. It increases the risk of falls (1), disabilities in activities of daily living (ADLs) (2)(3), and mortality (3). Many studies have investigated the effect of chronic diseases on motor performance. However, little attention has been paid to the common risk factors for these diseases, which may also be associated with motor impairment due to their strong relationships with diseases. Identifying these factors and understanding their relationships with motor impairment might help us to detect early motor impairment before the occurrence of clinically evident diseases and thus prevent more severe mobility disability in the elderly population.

Obesity and dyslipidemia are well established risk factors of vascular events and are associated with mobility-restricting diseases such as stroke (4)(5)(6), heart disease (4)(5)(7)(8), osteoarthritis (9)(10), and lower-extremity arterial diseases (11)(12). The evidence suggests a possible link of obesity and dyslipidemia with motor impairment. Several previous studies have explored this issue, but they have considered only body mass index (BMI) (13)(14)(15)(16) or total serum cholesterol concentration (17). Recent studies have shown that other obesity and lipid variables, such as waist-to-hip ratio, serum triglycerides, and high-density lipoprotein (HDL) cholesterol, were more important than BMI and total serum cholesterol concerning prediction of risks of vascular disease and mortality in women (4)(5)(8)(18)(19). Whether waist-to-hip ratio, triglycerides, and HDL cholesterol are related to motor impairment in a general female population has, to our knowledge, not been studied before.

On the basis of a large sample of women, the present study was aimed at describing motor performance measured by an optoelectronic test in seven age groups (38, 50, 62, 70, 74, 78, and 84 years of age) and studying the relationship between motor performance on one hand and anthropometric characteristics and serum lipid concentration on the other.


   Methods
Top
 Abstract
 Methods
Results
 Discussion
 References
 
Population
Representative samples were chosen from two population studies in Göteborg, Sweden: the Women's Health Study (20) and the H70 Study (21)(22). The Women's Health Study is a longitudinal population study of women that started in 1968, and the H70 Study is a longitudinal gerontological and geriatric population study of elderly persons, which has been going on since 1971.

In 1992–93, 1056 women aged 38, 50, 62, 70, 74, 78, and 84 participated in the Women's Health Study and in the H70 Study (20). A total of 873 women were examined by a motor performance test. Nonparticipation in the motor performance test was mainly due to mobility difficulties and refusal. Compared with participants, nonparticipants were more dependent in ADL and more frequently reported difficulties in walking indoors and outdoors and mounting stairs (all p < .001). Eight women with dementia according to DSR-III (23) were excluded, leaving 865 women for the present study (age 38, n = 57; age 50, n = 89; age 62, n = 231; age 70, n = 258; age 74, n = 165; age 78, n = 54; age 84, n = 11).

Motor Performance Test
Motor performance was measured by a Postural-Locomotion-Manual (PLM) test using an optoelectronic technique. Six markers were placed on the right side of the head, shoulder, elbow, hip, and ankle and on the left foot of each individual. The seventh marker was placed on the test object. A camera system emitted infrared light, which was reflected by the markers and registered in a computer. The positions of the markers were measured 50 times each second (Fig. 1).



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  		Figure 1. The Postural-Locomotion-Manual test.

 
The participants picked up the object from the floor, walked forward 1.5 m, and placed it on a shelf at the height of their chin. After that, they immediately went back to the starting point carrying the object. They were asked to repeat this motor act continuously during a 30-second period as fast as possible. Each motor act from the floor to the shelf included three phases: raising the body (the postural [P] phase), walking forward (the locomotion [L] phase), and the goal-directed arm movement (the manual [M] phase). The P phase started when the vertical speed of the head was higher than zero or when the object left the resting position, depending on which event occurred first. This phase ended when the vertical speed of the head reached a minimum value. The L phase started when one foot moved forward in the horizontal direction and ended when both feet were standing still. The M phase started when the angle between the upper arm and the trunk started to increase after passing a minimum value during rising and ended when the object was placed on the shelf. The movement time (MT) in the PLM test was defined as the time from the moment when the object was lifted from the floor until it was placed on the shelf and was regarded as an indicator of the overall motor performance. Because the P, L, and M phases were performed partly simultaneously, a simultaneity index (SI) was calculated to show the degree of simultaneity of the three PLM phases (the sum of the P, L, and M phase duration divided by the MT). A higher value of SI indicated a better motor coordination of three phases. For each motor act, the MT, the duration of each movement phase (P, L, and M phases), and SI were automatically calculated by the computer. Mean values of all motor acts of an individual were calculated as the PLM test results. This test was described in more detail in our previous papers (2)(24).

