<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">JDM</journal-id><journal-title-group><journal-title>Journal of Diabetes Mellitus</journal-title></journal-title-group><issn pub-type="epub">2160-5831</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/jdm.2018.83009</article-id><article-id pub-id-type="publisher-id">JDM-86775</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Medicine&amp;Healthcare</subject></subj-group></article-categories><title-group><article-title>
 
 
  Association between Comorbidities and Selected Sociodemographic Factors with Complications of Diabetes: Results from the National Diabetic Registry Malaysia
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Nor</surname><given-names>Asiah Muhamad</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Mohd</surname><given-names>Hatta Abdul Mutalip</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Normi</surname><given-names>Mustapha</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Nor</surname><given-names>Soleha Mohd Dali</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Tahir</surname><given-names>Aris</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Fatanah</surname><given-names>Ismail</given-names></name><xref ref-type="aff" rid="aff4"><sup>4</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Shahnaz</surname><given-names>Murad</given-names></name><xref ref-type="aff" rid="aff5"><sup>5</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Lokman</surname><given-names>Hakim Sulaiman</given-names></name><xref ref-type="aff" rid="aff6"><sup>6</sup></xref></contrib></contrib-group><aff id="aff4"><addr-line>Family Health Development Division, Ministry of Health Malaysia, Putrajaya, Malaysia</addr-line></aff><aff id="aff3"><addr-line>Institute for Medical Research, Ministry of Health Malaysia, Kuala Lumpur, Malaysia</addr-line></aff><aff id="aff1"><addr-line>Institute for Public Health, Ministry of Health Malaysia, Kuala Lumpur, Malaysia</addr-line></aff><aff id="aff2"><addr-line>Faculty of Science &amp;amp; Technology, Open University of Malaysia, Kuala Lumpur, Malaysia</addr-line></aff><aff id="aff5"><addr-line>Office of Deputy Director General of Health (Research and Technical), Ministry of Health, Putrajaya, Malaysia</addr-line></aff><aff id="aff6"><addr-line>Department of Community Medicine, International Medical University, Kuala Lumpur, Malaysia</addr-line></aff><author-notes><corresp id="cor1">* E-mail:<email>norasiahdr@gmail.com(NAM)</email>;</corresp></author-notes><pub-date pub-type="epub"><day>16</day><month>08</month><year>2018</year></pub-date><volume>08</volume><issue>03</issue><fpage>84</fpage><lpage>97</lpage><history><date date-type="received"><day>26,</day>	<month>May</month>	<year>2018</year></date><date date-type="rev-recd"><day>19,</day>	<month>August</month>	<year>2018</year>	</date><date date-type="accepted"><day>22,</day>	<month>August</month>	<year>2018</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  Background:
   This study aims to determine the hazard ratio of having any complication from diabetes mellitus, and the associations between comorbidities and risk of having any complications from diabetes mellitus among diabetic patients who have attended government primary care clinics. <b>Methods:</b> Secondary data were retrieved from the
   
  Malaysian National Diabetic Registry
   
  which included all patients who received care. The data from the study on the socio-demographic, diabetes complications, clinical and treatment characteristics were analyzed using descriptive statistics. Cox
   
  regression
   
  was performed to estimate the hazard ratio
   
  for comorbidities, tobacco use, duration of diabetes and socio-demography characteristics upon time to diabetic complications. <b>Results:</b> Adjusted for other covariates, 
  increase 
  number of comorbidities contributed the highest hazard ratio risk
  :
   1 comorbid (aHR: 2.47, 95% CI: 2.39, 2.55), 2 comorbidities (aHR: 4.34, 95% CI: 4.22, 4.47), 3 comorbidities (aHR: 6.56, 95% CI: 6.31, 6.81) and 4 comorbidities (aHR: 9.13, 95% CI: 8.20, 10.17). Other factors
  :
   age &gt;
   
  40 year
  s
   (8%) Malays (27%) and smokers (10%) have hazard risks to develop diabetic complications. <b>Conclusions:</b> Increase in number of comorbidities will increase the risk of getting diabetes complications.
   
  Other factors such as age, gender, race, smoking status and duration of diabetes are also noted to contribute to increase risk for diabetes complications.
