Supplementation of chickpea flour and spinach leaves powder in Nutri bars to overcome iron deficiency in young females

ABSTRACT

This study evaluated the iron-rich Nutri bar’s effect on iron-deficient females. Iron-rich Nutri-bars made with spinach powder and chickpea flour. The physicochemical profile of the bars was measured. Socioeconomic status and anthropometric data were taken for the effectiveness of the research. This effectiveness trial included 20 girls ages 20 to 25. After that, biochemical tests, including hemoglobin, ferritin, and total iron-binding capacity (TIBC) were conducted. Results showed that the iron-rich Nutri-bars (T3, 6.60) had more moisture than other treatments. T3 protein and fiber composition was 16.90% and 4.30%. In T3, crude fat and ash content were the lowest. All the proximate analyses of incorporated spinach powder and chickpea flour indicated a significant correlation (P > .005). A jury gave treatment T3 the highest score in overall acceptability. Iron and zinc concentrations were 13.2 and 5.9 mg/100 g in T3. Post-assessment height, weight, and body mass index (BMI) indicated a very significant (P > .005) connection compared to pre-assessment (P > .005). Selected young females' hemoglobin, serum ferritin, and total iron-binding capacity were tested biochemically. After the intervention, the experimental group’s mean hemoglobin (HB) was 12.21 ± 1.14 g/dl (P > .005). Increasing patterns support the current study’s iron improvement. Serum ferritin exhibited similarly substantial outcomes. TIBC dropped when iron status increased. Conclusively, iron-rich nutri-bars supplemented with spinach leaf powder and chickpea flour increased iron status in young females.

KEYWORDS:

• Nutri bar
• chickpea flour
• spinach leaves
• iron deficiency

Introduction

In developing countries, micronutrient deficiencies are more predictable than a specific nutrient deficiency due to inadequate intake and the scarce availability of micronutrients obtained from vegetarian food.^[1,2] Among the micronutrient deficiencies, iron deficiency anemia is a major nutritional problem worldwide that causes various serious health issues in women like maternal death during pregnancy and parturition. Iron deficiency anemia is a medical condition in which the red blood cells cannot carry enough oxygen because there are too many or too few of them. Anemia is the most common cause of iron deficiency. Iron is an important part of hemoglobin, blood, and protein. Anemia affects about 24.8% of the world’s population or 1.62 billion people. Children with iron deficiency anemia can get infections in their intestines, lose weight, and get respiratory infections repeatedly.^[3]

The most common way to lower the iron deficiency rate in a large population is to add iron supplements to the diet. Iron supplements like iron chloride, ferrous sulfate, and ferric citrate have been shown to help with iron deficiency anemia. Ferrous sulfate is a common iron supplement that is added to gold. Ferrous sulfate may easily cause side effects in people with sensitive guts and oxidases. Due to its toxicity, ferrous sulfate is an important iron supplement in the digestive system.^[4] For quail, iron supplements like ferrous sulfate and Fe₃O+ nanoparticles coated with cysteine are used.^[5] Iron deficiency anemia is usually caused by chronic blood loss, not getting enough iron or a combination of the two. Food fortification has been thought to be the best and safest way to add iron to diets that do not have enough of it. To prevent anemia in developing countries, it must be clear to the public that fortified food must use legal and available carriers in the area.^[6]

The most liable strategy is used to minimize the gaps in micronutrient deficiencies by adding different nutrients such as iron, protein, and micronutrient-rich foods to the diet. Value-added products are becoming more acceptable in the community, such as green leafy vegetables and chickpea flour combined with wheat flour to enhance the nutrient efficiency of traditional wheat flour recipes.^[7] Chickpea, commonly known as kabuli grams, is a highly cultivated crop worldwide due to its countless nutritional values. Chickpea flour is a rich source of nutrients, including protein, simple and complex carbohydrates, minerals, dietary fibers, and vitamins.^[8] Chickpea flour has many health benefits, preventing diabetes, lowering the risk of cancer, increasing satiation, and minimizing the cardio vascular disease (CVD) risk.^[9,10] Green leafy vegetables, mainly spinach, are the main source of micronutrients like vitamin A and other water-soluble vitamins, phosphorus, calcium, iron, and enough amount of β-carotene. Green leafy vegetables have a wide variety of bioactive components and many other non-nutritive factors such as phytochemicals, antioxidants, dietary fibers, and essential fatty acids. They have the most effective naturally occurring antioxidants like β-carotene and vitamin C, while phenolic agents are one of the main antioxidants mainly present in plant-based foods.^[10,11] Spinach contains various antioxidants that are functional to minimize the availability of free radicals in the body and impart various health benefits like reducing the risk of cardiovascular disease, atherogenic processes, and age-related eye problems.^[12]

Spinach leaves are very beneficial to human health. Vitamin C and phenol are used as anticancer agents. Dietary fibers are useful for lowering blood cholesterol and triglyceride levels and enhancing High-density lipoprotein (HDL).^[13,14] In recent years, to ensure the demand and interest of consumers with the growing population and behavioral changes have increased the availability of traditional and baked products. Thus, spinach and chickpea flour are easily accessible, nutritionally rich ingredients that could be incorporated into baked and traditional products to improve micronutrient deficiencies.^[15] The present study ensures the iron-rich value-added product (bar) by incorporating chickpea flour and spinach leaves flour. The purpose of this study is to investigate the effectiveness of iron-rich Nutri bars produced with spinach powder and chickpea flour in improving iron status in young girls. This paper investigates the bars’ nutritional qualities, overall acceptability, and biochemical effects on hemoglobin, serum ferritin, and total iron-binding capacity, with the goal of gaining insight into their potential as an iron-deficiency dietary intervention.

Materials and Methods

Procurement of raw materials

The current research work was performed at the Department of Nutritional Sciences, Government College University Faisalabad, Pakistan. Chickpea flour, spinach leaves, hydrogenated fat, rolled oats, and jaggery were procured from a local market in Faisalabad.

