Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND

Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations.

METHODS

The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds.

FINDINGS

The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles.

INTERPRETATION

Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere.

FUNDING

Bill & Melinda Gates Foundation.

Global fertility in 204 countries and territories, 1950-2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

BACKGROUND

Accurate assessments of current and future fertility-including overall trends and changing population age structures across countries and regions-are essential to help plan for the profound social, economic, environmental, and geopolitical challenges that these changes will bring. Estimates and projections of fertility are necessary to inform policies involving resource and health-care needs, labour supply, education, gender equality, and family planning and support. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 produced up-to-date and comprehensive demographic assessments of key fertility indicators at global, regional, and national levels from 1950 to 2021 and forecast fertility metrics to 2100 based on a reference scenario and key policy-dependent alternative scenarios.

METHODS

To estimate fertility indicators from 1950 to 2021, mixed-effects regression models and spatiotemporal Gaussian process regression were used to synthesise data from 8709 country-years of vital and sample registrations, 1455 surveys and censuses, and 150 other sources, and to generate age-specific fertility rates (ASFRs) for 5-year age groups from age 10 years to 54 years. ASFRs were summed across age groups to produce estimates of total fertility rate (TFR). Livebirths were calculated by multiplying ASFR and age-specific female population, then summing across ages 10-54 years. To forecast future fertility up to 2100, our Institute for Health Metrics and Evaluation (IHME) forecasting model was based on projections of completed cohort fertility at age 50 years (CCF50; the average number of children born over time to females from a specified birth cohort), which yields more stable and accurate measures of fertility than directly modelling TFR. CCF50 was modelled using an ensemble approach in which three sub-models (with two, three, and four covariates variously consisting of female educational attainment, contraceptive met need, population density in habitable areas, and under-5 mortality) were given equal weights, and analyses were conducted utilising the MR-BRT (meta-regression-Bayesian, regularised, trimmed) tool. To capture time-series trends in CCF50 not explained by these covariates, we used a first-order autoregressive model on the residual term. CCF50 as a proportion of each 5-year ASFR was predicted using a linear mixed-effects model with fixed-effects covariates (female educational attainment and contraceptive met need) and random intercepts for geographical regions. Projected TFRs were then computed for each calendar year as the sum of single-year ASFRs across age groups. The reference forecast is our estimate of the most likely fertility future given the model, past fertility, forecasts of covariates, and historical relationships between covariates and fertility. We additionally produced forecasts for multiple alternative scenarios in each location: the UN Sustainable Development Goal (SDG) for education is achieved by 2030; the contraceptive met need SDG is achieved by 2030; pro-natal policies are enacted to create supportive environments for those who give birth; and the previous three scenarios combined. Uncertainty from past data inputs and model estimation was propagated throughout analyses by taking 1000 draws for past and present fertility estimates and 500 draws for future forecasts from the estimated distribution for each metric, with 95% uncertainty intervals (UIs) given as the 2·5 and 97·5 percentiles of the draws. To evaluate the forecasting performance of our model and others, we computed skill values-a metric assessing gain in forecasting accuracy-by comparing predicted versus observed ASFRs from the past 15 years (2007-21). A positive skill metric indicates that the model being evaluated performs better than the baseline model (here, a simplified model holding 2007 values constant in the future), and a negative metric indicates that the evaluated model performs worse than baseline.

FINDINGS

During the period from 1950 to 2021, global TFR more than halved, from 4·84 (95% UI 4·63-5·06) to 2·23 (2·09-2·38). Global annual livebirths peaked in 2016 at 142 million (95% UI 137-147), declining to 129 million (121-138) in 2021. Fertility rates declined in all countries and territories since 1950, with TFR remaining above 2·1-canonically considered replacement-level fertility-in 94 (46·1%) countries and territories in 2021. This included 44 of 46 countries in sub-Saharan Africa, which was the super-region with the largest share of livebirths in 2021 (29·2% [28·7-29·6]). 47 countries and territories in which lowest estimated fertility between 1950 and 2021 was below replacement experienced one or more subsequent years with higher fertility; only three of these locations rebounded above replacement levels. Future fertility rates were projected to continue to decline worldwide, reaching a global TFR of 1·83 (1·59-2·08) in 2050 and 1·59 (1·25-1·96) in 2100 under the reference scenario. The number of countries and territories with fertility rates remaining above replacement was forecast to be 49 (24·0%) in 2050 and only six (2·9%) in 2100, with three of these six countries included in the 2021 World Bank-defined low-income group, all located in the GBD super-region of sub-Saharan Africa. The proportion of livebirths occurring in sub-Saharan Africa was forecast to increase to more than half of the world's livebirths in 2100, to 41·3% (39·6-43·1) in 2050 and 54·3% (47·1-59·5) in 2100. The share of livebirths was projected to decline between 2021 and 2100 in most of the six other super-regions-decreasing, for example, in south Asia from 24·8% (23·7-25·8) in 2021 to 16·7% (14·3-19·1) in 2050 and 7·1% (4·4-10·1) in 2100-but was forecast to increase modestly in the north Africa and Middle East and high-income super-regions. Forecast estimates for the alternative combined scenario suggest that meeting SDG targets for education and contraceptive met need, as well as implementing pro-natal policies, would result in global TFRs of 1·65 (1·40-1·92) in 2050 and 1·62 (1·35-1·95) in 2100. The forecasting skill metric values for the IHME model were positive across all age groups, indicating that the model is better than the constant prediction.

INTERPRETATION

Fertility is declining globally, with rates in more than half of all countries and territories in 2021 below replacement level. Trends since 2000 show considerable heterogeneity in the steepness of declines, and only a small number of countries experienced even a slight fertility rebound after their lowest observed rate, with none reaching replacement level. Additionally, the distribution of livebirths across the globe is shifting, with a greater proportion occurring in the lowest-income countries. Future fertility rates will continue to decline worldwide and will remain low even under successful implementation of pro-natal policies. These changes will have far-reaching economic and societal consequences due to ageing populations and declining workforces in higher-income countries, combined with an increasing share of livebirths among the already poorest regions of the world.

FUNDING

Bill & Melinda Gates Foundation.

Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND

Detailed, comprehensive, and timely reporting on population health by underlying causes of disability and premature death is crucial to understanding and responding to complex patterns of disease and injury burden over time and across age groups, sexes, and locations. The availability of disease burden estimates can promote evidence-based interventions that enable public health researchers, policy makers, and other professionals to implement strategies that can mitigate diseases. It can also facilitate more rigorous monitoring of progress towards national and international health targets, such as the Sustainable Development Goals. For three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has filled that need. A global network of collaborators contributed to the production of GBD 2021 by providing, reviewing, and analysing all available data. GBD estimates are updated routinely with additional data and refined analytical methods. GBD 2021 presents, for the first time, estimates of health loss due to the COVID-19 pandemic.

