Double and triple burden of non‐communicable diseases and its determinants among adults in Bangladesh: Evidence from a recent demographic and health survey

Al-Zubayer, Md Akib; Ahammed, Benojir; Sarder, Alamgir; Kundu, Subarna; Majumder, Uttam; Islam, Sheikh Mohammed Shariful

doi:10.1111/ijcp.14613

Cited by 18 publications

(20 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In recent years, the prevalence of T2D and hypertension has grown rapidly and is expected to increase the prevalence of CKD at an epidemic rate in South Asia [ 8 , 15 , 16 ]. Moreover, CKD causes an increased risk of myocardial infarction, stroke, and cardiovascular-related mortality in patients with T2D in comparison with non-diabetic patients [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

Factors Associated with Chronic Kidney Disease in Patients with Type 2 Diabetes in Bangladesh

Islam

Salehin

Zaman

et al. 2021

IJERPH

Self Cite

View full text Add to dashboard Cite

Diabetes and chronic kidney disease (CKD) are a major public health burden in low- and middle-income countries. This study aimed to explore factors associated with CKD in patients with type 2 diabetes (T2D) in Bangladesh. A cross-sectional study was conducted among 315 adults with T2D presenting at the outpatient department of Bangladesh Institute of Health Sciences (BIHS) hospital between July 2013 to December 2013. CKD was diagnosed based on the estimated glomerular filtration rate using the ‘Modification of Diet in Renal Disease’ equations and the presence of albuminuria estimated by the albumin-to-creatinine ratio. Multivariate logistic regression analysis was used to determine the factors associated with CKD. The overall prevalence of CKD among patients with T2D was 21.3%. In the unadjusted model, factors associated with CKD included age 40–49 years (OR: 5.7, 95% CI: 1.3–25.4), age 50–59 years (7.0, 1.6–39), age ≥60 years (7.6, 1.7–34), being female (2.2, 1.2–3.8), being hypertensive (1.9, 1.1–3.5), and household income between 10,001 and 20,000 Bangladeshi taka, BDT (2.9, 1.0–8.2) compared with income ≤10,000 BDT. However, after adjustment of other covariates, only the duration of hypertension and household income (10,001–20,000 BDT) remained statistically significant. There is a need to implement policies and programs for early detection and management of hypertension and CKD in T2D patients in Bangladesh.

show abstract

Section: Introductionmentioning

confidence: 99%

Factors Associated with Chronic Kidney Disease in Patients with Type 2 Diabetes in Bangladesh

Islam

Salehin

Zaman

et al. 2021

IJERPH

Self Cite

View full text Add to dashboard Cite

show abstract

“…It may also result in the adoption of Western lifestyles, resulting in a nutritional shift toward unhealthy food choices, such as increased intake of "fast foods" high in sugar and fat, both of which are known risk factors for overweight/obesity [ 58 ]. While overweight and obesity are risk factors for hypertension and diabetes [ 4 , 5 , 31 , 59 , 60 ]. However, due to increased access to health information and resources, there may be reduced burdens associated with behavioral and metabolic risk factors for NCDs among advantaged individuals [ 15 ].…”

Section: Discussionmentioning

confidence: 99%

“…Despite strong associations between predictors and burden of NCDs (hypertension and diabetes) are separate entities, and each has an independent effect on outcomes [ 34 ]. To investigate the effects, it was hypothesized that several predictors (e.g., individual demographic factors, socioeconomic factors, geographical factors, lifestyle factors and intermediary factors BMI) were associated with developing outcomes (hypertension and diabetes) aligned with previously did studies elsewhere [ 3 , 4 , 5 , 15 – 18 , 30 , 31 , 35 – 46 ,] and the combination of predictors was expected to predict people’s health outcomes (hypertension and diabetes) [ 34 ].…”

Section: Methodsmentioning

confidence: 98%

Socioeconomic inequalities in the risk factors of noncommunicable diseases (hypertension and diabetes) among Bangladeshi population: Evidence based on population level data analysis

Rahman

2022

PLoS ONE

View full text Add to dashboard Cite

Background Noncommunicable diseases (NCDs) such as hypertension and diabetes are among the most fatal disease and prevalent among the adult population worldwide, including Bangladesh, and pose a public health threat. Understanding the socioeconomic inequalities linked to NCD risk factors can aid in the development of effective strategies to reduce the disease’s recurrence. However, the literature on socioeconomic inequalities in hypertension and diabetes prevalence in Bangladesh is scant. Therefore, this study seeks to assess the inequality in hypertension and diabetes prevalence and to identify factors that may contribute to socioeconomic inequalities in Bangladesh. Methods The current study incorporated data from a recent round of Bangladesh Demographic and Health Survey (BDHS 2017–18). The age-standardized prevalence rates of hypertension and diabetes were reported, and the log-binomial regression technique was used to identify the relevant confounders. Additionally, socioeconomic inequalities were quantified using a regression-based decomposition technique in which the concentration index (CIX) and Concentration curve were produced to determine the socioeconomic factors contributing to inequality. Results Hypertension and diabetes were shown to have an age-standardized prevalence of (11.29% 95% CI: 11.13–11.69) and (36.98% 95% CI: 36.79–37.16), respectively. Both hypertension and diabetes were shown to be pointedly linked to the respondents’ age, wealth status, being overweight or obese, and a variety of respondents’ administrative divisions (p <0.001). In Bangladesh, household wealth status accounted for approximately 25.71% and 43.41% of total inequality in hypertension and diabetes, respectively. While BMI played a significant role in the emergence of inequality, the corresponding percentages for diabetes and hypertension are 4.95 and 83.38, respectively. In addition, urban areas contributed 4.56% inequality to increase diabetes among Bangladeshi inhabitants while administrative region contributed 4.76% of the inequality of hypertension. Conclusion A large proportion of Bangladesh’s adult population suffers from hypertension and diabetes. It is critical to recognize the value of equity-based initiatives in order to optimize the benefit-risk ratio and cost effectiveness of preventive health programmes. Integrating equity considerations into interventions is critical for policies and programmes to achieve their objectives. As a result, these findings can be taken into account when making existing and prospective policy decisions, as well as following its progression with economic development of Bangladesh.

show abstract

“…Comorbidity is a common problem in many people with chronic diseases such as individuals with DM commonly present with obesity, hypertension, dyslipidaemia and CVD. There are ample evidences of the association between DM and CVD [6,7]. Both CVD and DM share similar cardiometabolic, behavioral, environmental, and social risk factors.…”

Section: Introductionmentioning

confidence: 99%

Machine learning models for prediction of co-occurrence of diabetes and cardiovascular diseases: a retrospective cohort study

Abdalrada

Abawajy

Al-Quraishi

et al. 2022

J Diabetes Metab Disord

Self Cite

View full text Add to dashboard Cite

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

show abstract

Double and triple burden of non‐communicable diseases and its determinants among adults in Bangladesh: Evidence from a recent demographic and health survey

Cited by 18 publications

References 45 publications

Factors Associated with Chronic Kidney Disease in Patients with Type 2 Diabetes in Bangladesh

Factors Associated with Chronic Kidney Disease in Patients with Type 2 Diabetes in Bangladesh

Socioeconomic inequalities in the risk factors of noncommunicable diseases (hypertension and diabetes) among Bangladeshi population: Evidence based on population level data analysis

Machine learning models for prediction of co-occurrence of diabetes and cardiovascular diseases: a retrospective cohort study

Contact Info

Product

Resources

About