research on diabetes in philippines

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• v.35(1); 2020

Challenges and Opportunities for Diabetes Care in the Philippines in the Time of the COVID-19 Pandemic

Anna elvira arcellana.

1 Division of Endocrinology, Diabetes and Metabolism, University of the Philippines-Philippine General Hospital

Cecilia Jimeno

2 Past President, Philippine Society of Endocrinology, Diabetes and Metabolism

Patients with diabetes constitute a vulnerable population in the surge of the COVID-19 pandemic. COVID-19 is a viral illness caused by the virus SARS-CoV2 which originated in China, presenting with a range of clinical manifestations from fever, cough, myalgia, resembling a systemic viral illness which can progress to acute respiratory failure, and multiple organ dysfunction. In the Philippines, the burden of both diseases is high. The prevalence of diabetes, a chronic, metabolic disorder characterized by hyperglycemia, is about 7.1% in adults between 20-79 years old in 2019. 1 The country has been afflicted by a COVID-19 outbreak and as of this writing, there are already more than 6000 cases of COVID-19 infection, and more than 400 individuals have died of the disease in the Philippines. This led the government to declare an enhanced community quarantine (ECQ), which entails restricted operation and movement of people and goods, except for essential services, throughout the island of Luzon-the largest island in the Philippines, which comprises of about 57 million people, last March 16, 2020. This ECQ has been extended twice, and will remain enforced until May 15, 2020 at the earliest, 2 in order to control the outbreak while boosting testing capacity and the ability of healthcare facilities to respond to COVID-19 cases.

Those with diabetes can be both a direct and a collateral victim of this pandemic. Poor blood sugar control may lead to an immunocompromised state, leading to an increased risk of contracting and developing the complications of COVID-19. As a chronic disease, diabetes entails multimodal management integrating medical nutritional therapy, exercise, pharmacologic therapy, close monitoring and follow-up. Quarantine measures and restrictions in mobility have made diabetes care more challenging. The other way that persons with diabetes become collateral damage is because of the focus now on treating persons who have the COVID infection. The Philippine government has designated 19 COVID-referral hospitals in the National Capital Region, and 75 facilities throughout the Philippines. These referral hospitals were preferentially equipped by the government with manpower, personnel protective equipment, medications and other needs to be able to manage persons infected with COVID who are referred to their hubs from the community or other hospitals. However, most of the other hospitals still mostly admit only patients with COVID. This has led to a significant number of patients who would have been previously admitted to be turned away from hospitalization to prevent them from becoming infected, and instead given medications for home management. This is true for various disease conditions, including persons with diabetes.

COVID-19 INFECTION IN AN INHERENTLY HIGH-RISK POPULATION

Several theories have been proposed to explain the increased susceptibility of patients with diabetes to acquiring COVID-19 infection and developing fatal sequelae of the disease. Molecular studies have shown that in people with diabetes, the expression of the angiotensinconverting enzyme 2 (ACE-2) is augmented. SARS-CoV2, the virus responsible for the illness COVID-19 binds to its target cells through ACE-2. It is hypothesized that an increased expression of ACE-2 leads to a higher risk of COVID-19 infection with severe manifestations. 3 Another theory raised is impairment in the immune response of patients with diabetes in the form of dysfunction in the lymphocyte proliferative response, complement activation, monocyte, macrophage, and neutrophil actions. 4 Endothelial dysfunction also plays a role in the poor outcomes of T2DM patients with COVID-19 infection.

In a study of 1527 patients in China, 9.7% of the cohort had diabetes. It was found that the risk of developing severe clinical manifestations necessitating admission to an intensive care unit was twice higher in patients with diabetes and hypertension compared to other patients. 5 In China, the mortality rate of patients with diabetes and with COVID-19 was as much as 7.3%, which was significantly higher than those of patients without any co-morbidities, which was at 0.9%. 6 Indeed, the pandemic poses new demands on diabetes care in a developing country such as the Philippines.

CHALLENGES REGARDING NUTRITION

Diet is a central aspect of diabetes management. The COVID-19 pandemic gave rise to barriers to the attainment of adequate and optimal nutrition for patients. A diabetic diet consisting of a balanced diet made up of carbohydrates from fruits, vegetables, whole grains, legumes, and lowfat dairy products, and protein 7 is difficult to obtain in the time of COVID-19 because lockdown measures restricting mobility and tightly regulated periods to buy food result in limited food choices. Some localities in the Philippines have been placed under extreme enhanced community quarantine and hard lockdown in order to control outbreaks, which has made it difficult for people to buy fresh food. Under a quarantine set-up, most people resort to buying food that do not spoil easily such as canned goods and processed food so that supplies would last until the next market day. Canned goods and processed food usually contain a lot of additives, with a high amount of sodium and fat. Such food choices are detrimental for patients with cardiovascular and renal complications of diabetes.

Another co-morbidity that is usually associated with diabetes is obesity, and the burden of this disease is also significant in the Philippines at about 4.7%. 8 High prevalence clusters of obese individuals are usually found in urban areas, 9 because of the higher intake of processed, calorie-dense foods, and lower level of physical activity compared to their rural counterparts, who are usually engaged in farming or fishing as livelihood. Patients with diabetes and obesity have diminished food options during the lockdown, making them unable to comply with their nutritional prescriptions. In the Philippines, the officials of the smallest government unit, the barangay , usually distribute foodstuffs, which is uniform for everyone, making it difficult to adhere to the diabetic diet.

Malnutrition is a significant health problem in the Philippines, even prior to the surge of COVID-19 cases. In a cross-sectional study done locally, moderate and severe undernutrition was found to be as much as 20.5%. 10 Restrictions in trade have caused significant reductions in the supply of nutritious food, thereby worsening malnutrition across populations. The enhanced community quarantine also had dire economic consequences. Because of the lack of employment during this period, a lot of citizens do not have the financial resources to purchase even the most basic needs such as food. Government assistance strove to mitigate the economic ramifications of the pandemic through the provision of food and other basic necessities but issues on access and sustainability of such assistance still need to be addressed.

CHALLENGES WITH PHARMACOLOGIC MANAGEMENT

Majority of patients with diabetes are on multiple drugs for glycemic control and cardiovascular protection. The COVID-19 pandemic gave rise to barriers to access to pharmacologic therapy on multiple levels. Lockdown measures, not only in the Philippines, but in many parts of the word, led to interruptions in the manufacturing and delivery of drugs, causing a lot of medications to be out-ofstock. For instance, China and India, both of which are major sources of imported drugs, are severely hit by the pandemic, thus creating major roadblocks in the supply chain. Another barrier to access is the inability of patients to refill their prescriptions in the setting of an enhanced community quarantine. In order to address this hurdle, the Food and Drug Administration (FDA) issued a circular (No. 2020-007) last March 17, 2020, honoring electronic prescriptions made by physicians. 11 This is a positive move in terms of improving access to medications; however, several gaps remain such as indigent patients being unable to obtain prescriptions due to lack of access to the Internet. It is still unclear whether or not old prescriptions will be considered valid in pharmacies during this time of the pandemic. Lack of mobility also affects access to medications and this drawback is more pronounced in rural areas where there are only a limited number of pharmacies that are operational during the lockdown and they are usually few and far apart. Many patients are unable to travel to these drug stores because of the ban on public transportation during the lockdown.

The most prevalent barrier to access is the high cost of medications, especially for indigent individuals who have difficulty purchasing their own medications even before this pandemic. A significant number of patients with diabetes are daily wage earners, and the loss of income during the enhanced community quarantine makes them unable to secure their medications. Access programs from the Department of Health for both insulins and oral antihyperglycemic agents are halted during COVID-19. Even households from the middle-income class have also lost their livelihood during the enhanced community quarantine and patients from this socio-economic class do not receive full government assistance financially and are seldom enrolled in these access programs prior to the pandemic. The pandemic indeed magnified inequities in care. With this, another threat unfolds after the COVID-19 pandemic-with poor control of diabetes and other co-morbidities during this crisis, there will be a large number of patients seeking care for diabetes-related complications thereafter.

GAPS IN FOLLOW-UP AND MONITO RING

Diabetes is an intricate chronic disease that entails regular follow-up and monitoring. Assessing the status of patients with diabetes in the time of COVID-19 has been challenging both in the hospital and outpatient setting. The need for consultation and monitoring ought to be balanced with the urgency to reduce the exposure to infection of both patients and healthcare workers. Patients who have issues with health literacy, problems with mobility, and lack of access to resources such as mobile phones and the internet are at high risk of succumbing to diabetes-related morbidity and mortality in the time of COVID-19.

OPPORTUNITIES FOR INNOVATIVE DIABETES CARE DURING THE COVID-19 PANDEMIC

Recognizing that patients with diabetes represent a highly susceptible population, cooperation between healthcare workers, institutions, and patients gave rise to innovative solutions to respond to the challenges brought about by the COVID-19 pandemic. These strategies emphasize patient empowerment especially in the aspects of self-monitoring of blood glucose, adherence to lifestyle modification, hygiene and pharmacologic management, and monitoring for treatment-related adverse events like hypoglycemia. Tools like instructional videos, digital pamphlets, and infographics are increasingly being used today to enhance the health literacy of patients and caregivers. More efficient systems such as continuous glucose monitoring systems that enable real-time assessment of glucose control with minimal risk of transmission have been put in place.

Telemedicine, which pertains to the delivery of healthcare services by medical professionals in a setting where in physical distance is a limiting factor through information and communication technologies, 12 is now widely used in the country. This platform facilitates physicianpatient interaction, allowing for the analysis of subjective complaints, blood glucose levels, and the provision of treatment and lifestyle advice. Through telemedicine, physicians are able to advise patients more thoroughly on how to cope in terms of their nutrition, lifestyle and medications during the lockdown period. For instance, patients receive advice on better food choices such as fresh vegetables and home-cooked meals to consume, rather than calorie-dense, processed foods that are high in sodium and fat. Lack of exercise is also an issue discussed with patients with diabetes and strategies to address this such as home exercises (dance, stretching, yoga) that can be performed in a limited space are raised. Medication adjustments and sick day guidelines are also discussed. 12 Previous experiences suggest that telemedicine can be an effective tool for diabetes care. In a Cochrane review involving 2,768 patients from 21 randomized controlled trials, it was found that the HbA1c of patients on the telemedicine arm decreased by 0.31% ( p <0.001). 13 Telemedicine also forged closer networking among physicians in the Philippines and also abroad, enabling physicians from different working environments, with varying levels of experience with treating diabetes and COVID-19, to share helpful insights with each other.

Another key strategy in improving diabetes care in the time of COVID-19 is close coordination among healthcare providers, local government agencies, and other organizations giving aid in order to deliver services that are compatible with the needs of patients with diabetes. Nutritionists at the local government level can be tapped to provide diabetic diet for patients. 14 Diabetesspecific formulas can also be distributed to patients with diabetes for either supplemental nutrition or meal replacement to improve glucose control. Fresh produce, instead of mostly canned goods, can be provided by local government units as well, to promote more healthy food choices among its citizens. It is paramount for barangay health care workers to identify patients with diabetes in the community because these patients should keep a vigilant eye on their symptoms and there should be a lower threshold for COVID-19 testing and hospitalization of patients with diabetes.

FUTURE CHALLENGES AHEAD

Patients with diabetes are especially vulnerable to the harsh consequences of the COVID-19 pandemic. Holistic diabetes care involves protecting these patients as healthcare systems transition to the “new normal.” Once healthcare facilities reopen for diabetes follow-up, anticipatory care involves assessing patients for end-organ damage, checking vaccination status such as for influenza and pneumococcal vaccinations, and also evaluating for anxiety and depression levels of these patients in order to facilitate appropriate psychiatric referrals and assistance if necessary. Adhering to precautions against COVID-19 infection such as regular handwashing, cough hygiene, and social distancing, 10 must be inculcated to patients even after lockdown measures are lifted. Clinics must also be restructured to incorporate safety equipment and facilities to avoid the spread of infection. As we usher in a “new normal” for persons with diabetes, greater collaboration between the diabetes specialists- endocrinologists- and doctors in the community is encouraged so that not only preventive care is continued at the grassroots, but screening for diabetes and its complications continue with timely referral to specialists. The anticipated future then, after this crisis, is one of strong partnerships between doctors, patients, and institutions which are pivotal in improving the quality of diabetes care amidst formidable challenges in this global pandemic.

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Patient education for people living with diabetes in the Philippines: A scoping review of information needs, diabetes knowledge and effectiveness of educational interventions

Affiliations.

• 1 Cardiovascular Prevention and Rehabilitation Program, Toronto Rehabilitation Institute, University Health Network, Toronto, Canada. Electronic address: [email protected].
• 2 Cardiovascular Prevention and Rehabilitation Program, Toronto Rehabilitation Institute, University Health Network, Toronto, Canada.
• 3 Library & Information Services, University Health Network, Toronto Rehabilitation Institute, Toronto, Canada.
• 4 Cardiac Rehabilitation Unit, Chong Hua Hospital, Cebu City, Philippines.
• 5 Section of Endocrinology, Chong Hua Hospital, Cebu City, Philippines.
• PMID: 35525194
• DOI: 10.1016/j.dsx.2022.102494

Background and aims: Despite the growing burden of diabetes in the Philippines, available evidence indicates that its care and control are far from optimal, including patient education. The aim of this scoping review was to synthesize information in the available literature to describe the state of science of patient education for people living with diabetes in the Philippines, specific to educational needs, diabetes knowledge, and effectiveness of educational interventions.

