ArticlePDF AvailableLiterature Review

Relationship between nutrition knowledge and dietary intake

Authors:

Abstract and Figures

The present systematic review examined the relationship between nutrition knowledge and dietary intake in adults (mean age ≥ 18 years). Relevant databases were searched from the earliest record until November 2012. Search terms included: nutrition; diet or food knowledge and energy intake; feeding behaviour; diet; eating; nutrient or food intake or consumption. Included studies were original research articles that used instruments providing quantitative assessment of both nutrition knowledge and dietary intake and their statistical association. The initial search netted 1 193 393 potentially relevant articles, of which twenty-nine were eligible for inclusion. Most of them were conducted in community populations (n 22) with fewer (n 7) in athletic populations. Due to the heterogeneity of methods used to assess nutrition knowledge and dietary intake, a meta-analysis was not possible. The majority of the studies (65·5 %: community 63·6 %; athletic 71·4 %) reported significant, positive, but weak (r< 0·5) associations between higher nutrition knowledge and dietary intake, most often a higher intake of fruit and vegetables. However, study quality ranged widely and participant representation from lower socio-economic status was limited, with most participants being tertiary educated and female. Well-designed studies using validated methodologies are needed to clarify the relationship between nutrition knowledge and dietary intake. Diet quality scores or indices that aim to evaluate compliance to dietary guidelines may be particularly valuable for assessing the relationship between nutrition knowledge and dietary intake. Nutrition knowledge is an integral component of health literacy and as low health literacy is associated with poor health outcomes, contemporary, high-quality research is needed to inform community nutrition education and public health policy.
Content may be subject to copyright.
Systematic Review
Relationship between nutrition knowledge and dietary intake
Inge Spronk
1
, Charina Kullen
2
, Catriona Burdon
3,4
and Helen O’Connor
3
*
1
Division of Human Nutrition, Wageningen University, Bomenweg 2, 6703 HD Wageningen, The Netherlands
2
HQ Forces Command, Australian Army, Victoria Barracks, Paddington, NSW 2021, Sydney, Australia
3
Discipline of Exercise and Sport Science, University of Sydney, 75 East Street, Lidcombe, NSW 2141, Sydney, Australia
4
School of Health Sciences, University of Wollongong, Northfields Avenue, Wollongong, NSW 2522, Wollongong, Australia
(Submitted 24 June 2013 – Final revision received 19 December 2013 – Accepted 2 January 2014 – First published online 13 March 2014)
Abstract
The present systematic review examined the relationship between nutrition knowledge and dietary intake in adults (mean age $18 years).
Relevant databases were searched from the earliest record until November 2012. Search terms included: nutrition; diet or food
knowledge and energy intake; feeding behaviour; diet; eating; nutrient or food intake or consumption. Included studies were original
research articles that used instruments providing quantitative assessment of both nutrition knowledge and dietary intake and their statistical
association. The initial search netted 1 193 393 potentially relevant articles, of which twenty-nine were eligible for inclusion. Most of
them were conducted in community populations (n22) with fewer (n7) in athletic populations. Due to the heterogeneity of methods
used to assess nutrition knowledge and dietary intake, a meta-analysis was not possible. The majority of the studies (65·5 %: community
63·6 %; athletic 71·4 %) reported significant, positive, but weak (r,0·5) associations between higher nutrition knowledge and dietary
intake, most often a higher intake of fruit and vegetables. However, study quality ranged widely and participant representation
from lower socio-economic status was limited, with most participants being tertiary educated and female. Well-designed studies using
validated methodologies are needed to clarify the relationship between nutrition knowledge and dietary intake. Diet quality scores
or indices that aim to evaluate compliance to dietary guidelines may be particularly valuable for assessing the relationship between
nutrition knowledge and dietary intake. Nutrition knowledge is an integral component of health literacy and as low health literacy is
associated with poor health outcomes, contemporary, high-quality research is needed to inform community nutrition education and
public health policy.
Key words: Systematic reviews: Nutrition knowledge: Dietary intakes
Nutrition education programmes are designed to improve
nutrition knowledge, with the aim of supporting sound dietary
intake within the community or a specific target population
(1 – 4)
.
Nutrition education is widespread, with schools, government
and health promotion agencies delivering a range of messages
that incorporate a nutrition component
(5)
. Members of the
community in most industrialised countries are exposed to
education about dietary guidelines or core food group intake.
Specific education to prevent or manage lifestyle diseases
such as diabetes, CVD or cancer is also widely available
(6 – 8)
.
Despite the wide scope of nutrition education initiatives, it is
somewhat surprising that relatively few studies have evaluated
the level of nutrition knowledge in the general community or
other specific group samples, and that the impact of nutrition
knowledge on dietary intake is still largely unexplored.
Numerous factors including taste, convenience, food cost
or security and cultural or religious beliefs influence dietary
intake
(4,9 – 12)
. Factors that are well known to influence nutrition
knowledge include age, sex, level of education and socio-
economic status
(12)
. Women tend to have higher levels of
nutrition knowledge than men, and this difference has been
attributed to their more dominant role in food purchasing and
preparation or a lower interest in nutrition by men
(9,11,12)
.
Higher levels of nutrition knowledge have been reported in
those with higher education or socio-economic status
(5,10,12)
and greater levels of nutrition knowledge have been typically
found in middle-aged as opposed to younger or older per-
sons
(4,9,12)
. These demographic factors also influence dietary
intake
(11)
. The specific contribution of nutrition knowledge to
the overall quality of food intake is considered to be complex
*Corresponding author: H. O’Connor, fax þ61 2 9351 9204, email helen.oconnor@sydney.edu.au
British Journal of Nutrition (2014), 111, 1713–1726 doi:10.1017/S0007114514000087
qThe Authors 2014
British Journal of Nutrition
and is influenced by the interaction of many demographic and
environmental factors
(11)
. However, greater understanding of
the relationship between nutrition knowledge and dietary
intake is important as emerging evidence supports a strong
link between low health literacy, poor management of chronic
disease and increased health costs
(13,14)
. Although nutrition
knowledge is one component of health literacy, it is a central
factor as poor dietary intake is strongly linked to all of the
major lifestyle diseases and in industrialised countries, it
accounts for the majority of health costs
(15 – 17)
.
Measurement of nutrition knowledge is challenging
(12)
. Most
studies have used written questionnaires, but many of these
have inadequate or no validation. Responses rely heavily on
participant literacy, and this is more limited with lower levels
of education and socio-economic status
(18)
. Types of nutrition
knowledge assessed also vary widely across instruments, with
some measuring general concepts
(19 – 23)
while others explore
only some nutrition aspects such as fat
(24 – 27)
or fibre
(24,25)
.
Knowledge of nutrition facts, or declarative knowledge may
not translate through to skill or process knowledge, essentially
the ability to choose healthier foods, understand food labels
or select healthier options from a range of foods available. Nutri-
tion knowledge instruments that assess declarative nutrition
concepts may have little relevance to the set of knowledge
and skills required to make appropriate dietary decisions
that promote health. Zoellner et al.
(28)
have more recently
used the term ‘nutrition literacy’ rather than nutrition know-
ledge and defined this as ‘the degree to which individuals
have the capacity to obtain, process, and understand nutrition
information and skills needed in order to make appropriate
nutrition decisions’. This definition focuses on possession of
nutrition knowledge and skills that have practical relevance
to dietary choices.
As with nutrition knowledge, dietary intake is also difficult to
measure, particularly in samples that are large and powerful
enough to find significant associations between these variables.
Use of dietary records significantly adds to the burden of
respondents and researchers
(29)
, and examination of micro-
nutrients requires more than a few days or a week
(30)
. FFQ are
the most efficient, cost-effective and practical method for the
large-scale measurement of dietary intake, which also includes
the measurement of micronutrients
(29,31)
. However, this
method has limitations with accuracy
(31)
. Interview or recall
methods, particularly 24 h multiple-pass recalls, are now used
as a method of choice in large population-based surveys
(32)
.
Unfortunately, this method is resource-intensive. More recently,
dietary intakes typically obtained from FFQ or 24 h recall data
have been used to calculate a diet quality score or index that
provides an evaluation of the consistency of food intakes
with dietary guidelines rather than comparing with nutrient
reference values
(33,34)
. Individuals with high energy intakes
may easily meet nutrient reference values yet not consume
diets consistent with dietary guidelines
(35)
. Diet quality scores
or indices may therefore be a useful tool for investigating the
relationship between nutrition knowledge and dietary intake.
As diet is the cornerstone for maintaining health and
also for the management and prevention of a wide range
of medical conditions
(6 – 8)
, an understanding of the level of
nutrition knowledge and its association with dietary intake is
paramount. Although factors outside nutrition knowledge
including food security and availability
(4)
, skills in cooking
and food preparation
(12)
through to motivation to embrace a
healthy eating style
(5)
influence the ability to ‘operationalise’
nutrition knowledge into a healthy diet, some nutrition
knowledge is necessary. One must know before one can do.
As much of the sustained effort in nutrition promotion revolves
around improving knowledge of nutrition through dietary
guidelines, and healthy eating guides (e.g. MyPlate)
(36)
, the
specific influence of nutrition knowledge on dietary intake is
an important research question.
In two existing systematic reviews, the relationship between
nutrition knowledge and dietary intake has been examined
(4,37)
.
The first review
(37)
, published in 1985, was informed by a
limited number of studies (n9). Most of the included articles
(n6/9) used the same item test bank
(23)
(or an adapted version)
to assess nutrition knowledge and reasonably similar metho-
dology, so meta-analysis was possible. This review reported
a weak, positive relationship (r,0·2) between nutrition know-
ledge and dietary intake (P,0·01). Although six of the
nine studies reported no significant correlation, the direction
of the relationship was consistent and significant via meta-
analysis. A more recent systematic review on this topic only
included studies in athletes
(4)
and due to study heterogeneity,
a meta-analysis was not conducted. However, the majority of
the studies reported a weak, positive association (r,0·44)
between nutrition knowledge and dietary intake. As a com-
prehensive and contemporary review of this topic has not
been undertaken for some time, the aim of the present study
was to systematically review existing evidence from studies
investigating the relationship between nutrition knowledge
and dietary intake across all populations.
Methods
Search strategy
A systematic search using the terms nutrition knowledge, diet
knowledge or food knowledge and energy intake, feeding
behaviour, diet, eating, nutrient intake, food intake and food
consumption was conducted by one researcher (I. S.) from the
earliest record until November 2012. The databases included
SCOPUS, MEDLINE (OvidSP), SPORTDiscus (EBSCO), Web of
Science, CINAHL (EBSCO), ScienceDirect, AMED (OvidSP)
and AUSportMed (Informit Online). A hand search of the refer-
ence lists of the included articles was conducted to find
additional studies missed by database searching.
Eligibility criteria
Original research studies (including randomised controlled
trials and cross-sectional and quasi-experimental designs) con-
ducted in adult (mean age $18 years) human participants
and published in a peer-reviewed journal were included for
review. Abstracts, reviews, reports and theses were excluded.
Studies in all population groups and written in any language
were included. Studies were required to use an instrument
I. Spronk et al.1714
British Journal of Nutrition
that provided a quantitative assessment of nutrition know-
ledge via the report of a participant score. A quantitative
assessment for dietary intake was also required, but this could
be expressed as either intake of one or more nutrients (e.g.
g, mg, mg or percentage of energy), consumption of servings
of some or all core foods or a diet quality score or index.
Articles were also required to examine the association between
nutrition knowledge and dietary intake using statistical ana-
lysis. Instruments used for the assessment of either nutrition
knowledge or dietary intake did not need to be validated.