Preparations of iron-rich nutri-bar

The ingredients, such as spinach leaves powder and chickpeas, which were chosen for their high iron content and nutritious value, were processed into jaggery. On the other hand, the rolled oat was roasted to enhance its aroma character. After further preparation, the jaggery was converted into thick syrup by heating and adding hydrogenated fat. This syrup combination was heated so the previously added components would dissolve and blend. GMS (Glycerol Monostearate) paste and CMC (Carboxymethyl Cellulose) were added to the already-made syrup to act as stabilizers and thickeners. The components, including rolled oats, spinach powder, chickpea flour, and nuts in small bits, were poured into the hot syrup that had been made, and the mixture was mixed continually to get a uniform consistency. The hot liquid was put onto the molder tray almost immediately and then pressed to make a uniform shape. After 15–20 min in the baking oven at 160–170 degrees Celsius, the molder tray was put in. The iron-rich Nutri-bars were allowed to cool before being placed in a plastic bag and then kept at room temperature.

Formulation of nutritional bars

Spinach leaf powder and chickpea flour were added to nutri bars at 5%, 10%, and 15% of spinach and 45%, 40%, and 35% of chickpea flour in the replacement of the control bar, as mentioned in Table 1. Iron-rich nutri-bars have the same amount of other required ingredients. Different iron-rich Nutri-bars and a control sample were evaluated for their sensory evaluation.

Table 1. Treatment plan for iron-rich nutri-bars.

Bar	Spinach leaves powder %	Chickpea flour %	Jaggery %
TC	0%	50%	50%
T1	5%	45%	50%
T2	10%	40%%	50%
T3	15%	35%	50%

Compositional analyses of bars

A moisture analyzer (Drying oven 202-0A) was used to measure the moisture content in a sample mentioned in AOAC^[16] Protein was determined by applying the methods stated in AOAC^[16] Kjeldahl method was used to measure the total protein content in the bar. The crude fat was determined using the Soxhlet apparatus according to the methods described in AOAC.^[17] Hussain et al.’s^[18] method was used to determine the ash content in the bar in the muffle furnace at 550°C for 6 h. Crude fiber was determined using the methods stated in AOAC^[16]

Sensory evaluation

Evaluation of sensory characteristics (taste, color, odor, texture, and acceptability) was executed, ensuring the procedure of Sun et al.^[19] A panel of 10 evaluators aged 24 to 45 years (four males and six females) was instructed in the detailed evaluation of bars.

Minerals

Ash: A small amount (0.5–1.0 ml) of distilled water in a glass was mixed with 5 ml of distilled hydrochloric acid. This was used to moisten the ash. The mixture was heated in a boiling water bath (Memmert) until it evaporated completely. In the same manner as previously, another 5 ml of hydrochloric acid was added, and then the solution evaporated until it was dry. After adding 4 ml of hydrochloric acid and a few milliliters of water to this solution, it was heated in a boiling water bath (Memmert) and filtered into a volumetric flask of 100 ml of water with Whatman No. 40 filter paper. After the sample had cooled, the volume was brought up to 100 ml, and appropriate aliquots were employed to determine the amounts of the various minerals.

Iron: As reported in AOAC^[20] 10 ml of the wet digested sample solution was pipetted into a volumetric flask with a capacity of 25 ml triplicate to evaluate the iron concentration. In each volumetric flask, 1 ml of hydroxylamine hydrochloride solution, 5 ml of acetate buffer solution, and 2 ml of a-a, dipyridyl solution were added. The volume was raised to 25 ml with a glass of distilled water, and the contents were mixed well. Supertonic 20 was used to measure the color’s intensity at 510 nm. The standard curve of known iron concentrations was used to determine how much iron was in the digested sample solution.

Zinc: Hernandez et al.,^[21] method was used for the determination of zinc in bars using an atomic absorption spectrophotometer (DU-8800D). A 5 g sample was cooked in a porcelain crucible after being weighed. The resultant white ash was measured out, then dissolved in 3 ml of strong nitric acid and diluted with water in a 25 ml calibrated flask. Zinc was extracted from the solution and measured. A stock solution of zinc was created by diluting AAS-grade chemicals to standard concentrations.

Selection of subjects

For the research, 100 young women between the ages of 20 and 25 who were residents of several girl’s hostels in the city of Faisalabad in the province of Punjab in Pakistan were chosen at random. Forty young women with anemia were chosen for the study after having their blood hemoglobin, total iron-binding capacity, and ferritin levels assessed. Two groups were formed comprising 20 girls each, the experimental group and the control group.

Experimental technique

During the trial, a chosen group of young women were provided with two iron-rich Nutri bars that also contained spinach and chickpea flour. This treatment lasted for 4 weeks. They were instructed to consume one of these bars at each meal of the day, which included breakfast, lunch, and snacks.

Collection of data

To collect information on socioeconomic background, education, parents’ occupation and family size, awareness regarding anemia, rich sources of nutrients, dietary patterns, food habits, and so on. Personal interviews were conducted with each of the young women who had been selected and used a pretested questionnaire. The food intake of the selected subjects was evaluated using a method known as the 24-h recall. Other parameters that were investigated included anthropometric measurements such as weight, height, body mass index, hemoglobin content, total iron-binding capacity, and ferritin level in the blood.

Assessment of anthropometric measurement for nutritional status of subjects

The nutritional status of all the chosen young women was evaluated by identifying their body weight in kilograms and their height in centimeters, and then computing their body mass index values, following the procedures outlined by Jelliffe,^[22] that assessed each respondent’s height and weight by measuring their bodies according to the standard protocols. Body weight was done with a portable weighing balance with a one hundred kg capacity. The participant was standing straight on the scale with few clothes and bare feet. Their body weight was measured to the closest 0.1 kg. A non-stretchable measuring tape was used to measure the height of the selected younger girls to the closest 0.1 cm in the standing posture. The respondents’ actual height was determined to be within 0.1 cm using a measuring tape and the distance between the mark on the tape and the floor. The selected young girls’ body mass index (BMI) was determined by taking their body weight in kilograms and their height in meters, and then using the formula.