Methods: Medline, Embase, Emcare, CINAHL, Pubmed and American Psychological Association PsycInfo were searched from data inception through July 2021. Studies of any methodology (qualitative/quantitative/mixed methods), sample size, and language were eligible for inclusion.

Results: Of 2021 initial citations, 7 studies were included, with all being quantitative in design and with a median Critical Appraisal Skills Program score of 8/12. Information needs were described by one study and related to self-care abilities. Diabetes knowledge was measured in 6 studies and improved significantly after educational interventions. Overall, studies showed that educational interventions significantly impacted self-efficacy, anthropometric measures, hemoglobin A1c levels, utilization of care and routine programme and attitudes regarding their health.

Conclusions: The findings highlight the importance of a comprehensive and culturally appropriate educational intervention for this population. Further research is needed to develop such intervention and assess its effectiveness to change behaviour, such as increasing physical activity.

Keywords: Attitudes; Behaviour change; Diabetes mellitus type 2; Health knowledge; Patient education as topic; Philippines; Practice.

Copyright © 2022 Diabetes India. Published by Elsevier Ltd. All rights reserved.

Publication types

• Diabetes Mellitus* / epidemiology
• Diabetes Mellitus* / therapy
• Patient Education as Topic*
• Philippines / epidemiology

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• Open access
• Published: 09 May 2024

Prevalence and factors associated with diabetes-related distress in type 2 diabetes patients: a study in Hong Kong primary care setting

• Man Ho Wong 1 ,
• Sin Man Kwan 1 ,
• Man Chi Dao 1 ,
• Sau Nga Fu 1 &
• Wan Luk 1  

Scientific Reports volume  14 , Article number:  10688 ( 2024 ) Cite this article

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• Endocrine system and metabolic diseases

Diabetes-related distress (DRD) refers to the psychological distress specific to living with diabetes. DRD can lead to negative clinical consequences such as poor self-management. By knowing the local prevalence and severity of DRD, primary care teams can improve the DRD evaluation in our daily practice. This was a cross-sectional study conducted in 3 General Out-patient Clinics (GOPCs) from 1 December 2021 to 31 May 2022. A random sample of adult Chinese subjects with T2DM, who regularly followed up in the selected clinic in the past 12 months, were included. DRD was measured by the validated 15-item Chinese version of the Diabetes Distress Scale (CDDS-15). An overall mean score ≥ 2.0 was considered clinically significant. The association of DRD with selected clinical and personal factors was investigated. The study recruited 362 subjects (mean age 64.2 years old, S.D. 9.5) with a variable duration of living with T2DM (median duration 7.0 years, IQR 10.0). The response rate was 90.6%. The median HbA1c was 6.9% (IQR 0.9). More than half (59.4%) of the subjects reported a clinically significant DRD. Younger subjects were more likely to have DRD (odds ratio of 0.965, 95% CI 0.937–0.994, p  = 0.017). Patients with T2DM in GOPCs commonly experience clinically significant DRD, particularly in the younger age group. The primary care clinicians could consider integrating the evaluation of DRD as a part of comprehensive diabetes care.

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Introduction.

It is estimated that the prevalence of type 2 diabetes mellitus (T2DM) in adults in Hong Kong (HK) is approximately 10% of the population 1 . The Hospital Authority of Hong Kong provides public healthcare services to around 400,000 diabetic patients, with the General Out-patient Clinics (GOPCs) offering primary care to over 60% of these individuals 2 . People living with T2DM are affected by this chronic and progressive condition not only physically, but also emotionally. Diabetes-related distress (DRD) refers to the psychological distress specific to living with diabetes. It includes a wide range of emotions, such as feeling overwhelmed by the demands of self-management and restrictions. People with T2DM have to control diet, regularly do exercise and take medications 3 . Many of them may have fears of existing or future diabetes complications, concerns about hypoglycaemia and frustration with care providers 4 .

DRD involves emotional symptoms that may overlap with some psychological conditions, such as depression. However, a previous literature has demonstrated that DRD and depression are different constructs that need different assessment and management approaches 5 . Compared to depression, DRD is peculiar to the emotional distress caused by relentless self-management of diabetes and it does not imply underlying psychopathology. Also, DRD is more closely associated with diabetes-related behavioural and biomedical outcomes than depression. Particularly, it has been shown that DRD influences glycaemic control whereas the impact of depression appears to be equivocal 5 , 6 , 7 . Compared to depression, DRD is highly responsive to clinical intervention 4 . A systemic review has shown that interventions delivered by primary care clinicians, psychoeducation and motivational interviewing resulted in significant DRD reduction 8 .

DRD is prevalent among patients with T2DM, in which a meta-analysis demonstrated the overall prevalence of DRD was 36% 2 . Also, studies in China found that 42.5–77.2% of Chinese people with T2DM experienced DRD 9 , 10 , 11 , 12 . The occurrence of DRD may be influenced by age, gender, culture, type of diabetes, use of insulin, number of complications and duration of diabetes 13 . DRD can lead to negative clinical consequences as studies have shown that a high level of DRD was associated with poor self-management, suboptimal glycaemic control and poor quality of life 14 , 15 , 16 , 17 . The American Diabetes Association recommended that DRD should be routinely monitored, particularly when treatment targets are not met and/or at the onset of diabetes complications 18 . However, DRD is not assessed or recognized in most of the primary care practices in Hong Kong. Since the local prevalence and severity of DRD remain unknown, it is difficult to determine whether DRD assessment should be routinely included in local DM care.

The primary objective of this study was to study the proportion of clinically significant DRD among patients with T2DM in GOPCs in HK. The secondary objective was to identify the associated factors of DRD.

There are 2 hypotheses in this study. (1) The proportion of clinically significant DRD among patients with T2DM in GOPC in HK is common, which is at least 36%, according to existing literature. (2) There is a significant association of DRD with demographic and clinical parameters.

Methodology

Study design.

This was a cross-sectional and prospective study conducted in three GOPCs in HK from 1 December 2021 to 31 May 2022. The three GOPCs include South Kwai Chung Jockey Club GOPC, Ha Kwai Chung GOPC and Cheung Sha Wan Jockey Club GOPC. The inclusion criteria were all adult Chinese patients, who had known diagnosis of T2DM and had at least two regular follow-ups for T2DM in the selected clinic in the past 12 months.

The exclusion criteria were patients diagnosed with type 1 diabetes, patients who had active follow-up of T2DM or were prescribed DM medications in Medicine Department specialist out-patient clinic, patients with known psychiatric illnesses who had active follow-up in either Psychiatry specialists or mental health services, patients who did not have diabetes related blood tests in the past 12 months from the study period, pregnant women, patients who did not understand written Chinese and mentally incapacitated persons.

A list of patients assigned with the International Classification of Primary Care (ICPC) code T90 (Diabetes; non-insulin-dependent) in the selected clinic was drawn from the Hospital Authority’s Clinical Data Analysis and Reporting System (CDARS) 2 weeks prior to the scheduled follow-up appointment with a corresponding appointment number. Up to 5 patients were selected from the list using random number table each day during the study period. A reminder was set in the computer system to identify those selected patients. The patients were invited and asked for consent to participate the study by the attending doctors. Information sheets about the study were given. Patients would complete the questionnaire individually and return it to the healthcare assistant in the clinic. Patients who refused to participate or give consent in this study were regarded as non-responders. Patients who had incomplete questionnaires or missing data were excluded from the statistical analysis. This study follows the principles of Declaration of Helsinki.

Sample size

The sample size was calculated by using the sample size formula:

where the desired precision was taken to be within 5% at 95% confidence interval.

Z = value from standard normal distribution corresponding to desired confidence level (Z = 1.96 for 95% CI)

P is expected true proportion

e is desired precision (margin of error).

The expected proportion in the study population was set to be 36% based on the overall prevalence in the previous meta-analysis study 2 .

Assuming the response rate was 90%, the sample size was estimated to be 355/0.9 = 395 patients, which would round up to 400 patients. Thus, we would aim at recruiting at least 400 patients.

Measurement

Diabetes Distress Scale (DDS) is one of the most commonly used and validated self-report measures to evaluate DRD internationally. The DDS is specific to patients with T2DM and provides a more comprehensive assessment to overcome the psychometric limitations of other measures such as Problems Areas in Diabetes (PAID) scale 2 . Another strength is that DDS also allows healthcare providers to identify the key sources of DRD 4 . The Chinese version of the Diabetes Distress Scale (CDDS-15) was validated in Hong Kong with consistent factor structure and good internal reliability (Cronbach’s alpha 0.902), which is specific for clinical use in Hong Kong Chinese type 2 diabetic patients 19 . There are 3 categories of CDDS-15, consisting of emotional burden (6 items), regimen- and social support- related distress (6 items), and physician-related distress (3 items) 19 . Each item was rated by patients using a 6-point Likert scale from 1 for “not a problem” to 6 for “a very serious problem.” The total mean item score was determined by adding the responses for all items and dividing by 15. Each subscale mean score was calculated by summing item responses in that subscale and dividing by the corresponding number of items. As reported by the study “When is diabetes distress clinically meaningful?: establishing cut points for the Diabetes Distress Scale”, an overall mean score ≥ 2.0 is considered clinically significant 17 . DRD was regarded as a dichotomous variable in this study, with subjects considered to have clinically significant DRD if CDDS-15 mean score ≥ 2.0.

We collected the data by using a printout questionnaire, consisting of three components: (1) The score of the CDDS-15; (2) demographic characteristics such as age, gender, education level, employment status, need of financial assistance to support basic living with Comprehensive Social Security Assistance (CSSA), living arrangement, and smoking status; (3) clinical parameters were obtained by reviewing participants’ medical records, including duration of T2DM, number of oral hypoglycaemic agent, use of insulin, latest Haemoglobin A1c (HbA1c) level, body mass index (BMI), diabetes complications and frequency of hypoglycaemic episodes in the past month. (see Appendix).

The primary outcome was the proportion of DRD among patients with T2DM in the selected study centres. The secondary outcome was the associated factors of DRD including demographic characteristics and clinical parameters as mentioned above.

Statistical analysis

The collected data was analyzed using the IBM Statistical Product and Service Solutions (SPSS) version 25 software. Qualitative variables were presented as frequencies and percentages. Quantitative variables were described as mean and standard deviation (SD), or median and interquartile range (IQR), as appropriate.

Pearson’s Chi-squared test was performed to compare the qualitative variables between participants without clinically significant DRD (DDS < 2) and participants with clinically significant DRD (DDS ≥ 2). Student’s t- test and Mann–Whitney U test was applied for quantitative variables with normal and non-normal distribution, respectively. When variables showed a p -value < 0.2 in the univariate analysis, they would be incorporated into the multivariate analysis. It was done to assure that all potentially associated variables were studied. Logistic regression analysis was used to adjust the confounding effect between variables and to identify the associated factors of DRD in those participants. Findings were considered statistically significant when the p -value < 0.05.

Ethics approval and consent to participate

Informed consent in written form was obtained from all patients. The study was approved by the Hospital Authority Kowloon West Cluster Research Ethics Committee (KWC REC Reference: KW/EX-21-121(162-06)). The CDDS-15 questionnaire was granted permission for use in this study by American Diabetes Association (Permission Request Number: KL072021-MHW). This study follows the principles of Declaration of Helsinki.

Patients’ demographic and clinical characteristics

We distributed 408 questionnaires, thirty-eight patients refused to participate in the study and the response rate was 90.6%. Eight questionnaires were found to have incomplete data and were discarded. Therefore, the total number of questionnaires included in the statistical analysis was 362.

Among the 362 participants, the mean age was 64.2 years old (SD 9.5) and male to female ratio was approximately 1:1. Fewer than 8% of participants (n = 27) had attained tertiary education. Approximately 40% of the participants (n = 146) were retired. The median HbA1c was 6.9% (IQR 0.9). The median duration of living with T2DM since diagnosis was 7.0 years (IQR 10.0). The mean BMI was 26.0 (SD 3.9). For the regimen type, approximately 90% of the participants (n = 324) were taking oral hypoglycaemic agents with or without insulin. The participants’ demographic and clinical characteristics were presented in Table 1 .

Proportion of DRD

A total of 59.4% of the study participants were found to have clinically significant DRD according to the total mean item score (DDS ≥ 2). Among the 3 subscales of DRD, emotional burden was observed in 64.9% of participants, followed by regimen- and social support-related distress (64.1%). Physician-related distress (33.7%) was relatively less affected. This is illustrated in Fig.  1 .

The proportion of clinically significant DRD among patients with T2DM in different subscales (n = 362).

Factors associated with DRD

In the univariate analysis, age and employment status were found to be significantly associated with DRD (unadjusted p  < 0.05). These factors, together with other variables with unadjusted p  < 0.2 including BMI, HbA1c level and regimen type, were further analyzed in the multivariate logistic regression, as shown in Table 2 . Only age was significantly associated with the occurrence of DRD among patients with T2DM, in which the adjusted odds ratio was 0.965 (95% CI 0.937–0.994, adjusted p  = 0.017).

