Development of Food Multi-Mix Using a Linear Programming Approach to Fill the Nutrient Gap of Amino Acids and Micronutrients for Stunted Non-Wasted Children
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design and Population under Study
2.2. Ethics Statement
2.3. Anthropometry
2.4. Dietary Intake
2.5. Food Composition Database
2.6. Statistical Analysis
2.7. Preparation of Model Parameters
2.8. Linear Programming Analysis
2.9. Food Multi-Mix Formulation
- Identification of locally available and culturally accepted food according to the results of dietary assessment and interview;
- Processing of the identified food into powder or other intermediate form that include soaking, sprouting, heat treatment (boiling, steaming, pressure cooking) and fermentation depends on the identified food item;
- Laboratory analysis;
- Selection of the processed food into multi-mix based on the highest content of amino acid problem;
- Formulation of most optimal composition of food item to be included in the FMM to fulfil nutrients gap by using the linear programming optimization in Nutrisurvey version 2004 software, Germany;
- In setting the minimal goal of nutrient achievement, the biggest or highest gap, i.e., difference between 65% RNI to %RNI for nutrient when nutrient content was minimized (worst-case scenario) in the LPA was used (the lowest and the highest value shows the gap of RNI fulfillment. The lowest value was calculated from the gap between the 100%RNI with the % RNI achieved by the using the best diet NFP (best diet that are optimized from the average food pattern), whereas the highest nutrient gap shows the gap between the 65% RNI (the RNI should be achieved at least 65% from the diet) and the fulfillment of %RNI when nutrient content is minimized (worst-case scenario);
- In addition, the ratio between animal to plant protein sources was targeted to meet the minimum of 4, based on a difference between stunted, non wasted vs. non stunted, not wasted children in the study.)
- 1.
- Inputting the selected potential food items i.e., soaked cowpeas and buncis batik, boiled wader fish and curd;
- 2.
- Inputting the target nutrient achievement based on nutrient gap;
- 3.
- Inputting the minimum and maximum amount (in grams) for each food item;
- 4.
- Calculating the most optimum formulation to achieve the target nutrients.
3. Results
3.1. General Characteristics and Nutritional Status of the Children
3.2. Complementary Feeding Recommendation
3.3. Identification of Underutilized Locally Available Food
3.4. Food Multi-Mix
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
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Nutrients | Requirements | |
---|---|---|
Energy 1 (kcal) | 1350 | |
Protein 1(gram) | 20 | |
Fat 1 (gram) | 30 | |
Calcium 1 (mg) | 650 | |
Vitamin C 1 (mg) | 40 | |
Thiamin 1 (mg) | 0.5 | |
Riboflavin 1 (mg) | 0.5 | |
Niacin 1 (mg) | 6 | |
Vitamin B-6 1 (mg) | 0.6 | |
Folate 1 (mcg) | 160 | |
Vitamin B-12 1 (mcg) | 1.5 | |
Vit A (RE) 1 | 400 | |
Iron 1 (mg) | 7 | |
Zinc 1 (mg) | 3 | |
Isoleucine (mg/d) | 351 a | 526.5 b |
Leucine (mg/d) | 702 a | 1053 b |
Lysine (mg/d) | 572 a | 858 b |
SAA 2 (methionine and cysteine) (mg/d) | 286 a | 429 b |
AAA 3 (phenylalanine + tyrosine) (mg/d) | 520 a | 780 b |
Threonine (mg/d) | 312 a | 468 b |
