ABSTRACT
Background
Diabetes mellitus (DM) commonly coexists with dyslipidemia and elevated cardiovascular risk. Food‐based interventions containing antioxidants and polyphenols may support lipid metabolism. This study evaluated the short‐term effects of Golden Rice cookies enriched with active Piper crocatum extract on lipid profiles in adults with DM.
Methods
This quasi‐experimental pretest–posttest control group study included 102 adults with DM assigned in a 1:1 ratio to the intervention or control group. The intervention group received Golden Rice cookies enriched with P. crocatum extract, while the control group received similar cookies without the extract for 28 days. Total cholesterol, low‐density lipoprotein cholesterol (LDL‐C), high‐density lipoprotein cholesterol (HDL‐C), and triglycerides were measured before and after the intervention. Bivariate analyses were performed in the full sample, whereas analysis of covariance was performed among non‐statin participants, adjusting for baseline lipid values, age, body mass index, diabetes duration, carbohydrate intake, and protein intake.
Results
In the unadjusted analysis, total cholesterol and LDL‐C increased significantly in the intervention group, whereas total cholesterol decreased significantly in the control group. Between‐group analysis showed a significant difference only in total cholesterol. Among non‐statin participants, an exploratory adjusted analysis showed a significant between‐group difference in total cholesterol (p = 0.016; adjusted mean difference = −12.55 mg/dL; 95% confidence interval [CI] = −22.74 to −2.36). No significant adjusted differences were observed for LDL‐C, HDL‐C, or triglycerides.
Conclusion
A 28‐day intervention with Golden Rice cookies enriched with active P. crocatum extract was associated with a limited exploratory adjusted between‐group difference in total cholesterol among non‐statin adults with DM. These preliminary findings require confirmation in longer randomized controlled trials with stronger dietary control and mechanistic biomarker assessment.
Trial Registration
ClinicalTrials.gov number: NCT07268781
Keywords: diabetes mellitus, dyslipidemia, functional food, lipid profile, Piper crocatum
Significance Statement
This study provides preliminary clinical evidence on a locally developed food‐based intervention combining Golden Rice and active Piper crocatum extract in adults with diabetes mellitus. The findings indicate a limited exploratory adjusted between‐group difference in total cholesterol among non‐statin participants, with no significant adjusted differences in low‐density lipoprotein cholesterol (LDL‐C), high‐density lipoprotein cholesterol (HDL‐C), or triglycerides. Longer randomized controlled trials with mechanistic biomarker assessment are needed to confirm these preliminary findings.
1. Introduction
Diabetes mellitus (DM) is a chronic metabolic disorder characterized by impaired glucose regulation and is frequently accompanied by abnormalities in lipid metabolism [1, 2, 3]. In individuals with DM, chronic hyperglycemia, insulin resistance, oxidative stress, and low‐grade inflammation contribute to disturbances in lipid handling, including increased low‐density lipoprotein cholesterol (LDL‐C) levels, elevated triglyceride levels, and reduced high‐density lipoprotein cholesterol (HDL‐C) levels. These lipid abnormalities increase the risk of atherosclerosis and cardiovascular disease, which remain major causes of morbidity and mortality in adults with DM [1, 2].
The global burden of DM continues to increase, representing a major public health challenge [4, 5]. In addition to glycemic control, the management of dyslipidemia is an important component of diabetes care because lipid abnormalities contribute substantially to the development of cardiovascular complications [1, 2]. Pharmacological therapy remains the standard approach for managing diabetic dyslipidemia; however, long‐term management may be influenced by adherence, tolerability, cost, and access to care. Therefore, complementary food‐based nutritional strategies that are practical, acceptable, and culturally relevant may support comprehensive diabetes management.
Functional foods containing bioactive compounds have gained increasing attention as potential complementary strategies for improving metabolic health in recent years [6, 7]. Polyphenols, flavonoids, and carotenoids may influence lipid metabolism through antioxidant, anti‐inflammatory, and metabolic regulatory pathways [8, 9, 10]. These compounds have been reported to modulate oxidative stress, insulin sensitivity, hepatic lipid synthesis, and lipid particle oxidation, all of which are associated with diabetes‐related dyslipidemia.
Piper crocatum Ruiz & Pav., commonly known as Red Betel, is a medicinal plant widely used in Indonesia. It contains polyphenols, flavonoids, alkaloids, and other bioactive compounds [11, 12]. Experimental and preclinical studies suggest that P. crocatum has antioxidant, antihyperglycemic, anti‐inflammatory, and lipid‐modulating properties [13, 14, 15, 16, 17]. These biological activities provide a rationale for further investigation of P. crocatum as a potential component of food‐based interventions for individuals with metabolic disorders.
