Malnutrition indicator

Abstract

A system arranged to calculate one or more malnutrition indicators for an individual human being comprises processing circuitry arranged to: receive information about the individual, the information comprising demographic information of the individual, and at least two unique photographs of the individual (including a front-view and a side-view); extract measurements indicative of body shape from the photographs; generate a 3D model of the individual using the photographs; retrieve information from a body composition or health database, the database comprising internal body composition data and corresponding body shape and demographic data, the retrieved information being selected based on identifying a subset of data in the database based on the demographic information, and matching the measurements extracted from the photographs to body shape data in the identified subset of data; and determine a value for the malnutrition indicator by combining the extracted measurements with the retrieved information from the database..

Description

[0001] Malnutrition Indicator The current state of the art for the primary measurement and indication of malnutrition, uses bicep circumference, measured manually, in conjunction with the Body Mass Index (BMI). This is a basic and indiscriminate method of assessment, which does not highlight the needs of those with moderate or severe malnutrition as no account of the overall body shape of an individual is taken into account. The environmental and social factors of an individual’s location constitute contributing factors for malnutrition which non-governmental agencies, and the United Nations are able to assess from other known facts and data. However the distinction of the needs of individuals within any given location or cohort is less well defined. This invention will highlight that need and help to bridge the evidence gap with real-time data, collected potentially on a global scale using modern technology. This invention centres upon the use of part volumes of the human body from a 3-D scan in order to assess and measure the level and severity of malnutrition in an adult or a child, using just a camera, or a camera on a smartphone or tablet device. In 2006, I invented the concept of using part volumes for the measurement of obesity in healthcare, as is now defined by the Body Volume Index (BVI). The principle of using part volumes for the measurement of body composition was in order to distinguish between those of the same Body Mass Index (BMI) reading who had different weight distributions, and therefore different risks to their health. BMI was invented in 1835 by a Belgian mathematician, solely as a population based metric, but in recentdecades has been used incorrectly as an individual barometer of health risk.In simple terms, a person with the same BMI who is a bodybuilder or an athlete has less of a health risk than someone with excess abdominal volume. BVI using part-volume ratios addressed thatlimitation for the purposes of measuring obesity. BVI identifies somebody carrying more weight aroundthe abdomen, where deposits of fat are more common and of greater risk to human health. The 2006 patent, which was titled ‘Health Indicator’ was specifically designed to address the inadequacies and shortfalls of the BMI as an individual measure of obesity. However, during the course of the last 20 years of validation and development of BVI new technology has developed in the premise of smartphones that offers new avenues and opportunities, entirely different from the use of part volumes to measure obesity. This new application is specifically to address the needs at the polar opposite of obesity, namely those people who have excess volume in certain parts of the body or less volume in certain parts of thebody, but due to malnutrition and a lack of food. The evaluation of this has been considered anddeveloped during a five year period where trials in Africa and India with malnourished children has highlighted the potential benefits of using part volumes, but not to measure excess body fat per se. The requirements of identifying those at greater risk through malnutrition requires a different approach, different algorithms and an entirely different ethos that allows those most at risk to be identified more clearly. This principle of using weight distribution and volume distribution to distinguish between those at greater and lesser risk is not wholly different in either field as most human beings are essentially the same shape. However the applications and the reasons for measurement are entirely and wholly different. This invention centres entirely on the use of part volumes for identification of risk for malnutrition, not for obesity and therefore is entirely different from the application filed in 2006 as patentnumber GBGB0603864.0A. It is also entirely different in purpose and application to the application filedin 2017 as patent number PCT / GB2018 / 051122. In addition, the applicant has multiple granted patents, including US 11,676,728, US 11,631,501and US 12,002,589 (originating from GB 1706857.8) relating to body composition data and healthindicators such as obesity and cardio-metabolic risk for “standard” human populations, but the metrics have not previously been extended to apply to populations facing famine / starvation, or less extreme but still serious food shortages. The inventor appreciated that different factors come into play when assessingmalnutrition – for example with a relatively large stomach volume potentially indicating a ‘distendedstomach’ or ‘distended abdomen’, with an increased relative abdomen size due to malnutrition rather thandue to weight gain – such that different metrics are needed. A health indicator model for a standardpopulation is not appropriate for a malnourished population. As background to this new invention it is perhaps firstly important to identify and list the currentmethods for both measuring malnutrition and the criteria upon which moderate malnutrition and acute malnutrition are identified, designated and attributed to an individual adult or child. Malnutrition can be defined as unintentional weight loss and losing 5% to 10% or more of weight over 3 to 6 months is one of the main signs of malnutrition. People with a low body weight, with a BMI of under 18.5 are at risk of being malnourished. The BMI calculator can be used to work out a BMI for a person with malnutrition, but the indiscriminate nature of BMI which does not distinguish between those of moderate or severe malnutrition highlights the inadequacies of BMI as a measurement tool in this field. See Fig.1. In terms of current methods for measuring malnutrition, this can be undertaken using a variety of methods, including anthropometric measurements, physical examinations and other indicators. Anthropometric measurements predominantly use height, weight, BMI and bicep circumference of a person. However, thigh circumference and skinfold measurements are also used in consideration with other factors, such as hydration, and can also be collected and taken into account. Visual and physicalexaminations can also be applied, often referred to as a nutrition focussed physical examination (NFPE).These can assess nutritional status by looking for general characteristics like muscle wasting, edema, and subcutaneous fat loss. These methods are all valid and appropriate to measure malnutrition, but do require touching of a person and can be quite time consuming in terms of data collection. In terms of the background research that has led to this invention, we need to refer to the extensive discussions and indirect support received from the World Health Organization (WHO) since 2017. There was a recognition in 2017 by WHO of the benefit of digital technology being applied as an alternative to manual measurement, thus avoiding the need for personal touching another person, often in quite sensitive areas of the body. Therefore, in 2020, at the request of WHO, the BVI technology, which operates from 2-D images from a smartphone, was deployed in trials in Malawi, Zimbabwe and India to measure both adults and children. In one of the trials in Zimbabwe over 600 children were measured 300 who were malnourished. This highlighted the applications of using body volume to measure children who are malnourished, but this also highlighted the limitations of algorithms and assumptions on body fat, content if the abdominal area was large due to a lack of food as opposed to excess food, which is an assumption for measured obesity as known in the developed world. The Background to Malnutrition Measurement and the Current Art The current indicators of malnutrition are best illustrated by this table, as used to currently define malnutrition: - Malnutrition Indicators Nutrition Indicator Measurement Indicator Clinical IndicatorAcute Malnutrition (SAM & MAM)Weight-for-Height Wasting, kwashiorkorMid-upper arm circumference Wasting, kwashiorkorChronic Undernutrition Height-for-age StuntingUnderweight (composite indicator)Weight-for-age UnderweightOvernutrition Body Mass Index (weight / height ²) Overweight / ObesityMicronutrient Deficiencies Biochemical indicators Xerophthalmia, stomatitis, etc.https: / / executiveboard.wfp.org / document_download / WFP-0000037871 Fig.2 shows the different categories to indicate those who are described as being stunted or suffering from wasting. Fig.3 illustrates the distinction between those who are designated as being a ‘normal’ body shape’ as opposed to being classified as ‘kwashiorkor’ with a protruded abdomen. The World Food Programme (WFP) assists 80 million peoplein around 80 countries each year, the World Food Programme (WFP) is the leading humanitarian organisation saving lives and changing lives, delivering food assistance in emergencies and working with communities to improve nutrition and build resilience.” -WFP brings life-saving food to people displaced by conflict and made destitute by disasters, andhelp individuals and communities find life-changing solutions to the multiple challenges they face in building better futures. -WFP works to enhance nutrition in women and children, support smallholder farmers in improving productivity and reducing losses, help countries and communities prepare for and cope with climate-related shocks, and boost human capital through school feeding programmes. -However, in terms of the scope and responsibility of their operations for the deployment of foodand resources with these demands, the criteria for moderate malnutrition (managed by the WFP) and severe malnutrition (managed by UNICEF, a separate UN body) is at best, undefined and ambiguous. -The threshold for deciding whether a region of the world, or a part of that region has adults orchildren who are either moderately or severely malnourished at any given time is, at this time, reliant upon personal and organisational subjective analysis. This is in need of improvement and better definition, so that resources can be assigned more effectively and the distinction of responsibility between the WFP and UNICEF becomes easier to manage and apply in practice. In terms of how malnutrition