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Pharmacy Practice (Granada)

On-line version ISSN 1886-3655Print version ISSN 1885-642X

Pharmacy Pract (Granada) vol.17 n.4 Redondela Oct./Dec. 2019  Epub Apr 20, 2020 

Original Research

A comprehensive view of knowledge and osteoporosis status among type 2 diabetes mellitus in Malaysia: A cross sectional study

Shaymaa A Abdulameer (orcid: 0000-0002-6819-1873)1  , Mohanad N Sahib (orcid: 0000-0001-5790-2388)2  , Syed A Syed Sulaiman3  , Mohamed A Hassali (orcid: 0000-0001-9575-403X)4 

1PhD. Lecturer. Faculty of Pharmacy, Al-Rafidain University College. Baghdad (Iraq).

2PhD. Lecturer. Faculty of Pharmacy, AlRafidain University College. Baghdad (Iraq).

3PhD. Professor. School of Pharmaceutical Sciences, University of Science Malaysia. Pulau Pinang (Malaysia).

4PhD. Professor. School of Pharmaceutical Sciences, University of Science Malaysia. Pulau Pinang (Malaysia).



osteoporosis and diabetes mellitus are highly prevalent diseases that have potentially devastating effects on health and socioeconomic status.


The aims of this study were to assess: 1) the level of osteoporosis knowledge among T2DM patients; 2) the correlation, associations or differences of demographic characteristics, diabetes-related variable, as well as, lipid and blood pressure profiles with osteoporosis knowledge; and 3) the correlation between T-score measurement using quantitative ultrasound scan (QUS) and osteoporosis knowledge.


A cross-sectional study design was chosen, where data was collected using a self-report structured questionnaire using osteoporosis knowledge - Malay version questionnaire (OKT-M) among T2DM patients. Furthermore, the clinical data regarding the patients were collected retrospectively from the hospital medical record after patient interview was completed.


The average age of the patients was 62.67 (SD 9.24) years (ranged from 33 to 87 years). Males (231, 51.30%) slightly outnumbered females. Among the racial distribution, the proportion of Chinese patients (204, 45.30%) was higher than Malay (127, 28.20%) and Indian patients (119, 26.40%). In addition, more than three quarters (343, 76.20%) of patients had poor glycaemic control. The average OKT-M total score, OKT-M Exercise subscale and OKT-M Calcium subscale were 12.55 (SD 4.06), 8.60 (SD 2.89) and 8.40 (SD 3.36), respectively. Only 33.30% of the T2DM patients were found to have high level of osteoporosis knowledge. There was a lack of identification and recognition of osteoporosis risk factors. There were significant differences or associations between osteoporosis knowledge and education level, monthly income, employment status, family history of fracture, smoking habit, alcoholic status, insulin use, therapy type and diastolic blood pressure. In addition, significant and positive correlations were found between T-scores and OKT-M total score (n=450, rs= 0.244, P=0.000), OKT-M Exercise subscale (n=450, rs= 0.219, P=0.000) and OKT-M Calcium subscale (n=450, rs=0.199, P=0.000) among T2DM patients (all Ps<0.05).


Overall, the study results showed a valuable insight into the knowledge toward osteoporosis, as well as its relation to the bone loss among T2DM patients. It is important to understand the basics of osteoporosis prevention behaviours such as adequate calcium intake and regular exercise which are essential to build and maintain healthy bones throughout life among T2DM.

Keywords: Diabetes Mellitus Type 2; Osteoporosis; Health Knowledge; Attitudes; Practice; Health Literacy; Risk Factors; Cross-Sectional Studies; Malaysia


Type 2 diabetes mellitus (T2DM) is mounting health problem in the contemporary era, public health concerns with a major contributor to high levels of morbidity and mortality worldwide.1,2In Malaysia, a rapidly developing country, continued urbanisation and lifestyle modifications encourage sedentary lifestyles and more overweight and obesity which reflect a pronounced grown in the diabetes prevalence over the past decades.3,4Moreover, previous studies showed that poor or suboptimal glycaemic control among diabetic patients were common in Malaysia.5,6

On the other hand, osteoporosis is a clinically silent, highly prevalent disease that has potentially devastating effects, which is largely preventable.7Globally, osteoporosis is recognised as a common public health issue, especially in postmenopausal women and elderly individuals.8,9In addition, osteoporosis in Asian populations is a serious public health problem as Asian ancestry and T2DM are considered risk factors for osteoporosis with low bone mineral density (BMD) compared to other ethnicities.10 11-12

The challenge is to address the lack of knowledge towards the prevention of health behaviours of bone disease which were identified as the most important issues in the management of osteoporosis.13Whether, an individual participates in osteoporosis preventative lifestyle behaviours or not, it is essential to have a primary understanding about their knowledge regarding osteoporosis.14Subsequently, health educational programmes can be planned and implemented accordingly.

