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Moslemi M, Mahdavi-Roshan M, Joukar F, Mansour-Gahnaei F. Nutritional Assessment and Estimation of the Attributable Risk of Diabetes Mellitus to Simple Sugar Intake in Northern Iran: The PERSIAN Guilan Cohort Study. JNFS 2025; 10 (3) :413-422
URL: http://jnfs.ssu.ac.ir/article-1-1151-en.html
URL: http://jnfs.ssu.ac.ir/article-1-1151-en.html
Gastrointestinal and Liver Diseases Research Center, Guilan University of Medical Sciences, Rasht, Iran.
Keywords: Demography, Dietary pattern, Diabetes mellitus, Non-communicable diseases, Nutritional assessment.
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| Abstract (HTML) (378 Views)
1 Halal Research Center of IRI., Iran Food and Drug Administration, Ministry of Health and Medical Education, Tehran, Iran; 2 Department of Cardiology, Cardiovascular Diseases Research Center, Heshmat Hospital, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran; 3 Department of Clinical Nutrition, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran; 4 Gastrointestinal and Liver Diseases Research Center, Guilan University of Medical Sciences, Rasht, Iran.
To better determine the impact of sugar intake on the incidence of diabetes, the risk of DM in the total population was assessed using PAR formula. In the study by Montonen et al., the relative risk of type 2 DM incidence for individuals with fructose and glucose intake exceeding 56.2 g/day was 1.87. According to Table 3, Q3 of fructose and glucose intake was 56.16 g/day, which is close to the cut-off point reported in Montonen et al.'s study. Therefore, the authors conducted two scenarios to calculate PART2DM in the population.
First scenario: The analysis revealed that 25% of the population had more than 56.16 g/day fructose and glucose intake. Accordingly, 17.86% of the total population is at risk of type 2 DM incidence.
Second scenario: Evaluation of the data revealed that 24.92% of the total population consumed more than 56.2 g/day of fructose and glucose (the cut-off point of Montonen et al. (Montonen et al., 2007). Therefore, 17.82% of the total population is at risk of type 2 DM incidence.
Discussion
Socio-demographic and food intake information of the diabetic patients showed a high correlation between food habits and the development of DM. Food intake evaluation revealed a relatively high intake of carbohydrates and a low intake of fiber in this study (Table 2). This is likely attributed to the low proportion of patients with high socio-economic status and the low number of academically educated patients, especially among women. Inadequate knowledge is a significant factor affecting body health. According to Table 1, most patients had no academic degree, and likely, were not educated enough to follow a balanced diet. The role of socio-economic status in dietary patterns was confirmed in a study by Casari et al., where the rural population of Burkina Faso with lower socio-economic status consumed more carbohydrates than urban inhabitants (Casari et al., 2022). Additionally, rural Polish adolescents with low socio-economic status followed a low-fiber diet in a study by Krusinska et al. (Krusinska et al., 2017). Similarly, Egyptian mothers with low socio-economic status believed that a healthy diet is expensive and preferred to spend less to simply keep their children full. In comparison, those with high socio-economic status spent more money on their food (Ismail et al., 2022). Therefore, it would be expected that people with low to moderate socio-economic status tend to choose low-cost foods, such as carbohydrate-based rather than protein-based meals.
Fruits and vegetables are the main sources of dietary fiber in daily diet. The World Health Organization recommends at least 400 g/day of fruits and vegetables combined to maintain health (World Health Organization, 2022) . Moreover, a consumption of 200 g/day of fruits is recommended to prevent type 2 DM (Park, 2021). However, fruit consumption is controversial, and its effect on diabetes prevention is dose-dependent. It is reported that fruit intake exceeding the recommendation does not show a positive effect and might lead to an increased prevalence of type 2 DM (Park, 2021). According to Table 2, the consumption of fruits by patients exceeded the recommended amount, supplying high levels of simple sugars to the body. It was reported that the type of fruit is a deterministic factor in the development of DM, with some fruits potentially increasing the risk of type 2 DM (e.g., cantaloupe), while others have a protective effect (e.g., pear and apple). The authors suggested that phytochemicals such as flavonoids and chlorogenic acid present in fruits play different roles concerning DM development (Park, 2021, Seino et al., 2021). Flavonoids are associated with β-cell proliferation and insulin secretion. Furthermore, the consumption of lower glycemic index fruits is of interest in the control of DM. Importantly, the concentration of fructose and fiber in fruits is a deterministic factor in this regard. After ingestion, fibers are consumed by the intestinal microflora, leading to the production of short-chain fatty acids and the satiety hormone GLP-1. Moreover, both fructose and sucrose stimulate the secretion of GLP-1 and FGF-21 satiety hormones (Seino et al., 2021). As mentioned above, the effect of fructose (the main sugar in fruits) is dose-dependent. Chronic high intake of fructose may lead to insulin resistance, hyperglycemia, and fatty liver by depleting ATP stores and causing uric acid accumulation in the body, which increases the risk of oxidative stress. However, moderate fruit intake results in lower food consumption and a low glycemic index, which supports diabetes prevention and control (Ang and Yu, 2018, Mai and Yan, 2019). In addition, the consumption of sweetened foods appears to be high among diabetic patients, with the intake of simple sugars (Table 3) exceeding the maximum recommended range by health agencies (Cozma and Sievenpiper, 2014).
The average of two PART2DM predictions based on the Q3 and the cut-off point reported by Montonen et al. was 17.84% (Montonen et al., 2007). This predicted average differed slightly from the proportion of diabetic patients in the total population (24.01%). However, 17.46% of the total population were prediabetic individuals (fasting blood sugar 100-125 mg/dl), who may develop DM if they do not modify their dietary patterns toward lower intake of simple sugars and carbohydrates and increase their intake of dietary fibers. Accordingly, Tabak et al. reported that up to 70% of prediabetic individuals might eventually develop DM (Tabák et al., 2012). Nonetheless, a comparison of predictive data and observed results confirmed the association of an imbalanced diet with the incidence of type 2 DM in the population. The findings of this study are a breakthrough for the development of educational programs for both virtual and in-person education.
