1. Introduction
Nutrition is a critical part of health and development. Obviously, better nutrition enhances a strong immune system, lowers the risk of non-communicable diseases, and increases longevity [
1]. As an integral part of the nutrition principle, human diet planning is the process of selecting foods or food groups to meet an individual’s nutritional needs [
2]. The concept of energy balance and body weight regulation states that when energy intake is greater than energy expenditure, excess calories are stored in the body with a subsequent increase in body weight [
3]. It is important to understand and know the optimal requirements of nutrients for good health and well-being with a balanced weight. Many chronic diseases have been directly or indirectly associated with nutritional imbalance. Globally, diabetes mellitus (DM) is the most common non-communicable metabolic disease in which the person has a high blood glucose (blood sugar) level, either due to inadequate insulin production or because the body’s cells do not respond properly to insulin or both [
4]. More precisely, DM is a chronic metabolic disease characterized by higher-than-normal blood glucose levels (homeostasis level = 80–120 mg/dL). Glucose levels with measurements such as fasting blood glucose, postprandial blood glucose, and A1c of normal (<100 mg/dL; <140 mg/dL; <5.7%), prediabetes (100–125 mg/dL; 140–200 mg/dL; 5.7–6.4%) and diabetes (>125 mg/dL; >200 mg/dL; >6.4%), respectively.
As an undeniable fact, DM is reaching potentially epidemic proportions in India. The level of morbidity and mortality due to diabetes and its complications is enormous. Many factors influence the prevalence of disease throughout a country [
5]. The origin of diabetes in India is multifactorial and includes genetic factors, environmental influences, rising living standards and lifestyle changes. As per 2019 reports of the International Diabetes Federation (IDF), India is one of the topmost countries for the number of people with diabetes from the age group of 20–79 years, where one in six adults with diabetes in the world come from India. Diabetes-related deaths total 1,010,262, with 77 million adults in India at risk. According to a report released by the Ministry of Health and Family Welfare (MoHFW), India in the year 2019, as per the IDF Atlas, India accounts for over 7.29 crore people with diabetes and the estimated increase will be 13.4 crore by 2045. In addition, according to the World Health Organization’s (WHO) Global Diabetes Compact, there has been a 70% increase in global deaths due to diabetes, and it has risen to the ninth leading cause of death in the world. The prediction of people with diagnosed diabetes worldwide will be raised from 420 million to 570 million in 2030 and further it will reach 700 million in 2045.
A three-fold mechanism of proper diet, insulin intervention and physical activity for management of diabetes and slowing down the prevalence of the disease is need of the hour [
6]. The prime objective is to maintain a proper diet, i.e., optimizing excessive calories is one of the possible ways to reduce the burden of the disease [
7]. Awareness programs to be conducted on diet plans according to the rural and urban parts of India as well as worldwide to enlighten and increase knowledge of planning diabetic diets. Diet optimization for diabetes is increasingly used in the field of nutrition, where it is feasible to achieve all nutritional requirements with the available food recipes [
8]. Patients with diabetes are generally put on an approximate intake of a 1200 to 1800 calorie diet per day to promote weight loss and the maintenance of ideal body weight (for diabetic patients having glucose levels of more than 200 mg/dL in the blood).
In this nutritional framework, linear programming problems play a vital role in preparing optimized diet plans with satisfying nutrient requirements. Many researchers have devised various linear and goal programming problems in order to optimize food recipes for global countries in order to provide adequate nutrients for the population. Beginning with the study, to achieve nutritional balance in selected diets by considering 150 raw food materials to satisfy Thais’ daily nutritional requirements with complex inter-relationships of constraints with GP [
9]. An efficient method was proposed for solving linear goal programming problems with a smaller number of variables, which is a computationally better optimized model than the traditional methods [
10]. Some authors clearly overviewed the techniques such as Pareto efficiency, normalization and non-standard utility function modelling in GP. Further examined the connection between GP and multi-objective programming techniques and utility theory and discussed their ranks as well and another review by the same authors focused on the significant developments of theoretical GP models in the area of intelligent modelling and solution analysis [
11,
12].
In modern references, some authors proposed a two-stage linear programming model for low-cost healthy diets for Malay households. In Stage-1, the model was formulated to satisfy various nutrient requirements for the pre-determined age-gender groups and Stage-2 focused on optimizing diet plans for the whole household with minimum cost daily diet plans [
13]. In addition, other authors proposed the GP nutrition model to minimize the deviations from nutrients, energy value and food cost in order to meet the daily nutrient needs of the reference woman and reference man of households in Bosnia and Herzegovina, developed and extended by proposing a linear programming diet model to maximize energy density for choosing food recipes (containing macro and micro-nutrients) as recommended by WHO in order to reduce food costs [
14,
15]. Another work was done by proposing linear and goal programming optimization models for analyzing the food basket (consists of nearly 158 general consumption of food recipes) in Bosnia and Herzegovina in order to meet various nutritional requirements of WHO and World Bank recommendations. The parameters such as price and nutrient requirements are linearly related to food weight, where LP models deal with the minimal value and structure of the food basket of an average person and GP models with minimal deviations from nutrient needs if the budget is fixed [
16]. Another study proposed an efficient method for solving lexicographic GP problems and its formulation with different variable sizes to be a better model than the existing models. Furthermore, the same researchers reviewed recent improvements and new advancements for solving linear goal programming (LGP) [
17,
18]. The researchers proposed MinSum, MinMax and extended goal programming problems for diet management problems. The study focused on analyzing the impact of achievement functions in designing diet problems that comply with nutritional, palatable, and cost constraints [
19].
