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Research Article | DOI: https://doi.org/10.31579/2693-4779/225
1MBBS, MRCP (UK), MD Internal Medicine, Sudan Medical Specialization Board.
2MBBS, MRCP (UK), FRCP (EDIN & LONDON), Consultant Physician & Endocrinologist, Ribat University Hospital.
3MBBS, Sudan International University.
4MBBS, Elrazi University.
5Administration and research, Elmalik Academy of Medical Research, Khartoum, Sudan.
*Corresponding Author: Abrar Bakry Malik Nawwai, Administration and research, Elmalik Academy of Medical Research, Khartoum, Sudan.
Citation: Misk Mohamed Elsheikh Osman , Hisham Mohamed Abdelrahim, Mohmed Aatif Mohamed Nogdalla, Omer Mohamed Elsheikh Osman , Mohamed Eltayieb Elawad , Abrar Bakry Malik, (2024), Health-related Quality of Life among Patients with Type II Diabetes Mellitus, Clinical Research and Clinical Trials, 10(5); DOI:10.31579/2693-4779/225
Copyright: © 2024, Abrar Bakry Malik Nawwai. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Received: 12 August 2024 | Accepted: 28 August 2024 | Published: 25 September 2024
Keywords: health-related quality of life; type II DM; quality of life
Background: Diabetes mellitus is a chronic disease that causes considerable morbidity and mortality worldwide, resulting in an impaired quality of life in affected people.
Aim: To assess health-related quality of life among patients with type II diabetes mellitus and its associated factors.
Methods: A cross-sectional study design was conducted from January to July 2022 at Ribat University Hospital in Khartoum and Abdallah Khalil Diabetic Centre in Omdurman. A total of 400 patients with type II diabetes who visited the referred clinics were enrolled in the study. Data was collected by face-to-face interview using the revised Diabetes Quality of Life instrument to assess the health-related quality of life. Data was analyzed using SPSS version 23.0 and summarized using tables and charts. The association between health-related quality of life and sociodemographic characteristics, clinical factors and lifestyle factors was obtained using chi-square test.
Results: The mean score for overall health-related quality of life was 29.3 ± 11.5 while each domain of “satisfaction”, “impact” and “worry” had mean scores of 13.7 ± 4.9, 8.5 ± 4.4 and 7.1 ± 3.7, respectively. Since the scores obtained were only approximately half of the possible range of scores for quality of life, the overall health-related quality of life is considered to be moderate. This study also revealed that 40% of the participants have poor health-related quality of life. The relationship between HbA1c level & health-related quality of life was statistically significant (P value = 0.044) in which high glycosylated hemoglobin levels was associated with poor quality of life. Gender, age, education level, marital status, duration of diabetes and the presence of comorbidities and complications had statistically significant association with health-related quality of life.
Conclusion: This study demonstrates a moderate overall health-related quality of life among patients with T2DM. Besides, it also demonstrates a low quality of life among 40% of patients with T2D, suggesting that quality of life should be included in any modality used for treating diabetic patients.
The World Health Organization (WHO) defines health as a state of complete physical, mental, and social well-being (1). This definition has served as the foundation for the development of multiple definitions of health-related quality of life (HRQOL), as well as measures to assess it. According to United States Centers for Disease Control and Prevention (CDC), quality of life (QOL) is a multidimensional concept that includes evaluations of both positive and negative aspects of a person’s life. Since the 1980s, the term health-related quality of life has comprised those aspects of QOL that can be shown to affect physical or mental health (2). On the individual level, HRQOL includes physical and mental health perceptions including health risks and conditions, functional status, social support, and socioeconomic status. On the community level, HRQOL includes community-level resources, conditions, policies, and practices that influence a population’s health perceptions and functional status. On the basis of a synthesis of the scientific literature and advice from its public health partners, CDC has defined HRQOL as “an individual’s or group’s perceived physical and mental health over time” (3). Another definition by the WHO is that HRQOL refers to “the physical, psychological, and social domains of health that are influenced by a person’s experiences, beliefs, expectations, and perceptions” (4). The issue of HRQOL is particularly important for diseases such as diabetes, for which the health care regimen requires ongoing self-care behaviors that can interfere with patients’ desired lifestyles; therefore, healthcare providers should strive to understand the physical, emotional, and social impact of chronic diseases such as diabetes.