Golden Rice is a biofortified rice variety containing β‐carotene, a provitamin A carotenoid with antioxidant properties [18, 19, 20]. As a food matrix, Golden Rice may provide nutritional value while serving as a vehicle for delivering additional bioactive compounds. Incorporating Golden Rice and P.crocatum extract into cookies may offer a practical and acceptable form of functional food that can be integrated into daily dietary patterns, particularly in community‐based diabetes care settings [21].
Despite the biological potential of Golden Rice and P. crocatum, clinical evidence regarding their combined use within a functional food matrix for lipid profile modulation in adults with DM remains limited [11, 21, 22]. Previous studies have explored the potential of these ingredients in relation to metabolic or diabetic complications; however, evidence regarding their short‐term effects on total cholesterol, LDL‐C, HDL‐C, and triglyceride levels in adults with DM remains insufficient. Evaluating this intervention in a real‐world community setting may provide preliminary evidence for its role as a complementary nutritional strategy.
From a nursing perspective, nutrition education and lifestyle support are essential components of diabetes management. Nurses are well‐positioned to promote dietary adherence, monitor patient responses, and support culturally acceptable nutritional interventions in community settings [23, 24, 25, 26]. Therefore, a practical food‐based intervention, such as functional cookies, may support nursing‐led dietary education and community‐based diabetes care.
This study aimed to evaluate the short‐term effects of Golden Rice cookies enriched with active P. crocatum extract on lipid profile parameters in adults with DM. We hypothesized that 28 days of cookie consumption would modulate lipid profile parameters, including total cholesterol, LDL‐C, HDL‐C, and triglyceride levels.
2. Methods
2.1. Study Objective
This study aimed to evaluate the short‐term effects of Golden Rice cookies enriched with active P. crocatum extract on lipid profile parameters, including total cholesterol, LDL‐C, HDL‐C, and triglyceride levels, in adults with DM.
2.2. Study Design and Setting
This study used a single‐blind quasi‐experimental pretest–posttest control group design. The study was conducted in the service area of the Lompeta Singgani Tambu Community Health Center, Donggala Regency, Indonesia, between September and December 2025. Participants were followed for 28 days, and lipid profile parameters were measured at baseline and at the end of the intervention period.
2.3. Participants
Participants were recruited from among adults diagnosed with DM who received routine care at the Lompeta Singgani Tambu Community Health Center. Potentially eligible participants were identified through medical record screening and invited to participate if they met the eligibility criteria. All participants received detailed information about the study procedures and provided written informed consent before enrollment.
Participants were eligible if they were aged 18–59 years, had a diagnosis of DM based on medical records, could communicate effectively with the research staff, were permanent residents of the Tambu area of Donggala Regency, and were willing to comply with the intervention protocol, including daily cookie consumption.
Participants were excluded if they were pregnant, breastfeeding, or planning pregnancy; had severe mental health disorders that could interfere with study participation; or had severe comorbidities that could affect lipid metabolism, including chronic kidney disease, hepatitis, congestive heart failure, stroke, or acute coronary heart disease within the previous 3 months. Individuals who had consumed high‐dose herbal or antioxidant supplements within the previous month, had severe gastrointestinal disorders such as chronic diarrhea, or had known allergies to any of the ingredients used in the intervention cookies were also excluded.
Participants were considered to have dropped out if they withdrew before completing the intervention, missed cookie consumption for three or more consecutive days, became pregnant during the study period, required hospitalization or emergency medical treatment, died during the study period, or experienced significant discomfort or adverse effects related to cookie consumption.
2.4. Sample Size
The study population comprised patients with DM who received routine care at the Lompeta Singgani Tambu Community Health Center. The sample size was estimated using a finite population formula with a 95% confidence level and a 5% margin of error. Based on a total population of 122 eligible patients, the minimum required sample size was 93.
To account for potential dropouts, the target sample size was increased by approximately 10% to 102 participants. Participants were assigned to the intervention and control groups in a 1:1 ratio (n = 51 per group).
2.5. Group Allocation and Blinding
After all eligible participants had been identified, participant identification numbers were placed into a lottery and drawn sequentially. The participant whose number was drawn first was assigned to the intervention group, the next participant whose number was drawn was assigned to the control group, and subsequent participants were allocated alternately between the intervention and control groups until 51 participants were assigned to each group. The lottery therefore determined the order of participants, while group assignment followed an alternating allocation procedure. No formal random allocation sequence was generated, and allocation concealment was not implemented. Accordingly, the study was classified as a quasi‐experimental controlled study rather than a randomized controlled trial.