$BMI=\frac{Weightinkg}{Heightinmeter}$

Determination of different food intake status

The 24-h recall approach was used to obtain data on the amount of food consumed daily by the selected young girls.

Biochemical analysis

Hemoglobin: To determine the calorimetric value of the hemoglobin concentration in females, the cyanmethemoglobin approach was applied. This approach is based on the idea that, when measured against a standard solution, the addition of ferricyanide and potassium nitrate to a photoelectric calorimeter results in the transformation of mercury to cyanmethemoglobin, the absorbance of which is amplified at 540 nanometers. In this approach, the color is measured in a photoelectric calorimeter at 540 nm, and then 20 g/l of blood is transferred to Drabkin’s solution of 5000 ul in a test tube, where it is completely mixed (in 1 l of purified water, 1 g Na COs, 0.05 g KCN, and 0.20 g CoNFeK3). Standard curves are generated in various solutions using cyanmethemoglobin standard solutions.^[23]

Total iron-binding capacity (TIBC): To determine total iron-binding capacity (TIBC) and ferrozine in female participants, the technique developed by da Silva et al.^[24] was applied. A combination of 1 ml of the sample was analyzed in 3 ml of purified water. The compound was treated at room temperature for 20 min with 0.2 ml of 5 ml FFs of ferrozine and 0.1 ml of 1 mm of iron chloride. The absorbance was measured at 562 nanometers. Despite the sample, all of the refined water was utilized, except for the control, which was created in the same way. EDTA was employed as a positive control for the experiment. EDTA equivalent was proven to have been loaned by the (TIBC) concerning grams of protein. TIBC was determined by using the following equation, which is as follows:

$\mathrm{T}\mathrm{I}\mathrm{B}\mathrm{C}\left(\frac{\mathrm{u}\mathrm{m}\mathrm{o}\mathrm{l}}{1}\right)=\hspace{0.17em}25.1\mathrm{x}\mathrm{t}\mathrm{r}\mathrm{a}\mathrm{n}\mathrm{s}\mathrm{f}\mathrm{e}\mathrm{r}\mathrm{r}\mathrm{i}\mathrm{n}\left(\frac{\mathrm{g}}{1}\right)$

At a wavelength of 570 nanometers, ferrozine interacts with iron to produce a complex pink hue by absorbing light. As iron oxidizes, the intensity of the fluorescence decreases. The absorbance was measured at 570 nm in the spectrophotometer, and 100 mg of total serum protein was amalgamated with water-dissolved 3 mM ferrozine after various time intervals. For ferrous iron auto-oxidation control, the absorbance data of the background reference solution were precisely measured.

Serum Ferritin

Elzamzamy and Mostafa^[25] approach was used to determine serum ferritin levels in female patients. Ferritin and antibodies against anti-ferritin that are present in the sample have been adsorbed to the polystyrene surface of the microtiter wells. When the unbound protein is removed and horseradish peroxidase is introduced, anti-ferritin antibodies can bind together more effectively. A complex is formed between the bound ferritin and the enzyme antibodies that have been tagged. After one more phase of washing, the quantity of bound enzyme complex was measured with the aid of 3.31, 5.5°- tetramethylbenzidine (TMB), a medium that produces a colored reaction. The concentration of ferritin in the tested sample varies inversely proportionally with the amount of enzyme that was bound. The concentration of ferritin in the tested sample was measured at an absorbance of 450 nm. The amount of ferritin in the sample can be adjusted and put into the standard curve for sample dilution that was constructed using the standard found in the analyzed sample.

Statistical analysis

Questionnaires are coded on a four-level categorical variable scale. The data were recorded in Excel, and a program was used for statistical analysis. Statistical program SPSS version 2022 was used to analyze the entire measures of the present study. One-way ANOVA has been implied to contrast and calculate the applied intervention’s significance. The mean and percentages for the responses collected were calculated. The data were displayed as bar graphs for visual representation and understanding.^[26]

Results and discussion

Proximate analysis of bars

The proximate content of iron-rich Nutri-bars is presented in Table 2. The results were presented as T_c (3.90 ± 0.02), T₁ (5.3 ± 0.19), T_2, (5.0 ± 0.14), and T₃ (6.60 ± 0.08). The maximum value of moisture content was observed in T₃ (6.60 ± 0.08), while the minimum value of moisture in iron-rich nutri-bars was denoted by T_c (3.90 ± 0.02). It was concluded that a significant variation in the moisture content of iron-rich nutri-bars was seen from treatment Tc to treatment T₃. Researchers tried to develop energy and caloric-dense bars with the most phytochemicals from various protein-rich ingredients. According to the results of Verma et al.,^[27] the moisture content was higher in fruit-based functional snack bars, which was between 5.6% and 11.7%. Also, their availability can rise among adolescents.

Table 2. Impact of different treatments on mean of proximate analysis (%) of the iron-rich nutri-bar.

	TC	T1	T2	T3
Moisture (%)	3.90 ± 0.02	5.3 ± 0.19	5.0 ± 0.14	6.60 ± 0.08
Crude Fat (%)	9.98 ± 0.31	5.42 ± 0.25	5.67 ± 0.28	4.12 ± 0.12
Protein (%)	6.20 ± 0.01	14.38 ± 1.01	15.07 ± 0.98	16.90 ± 1.02
Fiber (%)	2.30 ± 0.00	4.12 ± 0.01	4.22 ± 0.02	4.30 ± 0.04
Ash (%)	1.32 ± 0.22	2.12 ± 0.01	2.03 ± 0.02	1.81 ± 0.01

T_c = Control bar.