In our study, 59.4% of patients with T2DM in the GOPC setting in HK suffered from clinically significant DRD. It is comparable to the studies in China with a reported prevalence 42.5–77.2% 9 , 10 , 11 , 12 . However, it is much higher than the overall prevalence 36% in the meta-analysis, in which the majority of the studies involved were from Western countries 2 . In Asia, the prevalence of DRD was reported to be 32%, 49%, and 53% in Singapore, Malaysia, and India, respectively 20 , 21 , 22 . The prevalence varies substantially across countries. This could be explained by the difference in the healthcare system, demographics, and cultural background.

Among the 3 subscales of DRD, the proportion of physician-related distress was the lowest in this study, which is similar to the findings in other studies 17 , 23 . Participants might not attribute their distress to physicians if they could obtain sufficient expertise and direction from physicians regarding their T2DM management. Nonetheless, healthcare professionals should pay more attention to the emotional side of diabetes care as more than 60% of subjects in this study had clinically significant emotional burden and regimen- and social support-related distress.

Our study showed that older age was associated with lower odds of DRD (OR 0.965). This is consistent with the results of other studies 24 , 25 , 26 . One study showed that the relation of DRD to psychological and behavioral outcomes is attenuated in older adults, regardless of the duration of T2DM 27 . One hypothesis is that older adults react less to stress because their previous experiences in coping with stress have led to better emotion regulation strategies 28 . On the other hand, younger patients usually have more responsibilities at work and family such as supporting their children and elderly family members 26 . These stressors can worsen the burden associated with the self-management of T2DM.

The HbA1c level was not significantly associated with DRD in our study. This is in line with the results of various international studies 2 , 16 , 23 . In contrast, a study conducted in a specialist clinic in HK using the CDDS-15 questionnaire showed that DRD had a positive relationship with HbA1c level 29 . The disparity may be explained by the difference in the healthcare setting and patients’ demographics. Also, only a minority of patients (7.5%) were prescribed insulin in the GOPC setting in our study, whereas 48% of the subjects were prescribed insulin in the specialist clinic in that study. In fact, there is mixed evidence in the literature regarding the relationship between glycaemic control and DRD 4 . Although DRD is modestly associated with poor glycaemic control, patients with good glycaemic control can also experience high DRD 4 , 16 . Achieving the HbA1c target may require intensive efforts that are potentially impacting other areas of their life such as social activities. This implies patients with T2DM may have an ongoing fear of disease complications or encounter challenges of self-management regardless of their latest glycaemic control.

The strengths of this study were that it was a multi-center study and there was a relatively high response rate. Measures such as invitations by healthcare providers could help reduce the number of non-responders. Moreover, it was one of the pioneer studies regarding DRD in the primary care setting in HK.

However, there are several limitations of this study. First, the use of a self-reported instrument in this study was influenced by social desirability bias. Physician-related distress might be underestimated in this study as patients might worry about negative effects on their treatment process if they declare a lack of confidence in the physician’s expertise in their diabetes management 30 . Second, the causality of the relationships could not be determined due to the study’s cross-sectional design. Further longitudinal studies are suggested to delineate causal relationships. Third, this study was conducted in three GOPCs only and there could be selection bias, therefore the study findings cannot be generalized to all patients with T2DM in HK. Fourth, it is important to acknowledge the restricted scope of this study on assessing other comorbidities such as hypertension and hyperlipidaemia. This study focused primarily on the clinical conditions directly associated with diabetes, including macrovascular and microvascular complications. Future studies could consider incorporating a boarder range of comorbidities to gain a more comprehensive understanding of the impact of diabetes-related distress. Lastly, as the study period coincided with the fifth wave of COVID-19 in HK, it could be a particularly stressful time for patients with T2DM to comply with their diet plan and exercise routine.

There are some clinical implications drawn from this study. Family physicians are on the frontlines responsible for the diagnosis and management of patients with T2DM and this study showed that a high proportion of patients with T2DM experience psychological distress. This finding alerts family physicians about the importance of a holistic approach in T2DM management. Regular evaluation of DRD by a self-reported instrument could be considered to incorporate with the annual assessment of T2DM in the GOPC setting. DRD does not typically disappear when left unaddressed, but DRD interventions do not require the expertise of a mental health professional 4 . In most cases, interventions offered by family physicians including motivational interviewing can help relieve DRD and thus improve the self-management of T2DM 4 , 8 . A practical guide on addressing DRD in clinical care is also available 4 . Further research on monitoring and addressing DRD in primary care in HK is warranted.

The psychological component of diabetes is not routinely assessed in most of the primary care practices in HK. This study demonstrated that a high proportion of patients with T2DM in GOPCs experience clinically significant DRD. Younger age was identified as an associated factor. Evaluation of DRD is suggested to integrate as a part of comprehensive diabetes care in the primary care setting.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

I would like to thank American Diabetes Association for granting us permission to use the CDDS-15 questionnaire in our study. In addition, I would like to thank all the doctors, nurses and staff for supporting this study.

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

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• Study protocol
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• Published: 03 June 2019

The Community Health Assessment Program in the Philippines (CHAP-P) diabetes health promotion program for low- to middle-income countries: study protocol for a cluster randomized controlled trial

• Gina Agarwal   ORCID: orcid.org/0000-0002-5691-4675 1 ,
• Ricardo N. Angeles 1 , 4 ,
• Lisa Dolovich 1 , 2 ,
• Janusz Kaczorowski 3 ,
• Jessica Gaber 1 ,
• Dale Guenter 1 ,
• Floro Dave Arnuco 4 ,
• Hilton Y. Lam 5 ,
• Lehana Thabane 6 ,
• Daria O’Reilly 6 ,
• Rodelin M. Agbulos 7 ,
• Rosemarie S. Arciaga 4 , 8 ,
• Jerome Barrera 4 ,
• Elgie Gregorio 4 ,
• Servando Halili Jr 9 ,
• Norvie Jalani 10 &
• Fortunato Cristobal 4  

BMC Public Health volume  19 , Article number:  682 ( 2019 ) Cite this article

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Type 2 diabetes is increasing globally, with the highest burden in low- to middle-income countries (LMICs) such as the Philippines. Developing effective interventions could improve detection, prevention, and treatment of diabetes. The Cardiovascular Health Awareness Program (CHAP), an evidence-based Canadian intervention, may be an appropriate model for LMICs due to its low cost, ease of implementation, and focus on health promotion and disease prevention. The primary aim of this study is to adapt the CHAP model to a Philippine context as the Community Health Assessment Program in the Philippines (CHAP-P) and evaluate the effect of CHAP-P on glycated hemoglobin (HbA1c) compared to a random sample of community residents in control communities.

Six-month, 26-community (13 intervention, 13 control) parallel cluster randomized controlled trial in Zamboanga Peninsula, an Administrative Region in the southern Philippines. Criteria for community selection include: adequate political stability, connection with local champions, travel feasibility, and refrigerated space for materials. The community-based intervention, CHAP-P sessions, are volunteer-led group sessions with chronic condition assessment, blood pressure monitoring, and health education. Three participant groups will be involved: 1) Random sample of community participants aged 40 or older, 100 per community (1300 control, 1300 intervention participants total); 2) Community members aged 40 years or older who attended at least one CHAP-P session; 3) Community health workers and staff facilitating sessions. Primary outcome: mean difference in HbA1c at 6 months in intervention group individuals compared to control. Secondary outcomes: modifiable risk factors, health utilization and access (individual); diabetes detection and management (cluster). Evaluation also includes community process evaluation and cost-effectiveness analysis.

CHAP has been shown to be effective in a Canadian setting. Individual components of CHAP-P have been piloted locally and shown to be acceptable and feasible. This study will improve understanding of how best to adapt this model to an LMIC setting, in order to maximize prevention, detection, and management of diabetes. Results may inform policy and practice in the Philippines and have the potential to be applied to other LMICs.

Trial registration

ClinicalTrials.gov ( NCT03481335 ), registered March 29, 2018.

Peer Review reports

As of 2013, an estimated 382 million people are living with type 2 diabetes globally, with the large majority of these individuals living in low- to middle-income countries (LMICs) [ 1 ]. It is estimated that 45.8% of individuals with diabetes are undiagnosed, with 83.8% of those undiagnosed being from LMICs [ 2 ]. The number of people with diabetes is expected to increase significantly by 2035, with the projected increase higher in low (108%) and low-middle income (60%) countries compared to upper-middle (51%) and high income (28%) countries [ 1 ]. For LMICs, one of the challenges of managing the impact of diabetes is developing effective and low-cost interventions to prevent or delay the onset of type 2 diabetes that can be successfully implemented, scaled up, and sustained [ 3 ]. Several studies have demonstrated the cost-effectiveness of early diagnosis and management of diabetes through the use of opportunistic screening and risk assessment screening tools [ 4 , 5 ]. Therefore, adopting and testing an effective low-cost intervention that enhances early diagnosis and management of diabetes shows promise for LMICs.

In 2013, the Philippines, considered an LMIC, had an overall diabetes prevalence of 6.0%, an estimated 1.7 million people with undiagnosed diabetes, and 54,535 diabetes-related deaths [ 6 ]. The Philippines is estimated to have over 6 million people with diabetes by the year 2035 [ 1 ]. The Philippines has begun implementation of the World Health Organization Package of Essential Noncommunicable Disease Interventions for primary care settings in low resource areas [ 7 ], created the National Centre for Disease Prevention and Control in 2000 including a diabetes-specific office, and has listed reduction of mortality and morbidity from lifestyle-related diseases such as diabetes as one of the goals in the “National Objectives for Health 2005-2010” [ 8 ]. However, there are currently some gaps in the areas of detection and treatment for diabetes. For example, though screening kits and medications are available at no cost, the case detection for new cases of diabetes is poor, the diabetes registry is poorly maintained, and the medications often get left unused in the stockrooms of local health centres (Dr M.A. Mabolo, Philippine Department of Health, personal communication, June 16, 2014). Knowledge about diabetes is also a gap in the Philippines; in a study in one region of the Philippines the mean score for diabetes knowledge among people diagnosed with diabetes was only 43% [ 9 ].

The Cardiovascular Health Awareness Program (CHAP) intervention model may be particularly suited to LMICs due to its low cost, implementability, and focus on population-based health promotion and disease prevention. CHAP is a community-based, primary care-centred, volunteer-led, free of charge, cardiovascular disease risk assessment and blood pressure monitoring program, which is combined with health education sessions for community-dwelling older adults [ 10 ]. A large community cluster randomized controlled trial in Canada demonstrated that the CHAP intervention resulted in a statistically significant 9% reduction in annual hospital admissions due to stroke, heart failure, and heart attacks in people aged 65 and over at the population [ 11 ]. The CHAP has been successfully expanded to include a diabetes risk assessment component in the Community Health Awareness of Diabetes (CHAD) program and other community adaptations [ 12 , 13 ].

The Community Health Assessment Program for the Philippines (CHAP-P) was based on a formal partnership between universities in the Philippines (Ateneo de Zamboanga University School of Medicine) and Canada (McMaster University Department of Family Medicine) with guidance from a Project Advisory Committee composed of collaborators and researchers from Canada, the Philippines, Peru, Thailand, Tunisia, and the UK. The CHAP-P intervention was developed through a multi-stage study that combined specific elements of the CHAP and CHAD, adapting the intervention to be more appropriate for LMICs in general and the local setting of communities in Southwestern Philippines (Zamboanga Peninsula) in particular. Zamboanga Peninsula was chosen as the program site for this initiative because it exemplifies underprivileged regions in many LMICs in terms of geographical isolation, poverty, and scarce health resources where low-cost, community-owned health programs – such as CHAP-P – are urgently needed.

This multi-stage research project is culminating in a parallel cluster randomized controlled trial (RCT), the protocol of which is the focus of this paper. The primary aim of this RCT is to determine the effects of the CHAP-P intervention on HbA1c levels among a random sample of community residents 40 years of age and older, compared to a random sample of community residents in control communities under usual care. The secondary aims are to determine CHAP-P’s effectiveness compared to usual care in impacting: i) modifiable lifestyle risk factors for developing type 2 diabetes; ii) self-reported health utilization and access to care; iii) diabetes detection and management indicators in clusters (screening rates, initiation of medical management, hospital admissions, and mortality due to diabetes and its complications); and iv) program cost-effectiveness and cost-utility.

Theoretical framework and development approach

The overall project is a three-phase mixed methods evaluation. Phase 1 was a qualitative community scan that examined the sociocultural, economic, and health service context in the Zamboanga Peninsula, Philippines in order to adapt the CHAP intervention for best fit. Phase 2 was a three-stage pilot study to finalize assessment tools and evaluation methods, and identify potential problems with implementation in preparation for the RCT. Finally, Phase 3 is the RCT described in this paper. See Fig.  1 for an overview of the overall project design.

Overview of the CHAP-P Research Program

Greenhalgh and colleagues’ model of diffusion of innovation [ 14 ] was used to guide the adaptation of CHAP to the Philippines context during Phase 1. Our project is also guided by the Integrated Innovation approach, which posits that one can create a synergistic effect when addressing an issue or challenge by combining social, business, and scientific innovations [ 15 ]. Social innovations can bring scientific solutions to a local setting, while business innovations can deliver them at an affordable price point. The Integrated Innovation approach will be combined with the knowledge-to-action process, which depicts the relationship between knowledge creation and action steps to promote the application of knowledge (in our case the generation of CHAP-P) and evaluation of the success of the actions taken [ 16 ].