To date, scarce papers have assessed osteoporosis knowledge among T2DM patients, and there is a paucity of literature regarding the relationship between osteoporosis knowledge and quantitative ultrasound scan (QUS) in clinical practice. Hence, the current study were aimed to assess: 1) the osteoporosis knowledge level among T2DM patients; 2) the sources of osteoporosis information among T2DM patients; 3) the correlation, associations and/or differences of demographic characteristics, diabetes-related variable, as well as, lipid and blood pressure (BP) profiles with osteoporosis knowledge; 4) the correlation between T-score measurement using QUS and osteoporosis knowledge.


Study design

A study with cross-sectional design was chosen, where data was collected using a self-report structured questionnaire among T2DM patients at Diabetes Outpatient Clinic of Penang General Hospital (PGH), Malaysia (from 1stAugust 2011 to 30thFebruary 2012). Furthermore, the clinical data were collected retrospectively using the hospital medical records after patient interview was completed.

Study population

The participants were enrolled using convenient sample method with patients eligible criteria: patients diagnosed with T2DM, diabetes duration at least 2 years (for more comprehensive medical records), aged 30 years or over (as the bone mass lose starting in the third decade), able to communicate in Bahasa Malaysia (read and write) and patients willing to participate. The prevalence based sampling technique was used to identify the representative sample of T2DM patients. According to the latest prevalence survey in Malaysian, T2DM prevalence was 14.90%.15 The final convenience sample of 450 patients with T2DM was included in the analysis of this study, which was considered to be acceptable with a margin of error (5%) and 99% confidence interval.

The study was approved by the Medical Research Ethics Committee, National Institute of Health Malaysia (Approval number: [(2) dlm.KKM/NIHSEC/08/0804/P11-101]. All participants were asked to sign the informed written consent form before participate in the study.

Research instruments

A structured questionnaire consisting of three parts was used; this included: (1) personal socio-demographic characteristics questionnaire (about yourself); (2) Osteoporosis Knowledge test Malay version (OKT-M); and (3) diabetes-related data and laboratory test results. All participants were administered a questionnaire before they underwent a QUS examination. For each of the diabetes-related data, laboratory results, blood pressure measurements, BMI were categorised according to the Malaysian Guidelines.16A validated OKT-M was used to assess the knowledge toward osteoporosis.17Based on the previous validation study of OKT-M, a cut-off point of 14 was used to classified the patients into two groups high and low.17

The QUS (SONOST 3000) measurement scores of the calcaneus region was used to calculate a bone mineral density (BMD) status according to the WHO criteria (normal, osteopenia and osteoporosis).18

Data analysis

Predictive analytics software (PASW, version 19.0) was used for statistical analysis. The significance level was set at a p-value less than 0.05 for all analyses. Percentages, frequencies and mean plus standard deviation (SD) were presented as required. The chi-square, Mann-Whitney U, Kruskal-Wallis, independent t-test and one-way analysis of variance were conducted when necessary. Pearson and Spearman’s correlations coefficient were used to measure the correlations.


In this study, a total of 500 T2DM patients were invited. Patients with incomplete responses (n=19) or missing of clinical data (n=31) were excluded from the analyses. Thus, the final convenience sample of T2DM that included in this study was 450 patients.

The average age of the patients was 62.67± 9.24 years (ranged from 33 to 87 years). Males (231, 51.30%) slightly outnumbered females (219, 48.70%). The majority of patients had an education level less than 12 years (285, 63.30%). The average body mass index (BMI) was 26.36±4.39 kg/m2, as shown in Table 1Regarding osteoporosis awareness, only 17.10% of the sample population obtained osteoporosis information from medical clinic.

Table 1. Relationships between osteoporosis knowledge levels and patients’ demographic characteristics (N=450) 

