U.S. patent application number 12/549958 was filed with the patent office on 2010-03-11 for processes and systems for achieving and assisting in improved nutrition.
Invention is credited to Wanema Frye, Ute Gerwig, Dawn Halkuff, Christine Jacobsohn, Maria Kinirons, Karen Miller-Kovach, Julia Peetz, Stephanie Lyn Rost.
Application Number | 20100062119 12/549958 |
Document ID | / |
Family ID | 41721934 |
Filed Date | 2010-03-11 |
United States Patent
Application |
20100062119 |
Kind Code |
A1 |
Miller-Kovach; Karen ; et
al. |
March 11, 2010 |
Processes and Systems for Achieving and Assisting in Improved
Nutrition
Abstract
Processes are provided for controlling body weight of a
consumer, as well as for selecting and purchasing foods, and for
producing food products, based on a combination of food energy data
and further nutritional data for a candidate food conveyed by an
integrated image. Related processes and systems are also provided
for assisting in the foregoing processes.
Inventors: |
Miller-Kovach; Karen;
(Charleston, SC) ; Gerwig; Ute; (Dusseldorf,
DE) ; Peetz; Julia; (Dusseldorf, DE) ;
Jacobsohn; Christine; (Dusseldorf, DE) ; Frye;
Wanema; (Overland Park, KS) ; Rost; Stephanie
Lyn; (Jersey City, NJ) ; Kinirons; Maria;
(East Islip, NY) ; Halkuff; Dawn; (New York,
NY) |
Correspondence
Address: |
PATENT DOCKET CLERK;COWAN, LIEBOWITZ & LATMAN, P.C.
1133 AVENUE OF THE AMERICAS
NEW YORK
NY
10036
US
|
Family ID: |
41721934 |
Appl. No.: |
12/549958 |
Filed: |
August 28, 2009 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
61092981 |
Aug 29, 2008 |
|
|
|
Current U.S.
Class: |
426/232 ;
426/231; 434/127; 705/26.1 |
Current CPC
Class: |
G06Q 50/10 20130101;
G09B 19/0092 20130101; G06F 19/00 20130101; G09B 5/02 20130101;
A23V 2002/00 20130101; A23L 33/30 20160801; G06Q 30/0635 20130101;
G06Q 99/00 20130101; G01N 33/02 20130101; G16Z 99/00 20190201; G06Q
30/0601 20130101; G16H 20/60 20180101; G06Q 30/0623 20130101 |
Class at
Publication: |
426/232 ;
426/231; 434/127; 705/27 |
International
Class: |
G01N 33/02 20060101
G01N033/02; G09B 19/00 20060101 G09B019/00; G06Q 30/00 20060101
G06Q030/00 |
Claims
1. A process for controlling body weight of a consumer, comprising,
for each of a plurality of candidate food servings, viewing each of
a plurality of images each associated with a respective one of the
plurality of candidate food servings and integrating a numeral
representing an energy content of the candidate food serving and an
auxiliary image feature representing a nutritional characteristic
of the candidate food serving other than its energy content;
selecting ones of the plurality of candidate food servings based on
the numeral and the auxiliary image feature in each of the viewed
plurality of associated images, such that a sum of the numerals in
the images associated with the selected food servings bears a
predetermined relationship to predetermined food energy benchmark
data for the consumer in a given period; and ingesting the selected
food servings.
2. The process of claim 1, wherein the auxiliary image feature
represents relative healthfulness data of the candidate food
serving.
3. The process of claim 2, wherein the relative healthfulness data
of the candidate food serving is based on (a) a selected respective
procedure for processing nutritional data of foods in a respective
food group comprising the candidate food serving, the respective
food group being one of a plurality of food groups of a respective
metagroup of a plurality of metagroups, each of the metagroups
comprising a plurality of food groups and having a different
respective procedure for processing the nutritional data of foods
in the food groups within such metagroup, and (b) selected
respective comparison data for the corresponding food group, at
least some of the food groups in each metagroup having different
respective comparison data than other food groups in such
metagroup.
4. The process of claim 2, wherein the relative healthfulness data
of the candidate food serving is based on a linear combination of
selected nutrient amounts present therein.
5. The process of claim 1, wherein the food energy data is based on
a human being's metabolic efficiency in utilizing first and second
nutrients in the candidate food servings as energy.
6. The process of claim 1, wherein the food energy data is based on
an energy contribution of each of its protein content, its
carbohydrate content, its dietary fiber content and its fat
content.
7. A process for assisting a consumer in evaluating food to be
purchased or consumed thereby, comprises: in a data processing
system, receiving input data representing a food to be purchased or
consumed by a consumer; in the data processing system, obtaining an
image dataset based on the input data, the image dataset including
numeral data representing an energy content of the food to be
purchased or consumed and an auxiliary image feature representing a
further nutritional characteristic of the food to be purchased or
consumed other than its energy content; and at least one of (a)
communicating the image dataset to a presentation device for
presentation to the consumer, and (b) presenting an image to the
consumer based on the image dataset, the image integrating the
numeral and the auxiliary image feature to convey the energy
content and the further nutritional characteristic of the food to
be purchased or consumed to the consumer.
8. The process of claim 7, wherein the auxiliary image feature
represents a relative healthfulness data of the food to be
purchased or consumed.
9. The process of claim 8, wherein the relative healthfulness data
of the food to be purchased or consumed is based on (a) a selected
respective procedure for processing nutritional data of foods in a
respective food group comprising the food to be purchased or
consumed, the respective food group being one of a plurality of
food groups of a respective metagroup of a plurality of metagroups,
each of the metagroups comprising a plurality of food groups and
having a different respective procedure for processing the
nutritional data of foods in the food groups within such metagroup,
and (b) selected respective comparison data for the corresponding
food group, at least some of the food groups in each metagroup
having different respective comparison data than other food groups
in such metagroup.
10. The process of claim 8, wherein the relative healthfulness data
of the food to be purchased or consumed is based on a linear
combination of selected nutrient amounts present therein.
11. The process of claim 7, wherein the food energy data is based
on a human being's metabolic efficiency in utilizing first and
second nutrients in the food to be purchased or consumed as
energy.
12. The process of claim 7, wherein the food energy data of the
food to be purchased or consumed is based on an energy contribution
of each of its protein content, its carbohydrate content, its
dietary fiber content and its fat content.
13. A process for selecting and purchasing food comprises viewing
an image associated with a respective food offered for purchase,
the image integrating a numeral representing an energy content of
the respective food and an auxiliary image feature representing a
further nutritional characteristic of the respective food other
than its energy content; selecting the respective food based on the
numeral and the auxiliary image feature in the viewed image; and
purchasing the selected respective food.
14. The process of claim 13, wherein the auxiliary image feature
represents relative healthfulness data of the respective food.
15. The process of claim 14, wherein the relative healthfulness
data of the respective food is based on (a) a selected respective
procedure for processing nutritional data of foods in a respective
food group comprising t the respective food, the respective food
group being one of a plurality of food groups of a respective
metagroup of a plurality of metagroups, each of the metagroups
comprising a plurality of food groups and having a different
respective procedure for processing the nutritional data of foods
in the food groups within such metagroup, and (b) selected
respective comparison data for the corresponding food group, at
least some of the food groups in each metagroup having different
respective comparison data than other food groups in such
metagroup.
16. The process of claim 14, wherein the relative healthfulness
data of the respective food is based on a linear combination of
selected nutrient amounts present therein.
17. The process of claim 13, wherein the food energy data is based
on a human being's metabolic efficiency in utilizing first and
second nutrients in the respective food as energy.
18. The process of claim 13, wherein the food energy data of the
respective food is based on an energy contribution of each of its
protein content, its carbohydrate content, its dietary fiber
content and its fat content.
19. A system for assisting a consumer in evaluating food to be
purchased or consumed thereby, comprises: an input operative to
receive input data representing a food to be purchased or consumed
by a consumer; a processor coupled with the input to receive the
input data and operative to obtain an image dataset based on the
input data, the image dataset including numeral data representing
an energy content of the food to be purchased or consumed and an
auxiliary image feature representing a further nutritional
characteristic of the food to be purchased or consumed other than
its energy content; and at least one of (a) communications coupled
with the processor to receive the image dataset therefrom and to
communicate the image dataset to a device for presentation to the
consumer, and (b) a presentation device coupled with the processor
to receive the image dataset and operative to present an image to
the consumer based on the image dataset, the image integrating the
numeral and the auxiliary image feature to convey the energy
content and further nutritional characteristic of the food to be
purchased or consumed to the consumer.
20. The system of claim 19, wherein the auxiliary image feature
represents relative healthfulness data of the food to be purchased
or consumed.
21. The system of claim 20, wherein the relative healthfulness data
of the food to be purchased or consumed is based on (a) a selected
respective procedure for processing nutritional data of foods in a
respective food group comprising t the food to be purchased or
consumed, the respective food group being one of a plurality of
food groups of a respective metagroup of a plurality of metagroups,
each of the metagroups comprising a plurality of food groups and
having a different respective procedure for processing the
nutritional data of foods in the food groups within such metagroup,
and (b) selected respective comparison data for the corresponding
food group, at least some of the food groups in each metagroup
having different respective comparison data than other food groups
in such metagroup.
22. The system of claim 20, wherein the relative healthfulness data
of the food to be purchased or consumed is based on a linear
combination of selected nutrient amounts present therein.
23. The system of claim 19, wherein the food energy data is based
on a human being's metabolic efficiency in utilizing first and
second nutrients in the food to be purchased or consumed.
24. The system of claim 19, wherein the food energy data of the
food to be purchased or consumed is based on an energy contribution
of each of its protein content, its carbohydrate content, its
dietary fiber content and its fat content.
25. A process for producing a food product having food energy data
and further nutritional data associated therewith, comprising,
obtaining a food product, supplying at least one of food
identification data and food nutrient data of the food product;
obtaining food energy data and further nutritional data for the
food product representing a nutritional characteristic thereof
other than energy content, based on the at least one of food
identification data and food nutrient data of the food product; and
associating an integrated image representing the food energy data
and the further nutritional data with the food product, the
integrated image depicting a numeral and an auxiliary image feature
to convey the energy content and further nutritional characteristic
of the food product respectively.
26. The process of claim 25, wherein obtaining the food product
comprises producing the food product.
27. The process of claim 25, comprising associating the integrated
image with the food product by including the integrated image on a
substrate associated with the food product.
28. The process of claim 27, wherein the substrate comprises a
package for the food product.
29. The process of claim 27, wherein the substrate comprises a
label accompanying the food product.
Description
BENEFIT AND RELATED APPLICATIONS
[0001] This application claims the benefit of U.S. provisional
patent application No. 61/092,981, filed Aug. 29, 2008, in the
names of Karen Miller-Kovach, Ute Gerwig, Julia Peetz, Christine
Jacobsohn, Wanema Frye, Stephanie Lyn Rost and Maria Kinirons. The
present application is related to U.S. patent application Ser. No.
______, entitled Processes and Systems Based on Metabolic
Conversion Efficiency (Attorney docket No. 26753.006); U.S. patent
application Ser. No. ______, entitled Processes and Systems Based
on Dietary Fiber as Energy (Attorney docket No. 26753.008); U.S.
patent application Ser. No. ______, entitled Processes and Systems
Using and Producing Food Healthfulness Data based on Food
Metagroups (Attorney docket No. 26753.010); U.S. patent application
Ser. No. ______, entitled Processes and Systems Using and Producing
Food Healthfulness Data based on Linear Combinations of Nutrients
(Attorney docket No. 26753.012); and U.S. patent application Ser.
