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Aims: In a high-income country, Australia, it is unclear how raised systolic blood pressure (SBP) ranks among other risk factors regarding the overall and cardiovascular disease (CVD) burden, and whether the situation has changed over time. Methods: We analysed the 2019 Global Burden of Disease (GBD) data, with focus on Australia. We assessed ten leading risk factors for all-cause and CVD deaths and disability-adjusted life-years (DALYs) and compared findings with the Australian Burden of Diseases Study. Results: From 1990 to 2019, raised SBP remained the leading risk factor for attributable all-cause deaths (followed by dietary risks and tobacco use), accounting for 29,056/75,235 (95% Uncertainty Interval (UI) [24,863 to 32,915]) deaths in 1990; 21,845/76,893 [17,678 to 26,044] in 2010; and 25,498/90,393 [20,152 to 30,851] in 2019. Contributions of raised SBP to cardiovascular deaths for both sexes were 54.0% [45.8 to 61.5] in 1990, 44.0% [36.7 to 51.3] in 2010 and 43.7% [36.2 to 51.6] in 2019, respectively. The contribution of raised SBP to cardiovascular deaths declined between 1990 and 2010 but exhibited an increase in males from 2010 onwards, with figures of 52.6% [44.7 to 60.0] in 1990, 43.1% [36.0 to 50.5] in 2010 and 43.5% [35.7 to 51.4] in 2019. The contribution of raised SBP to stroke deaths and DALYs in males aged 25–49 years were higher than other age groups, in excess of 60% and increasing steeply between 2010 and 2019. Conclusion: Raised SBP continues to be the leading risk factor for all-cause and cardiovascular deaths in Australia. We urge cross-disciplinary stakeholder engagement to implement effective strategies to detect, treat and control raised blood pressure as a central priority to mitigate the CVD burden. [ABSTRACT FROM AUTHOR]

Lifestyle risk behaviours such as smoking, physical inactivity, and unhealthy diet account for a considerable disease burden globally. These risk behaviours tend to cluster within an individual, which could have detrimental health effects. In this study, we aimed to examine the clustering effect of lifestyle risk behaviours on cardiovascular disease (CVD) and CVD risk among adults in the United Kingdom (UK). We performed a latent class (LC) analysis with distal outcomes using the UK Biobank baseline (2006–2010) data. First, we estimated LC measurement models, followed by an auxiliary model conditional on LC variables. We reported continuous (mean difference—MD) and binary (odds ratio—OR) outcomes with 95% confidence intervals. We included 283,172 and 174,030 UK adults who had data on CVD and CVD risk, respectively. Multiple lifestyle risk behaviour clustering (physically inactive, poor fruit & vegetable intake, high alcohol intake, and prolonged sitting) had a 3.29 mean increase in CVD risk compared to high alcohol intake. In addition, adults with three risk behaviours (physically inactive, poor fruit & vegetable intake, and high alcohol intake) had 25.18 higher odds of having CVD than those with two risk behaviours (physically inactive, and poor fruit and vegetable intake). Social deprivation, gender and age were also associated with CVD. Individuals' LC membership with two or more lifestyle risk behaviours negatively affects CVD. Interventions targeting multiple lifestyle behaviours and social circumstances should be prioritized to reduce the CVD burden. [ABSTRACT FROM AUTHOR]

Background: The current pandemic of COVID-19 impacted the psychological wellbeing of populations globally.Objectives: We aimed to examine the extent and identify factors associated with psychological distress, fear of COVID-19 and coping.Methods: We conducted a cross-sectional study across 17 countries during Jun-2020 to Jan-2021. Levels of psychological distress (Kessler Psychological Distress Scale), fear of COVID-19 (Fear of COVID-19 Scale), and coping (Brief Resilient Coping Scale) were assessed.Results: A total of 8,559 people participated; mean age (±SD) was 33(±13) years, 64% were females and 40% self-identified as frontline workers. More than two-thirds (69%) experienced moderate-to-very high levels of psychological distress, which was 46% in Thailand and 91% in Egypt. A quarter (24%) had high levels of fear of COVID-19, which was as low as 9% in Libya and as high as 38% in Bangladesh. More than half (57%) exhibited medium to high resilient coping; the lowest prevalence (3%) was reported in Australia and the highest (72%) in Syria. Being female (AOR 1.31 [95% CIs 1.09-1.57]), perceived distress due to change of employment status (1.56 [1.29-1.90]), comorbidity with mental health conditions (3.02 [1.20-7.60]) were associated with higher levels of psychological distress and fear. Doctors had higher psychological distress (1.43 [1.04-1.97]), but low levels of fear of COVID-19 (0.55 [0.41-0.76]); nurses had medium to high resilient coping (1.30 [1.03-1.65]).Conclusions: The extent of psychological distress, fear of COVID-19 and coping varied by country; however, we identified few higher risk groups who were more vulnerable than others. There is an urgent need to prioritise health and well-being of those people through well-designed intervention that may need to be tailored to meet country specific requirements. [ABSTRACT FROM AUTHOR]

Background: Depression is a common disorder that can lead to suicidal behaviours among the geriatric population. Aim: We aimed to assess depression, hopelessness, and suicidal ideation among the elderly population of Kashmir. Methods: A community-based cross-sectional study was conducted in three districts of Kashmir between June and August 2019. The sample consisted of 200 persons aged >65 years. Beck's Depression Inventory, Beck's Hopelessness Scale, and the Beck Suicide Ideation scale were used to determine depression, hopelessness, and suicide ideation. Pearson's correlation was performed to assess the relationships between depression, hopelessness, and suicide. Results: The prevalence of severe depression with a score of ⩾31 on Beck's Depression Inventory was 56% among the studied population. Most of these elderly were found to have moderate levels of suicidal ideation (62.5%) and hopelessness (61%). Depression had a positive correlation with suicidal ideation (r = 0.35). Hopelessness and suicidal intent had a more significant positive correlation (r = 0.54), as compared to depression and hopelessness (r = 0.43). Conclusion: More than half of the older persons in Kashmir had depression with superimposed hopelessness which is an important risk factor of suicidal ideation. [ABSTRACT FROM AUTHOR]

Purpose: To assess the relationship between healthcare seeking behaviors and glycemic control in patients with type 2 diabetes. Methods: A secondary data analysis was conducted among patients with type 2 diabetes from a randomized controlled trial conducted in a tertiary hospital, Bangladesh. Data on health center use, healthcare providers visited, self-monitoring of blood glucose, blood pressure, foot care, and physical activity were collected through structured questionnaires. Uncontrolled diabetes was defined as HbA1c ≥ 7%. Multivariable logistic regression models were performed. Result: Of the 265 patients (mean age 50.3 ± 9.9 years; 49.8% females), the majority (71.3%) had uncontrolled diabetes. More than one-third (34.9%) of the participants did not visit their physician or a healthcare center during the previous 3-months. Only 12.4% of participants checked their blood glucose, and 35.8% checked their blood pressure during the last week. Participants who did not visit a physician or a healthcare center during the past 3 months had twice the odds of having uncontrolled diabetes, compared with those who visited during the same period [OR 2.12, 95% CI (1.02–5.14), p = 0.04]. Conclusion: Regular consultation with a physician or visiting a healthcare center might help to improve glycemic control in patients with type 2 diabetes in Bangladesh. [ABSTRACT FROM AUTHOR]

Aim: Unintended pregnancy is a significant public health concern in South Asian countries because of its negative association with the socioeconomic and health outcomes for both children and mothers. The present study aimed to explore the prevalence of unintended pregnancy and explore its determinants among women of reproductive age in six South Asian countries. Methods: Nationwide latest demography and health survey data from six South Asian countries, including Bangladesh (2014), Pakistan (2017–2018), Nepal (2016), Afghanistan (2015), Maldives (2016–2017) and India (2015–2016) were pooled for the present study. Multivariate analysis was performed to explore the association between unintended pregnancy and its associated factors. Results: Amongst the total women (n = 41,689), overall, 19.1% pregnancies were reported as unintended (ranging from 11.9% in India to 28.4% in Bangladesh). The logistic regression model showed that younger women (15–19 years) had 1.42 times higher chance of unintended pregnancies. The odds of unintended pregnancies was 1.24 times higher for poorest women and 1.19 times higher for poorer women. Further, urban women (aOR = 0.70, 95% CI = 0.50–0.80), women having no children (aOR = 0.10, 95% CI = 0.09–0.12), smaller (≤4) family (aOR = 0.72, 95% CI = 0.67–0.78), those who intent to use contraceptive (aOR = 0.72, 95% CI = 0.60–0.86), currently living with partner (aOR = 0.90, 95% CI = 0.81–0.99), first cohabitation in teenage (≤19 years) (aOR = 0.85, 95% CI = 0.78–0.92) were less likely to report unintended pregnancies. Conclusions: This study has showed that women's age, wealth index, place of residence, number of children, family size, the intention of contraceptive use, living with a partner, and first cohabitation age are essential determinants of unintended pregnancy. These factors should be considered when trying to reduce unintended pregnancy in six South Asian countries. However, there is a need to improve health education, counselling, skills-building, sex education, modern contraceptive use and its access in this region. Intervention programs regarding reproductive health and policies are warranted to reduce rates of unintended pregnancy in South Asian countries. [ABSTRACT FROM AUTHOR]