Diabetes is a chronic disease that occurs either when the pancreas fails to produce enough insulin or when the body cannot effectively utilize the insulin it produces. It is a major cause of blindness, kidney failure, heart attacks, stroke and lower limb amputation (4). Diabetes mellitus and its complications have contributed tremendously to the burden of mortality and disability worldwide (4). The prevalence of this debilitating illness has increased dramatically in all parts of the world. The number of people with diabetes has raised from 108 million in 1980 to 422 million in 2014 (5). The prevalence has been rising more rapidly in low- and middle-income countries than in high-income countries (4). Globally, the number of patients with diabetes is expected to rise to 643 million by 2030 and 783 million by 2045. Indeed, the prevalence of diabetes in adults aged 18–99 years was estimated to be 8.4% in 2017 and predicted to rise to 9.9% in 2045 (6). The Middle East and North Africa (MENA) region has the highest regional prevalence of 16.2% and the second highest expected increase (86%) in the number of people with diabetes reaching 136 million by 2045 (7).
Based on the International Diabetes Federation's (IDF) diabetes atlas published in 2019, Sudan is included among countries with a diabetes prevalence of more than 12% (7). This is consistent with a recent study from Sudan that documented the prevalence to be around 20.8% (8).
Since diabetes is a chronic illness, therefore there is a need for assessing the HRQOL of patients at regular intervals. The complications of diabetes affect the organ system and are responsible for the majority of morbidity and mortality associated with the disease (9). The HRQOL is very important because it is a powerful tool to predict an individual’s capacity to manage the disease and maintain long-term health and wellbeing (10). The routine assessment of QOL as part of clinical practice can improve communication between patients and health care providers, identify frequently overlooked problems, assess them, and evaluate the effectiveness of the therapeutic efforts (11).
In spite of the fact that HRQOL is an important input for decision makers and policymakers and also for the development of guidelines, Sudan remains with scanty comprehensive studies about HRQOL in diabetics; a situation that will undermine the management of diabetes. In other words, it is questionable whether the factors associated with HRQOL of diabetic patients in the other studies apply to the patients in Sudan. These studies however provide a basis for obtaining an understanding of the factors associated with HRQOL of diabetic patients in the country. Particularly, this study seeks to establish how the factors in the literature related to diabetic patients in the Sudan.
A cross-sectional, descriptive, observational study design was conducted between January _ July 2022. The study was carried out at two diabetic clinics in Khartoum state: one in Ribat University Hospital in Khartoum and the other in Abdalla Khalil Diabetic Centre in Omdurman. The patients were recruited from the referred clinics. All male & female patients with type II diabetes mellitus on follow-up fulfilling the eligibility criteria were included in the study. The inclusion criteria were male & female patients with type II diabetes aged 40 years and above, and patients diagnosed for more than a year. The exclusion criteria were being pregnant, patients with cognitive impairment, patients with co-morbid conditions not directly related to diabetes, and patients with severe illness.
Sample size was calculated using a single population proportion formula assuming proportion of HRQOL among type 2 DM patients 50%, 5% margin of error (ε) and 95% (zα/2 = 1.96) and thus, the final sample size was calculated to be 385. The 50% was purposively selected so that it provided the largest minimum sample size. After adjusting for non-response, the sample size was calculated to be 400.
All diabetic patients who came to the hospitals were recruited consecutively until the minimum required sample size was reached. Proportional allocation was used to decide the number of participants from each hospital.
