Determinants of knowledge, attitude and practice in patients with both type 2 diabetes and chronic kidney disease in Fiji

Introduction

Type 2 diabetes mellitus (T2DM) is characterized by fasting blood glucose of more than 7 mmol/L or random blood sugar of more than 11 mmol/L in the presence of symptoms of increase thirst/hunger, frequent urination and weight loss (O’Neil et al., 2012). T2DM is the seventh-leading cause of death globally (Zheng et al., 2018), and various complications arise as a consequence of this disease—one of the major ones being chronic kidney disease (CKD) (Idris et al., 2018; Yakush Williams, 2017). CKD is defined as estimated glomerular filtration rate (eGFR) of less than 60 ml/min for at least 3 months (Bouchard et al., 2010) and it is the ninth-leading cause of deaths globally (Rifkin et al., 2012). Fiji’s STEP-wise Surveillance Report (STEPS) of 2011 showed that 15.6% of the adult (25–64 years) population had raised fasting blood sugar (Snowdon & Tukana, 2011). Since T2DM is the major cause of CKD, accounting for 44% of all cases and hence a rise in T2DM will lead to a greater burden of CKD in Fiji (Atkins & Zimmet, 2010). T2DM and CKD were found to be among the top four causes of premature deaths and death and disability combined in Fiji (IHME, 2016). The final stage of CKD is very costly since it requires renal dialysis optimally three times a week and renal transplant eventually whereby cost of each dialysis session in Fiji can range from $USD70 to USD120 (Consumer Council of Fiji, 2017). Apart from these costs, the healthcare expenses related to management of these medical conditions are borne by the government of Fiji and hence reducing these medical expenses for Fiji’s health ministry as a whole via addressing these 2 diseases from a public health perspective would be beneficial (MoHMS, 2015).

The knowledge, attitude and practice (KAP) survey, which uses scales and items to gather information from the patients on specific aspects of certain conditions (Kaliyaperumal, 2004), is a useful tool for assessing and improving control of patient’s disease, delaying associated complications (Ghannadi et al., 2016), influencing better health policy (Stanifer et al., 2015) and increasing awareness for disease prevention. Various factors have been linked to level of KAP in T2DM patients with CKD; for instance female gender has been linked to poor knowledge but good attitude (Yusoff et al., 2016) while males have been shown to have good practice (Stanifer et al., 2016). Similarly, employed participants were found to have higher knowledge while married respondents reported high attitude and practice (Mutiso et al., 2011; Thirsk et al., 2014; Yusoff et al., 2016). Consequently, a KAP survey of individuals with T2DM and CKD will provide an insight on the current status of the level of KAP and its determinants in a referral hospital in Fiji- Sigatoka Sub-divisional Hospital (SSH), which can be utilized to inform public health programs and help target high-risk cases to improve awareness, promote self-control in patients and reduce or delay complications from T2DM and CKD (Ghannadi et al., 2016).

This is the first study on KAP of T2DM patients with CKD in Fiji which aimed to identify the determinants of KAP in T2DM patients with CKD in Fiji in 2018. The specific objectives were to identify the level of each of the aspects of KAP and to investigate for significant links between the level of KAP and the socio-demographical features in T2DM patients with CKD in Fiji in 2018.

Methods

Results

Discussion

Participants with higher levels of education, the unemployed and those with high monthly income had higher knowledge, FID had low attitude but high practice scores, and the higher age category had lower attitude scores.

This research had sought to identify the determinants of knowledge, attitude and practice towards causes, prevention, diagnosis, treatment and management in T2DM patients with CKD at SSH in 2018. Those aged 61–70 years had a 0.53-point lower attitude score (p=0.05) compared to other age categories, while those aged >70 years had 1.78 points lower attitude score (p=0.01) compared to those in other age categories. On the contrary, those aged >30 years were associated with having a good attitude in another study (Yusoff et al., 2016). White et al. (2008) noted that people aged less than 60 years had better knowledge of kidney disease but nil discussion on association between age and attitude was mentioned by the authors. However, the association between increased education and knowledge is consistent with other studies. White et al. (2008) had also reported higher knowledge in participants with higher education which was supported by Khalil & Abdalrahim (2014); Stanifer et al. (2016) and Yusoff et al. (2016). This result makes sense since the higher the level of education, the more knowledge a person will have. Conversely, older age was linked to higher knowledge in another article from USA (Ryder et al., 2013) while it was associated with high practice scores in the Jordan study (Khalil & Abdalrahim, 2014).