Variable N (%) Osteoporosis knowledge level N (%) p OKT-M scores Mean (SD) [median] p
Low OKT level High OKT level
300 (66.7%) 150 (33.3%)
Age (years)** 0.520 0.462
<45 11 (2.4%) 7 (63.6%) 4 (36.4%) 12.82 (4.19) [14]
45-54 78 (17.3%) 47 (60.3%) 31 (39.7%) 13.19 (3.84) [13]
55-64 166 (36.9%) 116 (69.9%) 50 (30.1%) 12.40 (3.83) [13]
≥65 195 (43.3%) 130 (66.7%) 65 (33.3%) 12.41 (4.31) [12]
Gender* 0.424 0.327
Male 231 (51.3%) 150 (64.9%) 81 (35.1%) 12.75 (3.94) [13]
Female 219 (48.7%) 150 (68.5%) 69 (31.5%) 12.34 (4.17) [12]
Race** 0.075 0.068
Malay 127 (28.2%) 75 (59.1%) 52 (40.9%) 13.17 (3.94) [13]
Chinese 204 (45.3%) 139 (68.1%) 65 (31.9%) 12.17 (4.35) [12]
Indian 119 (26.4%) 86 (72.3%) 33 (27.7%) 12.55 (3.58 [12]
Educational levels* 0.000a 0.000a
<12 years 285 (63.3%) 215 (75.4%) 70 (24.6%) 11.76 (3.99) [12]
≥ 12 years 165 (36.7%) 85 (51.5%) 80 (48.5%) 13.93 (3.80) [14]
Marital Status* 0.713 0.747
Single 70 (15.6%) 48 (68.6%) 22 (31.4%) 12.69 (3.29) [12]
Not single 380 (84.4%) 252 (66.3%) 128 (33.7%) 12.53 (4.18) [13]
Monthly income* 0.000a 0.000a
Less than RM 2000 330 (73.3%) 242 (73.3%) 88 (26.7%) 12.02 (3.81) [12]
More than RM 2000 120 (26.7%) 58 (48.3%) 62 (51.7%) 14.03 (4.35) [15]
Menopausal status (N=219)* 0.331 0.737
Premenopausal 25 (11.4%) 15 (60.0%) 10 (40.0%) 12.56 (4.29) [13]
Postmenopausal 194 (88.6%) 135 (69.6%) 59 (30.4%) 12.31 (4.17) [12]
Employment status* 0.069 0.022a
Working 192 (42.7%) 119 (62.0%) 73 (38.0%) 13.10 (3.99) [13]
Not working 258 (57.3%) 181 (70.2%) 77 (29.8%) 12.14 (4.06) [12]
Family history of osteoporosis* 0.274 0.136
No 392 (87.1%) 265 (67.60%) 127 (32.4%) 12.45 (4.09) [12]
Yes 58 (12.9%) 35 (60.30%) 23 (39.7%) 13.24 (3.79) [13]
Family history of fracture* 0.004a 0.007a
No 359 (79.8%) 251 (69.90%) 108 (30.1%) 12.28 (4.17) [12]
Yes 91 (20.2%) 49 (53.80%) 42 (46.2%) 13.63 (3.39) [13]
Smoking habit* 0.124 0.028a
Not smoking 318 (70.7%) 219 (68.9%) 99 (31.1%) 12.24 (4.17) [12]
Smoking 132 (29.3%) 81 (61.4%) 51 (38.6%) 13.30 (3.66) [13]
Alcohol habit* 0.033a 0.005a
Non alcoholic 356 (79.1%) 246 (69.1%) 110 (30.9%) 12.28 (4.16) [12]
Alcoholic 94 (20.9%) 54 (57.4%) 40 (42.6%) 13.60 (3.47) [13]
BMI (Kg/m2)* 0.374 0.349
Non-obese (BMI ≤23 kg/m2) 98 (21.8%) 69 (70.4%) 29 (29.6%) 12.32 (4.09) [12]
Obese (BMI >23kg/m2) 352 (78.2%) 231 (65.6%) 121 (34.4%) 12.62 (4.05) [13]

Association, Chi-square test,



*Mann-Whitney U test;

**Kruskal-Wallis test;ap< 0.05

BMI: Body mass index; SD: standard deviation

The mean duration of diabetes of the sample population was 8.65 (SD 5.97) years (range 3-32 years). In addition, more than three quarters (343, 76.20%) of patients had poor glycaemic control, as shown in Table 2In addition, more than 50% of the patients had poor cholesterol levels, poor LDLC levels and poor control of their systolic blood pressure, as shown in Table 3

Table 2. Relationships between osteoporosis knowledge levels and diabetes-related variables (N=450) 

Variable N (%) Osteoporosis knowledge level N (%) p OKT-M scores Mean (SD) [Median] p
Low OKT level 300 (66.7%) High OKT level 150 (33.3%)
Diabetes duration (years)** 0.622 0.473
< 5 175 (38.9%) 111 (63.40%) 64 (36.6%) 12.70 (4.03) [13]
5 - 9 125 (27.8%) 85 (68.0%) 40 (32.0%) 12.68 (3.95) [13]
10 - 14 89 (19.8%) 60 (67.4%) 29 (32.6%) 12.58 (4.31) [12]
≥ 15 61 (13.6%) 44 (72.1%) 17 (27.9%) 11.84 (3.98) [12]
Therapy type* 0.093 0.003a
Mono therapy 115 (25.6%) 84 (73.0%) 31 (27.0%) 11.63 (4.32) [11.00]
Combined therapy 335 (74.4%) 216 (64.5%) 119 (35.5%) 12.87 (3.92) [13]
Insulin use* 0.190 0.035a
With insulin 67 (14.9%) 40 (59.7%) 27 (40.3%) 13.48 (3.93) [13]
Without insulin 383 (85.1%) 260 (67.9%) 123 (32.1%) 12.39 (4.06) [12]
Diabetic complication (DC)* 0.175 0.614
Positive (with DC) 330 (73.3%) 226 (68.5%) 104 (31.5%) 12.50 (3.99) [12]
Negative (without DC) 120 (26.7%) 74 (61.7%) 46 (38.3%) 12.69 (4.23) [13]
Co-morbidities* 0.656 0.704
Positive (with Co-morbidities) 426 (94.7%) 285 (66.9%) 141 (33.1%) 12.54 (4.09) [12]
Negative (without Co-morbidities) 24 (5.3%) 15 (62.5%) 9 (37.5%) 12.71 (3.26) [13]
Glycaemic control (HbA1c)* 0.938 0.801
Good HbA1c (< 6.5) 107 (23.8%) 71 (66.4%) 36 (33.6%) 12.37 (3.81) [13]
Poor HbA1c (≥ 6.5) 343 (76.2%) 229 (66.8%) 114 (33.2%) 12.61 (4.13) [12]

