METHODS: Using a randomised double-blind crossover design, 21 (men = 6, women = 15) T2D subjects consumed test meals (3.65 MJ) consisting of a high fat muffin (containing 50 g test fats provided as PO, IPO or HOS) and a milkshake. Postprandial changes in gut hormones, glucose homeostasis, satiety, lipid and inflammatory parameters after meals were analysed. Some of the solid fractions of the IPO were removed and thus the fatty acid composition of the PO and IPO was not entirely equal (PO vs IPO: palmitate 39.8 vs 38.7; oleate 43.6 vs 45.1). PO, IPO and HOS contained 9.7, 38.9 and 0.2 g/100 g total fatty acids of palmitic acid at the sn-2 position, respectively. At 37 °C, IPO contained 4.2% SFC whereas PO and HOS were completely melted.
RESULTS: Our novel observation shows that the incremental area under curve (iAUC) 0-6 h of plasma GIP concentration was on average 16% lower following IPO meal compared with PO and HOS (P
METHODS: University and secondary school students from low-income households (N = 202) were involved in this cross-sectional study. Participants completed the Depression Literacy Questionnaire (D-Lit), General Help Seeking Questionnaire (GHSQ), Mental Help Seeking Attitudes Scale (MHSAS), Self-Stigma of Seeking Help Scale (SSOSH), and Beliefs toward Mental Illness (BMI).
RESULTS: Mental help-seeking attitude had a significant relationship with self-stigma on seeking help (r = -.258, p r = .156, p = .027), and age (r = .187, p
METHODS: Participants were identified from the Department of Statistics Malaysia sampling frame. Surveys were carried out with individual households aged 18 years and older through self-administered questionnaires. Information was collected on demographics, household income, employment status, number of diseases, and HRQOL assessed using the EuroQol 5-Dimension 5-Level (EQ-5D-5L) tool.
RESULTS: Out of a total of 1899 participants, 620 (32.6%) were female and 328 (17.3%) were aged 60 years and above. The mean (SD) age was 45.2 (14.1) and mean (SD) household income was RM2124 (1356). Compared with younger individuals, older respondents were more likely to experience difficulties in mobility (32.1% vs 9.7%, p<0.001), self-care (11.6% vs 3.8%, p<0.001), usual activities (24.5% vs 9.1%, p<0.001), pain/discomfort (38.8% vs 16.5%, p<0.001) and anxiety/depression (21.4% vs 13.5%, p<0.001). The mean (SD) EQ-5D index scores were lower among older respondents, 0.89 (0.16) vs 0.95 (0.13), p = 0.001. After adjusting for covariates, age was a significant influencing factor (p = 0.001) for mobility (OR = 2.038, 95% CI:1.439-2.885), usual activities (OR = 1.957, 95% CI:1.353-2.832) and pain or discomfort (OR = 2.241, 95% CI:1.690-2.972).
CONCLUSION: Lower-income older adults had poorer HRQOL compared to their younger counterparts. This has important implications concerning intervention strategies that incorporate active ageing concepts on an individual and policy-making level to enhance the QOL and wellbeing, particularly among the older lower-income population.
METHODS: Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was adopted for the review which utilized three main journal databases, namely PubMed, EBSCOhost, and Web of Science. Tobacco addiction and alcohol abuse were excluded in this review. Retrieved citations were screened, and the data were extracted based on strict inclusion and exclusion criteria. Inclusion criteria include the article being full text, published from the year 2016 until 2020 and provided via open access resource or subscribed to by the institution. Quality assessment was done using Mixed Methods Appraisal Tools (MMAT) version 2018 to assess the methodological quality of the included studies. Given the heterogeneity of the included studies, a descriptive synthesis of the included studies was undertaken.
RESULTS: Out of 425 articles identified, 22 quantitative articles and one qualitative article were included in the final review. Both the risk and protective factors obtained were categorized into three main domains: individual, family, and community factors. The individual risk factors identified were traits of high impulsivity; rebelliousness; emotional regulation impairment, low religious, pain catastrophic, homework completeness, total screen time and alexithymia; the experience of maltreatment or a negative upbringing; having psychiatric disorders such as conduct problems and major depressive disorder; previous e-cigarette exposure; behavioral addiction; low-perceived risk; high-perceived drug accessibility; and high-attitude to use synthetic drugs. The familial risk factors were prenatal maternal smoking; poor maternal psychological control; low parental education; negligence; poor supervision; uncontrolled pocket money; and the presence of substance-using family members. One community risk factor reported was having peers who abuse drugs. The protective factors determined were individual traits of optimism; a high level of mindfulness; having social phobia; having strong beliefs against substance abuse; the desire to maintain one's health; high paternal awareness of drug abuse; school connectedness; structured activity and having strong religious beliefs.
CONCLUSION: The outcomes of this review suggest a complex interaction between a multitude of factors influencing adolescent drug abuse. Therefore, successful adolescent drug abuse prevention programs will require extensive work at all levels of domains.