Clinical Examination
Standing height and body weight were measured in the morning, with the subjects wearing light clothing, usually only underwear and socks. Body weight was recorded to the nearest 0.1 kg, and height was measured to the nearest cm. BMI was calculated from weight (kg) divided by height squared (m2). A steel tape was used to measure waist circumference midway between the lower rib margin and the iliac crest and hip circumference at the widest point of the buttocks. The circumferences were measured to the nearest 1 mm in a standing position. The waist circumference was divided by the hip circumference to give a ratio (19). Blood samples were taken from subjects after they had fasted overnight to measure total cholesterol, HDL cholesterol, and triglyceride concentrations with standard methods (19).

The presence of chronic conditions was ascertained from self-reported medical histories, physical examinations by a physician, and laboratory examinations. Vascular disease was defined as one or more of the following: angina pectoris (25), history of myocardial infarction, ST depression and/or pathological Q waves on the ECG, atrial fibrillation on the ECG, history of stroke, history of transient ischemic attack, and intermittent claudication. Hypertension and diabetes mellitus were defined as having a history of treatment. Other medical conditions included in the current analysis were history of cancer, hip fracture, chronic bronchitis, and joint or back pain. Smoking status was recorded as current, past, or no smoking; the former two categories defined a subject as a smoker. Physical exercise was classified as either exercise less than 4 hours a week or regular exercise.

Statistical Methods
PLM variables (MT, P, L, and M) and serum triglyceride concentration had a skewed distribution and were transformed into a more symmetrical distribution by taking logarithms in all the analyses. Median, percentile, and interquartile range were used to describe PLM variables.

Quadratic regression analyses were performed to examine the relationship between the PLM variables and age. Individual values of MT, P, L, M, and SI were fitted into the following quadratic regression equation: PLM = A0 + A1 x age + A2 x age2, where A0 represents the intercept and A1 and A2 represent the regression coefficients of age and age2, respectively. A statistically significant value of A2 in the final model indicates a curvilinear relationship between the PLM variables and age.

The relationships between the PLM variables and BMI, waist-to-hip ratio, and serum lipids were studied in two ways: first, BMI, waist-to-hip ratio, and serum lipid concentrations were categorized into quintiles; PLM test results regarding each quintile were presented. Second, taking BMI, waist-to-hip ratio, and serum lipids as continuous variables, partial correlation coefficients between the PLM variables and BMI, waist-to-hip ratio, and serum lipids were calculated with adjustment for age, vascular disease, hypertension, diabetes, smoking, physical exercise, chronic bronchitis, joint or back pain, hip fracture, and cancer.

The permutation t test and Mantel's extension test to control for age were used to analyze the differences of PLM test results between women with and without vascular diseases, hypertension, diabetes, smoking, or regular exercise.

Because anthropometric indexes, serum lipids, vascular disease, and other vascular risk factors may relate to each other, stepwise regression analyses were made to find the independent explanatory factors of the PLM variables. MT, L phase, M phase, or SI was the dependent variable in each model, whereas age, serum lipids, BMI, waist-to-hip ratio, treated hypertension, diabetes, vascular disease, physical exercise, smoking, hip fracture, cancer, chronic bronchitis, and joint or back pain were potentially independent variables. A p value <.05 was considered statistically significant.


   Results
Top
 Abstract
 Methods
 Results
Discussion
 References
 
Among 865 women, 183 had vascular disease, 162 had treated hypertension, 32 had treated diabetes, 97 had chronic bronchitis, 21 had joint or back pain, 13 had a history of hip fracture, and 95 had a history of cancer; 362 women were current smokers or ex-smokers. The mean (standard deviation) values of BMI, waist-to-hip ratio, total cholesterol, triglycerides, and HDL cholesterol were 25.9 (4.2), 0.82 (0.06), 6.23 mmol/l (1.15), 1.41 mmol/l (0.73), and 1.58 mmol/l (0.42), respectively.

PLM Test in Relation to Age
Fig. 2 presents the PLM test results of women in seven age groups. Women in the higher age groups showed slower speed (longer MT, and P, L, and M phase) and poorer coordination (lower SI). The most pronounced changes were observed between ages 78 and 84. The relationship between age and the PLM variables was further studied in a quadratic regression (Table 1 ). The statistically significant values of A2 (i.e., the regression coefficient of age2 in the models) indicated a curvilinear association between them.