No. ______, entitled Processes and Systems for Achieving and
Assisting in Improved Nutrition based on Food Energy Data and
Relative Healthfulness Data (Attorney docket No. 26753.016), each
of which is filed concurrently herewith and all of which are hereby
incorporated herein by reference in their entireties.
FIELD OF THE INVENTION
[0002] Processes are provided for selecting, ingesting and/or
purchasing foods for achieving weight control and/or healthful
nutrition, as well as processes for producing food products, and
systems for assisting with each of the foregoing.
BACKGROUND OF THE INVENTION
[0003] Weight Watchers International, Inc. is the world's leading
provider of weight management services, operating globally through
a network of Company-owned and franchise operations. Weight
Watchers provides a wide range of products, publications and
programs for those interested in weight loss and weight control.
With over four decades of weight management experience, expertise
and know-how, Weight Watchers has become one of the most recognized
and trusted brand names among weight conscious consumers.
[0004] Years ago, Weight Watchers pioneered innovative and
successful methods for weight control and systems for assisting
consumers in practicing such methods. Such methods and systems are
the subjects of U.S. Pat. No. 6,040,531; U.S. Pat. No. 6,436,036;
U.S. Pat. No. 6,663,564; U.S. Pat. No. 6,878,885 and U.S. Pat. No.
7,361,143, each of which is incorporated herein by reference in its
entirety. These methods assign values to food servings based on
their calorie content, which is increased on the basis of fat
content and decreased on the basis of dietary fiber content. This
assignment is carried out using a proprietary formula developed by
Weight Watchers scientists. The values for food servings consumed
each day are summed and the consumer ensures that they do not
exceed a predetermined maximum value. These methods afford a simple
and effective weight control framework, especially for those who
cannot devote substantial attention to their weight control
efforts.
[0005] While the existing Weight Watchers.RTM. program has provided
consumers with effective techniques that have assisted millions in
their efforts to lose excess body weight using its proprietary
formula, consumers have long expressed a desire that the formula
reflect the relative satiety of different foods. Unfortunately,
until now it has not been possible to quantify the aspect of
satiety so that it could be incorporated in such a formula.
[0006] While consumers are striving to control their body weight,
whether for the object of losing or gaining weight, or simply to
maintain the weight they have, they are also eager to ensure that
they are eating healthfully. Both government and private entities
are attempting to implement measures to educate consumers so that
they might chose and consume healthier foods. In the United States
of America (US), food products are required to display lists of
ingredients and provide additional information such as the content
of each macronutrient, total calories and content of nutrients such
as sodium and saturated fat that are particularly important to
those with cardiovascular diseases.
[0007] The Food Standards Agency of the United Kingdom has
implemented a food labeling system termed the "Traffic Light
Labeling" system that encourages food manufacturers to label their
foods in a standard fashion to enable consumers to compare one
product against another by comparing the amounts of four different
nutrients in each, including fat, saturated fat or "saturates",
sugar and salt, and, in some cases, calorie content. For each
nutrient, and the calorie content (if displayed), a color code is
provided to indicate whether the amount of that nutrient is "high"
(red color code), "medium" (amber color code) or "low" (green color
code). For those keeping track of one or more particular nutrients,
such as sodium and saturated fat in the case of those with a
cardiovascular condition, this labeling system can be quite
effective. But for those trying to develop an overall sense of the
healthfulness of each food product they are considering for
purchase and/or consumption, a considerable amount of judgment may
be necessary to determine whether to purchase or consume a
particular food product.
[0008] Published PCT application WO 98/45766 to Sanchez proposes a
food group nutritional value calculator that inputs data such as
that displayed in following the Traffic Light Labeling system along
with a consumer's selection of one of eight "food groups". Based on
the food group selection, the calculator carries out a
corresponding decision-tree algorithm by comparing the input
amounts of selected nutrients against standard values specific to
each of the separate food groups. Based on one or more such
comparisons, the food is classified as either "Excellent", "Very
Good", "Good" or "Avoid".
[0009] Consumers often are confused by the extensive nutritional
information printed on the packaging of foods. Some simply find it
too burdensome to read such information, often in relatively fine
print so that it can all fit in the available space, and then weigh
the relative merits and undesirable aspects of such information.
While the Traffic Light system provides a degree of simplification
to this process, it is still necessary for the consumer to look for
additional information on the packaging in order to acquire
information desired by those attempting to maintain, lose or gain
weight.
DISCLOSURE
[0010] FIGS. 1 through 9 are tables of data used in processes
disclosed herein for producing data representing the relative
healthfulness of various foods;
[0011] FIG. 10 is a flow chart illustrating certain disclosed
processes for weight control and selecting foods to be consumed
based on a desired nutritional characteristic;
[0012] FIGS. 11A through 11D illustrate exemplary images for use in
conveying energy content data and nutritional characteristic data
of foods;
[0013] FIG. 12 is a flow chart illustrating a process for selecting
and purchasing foods based on their energy content and a desired
nutritional characteristic;
[0014] FIG. 13 illustrates certain embodiments of a data processing
system useful in the processes disclosed herein;
[0015] FIG. 14 illustrates certain embodiments of a client/server
system useful in the processes disclosed herein; and
[0016] FIG. 15 is a flow chart for illustrating certain embodiments
of a process for producing a food product.
[0017] For this application the following terms and definitions
shall apply:
[0018] The term "energy content" as used herein refers to the
energy content of a given food, whether or not adjusted for the
metabolic conversion efficiency of one or more nutrients in the
food.
[0019] The term "metabolic conversion efficiency" as used herein
includes both absolute measures of metabolic conversion efficiency
and the metabolic conversion efficiency of nutrients relative to
each other.
[0020] The term "healthfulness" as used herein to refer to a food
or type of food refers to either or both of (a) the presence and/or
amount of one or more nutrients therein which can be detrimental to
a consumer's health, and (b) a characteristic thereof which tends
to promote healthful nutrition, whether evaluated on a relative or
absolute basis.
[0021] The term "energy density" as used herein to refer to a food
or type of food refers to an evaluation thereof that reflects its
energy content relative to an amount thereof, whether expressed on
an absolute basis or relative to the energy density of one or more
other foods or types of foods.
[0022] The term "data" as used herein means any indicia, signals,
marks, symbols, domains, symbol sets, representations, and any
other physical form or forms representing information, whether
permanent or temporary, whether visible, audible, acoustic,
electric, magnetic, electromagnetic or otherwise manifested. The
term "data" as used to represent predetermined information in one
physical form shall be deemed to encompass any and all
representations of corresponding information in a different
physical form or forms.
[0023] The term "presentation data" as used herein means data to be
presented to a user in any perceptible form, including but not
limited to, visual form and aural form. Examples of presentation
data include data displayed on a visual presentation device, such
as a monitor, and data printed on paper.
[0024] The term "presentation device" as used herein means a device
or devices capable of presenting data to a user in any perceptible
form.
[0025] The term "database" as used herein means an organized body
of related data, regardless of the manner in which the data or the
organized body thereof is represented. For example, the organized
body of related data may be in the form of one or more of a table,
a map, a grid, a packet, a datagram, a frame, a file, an e-mail, a
message, a document, a list or in any other form.
[0026] The term "image dataset" as used herein means a database
suitable for use as presentation data or for use in producing
presentation data.
[0027] The term "auxiliary image feature" as used herein means one
or more of the color, brightness, shading, shape or texture of an
image.
[0028] The term "network" as used herein includes both networks and
internetworks of all kinds, including the Internet, and is not
limited to any particular network or inter-network. For example,
"network" includes those that are implemented using wired links,
wireless links or any combination of wired and wireless links.
[0029] The terms "first", "second", "primary" and "secondary" are
used to distinguish one element, set, data, object, step, process,
activity or thing from another, and are not used to designate
relative position or arrangement in time, unless otherwise stated
explicitly.
[0030] The terms "coupled", "coupled to", and "coupled with" as
used herein each mean a relationship between or among two or more
devices, apparatus, files, circuits, elements, functions,
operations, processes, programs, media, components, networks,
systems, subsystems, and/or means, constituting any one or more of
(a) a connection, whether direct or through one or more other
devices, apparatus, files, circuits, elements, functions,
operations, processes, programs, media, components, networks,
systems, subsystems, or means, (b) a communication relationship,
whether direct or through one or more other devices, apparatus,
files, circuits, elements, functions, operations, processes,
programs, media, components, networks, systems, subsystems, or
means, and/or (c) a functional relationship in which the operation
of any one or more devices, apparatus, files, circuits, elements,
functions, operations, processes, programs, media, components,
networks, systems, subsystems, or means depends, in whole or in
part, on the operation of any one or more others thereof.
[0031] The terms "communicate," "communicating" and "communication"
as used herein include both conveying data from a source to a
destination, and delivering data to a communication medium, system,
channel, network, device, wire, cable, fiber, circuit and/or link
to be conveyed to a destination. The term "communications" as used
herein includes one or more of a communication medium, system,
channel, network, device, wire, cable, fiber, circuit and link.
[0032] The term "processor" as used herein means processing
devices, apparatus, programs, circuits, components, systems and
subsystems, whether implemented in hardware, software or both, and
whether or not programmable. The term "processor" as used herein
includes, but is not limited to one or more computers, hardwired
circuits, neural networks, signal modifying devices and systems,
devices and machines for controlling systems, central processing
units, programmable devices and systems, field programmable gate
arrays, application specific integrated circuits, systems on a
chip, systems comprised of discrete elements and/or circuits, state
machines, virtual machines, data processors, processing facilities
and combinations of any of the foregoing.
[0033] The term "data processing system" as used herein means a
system implemented at least in part by hardware and comprising a
data input device, a data output device and a processor coupled
with the data input device to receive data therefrom and coupled
with the output device to provide processed data thereto.
[0034] The terms "obtain", "obtained" and "obtaining", as used with
respect to a processor or data processing system mean (a) producing
data by processing data, (b) retrieving data from storage, or (c)
requesting and receiving data from a further data processing
system.
[0035] The terms "storage" and "data storage" as used herein mean
one or more data storage devices, apparatus, programs, circuits,
components, systems, subsystems, locations and storage media
serving to retain data, whether on a temporary or permanent basis,
and to provide such retained data.
[0036] The terms "food serving identification data" and "food
serving ID data" as used herein mean data of any kind that is
sufficient to identify a food and to convey an amount thereof,
whether by mass, weight, volume, or size, or by reference to a
standard or otherwise defined food serving, or by amounts of
constituents thereof. The terms "amount" and "amounts" as used
herein refer both to absolute and relative measures.
[0037] The terms "food identification data" and "food ID data" as
used herein mean data of any kind that is sufficient to identify a
food, whether or not such data conveys an amount thereof.
[0038] A process for controlling body weight of a consumer
comprises, for each of a plurality of candidate food servings,
viewing each of a plurality of images each associated with a
respective one of the plurality of candidate food servings and
integrating a numeral representing an energy content of the
candidate food serving and an auxiliary image feature representing
a nutritional characteristic of the candidate food serving other
than its energy content; selecting ones of the plurality of
candidate food servings based on the numeral and the auxiliary
image feature in each of the viewed plurality of associated images,
such that a sum of the numerals in the images associated with the
selected food servings bears a predetermined relationship to
predetermined food energy benchmark data for the consumer in a
given period; and ingesting the selected food servings.
[0039] In certain embodiments, the food energy data is based on a
human being's metabolic efficiency in utilizing first and second
nutrients in the candidate food servings as energy. In certain
embodiments, the food energy data is based on an energy
contribution of each of its protein content, its carbohydrate
content, its dietary fiber content and its fat content.
[0040] In certain embodiments, the auxiliary image feature
represents relative healthfulness of the candidate food servings.
