IES85703Y1 - A computer implemented method and system for generating dietary advice output - Google Patents

Abstract

ABSTRACT The present invention relates to a computer implemented method and system for generating and providing dietary advice output to a user. The method initially comprises receiving lifestyle and dietary inputs from a user. A prescription calorific intake is determined and a diet and nutrition (DAN) score is computed from the dietary advice is generating and displayed to the user as a user-friendly and individualised output. The present invention provides a user interface which is simple to navigate for both users and health providers, allowing them to engage in a patient- led, non-labour intensive collaborative effort to improve overall health outcomes.

Description

Introduction The present invention relates to a computer implemented method and system for generating dietary advice output.

Background Art The maintenance of a good balanced diet is extremely important to human health and wellbeing.

However, a significant majority of the population are unwilling or unable to regularly engage with health professionals in this area, with the effect that the availability of personalised meaningful dietetic advice tends to be limited. Moreover, there are significant difficulties encountered in monitoring the diet, lifestyle and clinical progress of patients in the community setting. A further problem exists that even when dietetic advice is provided great difficulty is often encountered by the public in deciphering the relative importance of individual healthy eating guidelines given. Difficulties are also encountered in providing accurate, individualised guidance to users on appropriate food portion size, a key determinant of diet-related health.

Accordingly, there is a need for a tool having functionallties required of a web-based clinical assessment and intervention tool allowing for a patient-led, non-labour intensive collaborative effort to improve overall health outcomes.

It is an object of the present invention to provide a computer implemented system and method for generating dietary advice which goes at least someway towards alleviating the above problem and/or which will provide the public and/or industry with a useful alternative.

It is acknowledged that the tenn ‘comprise’ may, under varying jurisdictions be provided with either an exclusive or inclusive meaning. For the purpose of this specification, and unless otherwise noted explicitly, the term comprise shall have an inclusive meaning - i.e. that it may be taken to mean an inclusion of not only the listed components it directly references, but also other non—specified components. This rationale should aiso be used when the terms ‘comprised’ and/or ‘comprising’ are used.

Further aspects of the present invention will become apparent form the ensuing description which is given by way of example only.

Statements of Invention According to the invention, there is provided a computer implemented method of providing dietary advice output to a user, the method comprising the steps of: i) receiving a stream of lifestyle, anthropometric and clinical data inputs from the user; ii) using the lifestyle, anthropometric and clinical data inputs to determine a prescription calorific intake for the user; iii) receiving a stream of dietary inputs from the user; iv) computing a diet and nutrition (DAN) score based on the prescription calorific intake and the user's dietary inputs, and v) generating and displaying prioritised dietary advice output based on the SCOTS.

In another embodiment of the invention, the stream of lifestyle inputs, anthropometric inputs, clinical inputs and dietary inputs correspond to responses provided by the user to a plurality of lifestyle, anthropometric, clinical and dietary related questions presented to the user on a graphical user interface of a computing device.

In another embodiment of the invention, the method comprises the further step of assigning each dietary related question a weighting.

In another embodiment of the invention, the method comprises the further step of associating with each dietary related question one of a plurality of dietary domains selected from a group including but not limited to meal pattern, fruit and vegetables, refined extrinsic sugars, oily fish, alcohol, salt/sodium and fluid.

In another embodiment of the invention, the method comprises the further step of configuring the weighting for each dietary related domain, question and answer so that it is modifiable.

In another embodiment of the invention. the method comprises the further step of configuring the dietary related domains, questions and answers, and the lifestyle, anthropometric and clinical related questions so that they are adapted to be added, modified or deleted by an administrator.

In another embodiment of the invention, the method comprises the further step of storing the dietary data inputs, anthropometric data inputs, clinical data inputs and lifestyle data inputs in a computer database or storage means.

In another embodiment of the invention, the method comprises the further step of adapting the database so that it is accessible to facilitate viewing of the stored data by a doctor of the user.

In another embodiment of the invention, the method comprises the further step of creating a database of user lifestyle, anthropometric, clinical and dietary inputs and facilitating statistical analyses of these user inputs by an administrator at the individual and group level.

Preferably, the dietary questions provide users with selectable food portion graphic images for assessing user portion sizes.

Preferably, the dietary advice output includes visual/printed food portion graphic images for displaying assigned food portion size advice to users.

In another embodiment of the invention, the method comprises the step of providing a dynamic total calorific prescription to users, which is automatically adjusted after weight loss to prevent inappropriate over-restriction of dietary intake.

In another embodiment of the invention, the method comprises the step of prioritising dietary advice domains dynamically based on domain scores and weightings, to enable users to decipher the personal importance of the dietary guidelines recommended.

Preferably, the method comprises the step of generating a dynamic "dietary training module", with new priorities for dietary intervention highlighted as previous recommendations are addressed. in another embodiment of the invention, the method comprises the step of generating a novel composite score for alcohol intake behaviour, based on the combination of weighted scores from three separate parameters, including weekly intake amount, frequency of intake and amount consumed per drinking occasion. Such a score will enable users to assess their alcohol consumption risk status.