is currently defined, this is broadly defined as follows:-Definition - in acute malnutrition, the amount of one or more macronutrients available to body tissues isinadequate to sustain optimal function. -Macronutrients deficiency - results from inadequate diet, poor absorption of ingested nutrients, orthe presence of a chronic inflammatory condition that increases requirements for nutrients while promoting a nutrient wasting catabolic state. How is Acute Malnutrition Diagnosed and Categorised? -Anthropometry- Oedema - a physical finding of severe malnutrition that presents bilaterally on the dorsum of thehands and feet. -Categorisation - acute malnutrition is differentiated as moderate or severe- Moderate malnutrition - a weight for height z score between 2 and 3 standard deviationsbelow the mean -Severe malnutrition - weight for height z score more than 3 standard deviations below themean or an arm circumference <110mm, or the presence of nutritional oedema. Clinical Features Associated with Complicated Malnutrition -Fever related to systemic infection typically Gram negative coliforms such as Escherichia coliand Klebsiella pneumoniae -Respiratory distress- Heart failure- Electrolyte derangements - hypophosphatemia, hypokalaemia, hypoglycaemia- Marked anorexia- Anaemia- Profuse diarrhoea- Shockhttps: / / www.bmj.com / content / bmj / 337 / 7680 / Clinical_Review.full.pdf- Most adult malnutrition is associated with disease and may arise due to:- Reduced dietary intake- Reduced absorption of macro- and / or micronutrients- Increases losses or altered requirements- Increased energy expenditureAccording to Mayo Clinic, anorexia nervosa is an eating disorder characterised byhttps: / / www.mayoclinic.org / diseases-conditions / anorexia-nervosa / symptoms-causes / syc-20353591 ), anabnormally low body weight, an intense fear of gaining weight, and a distorted perception of weight. Although similar in effect to malnutrition, this invention is intended primarily for those who have been affected by lack of nutrients and food, as opposed to anorexia, where symptoms are often accompanied and associated with other psychological factors. So in summary, as might be expected, the elements of malnutrition that lead to the condition and the environmental, social and socio-economic circumstances that lead a person or persons being malnourished are complex and intertwined. This invention will not solve malnutrition or address it, but it will help as an initial indicator or risk and of future possible malnutrition so that resources can be assigned by the WFP, by UNICEF, or others, such as non-governmental charitable organisations morequickly and effectively. The use of body volumes, as opposed to using BMI will assist the deployment ofresources for malnutrition and the elements of decision making that are associated with that. In addition to malnutrition as defined above, there are also other defined conditions where excess and abnormal abdominal volume is a deciding factor in assessing a person’s health. There is, for example, a condition called syndrome / symptoms-causes / syc-20351310) and also another condition called "Lipodystrophy".(https: / / www.yalemedicine.org / conditions / lipodystrophy#:~:text=Lipodystrophy%20is%20a%20group% 20of,develop%20it%20later%20in%20life.) The latter appears to be more random and less prevalent in the population, but both these conditions centre on localised abnormal fat storage in the torso or the abdominal area. Malnutrition has a similar effect on the body shape of sufferers and these alterations to body shape are consistent with factors associated with excess obesity, but malnutrition is diametrically opposed to the concept, the reasoning and the measurement of obesity. In most cases, excess obesity is related to self-inflicted lifestyle, nutritional or exercise activities, so the use of body volumes to measure malnutrition, Cushing's syndrome and Lipodystrophy are entirely new forms of art, not practised for measurement purposes in that field. The Consequences of Malnutrition -Muscle Function - Weight loss due to depletion of fat and muscle mass, including organ mass, isoften the most obvious sign of malnutrition. Muscle function declines before changes in muscle mass occur, suggesting that altered nutrient intake has an important impact independent of the effects on muscle mass.- Cardio-respiratory function - Micronutrient and electrolyte deficiencies (eg thiamine) may alsoaffect cardiac function, particularly during refeeding. Poor diaphragmatic and respiratory muscle function reduces cough pressure and expectoration of secretions, delaying recovery from respiratory tract infections. -Gastrointestinal function - Adequate nutrition is important for preserving GI function: chronicmalnutrition results in changes in pancreatic exocrine function, intestinal blood flow, villous architecture and intestinal permeability. The colon loses its ability to reabsorb water and electrolytes, and secretion of ions and fluid occurs in the small and large bowel. -Immunity and wound healing - Immune function is also affected, increasing the risk ofinfection due to impaired cell-mediated immunity and cytokine, complement and phagocyte function. The Malnutrition Universal Screening Tool (MUST) -MUST is a simple, rapid and easy method to screen patients and has been proven to be reliableand valid. It aims to identify those at risk by incorporating: -Current weight (BMI)- History of recent unintentional weight loss- Likelihood of future weight losshttps: / / www.ncbi.nlm.nih.gov / pmc / articles / PMC4951875 / #:~:text=Weight%20loss%20due%20to%20dep -Malnutrition is a serious condition that happens when your diet does not contain the right amountof nutrients. It can refer to:-> Undernutrition - not getting enough nutrients-> Overnutrition - getting more nutrients than neededSigns and Symptoms of Malnutrition: -Unintentional weight loss - losing 5% to 10% or more of weight over 3 to 6 months is one of themain signs of malnutrition -A low body weight - people with a BMI under 18.5 are at risk of being malnourished- A lack of interest in eating and drinking- Feeling tired all the time- Feeling weak- Getting ill often and taking a long time to recover- In children, not growing or not putting on weight at the expected rateWho is at Risk of Malnutrition: -Have a long-term health condition that affects appetite, weight and / or how well nutrients areabsorbed by the gut, such as Crohn’s disease -Have problems with swallowing (dysphagia)- Are socially isolated, have limited mobility, or a low income- Need extra energy, such as people with cystic fibrosis, are recovering from a serious injury orburns, and those with tremors or shaking hands -People who are 65 years+ are particularly at risk, and weight loss is not an inevitable result of oldage -Children under the age of 5Treatments for Malnutrition -Eat “fortified” foods that are high in calories and protein- Snack between meals- Have drinks that contain lots of calories- A doctor, nurse and / or dietitian may also suggest you take extra nutrients in the form ofnutritional drinks or supplements -Eating soft or liquid foods (for those who have difficulty eating)- A feeding tube - this can be either passed down your nose and into your stomach, or inserteddirectly into your stomach through the skin of the tummy (or those who have difficulty eating) -Nutrition that’s given directly into a vein (or those who have difficulty eating)Preventing Malnutrition -Healthy and balanced diets- You need to eat a variety of foods from the main food groups, including: fruit and vegetables,starchy foods, milk and dairy foods or non-dairy alternatives, and protein %20BMI) UNICEF: Definition of Child Malnutrition -Nearly half of all deaths in children under 5 are attributable to undernutrition; undernutrition putschildren at greater risk of dying from common infections, increases the frequency and severity of such infections, and delays recovery. -Poor nutrition in the first 1,000 days of a child’s life can also lead to stunted growth, which isassociated with impaired cognitive ability and reduced school and work performance. -More than one in five – 148.1 million children under 5 –were stunted in 2022, and at least 45.0million suffered from wasting at any given point of time in the year. Meanwhile, the number of children under 5 affected by overweight worldwide has increased from 33.0 million in 2000 to 37.0 million in 2022. -Estimates of child malnutrition will help determine whether the world is on track to achieve theSustainable Development Goals – particularly, target 2.2, to “end all forms of malnutrition by2030”, which falls under goal 2 to “end hunger, achieve food security and improved nutrition, and promote sustainable agriculture”. -In 28 countries, at least 30 percent of children were still affected by stunting in 2022- South Asia has the highest wasting prevalence of any region in the world- In 33 countries, at least one in every ten children under five is overweight Definition of Adult Nutrition One published definition of adult malnutrition is shown in the table on the subsequent page.The Need for Improvement and Better Diversification of Resources In view of the above, and despite the undoubted resources and intellect applied to the field of malnutrition, in this technical age, a better and more valid indicator of risk before interventions are applied is undoubtedly needed. This invention, developed since 2006, after eighteen years of research, development and validation is now proven as the Body Volume Index (BVI) to be a more valid indicator of risk for obesity than BMI ( https: / / www.jacc.org / doi / full / 10.1016 / S0735-1097%2822%2903019-4 ) This new applicationnow offers the opportunity to assist for an entirely different purpose; for the measurement and designation of malnutrition, and the variants of severity thereof. The Description of the New Art for New Methods of Measurement for Malnutrition In terms of the new methods of measuring malnutrition using part-volumes, or a combination of part-volumes in combination with other linear, circumference and other measures, the use of part-volumes itself for measurement is outlined below. These charts have been compiled and assessed using the existing datasets we have compiled on male and female adults and children, and are indicative only subject to further validation after submission of this patent application. It is envisaged that a combination of arm volume, leg volume and abdominal volume may be defining factors in allowing for a better distinction to be made between those of moderate and severe malnutrition. This would be an advance over the current practice of using BMI and arm circumference, measured manually at the midpoint, as a distinguishing factor. The following charts are designed to illustrate the parameters of low and medium volumetric measurement of body parts, using litres as a measurement for each individual. The part-volumes of an individual can be tracked and measured against the normative values for adults and children of both genders. The charts following the table below are indicative only for the purposes of this application:-