Data collection and questionnaire were carried out through face-to-face interviews with the patients after obtaining informed consent. The participants were interviewed in Arabic at the referred clinics. During the interview patients were asked about socio-demographic data (age, sex, marital status, educational level, occupation), clinical data (duration of diabetes, type of diabetes, type of treatment, diabetes-related complications, co-morbidities & HbA1c level) and lifestyle measures (diet control, smoking, alcohol consumption, foot care). HbA1c result within the last 6 months was recorded from the patients’ follow up cards. Glycaemic control was defined in accordance with the specifications of the ADA for non-pregnant adults and the IDF as follows: Good glycaemic control was determined when the HbA1c target was < 7>
The dependent variable was Overall HRQOL score, and the independent variables were socio-demographics (age, sex, marital status, educational level, occupation), clinical data (duration of diabetes, type of diabetes, type of treatment, HbA1c, diabetes-related complications and co-morbidities), and lifestyle measures (diet control, smoking, alcohol consumption, foot care).
Data was entered in Excel sheet then exported to SPSS version 23.0. Descriptive statistics was done for all variables then summarized by percentages for categorical variables and mean and standard deviation (SD) for scale variables then presented into tables and diagrams as appropriate. The data obtained on Likert scale were analysed by presenting each domain in a custom table, the sum score for each domain and the overall score was calculated and summarized by mean and SD and the minimum and maximum scores were documented as well. The outcome variable was binary. The overall DQOL was indicated as ‘low/poor quality of life’ (DQOL score> population mean) or ‘good quality of life (total DQOL score < population> population mean), high diabetes impact (impact score> population mean), and high diabetes worry (worry score> population mean). The association between DQOL and sociodemographic characteristics, clinical factors and lifestyle factors was obtained using chi-square test. For each test, a p-value of less than 0.05 was considered statistically significant. The scale variable was tested by independent t-test and again a p-value of less than 0.05 was considered statistically significant.
Regarding the ethical consideration, the written ethical clearance and approval for conducting this research was obtained from Sudan Medical Specialization Board Ethical Committee & Education & Development center. Written permission was obtained from the Ministry of Health & the administrative authority of each hospital included in the study. Written informed consent was obtained from all study participants before being involved in the study. Data collected was used for research purposes only and confidentiality issues were considered by using a serial number to identify participants.
The mean age of the participants was 58.4 ± 8.6. More than half of the participants were male (60%). The majority received formal education, however, only 6.3% were university graduates. Almost half of them were on oral drugs while one third was on insulin. Very few were on both of them [table-1].
| Variable | Frequency | Percentage % | Mean | SD | |
| Age | 58.4 | 8.6 | |||
| Gender | Female | 160 | 40.0% | ||
| Male | 240 | 60.0% | |||
| Marital status | Divorced | 8 | 2.0% | ||
| Married | 279 | 69.8% | |||
| Single | 70 | 17.5% | |||
| Widow | 43 | 10.8% | |||
| Education | No Formal Education | 98 | 24.5% | ||
| Primary | 123 | 30.8% | |||
| Secondary | 154 | 38.5% | |||
| University | 25 | 6.3% | |||
| Occupation | Employee | 63 | 15.8% | ||
| Housewife | 68 | 17.0% | |||
| Retired | 19 | 4.8% | |||
| Self-employed | 151 | 37.8% | |||
| Un-employed | 99 | 24.8% | |||
| Medical Insurance | No | 143 | 35.8% | ||
| Yes | 257 | 64.3% | |||
| Type of treatment | Diet only | 38 | 9.5 | ||
| Diet + Insulin | 130 | 32.5 | |||
| Diet + Oral hypoglycemic drug | 199 | 49.8 | |||
| Diet + Oral hypoglycemic drug + Insulin | 33 | 8.3 | |||
Table-1: Distribution of Diabetic Patients’ Characteristics. (n=400)
The majority of the patients diagnosed with DM within 5 to 10 years. 94.8% of the participants had poor glycemic control. The most prevalent comorbidity was hypertension (72.8%), while the most prominent complication is retinopathy (25.5%) [table-2].