Facebook has transformed social communication and offers the opportunity to share personal thoughts to people including suicide ideas, plans and attempts. Suicide after Facebook posts has been reported in different parts of the world and it has become a potential area of research for suicide prevention. The analysis of Facebook posts prior to suicide or Facebook live streaming may help in understanding the etiological factors, patterns of communication and possible prevention approaches for a particular community. However, there is a dearth of evidence about suicide incidents after Facebook posts and Facebook live streaming in low and middle-income countries. This study aims to explore the trends and phenomena of suicide after Facebook posts and live streaming in Bangladesh. We conducted an online search using the Google, Facebook and five daily online newspaper archives from 15th August to 15th September 2019. Two research assistants independently conducted the initial searching to find out people who committed suicide after Facebook posts or live streamed suicide in Bangladesh and documented 21 cases. After further evaluation of each of the 21 cases we confirmed 19 cases that met the selection criteria. All of them were under 35-years of age. We observed sucide after Facebook posts were more common in male(78%) e and students. Hanging was the most frequently used method of suicide followed by poisoning. Their Facebook posts and livestream videos indicated relationship problems, academic stress and mental disorders were the common stressors for their suicide. This study lays the foundation for the future researchers to work on suicidal posts on Facebook in Bangladesh and develop culture-specific, real-time suicide preventive systems using a social media platform. [ABSTRACT FROM AUTHOR]

To describe morbidity and mortality trends of type 2 diabetes in Australia, from 1990 to 2019, compared with similar sociodemographic index (SDI) countries. Australia-specific Global Burden of Diseases data were used to estimate age-standardised, age-specific, and sex-specific rates for prevalence, years lived with disability (YLDs), years of life lost (YLLs), disability-adjusted life years (DALYs), and deaths due to type 2 diabetes between 1990 and 2019. Australian data were compared with 14 similar SDI countries. Type 2 diabetes increased in Australia between 1990 and 2019. The age-standardised prevalence increased from 1,985 [95% Confidence Interval (CI): 1,786.7–2195.3] per 100,000 population, to 3,429 [95% CI 3,053.3–3,853.7]. Cases tripled, from 379,532 [342,465–419,475] to 1,307,261 [1,165,522–1,461,180]. The age-standardised death rates doubled, from 2,098 [1,953–2,203] per 100,000, to 4,122 [3,617–4,512]. DALYs doubled, from 70,348 [59,187–83,500] to 169,763 [129,792–216,150], with increases seen in YLDs and YLLs. Men displayed higher rates. Compared to similar SDI countries, Australia ranked 4th in terms of burden for type 2 diabetes. The burden of type 2 diabetes in Australia has increased considerably over three decades. There is an urgent need to prioritise resource allocation for prevention programs, screening initiatives to facilitate early detection, and effective and accessible management strategies for the large proportion of the population impacted by type 2 diabetes. [ABSTRACT FROM AUTHOR]

The article offers information on prevalence and correlates of fear of falling among older people in Bangladesh. It mentions three-fourths of people with a fear of falling limit their activities of daily living, leading to social isolation,6 decreased quality of life, and other health problems; and inevitable consequence of ageing.

Background: Patients' perspective of diabetes and adherence to its prescribed medications is a significant predictor of glycemic control and overall management of the disease. However, there is a paucity of such information in Bangladesh. This study aimed to explore patients' perspective of diabetes, their experience of taking oral hypoglycemic medications and explore factors that contribute to medication adherence in patients with type 2 diabetes in Bangladesh. Methods: We conducted in-depth face-to-face interviews with 12 type 2 diabetes patients attending a tertiary hospital in Dhaka city between February and March, 2014. Participants were purposively sampled representing different age groups, education levels, years since diagnosis with diabetes, and iglycemic status, to achieve maximum variation sampling. All interviews were conducted using a topic guide and were audio-recorded, transcribed verbatim, checked for errors, coded and analyzed by means of a qualitative content analysis framework. Results: The data analysis generated rich information on the participants' knowledge and perception on diabetes, its causes, self-management, medication use, adverse effects of medication use, medication adherence, and impact of diabetes, Although most of the participants demonstrated substantive knowledge on diabetes and its consequences, they also reported numerous misconceptions about the disease. Knowledge on diabetes medication, their appropriate use and side effects was rather poor. Respondents also reported non-compliance to dietary and physical activity advice by their physicians and concerns on diabetes diabetes-induced psychological stress. High cost of medications, concerns over medication side effects and forgetfulness was noted as factors for non-adherence to medication. Conclusion: Participants' knowledge and perception on diabetes are key factors determining their adherence to medications and, thereby, diabetes management. Healthcare providers should explore to better understand patients' perspective on diabetes, medication beliefs, identify psychological stress and provide more effective health education interventions to enhance medication adherence. [ABSTRACT FROM AUTHOR]

Background: Little is known about the association between diabetes and health related quality of life (HRQL) in lower-middle income countries. This study aimed to investigate HRQL among individuals with and without diabetes in Bangladesh.Methods: The analysis is based on data of a case-control study, including 591 patients with type 2 diabetes (cases) who attended an outpatient unit of a hospital in Dhaka and 591 age -and sex-matched individuals without diabetes (controls). Information about socio-demographic characteristics, health conditions, and HRQL were assessed in a structured interview. HRQL was measured with the EuroQol (EQ) visual analogue scale (VAS) and the EQ five-dimensional (5D) descriptive system. The association between diabetes status and quality of life was examined using multiple linear and logistic regression models.Results: Mean EQ-VAS score of patients with diabetes was 11.5 points lower (95 %-CI: -13.5, -9.6) compared to controls without diabetes. Patients with diabetes were more likely to report problems in all EQ-5D dimensions than controls, with the largest effect observed in the dimensions 'self-care' (OR = 5.9; 95 %-CI: 2.9, 11.8) and 'mobility' (OR = 4.5; 95 %-CI: 3.0, -6.6). In patients with diabetes, male gender, high education, and high-income were associated with higher VAS score and diabetes duration and foot ulcer associated with lower VAS scores. Other diabetes-related complications were not significantly associated with HRQL.Conclusions: Our findings suggest that the impact of diabetes on HRQL in the Bangladeshi population is much higher than what is known from western populations and that unlike in western populations comorbidities/complications are not the driving factor for this effect. [ABSTRACT FROM AUTHOR]

Background: Smart home systems can potentially improve heart failure (HF) self-management and care. However, evidence is lacking on clinicians' expectations and opinions about these systems. This study aimed to investigate key healthcare providers' perspectives on using smart home systems for self-management and care in people with HF.Methods: Semi-structured interviews were conducted with purposively selected healthcare providers experienced in caring for people with HF in Australia. Participants were presented with a schematic for a prototype smart home system comprising a central hub connected with medical devices and sensors. An inductive thematic analysis approach was used to establish the perceived benefits and barriers to using smart home systems and enhance the self-management of people with HF.Results: Overall, participants reported that smart home systems could improve the self-management of people with HF with some reservations and suggestions. Four substantive themes emerged from the qualitative findings: role of smart home systems in self-management, suggested features of a smart home system, benefits of smart home system, and factors that may influence smart home system uptake. Participants shared several reservations, such as the potential for increased workload and difficulty of technology use for some patients due to age and HF-related disabilities. Participants highlighted that the abilities and needs of people with HF must be considered when developing any smart home systems. Furthermore, these systems might benefit health institutions and people with HF by allowing remote monitoring and services and allowing patients to live at home independently.Conclusion: Healthcare providers considered smart home systems might be potentially helpful to monitor HF patients and deliver interventions to improve their lives, despite several reservations. Future research is needed to address these reservations, identify the needs and abilities of people with HF to use technologies, effects of smart home systems on HF self-management and their impact on clinical practice and health outcomes. [ABSTRACT FROM AUTHOR]

Background Diabetes affects both individuals and their families and has an impact on economic and social development of a country. Information on the availability, cost, and quality of medical care for diabetes is mostly not available for many low- and middle-income countries including Bangladesh. Complications from diabetes, which can be devastating, could largely be prevented by wider use of several inexpensive generic medicines, simple tests and monitoring and can be a cost saving intervention. This study will provide an in-depth and comprehensive picture of social and economic impacts of diabetes in Bangladesh and propose clear recommendations for improving prevention and management of diabetes. The objectives of the study are: 1) To study the association between diabetes and other health problems and its social impacts 2) To estimate the economic impact of diabetes including total direct and indirect costs 3) To measure the impact of diabetes on quality of life among diabetes patients in Bangladesh 4) To study the impact of diabetes on the health care system Methods This is a case-control study comparing cases with type 2 diabetes to controls without diabetes matched on age, sex and place of residence. 564 cases and 564 controls will be selected from the outpatient department of a tertiary hospital in Dhaka, Bangladesh. Data on socioeconomic status, health utility index, direct and indirect costs for diabetes, medication adherence, quality of life, treatment satisfaction, diet, physical activity, mental state examination, weight, height, hip and waist circumference, blood pressure, pulse, medication history, laboratory data and physical examination will be conducted. Outcome measures: The primary outcome measures will be association between diabetes and other health problems, cost of diabetes, impact of diabetes on quality of life and secondary outcome measures are impact of diabetes on healthcare systems in Bangladesh. Discussion This study will provide an in-depth and comprehensive picture of social and economic impacts of diabetics in Bangladesh and propose clear recommendations for improving prevention and management of diabetics. It will help to develop programs and policies for better management of Diabetics and cost effective strategies in Bangladesh context. [ABSTRACT FROM AUTHOR]