 
</p></abstract><kwd-group><kwd>Comorbidities</kwd><kwd> Complications</kwd><kwd> Diabetes</kwd><kwd> Primary Care</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>Diabetes is a major global health problem which has put a strain on the global economy with an estimated budget of US 1.31 trillion globally [<xref ref-type="bibr" rid="scirp.86775-ref1">1</xref>]. WHO reported a consistent incremental trend of global diabetes up to four-fold since 1980 [<xref ref-type="bibr" rid="scirp.86775-ref2">2</xref>]. A recent report by the International Diabetes Federation estimated 8.8% global prevalence of diabetes or 425 million adults aged 20 to 79 years old are diabetic [<xref ref-type="bibr" rid="scirp.86775-ref3">3</xref>]. The WHO data representing 130 countries indicated 382 million people had diabetes in 2013, and this number is expected to increase up to 592 million by 2035 [<xref ref-type="bibr" rid="scirp.86775-ref2">2</xref>]. The trend of diabetes has been on the rise especially in low and middle-income countries [<xref ref-type="bibr" rid="scirp.86775-ref3">3</xref>][<xref ref-type="bibr" rid="scirp.86775-ref4">4</xref>]with 84.5% of undiagnosed diabetes which will increase the number of diabetic cases in the future [<xref ref-type="bibr" rid="scirp.86775-ref3">3</xref>]. Diabetes can lead to complications that significantly impact the quality of life and causes premature mortality [<xref ref-type="bibr" rid="scirp.86775-ref4">4</xref>]. WHO estimated 3.7 million burden of deaths attributable to high blood glucose which includes 1.5 million diabetes deaths and additional 2.2 million deaths of other complications associated with high blood glucose level among upper middle income and low income countries [<xref ref-type="bibr" rid="scirp.86775-ref4">4</xref>].</p><p>The rise in diabetes prevalence has been attributed to numerous factors, including population growth and ageing [<xref ref-type="bibr" rid="scirp.86775-ref5">5</xref>]. Other factors, such as obesity and physical inactivity, have also contributed substantially to the global diabetes burden. Thus, preventing these factors can prevent or delay the onset of type 2 diabetes [<xref ref-type="bibr" rid="scirp.86775-ref5">5</xref>][<xref ref-type="bibr" rid="scirp.86775-ref6">6</xref>]. Several studies have also documented clinical evidence of multiple comorbidities which will increase the risk of diabetes complication and complicate diabetes management [<xref ref-type="bibr" rid="scirp.86775-ref7">7</xref>][<xref ref-type="bibr" rid="scirp.86775-ref8">8</xref>]. Comorbidities also increase the burden of medical expenditure and care for patients with diabetes and other range of complications for treatment [<xref ref-type="bibr" rid="scirp.86775-ref9">9</xref>][<xref ref-type="bibr" rid="scirp.86775-ref10">10</xref>]. Other study also indicates lower utilization of specialist care has been proven to contribute an increased risk of diabetes complications [<xref ref-type="bibr" rid="scirp.86775-ref11">11</xref>].</p><p>In Malaysia, the recently published population-based survey of National Health and Morbidity Survey 2015 indicates 17.5% of known and undiagnosed diabetes among adults aged 18 years and above [<xref ref-type="bibr" rid="scirp.86775-ref12">12</xref>]. The survey also revealed an incremental trend in diabetes prevalence from 5.5% among adults aged 18 to 19 years and peaks in older age [<xref ref-type="bibr" rid="scirp.86775-ref12">12</xref>]. Recent findings in Malaysia recruited patients from general hospitals, diabetes clinics and referral clinics reported high burden of diabetic patients with uncontrolled coexisted complications [<xref ref-type="bibr" rid="scirp.86775-ref13">13</xref>]. The study also found worsening glycemic control with multiple comorbidities despite of adherence to medication [<xref ref-type="bibr" rid="scirp.86775-ref13">13</xref>]. Another studies utilized a cohort of diabetes patients attended primary health care clinic in Malaysia reported high burden of comorbidities especially in hypertension and complications associated with diabetes [<xref ref-type="bibr" rid="scirp.86775-ref14">14</xref>][<xref ref-type="bibr" rid="scirp.86775-ref15">15</xref>].</p><p>Numerous studies have been conducted to investigate factors associated with diabetes complications [<xref ref-type="bibr" rid="scirp.86775-ref9">9</xref>][<xref ref-type="bibr" rid="scirp.86775-ref16">16</xref>]. There were several studies in Malaysia documented types of diabetes complications [<xref ref-type="bibr" rid="scirp.86775-ref13">13</xref>]and medication adherence [<xref ref-type="bibr" rid="scirp.86775-ref13">13</xref>][<xref ref-type="bibr" rid="scirp.86775-ref17">17</xref>]. However, based on our current knowledge, none of the studies measure time factor or duration of diabetes to the development of the complications associated with diabetes. Hence, we feel the necessity to further explore the risk of these coexisted conditions with other predictors by considering the time factor to developing diabetes-associated complications. Understanding on these coexisted conditions and other factors is important for health care practitioners especially at the primary health care setting to manage diabetic patient more effectively. This information is also essential for the primary health care provider to improve the quality of care and outcomes of diabetic patient to inhibit complications and reduce the burden of chronic or secondary care as a result of diabetes complication. Therefore, this study aims to determine the hazard factors of having any complication from diabetes mellitus, and its association with comorbidities among diabetes patients attended government primary health care clinics by utilizing data from the Malaysian National Diabetic Registry.