| Disease | Frequency | Percentage % | ||
| Complications | Nephropathy | No | 359 | 89.8% |
| Yes | 41 | 10.3% | ||
| Neuropathy | No | 350 | 87.5% | |
| Yes | 50 | 12.5% | ||
| Retinopathy | No | 298 | 74.5% | |
| Yes | 102 | 25.5% | ||
| Diabetic foot | No | 375 | 93.8% | |
| Yes | 25 | 6.3% | ||
| Myocardial infarction | No | 360 | 90.0% | |
| Yes | 40 | 10.0% | ||
| Peripheral Artery Disease | No | 392 | 98.0% | |
| Yes | 8 | 2.0% | ||
| Stroke | No | 362 | 90.5% | |
| Yes | 38 | 9.5% | ||
| Comorbidities | Hypertension | No | 109 | 27.3% |
| Yes | 291 | 72.8% | ||
| Dyslipidemia | No | 338 | 84.5% | |
| Yes | 62 | 15.5% | ||
| Obesity | No | 366 | 91.5% | |
| Yes | 34 | 8.5% | ||
Table-2: Complications of DM and Associated Comorbidities among the Participants (n=400)
Approximately one third of the participants (35%,32.5%) performed physical exercise and followed diet control, respectively. The majority were non-smokers & none of them consumed alcohol (79.3%, 100%), respectively [table-3].
| Variable | Frequency (n=400) | Percentage (%) | |
| Physical Exercise | No | 260 | 65.0% |
| Yes | 140 | 35.0% | |
| Diet control | No | 270 | 67.5% |
| Yes | 130 | 32.5% | |
| Smoking | No | 317 | 79.3% |
| Yes | 83 | 20.8% | |
| Alcohol consumption | No | 400 | 100.0% |
| Yes | 0 | 0.00% | |
| Foot Care | No | 354 | 88.5% |
| Yes | 46 | 11.5% | |
Table 3.3 Distribution of Lifestyle Factors.
Regarding DQOL statistics, the mean and SD for satisfaction, impact and worry were (13.7 
4.9, 8.5±4.4, and 7.1±3,7) respectively [table-4.1 and table-4.2].
Table-4.1: DQOL Responses of the Participants in Each Domain
| Items | Mean | SD | Minimum | Maximum | |
| Satisfaction domain | 6 | 13.7 | 4.9 | 7 | 27 |
| Impact domain | 4 | 8.5 | 4.4 | 4 | 20 |
| Worry domain | 3 | 7.1 | 3,7 | 3 | 15 |
| Overall DQOL | 13 | 29.3 | 11.5 | 15 | 61 |
Table-4.2: Summary Statistics on DQOL
The mean age of those with poor quality of life is significantly higher than those with good quality of life. The relationship is statistically significant. [table-5].
| Overall Quality of Life | N | Mean Age | SD | Std. Error Mean | Independent t-test |
Poor | 160 | 62.97 | 6.7 | .550 |
P value < 0> |
| Good | 240 | 55.36 | 8.8 | .527 |
Table-5: The Association between HRQOL and age of the participants (n=400)
Regarding, the association between HRQOL and other demographic characteristics, there was a statistically significant association between HRQOL and gender, medical insurance, marital status, education and occupation [table-6].