Association, Chi-square test,


‡ Difference,

*Mann-Whitney U test,

**Kruskal-Wallis test,

Table 3. Frequency and percent of lipid profile and blood pressure groups among the studied population (N=450) 

Variable Mean (SD) [Median] N (%) OKT-M score Mean (SD) [Median] p-value
TC 5.25 (0.91) [5.23] 0.439
Good < 5.2 mmol/L 216 (48.0%) 12.41(4.27) [12]
Poor ≥ 5.2 mmol/L 234 (52.0%) 12.68(3.86) [13]
HDLC 1.19 (0.27) [1.13] 0.219
Good ≥ 1.1 mmol/L 272 (60.4%) 12.40 (4.01) [12]
Poor < 1.1 mmol/L 178 (39.6%) 12.78 (4.12) [13]
LDL C 3.06 (0.77) [3.0] 0.614
Good ≤ 2.6 mmol/L 133 (29.6%) 12.70(4.29) [13]
Poor > 2.6 mmol/L 317 (70.4%) 12.49(3.96) [12]
TG 1.77 (1.06) [1.57] 0.347
Good ≤ 1.7 mmol/L 277 (61.6%) 12.68(3.96) [13]
Poor > 1.7 mmol/L 173 (38.4%) 12.35(4.20) [12]
SBP 136.48 (8.46) [136.67] 0.283
Good ≤ 130 mmHg 125 (27.8%) 12.82(3.97) [13]
Poor > 130 mmHg 325 (72.2%) 12.45(4.08) [12]
DBP 81.78 (4.88) [80.0] 0.026a
Good ≤ 80 mmHg 231 (51.3%) 12.13(3.97) [12]
Poor > 80 mmHg 219 (48.7%) 13.00(4.09) [13]

Mann-Whitney U test,


TC, total cholesterol; HDLC, high density lipoprotein cholesterol; LDLC, low density lipoprotein cholesterol, TG, triglyceride; SBP, systolic blood pressure; DBP, diastolic blood pressure

The average OKT-M total score, OKT-M Exercise subscale and OKT-M Calcium subscale were 12.55 (SD 4.06), 8.60 (SD 2.89) and 8.40 (SD 3.36) with correct percentages responses of 52.31%, 53.78% and 49.38%, respectively. Only 33.30% (17; SD 2.01 (16)) of the T2DM patients were found to have high level of OKT-M according to the cut-off point value.

In this study, most participants knew that “eating a diet low in milk products increases the chances of getting osteoporosis” (item one) with 60.40% answering correctly. On the other hand, the OKT-M showed that there were low items scores for: item three “Having big bones decrease your chance of getting osteoporosis”, item six “Being a woman of Asian origin increases your chances of getting osteoporosis” and item seven “Having ovaries surgically removed increases your chances of getting osteoporosis” with 22.40%, 45.80% and 34.90% correct answers, respectively. About 54.90% of participants identified that “being menopausal increases the chances of getting osteoporosis” (item two).

The participants (56.40%) recognized that “a diet high in green vegetables can help reduce the chances of getting osteoporosis” (item four). Furthermore, there was a lack of identification and recognition of the family history of osteoporosis as risk factors for developing osteoporosis with 52.9% correct answers to item five. Similarly, only 39.6% of T2DM were able to recognise that taking cortisone for a long time (item eight) is consider as a risk factor for developing osteoporosis. On the other hand, the most correct answer that assesses the knowledge of risk factors towards osteoporosis was item nine, where 77.3% of participants knew that “regular exercise can help decrease the chances of getting osteoporosis”.

T2DM patients showed a varied answer regarding knowledge of exercise toward osteoporosis. Most of the patients identified that running or jogging (item 15) and aerobic dancing (item 16) were the best way to lessen the risk of developing osteoporosis with 70.9% and 66.0%, respectively. However, the response of the participants regarding the other effective way of weight-bearing exercise were low with only 49.6% and 53.8% recognised that walking briskly (item 10) and bicycling (item 11), respectively.

As well as, more than three quarters of T2DM patients (81.8%, item 12) identified that three or more days a week of exercise is required to strengthen bones and more than half of the patients (60.7%, item 13) knew that 20-30 minutes/day should be enough to prevent osteoporosis. In contrast, less than half of the participants (33.1%, item 14) distinguished that breathing should be “much faster, but talking is possible during exercise”.

