MATERIALS AND METHODS: This was a randomised control clinical trial at the Faculty of Dentistry, University of Malaya. A total of 66 obese patients with chronic periodontitis were randomly allocated into the treatment group (n=33) who received NSPT, while the control group (n=33) received no treatment. Four participants (2 from each group) were non-contactable 12 weeks post intervention. Therefore, their data were removed from the final analysis. The protocol involved questionnaires (characteristics and OHRQoL (Oral Health Impact Profile-14; OHIP-14)) and a clinical examination.
RESULTS: The OHIP prevalence of impact (PI), overall mean OHIP severity score (SS) and mean OHIP Extent of Impact (EI) at baseline and at the 12-week follow up were almost similar between the two groups and statistically not significant at (p=0.618), (p=0.573), and (p=0.915), respectively. However, in a within-group comparison, OHIP PI, OHIP SS, and OHIP EI showed a significant improvement for both treatment and control groups and the p values were ((0.002), (0.008) for PI), ((0.006) and (0.004) for SS) and ((0.006) and (0.002) for EI) in-treatment and control groups, respectively.
CONCLUSION: NSPT did not significantly affect the OHRQoL among those obese with CP. Regardless, NSPT, functional limitation and psychological discomfort domains had significantly improved.
TRIAL REGISTRATION: ( NCT02508415 ). Retrospectively registered on 2nd of April 2015.
METHODS: A cross-sectional study was conducted from November 2019 to August 2020 on T1DM children between 6 and 18 years old who attended the Paediatric Endocrine Clinic Putrajaya Hospital. Anthropometry and bioelectrical impedance analysis (Inbody 720) were measured to analyse their effects towards glycated haemoglobin (HbA1c) via SPSS 21.
RESULTS: A total of 63 T1DM were recruited with an equal male-to-female ratio. The mean age was 12.4 ± 3.3 years old with a mean HbA1c of 9.8 ± 2.0%. The prevalence of overweight/obese and excessive body fat was 17.5 and 34.9%, respectively. Only 3 (6.8%) fulfilled the metabolic syndrome criteria. The waist circumference had a significant relationship with HbA1c. Every 10 cm increment of waist circumference was predicted to raise HbA1c by 0.8. The odds ratio of having abdominal obesity among T1DM with excessive body fat was 9.3 times.
CONCLUSIONS: Abdominal obesity is significantly associated with a poorer glycaemic control in T1DM children. Monitoring of waist circumference should be considered as part of the routine diabetic care.
METHODS: This was a multi-centre, open-label randomised crossover study. Twenty-four overweight/obese T1DM patients aged ⩾18 years old with HbA1c ⩾ 7.0% (53 mmol/mol) were recruited and randomised into two study arms. For first 6-week, one arm remained on standard of care (SOC), the other arm received metformin, adjunctive to SOC. After 2-week washout, patients crossed over and continued for another 6 weeks. Glycaemic variability, other glycaemic parameters and metabolic profile were monitored.
RESULTS: There were significant reduction in metformin group for GV: mean (0.18 ± 1.73 vs -0.95 ± 1.24, p = 0.014), %CV (-15.84 (18.92) vs -19.08 (24.53), p = 0.044), glycemic risk assessment of diabetes equation (-0.69 (3.83) vs -1.61 (3.61), p = 0.047), continuous overlapping net glycaemic action (0.25 ± 1.62 vs -0.85 ± 1.22, p = 0.013), J-index (-0.75 (21.91) vs -7.11 (13.86), p = 0.034), time in range (1.13 ± 14.12% vs 10.83 ± 15.47%, p = 0.032); changes of systolic blood pressure (2.78 ± 11.19 mmHg vs -4.30 ± 9.81 mmHg, p = 0.027) and total daily dose (TDD) insulin (0.0 (3.33) units vs -2.17 (11.45) units, p = 0.012). Hypoglycaemic episodes were not significant in between groups.
CONCLUSION: Metformin showed favourable effect on GV in overweight/obese T1DM patients and reduction in systolic blood pressure, TDD insulin, fasting venous glucose and fructosamine.
METHODS: Population-based surveys included 30,721 Malay, 10,865 Indian and 25,296 Chinese adults from The Malaysian Cohort, and 413,737 White adults from UK Biobank. Sex-specific linear regression models estimated associations of anthropometry and body composition (body mass index [BMI], waist circumference [WC], fat mass, appendicular lean mass) with systolic blood pressure (SBP), low-density lipoprotein cholesterol (LDL-C), triglycerides and HbA1c.
RESULTS: Compared to Malay and Indian participants, Chinese adults had lower BMI and fat mass while White participants were taller with more appendicular lean mass. For BMI and fat mass, positive associations with SBP and HbA1c were strongest among the Chinese and Malay and weaker in White participants. Associations with triglycerides were considerably weaker in those of Indian ethnicity (eg 0.09 [0.02] mmol/L per 5 kg/m2 BMI in men, vs 0.38 [0.02] in Chinese). For appendicular lean mass, there were weak associations among men; but stronger positive associations with SBP, triglycerides, and HbA1c, and inverse associations with LDL-C, among Malay and Indian women. Associations between WC and risk factors were generally strongest in Chinese and weakest in Indian ethnicities, although this pattern was reversed for HbA1c.