Background: The use of digital interventions for managing chronic diseases is significantly increasing. The aim of this study was to estimate the proportion of ownership of a mobile phone, and factors associated with the ability to read and access SMS delivered health information, and willingness to pay for it among people with hypertension in a rural area in Bangladesh.Methods: Data were collected from 307 participants aged 30 to 75 years with hypertension from a rural area in Bangladesh from December 2020 to January 2021. Outcome measures included ownership of a mobile phone, ability to read SMS, willingness to receive and pay for health information by SMS. Associated factors included age, gender, level of education, occupation, and socioeconomic status. We used regression analysis to identify variables associated with the outcome variables.Results: Overall, 189 (61.6%) people owned a mobile phone which was higher in men (73.3% vs. 50%, p < 0.001), younger people (82.6% aged 30-39 years vs. 53.5% aged 60-75 years, p < 0.001). Of the total participants, 207 (67.4%) were willing to receive SMS, and 155 (50.5%) were willing to pay for receiving SMS for health information. The prevalence was significantly higher among professionals (odds ratio (OR), 95% confidence interval (CI): 4.58, 1.73-12.1) and businesspersons (OR 3.68, 95% CI 1.49-9.10) compared to farmers, respectively. The median (interquartile range [IQR]) of willingness to pay for health information SMS was 10 (28) Bangladesh Taka (BDT) (1 BDT ~ 0.013 US$), and there were no specific factors that were associated with the willingness of any higher amounts of payment. In terms of reading SMS of people who own a mobile, less than half could read SMS. The proportion of people who could read SMS was significantly higher among men, younger people, educated people, middle class or rich people, professionals or businesspersons. Of people who could read SMS, the majority read SMS occasionally.Conclusion: A significant proportion of people are unable to read SMS. However, people are willing to receive and pay to receive SMS for health information. Education and awareness programs should be conducted among targeted groups, including people with low education and women. [ABSTRACT FROM AUTHOR]

Background: The use of antihypertensive medications is critical for controlling high blood pressure. We aimed to investigate associations between socio-demographic factors and antihypertensive medications use, and antihypertensive medications use with different types of drugs use with levels of systolic blood pressure (SBP) and diastolic blood pressure (DBP).Methods: For the present report we derived data from the baseline measurements of a cluster randomised control trial on 307 participants with previously diagnosed hypertension from the rural district of Narial in Bangladesh. We measured the participant's current blood pressure levels and recorded antihypertensive medications uses. Associated factors included socio-economic status, diabetes, antihypertensive medications use, and types of drugs and doses used for controlling blood pressure. We applied analysis of variance and logistic regression techniques to identify factors associated with blood pressure.Results: Of the total participants, 144 (46.9%) were on antihypertensive medications. After multivariate adjustment, binary logistic regression revealed that employees (odds ratio, (95% confidence interval (CI)) (OR 3.58, 95%CI 1.38-9.28) compared to farmers, and people with diabetes (OR 2.43, 95%CI 1.13-5.26) compared to people without diabetes were associated with a higher proportion of antihypertensive medications use. Of 144 participants on antihypertensive medications, 7 (5%) had taken two doses, 114 (79%) had taken one dose per day and the rest were irregular in medication use. The mean (standard deviation) [min, max] SBP and DBP were 149 (19) mmHg [114, 217] and 90 (10) mmHg [75, 126], respectively. Overall, there was no significant difference in SBP (p = 0.10) or DBP (p = 0.67) between participants with or without antihypertensive medications or using any type of medications (p = 0.54 for SBP and 0.76 for DBP). There was no significant association between antihypertensive medications use and elevated BP levels SBP/DBP≥140/90 mmHg (p = 0.42) CONCLUSION: Less than half of the people with hypertension were on medication. Irrespective of the antihypertensive medications use, most of the participant's blood pressure was high. Further study is needed with a large sample to understand the factors and aetiology of unmanaged hypertension in rural areas of Bangladesh where the prevalence of hypertension is very high. [ABSTRACT FROM AUTHOR]

Background: High blood pressure is an independent risk factor of cardiovascular disease (CVD) and is a major cause of disability and death. Managing a healthy lifestyle has been shown to reduce blood pressure and improve health outcomes. We aim to investigate the effectiveness of a lifestyle modification intervention program for lowering blood pressure in a rural area of Bangladesh.Methods: A single-center cluster randomized controlled trial (RCT). The study will be conducted for 6 months, a total of 300 participants of age 30 to 75 years with 150 adults in each of the intervention and the control arms. The intervention arm will involve the delivery of a blended learning education program on lifestyle changes for the management of high blood pressure. The education program comprises evidence-based information with pictures, fact sheets, and published literature about the effects of high blood pressure on CVD development, increased physical activity, and the role of a healthy diet in blood pressure management. The control group involves providing information booklets and general advice at the baseline data collection point. The primary outcome will be the absolute difference in clinic SBP and DBP. Secondary outcomes include the difference in the percentage of people adopting regular exercise habits, cessation of smoking and reducing sodium chloride intake, health literacy of all participants, and the perceived barriers and enablers to adopt behavior changes by collecting qualitative data. Analyses will include analysis of covariance to report the mean difference in blood pressure between the control and the intervention group and the difference in change in blood pressure due to the intervention.Discussion: The study will assess the effects of physical activity and lifestyle modification in controlling high blood pressure. This study will develop new evidence as to whether a simple lifestyle program implemented in a rural region of a low- and middle-income country will improve blood pressure parameters for people with different chronic diseases by engaging community people.Trial Registration: ClinicalTrials.gov NCT04505150 . Registered on 7 August 2020. [ABSTRACT FROM AUTHOR]

Study tools examining psychological distress, fear of COVID‐19 and coping amongst migrants and non‐migrants in Australia are very limited. The aim of this research was to assess the psychometric properties and correlation of the English version of Kessler Psychological Distress Scale (K‐10), Fear of COVID‐19 Scale (FCSV‐19S), and Brief Resilient Coping Scale (BRCS) tools during the COVID‐19 pandemic situation in Australia. Data from a cross‐sectional survey (n = 516) were utilized to examine reliability; 299 (57.9%) were migrants. High internal consistency, as evidenced by Cronbach's alpha, was found for the K‐10 (0.92), FCV‐19S (0.87) and BRCS (0.66) tools. The corresponding values for migrants and non‐migrants were (0.92, 0.87, 0.67) and (0.92, 0.86, 0.63), respectively. Item‐total correlations ranged 0.57‐0.78 for K‐10, 0.62–0.69 for FCV‐19S, and 0.39–0.50 for BRCS tools. EFA retained a single factor for each tool with adequate factor loadings. The scoring of K‐10 was significantly predicted by the scoring of FCV‐19S (r = 0.284, P < 0.001) and BRCS tool (r = 0.132, P < 0.01). Therefore, these tools can be used reliably amongst both migrant and non‐migrant population in Australia. [ABSTRACT FROM AUTHOR]

Unhealthy diet is associated with increased risk of cardiovascular diseases (CVD). However, there are no studies reporting the impact and trends of dietary risk factors on CVD in Australia. This study aimed to determine the burden of CVDs attributable to dietary risk factors in Australia between 1990 and 2019. We used data from the Global Burden of Diseases (GBD) study and quantified the rate (per 100,000) of deaths, disability-adjusted life years (DALYs), years lived with a disability (YLDs), and years of life lost (YLLs) for 21 CVDs attributable to 13 dietary risk factors (eight food groups and five nutrients) in Australia by sex and age groups (≥25 years and over). In 2019, the age-standardised rates of deaths, YLDs, YLLs, and DALYs attributable to dietary risk factors attributable to CVDs in the Australian population were 26.5, 60.8, 349.9, and 410.8 per 100,000 in women and 46.1, 62.6, 807.0, and 869.6 in men. Between 1990 and 2019, YLLs consistently contributed more towards the rates of DALYs than YLDs. Over the 30-year period, CVD deaths, YLLs, and DALYs attributable to dietary risk factors declined in both women and men. The leading dietary risk factors for CVD deaths and DALYs were a diet high in red meat (6.1 deaths per 100,000 [3.6, 8.7] and 115.6 DALYs per 100,000 [79.7, 151.6]) in women and a diet low in wholegrains (11.3 deaths [4.4, 15.1] and 220.3 DALYs [86.4, 291.8]) in men. Sex differences were observed in the contribution of dietary risk factors to CVD over time such that the lowest rate of decrease in deaths and DALYs occurred with diets high in sodium in women and diets high in processed meat in men. Although the burden of diet-related CVD has decreased significantly in the Australian population over the past 30 years, diets low in wholegrains and high in red meat continue to contribute significantly to the overall CVD burden. Future nutrition programs and policies should target these dietary risk factors. [ABSTRACT FROM AUTHOR]

