The disproportionate increase in the prevalence of non-communicable diseases (NCDs) has become a major public health shortcoming globally, especially in developing countries [1
]. Among NCDs, diabetes mellitus is considered one of the major global public health challenges of the twenty-first century [2
]. Globally, 285 million adults were affected by diabetes mellitus in 2010 and it is estimated that 439 million adults will be affected by 2030 [3
]. In the South-East Asian region, more than 72 million adults are living with diabetes and it is predicted that the number will exceed 123 million by 2035 [4
]. In Bangladesh, the prevalence of diabetes is 7.4%, higher among males compared to females, and is increasing over time [5
The global NCD epidemic, especially diabetes mellitus, is increasing rapidly due to several life-style related factors including unhealthy food habits, inadequate physical activity, high body mass index (BMI), and abuse of substances operated through high blood pressure, elevated blood glucose and plasma lipid levels [6
]. The shift in population age structure—an increasing proportion of the older aged population and rapid urbanization—stimulates the NCD risk [7
Life-style related behaviors, healthcare-related knowledge and accessibility are influenced by socioeconomic status (SES) and this likely drives a lack in acquiring diabetes-related awareness and a willingness to diagnose diabetes, which is important in order to control this disease among divergent people [8
]. Epidemiological studies have repeatedly confirmed the inverse association between the prevalence of diabetes and SES [10
Diabetes has multifaceted health consequences. In addition, patients may experience sudden unfortunate health hazards if it remains undiagnosed. Diabetes may lead to a serious problem in the later life of patients if it was undiagnosed for a long time. These patients are at greater risk of experiencing a stroke, coronary heart disease, dyslipidemia and peripheral vascular disease [14
]. Previous studies have estimated the prevalence and identified potential risk factors of diabetes in Bangladesh [15
]. However, limited studies have reported the prevalence of undiagnosed diabetes and associated socioeconomic inequalities in Bangladesh. Therefore, we aimed to estimate the prevalence of undiagnosed diabetes among adult diabetic patients and related socioeconomic inequalities in Bangladesh.
3.1. General Characteristics of the Study Participants
Among the patients studied, the average age was 52.7 years (95% CI 51.8, 53.6). There were almost equal numbers of males (49.0%; 95% CI 45.7%, 52.4%) and females (51.0%; 95% CI 47.6%, 54.3%) in the sample (Table 1
). However, more than one-third of the patients had no education (35.5%; 95% CI 31.4%, 39.5%). One in every four patients was overweight/obese (BMI ≥ 25 kg/m2
). Findings showed that 63% (95% CI 59.7%, 66.3%) of patients were involved in work that required light physical activity. A higher number of patients resided in a rural area than an urban area. The highest number of patients belonged to richest wealth quintile (39.1%; 95% CI 35.0%, 43.2%) and the lowest number of patients belonged to the poorest wealth quintile (12.1%; 95% CI 9.4%, 14.9%).
3.2. Prevalence of Undiagnosed Diabetes among Adult Diabetic Patients
According to our study, 938 cases were diagnosed as having diabetes with a mean FPG of 0.806 mmol/L (standard error 0.01). Among these patients, we found that 503 (53.4%) patients were undiagnosed during the survey (Table 2
). The prevalence of undiagnosed diabetes among adult diabetic patients varied across the patients’ education and BMI classification (p
-value < 0.001). A greater prevalence of undiagnosed diabetes was observed among patients with no education (67.2%) compared to patients with higher education (33.2%) and patients who were thin (66.8%) compared to patients with normal BMI (55.1%). Compared to patients of the richest wealth quintile (36.0%), the prevalence of undiagnosed diabetes was higher among patients of the poorest (75.9%) and poorer (75.3%) quintiles (Figure 2
). The rate of undiagnosed diabetes was higher among patients who were involved in heavy physical activity (71.3%) compared to those whose work requires light physical activity (50.2%). Notable variations in the prevalence of undiagnosed diabetes were also observed across administrative divisions (p
-value < 0.001) (Table 2
3.3. Determinants of Undiagnosed Diabetes
We found that patient age, education, BMI, physical activity, administrative division, place of residence and wealth quintiles were significantly associated with the prevalence of undiagnosed diabetes among adult diabetic patients in unadjusted regression analysis.
The good fitted (log pseudo-likelihood = −547.21912; pseudo R-square = 0.1203; Wald chi-square = 108.17; p-value <0.001) multiple binary logistic regression model showed that the age of patients was associated with undiagnosed diabetes. Elderly patients had a lower likelihood of being undiagnosed than patients with age 35–39 years (for patients with age ≥ 70 years: AOR = 0.35; 95% CI 0.19, 0.64). Patients who received primary education (AOR = 0.63; 95% CI 0.43, 0.93), secondary education (AOR = 0.48; 95% CI 0.30, 0.76) and higher education (AOR = 0.36; 95% CI 0.21, 0.62) were less likely to have undiagnosed diabetes compared to patients with no education.
Patients whose work required moderate physical activity (AOR = 1.53; 95% CI 1.01, 2.32), as well as heavy physical activity (AOR = 1.73; 95% CI 1.14, 2.64), were more likely to have undiagnosed diabetes than those involved in light physical activity. Moreover, patients with a poorer socioeconomic status had a high chance of having undiagnosed diabetes compared to higher socioeconomic quintiles. Patients of the poorest and poorer wealth quintiles were 4.08 (AOR = 4.08; 95% CI 2.12, 7.86) and 3.52 (AOR = 3.52; 95% CI 1.89, 6.54) times more likely to have undiagnosed diabetes than patients of the richest wealth quintiles.