T₁ = 50% jaggery, 45% chickpea, and 5% spinach leaves powder iron rich nutri-bar.

T₂ = 50% jaggery, 40% chickpea, and 10% spinach leaves powder iron rich nutri-bar.

T₃ = 50% jaggery, 35% chickpea, and 15% spinach leaves powder iron rich nutri-bar.

The mean value protein content of different treatments of iron-rich nutri-bars were presented as T_c (6.20 ± 0.01), T₁ (14.38 ± 1.01), T_2, (15.07 ± 0.98), and T₃ (16.90 ± 1.02). These results showed that the maximum mean value was in T₃ (16.90 ± 1.02). At the same time, the minimum mean value of protein content was examined in T_c (6.20 ± 0.01). Finally, it was noted that protein content increased from T_c to T_3. The results showed a significant association. The findings of Sutwal et al.^[28] were in line with this investigation. According to previous research, snack energy bars include a better crude protein percentage (6.36%) than fruit bars made from date and fruit paste. Regarding body growth and immunological development, a high protein intake appears to be beneficial.^[29]

The mean value of ash content was computed as T_c (1.32 ± 0.22), T₁ (2.12 ± 0.01), T_2, (2.03 ± 0.02), and T₃ (1.81 ± 0.01). The minimum mean value of ash was denoted as T_c (1.32 ± 0.22). In comparison, the maximum mean value of ash was noted in T₁ (2.12 ± 0.01). Thus, the variation in the mean value of ash was observed from T_c to T₃ randomly. These results also show a significant association. According to Ho et al., (2016), traditional nutri-bars contain 360 kcal, 11.9% crude fat, 49.5% total carbs, and less than 1% crude fiber. When hemp powder was mixed with rice extruded, the mixture’s moisture decreased, but the amount of ash, fat, and protein increased.^[30] There is a lot of ash, which is a great source of minerals for the growth and development of the body.^[29] Awolu et al.^[31] described similar results that showed the ash content (1.38 ± 0.01) continuously decreased as the concentration changed for all treatments.

The mean value of crude fat was noted as T_c (9.98 ± 0.31), T₁ (5.42 ± 0.25), T_2, (5.67 ± 0.28), and T₃ (4.12 ± 0.12). These results showed that the maximum mean value was in T_c (9.98 ± 0.31), whereas the minimum mean value of fat content was examined in T₃(4.12 ± 0.12). Finally, it was noted that fat content decreased from T_c to T_3. The results showed a significant association. The results of the present study were almost parallel as reported in Ho et al.^[32] When powdered hemp was combined with rice extrudate, the final product’s moisture content was lower, but the amounts of ash, fat, and protein were higher.^[30]

The mean value of fiber was presented as T_c (2.30 ± 0.00), T₁ (4.12 ± 0.01), T_2, (4.22 ± 0.02), and T₃ (4.30 ± 0.04). The maximum mean value of fiber was denoted by T₃ (4.30 ± 0.04). In comparison, the minimum mean value was noted in T_c (2.30 ± 0.00). Thus, the results indicated that crude fiber increased from T_c to T₁. These results also had a significant association. Snack bars containing inulin were made with apple extract of polyphenol and with apple extract of polyphenol containing dietary fiber bar of apple in these, the ash value was reported to be comparable. Powdered hemp reduced the moisture content of rice extruded while increasing the ash, lipid, and protein content.^[30]

Sensory analysis

The results of sensory analysis evaluated based on nine hedonic-scale methods are inserted in Figure 1. The color findings were presented as T_c (7.90 ± 0.25), T₁ (8.00 ± 0.2), T₂ (7.9 ± 0.2), and T₃ (7.7 ± 0.1). Statistical study analysis indicated that the color of energy-rich bars was dramatically affected in T_c to T₃ treatments. Moreover, these statistical results showed a significant color change when different concentrations of chickpea and spinach leaf powder were added to the product. A unique change in color of nutri-bar was observed in T₃ treatment, and the maximum score was noted in T_c and T₂. The minimum score was accessed in T₁ treatment in contrast to other treatments. T₁ contains 40% chickpea flour, 5% spinach leaf powder, and 55% jaggery. The value-added product’s attributes of color were similar to those studied by Naknaen and Itthisoponkul.^[33] It was also observed that the variation in hue with the passage of time is caused by enzymatic activity.^[34] The results of the present study were interlinked with the food items developed by Aksay et al.^[35] Anuar and Salleh^[36] investigations indicated that the color of spinach-rich energy bars had similar characteristics to oat-based energy bars.

Figure 1. Mean value of sensory analysis of nutri-bars.

The flavor results were presented as T_c (7.70 ± 0.2), T₁ (6.80 ± 0.2), T₂ (7.40 ± 0.1), and T₃ (7.50 ± 0.1). These results showed that the minimum score was observed in treatment T₁ (6.80) and the maximum score was in T₃ (7.50). Thus, the jury appreciated the flavor of T3 (7.50) treatment. Statistical data analysis indicated that iron-rich nutri-bars had a significant flavor attribute with different treatments of spinach leaves powder and chickpea. The current study results are more likely similar to the findings of Naknaen and Itthisoponkul.^[33] According to this study, the aromatic compounds found in food decomposed and showed flavor loss and sharp flavor production. Gonzalez-Cuello et al.^[37] demonstrated that aromatic compounds improve the flavor of food and enhance carbohydrate firmness in the final product. Aksay et al.^[35] studied bars’ physicochemical properties, and the results are more likely to the present study product analysis. A spinach-enriched bar has a similar perspective of taste to an oat-based bar as described by Anuar and Salleh^[36]

These taste results were presented as T_c (7.2 ± 0.1), T₁ (7.2 ± 0.2), T₂ (7.5 ± 0.25), and T₃ (7.9 ± 0.1). Thus, it was concluded that the taste of T₁ (7.20 ± 0.25) gained a minimum score and T₃ (7.90 ± 0.1) showed the maximum score. Table T₃ (7.90 ± 0.1) is appreciated by the panel of the jury as well as selected for the efficacy of the current study. Based on a statistical analysis of taste, there was no statistically significant difference between the taste of iron-rich Nutri bars. A spinach-enriched bar has a similar perspective of taste to an oat-based bar as described by Anuar and Salleh.^[36] Aksay et al.^[35] studied the physicochemical properties of bars and the results are more likely for the present study product analysis. The current study results are more likely similar to the Naknaen and Itthisoponkul^[33] study’s findings.