| Overall Quality of Life | Chi square | df | p-value | |||||
| Poor | Good | |||||||
| Frequency | Percentage | Frequency | Percentage | |||||
| Gender | Female | 97 | 60.6% | 63 | 39.4% | |||
| Male | 63 | 26.3% | 177 | 73.8% | 47.266 | 1 | <0> | |
| Medical Insurance | No | 75 | 52.4% | 68 | 47.6% | |||
| Yes | 85 | 33.1% | 172 | 66.9% | 14.369 | 1 | <0> | |
| Maritals Status | Divorced | 3 | 37.5% | 5 | 62.5% | |||
| Married | 105 | 37.6% | 174 | 62.4% | ||||
| Single | 19 | 27.1% | 51 | 72.9% | ||||
| Widow | 33 | 76.7% | 10 | 23.3% | 29.683 | 3 | <0> | |
| Education | No formal education | 72 | 73.5% | 26 | 26.5% | |||
| Primary | 39 | 31.7% | 84 | 68.3% | ||||
| Secondary | 49 | 31.8% | 105 | 68.2% | ||||
| University | 0 | 0.0% | 25 | 100.0% | 70.228 | 3 | <0> | |
| Occupation | Employee | 9 | 14.3% | 54 | 85.7% | |||
| Housewife | 41 | 60.3% | 27 | 39.7% | ||||
| Retired | 10 | 52.6% | 9 | 47.4% | ||||
| Self-employed | 26 | 17.2% | 125 | 82.8% | ||||
| Unemployed | 74 | 74.7% | 25 | 25.3% | 112.748 | 4 | <0> | |
Table-6: The Association between HRQOL and other Demographic characteristics of the participants (n=400)
Also, there was a statistically significant association between HRQOL and diabetes related factors [table-7].
| Overall Quality of Life | Chi square | df | P-value | |||||
| Poor | Good | |||||||
| Frequency | Percentage | Frequency | Percentage | |||||
| Duration | < 5> | 2 | 3.4% | 56 | 96.6% | |||
| 5 - 10 years | 58 | 30.5% | 132 | 69.5% | ||||
| > 10 Years | 100 | 65.8% | 52 | 34.2% | 81.515 | 2 | <0> | |
| Treatment | Diet only | 11 | 28.9% | 27 | 71.1% | |||
| Diet + Insulin | 79 | 60.8% | 51 | 39.2% | ||||
| Diet + OHD | 44 | 22.1% | 155 | 77.9% | ||||
| Diet + OHD + Insulin | 26 | 78.8% | 7 | 21.2% | 72.522 | 3 | <0> | |
| HbA1c | < 7> | 4 | 19.0% | 17 | 81.0% | |||
| = > 7 | 156 | 41.2% | 223 | 58.8% | 4.054 | 1 | 0.044 | |
Table-7: The Association between HRQOL and Diabetes related factors
In terms of association between HRQOL and complications, comorbidities, and life-style factors, there was a statistically significant association between them and HRQOL, except the foot care [table-8 - 10].
| Overall Quality of Life | Chi square | df | P value | |||||
| Poor | Good | |||||||
| Frequency | Percentage | Frequency | Percentage | |||||
| Nephropathy | No | 132 | 36.8% | 227 | 63.2% | |||
| Yes | 28 | 68.3% | 13 | 31.7% | 15.237 | 1 | <0> | |
| Neuropathy | No | 152 | 43.4% | 198 | 56.6% | |||
| Yes | 8 | 16.0% | 42 | 84.0% | 13.714 | 1 | <0> | |
| Retinopathy | No | 87 | 29.2% | 211 | 70.8% | |||
| Yes | 73 | 71.6% | 29 | 28.4% | 56.852 | 1 | <0> | |
| Diabetic foot | No | 135 | 36.0% | 240 | 64.0% | |||
| Yes | 25 | 100.0% | 0 | 0.0% | 40.000 | 1 | < 0> | |
| Myocardial Infarction | No | 125 | 34.7% | 235 | 65.3% | |||
| Yes | 35 | 87.5% | 5 | 12.5% | 41.782 | 1 | <0> | |
| Peripheral Arterial Disease | No | 152 | 38.8% | 240 | 61.2% | |||
| Yes | 8 | 100.0% | 0 | 0.0% | 12.245 | 1 | <0> | |
| Stroke | No | 134 | 37.0% | 228 | 63.0% | |||
| Yes | 26 | 68.4% | 12 | 31.6% | 14.132 | 1 | <0> | |
| *. The Chi-square statistic is significant at the .05 level | ||||||||
Table-8: The Association between HRQOL and Complications
| Overall Quality of Life |
Chi square |
df |
p-value | |||||
| Poor | Good | |||||||
| Frequency | Percentage | Frequency | Percentage | |||||
| Hypertension | No | 20 | 18.3% | 89 | 81.7% | |||
| Yes | 140 | 48.1% | 151 | 51.9% | 29.265 | 1 | <0> | |
