roisin mcgann_final report

Roisin McGann Human Nutrition PWE project 2014/15

Project Title: School Level Socioeconomic Differences in School Lunch Quality: A Cross Sectional Study of 8-11 year old Children

Student Name: Roisin McGann

Student ID: 12388981

Supervisor: Janas Harrington and Catherine Perry

UCD-Tutor: Celine Murrin

Academic Year: 2014/15

Submitted in completion of my third year professional work experience

To the Institute of Food and Health, University College Dublin

July 2015

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Personal Contribution to this work

The author’s responsibilities involved the development of the research question, the

conduction of the literature review, the planning and the undertaking of data analysis. The

report author additionally carried out data management tasks such as, recoding and

generating variables and performed various statistical tests throughout the analysis stage.

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ContentsPersonal Contribution to this work.......................................................................................................2

Chapter 1: Abstract...............................................................................................................................5

Chapter 2: Introduction........................................................................................................................6

2.1 Objective.................................................................................................................................6

2.2 Background.............................................................................................................................7

2.2.1 The issue...........................................................................................................................7

2.2.2 DEIS.................................................................................................................................7

2.2.3 The school place...............................................................................................................8

2.2.4 School Food Trust............................................................................................................9

2.2.5 Nutrient intake................................................................................................................10

2.2.6 Diet Quality....................................................................................................................12

Chapter 3: Methodology.....................................................................................................................14

3.1 Study design..........................................................................................................................14

3.1.1 Population samples.........................................................................................................14

3.1.2 Recruitment Methods.....................................................................................................14

3.2 Data collection in the Cork Children’s Lifestyle Study........................................................15

3.3.1 Dietary assessment.........................................................................................................15

3.2.2 Primary exposure............................................................................................................15

3.2.3 Co-variants.....................................................................................................................16

3.3 Data Management..................................................................................................................17

3.4 Statistical Procedures............................................................................................................17

Chapter 4: Results..............................................................................................................................19

4.2 Response Rate.......................................................................................................................19

4.2 Demographics........................................................................................................................19

4.3 Analysis of School Lunches..................................................................................................22

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4.3.1 Differences in nutrient intake.........................................................................................22

4.3.2 Difference in dietary quality...........................................................................................24

4.3 The lunchtime intakes of DEIS and non-DEIS 8-11 year olds compared to the SFT and EFSA standards..............................................................................................................................26

4.4 The contribution of lunchtime nutrient intake and dietary quality relative to energy intake28

4.5 Univariate and multivariate analysis of nutrient intake and the dietary quality of school lunch31

Chapter 5: Discussion.........................................................................................................................37

Strengths & Limitations of the study.............................................................................................38

Chapter 6: Conclusion........................................................................................................................39

Recommendations..........................................................................................................................40

Acknowledgements............................................................................................................................45

Appendices.........................................................................................................................................46

Appendix 1:....................................................................................................................................46

Appendix 2.....................................................................................................................................50

Appendix 3:....................................................................................................................................51

Appendix 4:....................................................................................................................................53

Data sources and study selection................................................................................................53

Data extraction and quality assessment......................................................................................54

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Chapter 1: Abstract

Socioeconomic differences in food intake are well documented. This study aims to explore the

potential differences in nutrient intake and dietary quality of school lunch by school level

socioeconomic status (SES). A secondary analysis of the “Cork Children’s lifestyle study”

(CCLaS), which is a representative study of children aged 8-11 (n=1075), was undertaken.

Analyses were stratified based on SES, characterised by a school-level measure of deprivation

known as Delivering Equality of Opportunity in Schools (DEIS). Children from areas that show

symptoms of deprivation would generally attend DEIS schools whereas their counterparts would

attend non-DEIS schools. Lunchtime intakes were assessed by an estimated 3-day dietary record.

Portion sizes were primarily estimated by a photographic food atlas. Food intakes were entered and

analysed using netWISP version 4. The School Food Trust (SFT) and the European Food Safety

Authority (EFSA) guidelines were used to assess nutritional intakes. Lunchtime energy (kcal) met

the SFT recommendations in DEIS schools but exceeded them in non-DEIS schools (p=0.001).

Protein, fat, carbohydrate, added sugar (AS) and dietary fibre (DF) intakes met recommendations in

both school-types however saturated fat (SF), sugar and sodium intakes were above

recommendations. Adjusting for age, gender, parental education and BMI, DEIS groups were more

likely to adequately consume fat, SF, sugar and sodium compared to non-DEIS groups, while, non-

DEIS attenders were more likely to adequately consume protein, fat, carbohydrate and fruit.

However after controlling for physical activity, no statistical association (p=0.074) was found

between the adequacy of SF consumption between DEIS and non-DEIS groups. Findings suggest

that no disadvantage occurs in school lunch quality in DEIS compared to non-DEIS schools, as they

were similar. However both school types would benefit from addressing SF, sodium and fibre

intakes.

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Chapter 2: Introduction

A large frame of epidemiologic evidence support the theory that food intake is affected by

occupation, education and income levels as well as two primary cofounders; age and sex (1).

The three demographic factors (occupation, education and income) are classified as

conventional indexes of socioeconomic status (SES). There are many publications relating to

SES and poor-quality diets (2) however, community level SES remains an area of interest. In

Ireland, schools in areas of high levels of social deprivation have been awarded DEIS status,

which is a social measure of deprivation.

This report is organised in the following manner. Firstly, the study objectives are highlighted

outlining what is expected to be investigated. Secondly, a background is provided into the

issue of social deprivation, how DEIS plans to address the topic, children and the school

place, school lunch and the role of diet and nutrition in everyday life. Next, the methodology

used to investigate the situation is outlined describing the study design, data collection and

the statistical procedures undertaken. The results are then presented underlining the

nutritional and the dietary quality of school lunches consumed by children aged 8-11 who

attended DEIS and non-DEIS schools. Finally, the report is summarised and conclusions are

drawn from the analysis. Recommendations to be used for further research are also

highlighted in the conclusion.

2.1 Objective

The primary objective of the present study was to investigate the quality of school lunch

defined by the SFT, consumed by 8-11 year old primary school children, living in Cork,

Ireland. Nutritional intake and dietary quality were examined and in completion, it was

estimated whether there were any significant differences associated with community level

SES (i.e. DEIS or non-DEIS school). The nutritional quality assessed adherence of total

energy (TE), protein, fat, saturated fat (SF), sugar, added sugar (AS), fibre, and sodium to the

SFT guidelines. A secondary objective was to explore any differences further by adjusting for

confounders such as gender, age, parental education, BMI and physical activity (PA) on

school lunch quality consumed in DEIS and non-DEIS primary schools.

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2.2 Background

2.2.1 The issueDeprivation is a multi-dimensional problem characterised by social, economic or cultural

discrepancies among groups. Typical outcomes of deprivation are exclusion and unequal

access to resources, capabilities and rights (3). Additionally, lower life expectancy and

increased risk of developing serious illnesses are associated with poor social and economic

factors (3). Deprivation and disadvantage usually results from various evolutions throughout

the lifespan, e.g. marital break-up in early childhood, level of education change, moving

away from home, starting work, changing job, redundancy and retirement (3).

Deprivation is been defined by Townsend (4), who stated; “Individuals, families and

population groups who are in poverty lack the resources to obtain the types of diet, participate

in the activities and have the living conditions and amenities which are customary or are at

least widely encouraged or approved in the societies to which they belong”(4).

Deprivation on a food level has received a great deal of attention in recent years as

imbalances in nutrient and food intake was found to be associated with health-related

problems later in life (5). This form of deprivation is otherwise known as food poverty,

defined as “the inability to access a nutritionally adequate diet and related impacts on health

culture and social participation” (6) . This is an emerging issue, which can negatively affect

children’s educational success by weakening their behavioural and cognitive functioning (5).

This can result in poor school performance, absenteeism and leaving school prior to receiving

any real qualification (5).

In Ireland, DEIS and non-DEIS schools have classified social deprivation on a community

level. Children and adolescents from areas that show various symptoms of deprivation, e.g.

high unemployment levels and high numbers of medical card holders would generally attend

DEIS schools whereas their counterparts would not.