The study used a single‐blind design in which participants were unaware of their group assignment. Both products were prepared with similar physical and sensory characteristics, including appearance, taste, and packaging, to minimize participants' ability to identify their assigned group.
2.6. Ethical Approval and Trial Registration
This study was conducted in accordance with the ethical principles of the Declaration of Helsinki. Ethical approval was obtained from the Health Research Ethics Committee of Hasanuddin University, Indonesia (approval no. 587/UN4.I8.3/TP.01.02/2025). All participants provided written informed consent prior to enrollment. The study protocol was registered at ClinicalTrials.gov (Identifier: NCT07268781).
2.7. Intervention
The intervention product consisted of ready‐to‐consume functional cookies formulated using Golden Rice flour and active P. crocatum extract [21]. Golden Rice flour was produced from biofortified Oryza sativa L. grains containing β‐carotene. The leaves of P. crocatum Ruiz & Pav. were used as the plant material for extract preparation. Botanical identification and authentication were conducted by a pharmacognosist from the Faculty of Pharmacy, Universitas Gadjah Mada. A voucher specimen (voucher no. PC‐UGM‐2023‐01) was deposited at the Department of Pharmaceutical Biology, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta, Indonesia. The plant material was macerated in 96% ethanol at a plant material‐to‐solvent ratio of 1:10 (w/v) for 72 h at room temperature (25°C ± 2°C), with gentle agitation and solvent replacement every 24 h. The resulting macerates were filtered, pooled, and concentrated under reduced pressure using a rotary evaporator at a temperature not exceeding 40°C. The concentrated extract was transferred into an airtight amber glass container and stored at 4°C until cookie production. The extraction yield was 12.5% (w/w), calculated as the weight of the dried extract divided by the initial weight of the dried plant material and multiplied by 100.
The resulting extract was characterized based on its total phenolic content, determined using the Folin–Ciocalteu method and expressed as gallic acid equivalents (GAE) [27]. The total phenolic content of the extract was 45 mg GAE/g extract.
Each cookie weighed approximately 20 g and provided 51 kcal. The intervention cookies contained 20% Golden Rice flour and 10% ethanol extract of P. crocatum. Therefore, each cookie contained approximately 2 g of P. crocatum extract. Based on the measured total phenolic content of 45 mg GAE/g extract, the estimated polyphenol content was 90 mg GAE per cookie, corresponding to an estimated daily intake of approximately 180 mg GAE from two cookies.
Participants in the control group received cookies with similar physical and sensory characteristics, including appearance, taste, and packaging, but without the active P. crocatum extract. Complete equivalence in the nutritional composition of the intervention and control cookies was not established by direct comparative analysis of the final products.
The cookies were manufactured by Evelyn Food Supplement, Indonesia, under standardized production procedures to ensure consistency in weight, composition, and active ingredient content across production batches. The cookies were designed as diabetes‐appropriate snack substitutes during the intervention period.
2.8. Intervention Protocol and Adherence Monitoring
The intervention period was 28 days. Participants in the intervention group were instructed to consume two cookies per day, equivalent to approximately 40 g and 102 kcal/day, with one cookie consumed in the morning and one in the evening. Participants were advised to consume the cookies as snack substitutes whenever possible rather than as additional food items. However, because the intervention was conducted in a community‐based setting, complete replacement of participants' usual snacks could not be strictly ensured. Participants in the control group followed the same consumption schedule using matched control cookies.
Participants were allowed to continue their usual medications, including oral antidiabetic and lipid‐lowering medications prescribed by their physicians throughout the study period. Adherence was monitored using daily food consumption records, weekly follow‐up visits, and verification of returned cookies. The research team regularly contacted the participants to reinforce adherence and monitor compliance.
Adverse events or discomfort related to cookie consumption were monitored at the weekly follow‐up visits throughout the intervention period.
2.9. Measurements
Lipid profile measurements were conducted at two time points: at baseline and at the end of the intervention period. Venous blood samples were collected after 8–12 h of overnight fasting to minimize the influence of recent dietary intake.
All laboratory analyses were performed at the accredited clinical laboratory of Anutapura Regional General Hospital, Palu, Central Sulawesi, Indonesia, using standardized clinical biochemistry procedures and quality control protocols.
