ABSTRACT
Context:
Physical Activity (PA) significantly contributes to the management and prevention of various non-communicable diseases (NCDs) such as diabetes, hypertension, cardiovascular diseases. A good PA for patients with Type 2 Diabetes Mellitus (T2DM), is identified as a key to management and improvement.
Aim:
This study aims to evaluate PA among diabetic patients along with factors preventing or enabling them performing PA to manage their health.
Settings and Design:
A cross-sectional study was conducted in Family Medicine Clinics of Indus Hospital and Health Network, Karachi.
Subject and Methods:
Study was conducted during August-2022 to April-2023. In this study 345 patients with T2DM aged between 25 and 65 years were enrolled in the study. The outcome variables i.e. PA, barriers and promoters of PA were assessed.
Statistical Analysis:
Data analysis was performed IBM SPSS v 26. Qualitative variables were reported as frequency (%) while quantitative variables were reported as mean ± SD/median (IQR). For controlling confounders, binary logistic regression was applied.
Results:
Among 345 patients, female was predominant (68.9%) and the median age of patients was 53 years. However, 94.5% patients were observed to have low PA. The most common barrier and promoter of PA was unavailability of place (14.5%) and good glycemic control (45.5%) respectively.
Conclusion:
The majority of the patients with T2DM were found to have low PA. The most common barriers and promoters of PA were the unavailability of a place to exercise and good glycaemic control, respectively.
Keywords: Barriers, diabetes mellitus, physical activity, promoters
Introduction
Globally, more than four hundred million individuals are living with diabetes. Among those, 90% of the burden comprises Type 2 Diabetes Mellitus (T2DM).[1] According to the World Health Organization (WHO), poor diet, physical inactivity, tobacco use, and harmful alcohol use are the four major factors that increase the risk of NCDs. Behaviour modifications like good Physical activity (PA) improve glycaemic control as measured by HbA1C.[2] Good glycaemic control may reduce the risk of micro-vascular as well as macro-vascular complications of T2DM. Furthermore, it also reduces the risk of cardiovascular diseases, which is the commonest cause of death in such patients.[3] Globally, physical inactivity alone is responsible for 9% of premature deaths.[4] In addition, it also influences certain metabolic abnormalities associated with T2DM.[5,6,7]
Globally, T2DM has emerged as a significant contributor to mortality and disability. Non-communicable diseases (NCDs) are responsible for approximately 41 million deaths annually in Lower-Middle-Income Countries (LMICs).[8] Similar to other LMICs, Pakistan is facing a huge burden of T2DM. In South Asian countries, the prevalence of T2DM among individuals aged 20–79 is striking: 7.1 million in Bangladesh, around 7 million in Pakistan, and 69.1 million in India.[9] Alarmingly, it is projected that in Pakistan number of T2DM will increase up to 13.8 million by 2030,[10] underscoring the urgent need to address diabetes management and prevention strategies. Key factors driving this rising prevalence in South Asia, including Pakistan, are behavioural patterns such as high consumption of carbohydrate-rich diets and lack of PA.[11]
Similar to many other Countries, a NCD unit has been established by the Ministry of Health, Pakistan. However, the country lacks a dedicated strategy to address PA.[12] In Pakistan, there is no clearly defined pathway for diagnostic and therapeutic management of diabetes. As a result, the responsibility for self-management beyond clinical treatment falls primarily on individuals with diabetes, many of whom engage in insufficient PA, lead sedentary lifestyles, and struggle with poor metabolic control.[13,14]
In Pakistani culture, several factors may influence PA. Families in Pakistan typically exhibit a collectivistic rather than individualistic structure.[15,16,17] Like many other Asian countries or collectivistic societies, cultural norms are deeply rooted in tradition.[18,19] Maintaining individual identity within these roles is highly valued and can impact the degree of control and support family members provide to one another.[18,19,20,21] Furthermore, various environmental barriers have also been identified, including unsafe neighbourhoods, a lack of recreational spaces, and limited time availability.