METHODS

The GBD 2021 disease and injury burden analysis estimated years lived with disability (YLDs), years of life lost (YLLs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries using 100 983 data sources. Data were extracted from vital registration systems, verbal autopsies, censuses, household surveys, disease-specific registries, health service contact data, and other sources. YLDs were calculated by multiplying cause-age-sex-location-year-specific prevalence of sequelae by their respective disability weights, for each disease and injury. YLLs were calculated by multiplying cause-age-sex-location-year-specific deaths by the standard life expectancy at the age that death occurred. DALYs were calculated by summing YLDs and YLLs. HALE estimates were produced using YLDs per capita and age-specific mortality rates by location, age, sex, year, and cause. 95% uncertainty intervals (UIs) were generated for all final estimates as the 2·5th and 97·5th percentiles values of 500 draws. Uncertainty was propagated at each step of the estimation process. Counts and age-standardised rates were calculated globally, for seven super-regions, 21 regions, 204 countries and territories (including 21 countries with subnational locations), and 811 subnational locations, from 1990 to 2021. Here we report data for 2010 to 2021 to highlight trends in disease burden over the past decade and through the first 2 years of the COVID-19 pandemic.

FINDINGS

Global DALYs increased from 2·63 billion (95% UI 2·44-2·85) in 2010 to 2·88 billion (2·64-3·15) in 2021 for all causes combined. Much of this increase in the number of DALYs was due to population growth and ageing, as indicated by a decrease in global age-standardised all-cause DALY rates of 14·2% (95% UI 10·7-17·3) between 2010 and 2019. Notably, however, this decrease in rates reversed during the first 2 years of the COVID-19 pandemic, with increases in global age-standardised all-cause DALY rates since 2019 of 4·1% (1·8-6·3) in 2020 and 7·2% (4·7-10·0) in 2021. In 2021, COVID-19 was the leading cause of DALYs globally (212·0 million [198·0-234·5] DALYs), followed by ischaemic heart disease (188·3 million [176·7-198·3]), neonatal disorders (186·3 million [162·3-214·9]), and stroke (160·4 million [148·0-171·7]). However, notable health gains were seen among other leading communicable, maternal, neonatal, and nutritional (CMNN) diseases. Globally between 2010 and 2021, the age-standardised DALY rates for HIV/AIDS decreased by 47·8% (43·3-51·7) and for diarrhoeal diseases decreased by 47·0% (39·9-52·9). Non-communicable diseases contributed 1·73 billion (95% UI 1·54-1·94) DALYs in 2021, with a decrease in age-standardised DALY rates since 2010 of 6·4% (95% UI 3·5-9·5). Between 2010 and 2021, among the 25 leading Level 3 causes, age-standardised DALY rates increased most substantially for anxiety disorders (16·7% [14·0-19·8]), depressive disorders (16·4% [11·9-21·3]), and diabetes (14·0% [10·0-17·4]). Age-standardised DALY rates due to injuries decreased globally by 24·0% (20·7-27·2) between 2010 and 2021, although improvements were not uniform across locations, ages, and sexes. Globally, HALE at birth improved slightly, from 61·3 years (58·6-63·6) in 2010 to 62·2 years (59·4-64·7) in 2021. However, despite this overall increase, HALE decreased by 2·2% (1·6-2·9) between 2019 and 2021.

INTERPRETATION

Putting the COVID-19 pandemic in the context of a mutually exclusive and collectively exhaustive list of causes of health loss is crucial to understanding its impact and ensuring that health funding and policy address needs at both local and global levels through cost-effective and evidence-based interventions. A global epidemiological transition remains underway. Our findings suggest that prioritising non-communicable disease prevention and treatment policies, as well as strengthening health systems, continues to be crucially important. The progress on reducing the burden of CMNN diseases must not stall; although global trends are improving, the burden of CMNN diseases remains unacceptably high. Evidence-based interventions will help save the lives of young children and mothers and improve the overall health and economic conditions of societies across the world. Governments and multilateral organisations should prioritise pandemic preparedness planning alongside efforts to reduce the burden of diseases and injuries that will strain resources in the coming decades.

FUNDING

Bill & Melinda Gates Foundation.

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950-2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

BACKGROUND

Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020-21 COVID-19 pandemic period.

METHODS

22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution.

FINDINGS

Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5-65·1] decline), and increased during the COVID-19 pandemic period (2020-21; 5·1% [0·9-9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98-5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50-6·01) in 2019. An estimated 131 million (126-137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7-17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8-24·8), from 49·0 years (46·7-51·3) to 71·7 years (70·9-72·5). Global life expectancy at birth declined by 1·6 years (1·0-2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67-8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4-52·7]) and south Asia (26·3% [9·0-44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations.

INTERPRETATION

Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic.

FUNDING

Bill & Melinda Gates Foundation.

Rural and urban differences in the prevalence and determinants of Type-2 diabetes in Bangladesh

OBJECTIVE

To estimate the prevalence of Type 2 Diabetes (T2D) in urban and rural settings and identify the specific risk factors for each location.

METHOD

We conducted this study using data from the 2017-18 Bangladesh Demographic and Health Survey (BDHS), sourced from the DHS website. The survey employed a stratified two-stage sampling method, which included 7,658 women and 7,048 men aged 18 and older who had their blood glucose levels measured. We utilized chi-square tests and ordinal logistic regression to analyze the association between various selected variables in both urban and rural settings and their relationship with diabetes and prediabetes.

RESULTS

The prevalence of T2D was 10.8% in urban areas and 7.4% in rural areas, while pre-diabetes affected 31.4% and 27% of the populations in these respective settings. The study found significant factors influencing diabetes in both urban and rural regions, particularly in the 55-64 age group (Urban: AOR = 1.88, 95% CI [1.46, 2.42]; Rural: AOR = 1.87, 95% CI [1.54, 2.27]). Highly educated individuals had lower odds of T2D, while wealthier and overweight participants had higher odds in both areas. In rural regions, T2D risk was higher among caffeinated drink consumers and those not engaged in occupation-related physical activity, while these factors did not show significant influence in urban areas. Furthermore, urban participants displayed a significant association between T2D and hypertension.

CONCLUSION

Our study outlines a comprehensive strategy to combat the increasing prevalence of T2D in both urban and rural areas. It includes promoting healthier diets to control BMI level, encouraging regular physical activity, early detection through health check-ups, tailored awareness campaigns, improving healthcare access in rural regions, stress management in urban areas, community involvement, healthcare professional training, policy advocacy like sugary drink taxation, research, and monitoring interventions. These measures collectively address the T2D challenge while accommodating the distinct features of urban and rural settings.

Coverage of defects over Posterior aspect of Ankle Joint and Heel with Lateral Calcaneal Artery Flap- Experience in Mymensingh Medical College Hospital

Lateral calcaneal artery flap is randomly used by many Plastic Surgeons for covering any defect on the posterior aspect of heel. A prospective observational study was conducted in the Department of Burn and Plastic Surgery, Mymensingh Medical College Hospital, Mymensingh, Bangladesh from January 2020 to June 2022, to see the outcome of the flap for coverage of defects over the posterior aspect of ankle joint and heel. A total number of 09 patients, selected by purposive sampling, were included in the study. The age of the patients ranged from 06 years to 70 years. The cause of the defects were post traumatic in 07 cases, electric burn in 01 case and pressure sore in 01 case. The defect sizes varied from 3×2 to 6×3cm. and flap size ranged from 4×2.5 to 7×4.5cm. The follow-up period ranged from 3 to 6 months. All the flaps survived completely without any complications; except in two cases. In one case, there was marginal epidermal necrolysis that healed secondarily without the need of any further surgical intervention. In the other case, there was gangrene of about 0.5 cm area at the flap tip, which was debrided and the resulting wound healed secondarily. The average operating time was 63 minutes. The results were satisfactory on the context of adequate coverage, and flap and donor site morbidity. So, the lateral calcaneal artery flap can be a good and safe option for the coverage of posterior ankle and heel defects.