Tryptophane (mg/d) | 83.2 a | 124.8 b |
Valine (mg/d) | 468 a | 702 b |
Histidine (mg/d) | 195 a | 292.5 b |
Characteristics | N = 87 |
---|---|
Father’s education level 1 | |
illiterate | 2 (2.3) |
Elementary school | 33 (37.9) |
Junior high school | 32 (36.8) |
Senior high school | 17 (19.5) |
Academy/University | 3 (3.4) |
Mother’s education level 1 | |
Illiterate | 1 (1.1) |
Elementary school | 24 (27.6) |
Junior high school | 44 (50.6) |
Senior high school | 16 (18.4) |
Academy/University | 2 (2.3) |
Types of HH 1: Nucleus family | 46 (52.9) |
Child’s sex 1: Boys | 45 (51.7) |
Father’s main occupation 1 | |
Farmer (Owner/shared land) | 27 (31) |
Breeder (cow/chicken/duck) | 6 (6.9) |
Fisherman | 1 (1.1) |
Farm/livestock worker | 24 (27.6) |
Daily worker non-farm/livestock (construction, industry, driver) | 10 (11.5) |
Employee | 7 (8) |
Entrepreneur | 11 (12.6) |
Main income from agricultural activities | 58 (66.7) |
Father’s age (year) 2 | 31.7 ± 6.6 |
Mother’s age (year) 2 | 26.1 ± 5.6 |
Number of people living in a HH 2 | 4 (4; 6) |
Number of people in HH who earn money 2 | 2 (1; 3) |
Total income from father and mother 2 (thousand rupiahs) | 2320 (1400; 3760) |
House ownership 1 | 32 (36.8) |
HH financial management by mothers 1 | 77 (88.5) |
Child’s age | 16.5 (13.7; 19.4) |
Weight (kg) | 8.45 ± 0.80 |
Length (cm) | 72.96 ± 3.08 |
WLZ 2 | −0.65 ± 0.73 |
LAZ 2 | −2.54 (−2.82; −2.20) |
WAZ 2 | −1.74 ± 0.60 |
First Run | Second Run 5 | Third Run 6 | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Nutrient | NFP 1 | Min | Max | Note | NFP 1 | Min | Max | Note | NFP 1 | Min | Max | Note |
Energy | 100 | 31.7 | 136.5 | Inadequate | 100 | 31.6 | 115.6 | Adequate | 100.00 | 31.6 | 115.6 | Inadequate |
Protein | 106.2 | 92.6 | 233 | Adequate | 208.2 | 139.9 | 234.3 | Adequate | 213.70 | 139.9 | 234.3 | Adequate |
Fat | 100 | 78.6 | 152.1 | Adequate | 121.8 | 99.8 | 162.1 | Adequate | 135.00 | 99.8 | 162.1 | Adequate |
Ca | 100 | 33.7 | 146.8 | Inadequate | ||||||||
Vit C | 149.6 | 61 | 272.7 | Inadequate | ||||||||
Vit B1 | 102.2 | 33.3 | 223.7 | Inadequate | ||||||||
Vit B2 | 153.9 | 63.6 | 321.9 | Inadequate | ||||||||
Vit B3 | 115.5 | 38.6 | 228.7 | Inadequate | ||||||||
Vit B6 | 100 | 19.6 | 141.9 | Inadequate | ||||||||
Folate | 102.2 | 23.1 | 222.6 | Inadequate | ||||||||
Vit B-12 | 104.5 | 23.9 | 161.7 | Inadequate | ||||||||
Vit A RE | 491.8 | 258.1 | 980 | Adequate | ||||||||
Iron | 100 | 44.1 | 191.5 | Inadequate | ||||||||
Zinc | 134 | 58.1 | 258.8 | Inadequate | ||||||||
His | 435.2 | 249.4 | 525.3 | Adequate | 34.6 | 16.6 | 35 | Absolute PN 4 | ||||
Lys | 398.8 | 229 | 481.1 | Adequate | 313.8 | 152.7 | 320.8 | Adequate | ||||
SAA 2 | 496.3 | 268.2 | 577.7 | Adequate | 366.8 | 178.8 | 385.1 | Adequate | ||||
AAA 3 | 540.7 | 330.7 | 650.5 | Adequate | 427.6 | 220.4 | 433.7 | Adequate | ||||
Thre | 482.3 | 292.8 | 574.1 | Adequate | 376.0 | 195.2 | 382.8 | Adequate | ||||
Tryp | 544.3 | 350.1 | 657.7 | Adequate | 415.2 | 233.4 | 438.5 | Adequate | ||||
Val | 409.6 | 256.6 | 488.8 | Adequate | 319.3 | 171.1 | 325.9 | Adequate | ||||
Leu | 417.6 | 268.2 | 497.7 | Adequate | 325.5 | 178.8 | 331.8 | Adequate | ||||
Isoleu | 487.2 | 307.4 | 593.3 | Adequate | 379.9 | 204.9 | 395.5 | Adequate |
Nutrient | WHO/UNICEF 98 | Nutrient Gap (% RNI) | |
