Diabetes management in Thailand: a literature review of the burden, costs, and outcomes

There is no national longitudinal diabetes registry in Thailand and the main source of prevalence data for diabetes is the national health examination survey (NHES). The aim of the NHES is to estimate the prevalence of particular health conditions and risk factors including obesity, diabetes, and mental, reproductive and elderly health. This survey was completed for the fourth time in 2009 (previous surveys were conducted in 1991, 1997, 2004). In 2009, a national representative sample of 20,450 (39,290 in 2009) individuals aged 15 and over was randomly selected using a four-stage sampling strategy from five provinces in each of the four regions and Bangkok. Diabetes prevalence was assessed by fasting blood glucose test and patients identified as diabetic if they had either FPG > = 7.0 mmol/L but lack of a previous diagnosis (undiagnosed diabetes) or a previous diagnosis of diabetes and intake of glucose lowering drugs during the past two weeks (diagnosed diabetes) [11, 12].

In April 2003, 9,419 diabetes patients (both Type 1 and 2) from eleven tertiary care hospitals overall Thailand were enrolled in the Thailand diabetes registry (TDR) project [13]. This project was a collaboration between the Clinical Research Cooperation Network (CRCN) and the Health System Research Institute (HSRI), supported by the Endocrine Society of Thailand. The first objective of this registry was to identify the characteristics of Thai diabetic patients in tertiary care medical centers and to determine the extent of long term diabetic complications. The second objective was to develop and strengthen a clinical research network in Thailand which included experts in diabetes mellitus. The third and final objective was to collect baseline data for future follow-up studies. Cross-sectional data were collected from 11 tertiary level hospitals with diabetes clinics between April and December 2003. Demographic data, clinical status of diabetes and its complications were collected to estimate the prevalence of complications and risk factors. Data quality was ensured by regular on-site visits of internal and external auditors. This project also had a second component which was a three-year cohort study from April 2003 to February 2006 to determine the causes of death in diabetes patients.

DiabCare is an international collaboration between NovoNordisk Asia Pacific Pte Ltd, Singapore; BioRad Pacific, Hong Kong; and diabetes associations in the participating countries (Bangladesh, China, India, Indonesia, Malaysia, Philippines, Singapore, South Korea, Sri Lanka, Taiwan, Philippines, and Vietnam). The aim of this partnership is to collect evidence on the disease pattern, management, control status, and complications of diabetes in the Asian diabetes population. Patients were recruited in hospitals and followed for 8 to 9 months depending on the study year. DiabCare Asia studies were conducted in 1998 [14], 1991, 2001, 2003, 2008. The next data collection round is planned in late 2012- early 2013. Thailand was surveyed during the 1998, 2001 [15], 2003, and 2008 rounds.

The InterASIA study on diabetes prevalence, risk factors for cardiovascular diseases, and diabetes management was conducted in 2000 in Thailand and China. This study, founded by Pfizer was a collaboration between universities in Australia, China, Thailand, and the US. The study was based on a nationally representative sample of the Thai general population [16].

Several other studies have been conducted on the burden of diabetes in Thailand. These include investigations on the incidence [17, 18] and prevalence of diabetes in population sub-groups [19], prevalence [20, 21] and incidence [22‐26] of diabetes Type 1 in children, incidence [27] and prevalence [28‐30] of gestational diabetes, and prevalence of type 2 diabetes in women with polycystic ovary syndrome [31]. Other studies looked at the prevalence of complications in the Thai diabetes population.

Data from the four NHES indicate that prevalence of diabetes in individuals aged 15 and over has increased over time from 2.3% in 1991 to 4.6% in 1997, to 6.8% in 2004, and to 6.9% in 2009 [32] (Figure 1). According to NHES 2009 and 2004, women experienced a higher prevalence than men [11, 12]. In contrast, findings from the InterASIA study in 2000 did not identify any difference in diabetes prevalence between men and women aged 35 and over (9.3% men vs. 9.9% women, p = 0.6) [16]. At the other end, an earlier study^a among Shinawatra employees, a group of relatively young individuals with high socioeconomic status, found a higher prevalence in men (2.2%, N = 1,250) than in women (0.1%, N = 2,365) [19].