Methods/design

Zamboanga Peninsula is an Administrative Region of the Philippines on the island of Mindanao in the southern Philippines consisting of three provinces (Zamboanga del Norte, Zamboanga del Sur, and Zamboanga Sibugay) and two independent cities (Isabela and Zamboanga City). In 2012, this region had the fourth highest poverty incidence of the 17 regions of the Philippines (33.7%) [ 17 ]. Communities are separated by sea and mountains, with several ethnic and linguistic groups spread throughout the region and connected by inconsistent transportation and communication systems. The provinces and cities are broken down into municipalities, and the municipalities are broken into the smallest administrative districts in the Philippines, known as barangays , which are small villages or neighbourhoods. Each municipality is classified with an income class ranging from first (the highest income class) to sixth (the lowest) based on their average income in a four-year period. For the evaluation purposes, we will be recruiting 100 randomly selected residents aged 40 and over from each of 26 barangays (communities).

This study is a 26-community parallel open-label cluster randomized controlled trial. A community cluster design was chosen as CHAP-P is intended as a community-level intervention. Potential communities will be stratified by province, population size, income class, and type (urban versus rural). Thirteen barangays will receive the CHAP-P sessions and will be considered intervention communities, while the other 13 communities will receive care as usual and will be considered control communities. This will be done through paired randomization with staggered starts. Communities will be selected and randomized by the local program manager. Criteria for community selection include: security, connection with a local champion, feasibility for travel, and facility with refrigerated space for the HbA1c kits. Barangays will be paired based on municipality, population size, and similarity in the setting (i.e., religion, being under the same health district providing health services, and distance from the municipal centre). This will be done based on the advice of the local health workers and leaders in the municipalities and cities. Allocation will be done by computer generated randomization. Measurements of individual participants will be taken as a repeated cross-sectional sample at baseline and at 6 months. The Pragmatic-Explanatory Continuum Indicator Summary 2 (PRECIS-2) [ 18 ] was used to make design decisions based on the pragmatism of the trial (see Fig.  2 ). Reporting will follow the CONSORT 2010 statement: extension for cluster randomized trials [ 19 ]; reporting of this protocol follows the SPIRIT 2013 checklist [ 20 ], see Additional file  5 .

PRECIS Diagram

Participant recruitment

There will be three participant groups in the study. First, 100 participants will be randomly selected and recruited from each of the 26 barangays involved in the trial for a community survey. Households will be chosen via door-to-door systematic random sampling conducted by research staff. Within selected households, individuals 40 years of age or older will be eligible to participate in the survey. If there is more than one eligible and willing individual within a household, the last-birthday selection method [ 21 ] will be used to choose a single individual to participate. If there are no eligible or willing participants within a household, the team will move on to the next household based on the systematic random sampling procedure. A member of the research staff team will ask individuals selected to participate in the study to provide consent, and the survey will be conducted with consenting individuals (See Additional files  1 , 2 , 3 and 4 for all consent forms). Participants will then be asked to go to a community location for the HbA1c test and to be provided with a small token of appreciation. The survey participants are not necessarily the same individuals who will attend the CHAP-P sessions in intervention communities, though entire communities will be invited to the CHAP-P sessions.

The second participant group are those that attend the CHAP-P sessions. CHAP-P participants are community residents aged 40 years of age or older. As part of participating in the CHAP-P sessions, individuals give consent to participate in the study and for the information collected during the sessions to be linked with municipal/city health office records.

The final participant group is the Barangay Health Workers (BHWs) and other Lead Local Organization (LLO) staff that will be involved in facilitating the CHAP-P sessions. They will be recruited through convenience sampling with research team members inviting those who have been involved with the CHAP-P intervention. Those BHWs and other LLO staff that consent to be part of the evaluation will be invited to participate in focus groups or key informant interviews, depending on their role and availability.

Due to the nature of the intervention as a community-wide health promotion program, this is an open label trial. However, community survey participants are not necessarily aware of the ongoing trial, community assignments, and study group allocation of their community.

Primary outcome and measure

The primary outcome is the mean difference in HbA1c at 6 months in a random sample of individuals from the random sample of individuals from the intervention barangays compared to the control barangays. HbA1c will be tested at a community location at baseline and 6 months, after the participants have completed the community survey in their homes.

Secondary outcomes and measures

There are a number of secondary outcomes which will evaluate the mean differences between intervention and control groups at 6 months. These outcomes, whether they pertain to cluster or individual participant level, and their measures and sources are listed in Table  1 .

Community process evaluation and fidelity checks

A community process evaluation will also be undertaken during the project in order to monitor the implementation of the CHAP-P intervention to assess for any problems or process issues during or after the implementation of the project. Monthly reports from communities, monthly observational fidelity checklists from research assistants, and qualitative focus groups/interviews will be analyzed for this component of the evaluation.

Cost-effectiveness and cost-utility

A cost-effectiveness analysis will be conducted comparing the program cost of implementing CHAP-P and healthcare resource utilization costs to percentage reduction in HbA1c. A cost-utility analysis will also be conducted to determine the cost of the program and healthcare resource utilization costs per quality-adjusted life year (QALY) gained, using the EuroQol-5 dimension-5 level (EQ-5D-5 L) [ 24 , 25 ] as the indicator of quality of life.

Data collection and management

Community survey participants will be interviewed in their homes by trained research staff at baseline and 6 months. Questionnaires will be completed on paper and later entered into a REDCap [ 26 ] database by trained research staff. This survey was adapted from the measure used in the CP@clinic program in Canada [ 13 ] and includes questions from other validated questionnaires as well as physical measurements such as blood pressure, height, weight, and waist circumference. The questions include: demographics; knowledge about diabetes and cardiovascular health; risk factors and behaviours, including the Finnish Diabetes Risk Calculator (FINDRISC) [ 23 ]; quality of life using the EQ-5D-5 L [ 24 , 25 ]; perceived confidence; perceived concern and understanding of risk; self-efficacy to improve health behaviours; physical activity using the International Physical Activity Questionnaire (IPAQ) [ 22 ]; and health utilization and access. The WatchBP Office Target will be used to measure blood pressure as it was found to show the most reliable results based on our pilot study [ 27 ]. This community survey will be completed at baseline and at 6 months and will use an open-cohort design.

After completing the community survey in their homes, these participants will be invited to a community location where they will have their glycated hemoglobin (HbA1c) tested using the A1CNow + point-of-care device, which is certified by the National Glycohemoglobin Standardization Program [ 28 ]. HbA1c testing will be conducted at baseline and 6 months, following the community survey at each time point.

Focus group discussions will be held at 6 months for study participants, BHWs, and other LLO staff using a standardized focus group guide consisting of open-ended questions primarily focused on identifying the barriers and facilitators to implementing CHAP-P. Further sources of data include monthly community reports from the communities, monthly observational checklists by research assistants, and record review of the CHAP-P session databases and Rural Health Unit databases.

For CHAP-P session participants, the FINDRISC, blood pressure, and other physical measurement data collected as part of the CHAP-P sessions will be included in the evaluation.

Paper data will be stored in a locked cabinet in a locked institutional office. Electronic data will be stored in an encrypted program (REDCap) or in password-protected files on a secure institutional network. Study data will be anonymized. For the community survey and CHAP-P session data, after the full data set is collected (including the HbA1c test results), data will be anonymized. For the qualitative data, once transcripts are produced from the interviews and focus groups, identifiers of participants will be removed.

Intervention

The 13 intervention barangays will receive the CHAP-P sessions. The intervention will occur as follows (see Fig.  3 ). First, residents will be invited to attend the CHAP-P sessions, which are facilitated by Barangay Health Workers (BHWs), who are trained local volunteers. The BHW role is a voluntary position accredited by local health boards, which provides primary health care service to the barangays [ 29 ]. BHWs will receive program-specific in-person training at the start of CHAP-P, with refresher sessions during their work with the program. During the CHAP-P sessions, the BHWs will collect participants’ consent, measure blood pressure, collect other physical measurements (height, weight, waist circumference), and collect participant information to determine clients’ risk of diabetes using the FINDRISC [ 23 ]. All data will be collected through an electronic REDCap mobile app database [ 26 ] via a tablet computer, which was found to be the most accurate and acceptable choice of data collection method for BHWs during the pilot stages [ 30 ].

CHAP-P Intervention

Based on findings during the assessment, BHWs will educate the CHAP-P participants on diabetes, cardiovascular risk factors, and healthy lifestyles, providing educational materials that have been adapted for a local context (including materials such as pamphlets, comic strips, and videos). Those CHAP-P participants whose FINDRISC scores indicate diabetes risk (moderate: score of 12–14, high: score of 15–20, or very high: score of > 20) will be referred to the Rural Health Unit for fasting blood glucose testing. Those who have blood pressure greater than 140/80 mmHg will be referred to the midwife, with those with blood pressure over 180/100 mmHg being immediately referred to the Rural Health Unit or District Hospital, and those with blood pressure under 180/100 mmHg being referred to the Rural Health Unit with less immediacy, for further evaluation and management. Those with other specific risk factors such as low physical activity, high salt intake, or smoking will be given further health education and referred to appropriate local programs. CHAP-P sessions will continue to be held twice a month in intervention communities, and residents will be encouraged to continue attending for ongoing follow-up and monitoring. The monthly observational fidelity checklists from research assistants will be undertaken to improve adherence to intervention protocols.

Data analysis

Quantitative outcomes.

The baseline characteristics will be analyzed using descriptive statistics reported by group as mean (standard deviation) or median (first quartile, third quartile) for continuous variables, and count (percentage) for categorical variables. The analysis of all outcomes to compare the groups will follow intention-to-treat principle. We will use multiple imputation to handle missing data. We will use Generalized Estimating Equations (GEE) to make comparisons between intervention and control communities, assuming an exchangeable correlation structure [ 31 ]. GEE will allow us to model the correlation of outcomes within communities. All results will be reported as estimates of effect, corresponding 95% confidence interval and associated p -values. All p-values will be reported to three decimal places with those less than 0.001 reported as p  < 0.001. All analyses will be performed using SAS 9.4 (Cary, NC) or Stata 11 (College Station, TX). See Table  2 for the statistical analysis plan.

Qualitative analysis

Transcripts will be cleaned and data will be summarized using thematic analysis (open coding axial coding, selective coding). QSR International NVivo 11 qualitative analysis software [ 32 ], will be used to store and manage qualitative data.

Economic analysis

Percentage decrease in participant HbA1c will be the measure of effectiveness used in the cost-effectiveness analysis. Cost per QALY will be calculated as the cost-utility measure; QALYs will be computed based on local EQ-5D-5 L values. Both cost-effectiveness and cost-utility analyses will include overall program cost measures and participant health resource utilization and cost thereof.

Power and sample size

CHAP-P is a community-wide intervention and community sizes vary from 3000 to 20,000 residents. We are using paired randomization, therefore intervention and control community pairs need to have relatively similar sizes. Our sample size for individuals was calculated based on a mean difference of HBA1c of 0.2% (SD = 1.09) with standard parameters (alpha = 0.05, power = 0.80). This required a sample size of 520 per arm. Based on our pilot, the intraclass correlation coefficient (ICC) was 0.006. We increased our ICC to 0.01 which inflated our sample size to 1034 per arm. We have opted to take 26 (13 pairs of intervention: control) communities with 100 residents per community giving a total sample size of 2600 residents (1300 per arm).

This study will provide a robust evaluation of a community diabetes program in the Philippines. Though the country is committed to preventing and treating lifestyle-related diseases such as diabetes, the level of commitment to implement programs and the amount of diabetes-related activities already being implemented varies greatly among communities [ 8 ]. Some community-based programs for type 2 diabetes tested in other LMICs including elements such as educational sessions, lifestyle instruction, and self-monitoring have shown significant positive outcomes including lowering weight, waist circumference, fasting plasma glucose levels, and HbA1c [ 33 , 34 ]. Diabetes self-management programs and other community-based interventions are being implemented across the Philippines, yet large-scale experimental studies are still a gap in the literature [ 9 , 35 , 36 , 37 ]. This study will help fill that gap.

A major strength of this study is the multi-phase, multi-year nature of the overall research program. The intervention was based on the evidence-based CHAP model from Canada, though needed to be adapted for the local context. Phase 1, the qualitative community scan, and Phase 2, piloting the elements, were vital to integrate the components and building a diabetes intervention that would make sense in the context of the Zamboanga Peninsula, Philippines. The mixed methods design included throughout the research program is another strength, with qualitative data included in this RCT to help explain and interpret quantitative results. Initially, a stepped-wedge cluster RCT was planned rather than a parallel cluster RCT, yet instead of solving issues of logistical constraints [ 38 ], it introduced some - the stepped-wedge design would have been more expensive and more time-consuming. Due to the variation in communities across the Philippines, the focus on a community-level approach is a key element in making a program such as CHAP-P work. The integration of perspectives from multiple key stakeholders throughout the process solidifies communities’ buy-in to the project. Finally, the health economics component of this study will provide policymakers and funders the information they need to decide whether implementation of a program such as CHAP-P is cost-effective for their communities.