[0002] Diagnosis Severe Protein Calorie Malnutrition Malnutrition of Moderate DegreeCriteria (at Acute Chronic Acu Chronic least 2 must Illness Social / Behaviou te Injury / Illne ral / Circumstances Illness Social / Behavioural / Circumstances be present) ss Environmental Injury / Illness Environmental >2% x 1 >5% x 1 1-2% x 1 week, month, >5% x 1 month, week, 5% x 1 month, 5% x 1 month, >5% x 1 >7.5% x 3 5% x 1 7.5% x month, months >7.5% x 3 months 3 month months 7.5% x 3 months Weight loss >7.5% x 3 >10% x 6 months months >10% x 6 months 7.5% x 3 10% x 6 months months 10% x 6 months >20% x 12 nths >20% x 12 mon 20% x 12 mo ths months 20% x 12 months <50% energy <75% energy <75% ntake intake en <75% energy i ergy intake Energy compared to compared to <50% energy intake compared to intake compared compared to <75% energy intake compared to Intake estimated estimated estimated energy needs ≥ 1 mo. to estimated estimated energy needs ≥ 3 mo. energy needs energy needs estimated energy nee energy needs ≥ 5 days ≥ 1 mo. ds > 7 days. ≥ 1 mo. Body Fat Moderate Severe Mild depletion depletion Severe depletion depletionMild depletion Mild depletionMuscle Mass Moderate Severe Mild depletion depletion Severe depletion depletionMild depletion Mild depletionFluid Moderate to accumulation SevereSevere Severe Mild Mild Mild