CONCLUSION: There were distinct patterns of adiposity and body composition and cardiovascular risk factors across ethnic groups. We need to better understand the mechanisms relating body composition with cardiovascular risk to attenuate the increasing global burden of obesity-related disease.
METHODS: Multivariable-adjusted Cox proportional hazards models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). After an average of 13.9 years of follow-up, there were 7024 incident prostate cancers and 934 prostate cancer deaths.
RESULTS: Height was not associated with total prostate cancer risk. Subgroup analyses showed heterogeneity in the association with height by tumour grade (P heterogeneity = 0.002), with a positive association with risk for high-grade but not low-intermediate-grade disease (HR for high-grade disease tallest versus shortest fifth of height, 1.54; 95% CI, 1.18-2.03). Greater height was also associated with a higher risk for prostate cancer death (HR = 1.43, 1.14-1.80). Body mass index (BMI) was significantly inversely associated with total prostate cancer, but there was evidence of heterogeneity by tumour grade (P heterogeneity = 0.01; HR = 0.89, 0.79-0.99 for low-intermediate grade and HR = 1.32, 1.01-1.72 for high-grade prostate cancer) and stage (P heterogeneity = 0.01; HR = 0.86, 0.75-0.99 for localised stage and HR = 1.11, 0.92-1.33 for advanced stage). BMI was positively associated with prostate cancer death (HR = 1.35, 1.09-1.68). The results for waist circumference were generally similar to those for BMI, but the associations were slightly stronger for high-grade (HR = 1.43, 1.07-1.92) and fatal prostate cancer (HR = 1.55, 1.23-1.96).
CONCLUSIONS: The findings from this large prospective study show that men who are taller and who have greater adiposity have an elevated risk of high-grade prostate cancer and prostate cancer death.
METHODS: We examined associations of body mass index (BMI), waist circumference (WC), and waist-hip ratio (WHR) with lung cancer risk among 1.6 million Americans, Europeans, and Asians. Cox proportional hazard regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) with adjustment for potential confounders. Analyses for WC/WHR were further adjusted for BMI. The joint effect of BMI and WC/WHR was also evaluated.
RESULTS: During an average 12-year follow-up, 23 732 incident lung cancer cases were identified. While BMI was generally associated with a decreased risk, WC and WHR were associated with increased risk after controlling for BMI. These associations were seen 10 years before diagnosis in smokers and never smokers, were strongest among blacks, and varied by histological type. After excluding the first five years of follow-up, hazard ratios per 5 kg/m2 increase in BMI were 0.95 (95% CI = 0.90 to 1.00), 0.92 (95% CI = 0.89 to 0.95), and 0.89 (95% CI = 0.86 to 0.91) in never, former, and current smokers, and 0.86 (95% CI = 0.84 to 0.89), 0.94 (95% CI = 0.90 to 0.99), and 1.09 (95% CI = 1.03 to 1.15) for adenocarcinoma, squamous cell, and small cell carcinoma, respectively. Hazard ratios per 10 cm increase in WC were 1.09 (95% CI = 1.00 to 1.18), 1.12 (95% CI = 1.07 to 1.17), and 1.11 (95% CI = 1.07 to 1.16) in never, former, and current smokers, and 1.06 (95% CI = 1.01 to 1.12), 1.20 (95% CI = 1.12 to 1.29), and 1.13 (95% CI = 1.04 to 1.23) for adenocarcinoma, squamous cell, and small cell carcinoma, respectively. Participants with BMIs of less than 25 kg/m2 but high WC had a 40% higher risk (HR = 1.40, 95% CI = 1.26 to 1.56) than those with BMIs of 25 kg/m2 or greater but normal/moderate WC.
CONCLUSIONS: The inverse BMI-lung cancer association is not entirely due to smoking and reverse causation. Central obesity, particularly concurrent with low BMI, may help identify high-risk populations for lung cancer.
METHODS: We investigated overall obesity and abdominal adiposity in relation to SIC in the European Prospective Investigation into Cancer and Nutrition (EPIC), a large prospective cohort of approximately half a million men and women from ten European countries. Overall obesity and abdominal obesity were assessed by body mass index (BMI), waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR). Multivariate Cox proportional hazards regression modeling was performed to estimate hazard ratios (HRs) and 95 % confidence intervals (CIs). Stratified analyses were conducted by sex, BMI, and smoking status.
RESULTS: During an average of 13.9 years of follow-up, 131 incident cases of SIC (including 41 adenocarcinomas, 44 malignant carcinoid tumors, 15 sarcomas and 10 lymphomas, and 21 unknown histology) were identified. WC was positively associated with SIC in a crude model that also included BMI (HR per 5-cm increase = 1.20, 95 % CI 1.04, 1.39), but this association attenuated in the multivariable model (HR 1.18, 95 % CI 0.98, 1.42). However, the association between WC and SIC was strengthened when the analysis was restricted to adenocarcinoma of the small intestine (multivariable HR adjusted for BMI = 1.56, 95 % CI 1.11, 2.17). There were no other significant associations.
CONCLUSION: WC, rather than BMI, may be positively associated with adenocarcinomas but not carcinoid tumors of the small intestine.
IMPACT: Abdominal obesity is a potential risk factor for adenocarcinoma in the small intestine.