Selection of studies and data extraction
After removal of duplicates, irrelevant articles were eliminated
on the basis of title and abstract by one reviewer (I. S.). The
full text of relevant articles was screened using the inclusion
criteria by two reviewers (I. S. and C. B.) (Fig. 1), and data
were independently extracted by two reviewers (I. S. and
C. K.). Information retrieved included participant and study
characteristics (sex, age, population, sample size, country and
sampling method), details on the instruments used to assess
nutrition knowledge (number and type of items, instrument
design, response formats, general or specific knowledge
measured, and validation) (Tables 1, 2 and 4) and type and
validity of dietary assessment conducted (Table 3). Outcomes
of statistical analysis assessing the association between nutrition
knowledge and dietary intake were also extracted (Table 3).
Disagreements arising from decisions around article exclusion
or inclusion or extraction of data were resolved by discussion
with a third researcher (H. O.). Studies were deemed too
heterogeneous for the data to be pooled for meta-analysis,
specifically with respect to instruments and/or approaches
used to collect nutrition knowledge and dietary intake data
(38)
.
Study quality
Study quality was independently assessed by two researchers
(I. S. and C. K.) using a modified version of the Downs
and Black scale
(39)
(Table 4). The original scale consists of
twenty-seven items that examine data reporting, statistical
power, and external and internal validity (including bias
and confounding). Of the twenty-seven original criteria, only
eleven logically applied to the study designs included in the
present review. Items specific to controlled/intervention
trials (item numbers 5, 8, 9, 1217, 19, 21 24, 26 and 27)
were excluded because none of the identified articles had
Energy intake, dietary intake,
feeding behaviour, diet, eating,
nutrient intake, food intake,
food consumption
(n 1 184 900)
Nutrition knowledge, diet
knowledge, food knowledge
(n 8493)
Articles (after duplicate
removal)
(n 3140)
Potentially relevant articles
(n 75)
Excluded articles (n 3065):
Irrelevant
Hand-searched articles
(n 10) Excluded articles (n 56):
• Relationship between
knowledge and dietary intake
not assessed (n 17)
• Review articles (n 3)
• Knowledge not assessed
quantitatively (n 7)
• No dietary intake assessed (n 8)
• Non-adult population (n 12)
• Abstract or thesis (n 9)
Included articles
(n 29)
Fig. 1. Flow chart showing the selection of studies.
Nutrition knowledge and dietary intake 1715
British Journal of Nutrition
Table 1. Nutrition knowledge in community populations
(Mean values and standard deviations)
Study
Participants
Nutrition knowledge
assessmentn(sex)
Age (years)
Popu-
lation Sample Country
Questionnaire summary
Mean SD Design*
No. of
items Question type
Baghurst &
McMichael
(40)
344 (247 M, 97 F) 18 US CON Australia Q GN, three sections: energy
nutrient content, medico-
physiological basis, myths
NST NST TF, other
400 (M) 22 SR
Bravo et al.
(41)
105 (M, F) 21 2 US CON Spain Q GN NST 20 NST
Byrd-Bredbenner
et al.
(42)
576 (M, F) NST US CON USA Q GN EQ† 50 MC
Dallongeville et al.
(10)
361 (M) 45–64 CO RAN France Q GN (focus on CHD risk) AEQ‡ 10 TF, other
De Vriendt et al.
(43)
630 (F) 18–39 CO RAN Belgium Adapted GNKQ GN AEQ§ 111 MC, TF, other
Dickson-Spillmann &
Siegrist
(20)
1043 (420 M, 623 F) 53 16 CO RAN Switzer-
land
Q GN (focus on procedural
knowledge)
ADQ 13 TF
Dissen et al.
(21)
279 (131 M, 148 F) 20·1 1·8 US CON USA Q (online) GN ADQ 22 MC
Gambaro et al.
(44)
270 (83 M, 187 F) 37·3 13·1 CO CON Uruguay Locally adapted GNKQ GN AEQ§ 106 MC, TF, other
Grotkowski &
Sims
(45)
40 (M, F) .62 CO CON USA Q GN EQk25 MC, TF
Guthrie & Fulton
(46)
2960 (F) 49 (18–97) CO RAN USA Q (focus on serving guidelines) ADQ 4 Other
Harnack et al.
(47)
10 286 (M, F) $18 CO RAN USA Q (focus on cancer prevention) ADQ,
EQ{
12 MC, TF, other
Jovanovic et al.
(48)
390 (120 M, 270 F) 21·9 M 2·3 M US CON Croatia GNKQ (part D diet disease
relationships)
EQ§ 30 MC, TF, other
21·5 F 2·3 F
Kresic et al.
(49)
1005 (264 M, 741 F) 21·7 2·3 US CON Croatia Adapted GNKQ GN AEQ§ 96 MC, TF, other
Kristal et al.
(27)
97 (F) 51·5 4·3 CO CON USA Q GN (focus on fat and cancer) ADQ 49 MC
Lee et al.
(25)
1539 (285 M, 1254 F) 72·7 7·8 CO CON USA Q GN (interview) (focus on
fibre, cholesterol/fat, servings)
ADQ,
AEQ**
25 NST
Schwartz
(50)
313 (F) NST CO CON USA Q GN AEQk30 TF, other
Sharma et al.
(51)
963 (373 M, 590 F) 18–60 CO RAN USA Q (telephone) GN ADQ 83 Other
Shepherd &
Stockley
(52)
210 16.65 CO CON UK Q (focus on dietary fat) EQ†† 14 MC, TF
Sims
(53)
61 (F) 28 CO CON USA Q GN AEQk36 MC, TF
Stafleu et al.
(54)
97 (F) 25 2·8 CO RAN The
Nether-
lands
Q (focus on cholesterol/fat) EQ‡‡ 22 MC, TF
97 (F) 49 5·1
97 (F) 76 5·9
Wardle et al.
(11)
1039 (455 M, 584 F) 51·5 CO RAN UK GNKQ GN EQ§ 110 MC, TF, other
Williams et al.
(55)
523 (F) 38·7 5·1 CO CON Australia Q GN AEQ§ 8 MC
M, male; F, female; US, university students; CON, convenience; Q, questionnaire; GN, general nutrition knowledge; NST, not stated; TF, true/false; other, open-ended questions; SR, military service recruits; EQ, existing question-
naire; MC, multiple choice; CO, community; RAN, random; AEQ, adapted existing questionnaire; GNKQ, general nutrition knowledge questionnaire; ADQ, author-designed questionnaire.
* Validation of the instruments is detailed in Table 4.
† Byrd-Bredbenner
(22)
.
Questionnaire of the Preventive Medicine Centre at the Pasteur Institute of Lille.
§ Parmenter & Wardle
(19)
.
kEppright et al.
(23)
.
{Cotugna et al.
(80)
.
** US Department of Agriculture Diet and Health Knowledge Survey.
†† Ruddell
(26)
.
‡‡ Paas et al.
(81)
.
I. Spronk et al.1716
British Journal of Nutrition
a randomised controlled design. Item 20 that probed the
accuracy and validity of main outcome measures was expanded
to more rigorously evaluate the quality of the validation of
instruments or approaches used to assess nutrition knowledge
and dietary intake. This resulted in a maximum possible score
of 17 points.
Validity of nutrition knowledge instruments used in the
included studies was assessed according to five domains
known to be central to the development of a sound and reliable
instrument: face validity; pre- or pilot testing; content validity
(review or evaluation of the instrument by experts); test
retest validity; internal consistency (intra-class correlation
and/or Cronbach’s
a
). One point was awarded for evidence
of reasonable and appropriate application of each method of
validation. Validity of the dietary intake assessment was based
not only on the use of an accepted method for collection of
dietary information (e.g. dietary record, FFQ, 24 h recall, diet
quality score), but also on appropriate application of the
methodology (e.g. methodology was valid for the sample size
and population demography used, sufficient days or detail of
intake obtained was appropriate to quantify the outcome
reported and in the case of questionnaire-based methods
such as FFQ or diet checklists, whether the instrument used
was validated). A maximum score of 2 points was awarded
for dietary intake assessment, 1 point for choice of an accepted
method and 1 point for appropriate application. Disagreements
were discussed with a third researcher (H. O.) until resolved.
Results
Identification and selection of studies
The initial search netted 1 193 393 potentially relevant articles.
After removal of duplicates and elimination of papers based
on exclusion criteria, twenty-nine articles were included for
review (Fig. 1). Most articles were written in English (twenty-
seven of twenty-nine). Of the twenty-nine articles included for
assessment, twenty-two were conducted in community popu-
lations (Table 1) and seven in athletic populations (Table 2).
Study characteristics
Community populations. Of the twenty-two
studies
(10,11,20,21,25,27,40 – 55)
conducted in community samples,
sixteen assessed participants from the general community
and six examined university student populations (Table 1).
Half (n11) of the studies were published after the year 2000.
Participant numbers ranged from 40 to 10 286. Most (n13)
were in mixed-sex samples with four conducted only in
women and one only in men; one article failed to identify the
sex of the participants. Women represented the majority of
participants measured (77 v. 23 %), although not all studies
provided detail on the sex distribution. Age ranged from 18 to
97 years with seven of the studies reporting a mean age $50
years. Most studies were conducted in either the USA (n10) or
Europe (n9) with the remainder from Australia (n2) and
South America (n1). Only eight of the twenty-two studies
used random sampling methods with the remainder conducted
Table 2. Nutrition knowledge in athletic populations
(Mean values and standard deviations)
Participants
Age (years)
Nutrition knowledge
assessment
Questionnaire summary
Study n(sex) Mean SD Population (sport, level) Sample Country Design* No. of items Question type
Frederick &
Hawkins
(56)
59 (F) 50 –65 18 PW CON USA Q GN AEQ† 34 TF
17– 25 27 AT (track, tertiary)
17– 25 14 US
Hamilton et al.
(57)
53 (41 M, 12 F) 24·5 M 6·7 M AT, (distance runners, national) CON New Zealand Q GN EQ‡ 20 MC
27·8 F 4·6 F Q SN ADQ 28 MC
Harrison
(58)
122 (69 M, 53 F) 24·4 M AT (mixed athletes, elite and recreational) CON New Zealand Q GN, SN NST 18 TF
23·1 F
O’Halloran et al.
(59)
14 (M) 21– 25 AT (basketball players, international) CON Canada Q GN, SN AEQ§ 87 TF
Rash et al.
(60)
113 (61 M, 52 F) 19·3 M 1·2 M AT (track, tertiary) CON USA Q GN, SN ADQ, AEQk10–25 TF
19·1 F 1·1 F
Werblow et al.
(61)
94 (F) NST AT (mixed athletes, tertiary) CON USA Q GN, SN ADQ 31 TF
Wiita et al.
(62)
54 (F) NST AT (cross-country running, secondary and tertiary) CON USA Q GN, SN AEQ{NST TF
F, female; PW, postmenopausal women; CON, convenience; Q, questionnaire; GN, general nutrition knowledge; AEQ, adapted existing questionnaire; TF, true/false; AT, athletes; US, university students; M, male; EQ, existing
questionnaire; MC, multiple choice; SN, sport nutrition knowledge; NST, not stated; ADQ, author-designed questionnaire.
* Validation of the instruments is detailed in Table 4.
† Annable
(82)
.
‡ Woolcott et al.
(83)
.
§ Barr
(84)
.
kJonnalagadda et al.
(85)
and Zawila et al.
(86)
.
{Werblow et al.
(61)
.
Nutrition knowledge and dietary intake 1717
British Journal of Nutrition
Table 3. Association between nutrition knowledge and dietary intake
Dietary assessment
Study Instrument Design* Validation Knowledge score correlations
Community samples
Baghurst &
McMichael
(40)
FFQ (.150 food and
beverage items)
EQ† VAL NS relationship
Bravo et al.