According to the NHES 2009, prevalence of diabetes was higher in urban areas in comparison to rural areas (P < 0.001 for both sexes) [11]. However, findings from NHES 2004, only found a statistically significant higher prevalence in urban men, in comparison to their rural counterparts, (P < 0.001) but not in urban women (p > 0.05) [12]. The existence of a difference in diabetes prevalence between urban and rural areas in Thailand was confirmed by findings from the InterASIA study in 2000 (12.1% urban vs. 8.4% rural, p = 0.01, in individuals aged 35 and over) [16]. No difference between urban and rural areas was identified in the InterASIA study in 2000 and the NHES survey in 2004 [12, 16].

Different studies on diabetes prevalence in Thailand agree that the prevalence of diabetes increases with age and reaches a peak at some point after age 55 depending on the study [11, 12, 16, 19].

An important problem in diabetes care is under-diagnosis as it delays start of treatment and exposes the patient to the risk of complications which leads to higher treatment costs. Levels of under-diagnosis improved between 2004 and 2009 and this improvement was more evident in women than men. Nevertheless, a large proportion of total diabetes patients remains undiagnosed (from 66.5% to 47.3% in men and from 51.4% to 23.4% in women between 2004 and 2009) [11].

Findings from the NHES 2009 suggest that women have better rates of diagnosis in comparison to men and this difference was statistically significant (there was a difference also in 2004 but this was not statistically significant) [11, 12]. However, the InterASIA study did not find a statistically significant difference in the proportion of diagnosed patient by gender (53% women vs. 47% men, p = 0.4) but it found that diagnosis rate was higher for people aged 55 and over (63% > =55 years old vs. 37% <54 years old, p = 0.01) [16].

A comparison of the findings from the NHES in 2009 with results from 2004, shows that the proportion of individuals with diabetes and concomitant hypertension did not significantly decrease in 2009 in both sexes [11]. However, the proportion of women with diabetes who were either abdominally obese or had high total cholesterol (≥5.2 mmol/L) increased from 18% in 2004 to 23.5% in 2009 and this difference was significant (both P < 0.01) [11].

An earlier study on the prevalence of DMT2 in children and adolescents (mean age 11.6 years) reported an increase from 5.8% to 13.3% between 1986 and 1995 [21]. The authors suggest a link between this increase and the concomitant increase in obesity from 5.8% to 13.3% between 1990 and 1996 [21].

Incidence of type 1 diabetes in children in North-East Thailand has increased over the years from in 0.17 per 100,000 in 1984 to 0.3 in 1995, to 0.39 in 2000 and 1.27 in 2005. In the other regions it has also grown although following a less linear trend particularly in the Central region (Figure 2).

Findings from a study in the Bangkok-Noi district in Bangkok, found an extremely small number of cases (maximum 1 per year) between 1991 and 1995 which, despite the size of the child population in this district, it still resulted in the highest prevalence rates for type 1 diabetes recorded in the country (2.18 per 100,000 in 1991, 0 in 1992, 1.97 in 1993, 2.06 in 1994, and 2.04 in 1995) [24].

Another study looked at the seasonal variation of diabetes type 1 and found that the peak seasons were the winter and the summer season and lower during the rainy season [20]. This was explained by the higher prevalence of infections in the winter season and the higher levels of pollution in the summer in comparison to the rainy season [20].

All studies (apart from the Bangkok study which did not discuss gender differences) on diabetes type 1 identified higher incidence in girls, with a girls to boys ratio ranging from 1.3 to 2. However, none of them tested for statistical significance. Peak age at onset was 10-14 in North and North-East region [22, 25, 26], 11-15 in the South region [23], and 9-12 in Bangkok [24].