Age is an independent variable that has been linked to various diseases in multiple studies; for instance, a rise in age is directly linked with an increased risk of cardiac events (Canto et al., 2012). Age has also been associated with KAP of diabetes, but there are few studies which have tested and found significant links between age and KAP in individuals with diabetic kidney disease (DKD) (Islam et al., 2014).

In terms of ethnicity, the current research showed that FID had significantly lower attitude scores but higher practice scores than iTaukei and Fijians of others Descent (FoD). This finding is evident in one of the aspects of practice at the daily SOPD clinics at SSH, since in Fiji’s SOPD clinics, the majority of the patients attending the clinic are FID, while iTaukei patients usually default their booked clinics and thus end up in making the majority of the numbers for NCD-related admissions. Kazley et al. (2015) had found poor knowledge scores in the African Americans but there was no mention of attitude or practice (Kazley et al., 2015).

The link between ethnicity and health-related KAP is extremely important in the Pacific setting as they are usually culturally influenced and tend to prioritize behaviors practiced by their ancestors over the past generations—this means that if their ancestors had certain attitude or practice regarding a health-issue, the Pacific people are inclined to follow the same. Culture seems to play an integral part in lots of decision-making in these PICs, as preferences are governed by the ethnic roots of most of the Pacific Islanders (Ryan et al., 2010). Subsequently, understanding and identifying the specific ethnic group with low KAP in SSH would help in tailoring the suitable health campaigns which are culturally appropriate and effective. Thus, this research shows that the iTaukei ethnicity will need to be considered while drafting and designing future public health preventive programs, as these are the individuals who need assistance with KAP towards DKD at SSH. Government could enact healthy lifestyle changes like compulsory tax on sugar, fat and tobacco and these legislative mechanisms can help the people of Fiji to be more inclined towards healthier choices, rather than the expensive, unhealthy ones.

The level of education had the strongest link with knowledge scores of the participants at SSH in 2018 whereby those with the highest level of education had higher mean knowledge scores. This result makes sense since the higher the level of education, the more knowledge a person will have. However, high education levels do not necessarily equate to high levels of attitude and practice (Sa’adeh et al., 2018). White et al. (2008) had also reported higher knowledge in participants with higher education which was supported by Stanifer et al. (2016); Khalil & Abdalrahim (2014) and Yusoff et al. (2016).

Health literacy deals with an individual’s ability to obtain, read, process and understand health-related information to make applicable health decisions (Jain & Green, 2016; Van den Broucke, 2014). The influence of health literacy on health-related decision-making helps to explain the link between knowledge and level of education as shown by this current study in SSH. As the participants of this study with higher levels of education are likely to have a better ability to comprehend medical information given to them, it seems likely that their knowledge scores would be relatively greater compared to those who have lower level of education (thus lower health literacy). Despite good self-reported ‘knowledge’ demonstrated in the survey, these were high-risk patients with a major complication and are at high risk for further poor outcomes. Thus, knowledge does not necessarily equate to good management at all times.

A major challenge for health professions is to use familial language (free of medical jargon) so that all at-risk populations with low health literacy levels understand how to best manage risk factors for diabetes-related complications. The real challenge of the health sector lies in this finding, since it means that health information must be translated into the simplest terms (free of medical jargon) and made available in the widest accessible form, so as to reach the greater subset of the population who lack higher education.

There are a lot of changes that need to occur in Fiji to reduce the epidemic of people developing diabetes and complications such as, improvement in patient awareness, patient-centered management, community-based active screening rather than passively waiting for patients to come for routine check-ups, and mobilizing community partnerships to reach out to the people on a larger scale.

