An Investigation into Body Mass Index and Lifestyle Characteristics within an Elderly Population
Journal Title: Obesity Research - Open Journal - Year 2016, Vol 3, Issue 2
Abstract
Understanding and detecting patterns of body composition change and lifestyle factors that influence the development of effective strategies to optimise the health and well-being of the elderly are important. Therefore current research aimed to discover the strength of the correlation between an elderly populations Body Mass Index (BMI) and lifestyle characteristics including diet, physical activity, mobility, balance, sleep, smoking, alcohol consumption and well-being and whether there were any gender differences between BMI measures and lifestyle characteristics. A convenience sample, of n=20 elderly individuals were used in this study (x±s; age=4.40±7.88 years; stretched stature=1.65±0.08 m and body mass=75.98±11.65 kg) consisting of 8 and 12 males. Body composition was measured through participant’s body mass (kg) divided by height (m) squared to gain a BMI measurement (kg/m²). Lifestyle characteristics were measured quantitatively through Likert scales that followed a pre-validated questionnaire similar to that of Ansari et al.1 BMI measures and Lifestyle questionnaire percentage scores within each gender were then compared using paired sample t-test (α=0.05) producing a Pearson’s Correlation figure to determine the strength of correlations between each lifestyle factor and BMI across genders. Results indicated that males had a slightly higher mean BMI of 28.14±3.27, with a range of 9.4 kg/m2 , as the female mean BMI was 27.65±5.06, with a range of 13.1 kg/m2 . A paired sample t-test produced a higher coefficient of 0.86 when considering male’s overall lifestyle characteristics questionnaire score and BMI measures, in contrast a coefficient of -0.18 was produced in females. Strong correlations (above 0.7) were detected suggesting a positive correlation between male’s diets, mobility, sleep, alcohol and well-being with BMI. Moderate correlations were shown between female’s diets, sleep and smoking habit with BMI. In conclusion, it is evident that lifestyle habits show positive correlations with BMI measures in both males and females. These characteristics should be optimised to improve BMI measures, promoting healthier lifestyles and hopefully reduce the suggested burden of the aging population on society.
Authors and Affiliations
Claire Mills
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