In another embodiment of the invention, the method comprises the step of creating a health surveillance relational database of user lifestyle, anthropometric, clinical and dietary data, alongside demographic, socio-economic, clinical outcome, ethnic and other personal data entered via an extensible user sign-up page.

Preferably, clinicians can append clinical data to users’ other data to extend this relational database.

Preferably, the method is executable as a software application which is adapted to be accessed by users via a website on the Internet. in another aspect of the invention, there is provided a computer implemented system for providing dietary advice output to a user, the system comprising: i) means for receiving a stream of lifestyle, anthropometric and clinical data inputs from the user; ii) means for using the lifestyle, anthropometric and clinical data inputs to determine a prescription calorific intake for the user; iii) means for receiving a stream of dietary inputs from the user; iv) means for computing a diet and nutrition (DAN) score based on the prescription calorific intake and the user's dietary inputs, and v) means for generating and displaying dietary advice output based on the SCOFG.

In another embodiment of the invention, the system comprises means for presenting a plurality of lifestyle, anthropometric, clinical and dietary related questions to the user on a graphical user interface of a computing device, and means for receiving and transmitting a stream of lifestyle, anthropometric and clinical inputs and dietary inputs corresponding to responses provided by the user to the questions.

In another embodiment of the invention, the system comprises means for assigning each dietary related domain, question and answer a weighting.

In another embodiment of the invention, the system comprises means for associating with each dietary related question one of a plurality of dietary domains selected from a group including but not limited to meal pattern, fruit and vegetables, refined extrinsic sugars, oily fish, alcohol, salt/sodium and fluid. in another embodiment of the invention, the system comprises means for configuring the weighting for each dietary related domain, question and answer so that they are modifiable.

In another embodiment of the invention, the system comprises means for configuring the dietary related domains, questions and answers, and the lifestyle, anthropometric and clinical related questions so that they are adapted to be added, modified or deleted by an administrator.

In another embodiment of the invention, the system comprises means for storing the dietary data inputs, anthropometric data inputs, clinical data inputs and lifestyle data inputs in a computer database or storage means.

In another embodiment of the invention, the system comprises means for adapting the database so that it is accessible to facilitate viewing of the stored data by a doctor of the user.

In another embodiment of the invention, the system comprises means for creating a database of user lifestyle, anthropometric, clinical and dietary inputs and facilitating statistical analyses of these user inputs by an administrator at the individual and group level.

Preferably, the system comprises means for generating dietary questions which provide users with selectable food portion graphic images for assessing user portion sizes.

Preferably, the system comprises means for generating dietary advice output which includes visuallprinted food portion graphic images for displaying assigned food portion size advice to users. in another embodiment of the invention, the system comprises the means for providing a dynamic total calorific prescription to users, which is automatically adjusted after weight loss to prevent inappropriate over-restriction of dietary intake.

In another embodiment of the invention, the system comprises the means for prioritising dietary advice domains dynamically based on domain scores and weightings to enable users to decipher the personal importance of the dietary guidelines recommended.

Preferably, the system comprises the means for generating a dynamic "dietary training module" intervention highlighted as previous recommendations are addressed. with new priorities for dietary In another embodiment of the invention, the system comprises means for permitting clinicians to automatically screen their database of registered patients/users at periodic intervals and to highlight users who are failing to make clinician defined clinicai (e.g. anthropometric) progress or behavioural progress with their dietary advice. in another embodiment of the invention, the system comprises means for automatically generating tailored e-mail or mobile text aierts from the clinician to high priority patients, enhancing their dietary compliance. in another embodiment of the invention, the system comprises means for generating a novel composite score for alcohol intake behaviour, based on the combination of weighted scores from three separate parameters, including weekly intake amount, frequency of intake and amount consumed per drinking occasion.

In another embodiment of the invention, the system comprises means for creating a health surveillance relational database of user lifestyle, anthropometric, clinical and dietary data, alongside demographic, socio-economic, clinical outcome, ethnic and other personal data entered via an extensible user sign-up page. ' Preferably, clinicians can append clinical data to users‘ other data to extend this relational database.

Preferably, the system is accessed by users via a website on the Internet.

According to a further aspect, there is provided a computer program product stored on a computer readable medium which when executed on a computer is adapted to perform the method steps above.

The present invention is a computer implemented web based tool that has been developed to assess users combined dietary risk of several common chronic diseases including cardiovascular disease (CVD), cancer, obesity, diabetes mellitus and osteoporosis. To assess overall health risk, algorithms have been developed which are deployed as a web based software application. These algorithms divide the diet into a number of weighted domains. These weightings have been developed de novo and reflect the relative importance of each of the domains to a number of prominent chronic diseases.

The method of the present invention is adapted to accommodate comparisons between different versions of an "ideal" diet according to the user’s own individual lifestyle, anthropometric and clinical characteristics, such as age, weight, activity level, total energy expenditure and clinical weight status. This individualised comparison facility allows the user’s dietary data to be compared specifically against the most suitable diet for them to assess “dietary risk”.