| Dyslipidemia | No | 108 | 32.0% | 230 | 68.0% | |||
| Yes | 52 | 83.9% | 10 | 16.1% | 58.841 | 1 | <0> | |
| Obesity | No | 135 | 36.9% | 231 | 63.1% | |||
| Yes | 25 | 73.5% | 9 | 26.5% | 17.406 | 1 | <0> | |
| *. The Chi-square statistic is significant at the .05 level | ||||||||
Table-9: The Association between HRQOL and Comorbidities
| Overall Quality of Life |
Chi square |
df |
p-value | |||||
| Poor | Good | |||||||
| Frequency | Percentage | Frequency | Percentage | |||||
| Physical Exercise | No | 126 | 48.5% | 134 | 51.5% | |||
| Yes | 34 | 24.3% | 106 | 75.7% | 22.161 | 1 | <0> | |
| Diet Control | No | 102 | 37.8% | 168 | 62.2% | |||
| Yes | 58 | 44.6% | 72 | 55.4% | 1.709 | 1 | 0.191 | |
| Smoking | No | 150 | 47.3% | 167 | 52.7% | |||
| Yes | 10 | 12.0% | 73 | 88.0% | 34.095 | 1 | <0> | |
| Alcohol Consumption | No | 160 | 40.0% | 240 | 60.0% | |||
| Yes | 0 | 0.00% | 0 | 0.00% | ||||
| Foot Care | No | 140 | 39.5% | 214 | 60.5% | |||
| Yes | 20 | 43.5% | 26 | 56.5% | .262 | 1 | 0.609 | |
Table-10: The Association between HRQOL and Lifestyle Factors
The current study assessed the HRQOL in Sudanese patients with T2DM using the revised DQOL questionnaire. It is sometimes difficult to compare studies using DQOL, since some authors use an inverse scoring system (higher scores reflecting better QOL). In the present study, the original scoring method was used; a high average score indicates a poor QOL. This study revealed that the mean ± SD score for overall revised DQOL instrument was 29.3 ± 11.5 while each domain of “satisfaction”, “impact” and “worry” had mean scores of 13.7 ± 4.9, 8.5 ± 4.4 and 7.1 ± 3.7, respectively. The scores obtained were only approximately half of the possible range of scores for QOL. Since a higher average score would signify a poorer QOL, it seems that the disease did not badly affect the QOL among T2DM patients. As a result, it can be said that the participants had a moderate HRQOL. They were satisfied with the amount of time they spent due to T2DM, the current treatment, knowledge and life in general. Apart from that, they also felt that T2DM had very seldom impact on their life and therefore were not really worried. These results are similar to a previous study in Malaysia where the results were also half of the possible range of scores for QOL and it concluded that patients with T2DM had an acceptable HRQOL (13). Since the majority of the participants had diabetes for more than 5 years, the moderate HRQOL finding can be justified by the fact that longer duration of illness means long duration on follow-up, therefore better experience in diabetic self-care practice, life style modification and adherence of medication. Moreover, it might signify a mean of coping strategy to reduce anxiety.
This study also revealed that 40% of the participants have overall score above the mean, i.e., poor DQOL. This is in consistency with previous studies in South Benin and Malaysia that reported that poor DQOL in 43% and 43.6% of the participants respectively (14,15). Studies conducted in Ethiopia (16) and Saudi Arabia (17) used different measurement scales and affirmed our findings. However, these results should be interpreted with caution when comparing the scores as the QOL value sets for each country depending on the choice of instruments, the number of levels, the quality of diabetes care, or the availability of access to support services.