Though we combined many elements to fit the program to the setting, there are still some limitations that warrant consideration. First, recruitment for CHAP-P sessions can be difficult, particularly within urban areas, and as a community intervention it is important to reach a substantial portion of the community. To improve penetration within the communities, we have decided to ensure the CHAP-P sessions rotate between puroks (a subdivision of a barangay) rather than having them in the same location week-by-week. Second, the mobile HbA1c test kit can be difficult to work with, as it only lasts for approximately 5 minutes in the heat and humidity of the Philippines. Due to that constraint, all HbA1c tests are now completed at a common community location; however, those locations still need refrigeration for the test kits, so access to refrigerated space is an inclusion criterion for communities. Finally, during the pilot studies there were some security concerns in the region that limited travel of the research team, so something similar may occur during the RCT implementation. This may affect the ability of the research team to visit communities for monthly fidelity checks, yet the intervention will be able to continue as BHWs can continue facilitating CHAP-P sessions in their local communities.

This study has the potential to improve diabetes detection, management, and prevention in the Philippines and similar LMICs. The results from this study will be shared with policymakers (municipal, provincial, regional, national) in the Philippines and our research partners in other LMICs and the Global Alliance for Chronic Diseases. Results will also be published in relevant conference and journals to disseminate our findings to other researchers and policy makers planning to implement an out-of-the-box program for diabetes detection, management, and prevention.

Abbreviations

Ateneo de Zamboanga University, Philippines

Barangay Health Worker

Community Health Awareness of Diabetes

Cardiovascular Health Awareness Program

Community Health Assessment Program in the Philippines

Canadian Institutes of Health Research

EuroQol-5 dimension-5 level (quality of life measure)

Finnish Diabetes Risk Score (measure)

Global Alliance of Chronic Diseases

Health Awareness and Behaviour Tool

Glycated hemoglobin

Hamilton Integrated Research Ethics Board, Canada

International Development Research Centre

International Physical Activity Questionnaire (measure)

Low- to middle-income country

Quality-adjusted life year

Randomized controlled trial

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Acknowledgements

The authors would like to thank the entire project team for their contributions to this research program, including staff and stakeholders in the Philippines and Canada, and the members of our international Project Advisory Group (including 5 primary investigators, 6 Canadian co-investigators or advisors, 5 Filipino co-investigators, a GACD representative, Canadian and Filipino research staff, and 4 other advisors from Tunisia, Thailand, and Peru).

This project is funded through the Canadian Institutes of Health Research (CIHR; project #139438) and the International Development Research Centre (IDRC; project # 107826–001) via the Global Alliance of Chronic Diseases (GACD; project DM04). The funding bodies had no role in study design, collection, analysis, interpretation of data, or in writing the manuscript.

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Department of Family Medicine, McMaster University, 1280 Main St W, Hamilton, Ontario, L8S 4L8, Canada

Gina Agarwal, Ricardo N. Angeles, Lisa Dolovich, Jessica Gaber & Dale Guenter

Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College Street, Toronto, Ontario, M5S 3M2, Canada

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School of Medicine, Ateneo de Zamboanga University, La Purisima St, 7000, Zamboanga City, Philippines

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Zamboanga City Health Office, Pettit Barracks, 7000, Zamboanga City, Philippines

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Contributions

GA and FC are leading the project for Canada and the Philippines, respectively. GA, FC, RNA, DG, LD, and JK contributed to the development of the research design and methods. RSA, RMA, JB, EG, SH, FDA, and NJ contributed to the contextualization of the research design and methods to the local setting. HYL and DO are contributing to the development of the methods for economic analysis. LT is contributing to the methodology for statistical analysis. JG contributed to drafting of the article, acquisition of ethical approval, and registration to Clinical Trials with GA and RNA. All authors read and approved the final manuscript.

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Correspondence to Gina Agarwal .

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Ethics approval and consent to participate.

This trial and all materials (consent, database, education materials) has obtained ethics approval from the Ateneo de Zamboanga (ADZU) research ethics board, Philippines (approval #2018-SM-0001), and the Hamilton Integrated Research Ethics Board (HiREB), Canada (project ID #4303). Any amendments regarding protocol changes will be submitted to both ethical review boards. The trial is also registered with ClinicalTrials.gov (identifier NCT03481335, first posted March 29, 2018; last updated August 17, 2018). Signed, written, informed consent will be obtained from study participants in all groups prior to participation in elements of the study. To maintain confidentiality, data will be de-identified prior to analysis. The data that is collected will only be made available for review by authorized persons including CHAP-P research team in the Philippines and Canada, institutional review boards, and transcriber of the focus groups. Information stored on computers will be protected by a password. Information stored on paper will be kept in locked cabinets.

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Additional files

Additional file 1:.

Consent Form – Community Survey Participant. (DOCX 165 kb)

Additional file 2:

Consent Form – CHAP-P Session Participant. (DOCX 169 kb)

Additional file 3:

Consent Form – Community Resident Focus Group. (DOCX 164 kb)

Additional file 4:

Consent Form – BHW. (DOCX 173 kb)

Additional file 5:

SPIRIT 2013 Checklist. (DOC 123 kb)

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Agarwal, G., Angeles, R.N., Dolovich, L. et al. The Community Health Assessment Program in the Philippines (CHAP-P) diabetes health promotion program for low- to middle-income countries: study protocol for a cluster randomized controlled trial. BMC Public Health 19 , 682 (2019). https://doi.org/10.1186/s12889-019-6974-z

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• Cluster randomized trial
• Low- to middle-income countries (LMICs)
• Philippines
• Diabetes mellitus
• Hypertension
• Health promotion
• Disease prevention

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Diabetes Care in the Philippines

• Gerry H. Tan

Diabetes  is increasing at an alarming rate in Asian countries including the Philippines. Both the prevalence and incidence of  type 2 diabetes  (T2D) continue to increase with a commensurate upward trend in the prevalence of  prediabetes .

The aim of this study was to review the prevalence of diabetes in the Philippines and to describe extensively the characteristics of diabetes care in the Philippines from availability of diagnostics tests to the procurement of medications.

A literature search was performed using the search words  diabetes care  and  Philippines . Articles that were retrieved were reviewed for relevance and then synthesized to highlight key features.

The prevalence of diabetes in the Philippines is increasing. Rapid urbanization with increasing dependence on electronic gadgets and sedentary lifestyle contribute significantly to this epidemic. Diabetes care in the Philippines is disadvantaged and challenged with respect to resources, government support, and economics. The national insurance system does not cover comprehensive diabetes care in a preventive model and private insurance companies only offer limited diabetes coverage. Thus, most patients rely on “out-of-pocket” expenses, namely,  laboratory procedures  and daily medications. Consequently, poor pharmacotherapy adherence impairs prevention of complications. Moreover,  behavioral modifications  are difficult due to cultural preferences for a traditional diet of refined sugar, including white rice and bread.

Conclusions

Translating clinical data into practice in the Philippines will require fundamental and transformative changes that increase diabetes awareness, emphasize  lifestyle change  while respecting cultural preferences, and promote public policy especially regarding the health insurance system to improve overall diabetes care and outcomes.

• diabetes care
• Philippines
• Southeast Asia
• type 2 diabetes

Next event in:

NATIONAL ASSEMBLY OF DIABETES EDUCATORS

News & Advances in Diabetes Self-care Essentials

November 7, 2023

Venue: Makati Diamond Residences, Makati City

MEAL PLANNING FOR DIABETICS

By: Ivy D. Ramallosa, RND

• The Philippines

Diabetes Philippines

The Pulse of the Philippine Diabetes Association (PDA) began to throb thirty six years ago, in the early part of July 1958. This was about the time when a group of internists and devoted physicians committed to the care, protection and recuperation of the diabetic patient banded together. It was the aim of this group to unify all interests and entities in the Philippines concerned about diabetes mellitus into a single association. Thus, today, PDA stands as the umbrella organization of all associations involved in the care of the diabetic patient.

On February 22, 1962, the Association was incorporated. Among the purposes for which the PDA was founded were to foster and support studies and researches on the prevention and care of diabetes mellitus, including cooperation with the government agencies to this effect; to collect, analyse, interpret, interchange and disseminate information about the disease in accordance with the latest findings, and to this end, to affiliate or establish relations with other diabetes institutions in other countries; and finally also to promote understanding of the individuals diabetics to lead normal and useful lives and conduct a Diabetes Detection Drive to find undiscovered diabetics.

• To generate public awareness and help towards early detection of the disease.
• To help support studies and foster research on the prevention and care of diabetes mellitus; to promote awareness and understanding so people with diabetes may lead normal and productive lives.
• To improve diabetes care, education and research to prevent the onset of the disease in high risk individuals and the complications in those already afflicted by it. To improve quality of life for Filipinos with diabetes.
• To act as the umbrella organization of all associations involved in the care for people with diabetes.

World Diabetes Day:

Each year World Diabetes Day is thematically linked to a specific aspect related to diabetes. Although, the Philippines has its own Diabetes Awareness Week celebration; in keeping with the IDF, The Diabetes Philippines celebrates World Diabetes Day each year. It is celebrated simultaneously in nationwide events through Diabetes Philippines Chapters.

Health Education:

Annual Convention aimed to update scientific community on new aspects and trends on the management and treatment of diabetes. The annual convention becomes a venue for the exchange of ideas and the echo of new developments in the field, with research becoming an important innovation, as recipients of Diabetes Philippines research grants present their studies at the event.

Course on Diabetes and Vascular Disease the main objective of the course is to update the community on significant and recent research on cardiovascular disease and diabetes, which hopefully will inspire the exploration of new treatment options and prevention in managing this dreaded complication.

DiabetesWorkshop is a postgraduate or refresher course for province-based general practitioners and internists. Through informative sessions, group discussions, workshops and case presentations, the workshops aim to upgrade doctor’s expertise in the management of diabetes, and tackle all aspects of the disease, from its pathogenesis and management, to dealing with acute and chronic complications

Diabetes Forums is a day of intensive course of lectures on different aspects of diabetes mellitus to equip the allied health professionals (nurses and dietitians) with the necessary tools to treat and manage diabetes mellitus.

Lay Annual Conventions/Gimik Diabetes – this provides a venue for people with diabetes and their families to learn more about diabetes and interact with other people with diabetes.

Screening Programmes:

Conducted regularly by the out-patient clinics sponsored by Diabetes Philippines Chapters all over the Philippines.

Message from the President

“ As a member of IDF, we are committed to improve the lives of people with diabetes in the Philippines. We take our roles seriously and find ways to help health care professionals manage their patients with diabetes and their families.”

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• Published: 13 May 2024

Patient medication management, understanding and adherence during the transition from hospital to outpatient care - a qualitative longitudinal study in polymorbid patients with type 2 diabetes

• Léa Solh Dost   ORCID: orcid.org/0000-0001-5767-1305 1 , 2 ,
• Giacomo Gastaldi   ORCID: orcid.org/0000-0001-6327-7451 3 &
• Marie P. Schneider   ORCID: orcid.org/0000-0002-7557-9278 1 , 2  

BMC Health Services Research volume  24 , Article number:  620 ( 2024 ) Cite this article

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Metrics details

Continuity of care is under great pressure during the transition from hospital to outpatient care. Medication changes during hospitalization may be poorly communicated and understood, compromising patient safety during the transition from hospital to home. The main aims of this study were to investigate the perspectives of patients with type 2 diabetes and multimorbidities on their medications from hospital discharge to outpatient care, and their healthcare journey through the outpatient healthcare system. In this article, we present the results focusing on patients’ perspectives of their medications from hospital to two months after discharge.

Patients with type 2 diabetes, with at least two comorbidities and who returned home after discharge, were recruited during their hospitalization. A descriptive qualitative longitudinal research approach was adopted, with four in-depth semi-structured interviews per participant over a period of two months after discharge. Interviews were based on semi-structured guides, transcribed verbatim, and a thematic analysis was conducted.

Twenty-one participants were included from October 2020 to July 2021. Seventy-five interviews were conducted. Three main themes were identified: (A) Medication management, (B) Medication understanding, and (C) Medication adherence, during three periods: (1) Hospitalization, (2) Care transition, and (3) Outpatient care. Participants had varying levels of need for medication information and involvement in medication management during hospitalization and in outpatient care. The transition from hospital to autonomous medication management was difficult for most participants, who quickly returned to their routines with some participants experiencing difficulties in medication adherence.

Conclusions

The transition from hospital to outpatient care is a challenging process during which discharged patients are vulnerable and are willing to take steps to better manage, understand, and adhere to their medications. The resulting tension between patients’ difficulties with their medications and lack of standardized healthcare support calls for interprofessional guidelines to better address patients’ needs, increase their safety, and standardize physicians’, pharmacists’, and nurses’ roles and responsibilities.