The present invention also generates user-friendly, individualised dietary advice output for users. By implementing this advice, users can improve their diet and nutrition (DAN) score, eliciting weight loss and improvements in other clinical risk factors such as blood pressure and serum lipid levels, as long as these changes are maintained. Hence, those with a higher score should be less susceptible to chronic diseases and their antecedent risk factors than those whose dietary assessment is less favourable.

The present invention fulfils all of the functionalities required of a web-based clinical assessment tool. It is based on robust scientific research and sound algorithmic formulae, which produce safe, reliable and effective guidelines. In this way, it addresses the significant gap in community-based dietetic services. The present invention also provides a user interface which is simple to navigate for both users and health providers, allowing them to engage in a patient-led, non-labour intensive collaborative effort to improve overall health outcomes. Such patient empowerment is fast becoming the cornerstone of the “health-driven” public health services in all developed countries.

The present invention provides a method and system which weights dietary domains and questions in relation to the a prion’ relative importance of their constituents to health status, specifically as this relates to the avoidance of the chronic degenerative diseases obesity, cardiovascular disease, diabetes mellitus, cancer, and osteoporosis and their antecedent risk factors. Further, it encompasses an "intelligent" dynamic system which facilitates the refinement of these algorithmic dietary domain and question weightings based on post hoc analyses of users‘ dietary data against their clinical outcome data, to enhance the predictive dietary risk models embodied in the system.

The methodology of the present invention may be embedded in a web-enabled software application designed to run on the industry standard open-source LAMP (Linux, Apache, MySQL, PHP) platform. Most of the application is coded in PHP although client-side Javascript, AJAX, Flash and content management language (for non-assessment areas) have been used where appropriate.

The software has additionally been developed to enable refinement of the algorithm based on the health outcomes of users in relation to their reported intake. in this way it will ‘‘learn" and develop as the number of users increases. Because the present invention has been developed for the web, this enables users to access their accounts and use the software from any networked computer.

This implementation of the present invention permits the simultaneous collection of dietary, lifestyle, anthropometric and clinical data which can be captured collectively in one relational database. This will enable nutrition and health research aimed at establishing the relative role of these dietary elements in disease risk to be carried out much more efficiently and reliably than at present.

In a further aspect of the invention, there is provided a method of treating a patient to reduce risk of chronic diseases, the method comprising: determining a total energy prescription for achieving or maintaining alhealthy body mass of said patient in accordance with said patient’s basal metabolic rate (BMR), daily physical activity level (PAL) and weight status score (WSS); ‘ identifying types and amounts of nutritional sources for said patient; monitoring said patient to determine changes and/or deviations from said total energy prescription; and recommending changes in at least one of said types and amounts of nutritional sources as needed for achieving or maintaining said healthy body mass of said patient. V Preferably, detennining said total energy prescription includes calculating a function of (BMR * PAL) — a predetermined value associated with said WSS.

Preferably, the method further comprises: determining a WSS range associated with said WSS amongst a plurality of WSS ranges, said WSS range associated with an energy deficit value; and selecting said energy deficit value as said predetermined value associated with said WSS.

Preferably, the method further comprises obtaining a weight metric, a height metric, a waist circumference metric, an age metric, a gender metric and physical activity intensity levels of predetermined time periods of at least one day for said patient.

Preferably, the method further comprises determining said patient’s BMR in accordance with said age metric, said gender metric and said weight metric.

Preferably, the method further comprises determining said patient’s PAL based on said physical activity intensity levels of predetermined time periods of at least one day.

Preferably, determining said patient’s PAL includes: obtaining a physical activity intensity level for each predetermined time period of a first day and a physical activity intensity level for each predetermined time period of a second day; determining a first average physical activity intensity level for said first day and a second average physical activity intensity level for said second day; and calculating said patient’s PAL according to a weighted average of said first average intensity level and said second intensity level.

Preferably, the method further comprises determining said patient’s WSS.

Preferably, determining said WSS includes: determining a body mass index (BMI) score for said patient in accordance with said weight metric and said height metric; determining a waist circumference score for said patient in accordance with said waist circumference metric; and calculating said WSS in accordance with said BMI score and said waist circumference score.

Preferably, calculating said WSS includes calculating a function of BMI score + waist circumference score. in a still further aspect of the invention, there is provided a system to estimate energy requirements of a user over a network, said system comprising: a basal metabolic rate (BMR) module configured to determine a basal metabolic rate in accordance with an age metric, a gender metric and a weight metric of said user; a physical activity level (PAL) module configured to determine a daily physical activity level for said user based on physical activity intensity levels of predetermined time periods of at least one day; a weight status score (WSS) module configured to determine a weight status score in accordance with said weight metric, a height metric and a waist circumference metric of said user; and a total energy prescription module configured to calculate a recommended total energy intake for said user in accordance with said basal metabolic rate, said physical activity level, and said weight status score.

Preferably, said total energy prescription module is configured to calculate a function of (said basal metabolic rate * said physical activity level) - a predetermined value associated with said weight status score.

Preferably, said WSS module is configured to: determine a weight status score range associated with said weight status score amongst a plurality of weight status score ranges, said weight status score range associated with an energy deficit value; and select said energy deficit value as said predetermined value associated with said weight status score.