The lipid profile parameters measured were total cholesterol, LDL‐C, HDL‐C, and triglyceride levels. Analyses were performed using an automated chemistry analyzer (Mindray BS‐240; Shenzhen Mindray Bio‐Medical Electronics Co., Ltd., China) and commercially available reagents. Total cholesterol was measured using the cholesterol oxidase–peroxidase aminoantipyrine enzymatic colorimetric method. Triglyceride levels were measured using the glycerol‐3‐phosphate oxidase–peroxidase aminoantipyrine method. LDL‐C and HDL‐C concentrations were determined using direct homogeneous enzymatic assays.
All laboratory procedures followed the standard operating procedures of the laboratory, including routine instrument calibration and internal quality control, to ensure measurement accuracy and reliability.
Body weight and height were measured at baseline using a OneMed analog mechanical weighing scale with an integrated height‐measuring rod (maximum weight capacity, 120 kg; maximum height measurement, 190 cm). Measurements were performed following standard anthropometric procedures, with participants standing upright and without footwear. Body mass index (BMI) was calculated as body weight in kilograms divided by height in meters squared (kg/m2). Baseline BMI was included as a covariate in the adjusted analysis. Body weight and BMI were not reassessed at the end of the 28‐day intervention; therefore, changes in these anthropometric measures during the intervention could not be evaluated.
2.10. Dietary Intake and Compliance Monitoring
Dietary intake was monitored using daily food diaries during the intervention period. Because dietary intake was monitored rather than experimentally standardized, variations in participants' usual dietary intake could not be completely controlled. Carbohydrate and protein intake estimates derived from the food diaries were included as covariates in the adjusted analysis because of their potential influence on lipid metabolism. Compliance with cookie consumption was assessed through daily records, weekly follow‐ups, and returned cookie counts.
2.11. Statistical Analysis
Numerical data are presented as mean ± standard deviation for normally distributed variables or as median and range for non‐normally distributed variables. Categorical data are presented as frequencies and percentages. The normality of the data distribution was assessed using the Shapiro–Wilk test.
Within‐group changes in lipid profile parameters before and after the intervention were analyzed using paired sample t‐tests for normally distributed variables or Wilcoxon signed‐rank tests for non‐normally distributed variables. Between‐group differences were analyzed using independent sample t‐tests or Mann–Whitney U‐tests, as appropriate. Categorical variables were analyzed using the chi‐square or Fisher exact tests.
Analysis of covariance (ANCOVA) was performed to evaluate adjusted between‐group differences in lipid profile outcomes after controlling for potential confounding factors. Because statin therapy is a strong pharmacological determinant of lipid profile changes, an exploratory adjusted ANCOVA was conducted among non‐statin participants to reduce confounding from lipid‐lowering therapy. The models were adjusted for the corresponding baseline lipid values, age, BMI, duration of DM, carbohydrate intake, and protein intake. Because the exclusion of statin users from the adjusted ANCOVA was not explicitly prespecified in the registered protocol or statistical analysis plan, this analysis was interpreted as exploratory and hypothesis‐generating.
All statistical analyses were performed using IBM SPSS Statistics version 26.0 (IBM Corp., Armonk, NY, USA). A two‐sided p value < 0.05 was considered statistically significant.
3. Results
3.1. Participant Characteristics and Baseline Data
A total of 102 adults with DM completed the 28‐day study, with 51 participants in the intervention group and 51 in the control group. Baseline demographic, clinical, and dietary characteristics are presented in Table 1.
Table 1.
Baseline characteristics of participants.
| Characteristics | Intervention (n = 51) | Control (n = 51) | p | SMD |
|---|---|---|---|---|
| Demographic and clinical variables | ||||
| Age (years) | 48.76 ± 7.28 | 48.94 ± 7.59 | 0.902a | −0.02 |
| Body mass index | 23.55 ± 3.25 | 25.22 ± 4.62 | 0.061d | −0.42 |
| Female, n (%) | 42 (82.4) | 39 (76.5) | 0.630b | — |
| Low education, n (%) | 42 (82.4) | 35 (68.6) | 0.107b | — |
| Employed, n (%) | 15 (29.4) | 13 (25.5) | 0.657b | — |
| Married, n (%) | 51 (100) | 48 (94.1) | 0.243c | — |
| Current smoker, n (%) | 4 (7.8) | 6 (11.8) | 0.505b | — |
| Diabetes duration (years) | 4.15 ± 3.26 | 4.37 ± 4.11 | 0.741db | −0.06 |
| Use of oral antidiabetic agents, n (%) | 38 (74.5) | 39 (76.5) | 0.818b | — |
| Statin use, n (%) | 9 (17.6) | 7 (13.7) | 0.586b | — |
| Baseline lipid profile (mg/dL) | ||||
| Total cholesterol | 191.98 ± 45.52 | 223.47 ± 46.36 | 0.001d | −0.69 |
| LDL‐C | 122.12 ± 35.59 | 140.63 ± 39.03 | 0.010d | −0.50 |
| HDL‐C | 43.19 ± 6.81 | 45.23 ± 8.32 | 0.179a | −0.27 |
| Triglycerides | 158.90 ± 88.10 | 174.14 ± 72.75 | 0.088d | −0.19 |
| Baseline dietary intake | ||||
| Carbohydrate (g/day) | 278.3 ± 78.8 | 352.6 ± 41.7 | < 0.001d | −1.17 |
| Protein (g/day) | 51.4 ± 18.1 | 59.8 ± 17.1 | 0.003d | −0.48 |
Note: Values are presented as mean ± standard deviation (SD) or n (%).