We identified three studies on incidence of DMT2 in adults in urban Thailand from a high socio-economic background [17, 18, 33]. All the three studies used the diagnostic criteria from the American Diabetes Association (ADA) using fasting plasma glucose tests (FPGs), in addition to that one study also used oral glucose tolerance tests (OGTTs). The most recent study was among professionals and office workers in Bangkok and found an incidence rate in the age-group 35-60, of 17.8 per 1000 person-years (PY) in men and 9.2 per 1000 PY in women in 2005 [17]. A second study among university hospital employees in Bangkok reported an incidence of 13.6 per 1000 PY in men and 6.4 per 1000 PY in women between 2001 and 2005. The study participants were over 35 years old and predominantly female (three-quarters). High BMI (>25 kg/m2), elevated FPG (> = 96 mg/dl) and alanine aminotransferase levels (> 18 mg/dl) were shown to be independent predictors of DMT2 [18]. Risk of diabetes in men was approximately twice as high as in women but this apparent association was confounded by higher BMI and FPG levels in men and the crude rates showed there was no association between gender and DMT2 [18]. Findings from this study were supported by an earlier study which found an overall incidence of 11.3 per 1000 PY among employees of a state enterprise in Bangkok between 1985 and 1997 [33].

Four studies on the prevalence of gestational diabetes mellitus (GDM) were identified [27‐29, 34]. They were hospital based (one hospital per study) and mostly used the diagnostic criteria of the National Diabetes Data Group (NDDG), (50 g + 100 g OGTT) with one study also comparing NDDG results with WHO criteria (75 g OGTT). All hospitals were located in Bangkok (Figure 3).

The highest prevalence (15.7%) was estimated in 1995 for women in their 24^th to 28^th week of gestation using WHO criteria [34]. When using NDDG criteria, the same study estimated a remarkably lower prevalence of 1.4% [34]. Another study highlighted the importance of the timing of diagnosis, 5.3% of screened pregnant women were diagnosed with gestational diabetes before their 20^th gestational week and an additional 4.9% of previously undiagnosed women were identified in a second round of testing during their 28^th to 32^nd week of pregnancy [27]. The 1987-1989 study followed a sub-sample of women after delivery by performing an OGTT using WHO criteria 4-6 weeks after childbirth. Results showed that 42.2% of the 71 women tested had abnormal carbohydrate tolerance, 7% had diabetes and 35.2% impaired glucose tolerance (IFG) [28].

The most recent study (March 2003-January 2005) aimed to assess the percentage of pregnancies with GDM which were missed at the time the study was conducted because clinical guidelines in the study hospital limit screening to women at high risk of developing GDM. Eligibility criteria for screening included pregnant women with at least one of the following risk-factors: aged 35 and over, family history of diabetes, previous birth over 4 kg, and other known risk-factors of GDM. This study showed that the prevalence of women aged 30 to 34 was 5.7%, and that of the 32 cases identified, 12 had one risk factor, one had two risk factors (1). More importantly 18 cases of GDM showed no risk factors and would have been missed due to the recommendations in the hospital’s guidelines at the time of the study [29].

The NHES is a nationally representative survey of the health status of the Thai population. NHES III and IV found a higher prevalence of DMT2 in women, older individuals, and in urban areas^b. Under-diagnosis was higher in men (2009: 47.3 vs. 23.4%, respectively; P < 0.001) [11, 12] and in those with less than secondary education [11]. Both surveys showed that nearly all patients who were diagnosed with diabetes were also treated with glucose-lowering medications (2004: men 2.6%, women 1.7%; 2009: men 5.6%, women 1.9% of diagnosed patients were treated) [11]. However, despite the high treatment rates, the percentage of treated and controlled patients (receiving treatment with glucose-lowering medication and with FPG <7.2 mmol/L) was still low (2004: men 7.7%, women 15.8%; 2009: men 17.5%, women 33.9% treated and controlled patients) [11].

The high percentage of treated patients among diagnosed diabetics suggests the availability of a resilient health care system in terms of access to treatment. However, access is hampered by the low diagnosis rates which need to be improved by increased screening of high-risk groups. A risk score to identify individuals at high-risk of developing diabetes was developed for the Thai population [33]. Wider implementation of this low-cost instrument can help identify high-risk individuals to be screened and therefore to increase the percentage of diabetes patients who is diagnosed. This would allow earlier start of treatment and could help in preventing part of the costs of complications arising from neglect of the disease. Another issue is the low rates of treated and controlled patients. To address these issues evidence is needed on factors responsible for poor treatment outcomes (e.g. patient compliance to treatment, performance of monitoring and self-management, etc.)