Preferably, the system further comprises a communication module configured to: receive over said network a weight metric, a height metric, a waist circumference metric, an age metric, a gender metric and physical activity intensity levels of predetermined time periods of at least one day for said user; and transmit over said network said total energy prescription.

Preferably, said communication module is further configured to receive a physical activity intensity level for each predetermined time period of a first day and a physical activity intensity level for each predetermined time period of a second day.

Preferably, said PAL module is further configured to: determine a first average physical activity intensity level for said first day and a second average physical activity intensity level for said second day; and calculate said patient's daily physical activity level according to a weighted average of said first average physicai activity intensity level and said second average physical activity intensity level.

Preferably, said WSS module is further configured to: determine a body mass index score for said user in accordance with said weight metric and said height metric; determine a waist circumference score for said user in accordance with said waist circumference metric; and calculate said weight status score in accordance with said body mass index score and said waist circumference score.

Preferably, said WSS module is further configured to calculate a function of said body mass index score + said waist circumference score.

In a yet further aspect of the invention, there is provided an apparatus to estimate total energy prescription of a user, said apparatus comprising: a basal metabolic rate (BMR) module configured to determine a basal metabolic rate in accordance with an age metric, a gender metric and a weight metric of said user, a physical activity level (PAL) module configured to determine a daily physical activity level for said user based on physical activity intensity levels of predetermined time periods of at least one day; a weight status score (WSS) module configured to determine a weight status score in accordance with said weight metric, a height metric and a waist circumference metric of said user; and a total energy prescription module configured to calculate a recommended total energy intake for said user in accordance with said basal metabolic rate, said physical activity level, and said weight status score.

Preferably, said total energy prescription module is configured to calcuiate a function of (said basal metabolic rate * said physical activity level) - a predetermined value associated with said weight status score.

Preferably, said WSS module is configured to: determine a weight status score range associated with said weight status score amongst a plurality of weight status score ranges, said weight status score range associated with an energy deficit value; and select said energy deficit value as said predetermined value associated with said weight status score.

Preferably, the apparatus further comprises: an input module configured to receive a weight metric, a height metric, a waist circumference metric, an age metric, a gender metric and physical activity intensity levels of predetermined time periods of at least one day for said user; and a display module configured to display said total energy prescription.

Preferably, said input module is further configured to receive a physical activity intensity level for each predetermined time period of a first day and a physical activity intensity level for each predetermined time period of a second day.

Preferably, said PAL module is further configured to: determine a first average physical activity intensity level for said first day and a second average physical activity intensity level for said second day; and calculate said patient’s daily physical activity level according to a weighted average of said first average intensity level and said second intensity level.

Preferably, said WSS module is further configured to: determine a body mass index score for said user in accordance with said weight metric and said height metric; determine a waist circumference score for said user in accordance with said waist circumference metric; and calculate said weight status score in accordance with said body mass index score and said waist circumference score.

Preferably, said WSS module is further configured to calculate a function of said body mass index score + said waist circumference score.

Detailed Description of the Invention The invention will be more clearly understood from the following description of some embodiments thereof, given by way of example only, with reference to the accompanying drawings, in which: Fig. 1 is a flow diagram showing steps in a computer implemented method for generating dietary advice according to the present invention; Fig. 2 is a block schematic showing the generation of a prescription calorific intake according to the present invention; Fig. 3 is a screen shot of a physical activity matrix used to collect physical activity data from a user; Fig. 4 is a table of body mass index (BMI) ranges and associated scores; Fig. 5 is a table of waist circumference ranges and associated scores; Fig. 6 is a table outlining the dietary intervention required based on the weight status SCOTS .

Figs. 7, 8 and 9 are tables showing dietary domains which are associated with each dietary question presented to a user and their associated clinical disorders; Fig. 10 is a screenshot of a graphical user interface presenting questions to be answered by users; Fig. 11 is a screenshot showing a summary of dietary status and diet and nutrition score calculated; Fig. 12 is a screenshot showing results and dietary advice recommendations; Fig. 13 is a screenshot illustrating an interface through which a user links to a health providers or doctors account; Fig. 14 is a screenshot illustrating a health providers view of all users registered to its account, and Figs. 15 and 16 are screenshots illustrating an administration section for the present invention.

With reference to Fig. 1, there is shown a flow diagram of the steps in a computer implemented method for generating dietary advice. In a first step 1, a user submits a plurality of lifestyle and anthropometric data inputs which, at step 2, are used to generate a prescription calorific intake for the user.

Fig. 2 is a block schematic showing the use of the lifestyle, anthropometric, age and gender data inputs to generate the prescription calorific intake. The user initialiy provides inputs including ageldate of birth 20a, gender 20b, weight 20c, height 20d and waist circumference 20e in either imperial (stone and lbs, feet and inches) or metric (kg, m, cm) measurements using drop down option boxes. The weight data 20c is used along with the age/date of birth 20a and gender data 20b given to calculate the basal metabolic rate (BMR) 21 using the Schofield equation shown below. In this way, BMR 21 is estimated for each participant based on their age, gender and seIf—reported bodyweight.