This study benefits from its large, population-based design within the PGCS, which enhances generalizability and leverages standardized protocols to ensure methodological rigor. The use of a validated, culturally adapted FFQ and the exclusion of implausible energy intakes strengthened the reliability of dietary assessments, while the integration of USDA and Iranian food composition databases improved nutrient estimation accuracy. Furthermore, calculating population attributable risk provided actionable insights into the preventable diabetes burden linked to simple sugars. However, the cross-sectional design precludes causal inference, and reliance on self-reported dietary data introduces potential recall bias, particularly as processed/ready-to-eat food sugars were excluded, possibly underestimating total intake. The use of external relative risk values for PAR calculations, though methodologically sound, may not fully reflect regional biological or behavioral contexts. Future longitudinal studies with repeated dietary measures and biomarkers (e.g., HbA1c) are warranted to establish causality, and expanding the Iranian Food Composition Table could refine nutrient assessments. Replication in diverse geographic and ethnic populations would improve generalizability, and inclusion of processed food sugar data would provide a more comprehensive risk profile.
Conclusion
This study revealed that an imbalanced diet was significantly associated with the development of DM in individuals. The calculation of PART2DM, as a predictive tool, confirmed that a high intake of simple sugars (especially fructose and glucose) affected DM incidence. It is expected that fruits play a major role, as they are considered the main source of dietary fiber and fructose (one of the dominant simple sugars in the diet) simultaneously. Fruits have a preventive role in DM development up to the recommended level (200 g/day), while they could be deleterious if consumed at higher levels. The type of fruit, considering its glycemic index and inclusion of phytochemicals, is a determining factor. Moreover, it is established that dietary patterns are affected by socio-economic status. In this study, a high proportion of the patients were those with low to moderate socio-economic status, low daily fiber, and high carbohydrate intake. It is assumed that changing food intake habits is difficult for individuals with low socio-economic status because they have limited options in selecting food items for their food basket. However, promoting their knowledge about the outcomes of an imbalanced and unhealthy diet may help them follow a cost-effective healthy dietary pattern. For example, using inexpensive and valuable proteinaceous meals such as herbal proteins instead of high carbohydrate-based foods to overcome hunger would be greatly important. On the other hand, changing preferences towards low-sugar foods and/or using alternative sweeteners with a low glycemic index will significantly affect the control of diabetes in the general population and diabetic patients.
Acknowledgments
This article is derived from a research project approved at Guilan University of Medical Sciences, Rasht, Iran. We would like to thank the staff of Guilan University of Medical Sciences for their efforts in data collection.
Authors’ contributions
Mansour-Ghanaei F, Moslemi M, Joukar F, and Mahdavi-Roshan M participated in the research design. Moslemi M, Joukar F, and Mahdavi-Roshan participated in writing the first draft. Mansour-Ghanaei F, Moslem M, Joukar F, and Mahdavi-Roshan M participated in the performance of the research and analytic tools. Moslem M, and Joukar F participated in data analysis. All authors reviewed and confirmed the final manuscript.
Conflict of interest
The authors declared no conflict of interest.
Funding
No funding.
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Nutritional Assessment and Estimation of the Attributable Risk of Diabetes Mellitus to Simple Sugar Intake in Northern Iran: The PERSIAN Guilan Cohort Study
Introduction
Diabetes mellitus (DM) is one of the most common non-communicable diseases (NCDs) in Iran, which may lead to death in the population under uncontrolled conditions (Moslemi et al., 2020), although it has a smaller share in annual deaths compared to cardiovascular diseases, cancers, and respiratory diseases (Ryan-Harshman and Aldoori, 2006). Several studies have shown the impact of food habits and daily diet on the incidence or prevention of Non-communicable diseases (NCDs) (Alkhatib et al., 2017, Aune et al., 2013, Curioni et al., 2022, Kopčeková et al., 2020, Soltanipour et al., 2019, Tariq et al., 2022). Unfortunately, the modernization of communities toward a higher intake of low-nutrition foods and high-sugar snacks is a noticeable risk factor in the prevalence of DM. The hunger rate has gradually decreased in Iran, while people commonly eat unhealthy foods, especially in industrial cities (Faramarzi et al., 2019). Interestingly, improving food knowledge toward healthy eating behavior at early age helps decrease the rate of NCDs in adulthood and reduces burdens on governments (Albuquerque et al., 2023, Lunze et al., 2015). Therefore, the development of educational programs following national surveys presenting dietary habits is of great importance. In this regard, governments are recommended to adhere to the global action plan developed by the World Health Organization (WHO) in 2013 to decrease the rate of NCDs in countries (Moslemi et al., 2020).
| ARTICLE INFO | ABSTRACT | |
| ORIGINAL ARTICLE | Background: Diabetes Mellitus (DM) is a non-communicable disease with an increasing rate across all age groups worldwide. It makes the body vulnerable to other chronic diseases. Besides medication therapy, DM can be controlled by following a healthy lifestyle. In this study, the dietary patterns of diabetic individuals assessed in the Prospective Epidemiological Research Studies of the Iranian Adults (PERSIAN) Guilan Cohort Study (PGCS) population. Methods: A comprehensive survey was conducted over three years among 10,276 individuals aged 35 to 70 in the PGCS population. Socio-demographic and food intake information of 2,531 diabetic patients was collected using a food frequency questionnaire (FFQ). Data analysis was conducted with SPSS software. The estimation of the attributable risk of DM related to the intake of simple sugars was performed using the population attributable risk (PAR) equation. Results: The intake of dietary fibers was lower than the recommended 25-38 g/day in these patients, while they consumed high carbohydrates (more than 65% of total calories/day) and simple sugars (more than 10% of total calories/day). More than 15% of total energy was provided by simple sugars in these patients. The average population attributable risk of DM (PARDM) in the total population was 17.84% based on the intake of fructose and glucose, which was close to the proportion of diabetic patients in this survey by considering the proportion of pre-diabetic patients. Conclusions: Regarding the significant effect of dietary patterns on the development of DM, the authors suggest developing educational programs to help individuals maintain a balanced diet to decrease the rate of DM in the coming years. | |
| Article history: Received: 8 Oct 2024 Revised: 21 Mar 2025 Accepted: 21 Mar 2025 |
||
| *Corresponding author fmansourghanaei@gmail.com Gastrointestinal and Liver Diseases Research Center, Guilan University of Medical Sciences, Rasht, Iran. Postal code: 41448-95655 Tel: +98 13 33535116 |
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| Keywords: Demography; Dietary pattern; Diabetes mellitus; Non-communicable diseases; Nutritional assessment. |
Introduction
Diabetes mellitus (DM) is one of the most common non-communicable diseases (NCDs) in Iran, which may lead to death in the population under uncontrolled conditions (Moslemi et al., 2020), although it has a smaller share in annual deaths compared to cardiovascular diseases, cancers, and respiratory diseases (Ryan-Harshman and Aldoori, 2006). Several studies have shown the impact of food habits and daily diet on the incidence or prevention of Non-communicable diseases (NCDs) (Alkhatib et al., 2017, Aune et al., 2013, Curioni et al., 2022, Kopčeková et al., 2020, Soltanipour et al., 2019, Tariq et al., 2022). Unfortunately, the modernization of communities toward a higher intake of low-nutrition foods and high-sugar snacks is a noticeable risk factor in the prevalence of DM. The hunger rate has gradually decreased in Iran, while people commonly eat unhealthy foods, especially in industrial cities (Faramarzi et al., 2019). Interestingly, improving food knowledge toward healthy eating behavior at early age helps decrease the rate of NCDs in adulthood and reduces burdens on governments (Albuquerque et al., 2023, Lunze et al., 2015). Therefore, the development of educational programs following national surveys presenting dietary habits is of great importance. In this regard, governments are recommended to adhere to the global action plan developed by the World Health Organization (WHO) in 2013 to decrease the rate of NCDs in countries (Moslemi et al., 2020).
