Negative attitudes towards ageing are reported to be associated with greater functional impairment in older adults.There is limited information regarding attitudes towards ageing and physical performance in regard to adults aged 55 to 64 years. The objective of our study was to examine the association of attitude towards ageing on physical performance which includes mobility, agility and falls risk. This cross sectional study was conducted at five senior citizen clubs around Klang Valley in Malaysia. A total of 154 community dwelling adults aged 55 and above (mean:65.8+6.82) participated in this study. Attitude towards ageing was measured using Kogan’s Attitude towards Older People Questionnaire (KAOP). Mobility and agility were measured using gait speed test and ten step test respectively. Risk of falls was assessed using physiological profile aproach (PPA). Approximately 75% of the participants had positive attitude towards ageing with high to very high risk of falls. A significant (p<0.05) correlation was demonstrated between attitude towards ageing, falls risk and gait speed.Regression analysis showed that attitudes toward ageing had a relationship with falls risk, explaining 6% of the variance, F (1, 152) =10.26, p<0.01.The results of this study suggest that there is some relationship between attitude towards ageing and falls risk measured using a combination of physical performance test. Positive attitude towards ageing should be promoted among adults in an earlier age for overall physical health among older adults.
attitudes towards ageing ; gait speed ; agility ; falls risk ; older adults

An in-depth understanding of the mechanism of lower extremity muscle coordination during walking is the key to improving the efficacy of gait rehabilitation in patients with neuromuscular dysfunction. This paper investigates the effect of changes in walking speed on lower extremity muscle synergy patterns and muscle functional networks. Eight healthy subjects were recruited to perform walking tasks on a treadmill at three different speeds, and the surface electromyographic signals (sEMG) of eight muscles of the right lower limb were collected synchronously. The non-negative matrix factorization (NNMF) method was used to extract muscle synergy patterns, the mutual information (MI) method was used to construct the alpha frequency band (8-13 Hz), beta frequency band (14-30 Hz) and gamma frequency band (31-60 Hz) muscle functional network, and complex network analysis methods were introduced to quantify the differences between different networks. Muscle synergy analysis extracted 5 muscle synergy patterns, and changes in walking speed did not change the number of muscle synergy, but resulted in changes in muscle weights. Muscle network analysis found that at the same speed, high-frequency bands have lower global efficiency and clustering coefficients. As walking speed increased, the strength of connections between local muscles also increased. The results show that there are different muscle synergy patterns and muscle function networks in different walking speeds. This study provides a new perspective for exploring the mechanism of muscle coordination at different walking speeds, and is expected to provide theoretical support for the evaluation of gait function in patients with neuromuscular dysfunction.
Humans ; Walking Speed ; Muscle, Skeletal/physiology* ; Electromyography ; Gait/physiology* ; Walking/physiology*