2.2.2 DEISBoth social and economic development of children and adolescents is enriched by education.

However, the Irish Government noted that certain population groups were not gaining from

the education system and consequently were unable to participate in Irish society to their

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maximum potential. The extent of educational under-achievement and early school leave

were higher in students from disadvantaged areas compared to areas of higher affluence (7).

In May 2005, a policy entitled Delivering Equality of Opportunity in Schools (DEIS) was

launched by the Department of Education and Skills. DEIS had the intention of addressing

the educational needs of Irish children and adolescents aged 3-18 years living in

disadvantaged communities (7). DEIS is one sequence of an intervention which addresses

disadvantage and deprivation in Ireland. It proposed to introduce a “second chance”

education and training system for deprived population groups as well as increase the

participation of underrepresented groups both in further and higher education. (7)

For primary schools, identification was grounded by a survey carried out by the Educational

Research Centre (ERC) in May 2005. From survey analysis, the ERC could identify any

deprivation characteristics, such as, unemployment, single parent, travellers, large families

(>5 children) and being eligible for free school books (7). Currently, DEIS operates in 657

primary schools, 336 being situated in an urban setting and 321 in a rural location.

2.2.3 The school placeIn the Republic of Ireland, primary school children are entitled to attend school 5 days a week

over a 37 week period spread throughout the year (8), making it an area in which

approximately one third of their wakeful day is spent (9). As a result, it is suggested that

school lunch should provide one third of their daily nutrient requirements (10). The school

place has recently been acknowledged as a priority setting for healthy food provision in order

to promote health and educational success (11). This is particularly important for low-income

groups as the school environment permits children to benefit from food experimentation

without any financial limitations (5). Some argue that school lunch is not important provided

that children maintain energy and nutrient balances over the whole day. However, this does

not take into account poorer children for which school lunch is a top priority as they could be

malnourished at home (12). Therefore, there is a paramount need to analyse school lunch

quality and assess whether children’s consumption agree with recommended nutrient

guidelines.

Growing up in Ireland (GUI), an Irish longitudinal childhood study recently reported 19% of

9 year old children are overweight with 7% being obese (13). Results showed that girls had a

significantly greater risk of being overweight or obese compared to boys (30% vs. 22%;

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P<0.001) (13). Previous Irish research demonstrates that children generally over-consume

sugar sweetened beverages as well as foods high fat and sugar and under-consume fruit and

vegetables at lunchtime (14). The National Taskforce on Obesity recommended that schools

should be encouraged to develop policies to promote healthy eating and address what is being

provided in school meals including school lunches (15).

Dissimilar to other European countries, canteen style facilities are typically unavailable in

Irish primary schools (16) and as a result, it is up to the child themselves or their guardian to

have their school lunch prepared at home and brought into school. This is otherwise known as

a packed lunch (9). However, the Irish Department of Social Protection provides funding

towards school meal provision through the ‘School Meal Programme’ for which

disadvantaged (DEIS) schools are prioritised (17). Filled rolls or sandwiches as well as two

other items, i.e. fruit, milk or yogurt are typically offered by the scheme (17)., The Irish

government has displayed increased support towards school meal provision over the past

decade, with social welfare expenditure reaching €32 million in 2008 (5). Other funding

schemes supporting school food included the School Retention Programme and the European

Union School Milk Scheme (5). There are no set nutrient standards for school lunch in

Ireland. Schools also have to choose lunches within the grant budget and can be guided to

provide healthy lunches following the food pyramid guidelines. A new resource was

published by Healthy Food for All in 2009, which provides updated guidelines that schools

can follow to provide healthy school lunches (5), however this is food rather than nutrient

based too.

2.2.4 School Food TrustIn 2005, the UK government established the School Meals Review Panel (18), which

published a report on developing school lunches to suit desired nutritional standards. This

brought upon the School Food Trust (SFT), a guide that provides information on how to meet

the British Government’s food and nutrient based standards for school lunch. Such standards

apply to all food and drink provided by school governing bodies to pupils on and off school

premises during the school period (19). As there are no Irish recommendations set for

weighted school lunch nutrient intakes, the present report used the lunchtime food and

nutrient guidelines provided by the SFT to analyse the lunchtime intakes of the sample of

children.

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In 2006, two standards were developed by the SFT, which set both food and nutrient based

standards for primary schools. These were implemented in September 2006 and 2008

respectively (19).

Children should get an appropriate balance of food and nutrients in order to grow and

develop. For many students school lunch could be their main meal of the day. Therefore, it is

important that a school lunch contains sufficient energy and nutrients to promote good

nutritional health and to protect those who are nutritionally vulnerable, i.e. underweight or

overweight. Nutrient based standards therefore aim to make school lunch healthier by giving

recommended energy intakes, minimum levels of vitamins and minerals and maximum

desirable levels of fat, SF, AS and sodium.

Nutrient based standards apply to the average school lunch on both a primary and a

secondary school level. For the purpose of the present study, primary school guidelines only

were focused on. Such guidelines state that a typical school lunch must provide 530 kcal

(±5%), 7.5-g of protein, <=20.6g of fat, <=6.5g of SF, >=70.6g of carbohydrate, <=15.5g of

AS, >=4.3g of DF and <=499mg of sodium. Weighted intakes for TS were not found in SFT

report and were therefore taken from the European Food Safety Authority guidelines (EFSA),

which recommended that 90g/day (30g for lunchtime intake) be consumed (20).

The food-based standards for school lunches apply to all school lunch services, including hot,

cold and packed lunch services provided on a school day. The current standards have set

minimum lunchtime requirements for healthier food and restrictions on less healthy foods

(19).

2.2.5 Nutrient intakeInadequate nutrient intake is critical in the aetiology of deficiency diseases and non-

communicable diseases such as type 2 Diabetes Mellitus (T2DM), cardio vascular disease

(CVD) and obesity (21). Increased energy intake is associated with overweight and obesity

(21), excessive fat and saturated fat (SF) is positively associated with insulin resistance (22)

and elevated sugar intake could increase serum triglycerides (23). Conversely, low intakes of

dietary fibre (DF) has been linked with higher insulin resistance, raised total and LDL-

cholesterol and an increased risk of obesity (24).

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A school lunch should deliver 30% of the individual’s total daily requirements, provided that

three main meals are consumed per day. As school lunch should offer one-third of the daily

intake it is necessary that its contribution be well balanced (19). Food energy is defined as

energy, which comes from food and is measured as percentage energy (%E). Food energy

comes from the macronutrients carbohydrate, fat and protein. Irish standards for food energy

are provided by the Irish food-based dietary guidelines (25)

Total carbohydrate (TC) is the most fundamental nutrient required in every meal and should

deliver between 45-65 %E to 5-13 year old children (25). TC is composed of TS, DF and

starch however this report assesses lunchtime TS and DF intake only. The proposed labelling

reference intake for TS is set by the EFSA (20) as no Irish recommendations were found.

EFSA suggest that TS should provide no more than 18%E for a 2000 kcal diet (20). TS is

comprised of indigenous and extrinsic sugars (20). Indigenous sugars include those naturally

present in foods such as fruit, vegetables and milk products. Extrinsic or added sugars (AS)

account for all sugars found in fruit juices, table sugar, honey, sucrose, glucose, syrups and

50% of the sugars found in canned, stewed, dried or preserved fruit (19). AS provide many

calories but few essential nutrients to the body (19) and high intakes could lead to tooth

decay. The Irish food-based dietary guidelines suggest no more than 10%E of AS be

consumed. An English survey highlighted that 50% of school lunches consumed by primary

school children are too high in AS (26).

DF are non-digestible carbohydrates that pass straight to the large intestine (27) and assists

bowel function, preventing issues such as diarrhoea and constipation (19). As DF is not

absorbed, it has a low energy content meaning no recommended food energy is set for its

consumption. A previous survey announced that 79% of boys do not obtain sufficient DF

from school meals (28). Protein is necessary for the growth and repair of body tissues, i.e.

muscle. To maintain protein balance, 5-13 year old children are guided to consume 10-30%E

(25).

