Prevalence, trends and associated factors of hypertension and diabetes mellitus in Bangladesh: Evidence from BHDS 2011 and 2017–18

The burden of diabetes and hypertension on healthy life expectancy in Bangladesh

Diabetes and hypertension are among the leading causes of death in Bangladesh. This study examined hypertension, diabetes, and either or both, free life expectancy, to measure the effect of the diseases on the overall health of individuals in Bangladesh with regional variations. We utilized data from Bangladesh Sample Vital Statistics 2018 for mortality and Bangladesh Demographic and Health Survey 2017-2018 for diabetes and hypertension. The Sullivan method was employed to estimate age-specific hypertension and diabetes-free life expectancy. Altogether, 10.3% of the people aged 18-19 years lived with either diabetes or hypertension. The hypertension-free life expectancy was 40.4 years, and the diabetes-free life expectancy was 53.2 years for those aged 15-19. Overall, individuals would expect to spend 38.7% of their lives with either of the diseases. Females suffered more from hypertension and males from diabetes. Still, females suffered more from the aggregate of both. Rural people had more diabetes and hypertension-free life expectancy than those of urban. Individuals of Mymensingh had the highest life expectancy free of both diseases compared to other divisions of Bangladesh. Diabetes and hypertension affect a considerable proportion of the life of the population in Bangladesh. Policy actions are needed to guide the prevention, diagnosis, and treatment of both diseases, specifically focusing on women and urban populations. Widespread health-enhancing actions need to be taken to diminish the effect of these two diseases in Bangladesh.

Mediating effect of BMI on the association of economic status and coexistence of hypertension and diabetes in Bangladesh: A counterfactual framework-based weighting approach

Background and Aims

Non-communicable diseases such as hypertension and diabetes are matters of huge concern worldwide, with an increasing trend in prevalence over the previous decade. First of all, this study aimed to evaluate the association between economic status (ES) and body mass index (BMI), ES and comorbidity of hypertension and diabetes, and BMI and comorbidity independently. Second, it explored the mediating role of BMI in the association between ES and comorbidity of hypertension and diabetes. Finally, it investigated whether the mediating effect differs with the place of residence, gender, and education levels.

Methods

A total of 11,291 complete cases from the Bangladesh demographic and health survey 2017-18 were utilized for this study. Survey-based binary logistic regression or multiple logistic regression was used to find the association among outcome, exposure, and mediator variables, and a counterfactual framework-based weighting approach was utilized for mediation analysis.

Results

Middle-income (adjusted odds ratio [AOR]: 1.696, 95% confidence interval [CI]: 1.219, 2.360) and rich (AOR: 2.770, CI: 2.054, 3.736) respondents were more likely to have comorbidity of hypertension and diabetes compared to the poor. The odds of comorbidity increased with the increase in BMI. A positive association was observed between ES and BMI. A significant mediating role of BMI in the association between ES and comorbidity was found. We observed that 19.85% (95% CI: 11.50%, 49.6%) and 20.35% (95% CI: 14.9%, 29.3%) of total effect was mediated by BMI for middle and rich respondents, respectively, compared to the poor.

Conclusions

The mediating role of BMI was greater for female, no or primary educated respondents, and respondents from rural areas. Therefore, the study will facilitate policymakers of Bangladesh and other countries with a similar set-up to decide on health policies regarding hypertension and diabetes.

Prevalence, Awareness, Treatment, and Control of Hypertension Among Older Adults in the Philippines

BACKGROUND

Little is known about the current prevalence and management of hypertension among older Filipinos. To address this gap, we examined the prevalence, awareness, treatment, and control of hypertension, as well as their correlates, among older Filipinos.

METHODS

We analyzed a nationally representative survey of Filipinos aged 60 years and older (N = 5 985) in the Philippines. Blood pressure (BP) measurements were taken using a digital BP apparatus. People with hypertension included those with a systolic BP ≥ 140 mmHg or a diastolic BP ≥ 90 mmHg, or those who reported current use of antihypertensive medication. People with undiagnosed hypertension were those who had measured hypertension but had not been diagnosed by a doctor as having hypertension, while people with untreated hypertension were those who had measured hypertension but not taking medication. Among those who were taking antihypertensive medication, respondents with measured hypertension were considered to have uncontrolled BP.