These texture results were presented as T_c (7.2 ± 0.1), T₁ (7.1 ± 0.1), T₂ (7.3 ± 0.2), and T₃ (7.5 ± 0.1). It has resulted that the texture of T₃ (7.5 ± 0.1) showed a maximum score, and T₁ (7.1 ± 0.1) had a minimum score. Thus, the T₃ (7.5 ± 0.1) was appreciated by a panel of jury and selected for the efficacy of the present study. According to statistical analysis, texture of the product did not substantially change from T₁ to T_3. The present study’s examination of texture relates to the work of Naknaen and Itthisoponkul^[33] The study’s findings are connected to the goods that Aksay et al.^[35] purchased. According to Salvador et al.^[34] textural changes throughout time are caused by enzyme activity.

The overall acceptability is depicted as T_c (7.5 ± 0.16), T₁ (7.3 ± 0.18), T₂ (7.53 ± 0.19), and T₃ (7.8 ± 0.1). The minimum score was given to T₁ (7.30 ± 0.18) and T₃ (7.8 ± 0.1) showed the maximum score. Thus, it was concluded that the T₃ (7.8 ± 0.1) has an excellent overall acceptability status compared to other treatments and was selected for the efficacy of the current study. The statistical analysis revealed that there is a greater acceptance shift from T₁ (7.3 ± 0.18) to T₃ (7.8 ± 0.1) of iron-rich Nutri-bars. According to the investigation of Naknaen and Itthisoponkul,^[33] the results obtained from the overall acceptability of final products match the results of the former study. The values of the overall acceptability of oat-based energy bars are similar to the attributes of the current study.^[36]

Mineral content of bars

The mineral content of different treatments of iron-rich nutri-bars is portrayed in Table 3. The concentration of iron (Fe) content in the control group treatment, denoted as T_c, was 5.5 per mg per 100 g. The concentration of iron content in the selected group treatment denoted by T₃ was 13.2 per mg/100 g. Thus, these results showed that the selected product enriched with spinach and chickpea flour contained a higher amount of iron (Fe) content. Hence, the treatment T₃ contained product should be more useful to enhance the efficacy of iron in females. Saini et al.^[38] studied that the value-added bar enriched with oatmeal, honey, and butter-based oats had a significant amount of iron content as compared to the control group. Zahra et al.^[39] investigated that the dried spearmint powder leaves had 45–46 mg of iron and 0.8 to 0.9 mg/100 g of copper in respect of all four methods.

Table 3. Mineral content of bars mg/100 g.

	Control (TC)	Selected (T3)
Iron	5.5	13.2
Zinc	3.4	5.69

T_c = Control bar.

T₃ = 50% jaggery, 35% chickpea, and 15% spinach leaves powder iron rich nutri-bar.

The concentration of zinc (Zn) content in the control group treatment, denoted as T_c, was 3.4 per mg per 100 g. The concentration of zinc (Zn) content in the selected group treatment denoted by T₃ was 5.69 per mg/100 g. Thus, these results showed that the selected product enriched with spinach and chickpea flour contained a higher amount of zinc (Zn) content. Hence, the treatment T₃ contained product should be more useful to enhance the efficacy of zinc (Zn) in females. The zinc content of iron-rich nutri-bar had a similar trend as reported in the study of Coconut nutri-bar.^[40]

Efficacy plan

Socio-economic status of the selected young women: The data relating to socio-economic status of the selected group is depicted in Table 4. The results showed that about 20% of the total numbers had the 15–18 years of age group and approximately 65% were categorized in the range of 19–22 years of age. The remaining 15% were belonging to the above 22 years of age. Only a small number (30%) of young women belonged to nuclear families. On the other hand, a large number (70%) of young girls belonged to joint families. The monthly family income of selected groups in which 55% had more than 20,000, 35% had 10,000 to 20,000, and 10% had less than 10,000. About 37.5% of the guardians of the selected groups were graduated, 30% were high school educated, 27.5% were middle school educated, and only 5% were illiterate. But 20% of the mothers of young girls were illiterate, 15% were middle school educated, 55% were high school educated, and only 10% were graduated. Fathers of young girls belonged to different professions like businessmen, Govt. officers, labor, and farming in a ratio of 57.5%, 10%, 10%, and 27.5% respectively. Similarly, about 90% of the mothers in selected groups were housewives by profession and 10% were Government officers by profession. Overall, the young girls who participated in the study belong to a joint family of 19–22 years of age.

Table 4. Socioeconomic status of selected females.