[0003] Arm Volume (measured from the wrist to the shoulder) Abdominal Volume (measuring the area from the sternum to the small of the back, to the line of the iliac crest towards the top of the crotch area) Fig.4 illustrates the invention of measuring abdominal volume from a digital 3-D body scan, from the bottom of the ribcage to the top of the iliac crest as a proportion of the total volume of achild or adult. This could become a significant advancement on current methods of measurementusing BMI and bicep circumference measurements only. According to a first aspect of the invention, we provide a malnutrition indicator device comprising using 2D images to obtain a three-dimensional model of a person, a body Volume calculator for calculating the volume of at least a first part of the person’s body and a second part of a person’s body from the three-dimensional model, and a malnutrition calculating device for calculating an indication of the person’s health based on the output from at least the body volume calculator. This is advantageous as the three-dimensional (3-D) model is used to calculate the indication of a person’s health, which takes into account the unique build and body shape of an individual person. An accurate indication of the person’s health can be calculated which can be used to accurately diagnose problems, develop weight gain programmes, assign food and diet resources or appropriately prescribe medication or drugs as necessary. It also obviates the need to hydrostatically weigh a patient and is therefore quicker, accurate and less intrusive for individuals whose socio- economic environments are challenging. The device of the invention is easy to use, non-invasive, patient friendly and completely safe by using non-penetrating photonic images generated from a digital camera, a camera on a smartphone or a camera on a tablet. The quality of these cameras to generate images are particularly accurate and so can provide a reliable indicator that is representative of a person’s malnutrition and overall health. Further, if the health indicator device is used on a person over a period of time, it can be used to identify people who are at risk of becoming malnourished by tracking, comparing and analysing their volumetric data with data from other environmental, medical and social factors. The use of mobile technology in developing nations is limited at this time, compared to developed countries, but this distinction is likely to become less prevalent in the future. The GlobalSystems for Mobile Communication (GSMA) has published data on the Mobile Economy in Sub-Saharan Africa (2023), which shows that smartphone adoption in the region is currently at 51%. The region also has the highest usage gap for mobile technology globally, with 680 million people unconnected (or 59% of the population). The Sub-Saharan Africa region also falls behind all regions globally, with only 25% of its population connected to mobile broadband services." However, the GSMA has projected that by 2030 at least 88 percent of Africans will own and use a mobile phone. The output from the Body Volume calculator can provide a more accurate indication of a person's malnutrition for those working at resource level centrally, or for those working in the field. Using the volume of at least the first and second parts of the person’s body has been found to be accurate as it takes account of body shape and body mass distribution that cannot easily be realised by making linear measurements such as a mid-arm point measurement, as in prior art methods. This is especially true if the first or second body parts comprise the volume of the abdominal region, which is used visually and subjectively to provide a reliable indication of a person’s level of malnutrition. The abdominal region contains the intestinal area, liver and kidneys and this region is of importance as its relative volume and composition can be used to accurately predict the malnourishment level in a given child or adult. The malnutrition calculating device may calculate the indication of a person's health based on the ratio between the volume of the first part and the volume of the second part. This is particularly advantageous as the use of volume ratios of different parts of the body gives an accurate indication of a person’s malnutrition level. Thus, by comparing the Volume of various body parts the shape of a person can be recognised. This is advantageous, as the indication of malnutrition calculated by the above device is accurate and is able to differentiate between people of different health status, but with the same BMI calculation, for example. Typical ratios may include neck Volume to whole body Volume, upper torso Volume to abdominal Volume, Abdominal Volume to Arm and Leg Volume or abdominal volume to whole body volume, or indeed a combination of these ratios. Preferably, the body volume calculator determines the volume of third, and / or fourth, and / or fifth and / or sixth body parts and the malnutrition calculating device calculates ratios between thevolumes of these parts to obtain the indication of a person’s health. The health calculating devicemay use further data such as body composition data to obtain the indication of a person’s malnutrition. The body composition data may include body fat composition, muscle mass, amount ofskin, blood, body water, bone and organs. Preferably, the health indicating device provides aprediction of the volume of the stomach using the Volume of the abdominal region where excessive expansion is known and accepted to be symptomatic of malnutrition. In the diagnosis of obesity, medical researchers have suggested that having excessive fat around the abdominal region has a high correlation with heart disease risk. Thus, the volume of the abdomen and in particular the area between the upper and lower waist may be given a higher importance factor than other parts of the body for obesity, but this principle also applies to the measurement of malnutrition. Excess abdominal volume in an adult o a child that is malnourished, constitutes a combination of other factors, causing what is often known as Kwashiorkor symptom ofdisease (See Fig.3). Kwashiorkor is a form of malnutrition caused by protein deficiency in the diet,and can typically affect young children in the tropics. This is more commonly called a ‘distended stomach’ or ‘distended abdomen’, which refers to an actual increase in measured abdominal size. Most preferably, the malnutrition calculating device calculates the Volume of the abdominal region as the first part, the Volume of the upper torso, or chest area, as the second part and the Volume of the lower torso, or pelvis area, as the third part. Preferably, the volume of the first part is compared to the volume of the second and third parts and the importance factor for the level of malnutrition determined therefrom. It will be appreciated that other part body volumes may be used.By determining the indication of a person's health in this way a differential anthropometric measure iscreated that takes account of differing torso shapes and differing whole body shapes, linking this data to bicep circumference or other body measurements to determine greater differentiation between individuals. Preferably the height calculating device uses the three dimensional model to calculate the height of the person. Preferably, the health calculating device receives a measurement of the circumference of the person’s upper arm. Preferably, the health calculating device receives a measurement of the circumference of the person’s thigh. Preferably, the health calculating device receives a measurement of the length of the person’s legs. This data may be measured obtained from the body volume calculator and body composition data. Which body composition data is used may be chosen depending on the particular part of the body measured by the body volume calculator. Preferably, the body composition data is obtained using cadaver study and analysis data. Most preferably, the body composition data comprises predetermined data that can be used by the health calculating means to estimate the composition of a part of a person’s body based on the volume obtained from the body volume calculator. The predetermined data may be obtained from published surveys of body composition and in particular such studies on malnutrition measurement using arm circumference, Body Mass Index and other metrics and methods. The body composition data, such as cadaver data, preferably includes data of the weight of constituent elements of a body part and the health calculating device includes comparison means to compare the three-dimensional model to the body composition data to estimate the weight of at least the first body part or second body part, based on the volume of those parts calculated by the body volume calculator. The weight of the abdominal area would be calculated taking the body composition components for malnutrition, as opposed to obesity, where the constituent parts of the abdomen weight will be different. This is advantageous to allow differentiation between the extreme thresholds of obesity and malnutrition. Body composition data allows the health indicating device to estimate how much of a given body part, based on its Volume, is made up of skin, bone, water, muscle etc and therefore estimate its weight for malnourished persons, where the constituent parts of the abdomen will be different than for those who are obese. This enables the malnutrition calculating device to provide an indication and estimation of the severity of malnutrition in a person, or a group of persons. A group of persons in this context could be those in a certain country, in a given region or part of that country, of a certain age, or a given gender or ethnic background. Therefore, using this data for example, governing bodies at the United Nations, or non- governmental agencies working in the field who are managing the needs for malnutrition can be informed on which parts of the area, or on which persons to focus their efforts. Preferably, the malnutrition device includes feedback means adapted to receive data regarding the person's malnutrition level at a previous time and wherein the malnutrition calculating device receives data from the feedback means to improve the management of a person's health. The malnutrition indicator device may include a height calculating device to obtain the person's height. The indication of the person’s health may be calculated using at least the Volume of the first and second parts and the person’s height. Preferably, the body volume calculator calculates the volume of predetermined parts of the person’s body, which are used by the malnutrition calculating device to calculate the indication of theperson’s level of malnutrition. Preferably, the predetermined parts are associated with an importancefactor, which is used to give more importance to particular parts of the body in the calculation of the person's health and preferably the measurement is made from the three-dimensional model, using the2-D photonic images collected from a device, such as a smartphone, tablet or camera. Preferably, thecircumference of the person’s bicep is used by the health calculating device to determine the indication of a person’s health. This is advantageous as current manual measurement methods for malnutrition use a reduction in bicep circumference, linked to the Body Mass Index, to determine the severity of malnutrition. Linking this data to the Body Volume Index calculations, provides a new, distinct advantage over the current and established methods. Preferably the malnutrition indicator comprises software that manipulates data output from the device taking the 2-D images and may obtain additional data. Preferably, the additional data includes cholesterol level, blood pressure, lipids profile and glucose or weight. Preferably the body volume calculator manipulates the data output from the device using triple integration, and applies artificial intelligence or machine learning techniques. The body scanning device may be of known type and preferably is a smartphone, tablet or camera, connected via Wi-Fi, account log in or on account to the internet. Alternatively, data can be collected on the device without internet access, and then uploaded to the body volume calculator manually or as and when internet connectivity is available at a later date. In summary, such a malnutrition indicator processes many measurements (typically 100 to 130 million) known as data points of several