Developments in Hand Surgery: Experience from a Tertiary Hospital of Northern Bangladesh

Hand Surgery is a specialized branch of Plastic and Reconstructive surgery. There are many conditions that require hand surgery, for example, congenital deformity, electric or flame burn, mechanical or road traffic injury, and post burn or post traumatic deformity. A retrospective observational study was conducted in the department of Burn and Plastic surgery, Mymensingh Medical College Hospital, Bangladesh during a 2 years period extending from 9th September 2021 to 8th September 2023. The objective of this study was to see the hand surgery status in a tertiary hospital of Bangladesh during the post Covid pandemic period. During this period 236 hand surgery procedures were performed in 176 patients. The age of the patients ranged from 02 to 78 years (Mean 31.14±1.52). One hundred and four (59.0%) were male and 72(41.0%) were female. Thirty-four (19.32%) patients had co-morbidities e.g., Epilepsy, Diabetes Mellitus, Chronic Kidney Diseases and HBsAg +ve. Causes of surgery included, wound due to electric burn 49(27.84%), flame burn 36(20.45%), post traumatic 24(13.64%), post infective 11(06.25%), tumor excision 02(2.24%), Dupuytren's contracture 03(1.70%), congenital anomalies 06(3.41%), post burn scar contractures 41(23.29%), nerve injury 01(00.57%) and carpal tunnel syndrome 01 (00.57%). Procedures were performed: post burn scar contracture release 41(17.37%), syndactly release 06(2.54%), release of post traumatic contracture 06(2.54%), carpal tunnel release 01(00.42%), release of Dupuytren's contracture 03(01.27%), nerve repair 01(00.42%), debridement, amputation and Fillet flap 29(12.29%), split thickness skin graft 46 (19.49%), V-Y advancement flap 06(2.54%), transposition flap 18(07.63%), cross finger flap 16 (06.78%), reverse cross finger flap 02 (00.85%), first dorsal metacarpal artery (FDMA) flap 05 (02.12%), reverse FDMA flap 01 (00.42%), metacarpal artery perforator flap 08(3.39%), radial artery perforator flap 04(01.69%), posterior interosseous artery flap 05(2.12%), abdominal flap 11(04.46%) and flap division and insetting 27(11.44%). Outcome of surgery was satisfactory in 225(95.34%) and 11(04.46%) cases had complications (p value 0.453), which was not significant. So, it can be concluded that the outcome of various types of hand surgery procedures in tertiary hospital of northern Bangladesh during the post Covid period was satisfactory overall.

Prediction of suicidal ideation with associated risk factors among university students in the southern part of Bangladesh: Machine learning approach

BACKGROUND

The prevalence of suicidal ideation has become an urgent issue, particularly among adolescents. The primary objective of this research is to determine the prevalence of suicidal ideation among students in the southern region of Bangladesh and to predict this phenomenon using machine learning (ML) models.

METHODS

The data collection process involved using a simple random sampling technique to gather information from university students located in the southern region of Bangladesh during the period spreading from April 2022 to June 2022. Upon accounting for missing values and non-response rates, the ultimate sample size was determined to be 584, with 51.5 % of participants identifying as male and 48.5 % female.

RESULTS

A significant proportion of students, precisely 19.9 %, reported experiencing suicidal ideation. Most participants were female (77 %) and unmarried (78 %). Within the machine learning (ML) framework, KNN exhibited the highest accuracy score of 91.45 %. In addition, the Random Forest (RF), and Categorical Boosting (CatBoost) algorithms exhibited comparable levels of accuracy, achieving scores of 90.60 and 90.59 respectively.

LIMITATIONS

Using a cross-sectional design in research limits the ability to establish causal relationships.

CONCLUSION

Mental health practitioners can employ the KNN model alongside patients' medical histories to detect those who may be at a higher risk of attempting suicide. This approach enables healthcare professionals to take appropriate measures, such as counselling, encouraging regular sleep patterns, and addressing depression and anxiety, to prevent suicide attempts.

Prevalence and determinants of hypertension in South-Asian Urban Communities: findings from Demographic and Health Surveys (DHS) data of South Asian countries

Hypertension increases risk of stroke and other cardiovascular diseases, however, its prevalence and determinants in South Asian urban communities using country representative community-based datasets is lacking. This study evaluated prevalence of hypertension and it's determinants among urban residents of three South Asian countries. Urban population data from demographic and health surveys in Bangladesh, India, and Nepal were extracted. Hypertension prevalence was defined as systolic/diastolic blood pressure ≥ 140/ 90 mmHg. Age, education, wealth, physical activity, alcohol, BMI were considered as risk factors associated with the increased risk of hypertension. We performed binary logistic regression and calculated adjusted Odds Ratios (AOR) with 95% confidence interval (CI) to assess factors related to hypertension. Hypertension prevalence was 37.4% in India, 25.1% in Bangladesh and 18.4% in Nepal. Prevalence increased with age in all settings. Females had reduced odds of hypertension in Bangladesh (AOR 0.75; CI: 0.69, 0.81) and Nepal (AOR 0.62; CI: 0.54, 0.71), but higher risk in India (AOR 2.54; CI: 2.45, 2.63). Low education, caffeine consumption, obesity was associated with higher prevalence of hypertension in all three countries. Smokers had increased odds of hypertension in India (AOR 1.11; CI: 1.06, 1.15) and Nepal (AOR 1.23; 1.02, 1.47). Overall, hypertension prevalence is high in all three countries. Modifiable socioeconomic and lifestyle factors (education, wealth index, smoking status, caffeine consumption and BMI) associated with hypertension. Comprehensive hypertension pacific and sensitive interventions (including behavioral modification treatments and timely screening and access to health care) are urgently needed to prevent and control hypertension among urban populations in South Asia.

Smoke-free status of homes and workplaces among Indian people: Evidence from Global Adult Tobacco SurveyData-2016/2017

AIMS

This study aimed to determine the impact of correlates on tobacco control/smoke-free status of homes and workplace among Indian people. To assess the magnitude of the problem, the relationship between smoke-free status and secondhand smoke (SHS) exposure was also explored.

METHODS

Data was extracted from the Global Adult Tobacco Survey Data (GATS)-2017. It was a household survey that included people aged 15 years or older and covered all 30 states and 2 Union Territories (UTs) of India. A logistic regression model was used to determine the correlates of smoke-free status of homes and workplaces. Additionally, the Pearson correlation was used to explore the relationship between smoke-free status and the proportion of participants exposed to SHS both at homes and in the workplaces.

RESULTS

The overall prevalence of smoke-free status in the home and workplace was 62.8% and 51.7%, respectively. Results of multivariate analysis (Logistic regression) illustrated that indicators like tobacco smoking status, place of residence, region, education, occupation, wealth quintile, and knowledge status about children's illness were significantly associated with the respondent's intention to live in a completely smoke-free environment both at home and in the workplace in India. This study revealed that SHS exposure was significantly negatively associated with a smoke-free status.