Masoumeh Moslemi; PhD1, Marjan Mahdavi-Roshan; PhD2,3, Farahnaz Joukar; PhD4
& Fariborz Mansour-Ghanaei; PhD*4,5
& Fariborz Mansour-Ghanaei; PhD*4,5
1 Halal Research Center of IRI., Iran Food and Drug Administration, Ministry of Health and Medical Education, Tehran, Iran; 2 Department of Cardiology, Cardiovascular Diseases Research Center, Heshmat Hospital, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran; 3 Department of Clinical Nutrition, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran; 4 Gastrointestinal and Liver Diseases Research Center, Guilan University of Medical Sciences, Rasht, Iran.
DM is characterized by hyperglycemia when the body is deficient in insulin due to insufficient insulin secretion and/or resistance of body cells to insulin. DM is mainly classified into type 1 (insulin deficiency), type 2 (predominantly insulin resistance), and gestational diabetes (Ballali and Lanciai, 2012, Fernandes et al., 2022). In general, glucose enters the cells from the bloodstream to supply energy through its metabolism by the tricarboxylic acid cycle in the mitochondria (Gasmi et al., 2021). In diabetic patients, glucose levels exceed the normal range in blood, putting the body at risk of several complications, such as cardiovascular diseases and kidney failure, due to oxidative stress (Charlton et al., 2020).
It was estimated that 9.5% of Iranians suffered from DM in 2021 (Najafi et al., 2024). Currently, there are about 420 million patients worldwide (World Health Organization, 2023). There is strong evidence addressing the adverse impact of a high-fat and carbohydrate diet and low intake of dietary fibers on the development of DM. A high fat level in blood may impair the function of β-cells responsible for insulin secretion in the pancreas, leading to hyperglycemia. In addition, some dietary fats, such as omega-6 fatty acids, may alter the expression of insulin signaling genes, and oxidative stress developed under dyslipidemia may block insulin signaling, leading to insulin resistance (Młynarska et al., 2025, Prasad et al., 2022). Furthermore, dietary fibers influence the secretion of incretin hormones and the degradation and absorption of nutrients in the lumen (Xie et al., 2021). In the study by Lindström et al. on 522 prediabetic patients, a high-fat, low-fiber diet significantly affected the incidence of type 2 DM, with a hazard ratio of 1.89 compared to the group consuming a low-fat, high-fiber diet (Lindström et al., 2006). Moreover, Breen et al. compared 248 adults in two groups: healthy individuals and patients with type 2 DM. They found that the healthy group consumed less fat and more fiber than the diabetic patients (Breen et al., 2014). On the other hand, Joshi et al. reported that the intake of carbohydrates in 796 Indian patients with type 2 DM exceeded the national recommendation in India (Joshi et al., 2014). Although results from a prospective cohort study by AlEssa et al. on 70,025 American women showed that carbohydrate content is not associated with DM (relative risk of 0.98), starch content directly contributes to the development of DM (relative risk of 1.23). In their study, total fiber, cereal fiber, and fruit fiber were found to reduce the risk of type 2 DM with relative risks of 0.8, 0.71, and 0.79, respectively (AlEssa et al., 2015).
According to the evidence, one feasible approach in the prevention and control of DM is following a healthy eating habit that includes the recommended amounts of dietary fibers (21-38 g/day), carbohydrates (45-65% of total calories/day), and fat (up to 20-35% of total calories/day) (Mahan and Escott-Stump, 2004). To determine the association of eating behaviors with DM types 1 and 2, the authors investigated 2,531 diabetic residents of Guilan (North of Iran) over three years (2014-2017). In this study, the amounts of the main dietary components affecting blood sugar levels were considered. This work is the first study to monitor the association of DM with dietary habits, especially simple sugars, in the Prospective Epidemiological Research Studies of the Iranian Adults (PERSIAN) Guilan Cohort Study (PGCS) population. The results provide a potent baseline for developing national strategies to control DM in the country.
Materials and Methods
Participants and experimental design
This was a cross-sectional study conducted within the framework of the Prospective Epidemiological Research Studies in Iran (PGCS) (Mansour-Ghanaei et al., 2019, Poustchi et al., 2018). Over three years (8 October 2014 to 20 January 2017), 10,276 individuals from Sowme’eh Sara, a county in northern Iran, aged between 35 and 70, were assessed. Of these, 2,531 diabetic patients (989 men and 1,542 women) were further evaluated for the dietary habits study. After excluding outliers based on dietary energy intakes (individuals with energy intake lower than 900 kcal and more than 4500 kcal were excluded), 2,467 diabetic individuals were included in the analysis.
