METHODS: We systemically searched PubMed, CENTRAL and Scopus up to June 2018. We searched for published interventional studies on biomarkers of glucose metabolism (defined as fasting glucose, fasting insulin, HOMA, 2-hour post prandial glucose and HbA1C) that compared palm oil- or palm olein-rich diets with other edible vegetable oils (such as olive oil, canola oil and soybean oil). Two reviewers independently extracted data and assessed study risks of bias. Mean differences of outcomes were pooled for the meta-analysis.
RESULTS: We identified 1921 potentially eligible articles with only eight included studies. Seven randomised cross-over trials and one parallel trial were included. Study population were among young to middle-aged, healthy, non-diabetic, and normal weight participants. Intervention duration ranged from three to seven weeks, and fat substitution ranged from 15% to 20% energy. There were insignificant differences in fasting glucose when compared to partially hydrogenated soybean oil [-0.15mmol/L (-0.46,0.16) P = 0.33, I2 = 48%], soybean oil [0.05mmol/L (-0.09,0.18) P = 0.49, I2 = 0%] and olive oil [0.04mmol/L (-0.09,0.17) P = 0.76, I2 = 0%]. Insignificant effects were also seen on fasting insulin when compared to partially hydrogenated soybean oil [1.72pmol/L (-11.39,14.84) P = 0.80, I2 = 12%] and olive oil diet [-0.14pmol/L (-4.87,4.59) P = 0.95, I2 = 0%].
CONCLUSION: Current evidence on the effects of palm oil consumption on biomarkers of glucose metabolism is poor and limited to only healthy participants. We conclude that little or no additional benefit will be obtained by replacing palm oil with other oils rich in mono or polyunsaturated fatty acids for changes in glucose metabolism.
METHODS: This study adopted a comparative case study design with a qualitative focus to identify similarities and differences of the potential barriers and facilitators to implementing the insulin PDA across different sites. Focus groups and individual interviews were conducted with 28 healthcare providers and 15 patients from five public health clinics under the Ministry of Health in Malaysia. The interviews were transcribed verbatim and analysed using the thematic approach.
RESULTS: Five themes emerged which were: 1) time constraint; 2) PDA costs; 3) tailoring PDA use to patient profile; 4) patient decisional role; and 5) leadership and staff motivation. Based on the interviews and drawing on observations and interview reflection notes, time constraint emerged as the common prominent factor that cut across all the clinics, however, tailoring PDA use to patient profile; patient decisional role; leadership and staff motivation varied due to the distinct challenges faced by specific clinics. Among clinics from semi-urban areas with more patients from limited education and lower socio-economic status, patients' ability to comprehend the insulin PDA and their tendency to rely on their doctors and family to make health decisions were felt to be a prominent barrier to the insulin PDA implementation. Staff motivation appeared to be stronger in most of the clinics where specific time was allocated to diabetes team to attend to diabetes patients and this was felt could be a potential facilitator, however, a lack of leadership might affect the insulin PDA implementation even though a diabetes team is present.
CONCLUSIONS: This study found time constraint as a major potential barrier for PDA implementation and effective implementation of the insulin PDA across different public health clinics would depend on leadership and staff motivation and, the need to tailor PDA use to patient profile. To ensure successful implementation, implementers should avoid a 'one size fits all' approach when implementing health innovations.
METHODS: A set of 74 items based on a conceptual framework analysis underwent revision and its content validity was established. Items were grouped into three domains. A development study was conducted to establish evidence regarding their factorial structure. A construct validation study was then conducted in which the retained items were tested in an independent sample using confirmatory factor analysis (CFA).
RESULTS: Four factors emerged from our development study and were labelled as pre-travel preparation-insect bites, pre-travel preparation-consultation, insulin and glycaemic control and travel risk behaviour. A CFA confirmed the factorial structure identified in the development study in an independent sample. Each factor loading had a significant (P insulin and glycaemic control (6.45), followed by travel risk behaviour (5.21) and pre-travel preparation (4.15).
CONCLUSIONS: This valid questionnaire for measuring the degree of preparedness of travellers with type 1 diabetes may prove a useful tool in studies involving travellers with type1 diabetes. Our results suggest that improvements are needed in relation to timely pre-travel consultation and screening for diabetic complications.