CONCLUSION

This study will help the policymakers to promote efficient policies for improving smoke-free status and to ensure a better environment both at home and in the workplace in India.

Knowledge, attitudes, and factors determining the willingness for COVID-19 vaccination among students in Bangladesh: An online-based cross-sectional study

Aim

The most effective way to avoid COVID-19 is through immunization against the virus that causes the disease. The primary objective of this study was to assess the extent of knowledge, attitudes, acceptability, and factors influencing COVID-19 vaccination acceptance among higher secondary and university students in Bangladesh.

Subject and methods

A structured questionnaire-based online survey was conducted among 451 students residing in Khulna and Gopalganj cities from February to August, 2022. The willingness to accept the COVID-19 vaccine was compared with a few covariates using the chi-square test, and we then used binary logistic regression to identify the determinants that led Bangladeshi students to receive the COVID-19 vaccine.

Results

During the study period, almost 70% of the students obtained immunizations, with 56% of men and 44% of women reporting having done so. The age range of 26-30 years had the highest percentage of students who had received vaccinations, and 83.9% of students agreed that the COVID-19 vaccine is crucial for students. The results of the binary logistic regression clearly show that gender, degree of education, and respondents' willingness, encouragement, and beliefs have a significant impact on students' eagerness to receive COVID-19 vaccination.

Conclusion

The rising trend in vaccination status among Bangladeshi students is highlighted by this study. Additionally, our results eloquently demonstrate that vaccination status varies by gender, education level, willingness, encouragement, and respondent's viewpoint. The outcomes of this study are essential for health policy makers and other interested parties to successfully organize their immunization program for young adults and children at various levels.

Dynamic changes in prevalence of type 2 diabetes along with associated factors in Bangladesh: Evidence from two national cross-sectional surveys (BDHS 2011 and BDHS 2017-18)

BACKGROUND AND AIMS

Prevalence of type 2 diabetes has been rising rapidly especially in low- and middle-income countries. The purpose of this study is to analyze the prevalence of type 2 diabetes in 2011 and 2017-18, and the risk factors based on the Bangladesh Demographic and Health Surveys (BDHS).

METHODS

The study comprised of data from the BDHS 2011 and the BDHS 2017-18 with 7565 (50.6% female) and 12,299 respondents (56.9% female) respectively. The plasma blood glucose was classified into normal, pre-diabetes, and diabetes categories. While univariate analysis was performed to determine the data, Chi-square and gamma analyses were used for bivariate estimation of the correlation between diabetes status and other comorbidities. Multinomial and ordinal logistic regression were also performed to trace the link between diabetes and various risk factors.

RESULTS

The 2011 BDHS survey indicated that nearly half of the participants (47.6%) had pre-diabetic condition, while 10.2% were diagnosed with diabetes. On the other hand, the BDHS 2017-18 demonstrated that 28.6% and 8.6% of participants had pre-diabetes and diabetes, respectively. Results of inferential statistics showed that gender (p<0.05), age, wealth status, physical activity, BMI (p<0.01), and caffeinated beverages (p<0.05), were significantly linked with diabetes status.

CONCLUSION

According to our findings, older people and people with lower education are more likely to develop diabetes. BMI` Physically active, wealth status, diet and lifestyle were significant predictors of type 2 diabetes. Healthy lifestyle, physical activities, proper knowledge and awareness can reduce the risk of T2D.

A Comparative Study of Collagen Sheet versus 1% Silver Sulfadiazine Dressing in Superficial Partial Thickness Burns

Burn injury causes a lot of suffering. The goal of burn management is to achieve rapid wound healing, pain relief, rehabilitation with minimum scars and optimal functional ability. Objective of this study was to compare the efficacy of collagen sheets and 1% silver sulfadiazine dressing (SSD) for superficial partial thickness burns. This prospective observational study was conducted among the patients of Department of Plastic surgery, Dhaka Medical College Hospital, and Sheikh Hasina National Institute of Burn and Plastic Surgery, Dhaka, from 1st April 2020 to 31st March 2021. Total 60 patients with superficial partial thickness burns by purposive sampling 30 patients of them were treated with collagen sheet dressing (Group A) and 30 patients with 1.0% silver sulfadiazine dressing (Group B). First case was selected by tossing a coin. Then every alternate patient was provided the same kind of dressing material (either collagen sheet or 1.0% silver sulfadiazine). Data were collected by semi structured data collection sheets. Pearson's chi-square test and student's 't' test were used for data analysis (p value was significant at <0.05). It was observed that a total of 18(60.0%) patients belonged to age <10 years in Group A and 17(56.7%) patients in Group B. The mean age was 14.9±14.2 years in Group A and 11.6±10.2 years in Group B. Good quality of healing was significantly higher in the collagen group compared to the SSD group (<0.05). The mean complete healing time in the collagen group was 10.47±2.21 days and in the 1.0% SSD group were 13.07±2.33 days. The mean healing time was significantly lower in the collagen group compared to the 1.0% SSD group (p<0.001). There was no significant difference in infection rate between the two groups (p>0.05). Considering the overall outcome, Collagen sheet dressing decreases pain, reduces the need for analgesics, aids in early healing as compared to the patients treated with 1% silver sulfadiazine.

Association Between Symptoms and Severity of Disease in Hospitalised Novel Coronavirus (COVID-19) Patients: A Systematic Review and Meta-Analysis

Background

Symptoms of the novel coronavirus disease (COVD-19) are well known, although asymptomatic cases were also reported due to this rapidly evolving viral disease. However, there has been limited research with inconsistent findings on symptoms of COVID-19 and disease severity. We aimed to evaluate the association between symptoms and severity of disease in adult patients with confirmed COVID-19 by performing a meta-analysis.

Methods

We conducted this study by searching four online databases (Medline, Web of Science, EMBASE and Cochrane library) of published studies that included symptoms of COVID-19 cases and severity of the disease between January 1, 2020, and October 31, 2021. PRISMA and MOOSE guidelines were followed, and only articles published in English were selected. We performed meta-analysis using Mantel-Haenszel random-effects model. Note that we included peer-reviewed studies conducted in Wuhan and published in the English language that reported the clinical characteristics of COVID-19, particularly the symptoms of novel coronavirus patients with their prevalence and distribution of patients based on the severity of the disease.

Results

Out of 255 articles identified, a total of twenty articles, including 5390 participants, met the inclusion criteria and were included. Among the participants, 2997 (55.60%) were males, and 974 (18.07%) reported severe conditions. Fever was the most commonly reported symptom in the reported COVID-19 confirmed cases (88.47%, 95% CI: 80.74-93.35%), which was followed by cough, fatigue, and less proportionally dyspnea and myalgia. Dyspnea was the only symptom, which was associated with severity of COVID-19 (OR 2.43, 95% CI: 1.52-3.89).

Conclusion

Dyspnoea was found to be associated with severity of COVID-19. People with existing respiratory illnesses, such as chronic obstructive pulmonary diseases need to be careful about the onset of such symptom and should seek medical attention.