Socio-demographic information of patients with type 1 and type 2 DM, including age, body mass index (BMI), education, marital status, socio-economic status, habitat, and smoking is reported in Table 1. The socio-economic status was based on the monthly income of the family head and other variables, including access to a washing machine, freezer, computer, Internet, automobile, color TV, mobile phone, laptop, etc., across different price ranges, as well as international travel.
Daily food intake of the patients, including the main dietary groups and simple sugars, is presented in Table 2. Diabetic patients were those diagnosed with DM by a doctor, having fasting blood sugar equal to or higher than 126 mg/dl, or taking insulin or antidiabetic medicine (Mansour-Ghanaei et al., 2019, Poustchi et al., 2018).
The participants completed a 125-item semi-quantitative food frequency questionnaire (FFQ) adapted for Iranians (Mirmiran et al., 2010). They reported the average frequency of consumption for each food over the past year per day, week, month, and year, or indicated if they never consumed it. The portion size was converted to grams using household measures. Data were categorized based on nutrients and food groups. Energy intake was calculated using the Food Composition Table (FCT) of the US Department of Agriculture (USDA) because the Iranian FCT was incomplete. However, the Iranian FCT was used as an alternative for traditional foods not listed in the USDA FCT (Ahuja et al., 2012, Azar and Sarkisian, 1980).
Ethical considerations
This project was approved by the Ethics Committee of Guilan University of Medical Sciences (IR.GUMS.REC.1402.594), and was in accordance with the ethical principles in the Declaration of Helsinki.
Data analysis
Initial assessment and analysis of the nutritional result was done by N4 software, and statistical analysis was done by IBM SPSS Statistics 26 (SPSS Inc., Chicago, IL, USA). Differences were significant at P-value≤0.05. Moreover, numeric and qualitative variables were compared between two groups of men and women by Independent Sample t-test and Chi-square test, respectively. Food intake data are reported as g/day by quartile and tertile other than mean±SD. To anticipate the risk of type 2 DM arising from daily intake of simple sugars in individuals, the average intake of simple sugars (especially glucose and fructose) in the total population (n=10,276) was calculated based on information provided by the participants through questionnaires. Simple sugars' intake included amounts directly consumed by the participants or as ingredients in their homemade meals; sugar from ready-to-eat or processed foods was not considered. The population attributable risk (PAR) of DM due to the intake of simple sugars in the total population was calculated according to Equation 1 (Moslemi et al., 2021):
PAR (%) =
Equation 1
where, Pe is the proportion of population exposed to the risk factor (i.e., fructose + glucose intake more than 56.2 g/day), and RR is the relative risk of risk factor with respect to DM, which was reported in a comprehensive study done by other scientists (Montonen et al., 2007, Moslemi et al., 2021).
Results
Socio-demographic information of the diabetic individuals is presented in Table 1. As seen, most patients of both genders were overweight or obese. A low percentage of diabetic patients had a college degree, and most were married. Despite the higher number of diabetic women, socio-economic status was slightly better among women, and a higher rate of smoking was observed in men.
This was a cross-sectional study conducted within the framework of the Prospective Epidemiological Research Studies in Iran (PGCS) (Mansour-Ghanaei et al., 2019, Poustchi et al., 2018). Over three years (8 October 2014 to 20 January 2017), 10,276 individuals from Sowme’eh Sara, a county in northern Iran, aged between 35 and 70, were assessed. Of these, 2,531 diabetic patients (989 men and 1,542 women) were further evaluated for the dietary habits study. After excluding outliers based on dietary energy intakes (individuals with energy intake lower than 900 kcal and more than 4500 kcal were excluded), 2,467 diabetic individuals were included in the analysis.
Socio-demographic information of patients with type 1 and type 2 DM, including age, body mass index (BMI), education, marital status, socio-economic status, habitat, and smoking is reported in Table 1. The socio-economic status was based on the monthly income of the family head and other variables, including access to a washing machine, freezer, computer, Internet, automobile, color TV, mobile phone, laptop, etc., across different price ranges, as well as international travel.
Daily food intake of the patients, including the main dietary groups and simple sugars, is presented in Table 2. Diabetic patients were those diagnosed with DM by a doctor, having fasting blood sugar equal to or higher than 126 mg/dl, or taking insulin or antidiabetic medicine (Mansour-Ghanaei et al., 2019, Poustchi et al., 2018).
The participants completed a 125-item semi-quantitative food frequency questionnaire (FFQ) adapted for Iranians (Mirmiran et al., 2010). They reported the average frequency of consumption for each food over the past year per day, week, month, and year, or indicated if they never consumed it. The portion size was converted to grams using household measures. Data were categorized based on nutrients and food groups. Energy intake was calculated using the Food Composition Table (FCT) of the US Department of Agriculture (USDA) because the Iranian FCT was incomplete. However, the Iranian FCT was used as an alternative for traditional foods not listed in the USDA FCT (Ahuja et al., 2012, Azar and Sarkisian, 1980).
Ethical considerations
This project was approved by the Ethics Committee of Guilan University of Medical Sciences (IR.GUMS.REC.1402.594), and was in accordance with the ethical principles in the Declaration of Helsinki.
Data analysis
Initial assessment and analysis of the nutritional result was done by N4 software, and statistical analysis was done by IBM SPSS Statistics 26 (SPSS Inc., Chicago, IL, USA). Differences were significant at P-value≤0.05. Moreover, numeric and qualitative variables were compared between two groups of men and women by Independent Sample t-test and Chi-square test, respectively. Food intake data are reported as g/day by quartile and tertile other than mean±SD. To anticipate the risk of type 2 DM arising from daily intake of simple sugars in individuals, the average intake of simple sugars (especially glucose and fructose) in the total population (n=10,276) was calculated based on information provided by the participants through questionnaires. Simple sugars' intake included amounts directly consumed by the participants or as ingredients in their homemade meals; sugar from ready-to-eat or processed foods was not considered. The population attributable risk (PAR) of DM due to the intake of simple sugars in the total population was calculated according to Equation 1 (Moslemi et al., 2021):
PAR (%) =
Equation 1
where, Pe is the proportion of population exposed to the risk factor (i.e., fructose + glucose intake more than 56.2 g/day), and RR is the relative risk of risk factor with respect to DM, which was reported in a comprehensive study done by other scientists (Montonen et al., 2007, Moslemi et al., 2021).