Purpose: To assess the relationship of early pregnancy maternal diet quality (DQ) with maternal plasma lipids and indicators of cardiometabolic health, including blood pressure (BP), gestational diabetes mellitus (GDM) and gestational weight gain (GWG). Methods: Women (n = 215) aged 18–40 years with singleton pregnancies were recruited at 10–20 weeks gestation. Diet quality was assessed by the Dietary Guideline Index, calculated at early ([mean ± SD]) (15 ± 3 weeks) and late (35 ± 2 weeks) pregnancy. Lipidomic analysis was performed, and 698 species across 37 lipid classes were measured from plasma blood samples collected at early (15 ± 3 weeks) and mid (27 ± 3 weeks)-pregnancy. Clinical measures (BP, GDM diagnosis, weight) and blood samples were collected across pregnancy. Multiple linear and logistic regression models assessed associations of early pregnancy DQ with plasma lipids at early and mid-pregnancy, BP at three antenatal visits, GDM diagnosis and total GWG. Results: Maternal DQ scores ([mean ± SD]) decreased significantly from early (70.7 ± 11.4) to late pregnancy (66.5 ± 12.6) (p < 0.0005). At a false discovery rate of 0.2, early pregnancy DQ was significantly associated with 13 plasma lipids at mid-pregnancy, including negative associations with six triglycerides (TGs); TG(54:0)[NL-18:0] (neutral loss), TG(50:1)[NL-14:0], TG(48:0)[NL-18:0], TG(52:1)[NL-18:0], TG(54:1)[NL-18:1], TG(50:0)[NL-18:0]. No statistically significant associations were found between early pregnancy DQ and BP, GDM or GWG. Conclusion: Maternal diet did not adhere to Australian Dietary Guidelines. Diet quality was inversely associated with multiple plasma TGs. This study provides novel insights into the relationship between DQ, lipid biomarkers and cardiometabolic health during pregnancy. [ABSTRACT FROM AUTHOR]

In this study we examined the associations of physical education class participation with physical activity among adolescents. We analysed the Global School-based Student Health Survey data from 65 countries (N = 206,417; 11–17 years; 49% girls) collected between 2007 and 2016. We defined sufficient physical activity as achieving physical activities ≥ 60 min/day, and grouped physical education classes as '0 day/week', '1–2 days/week', and ' ≥ 3 days/week' participation. We used multivariable logistic regression to obtain country-level estimates, and meta-analysis to obtain pooled estimates. Compared to those who did not take any physical education classes, those who took classes ≥ 3 days/week had double the odds of being sufficiently active (OR 2.05, 95% CI 1.84–2.28) with no apparent gender/age group differences. The association estimates decreased with higher levels of country's income with OR 2.37 (1.51–3.73) for low-income and OR 1.85 (1.52–2.37) for high-income countries. Adolescents who participated in physical education classes 1–2 days/week had 26% higher odds of being sufficiently active with relatively higher odds for boys (30%) than girls (15%). Attending physical education classes was positively associated with physical activity among adolescents regardless of sex or age group. Quality physical education should be encouraged to promote physical activity of children and adolescents. [ABSTRACT FROM AUTHOR]

Background: Traumatic brain injury (TBI) is one of the major health and socioeconomic problems in the world. Immune-enhancing enteral formula has been proven to significantly reduce infection rate in TBI patients. One of the ingredients that can be used in immunonutrition formulas to reduce inflammation and oxidative stress is pycnogenol.Objective: The objective of this work is to survey the effect of pycnogenol on the clinical, nutritional, and inflammatory status of TBI patients.Methods: This is a double-blind, randomized controlled trial. Block randomization will be used. An intervention group will receive pycnogenol supplementation of 150 mg for 10 days and a control group will receive a placebo for the same duration. Inflammatory status (IL-6, IL- 1β, C-reactive protein) and oxidative stress status (malondialdehyde, total antioxidant capacity), at the baseline, at the 5th day, and at the end of the study (10th day) will be measured. Clinical and nutritional status will be assessed three times during the intervention. The Sequential Organ Failure Assessment (SOFA) questionnaire for assessment of organ failure will be filled out every other day. The mortality rate will be calculated within 28 days of the start of the intervention. Weight, body mass index, and body composition will be measured. All analyses will be conducted by an initially assigned study arm in an intention-to-treat analysis.Discussion: We expect that supplementation of 150 mg pycnogenol for 10 days will improve clinical and nutritional status and reduce the inflammation and oxidative stress of the TBI patients.Trial Registration: This trial is registered at clinicaltrials.gov (ref: NCT03777683) at 12/13/2018. [ABSTRACT FROM AUTHOR]

It has been estimated that in the next decade, IHD prevalence, DALYs and deaths will increase more significantly in EMR than in any other region of the world. This study aims to provide a comprehensive description of the trends in the burden of ischemic heart disease (IHD) across the countries of the Eastern Mediterranean Region (EMR) from 1990 to 2019. Data on IHD prevalence, disability-adjusted life years (DALYs), mortality, DALYs attributable to risk factors, healthcare access and quality index (HAQ), and universal health coverage (UHC) were extracted from the Global Burden of Disease (GBD) database for EMR countries. The data were stratified based on the social demographic index (SDI). Information on cardiac rehabilitation was obtained from publications by the International Council of Cardiovascular Prevention and Rehabilitation (ICCPR), and additional country-specific data were obtained through advanced search methods. Age standardization was performed using the direct method, applying the estimated age structure of the global population from 2019. Uncertainty intervals were calculated through 1000 iterations, and the 2.5th and 97.5th percentiles were derived from these calculations. The age-standardized prevalence of IHD in the EMR increased from 5.0% to 5.5% between 1990 and 2019, while it decreased at the global level. In the EMR, the age-standardized rates of IHD mortality and DALYs decreased by 11.4% and 15.4%, respectively, during the study period, although both rates remained higher than the global rates. The burden of IHD was found to be higher in males compared to females. Bahrain exhibited the highest decrease in age-standardized prevalence (-3.7%), mortality (-65.0%), and DALYs (-69.1%) rates among the EMR countries. Conversely, Oman experienced the highest increase in prevalence (14.5%), while Pakistan had the greatest increase in mortality (30.0%) and DALYs (32.0%) rates. The top three risk factors contributing to IHD DALYs in the EMR in 2019 were high systolic blood pressure, high low-density lipoprotein cholesterol, and particulate matter pollution. The trend analysis over the 29-year period (1990–2019) revealed that high fasting plasma glucose (64.0%) and high body mass index (23.4%) exhibited increasing trends as attributed risk factors for IHD DALYs in the EMR. Our findings indicate an increasing trend in the prevalence of IHD and a decrease in mortality and DALYs in the EMR. These results emphasize the need for well-planned prevention and treatment strategies to address the risk factors associated with IHD. It is crucial for the countries in this region to prioritize the development and implementation of programs focused on health promotion, education, prevention, and medical care. [ABSTRACT FROM AUTHOR]

Background:Recently there has been dramatic increase in the use of mobile technologies for health (m-Health) in both high and low- and middle-income countries (LMICs). However, little is known whether m-Health interventions in LMICs are based on relevant theories critical for effective implementation of such interventions. This review aimed to systematically identify m-Health studies on health behavioral changes in LMICs and to examine how each study applied behavior change theories. Materials and Methods:A systematic review was conducted using the standard method from the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. By searching electronic databases (MEDLINE, EMBASE, and Cochrane Central Register of Controlled Trials [CENTRAL]), we identified eligible studies published in English from inception to June 30, 2017. For the identified m-Health studies in LMICs, we examined their theoretical bases, use of behavior change techniques (BCTs), and modes of delivery. Results:A total of 14 m-Health studies on behavioral changes were identified and, among them, only 5 studies adopted behavior change theory. The most frequently cited theory was the health belief model, which was adopted in three studies. Likewise, studies have applied only a limited number of BCTs. Among the seven BCTs identified, the most frequently used one was the social support (practical) technique for medication reminder and medical appointment. m-Health studies in LMICs most commonly used short messaging services and phone calls as modes of delivery for behavior change interventions. Conclusions:m-Health studies in LMICs are suboptimally based on behavior change theory yet. To maximize effectiveness of m-Health, rigorous delivery methods as well as theory-based intervention designs will be needed. [ABSTRACT FROM AUTHOR]