RESULTS

Results showed that 69.1% of older Filipinos had hypertension, but only 61.6% of people with hypertension were aware of their hypertension and 51.5% were untreated. Sociodemographic factors, such as age, sex, education, and living arrangements, were significantly associated with hypertension prevalence, hypertension awareness, lack of treatment for hypertension, and/or suboptimal BP control.

CONCLUSION

We observed a high prevalence of hypertension among older Filipinos and a relatively low level of awareness and treatment of hypertension among them. While there are government efforts to address the growing prevalence of hypertension in the country, more efforts should be made to bring these government programs to older Filipinos.

A quantile regression approach to identify risk factors for high blood glucose levels among Bangladeshi individuals

Background and Aims

Diabetes mellitus, characterized by high blood glucose, is an overwhelming public health concern globally, including in Bangladesh. The implication of this trend may pose a significant challenge to the health systems due to the lack of awareness and improper management of this chronic disease. To formulate strategies for public health planning, this study aims to explore the potential risk factors for elevated blood glucose levels among Bangladeshi individuals using advanced statistical methods and a nationally representative data set.

Methods

This study utilized data from the 2017-18 Bangladesh Demographic and Health Survey and included 11,863 individuals. A nonparametric Kruskal-Wallis test assessed the significant association between fasting plasma glucose levels and various risk factors. Additionally, a robust quantile regression model was applied to examine the net effects of each risk factor at different quantiles of the distribution.

Results

The prevalence of diabetes is 8.1% among individuals in the study population, with variations observed across different administrative divisions in the country. Respondents from the Dhaka division respondents had a higher likelihood (24.1%) of having elevated plasma glucose and the Rangpur division had a lower risk (10.3%) of developing diabetes disease. This study identified several potential risk factors associated with elevated blood glucose levels, including hypertensive disease, overweight and obese body mass index, higher economic status, reduced physical activities, and older age, significantly contributing to develop diabetes mellitus.

Conclusion

This study recommends promoting healthy lifestyles, increased physical activity, effective hypertension management, obesity reduction, and nationwide screening programs to control diabetes and noncommunicable diseases in Bangladesh. These preventive measures are crucial for reducing the existing prevalence of diabetes and working toward achieving the Sustainable Development Goals by 2030.

The burden of diseases and risk factors in Bangladesh, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019

BACKGROUND

Bangladesh has made substantial progress in improving socioeconomic and health indicators over the past 50 years, but data on national disease burden are scarce. We used data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to estimate the burden of diseases and risk factors in Bangladesh from 1990 to 2019.

METHODS

For this systematic analysis, we analysed data from vital registration systems, surveys, and censuses using multistage modelling processes to estimate life expectancy at birth, mortality rate, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs). Additionally, we compared the health status of Bangladesh with that of the other countries in the GBD south Asia region-Bhutan, India, Nepal, and Pakistan.

FINDINGS

Life expectancy at birth in Bangladesh increased from 58·2 years (95% uncertainty interval 57·1-59·2) in 1990 to 74·6 years (72·4-76·7) in 2019. Between 1990 and 2019, the age-standardised mortality rate decreased from 1509·3 (1428·6-1592·1) to 714·4 (604·9-838·2) deaths per 100 000 population. In 2019, non-communicable diseases represented 14 of the top 20 causes of death; the leading three causes were stroke, ischaemic heart disease, and chronic obstructive pulmonary disease. High blood pressure, high fasting plasma glucose, and smoking were the top three risk factors. From 1990 to 2019, the rate of all-cause DALYs decreased by 54·9% (48·8-60·4). In 2019, the leading causes of DALYs and YLLs were neonatal disorders, stroke, and ischaemic heart disease, whereas musculoskeletal disorders, depressive disorders, and low back pain were the leading causes of YLDs. Bangladesh has the lowest age-standardised rates of mortality, YLDs, and YLLs and the highest life expectancy at birth in south Asia.

INTERPRETATION

Over the past 30 years, mortality rates have reduced by more than half in Bangladesh. Bangladesh must now address the double burden of communicable and non-communicable diseases. Cost-effective, multisectoral efforts are needed to prevent and control non-communicable diseases, promote healthy lifestyles, and prevent premature mortality and disabilities.

FUNDING

Bill & Melinda Gates Foundation.

TRANSLATION

For the Bangla translation of the abstract see Supplementary Materials section.