Results
Socio-demographic information of the diabetic individuals is presented in Table 1. As seen, most patients of both genders were overweight or obese. A low percentage of diabetic patients had a college degree, and most were married. Despite the higher number of diabetic women, socio-economic status was slightly better among women, and a higher rate of smoking was observed in men.
| Table 1. Socio-demographic information of the individuals with diabetes mellitus among PGCS population. | ||||
| Variable | Men (n=974) | Women (n=1493) | Total (n=2467) | P-valuec |
| Age (year) | 54.41±8.55a | 54.64±8.68 | 54.55±8.62 | 0.641 |
| Body mass index (kg/m2) < 18.5 18.5-25 25-30 30 < |
19 (1.95)b 339 (34.80) 438 (44.97) 178 (18.28) |
3 (0.20) 197 (13.20) 549 (36.77) 744 (49.83) |
22 (0.89) 536 (21.73) 987 (40.01) 922 (37.37) |
< 0.001 |
| Education (years) 0 (illiterate) ≤ 5 6-12 12 < |
121 (12.42) 285 (29.26) 482 (49.49) 86 (8.83) |
481 (32.22) 507 (33.96) 479 (32.08) 26 (1.74) |
602 (24.40) 792 (32.10) 961 (38.95) 112 (4.54) |
< 0.001 |
| Marital status Single Married Widow Divorced |
7 (0.72) 953 (97.84) 12 (1.23) 2 (0.20) |
38 (2.54) 1242 (83.19) 193 (12.93) 20 (1.34) |
45 (1.82) 2195 (88.97) 205 (8.31) 22 (0.89) |
< 0.001 |
| Socio-economic status Low Moderate High |
358 (36.76) 320 (32.85) 296 (30.39) |
384 (25.72) 540 (36.17) 569 (38.11) |
742 (30.08) 860 (34.86) 865 (35.06) |
< 0.001 |
| Habitat Urban Rural |
438 (44.97) 536 (55.03) |
699 (46.82) 794 (53.18) |
1137 (46.09) 1330 (53.91) |
0.39 |
| Smoking Yes No |
516 (52.98) 458 (47.02) |
22 (1.47) 1471 (98.53) |
538 (21.81) 1929 (78.19) |
< 0.001 |
| a: Mean±SD; b: n(%); c: It obtained from an independent sample t-test for quantitative variables and from chi-square test for qualitative variables | ||||
The dietary intake of patients with diabetes is reported in Table 2. Accordingly, 65.84% and 66.27% of daily energy was supplied by carbohydrates in men and women, respectively. As expected, men had a higher energy intake than women. In particular, men had a higher intake than women in all food groups. In both genders, the intake of dietary fibers and carbohydrates was outside the recommended range (i.e., 25-38 g/day for dietary fibers and 45-65% of total calories/day for carbohydrates). Besides, the high intake of total carbohydrates, more than 15% of total energy was provided by simple sugars in both men and women. The share of each macronutrient and food group in the daily food intake of DM patients is illustrated in Figure 1.
To predict the incidence of DM in the total population (n=10,276), the relative risk of DM considering the intake of fructose and glucose was extracted from the study by Montonen et al. (Montonen et al., 2007). Table 3 shows that the intake of simple sugars significantly affects DM based on quartiles of consumption. The number of individuals with fructose + glucose intake of more than Q3 was calculated for the PAR formula.
To predict the incidence of DM in the total population (n=10,276), the relative risk of DM considering the intake of fructose and glucose was extracted from the study by Montonen et al. (Montonen et al., 2007). Table 3 shows that the intake of simple sugars significantly affects DM based on quartiles of consumption. The number of individuals with fructose + glucose intake of more than Q3 was calculated for the PAR formula.
| Table 2. Total energy and dietary intake of the diabetic individuals among PGCS population. | ||||||
| Variable | Men (n=974) | Women (n=1493) | Total (n=2467) | Q1 | Q2 | Q3 |
| Energy (kcal/day) | 2060.54±630.35 | 1890.12±623.99 | 1957.40±631.90 | 1494.85 | 1854.97 | 2306.85 |
| Dietary fibers | 23.23±8.72 | 21.16±8.02 | 21.98±8.36 | 15.98 | 20.46 | 26.58 |
| Total carbohydrate | 339.15±107.46 | 313.13±106.92 | 323.40±107.86 | 244.32 | 304.71 | 381.17 |
| Protein | 69.45±24.04 | 62.21±22.89 | 65.07±23.62 | 48.06 | 60.71 | 77.47 |
| Fat | 51.25±20.45 | 46.82±19.60 | 48.57±20.06 | 34.35 | 44.48 | 58.49 |
| Food group (g/day) | ||||||
| Bread and cereals | 482.27±186.82 | 448.13±191.16 | 461.61±190.15 | 329.82 | 434.07 | 557.77 |
| Dairies | 220.12±154.35 | 207.08±161.25 | 212.23±158.66 | 115.98 | 177.75 | 266.46 |
| Fruits | 296.29±171.85 | 277.66±164.84 | 285.01±167.85 | 171.09 | 251.87 | 355.20 |
| Vegetables | 608.10±294.96 | 573.03±271.79 | 586.87±281.63 | 391.86 | 530.33 | 712.98 |
| Simple sugars (g/day) | ||||||
| Fructose | 25.99±13.50 | 23.98±13.10 | 24.77±13.30 | 15.74 | 22.10 | 31.06 |
| Glucose | 20.21±9.84 | 18.64±9.67 | 19.26±9.77 | 12.52 | 17.27 | 23.85 |
| Fructose + Glucose | 46.20±23.20 | 42.62±22.64 | 44.03±22.92 | 28.29 | 39.32 | 54.89 |
| Sucrose | 30.20±23.02 | 28.83±25.29 | 29.37±24.42 | 13.38 | 22.37 | 37.93 |
| Lactose | 3.19±3.49 | 2.92±3.59 | 3.03±3.55 | 0.98 | 1.90 | 3.92 |
| Total of simple sugars | 79.59 ±38.74 | 74.37 ±40.47 | 76.43 ±39.87 | 48.94 | 68.07 | 94.71 |
| Q1: First quartile; Q2: Second quartile; Q3: Third quartile. | ||||||
|
1
|
| Figure 1. Share of each dietary component in the diet of diabetic individuals. |
| Table 3. Intake of simple sugars of the total participants among PGCS population. | |||
| Intake (g/day) | Q1 | Q2 | Q3 |
| Fructose | 16.31 | 22.92 | 31.62 |
| Glucose | 13.08 | 17.96 | 24.46 |
| Fructose + Glucose | 29.45 | 40.93 | 56.16 |
| Sucrose | 17.59 | 28.68 | 46.02 |
| Lactose | 0.94 | 1.88 | 3.94 |
| Q1: First quartile; Q2: Second quartile; Q3: Third quartile. | |||
To better determine the impact of sugar intake on the incidence of diabetes, the risk of DM in the total population was assessed using PAR formula. In the study by Montonen et al., the relative risk of type 2 DM incidence for individuals with fructose and glucose intake exceeding 56.2 g/day was 1.87. According to Table 3, Q3 of fructose and glucose intake was 56.16 g/day, which is close to the cut-off point reported in Montonen et al.'s study. Therefore, the authors conducted two scenarios to calculate PART2DM in the population.