In certain ones of such embodiments, the relative healthfulness of
each respective one of the candidate food servings is based on (a)
a selected respective procedure for processing nutritional data of
foods in a respective food group comprising respective one of the
candidate food servings, the respective food group being one of a
plurality of food groups of a respective metagroup of a plurality
of metagroups, each of the metagroups comprising a plurality of
food groups and having a different respective procedure for
processing the nutritional data of foods in the food groups within
such metagroup, and (b) selected respective comparison data for the
corresponding food group, at least some of the food groups in each
metagroup having different respective comparison data than other
food groups in such metagroup. In certain ones of such embodiments,
the relative healthfulness data of each of the candidate food
servings is based on a linear combination of selected nutrient
amounts present therein.
[0041] A process for assisting a consumer in evaluating food to be
purchased or consumed thereby, comprises: in a data processing
system, receiving input data representing a food to be purchased or
consumed by a consumer; in the data processing system, obtaining an
image dataset based on the input data, the image dataset including
numeral data representing an energy content of the food to be
consumed and an auxiliary image feature representing a further
nutritional characteristic of the food to be consumed other than
its energy content; and at least one of (a) communicating the image
dataset to a presentation device for presentation to the consumer,
and (b) presenting an image to the consumer based on the image
dataset, the image integrating the numeral and the auxiliary image
feature to convey the energy content and the further nutritional
characteristic of the food to be purchased or consumed to the
consumer.
[0042] In certain embodiments, the energy content of the food to be
purchased or consumed is based on a human being's metabolic
efficiency in utilizing first and second nutrients therein as
energy. In certain embodiments, the energy content of the food to
be purchased or consumed is based on an energy contribution of each
of its protein content, its carbohydrate content, its dietary fiber
content and its fat content.
[0043] In certain embodiments, the auxiliary image feature
represents relative healthfulness of the food to be purchased or
consumed. In certain ones of such embodiments, the relative
healthfulness of the food to be purchased or consumed is based on
(a) a selected respective procedure for processing nutritional data
of foods in a respective food group comprising the food to be
purchased or consumed, the respective food group being one of a
plurality of food groups of a respective metagroup of a plurality
of metagroups, each of the metagroups comprising a plurality of
food groups and having a different respective procedure for
processing the nutritional data of foods in the food groups within
such metagroup, and (b) selected respective comparison data for the
corresponding food group, at least some of the food groups in each
metagroup having different respective comparison data than other
food groups in such metagroup. In certain ones of such embodiments,
the relative healthfulness data of the food to be purchased or
consumed is based on a linear combination of selected nutrient
amounts present therein
[0044] A process for selecting and purchasing food comprises
viewing an image associated with a respective food offered for
purchase, the image integrating a numeral representing an energy
content of the respective food and an auxiliary image feature
representing a further nutritional characteristic of the respective
food other than its energy content; selecting the respective food
based on the numeral and the auxiliary image feature in the viewed
image; and purchasing the selected respective food.
[0045] In certain embodiments, the energy content of the respective
food offered for purchase is based on a human being's metabolic
efficiency in utilizing first and second nutrients therein as
energy. In certain embodiments, the energy content of the
respective food offered for purchase is based on an energy
contribution of each of its protein content, its carbohydrate
content, its dietary fiber content and its fat content.
[0046] In certain embodiments, the auxiliary image feature
represents relative healthfulness of the respective food offered
for purchase. In certain ones of such embodiments, the relative
healthfulness of the respective food offered for purchase is based
on (a) a selected respective procedure for processing nutritional
data of foods in a respective food group comprising the respective
food offered for purchase, the respective food group being one of a
plurality of food groups of a respective metagroup of a plurality
of metagroups, each of the metagroups comprising a plurality of
food groups and having a different respective procedure for
processing the nutritional data of foods in the food groups within
such metagroup, and (b) selected respective comparison data for the
corresponding food group, at least some of the food groups in each
metagroup having different respective comparison data than other
food groups in such metagroup. In certain ones of such embodiments,
the relative healthfulness data of the respective food offered for
purchase is based on a linear combination of selected nutrient
amounts present therein
[0047] A system for assisting a consumer in evaluating food to be
purchased or consumed thereby, comprises: an input operative to
receive input data representing a food to be purchased or consumed
by a consumer; a processor coupled with the input to receive the
input data and operative to obtain an image dataset based on the
input data, the image dataset including numeral data representing
an energy content of the food to be purchased or consumed and an
auxiliary image feature representing a further nutritional
characteristic of the food to be purchased or consumed other than
its energy content; and at least one of (a) communications coupled
with the processor to receive the image dataset therefrom and to
communicate the image dataset to a device for presentation to the
consumer, and (b) a presentation device coupled with the processor
to receive the image dataset and operative to present an image to
the consumer based on the image dataset, the image integrating the
numeral and the auxiliary image feature to convey the energy
content and further nutritional characteristic of the food to be
purchased or consumed to the consumer.
[0048] In certain embodiments, the energy content of the food to be
purchased or consumed is based on a human being's metabolic
efficiency in utilizing first and second nutrients therein as
energy. In certain embodiments, the energy content of the food to
be purchased or consumed is based on an energy contribution of each
of its protein content, its carbohydrate content, its dietary fiber
content and its fat content.
[0049] In certain embodiments, the auxiliary image feature
represents relative healthfulness of the food to be purchased or
consumed. In certain ones of such embodiments, the relative
healthfulness of the food to be purchased or consumed is based on
(a) a selected respective procedure for processing nutritional data
of foods in a respective food group comprising the food to be
purchased or consumed, the respective food group being one of a
plurality of food groups of a respective metagroup of a plurality
of metagroups, each of the metagroups comprising a plurality of
food groups and having a different respective procedure for
processing the nutritional data of foods in the food groups within
such metagroup, and (b) selected respective comparison data for the
corresponding food group, at least some of the food groups in each
metagroup having different respective comparison data than other
food groups in such metagroup. In certain ones of such embodiments,
the relative healthfulness data of the food to be purchased or
consumed is based on a linear combination of selected nutrient
amounts present therein
[0050] A process for producing a food product having food energy
data and further nutritional data associated therewith comprises
supplying at least one of food identification data and food
nutrient data of a food product; obtaining food energy data and
further nutritional data for the food product representing a
nutritional characteristic thereof other than energy content, based
on the at least one of food identification data and food nutrient
data of the food product; and associating an integrated image
representing the food energy data and the further nutritional data
with the food product, the integrated image depicting a numeral and
an auxiliary image feature to convey the energy content and further
nutritional characteristic of the food product respectively.
[0051] In certain embodiments, the integrated image is associated
with the food product by including the integrated image on a
substrate associated with the food product. In certain ones of such
embodiments, the substrate comprises packaging for the food
product. In certain ones of such embodiments, the substrate
comprises a label accompanying the food product. In certain
embodiments, the food energy data of the food product is based on a
human being's metabolic efficiency in utilizing first and second
nutrients therein as energy. In certain embodiments, the food
energy data of the food product is based on an energy contribution
of each of its protein content, its carbohydrate content, its
dietary fiber content and its fat content.
[0052] In certain embodiments, the auxiliary image feature
represents relative healthfulness of the food product. In certain
ones of such embodiments, the relative healthfulness of the food
product is based on (a) a selected respective procedure for
processing nutritional data of foods in a respective food group
comprising the food product, the respective food group being one of
a plurality of food groups of a respective metagroup of a plurality
of metagroups, each of the metagroups comprising a plurality of
food groups and having a different respective procedure for
processing the nutritional data of foods in the food groups within
such metagroup, and (b) selected respective comparison data for the
corresponding food group, at least some of the food groups in each
metagroup having different respective comparison data than other
food groups in such metagroup. In certain ones of such embodiments,
the relative healthfulness data of the food product is based on a
linear combination of selected nutrient amounts present
therein.
[0053] In certain embodiments, obtaining food energy data and
further nutritional data for the food product comprises obtaining
an image dataset representing the integrated image. In certain ones
of such embodiments, the image dataset is obtained in electronic
form, for example, via a network or on a storage medium. In certain
ones of such embodiments, the image dataset is obtained in a
visually perceptible form, such as in printed materials or
otherwise on a substrate.
[0054] Food servings can be specified in various ways, and
preferably in ways that are meaningful to consumers according to
their local dining customs. Food servings may be specified by
weight, mass, size or volume, or according to customary ways of
consuming food in the relevant culture. For example, in the United
States it is customary to use measures such as cups, quarts,
teaspoons, tablespoons, ounces, pounds, or even a "pinch", in
Europe, it is more common to use units such as liters, deciliters,
grams and kilograms. In China and Japan it is also appropriate to
use a measure such as a standard mass or weight held by chopsticks
when consuming food.
[0055] In certain embodiments, food energy data is produced based
on protein energy data representing the protein energy content,
carbohydrate energy data representing the carbohydrate energy
content and fat energy data representing the fat energy content, of
a candidate food serving, by applying respective weight data to
weight each of the protein energy data, the carbohydrate energy
data and the fat energy data, each of the weight data representing
the relative metabolic conversion efficiency of the corresponding
nutrient and forming the food energy data based on a sum of the
weighted protein energy data, the weighted carbohydrate energy data
and the weighted fat energy data. The data for the various
nutrients is provided either by the consumer or by another source
based on data from the consumer, such as food identification data.
If the protein energy data is represented as "PRO", the
carbohydrate energy data as "CHO" and the fat energy data as "FAT",
in certain ones of such embodiments, the food energy data
(represented as "FED") is obtained by processing the data in the
manner represented by the following equation:
FED=(Wpro.times.PRO)+(Wcho.times.CHO)+(Wfat.times.FAT), (1)
[0056] where Wpro represents the respective weighting data for PRO,
Wcho represents the respective weighting data for CHO and Wfat
represents the respective weighting data for FAT. In certain ones
of such embodiments, Wpro is selected from the range
0.7.ltoreq.Wpro.ltoreq.0.8, Wcho is selected from the range
0.9.ltoreq.Wcho.ltoreq.0.95 and Wfat is selected from the range
0.97.ltoreq.Wfat.ltoreq.1.0. In certain ones of such embodiments,
Wpro is substantially equal to 0.8, Wcho is substantially equal to
0.95 and Wfat is substantially equal to 1.0. Various measures of
energy can be employed, such as kilocalories (kcal) and kilojoules
(kJ).
[0057] In certain embodiments, food energy data is produced based
on protein data representing the mass or weight of the protein
content (represented as PROm), carbohydrate data representing the
mass or weight of the carbohydrate content (represented as CHOm)
and fat data representing the mass or weight of the fat content
(represented as FATm), of a candidate food serving. In such
embodiments, the protein data, carbohydrate data and fat data are
converted to energy data in producing the food energy data, by
processing the protein data, carbohydrate data and fat data in the
manner represented by the following equation:
FED=(Wpro.times.Cp.times.PROm)+(Wcho.times.Cc.times.CHOm)+(Wfat.times.Cf-
.times.FATm), (2)
[0058] where Cp is a conversion factor for converting PROm to data
representing the energy content of PROm, Cc is a conversion factor
for converting CHOm to data representing the energy content of
CHOm, and Cf is a conversion factor for converting FATm to data
representing the energy content of FATm. For example where the food
energy data is represented in kilocalories and PROm, CHOm and FATm
are expressed in grams, Cp is selected as 4 kilocalories/gram, Cc
is selected as 4 kilocalories/gram and Cf is selected as 9
kilocalories/gram. Mass and weight data can be expressed in the
alternative by units such as ounces and pounds.