(41)
3 d DR NA NA NS relationship
Byrd-Bredbenner
et al.
(42)
24 h recall NA NA NS relationship
Dallongeville et al.
(10)
3 d DR NA NA þCorrelation with intake of olive oil, cheese and cereals
2Correlation with intake of sunflower oil, dry vegetables, fat and monounsaturated fat from animal origin
De Vriendt et al.
(43)
2 d DR‡ NA NA þCorrelation with vegetable and fruit intake
Dickson-Spillmann &
Siegrist
(20)
FFQ (forty food and
beverage items)
ADQ NVAL þCorrelation with intake of vegetables, water, fruit, cereals, lentils, unsalted nuts and light sodas
2Correlation with intake of sausages, egg-based pasta, chips, croquettes, red meat, margarine, boiled
potatoes, low-fat milk and full-fat milk (P,0·01)
Dissen et al.
(21)
Fruit–vegetable
fibre–dietary fat
screener
EQ§ VAL þCorrelation with intake of vegetables and fruit in males
Gambaro et al.
(44)
FFQ (thirty food
groups)
NST PVAL þCorrelation with consumption of fruits, vegetables and low-fat products, in addition to a lower
consumption of high-fat and high-sugar foods
Grotkowski &
Sims
(45)
3 d DR NA NA NS relationship
Guthrie & Fulton
(46)
24 h recall (interview)
and 2 d DR
NA NA þCorrelation between knowledge of USDA Food Guide servings recommendations and intake of
vegetables, fruits, dairy products, meat, poultry, dried beans, eggs and nuts
Harnack et al.
(47)
FFQ (sixty-eight
items)
AEQkVAL þCorrelation with intake of vegetables, fruit and fibres
2Correlation with intake of energy from fat
Jovanovic et al.
(48)
FFQ (items NST) EQ{VAL þCorrelation between diet disease knowledge and higher intake of fish (P¼0·027, P¼0·001) and veg-
etables (P¼0·019, P¼0·001) in high-fibre groups of both sexes and intake of fruit in females (P¼0·038,
P¼0·007)
2Correlation between overall examined nutrition knowledge and daily energy intake (P¼0·019,
P¼0·001), energy density of the diet (P¼0·038, P¼0·001), SFA intake (P¼0·036, P,0·001), and
consumption of legumes (P¼0·027, P¼0·001) and soft drinks (P¼0·001, P,0·001) for both sexes in
high-fibre groups
Kresic et al.
(49)
FFQ (ninety-seven
food and beverage
items)
EQ{NVAL þCorrelation with adherence to dietary recommendations (P,0·001)
Kristal et al.
(27)
FFQ AEQkVAL þCorrelation with low-fat diets
2£4d DR þCorrelation between intake of fats from foods and preservatives and knowledge that processed foods
can cause cancer and percentage of energy consumed from fat
Lee et al.
(25)
2£24 h recall
(interview)
NA NA þCorrelation with number of servings of grains/cereals/breads/pasta, milk/cheese, and fruits and veg-
etables; intakes of vitamin E and Mg were greater. Quality of diets was superior for highest tertile of DKI
Schwartz
(50)
3 d frequency intake
of seventeen food
groups
ADQ NVAL NS relationship
Sharma et al.
(51)
FFQ (telephone
survey)
EQ** VAL Significant predictor for intake of grains (OR 6·42, 95 % CI 2·4, 17·1), dairy products (OR 2·25, 95 % CI
1·5, 3·4), meats (OR 2·02, 95 % CI 1·5, 2·8), beans (OR 8·18, 95 % CI 5·1, 13·0) and water (OR 2·49,
95 % CI 1·7, 3·6), but not for intake of fruits and (non-starchy) vegetables (OR 1·69, 95 % CI 0·89, 3·2)
Shepherd &
Stockley
(52)
FFQ (focus on fat) AEQ†† PVAL NS relationship between nutrition knowledge and consumption of foods
Sims
(53)
3 d DR NA NA NS relationship
Stafleu et al.
(54)
FFQ EQ‡‡ VAL NS relationship
I. Spronk et al.1718
British Journal of Nutrition
Table 3. Continued
Dietary assessment
Study Instrument Design* Validation Knowledge score correlations
Wardle et al.
(11)
Modified version of
the DINE
EQ§§ VAL þCorrelation with intake of vegetables (r0·36, P,0·001), fruit (r0·23, P,0·001) and fat (r0·21,
P,0·001)
þCorrelation with healthy eating after controlling for demographic variables
Williams et al.
(55)
FFQ for seven
dietary outcomes
ADQ VAL þCorrelation with intake of vegetables and chocolate/lollies and lower soft drink consumption
Athlete samples
Frederick &
Hawkins
(56)
24 h recall þFFQ
(thirty food items)
ADQ NVAL þCorrelation with milk score, servings of high-Ca foods and food-frequency score
2Correlation with use of carbonated beverages
Hamilton et al.
(57)
Dietary Practices
Questionnaire
(thirty-five different
foods)
ADQ NVAL þCorrelation with intake of cereals (r0·30, P,0·05) and fruit and vegetables (r0·33, P,0·05)
2Correlation with intake of fats and oils (r20·38, P,0·01), tea and coffee (r20·31, P,0·05) and ‘junk
foods’ (r20·29, P,0·05)
Sports nutrition section
þCorrelation with likelihood of consuming fruit and vegetables (r0·28, P,0·01)
2Correlation with consumption of electrolyte drinks (r20·38, P,0·01)
Harrison et al.
(58)
FFQ (fifteen food
group items)
EQ NVAL þCorrelation with health habits (r0·44, P,0·001)
O’Halloran et al.
(59)
3 d DR NA NA NS relationship
Rash et al.
(60)
FFQ EQkk VAL NS relationship
Werblow et al.
(61)
Food Patterns
Questionnaire
(forty-three items)
AEQ{{ PVAL þCorrelation with training-weight control-diet similarity score (r0·24) and pre-event-weight-control
similarity score (r0·25, P,0·05)
Wiita et al.
(62)
3 d DR NA NA Association between nutrition knowledge and diet quality score was statistically significant (þR
2
27 %)
EQ, existing questionnaire; VAL, validated; DR, dietary record; NA, not applicable; þ, positive; 2, negative; ADQ, author-designed questionnaire; NVAL, not validated; NST, not stated; PVAL, partly validated; USDA, US Depart-
ment of Agriculture; AEQ, adapted existing questionnaire; DKI, diet knowledge index; DINE, Dietary Instrument for Nutrition Education.
* Relevant to studies using questionnaires or checklists to assess dietary intake not for DR or 24 h recall.
† Baghurst & McMichael
(87)
.
‡ Pynaert et al.
(88)
.
§ Block et al.
(24)
.
kBlock et al.
(89)
.
{Kaic-Rac & Antonic
(90)
and Kulieri
(91)
.
** Baumgartner et al.
(92)
and McPherson et al.
(93)
.
†† Shepherd & Stockley
(94)
.
‡‡ Feunekes et al.
(95)
.
§§ Roe et al.
(63)
.
kk Rockett et al.
(96)
.
{{ Cho & Fryer
(97)
.
Nutrition knowledge and dietary intake 1719
British Journal of Nutrition
Table 4. Quality ratings
Validity
Reporting Knowledge tool Diet tool
Study
Hypothesis
stated/aim
stated
Main
outcomes
Intervention
described
Participant
description
Main
findings
described
Variability
estimates
P
(reported)
Representative
participants
Appropriate
statistical
tests
Adjust for
confounders
Face
validity
Pre-tested
or pilot
tested
Content
validity
Test–
retest
Internal
consistency
Accepted
diet method
used
Accepted
application
Total
score
Community samples
Baghurst &
McMichael
(40)
11 1 1 11 0 0 0 0 00 00 0 1 18
Bravo et al.
(41)
11 1 1 11 0 0 0 0 00 00 0 1 07
Byrd-Bredbenner
et al.
(42)
11 1 1 10 0 1 1 0 11 11 1 1 013
Dallongeville
et al.
(10)
11 1 1 11 1 1 1 1 01 00 0 1 012
De Vriendt et al.
(43)
11 1 1 11 1 0 1 1 11 11 1 1 015
Dickson-Spillmann
& Siegrist
(20)
11 1 1 10 1 0 1 0 11 10 1 1 012
Dissen et al.
(21)
11 1 1 11 1 0 1 1 01 00 0 1 112
Gambaro et al.
(44)
11 1 1 10 1 0 1 0 10 10 0 1 010
Grotkowski &
Sims
(45)
11 1 0 10 0 0 1 0 10 10 1 1 09
Guthrie & Fulton
(46)
11 1 1 11 0 1 1 1 00 00 0 1 111
Harnack et al.
(47)
11 1 1 11 1 1 1 1 10 00 0 1 113
Jovanovic et al.
(48)
11 1 1 11 1 0 1 0 11 11 1 1 115
Kresic et al.
(49)
11 1 1 10 1 0 1 1 11 11 1 1 014
Kristal et al.
(27)
11 1 1 10 0 0 1 1 11 11 1 1 013
Lee et al.
(25)
11 1 1 10 1 0 1 0 00 00 0 1 08
Schwartz
(50)
11 1 0 10 0 0 0 0 10 10 1 1 08
Sharma et al.
(51)
11 1 1 11 1 1 1 1 01 00 0 1 113
Shepherd et al.
(52)
11 1 1 10 1 0 1 1 11 10 0 1 012
Sims
(53)
11 1 1 10 0 0 1 0 10 10 1 1 010
Stafleu et al.
(54)
11 1 1 11 1 0 1 0 11 11 1 1 115
Wardle et al.
(11)
11 1 1 11 1 1 1 1 11 11 1 1 117
Williams et al.
(55)
11 1 1 11 1 1 1 1 01 00 0 1 012
Athlete samples
Frederick &
Hawkins
(56)
11 1 1 11 0 0 1 0 01 00 0 1 09
Hamilton et al.
(57)
11 1 1 11 0 0 1 0 11 11 1 1 013
Harrison
(58)
11 1 1 11 0 0 1 0 00 00 0 1 08
O’Halloran et al.
(59)
11 1 1 11 1 0 1 0 11 10 0 1 012
Rash et al.
(60)
11 1 1 11 0 0 1 0 11 10 0 1 112
Werblow et al.
(61)
11 1 1 10 0 0 1 0 11 10 0 1 010
Wiita et al.
(62)
10 0 0 00 0 0 0 0 00 00 0 1 02
I. Spronk et al.1720
British Journal of Nutrition
in convenience samples. There was limited representation of
participants with low socio-economic status, and some studies
failed to report this demographic characteristic.
Nutrition knowledge was measured with a written
questionnaire for eighteen of the twenty-two studies, one
study used Internet-based collection and the remainder were
by interview (n3). The instruments mostly probed general
nutrition concepts including knowledge of dietary guidelines,
sources and functions of nutrients, skill in choosing healthier
foods and nutrition myths. A smaller number measured
knowledge of specific nutrition areas including nutrition for
cancer prevention (n2), sources of dietary fat (n4), diet
disease relationships (n1) or CHD risk (n1). The number of
items contained within the instruments varied widely from
four to 111. Response formats included true or false, multiple
choice, open-ended items and ranking scales of statements
ranging from agree to disagree.
Athletic populations. Of the twenty-nine included articles,
seven studies
(56 – 62)
utilised an athletic population ranging
from elite to recreational athletes. Most studies were conduc-
ted between 1990 and 1995, with one study conducted
before 1990 and one after the year 2000. Participant numbers
in each study ranged from fourteen to 122 and age ranged
from 17 to 28 years; however, one study included a control
sample with participants aged up to 65 years. Of the seven
studies, one used only male participants, three used only
female participants and three used a mixed-sex population.