</p></sec><sec id="s2"><title>2. Methods</title><sec id="s2_1"><title>2.1. Data Collection</title><p>Data for this study was obtained from the National Diabetes Registry (NDR). The NDR routinely records information on patients with diabetes mellitus (DM) managed by participating Ministry of Health (MOH) health clinics since 2009. It consists of two related components, namely, the patient registry and clinical audit dataset. The audit dataset is a subset of the patient registry. On an annual basis, a proportion of patients from the registry are randomly selected for auditing of clinical variables and clinical outcomes and they are added to their registry record [<xref ref-type="bibr" rid="scirp.86775-ref15">15</xref>].</p><p>In all MOH health clinics, diabetes mellitus is diagnosed based on the plasma glucose criteria either fasting plasma glucose (FPG) or 2-hour plasma glucose (2-h PG) value after a 75-g oral glucose tolerance test (OGTT) or the A1C criteria. The cut-off point for FPG is 126 mg/dL (7.0 mmol/L), for 2-h PG is 200 mg/dL (11.1 mmol/L) and for A1C is 6.3% (45 mmol/mol). A diagnosis of diabetes mellitus is confirmed when the results for any of the two tests mentioned earlier are beyond the threshold [<xref ref-type="bibr" rid="scirp.86775-ref18">18</xref>].</p></sec><sec id="s2_2"><title>2.2. Site Selection Criteria</title><p>There are currently 1061 health clinics managing patients with DM. However, for this study we selected 963 participating health clinics throughout the country that provided complete data of diabetic patients to NDR. These 963 clinics were also chosen because these clinics participated in the NDR database project that compiled complete information of patients with DM in primary health care setting. Health clinics which did not participate in the NDR database system were excluded from this study.</p></sec><sec id="s2_3"><title>2.3. Patient Selection Criteria</title><p>The registry includes all patients with DM managed at the participating health clinics. These patients came with any type of DM namely Type 1 DM (T1DM), Type 2 DM (T2DM), and other types of DM, such congenital diabetes, cystic fibrosis-related diabetes, steroid-related diabetes that is induced by high doses of glucocorticoids, and several forms of monogenic diabetes. For the purpose of this study, only patients with T1DM and T2DM were included. Additional inclusion criteria were DM patients aged between 20 - 70 years old, diagnosed from year 1990 and above, with information of comorbidities; ischemic heart disease, cerebrovascular disease, hypertension and dyslipidemia. All patients with missing date of diagnosis and complications related to DM were excluded. A total of 729,743 patients were identified from the registry. Of these, 567,442 were included in the final analysis. All data were de-identified prior to analysis. This study was registered under the Malaysia National Medical Research Registry (NMRR) with the identification number NMRR-17-33234334 and funded by MOH. The Malaysian guideline permits the use of secondary data from the registry if the data are anonymised. Hence, the data were de-identified prior to analysis.</p></sec><sec id="s2_4"><title>2.4. Statistical Analysis</title><p>Analysis was performed to determine the distributions of socio-demographic factors, diabetes complications, namely, retinopathy, nephropathy, diabetic foot ulcer and amputation, and number of comorbidities. For all cases with diagnosis dates (diagnosed since 1 January 1990), the Cox proportional hazard model was performed to calculate crude and multivariable-adjusted hazard ratios (HRs) in the model with the variables; smoking status, type and duration of diabetes, and number of comorbidities. Time was defined as diagnosis date to time of complications; retinopathy, nephropathy, diabetic foot ulcer and amputation. Time periods were defined as less than five years, five to ten years and more than ten years. All analyses were performed using Stata SE 12.1 software. All reported p-values were 2-sided, and p &lt; 0.05 indicates a significant difference.</p></sec></sec><sec id="s3"><title>3. Results</title><p>During the study period, a total of 567,442 patients with mean age of 56.59 (SD 9.38) years met the inclusion criteria. About 57% (325,361) were females and more than 60% were Malays. A majority of the patients were nonsmokers (80.5%). The demographic characteristics of the respondents are presented in <xref ref-type="table" rid="table1">Table 1</xref>.</p><p>Clinical characteristics showed that almost 100% (564,140) of the patients were T2DM with a mean disease duration of 7.14 (SD4.90) years. With regards to comorbidities, almost 65% (365,765) had been diagnosed with hypertension, 55% (312,260) with dyslipidaemia, 4% ischemic heart disease and 1%</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> Demographic characteristics (N = 567,442)</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  colspan="2"   rowspan="2"  >Characteristics</th><th align="center" valign="middle"  rowspan="2"  >Retinopathy</th><th align="center" valign="middle"  rowspan="2"  >Nephropathy</th><th align="center" valign="middle"  rowspan="2"  >Diabetic Foot Ulcer</th><th align="center" valign="middle"  rowspan="2"  >Amputation</th><th align="center" valign="middle" ></th></tr></thead><tr><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" >N (%)</td><td align="center" valign="middle" >n (%)</td><td align="center" valign="middle" >n (%)</td><td align="center" valign="middle" >n (%)</td><td align="center" valign="middle" >n (%)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Age group</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >≤40</td><td align="center" valign="middle" >37,602 (6.63)</td><td align="center" valign="middle" >1116 (2.97)</td><td align="center" valign="middle" >1263 (3.36)</td><td align="center" valign="middle" >258 (0.69)</td><td align="center" valign="middle" >113 (0.30)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >&gt;40</td><td align="center" valign="middle" >529,840 (93.37)</td><td align="center" valign="middle" >35,321 (6.42)</td><td align="center" valign="middle" >38,281 (7.23)</td><td align="center" valign="middle" >6355 (1.20)</td><td align="center" valign="middle" >3419 (0.65)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Gender</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Male</td><td align="center" valign="middle" >242,081 (42.66)</td><td align="center" valign="middle" >15,069 (6.22)</td><td align="center" valign="middle" >18,273 (7.55)</td><td align="center" valign="middle" >3345 (1.38)</td><td align="center" valign="middle" >1852 (0.77)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Female</td><td align="center" valign="middle" >325,361 (57.34)</td><td align="center" valign="middle" >21,368 (6.57)</td><td align="center" valign="middle" >21,271 (6.54)</td><td align="center" valign="middle" >3268 (1.00)</td><td align="center" valign="middle" >1680 (0.52)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Race</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Malay</td><td align="center" valign="middle" >358,577 (63.19)</td><td align="center" valign="middle" >22,656 (6.32)</td><td align="center" valign="middle" >28,062 (7.83)</td><td align="center" valign="middle" >4855(1.35)</td><td align="center" valign="middle" >2508 (0.70)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Chinese</td><td align="center" valign="middle" >92,726 (16.34)</td><td align="center" valign="middle" >6394 (6.90)</td><td align="center" valign="middle" >5723 (6.17)</td><td align="center" valign="middle" >653 (0.70)</td><td align="center" valign="middle" >400 (0.43)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Indian</td><td align="center" valign="middle" >73,874 (13.02)</td><td align="center" valign="middle" >4314 (5.84)</td><td align="center" valign="middle" >4153 (5.62)</td><td align="center" valign="middle" >820 (1.11)</td><td align="center" valign="middle" >490 (0.66)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Others</td><td align="center" valign="middle" >42,265 (7.45)</td><td align="center" valign="middle" >3073 (7.27)</td><td align="center" valign="middle" >1606 (3.80)</td><td align="center" valign="middle" >285 (0.67)</td><td align="center" valign="middle" >134 (0.32)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Smoking status</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Yes</td><td align="center" valign="middle" >31,999 (5.64)</td><td align="center" valign="middle" >2239 (7.00)</td><td align="center" valign="middle" >2752 (8.60)</td><td align="center" valign="middle" >6612 (1.17)</td><td align="center" valign="middle" >320 (0.62)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >No</td><td align="center" valign="middle" >456,485 (80.45)</td><td align="center" valign="middle" >29,509 (6.46)</td><td align="center" valign="middle" >31,447 (6.89)</td><td align="center" valign="middle" >5088 (1.11)</td><td align="center" valign="middle" >2755 (0.60)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Not known</td><td align="center" valign="middle" >78,958 (13.91)</td><td align="center" valign="middle" >4673 (5.93)</td><td align="center" valign="middle" >5326 (6.76)</td><td align="center" valign="middle" >892 (1.13)</td><td align="center" valign="middle" >456 (0.58)</td><td align="center" valign="middle" ></td></tr></tbody></table></table-wrap><p>cerebrovascular disease. For each of these comorbidities, the proportion unknown ranged between 4.3% to 8.5%. In terms of complications, 7% (39,544) of the patients have nephropathy followed closely by retinopathy 6.42% (36,437), diabetic foot ulcer 1.17% (6613) and amputation 0.62% (3532). A minority comprising 0.04% (222) diabetic patients have all four complications as depicted in <xref ref-type="table" rid="table2">Table 2</xref>.</p><p><xref ref-type="table" rid="table3">Table 3</xref> shows the Cox proportional hazard model on the risk of having any complication, such as retinopathy, nephropathy and diabetic foot ulcer with multivariable-adjusted hazard ratios (HRs) for selected socio-demographic data, duration of diabetes, smoking, and number of comorbidities.</p><p>Age &gt; 40 years was significantly related to slightly higher risk of complications with an adjusted HR of 1.08 (95% CI; 1.04, 1.13) while female had lower risk with HR of 0.87 (95% CI; 0.86, 0.88) respectively. Malay ethnicity was significantly associated with having a significantly higher risk of any complication with adjusted HR of 1.27 (95% CI; 1.25, 1.30). Diabetic patients who smoke were also found to be associated with having complications with adjusted HR of 1.10 (95% CI; 1.07, 1.14). Compared to under-five years’ disease duration, longer periods were significantly associated with a progressively lower risk of complications (aHR 0.91; 95% CI 0.89, 0.93 for 5 - 10 years and 0.67; 95% CI 0.66, 0.69 for &gt; 10 years). As for the number of comorbidities, the associated risk significantly</p><table-wrap id="table2" ><label><xref ref-type="table" rid="table2">Table 2</xref></label><caption><title> Clinical characteristics (N = 567,442)</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Characteristics</th><th align="center" valign="middle" >N</th><th align="center" valign="middle" >%</th></tr></thead><tr><td align="center" valign="middle" >Type of diabetes</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Type 1</td><td align="center" valign="middle" >3302</td><td align="center" valign="middle" >0.58</td></tr><tr><td align="center" valign="middle" >Type 2</td><td align="center" valign="middle" >564,140</td><td align="center" valign="middle" >99.42</td></tr><tr><td