Machine Learning Approaches for Predicting Hypertension and Its Associated Factors Using Population-Level Data From Three South Asian Countries

Background

Hypertension is the most common modifiable risk factor for cardiovascular diseases in South Asia. Machine learning (ML) models have been shown to outperform clinical risk predictions compared to statistical methods, but studies using ML to predict hypertension at the population level are lacking. This study used ML approaches in a dataset of three South Asian countries to predict hypertension and its associated factors and compared the model's performances.

Methods

We conducted a retrospective study using ML analyses to detect hypertension using population-based surveys. We created a single dataset by harmonizing individual-level data from the most recent nationally representative Demographic and Health Survey in Bangladesh, Nepal, and India. The variables included blood pressure (BP), sociodemographic and economic factors, height, weight, hemoglobin, and random blood glucose. Hypertension was defined based on JNC-7 criteria. We applied six common ML-based classifiers: decision tree (DT), random forest (RF), gradient boosting machine (GBM), extreme gradient boosting (XGBoost), logistic regression (LR), and linear discriminant analysis (LDA) to predict hypertension and its risk factors.

Results

Of the 8,18,603 participants, 82,748 (10.11%) had hypertension. ML models showed that significant factors for hypertension were age and BMI. Ever measured BP, education, taking medicine to lower BP, and doctor's perception of high BP was also significant but comparatively lower than age and BMI. XGBoost, GBM, LR, and LDA showed the highest accuracy score of 90%, RF and DT achieved 89 and 83%, respectively, to predict hypertension. DT achieved the precision value of 91%, and the rest performed with 90%. XGBoost, GBM, LR, and LDA achieved a recall value of 100%, RF scored 99%, and DT scored 90%. In F1-score, XGBoost, GBM, LR, and LDA scored 95%, while RF scored 94%, and DT scored 90%. All the algorithms performed with good and small log loss values &lt;6%.

Conclusion

ML models performed well to predict hypertension and its associated factors in South Asians. When employed on an open-source platform, these models are scalable to millions of people and might help individuals self-screen for hypertension at an early stage. Future studies incorporating biochemical markers are needed to improve the ML algorithms and evaluate them in real life.

Knowledge, Attitudes, and Practices Concerning COVID-19 in Bangladesh: A Qualitative Study of Patients With Chronic Illnesses

The novel coronavirus disease (COVID-19) has posed a serious risk with pre-existing health conditions. This study was conducted to understand the knowledge, attitude, and practices concerning COVID-19 among patients with chronic illnesses in Bangladesh during the pandemic. The study was conducted in Khulna city of Bangladesh following a qualitative research design. We employed telephone interviews to collect data from 40 participants with four common pre-existing chronic illnesses (diabetes, hypertension, respiratory/asthma, and heart disease). Findings show that the majority of the participants had a moderate level of knowledge and an overall positive attitude regarding COVID-19 but appropriate safety practices were often ignored as the pandemic grows older. We also observed that the knowledge, attitude, and practice regarding COVID-19 varied based on age, marital status, education, social class, and rural/urban residence. We concluded that improving medical advice/support, promotion of awareness through mass media, strict monitoring of protective measures and subsidies from the government, and self-consciousness could be effective strategies to mitigate the transmission of the disease and reduce risks for patients with chronic illness in Bangladesh during the COVID-19 pandemic.

Prevalence and Triggering Factors of Childhood Anemia: An Application of Ordinal Logistic Regression Model

INTRODUCTION

Anemia is indeed a significant risk factor for children's health as it affects growth retardation and has severe short and prolonged effects that follow in morbidity and death. Notwithstanding such ways to tackle anemia, the prevalence remains high in India and poses a severe public health concern.

OBJECTIVES

The primary focus of this study was to find the prevalence and to determine the factors associated with the anemia of children under five years of age in India. Problem Statement. The increasing prevalence of childhood anemia and the life-threatening consequences for millions of children in India are a major concern. Knowing the relevant associated factors with childhood anemia is essential to reduce the frequency and severity level. Study design. For analysis purposes, this study utilized a cross-sectional study design. Methodology. Using the Indian Demographic and Health Survey 2015-16 data, we used chi-squared and gamma tests to find the association. Then, we utilized multinomial logistic regression and ordinal logistic regression to find the better model and the influencing factors of anemia in India.

RESULTS

In our study, we have found that children with highly educated mothers were 36.7% less likely (OR = 0.633, P ≤ 0.001, 95% CI: 0.608, 0.658) to be higher anemic than the children with not educated mother. Children with moderate and severe anemic mothers were 163.3% (OR = 2.633, P ≤ 0.001, 95% CI: 2.565, 7.704) more likely to be higher anemic than the children with not anemic mother. Not stunting children were 21.9% (OR = 0.781, P ≤ 0.001, 95% CI: 0 .764, 0.797) less likely to be higher anemic than the stunting children. Children aged 36-59 months were 73.9% (OR = 0.361, P ≤ 0.001, 95% CI: 0.353, 0.369) less likely to be higher anemic than the children aged 6-24 months. Again, the ACI value revealed that ordinal logistic regression was a better-fitted model for these data.

CONCLUSION

and contribution. The variables such as stunting, underweight, wasting, child age, size of the child, and source of drinking water were the most critical indicators for child anemia in India. In summary, our study result indicated the major socioeconomic and demographic factors associated with childhood anemia in India, which can help the policymaker to take quick decision to reduce the severity level.

Correction: Prevalence of unintended pregnancy and its associated factors: Evidence from six south Asian countries

[This corrects the article DOI: 10.1371/journal.pone.0245923.].

Machine Learning Approaches to Identify Patient Comorbidities and Symptoms That Increased Risk of Mortality in COVID-19

Providing appropriate care for people suffering from COVID-19, the disease caused by the pandemic SARS-CoV-2 virus, is a significant global challenge. Many individuals who become infected may have pre-existing conditions that may interact with COVID-19 to increase symptom severity and mortality risk. COVID-19 patient comorbidities are likely to be informative regarding the individual risk of severe illness and mortality. Determining the degree to which comorbidities are associated with severe symptoms and mortality would thus greatly assist in COVID-19 care planning and provision. To assess this we performed a meta-analysis of published global literature, and machine learning predictive analysis using an aggregated COVID-19 global dataset. Our meta-analysis suggested that chronic obstructive pulmonary disease (COPD), cerebrovascular disease (CEVD), cardiovascular disease (CVD), type 2 diabetes, malignancy, and hypertension as most significantly associated with COVID-19 severity in the current published literature. Machine learning classification using novel aggregated cohort data similarly found COPD, CVD, CKD, type 2 diabetes, malignancy, and hypertension, as well as asthma, as the most significant features for classifying those deceased versus those who survived COVID-19. While age and gender were the most significant predictors of mortality, in terms of symptom-comorbidity combinations, it was observed that Pneumonia-Hypertension, Pneumonia-Diabetes, and Acute Respiratory Distress Syndrome (ARDS)-Hypertension showed the most significant associations with COVID-19 mortality. These results highlight the patient cohorts most likely to be at risk of COVID-19-related severe morbidity and mortality, which have implications for prioritization of hospital resources.