[0059] In certain embodiments, food energy data is produced based
on total food energy data representing the total energy content,
protein energy data representing the protein energy content, and
dietary fiber energy data representing the dietary fiber energy
content, of a candidate food serving. More specifically, the food
energy data is produced by separating data representing the protein
energy content and the dietary fiber energy content (if present)
from the total food energy data to produce reduced energy content
data, applying respective weight data to weight each of the protein
energy data and the dietary fiber energy data, each of the weight
data representing the relative metabolic conversion efficiency of
the corresponding nutrient and forming the food energy data based
on a sum of the reduced energy content data, the weighted protein
energy data, and the weighted dietary fiber energy data. The data
for the various nutrients is provided either by the consumer or by
another source based on data from the consumer, such as food
identification data. If the total food energy data is represented
as "TFE", protein energy data is represented as "PRO" and the
dietary fiber energy data as "DF", in certain ones of such
embodiments where TFE includes an energy component of DF (as in the
case of foods labeled according to practices adopted in the US and
in the Dominion of Canada (CA)), the food energy data is obtained
by processing the data in the manner represented by the following
equation:
FED=(TFE-PRO-DF)+(Wpro.times.PRO)+(Wdf.times.DF), (3)
[0060] where Wpro represents the respective weighting data for PRO
and Wdf represents the respective weighting data for DF. In certain
ones of such embodiments, Wpro is selected from the range
0.7.ltoreq.Wpro.ltoreq.0.8 and Wdf is selected from the range
0<Wdf.ltoreq.0.5. In certain ones of such embodiments, Wpro is
substantially equal to 0.8 and Wdf is substantially equal to 0.25.
Various measures of energy can be employed, such as kilocalories
(kcal) and kilojoules (kJ).
[0061] For those instances where TFE does not include a dietary
fiber component (as in the case of foods labeled according to
practices adopted in Australia (AU) and the countries of central
Europe (CE)), the process of equation (3) is modified to the
following form:
FED=(TFE-PRO)+(Wpro.times.PRO)+(Wdf.times.DF). (4)
[0062] In certain embodiments, food energy data is produced based
both on the total food energy data, as well as on protein data
representing the mass or weight of the protein content (represented
as PROm) and dietary fiber data representing the mass or weight of
the dietary fiber content (represented as DFm), of a candidate food
serving. In such embodiments and for foods labeled as in the US and
CA, the protein data and dietary fiber data are converted to energy
data in producing the food energy data, by processing the total
food energy data, the protein data and dietary fiber data in the
manner represented by the following equation:
FED=[TFE.times.(Cp.times.PROm).times.(Cdf.times.DFm)]+(Wpro.times.Cp.tim-
es.PROm)+(Wdf.times.Cdf.times.DFm), (5)
[0063] where Cp is a conversion factor for converting PROm to data
representing the energy content of PROm and Cdf is a conversion
factor for converting DFm to data representing an energy content of
DFm. For example where the food energy data is represented in
kilocalories and PROm and DFm are expressed in grams, Cp is
selected as 4 kilocalories/gram and Cdf is selected as 4
kilocalories/gram. Mass and weight data can be expressed in the
alternative by units such as ounces and pounds.
[0064] For those instances where TFE does not include a dietary
fiber component (as in the case of foods labeled according to
practices adopted in AU and CE), the process of equation (5) is
modified to the following form:
FED=[TFE.times.(Cp.times.PROm)]+(Wpro.times.Cp.times.PROm)+(Wdf.times.Cd-
f.times.DFm). (6)
[0065] In certain embodiments, food energy data is produced based
on protein data representing the protein energy content of a
candidate food serving, carbohydrate data representing its
carbohydrate energy content, fat data representing its fat energy
content, and dietary fiber data representing its dietary fiber
energy content. This data is provided either by the consumer or
from another source based on data from the consumer, such as food
identification data. If the protein energy data is represented as
"PRO", the carbohydrate energy data as "CHO", the fat energy data
as "FAT", and the dietary fiber energy data as "DF", in certain
ones of such embodiments, the food energy data (represented as
"FED") is obtained by processing the data in the manner represented
by the following equation:
FED=PRO+CHO+FAT+DF. (7)
[0066] In certain ones of such embodiments, food energy data is
produced based on the protein energy data, the carbohydrate energy
data, the fat energy data, and the dietary fiber energy data, of
the candidate food serving, by applying respective weight data to
weight each of the protein energy data, the carbohydrate energy
data, the fat energy data and the dietary fiber energy data
representing its relative metabolic conversion efficiency and
forming the food energy data based on a sum of the weighted protein
energy data, the weighted carbohydrate energy data, the weighted
fat energy data and the weighted dietary fiber energy data. If Wpro
represents the respective weighting data for PRO, Wcho represents
the respective weighting data for CHO, Wfat represents the
respective weighting data for FAT and Wdf represents the respective
weighting data for dietary fiber, in certain ones of such
embodiments, the food energy data (represented as "FED") is
obtained by processing the data in the manner represented by the
following equation:
FED=(Wpro.times.PRO)+(Wcho.times.CHO)+(Wfat.times.FAT)+(Wdf.times.DF).
(8)
[0067] In certain ones of such embodiments, Wpro is selected from
the range 0.7.ltoreq.Wpro.ltoreq.0.8, Wcho is selected from the
range 0.9.ltoreq.Wcho.ltoreq.0.95, Wfat is selected from the range
0.97.ltoreq.Wfat.ltoreq.1.0 and Wdf is selected from the range
0<Wdf.ltoreq.0.5 In certain ones of such embodiments, Wpro is
substantially equal to 0.8, Wcho is substantially equal to 0.95,
Wfat is substantially equal to 1.0 and Wdf is substantially equal
to 0.25.
[0068] In certain embodiments, food energy data is produced based
on protein data representing the mass or weight of the protein
content (represented as PROm), carbohydrate data representing the
mass or weight of the carbohydrate content (represented as CHOm),
fat data representing the mass or weight of the fat content
(represented as FATm) and dietary fiber data representing the mass
or weight of the dietary fiber content (represented as DFm), of a
candidate food serving. In such embodiments, the protein data,
carbohydrate data, fat data and dietary fiber data, are converted
to energy data in producing the food energy data, by processing the
protein data, carbohydrate data, fat data and dietary fiber data in
the manner represented by the following equation:
FED=(Wpro.times.Cp.times.PROm)+(Wcho.times.Cc.times.CHOm)+(Wfat.times.Cf-
.times.FATm)+(Wdf.times.Cdf.times.DFm), (9)
[0069] where Cp is a conversion factor for converting PROm to data
representing an energy content of PROm, Cc is a conversion factor
for converting CHOm to data representing an energy content of CHOm,
Cf is a conversion factor for converting FATm to data representing
an energy content of FATm and Cdf is a conversion factor for
converting DFm to data representing an energy content of DFm. For
example where the food energy data is represented in kilocalories
and PROm, CHOm, FATm and DFm are expressed in grams, Cp is selected
as 4 kilocalories/gram, Cc is selected as 4 kilocalories/gram, Cf
is selected as 9 kilocalories/gram and Cdf is selected as 4
kilocalories/gram.
[0070] In the US and in CA, where food labeling standards include a
food product's dietary fiber in its total carbohydrate amount in
grams (represented as "Total_CHOm" herein), food energy data may
instead be produced by processing the protein data, carbohydrate
data, fat data and dietary fiber data in the manner represented by
the following equation:
FED=(Wpro.times.Cp.times.PROm)+(Wcho.times.Cc.times.[Total_CHOm-DFm])+(W-
fat.times.Cf.times.FATm)+(Wdf.times.Cdf.times.DFm). (10)
[0071] In certain embodiments, the food energy data is produced in
a modified fashion in order to discourage consumption of foods
having a high saturated fat content, so that the food energy data
(FED) is based both on the relative metabolic conversion efficiency
of selected nutrients and weighting data that promotes consumption
of relatively more healthful foods. In such embodiments, and where
(as in the US and CA) food labeling standards include a food
product's saturated fat (represented as "Sat_FATm" herein) in its
total amount of fat in grams (represented as "Total_FATm" herein),
the food energy data is produced by processing the protein data,
carbohydrate data, fat data, saturated fat data and dietary fiber
data in the manner represented by the following equation:
FED=(Wpro.times.Cp.times.PROm)+(Wcho.times.Cc.times.[Total_CHOm-DFm])+(W-
df.times.Cdf.times.DFm)+(Wfat.times.Cf.times.[Total_FATm-Sat_FATm])+(Wsfat-
.times.Cf.times.Sat_Fatm), (11)
[0072] wherein Wsfat represents modified weighting data for
Sat_FATm. In certain ones of such embodiments, Wpro is selected
from the range 0.7.ltoreq.Wpro.ltoreq.0.8, Wcho is selected from
the range 0.9.ltoreq.Wcho.ltoreq.0.95, Wfat is selected from the
range 0.97.ltoreq.Wfat.ltoreq.1.0, Wdf is selected from the range
0<Wdf.ltoreq.0.5, and Wsfat is selected from the range
1.0.ltoreq.Wsfat.ltoreq.1.3. In particular ones of such
embodiments, Wpro is substantially equal to 0.8, Wcho is
substantially equal to 0.95, Wfat is substantially equal to 1.0,
Wdf is substantially equal to 0.25 and Wsfat is substantially equal
to 1.3.
[0073] The relatively higher value assigned to Wsfat is based, in
part, on the desirability of discouraging consumption of saturated
fat, due to the ill-health effects associated with this nutrient.
The higher ranges and values of Wpro and Wcho in the presently
disclosed embodiments relative to those employed in embodiments
disclosed hereinabove, are useful for weight loss processes. That
is, consumers engaged in a weight loss process by limiting their
food energy consumption could, in some cases, be encouraged to eat
foods higher in saturated fat if it is assigned a relatively higher
weight than other nutrients, since this tends to reduce their
overall food energy consumption. By assigning relatively higher
ranges and values for Wpro and Wcho for use in processes that also
weight saturated fat higher than unsaturated fat, the potential to
encourage consumption of saturated fat is substantially reduced.
Accordingly, the weights assigned to Wpro and Wcho in the presently
disclosed embodiments are based both on the relative metabolic
conversion efficiency of protein and carbohydrates and the desire
to promote consumption of relatively more healthful foods.
