Glycaemic Quotient (GQ): Development and Proposal of a More Precise Tool for Diet Planning and Preparation

Introduction

Diabetologists and Nutritionists prescribe diets for diabetic patients to cut down the carbs, at the same time, maintaining adequate proteins and energy requirement intact. They select foods according to the carbohydrate content and glycaemic index [3,4] . In Indian population, people often depend heavily upon cereals like wheat and rice for food. Often in South India, rice occupies more than 70% of the diet per day [2] . But as per WHO, recommended carbohydrate required per day for a person is 40-50% of the Total Daily Energy Expenditure (TDEE), which is calculated by multiplying BMR and the activity factor, which depends upon the level of physical work done by the subject in a day and also hyper-metabolic states like pregnancy and lactation, which are found to be requiring high energy consumption [1] . Gym enthusiasts, body builders and athletes try to follow strict diet plan as suggested by their trainers. Mostly these are well orchestrated [5] . But daily workers often rely upon morning walks or small workout sessions at home to keep fit and the diet includes almost everything as it gets. These people may not get time to go to gym or they cannot get the trainers or suggested foods for fitness [2] . Diabetes mellitus had been heard to be found in society often affecting middle or old age people, who does not indulge in fitness activities.

They are often found fatigued, often very hungry and thirsty [2] . There are many advertisement in the media nowadays about treatments that control, reverse and cure diabetes mellitus. But the percentage of reversal or cure is very less [1, 5] . So it is found that adopting steps to prevent Diabetes is far more useful. Diabetes drugs including insulin secretalogues and synthetic insulins often control the disease from progressing to complications like diabetic nephropathy, diabetic retinopathy, diabetic neuropathy or diabetic foot. But these drugs once started have to be taken for longer duration [5,6] . Controlling diabetes at a prediabetes stage, often reverse the incidence of the disease [1,5] . With the advent of digitalisation, mobile applications and smart watches, people find help to curate their diet according to the calorie calculation in their food and steps they walk to burn the calorie [7,8] . Many parameters including BMI, BDI and MCPD are being calculated by people to assess their physical conditions like obesity and the chance of acquiring metabolic dysfunction [2,3,9] . According to National Programme for Non-Communicable Diseases, in India, the survey and surveillance of these disease are delayed and incomplete [6] . In India the data does not convey the precise incidence and prevalence of non communicable diseases [2,6] . Also, rural OPD and community screening programmes often relay upon FBS only on predicting diabetes mellitus. Diabetes mellitus is detected often in patients with prevalent symptoms. So, the chance of prevention and reversal is very less [2,6] . Obesity, overeating and decreased physical activity are found to be the risk factors for diabetes mellitus [2,3] . But in many South Asian countries, lean diabetes is also common, in whom who works daily [2,3,9] . So like BMI for obesity, we wanted to individuate a tool for personalised assessment of metabolic risk for everyone, to find the chance of acquiring metabolic dysfunction, despite being lean and works daily [9] . The study aims to find a precise reference range for easy assessment [9] . With the advent of smart technologies, calculation of personalised parameters can be made easy through applications and softwares to selfmonitor on routine basis.

Materials and Methods Study Design and Population

This cross-sectional study was conducted at General Hospital, Ahwa, which is located in the South of Gujarat. A total population of 451 of both sexes with age ranging from 18 years to 70 years were included in the study. The population was surveyed through questionnaire, during general OPD. The hospital is a tertiary care hospital with patients attending from all sectors of the society. No one was excluded from the study, ensuring sample comprising of different body composition and metabolic profiles.

Data Collection

Demographic data included age and sex. Anthropometric parameters included height, weight, waist circumference and BMI, which were measured using standardised methods. BMR, TDEE and MCPD [10] were calculated using standard formulae. Clinical evaluation included Blood pressure and biochemical parameters included FBS. Lifestyle factors like physical activity, addictive habits and other comorbidities were recorded.

Glycaemic Quotient is calculated by the formula

Where TDEE is expressed in kcal/day and FBS is expressed in mg/Dl. GQ is expressed in a scale from 0-100, like GI.

Statistical Analysis

Stratified grading system is devised for risk classification and clinical implication. Data was analysed using Microsoft Excel and Sci-py packages. Data was first analysed using descriptive statistics. Mean and SD of relevant parameters were calculated and recorded. Correlation analysis was done between GQ and observed parameters to find relation, using Pearson's coefficient. p-value less than 0.05 is considered statistically significant.

Discussion

As shown in Table 2, GQ showed a very strong positive correlation with MCPD (r = 0.921, p < 0.001), strong positive correlation with BMR (r = 0.529, p < 0.001) and TDEE (r = 0.529, p < 0.001) and moderately strong positive correlation with weight (r = 0.411, p < 0.001) and height (r = 0.347, p < 0.001) and a weak positive correlation with BMI(r = 0.222, p < 0.001). Also GQ showed strong negative correlation with FBS (r = -0.73, p < 0.001), moderately negative correlation with age (r = -0.311, p < 0.001), diabetes mellitus (r = -0.29, p < 0.001) and hypertension (r = -0.181, p < 0.001) and weak negative correlation with systolic BP (r = -0.11, p = 0.019). GQ showed no statistically significant association with diastolic BP, sedentary lifestyle, alcohol and tobacco abuse.