Dietary fat is a concentrated source of energy providing over double the calories weight for

weight than carbohydrate and protein. High fat intake can elevate LDL and lower HDL

concentrations in the blood (29) and could result in the development of cardio vascular

disease (CVD) (30). However, fat provides essential fatty acids by enhancing the absorption

of fat-soluble vitamins and as a result some fat in the diet is necessary. Children aged 5-13

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are advised to keep fat intakes within 25-35%E (25). Total fat (TF) is made up of saturated

and unsaturated fat however this report analyses only the children’s lunchtime saturated fat

(SF) intake.

SF is the main contributor of TF that is strongly associated with CVD development (31).

Atherosclerotic change in childhood has been correlated with the same risk factors as was

identified in adults, implicating that atherosclerosis could begin during childhood (32). As a

result, children are advised to maintain a healthy lipid profile i.e. to reduce their LDL and to

elevate their HDL concentrations (29) in order to reduce their likelihood of developing CVD.

No meal consumed by 5-13 year old children should contain more than 10%E of SF. See

appendix 4 for a detailed account on the instruments used to measure saturated fat intake.

Sodium is a component of salt, needed for nerve and muscle functioning and for fluid balance

maintenance in the body (19). However, as sodium is a micronutrient, it is needed only in

small amounts to have such a beneficial effect on the consumer. When sodium is over-

consumed it can lead to various health problems in later life such as high blood pressure,

stroke or heart and kidney diseases (19). As sodium does not provide energy to the body, no

food energy guideline is provided for its intake.

2.2.6 Diet QualityThe present study also examines the dietary quality of school lunches consumed by primary

school children attending DEIS and non-DEIS school in Ireland. The food groups selected as

markers of dietary quality were fruit and vegetables (F&V) and sugar sweetened beverages

(SSB).

Diet quality is an umbrella term used predominately in the nutritional epidemiology to

evaluate the dietary habits of a given population (33). It is also an index used to predict

various health outcomes and disease development (34). Diet quality can also describe an

individual’s diet with respect to the recommended guidelines (35), i.e. a healthy, balanced

and nutrient dense diet would provide the individual with their required needs to maintain

optimum health (35).

Diets high in fruit and vegetables (F&V) are less energy dense but provide the consumer with

ample nutrients and minerals (36). When consumed regularly, F&V are associated with

overall better health (37). The SFT recommends that at least two portions of F&V should be

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consumed during the school hours, one portion coming from fruit and the other coming from

vegetables (19). The current recommendation for F&V intake is five portions a day, which

equates to 45 g of fruit and vegetables per MJ of energy intake. Thus, one portion of both

fruit and vegetables equates to 9g per MJ of total energy intake (38). As the median energy

intake over the full day was 7.18 MJ, weighted lunchtime consumption of both fruit and

vegetable should be 65g. Conversely, SSBs are energy dense and nutrient poor (2). SSBs

include all soft drinks, fruit juices and vitamin water drinks containing added sugars

(39).Such beverages are sweetened by High Fructose Corn Syrup (HFCS), sucrose or fruit

juice concentrate (39). HFCS is a commonly consumed additive, particularly in the form of

SSB. It is 55% fructose and 45% glucose in a dissimilar manner to ordinary sucrose which

has a 50:50 fructose to glucose ratio (39). SSBs have received major attention in the public

health field, not only due to their high calorie to nutrient ratio, but also as they have been

positively associated with obesity (39). The SFT recommend lunchtime SSB consumption be

at 0ml (19).

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Chapter 3: Methodology

3.1 Study design

The present study is secondary analysis of a cross sectional study entitled the “Cork

Children’s lifestyle study” (CCLaS). Details of this study have been published elsewhere

(40). Briefly CCLaS recruited a sample of children aged between 8-11 years old living in

county Cork, Ireland.

3.1.1 Population samplesThe population was from DEIS and non-DEIS primary schools based in urban and rural

Cork, Ireland. Information on primary schools located in both Cork city and Mitchelstown

was attained from the Department of Education and Skills website, which provided

information such as the school name, location, size, assigned gender and disadvantaged

(DEIS) status (7).

Primary schools were classified as DEIS based on their familial socio-demographic and

socioeconomic profile. In Cork city, 40% of primary school children attend a DEIS school.

However, on a national level, 20% of primary schools are classified as DEIS (7).

A list of all primary schools based in Cork city and Mitchelstown were found on the

Department of Education and Skills website (7). Schools that catered towards children with

special needs and schools without age eligible children were excluded. At the time of

sampling there were 51 primary schools (n= 13,230 children) in Cork City which met the

sampling frame criteria (7). All 5 primary schools in Mitchelstown (n= 800 children) met the

sampling frame criteria (7).

3.1.2 Recruitment MethodsSchools were recruited in the following process. Principals of the selected primary schools

were sent a letter of invitation, an information sheet and a presentation outlining the study

details. The Principal was then contacted by telephone to arrange a meeting with an available

research assistant to discuss the study in further detail. With the Principals’ permission, the

research team introduced the study to the 3rd and 4th class children of each participating

school, and a parent/guardian information letter and consent form was given to each child to

bring home. The children were directed to discuss the study with their parents/guardians, and

to return the consent form to the school.

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3.2 Data collection in the Cork Children’s Lifestyle Study

3.3.1 Dietary assessmentAn estimated 3-day food diary, which noted the time, location, brand, the estimated portion

size and cooking method (where applicable) was completed by the children to assess dietary

intake. The children wrote down what they ate and drank on each of the three days, under six

pre-assigned meal titles. Potion sizes were estimated by a photographic food atlas (41),

manufacturer information and standard household measures. Where food weight was

unavailable in a food diary, medium portions from either the Irish food portion size database

(42), for ages 9-12 or the photographic food atlas (41) were used. The children were

recommended to seek assistance from their parents and teachers if necessary. After the 3-day

period, completion was checked through a detailed debriefing session by researchers with the

children using both a prompt sheet and the photographic food atlas (41).

The food diary data were entered into and analysed using the software ‘netWISP’ version 4

(Tinuviel Software, Anglesey, UK). WISP allocated the nutritional value to the food items

using McCance and Widdowson’s 7th edition (43) and the Irish Food Composition databases

(44). The nutritional information of foods unavailable in WISP was added manually by

research assistants.

The present paper assessed the nutritional and dietary quality of school lunch consumed by 8-

11 year old children attending DEIS and non-DEIS schools. The nutritional quality of school

lunch was assessed by comparing mean energy, protein, total fat (TF), saturated fat (SF),

carbohydrate, total sugar (TS), added sugar (AS), dietary fibre (DF) and sodium intakes to

one-third of the Recommended Dietary Allowance (RDA), a guideline set by the UKs School

Food Trust (SFT) (19). Where the SFT did not outline the RDA for TS intake at school, mean

intakes were compared to one third of the recommended allowance set by the European Food

Safety Authority (20). The dietary quality of school lunch was assessed by comparing median

intakes of fruit, vegetables and sugar sweetened beverages (SSB) to the same guidelines (19).

3.2.2 Primary exposureThe database for the present study was stratified in two different categories, DEIS and non-

DEIS schools and the analyses investigated whether there were any significant differences

between school/community level socioeconomic status and school lunch quality. School

lunches and macronutrients were examined within DEIS and non-DEIS schools.

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3.2.3 Co-variants

GenderThe gender of each participant was recorded by trained researchers prior to analysis.

AgeThe exact age of the participant was calculated by trained researchers by subtracting the

child’s date of birth from the date of examination. For the present report the age was

considered in a categorical form rather than continuous.

BMIThe BMI of each child was calculated by dividing their weight (kg) by their height (m) 2. The

devices used to calculate the height and weight of the children was a Leicester portable height

stick and the Tanita WB100MA mechanic scales respectively. One measurement only was

taken. The height of the children was measured to the nearest millimetre (mm) without

wearing any shoes while weight was measured to the nearest 0.1 kg without any shoes and

wearing light clothing. The children were then classified as underweight, normal weight,

overweight or obese using age and gender specific International Obesity Taskforce cut off

points (45). However for the present report BMI categories were collapsed to normal weight

and overweight/obese. The BMI of the children’s parents was attained via self-report from

the parent/guardian questionnaire and was categorised as underweight/ normal weight, and

overweight/obese using the WHO classification (46).

Parental education and family typeFamily type and parental education were reported by their parent/guardian in their assigned

questionnaire. The parent/guardian questionnaire was developed using questions from a

number of different sources (40).