[0074] In certain embodiments, for foods containing alcohol, the
foregoing processes as represented by equation (11) are modified to
add a term representing an energy component represented by the
amount of alcohol in the food. Where the amount of alcohol (by
weight or mass) is expressed in grams (represented as "ETOHm"
herein), this term is produced by multiplying ETOHm by a weighting
factor Wetoh and a conversion factor Cetoh, where Wetoh is selected
from the range 1.0.ltoreq.Wetoh.ltoreq.1.3, and in particular ones
of such embodiments is substantially equal to 1.29, and Cetoh is
selected as 9 kilocalories/gram, based on the principle that
alcohol is metabolized in the same pathway as fat. The higher value
assigned to Wetoh is based, in part, on the desirability of
discouraging consumption of alcohol, due to the ill-health effects
associated with this nutrient. Where a food contains alcohol, in
certain embodiments its food energy data is produced by processing
PROm, Total_CHOm, DFm, Total_FATm, Sat_FATm, and ETOHm in the
manner represented by the following equation:
FED=(Wpro.times.Cp.times.PROm)+(Wcho.times.Cc.times.[Total_CHOm-DFm])+(W-
df.times.Cdf.times.DFm)+(Wfat.times.Cf.times.[Total_FATm-Sat_FATm])+(Wsfat-
.times.Cf.times.Sat_Fatm)+(Wetoh.times.Cetoh.times.ETOHm). (12)
[0075] The process represented by equation (12) is modified for use
in CE and AU and is represented as follows:
FED=(Wpro.times.Cp.times.PROm)+(Wcho.times.Cc.times.Total_CHOm)+(Wdf.tim-
es.Cdf.times.DFm)+(Wfat.times.Cf.times.[Total_FATm-Sat_FATm])+(Wsfat.times-
.Cf.times.Sat_Fatm)+(Wetoh.times.Cetoh.times.ETOHm). (13)
[0076] In certain embodiments, for foods containing sugar alcohol,
the foregoing processes as represented by equations (12) and (13)
are modified to add a term representing an energy component
represented by the amount of sugar alcohol in the food. Where the
amount of sugar alcohol (by weight or mass) is expressed in grams
(represented as "SETOHm" herein), this term is produced by
multiplying SETOHm by a weighting factor Wsetoh and a conversion
factor Csetoh, where Wsetoh is selected from the range
0.9.ltoreq.Wsetoh.ltoreq.0.95, and in particular ones of such
embodiments is substantially equal to 0.95, and Csetoh is selected
from the range 0.2 to 4.0 kilocalories/gram, and in particular ones
of such embodiments is substantially equal to 2.4. Where a food
contains sugar alcohol, in certain embodiments its food energy data
is produced by processing PROm, Total_CHOm, DFm, Total_FATm,
Sat_FATm, ETOHm and SETOHm in the manner represented by the
following equation:
FED=(Wpro.times.Cp.times.PROm)+(Wcho.times.Cc.times.[Total_CHOm-DFm-SETO-
Hm])+(Wdf.times.Cdf.times.DFm)+(Wfat.times.Cf.times.[Total_FATm-Sat_FATm])-
+(Wsfat.times.Cf.times.Sat_Fatm)+(Wetoh.times.Cetoh.times.ETOHm)+(Wsetoh.t-
imes.Csetoh.times.SETOHm). (14)
[0077] The process represented by equation (14) is modified for use
in CE and AU and is represented as follows:
FED=(Wpro.times.Cp.times.PROm)+(Wcho.times.Cc.times.[Total_CHOm-SETOHm])-
+(Wdf.times.Cdf.times.DFm)+(Wfat.times.Cf.times.[Total_FATm-Sat_FATm])+(Ws-
fat.times.Cf.times.Sat_Fatm)+(Wetoh.times.Cetoh.times.ETOHm)+(Wsetoh.times-
.Csetoh.times.SETOHm). (15)
[0078] For the consumer's convenience, in many applications (such
as the Weight Watchers.RTM. program) the food energy data is
converted to simplified whole number data for a candidate food
serving by producing dietary data expressed as whole number data by
dividing the food energy data by factor data, such as data having a
value of 35, and rounding the resulting value to produce the
simplified whole number data. (Of course, to assign 35 as the value
of the factor data is arbitrary, and any other value such as 50, 60
or 70 may be used for this purpose.)
[0079] In the manner described above, the consumer can easily track
food consumption throughout a period, such as a day or a week,
(either manually or with the assistance of a data processing
system) to ensure that a predetermined sum of the dietary data for
the food consumed bears a predetermined relationship to a value of
predetermined whole number benchmark data based on one or more of
the consumer's age, body weight, height, gender and activity level.
For example, if the consumer is following a weight loss program,
the predetermined whole number benchmark data is set at a value
selected to ensure that the consumer will lose weight at a safe
rate if he or she consumes an amount of food during the period
having a sum of dietary data that does not exceed the predetermined
whole number benchmark data.
[0080] Since individual food energy needs vary with the
individual's age, weight, gender, height and activity level, in
certain embodiments the predetermined whole number benchmark data
is selected based on one or more of these variables. In such
embodiments, food energy needs are estimated based on methods
published by the National Academies Press, Washington, D.C., USA in
Dietary Reference Intakes for Energy, Carbohydrates, Fiber, Fat,
Fatty Acids, Cholesterol, Protein and Amino Acids, 2005, pages 203
and 204. More specifically, as explained therein these methods
estimate that men aged 19 years and older have a total energy
expenditure (TEE) determined as follows:
TEE=864-(9.72.times.age)+PA.times.(14.2.times.weight+503.times.height),
(16)
[0081] and that women aged 19 years and older have a TEE determined
as follows:
TEE=387-(7.31.times.age)+PA.times.(10.9.times.weight+660.7.times.height)-
, (17)
[0082] where age is given in years, weight in kilograms and height
in meters.
[0083] In such embodiments, these methods are employed on the basis
that all individuals have a "low active" activity level, so that
the activity level (PA) for men is set at 1.12 and PA for women is
set at 1.14. The published methods assume a 10 percent conversion
cost regardless of the types and amounts of nutrients consumed;
consequently, TEE is adjusted by subtracting 10 percent of the
calculated TEE. Also, the published method of calculating TEE
assigns an energy content of zero to certain foods having a
non-zero energy content. The total energy content of such foods
consumed within a given day generally falls within a range of 150
to 250 kilocalories, which may be normalized as 200 kilocalories.
Accordingly, TEE as determined by the published method is adjusted
to produce adjusted TEE (ATEE) in a process represented by the
following equation:
ATEE=TEE-(TEE.times.0.10)+200, (18)
[0084] where ATEE and TEE are given in kilocalories.
[0085] For consumers carrying out a process of reducing body
weight, the predetermined whole number benchmark is obtained by
subtracting an amount from the adjusted TEE selected to ensure a
predetermined weight loss over a predetermined period of time. For
example, a safe weight loss process can be selected to produce a
loss of two pounds per week, or a consumption of 1000 kilocalories
per day less than ATEE for a given individual. In this example, to
produce the predetermined whole number benchmark data (PWNB), where
the factor data used to produce the dietary data for the candidate
food servings (whether having a value of 35, 50, 60, 70 or other
value) is represented as FAC, such data is produced by a process
represented by the following equation:
PWNB=(ATEE-1000)/FAC. (19)
[0086] To achieve weight loss, the value of (ATEE-1000) in certain
embodiments is selected to fall within a range of 1000 kilocalories
to 2500 kilocalories, so that if (ATEE-1000) is less than 1000
kilocalories, then (ATEE is set equal to 1000 kilocalories, and if
(ATEE-1000) is greater than 2500 kilocalories, (ATEE-1000) is set
equal to 2500 kilocalories. However, in various other embodiments,
the upper limit of 2500 kilocalories varies from 2000 to 3000
kilocalories, and the lower limit of 1000 kilocalories varies from
500 to 1500 kilocalories.
[0087] In certain embodiments, the relative healthfulness data is
determined in a manner that depends on a particular food group of
the selected food. In certain ones of such embodiments, the
healthfulness data is determined in a first, common manner for
foods within a first metagroup comprising the following groups:
beans, dry & legumes; and oils. The healthfulness data (HD) for
these groups is obtained based on a linear combination of fat
content data, saturated fat content data, sugar content data and
sodium content data for the food. In one such embodiment, the
healthfulness data is produced by processing fat content data
(F_data), saturated fat content data (SF_data), sugar content data
(S_data) and sodium content data (NA_data), as follows, wherein
such data is determined as explained hereinbelow:
HD=[(2.times.(SF_data+F_data)+S_data+NA_data]/4/kcal_DV (20)
[0088] where kcal_DV is determined as explained hereinbelow. The
table of FIG. 1 illustrates how the foods in these groups are
ranked according to their healthfulness based on their respective
healthfulness data produced in accordance with the process
represented by equation (20) and a comparison thereof against the
exemplary comparison data included therein. These values may be
varied from place to place, from culture to culture and from time
to time, to provide a fair comparison of available foods and food
products.
[0089] It will also be appreciated that the food groups and
metagroups, and the corresponding procedures and comparison values,
as disclosed herein may be varied based on variations in the foods
and food products available from place to place, culture to culture
and over time. They may also vary to accommodate the needs and
desires of certain segments of the population, such as those with
special needs (for example, diabetic patients and those living in
extreme climates) and those with particular healthfulness goals
(which can vary, for example, with physical activity level). Such
groups, metagroups, procedures, and comparison values are selected
based on the similarities of foods and the manner in which related
foods vary in the amounts and types of nutrients that tend to
affect their healthfulness.
[0090] The value selected for kcal_DV is selected to represent a
daily calorie value that depends on the purposes or needs of the
class of consumers for whom the relative healthfulness data is
provided. For example, if this class encompasses individuals
desiring to loose body weight, the value of kcal_DV is selected as
a daily calorie target to ensure weight loss, such as 1500 kcal.
However, this value may differ from culture to culture and from
country to country. For example, the energy needs of those living
in China are generally lower than those living in the United
States, so that kcal_DV may be selected at a lower value for
Chinese individuals trying to reduce body weight than for those
living in the United States. As a further example, if the class of
consumers for whom the relative healthfulness data is provided
encompasses athletes attempting to maintain body weight during
training, kcal_DV may be set at a much higher level than 1500 kcal.
For most purposes, kcal_DV may be selected in a range from 1000
kcal to 3000 kcal.
[0091] The value of SF_data is determined relative to a recommended
or otherwise standardized limit on an amount or proportion of
saturated fat to be included in a person's daily food intake. The
recommended or otherwise standardized amount or proportion of
saturated fat to be consumed daily is based on the person's
presumed total food energy intake daily, and a proportion thereof
represented by saturated fat. In certain embodiments, for consumers
desiring to lose body weight, as explained hereinabove, a total
food energy intake of 1500 kcal is assumed (although the amount may
vary in other embodiments). If, for example, a maximum desirable
percentage of saturated fat consumed as a proportion of total daily
energy intake is assumed to be seven percent, then the total number
of calories in saturated fat that the person consumes daily on such
a diet should be limited to about 105 kcal (of a total of 1500
kcal). Since fat contains about nine kcal per gram, the person's
daily consumption of saturated fat in this example should be
limited to about twelve grams. However, the recommended or
standardized limit on the proportion or amount of saturated fat to
be consumed may vary from one class of consumer to another, as well
as from country to country and from culture to culture. SF_data is
determined by comparison to such a standard. In this example,
therefore, SF_data is determined as the ratio of (a) the mass of
saturated fat in a standard amount of the food under evaluation, to
(b) twelve grams. While a different procedure or other amounts or
proportions may be employed in other embodiments to evaluate the
saturated fat content of a food, it is desired to determine SF_data
in a manner that is reasonably comparable to the ways in which
F_data, S_data and NA_data are determined.
[0092] Similarly to SF_data, the value of F_data is determined
relative to a recommended or otherwise standardized limit on the
amount or proportion of total fat to be included in a person's
daily food intake. In those embodiments in which it is presumed
that a person consumes 1500 kcal daily and a recommended proportion
or limit of thirty percent of energy consumption in the form of fat
is adopted, this translates to fifty grams of total fat on a daily
basis. In this example, therefore, and in particular for
comparability to SF_data, F_data is determined as the ratio of (a)
the mass of total fat in a standard amount of the food under
evaluation, to (b) fifty grams. Of course, a different procedure or
other amounts or proportions may be employed in other embodiments
to evaluate the total fat content of a food.
[0093] In a similar manner, the value of S_data is determined
relative to a recommended or otherwise standardized limit on the
amount or proportion of sugar to be included in a person's daily
food intake. In those embodiments in which it is presumed that a
person consumes 1500 kcal daily and a recommended proportion or
limit of ten percent of food energy intake in the form of sugar is
adopted, this translates to thirty eight grams of sugar on a daily
basis (at four kcal per gram of sugar). In this example, therefore,
and in particular for comparability to SF_data and F_data, S_data
is determined as the ratio of (a) the mass of sugar in a standard
amount of the food under evaluation, to (b) thirty eight grams. Of
course, a different procedure or other amounts or proportions may
be employed in other embodiments to evaluate the sugar content of a
food.