Abbreviations: HDL‐C, high‐density lipoprotein cholesterol; LDL‐C, low‐density lipoprotein cholesterol; SMD, standardized mean difference.
Independent samples t‐test.
Chi‐square test.
Fisher exact test.
Mann–Whitney U‐test.
The mean age of participants was comparable between the intervention and control groups (48.76 ± 7.28 years vs. 48.94 ± 7.59 years; p = 0.902). Baseline BMI was 23.55 ± 3.25 kg/m2 in the intervention group and 25.22 ± 4.62 kg/m2 in the control group, with no statistically significant between‐group difference (p = 0.061). Most participants were female, accounting for 82.4% of the intervention group and 76.5% of the control group. No statistically significant differences were observed between groups in demographic characteristics, duration of diabetes, smoking status, employment status, use of oral antidiabetic agents, or statin use.
Baseline imbalances were observed in lipid profiles and dietary intake. Total cholesterol was significantly lower in the intervention group than in the control group (191.98 ± 45.52 mg/dL vs. 223.47 ± 46.36 mg/dL; p = 0.001). LDL‐C was also significantly lower in the intervention group than in the control group (122.12 ± 35.59 mg/dL vs. 140.63 ± 39.03 mg/dL; p = 0.010). No significant baseline differences were observed for HDL‐C or triglycerides. Baseline carbohydrate and protein intake were significantly higher in the control group than in the intervention group (p < 0.001 and p = 0.003, respectively). These baseline differences were considered in the exploratory adjusted analysis.
3.2. Adherence and Adverse Events
Adherence to cookie consumption was generally high, as assessed through daily consumption records, weekly follow‐ups, and returned cookie counts. Four participants reported mild symptoms during the intervention period: one participant in the intervention group reported gastric discomfort, and three participants in the control group reported itching, gastric discomfort, or dizziness. All symptoms were mild and were managed through monitoring, temporary interruption of cookie consumption when needed, or adjustment of the consumption schedule. No serious adverse events attributable to cookie consumption were reported.
3.3. Unadjusted Changes in Lipid Profile During the Intervention
Unadjusted changes in lipid profile parameters before and after the 28‐day intervention are presented in Table 2.
Table 2.
Unadjusted changes in lipid profile within and between groups.
| Outcome (mg/dL) | Group | Baseline mean ± SD | Post‐intervention mean ± SD | Mean change (Δ) | Within‐group p | Between‐group p |
|---|---|---|---|---|---|---|
| Total cholesterol | Control | 223.47 ± 46.36 | 217.00 ± 41.89 | −6.47 | 0.029a | |
| Intervention | 191.98 ± 45.52 | 200.27 ± 37.95 | +8.29 | 0.024a | ||
| Δ Difference (Control − Intervention) | −14.76 | 0.003b | ||||
| LDL‐C | Control | 140.63 ± 39.03 | 139.92 ± 30.49 | −0.71 | 0.870a | |
| Intervention | 122.12 ± 35.59 | 128.86 ± 28.78 | +6.75 | 0.007a | ||
| Δ Difference (Control − Intervention) | −7.45 | 0.086b | ||||
| HDL‐C | Control | 45.23 ± 8.32 | 43.60 ± 8.33 | −1.63 | 0.092c | |
| Intervention | 43.19 ± 6.81 | 42.60 ± 6.17 | −0.59 | 0.597c | ||
| Δ Difference (Control − Intervention) | −1.04 | 0.517b | ||||
| Triglycerides | Control | 174.14 ± 72.75 | 177.92 ± 78.25 | +3.78 | 0.969a | |
| Intervention | 158.90 ± 88.10 | 163.84 ± 91.46 | +4.94 | 0.992a | ||
| Δ Difference (Control − Intervention) | −1.16 | 0.926b |
Note: Mean change was calculated as post‐intervention value minus baseline value. Δ Difference was calculated as mean change in the control group minus the mean change in the intervention group.