Only 10.2% of participants responded correctly toward the recommended daily calcium intake for adults (item 22). In addition, only 56.2% of the patients responded correctly toward the number of daily servings of milk (item 23). Moreover, most of the patients correctly recognised yoghurt (71.8%) and cheese (64.7%) as good sources of calcium food (items 20 and 17, respectively). In this study, the patients were correctly recognised the classic calcium sources; but, they were not able to identified canned sardine (54.0%), broccoli (51.8%) and ice cream (29.3%) as alternative sources of calcium (items 18, 19 and 21, respectively). Finally, about 56.90% of participants correctly identified the best reason for taking a calcium supplement (item 24, if a person does not get enough calcium from diet).

There were significant associations between OKT-M levels and education groups, monthly income, family history of fracture and alcoholic habit (p<0.05, Table 1).

Furthermore, significant differences in the OKT-M scores were found between the education groups, monthly income, employment status, family fracture history, smoking and alcohol habit (p<0.05, Table 1).

Moreover, the Spearman’s correlation coefficient result between the OKT-M total scores and BMI of the patients was found to be low but significant (n=450, rs=0.13, p<0.05). However, insignificant negative correlation was found between OKT-M total score and age (n=450, r= -0.06, p>0.05).

An insignificant association between the two levels of OKT-M and the diabetes-related variables was found. In addition, significant differences in OKT-M scores were found among insulin use and therapy type (p<0.05) (Table 2). Moreover, an insignificant correlations were found between OKT-M score and diabetes duration in years (n=450, rs= -0.075, p=0.11) and HbA1c (n=450, rs= -0.055, p=0.24). Moreover, a significant difference (p<0.05, Table 3) and correlation (n=450, rs=0.103, p=0.028) were found between the OKT-M scores and diastolic blood pressure (DBP). However, there were insignificant correlations and differences between any of the other collected laboratory values and OKT-M (p>0.05) (Table 3).

The osteoporotic conditions results of the sample population were previously reported.12In brief, the average T-score value for the patients was (-1.67; SD 0.83) with (median: -1.65), (range: -3.4 to 1.2) and (CI 95%: -1.75 to -1.59)). The average T-score values of osteoporotic, osteopenic and normal BMD patients’ were (-2.76; SD 0.27), (-1.65; SD 0.39) and (-0.41; SD 0.44), respectively. According to QUS measurements, the prevalence of normal BMD (T-scores greater than -1 SD) in this sample population was 18% (n=81), while the prevalence of osteopenia (T-scores between -1 and -2.5 SD) and osteoporosis (T-scores less than -2.5 SD) were considered as 59.8% (n=269) and 22.2% (n=100), respectively.

In this study, significant and positive correlations were found between T-scores and OKT-M total score (n=450, rs=0.244, p<0.001), OKT-M Exercise subscale (n=450, rs=0.219, p<0.001) and OKT-M Calcium subscale (n=450, rs=0.199, p<0.001) among T2DM patients (all p-values<0.05). In short, as osteoporosis knowledge increased, the T-scores increased.


Osteoporosis is a significant health problem and poor OKT-M level is a problem requiring urgent attention. This study showed low level of knowledge regarding osteoporosis which consistent with other research.19On the other hand, other studies showed that there were high levels of osteoporosis knowledge in their population sample, which was dissimilar to the current observations.20 21-22

Within this sample of T2DM, less than 70% of patients identified that a food low in green leafy vegetables and dairy products increase the chances of getting osteoporosis. In contrast, other studies showed that more than 70% of their participants identified these risk factors.20,23Moreover, the patients’ knowledge regarding regular physical activity to prevent osteoporosis was good which consistent with other studies.13,23In contrast, other studies showed low level of knowledge toward exercise.24,25The knowledge of genetic risk factors of osteoporosis in T2DM was less convincing which consistent with other studies.23,26In contrast, other studies revealed that participants were able to recognise these predisposed risk factors to OP.13,23The knowledge regarding changes in life, like being menopausal or having ovaries surgically removed was also low. Similarly, other study showed inadequate knowledge regarding these risk factors.13On the other hand, other studies showed that more than three quarters of women knew the risks associated with menopausal status.20,23The knowledge about the risk of taking cortisone was inadequately recognised which consistent with other study.27In contrast, other studies demonstrated that more than half of the participants were able to recognise this risk factor.20,23

More than 50% of T2DM patients gave the correct answer about the best types of exercise for bone health. Similar results were found in other studies.13,23However, less than half of T2DM patients knew that walking briskly is good for bone health which was inconsistent with the other studies.23,28A systematic review study demonstrated that most of the participants were able to recognise the recommended level with the duration of exercise which was comparable to this study results.29In contrast, other study had shown inadequate knowledge regarding exercise intensity.28

The participants could identify dairy sources which was consistent with other studies.13,23However, non-dairy food sources were less well-known which was similar to other findings.13,23It was surprisingly that only 29.3% of T2DM patients recognised that the ice cream is a calcium dietary products which was inconsistent with other studies.13,23It was possible that those patients perceived other ‘healthier’ foods compared to ice cream from diabetic point of view.

