The purpose of this study was to compare various muscle quality indexes between Hispanics and non-Hispanic Caucasians when stratifying grip strength and appendicular lean mass measurements. Results demonstrated that, on average, Hispanics were shorter, heavier, possessed a greater BMI, %Fat, and waist and hip circumference than non-Hispanic Caucasians. Additionally, Hispanics had a lower HGS than non-Hispanic Caucasians. Despite these differences, there were trivial-to-small differences for all MQI comparisons (i.e., MQITOTAL, MQIARMS, MQIRA, and MQILA) between Hispanics and non-Hispanic Caucasians. However, MQI models that only included measurements of the arms (i.e., MQIARM, MQIRA, and MQILA) produced larger differences between males and females versus MQITOTAL, which included ALM of the arms and legs. Consequently, this led to sex being a better predictor than ethnicity, based on regression analyses, for MQIARMS, MQIRA, and MQILA; whereas ethnicity had the greatest predictability of MQI when incorporating ALM of the arms and legs (i.e., MQITOTAL).
While only a limited number of MQI comparisons between Hispanics and non-Hispanics have been completed, the present study agrees and conflicts with previous research, which is worth further discussion. For instance, when evaluating MQITOTAL, Lopes et al. (9) found Hispanic males and females exhibited slightly higher values (3.5 and 3.4 kg/kg, respectively) than non-Hispanic Caucasians (3.3 and 3.0 kg/kg, respectively). The current study demonstrated nearly identical MQITOTAL values between Hispanic and non-Hispanic males and females. Additionally, Arajuo et al. (8) found that Hispanic males have lower MQI values than non-Hispanic Caucasians (5.40 and 5.71 kg/kg, respectively) when computing HGS via one hand and the lean mass of both arms. The findings from Arajuo et al. (8) are consistent with the current study, which demonstrated Hispanic females had lower MQIARMS, MQIRA, and MQILA values than non-Hispanic Caucasian. Contrarily MQIARMS, MQIRA, and MQILA values were similar when comparing Hispanic and non-Hispanic Caucasians males in the present study.
The first step in discerning potential differences between current and previous studies includes analyzing the methodological approaches used to compute MQI. For instance, the present study used a GE Lunar Prodigy DXA to estimate body composition, whereas previous work used a Hologic DXA QDR 4500 (8, 9). Previous research has shown differences between GE and Hologic systems when seeking to estimate body composition (17). These are important factors to consider as other methodological body composition approaches (e.g., bioimpedance analysis, circumference measures) can be used to estimate ALM and subsequently calculate MQI (18, 19). In addition to methodological approaches, another explanation for the variance in MQI values exists within the differences of body composition between races and ethnicities. For example, non-Hispanic Caucasian populations tend to have a greater prevalence for sarcopenia and increased fat infiltration of skeletal muscle (i.e., myosteatosis) compared to African Americans (20). While myosteatosis comparisons of Hispanic adults have yet to be completed, it is plausible that the Hispanic women in the current study possessed higher levels of myosteatosis than non-Hispanic Caucasians, leading to lower MQI values versus their non-Hispanic Caucasian counterparts. Based on these potential rationales for differences in MQI, future studies are encouraged to include a measure of myosteatosis when seeking to compare MQ across various ethnic groups. Additionally, practitioners should be cautious of interpreting MQI results when body composition methods differ across study sites.
The assessment of HGS is also a component that needs to be considered when interpreting MQI findings across studies. For example, the current study used combined HGS (i.e., left hand + right hand) when computing MQITOTAL and MQIARMS. Moreover, when a single HGS was obtained (e.g., left hand), the corresponding arm (e.g., left arm) was used to compute MQI (e.g., MQILA). This process differs from other studies who have used dominant HGS and both arms for ALM when computing MQI. The reason for using dominant HGS, but both arms for ALM is not entirely clear. One potential rationale may be demonstrated by 10% dominance rules which states that dominant HGS is, on average, 10% greater, then the non-dominant hand (21). However, research has also shown that non-dominant HGS is equal to, or stronger than, the dominant hand in 28% of subjects (22), with recreational athletes having less profound differences in HGS between hands than non-athletes (23). Therefore, it is possible the 10% dominance rule once served as a basis when calculating MQI at some point. Nonetheless, the lack of standardization on how to measure MQI likely explains the range of methodological approaches, which makes interpreting results difficult. Until an agreement can be reached when measuring MQI, the current study recommends the following methodological approaches: 1). combined HGS and ALM of both upper extremities (i.e., left arm + right arm); 2) combined HGS and ALM of all 4 extremities (i.e., left arm + right arm + left leg + right left); or 3). single HGS and ALM of corresponding arm. Additionally, it should be noted that the present, and most previous, MQI estimations are calculated using only upper extremity strength (i.e., HGS). By only using upper body strength, generalizations and interpretations are limited, particularly when explaining between sex differences. This is particularly relevant as there are greater differences between sexes when examining muscular strength in the upper body as opposed to the lower body (24). Therefore, future research should consider MQI models accounting for both upper and lower body strength values as compared to respective ALM.
Notwithstanding the strengths of the present study, it is important to acknowledge the limitations. For example, the current study comprised of young and middle-aged adults. Ideally, the investigation would have comprised of adults across a larger age spectrum to gain a better understand of the relationship of MQI to age. However, it is worth noting that a limited amount of information, regarding MQ, is available in a Hispanic population. Therefore, this study adds to the literature by evaluating MQI in an underrepresented population. Our findings in Hispanic females (i.e., lower MQIARMS, MQIRA, and MQILA) also help raise awareness of potential disparities that exist across ethnicities when comparing MQIs. Future studies might investigate this disparity and seek to develop interventions and programs to improve the muscular strength to body composition ratio of Hispanic populations. Another limitation of the current study was not accounting for dominant HGS. Nonetheless, accounting for dominant HGS varies across studies, which is likely attributed to the lack of consensus on estimating MQI. All MQI models of the current study matched HGS with the corresponding arm(s) composition measurements. Thus, future studies might seek to account for dominant hand and determine whether MQI varies across dominant and non-dominant HGS when matched with corresponding arm for ALM.