Of these studies, five were conducted in North America and
two in New Zealand.
All studies used convenience samples either of mixed
sports (n2) or specific sports (including basketball (n1),
track (n2) and distance running (n2)). All studies used
written questionnaires and item number ranged from 10 to
87. The instruments all probed general nutrition knowledge
and most (n6) also included items on sports-specific knowl-
edge. Response formats utilised true or false, multiple choice
and open-ended items.
Measurement of dietary intake and association with
nutrition knowledge
Most studies used an FFQ to assess dietary intake (n14). Other
studies used dietary records (n9), 24 h recall (n4), an (adapted)
existing food pattern questionnaire (n2)
(61,63)
, an author-
designed food pattern questionnaire (n2)
(50,57)
or a fat and
fibre screener (n1)
(24)
. However, three studies used a
combination of these methods
(27,46,56)
. Some studies only
probed certain nutrients (e.g. fat, fibre or Ca), food groups
(vegetables or fruit) or general eating patterns (Table 3). Most
studies reported some significant, positive association between
nutrition knowledge and dietary intake or pattern. Only ten
studies reported no significant relationship (Table 3). The
associations were generally weak (r,0·5) and most often,
studies reported a positive relationship between higher
nutrition knowledge and a greater intake of vegetables (n11)
and fruit (n10) and a lower intake of fat (n7). Significant
positive associations were found between higher nutrition
knowledge and a greater intake of cereals or fish, a lower
intake of sweetened drinks, a higher intake of fibre or Ca
intake and a higher consumption of some core food groups
more consistent with public health guidelines (Table 3). When
comparing the community with athlete groups, five of the
seven athlete studies (71·4 %) found a positive association
between nutrition knowledge and dietary intake, whereas
within the community studies, fourteen of the twenty-two
studies (63·6 %) found some positive association with eight
reporting no significant association. Relatively few studies
(n5) reported a positive association between nutrition know-
ledge and a negative dietary attribute.
Study quality and validation
Studies scored a mean of 11·2 out of 17 points (range 217;
Table 4). The mean score for study reporting quality, overall
validity of design and data analysis was 7·4 out of 10 points
(range 110). The validity of nutrition knowledge instruments
scored a mean of 2·5 out of 5 points (range 05) and for the
assessment of dietary intake, the mean score was 1·3 out of
2 points (range 12). Major weakness in study quality
revolved around the failure to recruit representative samples
and adjustment for confounding factors such as age, sex and
level of education. Appropriate statistical methods and report-
ing of actual Pvalues or variability estimates were also lacking
in a number of the studies (Table 4).
Only eight of the twenty-nine studies used all five types
of validation for the nutrition knowledge instruments, and
seven studies failed to report any formal validation of the
instrument used. The British-developed General Nutrition
Knowledge Questionnaire
(19)
was the most extensively vali-
dated nutrition knowledge instrument. The General Nutrition
Knowledge Questionnaire or an adaptation of this instrument
was also the most commonly used (five of twenty-nine studies)
nutrition knowledge tool. Approximately 60 % (seventeen
studies) of the studies reported face and content validity
in addition to pilot testing of the instrument used. Only
27·6 % (eight studies) conducted test –retest analysis and
4·1 % (twelve studies) an evaluation of internal consistency.
Adaptation of original instruments was often conducted without
validation of the changes incorporated.
Of the fourteen studies utilising the FFQ method of dietary
assessment, eight used a validated FFQ, two used an FFQ
with partial validation and four had no validation. Length of
recording for dietary records varied between 2 and 3 d with
only one study reporting appropriate outcomes for the length
of recording conducted (e.g. energy and macronutrients, not
micronutrients). Collection period for the 24 h recall varied
between 1 and 3 d. Studies using a specific nutrient screener
(24)
or an (adapted) existing food pattern questionnaire
(61,63)
all
used validated instruments. Overall, only three studies
(11,47,53)
scored the full points for both nutrition knowledge and dietary
intake measurement quality.
Significant positive associations in the community studies
were more often observed in those conducted after the year
1990, using larger and representative samples, higher quality
scores for statistics and adjustment of confounders, and vali-
dated nutrition knowledge and dietary intake measures,
Nutrition knowledge and dietary intake 1721
British Journal of Nutrition
especially FFQ rather than dietary records to measure intake.
Most of the studies (six out of nine scoring the full 2 points
for dietary methodology quality) also showed a positive
association with nutrition knowledge.
The athlete studies were generally older and lower in
quality (9·4 v. 11·0) than those conducted in the community
populations, with none using a representative sample and
none using a well-validated nutrition knowledge instrument
(scoring full 5 points) and appropriate measurement of dietary
intake (scoring full 2 points).
Discussion
The present systematic review examined the relationship
between nutrition knowledge and dietary intake in adults.
Although it would seem both relevant and important to inves-
tigate the impact of nutrition knowledge on dietary intake,
this question has received limited research attention. A total
of twenty-nine relevant articles were identified, of which
twenty-two were conducted in community populations and
seven in athlete populations. Most of the studies (n19/29;
community: n14/22; athletic: n5/7) showed significant,
positive, but weak (r,0·5) associations between nutrition
knowledge and some aspect of dietary intake, most often a
higher intake of fruit and vegetables. Unfortunately, the
studies informing the present systematic review are of varied
quality, and relatively few
(11,27,42,43,48,49,54,57)
used nutrition
knowledge instruments that had been validated using the
five key forms of validation used to assess quality in the
present review. A limited number of studies measured or
reported dietary intake appropriately
(11,21,40,46 – 48,51,54,60)
.
Only three studies
(11,47,53)
used nutrition knowledge and
dietary intake assessments that were both valid. As nutrition
education is widespread in the community and represents a
significant investment by schools, governments and health
agencies, contemporary, high-quality research on the relation-
ship between nutrition knowledge and dietary intake is
required to evaluate and guide these initiatives into the future.
Although many factors including taste, convenience, food
costs, cultural and religious beliefs are known to influence diet-
ary intake
(4,9 – 12)
, nutrition education programmes aim to
improve knowledge and thereby positively influence dietary
intake
(1 – 4)
. The serious lack of well-designed, contemporary
research in this area fails to explore the contribution of nutrition
knowledge among these above-mentioned factors and a range
of other factors that may influence dietary intake. Although it
is implicit that one must have some basic knowledge of nutrition
to guide food choice, nutrition education programmes, which
focus purely on knowledge of facts or so-called declarative
knowledge rather than process knowledge or practical skills,
may be less effective in eliciting positive dietary change
(5)
.
Much of the research fails to tease out the influence of specific
aspects of nutrition knowledge on relevant dietary outcomes
(e.g. knowledge of fat sources and fat intake). However, studies
informing the present review that used nutrition knowledge
instruments that had undergone more extensive validation or
had a valid and appropriate dietary assessment more often
uncovered significant, positive associations between nutrition
knowledge and dietary intake. The lack of well-validated
instruments to measure nutrition knowledge is a major
limitation but also somewhat of a challenge to resolve, since
instruments need to reflect contemporary nutrition knowledge
and guidelines that are constantly evolving. They also need to
be culturally sensitive, and this may be a challenge when
assessing populations with diverse ethnicity.
Over the past 10 years, there has been increasing attention on
the importance of ‘health literacy’, an umbrella term for which
nutrition knowledge is an integral component
(28)
. An adequate
level of health literacy enables an individual to read, calculate
and utilise verbal or written information related to health
(64)
.
Therefore, an adequate degree of health literacy enables an
individual to respond in their best interest. Components of
health literacy include oral, print and media literacy, numeracy,
and cultural and conceptual knowledge
(28,64,65)
. Research
shows that individuals with poor health literacy are less
responsive to health education
(66)
, less successful in managing
chronic disorders
(31,64,67 – 69)
and incur higher health
costs
(13,14)
. A recent Australian study
(18)
has demonstrated that
individuals with limited health literacy were significantly more
likely to report having diabetes, cardiac disease or stroke and
those $65 years were more likely to have been admitted to
hospital. These negative health outcomes from low levels of
health literacy have also been reported in other countries
(70 – 72)
.
Emerging evidence also shows that the level of health literacy
may be lower than expected, with recent studies from Australia
and the USA indicating that a substantial proportion (close to
50 % in some studies) of the population has limited health
literacy
(18,28,71)
.
Although the level of health literacy and nutrition knowledge
are probably associated, an adequate level of health literacy may
not automatically translate to an adequate level of nutrition
knowledge, specifically those aspects relevant to making
appropriate dietary decisions
(73)
or what Zoellner et al.
(28)
define as ‘nutrition literacy’. Health literacy may be situation
or topic specific. A recent study conducted in the USA has
evaluated the impact of health literacy using a tool (Newest
Vital Sign)
(74)
relevant to nutrition, as it included assessment
of reading a food label. This study reported that for every 1
point increase in health literacy, there was a 1·21 point increase
in the US Department of Agriculture Healthy Eating Index score.
The association was significant (P,0·01) even after controlling
for all other relevant variables
(75)
. The health literacy score in
this study also significantly predicted consumption of sugar-
sweetened beverages (the lower the score, the higher the
consumption). Although low health literacy has been linked
with various poor health outcomes, this is one of the first
studies to make a link with diet quality. Unfortunately, although
research on health literacy has expanded in recent years,
there are limited studies focusing specifically on how different
aspects of nutrition knowledge and skills influence dietary
intake and health.
Clearly, failure to evaluate the print and numeracy literacy
of an instrument used to assess nutrition knowledge, or
dietary intake (if written assessment is used), limits the
capacity to assess outcomes, as this is confounded by an
inability to read and comprehend the items. However, it is
I. Spronk et al.1722
British Journal of Nutrition
also clear that limited literacy is also probably a serious
limitation for acquiring nutrition knowledge, selecting and
implementing a healthy diet, and making other positive
choices in relation to health
(28)
. Although some of the studies
informing the present review conducted pilot testing of the
nutrition knowledge instrument used, none specifically
evaluated the level of health literacy required for completion.
The pilot testing was often performed on a small convenience
sample, which was typically not adequately described and
may not have emulated the demographic (and probably
literacy) characteristics of the wider population of participants.
One aspect of nutrition knowledge that is either missing or
under-represented from instruments used in the included
studies is assessment of food label reading. Item descriptors
did not include evaluation of food label reading, and this
would seem to be a critical component of nutrition knowledge,
particularly process knowledge required to make informed
food selection. A number of studies have specifically examined
food label reading skills, and evidence suggests that many
consumers find this challenging
(76)
. Understanding food labels
requires sound literacy and numeracy skills in addition to
knowledge of what ingredients or nutrients are desirable
(e.g. whole grains, dietary fibre, etc.) or undesirable (e.g. satu-
rated fat, salt, etc.). Some knowledge of the relative amounts
of these ingredients or nutrients in the daily diet is also
needed to implement a healthy eating plan
(12)
. The lack of
items probing food label reading skills within the instruments
identified by the present review was surprising, but reflects
the challenge of constructing an instrument to measure what
could be considered as a diverse array of areas that can poten-
tially be deemed related to nutrition knowledge.
A lack of consensus as to what should be included in instru-
ments designed to measure nutrition knowledge is especially
problematic for systematic review as pooling of studies for
meta-analysis is not valid when outcome measurement is
heterogeneous. Many of the instruments assessing nutrition
knowledge were author-designed, only used for one study
and had limited validation. The link between the items
measuring nutrition knowledge and dietary intake was often
not clarified or discussed. Items probing theoretical or
declarative nutrition knowledge may have no relationship to
the practical knowledge required to choose a healthy diet,
i.e. knowing an orange is good source of vitamin C may not
be related to knowing how many servings of the fruit are
required to meet the dietary guidelines and satisfy nutrient
reference values and then selection of a diet consistent with
individual needs.