In addition, most participants incorrectly identified the recommended amount of calcium intake which was similar to other studies.13,23

The results of this study showed insignificant differences and an association between the OKT-M level and patients’ age which were consistent with the previous study.30 In contrast, other studies reported positive or negative correlations between osteoporosis knowledge and age.23,31It was difficult to explain these distinct differences between the results due to the differences in the study design and instruments used to assess the level of osteoporosis knowledge.

There was an insignificant association and difference between OKT-M level and gender which was similar to other report.32On the other hand, other studies demonstrated that women had significantly greater osteoporosis knowledge than men.33,34These results were not surprising, as most of the research studies, advertising and public educational programmes focus on osteoporosis in women.

The results indicated that T2DM patients with higher education levels have significantly better knowledge of osteoporosis which was similar to other study.35In contrast, study at the community level had shown that educational level was not correlated with osteoporosis knowledge.36The reason behind this variation may be attributed to the differences in the cultural backgrounds, level of education, sample size and the types of questions.

A significant differences between OKT-M levels with monthly income and employment status were found which were consistent with other studies.36,37This can be explained by the fact that higher incomes enable the individuals to improve their health behaviours. Higher socioeconomic status is known to be associated with better access to healthcare services, healthier lifestyle choices and more easily accessible sports centres.38

The results showed a higher level of OKT-M among T2DM patients with a family fracture history. The interpretation of these results should be made with caution as only a 20.2% of the patients had a family fracture history. Moreover, insignificant relationship and difference were found between family history of osteoporosis and OKT-M level which may be due to the fact that only 12.9% of the participants had a family history of osteoporosis. Similar results was found in another study.39

The present study showed diabetic patients who were alcoholic or smokers were found to be more knowledgeable about osteoporosis which was dissimilar to other result.40Other study showed that adolescent males scored higher healthy behaviours in avoiding harmful behaviours.41However, this may be due to healthcare professionals informing them about the risk factors of these habits on bone health and general health, as well as, diabetic disease.

There were no previous studies addressing the relation between OKT-M and diabetes-related variables. Nevertheless, indirect relations may explain the results. Other studies among T2DM patients showed that poor glycaemic control, long duration of diabetes and treatment type seem to play a key role in decreasing or increase bone mass.10,12There was only a significant association and difference in OKT-M score with diastolic blood pressure groups (DBP). A study had proposed a positive relationship between BMD and the presence of hypertension.42Furthermore, the cardiovascular risk factors did not appear to influence the BMD among T2DM patients which consistent with other study.43

The results showed significant positive correlations between T-scores and both OKT-M and subscales among T2DM patients which consistent with other studies.26,44Thus, educational programmes regarding factors such as knowledge, health beliefs, and self-efficacy are of particular importance for integral aspects of health promotion interventions to improve bone health.14,45 46 47 48 49-50


As it is not a randomised control study and only targeted outpatients with T2DM in Penang, the results cannot be generlised. Moreover, the final results may be influenced by unequal numbers of gender, ethnic or age groups.


A low level of osteoporosis knowledge was apparently high regarding some specific elements like risk factors, dietary calcium intake and physical activity. Overall, the present study findings emphasises that there was a significant gap in T2DM patients understanding of osteoporosis and healthy lifestyle behavior. Moreover, the current results discovered the areas of a particular concern for further research to give an additional comprehensive approach to improve the awareness toward osteoporosis. The results of this study are crucial to improve the osteoporosis preventive strategy for high risk populations by developing an effective health educational programme.


1 Zimmet P, Alberti K, Shaw J. Global and societal implications of the diabetes epidemic. Nature. 2001;414(6865):782-787. [ Links ]

2 Roglic G, Unwin N, Bennett PH, Mathers C, Tuomilehto J, Nag S, Connolly V, King H. The burden of mortality attributable to diabetes. Diabetes Care. 2005;28(9):2130-2135. [ Links ]

3 Rashid AR. Suboptimal treatment in chronic diseases–time to go back to basics. Med J Malaysia. 2008;63(3):185-187. [ Links ]

4 Letchuman G, Wan Nazaimoon W, Wan Mohamad W, Chandran L, Tee G, Jamaiyah H, Isa M, Zanariah H, Fatanah I, Ahmad Faudzi Y. Prevalence of Diabetes in the Malaysian National Health Morbidity Survey III 2006. Med J Malaysia. 2010;65(3):180-186. [ Links ]

5 Mafauzy M. Diabetes mellitus in Malaysia. Med J Malaysia. 2006;61(4):397-398. [ Links ]

6 Kamarul Imran M, Ismail AA, Naing L, Wan Mohamad WB. Type 2 diabetes mellitus patients with poor glycaemic control have lower quality of life scores as measured by the Short Form-36. Singapore Med J. 2010;51(2):157-162. [ Links ]

7 Horan A, Timmins F. The role of community multidisciplinary teams in osteoporosis treatment and prevention. J Orthop Nurs. 2009;13(2):85-96. [ Links ]