Regarding each domain, the results reveal that the highest percentage of participants have a poor QOL in “Satisfaction” and “Worry” domains, (39.8% and 39.5% respectively), while 36.5% have a poor QOL in “Impact” domain; there is no much variation between the domains. These findings are almost similar to a recent study in Malaysia where participants had worse QOL in “Satisfaction” domain (40.4%), however in contrast to this study, the least percentage (31.9%) of participants had a poor QOL level in the “Worry” domain (15). Not only this, but also another study aimed to assess the factors associated with QOL in Patients with T2DM in South Benin using the revised DQOL instrument concluded that more than half of participants reported problems in the impact and satisfaction domains, whereas one third in the worry domain (14). The reason for this may be due to sociocultural variations and lifestyle differences.
Although the overall HRQOL score was moderate/acceptable, 40% of patients have a poor QOL. Hence, it is important to assess the influencing factors of HRQOL in patients with T2DM for the better planning of interventions to improve the physical and psychosocial burden of the disease, and hence to attain better HRQOL.
The findings in the literature regarding the QOL of patients with T2DM and its association with sociodemographic factors have been variable. To begin with, this study revealed that the mean age was 58.4 ± 8.56 years. This result is similar to a study in Egypt (18) which similar mean age of 54.74 years. This indicates that type 2 diabetes is more commonly observed among the middle-aged. This could be explained as diabetes can go silently, undetected for a long time, without symptoms and many people first became aware that they had diabetes when they developed one of its potentially life-threatening complications, such as heart disease. The mean age of those with poor quality of life is significantly higher than those with good quality of life (P value <0>
Regarding the level of education, the current study has shown that low educational levels adversely affect patients' QOL. Illiterate patients have the worse QOL scores compared to those with higher educational levels. Not only this, but it also showed that all patients who are university graduates had a good QOL. This finding was consistent with previous studies conducted in Ethiopia (24). The possible explanation of this finding is that patients who were educated in university level might have better social relationship with the community, adapted to the environment easily, might have planned recreational time, better understanding regarding behavioural risk factors and diabetic self-care practice and the effects of diabetes on their health; thus, they are more likely to adjust to their recommended treatment and diet regimen.
HRQOL of unemployed patients with T2DM is poor as compared with those patients who are employers. A national survey conducted in Iran has also reported a significant association between employment and HRQOL of patients with T2DM (25). A study done in Nigeria on QOL of patients with DM and Benin has also showed significant association of occupation with QOL (26,14). This may be explained by the fact that improvement in socioeconomic status can improve QOL. Furthermore, the subjects with health insurance had a better QOL than those without insurance, this can be attributed to regular check-ups, and the insurance company covering medications and other costs therefore promoting medication adherence.
Many studies reported an association between increased duration of diabetes and poor HRQOL, in both types of diabetes (27,24, 14). On the other hand, there are also contradicting findings about the association between duration of diabetes and HRQOL (28,29). In this present study we found a negative association between diabetes duration and HRQOL. The longer duration of diabetes is associated with the poor HRQOL. This may be due to the fact that long disease duration increases renal, eye, neural and other complications of diabetes, and being dependent on medications for a longer time which may cause side effects and then contributes to impairment in HRQOL.