It would seem logical that future instruments include items
that probe knowledge and understanding of dietary guidelines
with assessment of practical knowledge including recom-
mended servings of core foods and how to select foods with
key health attributes (e.g. those lower in fat or salt) by reading
a food label. Dietary assessment that probes adherence to
dietary guidelines would then also seem the best approach
to explore links between nutrition knowledge and dietary
intake, as the knowledge being tested is logically related to
the dietary outcomes. A lack of connectedness with nutrition
knowledge and dietary intake assessments in a number of
the articles possibly explains the weak or lack of association
observed. The importance of probing both knowledge and
understanding of dietary guidelines is supported by a recent
systematic review exploring consumer responses to healthy
eating, physical activity and weight-related guidelines. The
review reported that many consumers found guidelines con-
fusing, and that there was also a lack of research investigating
the impact of guidelines on dietary behaviour
(77)
.
Despite the weaknesses of the articles informing the present
review, the majority reported a significant and positive
association between nutrition knowledge and some aspect of
dietary intake. Relatively few (n5) studies reported negative
associations, although approximately one-third failed to
observe any association (n10). Studies with larger samples
and validated instruments used to measure nutrition knowledge
or dietary intake more often observed significant positive
associations. This is encouraging and supports investment in
improving nutrition knowledge. Further research, which
improves on flaws identified in the present review, would
reduce measurement noise and be able to better characterise
associations. Importantly, ongoing research should aim to
identify which specific aspects of nutrition knowledge are
more significantly associated with dietary intake. This would
inform nutrition education from public health policy extending
through to clinical counselling. Nutrition misconceptions and
difficulty in understanding or comprehending dietary guide-
lines or food labels probably vary across populations, sexes
and cultures, and a deeper understanding of this would help
to provide education that is targeted and relevant. As a
substantial amount of effort and public funding is directed at
nutrition education initiatives, it is paramount that contem-
porary, high-quality research is undertaken. This would seem
particularly important for populations with low socio-economic
status who are most likely to have low health literacy and a
greater risk of lifestyle disease, and for which the present
review demonstrates that evidence is lacking. Evaluation of
nutrition education campaigns is often restricted to basic
awareness of the key messages with less comprehensive assess-
ment of how such interventions change dietary behaviour
(78,79)
.
A better understanding of this relationship may assist in the
development of more effective community nutrition education
and guide-targeted public health policy and funding.
The limitations of the present review include the quality of
the existing evidence. Quality rating scores ranged from 2 to
17 with a mean of 11·2. Some studies had weak designs, low
sample size and power and few recruited representative
samples. Of the twenty-nine studies, fourteen were conducted
in either university students or athletes where the majority of
the participants were tertiary educated. In fact, relatively few
of the remaining fifteen studies included a diverse range of
participants, including those with social disadvantage. A sub-
stantially higher number of females were recruited in the
included studies, and there is a well known bias with both
sex and socio-economic status for the level of nutrition
knowledge
(9,11,12)
. Clearly, studies in representative samples
using well-validated instruments that also assess nutrition
knowledge with practical relevance to appropriate food
choice and adherence to dietary guidelines would seem
Nutrition knowledge and dietary intake 1723
British Journal of Nutrition
relevant for the future. This may be less relevant to athletic
populations who are known to have specific nutrition needs,
although even in athletes, diets should still remain consistent
with dietary guidelines.
In conclusion, the present review provides evidence of a
weak, positive association between nutrition knowledge and
dietary intake. However, the quality of the evidence is limited
and future studies require the use of well-designed and well-
validated instruments to assess nutrition knowledge and dietary
intake. These instruments must identify the health literacy level
necessary for completion and should be designed with the
understanding that this may be low or limited in a wide sector
of the population. It would seem implicit that items contributing
to the nutrition knowledge assessment in the community
populations be relevant to core facts and skills essential for
selection of an appropriate diet. Logically, this should include
at a minimum, knowledge and understanding of dietary guide-
lines, quantities of food groups needed to maintain health and
the skill to discriminate between food products by reading a
food label. Linking knowledge to dietary patterns or diet quality
scores or indices that aim to assess the adherence to dietary
guidelines would then seem most effective for assessing the
relationship between nutrition knowledge and dietary intake.
As the burden of nutrition-related disease continues to rise
worldwide, it would seem paramount to invest in high-quality
research to advance and refine the measurement of nutrition
knowledge for the future. Contemporary research will guide
evidence-based nutrition education initiatives and public
health policy and optimise public health campaign effectiveness
to reduce the burden of diet-related disease.
Acknowledgements
The authors gratefully acknowledge Dr Janelle Gifford
(Faculty of Health Sciences, University of Sydney) for editorial
assistance.
The present review did not receive any funding or
sponsorship.
The authors’ contributions are as follows: I. S., C. B. and
H. O. contributed to the conception and design of the review.
All authors contributed to the interpretation and analysis of
the data and to the writing and editing of the manuscript.
None of the authors has any conflict of interest to declare.
References
1. Lee YM, Lee MJ & Kim SY (2005) Effects of nutrition education
through discretional activities in elementary school: focused
on improving nutrition knowledge and dietary habits in 4th-,
5th- and 6th-grade students. J Korean Diet Assoc 11, 331 –340.
2. Powers A, Struempler B, Guarino A, et al. (2005) Effects
of a nutrition education program on the dietary behavior
and nutrition knowledge of second-grade and third-grade
students. J School Health 75, 129133.
3. Morgan P, Warren J, Lubans D, et al. (2010) The impact
of nutrition education with and without a school garden
on knowledge, vegetable intake and preferences and quality
of school life among primary-school students. Public Health
Nutr 13, 19311940.
4. Heaney S, O’Connor H, Michael S, et al. (2011) Nutrition
knowledge in athletes: a systematic review. Int J Sport Nutr
Exerc Metab 21, 248 261.
5. Worsley A (2002) Nutrition knowledge and food consump-
tion: can nutrition knowledge change food behaviour? Asia
Pac J Clin Nutr 11, S579S585.
6. WHO (2011) Framework for Care and Control of Tuberculosis
and Diabetes. Geneva: WHO.
7. WHO (2007) Cancer Control: Knowledge into Action.
Geneva: WHO.
8. WHO (2007) Prevention of Cardiovascular Disease. Geneva:
WHO.
9. Hendrie G, Coveney J & Cox D (2008) Exploring nutrition
knowledge and the demographic variation in knowledge
levels in an Australian community sample. Public Health
Nutr 11, 13651371.
10. Dallongeville J, Marecaux N, Cottel D, et al. (2001) Associ-
ation between nutrition knowledge and nutritional intake
in middle-aged men from Northern France. Public Health
Nutr 4, 2733.
11. Wardle J, Parmenter K & Waller J (2000) Nutrition knowledge
and food intake. Appetite 34, 269275.
12. Parmenter K, Waller J & Wardle J (2000) Demographic vari-
ation in nutrition knowledge in England. Health Educ Res
15, 163174.
13. Eichler K, Wieser S & Bru¨gger U (2009) The costs of limited
health literacy: a systematic review. Int J Public Health 54,
313324.
14. Vernon JA, Trujillo A, Rosenbaum S, et al. (2007) Low Health
Literacy: Implications for National Health Policy. Washington,
DC: Department of Health Policy, School of Public Health and
Health Services, The George Washington University, http://
sphhs.gwu.edu/departments/healthpolicy/CHPR/downloads/
LowHealthLiteracyReport10_4_07.pdf.
15. Roberts CK & Barnard RJ (2005) Effects of exercise and diet
on chronic disease. J Appl Phys 98, 3 30.
16. Woo J (2000) Relationships among diet, physical activity and
other lifestyle factors and debilitating diseases in the elderly.
Eur J Clin Nutr 54, Suppl. 3, S143 S147.
17. Harris JR & Wallace RB (2012) The Institute of Medicine’s new
report on living well with chronic illness. Prev Chronic Dis 9, E148.
18. Adams R, Appleton S, Hill C, et al. (2009) Risks associated
with low functional health literacy in an Australian
population. Med J Aust 191, 530534.
19. Parmenter K & Wardle J (1999) Development of a general
nutrition knowledge questionnaire for adults. Eur J Clin
Nutr 53, 298308.
20. Dickson-Spillmann M & Siegrist M (2011) Consumers’
knowledge of healthy diets and its correlation with dietary
behaviour. J Hum Nutr Diet 24, 54– 60.
21. Dissen A, Policastro P, Quick V, et al. (2011) Interrelation-
ships among nutrition knowledge, attitudes, behaviors and
body satisfaction. Health Educ 111, 283295.
22. Byrd-Bredbenner C (1981) A nutrition knowledge test for
nutrition educators. J Nutr Educ 13, 9799.
23. Eppright E, Fox H, Fryer B, et al. (1970) The North Central
Regional Study of diets of preschool children. 2. Nutrition
knowledge and attitudes of mothers. JHomeEcon62, 327 –332.
24. Block G, Gillespie C, Rosenbaum E, et al. (2000) A rapid
food screener to assess fat and fruit and vegetable intake.
Am J Prev Med 18, 284 288.
25. Lee C, Godwin S, Tsui J, et al. (1997) Association between
diet knowledge and quality of diets in Southern rural elderly.
J Nutr Elder 17, 517.
26. Ruddell F (1979) Consumer Food Selection and Nutrition
Information. New York: Praeger Publishers.
I. Spronk et al.1724
British Journal of Nutrition
27. Kristal A, Bowen D, Curry S, et al. (1990) Nutrition
knowledge, attitudes and perceived norms as correlates of
selecting low-fat diets. Health Educ Res 5, 467477.
28. Zoellner J, Connell C, Bounds W, et al. (2009) Peer reviewed:
nutrition literacy status and preferred nutrition communi-
cation channels among adults in the lower Mississippi
Delta. Prev Chronic Dis 6, A128.
29. Penn L, Boeing H, Boushey C, et al. (2010) Assessment of
dietary intake: NuGO symposium report. Genes Nutr 5,
205213.
30. Nelson M, Black A, Morris J, et al. (1989) Between- and
within-subject variation in nutrient intake from infancy to
old age: estimating the number of days required to rank
dietary intakes with desired precision. Am J Clin Nutr 50,
155167.
31. Caballero B, Allen L & Prentice A (2005) Encyclopedia of
Human Nutrition. Oxford: Elsevier Academic Press.
32. Rutishauser I (2005) Dietary intake measurements. Public
Health Nutr 8, 11001107.
33. Collins C, Young A & Hodge A (208) Diet quality is
associated with higher nutrient intake and self-rated health
in mid-aged women. J Am Coll Nutr 27, 146 157.
34. Guenther P, Reedy J & Krebs-Smith S (2008) Development of
the healthy eating index 2005. J Am Diet Assoc 108,
18961901.
35. Heaney S, O’Connor H, Gifford J, et al. (2010) Comparison
of strategies for assessing nutritional adequacy in elite
female athletes’ dietary intake. Int J Sport Nutr Exerc Metab
20, 245256.
36. Britten P, Marcoe K, Yamini S, et al. (2006) Development of
food intake patterns for the MyPyramid Food Guidance
System. J Nutr Educ Behav 6, 6 Suppl., S78 S92.
37. Axelson M, Federline T & Brinberg D (1985) A meta-analysis
of food- and nutrition-related research. J Nutr Educ 17,
5154.
