Development and validation of a tool to assess Aahara shakthi (Abhyavaharana shakthi and Jarana shakthi) in Ayurveda and application of the tool to optimize prediction equation of Basal Metabolic Rate

INTRODUCTION

Metabolic diseases refer to a broad term that includes all diseases that result from disturbances in the body’s biochemical metabolism. One area of science that is beneficial for treating metabolic diseases is dietetics. Eating regular meals by paying attention to the calorie content and calculating the right amount of food for one’s individual needs is a foundational step toward preventing the onset of metabolic diseases. Estimation of BMR using prediction equations is a fundamental part of clinical dietetic practice, and it is crucial for determining total daily energy expenditure (TDEE) and overall caloric needs. The total daily energy expenditure (TDEE) is the number of calories an individual burns in a day. It is calculated by considering three factors,

1)    Basal Metabolic Rate (BMR): The energy used at rest to maintain basic physiological functions.

2)    Physical Activity: The calories burned through all forms of movement, including exercise and daily activities.

3)    Thermic Effect of Food (TEF): The calories burned during the digestion and processing of food, typically accounting for about 10% of total caloric intake.

Numerous published prediction equations are available to estimate BMR, with 248 different formulas being identified within the literature. The equations of Schofield, Henry, Mifflin–St Jeor, Harris–Benedict and Owen are widely used. BMR equations usually rely on body weight as the dominant predictor and also consider age, sex and height. Among all the prediction equation to estimate BMR, Mifflin–St Jeor is considered to be more accurate based on a previous comparative study conducted to evaluate the validity of prediction equations. However, this prediction equation neglects a critical aspect of individual physiology that is digestive capacity, or Aahara Shakthi, as emphasized in Ayurvedic literature. Aahara sakthi is one among the Dasha vidha pareeksha which is determined by two factors i.e *Abhyavahara Sakthi (*capacity of food intake)and Jarana Sakthi (capacity to digest the food).

Abhyavaharana Shakti is indicative of intake of food quantity, it differs from person to person and time to time and also according to moods and mental health. Jarana Shakti reflects the process of digestion, largely influenced by the characteristics of food and the condition of Agni.

In unhealthy individuals, while Abhyavaharana Shakti may be good, it can be influenced by other factors such as the timing of regular meals, the sight, taste, or aroma of food, as well as the presence of condiments and seasonings, or even the mere thought of food. Whereas, basal metabolic rate (BMR) is considered to increase after eating due to the thermic effect of food (TEF), which is the energy required to digest, absorb, and process nutrients from food. Although factors like meal size, food type, and age influence the thermic effect of food, it is calculated by multiplying the basal metabolic rate (BMR) by a constant value of 0.1 without considering the individual variation.

Since the status of digestion and food intake is likely to vary according to individual constitution, age, seasonal rhythm, and so on, it is important to accurately evaluate Aahara shakthi of an individual through an integrated approach which can further help in prevention of disease and promotion of health. Hence, this study aims to optimize the Mifflin–St Jeor equation by developing an integrated tool that incorporates Aahara shakthi (digestive capacity) into the calculation of energy requirements, thereby providing a more personalized assessment.

BACKGROUND AND RATIONALE

Metabolic diseases refer to a broad term that includes all diseases that result from disturbances in the body’s biochemical metabolism. It can be further distinguished as inherited and acquired metabolic diseases. Acquired metabolic diseases includes obesity, osteoporosis, and diabetes etc. Over the last decades, the incidence of many of these diseases has increased dramatically, becoming a significant epidemiological problem. It is estimated that one third of the world’s population is overweight or obese. In 2017, approximately 462 million people had type 2 diabetes, constituting 6.28% of the world’s population (the prevalence rate was 6059 cases per 100,000).

Metabolic diseases are caused by lifestyle changes, including reduced physical activity and unhealthy eating habits characterized by an imbalance between energy intake and energy expenditure. Effective prevention and early intervention strategies are vital for reducing the burden of metabolic diseases. Calculating calorie intake is one such strategy that can help individuals to prevent metabolic diseases. It allows for personalized nutrition intake, helping to manage conditions like insulin resistance or dyslipidaemia, which are risk factors for metabolic diseases.

Current energy requirement calculations are based on BMR, physical activity & thermic effect of food. Mifflin-St Jeor equation is one of the widely used prediction equation for calculating BMR which take into consideration of age, weight and height of an individual. But this equation does not consider individual variations in Aahara shakthi (digestive capacity). It is definite that, poor digestion can significantly affect nutrient absorption and overall energy utilization. Ayurveda proposes that Aahara shakthi plays a vital role in digestive health, influencing metabolic processes and nutrient assimilation. Incorporating this dimension into the Mifflin-St Jeor equation could enhance or optimize energy requirement assessments and there by address the gap in existing methodologies.