align="center" valign="middle" >Duration of diabetes (year)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Mean(SD)</td><td align="center" valign="middle"  colspan="2"  >7.14 (4.90)</td></tr><tr><td align="center" valign="middle" >&lt;5</td><td align="center" valign="middle" >200,666</td><td align="center" valign="middle" >35.36</td></tr><tr><td align="center" valign="middle" >5 - 10</td><td align="center" valign="middle" >237,419</td><td align="center" valign="middle" >41.84</td></tr><tr><td align="center" valign="middle" >&gt;10</td><td align="center" valign="middle" >129,357</td><td align="center" valign="middle" >22.80</td></tr><tr><td align="center" valign="middle" >Ischemic heart disease</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Yes</td><td align="center" valign="middle" >22,285</td><td align="center" valign="middle" >3.93</td></tr><tr><td align="center" valign="middle" >No</td><td align="center" valign="middle" >496,941</td><td align="center" valign="middle" >87.58</td></tr><tr><td align="center" valign="middle" >Not known</td><td align="center" valign="middle" >48,216</td><td align="center" valign="middle" >8.50</td></tr><tr><td align="center" valign="middle" >Cerebrovascular disease</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Yes</td><td align="center" valign="middle" >6332</td><td align="center" valign="middle" >1.12</td></tr><tr><td align="center" valign="middle" >No</td><td align="center" valign="middle" >516,033</td><td align="center" valign="middle" >90.94</td></tr><tr><td align="center" valign="middle" >Not known</td><td align="center" valign="middle" >45,077</td><td align="center" valign="middle" >7.94</td></tr><tr><td align="center" valign="middle" >Hypertension</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Yes</td><td align="center" valign="middle" >365,765</td><td align="center" valign="middle" >64.46</td></tr><tr><td align="center" valign="middle" >No</td><td align="center" valign="middle" >177,308</td><td align="center" valign="middle" >31.25</td></tr><tr><td align="center" valign="middle" >Not known</td><td align="center" valign="middle" >24,369</td><td align="center" valign="middle" >4.29</td></tr><tr><td align="center" valign="middle" >Dyslipidaemia</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Yes</td><td align="center" valign="middle" >312,260</td><td align="center" valign="middle" >55.03</td></tr><tr><td align="center" valign="middle" >No</td><td align="center" valign="middle" >224,729</td><td align="center" valign="middle" >39.60</td></tr><tr><td align="center" valign="middle" >Not known</td><td align="center" valign="middle" >30,453</td><td align="center" valign="middle" >5.37</td></tr><tr><td align="center" valign="middle" >Complication</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Retinopathy</td><td align="center" valign="middle" >36,437</td><td align="center" valign="middle" >6.42</td></tr><tr><td align="center" valign="middle" >Nephropathy</td><td align="center" valign="middle" >39,544</td><td align="center" valign="middle" >7.00</td></tr><tr><td align="center" valign="middle" >Diabetic foot ulcer</td><td align="center" valign="middle" >6613</td><td align="center" valign="middle" >1.17</td></tr><tr><td align="center" valign="middle" >Amputation</td><td align="center" valign="middle" >3532</td><td align="center" valign="middle" >0.62</td></tr><tr><td align="center" valign="middle" >All the above</td><td align="center" valign="middle" >222</td><td align="center" valign="middle" >0.04</td></tr></tbody></table></table-wrap><p>increased with increasing number of comorbidities from aHR 2.47 (95% CI 2.39, 2.55) for one comorbidity to 9.13 (95% CI 8.20, 10.17) for patients with 4 comorbidities (<xref ref-type="table" rid="table3">Table 3</xref>).</p><table-wrap id="table3" ><label><xref ref-type="table" rid="table3">Table 3</xref></label><caption><title> Cox Proportional Hazard Ratio analysis to determine hazard of having any complication (N = 567,442)</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Factors</th><th align="center" valign="middle" >n</th><th align="center" valign="middle" >Hazard ratio</th><th align="center" valign="middle" >95% CI</th><th align="center" valign="middle" >p-value</th></tr></thead><tr><td align="center" valign="middle" >Age group</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >≤40 (ref)</td><td align="center" valign="middle" >37,602</td><td align="center" valign="middle" >1.00</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >&gt;40</td><td align="center" valign="middle" >529,840</td><td align="center" valign="middle" >1.08</td><td align="center" valign="middle" >1.04, 1.13</td><td align="center" valign="middle" >&lt;0.001</td></tr><tr><td align="center" valign="middle" >Gender</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Male (ref)</td><td align="center" valign="middle" >242,081</td><td align="center" valign="middle" >1.00</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Female</td><td align="center" valign="middle" >325,361</td><td align="center" valign="middle" >0.87</td><td align="center" valign="middle" >0.86, 0.88</td><td align="center" valign="middle" >&lt;0.001</td></tr><tr><td align="center" valign="middle" >Race</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Chinese (ref)</td><td align="center" valign="middle" >92,726</td><td align="center" valign="middle" >1.00</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Malay</td><td align="center" valign="middle" >358,577</td><td align="center" valign="middle" >1.27</td><td align="center" valign="middle" >1.25, 1.30</td><td align="center" valign="middle" >&lt;0.001</td></tr><tr><td align="center" valign="middle" >Indian</td><td align="center" valign="middle" >73,874</td><td align="center" valign="middle" >0.96</td><td align="center" valign="middle" >0.93, 