million positions on the Surface of a person’s body, using the 2-D images. These data points can then be appropriately joined or associated with neighbouring points to form a three dimensional image of a person. It will be appreciated that other devices capable of taking the appropriate measurements to generate the three dimensional model may also be used. Preferably the indication of a person's level of malnutrition is scaled such that it corresponds to the known BMI scale. This is advantageous as it provides a value that is an accurate representation of a person’s level of malnutrition that is readily recognised. It is modified to correspond to a widely known and long established BMI scale, but to differentiate the level of malnutrition for those who are assigned the same BMI value. Preferably the indication is scaled by a constant. However, it may be scaled by a function. Preferably the malnutrition indicator device stores the 3-D model and the indication of a person's health. Preferably the health indicator device determines whether the person being scanned has been scanned previously and, if so, shows at least a comparison between the present 3-D model and the previous 3-D model. It may also show comparison information with average or aggregatedscans of people with similar measurements or the national average or international average. Thedevice may also show a comparison between the previous indication of a person’s malnutrition level and the present indication of a person’s malnutrition. Preferably the health indicator device is used to collect statistics, which are stored in a database. Preferably, the database can be accessed from a secure web server. According to a second aspect of the invention, a method for calculating the level of malnutrition of a person comprising the steps of scanning the person’s body using 2-D images of a person using a camera, generating a three-dimensional model of the person’s body using outlines from those 2-D images; calculating the volume of a first part of the person's body from the three- dimensional model; calculating the volume of a second part of the person’s body from the three- dimensional model; and calculating an indication of the malnutrition of the person, from at least thecalculated volume of the first and second parts of the person's body. Alternatively, one 2-D image ofthe side of the person may be used for this aspect of the invention. The indication of health is obtained quickly, easily and accurately by the above method. As 2- D images from a smartphone, tablet or camera device are used, the data collected is a true and undistorted representation of a person's size and body shape. The calculation of a person’s volume or, in particular, the volume of predetermined body parts gives an accurate representation of a person’s shape and body volume without the need to submerge them in water, for example. Further, the present method allows the volume of parts of the body to be determined and, using predetermined data or further measurement, an estimate of the body composition per body section can be obtained. The indication of malnutrition obtained provides a novel useful anthropometric measure that is an accurate assessment of a person's shape and an alternative to BMI and other manual based anthropometric measurement techniques, such as bicep circumference measured using a tape measure. Preferably, the indication of the person's health is calculated by the ratio between the first volume and the second volume. As discussed in relation to the first aspect of the invention, comprises (a) the Volume of various first and second body parts(b) generating a three-dimensional model of the person’s body;(c) measuring at least the person’s weight(d) generating a data record including the three dimensional model and at least the person’sweight; and (e) repeating steps (a) through (d) at predetermined time intervals and generating a further datarecord showing any changes in the three dimensional model and / or at least the person’s weight This is advantageous as the person undergoing management of malnutrition, or persons managing that on their behalf, has a representation of how their body shape is changing. Persons in this context means United Nations or non-governmental department officials managing malnutrition needs and resources of individuals suffering from malnutrition. Thus, by having the graphical representation of their body shape as well as the numerical data, it gives the person a more informative insight into what has been achieved and what still needs to be achieved to address and resolve their malnutrition needs. This method is particularly applicable in a local setting in a developing or troubled setting, troubled in this context meaning famine, war, poverty, political upheaval or a combination of these. Further, simply seeing the 3-D representation may encourage and motivate the person into admitting that a change in weight is necessary and act as a psychological tool for management of healthcare purposes. This is particularly useful for people with eating disorders such as Anorexia or elderly patients who suffer from malnutrition as the perception of their own body shape may differ from the reality. A common symptom of Anorexia in patients in a healthcare setting is a denial thatthey are painfully thin. Indeed many anorexics truly believe they are overweight. By showing them animage of their body from the 3-D model, it may have the required psychological impact to help them accept the reality that they are severely underweight and do have a medical condition. Further, use of a device, such as a smartphone to collect 2-D images of a person, or for a person to ‘self-scan’ using the front facing camera is less invasive than manual methods. Having another person make numerous “hands on' measurements means there is no intervention or touching of another person that is required. Still further, manually measuring someone can lead to inaccuracies due to how tight the measuring tape is held. In current practice, bicep circumference is manually measured for malnutrition measurement, alongside BMI, but this method takes no account whatsoever of body shape, or changes in body shape. Using 2-D images collected from a smartphone or tablet, the person is more relaxed due to the absence of any physical contact, with the data collected also being more accurate and more detailed. The further data sheet preferably shows the three-dimensional models of the body taken at each predetermined time to visually show any changes. Most preferably the models of the body are overlaid on one another or they may be positioned side by side. The further data sheet may include additional information, and / or changes in said additional information, may be chosen. However, the first body part preferably comprises the abdominal area and the second body part preferably comprises the upper torso. Preferably, the volume of further predetermined parts of the body such as neck, chest, waist and hip measurements, blood pressure, cholesterol level, blood analysis, heart rate and variability arealso measured. The data sheet or further data sheet may be such that it can be sent to therepresentative managing the malnutrition needs in a given area by e-mail or by SMS or MMS message. The collective data of all and any individuals in any given area of the world can be identified using GPS, What3Words, Satellite or other location precision methods. This collective data can then be accessed and used in the calculation of the indication of the malnutrition needs of given areas in the world by United Nations or non-governmental officials. The weight, height and / or leg length of persons in any given area may also be used in the calculation of the indication of the malnutrition needs in any given area. Preferably, the method includes obtaining body composition data based on the volume of the first or second parts and using the body composition data in the indication of a person's level of malnutrition. Preferably the method includes obtaining a blood pressure measurement of the person. This may be measured during the scanning of the person's body or afterwards. The method may also include measuring the cholesterol level of a person. The blood pressure and / or cholesterol measurement may be used in the calculation of the health of a person. A blood sample may also be taken. According to a third aspect of the invention, we provide a method of malnutrition management comprising the steps of (a) scanning a person’s body using a smartphone, tablet or stand-alone camera; and sending this data, and aggregated data thereof to a central data portal. The sending and storing of data in this way may be effected via a website such as www.bodyvolume.comor via an API to www.wfp.org . The time intervals for measurement may be between 1 and 52 weeksand are preferably between 10 and 15 weeks. Most preferably the time interval is 13 weeks between scans, although it will be appreciated that time intervals between scans may vary according to external circumstances and needs being managed by malnutrition professionals from non-governmental agencies working in the field. Preferably, the method of weight management defined employs the use of the health indicator device of the first aspect of the invention. According to a fourth aspect of the invention, a method for assisting a person who is managing the malnutrition of individuals in a given area comprising the steps of (a) arranging for data collection at given intervals; at least comprising scanning said person using 2-D images and generating a three-dimensional model of said persons; (a) scheduling further sessions;(b) performing said further sessions and generating a data sheet showing at least said three-dimensional models from the present session and any changes from the previous sessions; (c) repeating steps (b) and (c) until the number of sessions completed is equal to the number ashas been arranged by the management resources assigned to give guidance thereof. Guidance for these will be for, from and on behalf of the United Nations and other non-governmentalagencies working in the field of malnutrition management. Preferably the further sessions of measurement are scheduled between 4 and 13 weeks after the present session or at a suitable time as determined by the management personnel at the United Nations or the non-governmental agencies. Preferably costs to cover data collection resources arranged and performed by United Nations and non-governmental staff, are covered by philanthropic or United Nations member nations donations for the same. Preferably the session includes the steps defined in accordance with the second aspect of the invention or using the device of the first aspect of the invention. According to a fifth aspect of the invention we provide a database means adapted to receive at least one record, the record comprising an identification reference associated with a person and at least information obtained by scanning the person using a body scanner, wherein the database means includes access means to allow access to the information stored in the database means. The database will include aggregated data from records of persons in the same country, in the same location of agiven country, or in an identified location within that country. It is assumed, in accordance withGDPR and other regulatory obligations, that individuals will not be identified, but management of this process will be determined by the United Nations and their respective agencies for the management of malnutrition resources. Preferably the identification reference comprises the geographic location of the person that is scanned. Alternatively, it may be a designated serial number that is assigned to the information obtained from the device used on site and in the field. Most preferably, the identification reference is derived from the gender, date of birth, date and time of the scan, ethnicity and the general location of where the scan was performed. Accordingly the database means stores anonymous information andtherefore the identifying information of the person who was scanned is associated with theidentification reference and not stored, other than on secure United Nations or non-governmentaldepartment records. Preferably, the database is available via a secure server to users within the United Nations agencies with appropriate secure authentication and permission for malnutrition management. This is assumed to be UNICEF and the World Food Programme of the United Nations, although secure