38. Liberati A, Altman DG, Tetzlaff J, et al. (2009) The PRISMA
statement for reporting systematic reviews and meta-analyses
of studies that evaluate health care interventions: explanation
and elaboration. Ann Intern Med 151,W-65W-94.
39. Downs S & Black N (1998) The feasibility of creating a check-
list for the assessment of the methodological quality both of
randomised and non-randomised studies of health care inter-
ventions. J Epidemiol Community Health 52, 377–384.
40. Baghurst K & McMichael A (1980) Nutrition knowledge and
dietary intake in young Australian populations. Community
Health Stud 4, 207214.
41. Bravo A, Martin N & Gonzalez A (2006) Evaluation of dietary
habits of a population of university students in relation with
their nutritional knowledge. Nutr Hosp 21, 466473.
42. Byrd-Bredbenner C, O’Connell L, Shannon B, et al. (1984)
A nutrition curriculum for health education: its effect on
students’ knowledge, attitude, and behavior. J School Health
54, 385388.
43. De Vriendt T, Matthys C, Verbeke W, et al. (2009) Determinants
of nutrition knowledge in young and middle-aged Belgian
women and the association with their dietary behaviour.
Appetite 52, 788 792.
44. Gambaro A, Raggio L, Dauber C, et al. (2011) Nutritional
knowledge and consumption frequency of foods a case
study. Arch Latinoam Nutr 61, 308315.
45. Grotkowski M & Sims L (1978) Nutritional knowledge,
attitudes, and dietary practices of the elderly. J Am Diet
Assoc 72, 499506.
46. Guthrie J & Fulton L (1995) Relationship of knowledge
of food group servings recommendations to food group
consumption. Fam Econ Nutr Rev 8, 217.
47. Harnack L, Block G, Subar A, et al. (1997) Association of
cancer prevention-related nutrition knowledge, beliefs, and
attitudes to cancer prevention dietary behavior. J Am Diet
Assoc 97, 957965.
48. Jovanovic G, Kresic G, Zezelj S, et al. (2011) Cancer and
cardiovascular diseases nutrition knowledge and dietary
intake of medical students. Coll Anthropol 35, 765 774.
49. Kresic G, Jovanovic G, Zezelj S, et al. (2009) The effect of
nutrition knowledge on dietary intake among Croatian uni-
versity students. Coll Anthropol 33, 1047 1056.
50. Schwartz N (1975) Nutritional knowledge, attitudes, and
practices of high school graduates. J Am Diet Assoc 66,
2831.
51. Sharma S, Gernand A & Day R (2008) Nutrition knowledge
predicts eating behavior of all food groups except fruits
and vegetables among adults in the Paso del Norte region:
que
´sabrosa vida. J Nutr Educ Behav 40, 361 368.
52. Shepherd R & Stockley L (1987) Nutrition knowledge,
attitudes, and fat consumption. J Am Diet Assoc 87, 615 619.
53. Sims L (1978) Dietary status of lactating women. II. Relation
of nutritional knowledge and attitudes to nutritional intake.
J Am Diet Assoc 73, 147 154.
54. Stafleu A, Van Staveren W, De Graaf C, et al. (1996) Nutrition
knowledge and attitudes towards high-fat foods and low-fat
alternatives in three generations of women. Eur J Clin Nutr
50, 3341.
55. Williams L, Campbell K, Abbott G, et al. (2012) Is maternal
nutrition knowledge more strongly associated with the
diets of mothers or their school-aged children? Public
Health Nutr 15, 13961401.
56. Frederick L & Hawkins S (1992) A comparison of nutrition
knowledge and attitudes, dietary practices, and bone
densities of postmenopausal women, female college athletes,
and nonathletic college women. JAmDietAssoc92, 299 – 305.
57. Hamilton G, Thomson C & Hopkins W (1994) Nutri-
tion knowledge of elite distance runners. NZ J Sports Med
22, 2629.
58. Harrison J, Hopkins W, MacFarlane D, et al. (1991) Nutrition
knowledge and dietary habits of elite and non-elite athletes.
Aus J Nutr Diet 48, 124127.
59. O’Halloran C, Bowlby M & Pipe A (1990) Nutrition knowl-
edge and dietary practices of elite male basketball players.
J Can Diet Assoc 51, 357 360.
60. Rash C, Malinauskas B, Duffrin M, et al. (2008) Nutrition-
related knowledge, attitude, and dietary intake of college
track athletes. Sport J 11, 4854.
61. Werblow J, Fox H & Henneman A (1978) Nutritional know-
ledge, attitudes, and food patterns of women athletes. JAm
Diet Assoc 73, 242245.
62. Wiita B, Stombaugh I & Buch J (1995) Nutrition knowledge
and eating practices of young female athletes. J Phys Educ
Recreation Dance 66, 36 41.
63. Roe L, Strong C, Whiteside C, et al. (1994) Dietary
intervention in primary care: validity of the DINE method
for diet assessment. Fam Pract 11, 375381.
64. Nielsen-Bohlman L, Panzer A & Kindig D (2004) Health
Literacy: A Prescription to End Confusion. Washington, DC:
National Academies Press.
65. Hindin T, Contento I & Gussow J (2004) A media literacy
nutrition education curriculum for head start parents about
the effects of television advertising on their children’s food
requests. J Am Diet Assoc 104, 192198.
66. Schillinger D, Barton L, Karter A, et al. (2006) Does literacy
mediate the relationship between education and health
outcomes? A study of a low-income population with
diabetes. Public Health Rep 121, 245254.
Nutrition knowledge and dietary intake 1725
British Journal of Nutrition
67. White S, Chen J & Atchison R (2008) Relationship of
preventive health practices and health literacy: a national
study. Am J Health Behav 32, 227242.
68. DeWalt D & Hink A (2009) Health literacy and child health
outcomes: a systematic review of the literature. Pediatrics
124, 3 Suppl., S265S274.
69. Berkman N, Sheridan S, Donahue K, et al. (2011) Health
literacy interventions and outcomes: an updated systematic
review. Evid Rep Technol Assess (Full Rep) 1 941.
70. Baker D, Gazmararian J, Williams M, et al. (2002) Functional
health literacy and the risk of hospital admission among
Medicare managed care enrollees. Am J Public Nutr 92,
12781283.
71. Ibrahim S, Reid F, Shaw A, et al. (2008) Validation of a health
literacy screening tool (REALM) in a UK population with
coronary heart disease. J Public Health 30, 449 455.
72. Williams M, Baker D, Parker R, et al. (1998) Relationship
of functional health literacy to patients’ knowledge of their
chronic disease: a study of patients with hypertension and
diabetes. Arch Intern Med 158, 166 172.
73. Parker R, Baker D & Williams M (1995) The test of functional
health literacy in adults. J Gen Intern Med. 10, 537 541.
74. Weiss B, Mays M, Martz W, et al. (2005) Quick assessment
of literacy in primary care: the newest vital sign. Ann Fam
Med 3, 514522.
75. Zoellner J, You W, Connell C, et al. (2011) Health literacy is
associated with Healthy Eating Index scores and sugar-
sweetened beverage intake: findings from the rural lower
Mississippi Delta. J Am Diet Assoc 111, 10121020.
76. Cowburn G, Cowburn G & Stockley L (2005) Consumer
understanding and use of nutrition labelling: a systematic
review. Public Health Nutr 8, 2128.
77. Boylan S, Louie J & Gill T (2012) Consumer response to
healthy eating, physical activity and weight-related recom-
mendations: a systematic review. Obesity Rev 13, 606617.
78. Contento IR, Randell JS & Basch CE (2002) Review and
analysis of evaluation measures used in nutrition education
intervention research. J Nutr Educ Behav 34, 2 25.
79. Contento I, Balch GI, Bronner YL, et al. (1995) The effective-
ness of nutrition education and implications for nutrition
education policy, programs, and research: a review of
research. J Nutr Educ 27, 355364.
80. Cotugna N, Subar AF, Heimendinger J, et al. (1992) Nutrition
and cancer prevention knowledge, beliefs, attitudes, and
practices: the 1987 National Health Interview Survey. JAm
Diet Assoc 92, 963968.
81. Paas G, Scheijder P, Wedel M, et al. (1994) De ontwikkeling
van een vragenlijst naar voedingskennis (The development
of a nutrition knowledge questionnaire). Ned Tijdschr
Die
¨tisten 49, 7881.
82. Annable J(1976) Nutrition knowledge, attitudes and food
patterns of women athletes at the University of Nebraska.
PhD Thesis, University of Nebraska.
83. Woolcott DM, Kawash GF & Sabry JH (1981) Correlates of
nutrition knowledge in Canadian businessmen. J Nutr Educ
13, 153156.
84. Barr S (1987) Nutrition knowledge of female varsity athletes
and university students. J Am Diet Assoc 87, 1660.
85. Jonnalagadda SS, Rosenbloom CA & Skinner R (2001)
Dietary practices, attitudes, and physiological status of
collegiate freshman football players. J Strength Cond Res
15, 507513.
86. Zawila LG, Steib C-SM & Hoogenboom B (2003) The female
collegiate cross-country runner: nutritional knowledge and
attitudes. J Athl Train 38, 6774.
87. Baghurst K & McMichael A (1978) Evaluation of question-
naire methods of measurement of alcohol consumption in
young Australians. Comm Health St 2, 135139.
88. Pynaert I, Matthys C, De Bacquer D, et al. (2007) Evaluation
of a 2-day food record to determine iron, calcium and
vitamin C intake in young Belgian women. Eur J Clin Nutr
62, 104110.
89. Block G, Hartman AM & Naughton D (1990) A reduced dietary
questionnaire: development and validation. Epidemiology 1,
5864.
90. Kaic-Rak A & Antonic K (1990) Tables of Chemical Compo-
sition of Food and Drinks. Zagreb: Institute for Public Health.
91. Kulier I (1996) Standard Euro – Food Composition Tables.
Zagreb: Hrvatski Farmer.
92. Baumgartner K, Gilliland F, Nicholson C, et al. (1997) Validity
and reproducibility of a food frequency questionnaire
among Hispanic and non-Hispanic white women in New
Mexico. Ethn Dis 8, 8192.
93. McPherson RS, Kohl HW, Garcia G, et al. (1995)
Food-frequency questionnaire validation among Mexican-
Americans: Starr County, Texas. Annals of Epidemiol 5,
378385.
94. Shepherd R & Stockley L (1985) Fat consumption and
attitudes towards food with a high fat content. Human
Nutr Appl Nutr 39, 431432.
95. Feunekes GI, Van Staveren WA, De Vries J, et al. (1993)
Relative and biomarker-based validity of a food-frequency
questionnaire estimating intake of fats and cholesterol. Am
J Clin Nutr 58, 489496.
96. Rockett HR, Breitenbach M, Frazier AL, et al. (1997)
Validation of a youth/adolescent food frequency question-
naire. Prev Med 26, 808 816.
97. Cho M & Fryer B (1974) What foods do physical education
majors and basic nutrition students recommend for athletes?
J Am Diet Assoc 65, 541 544.
I. Spronk et al.1726
British Journal of Nutrition
... A relatively new concept, a critical component of food literacy is food knowledge [17]. Despite the importance of food knowledge, a relatively small number of studies have investigated the links between food knowledge and diet [18]. Knowledge about food and nutrition has been shown to correlate with improved dietary intake among adults [18], and among adolescents aged 14 to 19 years, knowledge of how to eat a healthy diet has been identified as one of a number of psychosocial factors (i.e., increased awareness and self-efficacy) associated with healthful dietary behaviours [19]. ...