0.99</td><td align="center" valign="middle" >0.005</td></tr><tr><td align="center" valign="middle" >Others</td><td align="center" valign="middle" >42,265</td><td align="center" valign="middle" >1.05</td><td align="center" valign="middle" >1.01, 1.08</td><td align="center" valign="middle" >0.011</td></tr><tr><td align="center" valign="middle" >Smoking status</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >*No (ref)</td><td align="center" valign="middle" >535,443</td><td align="center" valign="middle" >1.00</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Yes</td><td align="center" valign="middle" >31,999</td><td align="center" valign="middle" >1.10</td><td align="center" valign="middle" >1.07, 1.14</td><td align="center" valign="middle" >&lt;0.001</td></tr><tr><td align="center" valign="middle" >Type of diabetes</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Type 1 (ref)</td><td align="center" valign="middle" >3302</td><td align="center" valign="middle" >1.00</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Type 2</td><td align="center" valign="middle" >564,140</td><td align="center" valign="middle" >0.92</td><td align="center" valign="middle" >0.83, 1.02</td><td align="center" valign="middle" >0.110</td></tr><tr><td align="center" valign="middle" >Duration of diabetes (year)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >&lt;5 (ref)</td><td align="center" valign="middle" >200,666</td><td align="center" valign="middle" >1.00</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >5 - 10</td><td align="center" valign="middle" >237,419</td><td align="center" valign="middle" >0.91</td><td align="center" valign="middle" >0.89, 0.93</td><td align="center" valign="middle" >&lt;0.001</td></tr><tr><td align="center" valign="middle" >&gt;10</td><td align="center" valign="middle" >129,357</td><td align="center" valign="middle" >0.67</td><td align="center" valign="middle" >0.66, 0.69</td><td align="center" valign="middle" >&lt;0.001</td></tr><tr><td align="center" valign="middle" ><sup>#</sup>Number of comorbidity</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >0</td><td align="center" valign="middle" >136,983</td><td align="center" valign="middle" >1.00</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >1</td><td align="center" valign="middle" >174,970</td><td align="center" valign="middle" >2.47</td><td align="center" valign="middle" >2.39, 2.55</td><td align="center" valign="middle" >&lt;0.001</td></tr><tr><td align="center" valign="middle" >2</td><td align="center" valign="middle" >235,632</td><td align="center" valign="middle" >4.34</td><td align="center" valign="middle" >4.22, 4.47</td><td align="center" valign="middle" >&lt;0.001</td></tr><tr><td align="center" valign="middle" >3</td><td align="center" valign="middle" >19,020</td><td align="center" valign="middle" >6.56</td><td align="center" valign="middle" >6.31, 6.81</td><td align="center" valign="middle" >&lt;0.001</td></tr><tr><td align="center" valign="middle" >4</td><td align="center" valign="middle" >837</td><td align="center" valign="middle" >9.13</td><td align="center" valign="middle" >8.20, 10.17</td><td align="center" valign="middle" >&lt;0.001</td></tr></tbody></table></table-wrap><p>Notes: *No indicates “No” and “Not known” categories. Reference category = 1.00. Backward stepwise method was applied. *Comorbidities; ischemic heart disease, cerebrovascular disease, hypertension and dyslipidemia; Complications; retinopathy, nephropathy and diabetic foot ulcer.</p></sec><sec id="s4"><title>4. Discussion</title><p>The present study examined the hazard factors affecting the risk of developing complications in diabetic patients from the NDR registry. These were nephropathy, retinopathy, diabetic foot ulcer, amputation, and combination of all four complications. In this large primary care clinic attendance database, our study showed that the presence of comorbidity especially patients with more comorbidities, smoking, older age ethnicity had increased risk of diabetic complications at any time during the follow up from this study.</p><p>Our study found an incremental risk of complications with the increasing number of comorbidities. Studies reported the preponderance of diabetes patients with one comorbidity as compared to multiple comorbidities [<xref ref-type="bibr" rid="scirp.86775-ref19">19</xref>][<xref ref-type="bibr" rid="scirp.86775-ref20">20</xref>]and the presence of comorbidity was significantly associated with diabetic complications [<xref ref-type="bibr" rid="scirp.86775-ref20">20</xref>][<xref ref-type="bibr" rid="scirp.86775-ref21">21</xref>]. Hypertension, hyperlipidemia and obesity were the commonest comorbidity and about 20% had the secoexisted comorbidities [<xref ref-type="bibr" rid="scirp.86775-ref20">20</xref>]. It was also reported an incremental trend of obesity correlates with the rise of diabetes especially in T2DM [<xref ref-type="bibr" rid="scirp.86775-ref22">22</xref>].</p><p>Several studies reported hypertension was the commonest comorbidity among diabetic patients and the findings are consistent with the present study where 64.5% patients had coexisted hypertension [<xref ref-type="bibr" rid="scirp.86775-ref7">7</xref>][<xref ref-type="bibr" rid="scirp.86775-ref19">19</xref>][<xref ref-type="bibr" rid="scirp.86775-ref23">23</xref>][<xref ref-type="bibr" rid="scirp.86775-ref24">24</xref>]. In India, hypertension was the most frequent comorbid among T2DM patients living in urban area [<xref ref-type="bibr" rid="scirp.86775-ref7">7</xref>]. Hypertension has been identified as an important risk factor for nephropathy and increases the risk of macrovascular and microvascular complications, which require multifactorial medication for effective treatment [<xref ref-type="bibr" rid="scirp.86775-ref8">8</xref>]. The results from other studies have proven that older people are more likely to present with cardiovascular complications, higher rates of comorbid conditions, mortality, and geriatric syndromes than elderly without diabetes [<xref ref-type="bibr" rid="scirp.86775-ref19">19</xref>]. Generally, the incidence and prevalence of diabetes due to obesity and aging population attributable to 15% increment in health care expenditure by 2031 [<xref ref-type="bibr" rid="scirp.86775-ref25">25</xref>].