METHODS: This was a cross sectional study carried out in two primary care clinics in a semi-urban locality of Ampangan, Negeri Sembilan, Malaysia. Data was collected through self-administered questionnaires assessing the demographic characteristics, medical history, lifestyle and physical activity. The Short Form 36-items health survey was used to measure HRQOL among the pre-diabetics. Data entry and analysis were performed using the SPSS version 19.
RESULTS: A total of 268 eligible pre-diabetics participated in this study. The prevalence of normal weight, overweight and obesity were 7.1%, 21.6% and 71.3% respectively. Their mean (SD) age was 52.5 (8.3) years and 64.2% were females. Among the obese pre-diabetics, 42.2% had both IFG and IGT, 47.0% had isolated IFG and 10.8% had isolated IGT, 36.2% had combination of hypertension, dyslipidemia and musculoskeletal diseases. More than 53.4% of the obese pre-diabetics had family history of diabetes, 15.7% were smokers and 60.8% were physically inactive with mean PA of <600 MET-minutes/week. After adjusted for co-variants, Physical Component Summary (PCS) was significantly associated with BMI categories [F (2,262)=11.73, p<0.001] where pre-diabetics with normal weight and overweight had significantly higher PCS than those obese; normal vs obese [Mdiff=9.84, p=0.006, 95% CIdiff=2.28, 17.40] and between overweight vs obese [Mdiff=8.14, p<0.001, 95% CIdiff=3.46, 12.80].
CONCLUSION: Pre-diabetics who were of normal weight reported higher HRQOL compared to those overweight and obese. These results suggest a potentially greater risk of poor HRQOL among pre-diabetics who were overweight and obese especially with regard to the physical health component. Promoting recommended amount of physical activity and weight control are particularly important interventions for pre-diabetics at the primary care level.
METHODS: We analysed data from 264,906 European adults from the EPIC prospective cohort study, aged between 40 and 70 years at the time of recruitment. Flexible parametric survival models were used to model risk of death conditional on risk factors, and survival functions and attributable fractions (AF) for deaths prior to age 70 years were calculated based on the fitted models.
RESULTS: We identified 11,930 deaths which occurred before the age of 70. The AF for premature mortality for smoking was 31 % (95 % confidence interval (CI), 31-32 %) and 14 % (95 % CI, 12-16 %) for poor diet. Important contributions were also observed for overweight and obesity measured by waist-hip ratio (10 %; 95 % CI, 8-12 %) and high blood pressure (9 %; 95 % CI, 7-11 %). AFs for physical inactivity and excessive alcohol intake were 7 % and 4 %, respectively. Collectively, the AF for all six risk factors was 57 % (95 % CI, 55-59 %), being 35 % (95 % CI, 32-37 %) among never smokers and 74 % (95 % CI, 73-75 %) among current smokers.
CONCLUSIONS: While smoking remains the predominant risk factor for premature death in Europe, poor diet, overweight and obesity, hypertension, physical inactivity, and excessive alcohol consumption also contribute substantially. Any attempt to minimise premature deaths will ultimately require all six factors to be addressed.
METHODS: Baseline plasma fatty acid concentrations were determined in a representative EPIC sample from the 23 participating EPIC centers. A total of 1,945 individuals were followed for a median of 4.9 years to monitor weight change. The association between elaidic acid level and percent change of weight was investigated using a multinomial logistic regression model, adjusted by length of follow-up, age, energy, alcohol, smoking status, physical activity, and region.
RESULTS: In women, doubling elaidic acid was associated with a decreased risk of weight loss (odds ratio (OR) = 0.69, 95% confidence interval (CI) = 0.55-0.88, p = 0.002) and a trend was observed with an increased risk of weight gain during the 5-year follow-up (OR = 1.23, 95% CI = 0.97-1.56, p = 0.082) (p-trend
METHODS: Housewives aged 18 to 59 years old from the MyBFF@home study were selected and pain was measured using the Visual Analogue Scale (VAS) questionnaire. VAS measured the pain intensity at different parts of the body (score of 0-10). Data were collected at base line, 3 months and 6 months among the housewives in both the control and intervention group. Pain scores and other variables (age, Body Mass Index (BMI) and waist circumference) were analysed using SPSS version 22.
RESULTS: A total of 328 housewives completed the VAS questionnaires at baseline, while 185 (56.4%) of housewives completed the VAS at 3 months and 6 months. A decreasing trend of mean pain score in both groups after 6 months was observed. However, the intervention group showed a consistent decreasing trend of pain score mainly for back pain. In the control group, there was a slight increment of score in back pain from baseline towards the 6 months period. Older housewives in both groups (aged 50 years and above) had a higher mean score of leg pain (2.86, SD: 2.82) compared to the other age group. Higher BMI was significantly associated with pain score in both groups.
CONCLUSION: There were some changes in the level of body pain among the housewives before and after the intervention. Older obese women had a higher pain score compared to younger obese women. Pain was associated with BMI and change in BMI appears to be beneficial in reducing body pain among overweight and obese individuals.
METHODS AND STUDY DESIGN: A cross-sectional study was conducted on 112 healthy men and women from 3 main ethnic group (Malay, Chinese, and Indian) who were aged 18-60 years. The participants were categorized into normal body mass index (BMI), overweight and obese groups according to WHO criteria for BMI in Asian populations (18.5 kg/m2