	Subjects selected (n = 40)
Particulars	Total number	Percentage %
Age 15–18 19–22 >22	08 26 06	20 65 15
Family type Joint Nuclear	28 12	70 30
Family monthly income <10000 10000–20000 >20000	04 14 22	10 35 55
Father’s Occupation Business Govt. officer Labor Farming	23 04 04 09	57.5 10 10 22.5
Mother’s Occupation Housewife Business Govt. officer Labour Farming	36-04--	90-10--
Education level of mother Illiterate Middle school High school Graduate	08 06 22 04	20 15 55 10
Education level of father Illiterate Middle school High school Graduate	02 11 12 15	05 27.5 30 37.5

Dietary habits of the selected females

The data obtained from the food consumption pattern of selected young girls is depicted in Table 5. This data shows a variety of eating patterns of subjects including food habits, meal patterns, beverage, fruit consumption, leafy vegetable consumption, fast food consumption, and any type of supplementation. According to data about 77.5% of young girls were vegetarian, and the remaining 22.5% were non-vegetarian (consuming egg 15% and meat 7.5%). Similarly, the meal pattern of selected young girls includes two times, three times, and four times. About 80% were consuming two meals, 17.5% were consuming three meals and a small percentage (2.5%) of young girls were involved in four times the consumption of meals. The beverage intake includes tea, milk, and cold drinks. A relatively high percentage (about 70%) of young girls were consuming tea, 12.5% had a habit of milk consumption and 17.5% were found to be drinking cold drinks. A higher percentage (45%) of selected groups were consuming fruits twice a week, 40% were consuming fruits once in a day and only 15% were consuming fruit four times in a week. In leafy vegetable consumption, 37.5% were consuming spinach, 10% were eating fenugreek and a higher percentage (52.5%) were consuming other types of leafy vegetables. Along with these meal patterns, young girls in this study were consuming fast food daily, twice a week and four times a week in a concentration of 25%, 20%, and 55%, respectively. About 7.5% were taking supplements with iron-rich Nutri bars and the remaining 92.5% were not taking any type of supplements in their regular diet.

Table 5. Assessment of dietary habits of selected females through food questionnaire.

Dietary Pattern	Number of subjects (n = 40)	Percentage (%)
Food habits Vegetarian Non-vegetarian Egg Meat	31 06 03	77.5% 15% 7.5%
Meal pattern Two time Three time Four time	32 07 01	80% 17.5% 2.5%
Beverages Tea Milk Cold drinks	28 05 07	70% 12.5% 17.5%
Fast food consumption Daily One’s in week Twice or more in week	10 08 22	25% 20% 55%
Leafy vegetables consumption Spinach Fenugreek leaves Others	15 04 21	37.5% 10% 52.5%
Fruits consumption One’s day Twice a week Four times in a week	16 18 06	40% 45% 15%
Any supplementation Yes No	03 37	7.5% 92.5%

Anthropometry of participants

The mean values of anthropometric measurements, including height, weight, and BMI of both the control and experimental group of study are presented in Table 6. Anthropometric measurements including height, weight, and BMI of both control and experimental groups before and after assessment of the study are presented in Table 7. The mean value of height according to the pre-assessment and post-assessment of the control group was 156.87 ± 7.5 and 156.92 ± 7.46 cm, respectively. Similarly, the mean value of weight for pre-assessment (55.23 ± 9.47) and post-assessment (54.93 ± 8.45 kg) of the control group is presented in Table 6. The mean value for BMI of the control group in terms of pre- and post-assessment was 22.31 ± 2.51 and 22.21 ± 2.21 Kg/m². Based on a statistical analysis of control group parameters, the results were highly non-significant (P > .05). On the other hand, the mean value of height, weight, and BMI of the experimental group in terms of pre-assessment was 158.81 ± 5.81 cm, 50.35 ± 5.94 Kg, 19.99 ± 2.46 Kg/m², respectively. At the same time, the mean value of these parameters like height, weight, and BMI of the experimental group in terms of post-assessment was 158.81 ± 5.81 cm, 51.48 ± 6.03 Kg, and 20.44 ± 2.47 Kg/m². The statistical analysis of the experimental group showed a highly significant result (P < .05). Thus, it was concluded that the treatment T₃ is very liable as compared to other treatments due to its significant results in the anthropometric measurements.

Table 6. Anthropometry mean of subjects of control and experimental groups.

	Control group (n = 20)			Experimental group (n = 20)
Characteristics	Pre-assessment	Post-assessment	P-value	Pre-assessment	Post-assessment	P-value
Height (cm)	156.87 ± 7.55	156.92 ± 7.46	0.2412	158.81 ± 5.81	158.81 ± 5.81	0.00
Weight (Kg)	55.23 ± 9.47	54.93 ± 8.45		50.35 ± 5.94	51.48 ± 6.03
BMI (Kg/m^2)	22.31 ± 2.51	22.21 ± 2.21		19.99 ± 2.46	20.44 ± 2.47

Mean ± Standard deviation.

Control group = Without iron rich nutri-bar.

Experimental group = With iron rich nutri-bar.

Table 7. Anthropometry of control and intervention group subjects.

	Control group (n = 20)			Experimental group (n = 20)
Characteristics	Pre-assessment	Post-assessment	P-value	Pre-assessment	Post-assessment	P-value
Height (cm)			0.330			0.256
<150	3 (15%)	3 (15%)		2 (10%)	2 (10%)
>150	17 (85%)	17 (85%)		18 (90%)	18 (90%)
Weight (kg)			0.368			0.000
<45	3 (15%)	3 (15%)		0%)	0%)
45–55	5 (25%)	6 (30%)		17 (85%)	17 (85%)
>55	12 (60%)	11 (55%)		3 (15%)	3 (15%)
BMI (kg/m2)			0.465			0.000
<18.5	2 (10%)	2 (10%)		8 (40%)	3 (15%)
18.5–24.9	16 (80%)	17 (85%)		10 (50%)	15 (75%)
>24.9	2 (10%)	1 (5%)		2 (10%)	2 (10%)

Control group = Without iron rich nutri-bar.

Experimental group = With iron rich nutri-bar.

Height

The individuals who participated in the study of the control group before and after assessment with height <150 cm were 3 (15%). While the two (10%) individuals of experimental group pre- and post-assessment with height <150 cm. The number of individuals with height >150 cm in the control group was 17 (85%) of the total participants. In the experimental group, 18 (90%) individuals were noted with height >150 cm. In the control group, the mean value of height before assessment and after assessment was 156.87 ± 7.5 and 156.92 ± 7.46 cm, respectively. In the experimental group, the height before and after assessment was noted as 158.81 ± 5.81. While the statistical analysis showed that the height of the control groups was a highly non-significant association (P > .05). On the contrary, statistical analysis of the experimental group showed a highly significant association (P < .05) between the height of individuals before and after assessment. Hence, there was a variation in the height of the control and experimental groups. In the control group, the mean value of height before assessment and after assessment was 55.60. But in the experimental group, the height before and after assessment was noted as 57.20. The mean value of the weight in the experimental group before and after assessment was 35.8 & 37.04. In the experimental group, the mean value of BMI before and after assessment was 16.93 & 17.53.