Surprisingly, unemployed participants were found to have significantly higher level of knowledge in this study, although were not associated with better attitude and practice. Stanifer et al. (2016) had found similar link between unemployed participants and knowledge (Stanifer et al., 2016). On the contrary, Yusoff et al. (2016) concluded that employed people had higher knowledge and attitude which was supported by Li et al. (2014) and Ryder et al. (2013). These are lot of contrasting findings regarding link between employment and level of knowledge and perhaps future studies of DKD patients locally, regionally or internationally could clarify the doubts.

Ruhm (2005) found that health-related prevention behaviors were higher in unemployed people. This analysis was made from a Behavioral Risk Factor Surveillance System (BRFSS) in USA, and could probably explain the findings of the current research whereby unemployed participants had higher knowledge levels (Ruhm, 2005). However, the attitude and practice levels could not be linked with unemployment in SSH in 2018 and thus it is difficult to use the BRFSS solely as it deals with behaviors rather than knowledge alone.

Patients with T2DM and CKD at SSH in 2018 with high average monthly income had significantly higher knowledge levels regarding DKD, although the link to attitude and practice was insignificant. Similarly, Yusoff et al. (2016) found poor knowledge in those with low family income, while Khalil & Abdalrahim (2014) had showed that participants with high monthly income had high practice scores. Income is one of the key pillars of socioeconomic status (SES)—the other two being occupation and education. Therefore, it makes sense if participants with high monthly income have high knowledge since the interplay between the social gradient and health literacy is quite predictable (Diamond et al., 2011; Quinlan et al., 2013).

Fiscella (2016) stated that a person’s behavior is limited by their SES and hence their health-seeking behavior will change if their access to resources is increased (Fiscella, 2016). This means that the socio-economic disparities of participants with lower monthly income at SSH will need to be tackled by primary healthcare workers to influence KAP. This is difficult and thus may involve health and policy-making at the operational level to take into account the issues of health equality and equity.

Conclusion

This research was able to identify high-risk groups with low levels of knowledge, attitude and practice, towards whom targeted public health interventions can be targeted in future. The results of this study can enable informed public-health policies to be made to target the high risk specific groups with low KAP scores and consequently potentially increasing their knowledge, attitudes and practice within these populations through well-planned, appropriate and tailored strategies that are culturally acceptable and suit the identified groups. Consequently, health promotion activities are vital in improving knowledge, attitude and practice, and it is recommended that health promotion and interventional studies to be conducted using the results of this study among patients targeted toward at-risk groups identified in this study to potentiate the greatest improvements in health outcomes and to measure the effectiveness of health promotion intervention. Further research like clustered randomized intervention trials are necessary to identify test strategies to improve management and outcomes for these high risk patients.

Recommendations

It is recommended that in order to raise the level of knowledge, attitude and practice, in high risk populations, the barriers to healthcare need to be identified and removed or reduced. There could be for example, provisions made for mobile outreach health-clinics for rural communities, who have difficulty in accessing hospital services. Additionally, there needs to be financial support or free transport for patients to attend clinic, if they face difficulties in accessing medical care due to financial issues. The patients need to have convenient and varied clinic times that include pharmaceutical services. They need to be booked for clinics at a time suitable for them keeping in mind their transport issues, distance of travel, work and other commitments, and so forth. Thus, flexibility in the appointment system for patients can help increase their compliance to attendance at clinics (including mobile clinics) therefore increase their access to wide array of health services thus leading to an increase the number of contacts with health professional, improve self-management for those with chronic conditions, reduce diabetes-related complications and reduce inequalities in health care provision in Fiji and greater medical services including awareness. The barriers to healthcare need to be identified and consequently attempts made to reduce them so as to help empower patients to live a healthier life, make smart health choices, manage their illness and avoid complications. The most important factor will be to recognize the high risk patients so that an intensive and comprehensive health care intervention/program is delivered to them.

Data availability