First scenario: The analysis revealed that 25% of the population had more than 56.16 g/day fructose and glucose intake. Accordingly, 17.86% of the total population is at risk of type 2 DM incidence.
Second scenario: Evaluation of the data revealed that 24.92% of the total population consumed more than 56.2 g/day of fructose and glucose (the cut-off point of Montonen et al. (Montonen et al., 2007). Therefore, 17.82% of the total population is at risk of type 2 DM incidence.
Discussion
Socio-demographic and food intake information of the diabetic patients showed a high correlation between food habits and the development of DM. Food intake evaluation revealed a relatively high intake of carbohydrates and a low intake of fiber in this study (Table 2). This is likely attributed to the low proportion of patients with high socio-economic status and the low number of academically educated patients, especially among women. Inadequate knowledge is a significant factor affecting body health. According to Table 1, most patients had no academic degree, and likely, were not educated enough to follow a balanced diet. The role of socio-economic status in dietary patterns was confirmed in a study by Casari et al., where the rural population of Burkina Faso with lower socio-economic status consumed more carbohydrates than urban inhabitants (Casari et al., 2022). Additionally, rural Polish adolescents with low socio-economic status followed a low-fiber diet in a study by Krusinska et al. (Krusinska et al., 2017). Similarly, Egyptian mothers with low socio-economic status believed that a healthy diet is expensive and preferred to spend less to simply keep their children full. In comparison, those with high socio-economic status spent more money on their food (Ismail et al., 2022). Therefore, it would be expected that people with low to moderate socio-economic status tend to choose low-cost foods, such as carbohydrate-based rather than protein-based meals.
Fruits and vegetables are the main sources of dietary fiber in daily diet. The World Health Organization recommends at least 400 g/day of fruits and vegetables combined to maintain health (World Health Organization, 2022) . Moreover, a consumption of 200 g/day of fruits is recommended to prevent type 2 DM (Park, 2021). However, fruit consumption is controversial, and its effect on diabetes prevention is dose-dependent. It is reported that fruit intake exceeding the recommendation does not show a positive effect and might lead to an increased prevalence of type 2 DM (Park, 2021). According to Table 2, the consumption of fruits by patients exceeded the recommended amount, supplying high levels of simple sugars to the body. It was reported that the type of fruit is a deterministic factor in the development of DM, with some fruits potentially increasing the risk of type 2 DM (e.g., cantaloupe), while others have a protective effect (e.g., pear and apple). The authors suggested that phytochemicals such as flavonoids and chlorogenic acid present in fruits play different roles concerning DM development (Park, 2021, Seino et al., 2021). Flavonoids are associated with β-cell proliferation and insulin secretion. Furthermore, the consumption of lower glycemic index fruits is of interest in the control of DM. Importantly, the concentration of fructose and fiber in fruits is a deterministic factor in this regard. After ingestion, fibers are consumed by the intestinal microflora, leading to the production of short-chain fatty acids and the satiety hormone GLP-1. Moreover, both fructose and sucrose stimulate the secretion of GLP-1 and FGF-21 satiety hormones (Seino et al., 2021). As mentioned above, the effect of fructose (the main sugar in fruits) is dose-dependent. Chronic high intake of fructose may lead to insulin resistance, hyperglycemia, and fatty liver by depleting ATP stores and causing uric acid accumulation in the body, which increases the risk of oxidative stress. However, moderate fruit intake results in lower food consumption and a low glycemic index, which supports diabetes prevention and control (Ang and Yu, 2018, Mai and Yan, 2019). In addition, the consumption of sweetened foods appears to be high among diabetic patients, with the intake of simple sugars (Table 3) exceeding the maximum recommended range by health agencies (Cozma and Sievenpiper, 2014).
The average of two PART2DM predictions based on the Q3 and the cut-off point reported by Montonen et al. was 17.84% (Montonen et al., 2007). This predicted average differed slightly from the proportion of diabetic patients in the total population (24.01%). However, 17.46% of the total population were prediabetic individuals (fasting blood sugar 100-125 mg/dl), who may develop DM if they do not modify their dietary patterns toward lower intake of simple sugars and carbohydrates and increase their intake of dietary fibers. Accordingly, Tabak et al. reported that up to 70% of prediabetic individuals might eventually develop DM (Tabák et al., 2012). Nonetheless, a comparison of predictive data and observed results confirmed the association of an imbalanced diet with the incidence of type 2 DM in the population. The findings of this study are a breakthrough for the development of educational programs for both virtual and in-person education.
This study benefits from its large, population-based design within the PGCS, which enhances generalizability and leverages standardized protocols to ensure methodological rigor. The use of a validated, culturally adapted FFQ and the exclusion of implausible energy intakes strengthened the reliability of dietary assessments, while the integration of USDA and Iranian food composition databases improved nutrient estimation accuracy. Furthermore, calculating population attributable risk provided actionable insights into the preventable diabetes burden linked to simple sugars. However, the cross-sectional design precludes causal inference, and reliance on self-reported dietary data introduces potential recall bias, particularly as processed/ready-to-eat food sugars were excluded, possibly underestimating total intake. The use of external relative risk values for PAR calculations, though methodologically sound, may not fully reflect regional biological or behavioral contexts. Future longitudinal studies with repeated dietary measures and biomarkers (e.g., HbA1c) are warranted to establish causality, and expanding the Iranian Food Composition Table could refine nutrient assessments. Replication in diverse geographic and ethnic populations would improve generalizability, and inclusion of processed food sugar data would provide a more comprehensive risk profile.