... Despite the importance of food knowledge, a relatively small number of studies have investigated the links between food knowledge and diet [18]. Knowledge about food and nutrition has been shown to correlate with improved dietary intake among adults [18], and among adolescents aged 14 to 19 years, knowledge of how to eat a healthy diet has been identified as one of a number of psychosocial factors (i.e., increased awareness and self-efficacy) associated with healthful dietary behaviours [19]. However, few studies have focused on the relationship between dietary intake and food knowledge in younger children. ...
... To our knowledge, this is the first study that examined the association of food knowledge with intake of total FVs among children aged 9-14. Of the studies that focused on food knowledge and dietary intake, the majority have focused on adults [18], athletes [34,35] and university students [36]. Very few studies internationally have investigated associations between dietary intake and nutrition knowledge among children; those that have been published are among children in Italy, Japan, and the US, and none focused specifically on FV intake. ...
Article
Full-text available
Interventions to improve dietary quality and intake of fruits and vegetables (FV) among Canadian children have had modest success, and it has been suggested that food knowledge could be key to improvement. Programs have been criticized for insufficiently connecting food knowledge with food skills and decision making about dietary intake. The objective of this study was to investigate factors associated with FV consumption by elementary school children, aged 9–14 years, in Ontario, Canada, including food knowledge, socioeconomic status, sociodemographic characteristics, and the food environment. In 2017–2019, a cross-sectional survey was administered to 2443 students at 60 elementary schools across Southwestern Ontario (SWO), Canada. A parent survey was used to validate self-reported sociodemographic variables. The mean intake of FV reported by these participants was 2.6 (SD 1.1) and 2.4 (SD 1.2) servings/day, respectively. A FV intake below WHO guidelines was reported by 40.7% of respondents. Knowledge score, child age, and parent employment status significantly predicted higher reported intake of FV. This study shows that FV intake among this population group is low, and increased intake is associated with higher food knowledge. To encourage healthy eating, school-based food and nutrition programs that incorporate multiple components and emphasize food literacy are needed.
... Cultural and religious factors, availability of food products, and consumer behaviors also shape dietary choices [6,7]. A growing number of researchers underline the impact of nutrition knowledge on diet-related behaviors [8][9][10]. Nutrition knowledge refers to awareness of practices and concepts related to nutrition and health such as adequate food intake, diet-related diseases, foods representing major sources of nutrients, as well as dietary guidelines and recommendations [8][9][10]. ...
... A growing number of researchers underline the impact of nutrition knowledge on diet-related behaviors [8][9][10]. Nutrition knowledge refers to awareness of practices and concepts related to nutrition and health such as adequate food intake, diet-related diseases, foods representing major sources of nutrients, as well as dietary guidelines and recommendations [8][9][10]. The Internet, family members, and friends, as well as television, are the most common sources of nutrition knowledge reported globally [11,12]. ...
Article
Full-text available
An unhealthy diet is an important risk factor for disability and premature death. This study aimed to assess nutrition knowledge, dietary habits, and food label use among adults in Poland as well as to identify factors associated with diet-related behaviors. A cross-sectional survey was carried out in July 2020 on a non-probability quota-based sample of 1070 adult citizens of Poland. The most common sources of nutrition knowledge were news websites (41.8%) or family/friends (32.4%). Over one-quarter of adults in Poland were on a diet (28.7%). Over one-tenth of respondents (11.9%) consumed less than three meals per day. Half of the respondents (50.3%) declared that they use food labels when shopping, and 15.4% checked the nutrition information on restaurant menus. Female gender (OR:1.70; 95%CI:1.26–2.29; p < 0.001), presence of chronic diseases (OR:1.83; 95%CI:1.37–2.44; p < 0.001), regular physical activity (p < 0.001), and being a non-smoker (OR:1.45; 95%CI:1.02–2.06; p = 0.04) were significantly associated with higher odds of being on a diet. Females (OR:1.63; 95%CI:1.24–2.15; p < 0.001), respondents with higher education (OR:1.53; 95%CI:1.17–2.01; p = 0.002), those who had never been married (OR:1.49; 95%CI:1.07–2.07; p = 0.02), respondents with chronic diseases (OR:1.73; 95%CI:1.30–2.31; p < 0.001), those with regular physical activity (p < 0.05), as well as non-smokers (OR:1.42; 95%CI:1.04–1.95; p = 0.03) had higher odds of checking the food labels. This study showed a significant gap in nutrition knowledge among adults in Poland.
... Dietary practices in a society are shaped by circumstantial factors, such as nutrition knowledge, income, accessibility, urbanization, marketing of food products, climate change, conflict and humanitarian crisis, unprecedented outbreak of diseases, and so on. The importance of nutrition knowledge in dietary practices is noted in different literatures varying with age, education, gender, geography, and so on (Spronk et al. 2014). Ability to purchase food may have improved due to increasing income, but high costs of nutritious food restricted its access to many especially low-income groups and urban populations. ...
Chapter
Full-text available
Access to nutrition and safe food is a key to sustaining life and promoting good health. Thus, the sustainable development goals (SDGs) reawaken the world alluding to the interweaving connects of health, nutrition, and food safety. This chapter introduces the current scenario of nutrition and food safety and how both traverse important issues in health including the trends of morbidity and mortality as well as the social determinants of health. Furthermore, key elements of nutrition and food safety will be introduced to further explicate how factors and drivers shape and influence food supply including production and access, food safety, and consumer behavior and practices. Finally, we argue how considerable efforts have been made drawing on the current context of changing nutrition and food safety driven by multiple factors embracing externalities, and endogenous factors are being contested and negotiated to make an impact on health equity at a global scale. To further the progress of the SDGs, we conclude with propositions to support international organizations, national government, and local stakeholders to work not in sectoral fragmentation, but together. With the appropriate commitment, investment, and actions at global, regional, and country level, no one will be left behind from attaining good health by reinforcing synergies and trade-offs among SDGs related to nutrition and food safety
... Families enjoyed spending time together [29,32], and some parents also described that these moments became an opportunity for transmitting food-related knowledge [29]. Knowledge about food has been shown to influence food decisions [85,86] and inform meal planning [87], the latter being linked with an improved diet quality and less obesity [88]. Moreover, the importance of maternal nutrition knowledge on the diet quality of children/adolescents has been reported in several studies [89,90], including considerations for the mediating effect of the home environment [91]. ...
Article
Full-text available
Home confinement during the COVID-19 pandemic has been accompanied by dramatic changes in household food dynamics that can significantly influence health. This systematic literature review presents parental perspectives of the impact of COVID-19 lockdown (up to 30 June 2022) on food preparation and meal routines, as well as other food-related behaviors, capturing both favorable and unfavorable changes in the household food environment. Themes and trends are identified and associations with other lifestyle factors are assessed. Overall, families enjoyed more time together around food, including planning meals, cooking, and eating together. Eating more diverse foods and balanced home-cooked meals (e.g., fresh fruit and vegetables) was combined with overeating and increased snacking (e.g., high-calorie snacks, desserts, and sweets), as parents became more permissive towards food; however, food insecurity increased among families with the lowest income. Adoption of meal planning skills and online shopping behavior emerged alongside behaviors aimed at self-sufficiency, such as bulk purchasing and stockpiling of non-perishable processed foods. These results are an important first step in recognizing how this pandemic may be affecting the family food environment, including low-income families. Future obesity prevention and treatment initiatives, but also ongoing efforts to address food management, parental feeding practices, and food insecurity, can account for these changes moving forward.
... Additionally, an intervention study showed that nutritional education sessions about the MDP significantly improved adherence to the MDP between pre-and post-intervention groups [31]. However, it is important to note that nutritional education does not always translate into the adoption of healthy dietary patterns [32] because dietary intake is affected by the interaction of several environmental, social, and intrinsic factors [10]. ...
Article
Full-text available
The aim of this cross-sectional study was to understand how the public in a non-Mediterranean multi-ethnic society perceived the Mediterranean dietary pattern (MDP) and its general health benefits. A total of 373 participants took part in this study. Most of the sample were young adults, females and had been living in Australia for over 10 years. Knowledge of the MDP score, attitudes towards the MDP score and an adherence to the MPD score were measured. Normality of variables was tested. Simple linear regression and Chi-squared tests were conducted to examine associations. ANOVA tests were used to report participants’ demographics across various attitudes scores. Less than half of participants were aware of the MDP guidelines, food choices and health benefits. As for adherence to the MDP, 20% of the sample were found to have high adherence to the MDP. Results also showed that participants with high knowledge about the MDP were twice more likely to have higher MDP adherence rates, OR 95% CI = 2.3 (1.3, 4.0), p-value = 0.002. This paper provided new insights about the association between nutritional knowledge and adherence to the MDP in a multi-ethnic non-Mediterranean setting.
... Poor dietary habits are implicated in ∼20% of deaths worldwide world each year (3). As a crucial influencing factor of eating behavior, nutrition literacy affected people's diet choice and health (4)(5)(6)(7). ...
Article
Full-text available
Objectives To develop and validate a short-form nutrition literacy (NL) assessment tool for Chinese college students based on a 43-item NL measurement scale. Methods To develop and validate short-form NL scale, 1359 college students were surveyed, the data were analyzed using exploratory factor analysis, linear regression analysis, Item analysis, confirmatory factor analysis, and Pearson correlation. Results The 12-item short-form NL scale (NL-SF12) was developed using factor analysis and regression analysis, which accounted for 96.4% of the variance. The correlation coefficient between the NL-SF12 and NL-43 was 0.969, indicating satisfactory criterion-related validity. The NL-SF12 had a Cronbach's α of 0.890, suggesting strong internal consistency reliability, and content validity index was greater than 0.9, indicating that each domain accurately reflects the connotation of nutrition literacy. The model–data fit and convergent validity of the confirmatory factor analysis results were both good. Conclusion The NL-SF12 is an effective measurement tool with a good reliability and acceptable validity to assess comprehensively NL for college students, and is applicable to quick, widespread use in population study and practice with low respondent burden.
... 4 Con base en la hipótesis, según la cual el nivel de acceso a conocimientos científicos en alimentación y nutrición puede favorecer e incluso determinar las conductas alimentarias de las personas, desde hace tres décadas se ha incrementado el interés por estudiar en qué medida los individuos orientan sus conductas alimentarias basándose en reglas fundamentadas en conocimiento científico. 5 De allí se ha propuesto la necesidad de elaborar instrumentos sensibles para medir en los grupos humanos el nivel de conocimientos científicos en nutrición. 6 El General Nutrition Knowledge Questionnaire for Adults (GNKQA), es un instrumento empleado para investigar y evaluar el nivel de conocimientos científicos en nutrición en población adulta, el cual fue diseñado y validado por Parmenter y Waedle 1999, 6 y validado en diferentes contextos socioculturales y geográficos. ...