In general, PA is encouraged for health as it has been recognized that a considerable portion of chronic diseases, and particularly diabetes mellitus, are closely attributed to sedentary habits and poor lifestyle.[22,23] However, maintaining long-term adherence to PA programs remains a significant challenge. Many individuals struggle to sustain a self-motivated, home-based PA without the structure of an exercise class. Environmental as well as personal barriers contribute to difficulties in initiating or continuing regular PA. It is commonly observed that almost one-third of patients presenting in Family Medicine clinics with Diabetes Mellitus have more emphasis on pharmacological management rather than non-pharmacological management. In the given context, family physicians who form the foundation in any healthcare system by being the primary contact points for patients, hold the responsibility to organize their focus of efforts in promoting PA in their clinical practices.[24,25]
PA is a behaviour constructed through complex interactions of various factors, including intrapersonal, interpersonal, and environmental. Not all healthcare organizations emphasize focusing on and educating people with diabetes on these areas.[12,26] Due to limited literature, it remains undistinguishable what exact factors may influence PA. Various studies have been done on PA in the general population.[27,28,29,30] However, in the local context, studies on PA in T2DM using validated tools are scarce. This study seeks to assess the PA among T2DM patients attending Family Medicine clinics and the factors preventing or enabling them from performing PA to manage their fitness and health.
Subjects and Methods
A cross-sectional study was carried out in the Family Medicine clinic of Indus Hospital and Health Network from February 2022 to August 2023. Approval was taken from the Institutional Review Board (IRB). All patients aged between 25 and 65 years presenting to the outpatient family medicine clinics and having been diagnosed with T2DM for at least five years were enrolled in the study by using non-probability consecutive sampling. However, patients with physical disability such as amputation, fracture, terminal illness like malignancy or end stage renal failure, or congestive cardiac failure and dementia or mentally challenged were excluded. Sample size was calculated by using Open-Epi online sample size calculator by using the confidence level 95%, desired precision 05% and frequency of diabetic patients with adequate PA 34%.[19] The statistically calculated sample size of our study was 345.
In our study, a patient was classified as physically active “if they engaged in moderate-intensity aerobic PA for 150–300 min, vigorous-intensity aerobic PA for 75–150 min, or a combination of moderate and vigorous intensity activities equivalent to these durations over the past month”. This was determined by using the WHO Global PA Questionnaire (GPAQ). Activity in the form of cycling, yoga, outdoor sports, gardening, jogging, and/or walking. Moreover, barriers and promoters of PA were included in the study based on a literature search. Barriers include: unwillingness, feeling tired/laziness, fear of injury, joint pain, lack of time, increased workload, lack of road safety, and unavailability of a place. However, good for blood pressure control, good for diabetic control, reduced joint pain, weight management, feel good/relax, increase appetite, get good sleep, doctors advise, family forced, and friends’ suggestion were taken as promoters of PA.
Data was analysed by using IBM SPSS v 26. Based on normality, mean (SD) or median (IQR) were calculated for quantitative variables such as age, duration of DM, years of education, and monthly income. Normality of data was assessed by using the Shapiro–Wilk test, while qualitative variables such as gender, place of residence, marital status, religion, ethnicity, occupation, PA, and exercise benefits and barriers were presented as frequency (%). Missing data were excluded from the inferential analysis. For controlling confounders, binary logistic regression was applied. Initially, univariate analysis was performed; all variables with a P value < 0.25 in univariate analysis were analysed in the multivariate model. Both adjusted and unadjusted odds ratio was calculated with a 95% confidence level, taking P value ≤ 0.05 as statistically significant.
Results
In this study we enrolled 345 type 2 diabetes patients. The median age of patient was 53 (47–58) years and median body mass index was 28 Kg/m2, systolic blood pressure was 130 mmHg, diastolic blood pressure was75 mmHg, blood glucose levels were 160 mg/dl and cholesterol levels were 160 mg/dl as describe in Table 1.
Table 1.
Distribution of Age, BMI, SBP, DBP, Cholesterol and FBS of Study Population
| Variable | Median (IQR) |
|---|---|
| Age (Years) | 53 (47-58) |
| BMI (Kg/m2) | 28 (25-32) |
| SBP (mmHg) | 130 (119-140) |
| DBP (mmHg) | 75 (70-80) |
| Cholesterol (mg/dl) | 160 (150-175) |
| FBS (mg/dl) | 160 (150-180) |
BMI=Body mass index, SBP=Systolic blood pressure, DBP=Diastolic blood pressure, FBS=Fasting blood sugar, IQR=Interquartile range
Among 345 patients, 237 (68.9%) were female, while 107 (31.1%) were male. Table 2 shows the distribution of ethnicity and occupation.