Weight

In the control group with pre- and post-assessment, only three individuals (15%) had less than 45 Kg weight. While there was no individual observed in the range of <45 kg weight of the intervention group. In the range of weight, 45–55 kg included five (25%) individuals in the pre-assessment and six (30%) subjects in the post-assessment control group. While in the experimental group before and after assessment, 17 (85%) individuals were noted to be in a range of 45–55 kg weight. In the control group with pre- and post-assessment, 12 (60%) and 11(55%) subjects, respectively, had greater than 55 kg. Whereas in the experimental group with pre- and post-assessment, only three (15%) individuals were in a range of >45 Kg weight. According to the statistical results, it was concluded that the weight of the control group was highly non-significant association (P > .05). In contrast, the experimental group showed a highly significant association with weight (P < .05).

Body Mass Index (BMI)

In the control group, only two (10%) individuals had less than 18.5 Kgm⁻² BMI in both pre- and post-assessment conditions. In the experimental group with pre- and post-assessment, 8(40%) and three (15%) individuals were in a range of <18.5 Kgm⁻² BMI. In the range of BMI 18.5–24.9 Kgm⁻² 16 (80%) and 17 (85%) individuals were found in terms of pre- and post-assessment of the control group, respectively. Meanwhile, in the experimental group 10 and 15 individuals had 18.5–24.9 Kgm⁻². BMI in terms of pre- and post-assessment, respectively. The individuals in the control group with >24.9 Kgm⁻² BMI were two (10%) and one (5%) in terms of pre- and post-assessment, respectively. Whereas only two (10%) individuals of the experimental group with pre- and post-assessment were in a range of >24.9 Kgm⁻² BMI. According to statistical assays, it was observed that the results of the BMI of control groups showed a high non-significance association (P > .05). In contrast to the control group, the BMI of the experimental group showed a highly significant association (P < .05). A study designed in Vietnamese showed a significant improvement in the nutritional status as well as growth patterns of rural school-going children. A significant improvement was also observed in the height and weight of these children due to the consumption of micro and macronutrients in a sustainable food cost.^[41] There was no significant alteration observed in the BMI of men and women before and after treatment. Machado et al.^[42] studied the effects of quinoa bars that showed a favorable result in the reduction of BMI of experimental group subjects.

Biochemical assessment

Hemoglobin (Hb): The mean value of biochemical assessment, including Hemoglobin (Hb), Total iron-binding capacity (TIBC), and Serum ferritin concentration in the blood of control and experimental group before and after the assessment is presented in Table 8. The mean value of Hb of the control group before and after assessment was 11.04 ± 1.07 and 11.10 ± 0.99 (g/dl), respectively. A statistical analysis of the mean value of the control group with pre and post assessment showed a highly non-significant association (P > .05). On the other hand, the mean value of Hb of the experimental group in pre- and post-assessment was 11.18 ± 1.09 and 12.21 ± 1.14 (g/dl), respectively. These results interpret that the mean value of hemoglobin (Hb) increased from the control group to the experimental group.

Table 8. Biochemical assessment mean of subjects of control and experimental group.

	Control group (n = 20)			Experimental group (n = 20)
Characteristic	Pre-assessment	Post-assessment	P-value	Pre-assessment	Post-assessment	P-value
Hb (g/dl)	11.04 ± 1.07	11.10 ± 0.99	0.197	11.18 ± 1.09	12.21 ± 1.14	0.000
TIBC (mcg/dL)	343.60 ± 37.05	340.55 ± 36.34	0.110	347.95 ± 39.08	326.30 ± 30.59	0.000
Serum ferritin (ng/mL)	44.22 ± 21.6	43.10 ± 21.34	0.539	32.91 ± 14.9	36.40 ± 14.6	0.000

Mean ± Standard deviation.

Control group = Without iron rich nutri-bar.

Experimental group = With iron rich nutri-bar.

The percentage of subjects involved in the biochemical analysis including Hemoglobin (Hb), Total iron-binding capacity (TIBC), and Serum ferritin concentration of the control and experimental group pre- and post-assessment is described in Table 9. Different ranges of Hb assessment included diverse percentages of respondents in pre- and post-assessment of control as well as intervention groups. In the control group, the individual with a value of hemoglobin less than 10 g/dl in pre-assessment was 3three(15%) and no one (zero) was found in post-assessment. Similarly, in the experimental group, the respondents in the range of Hemoglobin <10 g/dl in pre-assessment was two (20%). Only one respondent (5%) was reported in the post-assessment. In the control group, the individuals involved in the range of 10–11.5 g/dl of Hb in pre-assessment were 11 (55%) and 14 (70%) were post-assessment. While the respondents having Hb range 10–11.5 g/dl in pre-assessment were 10 (40%) and only 4 (20%) reported in post-assessment. The individuals involved in the range of greater than 11.5 g/dl Hb in pre- and post-assessment were six (30%) in the control group. On the other hand, the individuals having greater than 11.5 g/dl Hb before assessment was 8 (40%) and 15 (75%) reported after assessment of the experimental group.

Table 9. Biochemical assessment of subjects of control and experimental group.