Background: Mobile phone technologies including SMS (short message service) have been used to improve the delivery of health services in many countries. However, data on the effects of mobile health technology on patient outcomes in resource-limited settings are limited. The aim of this study therefore is to measure the impact of a mobile phone SMS service on treatment success of newly diagnosed type 2 diabetes in an urban area of Bangladesh.Methods/design: This is a single-centred randomized controlled intervention trial (prospective) comparing standard-of-care with standard-of-care plus a mobile phone-based SMS intervention for 6 months. A total of 216 participants with newly diagnosed type 2 diabetes will be recruited. Data will be collected at the outpatient department of Bangladesh Institute of Health Science (BIHS) hospital at baseline and after 6 months. The primary outcome measure will be change in HbA1c between baseline and 6 months. The secondary outcome measures are self-reported medication adherence, clinic attendance, self-reported adoption of healthy behaviours, diabetes knowledge, quality of life and cost effectiveness of the SMS intervention. The inclusion criteria will be as follows: diagnosed as patients with type 2 diabetes by the BIHS physician, using oral medication therapy, living in Dhaka city, registered with the BIHS hospital, using a mobile phone, willing to return for follow up after 6 months and providing written informed consent. Participants will be allocated to control and intervention arms after recruitment using a randomization software. Data will be collected on socio-demographic and economic information, mobile phone use and habits, knowledge of prevention, management and complications of diabetes, self-perceived quality of life assessment, self-reported diseases, medical history, family history of diseases, medication history, medication adherence, health seeking behaviour, tobacco use, physical activity, diet, mental health status, life events and disability, anthropometric measurements of weight, height, blood pressure and blood tests for HbA1c.Discussion: Mobile phone SMS services have the potential to communicate with diabetes patients and to build awareness about the disease, improve self-management and avoid complications also in resource-limited setting. If this intervention proves to be efficient and cost-effective in the current trial, large-scale implementation could be undertaken.Trial Registration: DRKS00005188 . [ABSTRACT FROM AUTHOR]

Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease, which can progress from simple steatosis to advanced cirrhosis and hepatocellular carcinoma. Clinical diagnosis of NAFLD is crucial in the early stages of the disease. The main aim of this study was to apply machine learning (ML) methods to identify significant classifiers of NAFLD using body composition and anthropometric variables. A cross-sectional study was carried out among 513 individuals aged 13 years old or above in Iran. Anthropometric and body composition measurements were performed manually using body composition analyzer InBody 270. Hepatic steatosis and fibrosis were determined using a Fibroscan. ML methods including k-Nearest Neighbor (kNN), Support Vector Machine (SVM), Radial Basis Function (RBF) SVM, Gaussian Process (GP), Random Forest (RF), Neural Network (NN), Adaboost and Naïve Bayes were examined for model performance and to identify anthropometric and body composition predictors of fatty liver disease. RF generated the most accurate model for fatty liver (presence of any stage), steatosis stages and fibrosis stages with 82%, 52% and 57% accuracy, respectively. Abdomen circumference, waist circumference, chest circumference, trunk fat and body mass index were among the most important variables contributing to fatty liver disease. ML-based prediction of NAFLD using anthropometric and body composition data can assist clinicians in decision making. ML-based systems provide opportunities for NAFLD screening and early diagnosis, especially in population-level and remote areas. [ABSTRACT FROM AUTHOR]

Background: Stigma affects different life aspects in people living with bipolar disorder and their families. This study aimed to examining the experience of stigma and evaluating predictors, consequences and strategies to combat stigma in people with bipolar disorder and their families. Methods: We conducted a systematic review according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) in 2022. We extensively reviewed six online databases (PubMed, Scopus, Medline, EMBASE, Web of Science and Google Scholar). Articles published in the English language about stigma in people living with bipolar disorders and their families were included. Results: A total of 42,763 articles were retrieved, of which 40 articles from 14 countries were included in this study (n = 7417 participants). Of the 40 articles, 29 adopted quantitative methods (72.5%), two used mixed-methods (5%), eight used qualitative (20%) methods, and one was a case series (2.5%). The results of the studies were categorized into four themes: 1. Stigma experienced by people living with bipolar disorders and their families, 2. Predictors of stigma in people living with bipolar disorders and their families, 3. Consequences of stigma in people living with bipolar disorders and their families, 4. Effective interventions and strategies to reduce stigma in people living with bipolar disorders and their families. Conclusion: The results of this study might be useful to design psychiatric cognitive interventions to reduce stigma in people living with bipolar disorders and their families and designing community-based interventions to normalize bipolar disorder at the community level. [ABSTRACT FROM AUTHOR]

Background: Regular physical activity is effective for preventing and managing depression; however, only a few studies have assessed physical activity using device-based measures. We aimed to examine the association between device-based total physical activity and late-life depressive symptoms and explore which factors may explain this relationship.Methods: Data from 10 European countries who participated in wave 8 of the Survey of Health, Ageing and Retirement in Europe (SHARE) were analyzed. Triaxial accelerometers (Axivity AX3; Axivity, Newcastle UK) were used to assess total physical activity. Depressive symptoms were assessed through the EURO-D scale. Possion regression models and mediation analysis were performed.Results: The final sample included 785 older adults (70 participants had missing data in one or more variables and were excluded from the analysis) [mean (SD): age 68.6 (8.8) years; 59.2 % female]. After adjusting for several confounders, a 10 % increase in the mean acceleration was associated with lower depressive symptoms (B = -0.0228; 95%CI = -0.0395, -0.0061). This association was partly explained by limitations in activities of daily living and quality of life.Limitations: Cross-sectional design, convenience sample, bi-directionality, lack of cutoff points for classification of the Axivity AX3 placed in the thigh, into intensities.Conclusions: Higher device-based total physical activity was linked with lower depressive symptoms in older European adults. Future studies employing device-based measures that allow to better capture important physical activity dimensions (i.e., intensity) will better inform about dose-response relationships. [ABSTRACT FROM AUTHOR]

Mobile health (mHealth) has been defined as medical and public health practice supported by mobile devices, such as mobile phones, patient monitoring devices and personal digital assistants. Cardiovascular mHealth is, arguably, leading the mHealth space, through innovation, research and implementation, and especially in the areas of prevention, cardiac rehabilitation and education. mHealth includes simple strategies, such as the use of short message service (SMS) or text messages in successful short-term smoking-cessation, weight loss and diabetes management programs. The recent Australian Tobacco, Exercise and Diet Messages (TEXT ME) randomised clinical trial addressed multiple cardiovascular risk factors. mHealth can also involve more complex strategies, such as smart phone applications (apps), global positioning systems (GPS) and Bluetooth technologies. Although many apps could be considered suitable for primary prevention, they are largely unregulated and most are not evidence-based. Some have been well-developed, such as the Food Switch app and an iPhone electrocardiogram (ECG) system. The "explosion" of apps has driven initiatives such as the Mobile Applications Rating Scale (MARS). More recently, the use of sensors to monitor and provide feedback to patients and healthcare providers is being explored. With almost two billion people currently owning a Smartphone, and 50% of adults (globally) predicted to own one by 2018, mHealth provides the prospect of delivering efficient, affordable healthcare services to widespread populations both locally and globally. In particular, it has the potential to reduce socioeconomic disparity and alleviate the burden of cardiovascular disease. There is now a need to rethink traditional health service structures and bioengineering capacity, to ensure mHealth systems are also safe, secure and robust. [ABSTRACT FROM AUTHOR]

Background: Globally, stroke is a leading cause of death and disability, with most care undertaken by caregivers who are generally family and friends without prior experience of care. The lack of experience or unpreparedness results in feelings of uncertainty, burnout, anxiety, burden, etc. Hence, it is necessary to identify the needs of caregivers to better support them in their caregiving journey and improve the quality of care delivered. Methods: The study employed a grounded theory methodology that utilizes information gathered from literature reviews and social media to represent the needs and create a storyline visually. The storyline is further refined and evaluated using an online survey of 72 participants recruited through online stroke caregiving communities. Results: The study identified four core categories of needs: (i) Information: sufficient information delivered in layman's terms based on the individual situation of the caregiver and survivor through oral and hands-on demonstrations, (ii) Involvement: inclusion in the decision-making processes at different stages of recovery through face-to-face communication at the hospital, (iii) Self-care: ability to engage in work and leisure activities, (iv) Support: receive support in the form of resources, services and finances from different other stakeholders. Conclusions: There is a need to create a caregiver-centered approach in stroke recovery to ensure limited obstruction to care and reduced uncertainty in stroke recovery. Moreover, through the inclusion of caregivers in stroke recovery, it may be possible to reduce the burden of care to the caregiver and ensure the satisfaction of the healthcare system throughout stroke recovery. [ABSTRACT FROM AUTHOR]

Predicting treatment outcomes in traumatic brain injury (TBI) patients is challenging worldwide. The present study aimed to achieve the most accurate machine learning (ML) algorithms to predict the outcomes of TBI treatment by evaluating demographic features, laboratory data, imaging indices, and clinical features. We used data from 3347 patients admitted to a tertiary trauma centre in Iran from 2016 to 2021. After the exclusion of incomplete data, 1653 patients remained. We used ML algorithms such as random forest (RF) and decision tree (DT) with ten-fold cross-validation to develop the best prediction model. Our findings reveal that among different variables included in this study, the motor component of the Glasgow coma scale, the condition of pupils, and the condition of cisterns were the most reliable features for predicting in-hospital mortality, while the patients' age takes the place of cisterns condition when considering the long-term survival of TBI patients. Also, we found that the RF algorithm is the best model to predict the short-term mortality of TBI patients. However, the generalized linear model (GLM) algorithm showed the best performance (with an accuracy rate of 82.03 ± 2.34) in predicting the long-term survival of patients. Our results showed that using appropriate markers and with further development, ML has the potential to predict TBI patients' survival in the short- and long-term. [ABSTRACT FROM AUTHOR]