---|---|---|---|
Lowest 1 | Highest 2 | ||
Energy (kcal) | 746 | 33.3 | 246.18 |
Protein 3 (gram) | 10.9 | - | 6 |
Thiamin (mg) | 0.5 | 31.7 | 0.16 |
Riboflavin (mg) | 0.6 | 1.4 | 0.19 |
Niacin (mg) | 8 | 26.4 | 2.11 |
B6 (mg) | 0.7 | 45.4 | 0.32 |
Folate (mcg) | 50 | 41.9 | 20.95 |
B12 (mcg) | 0.5 | 41.1 | 0.21 |
Vit C (mg) | 30 | 4 | 1.20 |
Ca (mg) | 350 | 31.3 | 109.55 |
Fe (mg) | 6 | 20.9 | 1.25 |
Zn (mg) | 2.8 | 6.9 | 0.19 |
Nutrient | Req 1 | CFR 2 | FMM 3 | ||||||
---|---|---|---|---|---|---|---|---|---|
Med | Max | FMM0 4 | FMM1 5 | FMM2 6 | FMM3 7 | FMM4 8 | FMM5 9 | ||
Energy (kcal) | 746 | 412.5 | 834.5 | 241.1 | 246.3 | 245.4 | 246.6 | 277.7 | 245.9 |
Protein (g) | 10.9 | 22.8 | 47.3 | 14.8 | 24.2 | 26.6 | 26.8 | 29.3 | 31.2 |
Vit. B1 (mg) | 0.5 | 0.2 | 0.4 | 0 | 0.1 | 0.1 | 0.1 | 0.1 | 0 |
Vit B2 (mg) | 0.6 | 0.5 | 0.9 | 0 | 0.1 | 0.1 | 0.1 | 0.2 | 0.4 |
Vit. B6 (mg) | 0.7 | 0.4 | 0.9 | 0 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 |
Tot. fol.acid (mcg) | 50 | 79.3 | 154.4 | 19.4 | 7.9 | 7.7 | 12.1 | 20.9 | 31 |
Vit. B12 (mcg) | 0.5 | 1.5 | 2.6 | 0 | 0 | 0 | 0.1 | 0.3 | 0.7 |
Vit. C (mg) | 30 | 38.2 | 63.8 | 0 | 0 | 0 | 0 | 0 | 0 |
Calcium (mg) | 350 | 313.3 | 638.9 | 0 | 8 | 6.4 | 11.4 | 21.4 | 30 |
Iron (mg) | 6 | 6.2 | 12.1 | 4.1 | 3.9 | 4.2 | 3.9 | 4.1 | 4.1 |
Zinc (mg) | 2.8 | 1.6 | 3 | 2.5 | 7.8 | 8.7 | 8.7 | 8.9 | 8.8 |
Isoleucine (g) | 0.53 | 1.1 | 2.3 | 0.7 | 1.1 | 1.2 | 1.3 | 1.4 | 1.5 |
Leucine (g) | 1.05 | 1.9 | 3.9 | 1.2 | 2 | 2.2 | 2.3 | 2.5 | 2.7 |
Lysine (g) | 0.86 | 1.5 | 3.2 | 0.7 | 1.5 | 1.6 | 1.7 | 1.9 | 2.1 |
SAA (g) | 0.43 | 0.8 | 1.7 | 0 | 0.8 | 0.8 | 0.8 | 1 | 1.1 |
AAA (g) | 0.78 | 1.8 | 3.7 | 2 | 3 | 3.3 | 3.3 | 3.5 | 3.7 |
Threonine (g) | 0.47 | 1 | 2.1 | 0.9 | 1.3 | 1.5 | 1.5 | 1.6 | 1.7 |
Tryptophane (g) | 0.12 | 0.3 | 0.5 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.3 |
Valine (g) | 0.70 | 1.2 | 2.5 | 0.8 | 1.3 | 1.4 | 1.5 | 1.6 | 1.7 |
Histidine (g) | 0.29 | 0.6 | 1.2 | 0.6 | 0.8 | 0.9 | 0.9 | 1 | 1 |
Arginine (g) | NA | 1.4 | 3 | 1.1 | 1.9 | 2.1 | 2.1 | 2.3 | 2.3 |
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Wirawan, N.N.; Fahmida, U.; Purwestri, R.C.; Timan, I.S.; Hegar, B. Development of Food Multi-Mix Using a Linear Programming Approach to Fill the Nutrient Gap of Amino Acids and Micronutrients for Stunted Non-Wasted Children. Foods 2023, 12, 64. https://doi.org/10.3390/foods12010064
Wirawan NN, Fahmida U, Purwestri RC, Timan IS, Hegar B. Development of Food Multi-Mix Using a Linear Programming Approach to Fill the Nutrient Gap of Amino Acids and Micronutrients for Stunted Non-Wasted Children. Foods. 2023; 12(1):64. https://doi.org/10.3390/foods12010064
Chicago/Turabian StyleWirawan, Nia N, Umi Fahmida, Ratna C Purwestri, Ina S Timan, and Badriul Hegar. 2023. "Development of Food Multi-Mix Using a Linear Programming Approach to Fill the Nutrient Gap of Amino Acids and Micronutrients for Stunted Non-Wasted Children" Foods 12, no. 1: 64. https://doi.org/10.3390/foods12010064
APA StyleWirawan, N. N., Fahmida, U., Purwestri, R. C., Timan, I. S., & Hegar, B. (2023). Development of Food Multi-Mix Using a Linear Programming Approach to Fill the Nutrient Gap of Amino Acids and Micronutrients for Stunted Non-Wasted Children. Foods, 12(1), 64. https://doi.org/10.3390/foods12010064