8 Burge R, Dawson-Hughes B, Solomon DH, Wong JB, King A, Tosteson A. Incidence and economic burden of osteoporosis-related fractures in the United States, 2005–2025. J Bone Miner Res. 2007;22(3):465-475. [ Links ]

9 Nguyen ND, Ahlborg HG, Center JR, Eisman JA, Nguyen TV. Residual lifetime risk of fractures in women and men. J Bone Miner Res. 2007;22(6):781-788. [ Links ]

10 Abdulameer SA, Syed Sulaiman SA, Hassali MA, Subramaniam K, Sahib MN. Osteoporosis and type 2 diabetes mellitus: what do we know, and what we can do? Patient Prefer Adherence. 2012;6:435-448. [ Links ]

11 Tung WC. Osteoporosis among Asian American women. Home Health Care Manag Pract. 2012;24(4):205-207. [ Links ]

12 Abdulameer SA, Sahib MN, Sulaiman SAS. The Prevalence of Osteopenia and Osteoporosis Among Malaysian Type 2 Diabetic Patients Using Quantitative Ultrasound Densitometer. Open Rheumatol J. 2018;12:50-64. [ Links ]

13 Edmonds E, Turner LW, Usdan SL. Osteoporosis knowledge, beliefs, and calcium intake of college students: Utilization of the health belief model. Open J Prev Med. 2012;2(1):27-34. [ Links ]

14 Abdulameer SA, Sahib MN. Cross-Cultural adaptation and psychometric properties of Osteoporosis Knowledge Tool-Arabic version among Iraqi population. Open Rheumatol J. 2019;13(1):30-38. [ Links ]

15 Zanariah H, Chandran LR, Wan Mohamad WB, Wan Nazaimoon WM, Letchuman GR, Jamaiyah H, Fatanah I, Nurain MN, Helen Tee GH, Mohd Rodi I. Prevalence of diabetes mellitus in Malaysia in 2006-results of the 3rd National Health and Morbidity Survey (NHMS III). Diabetes Res Clin Pract. 2008;79:21-29. [ Links ]

16 Ministry of Health Malaysia. Clinical Practice Guidelines: Management of type 2 diabetes mellitus. Available from World Wide Web: (accessed Jan 20, 2012). [ Links ]

17 Abdulameer SA, Syed Sulaiman SA, Hassali MA, Subramaniam K, Sahib MN. Psychometric Properties of Osteoporosis Knowledge Tool and Self-Management Behaviours Among Malaysian Type 2 Diabetic Patients. J Community Health. 2013;38(1):95-105. [ Links ]

18 Kanis J. Assessment of fracture risk and its application to screening for postmenopausal osteoporosis: synopsis of a WHO report. Osteoporos Int. 1994;4(6):368-381. [ Links ]

19 Osman AA. Assessment of Osteoporosis KAP among women in Assir region, Saudi Arabia. J Med Med Sci. 2013;4(2):50-55. [ Links ]

20 Ziccardi SL, Sedlak CA, Doheny MO. Knowledge and health beliefs of osteoporosis in college nursing students. Orthop Nurs. 2004;23(2):128-133. [ Links ]

21 Zhang RF, Chandran M. Knowledge of osteoporosis and its related risk factors among nursing professionals. Singapore Med J. 2011;52(3):158-162. [ Links ]

22 Moodley LM, Rambiritch V. An assessment of the level of knowledge of diabetic patients, in a primary health care setting, on diabetes mellitus. S Afr Fam Pract. 2007;49(10):6-16. [ Links ]

23 Von Hurst PR, Wham CA. Attitudes and knowledge about osteoporosis risk prevention: a survey of New Zealand women. Public Health Nutr. 2007;10(7):747-753. [ Links ]

24 Orces CH, Casas C, Lee S, Garcia-Cavazos R, White W. Determinants of osteoporosis prevention in low-income Mexican-American women. South Med J. 2003;96(5):458-464. [ Links ]

25 Cinda A, Sava S. What do men who are at risk of osteoporosis know about osteoporosis in developing countries? Scand J Caring Sci. 2004;18(2):188-192. [ Links ]

26 Chang S, Yang R, Chung U, Chen C, Cheng M. Perception of risk factors and DXA T score among at risk females of osteoporosis. J Clin Nurs. 2010;19(13-14):1795-1802. [ Links ]

27 Satterfield T, Johnson SM, Slovic P, Neil N, Schein JR. Perceived risks and reported behaviors associated with osteoporosis and its treatment. Women Health. 2000;31(4):21-40. [ Links ]

28 Matthews HL, Laya M, DeWitt DE. Rural women and osteoporosis: awareness and educational needs. J Rural Health. 2006;22(3):279-283. [ Links ]

29 Asikainen T, Kukkonen-Harjula K, Miilunpalo S. Exercise for health for early postmenopausal women: a systematic review of randomised controlled trials. Sports Med. 2004;34(11):753-778. [ Links ]