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  		Figure 2. The Postural-Locomotion-Manual test results of 865 women in seven age groups.

 

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  		Table 1. Quadratic Regression Analysis of the Relationship Between the Postural-Locomotion-Manual (PLM) Test Results and Age (PLM = A0+ A1 x age + A2 x age2)

 
PLM Test in Relation to Anthropometric Characteristics, Serum Lipids, and Vascular Diseases
PLM test results regarding each quintile of BMI and waist-to-hip ratio are presented in Table 2 . After controlling for age and age2, both high BMI and high waist-to-hip ratio were associated with poor PLM performance, including prolonged MT, L phase, and M phase and low SI. These associations became slightly weaker, but most of them remained significant after further controlling for age, age2, vascular disease, hypertension, diabetes, smoking, physical exercise, cancer, hip fracture, chronic bronchitis, and joint or back pain (Table 2 ).


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  		Table 2. Postural-Locomotion-Manual (PLM) Test Results in Relation to Body Mass Index and Waist-to-Hip Ratio

 
PLM test results regarding each quintile of triglycerides, HDL cholesterol, and total cholesterol concentration are shown in Table 3 . After adjustment for age and age2, high triglycerides and low HDL cholesterol were both correlated to prolonged MT, L phase, and M phase and low SI. Most of these associations remained after further adjustment for age, age2, vascular disease, hypertension, diabetes, smoking, physical exercise, cancer, hip fracture, chronic bronchitis, and joint or back pain. Total cholesterol concentration was not correlated to any PLM variables after controlling for age and diseases (Table 3 ).


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  		Table 3. Postural-Locomotion-Manual (PLM) Test Results in Relation to Serum Lipid Concentration

 
Women with vascular diseases showed longer MT (p < .001), L phase (p < .001), and M phase (p = .024) than those without vascular diseases. Treated hypertensive women had prolonged MT (p = .004), prolonged L phase (p = .044), and low SI (p = .041). Women who exercised less than 4 hours a week showed longer MT and all three phases and lower SI than those who exercised regularly (all p < .001). PLM test results did not differ between diabetic and nondiabetic women or between smokers and nonsmokers.

Independent Explanatory Factors of PLM Variables
Stepwise regression analyses were made to find independent explanatory factors of MT, L phase, M phase, and SI. P phase was not included because none of the variables of serum lipids, anthropometric indexes, and vascular disease was correlated to P phase in previous analyses. In the final models, high age, high triglycerides, low HDL cholesterol, high waist-to-hip ratio, physical exercise less than 4 hours a week, and vascular diseases were independent predictors of poor PLM performance (Table 4 ). High BMI was associated with prolonged L phase.


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  		Table 4. Stepwise Regression Analysis of the Relationship Between the Postural-Locomotion-Manual (PLM) Test Results and Age, Anthropometric Characteristics, Serum Lipids, and Vascular Disease

 

   Discussion
Top
 Abstract
 Methods
 Results
 Discussion
References
 
On the basis of a large sample of women aged 38 to 84 years, the present study shows that motor performance deteriorates with age in a curvilinear way. High BMI, high waist-to-hip ratio, high triglycerides, and low HDL cholesterol were all associated with poor motor performance after adjustment for age, vascular disease, hypertension, diabetes, smoking, physical exercise, and some chronic diseases. Stepwise regression analyses showed that age, waist-to-hip ratio, triglycerides, HDL cholesterol, physical exercise, and vascular diseases were independent predictors of motor performance. The cross-sectional study design limited the interpretation of our findings. Further longitudinal studies are needed to confirm these findings.

The participants in the Women's Health Study and the H70 Study were representative of women at the ages studied in Göteborg, Sweden (20)(22). However, the women in the present study represented a relatively healthy population because those with severe diseases or disabilities were unable to perform the PLM test and were excluded from the study. Compared with the nonparticipants, participants had less self-reported difficulties in walking indoors and outdoors and mounting stairs and were less dependent in ADLs. If anything, this positive selection might underestimate the association between poor mobility and its potential risk factors in a total female population.