</p><p>In this study, nephropathy and retinopathy were more prevalent as compared to other complications and this finding concurs with other studies [<xref ref-type="bibr" rid="scirp.86775-ref16">16</xref>][<xref ref-type="bibr" rid="scirp.86775-ref24">24</xref>]. Retinopathy was found to be a constant complication in diabetes patients [<xref ref-type="bibr" rid="scirp.86775-ref16">16</xref>]and all these complications were more predominant among older age [<xref ref-type="bibr" rid="scirp.86775-ref16">16</xref>]. Among all the complications, neuropathy and nephropathy were the commonest combined complications [<xref ref-type="bibr" rid="scirp.86775-ref16">16</xref>]. According to Donate-Correa et al. [<xref ref-type="bibr" rid="scirp.86775-ref26">26</xref>], one third of diabetic patients are affected by diabetic nephropathy indicates significant of social and economic burdens that could lead to the chronic of end-stage renal disease [<xref ref-type="bibr" rid="scirp.86775-ref27">27</xref>]. A patient with early nephropathy has two times higher risk of retinopathy while a patient with advanced nephropathy has six times higher risk of retinopathy [<xref ref-type="bibr" rid="scirp.86775-ref28">28</xref>]. A study reported that predictive factors for neuropathy include duration of diabetes, retinopathy, HbA1C at second visit, and creatinine clearance on third visit [<xref ref-type="bibr" rid="scirp.86775-ref29">29</xref>]. Other diabetic complication such as end stage renal disease (ESRD) has shown significant predictor with diabetes-associated mortality adjusted for socioeconomic status [<xref ref-type="bibr" rid="scirp.86775-ref30">30</xref>]. Other study has documented neuropathy as the most predominant complication among diabetic patients [<xref ref-type="bibr" rid="scirp.86775-ref16">16</xref>]especially among Asian patients [<xref ref-type="bibr" rid="scirp.86775-ref31">31</xref>].</p><p>In this study, the percentage of diabetic foot ulcer (DFU) was lower than nephropathy and retinopathy. Though it was lower than the global prevalence, DFU causes the highest number of hospital admissions along with considerable costs [<xref ref-type="bibr" rid="scirp.86775-ref3">3</xref>]. This complication includes longer lengths of hospital stay, higher hospital costs and higher mortality rates as compared to hospitalized diabetes patients without foot-related complications [<xref ref-type="bibr" rid="scirp.86775-ref32">32</xref>][<xref ref-type="bibr" rid="scirp.86775-ref33">33</xref>]. About 15% of DM patients will experience a foot ulcer at some point in their life [<xref ref-type="bibr" rid="scirp.86775-ref34">34</xref>]and the mortality risk increases by 2.4-fold over diabetic patients without ulcers [<xref ref-type="bibr" rid="scirp.86775-ref35">35</xref>].</p><p>Amputation was among the less observed complication in this study. Finding from a population-based study in Malaysia reported 4.3% of people with known diabetes reported of lower limb amputations [<xref ref-type="bibr" rid="scirp.86775-ref36">36</xref>]. However, those findings contradicted with this study where less than 1% of patients underwent leg amputation. According to Goodney et al. the highest risk for amputation are those with persistent hypertension and obesity, poor care delivery in remote settings, and poor engagement in health care systems [<xref ref-type="bibr" rid="scirp.86775-ref37">37</xref>]. Moreover, other study documented more evidence that amputation have contributed to the largest changes in quality of life of diabetic patients besides stroke and loss of vision [<xref ref-type="bibr" rid="scirp.86775-ref38">38</xref>].</p><p>Numerous studies discussed age as a strong independent predictor for diabetes and comorbidity [<xref ref-type="bibr" rid="scirp.86775-ref7">7</xref>][<xref ref-type="bibr" rid="scirp.86775-ref24">24</xref>]. Evidently, multiple comorbidities are more prevalent among older people [<xref ref-type="bibr" rid="scirp.86775-ref24">24</xref>]and types of diabetic-associated complications [<xref ref-type="bibr" rid="scirp.86775-ref16">16</xref>][<xref ref-type="bibr" rid="scirp.86775-ref19">19</xref>]. Those findings coincide with our finding where older patients (&gt;40 years old) are more prone with diabetes complications. Hypertension and hyperlipidemia are more common among older patients with T2DM compared to younger age [<xref ref-type="bibr" rid="scirp.86775-ref19">19</xref>]. Thus, management of older diabetic patients with multi comorbidities could reduce mortality associated with diabetes complication [<xref ref-type="bibr" rid="scirp.86775-ref3">3</xref>].</p><p>Our study found being female is a protective factor for having any complications. This finding supports other studies, as males tend to increase comorbidity burden, which consequently impact further diabetic-related complications [<xref ref-type="bibr" rid="scirp.86775-ref19">19</xref>][<xref ref-type="bibr" rid="scirp.86775-ref33">33</xref>]. It is well known that cigarette smoking increases the risk of developing diabetes [<xref ref-type="bibr" rid="scirp.86775-ref30">30</xref>]. Smoking is also more prevalent among males in this study and this condition consequently contributed to higher risk of diabetic-associated complications among males. Numerous studies have documented the impact of smoking to diabetes and consequent diabetes complications and smoking also significantly exacerbates diabetic nephropathy in T2DM patients [<xref ref-type="bibr" rid="scirp.86775-ref39">39</xref>].