Determinants of carbohydrate consumption in patients with type 2 diabetes based on the health belief model

FATEMEH MOHEBIAN,1 MOHSEN SHAMSI,1 RAHMATOLLAH MORADZADEH,2 MAHBOOBEH KHORSANDI,1 FATEMEH AZIZI-SOLEIMAN3

1 Department of Health Education, School of Health, Arak University of Medical Sciences, Arak, Iran
2 Department of Epidemiology, School of Health, Arak University of Medical Sciences, Arak, Iran
3 Department of Nutrition, School of Health, Arak University of Medical Sciences, Arak, Iran

Address for correspondence: Dr Fatemeh Azizi-Soleiman* Assistant Professor of Nutrition Sciences, Department of Nutrition, School of Health, Arak University of Medical Sciences, Arak, Iran, Postal code: 3818146851
E-mail: fatemehazizi87@gmail.com

Co-corresponding author: Dr Mahboobeh Khorsandi
Professor of Health Education and Health Promotion, Arak University of Medical Sciences, Arak, Iran, Postal code: 3818146851
E-mail: khorsandi.mahboobeh@gmail.com

Abstract

Background: Diabetes is a chronic condition in which serious complications can only be avoided by managing blood sugar levels. Carbohydrates are the most crucial macronutrients that greatly influence blood glucose levels, and tracking carbohydrate intake is a vital strategy for managing diabetes-related glycaemic control. This study aimed to explore the predictors of carbohydrate consumption in diabetic patients using the health belief model (HBM).

Methods: This cross-sectional study was conducted on 202 people with type 2 diabetes (T2DM) from health service centers in Arak City from 2019 to 2020, selected using a systematic random sampling method. Data were gathered using a researcher-designed questionnaire covering knowledge, HBM constructs and patients' carbohydrate consumption behaviours, with linear regression employed to assess the predictive model of these constructs.

Results: A significant positive association was found between perceived severity (r = 0.271, p < 0.001), perceived benefits (r =0.422, p < 0.001), self-efficacy (r = 0.390, p < 0.001), knowledge (r = 0.401, p < 0.001), and carbohydrate consumption behaviour. Conversely, carbohydrate consumption behaviour and perceived susceptibility (r = -0.172, p = 0.014) were negatively correlated. The following factors were associated with  carbohydrate  consumption  behaviour: awareness (β = 0.278, p < 0.001), perceived barriers (β = -0.241, p < 0.001), perceived benefits (β = 0.335, p < 0.001), and self-efficacy (β = 0.177, p < 0.001), with an explanatory power of 32.7% (p<0.001). Regarding fasting blood sugar (FBS) and glycosylated haemoglobin (HbA1c), knowledge was the strongest predictor.

Conclusion: Our findings demonstrated the efficiency of the health belief model in prediction of carbohydrate intake in people with T2DM.

Br J Diabetes 2025;25:(1)8-13
https://doi.org/10.15277/bjd.2025.477

Key words: diet, diabetes, health belief model, health education

Introduction

Diabetes is a non-communicable disease referred to as a "latent epidemic" by the World Health Organization. In 2021, an estimated 485 million adults aged 20 to 79 years were diagnosed with diabetes, with a range of 456 to 517 million.1 Type 2 diabetes(T2DM) accounted for 96.0% of all diabetes cases in 2021. Global diabetes prevalence increased by 90.5% from 1990 to 2021, with some regions, such as North Africa and the Middle East, experiencing over a rise of more than 100%.1 In 2023, Hazar et al. reported that the prevalence of diabetes among Iranians over 25 years old was 10.80%.2 In 2019, diabetes directly caused 1.5 million deaths, with 48% occurring before the age of 70. Additionally, diabetes contributed to 460,000 kidney disease deaths, and elevated blood glucose accounted for approximately 20% of cardiovascular deaths.3 Individuals with diabetes face at least double the risk of death compared to those without the condition. Uncontrolled blood sugar can lead to serious consequences, including vision loss, nephropathy, peripheral neuropathy, cardiovascular diseases, lipid disorders and kidney failure.4