Enhancing care quality and accessibility through digital technology-supported decentralisation of hypertension and diabetes management: a proof-of-concept study in rural Bangladesh

OBJECTIVE

The critical shortage of healthcare workers, particularly in rural areas, is a major barrier to quality care for non-communicable diseases (NCD) in low-income and middle-income countries. In this proof-of-concept study, we aimed to test a decentralised model for integrated diabetes and hypertension management in rural Bangladesh to improve accessibility and quality of care.

DESIGN AND SETTING

The study is a single-cohort proof-of-concept study. The key interventions comprised shifting screening, routine monitoring and dispensing of medication refills from a doctor-managed subdistrict NCD clinic to non-physician health worker-managed village-level community clinics; a digital care coordination platform was developed for electronic health records, point-of-care support, referral and routine patient follow-up. The study was conducted in the Parbatipur subdistrict, Rangpur Division, Bangladesh.

PARTICIPANTS

A total of 624 participants were enrolled in the study (mean (SD) age, 59.5 (12.0); 65.1% female).

OUTCOMES

Changes in blood pressure and blood glucose control, patient retention and patient-visit volume at the NCD clinic and community clinics.

RESULTS

The proportion of patients with uncontrolled blood pressure reduced from 60% at baseline to 26% at the third month of follow-up, a 56% (incidence rate ratio 0.44; 95% CI 0.33 to 0.57) reduction after adjustment for covariates. The proportion of patients with uncontrolled blood glucose decreased from 74% to 43% at the third month of follow-up. Attrition rates immediately after baseline and during the entire study period were 29.1% and 36.2%, respectively.

CONCLUSION

The proof-of-concept study highlights the potential for involving lower-level primary care facilities and non-physician health workers to rapidly expand much-needed services to patients with hypertension and diabetes in Bangladesh and in similar global settings. Further investigations are needed to evaluate the effectiveness of decentralised hypertension and diabetes care.

Prevalence and determinants of non-communicable diseases risk factors among reproductive-aged women: Findings from a nationwide survey in Bangladesh

INTRODUCTION

Knowing the risk factors like smoking status, overweight/obesity, and hypertension among women of reproductive age could allow the development of an effective strategy for reducing the burden of non-noncommunicable diseases. We sought to determine the prevalence and determinants of smoking status, overweight/obesity, hypertension, and cluster of these non-noncommunicable diseases risk factors among Bangladeshi women of reproductive age.

METHODS

This study utilized the Bangladesh Demographic and Health Survey (BDHS) data from 2017-2018 and analyzed 5,624 women of reproductive age (age 18-49 years). This nationally representative cross-sectional survey utilized a stratified, two-stage sample of households. Poisson regression models with robust error variance were fitted to find the adjusted prevalence ratio (APR) for smoking, overweight/obesity, hypertension, and for the clustering of non-noncommunicable diseases risk factors across demographic variables.

RESULTS

The average age of 5,624 participants was 31 years (SD = 9.1). The prevalence of smoking, overweight/obesity, and hypertension was 9.6%, 31.6%, and 20.3%, respectively. More than one-third of the participants (34.6%) had one non-noncommunicable diseases risk factor, and 12.5% of participants had two non-noncommunicable diseases risk factors. Age, education, wealth index, and geographic location were significantly associated with smoking status, overweight/obesity, and hypertension. Women between 40-49 years had more non-noncommunicable diseases risk factors than 18-29 years aged women (APR: 2.44; 95% CI: 2.22-2.68). Women with no education (APR: 1.15; 95% CI: 1.00-1.33), married (APR: 2.32; 95% CI: 1.78-3.04), and widowed/divorced (APR: 2.14; 95% CI: 1.59-2.89) were more likely to experience multiple non-noncommunicable diseases risk factors. Individuals in the Barishal division, a coastal region (APR: 1.44; 95% CI: 1.28-1.63) were living with a higher number of risk factors for non-noncommunicable diseases than those in the Dhaka division, the capital of the country. Women who belonged to the richest wealth quintile (APR: 1.82; 95% CI: 1.60-2.07) were more likely to have the risk factors of non-noncommunicable diseases.

CONCLUSIONS

The study showed that non-noncommunicable diseases risk factors are more prevalent among women from older age group, currently married and widowed/divorced group, and the wealthiest socio-economic group. Women with higher levels of education were more likely to engage in healthy behaviors and found to have less non-noncommunicable diseases risk factors. Overall, the prevalence and determinants of non-noncommunicable diseases risk factors among reproductive women in Bangladesh highlight the need for targeted public health interventions to increase opportunities for physical activity and reduce the use of tobacco, especially the need for immediate interventions in the coastal region.