access may become available to other United Nations departments, subject to their discretion and approval. It is also assumed that collated aggregate data may become published by the United Nations and the World Health Organization for public health and public policy purposes. Preferably the information obtained by scanning the person comprises a three-dimensional model of the person’s body. Preferably the information includes the volume of a first part and asecond part of the person's body calculated from the three-dimensional model of the person's body.Preferably the information includes body composition data derived from the body volume measurements of at least the first and second parts of the person's body. Preferably the information includes an indication of the person’s health derived from the volume, calculated from the three- dimensional model, of at least the first and second predetermined parts of the person’s body. Preferably, the predetermined parts are associated with an importance factor, which is used to give more importance to particular parts of the body in the calculation of the person's health. The importance factor may comprise a multiplier, or alternatively it may be a function. Preferably the calculation of a person's level of malnutrition comprises an algorithm that uses a plurality of ratios of the volume of predetermined parts of the person's body. Preferably the importance factor is determined from any combination of the gender, age and ethnicity of the person. Preferably, the database means is located on a computer server. Preferably the access means is adapted to allow access to the information over the Internet. Preferably the access means allows access to the information over a secure channel, such as SSL (Secure Socket Layer). Preferably, the access means requires registration details or payment to allow access to the information. The use of registration details allow only the appropriate people to access the information, such as, for anorexia,the person to whom the information relates, their medical practitioners, health professional or otherperson they specify as being able to access the data. For malnutrition as managed by the United Nations, access is allowed only to those with appropriate management authority and under secure data access protocols. Preferably the database means is adapted to receive a plurality of entries for each identification reference and the date on which the information from the device and the body volume calculator is obtained. According to a sixth aspect of the invention, we provide a malnutrition indicator device comprising a body scanner to obtain a three-dimensional model of a person, a body volume calculatorfor calculating the volume of at least a part of the person's body from the three-dimensional model, aheight calculating device to obtain the person’s height and a health calculating device for calculating an indication of the person's malnutrition based on the output from at least the body volume calculator and the height calculating device. According to a seventh aspect of the invention, a method for calculating the malnutrition of a person comprising the steps of scanning the person's body using 2-D images from a camera on a smartphone, tablet or a stand-alone camera, generating a three-dimensional model of the person’s body; calculating the volume of at least a part of the person’s body from the three-dimensional model; measuring the height of the person’s body; and calculating an indication of the malnutrition of the person from at least the calculated volume and height of the person's body. According to an eighth aspect of the invention, we provide a method of malnutrition management comprising the steps of (a) scanning a person’s body using 2-D images from a camera on a smartphone, tablet or stand-alone camera; (b) generating a three-dimensional model of the person’s body; (c) measuring at least the person’s height and weight; (d) generating a data sheet including the three dimensional model and at least the person's weight; and (e) repeating steps (a) through (d) at predetermined time intervals and generating a further data sheet showing any changes in the three dimensional model and / or at least the person’s weight. According to a ninth aspect of the invention there is provided a machine readable medium containing instructions to allow any of the above methods to be provided. According to a tenth aspect of the invention there is provided a machine readable medium containing instructions to cause any of the above apparatus to function. According to an eleventh aspect of the invention there is provided an artificial intelligence module to determine the malnutrition indicator value, containing instructions to cause any of the above apparatus to function. The machine readable medium according to any of the above aspects of the invention may comprise any of the following: a floppy disk, a CD ROM / RAM, a DVD ROM / RAM (including -R / - RW and +R / +RW), a Blu ray disc, an HD DVD, a memory (including a Memory Stick, SD card, Flash memory card or the like), a hard drive, any form of magneto optical storage, a transmitted signal (including an Internet download, an FTP transfer or the like), an on-line data server, a wearable device, or a wire. According to an eleventh aspect of the invention, we provide a method of calculating the weight of parts of a person’s body comprising the steps of scanning a person in a body scanner; generating a three-dimensional model of the person’s body; splitting the three-dimensional model into at least one part; calculating the volume of the at least one part from the three-dimensional model; using the volume of the or each body part, cadaver and MRI data to estimate the composition of the or each body part. This is advantageous as the method allows detailed analysis of the composition of body parts without the need for scanning techniques that use body-penetrating radiation. Thus, theabove method allows the amount of organs, blood, water or tissue, for example, to be accuratelyestimated from the volume of the body part, and the cadaver and MRI data. The method may include the step of using the volume of each body part and the cadaver data to estimate the weight of each component of that body part. The components of a body part such as an arm may include the weight of the skin, bone, muscle mass, body fat or adipose tissue, blood and water. For the upper torso the components may include the weight of the Lungs, Heart, Spleen and all the skin, bone, muscle mass, body fat or adipose tissue, blood and water. For the lower torso the components may include the reproductive organs, Bladder and all the skin, bone, muscle mass, body fat or adipose tissue, blood and water. For the abdominal area the components may include the Liver, Kidneys, Large Intestine, Small Intestine, Stomach and all the skin, bone, muscle mass, body fat or adipose tissue, blood and water. It will be appreciated that other body parts will be analysed according to their relevant components. Although the components differ depending on which part of the body is analysed, preferably the weight of at least the amount of blood, bone, water, tissue and fat is determined. In this context fat is assumed to be the amount of lipids extractable from adipose tissue. In FIG.5, a malnutrition indicator device 1 is shown comprising a smartphone or tablet 2, data collection means 3 and manipulation means 4. The manipulation means 4 has a connection 5 to the Internet 6 so that it can communicate with database means 7. It will be appreciated that the connection need not be via the Internet 6 and may be over a Local Area Network, a direct connection or over a telephone line depending upon the location of the manipulation means 4 and the database means 7. The database means 7 also has access means 8 to enable it to be accessed remotely by United Nations or non-governmental agency personnel 9. In this embodiment, United Nations management personnel can access the database means 7 via the access means 8 over the Internet via a web-based interface. The connection 5, 6 between the manipulation means 4 and the database means 7 comprises a secure file transfer protocol connection, although any appropriate connection, secure or otherwise, could be used. The connection between the GP9 and the database means 7 is also a secure connection, using known secure Internet transfer methods such as SSL. The body scanner 2 comprises a camera embedded on a smartphone, a tablet or a camera. The scanner uses 2-D images of the person’s body, to create outlines of that person’s body, from whichmeasurements of the size and shape of the person for the generation of a three-dimensional model canbe obtained. The data collection means 3 comprises software loaded onto a computer that is connected to the scanner 2. The manipulation means 4 also comprises software loaded on to the same computer,wherein the manipulation software receives its input from the output of the scanner software 3. Themanipulation software 4 includes a body Volume calculator 11 and a health calculating device 19 both embodied as software. The manipulation means 4 passes the data from the data collection means 3 to the body volume calculator 11 with any additional information as appropriate. For example, the manipulation means may specify which body parts the volume calculator 11 should calculate the volume of. The output from the body volume calculator 11 passes to the health calculating device 19. The device 19 calculates a ratio between the first volume, corresponding to the first body part output by the volume calculator, and the second volume corresponding to the second body part output by the volume calculator. The manipulation means 4 also receives input from the body composition database means 51. The database means 51 contains information from medical Surveys, for example, on the composition of people of different sizes, shapes, gender, ages and ethnicity. Thus, by comparing theinformation entered into the manipulations means 4 about the person being scanned and themeasurements made from the three-dimensional model, the manipulation means 4 can extract the typical body composition for that person from the database means 51. This information is used by the malnutrition calculating device 19, in combination with the ratio between the first and second Volumes to generate the indication of a person’s level of malnutrition. The indication of a person's malnutrition obtained can be used by United Nations personnel to assess the level of a given group of persons level of malnutrition. This allows the United Nations personnel the ability to evaluate, assign and deploy the appropriate resources to better manage malnutrition in a given region of the world. The United Nations or non-governmental bodies can then better recommend preventative measures, to improve the health and nutrition of the persons in that region. The manipulation means 4 also receives input from a feedback means 52. The feedback means receiving information entered by a field worker working on behalf of the United Nations or anon-governmental agency, for example, about any health problems that have developed in the scannedperson. Such information can be used by the manipulation means can be used to validate or improve the indication of a person's health initially calculated by the malnutrition calculator 19. For example, if the indication of a person's malnutrition indicated that the person had a high risk of prospective serious illness or death, this information can be received by the feedback means 52. The malnutrition calculator 19 then alters an importance factor associated with the body volumes it used to calculate the indication of a person's health, so that subsequent calculations of people with a similar size, shape or composition yield an indication of malnutrition that emphasises the risk in that area to United Nations or non-governmental agency personnel. The feedback means 52 therefore provides the United Nations 1 with a means to validate and iteratively improve the accuracy of the results the malnutrition indicator 19 produces. The connection 5 may also be used to update the manipulation software 4 from a computer server (not shown) also connected to the Internet. The manipulation means 4 is also connected to an output means 12, which comprises a printer. The printer 12 is able to print a datasheet 13, 50 showing at least the output from the manipulation means 4. FIG.6 shows a flow chart of the scanning method. In use, a second person