Background: Improved understanding of participant engagement in web-based dietary interventions is needed. Engagement is a complex construct that may be best explored through mixed methods to gain comprehensive insight. To our knowledge, no web-based dietary intervention in people with type 2 diabetes (T2D) has previously used a mixed methods approach. The aim of this study was to explore factors that may contribute to effective engagement in a web-based dietary program for people with T2D. Methods: This study employed a mixed methods intervention design, with a convergent design embedded for post-intervention evaluation. The convergent design collected and analyzed quantitative and qualitative data independent of each other, with the two datasets merged/compared during results/interpretation. Quantitative data collected from intervention group participants (n = 40) were self-administered questionnaires and usage data with average values summarized. Qualitative data were participant semi-structured interviews (n = 15) incorporating a deductive-inductive thematic analysis approach. Results: The results from the quantitative and qualitative data indicated positive overall engagement with the web-based dietary program. Factors that contributed to effective engagement were sustained frequency and intensity of engagement; structured weekly program delivery; participants affective engagement prior to and during the intervention, with positive affective states enhancing cognitive and behavioral engagement; and participants experience of value and reward. In addition, the user-centered development process employed prior to intervention delivery played an important role in facilitating positive engagement outcomes. Conclusion: This study yielded novel findings by integrating qualitative and quantitative data to explore engagement with a web-based dietary program involving people with T2D. Effective engagement occurred in this intervention through a combination of factors related to usage and participants' affective, cognitive and behavioral states. The engagement outcomes that emerged will be useful to current and future researchers using digital technologies to deliver lifestyle interventions for T2D or other chronic health conditions. [ABSTRACT FROM AUTHOR]

Aim: This rapid review examines the technology‐based interventions for caregivers of stroke proposed in the literature while also identifying the acceptance, effectiveness and satisfaction of the implemented approaches. Background: The increasing burden of supporting stroke survivors has resulted in caregivers searching for innovative solutions, such as technology‐based interventions, to provide better care. Hence, its potential to support caregivers throughout the disease trajectory needs to be assessed. Evaluation: Five electronic databases were systematically searched for articles related to stroke caregiving technologies based on well‐defined inclusion and exclusion criteria. Key issue(s): Fifteen articles met the inclusion criteria that focused on supporting caregivers through functionalities such as education, therapy and support, remote consultations, health assessments and logs and reminders using different devices. The majority of interventions demonstrated positive conclusions for caregiving impact, acceptance, effectiveness and satisfaction. Conclusion: Findings highlight the influences of technology in improving stroke caregiving and the need to include user‐centred design principles to create a meaningful, actionable and feasible system for caregivers. Implications for nursing management: Technology can educate and support stroke caregivers, thereby minimizing uncertainty and ensuring better care for the survivor. [ABSTRACT FROM AUTHOR]

Background: Enteral immunomodulatory nutrition is recommended as an adjuvant therapy for patients in intensive care units (ICU), but its effectiveness is incompletely understood. Aim: The aim of this review was to examine the effect of a commonly used immunomodulatory formula—omega‐3 fatty acids, γ‐linolenic acid, and antioxidants—on clinical outcomes and mortality risk in critically ill patients. Design: Systematic review and meta‐analysis of randomized controlled trials (RCTs). Method: PubMed, Scopus, and Institute for Scientific Information (ISI) Web of Knowledge databases were searched until 18 February 2021. RCTs that used the immunomodulatory formula in the ICU were included. Results: Ten RCTs (1166 participants) were included in the meta‐analysis. The immunomodulatory formula reduced the duration of ICU stay weighted mean difference [(WMD): −2.97 days; 95%CI: −5.59, −0.35)], mechanical ventilation (WMD = −2.20 days, 95%CI: −4.29, −0.10), sequential organ failure assessment and multiple organ dysfunction scores (Hedge's g: −0.42 U/L; 95% CI: −0.74, −0.11), decreased 8‐day overall mortality risk (RR = 0.74, 95% CI: 0.58, 0.91), and extended the ICU‐free days (WMD: 4.06 days, 95% CI: 0.02, 8.09). The improvement in respiratory function and reduction in mortality risk was more in patients with acute lung injury (ALI) and acute respiratory distress syndrome (ARDS). Furthermore, the reduction in mechanical ventilation and mortality risk was more evident in older (>60 years) vs young adults. Conclusion and Relevance to Clinical Practice: Taken together, the immunomodulatory formula may enhance clinical practice for critical care nurses, such that the prevalence and/or susceptibility to secondary conditions commonly encountered in the ICU (ie, ALI and ARDS) could be attenuated, ultimately allowing critical care nurses to focus their care on the primary reason for which a patient is in the ICU. The study protocol was registered in PROSPERO. [ABSTRACT FROM AUTHOR]

Coronary artery disease (CAD) is a prevalent disease with high morbidity and mortality rates. Invasive coronary angiography is the reference standard for diagnosing CAD but is costly and associated with risks. Noninvasive imaging like cardiac magnetic resonance (CMR) facilitates CAD assessment and can serve as a gatekeeper to downstream invasive testing. Machine learning methods are increasingly applied for automated interpretation of imaging and other clinical results for medical diagnosis. In this study, we proposed a novel CAD detection method based on CMR images by utilizing the feature extraction ability of deep neural networks and combining the features with the aid of a random forest for the very first time. It is necessary to convert image data to numeric features so that they can be used in the nodes of the decision trees. To this end, the predictions of multiple stand-alone convolutional neural networks (CNNs) were considered as input features for the decision trees. The capability of CNNs in representing image data renders our method a generic classification approach applicable to any image dataset. We named our method RF-CNN-F, which stands for Random Forest with CNN Features. We conducted experiments on a large CMR dataset that we have collected and made publicly accessible. Our method achieved excellent accuracy (99.18%) using Adam optimizer compared to a stand-alone CNN trained using fivefold cross validation (93.92%) tested on the same dataset. [ABSTRACT FROM AUTHOR]

Introduction Bangladesh provides free healthcare to its citizens through 10,723 community clinics which provide one-stop healthcare services that is vital in ensuring primary healthcare. Measuring beneficiary' contentment is crucial to improve the quality of care and the perceived service quality have a significant impact on how often people use those health services. This study focuses on perceived quality and satisfaction of beneficiaries about the primary health care services and benefits of community clinics in Bangladesh. Methods A quantitative descriptive survey was conducted from March 2019 to April 2019 in the catchment area of 80 community clinics located at 16 Upazila under eight districts of eight divisions in Bangladesh. The survey compiled local data on client's experience on health care service of community clinics. Besides, Sixteen Upazilas from eight districts were randomly selected for conducting interviews. Results Data was provided by a total of 760 female participants, among them majority (41%) belonged to the age group of 18-24 years old, and this very group showed more satisfaction than others (Odds Ratio 1.44). Besides, childless married women were also found to be content with the community clinic services compared to the remaining types of clients (Odds Ratio 1.64). However, gender, education, and economic perspective were positive aspects of getting service from community clinics. Conclusions Although there is a challenge balancing psychosocial and medical care, promoting client-oriented care with a focus on the cultural factors of the area is vital. This can be done through community-focused training together with explaining written prescriptions to the beneficiary, including the signs, symptoms, treatment, and referral points. The study findings will enable responsible authority to improve quality of primary health care services, realizing beneficiary' ideas of community clinic service quality. [ABSTRACT FROM AUTHOR]

Background: Skilled birth attendants (SBAs) play a crucial role in reducing infant and maternal mortality. Although the ratio of skilled assistance at birth has increased in Bangladesh, factors associated with SBA use are unknown. The main goal of our study was to reveal the individual- and community-level factors associated with SBA use during childbirth in Bangladesh. We also showed the prevalence and trend of SBA use and related independent variables in Bangladesh over the past decade. Methods: This study utilized the Bangladesh Health and Demographic Survey (BDHS) 2017–2018, a cross-sectional study. We used binary logistic regression to examine the extent of variation in SBA use attributable to the individual- and community-level variables. Results: Overall, 53.35% of women received assistance from SBAs during childbirth. The average annual rate of increase (AARI) in the number of SBA-assisted births over the past 10 years was 8.88%. Respondents who gave birth at or above 19 years had 1.40 times (AOR = 1.40; 95% CI: 1.21–1.62) greater odds of having skilled delivery assistance than respondents aged 18 years old or less. Women and their husband's education levels were significantly associated with using skilled assistance during delivery, with odds of 1.60 (AOR = 1.60; 95% CI: 1.45–2.01) and 1.41 (AOR = 1.41; 95% CI: 1.21–1.66), respectively compared to those with education up to primary level. Women from rich families and those receiving better antenatal care (ANC) visits were more likely to have professional delivery assistance. Community-level factors also showed significance towards having professional assistance while giving birth. Women from urban communities and those who utilized more than four ANC visits and had completed secondary or higher education showed a greater tendency to use an SBA during childbirth than their counterparts. Conclusion: The use of SBAs during delivery was significantly associated with some individual- and community-level factors. To reduce maternal and child mortality, there is a need to focus on rural and uneducated people who are less likely to access these facilities. Special programs could increase awareness and help the poor community obtain the minimum facility in maternal care. [ABSTRACT FROM AUTHOR]