Therefore, this study aims to develop an optimized, and reliable prediction equation to be used in clinical dietetics by developing and validating a tool to assess Aahara shakthi (Abhyavaharana shakthi and jarana shakthi) and further by incorporating a correction term into the Mifflin-St Jeor equation based on the obtained score. This might help in personalizing the calculation of energy requirement assessments by providing a structured and empirical method for estimating the calorie intake.

OBJECTIVES

Primary:

1.     To develop and validate a tool for assessing Aahara Shakthi (Abhyavaharana shakthi and Jarana shakthi) of an individual and to introduce a correction term into the Mifflin-St Jeor equation based on the study for effective use of Basal Metabolic Rate in Ayurveda Dietetics

Secondary:

1.     To validate the tool by comparing it with selected objective parameters such as thyroid profile and serum ghrelin.

2.     To establish the agreement of the developed tool by panel diagnosis.

3.     To study the relation between Aahara shakthi and Prakrithi using the developed tool.

4.     To evaluate the validity of the optimized prediction equation of BMR by comparing it with BMR measured by an Indirect calorimeter or Body composition analyser.

MATERIAL AND METHODS

Stage - I: Preliminary stage

Defining abhyavaharana shakthi, jarana shakthi and factors to be considered for its assessment through

Literature review.

Consensus method with experts including clinicians or experienced practitioners,experts in Ayurveda and modern nutrition, subject experts in tool development and academicians.

Stage – II: Tool Development and Validation

I.      Item generation:

·       Through literature review and consensus method

·       Identifying the domains

·       Framing questions and sub-questions for the assessment of each domain.

II.    Selection of the type of response scales

·       Depending on the need, response for each item will be decided (Dichotomous response or Likert’s scale will be used)

III.  Pre-testing questionnaire:

·       After preparing the initial draft, the questionnaire will be sent to experts for assessing the theoretical construct and to ensure the relevance and accuracy of the items.

·       The draft will be examined by the experts for its,

1.     Face validity

2.     Content validity

·       Cognitive interview will be done to assess the respondent and interviewer friendliness of the questionnaire regarding its comprehension, retrieval, and judgment.

IV.  Reliability assessment      :

The stability or consistency of the tool will be assessed by:

·       Test-Retest Reliability (intraclass correlation coefficient/Spearman rank correlation coefficient/ Pearson correlation coefficient)

·       Internal consistency (Cronbach’s alpha/ split-half reliability)

V.    Item Revision.

·       If any of the items are found to have poor face and content validity or low reliability then the respective items will be revised or deleted to refine the tool.

Stage- III: Empirical Evaluation

·       Application of the validated tool in field trials (large sample study)

·       Sample size will be calculated based on sample to variable ratio. The ratio of variable to sample has to be 5:1(Bryant and Yarnold, 1995, David Garson ,2008)

·       Tool will be tested for:

Construct validity (factorial validity)

·       Factorial validity is a sub-type of construct validity. It assesses the inter-correlation between questions. Principal component analysis will be used to evaluate the factorial validity. The steps in principal component analysis includes:

a)     Ascertaining the suitability of factor analysis

b)    Extraction of factors

c)     Factor rotation

·       Statistical data would be computed through statistical package for social sciences (SPSS), Software version 26.0 by IBM (Chicago, Illinois, US)

Stage- IV: Diagnostic test assessment

The new tool will be evaluated for its clinical validity through diagnostic accuracy studies. These studies are prototypes of criterion validity. Establishing criterion validity involves correlation between the new tool and another instrument that is considered as an accurate indicator. Several methods could be adopted to establish criterion validity. This includes validating the test result in relation to other relevant clinical characteristics

Thus, 4th stage of the study includes the following assessments:

1.     Comparative Analysis by comparing the questionnaire results with selected objective parameters such as thyroid profile and serum ghrelin to validate the tool’s accuracy and relevance.

·       Ghrelin is a hormone with well-investigated functions concerning body composition, energy homeostasis and feeding behaviour in humans

·       Basal metabolic rate is mostly determined by the thyroid hormones T3 and T4, which respond to thyroid-stimulating hormone (TSH).

2.     Panel diagnosis will be done to establish the agreement of the developed tool (clinical assessment of Aahara Shakthi by experienced practitioners).

·       Kappa’s agreement (Cohen’s Kappa) and percentage (%) agreement will be applied to identify the relation.

3.     The relation between Aahara shakthi and Prakrithi will be studied using the developed tool. Assessment will be done by Chi-Square test.

4.     Regression analysis will be done to find the correction factor.

5.     The validity of the optimized prediction equation of BMR will be evaluated by comparing it with BMR measured by Indirect calorimeter or Body composition Analyser, and an assessment will be done by Bland-Altman Analyses.