Abbreviations: HDL‐C, high‐density lipoprotein cholesterol; LDL‐C, low‐density lipoprotein cholesterol; SD, standard deviation.
aWilcoxon signed‐rank test. bMann–Whitney U‐test. cPaired t‐test.
In the intervention group, total cholesterol increased significantly after the intervention, with a mean change of +8.29 mg/dL (p = 0.024). LDL‐C also increased significantly, with a mean change of +6.75 mg/dL (p = 0.007). No significant within‐group changes were observed in HDL‐C or triglycerides.
In the control group, total cholesterol decreased significantly after the intervention, with a mean change of −6.47 mg/dL (p = 0.029). No significant within‐group changes were observed in LDL‐C, HDL‐C, or triglycerides.
The between‐group comparison of change scores showed a significant difference only for total cholesterol (control minus intervention: Δ Difference, −14.76 mg/dL; 95% confidence interval [CI] = −24.22 to −5.31; p = 0.003), reflecting a greater increase in total cholesterol in the intervention group relative to the control group over the 28‐day period. No significant between‐group differences in change scores were observed for LDL‐C (p = 0.086), HDL‐C (p = 0.517), or triglycerides (p = 0.926).
3.4. Exploratory Adjusted Between‐Group Analysis
To account for baseline differences and potential confounding factors, an exploratory ANCOVA was conducted among participants who were not using statins. A total of 86 non‐statin participants were included in the adjusted analysis. The models were adjusted for the corresponding baseline lipid value, age, BMI, duration of diabetes, carbohydrate intake, and protein intake. As the exclusion of statin users from the adjusted analysis was not explicitly prespecified in the registered protocol or statistical analysis plan, the ANCOVA findings were considered exploratory and hypothesis‐generating. The adjusted results are presented in Table 3.
Table 3.
Exploratory adjusted between‐group differences in lipid profile among non‐statin participants (ANCOVA).
| Outcome (mg/dL) | F | p | Partial η 2 | Adjusted mean difference (95% CI) |
|---|---|---|---|---|
| Total cholesterol | 6.013 | 0.016 | 0.072 | −12.55 (−22.74 to −2.36) |
| LDL‐C | 0.040 | 0.843 | 0.001 | −0.77 (−8.53 to 6.98) |
| HDL‐C | 0.466 | 0.497 | 0.006 | 1.12 (−2.15 to 4.40) |
| Triglycerides | 0.044 | 0.834 | 0.001 | −3.12 (−32.57 to 26.33) |
Note: ANCOVA was performed among non‐statin participants (n = 86). Models were adjusted for baseline lipid values, age, BMI, diabetes duration, and dietary intake (carbohydrate and protein). Adjusted mean difference was calculated as intervention–control. Because exclusion of statin users was not explicitly prespecified, this analysis was considered exploratory.
Abbreviations: ANCOVA, analysis of covariance; BMI, body mass index; CI, confidence interval; HDL‐C, high‐density lipoprotein cholesterol; LDL‐C, low‐density lipoprotein cholesterol.
In this exploratory analysis, a significant adjusted between‐group difference was observed for total cholesterol (F = 6.013; p = 0.016; partial η 2 = 0.072). The adjusted mean difference was −12.55 mg/dL (95% CI = −22.74 to −2.36), corresponding to a lower adjusted mean total cholesterol in the intervention group than in the control group.
No statistically significant adjusted between‐group differences were observed for LDL‐C (adjusted mean difference = −0.77 mg/dL; 95% CI = −8.53 to 6.98; p = 0.843), HDL‐C (adjusted mean difference = 1.12 mg/dL; 95% CI = −2.15 to 4.40; p = 0.497), or triglycerides (adjusted mean difference = −3.12 mg/dL; 95% CI = −32.57 to 26.33; p = 0.834). The corresponding partial η 2 values were 0.001 for LDL‐C, 0.006 for HDL‐C, and 0.001 for triglycerides. Overall, the exploratory adjusted analysis identified a significant between‐group difference only for total cholesterol.