Table 2.
Distribution of Ethnicity and Occupation of study population
| Variables | n (%) |
|---|---|
| Ethnicity¥ | |
| Sindhi | 18 (5.3) |
| Punjabi | 20 (5.8) |
| Balochi | 2 (0.6) |
| Pushto | 12 (3.5) |
| Urdu | 290 (84.8) |
| Occupation | |
| Laborer | 1 (0.3) |
| Professionals | 16 (4.6) |
| Private Business | 56 (16.2) |
| Unemployed | 34 (9.9) |
| Home-makers | 237 (68.7) |
| Others | 1 (0.2) |
Professional: Baker, Carpenter, electrician, barber. ¥Sample is not equal to calculated sample size due to missing data
Furthermore, in our study 326 (94/5%) patient with T2DM had low PA and 19 (5.50%) had moderate PA [Figure 1].
Figure 1.
Distribution of PA among T2DM patient
Unavailability of place is the most common barrier of PA (n = 50, 14.5%) followed by feeling tired or laziness (n = 39, 11.3%) and unwillingness (n = 38, 11.0%). In addition, the most common promoter was good glycemic control (n = 157, 45.5%) followed by advice by doctor (n = 100, 29%) and good blood pressure control (n = 24, 7%). Details of barriers and promoter shown in Figures 2 and 3.
Figure 2.
Distribution of Barriers of PA among patients with T2DM
Figure 3.
Distribution of promoters of PA among patients with T2DM
The overall median MET score was 240, and the median score of transport activity was 160. However, walking for travel was the primary contributor, accounting for over three-quarters (86.28%) of the total PA, followed by work-related activities, which made up 12.38%. In contrast, recreational activities (leisure activities) were significantly less common, comprising only 1.32% [Table 3].
Table 3.
Distribution of MET score of each domain of GPAQ
| GPAQ Domain | Mean (SD) | Median (IQR) | Contribution in Physical Activity (%) |
|---|---|---|---|
| Work Activity (P1-P6 of GPAQ) | 54.49 (196) | 0 (0) | 12.38% |
| Travel to and from place (P7-P9 of GPAQ) | 180.57 (194.43) | 160 (0-320) | 86.28% |
| Recreational Activity (P10-P16 of GPAQ) | 3.01 (33.55) | 0 (0) | 1.32% |
| Overall MET Score | 238.08 (237.04) | 240 (0-400) | -- |
MET=Metabolic Equivalent, IQR=Interquartile Range, GPAQ=Global Physical Activity Questionnaire
Table 4 shows the association between PA and baseline characteristics. Findings of our study show that the odds of doing low PA are higher among patients with a BMI greater than or equal to 30 Kg/m2 as compared to BMI less than 30 Kg/m2 [aOR 6.54, 95% CI 1.45-29.34, P value 0.014]. Similarly, the odds of low PA among patients with raised cholesterol is lower as compared to normal cholesterol (aOR 0.17, 95% CI 0.06–0.54, P value 0.002).
Table 4.