Schofield Equation for the Estimation of Basal Metabolic Rate (BMR) Key: W = Body weight in Kilograms.

Men: - 17 years BMR=17.7xW+657 18 -29 years BMR= 15.1 xW + 692 —59yearsBMR=11.5xW + 873 60-74 years BMR = 11.9 x W + 700 75+ years BMR = 8.4 x W + 8 Women: - 17 years BMR = 13.4 xW + 692 18 — 29 years BMR = 14.8 x W + 487 — 59 years BMR = 8.3 x W + 846 60-74 years BMR = 9.2 x W + 68? 75+ years BMR = 9.8 x W + 624 In order to estimate total energy expenditure (TEE 23), the BMR 21 calculated from the Schofield equation is multiplied by an average physical activity level (PAL) factor 22. This daily PAL factor—22 is estimated by averaging a series of 15 PAL factors for 24 x 1 hour periods over the course of the day. In other words, the person will estimate how active they are for each one hour period of the day.

Fig. 3 is a graphical representation of a physical activity matrix 30 which is used to gather the inputs from a user in order to calculate the PAL factor 22 referrred to in Fig. 2. In the instance shown, it is provided as a flash screen in which an activity level (from ‘I — 15) may be selected by a user. The physical activity matrix 30 is thus a graphical interface presented on a screen of a computing device comprising a plurality of check boxes 31 which are arranged as a matrix and are based on estimated metabolic equivalent scores (METs) for different activities from Ainsworth et al.’s Compendium of Physical Activities (2000). The MET estimations from this publication have been categorised into 15 novel physical activity levels. These 15 levels have been incorporated into a “flash screen” in which users scroll over the matrix to estimate their hourly activity levels for a weekday and a weekend day. For each level, the mid-interval value is used to estimate the user's physical activity level for that hour long period. MET data from the completed physical activity matrix is used to estimate a final figure for the user's average physical activity level (PAL).

With reference again to Fig.2, the PAL factor 22 is then applied to the outcome result of a standard equation (Schofield, 1985) to estimate the user's overall total energy expenditure (TEE) 23. The use of a flash screen to estimate hourly activity levels in this way, the processing of this data to produce the final PAL figure and the application of this derived figure to BMR estimates derived from the Schofield equation in order to estimate total energy expenditure are steps which overcome the significant difficulty previously encountered in PAL and TEE estimation with free living subjects. This process is repeated to describe the typical physical activity level for each one hour "chunk" of an average weekend day.

The average PAL for a typical week will be calculated using the formula: [(Average weekday PAL x 5) + (Average weekend PAL x 2)]I7 The average PAL figure 22 for the entire week is multiplied by the BMR 21 derived by the Schofield equation, to yield the overall average total energy expenditure (TEE) 23 of that person each day (usually ~2000-2500 kCa|s/day). This average energy expenditure is equal to the energy intake required to maintain bodyweight at current levels.

The question of whether weight maintenance or weight loss is required is next addressed.

At this point, the person’s weight 20c and height 20d are both known. These data are used to automatically derive the person's body mass index (BMI) 24 using the following equation: BMI = Weight in kgsl(Height in metres)2 However, because BMI 24 only reflects weight for height, rather than why the person is ovenlveight, the person’s waist circumference measurement 20e must now be used to further qualify their weight status. In other words, the waist measurement is used to indicate whether the person has a high BMI 24 due to excess fat around their mid-section (high clinical risk), as opposed to say those who might just have a high bodyweight due to their large (stocky) build (no additional risk).

Weight status 25 is assessed by means of both body mass index (BMI) 24 and waist circumference 20e. The BMI 24 ranges are scored according to the table shown in Fig. 4.

Weight status is also defined in terms of waist circumference cut-off points. Here, scores will be allocated based on the criteria shown in Fig. 5. Overall, weight status score (WSS) is defined using these two scores. Those scoring less than the low risk threshold will require weight loss advice, while those achieving a score above this low risk threshold should aim to maintain weight at current levels. Fig. 6 is a table outlining the dietary interventions required based on WSS-assessed risk.

The methodology described thus estimates users‘ weight status score (WSS) and is based on two measures of ovenlveight and obesity, namely body mass index (BMI) and waist circumference. The WSS algorithm generated places emphasis on waist circumference status, reflecting the greater clinical risk associated with increased waist circumference than BMI in the recent literature. The two parameters are combined in such a way as to capture those who are genuinely oveniveight (i.e. increased weight due to fat tissue), while disregarding those whose high BMI is not conferred by excess central adiposity of fat tissue (e.g. those of stocky build). This novel WSS algorithm therefore overcomes the problem of mis-classifying the latter group as appropriate candidates for weight loss intervention. The WSS algorithm also provides an estimation of the degree of overweight or obesity.

The TEE 23 and WSS 25 obtained are then used to generate a prescription calorific intake or model diet for the user.