METHODS: We performed a cross-sectional study on KTRs with functioning renal allograft and at least 3 months post transplant. Dietary protein, salt, and dietary acid load were estimated using 24-hour urine collection. Demographic characteristics, concomitant medications, medical history, and laboratory results were obtained from electronic medical records.
RESULTS: A total of 204 KTRs were recruited with median age of 48 years (interquartile range [IQR], 18 years); male to female ratio was 61:39. A total of 79.9% (n = 163) were living related kidney transplants. The median duration after transplant was 71 months (IQR, 131 months), and median eGFR was 65 mL/min/1.73 m2 (IQR, 25 mL/min/1.73 m2). The prevalence rates of proteinuria (defined as ≥ 0.5 g/d) and metabolic acidosis (defined as at least 2 readings of serum bicarbonate ≤ 22 mmol/L in the past 6 months) were 17.7 % and 6.2%, respectively. High dietary protein of > 1.2 g/kg ideal body weight (adjusted odds ratio, 3.13; 95% CI, 1.35-7.28; P = .008) was significantly associated with proteinuria. Dietary protein, salt, and acid load did not correlate with chronic metabolic acidosis.
CONCLUSIONS: The prevalence rate of proteinuria is consistent with published literature, but metabolic acidosis rate is extremely low in our cohort. High protein intake (> 1.2 g/kg ideal body weight) is a risk factor of proteinuria and may have negative impact on KTR outcome.
METHODS: The South East Asia Community Observatory (SEACO) is a dynamic prospective community cohort. We contacted a random sample of 1007 adults (18+) who had previously provided PA data in 2018. We asked about PA during the MCO (March-May 2020) and at the time of interview (June 2020).
RESULTS: During the MCO, PA reduced by a mean of 6.7 hours/week (95% confidence interval (CI) = 5.3, 8.0) compared to 2018, with the largest reductions among those in employment. By June, PA was 3.4 hours/week (95% CI = 2.0, 4.8) less than 2018, leaving 34% of adults currently inactive (20% in 2018). Reductions in occupational PA were not replaced with active travel or activity at home. Despite these observed reductions, most participants did not think the MCO had affected their PA.
CONCLUSIONS: Movement restrictions are associated with lower PA lasting beyond the period of strict restrictions; such longer-term reductions in PA may have a detrimental impact on health. Future MCOs should encourage people to be active, but may additionally need targeted messaging for those who don't necessarily realise they are at risk. In particular, policies developed in more affluent countries may not easily translate to LMICs.
METHODS AND ANALYSIS: This two-phase sequential explanatory mixed-methods design, incorporating a quantitative design (phase I) and a qualitative study (phase II), is to be conducted in 4 government hospitals and 10 other non-governmental organisations or private dialysis centres within Klang Valley, Malaysia. A cross-sectional survey (phase I) will include 236 patient-caregiver dyads, while focus group discussions (phase II) will include 30 participants. The participants for both phases will be recruited purposively. Descriptive statistics, independent sample t-tests and multiple regression analysis will be used for analyses in phase I, and thematic analysis will be used in phase II.
ETHICS AND DISSEMINATION: Approval for the study has been obtained from the National Medical Research and Ethics Committee (MREC) (NMRR-21-1012-59714) and the Research Ethics Committee of Hospital Canselor Tuanku Muhriz UKM (UKM PPI/111/8/JEP-2021-078) and University of Malaya Medical Centre (MREC ID NO: 2 02 178-10346). Informed consent of the participants will be obtained beforehand, and no personal identifiers will be obtained from the participants to protect their anonymity. The findings will be published in peer-reviewed scientific journals and presented at national or international conferences with minimal anonymised data.
OBJECTIVE: This paper presents the protocol for a systematic review that aims to provide evidence of the impact of heat waves on health care services in LMICs.
METHODS: We will identify peer-reviewed studies from 3 online databases, including the Web of Science, PubMed, and SCOPUS, published from January 2002 to April 2023, using the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) guidelines. Quality assessment will be conducted using the Navigation Guide checklist. Key search terms include heatwaves, extreme heat, hospitalization, outpatient visit, burden, health services, and morbidity.
RESULTS: This systematic review will provide insight into the impact of heat waves on health care services in LMICs, especially on emergency department visits, ambulance call-outs, hospital admissions, outpatient department visits, in-hospital mortality, and health care operational costs.
CONCLUSIONS: The results of this review are anticipated to help policymakers and key stakeholders obtain a better understanding of the impact of heat waves on health care services and prioritize investments to mitigate the effects of heat waves in LMICs. This entails creating a comprehensive heat wave plan and ensuring that adequate infrastructure, capacity, and human resources are allocated in the health care sector. These measures will undoubtedly contribute to the development of resilience in health care systems and hence protect the health and well-being of individuals and communities.
TRIAL REGISTRATION: PROSPERO CRD42022365471; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=365471.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/44702.