Impact of Lockdown Measures on Health Outcomes of Adults with Type 2 Diabetes Mellitus in Bangladesh

COVID-19 lockdown measures appreciably affected patients' lifestyles, negatively impacting on their health. This includes patients with Type 2 Diabetes Mellitus (T2DM). Care of these patients was also negatively impacted due to a priority to treat patients with COVID-19, certainly initially, within hospitals and clinics in Bangladesh, combined with a lack of access to clinics and physicians due to lockdown and other measures. This is a concern in Bangladesh with growing rates of T2DM and subsequent complications. Consequently, we sought to critically analyze the situation among patients with T2DM in Bangladesh during the initial stages of the pandemic to address this information gap and provide future direction. Overall, 731 patients were recruited by a simple random sampling method among patients attending hospitals in Bangladesh, with data collected over 3 timescales: before lockdown, during the pandemic, and after lockdown. Data extracted from patients' notes included current prescribed medicines and key parameters, including blood sugar levels, blood pressure, and comorbidities. In addition, the extent of record keeping. The glycemic status of patients deteriorated during lockdown, and comorbidities as well as complications related to T2DM increased during this period. Overall, a significant proportion of key datasets were not recorded in patients' notes by their physician before and during lockdown. This started to change after lockdown measures eased. In conclusion, lockdown measures critically affected the management of patients with T2DM in Bangladesh, building on previous concerns. Extending internet coverage for telemedicine, introduction of structured guidelines, and appreciably increasing data recording during consultations is of the utmost priority to improve the care of T2DM patients in Bangladesh.

Analytical quality by design-based RP-HPLC method for quantification of pioglitazone and candesartan cilexetil in bilayer tablet and its forced degradation studies

Aim: The current project involves developing an RP-HPLC method for simultaneous quantification of Candesartan Cilexetil and Pioglitazone based on analytical quality by design (AQbD).

Materials and methods: When analysed in the Design Expert application, the critical method parameters were systematically refined using Central Composite Design and contours were derived for significant variables. A contour plot has been used to discover the technique operable design region that governs response variation, which is then empirically tested.

Results: Successful chromatographic separation of title analytes was achieved on kromasil C18 (150 × 4.6 mm, 5 µm) column at 30 °C with mobile phase comprising 60% 20 Mm Potassium dihydrogen orthophosphate and 40% acetonitrile (v/v), isocratic elution pattern, 0.9 mL/min flow rate, and UV detection at 220 nm. The linear model for Candesartan Cilexetil was from 4 to 24 µg/ mL and Pioglitazone at 7.5–45 µg/ mL, respectively.

Conclusion: The method met all the ICH Q2 (R1) validation criteria. The current approach aided for analysing simultaneous drugs can be expanded into quantifying drugs in biological matrix predominance with maximum recovery.

Early Prediction of Diabetes Using an Ensemble of Machine Learning Models

Diabetes is one of the most rapidly spreading diseases in the world, resulting in an array of significant complications, including cardiovascular disease, kidney failure, diabetic retinopathy, and neuropathy, among others, which contribute to an increase in morbidity and mortality rate. If diabetes is diagnosed at an early stage, its severity and underlying risk factors can be significantly reduced. However, there is a shortage of labeled data and the occurrence of outliers or data missingness in clinical datasets that are reliable and effective for diabetes prediction, making it a challenging endeavor. Therefore, we introduce a newly labeled diabetes dataset from a South Asian nation (Bangladesh). In addition, we suggest an automated classification pipeline that includes a weighted ensemble of machine learning (ML) classifiers: Naive Bayes (NB), Random Forest (RF), Decision Tree (DT), XGBoost (XGB), and LightGBM (LGB). Grid search hyperparameter optimization is employed to tune the critical hyperparameters of these ML models. Furthermore, missing value imputation, feature selection, and K-fold cross-validation are included in the framework design. A statistical analysis of variance (ANOVA) test reveals that the performance of diabetes prediction significantly improves when the proposed weighted ensemble (DT + RF + XGB + LGB) is executed with the introduced preprocessing, with the highest accuracy of 0.735 and an area under the ROC curve (AUC) of 0.832. In conjunction with the suggested ensemble model, our statistical imputation and RF-based feature selection techniques produced the best results for early diabetes prediction. Moreover, the presented new dataset will contribute to developing and implementing robust ML models for diabetes prediction utilizing population-level data.