In the instance shown, there are six versions of prescription calorific intakes which differ in their overall calorie content in a “model" diet. These versions are 1200kCa|s, indicated generally by the reference numeral 26a, 1500kCa|s, indicated generally by the reference numeral 26b, 1800kCals, indicated generally by the reference numeral 26c, 2100kCals, indicated generally by the reference numeral 26d, 2400kCa|s, indicated generally by the reference numeral 26s and 2700kCa|s, indicated generally by the reference numeral 26f.

The allocation of one of these calorie specific versions of the DAT to participants is now described.

For those requiring moderate weight loss advice according to their weight status score (see Fig. 6), a calorie deficit of ~500kCaIs per day below weight maintenance requirements is sought. Hence, for a respondent with a total energy requirement of 2335 kCals/day and a "slight" or “moderate" risk designation based on WSS, this person will have a prescription calorific intake of about 1835kCals, and will therefore be directed into the 1800kCa| prescription 26c. For a similar respondent with a weight status score indicating “minimal” or “low" risk, this person's diet should provide about 2200-2400 kCa|s/day, so that this person will be directed to the 2400kCa|s prescription 26e.

For users who require significant weight loss according to their weight status score (see Fig. 6), that is, those with a weight status score indicating “high” or “very high” risk, then a larger calorie deficit should be sought. Hence, a user with a total daily energy requirement of 2120kCa|s for weight maintenance and a very low weight status score will be prescribed the 1200kCal prescription 26a, as this calorie intake comes closest to their estimated weight maintenance requirement minus their greater calorie deficit.

This allocation of the correct prescription caiorific intake version requires that respondents be appropriately "streamed” to the version which is most suitable for their needs. In the case of those seeking moderate weight ioss, the version prescribed is that version which is immediately below their total energy requirement for weight maintenance minus 500kCa|s, unless this prescription is more than 100kCa|s below this point. Otherwise, the version which is immediately above the total energy requirement minus 500kCa|s is used.

For example, if a person has a total energy requirement of 2200kCa|s for weight maintenance and their weight status score indicates that they require ~500kCa| deficit for moderate weight loss, the question arises as to whether the 1500kCals prescription 26b or the 1800kCa|s prescription 260 is more appropriate. In this case, because the 1500kCa|s version is more than 100kCa|s below the 1700kCa|s estimated ideal prescription, the person is prescribed the 1800kCa| prescription.

In dealing with those who require significant weight loss, a larger calorie deficit beiow total daily calorie requirements is required. Here, the same principle will apply, with the person prescribed the prescription calorific intake which is immediately below their total energy requirement for weight maintenance minus this larger deficit, unless this version is more than 200kCa|s below this point. Where this is the case, the version immediateiy above the total energy requirement minus their larger deficit is used.

Hence, the appropriate prescription calorific intake which is allocated to the person wilt depend not just on their own characteristics in terms of requirement for weight loss. The way in which the most appropriate version is selected will aiso depend on whether the person requires moderate or significant weight loss, with those seeking only moderate weight loss treated less aggressively (lower likelihood of prescription calorific intake significantly below their total energy requirement minus 500kCals) than those requiring significant weight loss.

For those seeking to maintain weight, the prescription calorific intake which is closest to their estimated total energy requirement either above or below will be given. importantly, those who are seeking either moderate or significant weight loss can be directed to return to the site at least every two weeks, entering their new weight and waist circumference measurements each time, so that they will be automaticaliy re-assigned a less stringent dietary prescription once weight loss is achieved. in other words, as their weight loss progresses, their weight status score will improve and they will move from the "significant weight loss required" category to the "moderate weight loss required" category, hence being prescribed a smaller calorie deficit version of the DAT.

Unlike other dietary assessment software applications which base ideal portion size estimations on an assumed daily energy requirement of ~2000kCals, the present invention employs scientific equations to estimate the user’s precise daily energy requirement. The user’s inputted dietary data are then compared against the dietary template which most closely matches their requirements, from a choice of six possible options. In so doing, this software overcomes the previous difficulties encountered in providing accurate, individualised guidance to users on appropriate portion size, a key determinant of diet-related health. Additionally, a range of food portion size images are displayed to the user alongside the related dietary question during the dietary assessment, to aid portion size estimation by users. An image depicting the precise portion size of that food recommended to the user is subsequently displayed to the user in the dietary advice module, and in their printed dietary advice. By explicitly describing users‘ recommended portion sizes graphically, this overcomes the significant ambiguity of portion size selection which has compromised the effectiveness of previous dietary software.

With reference again to Fig. 1, at step 3, a stream of dietary inputs from the user are received once the prescription calorific intake has been determined. The dietary inputs are received from a user in response to a plurality of dietary related questions presented to the user on a graphical user interface of a computing device. Each dietary related question is assigned a weighting and is associated with one of a plurality of dietary domains shown in Figs. 7 to 9. Within each of these domains, a series of simple questions, determine the user’s sub-score for that domain.