Physical ActivityModerate to Vigorous Physical Activity (MVPA) was defined as whether each child met the

World Health Organisation’s (WHO) recommendations for physical activity (PA) of 60

minutes per day, throughout the testing period (40). A validated tri-axial GENEActiv

accelerometer (47) was used to measure PA over a consecutive 7 day period. Thresholds

were applied to categorise number of minutes of moderate to vigorous physical activity

(MVPA) per day. Children with valid data were those who wore the accelerometer for ≥600

minutes per day or for at least 3 days (n=969). Children who engaged in ≥60 minutes of

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MVPA on each of the 7 days were categorised as meeting World Health Organisation MVPA

recommendations.

Underreporting of food intake in the Cork Children’s Lifestyle StudyThe children considered to be underreporting energy were excluded from the analysis.

Plausible and under-reporters for energy were identified by calculating an energy intake to

basal metabolic rate (BMR) ratio for each child using methods outlined by Schofield, 1985

(48). Cut off values for energy intake to BMR were defined by an equation developed by

Goldberg et al (49), with updated cut off points for children defined by Black (50)

3.3 Data ManagementData analysis was completed using the statistical software Stata 13. In order to complete such

analyses many different tasks were completed using Stata.

A brief synopsis on the data management skills used in the analysis is presented in appendix

1, however this is fully highlighted in the stata do-file (appendix 5). Furthermore, variables

were created in order to assess the mean percentage energy (%E) of lunchtime macronutrient

intake (protein, carbohydrate, SF, TS, and AS) relative to the full school day. New variables

were also created to define whether the individual child was a food group consumer or not.

The SFT set upper limit recommendations for lunchtime fat, SF, sugar, AS and sodium intake

as well as lower limit recommendations for lunchtime protein, carbohydrate, DF, fruit and

vegetable intake. Lunchtime energy intake was given a range of +/-5%, stating that children

should consume between 503 and 557kcal. Binary variables were created for each variable

defining nutrient and food group intake, transforming it from a continuous to a categorical

form. The categorical variable defined whether lunchtime standards met the recommended

guidelines or not. Such variables allowed for the analysis of logistic regression. As the SFT

neither recommended that 0ml of SSBs be consumed at lunchtime, a new binary variable

defining whether the children were consumers or non-consumers was generated via the

creation of a variable with quantile categories and recoding. Various other variables were also

generated from old variables by recoding.

3.4 Statistical ProceduresStatistical tests were run on Stata 13 Descriptive statistics were calculated to summarise mean

and median intakes of nutrients and food groups. Significant differences between school type

and nutrient intakes were assessed. Prior analysis, assumptions for undergoing an

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independent sample t tests were tested for using the generated continuous variables. Similar

to the various data management procedures, a broad description on how each statistical test

was run is given in appendix 1, while the stata do-file in appendix 5 describes the process

fully. As the distribution of intakes for all nutrients and food groups differed considerably

from a normal distribution and were not normalised by log or square root transformation for

this study, differences in school lunch between school types were evaluated using a non-

parametric Wilcoxon signed rank test. Such test was used to assess differences in school

lunch nutritional quality according to school category. A P-value of <= 0.05 was used to

define statistical significance (see appendix 1 pg. 48).

A χ2 test was used to assess the association between those who met the recommended

standards for nutrient and food group intakes and those who did not based on school type (see

appendix 1). Similar to the Wilcoxon signed rank test, a P value of <= 0.05 was used to

define statistical significance. The association between children who met the desired

lunchtime standards and those who did not were analysed by logistic regression analysis (see

appendix 1).

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Chapter 4: Results

4.2 Response RateFifty-six primary schools, 51 urban and 5 rural, were asked to participate in the CCLaS study

in the hope of recruiting 1,000 participants. Of the 56 primary schools requested 46 (n=1643)

responded positively with an interest in participating in the study. The prepilot study recruited

2 city schools, with 55 children (52.88%) agreeing to participate. For the pilot study, 3 city

schools were selected using a probability proportionate to size (PPS) sampling strategy to

select urban primary schools in a random fashion. These three urban schools from the PPS

sample agreed to participate, which received a child level response rate of 85 out of 151

children. Twenty-two schools; 8 PPS urban, 3 rural and 11 (purposively sampled) primary

schools agreed to participate in the main study contributing 935 out of 1386 children. In

conclusion, a response rate of 65.5% at the child level was obtained (n=1075 participants)

and 58.7% at the school level (27 primary schools).

Those willing to participate were asked to complete a consecutive 3-day questionnaire. In

total, 1,060 children provided a food diary, 379 of which attended a DEIS school while 681

attended a non-DEIS school. However, under-reporters for energy were excluded leaving the

analysed population as 724 (68.3%) children, 253 (34.94%) from DEIS groups and

471(65.06%) from non-DEIS groups. Reluctance to participate was cited by the school

principal. Few schools gave no response (n=3) or an outright “no” without any explanation

(n=4), more claimed that they were over-surveyed (n=5) or had concerns over the methods

(n=3). Certain schoolteachers were not willing to participate in the study, which also led to

refusal to take part in the study (n=2) while other schools had practical issues, which

restricted their participation in the study (n=2).

4.2 DemographicsThe demographic characteristics important to characterising food intake are displayed below.

Table 1 outlines the proportion of children by different categories of five different

demographics including gender, age, BMI, birth weight and current health status. Table 2

outlines the proportion of children by different categories of parent or familial characteristics

including family type, ethnicity, parent/guardian BMI, parental education and the current

health status of the parent or guardian. The proportions were further stratified by a school

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level of deprivation i.e. DEIS and non-DEIS. The percentage of DEIS and non-DEIS

participants in each demographic group are also highlighted alongside in each cell of tables 1

and 2.

Table 1, the demographic characteristics of the participating children stratified by school level of deprivation (DEIS vs. non-DEIS)

Participants

Demographic characteristics DEIS (%)N=253, 34.94%

Non-DEIS (%)N=471, 65.06%

Total (%)N=724, 100%

N (%)

Sex

Male 180 (41.96%) 249 (58.04%) 429 (100.00%)

Female 72 (24.49%) 222 (75.51) 294 (100.00%)

Age

8 years old 14 (19.18%) 59 (80.82%) 73 (100.00%)

9 years old 112 (36.25%) 197 (63.75%) 309 (100.00%)

10 years old 120 (37.04%) 204 (62.96%) 324 (100.00%)

11 years old 7 (38.89%) 11 (61.11%) 18 (100.00%)

BMI

Underweight/normal weight 201 (34.30%) 385 (65.70%) 586 (100.00%)

Overweight/obese 50 (38.17%) 81 (61.83%) 131 (100.00%)

Birth weight

Below average 10 (27.78%) 26 (72.22%) 36 (100.00%)

Average 208 (35.08%) 385 (64.92%) 593 (100.00%)

Above average 6 (23.08%) 20 (76.92%) 26 (100.00%)

Current Health status

Excellent 135 (30.54%) 307 (69.46%) 442 (100.00%)

Good 96 (39.67%) 146 (60.33%) 242 (100.00%)

Fair/ poor 6 (50.00%) 6 (50.00%) 12 (100.00%)

Total sample, 724 (68.3%) participants were analysed as they were considered plausible energy reporters. 336 (31.7%) were excluded due to underreporting their energy intake.DEIS group, 253 (66.75%) participants were analysed as they were considered plausible energy reporters. 126 (33.25%) were excluded due to underreporting.Non-DEIS group 471 (69.2%) participants were analysed as they were considered plausible reporters. 210 (30.8%) were excluded due to underreporting.