[0094] In a manner similar to those described above, the value of
NA_data is determined relative to a recommended or otherwise
standardized limit on the amount or proportion of sodium to be
included in a person's daily food intake. In those embodiments in
which a recommended limit of 2400 mg of sodium consumed daily is
adopted, NA_data is determined as the ratio of (a) the mass of
sodium in a standard amount of the food under evaluation, to (b)
2400 mg. Of course, a different procedure or other amounts or
proportions may be employed in other embodiments to evaluate the
sodium content of a food.
[0095] In such embodiments, the healthfulness data is determined in
a second, common manner for foods within a second metagroup
comprising the following groups: beef (cooked), cookies, cream
& creamers, eggs, frankfurters, game (raw), game (cooked), lamb
(cooked), luncheon meats, pizza, pork (raw), pork (cooked),
sausage, snacks pretzels, veal (raw) and veal (cooked). The
healthfulness data (HD) for these groups is obtained based on a
linear combination of the food's fat content data, saturated fat
content data, sugar content data, sodium content data and energy
density data. In one such embodiment, the healthfulness data is
produced by processing F_data, SF_data, S_data, NA_data and ED_data
of the food, as follows, wherein F_data, SF_data, S_data and
NA_data are obtained as explained hereinabove:
HD=ED_data+([(2.times.SF_data)+(2.times.F_data)+NA_data+S_data].times.10-
0/M_serving), (21)
[0096] where M_serving is the mass or weight of a standard serving
of the food. In this particular embodiment, ED_data is obtained as
the energy content of the food (in kcal) divided by its mass (in
grams). The tables of FIGS. 1A and 1B illustrate how the foods in
these groups are ranked according to their healthfulness based on
their respective healthfulness data produced in accordance with the
process represented by equation (21) and a comparison thereof
against the exemplary comparison data included therein.
[0097] In such embodiments, the healthfulness data is determined in
a third, common manner for foods within a third metagroup
comprising the following groups: beverages; alcoholic beverages;
sweet spreads jams, syrups, toppings & nut butters. The
healthfulness data (HD) for these groups is obtained based on a
linear combination of the food's fat content data, saturated fat
content data, sugar content data, sodium content data and energy
density data. In one such embodiment, the healthfulness data is
produced by processing F_data, SF_data, S_data, NA_data, ED_data
and M_serving, as follows:
HD=(ED_data/3)+[(2.times.SF_data)+(2.times.F_data)+(2.times.S_data)+NA_d-
ata]+M_serving. (22)
[0098] The table of FIG. 2 illustrates how the foods in these
groups are ranked according to their healthfulness based on their
respective healthfulness data produced in accordance with the
process represented by equation (22) and a comparison thereof
against the exemplary comparison data included therein.
[0099] In such embodiments, the healthfulness data is determined in
a fourth, common manner for foods within a fourth metagroup
comprising the following groups: cheese, dairy & non-dairy,
hard; and cheese, cottage & cream. The healthfulness data (HD)
for these groups is obtained based on a linear combination of the
food's fat content data, saturated fat content data, sugar content
data, sodium content data and energy density data. In one such
embodiment, the healthfulness data is produced by processing
F_data, SF_data, S_data, NA_data, ED_data and M_serving, as
follows:
HD=ED_data+[(4.times.SF_data)+(4.times.F_data)+S_data+NA_data].times.100-
/M_serving. (23)
[0100] The table of FIG. 2A illustrates how the foods in these
groups are ranked according to their healthfulness based on their
respective healthfulness data produced in accordance with the
process represented by equation (23) and a comparison thereof
against the exemplary comparison data included in FIG. 2A.
[0101] In such embodiments, the healthfulness data is determined in
a fifth, common manner for foods within a fifth metagroup
comprising the following groups: breads; bagels; tortillas, wraps;
breakfast pancakes, waffles, pastries; and vegetable dishes The
healthfulness data (HD) for these groups is obtained based on a
linear combination of the food's fat content data, saturated fat
content data, sugar content data, sodium content data and energy
density data. In one such embodiment, the healthfulness data is
produced by processing F_data, SF_data, S_data, NA_data, ED_data
and M_serving, as follows:
HD=ED_data+[(2.times.SF_data)+F_data+S_data+(2.times.NA_data).times.DF_d-
ata].times.100/M_serving.
[0102] The value of DF_data is determined relative to a recommended
or otherwise standardized minimum amount or proportion of dietary
fiber to be included in a person's daily food intake. One such
recommendation is that a minimum of ten grams of dietary fiber be
consumed by a person for every 1000 kcal consumed daily. In those
embodiments in which it is presumed that a person consumes 1500
kcal daily, this translates to a recommended minimum of fifteen
grams of dietary fiber on a daily basis. Of course, a different
procedure or other amounts or proportions may be employed in other
embodiments to evaluate the recommended amount of dietary fiber to
be consumed on a periodic basis. In this particular example, the
value of DF_data is obtained as the ratio of the mass of dietary
fiber in a standard serving of then food, to fifteen grams.
[0103] The table of FIG. 3 illustrates how the foods in these
groups are ranked according to their healthfulness based on their
respective healthfulness data produced in accordance with the
process represented by equation (24) and a comparison thereof
against the exemplary comparison data included in FIG. 3.
[0104] In such embodiments, the healthfulness data is determined in
a sixth, common manner for foods within a sixth metagroup
comprising the following groups: grains & pasta, cooked; and
grains & pasta, uncooked. The healthfulness data (HD) for these
groups is obtained based on a linear combination of the food's fat
content data, saturated fat content data, sugar content data,
sodium content data, energy density data and dietary fiber content
data. In one such embodiment, the healthfulness data is produced by
processing F_data, SF_data, S_data, NA_data, ED_data and DF_data,
as follows:
HD=(ED_data/3)+[([SF_data+F_data+(2.times.S_data)+(2.times.NA_data)]/4).-
times.DF_data].times.100/M_serving. (25)
[0105] The table of FIG. 3A illustrates how the foods of the groups
in the sixth metagroup are ranked according to their healthfulness
based on their respective healthfulness data produced in accordance
with the process represented by equation (25) and a comparison
thereof against the exemplary comparison data included in FIG.
3A.
[0106] In such embodiments, the healthfulness data is determined in
a seventh, common manner for foods within a seventh metagroup
comprising the following groups: breakfast cereals, hot, cooked;
breakfast cereals, hot, uncooked; and fruit salads. The
healthfulness data (HD) for these groups is obtained based on a
linear combination of the food's saturated fat content data, fat
content data, sugar content data, sodium content data and energy
density data. In one such embodiment, the healthfulness data is
produced by processing SF_data, F_data, S_data, NA_data and
ED_data, as follows:
HD=ED_data+[SF_data+(2.times.F_data)+(2.times.S_data)+(2.times.NA_data].-
times.100/M_serving. (26)
[0107] The table of FIG. 4 illustrates how the foods in these
groups are ranked according to their healthfulness based on their
respective healthfulness data produced in accordance with the
process represented by equation (26) and a comparison thereof
against the exemplary comparison data included in FIG. 4.
[0108] In such embodiments, the healthfulness data is determined in
an eighth, common manner for foods within an eighth metagroup
comprising the following groups: bars; cakes and pastries; and
candy. The healthfulness data (HD) for these groups is obtained
based on a linear combination of the food's fat content data,
saturated fat content data, sodium content data, energy density
data and sugar content data. In one such embodiment, the
healthfulness data is produced by processing F_data, SF_data,
NA_data, ED_data and S_data, as follows:
HD=ED_data+[(2.times.SF_data)+F_data+(2.times.S_data)+(2.times.NA_data)]-
.times.100/M_serving. (27)
[0109] The table of FIG. 5 illustrates how the foods in these
groups are ranked according to their healthfulness based on their
respective healthfulness data produced in accordance with the
process represented by equation (27) and a comparison thereof
against the exemplary comparison data included in FIG. 5.
[0110] In such embodiments, the healthfulness data is determined in
a ninth, common manner for foods within a ninth metagroup
comprising the following groups: dips; dressings; gravies; sauces;
soups, condensed; soups, RTE; and spreads (other than sweet). The
healthfulness data (HD) for these groups is obtained based on a
linear combination of the food's fat content data, saturated fat
content data, sodium content data, sugar content data and energy
density data. In one such embodiment, the healthfulness data is
produced by processing F_data, SF_data, S_data, NA_data, and
ED_data, as follows:
HD=ED_data+[(2.times.SF_data)+F_data+S_data+(2.times.NA_data)].times.100-
/M_serving. (28)
[0111] The table of FIG. 6 illustrates how the foods in these
groups are ranked according to their healthfulness based on their
respective healthfulness data produced in accordance with the
process represented by equation (28) and a comparison thereof
against the exemplary comparison data included in FIG. 6.
[0112] In such embodiments, the healthfulness data is determined in
a tenth, common manner for foods within a tenth metagroup
comprising the following groups: beans, dry & legumes dishes;
beef dishes; breakfast mixed dishes; cheese dishes; chili, stew;
egg dishes; fish & shellfish dishes; lamb dishes; pasta dishes;
pasta, cooked; pork dishes; poultry dishes; rice & grains
dishes; salads, main course; salads, side; sandwiches; veal dishes
and vegetarian meat substitutes. The healthfulness data (HD) for
these groups is obtained based on a linear combination of the
food's fat content data, saturated fat content data, sodium content
data, sugar content data and energy density data. In one such
embodiment, the healthfulness data is produced by processing
F_data, SF_data, NA_data, S_data and ED_data, as follows:
HD=ED_data+[(2.times.SF_data)+(2.times.F_data)+S_data+(2.times.NA_data)]-
.times.100/M_serving. (29)
[0113] The tables of FIGS. 7 and 7A illustrate how the foods in
these groups are ranked according to their healthfulness based on
their respective healthfulness data produced in accordance with the
process represented by equation (29) and a comparison thereof
against the exemplary comparison data included in FIGS. 7 and
7A.
[0114] In such embodiments, the healthfulness data is determined in
an eleventh, common manner for foods within an eleventh metagroup
comprising the following groups: fruit fresh, frozen & dried;
and fruit & vegetable juices. The healthfulness data (HD) for
these groups is obtained based on a linear combination of the
food's sodium content data, sugar content data, saturated fat
content data, fat content data and energy density data. In one such
embodiment, the healthfulness data is produced by processing
NA_data, S_data, SF_data, F_data and ED_data, as follows:
HD=ED_data+[(2.times.S_data)+NA_data+SF_data+F_data].times.100/M_serving-
. (30)
[0115] The table of FIG. 8 illustrates how the foods in these
groups are ranked according to their healthfulness based on their
respective healthfulness data produced in accordance with the
process represented by equation (30) and a comparison thereof
against the exemplary comparison data included in FIG. 8.
[0116] In such embodiments, the healthfulness data is determined in
a twelfth, common manner for foods within a twelfth metagroup
comprising the following groups: vegetables, raw; and vegetables,
cooked. The healthfulness data (HD) for these groups is obtained
based on a linear combination of the food's sodium content data,
sugar content data, saturated fat content data, fat content data
and energy density data. In one such embodiment, the healthfulness
data is produced by processing NA_data, S_data, SF_data, F_data and
ED_data, as follows:
HD=ED_data+[S_data+(1.5.times.NA_data)+(5.times.SF_data)+(5.times.F_data-
)].times.100/M_serving. (31)
[0117] The table of FIG. 8A illustrates how the foods in these
groups are ranked according to their healthfulness based on their
respective healthfulness data produced in accordance with the
process represented by equation (31) and a comparison thereof
against the exemplary comparison data included in FIG. 8A.