	Control group (n = 20)			Experimental group (n = 20)
Characteristics	Pre-assessment	Post assessment	P-value	Pre-assessment	Post-assessment	P-value
Hb (g/dl)			0.197			0.000
<10	3 (15%)	0%)		2 (20%)	1 (5%)
10–11.5	11 (55%)	14 (70%)		10 (40%)	4 (20%)
TIBC (mcg/dL)			0.110			0.000
<300	2 (10%)	2 (10%)		1 (5%)	2 (10%)
300–400	18 (90%)	18 (90%)		17 (85%)	18 (90%)
Serum ferritin (ng/mL)			0.539			0.000
<50	14 (70%)	14 (70%)		17 (85%)	17 (85%)
50–159	6 (30%)	6 (30%)		3 (15%)	3 (15%)
>159	0%)	0%)		0%)	0%)

Control group = Without iron rich nutri-bar.

Experimental group = With iron rich nutri-bar.

Devulapalli and Gokhale^[43] studied that the millet-based product enriched with iron supplementation showed a significant improvement in anemic girls by increasing the Hb level of these subjects. Another study supports the results of the current study to improve the Hb status by consumption of iron-rich Nutri-bars. According to the investigation, no significant results were observed in the children who were consuming maize-based porridge and grain-enriched flour. In the MNP group a significant increase in the concentration of PF and Hb was noticed as compared to the control group by a sufficient decrease in concentration of TfR. Thus, in the MNP group, a sufficient decrease in anemia of respondents was noted.^[44]

Total iron-binding capacity (TIBC): The mean value of total iron-binding capacity (TIBC) of the control group before and after the assessment was 343.60 ± 37.05 and 340.55 ± 36.34 (mcg/dL), respectively. The mean value of total iron-binding capacity (TIBC) of the experimental group in pre- and post-assessment was 347.95 ± 39.08 and 326.30 ± 30.59 (mcg/dL), respectively. These results interpret that the mean value of TIBC decreased from the control group to the experimental group.

Different ranges of total iron-binding capacity (TIBC) assessment included diverse percentages of respondents in pre- and post-assessment of control as well as intervention groups. In the control group, the individual with a value of total iron-binding capacity (TIBC) less than 300 mcg/dL in pre-assessment was two (10%) and the same number two (10%) was found in post-assessment. Similarly, in the experimental group, the respondents in the range of total iron-binding capacity (TIBC) <300 mcg/dL in pre-assessment was one (5%) and only 2(10%) individuals were reported in post-assessment. In the control group, the individuals involved in the range of 300–400 mcg/dL of total iron-binding capacity (TIBC) in pre-assessment and post-assessment were the same 18 (90%). While the respondents having total iron-binding capacity (TIBC) range 300–400 mcg/dL in pre-assessment were 17 (85%) and 18 (90%) reported in post-assessment.

The individuals involved in the range of greater than 400 mcg/dL total iron-binding capacity (TIBC) in pre- and post-assessment were zero of the control group. On the other hand, the individuals having greater than 400 mcg/dL total iron-binding capacity (TIBC) before and after assessment were two (10%) in pre-assessment and zero in post-assessment of the experimental group. The statistical analysis of the subject’s percentage in the control group before and after the assessment showed a highly non-significant association (P > .05). Whereas in the experimental group, the statistical representation showed highly significant results (P < .01). The findings of this study regarding TIBC were found to correlate with one another and revealed a tendency that was comparable to that which was observed in efficacy studies of natural and synthetic iron sources among anemic pregnant women in the community.^[45] The results of the current study also showed a similar trend as demonstrated in the assessment of iron deficiency in pregnant women by determining iron status.^[46]

Serum Ferritin

The mean value of serum ferritin of the control group before and after the assessment was 44.22 ± 21.6 and 43.10 ± 21.34 (ng/ml), respectively. The mean value of serum ferritin of the experimental group in pre- and post-assessment was 32.91 ± 14.9 and 36.40 ± 14.6 (ng/ml), respectively. These results interpret that the mean value of serum ferritin decreased from the control group to experimental group

Different ranges of serum ferritin assessment included a diverse percentage of respondents in pre- and post-assessment of control as well as intervention groups. In the control group, the individual with the value of serum ferritin less than 50 ng/ml in pre-assessment was 14 (70%), and the same number 14 (70%) was found in post-assessment. Similarly, in the experimental group, the respondents in the range of serum ferritin <50 ng/ml in pre-assessment were 17 (85%) and the same number of individuals 17 (85%) were reported in post-assessment. In the control group, the individuals involved in the range of 50–159 ng/ml of serum ferritin in pre-assessment and post-assessment were the same six (30%). While the respondents had a serum ferritin range 50–159 ng/ml in pre-assessment 3 (15%) and the same numbers 3 (15%) reported in post-assessment. The individuals involved in the range of greater than 159 ng/ml serum ferritin in pre- and post-assessment were zero of the control group. On the other hand, the individuals having greater than 150 ng/ml serum ferritin before and after assessment were zero in the experimental group. The statistical analysis of the subject’s percentage in the control group before and after the assessment showed a highly non-significant association (P > .05). Whereas in the experimental group, the statistical representation showed highly significant results (P < .01). The results of the present study about serum ferritin were correlated and showed a similar trend as demonstrated in efficacy studies of natural and synthetic iron sources among anemic pregnant women in the community.^[45]

Conclusion and recommendations

It has been concluded from this study that iron-rich Nutri bars formulated with spinach powder and chickpea flour have the potential to effectively improve iron status in young females. The Nutri bars exhibited favorable physicochemical attributes, high acceptability, and significant increases in hemoglobin and serum ferritin levels. The findings suggest that incorporating these bars into the diet can be a promising strategy to combat iron deficiency in this demographic, with implications for public health and nutrition interventions. However, more research needs to be conducted to combat iron deficiency in anemic people. Further research is needed to overcome iron deficiency in developing countries.

Acknowledgments

The authors thank the Research Supporting Project for funding this work through Research Supporting Project number (RSPD2023R708), King Saud University, Riyadh, Saudi Arabia.

Disclosure statement

No potential conflict of interest was reported by the author(s).