Double and triple burden of non‐communicable diseases and its determinants among adults in Bangladesh: Evidence from a recent demographic and health survey
Abstract:Non-communicable diseases (NCDs) including cardiovascular diseases, cancer, chronic respiratory diseases, and diabetes are the primary and leading causes of death and disability globally. 1,2 One of the most critical targets of sustainable development goals is reducing the burden of NCDs. 3 NCDs accounted for 41 million deaths worldwide with around 34.85 million deaths in low-and middle-income countries (LMICs). 4 However, this is projected to increase from 38 to 52 million deaths between 2012 and 2030. 5 The … Show more
“…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 ].…”
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.
“…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 ].…”
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.
“…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 ].…”
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.
“…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.…”
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.
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