The World Health Organization finds that adhering to basic healthy lifestyle standards effectively prevents or delays T2DM.4 The International Diabetes Association asserts that diabetes- related diseases can be prevented through proper education.5 Research indicates that educational interventions, along with ongoing patient support, can enhance glycaemic control, improve quality of life, heighten treatment satisfaction, and increase knowledge and awareness.6 The health belief model (HBM) is an effective framework in health education, viewing behaviour as influenced by a person's knowledge and attitude. It posits that awareness of a health threat shapes individuals' health-related behaviours.7 According to the HBM, a person is motivated to adopt healthy behaviours when he perceives himself as susceptible to a disease (perceived susceptibility), recognizes the seriousness of the disease's consequences (perceived severity), and believes in the effectiveness of recommended actions to reduce risk (perceived benefits). He also considers obstacles to these behaviours, such as costs (perceived barriers), assesses his ability to engage in the behaviour (perceived self-efficacy), and responds to both internal and external cues (guidelines for action), ultimately leading to healthier choices.8 Patients' adherence to medical advice and involvement in self-care behaviours can be influenced by their health beliefs.9 Previous research findings have illustrated the successful implementation of the HBM in both the explanation and prediction of health behaviours in patients with diabetes.10-12

Given the significance of blood sugar control in preventing diabetes complications, managing post-meal blood sugar through lifestyle adjustments and proper nutrition — particularly by limiting carbohydrates and consuming high-fibre foods — is crucial for controlling this disease. The reduction of carbohydrate intake is an effective strategy for improving glycaemic control in patients suffering from diabetes.13-15 Therefore, identifying the factors that affect behaviour with regard to carbohydrate consumption can help to control this behaviour and ultimately control diabetes. The aim of this study was to determine factors influencing the carbohydrate intake of people with T2DM based on the HBM.

Materials and methods

Study population

The present cross-sectional study was conducted on 202 people with T2DM in Arak from November 2019 to July 2020. Systematic random sampling was used for this study. The sample size was assessed based on the following formula:

1357 Mohebian Formula

where n = sample size, Z = critical value for ɑ = [0.05] and d = [9].16 The minimum required sample size was calculated as 184. Accounting for a dropout rate of 10%, the sample size was adjusted to 202 patients. The study's inclusion criteria encompassed individuals aged 30 to 60 years diagnosed with T2DM who were permanent residents of the town. Participants were required to have a minimum one-year history of T2DM, be currently utilizing oral anti-diabetic medications, and to possess the ability to read and write. The exclusion criteria involved individuals who were receiving insulin therapy, adhering to any specific dietary regimens, or who had a medical history of intestinal, pulmonary, hepatic, renal, cardiac or infectious diseases. Those with thyroid disorders, pregnant or breastfeeding women, and individuals who had experienced any alterations in diet, lifestyle or dosage of diabetic medications in the past six months were also excluded. The study was conducted on T2DM patients who had been referred to comprehensive health service centres of Arak. They were divided into four strata, according to the opinion of the health department staff, based on their socio-economic status. These centres with a covered a population of almost good, medium, low-medium and poor economic status. A total of eight centres was determined and 25 people were selected from each centre. Patients from each centre were selected and contacted in accordance with the inclusion criteria. If they were satisfied and interested, they were included in the study.

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Data collection tool

The data collection tool included a researcher-made questionnaire that was completed by self-reporting and semi-structured interviews (see Appendix 1). This questionnaire was set up in two parts.

The first part contained 22 questions about the demographic information of people with T2DM and the second part contained 9 questions about knowledge, 2 questions for perceived susceptibility, 5 questions for perceived severity, 8 questions for perceived benefits, 7 questions for perceived barriers, 8 questions for self-efficacy, 6 questions for behaviour, 5 questions for internal cues for action, and 6 questions for external cues for action. To score the questionnaire in the knowledge part, one point was given for each correct answer and zero score was considered for the answer “I don't know”. The knowledge items included in the questionnaire evaluated individuals with T2DM on their awareness of the disease, food groups (food pyramid), carbohydrate containing foods (simple and complex), colour-coded food labeling, cooking methods and blood sugar monitoring tests.

In the constructs section (perceived sensitivity, perceived severity, perceived benefits, perceived barriers, self-efficacy, performance and internal action guidelines and external action guidelines) a five-point Likert scale from “completely disagree” to “completely agree” was used: the range of points for each question varied from 1 to 5, so that the answers were given 1 point, 2 points, 3 points, 4 points or 5 points. In the self-efficacy section, the score of each question varied between 1 and 10, so that the answer “I am not sure at all” was given a score of 1 and “I am absolutely sure” was given a score of 10. The score of each question related to behaviour varied between 0 and 3: the answer of “never” was given 0 points, 1 point to “some extent”, 2 points to “most of the time” and 3 points for “always”. In the cues for action section (both internal and external), questions were in the form of yes and no. If the answer was “yes”, the score was between 1 and 4 points, “always” was given 4 points, “often” 3 points, “somewhat” 2 points and “rarely” 1 point. If the answer was “no”, zero points were assigned to it.