Article
Full-text available
Introducción: el cuestionario de conocimientos en nutrición General Nutrition Knowledge Questionnaire for Adults (GNKQA), ha sido validado en diversos contextos socioculturales; pero para usarlo en Oaxaca, México, se requiere evaluar previamente su fiabilidad y validez. Objetivo: evaluar la fiabilidad y validez del GNKQA en adultos alfabetizados de Oaxaca. Método: el instrumento se adaptó transculturalmente mediante traducción lingüística bidireccional y equivalencia semántica. En una muestra de estudiantes universitarios de Oaxaca se evaluó la fiabilidad conforme al tiempo de aplicación e inteligibilidad. La validez de constructo se determinó por el método de grupos extremos, uno de estudiantes de nutrición y otro de licenciaturas ajenas al campo de la biología y la salud. Mediante prueba T para muestras independientes con significancia del 95%, se compararon los puntajes promedio por grupo obtenidos en el cuestionario. Además, se compararon los quintiles de ambos grupos. La consistencia interna se evaluó por el coeficiente a Cronbach. Resultados: el tiempo de aplicación fue 32 minutos en promedio. Cuatro alimentos fueron desconocidos, en porcentajes menores: guachinango (3.5%), almidón (1.2%), leche desnatada (1.8%) y queso panela (2.4%). El 97.5% de los individuos de otras carreras obtuvo puntajes inferiores a cualquiera de nutrición, con una significancia p < 0.000. El instrumento en conjunto obtuvo un a Cronbach 0.803. Conclusión: el GNKQA es útil para evaluar conocimientos en nutrición en adultos jóvenes alfabetizados de Oaxaca, y puede servir para estudiar la relación entre tales conocimientos y las prácticas alimentarias.. Palabras clave: conocimientos, actitudes y práctica en salud, conductas alimentarias, encuestas y cuestionarios, alimentación, Oaxaca. Introduction: The General Nutrition Knowledge Questionnaire for Adults (GNKQA) has been validated in various sociocultural contexts. To use it in Mexico and specifically in Oaxaca, its reliability and validity must be pre-evaluated. Objective. To evaluate the reliability and validity of GNKQA in literate adults in Oaxaca. Method: The instrument was transculturally adapted through bidirectional linguistic translation and semantic equivalence and was applied to a sample of university students in Oaxaca. Evaluation of reliability was by time of application and intelligibility. Construct validity was determined by T-test for independent samples by comparing the average scores obtained in the questionnaire of two groups: students of nutrition and from computer and social sciences. The quintiles of both groups were compared. Internal consistency was assessed by Cronbach's alpha. Results: The application time was 32 minutes average. Four foods were unknown by a minority: Huachinango (fish) (3.5%), starch (1.2%), skimmed milk (1.8%) and panela cheese (2.4%). The 97.5% of individuals from computer and social sciences obtained lower scores than any of the nutrition students, with a significance p < .000. The complete questionnaire obtained a 0.803 Cronbach´s alpha. Conclusion: The GNKQA is useful for evaluate nutrition knowledge in literate young adults of Oaxaca and could be used to study the relationship between such knowledge and food practices.
Article
Background and Study Aim. Nutrition knowledge is related to dietary behavior in athletes. Therefore, it may also have an impact on performance. Athletes with better nutrition knowledge have more healthy dietary habits. This meta-analysis study focused on the impact of gender on the nutrition knowledge levels of physical education and sports stakeholders. Material and Methods. This study adopted a meta-analysis research design, which is used to analyze, synthesize, and interpret quantitative findings from an array of studies through advanced statistical techniques. A meta-analysis involves combining the findings of studies carried out in different places and at different times on the same topic and obtaining a quantitatively accurate result based on a large sample. This study employed the Comprehensive Meta-Analysis (CMA, v. 2.0) to determine effect sizes and the variance of each study and to compare groups. Cohen’s kappa intercoder reliability and outlier tests were performed using the Statistical Package for Social Sciences (SPSS). Results. We focused on 31 studies with a total sample size of 4575. We calculated the effect size of each study. We found a statistically significant effect size in favor of female stakeholders (d = 0.15; 95% CI -0.22 -0.09) in the fixed effects model, which was a weak result according to Cohen’s classification. We determined a statistically significant effect size in favor of female stakeholders (d = 0.15; 95% CI -0.29-0.01) in the random-effects model. These results suggest a slight difference in nutrition knowledge levels between male and female physical education and sports stakeholders. This result can pave the way for further research. Conclusions. It is understood from the physical education and sports stakeholders that there is a weak difference in the nutritional knowledge levels of women compared to men. It is thought that people who study on sports nutrition and nutrition programs will benefit from the present finding. In addition, it is estimated that the researches to be carried out on the relevant subject will take the current study as a reference.
Article
Full-text available
4-2-2 Umami-naka, Koryo-cho, Kitakatsuragi-gun, Nara 635-0832, Japan) 1.はじめに 先行研究によると,専門家と非専門家など,明らか に異なるレベルの知識を持つグループを比較し,知識 と食行動が健康上の結果を含む他の要因と関連してい るかどうかを調査している 1) 2) .また,専門教育を受 講している大学生についても同様の調査が行われてい る 3) .これらの比較の1つに栄養士と非栄養士があり, 栄養知識に関する質問票を検証するために使用されて いる 4) 5) .栄養士は,非栄養士よりも栄養に関する知 識が豊富であることから,健康的な食行動をとると考 えられ,食物選択と栄養摂取にも影響を与える可能性 がある 6) と考えられてきた.ところが,日本で実施さ れた栄養士女性と一般成人女性を対象に, ナトリウム, カリウムの摂取量, 食品の摂取量を比較した調査では, 栄養士群の方が,栄養知識レベルが高く,食塩摂取に も気を遣っていたにも関わらず,ナトリウムおよびカ リウム排泄量に関しては一般女性群と有意な差は見ら れなかったことが明らかになった 7) .これにより,個 人の栄養知識の高さや健康的な食行動への意識が必ず しも適切な栄養摂取に結びつくとは限らないことが示 唆された. そこで,栄養の専門教育を受講し,栄養知識が豊富 と考えられる栄養関連学科に所属する女子大学生と他 学科所属の女子大学生を比較し,栄養士と一般女性の 結果と同様に,栄養知識と食行動が栄養摂取に及ぼす 関連性が希薄であれば,食事に関する事項について栄 養関連学科に所属する女子大学生という属性をバイア スと捉える必要はなくなると考えられる. これにより, 栄養関連学科に所属する女子大学生が持つ自らの食課 題は,若い世代の食課題と捉えることが可能となる. 農林水産省で策定された第4次食育推進計画の中に, 栄養バランスに配慮した食生活を実践する若い世代を 増やす,という目標がある.しかしながら,若い世代 はその他の世代よりも実践する者の割合が低く,男性 は将来の肥満が懸念されることや女性はやせの者が多 いなど,食生活に起因する課題が多数あることが現状 である 8) .そこで,これらの若い世代に対する食課題 を解決するために,栄養関連学科に所属する女子大学 生が,自らの課題解決をロールモデルとすることで, より実践的な食育活動が実施できると考えられる.こ のように,食課題解決に向けて研究活動を積極的に行 2022年3月30日 投稿 2022年5月24日 受理 要約 栄養知識・意識が高く,食行動に気を遣っていると思われる栄養関連学科の女子大学生と一般女子大 学生の2群を食事歴法により比較した結果,食行動に有意な差が見られたものの,栄養素摂取量と栄養素不 適切者割合には有意な差が見られなかった.このことから,栄養知識と食行動は,実際の栄養摂取と関連性 が希薄であることが明らかとなり,併せて栄養摂取に関して,栄養関連学科女子大学生の一般性も示唆され た.すなわち,栄養関連学科女子大学生が持つ自らの食課題を若い世代の課題と捉え,解決に向けたより実 践的な研究,食育活動を期待できる.ただ,栄養摂取改善には,個人の努力では限界があるため,学食等の 食環境整備も併せて必要と考える. Keywords:栄養摂取,栄養知識,食意識,食行動,一般性
Article
Perceived (or subjective) wellbeing is regarded as key to understanding consumer food choices and the development of strategies to promote desirable eating habits. Yet, in-depth understanding of the specific factors that contribute to people's perceived wellbeing across cultures is lacking. These factors motivated the present research that used word associations to conduct an exploratory analysis of consumer conceptualisations of food-related wellbeing (WB). Adults (n = 4945) living in the United Kingdom, Australia, Singapore or Germany, speaking respectively, English or German, took part in the study. Health, pleasure, food quality, positive emotions and social aspects of food consumption were the main associations with food-related wellbeing. Absence hereof was associated with unhealthiness, disgust, negative emotions and poor mental health. The differences in these main associations emphasised the importance of exploring wellbeing, as well as lack hereof. Not doing so leads to an incomplete understanding of this multidimensional construct. The research was conducted with four terms related to wellbeing (each in their positive and negative versions): ‘sense of wellbeing’ and ‘lack of wellbeing’, ‘feeling good’ and ‘feeling bad/unhappy’, ‘satisfied with life’ and ‘dissatisfied with life’ and ‘fulfilled in life’ and ‘unfulfilled in life’. Because these different terms gave rise to different wellbeing associations, researchers in this area must choose their empirical approach with care. The terms ‘sense of wellbeing’ and ‘feeling good’ tended to more frequently give rise to health-related associations. Conversely, ‘satisfied with life’ and ‘fulfilled in life’ tended to more frequently give rise to positive spiritual and emotional associations of food-related wellbeing. The main conceptualisations of food-related wellbeing were cross-culturally similar, but extension of the present research to other Asian countries was recommended based on several differences between Singaporean participants and those from other countries. In ethnically diverse countries like Singapore, further within-country investigations of different cultures also have merit.
Book
Full-text available
Nearly half of all American adults—90 million people—have difficulty understanding and acting upon health information. The examples below were selected from the many pieces of complex consumer health information used in America. • From a research consent form: “A comparison of the effectiveness of educational media in combination with a counseling method on smoking habits is being examined.” (Doak et al., 1996) • From a consumer privacy notice: “Examples of such mandatory disclosures include notifying state or local health authorities regarding particular communicable diseases.” • From a patient information sheet: “Therefore, patients should be monitored for extraocular CMV infections and retinitis in the opposite eye, if only one infected eye is being treated.” Forty million Americans cannot read complex texts like these at all, and 90 million have difficulty understanding complex texts. Yet a great deal of health information, from insurance forms to advertising, contains complex text. Even people with strong literacy skills may have trouble obtaining, understanding, and using health information: a surgeon may have trouble helping a family member with Medicare forms, a science teacher may not understand information sent by a doctor about a brain function test, and an accountant may not know when to get a mammogram. This report defines health literacy as “the degree to which individuals have the capacity to obtain, process, and understand basic health information and services needed to make appropriate health decisions” (Ratzan and Parker, 2000). However, health literacy goes beyond the individual obtaining information. Health literacy emerges when the expectations, preferences, and skills of individuals seeking health information and services meet the expectations, preferences, and skills of those providing information and services. Health literacy arises from a convergence of education, health services, and social and cultural factors. Although causal relationships between limited health literacy and health outcomes are not yet established, cumulative and consistent findings suggest such a causal connection. Approaches to health literacy bring together research and practice from diverse fields. This report examines the body of knowledge in this emerging field, and recommends actions to promote a health-literate society. Increasing knowledge, awareness, and responsiveness to health literacy among health services providers as well as in the community would reduce problems of limited health literacy. This report identifies key roles for the Department of Health and Human Services as well as other public and private sector organizations to foster research, guide policy development, and stimulate the development of health literacy knowledge, measures, and approaches. These organizations have a unique and critical opportunity to ensure that health literacy is recognized as an essential component of high-quality health services and health communication.
Article
This paper describes a nutrition knowledge survey carried out on a cross-section of the adult population of England (n = 1040), looking at knowledge relating to current dietary recommendations, sources of nutrients, healthy food choices and diet-disease links. Serious gaps in knowledge about even the basic recommendations were discovered, and there was much confusion over the relationship between diet and disease. Significant differences in knowledge between socio-demographic groups were found, with men having poorer knowledge than women, and knowledge declining with lower educational level and socio-economic status. Possible reasons for these differences and implications for public education campaigns and socio-economic inequalities in health are discussed.
Article
Nutritional knowledge and dietary intake was assessed in two differing young Australian populations that had recently completed their schooling. No relationship was found between dietary practice and nutritional knowledge. These findings have implications for health education programs aimed at the young adult in that health-oriented knowledge may not necessarily be translated to health-oriented behaviour.