OBJECTIVE: To identify how to improve surveillance of movement behaviours, from the perspective of experts.
METHODS: This Delphi Study involved 62 experts from the SUNRISE International Study of Movement Behaviours in the Early Years and Active Healthy Kids Global Alliance (AHKGA). Two survey rounds were used, with items categorised under: (1) funding, (2) capacity building, (3) methods, and (4) other issues (e.g., policymaker awareness of relevant WHO Guidelines and Strategies). Expert participants ranked 40 items on a five-point Likert scale from 'extremely' to 'not at all' important. Consensus was defined as > 70% rating of 'extremely' or 'very' important.
RESULTS: We received 62 responses to round 1 of the survey and 59 to round 2. There was consensus for most items. The two highest rated round 2 items in each category were the following; for funding (1) it was greater funding for surveillance and public funding of surveillance; for capacity building (2) it was increased human capacity for surveillance (e.g. knowledge, skills) and regional or global partnerships to support national surveillance; for methods (3) it was standard protocols for surveillance measures and improved measurement method for screen time; and for other issues (4) it was greater awareness of physical activity guidelines and strategies from WHO and greater awareness of the importance of surveillance for NCD prevention. We generally found no significant differences in priorities between low-middle-income (n = 29) and high-income countries (n = 30) or between SUNRISE (n = 20), AHKGA (n = 26) or both (n = 13) initiatives. There was a lack of agreement on using private funding for surveillance or surveillance research.
CONCLUSIONS: This study provides a prioritised and international consensus list of actions required to improve surveillance of movement behaviours in children and adolescents globally.
METHODS: We surveyed 16 512 adults from July 2020 to August 2021 in 30 territories. Participants self-reported their medical histories and the perceived impact of COVID-19 on 18 lifestyle factors and 13 health outcomes. For each disease subgroup, we generated lifestyle, health outcome, and bridge networks. Variables with the highest centrality indices in each were identified central or bridge. We validated these networks using nonparametric and case-dropping subset bootstrapping and confirmed central and bridge variables' significantly higher indices through a centrality difference test.
FINDINGS: Among the 48 networks, 44 were validated (all correlation-stability coefficients >0.25). Six central lifestyle factors were identified: less consumption of snacks (for the chronic disease: anxiety), less sugary drinks (cancer, gastric ulcer, hypertension, insomnia, and pre-diabetes), less smoking tobacco (chronic obstructive pulmonary disease), frequency of exercise (depression and fatty liver disease), duration of exercise (irritable bowel syndrome), and overall amount of exercise (autoimmune disease, diabetes, eczema, heart attack, and high cholesterol). Two central health outcomes emerged: less emotional distress (chronic obstructive pulmonary disease, eczema, fatty liver disease, gastric ulcer, heart attack, high cholesterol, hypertension, insomnia, and pre-diabetes) and quality of life (anxiety, autoimmune disease, cancer, depression, diabetes, and irritable bowel syndrome). Four bridge lifestyles were identified: consumption of fruits and vegetables (diabetes, high cholesterol, hypertension, and insomnia), less duration of sitting (eczema, fatty liver disease, and heart attack), frequency of exercise (autoimmune disease, depression, and heart attack), and overall amount of exercise (anxiety, gastric ulcer, and insomnia). The centrality difference test showed the central and bridge variables had significantly higher centrality indices than others in their networks (P
METHODS: A cohort of 686 women (376 Chinese, 186 Malay, and 124 Indian) with a singleton pregnancy attended a clinic visit at 26-28 weeks of gestation as part of the Growing Up in Singapore Towards healthy Outcomes mother-offspring cohort study. Self-reported sleep quality and sleep duration were assessed using the Pittsburgh Sleep Quality Index (PSQI). GDM was diagnosed based on a 75-g oral glucose tolerance test administered after an overnight fast (1999 WHO criteria). Multiple logistic regression was used to model separately the associations of poor sleep quality (PSQI score > 5) and short nocturnal sleep duration (<6 h) with GDM, adjusting for age, ethnicity, maternal education, body mass index, previous history of GDM, and anxiety (State-Trait Anxiety Inventory score).
RESULTS: In the cohort 296 women (43.1%) had poor sleep quality and 77 women (11.2%) were categorized as short sleepers; 131 women (19.1%) were diagnosed with GDM. Poor sleep quality and short nocturnal sleep duration were independently associated with increased risk of GDM (poor sleep, adjusted odds ratio [OR] = 1.75, 95% confidence interval [CI] 1.11 to 2.76; short sleep, adjusted OR = 1.96, 95% CI 1.05 to 3.66).