Fig. 10 is a screenshot of questions relating to alcohol consumption being presented for users to answer. Alcohol intake quantities are also demonstrated and the units contained in typical types of alcoholic drinks explained using the images 32 so that users are able to accurately estimate their alcohol intake patterns in terms of units consumed. The section of the dietary algorithm which refers to alcohol intake attributes scores based on three parameters, namely total intake per week, number of drinking occasions per week and typical intake per drinking occasion. The relative importance of each of these parameters to health is reflected in the score attributed to each, and these scores are ultimately combined to provide a novel overall risk score for alcohol consumption. This feature overcomes the ambiguity of alcohol-related public health guidelines by combining these discrete elements into one score, and providing explicit guidelines to the user based on each of the parameters measured.

Referring now to step 4 in Fig. 1, these sub-scores for each domain are ultimately added together at the end of the assessment process to generate an overall dietary score, with 100% representing the ideai. Accordingly, all of the questions taken together carry a combined score of 100%. The generation of this score allows a broad overview of the users “dietary risk” based on the answers provided. Those who achieve high scores will be less likely to succumb to the chronic disorders cited previously, than those who achieve lower scores. These discrete nutritional/dietary elements have been “scored” based on their relative importance to a number of chronic disorders which occur with high prevalence in developed countries. The formulation of the user's dietary risk score using these algorithms is also novel. These algorithms overcome the difficulty encountered by the public in deciphering the relative importance of individual healthy eating guidelines.

The dietary algorithms have also been designed to be adaptable based on user outcomes. By placing dietary input data against clinical outcome measures such as weight and waist circumference, blood pressure, blood lipids (or others), post-hoc regression analyses will enable the dietary algorithm to be further refined to emphasise the domains most associated with improvements in clinical status. For example, if increased fruit and vegetable intake is seen to elicit greater than anticipated improvements in a number of clinical parameters, its weighting in the dietary algorithm may be revised upwards to reflect this, with the new algorithm always reverting or normalising to a maximum score of 100 (96). In this way, an “intelligent system” which "|eams” from analysis of user data has been created. This novel functionality addresses the issue of rigidity encountered with other systems, where guidelines generated for users rely on a prion’ assumptions regarding the most appropriate dietary interventions.

At step 5 of Fig. 1, users enter the advice section of the present invention. As shown in Fig. 11, in this section they are presented with a summary of their dietary status, indicated generally by the reference numeral 40, as reported on the dietary assessment questions, as well as their diet and nutrition (DAN) score, indicated generally by the reference numeral 42. While the advice section shown above gives a brief summary of the user's overall dietary intake status, it also prompts the user to view their "Detailed Results and Recommendations”. This section goes through each of the various dietary domains reminding the user of their response to each of the dietary assessment questions and providing explicit guidelines on what changes they should make to improve their Diet and Nutrition (DAN) score, and hence ultimately improve their health outcome. An example showing part of the detailed results and recommendations is shown in Fig. 12.

A novel prioritisation process has also been developed which orders the dietary domains in the advice section, based on their relative importance and the user's domain score. This therefore constitutes a dynamic "training module", where users will be presented with new dietary priorities as they address issues previously highlighted and re-visit the site.

Fig. 13 is a screenshot illustrating the interface through which a user links to the GPs account. Fig. 14 is a screenshot illustrating the interface through which a GP views all of the users registered under that doctor.

The present invention also provides a “Doctor” section which, allows clinicians to register and generate unique coded tokens which can then be distributed to patients to enable them to access the site. in this way, the clinician develops a cohort of patient users, whose archived diet and lifestyle input data are accessible by their doctor. Alternatively, the user/patient may generate a unique token which can be handed to their GP. Once registered under the Doctor domain, the GP can then key in this reference token to gain access to their patient’s archived diet and lifestyle data. Each user is thus provided with an account which can be linked to that of their general practitioner (GP) or health provider.

As referred to above, this can occur in one of two ways. In the first instance, the GP will generate a token with a unique identifier which they will pass to the patient. The patient then simply enters this sequence into appropriate section to link into that GP’s account as a patient. in an alternative embodiment, the user may generate a token which they then pass to the GP, allowing the GP to create a link to the user's account. The net resuit is the same in each case — the GP or health provider is granted access to the users account to track their progress in terms of dietary change and weight status. Like the user, this access will apply not just to current results, but also to the fuli archive of patient results since first use. Irrespective of the access route, the clinician can then append further clinical data (e.g. blood pressure or blood lipid results) to the patient user’s lifestyle record as required.

The present invention has been designed to be extensible in both the “lifestyle” and “dietary” domains. In the lifestyle domain, extra fields may be added to enable the inclusion of additional clinical parameters (e.g. blood pressure, cholesterol level etc.) for that user. These data may be added by the user themselves, or by their clinician or GP provided their user account is linked to the relevant Doctor account.

An "exceptions reporting" functionality has also been developed, which allows doctors to prioritise high risk patients for communication by a two—tiered process. The doctor is abie to flag the patient as a high priority at the point when he provides them with the user token (or when they provide him with a token). This is a non-dynamic selection process based on the patient's baseline clinical status. The second means of flagging priority patients is through regular scanning of the database on a weekly or fortnightly basis to identify patients not making progress according to criteria which may be set by the clinician.