Background: Diabetic mellitus (DM) and cardiovascular diseases (CVD) cause significant healthcare burden globally and often co-exists. Current approaches often fail to identify many people with co-occurrence of DM and CVD, leading to delay in healthcare seeking, increased complications and morbidity. In this paper, we aimed to develop and evaluate a two-stage machine learning (ML) model to predict the co-occurrence of DM and CVD. Methods: We used the diabetes complications screening research initiative (DiScRi) dataset containing >200 variables from >2000 participants. In the first stage, we used two ML models (logistic regression and Evimp functions) implemented in multivariate adaptive regression splines model to infer the significant common risk factors for DM and CVD and applied the correlation matrix to reduce redundancy. In the second stage, we used classification and regression algorithm to develop our model. We evaluated the prediction models using prediction accuracy, sensitivity and specificity as performance metrics. Results: Common risk factors for DM and CVD co-occurrence was family history of the diseases, gender, deep breathing heart rate change, lying to standing blood pressure change, HbA1c, HDL and TC\HDL ratio. The predictive model showed that the participants with HbA1c >6.45 and TC\HDL ratio > 5.5 were at risk of developing both diseases (97.9% probability). In contrast, participants with HbA1c >6.45 and TC\HDL ratio ≤ 5.5 were more likely to have only DM (84.5% probability) and those with HbA1c ≤5.45 and HDL >1.45 were likely to be healthy (82.4%. probability). Further, participants with HbA1c ≤5.45 and HDL <1.45 were at risk of only CVD (100% probability). The predictive accuracy of the ML model to detect co-occurrence of DM and CVD is 94.09%, sensitivity 93.5%, and specificity 95.8%. Conclusions: Our ML model can significantly predict with high accuracy the co-occurrence of DM and CVD in people attending a screening program. This might help in early detection of patients with DM and CVD who could benefit from preventive treatment and reduce future healthcare burden. [ABSTRACT FROM AUTHOR]

Disease screening identifies a disease in an individual/community early to effectively prevent or treat the condition. COVID-19 has restricted hospital visits for screening and other healthcare services resulting in the disruption of screening for cancer, diabetes, and cardiovascular diseases. Smartphone technologies, coupled with built-in sensors and wireless technologies, enable the smartphone to function as a disease-screening and monitoring device with negligible additional costs and potentially higher quality results. Thus, we sought to evaluate the use of smartphone applications for disease screening and the acceptability of this technology in the medical and healthcare sectors. We followed a systematic review process using four databases, including Medline Complete, Web of Science, Embase, and Proquest. We included articles published in English examining smartphone application utilisation in disease screening. Further, we presented and discussed the primary outcomes of the research articles and their statistically significant value. The initial search yielded 1046 studies for the initial title and abstract screening. Of the 105 articles eligible for full-text screening, we selected nine studies and discussed them in detail under four main categories: an overview of the literature reviewed, participant characteristics, disease screening, and technology acceptance. According to our objective, we further evaluated the disease-screening approaches and classified them as clinically administered screening (33%, n = 3), health-worker-administered screening (33%, n = 3), and home-based screening (33%, n = 3). Finally, we analysed the technology acceptance among the users and healthcare practitioners. We observed a significant statistical relationship between smartphone applications and standard clinical screening. We also reviewed user acceptance of these smartphone applications. Hence, we set out critical considerations to provide equitable healthcare solutions without barriers when designing, developing, and deploying smartphone solutions. The findings may increase research opportunities for the evaluation of smartphone solutions as valid and reliable screening solutions. [ABSTRACT FROM AUTHOR]

The evolving pandemic of non-communicable diseases like hypertension, diabetes mellitus are globally on the rise, and the trend is also escalating in Bangladesh. We aimed to assess the prevalence trend and associated factors of hypertension (HTN), diabetes mellitus (DM), and hypertension- diabetes mellitus combined (HDC) among Bangladeshi adults from 2011 to 2018. Two nationally representative cross-sectional data from Bangladesh Demographic and Health Survey (BDHS): 2011 and 2017–18 were utilized. According to baseline characteristics, the average annual rate of change (AARC) was applied to quantify the annual rate of increase/decrease in HTN, DM, and HDC from 2011 to 2018. The prevalence ratios of HTN, DM, and HDC were assessed through modified Poisson regression with robust error variance (PR, 95% Confidence Interval (CI)). The data were prepared in SPSS version 23 and exported to Stata version 13 for further analysis. Among 11,686 participants, the overall mean age of the study participants was 52.79 years, Standard Deviation (SD)±12.99, and 42.28% were female. From 2011–2018, HTN, DM, and HDC prevalence in Bangladesh has increased by 13, 3.2, and 3.1 percentage points, respectively. The average annual rate of increase was observed in the HTN and HDC prevalence by all socio-economic and demographic categories during 2011–2018. The prevalence of HDC among Chittagong residents was approximately double in 2018: 3.95% (2011) versus 6.59% (2018). Increased age, inactive workers, overweight adults, and adults in wealthy families were common risk factors associated with HTN, DM, and HDC in Bangladesh. The prevalence of developing HTN and HDC was significantly higher among adults aged ≥ 70 years (PR: 2.70, 95% CI: 2.42–3.00; PR: 2.97, 95% CI: 2.08–4.24, respectively). A comprehensive approach of different stakeholders is required to develop appropriate strategies, including appropriate weight management, adequate physical activity, and healthier food habits. Health agencies should take initiatives to spread awareness among people at an early age, but special attention is needed for older people and those at risk for NCDs. [ABSTRACT FROM AUTHOR]

Aims: Mortality in children aged under two years is a severe public health problem in many developing countries. The aims of the study were to reveal the prevalence and factors associated with mortality in children under two years in Bangladesh. Methods: Data were analyzed using the Bangladesh Demographic and Health Survey 2014. A total of 7886 participant data used in this study. The chi-square test of association was performed with dependent and independent variables to measure the prevalence rate, while the final model binary logistic and log-binomial regressions were used to identify the potential risk factors for under-two mortalities. Results: The prevalence of under-2 mortalities in Bangladesh was 3.9%. Regression analysis revealed that a lower level of paternal education, succeeding birth interval less than 24 months, multiple birth babies, and smaller than the average size at birth were significantly associated with children's mortality under two years in Bangladesh. Conclusions: Despite improvements in the reduction of child mortality in Bangladesh, many children died within the first 24 months of life, mostly preventable. Programs towards increasing education levels and pregnancy intervals might help in preventing infant mortality in Bangladesh. [ABSTRACT FROM AUTHOR]

Caesarean delivery (C-section) has been increasing worldwide; however, many women from developing countries in Sub-Saharan Africa are deprived of these lifesaving services. This study aimed to explore the impact of certain socioeconomic factors, including respondent's education, husband's education, place of residence, and wealth index, on C-section delivery for women in Sub-Saharan Africa. We used pooled data from 36 demographic and health surveys (DHS) in Sub-Saharan Africa. Married women aged 15–49 years who have at least one child in the last five years were considered in this survey. After inclusion and excluding criteria, 234,660 participants were eligible for final analysis. Binary logistic regression was executed to determine the effects of selected socioeconomic factors. The countries were assembled into four sub-regions (Southern Africa, West Africa, East Africa, and Central Africa), and a meta-analysis was conducted. We performed random-effects model estimation for meta-analysis to assess the overall effects and consistency between covariates and utilization of C-section delivery as substantial heterogeneity was identified (I2 > 50%). Furthermore, the meta-regression was carried out to explain the additional amount of heterogeneity by country levels. We performed a sensitivity analysis to examine the effects of outliers in this study. Findings suggest that less than 15% of women in many Sub-Saharan African countries had C-section delivery. Maternal education (OR 4.12; CI 3.75, 4.51), wealth index (OR 2.05; CI 1.94, 2.17), paternal education (OR 1.71; CI 1.57, 1.86), and place of residence (OR 1.51; CI 1.44, 1.58) were significantly associated with the utilization of C-section delivery. These results were also consistent in sub-regional meta-analyses. The meta-regression suggests that the total percentage of births attended by skilled health staff (TPBASHS) has a significant inverse association with C-section utilization regarding educational attainment (respondent & husband), place of residence, and wealth index. The data structure was restricted to define the distinction between elective and emergency c-sections. It is essential to provide an appropriate lifesaving mechanism, such as C-section delivery opportunities, through proper facilities for rural, uneducated, impoverished Sub-Saharan African women to minimize both maternal and infant mortality. [ABSTRACT FROM AUTHOR]