Peer Review reports

Introduction

Continuity of patient care is characterized as the collaborative engagement between the patient and their physician-led care team in the ongoing management of healthcare, with the mutual objective of delivering high-quality and cost-effective medical care [ 1 ]. Continuity of care is under great pressure during the transition of care from hospital to outpatient care, with a risk of compromising patients’ safety [ 2 , 3 ]. The early post-discharge period is a high-risk and fragile transition: once discharged, one in five patients experience at least one adverse event during the first three weeks following discharge, and more than half of these adverse events are drug-related [ 4 , 5 ]. A retrospective study examining all discharged patients showed that adverse drug events (ADEs) account for up to 20% of 30-day hospital emergency readmissions [ 6 ]. During hospitalization, patients’ medications are generally modified, with an average of nearly four medication changes per patient [ 7 ]. Information regarding medications such as medication changes, the expected effect, side effects, and instructions for use are frequently poorly communicated to patients during hospitalization and at discharge [ 8 , 9 , 10 , 11 ]. Between 20 and 60% of discharged patients lack knowledge of their medications [ 12 , 13 ]. Consideration of patients’ needs and their active engagement in decision-making during hospitalization regarding their medications are often lacking [ 11 , 14 , 15 ]. This can lead to unsafe discharge and contribute to medication adherence difficulties, such as non-implementation of newly prescribed medications [ 16 , 17 ].

Patients with multiple comorbidities and polypharmacy are at higher risk of ADE [ 18 ]. Type 2 diabetes is one of the chronic health conditions most frequently associated with comorbidities and patients with type 2 diabetes often lack care continuum [ 19 , 20 , 21 ]. The prevalence of patients hospitalized with type 2 diabetes can exceed 40% [ 22 ] and these patients are at higher risk for readmission due to their comorbidities and their medications, such as insulin and oral hypoglycemic agents [ 23 , 24 , 25 ].

Interventions and strategies to improve patient care and safety at transition have shown mixed results worldwide in reducing cost, rehospitalization, ADE, and non-adherence [ 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 ]. However, interventions that are patient-centered, with a patient follow-up and led by interprofessional healthcare teams showed promising results [ 34 , 35 , 36 ]. Most of these interventions have not been implemented routinely due to the extensive time to translate research into practice and the lack of hybrid implementation studies [ 37 , 38 , 39 , 40 , 41 ]. In addition, patient-reported outcomes and perspectives have rarely been considered, yet patients’ involvement is essential for seamless and integrated care [ 42 , 43 ]. Interprofessional collaboration in which patients are full members of the interprofessional team, is still in its infancy in outpatient care [ 44 ]. Barriers and facilitators regarding medications at the transition of care have been explored in multiple qualitative studies at one given time in a given setting (e.g., at discharge, one-month post-discharge) [ 8 , 45 , 46 , 47 , 48 ]. However, few studies have adopted a holistic methodology from the hospital to the outpatient setting to explore changes in patients’ perspectives over time [ 49 , 50 , 51 ]. Finally, little is known about whether, how, and when patients return to their daily routine following hospitalization and the impact of hospitalization weeks after discharge.

In Switzerland, continuity of care after hospital discharge is still poorly documented, both in terms of contextual analysis and interventional studies, and is mainly conducted in the hospital setting [ 31 , 35 , 52 , 53 , 54 , 55 , 56 ]. The first step of an implementation science approach is to perform a contextual analysis to set up effective interventions adapted to patients’ needs and aligned to healthcare professionals’ activities in a specific context [ 41 , 57 ]. Therefore, the main aims of this study were to investigate the perspectives of patients with type 2 diabetes and multimorbidities on their medications from hospital discharge to outpatient care, and on their healthcare journey through the outpatient healthcare system. In this article, we present the results focusing on patients’ perspectives of their medications from hospital to two months after discharge.

Study design

This qualitative longitudinal study, conducted from October 2020 to July 2021, used a qualitative descriptive methodology through four consecutive in-depth semi-structured interviews per participant at three, 10-, 30- and 60-days post-discharge, as illustrated in Fig.  1 . Longitudinal qualitative research is characterized by qualitative data collection at different points in time and focuses on temporality, such as time and change [ 58 , 59 ]. Qualitative descriptive studies aim to explore and describe the depth and complexity of human experiences or phenomena [ 60 , 61 , 62 ]. We focused our qualitative study on the 60 first days after discharge as this period is considered highly vulnerable and because studies often use 30- or 60-days readmission as an outcome measure [ 5 , 63 ].

This qualitative study follows the Consolidated Criteria for Reporting Qualitative Research (COREQ). Ethics committee approval was sought and granted by the Cantonal Research Ethics Commission, Geneva (CCER) (2020 − 01779).

Recruitment took place during participants’ hospitalization in the general internal medicine divisions at the Geneva University Hospitals in the canton of Geneva (500 000 inhabitants), Switzerland. Interviews took place at participants’ homes, in a private office at the University of Geneva, by telephone or by secure video call, according to participants’ preference. Informal caregivers could also participate alongside the participants.

Study flowchart

Researcher characteristics

All the researchers were trained in qualitative studies. The diabetologist and researcher (GG) who enrolled the patients in the study was involved directly or indirectly (advice asked to the Geneva University Hospital diabetes team of which he was a part) for most participants’ care during hospitalization. LS (Ph.D. student and community pharmacist) was unknown to participants and presented herself during hospitalization as a “researcher” and not as a healthcare professional to avoid any risk of influencing participants’ answers. This study was not interventional, and the interviewer (LS) invited participants to contact a healthcare professional for any questions related to their medication or medical issues.

Population and sampling strategy

Patients with type 2 diabetes were chosen as an example population to describe polypharmacy patients as these patients usually have several health issues and polypharmacy [ 20 , 22 , 25 ]. Inclusions criteria for the study were: adult patients with type 2 diabetes, with at least two other comorbidities, hospitalized for at least three days in a general internal medicine ward, with a minimum of one medication change during hospital stay, and who self-managed their medications once discharged home. Exclusion criteria were patients not reachable by telephone following discharge, unable to give consent (patients with schizophrenia, dementia, brain damage, or drug/alcohol misuse), and who could not communicate in French. A purposive sampling methodology was applied aiming to include participants with different ages, genders, types, and numbers of health conditions by listing participants’ characteristics in a double-entry table, available in Supplementary Material 1 , until thematic saturation was reached. Thematic saturation was considered achieved when no new code or theme emerged and new data repeated previously coded information [ 64 ]. The participants were identified if they were hospitalized in the ward dedicated to diabetes care or when the diabetes team was contacted for advice. The senior ward physician (GG) screened eligible patients and the interviewer (LS) obtained written consent before hospital discharge.

Data collection and instruments

Sociodemographic (age, gender, educational level, living arrangement) and clinical characteristics (reason for hospitalization, date of admission, health conditions, diabetes diagnosis, medications before and during hospitalization) were collected by interviewing participants before their discharge and by extracting participants’ data from electronic hospital files by GG and LS. Participants’ pharmacies were contacted with the participant’s consent to obtain medication records from the last three months if information regarding medications before hospitalization was missing in the hospital files.

Semi-structured interview guides for each interview (at three, 10-, 30- and 60-days post-discharge) were developed based on different theories and components of health behavior and medication adherence: the World Health Organization’s (WHO) five dimensions for adherence, the Information-Motivation-Behavioral skills model and the Social Cognitive Theory [ 65 , 66 , 67 ]. Each interview explored participants’ itinerary in the healthcare system and their perspectives on their medications. Regarding medications, the following themes were mentioned at each interview: changes in medications, patients’ understanding and implication; information on their medications, self-management of their medications, and patients’ medication adherence. Other aspects were mentioned in specific interviews: patients’ hospitalization and experience on their return home (interview 1), motivation (interviews 2 and 4), and patient’s feedback on the past two months (interview 4). Interview guides translated from French are available in Supplementary Material 2 . The participants completed self-reported and self-administrated questionnaires at different interviews to obtain descriptive information on different factors that may affect medication management and adherence: self-report questionnaires on quality of life (EQ-5D-5 L) [ 68 ], literacy (Schooling-Opinion-Support questionnaire) [ 69 ], medication adherence (Adherence Visual Analogue Scale, A-VAS) [ 70 ] and Belief in Medication Questionnaire (BMQ) [ 71 ] were administered to each participant at the end of selected interviews to address the different factors that may affect medication management and adherence as well as to determine a trend of determinants over time. The BMQ contains two subscores: Specific-Necessity and Specific-Concerns, addressing respectively their perceived needs for their medications, and their concerns about adverse consequences associated with taking their medication [ 72 ].

Data management

Informed consent forms, including consent to obtain health data, were securely stored in a private office at the University of Geneva. The participants’ identification key was protected by a password known only by MS and LS. Confidentiality was guaranteed by pseudonymization of participants’ information and audio-recordings were destroyed once analyzed. Sociodemographic and clinical characteristics, medication changes, and answers to questionnaires were securely collected by electronic case report forms (eCRFs) on RedCap®. Interviews were double audio-recorded and field notes were taken during interviews. Recorded interviews were manually transcribed verbatim in MAXQDA® (2018.2) by research assistants and LS and transcripts were validated for accuracy by LS. A random sample of 20% of questionnaires was checked for accuracy for the transcription from the paper questionnaires to the eCRFs. Recorded sequences with no link to the discussed topics were not transcribed and this was noted in the transcripts.

Data analysis

A descriptive statistical analysis of sociodemographic, clinical characteristics and self-reported questionnaire data was carried out. A thematic analysis of transcripts was performed, as described by Braun and Clarke [ 73 ], by following six steps: raw data was read, text segments related to the study objectives were identified, text segments to create new categories were identified, similar or redundant categories were reduced and a model that integrated all significant categories was created. The analysis was conducted in parallel with patient enrolment to ensure data saturation. To ensure the validity of the coding method, transcripts were double coded independently and discussed by the research team until similar themes were obtained. The research group developed and validated an analysis grid, with which LS coded systematically the transcriptions and met regularly with the research team to discuss questions on data analysis and to ensure the quality of coding. The analysis was carried out in French, and the verbatims of interest cited in the manuscript were translated and validated by a native English-speaking researcher to preserve the meaning.

In this analysis, we used the term “healthcare professionals” when more than one profession could be involved in participants’ medication management. Otherwise, when a specific healthcare professional was involved, we used the designated profession (e.g. physicians, pharmacists).

Patient and public involvement

During the development phase of the study, interview guides and questionnaires were reviewed for clarity and validity and adapted by two patient partners, with multiple health conditions and who experienced previously a hospital discharge. They are part of the HUG Patients Partners + 3P platform for research and patient and public involvement.

Interviews and participants’ descriptions

A total of 75 interviews were conducted with 21 participants. In total, 31 patients were contacted, seven refused to participate (four at the project presentation and three at consent), two did not enter the selection criteria at discharge and one was unreachable after discharge. Among the 21 participants, 15 participated in all interviews, four in three interviews, one in two interviews, and one in one interview, due to scheduling constraints. Details regarding interviews and participants characteristics are presented in Tables  1 and 2 .

The median length of time between hospital discharge and interviews 1,2,3 and 4 was 5 (IQR: 4–7), 14 (13-20), 35 (22-38), and 63 days (61-68), respectively. On average, by comparing medications at hospital admission and discharge, a median of 7 medication changes (IQR: 6–9, range:2;17) occurred per participant during hospitalization and a median of 7 changes (5–12) during the two months following discharge. Details regarding participants’ medications are described in Table  3 .

Patient self-reported adherence over the past week for their three most challenging medications are available in Supplementary Material 3 .

Qualitative analysis

We defined care transition as the period from discharge until the first medical appointment post-discharge, and outpatient care as the period starting after the first medical appointment. Data was organized into three key themes (A. Medication management, B. Medication understanding, and C. Medication adherence) divided into subthemes at three time points (1. Hospitalization, 2. Care transition and 3. Outpatient care). Figure  2 summarizes and illustrates the themes and subthemes with their influencing factors as bullet points.

Participants’ medication management, understanding and adherence during hospitalization, care transition and outpatient care

A. Medication management

A.1 medication management during hospitalization: medication management by hospital staff.

Medications during hospitalization were mainly managed by hospital healthcare professionals (i.e. nurses and physicians) with varying degrees of patient involvement: “At the hospital, they prepared the medications for me. […] I didn’t even know what the packages looked like.” Participant 22; interview 1 (P22.1) Some participants reported having therapeutic education sessions with specialized nurses and physicians, such as the explanation and demonstration of insulin injection and glucose monitoring. A patient reported that he was given the choice of several treatments and was involved in shared decision-making. Other participants had an active role in managing and optimizing dosages, such as rapid insulin, due to prior knowledge and use of medications before hospitalization.

A.2 Medication management at transition: obtaining the medication and initiating self-management

Once discharged, some participants had difficulties obtaining their medications at the pharmacy because some medications were not stored and had to be ordered, delaying medication initiation. To counter this problem upstream, a few participants were provided a 24-to-48-hour supply of medications at discharge. It was sometimes requested by the patient or suggested by the healthcare professionals but was not systematic. The transition from medication management by hospital staff to self-management was exhausting for most participants who were faced with a large amount of new information and changes in their medications: “ When I was in the hospital, I didn’t even realize all the changes. When I came back home, I took away the old medication packages and got out the new ones. And then I thought : « my God, all this…I didn’t know I had all these changes » ” P2.1 Written documentation, such as the discharge prescription or dosage labels on medication packages, was helpful in managing their medication at home. Most participants used weekly pill organizers to manage their medications, which were either already used before hospitalization or were introduced post-discharge. The help of a family caregiver in managing and obtaining medications was reported as a facilitator.