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Table 2, the demographic family/ parental characteristics stratified by school level of

deprivation

Participants

Demographic characteristics DEIS (%)N=253, 34.94%

Non-DEIS (%)N=471, 65.06%

Total (%)N=724, 100%

N (%)

Family type

One Parent 70 (54.69%) 58 (45.31%) 128 (100.00%)

Two Parent 158 (28.73%) 392 (71.27%) 550 (100.00%)

Ethnicity

Irish 196 (33.79%) 384 (66.21%) 580 (100.00%)

Non-Irish 23 (31.51%) 50 (68.49%) 73 (100.00%)

Parental BMI

Underweight/ normal weight 93 (25.14%) 227 (74.86%) 370 (100.00%)

Overweight/ obese 97 (41.28%) 138 (58.72%) 235 (100.00%)

Level of education

Third level 37 (17.05%) 180 (82.95%) 217 (100.00%)

Post second 75 (34.88%) 140 (65.12%) 215 (100.00%)

Higher second 64 (43.24%) 84 (56.76%) 148 (100.00%)

Lower secondary or less 47 (52.81%) 42 (47.19%) 89 (100.00%)

Parental Current health status

Excellent 157 (31.03%) 349 (68.97%) 506 (100.00%)

Good 63 (42.00%) 87 (58.00%) 150 (100.00%)

Fair/ poor 17 (45.95%) 20 (54.05 %) 37 (100.00%)

Total sample, 724 (68.3%) of the participant’s parent/guardian were analysed as they were considered plausible reporters. 336 (31.7%) of the participant’s parent/guardian were excluded due to underreporting.DEIS, 253 (66.75%) of the participant’s parent/guardian were analysed as they were considered plausible reporters. 126 (33.25%) of the participant’s parent/guardian were excluded due to underreporting.Non-DEIS, 471 (69.2%) of the participant’s parent/guardian were analysed as they were considered plausible reporters. 210 (30.8%) of the participant’s parent/guardian were excluded due to underreporting.Ethnicity, non-Irish ethnicities were specified as British-African, British Caribbean, East European, English, English mother and an Irish father, European, father is Bulgarian, Filipino, Georgian, Hungarian, Indian, Irish Gypsy, Irish/Dutch, Irish/Indian, Irish/Swiss, Italian, Kolokoli, Lithuanian, Polish, Romanian, Scottish.

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4.3 Analysis of School Lunches

4.3.1 Differences in nutrient intake

The mean lunchtime energy intake relative to the Mean Daily Intake (MDI) of the total

sample (n=724) was 536.21 (305.52) kcal. School energy was found to be higher in non-

DEIS schools (n=471) that consumed 544kcal compared to DEIS schools (n=253) that

consumed 543.93 (279.97) kcal at lunchtime. These results were deemed statistically

significant (table 3).

Nutrient intakes varied between DEIS and non-DEIS schools. Lunchtime intakes of protein,

total fat (TF), saturated fat (SF), carbohydrate, total sugar (TS), dietary fibre (DF) and sodium

were higher in non-DEIS schools. Statistical associations were found between lunchtime, TF,

carbohydrate, TS and DF intakes and school category (table 3). Added sugars (AS) were the

only nutrient group found to be higher in DEIS schools, however the association (p=0.09)

was insignificant (table 3).

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Table 3; the mean lunchtime nutritional quality consumed by 8-11 year old children stratified by DEIS status

Total sample(n=724)

DEIS (n=253) Non-DEIS (n =471)

Guideline School intake Total daily intake School intake % School intake‡ Total daily intake School intake % School intake‡

Nutrient Mean (SD) P-valueEnergy (MJ) 2.11-2.33 2.43 (1.32) 7.99 (2.42) 2.28 (1.17) 7.82 (2.71) 2.51 (1.39)Energy (kcal) 503-557 580.18 (315.55) 1908.66 (578.77) 543.93(279.97) 28.83% (11.72) 1868.97 (646.49) 599.49 (331.76) 31.99% (10.62) 0.001Protein (g) 7.5-47.25 17.85(11.19) 68.13 (27.26) 16.91 (10.75) 25.16% (12.67) 67.67 (26.22) 18.35 (11.4) 27.25% (11.88) 0.08TF (g) 2.53-20.6 19.45 (15.82) 67.98 (27.01) 17.59 (11.43) 26.85% (14.83) 66.62 (31.82) 20.44 (17.67) 30.04% (14.53) 0.01SF (g) <=6.5 8.15 (6.11) 28.51 (12.97) 7.79 (5.83) 28.03% (16.8) 27.59 (11.95) 8.36 (6.25) 29.72% (16.1) 0.2Carbohydrate (g) 70.6-217.11 87.92 (49.22) 269.24 (88.39) 83.86 (51.77) 30.83% (12.35) 262.71 (88.79) 90.1 (47.71) 34.13% (11.03) 0.002TS (g) <=30 40.37 (34.05) 112.85 (63.34) 35.33 (39.07) 29.73% (16.44) 116.24 (49.75) 43.08 (30.73) 36.12% (15.92) <0.0001AS (g) <=15.5 10.96 (25.64) 45.59 (50.29) 12.99 (31.8) 23.57% (27.98) 38.91 (35.59) 9.87 (21.58) 19.84% (25.25) 0.09DF (g) >=4.2 5.01 (3.53) 13.63 (4.94) 4.36 (2.5) 32.16% (14.16) 15.332 (7.07) 5.36 (3.93) 34.98% (13.97) 0.0001Sodium (mg) 0-499 828.1(506.02) 2660.2 (1130.58) 827.28(527.6) 31.27% (15.71) 2466.25 (1144.77) 828.55 (494.61) 34.55% (15.05) 0.47

Total sample, the data was analysed from 724(68.3%) plausible energy reporters. 336 (31.7%) participants were excluded due to underreporting their energy intake to their food diary.DEIS, the data was analysed from 253 (66.75%) plausible reporters.Non-DEIS, the data was analysed from 471 (69.2%) plausible non-DEIS reporters.‡ Percentage school intake relative to the whole dayP-value: this represents the differences in mean lunchtime nutrient intake in DEIS and non-DEIS schools. Differences were assessed using a Wilcoxon signed rank test.Lunchtime standards were unavailable for TS and were therefore attained from the European Food Safety Authority (20)TF, total fat; SF, saturated fat; Carb, carbohydrate; TS, total sugar; AS, added sugar; DF, dietary fibre

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4.3.2 Difference in dietary qualityThe dietary quality of school lunches was assessed by adherence to recommendations for

both sugar-sweetened beverages (SSB) and fruit and vegetables (F&V). Of the above food

groups, the most consumed was fruit for the whole sample however, this differed slightly in

DEIS populations where SSB had the highest proportion of consumers (table 4). The food

group that had the lowest proportion of consumers was vegetables, similar results were

attained when DEIS and non-DEIS were analysed individually (table 4).

Those categorised as fruit consumers had median lunchtime fruit intakes of 91.7 and 102g for

DEIS and non-DEIS groups respectively (table 4). This met the standards set by the SFT

(table 5). A high amount of fruit was consumed at school lunch relative to the daily intake

and this was similar in DEIS and non-DEIS schools. Median lunchtime vegetable intakes for

vegetable consumers were 23.7 and 22.5g in DEIS and non-DEIS schools (table 4). Such

intakes were lower than that of fruit however, they were still deemed acceptable by the SFT

(table 5), however the majority of the sample were categorised as non-consumer (76%).

There were significant differences in the proportion of DEIS and non-DEIS schools

categorised as a lunchtime fruit (p<0.0001) and vegetable consumer (p=0.002) (appendix

table 2.1). The total median lunchtime intake of SSB was 226.5ml for non-consumers. Non-

DEIS populations had a higher median lunchtime intakes (242ml) compared to DEIS

populations who consumed a median of 200ml (table 4). However, DEIS schools had a

higher proportion of SSB consumers (47.83%) compared to non-DEIS schools (44.37%) thus,

less DEIS children are meeting the SFT guidelines (table 5). There was no statistical

association (p=0.374) between school type and being lunchtime SSB consumer. Appendix

table 2.1 highlights the proportions and the association of lunchtime consumers and non-

consumers for fruit, vegetables and SSBs.