CONCLUSIONS: During pregnancy, Asian women with poor sleep quality or short nocturnal sleep duration exhibited abnormal glucose regulation. Treating sleep problems and improving sleep behavior in pregnancy could potentially reduce the risk and burden of GDM.
METHODS: Ten government maternal and child health clinics in Kuala Lumpur, Malaysia will be randomly selected. Sample size of 438 first-trimester pregnant women will be followed-up until the birth of their infant. Salivary melatonin and cortisol concentration among subsample will be determined using enzyme-linked immunosorbent assay. Data on sleep quality, psychological distress and morningness/eveningness chronotype of pregnant women will be collected using validated questionnaires. Pedometer will be used to measure 5-day physical activity data. Total gestational weight gain will be determined at the end of pregnancy. Utilization of 3-day food record is to capture meal timing and nutrient intake. All measurements will be done in 2nd and 3rd trimester. Birth outcomes will be collected through clinic records and Centers for Disease Control and Prevention (CDC) Neonatal questionnaire. Infants will be followed-up at 6 and 12 months old to obtain anthropometric measurements.
DISCUSSION: There is a growing recognition of the role of maternal circadian rhythm, which entrains fetal circadian rhythms that may subsequently have long-term health consequences. The present study will identify the effect of circadian rhythm on pregnancy outcomes and infant growth in the first year of life.
METHOD: A systematic review and metanalysis was conducted in accordance with the PRISMA criteria. The PubMed, Scopus, Science direct, Web of science, CINHAL, Medline, and Google Scholar databases were searched with no lower time-limt and until 24 June 2020. The heterogeneity of the studies was measured using I2 test and the publication bias was assessed by the Egger's test at the significance level of 0.05.
RESULTS: The I2 test was used to evaluate the heterogeneity of the selected studies, based on the results of I2 test, the prevalence of sleep disturbances in nurses and physicians is I2: 97.4% and I2: 97.3% respectively. After following the systematic review processes, 7 cross-sectional studies were selected for meta-analysis. Six studies with the sample size of 3745 nurses were examined in and the prevalence of sleep disturbances was approximated to be 34.8% (95% CI: 24.8-46.4%). The prevalence of sleep disturbances in physicians was also measured in 5 studies with the sample size of 2123 physicians. According to the results, the prevalence of sleep disturbances in physicians caring for the COVID-19 patients was reported to be 41.6% (95% CI: 27.7-57%).
CONCLUSION: Healthcare workers, as the front line of the fight against COVID-19, are more vulnerable to the harmful effects of this disease than other groups in society. Increasing workplace stress increases sleep disturbances in the medical staff, especially nurses and physicians. In other words, increased stress due to the exposure to COVID-19 increases the prevalence of sleep disturbances in nurses and physicians. Therefore, it is important for health policymakers to provide solutions and interventions to reduce the workplace stress and pressures on medical staff.
MATERIALS AND METHODS: A descriptive study involved 58 Malays and 15 Chinese women newly diagnosed with breast cancer prior to treatment. Quality of life was measured using the Malay version of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) and its breast-specific module (QLQ-BR23). Socio-demographic and clinical data were also collected. All the data were analyzed using SPSS version 20.0.
RESULTS: Most of the women were married with at least a secondary education and were in late stages of breast cancer. The Malay women had lower incomes (p=0.046) and more children (p=0.001) when compared to the Chinese women. Generally, both the Malay and Chinese women had good functioning quality-of-life scores [mean score range: 60.3-84.8 (Malays); 65.0-91.1 (Chinese)] and global quality of life [mean score 60.3, SD 22.2 (Malays); mean score 65.0, SD 26.6 (Chinese)]. The Malay women experienced more symptoms such as nausea and vomiting (p=0.002), dyspnoea (p=0.004), constipation (p<0.001) and breast-specific symptoms (p=0.041) when compared to the Chinese.
CONCLUSIONS: Quality of life was satisfactory in both Malays and Chinese women newly diagnosed with breast cancer in Kelantan. However, Malay women had a lower quality of life due to high general as well as breast-specific symptoms. This study finding underlined the importance of measuring quality of life in the newly diagnosed breast cancer patient, as it will provide a broader picture on how a cancer diagnosis impacts multi-ethnic patients. Once health care professionals understand this, they might then be able to determine how to best support and improve the quality of life of these women during the difficult times of their disease and on-going cancer treatments.