Association of baseline characteristics with physical activity in patients with T2DM
| Variable | Physical Activity | COR (95% CI) | aOR (95% CI) | ||
|---|---|---|---|---|---|
|
| |||||
| Low n (%) | Moderate n (%) | Vigorous n (%) | |||
| Age¥ | |||||
| ≤40 Years | 1 (2.4) | 41 (97.6) | 0 | Ref | Ref |
| 41–60 Years | 14 (5.6) | 237 (94.4) | 0 | 0.41 (0.05–3.22) | 0.51 (0.06-4.14) |
| >60 Years | 4 (7.8) | 47 (92.2) | 0 | 0.28 (0.03–2.66) | 0.35 (0.03-3.41) |
| Gender¥ | |||||
| Male | 100 (93.5) | 7 (6.5) | 0 | Ref | Ref |
| Female | 225 (94.9) | 12 (5.1) | 0 | 1.31 (0.50–3.43) | 1.24 (0.45-3.41) |
| BMI¥ | |||||
| <30 Kg/m2 | 183 (91.5) | 17 (8.5) | 0 | Ref | Ref |
| ≥30 Kg/m2 | 141 (98.6) | 2 (1.4) | 0 | 6.54 (1.48–28.81)* | 6.54 (1.45-29.33)* |
| Ethnicity¥ | |||||
| Sindhi | 17 (94.4) | 1 (5.6) | 0 | Ref | -- |
| Punjabi | 17 (85) | 3 (15) | 0 | 0.33 (0.31–3.53) | -- |
| Balochi | 2 (100) | 0 (0) | 0 | -- | -- |
| Pushto | 8 (66.7) | 4 (33.3) | 0 | 0.11 (0.01–1.23) | -- |
| Urdu | 279 (96.2) | 11 (3.8) | 0 | 1.49 (0.18–12.24) | -- |
| Occupation¥ | |||||
| Labour | 0 (0) | 1 (100) | 0 | -- | -- |
| Professional | 14 (87.5) | 2 (12.5) | 0 | -- | -- |
| Own Work | 55 (98.2) | 1 (1.8) | 0 | -- | -- |
| Unemployed | 31 (91.2) | 3 (8.8) | 0 | -- | -- |
| Housewife | 224 (94.9) | 12 (5.1) | 0 | -- | -- |
| Cholesterol¥ | |||||
| Normal | 289 (95.7) | 13 (4.3) | 0 | Ref | Ref |
| Raised | 26 (81.3) | 6 (18.8) | 0 | 0.19 (0.068–0.55)* | 0.17 (0.05–0.54)* |
| Hypertension | |||||
| No | 163 (94.2) | 10 (5.8) | 0 | Ref | |
| Yes | 163 (94.8) | 9 (5.2) | 0 | 1.11 (0.44–2.80) | |
COR=Crude Odds Ratio, aOR=Adjusted Odds Ratio, CI=Confidence Interval, BMI=Body Mass Index. *P<0.05. Odds ratio of occupation not calculated due to the low number of patients in each category. ¥The sample is not equal to the calculated sample size due to missing data
Discussion
This study aims to assess the PA among patients diagnosed with T2DM and to identify the factors that facilitate or hinder their engagement in PA using the validated tools of GPAQ and BPPA respectively. In the study, 345 patients with T2DM were enrolled. The median age of patient was 53 (47–58) years. Among 345 patient, 237 (68.9%) were females while 107 (31.1%) were males.
In this study, a low level of PA was reported in the majority (94.6%) of the participants. Contrary to our study findings, studies conducted in Venezuela reported low PA in a lesser portion of the population; Venezuela, 17.6%, Peru, 20%, and Argentina, 52%.[31,32,33,34] However, a study from Lahore reported that patients with T2DM exhibited a low level of PA, which could negatively impact the management of T2DM.[11] These findings are comparable to the findings of our study.