might oversee the scanning process using the rear-facing camera on a smartphone, or a person might scan themselves using the front-facing camera, set up in ‘selfie’ mode. Alternatively, a camera can be used. A person would be briefed to be scanned on the scanning process including what posture to adopt and how to initiate the scanning process. The person would undress to underwear or other tight fitting clothing to be scanned. The person is scanned, adopting the predetermined position of a star front on shape and a sideways on shape for the images to initiate the scanning process. The smartphones, tablets and cameras used by embodiments of the present invention are known and will not be described in detail. However, in summary, a plurality of 2-D images are sent to a cloud server 601 to extract body shape outlines in a specific pattern which is then representative of the person’s body. The resultant raw data comprises a 3-D cloud of data points that is processed by the data collection means 3 at step 605 to generate a “wire-frame' three-dimensional model of the person using machine learning and artificial intelligence at 7a to produce predictive body composition and other metrics. The raw or model data is stored in storage means 2, 4 of a ‘cloud server’ at 602. The stored data can be recalled from the storage means as and when required. The storage means may comprise memory, a hard disk and optical media or may be a remote device connected to the data collection by communication means.The communication means may be via the internet or offline in remote inaccessible areas to then beuploaded in future to the data storage systems. The data collection means 3 may also make simple calculations on the model data such as the height, or length of the person. Therefore, the model data and the calculations are received by the manipulation software 4. The data from the data collection means 3 is output to the manipulation software 4. The manipulation Software 4 is adapted to receive additional information about the person being scanned, such as the location of the region of a country. This additional information is received automatically via other external data input screens and / or blood pressure measurers (not shown). Further additional information is also inputted manually from records or by physically making measurements. There may also be an identifier code to identify an individual, without divulging their personal contact details or specific location. The information received automatically may be via a dedicated device interface or a serial connection, for example. It will be appreciated that any appropriate means for receiving the information may be employed. Step 603 represents at least the actions performed by the body volume calculator3, 24 and the malnutrition calculator 7a. The body volume calculator modifies the 3-D model data and applies a triple integration to calculate the level of malnutrition. It will be appreciated that any appropriate method may be used by the volume calculator to calculate the volume of the first body part and the second body parts to ascertain the level and predicted level of nutrition. The first and second volumes calculated from the model therefore correspond to the volume of the person or part volume thereof. The volume calculator 11 calculates at least the volume of a first part, such as the mid-section around the stomach, and a second part, which may comprise the volume of the person's whole body. The parts chosen may vary depending upon the person’s malnutrition problem or medical condition or the health risk to be predicted to assist with treatment thereof. The volumes of the various parts of the model calculated by the body volume calculator 7a are passed to the health-calculating device 7b via the cloud server. The volume of these predetermined parts, such as the abdominal region, upper arm, or hips for example, are then associated with an importance factor for malnutrition. Similarly, the importance factor associated with each part of the body will vary depending upon the person's malnutrition level or medical condition. The importance factor may be used to apply a bias to the volumes calculated for certain parts of the body, such as the abdomen. Thus, the indication of a person's malnutrition can take account of the impact on the health that different body fat and adipose tissue distributions will have. The use of importance factors could also be used to take account of the composition of different parts of the body due to differing bone, tissue or organ masses if the weight or body density of a person isused in the calculation of a person’s health, for anorexia, or for malnutritionHowever, in this embodiment the data collection means 3 is adapted to receive data from the body composition database. The data from the body composition database allows the malnutrition calculating device to estimate the level of malnutrition of the person being scanned. It will be appreciated that the importance factor may comprise a function, the coefficients of which may take account of sex, gender, ethnicity, age, other biometric data and the information from the feedback means. The health-calculating device then calculates an indication of the person's malnutrition using the ratio between the first and second volumes of the parts of the body and their associated importance factors. For example, for assessment of malnutrition purposes, the model of the body 14 may be separated into many parts, each being associated with an importance factor to obtain an accurate and representative indication of a person's health. The importance factor also allows for the natural differences in body shape caused by gender, age and ethnicity to be taken account of. Thus, the device may use the ratio of the volume of the person's abdominal region to the whole body volume and scale it appropriately by the importance factor. Alternatively, when the device 60 is used in a remote field location, the indication of a person’s malnutrition may be calculated using the volume of a person’s whole body. Once the manipulation software has performed its manipulation of the data output from the data collection software, a record is created of the person’s scan and the statistics calculated by the manipulation software. If the person has been scanned previously, the model data and other statistics are appended to the previously created record. The record is also stored and displayed to the person and / or operator on a display means (not shown). A datasheet 13 (or further datasheet if data of a previous scan is included) is printed at step 31 by the output means 12. Two exemplary views of the output from the display means from which the datasheet is printed is shown in FIGS.3 and 4. Thesheet includes an identifiable reference 35 for the scanned person 14 and measurements 36, 37, 38made from the three-dimensional model of the person’s body. The reference details may include an identification reference assigned to the person, their village, country, date of birth, medication being taken, allergies and details of their genetics, for example. The measurements 36, 37, 38 may include arm and leg lengths and widths and waist, hips, chest, bust, underbust, bicep, thigh and neck measurements, for example. The datasheet 13 also includes a graphical representation 40 of the three- dimensional model shown in front view and in side view. The provision of the graphical representation 40 creates an accurate image of their body more abstract than a photograph or reflection in a mirror, that can be used for more intuitive and detailed analysis of the nutrition requirements of a person. This is particularly useful for those suffering from eating disorders, such as anorexia, where the person believes, when looking at their body in the flesh, that they are overweight. Finally, a summary 41 of the statistics and the indication of the person's health and / or malnutrition status is provided calculated from the volumes of the first and second parts of the body. A further datasheet may be substantially similar to that shown in FIG.3, but will show any changes in the measurements and / or 3-D model. Thus, the further datasheet is a composite data sheet showing information from two or more data sheets. FIGS.4A and B show how the changes in the model may be represented in the composite datasheet. FIG. 4A shows the 3-D model after the person has been scanned for the first time. FIG.4B shows two 3-D model sections overlaid to show the change in body size and body shape. The composite data sheet may also include graphs showing the change said body volume calculator is configured to calculate from said three-dimensional model first volume comprising a first body part of said person and a second volume comprising a second body part of said person; said health calculating device is configured to calculate an indication of the health of said person using the body composition of said person by retrieving composition data from said body database and incorporating said composition data into said first volume and said second volume and calculating said indication using a ratio of said incorporated first volume to said incorporated second volume. In FIG.2, a file is created from the patient record that includes the three-dimensional model and the values calculated by the manipulation software 4. The file does not (although it may) contain the personal details of the scanned person, but only the identification reference. The file may be compressed and sent to the database means 7. The database means 7 in FIG.6 interprets the data and determines, from cross-referencing the identification reference with the contents of the database, whether the record is new or in addition to data already stored. Accordingly, the database means creates a new record or appends then data contained in the file to a previously created record and stores the record. The information store of the database means is secure to prevent unauthorised access to the data contained therein. The access means comprises a secure web-based interface. The interface allows secure access to the database means 7 by using registration details such as a username and password that is transmitted to the database means over a SSL connection. Thus, the access means transmits the appropriate record to the United Nations or World Health Organization (WHO) personnel and / or to the person represented. The record or records can then be viewed, printed or stored. FIG.7 shows a second datasheet 50 printed by printer 12. This datasheet shows a representation of the three-dimensional model 55 generated by the device 3. It also includes a plurality of measurements 56, some of which are calculated by the body volume calculator. In particular, the volume of the neck, upper torso, lower torso, abdomen, left arm, right arm, legs and total body is shown as calculated from the three dimensional model obtained by scanning the person. The indication of a person's malnutrition is given as a figure labelled BVI, for the Body Volume Index, which may be calculated using the ratios between the above-mentioned Volumes. Alternatively, a variant of an indicator of a person’s malnutrition, may be using a ratio of abdomenvolume to total body volume to highlight those with distended abdomens. Alternatively, a variant ofan indicator of a person’s nutrition could be using a ratio of arm volume to total body volume, possibly including leg volume as a comparative and linked indicator of malnutrition. Bicep circumference, measured digitally as opposed to manually, offers consistency and links to current methods as these involve BMI (height and weight only) and arm circumference, measured manually. The use of, and measurement of abdominal volume, arm volume and leg volume, as a proportion of total body volume, and measured digitally, will offer new insights and solutions to the management and delivery of solutions for malnutrition. For the avoidance of doubt, this invention relates to the measurement and prediction of malnutrition. It is not the measurement of obesity and health risk, as has been embodied in previous inventions by the same inventor, and by the same applicants. This invention is for the application of using part-volumes for more defined and better measurement at the opposite end of the spectrum of human existence; for obesity as opposed to malnutrition. The population in under-developed and developing nations are currently disenfranchised, deprived and disadvantaged of resources by being assessed incorrectly at the outset.