Glycaemic Quotient of a person is defined as the maximum glycaemic tolerability of that person. It is the metabolic capacity of the individual to utilise glucose in their body. It is measured on a scale from 0 to 100 similar to Glycaemic Index. This study shows association of GQ value with measured parameters. Glycaemic tolerability of an individual is positively associated with their BMR and TDEE, which are directly proportional to weight, height, and physical activity and inversely proportional to age as shown in Table 1. Glycaemic tolerability of an individual is also found to be positively associated with their BMI [20] . This clarifies the results from a recent study with similar findings. Also, it is found to be negatively associated with age, FBS, diabetes, systolic BP and hypertension. Elderly, diabetic and hypertensive individuals are found to have lesser glycaemic tolerability. Diastolic BP, sedentary lifestyle, alcohol and tobacco abuse are found not to be influencing glycaemic tolerability.

Population Dynamics and Metabolic Variability

Basal characteristics from Table 2, show a cross-sectional population demography, ageing from 15 years to 88 years with mean age 51+/-14 years, including subjects with comorbidities like diabetes and hypertension. From this study, we can elucidate that GQ is a versatile tool, that take into consideration physical activity, and also underlying metabolic state. GQ helps the practitioner to counsel the patient, explaining the importance of physical activity, using the simple formula. Human body functions with specific metabolic rate and it varies from individual to individual [14] . It can be influenced by stress or hormonal variations like thyroid hormones and eostrogen [15] . We know that, stress increases metabolic rate due to the release of adrenal hormones like cortisol and other adrenocorticosteroids [15] . In hyperthyroidism, patient experiences increased catabolic enzyme activity, and energy release. The opposite is true in hypothyroidism where the person finds difficult to loose weight despite consistent fasting and starvation [16] . Some fat individuals eat very less. Dieticians find difficult to prescribe diet plans for them. Some thin people eat more, still don't gain weight. These are because of underlying metabolic conditions like thyroid diseases or PCOD [16] . Some people gain or loose weight suddenly if some stress factors are removed or underlying hormonal conditions are managed by medications [15] . Most metabolically normal fat people tend to eat more and metabolically normal thin people tend to eat less [17] . Prescribed diet for weight loss, for fat people, may leave them more hungry, but this strategy may work over time coupled with routine exercise schedules, with decreased in body weight [9] . Decrease in weight results in decrease in TDEE and in turn GQ. Low GQ slows the glucose metabolism in the body, thereby reducing triglycerides synthesis and fat accumulation. For thin people, who find it difficult to eat more, personal trainers advise to build muscle mass to bring up TDEE, by increasing weight and increased utilisation of glucose by muscles. This in turn increases GQ of the person increasing metabolic tolerability of the person to eat foods with higher glycaemic index resulting in more weight gain.

The GQ Mechanism

Glycaemic Quotient formula is having Total Daily Energy Expenditure in the numerator and Fasting Blood Sugar in the denominator [12] . TDEE depends upon BMR and activity factor [13] . So, value of GQ increases if the weight, height or physical activity increases and decreases with age and fasting blood sugar. If the person started practicing daily exercises, GQ increases. If the person reduced physical activity, started loosing weight or started following a low GI diet causing a decrease in the value of FBS, GQ decreases [12, 21] .

GQ as a Diagnostic and Prescriptive Tool

GQ is introduced as a tool to curate personalised diet for individuals. Both GQ and GI are expressed in scale from 0 to 100. Individuals are recommended to consume foods with glycaemic index value less than their GQ value. Diet can be prepared by selecting foods with appropriate GI from the GQ-GI chart as shown in Table 4. This allows individuals to plan diet for themselves and prevent onset of Diabetes. And also, this allows to curate diet plans for individuals who are undergoing treatment for lifestyle diseases like diabetes [11,21] and for whom weight loss or weight gain is being planned [18, 19] . As per derived stratified scoring of GQ, an individual's GQ score classify them according to metabolic risk they possess as shown in [14] . GQ also explains the reason for increased chance of diabetes in elderly patients than young patients due to decrease in GQ score with age. GQ depends on TDEE, which decreases with age. In cold seasons, activity of enzymes decreases, compared to hot seasons. Since metabolism depends upon enzyme activity, TDEE also tend to decrease with decrease in temperature. This further decreases the GQ score, recommending low GI foods in the cooler seasons and high GI foods in the summer seasons.

The "Safe Zone" If your GQ is 40, eating a food with a GI of 70 (like a donut) creates a "Metabolic Gap." This gap is where your body struggles to manage blood sugar, leading to insulin resistance, fat storage and increased diabetes risk. Stay in the Safe Zone by keeping Food GI < GQ.

Conclusion

Glycaemic Quotient with the GQ-GI chart (Table 4), as we discussed, provides an easy and individualized tool for diet planning and preparation. This helps dieticians, nutritionists and endocrinologists to plan diet, prevent metabolic dysfunction, lifestyle diseases, maintain healthy weight and ensure treatment progress. Individuals can search the GQ-GI chart to find appropriate foods that have GI value less than their GQ value and prepare personalised diet accordingly.

Elderly people tend to have low GQ due to low, and high metabolic risk. Low GQ people are having very high metabolic risk to develop diabetes.

Acknowledgement

AcknowledgementsAll the authors contributed equally to the research. All the tests were done at General Hospital, Ahwa Laboratory. Patients attending general OPD were surveyed through Questionnaire. The Superintend, OPD nurses and attendants, laboratory in charges and the laboratory staffs were essential and helpful in the study. Financial Support and SponsorshipNil.

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