30 Pande K, Pande S, Tripathi S, Kanoi R, Thakur A, Patle S. Poor knowledge about osteoporosis in learned Indian women. J Assoc Physicians India. 2005;53:433-436. [ Links ]

31 Miura S, Yagi M, Saavedra OL, Yamamoto S. Sociodemographic Variation in Knowledge of Osteoporosis and Locally Available Calcium-Rich Foods Among Urban Women Living on Low Incomes in Davao, Philippines. Health Care Women Int. 2010;31(5):387-401. [ Links ]

32 Carlsson L, Johnson C. Osteoporosis Health Beliefs and Practices Among Korean Immigrants in Nova Scotia J Immigr Health. 2004;6(2):93-100. [ Links ]

33 Johnson CS, McLeod W, Kennedy L, McLeod K. Osteoporosis health beliefs among younger and older men and women. Health Educ Behav. 2008;35(5):721-733. [ Links ]

34 Yeap SS, Goh EM, Das Gupta E. Knowledge about osteoporosis in a Malaysian population. Asia Pac J Public Health. 2010;22(2):233-241. [ Links ]

35 Rafraf M, Bazyun B, Afsharnia F. Osteoporosis-related life habits and knowledge about osteoporosis among women in Tabriz, Iran. Iran Med J. 2009;8(2):17-20. [ Links ]

36 Riaz M, Abid N, Patel J, Tariq M, Khan MS, Zuberi L. Knowledge about Osteoporosis among healthy women attending a tertiary care hospital. J Pak Med Assoc. 2008;58(4):190-194. [ Links ]

37 Zaini WM, Md Ariff A. Bone Mineral Density Assessment in Pre- and Postmenopausal Women: Comparison Between T-Scores by Heel QUS and DXA in HRPZII. Med J Malaysia. 2012;67(5):487-490. [ Links ]

38 Kim S, Symons M, Popkin BM. Contrasting socioeconomic profiles related to healthier lifestyles in China and the United States. Am J Epidemiol. 2004;159(2):184-191. [ Links ]

39 Liza H, Darat HN, Pande KC. Knowledge about osteoporosis in Bruneian women attending an orthopaedic clinic. Malays Orthop J. 2009;3(1):28-31. [ Links ]

40 Shin H-Y, Kang HC, Lee K, Park SM. Association between the awareness of osteoporosis and the quality of care for bone health among Korean women with osteoporosis. BMC Musculoskelet Disord. 2014;15:334. [ Links ]

41 Chen S-W, Yang S-C, Wang R-H, Lin ML. Osteoporosis prevention behaviors practiced among youth in Taichung City, Taiwan. Am J Health Behav. 2012;36(6):736-745. [ Links ]

42 Olmos JM, Hernandez JL, Martínez J, Castillo J, Valero C, Perez Pajares I, Nan D, Gonzalez-Macías J. Bone turnover markers and bone mineral density in hypertensive postmenopausal women on treatment. Maturitas. 2010;65(4):396-402. [ Links ]

43 Broussard DL, Magnus JH. Influence of cardiovascular disease risk factors on the relationship between low bone mineral density and type 2 diabetes mellitus in a multiethnic US population of women and men: a cross-sectional study. Gend Med. 2008;5(3):229-238. [ Links ]

44 Chang SF. Explore the effectors of bone mineral density in community women. J Nurs Res. 2004;12(4):327-336. [ Links ]

45 Bandura A. Self-efficacy: toward a unifying theory of behavioral change. Psychol Rev. 1977;84(2):191-215. [ Links ]

46 Abdulameer SA, Syed Sulaiman SA, Hassali MA, Subramaniam K, Sahib MN. Psychometric properties and osteoprotective behaviors among type 2 diabetic patients: osteoporosis self-efficacy scale Malay version (OSES-M). Osteoporos Int. 2013;24(3):929-940. [ Links ]

47 Abdulameer SA, Syed Sulaiman SA, Hassali MA, Sahib MN, Subramaniam K. Psychometric properties of the Malay version of the Osteoporosis Health Belief Scale (OHBS-M) among Type 2 diabetic patients. Int J Rheum Dis. 2014;17(1):93-105. [ Links ]

48 Sahib MN. Validation and Assessment of Osteoporosis Self-Efficacy Among Iraqi General Population. Open Nurs J. 2018;12:76-85. [ Links ]

49 Sahib MN. Psychometric properties and assessment of the Osteoporosis Health Belief Scale among the general Arabic population. Patient Prefer Adherence. 2018;12:223-232. [ Links ]

50 Doheny MO, Sedlak CA, Estok PJ, Zeller RA. Bone density, health beliefs, and osteoporosis preventing behaviors in men. Orthop Nurs. 2011;30(4):266-272. [ Links ]

FUNDING: The author, SA Abdulameer gratefully acknowledges the Universiti Sains Malaysia, Penang, Malaysia, for granting her the USM Postgraduate Student Fellowship.

Received: July 24, 2019; Accepted: December 01, 2019; pub: December 13, 2019


The authors have no conflicts of interest or financial interests in any product or service mentioned in the article to report.

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