[0118] In such embodiments, the healthfulness data is determined in
a thirteenth, common manner for foods within a thirteenth metagroup
comprising the following groups: gelatin, puddings; ice cream
desserts; ice cream novelties; ice cream, sherbet, sorbet; sweet
pies; and sweets--honey, sugar, syrup, toppings. The healthfulness
data (HD) for these groups is obtained based on a linear
combination of the food's sodium content data, fat content data,
saturated fat content data, sugar content data, and energy density
data. In one such embodiment, the healthfulness data is produced by
processing NA_data, F_data, SF_data, S_data, and ED_data, as
follows:
HD=ED_data+[(2.times.SF_data)+F_data+NA_data+(2.times.S_data)].times.100-
/M_serving. (32)
[0119] The table of FIG. 9 illustrates how the foods in these
groups are ranked according to their healthfulness based on their
respective healthfulness data produced in accordance with the
process represented by equation (32) and a comparison thereof
against the exemplary comparison data included in FIG. 9.
[0120] In such embodiments, the healthfulness data is determined in
a fourteenth, common manner for foods within the following group:
breakfast cereals, RTE. The healthfulness data (HD) for this group
is obtained based on the saturated fat content data of the food, as
well as its fat content data, sugar content data, sodium content
data, dietary fiber content data and energy density data. In one
such embodiment, the healthfulness data is produced by processing
SF_data, F_data, S_data, NA_data, DF_data, and ED_data, as
follows:
HD=(ED_data/3)+[(2.times.S_data)+SF_data+F_data+NA_data-DF_data].times.1-
00/M_serving. (33)
[0121] For this group, the most healthful foods have an HD value
less than or equal to -0.36, while less healthful foods have an HD
value greater than -0.36 and less than or equal to 1.66, even less
healthful foods have an HD value greater than 1.66 and less than or
equal to 2.91 and the most unhealthful foods have an HD value
greater than 2.91.
[0122] In such embodiments, the healthfulness data is determined in
a fifteenth, common manner for foods within an fifteenth metagroup
comprising the following group: coffee/tea drinks with milk. The
healthfulness data (HD) for this group is obtained based on the
saturated fat content data, the fat content data, the sodium
content data and the sugar content data of the food. In one such
embodiment, the healthfulness data is produced by processing
SF_data, F_data, S_data and NA_data, as follows:
HD=([(2.times.SF_data)+(2.times.F_data)+(2.times.S_data)+NA_data]/4)/kca-
l_DV. (34)
[0123] For this group, the most healthful foods have an HD value
less than or equal to 3.25, while relatively less healthful foods
have an HD value greater that 3.25 and less than or equal to 3.471,
even less healthful foods have an HD value greater than 3.471 and
less than or equal to 4.18 and the least healthful foods have an HD
value greater than 4.18.
[0124] In such embodiments, the healthfulness data is determined in
a sixteenth, common manner for foods within the following group:
crackers. The healthfulness data (HD) for this group is obtained
based on the saturated fat content data, the fat content data, the
sugar content data, the sodium content data and the energy density
data of the food. In one such embodiment, the healthfulness data is
produced by processing SF_data, F_data, S_data, NA_data and
ED_data, as follows:
HD=(ED_data/3)+[(2.times.SF_data)+F_data+S_data+(2.times.NA_data)].times-
.100/M_serving. (35)
[0125] For this group, none of the foods are graded in the most
healthful foods category, while relatively less healthful foods
have an HD less than or equal to 1.805, even less healthful foods
have an HD value greater than 1.805 and less than or equal to 3.2,
and the least healthful foods have an HD value greater than
3.2.
[0126] In such embodiments, the healthfulness data is determined in
a seventeenth, common manner for foods within the following group:
fish, cooked. The healthfulness data (HD) for this group is
obtained based on the saturated fat content data, the fat content
data, the sugar content data, the sodium content data and the
energy density data of the food. In one such embodiment, the
healthfulness data is produced by processing SF_data, F_data,
S_data, NA_data and ED_data, as follows:
HD=ED_data+[(4.times.SF_data)+(4.times.F_data)+S_data+(2.times.NA_data)]-
.times.100/M_serving. (36)
[0127] For this group, the most healthful foods have an HD value
less than or equal to 3.2, while relatively less healthful foods
have an HD value greater that 3.2 and less than or equal to 4.7,
even less healthful foods have an HD value greater than 4.7 and
less than or equal to 6.6, and the least healthful foods have an HD
value greater than 6.6.
[0128] In such embodiments, the healthfulness data is determined in
a eighteenth, common manner for foods within the following group:
fruit, canned. The healthfulness data (HD) for this group is
obtained based on the saturated fat content data, the fat content
data, the sugar content data, the sodium content data and the
energy density data of the food. In one such embodiment, the
healthfulness data is produced by processing SF_data, F_data,
S_data, NA_data and ED_data, as follows:
HD=ED_data+[(2.times.SF_data)+(2.times.F_data)+(4.times.S_data)+(2.times-
.NA_data)].times.100/M_serving. (37)
[0129] For this group, the most healthful foods have an HD value
less than or equal to 1.56, while relatively less healthful foods
have an HD value greater that 1.56 and less than or equal to 1.93,
even less healthful foods have an HD value greater than 1.93 and
less than or equal to 3.27, and the least healthful foods have an
HD value greater than 3.27.
[0130] In such embodiments, the healthfulness data is determined in
a twentieth, common manner for foods within the following group:
nuts, nut butters. The healthfulness data (HD) for this group is
obtained based on the saturated fat content data, the fat content
data, the sugar content data, the sodium content data and the
energy density data of the food. In one such embodiment, the
healthfulness data is produced by processing SF_data, F_data,
S_data, NA_data and ED_data, as follows:
HD=(ED_data/3)+[(2.times.SF_data)+F_data+S_data+NA_data].times.100/M_ser-
ving. (38)
[0131] For this group, none of the foods are graded within the most
healthful foods category, while relatively less healthful foods
have an HD value less than or equal to 1.5, even less healthful
foods have an HD value greater than 1.5 and less than or equal to
5.6, and the least healthful foods have an HD value greater than
5.6.
[0132] In such embodiments, the healthfulness data is determined in
a twenty-first, common manner for foods within the following group:
snacks, other. The healthfulness data (HD) for this group is
obtained based on the saturated fat content data, the fat content
data and the energy density data of the food. In one such
embodiment, the healthfulness data is produced by processing
SF_data, F_data and ED_data, as follows:
HD=ED_data+[SF_data+F_data].times.100/M_serving. (39)
[0133] For this group, none of the foods are graded within the most
healthful foods category or in the relatively less healthful foods
category, while even less healthful foods have an HD value less
than or equal to 5.491, and the least healthful foods have an HD
value greater than 5.491.
[0134] In such embodiments, the healthfulness data is determined in
a twenty-second, common manner for foods within the following
group: snacks--popcorn. The healthfulness data (HD) for this group
is obtained based on the saturated fat content data of the food, as
well as its fat content data, sugar content data, sodium content
data, dietary fiber content data and energy density data. In one
such embodiment, the healthfulness data is produced by processing
SF_data, F_data, S_data, NA_data, DF_data and ED_data, as
follows:
HD=ED_data+[(2.times.S_data)+SF_data+F_data+NA_data-DF_data].times.100/M-
_serving. (40)
[0135] For this group, the most healthful foods have an HD value
less than or equal to 3.02, while less healthful foods have an HD
value greater than 3.02 and less than or equal to 4.0, even less
healthful foods have an HD value greater than 4.0 and less than or
equal to 6.3 and the most unhealthful foods have an HD value
greater than 6.3.
[0136] Consumers often are confused by the extensive nutritional
information printed on the packaging of foods. Some simply find it
too burdensome to read such information, often in relatively fine
print so that it can all fit in the available space, and then weigh
the relative merits and undesirable aspects of such information.
While the Traffic Light system provides a degree of simplification
to this process, it is still necessary for the consumer to look for
additional information on the packaging in order to acquire
information desired by those attempting to maintain, lose or gain
weight.
[0137] In certain embodiments, methods are provided for selecting
and ingesting foods in a way that enables the consumer to control
body weight, while simplifying the task of evaluating the
desirability of each of various foods based on multiple criteria.
With reference to FIG. 10, at the beginning of a predetermined
period, such as a day or a week, the consumer or a data processing
system sets 110 a variable "SUM" equal to zero.
[0138] When the consumer considers whether to ingest a candidate
food serving, the consumer views 120 an integrated image including
both a numeral representing an energy value of the food serving and
an auxiliary image feature representing a further nutritional
quality of the food serving. In certain ones of such embodiments,
the further nutritional quality comprises the relative
healthfulness of the candidate food serving. Such relative
healthfulness may be determined as disclosed in this application,
or in another manner. In certain advantageous embodiments, such
relative healthfulness is represented by distinctly different and
suggestive image colors, shades, shapes, brightness, or textures.
In certain ones of such embodiments, the further nutritional
quality represents a relative heart healthiness of the candidate
food serving, while in others it represents sugar content for use
by diabetic consumers. In certain ones of such embodiments, the
further nutritional quality represents an amount, presence or
absence of a particular nutrient or nutrients. For example, body
builders may wish to know the amount of protein in a serving of a
particular candidate food serving or whether such protein includes
all essential amino acids.
[0139] The integrated image may be imprinted on the packaging or
label of the candidate food serving, or it may be displayed by a
data processing system, such as a PDA, cellular telephone, laptop
computer or desktop computer, as described more fully hereinbelow.
It may also be displayed in a printed document.
[0140] The integrated image in certain embodiments comprises a
numeral representing the energy content of an associated food
displayed on a background colored to represent a further
nutritional quality of the candidate food serving. An example of
such an integrated image is provided in FIG. 11A wherein the
numeral comprises an integer on a green background with a
triangular border. In certain advantageous embodiments the color
green is used to represent a favorable nutritional quality relative
to other candidate food servings in a predetermined food group
including the associated candidate food serving. For example, green
may represent those foods that provided the greatest satiety for
minimal energy content as well as a nutritional profile which most
closely complements public health guidelines. The color blue may be
used to represent foods having a relatively lower healthfulness
profile, such as foods with a nutritional profile that is not as
closely aligned with public health recommendations but does have
satiety and nutritional virtues. The color pink may be used to
represent foods with a relatively lower healthfulness profile than
those coded blue, such as foods that provide minimal satiety or
nutritional value to overall intake but are likely to enhance the
tastefulness or convenience of eating. The color white may be used
to represent foods falling within the lowest healthfulness profile,
such as foods that, while not making much of a contribution to
overall nutrition or feelings of satiety, provide pleasure and can
be part of a healthy eating plan when consumed in moderation.
[0141] A further example of such an integrated image is provided in
FIG. 11B wherein the numeral comprises a different integer within a
circular border. The shape of the border may be used by itself to
represent relative healthfulness or another nutritional
characteristic, while the numeral represents food energy data. In
other embodiments, both the shape of the border and a color,
shading or texture enclosed by the border can provide the data for
the nutritional characteristic represented by the shape in FIG.
11B.
[0142] Still another example of an integrated image is provided in
FIG. 11C wherein the numeral 6.5 appears within the image to
provide food energy data, and the rectangular border of the image,
with or without a color, shading or texture code, provides the data
for the further nutritional characteristic.