Background: Stroke has been linked to a lack of physical activity; however, the extent of the association between inactive lifestyles and stroke risk has yet to be characterized across large populations. Purpose This study aimed to explore the association between activity‐related behaviors and stroke incidence. Methods: Data from 1999 to 2018 waves of the concurrent cross‐sectional National Health and Nutrition Examination Survey (NHANES) were extracted. We analyzed participants characteristics and outcomes for all participants with data on whether they had a stroke or not and assessed how different forms of physical activity affect the incidence of disease. Results: Of the 102,578 individuals included, 3851 had a history of stroke. A range of activity‐related behaviors was protective against stroke, including engaging in moderate‐intensity work over the last 30 days (OR = 0.8, 95% CI = 0.7–0.9; P = 0.001) and vigorous‐intensity work activities over the last 30 days (OR = 0.6, 95% CI = 0.5–0.8; P < 0.001), and muscle‐strengthening exercises (OR = 0.6, 95% CI = 0.5–0.8; P < 0.001). Conversely, more than 4 h of daily TV, video, or computer use was positively associated with the likelihood of stroke (OR = 11.7, 95% CI = 2.1–219.2; P = 0.022). Conclusion: Different types, frequencies, and intensities of physical activity were associated with reduced stroke incidence, implying that there is an option for everyone. Daily or every other day activities are more critical in reducing stroke than reducing sedentary behavior duration. [ABSTRACT FROM AUTHOR]

Introduction: To reduce mortality in hospitalized patients with COVID‐19 and cardiovascular disease (CVD), it is necessary to understand the relationship between patient's symptoms, risk factors, and comorbidities with their mortality rate. To the best of our knowledge, this paper is the first which take into account the determinants like risk factors, symptoms, and comorbidities leading to mortality in CVD patients who are hospitalized with COVID‐19. Methods: This study was conducted on 660 hospitalized patients with CVD and COVID‐19 recruited between January 2020 and January 2021 in Iran. All patients were diagnosed with the previous history of CVD like angina, myocardial infarction, heart failure, cardiomyopathy, abnormal heart rhythms, and congenital heart disease before they were hospitalized for COVID‐19. We collected data on patient's signs and symptoms, clinical and paraclinical examinations, and any underlying comorbidities. t test was used to determine the significant difference between the two deceased and alive groups. In addition, the relation between pairs of symptoms and pairs of comorbidities has been determined via correlation computation. Results: Our findings suggest that signs and symptoms such as fever, cough, myalgia, chest pain, chills, abdominal pain, nausea, vomiting, diarrhea, and anorexia had no impact on patients' mortality. There was a significant correlation between COVID‐19 cardiovascular patients' mortality rate and symptoms such as headache, loss of consciousness (LOC), oxygen saturation less than 93%, and need for mechanical ventilation. Conclusions: Our results might help physicians identify early symptoms, comorbidities, and risk factors related to mortality in CVD patients hospitalized for COVID‐19. [ABSTRACT FROM AUTHOR]

Background: Caregivers often use the internet to access information related to stroke care to improve preparedness, thereby reducing uncertainty and enhancing the quality of care. Method: Social media communities used by caregivers of people affected by stroke were identified using popular keywords searched for using Google. Communities were filtered based on their ability to provide support to caregivers. Data from the included communities were extracted and analysed to determine the content and level of interaction. Results: There was a significant rise in the use of social media by caregivers of people affected by stroke. The most popular social media communities were charitable and governmental organizations with the highest user interaction–this was for topics related to stroke prevention, signs and symptoms, and caregiver self-care delivered through video-based resources. Conclusion: Findings show the ability of social media to support stroke caregiver needs and practices that should be considered to increase their interaction and support. [ABSTRACT FROM AUTHOR]

Deep neural networks (DNNs) have been widely applied for detecting COVID-19 in medical images. Existing studies mainly apply transfer learning and other data representation strategies to generate accurate point estimates. The generalization power of these networks is always questionable due to being developed using small datasets and failing to report their predictive confidence. Quantifying uncertainties associated with DNN predictions is a prerequisite for their trusted deployment in medical settings. Here we apply and evaluate three uncertainty quantification techniques for COVID-19 detection using chest X-Ray (CXR) images. The novel concept of uncertainty confusion matrix is proposed and new performance metrics for the objective evaluation of uncertainty estimates are introduced. Through comprehensive experiments, it is shown that networks pertained on CXR images outperform networks pretrained on natural image datasets such as ImageNet. Qualitatively and quantitatively evaluations also reveal that the predictive uncertainty estimates are statistically higher for erroneous predictions than correct predictions. Accordingly, uncertainty quantification methods are capable of flagging risky predictions with high uncertainty estimates. We also observe that ensemble methods more reliably capture uncertainties during the inference. DNN-based solutions for COVID-19 detection have been mainly proposed without any principled mechanism for risk mitigation. Previous studies have mainly focused on on generating single-valued predictions using pretrained DNNs. In this paper, we comprehensively apply and comparatively evaluate three uncertainty quantification techniques for COVID-19 detection using chest X-Ray images. The novel concept of uncertainty confusion matrix is proposed and new performance metrics for the objective evaluation of uncertainty estimates are introduced for the first time. Using these new uncertainty performance metrics, we quantitatively demonstrate when we could trust DNN predictions for COVID-19 detection from chest X-rays. It is important to note the proposed novel uncertainty evaluation metrics are generic and could be applied for evaluation of probabilistic forecasts in all classification problems. [ABSTRACT FROM AUTHOR]

Introduction: The COVID-19 pandemic has enormously affected the psychological well-being, social and working life of millions of people across the world. This study aimed to investigate the psychological distress, fear and coping strategies as a result of the COVID-19 pandemic and its associated factors among Malaysian residents. Methods: Participants were invited to an online cross-sectional survey from Aug-Sep 2020. The study assessed psychological distress using the Kessler Psychological Distress Scale, level of fear using the Fear of COVID-19 Scale, and coping strategies using the Brief Resilient Coping Scale. Univariate and multivariate logistic regression analyses were conducted to adjust for potential confounders. Results: The mean age (±SD) of the participants (N = 720) was 31.7 (±11.5) years, and most of them were females (67.1%). Half of the participants had an income source, while 216 (30%) identified themselves as frontline health or essential service workers. People whose financial situation was impacted due to COVID-19 (AOR 2.16, 95% CIs 1.54–3.03), people who drank alcohol in the last four weeks (3.43, 1.45–8.10), people who were a patient (2.02, 1.39–2.93), and had higher levels of fear of COVID-19 (2.55, 1.70–3.80) were more likely to have higher levels of psychological distress. Participants who self-isolated due to exposure to COVID-19 (3.12, 1.04–9.32) and who had moderate to very high levels of psychological distress (2.56, 1.71–3.83) had higher levels of fear. Participants who provided care to a family member/patient with a suspected case of COVID-19 were more likely to be moderately to highly resilient compared to those who did not. Conclusion: Vulnerable groups of individuals such as patients and those impacted financially during COVID-19 should be supported for their mental wellbeing. Behavioural interventions should be targeted to reduce the impact of alcohol drinking during such crisis period. [ABSTRACT FROM AUTHOR]

COVID-19 has caused many deaths worldwide. The automation of the diagnosis of this virus is highly desired. Convolutional neural networks (CNNs) have shown outstanding classification performance on image datasets. To date, it appears that COVID computer-aided diagnosis systems based on CNNs and clinical information have not yet been analysed or explored. We propose a novel method, named the CNN-AE, to predict the survival chance of COVID-19 patients using a CNN trained with clinical information. Notably, the required resources to prepare CT images are expensive and limited compared to those required to collect clinical data, such as blood pressure, liver disease, etc. We evaluated our method using a publicly available clinical dataset that we collected. The dataset properties were carefully analysed to extract important features and compute the correlations of features. A data augmentation procedure based on autoencoders (AEs) was proposed to balance the dataset. The experimental results revealed that the average accuracy of the CNN-AE (96.05%) was higher than that of the CNN (92.49%). To demonstrate the generality of our augmentation method, we trained some existing mortality risk prediction methods on our dataset (with and without data augmentation) and compared their performances. We also evaluated our method using another dataset for further generality verification. To show that clinical data can be used for COVID-19 survival chance prediction, the CNN-AE was compared with multiple pre-trained deep models that were tuned based on CT images. [ABSTRACT FROM AUTHOR]

Purpose: This study examined the role of subject‐selection reasons and learning environment factors in students' depression and suicidality. Design and Methods: This study surveyed 960 students from five different Bangladeshi universities using questions concerning socio‐demographics, lifestyles, subject‐selection reasons, learning and academic environment, suicidal behaviors, and the Bangla Patient Health Questionnaire. Findings: Approximately half of the participants were depressed (47.7%), and just over a quarter reported past‐year suicidality (28.5%). Risk factors for both depression and suicidal behavior included not studying at their desired institute, selecting subjects based on future career prospects (rather than choosing what they want to study), not having a study‐friendly and research‐friendly environment, and unsupportive teachers. Practical Implications: The findings will help in formulating policies for educational institutions as well as providing benchmark data for further studies. [ABSTRACT FROM AUTHOR]