The questions related to severity and sensitivity addressed issues related to diabetes and its complications. The section related to perceived benefits and barriers addressed the effect of choosing healthy carbohydrates on disease control and the existing barriers to selecting healthy carbohydrates. Eight questions assessed patients' self-efficacy (e.g. I can reduce consumption of sweets). Cues to action items (10 questions) were elements that could encourage patients to choose healthy carbohydrates (e.g. “Consumption of healthy carbohydrates boosts my feeling of being healthy”). The behavioural assessment item consisted of six questions designed to evaluate the patient’s behaviour regarding food groups, colour- coded food labels, self-monitoring blood sugar and self-monitoring body weight.

In order to measure the validity of the questionnaire, the content validity method was used in such a way that it was reviewed by 10 experts (five professionals in health education, three nutritionists and two epidemiologists) and their opinions were applied in the questionnaire. At this stage, three questions were removed due to the low content validity ratio and finally validity of the questionnaire was confirmed. The reliability of the questionnaire was also measured through Cronbach's alpha test method on 20 people with T2DM who were similar to the study population in terms of demographic characteristics. The results were similar. Internal validity using Cronbach's alpha coefficients showed that all coefficients were favourable and satisfactory and confirmed, with values above 0.7.

After correcting the questions, the final questionnaire was compiled. Patients were advised to keep a food diary for three days (two weekdays and one day of the weekend). To ensure that there were no potential changes in carbohydrate intake, these notes were reviewed by a nutritionist. Before the patients entered the study, the necessary explanations about the purpose of the research were given to them and informed written consent was obtained. This study was performed according to the principles of the Declaration of Helsinki and approved by the Ethics Committee of Arak University of Medical Sciences (ID IR.ARAKMU.REC.1398.079).

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Statistical analysis

The statistical analyses were conducted utilizing SPSS software (Version 23, IBM Corporation, Armonk, NY, USA). The Spearman/Pearson correlation coefficient was used to examine the associations between the HBM constructs and carbohydrate intake behaviours. In order to determine the predictive power of the structures, the linear regression test was used with the backward method. P < 0.05 was considered to be a statistically significant level.

Results

Of the 202 participants, 70.8% were female and 84.2% were married, with a mean age of 54.7 years (SD=9.3). Of the participants, 34.6% had completed high school or education beyond this level. The average fasting blood sugar was 156.9±50.3 mg/dL (8.7±2.8 mmol/L) and the average HbA1c was 7.1±1.3% (54 mmol/L) (Table 1).

Table 2 presents the range, means and standard deviations of the Health Belief Model (HBM) constructs related to carbohydrate intake behaviour and knowledge. Patients scored highest in self-efficacy and perceived severity, while behaviour received the lowest score.

Table 3 shows bivariate associations between the HBM variables and carbohydrate consumption behaviour. Significant positive associations were found between the four constructs perceived severity, perceived benefits, self-efficacy and knowledge and carbohydrate consumption

© 2025. This work is openly licensed via CC BY 4.0

© 2025. This work is openly licensed via CC BY 4.0.

This license enables reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. CC BY includes the following elements: BY – credit must be given to the creator.

Copyright ownership The author(s) retain copyright.

Conflict of interest The authors declare they have no conflict of interest.

Funding This work was supported by the Arak University of Medical Sciences (grant number: 5901).

Ethics approval and consent to participate This study was performed according to the principles of the Declaration of Helsinki and approved by the Ethics Committee of Arak University of Medical Sciences (ID IR.ARAKMU.REC.1398.079). Before the patients entered the study, the necessary explanations about the purpose of the research were given to them and informed written consent was obtained.

Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. and developed the idea for the study and, under the supervision of M KH, revised the manuscript. This study is being conducted by FM as part of her MSc thesis (5901). Final approval of the manuscript was obtained from all authors.

Acknowledgements We want to express our gratitude to everyone who took part in the study.

Authors' contributions As a team, all authors contributed to the conception and design of the study. M KH, FAS, M SH and RM conceived

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Appendix 1

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