A.3 Medication management in outpatient care: daily self-management and medication burden

A couple of days or weeks after discharge, most participants had acquired a routine so that medication management was less demanding, but the medication burden varied depending on the participants. For some, medication management became a simple action well implemented in their routine (“It has become automatic” , P23.4), while for others, the number of medications and the fact that the medications reminded them of the disease was a heavy burden to bear on a daily basis (“ During the first few days after getting out of the hospital, I thought I was going to do everything right. In the end, well [laughs] it’s complicated. I ended up not always taking the medication, not monitoring the blood sugar” P12.2) To support medication self-management, some participants had written documentation such as treatment plans, medication lists, and pictures of their medication packages on their phones. Some participants had difficulties obtaining medications weeks after discharge as discharge prescriptions were not renewable and participants did not see their physician in time. Others had to visit multiple physicians to have their prescriptions updated. A few participants were faced with prescription or dispensing errors, such as prescribing or dispensing the wrong dosage, which affected medication management and decreased trust in healthcare professionals. In most cases, according to participants, the pharmacy staff worked in an interprofessional collaboration with physicians to provide new and updated prescriptions.

B. Medication understanding

B.1 medication understanding during hospitalization: new information and instructions.

The amount of information received during hospitalization varied considerably among participants with some reporting having received too much, while others saying they received too little information regarding medication changes, the reason for changes, or for introducing new medications: “They told me I had to take this medication all my life, but they didn’t tell me what the effects were or why I was taking it.” P5.3

Hospitalization was seen by some participants as a vulnerable and tiring period during which they were less receptive to information. Information and explanations were generally given verbally, making it complicated for most participants to recall it. Some participants reported that hospital staff was attentive to their needs for information and used communication techniques such as teach-back (a way of checking understanding by asking participants to say in their own words what they need to know or do about their health or medications). Some participants were willing to be proactive in the understanding of their medications while others were more passive, had no specific needs for information, and did not see how they could be engaged more.

B.2 Medication understanding at transition: facing medication changes

At hospital discharge, the most challenging difficulty for participants was to understand the changes made regarding their medications. For newly diagnosed participants, the addition of new medications was more difficult to understand, whereas, for experienced participants, changes in known medications such as dosage modification, changes within a therapeutic class, and generic substitutions were the most difficult to understand. Not having been informed about changes caused confusion and misunderstanding. Therefore, medication reconciliation done by the patient was time-consuming, especially for participants with multiple medications: “ They didn’t tell me at all that they had changed my treatment completely. They just told me : « We’ve changed a few things. But it was the whole treatment ». ” P2.3 Written information, such as the discharge prescription, the discharge report (brief letter summarizing information about the hospitalization, given to the patient at discharge), or the label on the medication box (written by the pharmacist with instructions on dosage) helped them find or recall information about their medications and diagnoses. However, technical terms were used in hospital documentations and were not always understandable. For example, this participant said: “ On the prescription of valsartan, they wrote: ‘resume in the morning once profile…’[once hypertension profile allows]… I don’t know what that means.” P8.1 In addition, some documents were incomplete, as mentioned by a patient who did not have the insulin dosage mentioned on the hospital prescription. Some participants sought help from healthcare professionals, such as pharmacists, hospital physicians, or general practitioners a few days after discharge to review medications, answer questions, or obtain additional information.

B.3 Medication understanding in the outpatient care: concerns and knowledge

Weeks after discharge, most participants had concerns about the long-term use of their medications, their usefulness, and the possible risk of interactions or side effects. Some participants also reported having some lack of knowledge regarding indications, names, or how the medication worked: “I don’t even know what Brilique® [ticagrelor, antiplatelet agent] is for. It’s for blood pressure, isn’t it?. I don’t know.” P11.4 According to participants, the main reasons for the lack of understanding were the lack of information at the time of prescribing and the large number of medications, making it difficult to search for information and remember it. Participants sought information from different healthcare professionals or by themselves, on package inserts, through the internet, or from family and friends. Others reported having had all the information needed or were not interested in having more information. In addition, participants with low medication literacy, such as non-native speakers or elderly people, struggled more with medication understanding and sought help from family caregivers or healthcare professionals, even weeks after discharge: “ I don’t understand French very well […] [The doctor] explained it very quickly…[…] I didn’t understand everything he was saying” P16.2

C. Medication adherence

C.2 medication adherence at transition: adopting new behaviors.

Medication adherence was not mentioned as a concern during hospitalization and a few participants reported difficulties in medication initiation once back home: “I have an injection of Lantus® [insulin] in the morning, but obviously, the first day [after discharge], I forgot to do it because I was not used to it.” P23.1 Participants had to quickly adopt new behaviors in the first few days after discharge, especially for participants with few medications pre-hospitalization. The use of weekly pill organizers, alarms and specific storage space were reported as facilitators to support adherence. One patient did not initiate one of his medications because he did not understand the medication indication, and another patient took her old medications because she was used to them. Moreover, most participants experienced their hospitalization as a turning point, a time when they focused on their health, thought about the importance of their medications, and discussed any new lifestyle or dietary measures that might be implemented.

C.3 Medication adherence in outpatient care: ongoing medication adherence

More medication adherence difficulties appeared a few weeks after hospital discharge when most participants reported nonadherence behaviors, such as difficulties implementing the dosage regimen, or intentionally discontinuing the medication and modifying the medication regimen on their initiative. Determinants positively influencing medication adherence were the establishment of a routine; organizing medications in weekly pill-organizers; organizing pocket doses (medications for a short period that participants take with them when away from home); seeking support from family caregivers; using alarm clocks; and using specific storage places. Reasons for nonadherence were changes in daily routine; intake times that were not convenient for the patient; the large number of medications; and poor knowledge of the medication or side effects. Healthcare professionals’ assistance for medication management, such as the help of home nurses or pharmacists for the preparation of weekly pill-organizers, was requested by participants or offered by healthcare professionals to support medication adherence: “ I needed [a home nurse] to put my pills in the pillbox. […] I felt really weak […] and I was making mistakes. So, I’m very happy [the doctor] offered me [home care]. […] I have so many medications.” P22.3 Some participants who experienced prehospitalization non-adherence were more aware of their non-adherence and implemented strategies, such as modifying the timing of intake: “I said to my doctor : « I forget one time out of two […], can I take them in the morning? » We looked it up and yes, I can take it in the morning.” P11.2 In contrast, some participants were still struggling with adherence difficulties that they had before hospitalization. Motivations for taking medications two months after discharge were to improve health, avoid complications, reduce symptoms, reduce the number of medications in the future or out of obligation: “ I force myself to take them because I want to get to the end of my diabetes, I want to reduce the number of pills as much as possible.” P14.2 After a few weeks post-hospitalization, for some participants, health and illness were no longer the priority because of other life imperatives (e.g., family or financial situation).

This longitudinal study provided a multi-faceted representation of how patients manage, understand, and adhere to their medications from hospital discharge to two months after discharge. Our findings highlighted the varying degree of participants’ involvement in managing their medications during their hospitalization, the individualized needs for information during and after hospitalization, the complicated transition from hospital to autonomous medication management, the adaptation of daily routines around medication once back home, and the adherence difficulties that surfaced in the outpatient care, with nonadherence prior to hospitalization being an indicator of the behavior after discharge. Finally, our results confirmed the lack of continuity in care and showed the lack of patient care standardization experienced by the participants during the transition from hospital to outpatient care.

This in-depth analysis of patients’ experiences reinforces common challenges identified in the existing literature such as the lack of personalized information [ 9 , 10 , 11 ], loss of autonomy during hospitalization [ 14 , 74 , 75 ], difficulties in obtaining medication at discharge [ 11 , 45 , 76 ] and challenges in understanding treatment modifications and generics substitution [ 11 , 32 , 77 , 78 ]. Some of these studies were conducted during patients’ hospitalization [ 10 , 75 , 79 ] or up to 12 months after discharge [ 80 , 81 ], but most studies focused on the few days following hospital discharge [ 9 , 11 , 14 , 82 ]. Qualitative studies on medications at transition often focused on a specific topic, such as medication information, or a specific moment in time, and often included healthcare professionals, which muted patients’ voices [ 9 , 10 , 11 , 47 , 49 ]. Our qualitative longitudinal methodology was interested in capturing the temporal dynamics, in-depth narratives, and contextual nuances of patients’ medication experiences during transitions of care [ 59 , 83 ]. This approach provided a comprehensive understanding of how patients’ perspectives and behaviors evolved over time, offering insights into the complex interactions of medication management, understanding and adherence, and turning points within their medication journeys. A qualitative longitudinal design was used by Fylan et al. to underline patients’ resilience in medication management during and after discharge, by Brandberg et al. to show the dynamic process of self-management during the 4 weeks post-discharge and by Lawton et al. to examine how patients with type 2 diabetes perceived their care after discharge over a period of four years [ 49 , 50 , 51 ]. Our study focused on the first two months following hospitalization and future studies should focus on following discharged and at-risk patients over a longer period, as “transitions of care do not comprise linear trajectories of patients’ movements, with a starting and finishing point. Instead, they are endless loops of movements” [ 47 ].

Our results provide a particularly thorough description of how participants move from a state of total dependency during hospitalization regarding their medication management to a sudden and complete autonomy after hospital discharge impacting medication management, understanding, and adherence in the first days after discharge for some participants. Several qualitative studies have described the lack of shared decision-making and the loss of patient autonomy during hospitalization, which had an impact on self-management and created conflicts with healthcare professionals [ 75 , 81 , 84 ]. Our study also highlights nuanced patient experiences, including varying levels of patient needs, involvement, and proactivity during hospitalization and outpatient care, and our results contribute to capturing different perspectives that contrast with some literature that often portrays patients as more passive recipients of care [ 14 , 15 , 74 , 75 ]. Shared decision-making and proactive medication are key elements as they contribute to a smoother transition and better outcomes for patients post-discharge [ 85 , 86 , 87 ].

Consistent with the literature, the study identifies some challenges in medication initiation post-discharge [ 16 , 17 , 88 ] but our results also describe how daily routine rapidly takes over, either solidifying adherence behavior or generating barriers to medication adherence. Participants’ nonadherence prior to hospitalization was a factor influencing participants’ adherence post-hospitalization and this association should be further investigated, as literature showed that hospitalized patients have high scores of non-adherence [ 89 ]. Mortel et al. showed that more than 20% of discharged patients stopped their medications earlier than agreed with the physician and 25% adapted their medication intake [ 90 ]. Furthermore, patients who self-managed their medications had a lower perception of the necessity of their medication than patients who received help, which could negatively impact medication adherence [ 91 ]. Although participants in our study had high BMQ scores for necessity and lower scores for concerns, some participants expressed doubts about the need for their medications and a lack of motivation a few weeks after discharge. Targeted pharmacy interventions for newly prescribed medications have been shown to improve medication adherence, and hospital discharge is an opportune moment to implement this service [ 92 , 93 ].

Many medication changes were made during the transition of care (a median number of 7 changes during hospitalization and 7 changes during the two months after discharge), especially medication additions during hospitalization and interruptions after hospitalization. While medication changes during hospitalization are well described, the many changes following discharge are less discussed [ 7 , 94 ]. A Danish study showed that approximately 65% of changes made during hospitalization were accepted by primary healthcare professionals but only 43% of new medications initiated during hospitalization were continued after discharge [ 95 ]. The numerous changes after discharge may be caused by unnecessary intensification of medications during hospitalization, delayed discharge letters, lack of standardized procedures, miscommunication, patient self-management difficulties, or in response to an acute situation [ 96 , 97 , 98 ]. During the transition of care, in our study, both new and experienced participants were faced with difficulties in managing and understanding medication changes, either for newly prescribed medication or changes in previous medications. Such difficulties corroborate the findings of the literature [ 9 , 10 , 47 ] and our results showed that the lack of understanding during hospitalization led to participants having questions about their medications, even weeks after discharge. Particular attention should be given to patients’ understanding of medication changes jointly by physicians, nurses and pharmacists during the transition of care and in the months that follow as medications are likely to undergo as many changes as during hospitalization.

Implication for practice and future research

The patients’ perspectives in this study showed, at a system level, that there was a lack of standardization in healthcare professional practices regarding medication dispensing and follow-up. For now, in Switzerland, there are no official guidelines on medication prescription and dispensation during the transition of care although some international guidelines have been developed for outpatient healthcare professionals [ 3 , 99 , 100 , 101 , 102 ]. Here are some suggestions for improvement arising from our results. Patients should be included as partners and healthcare professionals should systematically assess (i) previous medication adherence, (ii) patients’ desired level of involvement and (iii) their needs for information during hospitalization. Hospital discharge processes should be routinely implemented to standardize hospital discharge preparation, medication prescribing, and dispensing. Discharge from the hospital should be planned with community pharmacies to ensure that all medications are available and, if necessary, doses of medications should be supplied by the hospital to bridge the gap. A partnership with outpatient healthcare professionals, such as general practitioners, community pharmacists, and homecare nurses, should be set up for effective asynchronous interprofessional collaboration to consolidate patients’ medication management, knowledge, and adherence, as well as to monitor signs of deterioration or adverse drug events.