In all cases, the prioritised patients are sent an automatic e-mail reminder to go onto the site and re-take the assessment, unless the doctor manually de-selects them before the e- mail alert is sent.

These elements overcome the significant difficulties encountered in monitoring the diet, lifestyle and clinical progress of patients requiring such interventions in the community setting. The system also facilitates rapid, automated prioritisation of patients not achieving progress with their dietary regimen, a novel functionality in such dietary assessment applications. Additionally, these patient-doctor linkages facilitate easier communication of clinical results (e.g. blood pressure, blood sugar, cholesterol) between clinician and patient.

Also provided is an administration section, the implementation of which is illustrated in Figs. 15 and 16, which is adapted to control all parameters governing the use of the site by users and GPslother health providers. It may also be used to review usage patterns, carry out statistical analyses on user data at the individual and group level, change the language of the site or alter the graphics associated with the different sections and questions. Further functionality includes the ability of the administrator to programme automatic e-mail reminders to users to log on and re-take the assessment, helping to improve compliance with their dietary guidelines. The administration section altows the sections, questions and answer options, as well as their respective weightings to be altered or amended as requirements dictate. This section can also facilitate the appendage of clinical data such as blood pressure, serum lipid measurements, blood sugar measurements or other clinical parameters by either the GP or the patient themselves in order to further motivate patients by tracking changes in these parameters alongside their dietary changes. A Survey section contains a number of patient profile questions which may be considered as "further information", while the user sign-up page has been designed to be extensible to derive further user characteristics as required.

The present invention also includes a print facility which prioritises dietary domains in the dietary advice section based on their relative importance to health and the domain score.

Aspects of the present invention have been described by way of example only and it should be appreciate that additions and/or modifications may be made thereto without departing from the scope thereof.

Claims (5)

1. A computer implemented method of providing dietary advice output to a user, the method comprising the steps of: i) receiving a stream of lifestyle, anthropometric and clinical data inputs from the user; ii) using the lifestyle and anthropometric data inputs to determine a prescription calorific intake for the user; iii) receiving a stream of dietary data inputs from the user; iv) computing a diet and nutrition (DAN) score based on the prescription calorific intake and the dietary inputs, and v) generating and displaying dietary advice output based on the score.

2. A computer implemented method as claimed in Claim 1, in which the stream of lifestyle data inputs, anthropometric data inputs, clinical data inputs and dietary data inputs correspond to responses provided by the user to a plurality of lifestyle, anthropometric, clinical and dietary related questions presented to the user on a graphical user interface of a computing device, the method comprising the further steps of: assigning each dietary related domain and question a weighting and associating with each dietary related question one of a plurality of dietary domains selected from the group including, but not limited to, meal pattern, fruit and vegetables, refined extrinsic sugars, oily fish, alcohol, salt/sodium and fluid; configuring the weighting for each dietary related domain and question so that it is modifiable, and configuring the dietary related domains, questions and answers, and the lifestyle, anthropometric and clinical related questions so that they are adapted to be added. modified or deleted by an administrator.

3. A computer implemented method as claimed in Claim 2, comprising the further steps of: storing the dietary data inputs, anthropometric data inputs, clinical data inputs and lifestyle data inputs in a computer database; adapting the database so that it is accessible to facilitate viewing of the stored data by a doctor of the user; configuring the method so that it is executable as a software application which is adapted to be accessed by users via a website on the Internet; creating a database of user lifestyle, anthropometric, clinical and dietary data inputs and facilitating statistical ana|yse_s of these user inputs by an administrator at the individual and group level; adapting the dietary questions to provide users with selectable food portion graphic images for assessing user portion sizes; adapting the dietary advice output to include visualfprinted food portion graphic images for displaying assigned food portion size advice to users; providing a dynamic total calorific prescription to a user, which automatically adjusts after weight loss to prevent inappropriate over-restriction of dietary intake; prioritising dietary advice domains dynamically based on individual domain scores and the relative weightings of these domains; generating a dynamic "dietary training module", which highlights new priorities for dietary intervention as previous recommendations are addressed; generating a novel composite score for alcohol intake behaviour, based on the combination of weighted scores from three separate parameters, including weekly intake amount, frequency of intake and amount consumed per drinking occasion; creating a relational database of user lifestyle, anthropometric, clinical and dietary data, alongside demographic, socio—economic, clinical outcome, ethnic and other personal data entered via an extensible user sign-up page; and appending clinical data to users’ other data by clinicians to extend the relational database.

4. A computer implemented system for providing dietary advice output to a user, the system comprising: i) means for receiving a stream of lifestyle, anthropometric and clinical data inputs from the user; ii) means for using the lifestyle and anthropometric data inputs to determine a prescription calorific intake for the user; iii) means for receiving a stream of dietary data inputs from the user; iv) means for computing a diet and nutrition (DAN) _score based on the prescription calorific intake and the dietary inputs, and v) means for generating and displaying dietary advice output based on the score .

5. A computer implemented method of providing dietary advice output to a user substantially as herein described with reference to and as shown in the accompanying drawings. MACLACHLAN & DONALDSON Applicant’s Agents 47 Merrion Square Dublin 2