Furthermore, there is high variability in the level of PA observed in different studies: 15% to 61% of people performed moderate to vigorous PA/week.[35] In our study, low PA was higher as compared to previous studies conducted in Pakistan and other countries. The most likely reason for this discrepancy is the method of evaluation of PA. The most common assessment tool used for assessment of PA was the International PA Questionnaire (IPAQ). Even studies utilizing the IPAQ have shown varied results,[31,32,33,34] likely due to reliance of questionnaire on the participants’ memory, which may lead to overestimation of PA in work and domestic activities.[36] We used GPAQ in our study due to its higher internal reliability. The GPAQ revealed notable differences across categories, including step count, BMI, waist circumference, body fat percentage, fitness levels, and activity measured by accelerometer. Its short-term test–retest reliability over 10 days ranged from 0.83 to 0.96, while long-term reliability over three months was reported between 0.53 and 0.83.[37]
PA development is a complex process influenced by various factors, including intrapersonal, interpersonal, and environmental elements.[38,39] Many of the facilitators and obstacles to PA observed in the Middle East and North Africa (MENA) region are consistent with global findings. However, our research reveals differences in reported facilitators and barriers among MENA countries. While some broad interventions are necessary, it’s essential to tailor specific approaches to each country, taking into account local sociocultural and environmental factors that impact PA.[39]
According to the findings of our study, body mass index (BMI) and raised cholesterol are associated with low PA. Our findings are consistent with most previous studies. Patients with raised BMI have low PA.[40,41] This may be physical limitations and associated habits in patients with raised BMI.[40] A previous study conducted in Pakistan in 2019 reported sedentary lifestyle in 2.8%, under active 5.3%, light regular activity 6.8%, and active 64.3% of the people evaluated with T2DM.[42] Our study highlighted the other common barriers to perform PA, which include; unavailability of space which refers to lack of jogging track, parks and gyms in surrounding, lack of willingness which is characterized by difficulty in controlling emotions and actions while laziness often associated with feeling sleepy or tired; and lack of time which is linked to personal interest or motivation. These findings resonate with prior research, which similarly highlights these obstacles as prevalent barriers to engaging in regular PA.[29,30,43,44,45] Addressing infrastructural inadequacies, fostering behavioural change, and enhancing personal motivation are pivotal strategies to mitigate the negative impacts of low PA on public health. By tackling these barriers, we can better support individuals in achieving healthier lifestyles and reducing the burden of conditions associated with physical inactivity.
In addition, previous studies reported an inverse relationship of age with PA, and women had a higher number of PA.[40,41] These findings are inconsistent with our study findings, which show no difference in PA with regard to age and gender. In our study, no significant association was found between PA and occupation. Results from previous studies showed that the differences in moderate to vigorous PA levels across the occupation categories became insignificant.[46,47] This indicates that sociodemographic factors play a major role in predicting levels of PA than occupation category. As occupation is closely linked with socioeconomic status which it is difficult to assess the association between PA and occupation category.[46,47]
Regarding the factors promoting PA, the most common promoter was good glycaemic control, followed by advice from a doctor and good blood pressure control. Our findings are in line with previous studies, which show health benefits, well-being, doctor advice, physical appearance, social interaction, and enjoyment as some common promoters reported.[48,49,50]
Evidence from low- and middle-income countries indicates that comprehensive strategies integrating components such as media campaigns, behavioural interventions, social engagement, policy reforms, and environmental improvements can effectively promote PA. Adding simple measures to their practice, like motivational counselling, exercise prescriptions and advising small modifications in everyday life would not only improve physical health but also the psychological aspects of the overall well-being of patients.[22,50] These efforts should be multifaceted, involving collaboration across sectors like public health, transportation, recreation, and healthcare, and should target diverse settings such as workplaces, schools, and community organizations. However, significant challenges remain, including a lack of adequately trained personnel to implement PA-related policies. Overcoming these barriers is essential for achieving meaningful progress in increasing PA levels. A critical next step involves building capacity for monitoring PA, conducting intervention research, and implementing policies, especially in low- and middle-income countries.[39]
A key strength of this study is the use of validated tools to assess participants’ PA and identify the factors influencing their PA. Moreover, the major limitation of this study is the cross-sectional nature of the study, which restricts the evaluation of the causal relationship between different demographic/clinical factors and PA. On the other hand, barriers and promoters were dealt with as a multi-response variable in this study, due to which not all barriers and promoters were responded to by every participant. This makes it difficult to put barriers and promoters in the regression model. Moreover, being a single-center study, the findings cannot be generalized.
Conclusion
In patients with T2DM, low PA is more prevalent. The most common barriers and promoters were the unavailability of a place and good glycaemic control, respectively. Through appropriate counselling and/or through the use of an activity diary, obstacles can be addressed to a great extent. According to the WHO Global Action Plan on PA 2018–2030, it has been proposed to initiate community awareness campaigns, implement public education programs as well as community activities. It is advised that studies utilizing objective measurement be conducted across different settings of the country to elucidate these findings more precisely and contextually.
Ethical clearance
Our study was approved by Institutional Review Board (IRB) of Indus Hospital Health Network.
Conflicts of interest
There are no conflicts of interest.
Funding Statement
Nil.
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