The older women had lower speed in performance of the whole PLM task and each individual phase as well as poorer coordination of the three phases compared with the younger women. This is in agreement with previous PLM studies in healthy individuals (24)(26). The most striking deterioration was seen in the oldest age group (age 84). However, this age group comprised only 11 women. On the other hand, they might represent a relatively healthy 84-year-old population with better motor performance. Among the eight nonparticipants aged 84, seven reported difficulties in mobility, and five were dependent in ADLs.

The mechanisms underlying impaired motor performance in old age are complex and involve many physiological and pathological changes (27)(28). Vascular disease is an important pathological condition (27)(28), as supported by previous studies (29)(30) as well as by the present study. Moreover, the association between poor PLM performance and vascular risk factors, including obesity, high triglycerides, low HDL cholesterol, treated hypertension, and low physical exercise, further underlined the importance of vascular diseases in the development of motor impairment in women.

Our results are consistent with previous findings that people with high BMI had poor mobility (13)(14)(15)(16). Such a relationship appeared to be a result of a relatively high prevalence and severity of chronic diseases, such as heart disease and osteoarthritis, in people with high BMI (13)(31). An even more interesting finding of the present study is that waist-to-hip ratio is strongly associated with poor PLM performance, independent of BMI and vascular disease. An increasing number of studies have shown that in women, abdominal obesity (waist-to-hip ratio) was a better marker than overall obesity (BMI) for prediction of heart disease (4)(8), stroke (4)(6), and mortality (18)(19). Compared with BMI, waist-to-hip ratio had a stronger correlation to metabolic abnormalities such as glucose intolerance, hypertension, and dyslipidemia (18)(32). In addition, increasing abdominal adiposity was associated with unhealthy lifestyle factors, including smoking, alcohol consumption, and low physical exercise (33). All these findings indicated that the association between increasing abdominal adiposity and poor mobility was biologically plausible.

We found that high triglycerides and low HDL cholesterol were associated with prolonged PLM performance, but total serum cholesterol was not. The relationship between serum lipids and mobility disability has not been subjected to many previous studies. We were aware of only two recent studies, one based on a male population (17) and the other based on a nondisabled elderly population (34). The underlying mechanisms of the association between high triglycerides and low HDL cholesterol and motor impairment are unclear, but there are some possible explanations. First, high triglycerides and low HDL cholesterol increase the risks of vascular disease events such as stroke (5), heart disease (5)(7), and lower extremity arterial diseases (11)(12), which, in turn, could cause declines in mobility. It is worth emphasizing that the influences of several clinically diagnosed vascular diseases on the relationship between motor impairment and serum lipids were controlled in our study. However, we cannot exclude the possibility that some participants may have other types of or preclinical vascular diseases, which were not recorded and controlled in the present study but may mediate this association. Second, dyslipidemia has been identified as a risk factor of white-matter lesions (35), brain atrophy (36), and silent brain infarction (37). These neuroimaging findings were quite common, and all have been found to relate to impaired motor function in elderly persons (37)(38)(39)(40). Therefore, the association between lipids and motor impairment might, to some extent, reflect the existence of these brain abnormalities. Third, it has been frequently reported that high triglycerides and low HDL cholesterol were associated with a low level of physical exercise (41)(42). Physical inactivity increased the risk of mobility disability (15)(17).

The strengths of this study included the following facts: It was based on a large female population across a wide age range (38–84 years); motor performance, anthropometric characteristics, and serum lipids were objectively and precisely measured in the laboratory; and this was, to our knowledge, the first study that investigated the relationship between motor performance and waist-to-hip ratio and serum lipids in a population-based sample of women.

In summary, high age, high waist-to-hip ratio, high triglycerides, and low HDL cholesterol were associated with poor motor performance in women. Monitoring abdominal adiposity and serum lipids in clinical work might help us to identify people with early motor impairment and to prevent further functional decline, which leads to more severe disability. Reducing body weight, treating dyslipidemia, and maintaining regular physical exercise might be effective ways to prevent motor decline.


   Acknowledgments
 
This study was supported by grants from the Lions Foundation, the Hjalmar Svensson Foundation, the Göteborg Medical Society, and the Medical Faculty at Göteborg University.

We thank Professor Calle Bengtsson, Department of Primary Health Care, Göteborg University, who kindly allowed us to use data from the Women's Health Study. We also thank Barbro Eriksson, research laboratory technician at the Institute of Clinical Neurosciences, Göteborg University, who helped to process the data of the PLM test.

Received February 5, 2001

Accepted February 14, 2001


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 Discussion
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