Patients who are taking insulin and oral anti diabetic medication treatment regimen had negatively affected HRQOL as compared with those patients who are taking oral anti diabetic medication only. This study finding was consistent with studies conducted in China, Indonesia and Malaysia (30,31). This might be the physiological side effect of insulin and oral anti diabetic medication. Taking insulin and oral anti diabetic medication may disturb the metabolic process of the body and developing brain cell toxicity followed by disturbing body image and headache. On the contrary, other studies reported that insulin-treated diabetic patients had reduced impact on HRQOL than oral hypoglycaemic drugs/diet-treated patients (32). The difference might be due to genetic variation for medication side effects, diabetic self-care practice difference may be interrupting regular medication intake and socio-demographic factors. In Uganda, the type of treatment was not significantly associated with the quality of life of diabetic patients. The nonsignificant influence of type of medication on quality of life of diabetic patients in Uganda supports the argument of mixed conclusion reached by whether or not insulin is administered (33). Furthermore, another study in India concluded that the QOL of patients on combination therapy with insulin and OHA was better than the patients on monotherapy with only insulin or OHA (34). These may be attributed to the fact that using combination therapy of insulin and OHA gives a better glycemic control.
The relationship between glycemic control and QOL is the subject of debate. This study revealed a statistically significant relationship between HbA1c level & poor QOL (P value = 0.044). This result was also documented previously (34). Glycaemic control was shown to be a definitive determinant of HRQOL, with high glycosylated haemoglobin levels identified as an independent determinant of impaired overall DQOL score as well as scores of every domain in DM (35). It can be summarized from these data that maintaining adequate metabolic control is essential to maintaining QOL in patients with DM; the way each patient achieves this control seems to be irrelevant. On the other hand, tight glycemic control has also been found to have negative impact on quality of life due to restrains on daily life activities (36).
Diabetic patients are more susceptible to macro or microvascular complications than those without T2DM. The most commonly observed diabetic complication was diabetic retinopathy (25.5%). The present study indicated a significantly worse HRQOL among patients with diabetes complication than the patients with diabetes alone. This is similar to previous results (21,16). The long-term complications, particularly microvascular disease, have been directly related to poor glycemic control (37). As many patients are likely to remain undiagnosed for several years before symptoms appear, many will show evidence of diabetic complications at diagnosis.
In this study, the most predominant comorbidity is hypertension 72.8%. Similar results were seen in previous studies (38). A previous study reported that more than 50% of the total diabetes patients had hypertension and the similar observation is reported in our study (39). Several studies have shown that the presence of comorbidities decreases the QOL of patients with diabetes (40,41). Likewise, this study supported this by revealing a statistically significant relationship between the presence of comorbidity and poor QOL. (P value <0>
This study reveals that lifestyle factors such as smoking and physical exercise were significant predictors of quality of life of diabetic patients. In this study, patients who had history of smoking had worse HRQOL. This result was supported by the report from CDC and a study from the USA that indicated the direct impact of smoking altering the health condition of the patients with diabetes and reduced their HRQOL. Smokers are more likely to have central fat accumulation than non-smokers, and smoking is known to induce insulin resistance and compensatory insulin secretion responses, which could explain the increased risk of diabetes in those who smoke. An interventional study in Sandiego, California showed that exercising and adhering to the recommended diet had a positive impact on the HRQOL of patients (42). Studies in Nigeria (43) and Ethiopia (40) are also in line with this finding. Although the result in this study is similar with regards to physical exercise, diet control did not show similar results. This study showed that physical exercise has a significant association with QOL but diet control does not; the relationship was not statistically significant (P value <0>
To conclude, this study demonstrates a moderate overall HRQOL among patients with T2DM. Besides, it also demonstrates a low QOL among 40% of patients with T2DM, suggesting that QOL should be included in any modality used for treating diabetic patients. Glycaemic control was shown to be a definitive determinant of HRQOL, with high glycosylated haemoglobin levels identified as an independent determinant of impaired overall DQOL score. Thus, younger age, male gender, being a university graduate, the absence of comorbidities and complications and having a good glycemic control are all factors that can be considered as predictors of good QOL.
Journal of Women Health Care and Issues By the present mail, I want to say thank to you and tour colleagues for facilitating my published article. Specially thank you for the peer review process, support from the editorial office. I appreciate positively the quality of your journal.