Sociodemographic factors and early marriage among women in Bangladesh, Ghana and Iraq: An illustration from Multiple Indicator Cluster Survey

Early marriage is a form of violation of child rights to grow and develop. The Sustainable Development Goals had included early marriage in target 5.3, aiming to eliminate by 2030. This study examines the socio-demographic factors associated with women's early marriage in Bangladesh, Ghana, and Iraq using information extracted from 2019, 2017-2018, and 2018 Multiple Indicator Cluster Surveys (MICSs) of Bangladesh, Ghana, and Iraq, respectively. The chi-square test examined the association between socio-demographic factors and early marriage separately in all three countries. In logistic regression, key factors were primarily evaluated for determining effects on early marriage separately in all three countries. The mean age of the mother at first marriage was found to be 16.86, 20.23, and 20.05 years in Bangladesh, Ghana, and Iraq successively. According to surveys conducted in Bangladesh, Ghana, and Iraq, education levels of household heads and women, wealth status, mass media, number of household members, and residence were significant factors linked to early marriage. The odds of getting married early were significantly higher among women with no formal education and primary education than women with secondary or higher education in all three countries. In terms of economic status, a negative association was found between wealth status and early marriage in both Bangladesh and Ghana. Based on the findings, the study recommended that government take the necessary steps to reduce child marriage in all three countries by raising women's education and campaigning women by media to harmful effects of early marriage, particularly women from low-income families.

People’s Concerns With the Prediction of COVID-19 in Bangladesh: Application of Autoregressive Integrated Moving Average Model

Introduction: The coronavirus disease 2019 (COVID-19) has become a public health concern, and behavioral adjustments will minimize its spread worldwide by 80%. The main purpose of this research was to examine the factors associated with concerns about COVID-19 and the future direction of the COVID-19 scenario of Bangladesh. Methods: The binary logistic regression model was performed to assess the impact of COVID-19 concern in Bangladesh. Based on data obtained through online surveys in November 2020 and to predict the next 40 days daily confirmed and deaths of COVID-19 in Bangladesh by applying the Autoregressive Integrated Moving Average (ARIMA) model. Results: The study enrolled 400 respondents, with 253 (63.2%) were male, and 147 (36.8%) were female. The mean age of respondents was 25.13 ± 5.74 years old. Almost 70% of them were found to be concerned about the COVID-19 pandemic. The result showed that respondents’ education level, knowledge regarding COVID-19 transmits, households with aged people, seasonal flu and HD/respiratory problems, and materials used while sneezing/coughing significantly influenced COVID-19 concerns. The analysis predicted that confirmed cases would gradually decrease for the ARIMA model while death cases will be constant for the next 40 days in Bangladesh. Conclusion: The current study suggested that knowledge about COVID-19 spread and education played a vital role in the decline of COVID-19 concerned. A particular program should focus on creating an awareness of the disadvantages of concerns about the COVID-19 pandemic by augmenting knowledge about COVID-19 spread, enhancing Education in Bangladesh.

Factors associated with age of mother at first birth in Albania: application of quantile regression model

The objective of this study was to explore the risk factors that can determine the age of mother at first birth in Albania. The necessary information was extracted from a nationally representative sample survey, Albania Demographic and Health Survey, 2017-18 dataset. To identify the possible risk factors of the age of mother at first birth, we applied quantile regression model. The mean age of mother at first birth was found to be 22.38 years with standard deviation of 3.56 years. The minimum and maximum age was reported 15 and 45 years, respectively. From the result of quantile regression, respondent's current age, education level and partner's higher education level were found positive impact on age of the mother at first birth. However, rural area, partner's age and smoking status found negative impact on age of the mother at first birth. This study suggests that women's education should be more prioritized because it can interfere with the idea of early marriage. Awareness can also be raised by social activities since the improvement of social conditions and reduction of social deprivation can increase the age of mother at first birth.

Mental Health of Physicians During COVID-19 Outbreak in Bangladesh: A Web-Based Cross-Sectional Survey

There have been numerous studies about the health implication of COVID-19 on patients, but little attention has been paid to the impacts of the pandemic on physicians. Our paper attends to this gap by exploring the mental health of physicians in Bangladesh during the COVID-19 pandemic. This is particularly important since the mental health of physicians impacts not only on themselves, but also their professional performance and hence the care of patients. This study examined physicians' mental health outcomes by evaluating the prevalence and associated potential risk factors of anxiety and depression. Using a web-based cross-sectional survey, we collected data from 114 physicians. Seven-item Generalized Anxiety Disorder (GAD-7) scale and Nine-item Patient Health Questionnaire (PHQ-9) were used to measure the anxiety and depression, respectively. Multivariate logistic regression models were used to explore the potential risk factors related to anxiety and depression. The prevalence of anxiety and depression were 32.5 and 34.2%, respectively. Findings revealed that marital status, work per day and current job location were the main risk factors for anxiety while sex, age, and marital status were the main risk factors for depression. Our results highlight the need to implement policies and strategies for positively impacting the mental health of physicians during and after the COVID-19 pandemic.

Prevalence of unintended pregnancy and its associated factors: Evidence from six south Asian countries

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.

Prevalence of Diabetes Mellitus and Its Associated Factors in Bangladesh: Application of Two-level Logistic Regression Model

This study intends to explore the prevalence of diabetes mellitus (DM) and its associated factors in Bangladesh. The necessary information was extracted from Bangladesh Demographic and Health Survey (BDHS) 2011. In bivariate analysis, Chi-square test was performed to assess the association between selected covariates and diabetes status. A two-level logistic regression model with a random intercept at each of the individual and regional level was considered to identify the risk factors of DM. A total of 7,535 individuals were included in this study. From the univariate analysis, the prevalence of DM was found to be 33.3% in 50-54 age group for instance. In bivariate setup, all the selected covariates except sex of the participants were found significant for DM (p < 0.05). According to the two-level logistic regression model, the chance of occurring DM increases as age of the participants' increases. It was observed that female participants were more likely to have DM. The occurrence of DM was 62% higher for higher educated participants, 42% higher for the individuals who came from rich family and 63% higher for the individuals having hypertension. The chance of developing diabetes among overweighed people was almost double. However, the individuals engaged in physical work had less chance to have DM. This study calls for greater attention of government and other concerned entities to come up with appropriate policy interventions to lower the risk of DM.

Factors Associated with Cultivation of Tobacco in Bangladesh: A Multilevel Modelling Approach

An increasing number of studies provide evidence on the serious negative consequences of tobacco farming on economic livelihoods, human health and the environment. There is, however, only limited research on tobacco farming in Bangladesh, a significant producer of tobacco leaf. It is not yet well understood why many farmers choose to grow tobacco considering the challenging context. Accordingly, this study examines the factors that influence farmers' decisions to grow tobacco in Bangladesh. Socio-demographic and economic information was collected from 220 tobacco farmers and 117 non-tobacco farmers from the major tobacco-growing district of Kushtia, for a total sample of 337. These farmers were recruited from two sub-districts (or upazilla- Daulatpur and Mirpur) using a stratified random sampling. A two-level logistic regression model was applied for the identification of the variables that condition farmers' decisions to cultivate tobacco leaf. Almost two-thirds of the sampled farmers (65.3%) chose to farm tobacco. The results demonstrate that the following variables shape most farmers' decisions to cultivate tobacco: older age, less education, tobacco firms' short-term financial support of growing tobacco, greater ease of selling tobacco products at market, better access to credit (also provided by the tobacco companies), and farmer's perception about higher profits from tobacco cultivation compared to other crops. This study strongly suggests that the government and others working on tobacco control should consider engaging in initiatives to increase farmers' education, perhaps particularly for older farmers, and provide meaningful financial support in part by helping to increase access to credit and ensuring a better market facility to sell their other healthier agricultural crops, goods and services.