Data on diabetes type 1 in Thai children aged 0-15 suggests an increased incidence over the last 20 years from less than 0.3 cases per 100,000 in 1984 in all regions to 1.27 cases per 100,000 in the North-East region in 2005. However, interpretation of this data requires caution. Apart from the Bangkok study, all the other studies restricted their data collection to hospitals. Incidence was calculated by dividing the total number of cases reported by hospitals with the total child population in the hospitals’ catchment area. Although hospitals’ response rate was generally high (range: 84.7% to 94.5%) [22, 25], this means that in addition to not capturing diabetes type 1 cases who did not attend a hospital, the results were also importantly influenced by missing data from hospitals that did not participate in the survey.

Under-diagnosis is likely to have played a major role in the 1990s and first half of the 2000s because of incomplete insurance coverage which created barriers to health care access. Furthermore, apart from the North-East region, no data is available after 1997 and the most recent incidence data for the North-East region are for 2005.

The latest data on the incidence of DMT2 in Thai adults show an incidence rate of 13.6 in men per 1000 PY and 6.4 per 1000 PY in women [18]. However this data is out-of-date as it refers to the time period 2001 to 2005 and is not representative of the entire country as it based on urban high-socio-economic status individuals working in the healthcare sector.

Due to different gestational weeks and age of the prospective mother when the glucose test was conducted, it is not possible to draw definitive conclusions on the evolution of the prevalence of GDM over time. Data only included women attending antenatal care which might be biased towards higher socio-economic groups due to the lack of universal coverage at the time of the surveys. Despite these challenges, two main findings seem to emerge. First, a very large difference (eleven-fold) was reported when using different diagnostic criteria (NDDG (1.4%) vs. WHO criteria (15.7%)) on the same sample of women and another recent study that used the new criteria of international association of the diabetes and pregnancy study groups (IADPSG) found the prevalence of GDM in Bangkok was 23.0% [58]. Second, use of eligibility criteria which limit screening to women at high risk of developing GDM independently of their age have shown to miss more than 50% of cases among women aged 30 and over.

Data on the cost of diabetes without complications mainly comes from a study in one-hospital in North-East Thailand. Generalisability of local studies on cost of illness is affected by variation of input prices across the country, the level of care of the hospital analysed, and the patient status. One study in Thailand for example showed that a visit to the regional hospital was 3.48 times more expensive than a visit to a community hospital (THB 1,181 vs. THB 339 in 2002) [59]. Another issue was the uncertainty and large variation around the results (very large standard deviations were reported).

According to data from the Thailand diabetes registry, diabetic nephropathy was the most common complication accounting for 43.9% of all complications followed by retinopathy (30.7%), ischaemic heart disease (8.1%), and cerebrovascular disease (4.4%) [13]. Another study in the out-patient department of a university hospital found a lower prevalence for diabetic nephropathy, 37%, a similar prevalence for retinopathy, 31.2% but a substantially higher prevalence for cardiovascular and cerebrovascular disease, 28.9% and 10.6%, respectively.

The first study also highlighted the existence of high prevalence of risk factors for diabetes and its complications (dyslipidaemia, hypertension, and obesity (BMI ≥ 25 kg/m²) was 73.3%, 63.3%, and 52.6% respectively) [13].

Complications are the single largest driver of the cost of diabetes because they require more intensive care such as hospitalisation and often surgery. Studies showed that the median cost of illness for patients with complications in comparison to patients without complications was USD$ 480 vs. USD 115 [37], USD$ 190 for diabetic foot, USD$ 260 for cerebrovascular event, USD$ 336 for gangrene in comparison to USD$ 101 for patients without complications [52]. Interestingly, the latter study which was based on retrospective data analysis and cost forecast, found that the highest proportion of treatment cost was caused by pharmacy services (45%) followed by outpatient (24%) and inpatient services (16%) [52]. The first study found a similar share of inpatient costs (11%) but in addition to direct costs it also estimated indirect costs and the contribution of informal care, mortality, and permanent disability to the cost of illness (27.8%, 17.5%, 18.7%, respectively) [37] (Table 5). This data shed some light on substantial indirect costs caused by morbidity and reduced ability to work. Preventing complications, and related disability, by improving diabetes control is therefore of paramount importance to reduce the health and economic burden of diabetes.

There is a large variation in the estimates of the prevalence and costs of complications in Thailand. More studies at different levels of care and covering all the regions are needed to get a full picture of the prevalence and the cost of diabetes complications in the country.