[0143] FIG. 11D illustrates a still further integrated image in
which a numeral representing an energy content of a candidate food
serving is colored to represent the further nutritional
characteristic of the candidate food serving. While the numeral of
FIG. 11D is not enclosed within a border, in certain embodiments a
border is provided. In still other embodiments, the numeral is
shaded or textured to provide the data for the further nutritional
characteristic. Various other shapes may also be used, such as a
star, oval or donut shape. Any shapes, colors, textures and
shadings may be used, whether alone or in combination to provide
the data for the additional nutritional characteristic. Moreover,
arabic numerals need not be used, so that any data representing
numerical data (such as roman numerals) can serve as the numeral
data to represent energy content.
[0144] With reference again to FIG. 10, based on the data provided
by the integrated image, that is, the energy content data and the
further nutritional quality data provided thereby, the consumer
determines whether to accept or reject 130 the candidate food
serving for consumption. For example, the consumer may wish to
consume a snack food and must decide between a bag of fried corn
chips and a bag of popcorn. He or she views the integrated image on
each bag, and decides to consume the popcorn both because its
energy content and healthfulness relative to the fried corn chips
as revealed by the integrated image are more favorable than those
of the fried corn chips. The integrated image thus provides an
easily viewed and readily understood evaluation of multiple
nutritional qualities of a candidate food serving.
[0145] In certain embodiments, with or without the use of a data
processing system, the consumer adds the data represented by the
numeral in the integrated image associated with the candidate food
serving to the SUM 140, and if the SUM is less than a predetermined
daily or weekly maximum MAX 150, the consumer ingests 160 the
candidate food serving. In the alternative, the consumer first
ingests the candidate food serving and then adds the number data
represented by the numeral in the integrated image to SUM. For
example, the consumer might not know the precise value of SUM plus
the number data, but is aware that it is relatively low compared to
MAX.
[0146] A method of selecting and purchasing food for consumption
utilizing the integrated image is illustrated in FIG. 12. When a
consumer considers whether to purchase a given food for
consumption, the consumer views 310 an integrated image associated
with the food including both a numeral representing an energy value
of the food and an auxiliary image feature representing a further
nutritional quality of the food. The food may be a packaged food,
such as a Weight Watchers.RTM. packaged food that displays the
integrated image on its packaging. Instead it may be a packaged
food that does not display such an image, so that the consumer
inputs an identification of the packaged food in a device such as a
PDA or cellular telephone to obtain a display of the integrated
image for evaluation, as disclose more fully hereinbelow. It might
also be a food such as produce that is unpackaged and the consumer
may obtain an associated integrated image in the same manner as for
the packaged food lacking the image.
[0147] Based on the data provided by the integrated image, that is,
the energy content data and the further nutritional quality data
provided thereby, the consumer determines whether to accept or
reject 320 the food for purchase. For example, the consumer may
wish to purchase cookies and wishes to decide between two competing
brands of the same kind of cookie. Each may have the same energy
content, so that the consumer may wish to choose the brand having a
more favorable healthfulness based on differing colors, shapes,
textures, shadings or combinations thereof seen in the integrated
image on each package. Or else if each has an image having the same
auxiliary image feature, the consumer may wish to select the brand
having a lower energy content per serving.
[0148] When the consumer has selected all of the foods to be
purchased 330, he or she then purchases the selected foods 340 and
delivers or has them delivered 350 to his/her household for
consumption.
[0149] FIG. 13 illustrates a data processing system 40 of certain
embodiments useful in carrying out the process of FIGS. 10 and 12.
The data processing system 40 comprises a processor 44, a storage
50 coupled with the processor 44, an input 56 coupled with
processor 44, a presentation device 60 coupled with processor 44
and communications 64 coupled with processor 44.
[0150] Where system 40 is implemented as a PDA, laptop computer,
desktop computer or cellular telephone, in certain ones of such
embodiments the input 56 comprises one or more of a keypad, a
keyboard, a point-and-click device (such as a mouse), a
touchscreen, a microphone, switch(es), a removable storage or the
like, and presentation device 60 comprises an LCD display, a plasma
display, a CRT display, a printer, lights, LED's or the like.
[0151] In certain ones of such embodiments, storage 50 stores (A)
the weighting data and conversion factors necessary to carry out
one or more of the processes summarized in equations (1) through
(15) hereinabove to produce food energy data, and (B) data
identifying the predetermined food groups and instructions for
carrying out the processes necessary to produce the relative
healthfulness data as summarized in equations (20) through (40)
hereinabove.
[0152] For producing relative healthfulness data for the food to be
consumed or the food offered for sale, using input 56, the consumer
inputs data identifying the food to be consumed or food offered for
sale or an identification of its predetermined food group, and
processor 44 retrieves appropriate instructions from storage 50 for
carrying out the respective process for the identified food group.
Storage 50 stores data associating food identity data with the
corresponding food groups, so that when the consumer inputs food
identification data, processor 44 accesses such data to identify
its food group and then retrieves the appropriate processing
instructions based thereon. Processor 44 then prompts the consumer,
via presentation device 60, to enter the relevant ones of F_data,
SF_data, DF_data, S_data, NA_data, M_serving, kcal DV, DD and
ED_data for a food to be purchased or candidate food serving
depending on the process to be carried out. Processor 44 then
processes the input data according to one of equations (20) through
(40) to produce the relative healthfulness data.
[0153] For producing food energy data for the food to be consumed
or the food offered for sale, using input 56, the consumer inputs
appropriate data (as disclosed hereinabove), for a food or
candidate food serving depending on the process to be carried out.
Processor 44 retrieves the necessary weighting data and conversion
factors, as need be, from storage 50 and processes the input data
according to one of equations (1) through (15) to produce the food
energy data.
[0154] Using the relative healthfulness data and food energy data
thus produced, processor 44 uses this data to retrieve an image
dataset from storage 50 including data for producing the auxiliary
image feature corresponding to the healthfulness data and numeral
data corresponding to the food energy data, and controls
presentation device 60 to display an integrated image based on the
image dataset depicting the numeral and the auxiliary image feature
to convey the energy content and the relative healthfulness of the
food offered for sale or to be consumed to the consumer.
[0155] In certain ones of such embodiments, storage 50 stores
relative healthfulness data and food energy data for a plurality of
predetermined foods, which can be retrieved using an address based
on an identification of the food input by the consumer using input
56. Processor 44 produces addresses for the corresponding relative
healthfulness data and food energy data in storage 50 and reads the
relative healthfulness data and food energy data therefrom using
the addresses. Using the relative healthfulness data and food
energy data thus produced, processor 44 uses this data to retrieve
an image dataset from storage 50 including data for producing the
auxiliary image feature corresponding to the healthfulness data and
numeral data corresponding to the food energy data, and controls
presentation device 60 to display the integrated image.
[0156] In certain ones of such embodiments, storage 50 stores the
image datasets for the integrated images for a plurality of
predetermined foods, which can be retrieved using an address based
on an identification of the food input by the consumer using input
56. Based on the food identification data input by the consumer
using input 56, processor 44 produces an address corresponding to
the input data and retrieves an image dataset from storage 50
corresponding thereto to control presentation device 60 to display
the integrated image for the food thus identified.
[0157] In certain ones of such embodiments, the relative
healthfulness data and food energy data stored in storage 50 is
downloaded from a server via a network. With reference to FIG. 14,
a plurality of data processing systems 40' and 40'', each
corresponding to data processing system 40 access a server 76 via a
network 70 to obtain the relative healthfulness data and food
energy data, either to obtain a database of relative healthfulness
data and food energy data or to update such a database stored in
the storage 50. Network 70 may be a LAN, WAN, metropolitan area
network or an internetwork, such as the Internet. Server 76 stores
relative healthfulness data and food energy data for a large number
and variety of foods and candidate food servings which have been
produced thereby, obtained from another host on network 70 or a
different network, or input from a removable storage device or via
an input of server 76.
[0158] In certain ones of such embodiments, processor 44 of one of
data processing systems 40' and 40'' receives the input data from
input 56 and the consumer, and controls communications 64 to
communicate such data to server 76 via network 70. Server 76 either
retrieves the corresponding relative healthfulness data and food
energy data from a storage thereof (not shown for purposes of
simplicity and clarity), or produces the relative healthfulness
data and food energy data from the received data using the process
identified by the food group identification data and a selected one
of the food energy data production processes, as appropriate, and
communicates the relative healthfulness data and food energy data
to communications 64. Processor 44 then retrieves the corresponding
image dataset from storage 50 and controls presentation device 60
to display the corresponding integrated image to the consumer.
[0159] In certain ones of such embodiments, processor 44 of one of
data processing systems 40' and 40'' receives the input data from
input 56 and the consumer, and controls communications 64 to
communicate such data to server 76 via network 70. Server 76
retrieves a corresponding image dataset for the corresponding
integrated image and communicates it to communications 64.
Processor 44 then uses the received image dataset to control the
presentation device 60 to display the integrated image to the
consumer.
[0160] FIG. 15 is a flow chart used to illustrate certain
embodiments of a process for producing a food product having the
integrated image associated therewith. A food product is obtained
400, whether by producing the food product, by retrieving it from
inventory or receiving a delivery thereof. Accordingly, the food
product may be a processed food product, or it may be a raw food
product, such as an agricultural product or seafood.
[0161] At least one of food identification data and food nutrient
data of the food product is supplied 410. The food identification
data may be the name of the food, a stock keeping unit or other
data as described hereinbelow. In certain ones of such embodiments,
food energy data for the food product and further data representing
a further nutritional characteristic of the food product, such as
relative healthfulness data, is obtained 420 based on the food
identification data or the food nutrient data, using one of the
processes disclosed hereinabove.
[0162] In certain ones of such embodiments, the food identification
data is input to a data processing system storing food energy data
and such further data for one or more food products. In this
example, the food identification data may be a name of the food
product, an identifier such as a stock keeping unit, or data which
associates the food product with its respective stored food energy
data. In certain ones of such embodiments, such food nutrient data
is supplied to a data processing system as may be required to
produce food energy data and the further data for the food product
using one of the processes disclosed hereinabove. In certain ones
of such embodiments, the data is obtained from an appropriate
record or calculated in accordance with one of the processes
disclosed hereinabove.
[0163] Using the food energy data and the further data, a processor
of the data processing system retrieves an image dataset from a
storage of the data processing system including data for producing
the auxiliary image feature corresponding to the further
nutritional characteristic of the food product, such as its
relative healthfulness, and numerical data corresponding to the
food energy data, so that the integrated image may be produced.
[0164] In certain ones of such embodiments, a storage of the data
processing system stores image datasets corresponding to food
identification data and/or food nutrient data. The at least one of
food identification data and food nutrient data of the food product
is used by a processor of the data processing system to retrieve
the image dataset from a storage of the data processing system.
[0165] In certain ones of such embodiments, the integrated image
data is obtained for a known food product, with or without the use
of a data processing system. For example, the integrated image data
may be obtained from publicly available packaging or labels, as
data obtained in electronic form via a network, such as the
Internet or as data obtained from other printed or electronically
accessible sources.
[0166] The integrated image data obtained as disclosed hereinabove
is associated 430 with the food product. In certain ones of such
embodiments, the integrated image data is printed, applied or
otherwise made visible on packaging of the food product. In certain
ones of such embodiments, the integrated image data is made visible
on a label affixed on or to the food product, such as an
adhesive-backed label on produce or a label tethered to a food
product.
[0167] The foregoing disclosure of certain embodiments provides
exemplary ways of implementing the principles of the present
invention, and the scope of the invention is not limited by this
disclosure. This invention can be embodied in many different forms
and should not be construed as limited to the embodiments set forth
herein; rather, these embodiments are provided so that this
disclosure will be thorough and complete to those skilled in the
art. The scope of the present invention is instead defined by the
following claims.
* * * * *