Ethnic variation in the impact of metabolic syndrome components and chronic kidney disease

Association between Body Mass Index and Chronic Kidney Disease in Asian Populations: A Participant-level Meta-Analysis

Obesity and chronic kidney disease (CKD) are major public health problems worldwide. However, the association between body mass index (BMI) and CKD is inconclusive in Asians. In this meta-analysis, eight population-based studies, from China, India, Russia (Asian), Singapore and South Korea, provided individual-level data (n=50037). CKD was defined as an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m². BMI was analyzed both as a continuous variable and in three categories: <25kg/m², normal; 25-29.9kg/m², overweight; and ≥30kg/m², obese. The association between BMI and CKD was evaluated in each study using multivariable logistic regression models and individual estimates were pooled using random-effect meta-analysis to obtain the pooled odds ratio (OR) and 95% confidence interval (CI). Associations were also evaluated in subgroups of age, gender, smoking, diabetes, and hypertension status. Of 50037 adults, 4258 (8.5%) had CKD. 13328 (26.6%) individuals were overweight while 4440 (8.9%) were obese. The prevalence of any CKD ranged from 3.5% to 29.1% across studies. In pooled analysis, both overweight and obesity were associated with increased odds of CKD, with pooled OR (95% CI) of 1.15 (1.03-1.29) and 1.23 (1.06-1.42), respectively. In subgroup analyses, significant associations between BMI and CKD were observed in adult males, non-smokers, and those with diabetes and arterial hypertension (all p<0.05). When evaluated as a continuous variable, BMI was not significantly associated with CKD. If confirmed in longitudinal studies, these results may have clinical implications in risk stratification and preventive measures, given that obesity and CKD are two major chronic diseases with substantial public health burden worldwide.

Determinants of poor sleep quality in elderly patients with diabetes mellitus, hyperlipidemia and hypertension in Singapore

AimThe objective of this study was to assess determinants of poor sleep quality which is an under-diagnosed and under-treated problem in elderly patients with diabetes mellitus, hyperlipidemia and hypertension. BACKGROUND: Poor sleep quality is linked to decreased quality of life, increased morbidity and mortality. Poor sleep quality is common in the elderly population with associated cardiometabolic risk factors such as diabetes, hyperlipidemia and hypertension. METHODS: This is a cross-sectional study undertaken in the primary healthcare setting (Singhealth Polyclinics-Outram) in Singapore. Singaporeans aged 65 years and above who had at least one of the three cardiometabolic risk factors (diabetes, hypertension and hyperlipidemia) were identified. Responders' sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) questionnaire and were divided into those with good quality sleep and those with poor quality sleep, based on the PSQI score. Information on demographics, co-morbidities and lifestyle practices were collected. Descriptive and multivariate analyses of determinants of poor sleep were determined.FindingsThere were 199 responders (response rate 88.1%). Nocturia (adjusted prevalence rate ratio 1.54, 95% confidence interval 1.06-2.26) was found to be associated with an increased risk of poor sleep quality in elderly patients with diabetes mellitus, hypertension and hyperlipidaemia. Nocturia, a prevalent problem in the Asian elderly population, has been found to be associated with poor sleep quality in our study. Hence, it is imperative to identify and treat patients with nocturia to improve sleep quality among them.

Clinical review: Drugs commonly associated with weight change: a systematic review and meta-analysis

CONTEXT

Various drugs affect body weight as a side effect.

OBJECTIVE

We conducted this systematic review and meta-analysis to summarize the evidence about commonly prescribed drugs and their association with weight change.

DATA SOURCES

MEDLINE, DARE, and the Cochrane Database of Systematic Reviews were searched to identify published systematic reviews as a source for trials.

STUDY SELECTION

We included randomized trials that compared an a priori selected list of drugs to placebo and measured weight change.

DATA EXTRACTION

We extracted data in duplicate and assessed the methodological quality using the Cochrane risk of bias tool.

RESULTS

We included 257 randomized trials (54 different drugs; 84 696 patients enrolled). Weight gain was associated with the use of amitriptyline (1.8 kg), mirtazapine (1.5 kg), olanzapine (2.4 kg), quetiapine (1.1 kg), risperidone (0.8 kg), gabapentin (2.2 kg), tolbutamide (2.8 kg), pioglitazone (2.6 kg), glimepiride (2.1 kg), gliclazide (1.8 kg), glyburide (2.6 kg), glipizide (2.2 kg), sitagliptin (0.55 kg), and nateglinide (0.3 kg). Weight loss was associated with the use of metformin (1.1 kg), acarbose (0.4 kg), miglitol (0.7 kg), pramlintide (2.3 kg), liraglutide (1.7 kg), exenatide (1.2 kg), zonisamide (7.7 kg), topiramate (3.8 kg), bupropion (1.3 kg), and fluoxetine (1.3 kg). For many other remaining drugs (including antihypertensives and antihistamines), the weight change was either statistically nonsignificant or supported by very low-quality evidence.

CONCLUSIONS

Several drugs are associated with weight change of varying magnitude. Data are provided to guide the choice of drug when several options exist and institute preemptive weight loss strategies when obesogenic drugs are prescribed.