Another study proposed a goal programming model for optimal dietary variations for diabetes patients with minimal attainment of sufficient nutrients in Indonesia [
20]. Other researchers compared weighted goal programming (WGP) and LP models for the targeted DASH diet’s tolerable intake levels within 1500 mg sodium for various calorie levels. The WGP is more efficient in minimizing the deviation from tolerable target levels at desired cost than the LP model [
21]. In parallel, some researchers have developed a nutrition optimization model to satisfy the daily nutrient needs of adolescents through pre-emptive goal programming. To minimize the sum of percentage of nutrient deviations according to its priorities of twenty most frequently consumed foods from Indonesian recommended dietary allowances and the available budget as goal and system constraints [
22]. Another study proposed goal programming problems for optimal dietary intake patterns to prevent obesity and calcium deficiency in the Taiwan population. The study concluded with essentially healthier and the promotion of low-fat density foods [
23]. The researchers employed linear programming diet optimization models to suggest a realistic and affordable diet with recommended nutrient intake of locally available foods for pregnant women in Malaysia [
24]. On the other hand, some authors reviewed four optimization algorithms, such as linear programming, dynamic programming, genetic algorithms and particle swarm optimization, that play a major role in diet optimization problems [
25].
All of the studies cited above have focused on optimizing diet plans for both healthy people and those suffering from specific diseases. Limited works have been done on diet plans for diabetes patients based on glucose levels. In the present study, the motivation is to develop six optimized diet plans for diabetes patients with different energy levels (1104 to 1986 Calories). It mainly focuses on optimizing diet plans with varied energy levels (in calories) by satisfying the nutrient requirements of the limited menu recipes for diabetes management in India.
3. Results and Discussion
Overall, the results show diet plans with optimal food recipes for satisfying the nutritional requirements of Menus 1–6 with five-time intervals (breakfast, morning snack, lunch, evening snack, and dinner) for the total energy levels such as 2199.9, 2310.8, 1785.7, 2606, 2196.2, and 2616.8 calories which are optimized by LPP, PGP and NPGP as shown in
Table 2,
Table 3,
Table 4,
Table 5,
Table 6 and
Table 7. Menu-1 framed with 16 recipes and the solution of LPP, optimized 11 recipes with energy levels to 1535 calories. Further, the solution of PGP and NPGP optimized 14 recipes for energy levels of 1570 calories. Menu-2 contains 16 recipes and the results of LPP optimized 12 recipes with energy levels of 1520.9 calories and the solutions of PGP and NPGP have considered all 16 food recipes with 1756.7 calories of energy out of 2310.8 calories. Menu-3 consists of 16 recipes and the LPP solution optimized 12 recipes with energy levels of 1272.5 calories and solutions of PGP and NPGP have considered 14 food recipes with 1284 calories of energy out of 1785.7 calories. Furthermore, Menu-4 with 16 recipes and the solution of LPP optimized 13 recipes with energy levels of 1568 calories and solutions of PGP and NPGP optimized 14 recipes with 1583.7 calories of energy out of 2606 calories. Menu-5 with 13 recipes and the solution of LPP optimized 11 recipes with energy levels of 1096.4 calories and the solutions of PGP and NPGP optimized all 13 recipes with 1104.7 calories of energy out of 2196.2 calories. Finally, Menu-6 with 16 recipes and the solution of LPP optimized 13 recipes with energy levels of 1962.9 calories and the solutions of PGP and NPGP optimized 13 and 12 recipes with 1986.8 calories of energy out of 2616.8 calories. Hence, LPP, PGP and NPGP optimized the entire menu by minimizing the total energy for meeting the sufficient nutritional requirements of patients with blood glucose levels of above 200 mg/dL which are depicted in
Table 8. The menus with optimized recipes obtained through LPP, PGP and NPGP are represented in
Figure 1.
Nutritional recommendations for optimal disease management are challenging to implement in reality. Patients with DM are already overweight at diagnosis and gain more weight while taking oral medications and/or insulin. DM individuals may also increase energy intake through possible overtreatment of medication-induced hypoglycemia [
3]. When tailoring dietary intake levels, the priority should be given to energy reduction and changing dietary composition to optimize intake of essential nutrients and maintain eating patterns. The present study focuses on choosing food recipes with a low glycemic index with the respective nutritional values [
30,
31]. The linear and goal programming problems in the study produce optimal and feasible solutions to the diet problems in balancing nutrient requirements. Goal programming problems are more flexible in producing a combination of food recipes to fulfill all nutrient goals according to their priorities. The results obtained from PGP and NPGP meet the daily nutrient portions in menu planning. However, alternative menu combinations are possible to replace food recipes with the same source of nutrients through these optimization models. Quantities of food recipes can be selected based on the varying sugar levels of diabetes patients for satisfying energy balance. The study helps to maintain glucose levels with optimized food menus and to promote a healthy lifestyle for DM patients in India.