Conclusion
This study revealed that an imbalanced diet was significantly associated with the development of DM in individuals. The calculation of PART2DM, as a predictive tool, confirmed that a high intake of simple sugars (especially fructose and glucose) affected DM incidence. It is expected that fruits play a major role, as they are considered the main source of dietary fiber and fructose (one of the dominant simple sugars in the diet) simultaneously. Fruits have a preventive role in DM development up to the recommended level (200 g/day), while they could be deleterious if consumed at higher levels. The type of fruit, considering its glycemic index and inclusion of phytochemicals, is a determining factor. Moreover, it is established that dietary patterns are affected by socio-economic status. In this study, a high proportion of the patients were those with low to moderate socio-economic status, low daily fiber, and high carbohydrate intake. It is assumed that changing food intake habits is difficult for individuals with low socio-economic status because they have limited options in selecting food items for their food basket. However, promoting their knowledge about the outcomes of an imbalanced and unhealthy diet may help them follow a cost-effective healthy dietary pattern. For example, using inexpensive and valuable proteinaceous meals such as herbal proteins instead of high carbohydrate-based foods to overcome hunger would be greatly important. On the other hand, changing preferences towards low-sugar foods and/or using alternative sweeteners with a low glycemic index will significantly affect the control of diabetes in the general population and diabetic patients.
Acknowledgments
This article is derived from a research project approved at Guilan University of Medical Sciences, Rasht, Iran. We would like to thank the staff of Guilan University of Medical Sciences for their efforts in data collection.
Authors’ contributions
Mansour-Ghanaei F, Moslemi M, Joukar F, and Mahdavi-Roshan M participated in the research design. Moslemi M, Joukar F, and Mahdavi-Roshan participated in writing the first draft. Mansour-Ghanaei F, Moslem M, Joukar F, and Mahdavi-Roshan M participated in the performance of the research and analytic tools. Moslem M, and Joukar F participated in data analysis. All authors reviewed and confirmed the final manuscript.
Conflict of interest
The authors declared no conflict of interest.
Funding
No funding.
References
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Park HA 2021. Fruit intake to prevent and control hypertension and diabetes. Korean journal of family medicine. 42 (1): 9.
Poustchi H, et al. 2018. Prospective epidemiological research studies in Iran (the PERSIAN Cohort Study): rationale, objectives, and design. American journal of epidemiology. 187 (4): 647-655.
Prasad M, et al. 2022. A comprehensive review on high-fat diet-induced diabetes mellitus: an epigenetic view. Journal of nutritional biochemistry. 107: 109037.
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Seino Y, Iizuka K & Suzuki A 2021. Eating whole fruit, not drinking fruit juice, may reduce the risk of type 2 diabetes mellitus. Journal of diabetes investigation. 12 (10): 1759.
Soltanipour S, Hasandokht T, Soleimani R, Mahdavi-Roshan M & Jalali MM 2019. Systematic review and meta-analysis of the effects of soy on glucose metabolism in patients with type 2 diabetes. Review of diabetic studies. 15 (1): 60-70.
Tabák AG, Herder C, Rathmann W, Brunner EJ & Kivimäki M 2012. Prediabetes: a high-risk state for developing diabetes. Lancet. 379 (9833):2279.
Tariq MNM, et al. 2022. Lifestyle interventions for prevention and management of diet-linked non-communicable diseases among adults in Arab countries. In Healthcare, p. 45. MDPI.
World Health Organization 2022. Healthy diet, https:// www.who.int/news-room/fact-sheets/ detail/ healthy-diet.
World Health Organization 2023. Noncommunicable diseases-World Diabetes Day 2022,https:// www.who.int/campaigns/world-diabetes- day/2023.
Xie Y, Gou L, Peng M, Zheng J & Chen L 2021. Effects of soluble fiber supplementation on glycemic control in adults with type 2 diabetes mellitus: a systematic review and meta-analysis of randomized controlled trials. Clinical nutrition. 40 (4): 1800-1810.
Ahuja J, et al. 2012. USDA food and nutrient database for dietary studies, 5.0–documentation and user guide. In US Department of Agriculture, Agricultural Research Service, Food Surveys Research Group: Beltsville, MD, USA.
Albuquerque G, Lunet N, Breda J & Padrão P 2023. Food, nutrition and diet in urban areas from low-and middle-income countries in the WHO European Region. Public health nutrition. 26 (S1): s1-s5.
AlEssa HB, et al. 2015. Carbohydrate quality and quantity and risk of type 2 diabetes in US women. American journal of clinical nutrition. 102 (6): 1543-1553.
Alkhatib A, et al. 2017. Functional foods and lifestyle approaches for diabetes prevention and management. Nutrients. 9 (12): 1310.
Ang BRG & Yu GF 2018. The role of fructose in type 2 diabetes and other metabolic diseases. Journal of nutrition & food sciences. 8 (1): 659.
Aune D, Norat T, Romundstad P & Vatten LJ 2013. Dairy products and the risk of type 2 diabetes: a systematic review and dose-response meta-analysis of cohort studies. American journal of clinical nutrition. 98 (4): 1066-1083.
Azar M & Sarkisian E 1980. Food composition table of Iran. Tehran: National Nutrition and Food Research Institute, Shaheed Beheshti University. Farsi.
Ballali S & Lanciai F 2012. Functional food and diabetes: a natural way in diabetes prevention? International journal of food sciences and nutrition. 63 (sup1): 51-61.
Breen C, et al. 2014. High saturated-fat and low-fibre intake: a comparative analysis of nutrient intake in individuals with and without type 2 diabetes. Nutrition & diabetes. 4 (2): e104-e104.
Casari S, et al. 2022. Changing dietary habits: the impact of urbanization and rising socio-economic status in families from Burkina Faso in Sub-Saharan Africa. Nutrients. 14 (9): 1782.