Future research should consolidate our first attempt to develop a framework to better characterize medication at the transition of care, using Fig. 2   as a starting point. Contextualized interventions, co-designed by health professionals, patients and stakeholders, should be tested in a hybrid implementation study to test the implementation and effectiveness of the intervention for the health system [ 103 ].

Limitations

This study has some limitations. First, the transcripts were validated for accuracy by the interviewer but not by a third party, which could have increased the robustness of the transcription. Nevertheless, the interviewer followed all methodological recommendations for transcription. Second, patient inclusion took place during the COVID-19 pandemic, which may have had an impact on patient care and the availability of healthcare professionals. Third, we cannot guarantee the accuracy of some participants’ medication history before hospitalization, even though we contacted the participants’ main pharmacy, as participants could have gone to different pharmacies to obtain their medications. Fourth, our findings may not be generalizable to other populations and other healthcare systems because some issues may be specific to multimorbid patients with type 2 diabetes or to the Swiss healthcare setting. Nevertheless, issues encountered by our participants regarding their medications correlate with findings in the literature. Fifth, only 15 out of 21 participants took part in all the interviews, but most participants took part in at least three interviews and data saturation was reached. Lastly, by its qualitative and longitudinal design, it is possible that the discussion during interviews and participants’ reflections between interviews influenced participants’ management, knowledge, and adherence, even though this study was observational, and no advice or recommendations were given by the interviewer during interviews.

Discharged patients are willing to take steps to better manage, understand, and adhere to their medications, yet they are also faced with difficulties in the hospital and outpatient care. Furthermore, extensive changes in medications not only occur during hospitalization but also during the two months following hospital discharge, for which healthcare professionals should give particular attention. The different degrees of patients’ involvement, needs and resources should be carefully considered to enable them to better manage, understand and adhere to their medications. At a system level, patients’ experiences revealed a lack of standardization of medication practices during the transition of care. The healthcare system should provide the ecosystem needed for healthcare professionals responsible for or involved in the management of patients’ medications during the hospital stay, discharge, and outpatient care to standardize their practices while considering the patient as an active partner.

Data availability

The anonymized quantitative survey datasets and the qualitative codes are available in French from the corresponding author on reasonable request.

Abbreviations

adverse drug events

Adherence Visual Analogue Scale

Belief in Medication Questionnaire

Consolidated Criteria for Reporting Qualitative Research

case report form

standard deviation

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Acknowledgements

The authors would like to thank all the patients who took part in this study. We would also like to thank the Geneva University Hospitals Patients Partners + 3P platform as well as Mrs. Tourane Corbière and Mr. Joël Mermoud, patient partners, who reviewed interview guides for clarity and significance. We would like to thank Samuel Fabbi, Vitcoryavarman Koh, and Pierre Repiton for the transcriptions of the audio recordings.

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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LS, GG, and MS conceptualized and designed the study. LS and GG screened and recruited participants. LS conducted the interviews. LS, GG, and MS performed data analysis and interpretation. LS drafted the manuscript and LS and MS worked on the different versions. MS and GG approved the final manuscript.

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Solh Dost, L., Gastaldi, G. & Schneider, M. Patient medication management, understanding and adherence during the transition from hospital to outpatient care - a qualitative longitudinal study in polymorbid patients with type 2 diabetes. BMC Health Serv Res 24 , 620 (2024). https://doi.org/10.1186/s12913-024-10784-9

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DOI : https://doi.org/10.1186/s12913-024-10784-9

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• Type 2 diabetes

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Methods for the National Diabetes Statistics Report

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Data collection

The estimates (unless otherwise noted) were derived from various data systems of the Centers for Disease Control and Prevention (CDC), Indian Health Service (IHS), Agency for Healthcare Research and Quality (AHRQ), and U.S. Census Bureau and from published research studies. Estimated percentages and total number of people with diabetes and prediabetes were derived from the National Health and Nutrition Examination Survey (NHANES), National Health Interview Survey (NHIS), IHS National Data Warehouse (NDW), Behavioral Risk Factor Surveillance System (BRFSS), United States Diabetes Surveillance System (USDSS), and U.S. resident population estimates.

Diagnosed diabetes status was determined from self-reported information provided by survey respondents. Undiagnosed diabetes was determined by measured fasting plasma glucose or A1C levels among people without self-reported diagnosed diabetes. Numbers and rates for acute and long-term complications of diabetes were derived from the National Inpatient Sample (NIS) and National Emergency Department Sample (NEDS), as well as NHIS.

For some measures, estimates were not available for certain racial and ethnic subgroups due to small sample sizes.

Diabetes estimates

An alpha level of 0.05 was used when determining statistically significant differences between groups. Age-adjusted estimates were calculated among adults aged 18 years or older by the direct method to the 2000 U.S. Census standard population, using age groups 18–44, 45–64, and 65 years or older. Most estimates of diabetes in this report do not differentiate between type 1 and type 2 diabetes. However, as type 2 diabetes accounts for 90% to 95% of all diabetes cases, the data presented here are more likely to be characteristic of type 2 diabetes, except as noted.

More information about the data sources, methods, and references is available in Appendix B: Detailed Methods and Data Sources .

Diabetes is a chronic disease that affects how your body turns food into energy. About 1 in 10 Americans has diabetes.

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• News Releases

Semaglutide can produce clinically meaningful weight loss and reduce waist size for at least 4 years in adults with overweight or obesity who don’t have diabetes, and delivers cardiovascular benefits irrespective of weight lost

European Association for the Study of Obesity

Two important studies based on the largest and longest clinical trial of the effects of semaglutide on weight in over 17,000 adults with overweight and obesity but not diabetes find patients lost on average 10% of their body weight and over 7cm from their waistline after 4 years.

Clinically meaningful weight loss was achieved by men and women of all races, ages, and body sizes, across all regions, with a lower rate of serious adverse events compared with placebo.

Over half of adults taking semaglutide moved down at least one BMI category after 2 years compared to 16% receiving placebo; and 12% reached a healthy BMI (25 kg/m² or less) compared with 1% in the placebo group.

Importantly, the findings also indicate that semaglutide delivers cardiovascular benefits irrespective of starting weight and the amount of weight lost—suggesting that even patients with mild obesity or those not losing weight are likely to gain some advantage.

Two important studies are being presented at this year’s European Congress on Obesity (ECO) in Venice, Italy (12-15 May), based on the landmark Semaglutide and Cardiovascular Outcomes (SELECT) trial from the same international author group. The first new study, led by Professor Donna Ryan from Pennington Biomedical Research Centre, New Orleans, USA, and being published simultaneously in Nature Medicine , examines the long-term weight effects of semaglutide. The second study led by led by Professor John Deanfield from University College London, UK, investigates whether the cardiovascular benefits are related to starting weight or the amount of weight lost.

Semaglutide is a GLP-1 medication primarily prescribed for adults with type 2 diabetes but is also approved for weight loss in people with obesity or overweight who have at least one other health issue. This class of medications simulate the functions of the body’s natural incretin hormones, which help to lower blood sugar levels after a meal. Adjusting these hormone levels can also make people feel full, and in doing so, helps lower their daily calorie intake.

In 2023, the SELECT trial reported that adults with overweight or obesity but not diabetes taking semaglutide for more than 3 years had a 20% lower risk of heart attack, stroke, or death due to cardiovascular disease, and lost an average 9.4% of their bodyweight [1]. 

Between October 2018 and June 2023, 17,604 adults (aged 45 or older; 72% male) from 804 sites in 41 countries with overweight or obesity (BMI of 27 kg/m² or higher) were enrolled and treated with Semaglutide (2.4mg) or placebo for an average of 40 months. They had previously experienced a heart attack, stroke and/or had peripheral artery disease, but did not have type 1 or type 2 diabetes when they joined the study.

The researchers examined markers of obesity that include body composition and fat distribution (waist circumference and waist circumference-to-height ratio [WHtR]), rather than just BMI alone, to help clarify the effect of semaglutide on central abdominal fat which has been proven to cause greater cardiovascular risk than general obesity.

Clinically meaningful weight loss in all sexes, races, body sizes, and regions

The first new study shows that once-weekly treatment with semaglutide can produce clinically meaningful and sustained weight loss and decrease waist size for at least 4 years in adults with overweight or obesity who do not have diabetes, with a lower rate of serious adverse events compared with placebo.

Importantly, men and women of all races, ages, and body sizes, across all geographical regions were able to achieve sustained, clinically meaningful weight loss.

“Our long-term analysis of semaglutide establishes that clinically relevant weight loss can be sustained for up to 4 years in a geographically and racially diverse population of adults with overweight and obesity but not diabetes,” says Professor Ryan. “This degree of weight loss in such a large and diverse population suggests that it may be possible to impact the public health burden of multiple obesity-related illnesses. While our trial focused on cardiovascular events, many other chronic diseases including several types of cancer, osteoarthritis, and anxiety and depression would benefit from effective weight management.”

In the semaglutide group, weight loss continued to week 65 and was sustained for 4 years, with participants’ losing on average 10.2% of their body weight and 7.7cm from their waistline, compared with 1.5% and 1.3cm respectively in the placebo group.

Similarly, in the semaglutide group, average WHtR fell by 6.9% compared with 1% in the placebo group.

These improvements were seen across both sexes and all categories of race and age, irrespective of starting blood sugar (glycaemic) status or metabolically unhealthy body fat. However, women taking semaglutide tended to lose more weight on average than men, and Asian patients lost less weight on average than other races.

Interestingly, after 2 years over half (52%) of participants treated with semaglutide had transitioned to a lower BMI category compared with 16% of those given placebo. For example, the proportion of participants with obesity (BMI 30kg/m² or higher) declined from 71% to 43% in the semaglutide group, and from 72% to 68% in the placebo group. Moreover, 12% of adults in the semaglutide group achieved a healthy weight (BMI 25kg/m² or less) compared with 1.2% in the placebo group

For each BMI category (<30, ≤30-<35, ≤35-<40, and ≥40 kg/m2) there were lower rates (events per 100 years of observation) of SAEs with semaglutide (43.23, 43.54, 51.0, 47.06) than with placebo (50.48, 49.66, 52.73, 60.85) respectively.

There were no unexpected safety issues with semaglutide in the SELECT trial. The proportion of participants with serious adverse events (SAEs) was lower in the semaglutide group than the placebo group (33% vs 36%), mainly driven by differences in cardiac disorders (11.5% vs 13.5%).   More patients receiving semaglutide discontinued the trial due to gastrointestinal symptoms, including nausea and diarrhoea, mainly during the 20-week dose escalation phase. Importantly, semaglutide did not lead to an increased rate of pancreatitis, but rates of cholelithiasis (stones in gallbladder) were higher in the semaglutide group.   

Cardiovascular benefits irrespective of weight loss

The second study examined the relationship between weight measures at baseline, and change in weight during the study with cardiovascular outcomes.  These included time to first major adverse cardiovascular event (MACE) and heart failure measures.

The findings showed that treatment with semaglutide delivered cardiovascular benefits, irrespective of the starting weight and the amount of weight lost. This suggests that even patients with relatively mild levels of obesity, or those who only lose modest amount of weight, may have improved cardiovascular outcome.

“These findings have important clinical implications”, says Professor Deanfield. “Around half of the patients that I see in my cardiovascular practice have levels of weight equivalent to those in the SELECT trial and are likely to derive benefit from taking Semaglutide on top of their usual level of guideline directed care.” 

He adds, “Our findings show that the magnitude of this treatment effect with semaglutide is independent of the amount of weight lost, suggesting that the drug has other actions which lower cardiovascular risk beyond reducing unhealthy body fat. These alternative mechanisms may include positive impacts on blood sugar, blood pressure, or inflammation, as well as direct effects on the heart muscle and blood vessels, or a combination of one or more of these.”

Despite these important findings, the authors caution that SELECT is not a primary prevention trial so that the data cannot be extrapolated to all adults with overweight and obesity to prevent MACE; and despite being large and diverse, it does not include enough individuals from different racial groups to understand different potential effects.

Nature Medicine

COI Statement

DR is an Advisor/consultant: Altimmune, Amgen, Biohaven, Calibrate, Carmot, CINRx, Currax, Epitomee, Gila, Ifa Celtic, Lilly, Nestle, Novo Nordisk, Scientific Intake, Structure Therapeutics, Wondr Health, Xeno Bioscience, Zealand. Speaker’s Bureau: Novo Nordisk, Lilly. Stock Options: Epitomee, Calibrate, Roman, Scientific Intake, Xeno. Research: SELECT Steering Committee (Novo Nordisk). DSMB: IQVIA setmelanotide (2); Lilly(1). JD received CME honoraria and/or consulting fees from Amgen, Boehringer Ingelheim, Merck, Pfizer, Aegerion, Novartis,  Sanofi, Takeda, Novo Nordisk, Bayer. Research grants from British Heart Foundation, MRC(UK), NIHR, PHE, MSD, Pfizer, Aegerion, Colgate, Roche.  Member of Study Steering Committees for Novo Nordisk (SOUL and SELECT) Editorial support was provided by Richard Ogilvy-Stewart of Titan, OPEN Health Communications, and funded by Novo Nordisk A/S, in accordance with Good Publication Practice guidelines (www.ismpp.org/gpp-2022). Funding Research relating to this abstract was funded by Novo Nordisk.

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