</p><p>Our study found Malays and other ethnics had increased risk for diabetes complications and Indians had lower risk for diabetic complication adjusted for other covariates. This situation might be attributable to other predisposes risk factor such as BMI where the Malays were more prone to obesity and other metabolic syndrome that coexist with diabetes [<xref ref-type="bibr" rid="scirp.86775-ref30">30</xref>]. One review highlighted high rates of diabetes among Asian population attributable to high prevalence of obesity which is more common in developing countries [<xref ref-type="bibr" rid="scirp.86775-ref30">30</xref>]. As compared to western countries, Asian people are more prone to abdominal obesity and low muscle mass with increased insulin resistance and the waist circumference reflecting central obesity substantially increased the risk of developing T2DM [<xref ref-type="bibr" rid="scirp.86775-ref30">30</xref>][<xref ref-type="bibr" rid="scirp.86775-ref31">31</xref>]. Obese patients were more likely to develop diabetic retinopathy such in Indian population and those with central obesity are associated with two times more likely to develop diabetic retinopathy [<xref ref-type="bibr" rid="scirp.86775-ref40">40</xref>].</p><p>Our study found duration of diabetes of more than 5 years was significantly protective for diabetic complications. This is contradicting with other studies as patients with comorbidities typically had longer diabetes duration, high HbA1c [<xref ref-type="bibr" rid="scirp.86775-ref13">13</xref>][<xref ref-type="bibr" rid="scirp.86775-ref41">41</xref>]and increased the odds of diabetic complications [<xref ref-type="bibr" rid="scirp.86775-ref3">3</xref>][<xref ref-type="bibr" rid="scirp.86775-ref13">13</xref>]. This conflicting finding might be associated with our sample population as we only included patients attended primary health care clinics. Primary care services provide multidisciplinary and extensive diabetic care with continuous monitoring to reduce further complications [<xref ref-type="bibr" rid="scirp.86775-ref22">22</xref>]as compared to patients with uncontrolled chronic diabetic with high rate of complications from the hospital [<xref ref-type="bibr" rid="scirp.86775-ref42">42</xref>]. This is further supported by data where about 1.1 million of diagnosed diabetes patients in Malaysia received treatment at primary health care for early prevention of diabetes complications [<xref ref-type="bibr" rid="scirp.86775-ref22">22</xref>]and patients with more comorbidity tended to have more frequent clinic visit than patients with no documented comorbidities [<xref ref-type="bibr" rid="scirp.86775-ref20">20</xref>].</p><sec id="s4_1"><title>4.1. Recommendations</title><p>Health care workers assessing diabetic patients are recommended to establish health risk-assessment tools that include comorbidities and lifestyle assessment for use in primary clinical care setting for prevention strategies of diabetes complications. It is vital to increase awareness among the public about the constellation of diseases related to having diabetes and its associated morbidities and mortality risks. Lifestyle management is essential to regulate blood glucose include physical activity and sleeping pattern [<xref ref-type="bibr" rid="scirp.86775-ref6">6</xref>]. Other study also reported counseling for diabetic patients to modify their diet such as glycemic control has significant cost saving through control of complications associated with T2DM [<xref ref-type="bibr" rid="scirp.86775-ref43">43</xref>].</p></sec><sec id="s4_2"><title>4.2. Limitations</title><p>NDR data only collect information of diabetic patients attending government primary health care clinics in Malaysia and they do not include patients attending secondary and tertiary government hospital care and private healthcare either general practitioner or private hospitals [<xref ref-type="bibr" rid="scirp.86775-ref15">15</xref>]. These data also rely on the quality of documentation from the primary health care clinics and we anticipate incomplete information from certain variables in the NDR that reduce sample population in our analysis.</p></sec></sec><sec id="s5"><title>5. Conclusions</title><p>Among all factors, increase in number of comorbidities will increase the risk of diabetes complications. Age, gender, race, smoking status, duration of diabetes and the number of comorbidities (ischemic heart disease, cerebrovascular disease, hypertension and dyslipidemia) are the hazard factors of having any complications to the patients. Older age and male gender are more likely to have the hazard or risk for complication.</p></sec><sec id="s6"><title>Acknowledgements</title><p>We thank the Director General of Health, Ministry of Health, Malaysia for permission to publish this report. We also thank Dr. Rozlan Ishak and Dr. Feisul Idzwan Mustapha for their continuous support and assistance. Our appreciation goes to everybody in Non-Communicable Disease Section, Disease Control Division, Ministry of Health, Malaysia.</p></sec><sec id="s7"><title>Funding</title><p>This work was supported by the Ministry of Health Malaysia.</p></sec><sec id="s8"><title>Conflicts of Interest</title><p>The authors declare no conflicts of interest regarding the publication of this paper.</p></sec><sec id="s9"><title>Cite this paper</title><p>Muhamad, N.A., Mutalip, M.H.A., Mustapha, N., Dali, N.S.M., Aris, T., Ismail, F., Murad, S. and Sulaiman, L.H. (2018) Association between Comorbidities and Selected Sociodemographic Factors with Complications of Diabetes: Results from the National Diabetic Registry Malaysia. 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