4. Discussion
This study evaluated the short‐term effects of Golden Rice cookies enriched with active P. crocatum extract on lipid profile parameters in adults with DM. The principal finding was a significant exploratory adjusted between‐group difference in total cholesterol among non‐statin participants. No significant adjusted between‐group differences were observed for LDL‐C, HDL‐C, or triglycerides. Importantly, the unadjusted findings were not consistently favorable: total cholesterol and LDL‐C increased significantly in the intervention group, whereas total cholesterol decreased significantly in the control group. Therefore, the findings do not demonstrate a consistent lipid‐modifying benefit and should be interpreted as preliminary and hypothesis‐generating.
The discrepancy between the unadjusted and adjusted findings requires careful interpretation. Baseline total cholesterol and LDL‐C levels were significantly lower in the intervention group than in the control group, and carbohydrate and protein intakes also differed between groups. These baseline imbalances may have influenced the magnitude and direction of the observed unadjusted changes. The exploratory ANCOVA statistically adjusted for baseline lipid values and selected covariates and was restricted to non‐statin participants; consequently, the adjusted estimates differed from the unadjusted change‐score comparisons. However, statistical adjustment cannot eliminate residual or unmeasured confounding, particularly in a quasi‐experimental study. Moreover, because exclusion of statin users was not explicitly prespecified, the adjusted analysis should not be regarded as confirmatory or as providing evidence of a causal intervention effect.
The present findings should also be considered in the context of existing human evidence. A meta‐analysis of randomized controlled trials of dietary polyphenols reported significant pooled reductions in total cholesterol and triglycerides, whereas no significant effects were observed for LDL‐C or HDL‐C; however, substantial heterogeneity and risk of bias were noted across trials [28]. Thus, the heterogeneous lipid responses observed in the present study are not unexpected and indicate that cardiometabolic responses to polyphenol‐containing interventions may vary according to the food matrix, polyphenol source, dose, intervention duration, and participant characteristics. Human evidence specifically involving P. crocatum remains limited. A recent 12‐week randomized controlled trial of P.crocatum‐enriched functional foods in adults with diabetes and early renal dysfunction reported favorable changes in MMP‐9 and NGAL‐related biomarkers, supporting potential biological activity but not establishing a lipid‐lowering effect [22]. Accordingly, the present lipid findings should be regarded as complementary preliminary evidence rather than confirmation of clinical efficacy.
The exploratory adjusted between‐group difference in total cholesterol may have biological plausibility because Golden Rice and P. crocatum contain bioactive compounds with potential antioxidant and metabolic activities [8, 9, 10]. Golden Rice contains β‐carotene, a provitamin A carotenoid with antioxidant properties, whereas P. crocatum contains polyphenols and flavonoids that may influence oxidative stress, inflammation, and lipid metabolism. In theory, these compounds may help reduce oxidative stress, inhibit LDL oxidation, and modulate pathways involved in lipid handling [11, 15, 17, 21, 22, 28, 29, 30, 31, 32]. Nevertheless, biological plausibility should not be interpreted as evidence that these mechanisms explain the present findings. This study did not measure oxidative stress biomarkers, inflammatory markers, β‐carotene status, or circulating polyphenol metabolites; therefore, the proposed mechanisms remain hypothetical.
The absence of significant adjusted between‐group differences in LDL‐C, HDL‐C, and triglycerides may represent a true absence of a short‐term effect or may reflect limitations of the 28‐day intervention period and the multiple determinants of lipid metabolism in adults with diabetes. Lipid levels are influenced by insulin resistance, hepatic lipid production, adipose tissue lipolysis, dietary intake, medication use, and physical activity [1, 2, 3]. Although dietary intake was monitored and carbohydrate and protein intake were incorporated into the adjusted models, diet was not experimentally standardized, and day‐to‐day dietary variation remained possible. Physical activity was not systematically assessed, and medication‐related confounding could not be completely eliminated.
The exploratory restriction of the adjusted analysis to 86 non‐statin participants was intended to reduce the influence of statins, which are strong pharmacological modifiers of total cholesterol and LDL‐C [1, 2, 33, 34]. However, this analytic decision was not explicitly prespecified in the registered protocol or statistical analysis plan. The resulting estimates should therefore be considered exploratory and hypothesis‐generating. The smaller analytic sample may also have reduced precision, particularly for outcomes with very small partial η 2 values.
From a practical perspective, the intervention was feasible and generally well tolerated. Adherence to cookie consumption was high, and only mild symptoms were reported during the intervention period, with no serious adverse events attributable to cookie consumption. These observations support the feasibility of delivering a standardized cookie‐based intervention in a community setting but should not be interpreted as evidence of lipid‐lowering efficacy. From a nursing perspective, such food‐based approaches may provide a practical platform for dietary education, adherence support, and lifestyle counseling [23, 24, 25, 26]. Their incorporation into diabetes care, however, requires stronger evidence of clinical effectiveness before specific therapeutic recommendations can be made.
