Background: Studies has demonstrated the development of Kinesiophobia in Low Back Pain (LBP) and identified as one of the risk factor for chronicity in LBP. In addition to deconditioning effect, Kinesiophobia also install functional disability and does that affect quality of life? Literatures had exposed the association of Kinesiophobia in chronic and acute low back pain separately but paucity in estimating their quality of life thus this study aims to explore the impact of Kinesiophobia on the quality of life in LBP.Materials and Methods: One hundred and twenty study participants were recruited by convenient sampling method between 18 -60 years of age. Data were collected by using Tampa scale of Kinesiophobia, Numerical Pain Rating Scale, SF-36 Health Status Questionnaire and Modified Oswestry Disability Questionnaire for LBP. Secured scores were analysed in SPSS software to identify the association between Kinesiophobia and other functional scales.Results: Mean age of the study participant was 39.79±11.22 years. Prevalence rate of high degree of Kinesiophobia was found as to be 58.33% (n=70). As the intensity of pain increases in LBP, the development of Kinesiophobia also increased and its association exhibited as weak positive linear correlation (r=0.256, p=0.032). Development of Kinesiophobia has demonstrated increased functional disability where correlation between Kinesiophobia and Oswestry disability shows moderate positive correlation (r = 0.495, p=0.000) simultaneously correlation between Kinesiophobia and SF-36 shows moderate negative correlation (r = -0.420, p=0.000) indicating decreased Quality of Life.Conclusions: It has been found that there is a direct relationship between the pain and the development of Kinesiophobia in LBP which in turn increase in the development of functional disability thus marking decreased QOL.

Purpose: Falls are an emerging public health problem causing a cascade of medical, functional, and socio-economic consequences. Apart from other widely explored risk factors affecting balance, anthropometric factors are also known to have an impact on balance. However, this relationship hasn’t been studied extensively in older adults. This study aimed to evaluate the relationship between the anthropometric factors such as Body Mass Index (BMI), Body Fat Mass (BFM), Waist-Hip Ratio (WHR), Lower Limb Length (LLL), Foot Length (FL) and balance in the elderly among fallers and non-fallers. Method: This cross-sectional study was performed on 100 fallers and 100 non-fallers, aged 60 years and above. These participants were recruited by a stratified random sampling technique from Navi Mumbai region. All the above anthropometric factors were measured and recorded. Each participant’s balance was assessed using the Mini-BESTest scale. Obtained scores were analysed in SPSS software; descriptive statistics, Spearman correlation coefficient, and Z scores were applied. Results: A sample size of 100 non-fallers, 50% male and 50% females, participated in this study. Among those participants classified as “fallers,” 56% were males and 44% were females. The mean age of the non-fallers was 66±5.01 and the mean age of the fallers was 67.72±6.73. In fallers, WHR showed good negative correlation (r= -.807), BFM as moderate (r= -.577) and BMI as fair (r= -.426) whereas in non-fallers, BMI showed moderate (r= -.546) and fair negative correlation for both WHR (r= -.303) and BFM (r= -.441). However, LLL and FL in both groups show little or no correlation. The Association of all anthropometric factors with the balance between fallers and non-fallers showed no-significant difference. It may be inter-group variance for age, gender and BMI, as participants were not matched for these variables during the recruiting phase. Additionally, the reason for the fall was not explored, thus adding to the limitations of our study. Conclusion: This study demonstrated the impact of increased WHR, BFM and BMI on balance in the elderly fallers and non-fallers. Thus, it is important to screen these factors while assessing biological risk factors for predicting falls. This study further recommends exploring the normative value for anthropometric factors in a healthy elderly population.