METHODS: Sub-sample of 2,229 parent-offspring pairs with parental pre-pregnancy BMI and offspring BMI and WC at 21 years were used from the MUSP (Mater-University of Queensland Study of Pregnancy cohort). Multivariable results were adjusted for maternal factors around pregnancy (e.g. gestational weight and smoking during pregnancy) and offspring factors in early life (e.g. birth weight) and at 14 years (e.g. sports participation and mealtime with family).
RESULTS: After adjustments for confounders, each unit increase in paternal and maternal BMI, the BMI of young adult offspring increased by 0.33kg/m(2) and 0.35kg/m(2) , and the WC increased by 0.76 cm and 0.62 cm, respectively. In the combination of parents' weight status, offspring at 21 years were six times the risk being overweight/obese (OW/OB) when both parents were OW/OB, compared to offspring of healthy weight parents.
CONCLUSIONS: Prenatal parental BMI are independently related to adult offspring BMI and WC.
IMPLICATIONS: Both prenatal paternal-maternal weight status are important determinants of offspring weight status in long-term. Further studies are warranted to investigate the underlying mechanisms.
Methods: a cross-sectional study was conducted, using the Kedah audit samples data extracted from the National Diabetes Registry (NDR) from the year 2014 to 2018. A total of 25,062 registered type 2 diabetes mellitus patients were selected using the inclusion and exclusion criteria from the registry. Only patients with complete data on their HbA1C, lipid profile, waist circumference and BMI were analysed using SPSS version 21.
Results: the means for the age, BMI and waist circumference of the samples were 61.5 (±10.85) years, 27.3 (±5.05) kg/m2 and 89.46 (±13.58) cm, respectively. Poor glycaemic control (HbA1c>6.5%) was observed in 72.7% of the patients, with females having poorer glycaemic control. The BMI and waist circumference were found to be significantly associated with glycaemic control (P<0.001). The total cholesterol, triglycerides and low-density lipoproteins values showed positive correlation with glycaemic control (r = 0.178, 0.157, 0.145, p<0.001), while high-density lipoproteins values are negatively correlated (r = -0.019, p<0.001).
Conclusion: implementing lifestyle changes such as physical activity and dietary modifications are important in the management of BMI, waist circumference and body lipids, which in turn results in improved glycaemic control.