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Table 4; the median (IQR) lunchtime fruit, vegetable and SSB intakes of food group consumers stratified by DEIS status

Total sample (n=724) DEIS (n=253) Non-DEIS (n=471)

Consumers Non-consumers Daily intake School intake Daily intake School intake % School intake Daily intake School intake % School intake

Dietary Group n (%) n (%) Median (IQR) p-value

Fruit (g) 416 (57.46%) 308 (42.54%) 146.1 (165.7) 87.5 (82) 115 (147.3) 91.7 (87.3) 100% (29.17) 165 (176.3) 102 (120.7) 83.87% (49.95) 0.102

Vegetables (g) 174 (24.03%) 550 (75.97%) 62.67 (67.5) 22.7 (27.5) 40.8 (75) 23.7 (27) 62.01% (66.85) 67.7 (60) 22.5 (27.5) 39.15% (34.82) 0.74

SSB (ml) 330 (45.58%) 394 (54.42%) 392 (383.3) 226.5 (255.7) 428 (416.7) 200 (283.5) 55.56% (44.56) 380 (350) 242.7 (242) 64.99% (55.19) 0.63

Consumers only were analysed, see appendix table 2.1 for the association between the proportions of non-consumers compared to consumersFruit; 113 (44.66%) DEIS and 303 (64.33%) non-DEIS attenders were included in the above analysis as they were both plausible energy reporters and lunchtime fruit consumersVegetables, 44 (17.39%) DEIS and 130 (27.6%) non-DEIS attenders were included in the above analysis as they were both plausible reporters and lunchtime vegetable consumers.SSB, 121 (47.83%) and 209 (44.37%) of the non-DEIS attenders were included in the above analysis as they were both plausible reporters and lunchtime SSB consumers. P-value; this represents the association between median lunchtime dietary quality in DEIS and non-DEIS schools. Associations were assessed using the Wilcoxon signed rank test.SSB, Sugar Sweetened Beverages; IQR, Interquartile Range

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4.3 The lunchtime intakes of DEIS and non-DEIS 8-11 year olds compared to the SFT and EFSA standards

Lunchtime nutrient and food group intakes among DEIS and non-DEIS groups are noted and

compared to the school food trust (SFT) (19) and European Food Safety Authority (EFSA)

(20) standards and are highlighted in table 5.

Analysis revealed that nutrient standards were exceeded for SF, TS and sodium intakes while

on the other hand were met for protein, TF, carbohydrate, AS and DF intake. Mean lunchtime

energy intake exceeded such standards in non-DEIS schools but remained within the

recommended range for DEIS population groups (table 5).

The dietary quality of school lunch is additionally highlighted in table 5. Analyses only

conducted on consumers, lunchtime standards were met for mean fruit intake in both DEIS

and non-DEIS groups. However lunchtime standards were not met for mean vegetable intake.

A greater proportion of non-DEIS participants (n=262, 55.63%) were non-consumers of SSB

compared to DEIS participants (n=132, 52.17%) however when SSB consumers and non-

consumers were compared across DEIS and non-DEIS groups no statistical association was

found (p=0.374).

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Table 5; Lunchtime nutrient and food group intakes according to set standards1 for primary school childrenDEIS2 Non-DEIS3

Nutrient/ Food group Min/Max %4 Nutrient Standard Nutrient intake % Standard Met Nutrient intake % Standard Met

Nutrient5 Mean (SD) Mean (SD)Energy (kcal) EAR6 30% (±5%) 503-557kcal 543.93 (279.9) 28.8% Yes 599.49 (331.76) 32% NoProtein (g) Min 10-30%E7 7.5-47.25g 16.91(10.75) 12.56%E Yes 18.35 (11.4) 12.6%E YesTotal Fat (g) Max 25-35%E 2.53-20.6g 17.59(11.43) 28.9 %E Yes 20.44 (17.67) 29.2%E YesSaturated fat (g) Max <=10%E <=6.5g 7.79 (5.83) 12.8%E No 8.36 (6.25) 12.2%E NoCarbohydrate (g) Min 45-65%E 70.6-217.11g 83.86 (51.77) 63.7%E Yes 90.1(47.71) 61.24%E YesTotal sugar8(g) Max 18%E <=30g 35.33 (39.07) 25.2%E No 43.08 (30.73) 29.38%E NoAdded sugar (g) Max <=10%E <=15.5g 12.99 (31.8) 8.26%E Yes 9.87 (21.58) 6.03%E YesDietary Fibre (g) Min 30% >=4.2g 4.36 (2.5) 32.16% Yes 5.36 (3.93) 35% YesSodium (mg) Max 30% 0-499mg 827.28 (527.6) 31.27% No 828.55 34.5% No

Food group9 Median (IQR) Median (IQR)Fruit (g)10 No less than one portion a day 65g 91.7 (87.3) 1.4 portions Yes 101 (118.0) 1.6 portions YesVegetables11 (g) No less than one portion a day 65g 23.7 (27.0) 0.36

portionNo 22.5 (27.5) 0.35 portion No

SSB12 (ml) The School Food Trust strongly encourages schools not to provide drinks that are sweetened.

200 (283.5) No 242.7 (242) No

1 Other than for sugar, all lunchtime nutrient and dietary standards were set by 19. School Food Trust. A guide to introducing the Government’s food-based and nutrient-based standards for school lunches 2007 [cited 2015 21 April]. Available from: http://www.childrensfoodtrust.org.uk/assets/sft_nutrition_guide.pdf.2 Data was analysed from 253 (34.9%) DEIS children as they were plausible reporters3 Data was analysed from 471 (65.1%) non-DEIS children as they were plausible reporters4 %, The recommended food energy that should be consumed per each nutrient and dietary group at lunchtime as well as over the whole day 25. Flynn MA, O'Brien CM, Faulkner G, Flynn CA, Gajownik M, Burke SJ. Revision of food-based dietary guidelines for Ireland, Phase 1: evaluation of Ireland's food guide. Public health nutrition. 2012;15(03):518-26.5 The nutrient intake data was slightly smaller as not all DEIS children provided the necessary information in their food diary. The sample population was 1,057 children in total, 681 from the non-DEIS group and 376 from the DEIS population6 EAR, Estimated Average Requirement7 %E, the percentage energy of nutrient intake8 Sugar, standards were set by. 20. European Food Safety Authority. Review of labelling reference intake values: "Scientific Opinion of the Panel on Dietetic Products, Nutrition and Allergies on a request from the Commission related to the review of labelling reference intake values for selected nutritional elements". The EFSA Journal. 2009(1008,):1-14.9 Median intakes of the consumers of each food group only were included in the analysis10 418 (57.7%) participants in total were included in the analysis as they were fruit consumers and plausible reporters, 113 (27.0%) were from the DEIS group whilst 305 (73.0%) were from the non-DEIS population. Non-consumers for fruit at lunchtime from the total sample was 306 (42.3 %), 140(45.8%) from DEIS schools and 166(54.2%) from non-DEIS schools. 11174 (24.0%) participants in total were included in the analysis as they were vegetable consumers and plausible reporters, 44 (11.6%) were from the DEIS group whilst 130 (19.1%) were from the non-DEIS population. Non-consumers for vegetables at lunchtime from the total sample was 550 (76%), 209(82.6%) from DEIS schools and 341(72.4%) from non-DEIS schools.12 SSB; Sugar Sweetened Beverages. 330 (31.12%) participants in total were included in the analysis as they were vegetable consumers and plausible reporters, 209 (30.7%) were from the DEIS group whilst 121 (31.9%) were from the non-DEIS population. In total 394 (54.4%) plausible reporters met the SSB recommendations by being non-consumers at lunchtime, 132 (52.2%) were from the DEIS group whilst 262 (55.6%) were from the non-DEIS population

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4.4 The contribution of lunchtime nutrient intake and dietary quality relative to energy

intake

The mean daily energy intakes on schooldays were 1908.66 and 1868.97 kcal for DEIS and

non-DEIS schools respectively, with energy intakes from foods eaten at school assessed as

543.93 kcal for DEIS populations and 599.49 kcal for non-DEIS populations (table 3).

Overall, mean lunchtime protein intakes were 12.6 percent energy (%E). Mean lunchtime fat

intakes were 29.09 %E for the total population. Similarly, those who attend DEIS schools

were found to be below the total average with mean lunchtime fat intakes of 28.9%E whereas

those who attend non-DEIS schools have higher lunchtime intakes (29.2%E, p=0.99). For

total carbohydrate, mean lunchtime intakes were 61.41 %E, with DEIS attenders having the

higher intakes of 63.7 %E and non-DEIS attenders having slightly lower intakes of 61.24 %E

(p=0.8). Lunchtime SF intakes for the total sample were 12.4%E, with DEIS and non-DEIS

populations consuming 12.8 and 12.2 %E of SF during school lunch respectively (p=0.79).

