METHODS: We used relevant key words to search electronic databases to identify studies published up to 2019 that used receiver operating characteristic (ROC) curves for assessing the cut-off points of anthropometric indices. We used a random-effects model to pool study results and assessed between-study heterogeneity by using the I2 statistic and Cochran's Q test.
RESULTS: This meta-analysis included 38 cross-sectional and 2 cohort studies with 105 to 137,256 participants aged 18 or older. The pooled area under the ROC curve (AUC) value for BMI was 0.66 (95% CI, 0.63-0.69) in both men and women. The pooled AUC values for WC were 0.69 (95% CI, 0.67-0.70) in men and 0.69 (95% CI, 0.64-0.74) in women, and the pooled AUC values for WHR were 0.69 (95% CI, 0.66-0.73) in men and 0.71 (95% CI, 0.68-0.73) in women.
CONCLUSION: Our findings indicated a slight difference between AUC values of these anthropometric indices. However, indices of abdominal obesity, especially WHR, can better predict CVD occurrence.
AIMS: To systematically identify and summarize the available literature on whether the modifiable risk factors associated with prediabetes displays similar relationship in both the genders.
METHODS: A systematic search was performed on electronic databases i.e. PubMed, EBSCOhost, and Scopus using "sex", "gender", "modifiable risk factors" and "prediabetes" as keywords. Reference list from identified studies was used to augment the search strategy. Methodological quality and results from individual studies were summarized in tables.
RESULTS: Gender differences in the risk factor association were observed among reviewed studies. Overall, reported association between risk factors and prediabetes apparently stronger among men. In particular, abdominal obesity, dyslipidemia, smoking and alcohol drinking habits were risk factors that showed prominent association among men. Hypertension and poor diet quality may appear to be stronger among women. General obesity showed stringent hold, while physical activity not significantly associated with the risk of prediabetes in both the genders.
CONCLUSIONS: Evidence suggests the existence of gender differences in risk factors associated with prediabetes, demands future researchers to analyze data separately based on gender. The consideration and the implementation of gender differences in health policies and in diabetes prevention programs may improve the quality of care and reduce number of diabetes prevalence among prediabetic subjects.
Methods: Analyses were performed on 243 women (mean body mass index 31.27 ± 4.14 kg/m2) who completed a 12-month lifestyle intervention in low socioeconomic communities in Klang Valley, Malaysia. Analysis of covariance (ANCOVA) was used to compare changes of cardiometabolic risk factors across weight change categories (2% gain, ±2% maintain, >2 to <5% loss, and 5 to 20% loss) within intervention and control group.
Results: A graded association for changes in waist circumference, fasting insulin, and total cholesterol (p=0.002, for all variables) across the weight change categories were observed within the intervention group at six months postintervention. Participants who lost 5 to 20% of weight had the greatest improvements in those risk markers (-5.67 cm CI: -7.98 to -3.36, -4.27 μU/mL CI: -7.35, -1.19, and -0.59 mmol/L CI: -.99, -0.19, respectively) compared to those who did not. Those who lost >2% to <5% weight reduced more waist circumference (-4.24 cm CI: -5.44 to -3.04) and fasting insulin (-0.36 μU/mL CI: -1.95 to 1.24) than those who maintained or gained weight. No significant association was detected in changes of risk markers across the weight change categories within the control group except for waist circumference and adiponectin.
Conclusion: Weight loss of >2 to <5% obtained through lifestyle intervention may represent a reasonable initial weight loss target for women in the low socioeconomic community as it led to improvements in selected risk markers, particularly of diabetes risk.
METHODS: A retrospective analysis of all patients with diverticulitis admitted from November 2015 to April 2018 at a single institution was performed. Data collected included demographics, vital signs, biochemistry results, CT scan findings and management outcomes. The patients were divided into uncomplicated (U) and complicated diverticulitis (C) groups. Visceral fat area (VFA), subcutaneous fat area (SFA) and VFA/SFA ratio (V/S) were measured at L4/L5 level by the radiologist. Statistical analysis was performed to evaluate the association of VFA, SFA, V/S with the parameters in both U and C groups.
RESULTS: 352 patients were included in this study (U:C = 265:87). There was no significant difference in vital signs and biochemistry results in both groups. There was no significant difference in VFA, SFA, V/S ratios in both groups. In patients with V/S ratio > 0.4, they were 5.06 times more likely to undergo emergency intervention (95% CI 1.10-23.45) (p = 0.03). On multivariate analysis, a heart rate > 100 (OR 2.9, 95% CI 1.2-6.7), CRP > 50 (OR 3.4, 95% CI 1.9-6.0), WCC 12 (OR 2.1, 95% CI 1.2-3.6) and V/S ratio > 0.4 (OR 2.8, 95% CI 1.5-5.4) were predictive of complicated diverticulitis.
CONCLUSION: The quantitative radiological measurement of visceral adiposity is useful in prognostication in patients presenting with diverticulitis.
DESIGN: A cross-sectional study administered using an online questionnaire.
SETTING: Conducted in 447 primary schools in a state in Malaysia.
PARTICIPANTS: One school administrator from each school served as a participant.
MEASURES: The questionnaires consisted of 32 items on awareness, policy implementation, and facilitators and barriers to policy implementation.
ANALYSIS: Descriptive analysis was used to describe the awareness, facilitators, and barriers of policies implementation. Association between schools' characteristics and policy implementation was assessed using logistic regression.
RESULTS: The majority (90%) of school administrators were aware of the policies. However, only 50% to 70% of schools had implemented the policies fully. Reported barriers were lack of equipment, insufficient training, and limited time to complete implementation. Facilitators of policy implementation were commitment from the schools, staff members, students, and canteen operators. Policy implementation was comparable in all school types and locality; except the policy on "Food and Drinks sold at the school canteens" was implemented by more rural schools compared to urban schools (odds ratio: 1.74, 95% confidence interval: 1.13-2.69).
CONCLUSION: Majority of the school administrators were aware of the existing policies; however, the implementation was only satisfactory. The identified barriers to policy implementation were modifiable and thus, the stakeholders should consider restrategizing plans in overcoming them.