Machine learning algorithms for predicting malnutrition among under-five children in Bangladesh

OBJECTIVE

The aim of this study was is to predict malnutrition status in under-five children in Bangladesh by using various machine learning (ML) algorithms.

METHODS

For analysis purposes, the nationally representative secondary records from the 2014 Bangladesh Demographic and Health Survey (BDHS) were used. Five well-known ML algorithms such as linear discriminant analysis (LDA), k-nearest neighbors (k-NN), support vector machines (SVM), random forest (RF), and logistic regression (LR) have been considered to accurately predict malnutrition status among children. Additionally, a systematic assessment of the algorithms was performed by using accuracy, sensitivity, specificity, and Cohen's κ statistic.

RESULTS

Based on various performance parameters, the best results were accomplished with the RF algorithm, which demonstrated an accuracy of 68.51%, a sensitivity of 94.66%, and a specificity of 69.76%. Additionally, a most extreme discriminative ability appeared by RF classification (Cohen's κ = 0.2434).

CONCLUSION

On the basis of the findings, we can presume that the RF algorithm was moderately superior to any other ML algorithms used in this study to predict malnutrition status among under-five children in Bangladesh. Finally, the present research recommends applying RF classification with RF feature selection when the prediction of malnutrition is the core interest.

Successful Multi-vessel Percutaneous Coronary Intervention for Recent Myocardial Infarction in a Patient with Dextrocardia and Situs Inversus

Dextrocardia with situs inversus is a state which is characterized by abnormal positioning of the heart and other internal organs. It is a rare congenital anomaly and the exact cause is not known. More than 60 recognized genes are significant for the proper positioning and patterning of the organs in the body. However, a specific genetic cause of dextrocardia with situs inversus has not been identified and inheritance prototypes have not been established in the majority cases. There are partial available case reports of successful percutaneous coronary intervention (PCI) in these patients who have atherosclerotic coronary artery disease, especially when presenting with myocardial infarction. PCI is technically difficult because of dextrocardia. We hereby describe a 51-year-old male, who had a recent inferior wall myocardial infarction and underwent successful coronary angiography and PCI at a tertiary level hospital in Dhaka, Bangladesh.

Crane Principle in Plastic Surgery- Experience in Mymensingh Medical College Hospital

The crane principle is a Plastic surgical technique whereby, a pedicled flap can be used as an engineering crane to lift and transport subcutaneous tissue from one area and deposit it in another. The flap can be returned later to its original bed. It takes only one week for the conveyance. Here we present a case of 25 year old female patient with degloving injury of scalp with exposed skull bone was initially managed with transposition flap for coverage of the scalp defect in Mymensingh Medical College Hospital (MMCH), Mymensingh, Bangladesh on 07 December 2017. After 8 months the scalp flap was returned to its original site following the crane principle and the new wound was covered by split-thickness skin graft. The flap survived completely and patient was satisfied.

Influence of the Interval between Antenatal Corticosteroid Therapy and Delivery on the Incidence of Respiratory Distress Syndrome in Neonate

In spite of the recommendation for rescue antenatal corticosteroids (ACS), the optimal time interval between primary and rescue courses has not been clearly demonstrated. The aim of this retrospective study was to determine the effects of the interval between a single ACS (Dexamethasone) course and delivery on the incidence of respiratory distress syndrome (RDS) in neonates at Mymensingh Medical College Hospital Center from 1st January 2017 to 30th June 2017. Injection Dexamethasone 2 doses (12.5mg IM 12 hourly for 2 doses) or 4 doses (6mg IM every 12 hours for 4 doses) use to arrest preterm labor as well as to prevent RDS delivered beyond 48 hours after ACS administration between 24 and 34 weeks gestation. The risk of RDS was compared between patients who delivered within seven days (Group I) and 7-14 days (Group II) after ACS administration. We included 140 and 60 patients in Group I and Group II respectively. After adjusting for confounders, the ACS delivery interval was significantly associated with RDS in Group II (adjusted odds ratio 12.8, 95% confidence interval 1.31-164.7). A longer ACS delivery interval is associated with a higher risk of RDS. Thus, the use of a rescue course could be expected to reduce the incidence of RDS in patients beyond seven days after ACS administration who remain at risk for preterm delivery within seven days, especially in cases of placenta previa and/or women bearing a male fetus.

Posterior Tibial Artery Perforator Based Propeller Flap for Lower Leg and Ankle Defect Coverage: A Prospective Observational Study

Reconstruction of lower leg and ankle defect with exposed bone or tendon is a challenging task for a Plastic Surgeon. There are various options, among them perforator based propeller flap is a very good option though this is a microsurgical procedure but no need of microvascular anastomosis. This study was designed to see the clinical results of Posterior tibial artery perforator based propeller flap for lower leg and ankle defect coverage. The study was a prospective observational study. It was conducted in the Department of Burn and Plastic Surgery, Mymensingh Medical College Hospital, Mymensingh, Bangladesh from July 2017 to June 2018. Sample size was 9. Sampling was carried out purposively. Postoperative follow up period was up to 6 weeks. Among the 9 cases, 8 flaps completely survived, 1 case developed marginal necrosis which was secondarily healed. There were total 2 complications among 9 cases i.e. transient venous congestion and superficial epidermonecrolysis which were resolved spontaneously. Regarding the cause of the defect, maximum cases were post traumatic wound (66.7%), others were post infective, post malignancy excision and post electric burn wound. Defect size was 2cm×2cm to 7cm×5cm. Maximum dimension of the flap was 19cm×6cm and minimum size was 7cm×3cm. Posterior tibial artery perforator location was 4cm to 9cm from lowest level of medial malleolous (mean 6.2±1.6cm). Rotation of the flap was 145°-180° (mean 163°±1.39°). In all cases donor site was covered with split thickness skin graft. Operation time was 120 minutes to 180 minutes; mean operative time was 143.3±2.38 minutes. After operation hospital stay was 10 days to 21 days, mean 11.44±3.64 days. So, posterior tibial artery perforator based propeller flap for lower leg and ankle defect coverage is a very good option.

Exploring Association Between Individuals' Stature and Type 2 Diabetes Status: Propensity Score Analysis

In this article, relationship between respondents' height and occurrence of diabetes has been investigated. This study uses Bangladesh Demographic and Health Survey (BDHS) 2011 data collected from an observational study. Considering height (tall/normal/short) based on percentiles separately for men and women, logistic regression model was fitted to the propensity score (PS)-adjusted weighted data. No significant relationship between respondents' height and diabetes was observed. We also found that the occurrence of diabetes significantly varies with respect to sex, education level, wealth index, body mass index (BMI), and region/division. As, in general, women are shorter than men by nature, we strongly argue that height categories should be defined separately whenever estimation of the effect of height on some response is of interest.