Mean lunchtime TS consumed among the total sample was 27.92 %E. Non-DEIS schools had

higher lunchtime sugar intakes than non-DEIS (29.38 vs. 25.27 %E). This was considered

significant between DEIS and non-DEIS groups (p=0.002). For the total sample, mean AS

consumed at school lunch was 6.8%E. Mean lunchtime AS consumption was higher for the

DEIS attenders (8.26%E) compared to the non-DEIS attenders (6.03%E, p=0.09). The mean

%E provided by the aforementioned nutrients over the full day as well as at lunchtime is

highlighted in figure 1. Figure 2 represents the %E contribution of protein, fat, SF,

carbohydrate, TS and AS towards the children’s mean daily intake as well as their mean

lunchtime intake. The resulting data is divided into DEIS and non-DEIS populations.

Similarly, figure 3 represents the breakdown of lunchtime %E between DEIS and non-DEIS

populations with respect to each nutrient.

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Figure 1, the food energy13 attained from nutrients (protein14, total fat15, saturated fat16, carbohydrate17, total sugar18 and added sugar19) over the full school day vs. school lunch. Analysed from a sample of 8-11 year old children20 divided into DEIS and non-DEIS groups.21

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13 Food energy; the recommendations of energy contribution for nutrients protein, fat, saturated fat, carbohydrate and added sugar were taken from a report published by the Irish food-based dietary guidelines 25. Flynn MA, O'Brien CM, Faulkner G, Flynn CA, Gajownik M, Burke SJ. Revision of food-based dietary guidelines for Ireland, Phase 1: evaluation of Ireland's food guide. Public health nutrition. 2012;15(03):518-26.Recommendations for total sugar energy contribution was not included in the Irish food based dietary guidelines report and were therefore taken from the set standards by the European Food Safety Authority 20. European Food Safety Authority. Review of labelling reference intake values: "Scientific Opinion of the Panel on Dietetic Products, Nutrition and Allergies on a request from the Commission related to the review of labelling reference intake values for selected nutritional elements". The EFSA Journal. 2009(1008,):1-14.14 Protein; the recommended food energy from protein for children aged 5-13 is 10-30%E 15 Fat; the recommended food energy from protein for children aged 5-13 is 25-35%E 16 Saturated fat; the recommended food energy from protein for children aged 5-13 is <=10%E17 Carbohydrate; the recommended food energy from protein for children aged 5-13 is 45-65 %E18 Sugar; the recommended food energy from protein for children aged 5-13 is <=18%E19 Added sugar; the recommended food energy from protein for children aged 5-13 is <=10%E20 Sample of 8-11 year old children; all energy under-reporters (n=336, 31.7%) were excluded from the analysis leaving only 724 (68.3%) participating children21 Significant differences were found between the full day consumption of total sugar between DEIS and non-DEIS schools. Associations were assessed using the Wilcoxon signed rank test

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Figure 2, percent energy (%E) macronutrient intakes over the full school day by 8-11 year old children attending DEIS and non-DEIS schools, Co. Cork Ireland

Figure 3, percent energy (%E) lunchtime macronutrient intake by 8-11 year old children attending DEIS and non-DEIS schools, Co. Cork Ireland

9.6%

21.0%

8.7%38.9%

16.4%

5.4%

9.5%

21.0%

8.8%

39.0%

15.5%

6.2%

non-DEIS DEIS

Whole day protein %E Whole day fat %EWhole day SF %E Whole day carbohydrate %EWhole day sugar %E Whole day AS %E

The 24 hour school day macronutrient intake by DEIS and non-DEIS populations

8.4%

19.4%

8.1%

40.6%

19.5%

4.0%

8.4%

19.3%

8.6%

41.3%

16.9%

5.5%

non-DEIS DEIS

Lunchtime protein %E Lunchtime fat %ELunchtime SF %E Lunchtime carbohydrate %ELunchtime sugar %E Lunchtime AS %E

The Lunchtime Macronutrient %E in DEIS and non-DEIS populations

Energy under-reporters (n=366, 31.7%) were excluded from the analysis, leaving a total sample of 724 (68.3%) stratified by DEIS (n=253, 34.94%) and non-DEIS (n=471, 65.06%) groups %E, the percentage energy of macronutrient intake; SF, saturated fat; AS, added sugar

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4.5 Univariate and multivariate analysis of nutrient intake and the dietary quality of

school lunch

A univariate analysis of nutrient intake is outlined in table 6. A higher number of DEIS

students consumed adequate amounts of TS compared to non-DEIS students. However, more

non-DEIS students consumed adequate amounts of, carbohydrate and DF compared to their

counterparts. There were no significant differences between school type and intake adequacy

for energy, protein, TF, SF, AS and sodium. In table 7, a univariate analysis of dietary quality

is outlined portraying the odds ratio (OR) and the 95 % Confidence Interval (CI) for the

lunchtime intake of fruit, vegetables and SSBs. The univariate model takes only the assessed

food group and DEIS status into consideration.

The lunchtime nutrient intake and dietary quality were compared to five important

demographic factors including gender, age, BMI, the BMI of the parent or guardian and the

family type of the children. The comparison of school lunch quality in accordance to the

aforementioned demographic factors for DEIS groups is displayed in table 8 and is followed

by the same comparison for non-DEIS groups in table 9.

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Table 6, a univariate analyses on the proportion of 8-11 year old children attending DEIS and non-DEIS primary schools consuming adequate lunchtime nutrient intake, CCLaS, Co. Cork.

Total (n=724) DEIS (n=471) Non-DEIS (n=253)

Nutrient n % n % n % P-Value

Energy (kcal) 67 9.25 % 19 7.51 % 48 10.19 % 0.235Protein (g) 623 86.05 % 207 81.82 % 416 88.32 % 0.016Total Fat (g) 448 61.88 % 166 65.61 % 282 59.87 % 0.129Saturated Fat (g) 356 49.17 % 131 51.78 % 225 47.77 % 0.304Carbohydrate (g) 429 59.25 % 130 51.38 % 229 63.48 % 0.002Total Sugar (g) 313 43.23 % 145 57.31 % 168 35.67 % <0.0001Added Sugar (g) 573 79.14 % 191 75.49 % 382 81.10 % 0.076Dietary Fibre (g) 374 51.66 % 106 41.90 % 268 56.90 % <0.0001Sodium (mg) 174 24.03 % 103 21.87 % 71 28.06 % 0.063The adequacy of each nutrient intake is defined by the SFT (19), this excludes total sugar which is defined by EFSA (20) as no known recommendation is given in the SFT reportNutrient intake, 724(68.3%) plausible energy reporters were included in the nutrient intake analysis. 336 (31.7%) were excluded due to energy under-reporting. 253(66.75%) plausible DEIS reporters and 471 (69.2%) plausible non-DEIS reporters were included in the lunchtime nutrient intake analysis.P-value, the differences between DEIS and non-DEIS populations meeting the recommended guidelines for lunchtime nutrient and food group intake. The differences were assessed using χ2 tests of association

Table 7, a univariate analyses on the dietary quality of school lunch by 8-11 year old children attending DEIS and non-DEIS primary schools, CCLaS, Co. Cork.Food Group 0R 95 % CIFruit (g) 0.45 0.33-0.61Vegetables (g) 0.55 0.38-0.81Sugar Sweetened Beverages (ml) 1.14 0.85-1.56The univariate model takes only the appropriate food group and DEIS status into accountFruit, consumers and plausible energy reporters only were analysed (n=416, 57.46%). This was further stratified by DEIS status (DEIS: n=113, 44.66%; non-DEIS: n=303, 64.5%) Vegetable, consumers and plausible energy reporters only were analysed (n=174, 24.03%). This was further stratified by DEIS status (DEIS: n=44, 17.39%; non-DEIS: n=130, 27.6%). SSB, consumers and plausible reporters only were included in the analysis (n=330, 45.58%). This was further stratified by DEIS status (DEIS: n=121, 47.83%; non-DEIS=209, 44.37%). SSB non-consumers (n=394, 54.42%) meet the SFT standard of 0ml per school lunch. This was further stratified by DEIS status, (DEIS: n=132, 52.17%; non-DEIS: n=262, 55.63%).