Claims

1. Claims 1. A system arranged to calculate one or more malnutrition indicators for an individual human being, comprising: processing circuitry arranged to: receive information about the individual, the information comprising demographic information of the individual, and at least two unique digital photographs of the individual, wherein the at least two unique digital photographs include a front-view image and a side-view image; extract measurements indicative of body shape from the at least two received unique digital photographs; generate a 3D model of the individual using the captured at least two unique digital photographs; retrieve information from a body composition or health database, the body composition database comprising internal body composition data and corresponding body shape and demographic data of other individual human beings, the retrieved information being selected based on identifying a subset of data in the database based on the received demographic information, and matching the measurements extracted from the captured at least two unique digital photographs to body shape datain the identified subset of data in the database;and, after retrieving the information, determine a value for the malnutrition indicator by combining one or more of the extracted measurements with the retrieved information from the body composition database.

2. The system of claim 1, in which the processing circuitry is provided by either or both of: (i) a smartphone or tablet camera, or a camera that is used to take the at least two uniquedigital photographs of the individual human being; and (ii) a server, wherein the server is a cloud server.

3. The system of claim 1 or claim 2, wherein the processing circuitry is arranged to extract, and use in the malnutrition indicator determination, one or more body surface area measurements.

4. The system of any preceding claim, wherein the processing circuitry is arranged to calculate a plurality of body part volumes of the individual based on the at least two received unique digital photographs, and to use the plurality of body part volumes in the malnutrition indicator determination.

5. The system of any preceding claim, wherein the malnutrition indicator is a Body Volume Index (BVI), and wherein determining the BVI comprises inputting at least one item of demographic information, at least one body part volume measurement and at least one body length measurement of the individual into an empirical formula for BVI, the empirical formula being determined from a database comprising corresponding demographic information, body part volume, length information and internal body composition data for a plurality of individuals.

6. The system of any preceding claim, wherein the body length measurement includes the circumference of the bicep in the upper arm, measured digitally in centimetres or inches.

7. The system of Claim 1 wherein there is receipt of demographic information of the individual and a single unique digital photograph of the individual via an internet connection, wherein the single unique digital photograph is a side-view image and the demographic information includes gender; 8. The system of claim 6, wherein bicep circumference is processed to obtain Total Body Fat and Visceral Fat data using abdominal volume and reference to MRI data, those data being provided as at least part of the internal body composition data.

9. The system of any preceding claim, wherein the demographic information comprises at least one of age, country of origin, location or region and gender.

10. The system of any preceding claim, wherein the processing circuitry is arranged to use atleast one body part volume measurement in the determination of the malnutrition indicator, the atleast one body part volume measurement optionally being or comprising abdominal volume.

11. The system of any preceding claim, wherein the processing circuitry is arranged to use at least one body length measurement in the determination of the malnutrition indicator, the at least onebody length measurement optionally comprising at least one of height, and waist girth.

12. The system of any preceding claim, wherein the first database further comprises supplemental malnutrition information for the individual provided by at least one of a third party and the individual human being.

13. A method of calculating one or more malnutrition indicators for an individual human being, the method comprising: receiving information about the individual, the information comprising demographic information of the individual, and at least two unique digital photographs of the individual, wherein the at least two unique digital photographs include a front-view image and a side-view image; extracting measurements indicative of body shape from the at least two received unique digital photographs; generating a 3D model of the individual using the captured at least two unique digital photographs; retrieving information from a body composition database, the body composition database comprising internal body composition data and corresponding body shape and demographic data of other individual human beings, the retrieved information being selected based on identifying a subset of data in the database based on the received demographic information, and matching the measurements extracted from the captured at least two unique digital photographs to body shape datain the identified subset of data in the database;and, after retrieving the information, determining a value for the malnutrition indicator by combining one or more of the extracted measurements with the retrieved information from the body composition database.

14. The method of claim 13, further comprising capturing the at least two unique digital photographs of the individual, the at least two unique digital photographs of the individual optionallybeing captured using a camera of a smartphone or tablet, or another camera.

15. The method of claim 13 or claim 14, further comprising displaying at least one of the determined malnutrition indicators and the generated 3D model on a screen, the screen optionally being a screen of a smartphone of the individual.

16. The method of any of claims 13 to 15, comprising calculating a plurality of body part volumes of the individual based on the at least two received unique digital photographs, and using the plurality of body part volumes in the malnutrition indicator determination.

17. The method of any of claims 13 to 16, further comprising inputting at least one of the following: (i) a weight of the individual; and (ii) a measure of malnutrition level of the individual. (iii) a measure of the malnutrition level of individuals in a given location (iv) a measure of risk of death for individuals in a given location.

18. The method of any of claims 13 to 17, wherein the demographic information comprises at least one of age, ethnic origin and gender.

19. The method of any of claims 13 to 18, wherein the step of extracting measurements comprises extracting at least one body length measurement, the at least one body length measurement comprising at least one of height, hip girth, and waist girth.

20. A machine readable medium containing instructions which, when read by a machine, causes that machine to perform the method of any of claims 13 to 19.

21. The machine readable medium of Claim 20, wherein the performed method further comprises the step of altering a coefficient using an artificial intelligence module.

22. The machine readable medium of Claim 20, wherein the performed method is arranged to be implemented by an Application Programming Interface, API.

23. The machine readable medium of Claim 20, wherein the performed method further comprises using artificial intelligence to determine the malnutrition indicator value.

24. Use of a malnutrition indicator determined: (i) according to the method of any of claims 13 to 23 ; and / or (ii) using the system of any of claims 1 to 12; in the calculation of a malnutrition improvement and prevention programme.

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