Relationship between muscle mass and muscle strength, and the impact of comorbidities: a population-based, cross-sectional study of older adults in the United States

By the year 2020, there are projected to be almost 55 million Americans, in the USA, over the age of 65 and more than 6 million over the age of 85 [1]. One consequence of the aging of the population will be an increase in the number of Americans who will experience the predictable loss of muscle mass and muscle strength that occurs with aging [2]. While not necessarily pathological, this age-related loss of muscle mass and strength has been shown to have important health consequences [3, 4], predisposing the elderly to falls and contributing to other functional limitations [5, 6].

Although the positive correlation between muscle mass and muscle strength has been well established [2, 7–11], it is not clear whether higher muscle mass necessarily translates into greater muscle strength or whether gains in muscle strength cannot be achieved without corresponding gains in muscle mass. For example, Park et al. (2006) and colleagues found in the Health, Aging, and Body Composition (Health ABC) study that, while older adults with type II diabetes had higher muscle mass compared with their non-diabetic counterparts, they did not exhibit greater muscle strength [12]. Similarly, Raue and colleagues, studying the impact of conditioning on muscle mass and muscle strength in octogenarian women, found that whole muscle strength increased with resistance training, while muscle mass did not increase [13].

A number of clinical conditions have also been shown to correlate with muscle mass and/or strength, and it is possible that heterogeneity among older adults with respect to these conditions, many of which are increasingly prevalent with age [14], may contribute to the indeterminate relationship between muscle mass and muscle strength. While several studies corroborate the impact of comorbid conditions such as diabetes, obesity, and osteoarthritis on muscle mass, muscle strength, or related functional outcomes [12, 15–18], no study has systematically explored the complex interactions between these conditions and muscle mass and strength.

In the present study, we aimed to better understand the relationship between muscle mass and muscle strength in US older adults, and to examine the impact of a variety of comorbidities on muscle strength and the relationship between muscle mass and muscle strength. Our specific objectives were as follows: (1) to describe muscle mass and muscle strength, stratified by age and gender; (2) to assess the degree to which muscle mass and strength are correlated, adjusting for the effects of age and gender; and (3) to explore the impact of a variety of comorbid conditions on muscle strength and/or the relationship between muscle mass and strength. For the latter objective, our general hypothesis was that certain factors, such as obesity and arthritis, might limit the degree to which higher muscle mass translates into greater muscle strength. Insights gained from these analyses could aid in the management of patients, who have muscle atrophy or wasting by providing norms and targets for rehabilitation and by raising awareness of the influence of other comorbid conditions.

The distributions of aASM and IQS, stratified by gender and age, are presented in Figure 1 and Figure 2, respectively. Both aASM and IQS tend to decrease with age in older adult men and women, and women appear to have a lower mean aASM and IQS than men within the same age group. In men, aASM appears to decrease steadily after age 65, while a similar decrease in women occurs somewhat later (Figure 1). Mean IQS tends to decline in both men and women as early as the starting age of the study cohort (the sixth decade of life), with the IQS decline in men appearing somewhat steeper than for women.

Results from the multiple regression models that incorporated each of the comorbidities suggested that diabetes, CHD/CHF, and vision problems had significant negative main effects on IQS (P < 0.05), while corresponding interaction effects between the comorbidity and aASM were not statistically significant (P > 0.05) (Table 2). Specifically, individuals with diabetes, CHD/CHF, and vision problems demonstrated an IQS, on average, of −27.1 (95% CI: -42.1,-12.0), -20.7 (95% CI: -36.1,-5.3) and −20.1 (95% CI: -34.4, -5.7) newtons less, respectively, than the age, gender, and aASM comparable older adults without these comorbid conditions.

Body mass index, arthritis, and osteoporosis had both significant main effects and interaction effects on IQS, while asthma had a significant interaction effect, but an insignificant main effect on IQS, which made the corresponding regression coefficients less directly interpretable. Cancer and bronchitis/emphysema had neither significant main nor interaction effects.

The relationship between muscle mass and IQS among subgroups with and without the comorbidities for which there were significant interaction effects (e.g., obesity, arthritis, asthma, and osteoporosis) is shown visually in Figure 3. Subgroup analyses suggested that the regression slopes for aASM were comparable among underweight (47.9 [95% CI: 20.4,74.0], healthy weight (54.4 [95% CI: 42.3,66.5]) and overweight subgroups (47.4 [95% CI: 38.5,56.4]), while the slope for the obese subgroup (23.8 [95% CI: 13.1,34.4]) differed significantly from that of both the healthy weight and overweight subgroups. As such, for simplicity, the influence of weight was shown in the Figure 3A by stratifying subjects into only two subgroups, obese and non-obese. As shown in this figure, obese subjects (red diamonds) tend to have, on average, lower strength at a given aASM value compared to non-obese subjects (blue squares), and the regression line for this subgroup (red line) is consistently below that for the non-obese subgroup.