Charlton A, Garzarella J, Jandeleit-Dahm KA & Jha JC 2020. Oxidative stress and inflammation in renal and cardiovascular complications of diabetes. Biology. 10 (1): 18.
Cozma AI & Sievenpiper JL 2014. The role of fructose, sucrose and high-fructose corn syrup in diabetes. European endocrinology. 10 (1): 51.
Curioni CC, da Silva ACF, da Silva Pereira A & Mocellin MC 2022. The role of dietary habits on development and progress of risk factors of chronic non-communicable diseases. In Healthy lifestyle: From pediatrics to geriatrics (ed. R. Kelishadi), pp. 105-129. Spriger.
Faramarzi E, et al. 2019. Association between food insecurity and metabolic syndrome in North West of Iran: Azar Cohort study. Journal of cardiovascular and thoracic research. 11 (3): 196.
Fernandes I, Oliveira J, Pinho A & Carvalho E 2022. The role of nutraceutical containing polyphenols in diabetes prevention. Metabolites. 12 (2): 184.
Gasmi A, et al. 2021. Krebs cycle: activators, inhibitors and their roles in the modulation of carcinogenesis. Archives of toxicology. 95 (4): 1161-1178.
Ismail DMAS, Mahran DG, Moftah FM & Aziz MM 2022. Perceived barriers to healthy eating among mothers of preparatory school girl students in an Egyptian City: a qualitative study. Egyptian journal of hospital medicine. 88 (1): 3346-3351.
Joshi SR, et al. 2014. Results from a dietary survey in an Indian T2DM population: a STARCH study. BMJ open. 4 (10): e005138.
Kopčeková J, et al. 2020. Association between selected dietary habits and lipid profiles of patients with cardiovascular disease. International journal of environmental research and public health. 17 (20): 7605.
Krusinska B, et al. 2017. Fibre-related dietary patterns: Socioeconomic barriers to adequate fibre intake in Polish adolescents. A short report. Nutrients. 9 (6): 590.
Lindström J, et al. 2006. High-fibre, low-fat diet predicts long-term weight loss and decreased type 2 diabetes risk: the Finnish Diabetes Prevention Study. Diabetologia. 49: 912-920.
Lunze K, Yurasova E, Idrisov B, Gnatienko N & Migliorini L 2015. Food security and nutrition in the Russian Federation–a health policy analysis. Global health action. 8 (1): 27537.
Mahan LK & Escott-Stump S 2004. Krause's food, nutrition, & diet therapy. Saunders Philadelphia.
Mai BH & Yan L-J 2019. The negative and detrimental effects of high fructose on the liver, with special reference to metabolic disorders. Diabetes, metabolic syndrome and obesity. 12: 821-826.
Mansour-Ghanaei F, et al. 2019. The PERSIAN Guilan cohort study (PGCS). Archives of Iranian medicine. 22 (1): 39-45.
Mirmiran P, Esfahani FH, Mehrabi Y, Hedayati M & Azizi F 2010. Reliability and relative validity of an FFQ for nutrients in the Tehran lipid and glucose study. Public health nutrition. 13 (5): 654-662.
Młynarska E, et al. 2025. Type 2 diabetes mellitus: new pathogenetic mechanisms. Journal of pharmaceutical negative results. 26 (3): 5234-5245.
Montonen J, Järvinen R, Knekt P, Heliövaara M & Reunanen A 2007. Consumption of sweetened beverages and intakes of fructose and glucose predict type 2 diabetes occurrence. Journal of nutrition. 137 (6): 1447-1454.
Moslemi M, et al. 2020. National food policies in the Islamic Republic of Iran aimed at control and prevention of noncommunicable diseases. Eastern Mediterranean Health Journal. 26 (12): 1556-1564.
Moslemi M, Mahdavi-Roshan M, Joukar F, Naghipour M & Mansour-Ghanaei F 2021. Food behaviors and its association with hypertension and cardiovascular diseases in Sowme’eh Sara (North of Iran): the PERSIAN Guilan Cohort Study (PGCS). Preventive nutrition and food science. 26 (3): 262.
Najafi F, et al. 2024. The incidence of diabetes mellitus and its determining factors in a Kurdish population: insights from a cohort study in western Iran. Scientific Reports. 14 (1): 15761.
Park HA 2021. Fruit intake to prevent and control hypertension and diabetes. Korean journal of family medicine. 42 (1): 9.
Poustchi H, et al. 2018. Prospective epidemiological research studies in Iran (the PERSIAN Cohort Study): rationale, objectives, and design. American journal of epidemiology. 187 (4): 647-655.
Prasad M, et al. 2022. A comprehensive review on high-fat diet-induced diabetes mellitus: an epigenetic view. Journal of nutritional biochemistry. 107: 109037.
Ryan-Harshman M & Aldoori W 2006. New dietary reference intakes for macronutrients and fibre. . Canadian family physician. 52 (2): 177.
Seino Y, Iizuka K & Suzuki A 2021. Eating whole fruit, not drinking fruit juice, may reduce the risk of type 2 diabetes mellitus. Journal of diabetes investigation. 12 (10): 1759.
Soltanipour S, Hasandokht T, Soleimani R, Mahdavi-Roshan M & Jalali MM 2019. Systematic review and meta-analysis of the effects of soy on glucose metabolism in patients with type 2 diabetes. Review of diabetic studies. 15 (1): 60-70.
Tabák AG, Herder C, Rathmann W, Brunner EJ & Kivimäki M 2012. Prediabetes: a high-risk state for developing diabetes. Lancet. 379 (9833):2279.
Tariq MNM, et al. 2022. Lifestyle interventions for prevention and management of diet-linked non-communicable diseases among adults in Arab countries. In Healthcare, p. 45. MDPI.
World Health Organization 2022. Healthy diet, https:// www.who.int/news-room/fact-sheets/ detail/ healthy-diet.
World Health Organization 2023. Noncommunicable diseases-World Diabetes Day 2022,https:// www.who.int/campaigns/world-diabetes- day/2023.
Xie Y, Gou L, Peng M, Zheng J & Chen L 2021. Effects of soluble fiber supplementation on glycemic control in adults with type 2 diabetes mellitus: a systematic review and meta-analysis of randomized controlled trials. Clinical nutrition. 40 (4): 1800-1810.
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