Despite these strengths, this study has several limitations. First, the quasi‐experimental design and the use of lottery‐based participant ordering followed by alternating group assignment, without formal random sequence generation or allocation concealment, may have introduced selection bias because group assignment became predictable after the initial allocation. In addition, baseline differences in total cholesterol and LDL‐C limit causal inference. Second, the adjusted analysis among non‐statin participants was exploratory and not explicitly prespecified, and residual confounding cannot be excluded. Third, the 28‐day intervention period may have been insufficient to evaluate sustained lipid responses. Fourth, dietary intake was monitored but not experimentally standardized; physical activity was not systematically assessed; and medication adherence was not independently verified. Fifth, although participants were advised to consume the cookies as snack substitutes whenever possible, complete replacement of their usual snacks could not be verified, and body weight and BMI were not reassessed after the intervention. Sixth, the final baked cookies were not directly analyzed for total phenolic content, and complete nutritional equivalence between the intervention and control cookies was not established by direct comparative analysis. Seventh, this study did not measure mechanistic biomarkers such as oxidative stress markers, inflammatory markers, apolipoproteins, β‐carotene status, or circulating polyphenol metabolites. Finally, the study was conducted in a single community setting, which may limit the generalizability.
Future studies should use longer, adequately powered, fully randomized, double‐blind controlled trials, with crossover designs considered where feasible to reduce interindividual variability and baseline imbalance. Statin use and other lipid‐lowering therapies should be addressed through prespecified stratification or analytic strategies, accompanied by more rigorous assessment of dietary intake, medication adherence, physical activity, and changes in body weight. Additional biomarker assessments, including oxidative stress, inflammation, apolipoproteins, carotenoid status, and polyphenol metabolites, are needed to investigate biological mechanisms. Direct compositional analysis of the final baked intervention and control products should also be performed to quantify retained bioactive compounds and establish nutritional comparability after processing.
5. Conclusion
Golden Rice cookies enriched with active P. crocatum extract were associated with a significant exploratory adjusted between‐group difference in total cholesterol among non‐statin participants after 28 days of intervention. However, no significant adjusted between‐group differences were observed for LDL‐C, HDL‐C, or triglycerides. Given the unfavorable unadjusted changes in total cholesterol and LDL‐C in the intervention group, the baseline imbalances between groups, and the exploratory nature of the adjusted analysis, these findings should be considered preliminary and hypothesis‐generating rather than evidence of a clinically established lipid‐lowering effect. Longer, adequately powered randomized controlled trials with stronger control of potential confounders and mechanistic biomarker assessments are needed before clinical recommendations can be made.
Author Contributions
A.S.A., A.S., and A.M.I. designed the research. A.S.A. conducted the research, collected the data, analyzed the data, performed the statistical analysis, and drafted the manuscript. A.S. supervised the study, served as the corresponding author, critically revised the manuscript, and had primary responsibility for the final content. A.M.I. supervised the study and critically revised the manuscript. All authors read and approved the final manuscript.
Funding
The authors have nothing to report.
Ethics Statement
This study was conducted in accordance with the ethical principles of the Declaration of Helsinki. Ethical approval was obtained from the Health Research Ethics Committee of Hasanuddin University, Indonesia (approval no. 587/UN4.I8.3/TP.01.02/2025). The study protocol was registered at ClinicalTrials.gov (Identifier: NCT07268781).
Consent
All participants received detailed information about the study procedures and provided written informed consent before enrollment.
Conflicts of Interest
The authors declare no conflicts of interest.
Use of Large Language Models, AI and Machine Learning Tools
During the preparation of this manuscript, the authors used OpenAI ChatGPT to assist with English‐language editing, improve clarity and academic expression, and refine the organization and presentation of selected sections of the manuscript. The tool was not used to generate research data, perform statistical analysis, or make research or clinical decisions. All AI‐assisted text was critically reviewed and revised by the authors, who take full responsibility for the accuracy and integrity of the final manuscript.
Acknowledgments
The authors thank the participants who took part in this study. The authors also thank the staff of Lompeta Singgani Tambu Community Health Center, Donggala Regency, and the clinical laboratory staff of Anutapura Regional General Hospital, Palu, for their support during data collection and laboratory analysis.
Data Availability Statement
The data supporting the findings of this study are available from the corresponding author upon reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data supporting the findings of this study are available from the corresponding author upon reasonable request.