In Figure 3B, the regression line for the non-arthritis subgroup was generally higher than that for the arthritis subgroup. While the difference in the slopes of these regression lines was not statistically significant, the regression lines can be seen to diverge as aASM increases and to become closer and eventually to cross at lower values of aASM. A similar pattern was seen for subgroups with and without osteoporosis and asthma (Figure 3C and 3D).

In this cross-sectional, population-based study of older US adults, we described the distribution of muscle mass and muscle strength stratified by age and gender. We found that muscle mass and muscle strength were positively correlated after adjusting for age and gender. We also found that certain comorbidities had significant impacts on muscle strength and/or on the relationship between muscle mass and muscle strength.

To our knowledge, this is the first study to characterize the distribution of height-adjusted appendicular skeletal muscle mass in a nationally representative sample of older adults in the US. Kelly et al. (2009) provided nationally representative reference data on DXA body composition reference values, but did not include reference data on lean mass exclusive of bone mineral content, which is considered a better representation of skeletal muscle mass [24]. The distributions of aASM and IQS can serve as reference values for US older adults and may prove useful in the evaluation of abnormalities involving muscle mass and muscle strength.

In this study, we observed that both muscle mass and muscle strength declined with advancing age in older adults, and that women have a relatively lower muscle mass and strength compared with men of the same age, and these findings are consistent with previous research [8–10, 28–30]. Our observation that age-associated decrements were more pronounced for muscle strength than for muscle mass corroborates the finding from a 3-year longitudinal study of 1,880 older adults; this finding showed that muscle quality (defined as muscle strength per unit of muscle mass) declines with advancing age [31].

This study quantified the positive association between muscle mass and muscle strength in older adults, and found that muscle mass explained about 13% of variance in muscle strength, independent of age and gender. After adjusting for age and gender, every one unit increase in aASM was associated with a corresponding 31.6 newton increase in IQS. As these results are derived from a cross-sectional study, any causal inference is precluded. Nevertheless, these data underscore the need for further prospective research that evaluates the downstream effects of interventions, which are aimed at preserving muscle mass, on muscle strength and physical function.

Our study also revealed that certain comorbidities impact muscle strength or the muscle mass/strength relationship. Diabetes, CHD/CHF, and vision problems were independent predictors of low muscle strength, which suggests that individuals with these comorbidities have, on average, lower muscle strength compared with individuals of similar age, gender, and muscle mass. Our finding regarding the effect of diabetes is consistent with work conducted by Park et al. (2006), wherein diabetics in the Health ABC Study were observed to have poorer muscle quality than non-diabetics [12]. Older diabetic men and women in that study exhibited greater muscle mass without a corresponding increase in muscle strength relative to non-diabetic older adults. Research in exercise physiology has established a robust dose–response relationship between physical exercise and muscular adaptation, which leads to increased motor unit activation and a proportionately greater increase in muscle strength than in muscle mass [32]. Conversely, decreased physical activity is a known risk factor for diabetes [33], and diabetics, on average, are likely to exhibit poorer muscle quality relative to their non-diabetic peers. In addition, vascular and metabolic deficits (e.g., decreased oxygen supply or impaired glucose extraction and utilization by muscle) may also contribute to physiologic impairment of muscle cells in diabetics, which results in diminished muscle strength. Deconditioning, likely, also contributes to the decrease in muscle strength that is observed in subjects with CHD/CHF, vision problems, and obesity, as these groups may be more limited in their ability to engage in regular physical activity. In addition, the increase in intramyocellular fat, which is seen in obese subjects, may also adversely affect muscle quality and force production, although the mechanism for this result is unclear [12].

While arthritis, asthma and osteoporosis all appeared to alter the relationship between muscle mass and muscle strength to some extent, interpretation of these effects is challenging due to the significant interaction effects observed. It is possible that these conditions are meaningful effect modifiers, but the results from our subgroup analyses (e.g., absence of statistically significantly differences in regression line slopes) failed to establish this. It may be that these effects are relatively marginal or perhaps more complex (e.g., non-linear), thus, requiring a larger sample size or more complex modeling approaches. Further research is warranted to better understand the effects of these comorbidities.

These findings should be interpreted in the context of study limitations. First, the cross-sectional nature of the data limits our ability to do more than describe asso-ciations, and future longitudinal research is needed to better understand the causal nature of these associations. Second, comorbidities were based upon self-report, rather than on formal clinical assessment, which raises concerns about recall and other biases. Finally, comorbidities were examined individually; whereas, in many cases, multiple comorbidities may co-occur. Unfortunately, incorporating additional two-way or three-way interaction effects would have significantly impacted the power available to draw meaningful conclusions.

In conclusion, among individuals aged 50 and older in the US, muscle mass and muscle strength are positively correlated, independently of the associations of age and gender with muscle mass and strength. Certain comorbid medical conditions serve as independent predictors of lower muscle strength (e.g., diabetes, CHD/CHF, vision problems) or modify the relationship between muscle mass and muscle strength (e.g., obesity).