Moreover, significant geographic variation was evident in the prevalence of undiagnosed diabetes among adult diabetic patients. Residents of Dhaka (AOR = 0.36; 95% CI 0.21, 0.64), Khulna (AOR = 0.51; 95% CI 0.28, 0.92) and Rajshahi (AOR = 0.38; 95% CI 0.22, 0.67) had a 64%, 49% and 62% less chance of having undiagnosed diabetes, respectively, than patients from Barisal (Table 3
3.4. Socioeconomic Inequalities in Undiagnosed Diabetes
We found that the prevalence of undiagnosed diabetes among adult diabetic patients was disproportionately distributed among worse-off socioeconomic groups (C = −0.35; 95% CI −0.43, −0.27). The absolute difference in the distribution of undiagnosed diabetes was 39.9% between poorest and richest. Moreover, we found a 2.11 poor (quintile 1): rich (quintile 5) ratio for the distribution in the prevalence of undiagnosed diabetes in Bangladesh (Figure 2
). The C estimate (C = −0.35) using Erreyger’s corrected approach showed similar results.
Undiagnosed diabetes may lead to adverse health consequences. This study adopted nationally representative survey data (BDHS 2011) to estimate the prevalence of undiagnosed diabetes among adult diabetic patients, along with the risk factors associated with it.
The BDHS 2011 estimated that the diabetes prevalence among adults is 11.2% in Bangladesh, of which more than half of the study participants were identified as having a FPG ≥ 7.0 mmol/L who were not screened or diagnosed with diabetes before the survey. This might be due to the lack of accessibility, availability and utilization of healthcare services. It is evident from the Bangladesh Health Facility Survey 2014 that services for diabetes are offered from district to union level but diabetes diagnosis capacity are limited to Upazila Health Complex (sub-district level). Only one-third of the district and Upazila-level health facilities had diagnostic materials [27
]. This indicates that in a resource-poor setting like Bangladesh, less coverage of healthcare services and insufficient screening materials may lead to a higher proportion of undiagnosed diabetes. Nonetheless, knowledge, perception and the management of diabetes are influenced by people’s access to healthcare centers [28
]. Therefore, patients living away from healthcare centers that provide diabetes care may have a poorer understanding of the importance of diabetes screening and its management. Moreover, people do not usually seek care unless they are exposed to severe health hazards and therefore early symptoms of diabetes are often ignored [29
Few studies have been conducted on undiagnosed diabetes in low- and middle-income countries to date. Latif et al. reported in 2011 that among patients with diabetes, nearly half were undiagnosed in Bangladesh [30
]. A similar prevalence of undiagnosed diabetes has been observed in a study conducted in the rural residences of Bangladesh [31
]. Our results align with these findings. Around one-third of diabetes cases are undiagnosed worldwide [14
], which is lower than the current rate of undiagnosed diabetes among Bangladeshis as estimated in this study. However, findings from several studies suggest that this ratio is lower in developed countries [17
]. In a study conducted in Quebec, Canada, 40% of diabetes patients were found to be undiagnosed [32
]. In the USA, more than one-third of patients were found to be undiagnosed diabetics in two different studies conducted on adolescents and the adult Mexican border populations, respectively [33
]. Seven million undiagnosed diabetic patients were identified by 2010 [35
]. In contrast, less than 10% undiagnosed diabetes was found in Norway and England [18
A number of previous studies have reported a higher risk of diagnosed diabetes among people: in older age, residing in an urban area, with a higher education level, who are overweight, and who were involved in less physical activity [16
]. We found that people aged less than 50 years, rural dwellers, less educated, thin patients, and those who were involved in heavy physical activity were at higher risk of having undiagnosed diabetes. This may be because of the misconception that people who are relatively young, underweight or those involved in heavy physical activity are less likely to suffer from any severe disease. These groups may therefore be less conscious about their health status [39
]. People with no educational background and living in a rural area are not aware of the symptoms of diabetes and they may not consider this as a threat to their health [40
]. Therefore, even if they are exposed to one or more symptoms of diabetes, they still may not consult a healthcare provider.
Our study demonstrates that inequalities exist in the prevalence of undiagnosed diabetes across the wealth quintiles and this was more prevalent among the poor compared to the rich. This is contrary to the study conducted on patients with diabetes which found inequality in the opposite dimension [41
]. Greater awareness and more utilization of healthcare benefits among the rich may be the reason behind this disparity [42
]. To reduce this gap, public health strategies should concentrate more on the cost-effective allocation of resources which has to be equitable for all.
In Bangladesh, despite the risk factors of [15
] and the inequalities in [41
], diabetes prevalence was well detected at a national level, which has guided people and policy makers to control the disease. However, controlling this disease will not be meaningful unless all patients are accurately diagnosed and detected. Also, the identification of unequal distribution of patients with undiagnosed diabetes across different socioeconomic groups is essential for setting priorities and allocation of resources. The findings of this study will further guide policy makers in this aspect by taking the disparities in the distribution of undiagnosed diabetes into consideration.
We endeavoured to identify the potential risk factors by taking cluster variation into account. However, there could be residual or unmeasured confounders. We used cross-sectional data which prevents us from detecting causal relationships between undiagnosed diabetes and confounders.
To date, no large-scale study had been conducted on undiagnosed diabetes in Bangladesh. This study provides a rare opportunity to estimate the prevalence of undiagnosed diabetes as a major threat to health outcomes in Bangladesh through a nationally representative survey. Furthermore, risk factors were identified using the odds ratio, which is widely accepted. The incorporation of a biomarker test in the BDHS 2011 provided evidence of glucose abnormalities in a substantial proportion of individuals, indicating that screening practices for diabetes need to be widened with the greatest possible coverage of the population.