Present study was undertaken primarily to analyze the trends in frailty status of a cohort of community dwelling elderly, residing in the Dakshina Kannada district of Karnataka state in India over a period of 3 months as well as to analyze the strength of association between change in frailty score and cognition, nutritional status, gait velocity, functional mobility, body mass, and strength The recruitment period of the study coincided with the beginning of ongoing SARS COVID 19 which proved to be a major hindrance in approaching, screening and evaluating elderly subjects. Over the period of study, a total of 28 subjects were screened, of which 22 fulfilled the criteria of inclusion in the study. However of the 22 subjects, the follow up evaluation could be done only for a total of 19 subjects and hence the goals of the study were realigned to investigate the influence of pandemic induced lockdown and the associated reduction in physical activity on the outcome variables. In the current study we found that there is an observable change in frailty status over a period of 3 months but it was not statically significant.
Frailty is an umbrella term and there are many tools to measure Frailty. EPIF scale was used in the current study because it covers all domains of frailty (like physical, psychological, social functioning and general health), and has been proven to have good reliability and validity.(15) The data collection involved administering 4 questionnaires (EPIF, MOCA, MNAT NESTLE®) which on an average took 45 min- 1 hour to complete. Objective measures of strength, functional mobility, gait velocity, and body composition analysis would take an additional hour to complete. This made the entire data collection process a time consuming one thereby adversely affecting the number of subjects recruited in a day. However other than the afore mentioned 3 subjects who chose to forgo the follow-up evaluation because of the pandemic situation, there were no additional dropouts in the span of study and no reported discomfort or adverse event pertaining to data collection.
The primary objective of the study was to detect any association between changes in frailty status and other outcome variables. It must be noted that there was only very minimal difference (over a period of 3 months) in Frailty score (mean difference 0.625) and findings were not statically significant. We could not find any statically significant relationship between changes in frailty score and the changes in strength, muscle mass, cognition, nutritional status, gait velocity, or functional mobility.
However it must be emphasized that, when the independent variables were compared at baseline and 3 month of follow-up there was a statistically significant difference found in the scores of MOCA, TUG, visceral fat, PASE and muscle mass. The muscle mass and gait velocity showed a marginal but statically significant reduction, whereas total body fat as well as visceral fat content showed an increment. Cognitive functions as measured by MOCA and gait velocity (implied by an increase in time taken to complete 10M walk test) showed a decline in the above mentioned period, whereas the time taken to complete TUG had marginally increased. The observed differences in MOCA scores though were never sufficient to imply a cognitive decline. It can be inferred from these finding that a short span of 3 months has brought about measurable differences in variables which have been previously associated with frailty.
Previous research corroborated our findings in that there is a definitive decline in muscle mass ranging between 2 to 4% annually in older men and women of all ethnicity. There is also a concurrent increase in body fat content averaging about 0.8% within the same time span.(16)
Factors that influence body composition, especially muscle mass include genetic variables, metabolic variables, endocrinological variables, co-morbidities, diet, alcoholism, smoking, as well as gender and ethnicity. It must be emphasized however that physical activity as an independent variable is a strong predictor for loss of muscle mass and changes in body composition in elderly.(17)The data collection of present study coincided with the period of pandemic enforced restriction and all of the recruited subjects had reported a considerable decline in the amount of physical activity they indulged in the same period. For measuring physical activity we had used Physical activity Scale for elderly (PASE) and we found a highly significant reduction in the physical activity (Mean Difference = 43, p < 0.05) over the period of 3 months. For the population which we had studied, the major source of physical activity used to be walking in public places like parks or attending organized social gatherings like yoga and group exercise sessions. Since most of these activities were deemed to be unsafe, especially in elderly population, there was virtually a complete absence of these activities in the lockdown period.
Our data analysis shows there is a statically significant decline in functional mobility as measured by TUG with ageing, but it must be emphasized that this decline was barely consequential and for all intentions and purpose it is safe to assume there was no decline in functional mobility of the studied cohort. Gait velocity showed a statically significant but minuscule difference when compared over a period of 3 months.
In all major muscle groups of lower extremity, there was a significant difference noted in strength which ranged from a difference of 0.7 kg to 1.5 kg. One of the key associated finding was that the decline in strength of bilateral hip and knee musculature (hip abductors, hip adductors, knee extension of right side and knee extensors, hip flexors, hip extensors and hip adductors on the left side) showed statically significant moderate correlation with decline in muscle mass. Previous studies have shown that there is insufficient evidence of a liner relationship between the loss of muscle strength and muscle mass in aging, though both have been individually established as definitive outcomes of ageing. Other factors affecting muscle strength have been identified as impaired reciprocal inhibition, alteration in rate coding of motor unit activation, as well as changes in metabolic characteristic of muscle fibers. These changes can happen independent of the changes in muscle mass.(18)The changes in muscle strength could then be attributed to the definitive decline in physical activity levels as previously stated, which would have precipitated a deconditioning/reversal effect on muscle strength. In our study cohort we observed neither statically significant nor any amount of change in the nutritional status of study population as measured by MNAT®.