Fetomaternal Outcome in Eclampsia in Relationship with Gravidity

Eclampsia is a well-recognized major cause of maternal and perinatal morbidity and mortality. Patient's age, occupational status, socioeconomic status, educational status, regular ANC (antenatal care) and gravidity may affect the outcome of mother and foetus. The purpose of this study is to see the fetomaternal outcome in eclampsia in relationship with gravidity. This prospective observational cross-sectional study carried out among the alternate cases of primigravid and multigravid eclamptic patients. Total number of patients was 100 eclamptic patients among them, 50 patients were primigravida and 50 patients were multigravida. The study was conducted in Eclampsia unit of Department of Gynaecology and Obstetrics, Dhaka Medical College Hospital, Dhaka, Bangladesh from 21 November 2011 to 20 May 2012. In this study, it was observed that ARF (acute renal failure) occurred in 6%, of these 4 cases of multigravida and 2 cases of primigravida. Cerebro vascular accident (CVA) was reported in 16 patients and 26% in multigravida and 6% in primigravid patients. HELLP (Haemolysis, Elevated liver enzymes and low platelets) syndrome developed in 25 cases of multigravida and 6 cases of primigravida. Heart failure occurred in 7% cases, out of these 6 cases were multigravida and 1 case was primigravida. Pulmonary edema was observed in 41%, among were 21 cases of multigravida and 20 cases of primigravida. Incidence of DIC (disseminated intravascular coagulation) was noted in 2 cases of multigravida and 1 case of primigravida. PPH (postpartum haemorrhage) occurred in 10 cases of multigravida and 3 cases of primigravid patients. Puerperal psychosis was reported in 8% of multigravida and 4% of primigravida. Total 4% of patients expired, among them 3 cases were multigravida and 1 case was primigravida. Perinatal mortality was 21 cases in multigravida and 8 cases in primigravida. The incidence of live birth, in case of multigravida was 39 cases and primigravida 45 cases. Data were analyzed by paired student's 't' test. There was no statistically significant difference between primi and multigravida in feto-maternal outcome. This study reveals that gravidity does not alter the feto-maternal outcome in eclampsia.

Household food insecurity and dietary diversity as correlates of maternal and child undernutrition in rural Cambodia

OBJECTIVES

To assess household food insecurity and dietary diversity as correlates of maternal and child anthropometric status and anemia in rural Cambodia.

METHODS

Trained interviewers administered a survey to 900 households in four rural districts of Prey Veng, Cambodia. The Household Food Insecurity Access Scale (HFIAS) and Household Dietary Diversity Score (HDDS) were used to assess household food insecurity and dietary diversity. The height, weight and hemoglobin concentration of the mother and youngest child under 5 years in each household were measured. Multivariate logistic regression models were constructed to assess the association between household food insecurity and dietary diversity, and child stunting and wasting, maternal thinness, maternal and child anemia.

RESULTS

The mean (s.d.) HFIAS and HDDS scores were 5.3 (3.9) and 4.7 (1.6), respectively. The respective prevalences of mild, moderate and severe food insecurity were 33, 37 and 12%. Maternal thinness, child stunting and child wasting were present in 14.6, 25.4 and 8.1% of respondents, respectively. The risk of maternal thinness, but not child stunting or wasting, increased as the severity of household food insecurity increased. Household food insecurity was also positively associated with maternal, but not child, anemia. Household dietary diversity status was not significantly associated with any of the outcomes we assessed.

CONCLUSIONS

Efforts to improve household food security are important as a means of promoting maternal nutritional status; however, additional research is needed to better understand the role of other factors that are driving the burden of child undernutrition in Cambodia.

Mapping the mesoscale interface structure in polycrystalline materials

A new experimental approach to the quantitative characterization of polycrystalline microstructure by scanning electron microscopy is described. Combining automated electron backscattering diffraction with conventional scanning contrast imaging and with calibrated serial sectioning, the new method (mesoscale interface mapping system) recovers precision estimates of the 3D idealized aggregate function G(x). This function embodies a description of lattice phase and orientation (limiting resolution approximately 1 degree) at each point x (limiting spatial resolution approximately 100 nm), and, therefore, contains a complete mesoscale description of the interfacial network. The principal challenges of the method, achieving precise spatial registry between adjacent images and adequate distortion correction, are described. A description algorithm for control of the various components of the system is also provided.

A closed-form neural network for discriminatory feature extraction from high-dimensional data

We consider a new neural network for data discrimination in pattern recognition applications. We refer to this as a maximum discriminating feature (MDF) neural network. Its weights are obtained in closed-form, thereby overcoming problems associated with other nonlinear neural networks. It uses neuron activation functions that are dynamically chosen based on the application. It is theoretically shown to provide nonlinear transforms of the input data that are more general than those provided by other nonlinear multilayer perceptron neural network and support-vector machine techniques for cases involving high-dimensional (image) inputs where training data are limited and the classes are not linearly separable. We experimentally verify this on synthetic examples.

Serine phosphorylation of paxillin by heregulin-beta1: role of p38 mitogen activated protein kinase

The mechanisms through which heregulin (HRG) regulates the progression of breast cancer cells to a more invasive phenotype are currently unknown. Recently we have shown that HRG treatment of breast cancer cells leads to the formation of lamellipodia/filopodia, and increased cell migration and invasiveness through the phosphatidylinositol 3-kinase (PI-3 kinase). Since the process of cell migration must involve changes in adhesion, we explored the potential HRG regulation of paxillin, a major cytoskeletal phosphoprotein of focal adhesion. We report that HRG stimulation of non-invasive breast cancer cells resulted in stimulation of p38 mitogen-activated protein kinase (p38MAPK), extracellular signal-regulated kinases (ERK) and PI-3K, and a concurrent unexpected increase in the level of paxillin phosphorylation on serine residue which was sensitive to protein-phosphatase 2b but not to protein tyrosine phosphatase 1. In addition, HRG triggered a rapid redistribution of paxillin to the perinuclear regions from the tyrosine-phosphorylated focal adhesions, and increased cell scattering. There was no effect of HRG on the state of phosphorylation and localization of focal adhesion kinase. The HRG-induced increase in serine phosphorylation of paxillin and cell scattering were selectively inhibited by a specific inhibitor of p38MAPK or a dominant-negative p38MAPK mutant, but not by inhibitors of p42/44MAPK or PI-3 kinase pathways. For the first time our results have shown that HRG, a potent migratory growth factor stimulates serine phosphorylation of paxillin. These findings suggest a role of p38MAPK-dependent signal transduction pathway(s) in serine phosphorylation and disassembly of the paxillin from the focal complexes during HRG-induced cell shape alterations and motility.

Dengue Fever as A Cause of Acute Disseminated Encephalomyelitis (ADEM)

Dengue fever is very common in Bangladesh. Every year a large number of urban populations suffer from this viral infection. Various presentations of dengue fever have been documented. Neurological complications in dengue fever are relatively uncommon. Among these, Acute Disseminated Encephalomyelitis (ADEM) has been observed in very few cases. Here we present a case of 13 year old girl suffering from ADEM following dengue fever. Keyword: Acute Disseminated Encephalomyelitis, Dengue fever, Neurological complication.DOI: http://dx.doi.org/10.3329/jom.v12i2.8428 JOM 2011; 12(2): 185-187