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Table 8, the mean and the median lunchtime nutrient and food group intake among DEIS groupsDEIS

Factors Energy(Kcal)

Protein(g)

Fat(g)

SF(g)

Carbohydrate(g)

TS(g)

AS(g)

DF (g) Sodium(mg)

Fruit (g) Veg (g) SSB (ml)

Total n (%) Mean (SD) Median (IQR)Gender

Male 180 (71.4%) 550.6(288.9) 17.4(11) 17.7 (11.3) 8.35 (6) 84.15 (52.1) 34.5 (31.3) 12.7 (28) 4.17 (2.27) 796.71 (514.9) 86.7 (72.5) 25 (26) 200 (311.7)Female 72 (28.6%) 527.2 (259.5) 15.7 (9.2) 16.6 (11.8) 6.39 (5.2) 83.19 (51.65) 37.7 (45.1) 13.75 (40.15) 4.82 (2.27) 604.97 (460.6) 101 (125.7) 22.4 (26.7) 239 (191.7)

Age8 14 (5.5%) 361.2 (217.9) 14.5 (8.4) 17.1 (10.9) 6.3 (4.3) 97.21 (97.84) 51.7 (83.4) 23.17 (58.6) 3.6 (2.25) 633.7 (318.9) 71.7 (92) 15.7 (4.7) 172 (185)9 112 (44.3%) 548 (254.4) 18 (10.4) 18.4 (11.5) 8.3 (5.7) 81.9 (45.7) 32.3 (32.6) 14.15 (30.65) 4.13 (2.2) 884.3 (496.9) 76.7 (76) 28.4 (41.7) 200 (266.7)10 120 (47.4%) 541.3 (286.4) 16.2 (11.5) 17 (11.5) 7.6 (6) 85.28 (51.08) 37 (37.7) 11.1 (29.5) 4.67 (2.8) 800.8 (574.5) 104.3(111) 20.4 (23.3) 239 (323.3)11 7 (2.78%) 443.1 (172.6) 16.05 (7) 15.1 (10.8) 7.1 (6.6) 64.34(21.9)) 23.1 (14.8) 6.3 (5.3) 4.16 (2) 756.2 (434) 95.7(120.8) nil 102.5 (46.7)

BMI (child)Normal weight 201 (80.1%) 592.4(259.44) 16.2 (10.8) 17.3 (18.6) 7.8 (5.9) 81.4 (43.5) 33.8 (29) 11.2 (23.85) 4.4 (2.5) 825.7 (542.4) 102 (100) 26.7 (29) 200 (275.3)

Overweight/ Obese 50 (19.9%) 612.85(346.2) 20.1 (10.3) 19 (11.8) 7.9 (5.5) 95.28 (76.4) 42.4 (65.8) 20.4 (53) 4.5 (2.4) 844.3 (463.8) 66 (56.5) 13.7 (12.3) 233.3 (366.7)BMI (parent)

Normal weight 93 (48.95%) 481.9 (230.8) 15.5 (9.4) 16.2 (10.9) 7 (5.3) 72.3 (34.3) 29.02 (20.7) 8.55 (9.6) 4.2 (2.7) 731.4 (480.8) 99.5 (104.3) 31 (36.7) 173.3 (165)Overweight/ Obese 97 (51.05%) 576.6 (31.8) 16.7 (10.1) 18.5 (12.3) 8.2 (6.1) 90.4 (55.2) 39.6 (41.3) 15.7 (31.97) 4.3 (2.4) 844.5 (494.1) 79.3 (92.7) 13.3 (8) 286.5 (298.3)

Family TypeOne Parent 70 (30.7%) 539.1 (269.6) 16.2 (9.01) 18.4 (12.3) 8.2 (6.4) 81.4 (41.4) 33.1 (23.8) 8.7 (12.2) 4.6 (2.9) 829 (538.3) 119 (120.5) 37 (51.2) 200 (306.7)

Two Parents 158 (69.3%) 531 (277.9) 16.6 (10.9) 16.7 (11.3) 7.3 (5.5) 82.8 (53.6) 36.1 (43) 14.4 (34.9) 4.1 (2.24) 789.8 (496.4) 90 (80.7) 16.7 (19.5) 208.3 (236.7)Total DEIS group, it was only the children who were plausible energy reporters, which were included in the analysis (n=253, 67.29%)Food groups, the analysed sample included plausible reporters and food group consumers only; 113 (30.05%) participants, who provided a food diary, were included in the analysis as they were fruit consumers and plausible reporters, 44 (11.7%) participants, who provided a food diary, were included in the analysis as they were vegetable consumers and plausible reporters and 209 (55.6%) participants, who provided a food diary, were included in the analysis as they were SSB consumers and plausible reporters, 252 plausible DEIS children reported their gender and were included in the above analysis253 plausible DEIS children reported their age and were included in the above analysis251 plausible DEIS children reported their BMI and were included in the above analysis190 of the DEIS children’s parents reported their BMI and were included in the above analysis228 of the DEIS children’s parents reported their marital status and were included in the above analysisn; the number of DEIS participants where plausible information on nutrient intake was available, by each demographic factor

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Table 9, the Mean and median lunchtime nutrient and food group intake among non-DEIS groupsNon-DEIS

Factors Energy(kcal)

Protein (g) Fat(g)

SF(g)

Carbohydrate(g)

TS(g)

AS (g) DF (g) Sodium(mg)

Fruit (g) Veg (g) SSB (ml)

Total n (%) Mean (SD) Median (IQR)Gender

Male 249(25.9%) 659.1 (398.1) 20.73 (12.6) 23.17 (21.7) 9.22 (6.7) 96.98 (55) 45.7 (31.3) 9.5 (18.35) 5.8 (3.4) 917.6 (554.5) 126 (116.3) 29.3 (42.5) 258.3 (255.2)Female 222(47.1%) 532.6 (218.5) 15.65 (10.3) 17.38 (10.9) 7.39 (5.5) 82.39 (83.2) 40.2 (29.8) 10.3 (24.7) 4.8 (4.4) 728.6 (395.3) 93.2 (111.7) 20 (20.2) 239 (191.7)

Age8 59 (12.5%) 620.4 (317.5) 17.54 (11) 21.9 (17.1) 9.1 (5.8) 93.5 (51.6) 46.3 (41.9) 13.3 (39.1) 4.8 (2.5) 738.6 (359.5) 98 (105.3) 30.5 (27.5) 200 (257.3)

9 197(41.8%) 568.3 (237.7) 17.4 (10.16) 18.03 (12.3) 7.7 (6.3) 88.5 (38.4) 43 (27.7) 9.3 (16.35) 5.24 (3) 847.1 (538.8) 100.7 (130.2) 19.3 (19.5) 269.3 (241.7)10 204(43.3%) 623.3 (407.8) 19.24 (12.4) 22.23 (21.7) 8.83 (6.1) 91.1 (54.9) 38.4 (15.6) 9.45 (18.9) 5.4 (3.1) 814.7 (480) 104 (107) 25 (33.5) 200 (204.7)11 11 (2.4%) 604.8 (268.3) 22.4 (14.3) 22.4 (15.8) 7.8 (8.4) 82.4 (35) 41.8 (28.2) 8.92 (20.6) 10.02(17) 995.4 (572.8) 249 (172.7) 14 (2.2) 320.8 (241.7)

BMI (child)Normal weight 385(82.6%) 592 (337.2) 16.2 (10.76) 20.4 (18.6) 8.28 (6.2) 88.85 (46.3) 41.7 (27.9) 9.3 (17.7) 5.3 (4.1) 817.1 (192.3) 100.7 (115.2) 24 (26) 234.7 (233.7)

Overweight/obese 81 (17.4%) 649.9 (304.8) 20.93 (12.85) 21.4 (12.5) 9.06 (5.5) 98.1 (53.9) 50.1 (41.6) 12.9 (34.9) 5.4 (3.3) 909 (501.6) 131.2 (132.2) 11.3 (21) 272.7 (212.5)BMI (parent)

Normal weight 277(66.7%) 584.3 (278.7) 18.5 (11.9) 19.4 (13.5) 8.1 (5.9) 88.3 (45.4) 43 (32.5) 10 (23.4) 5.4 (3.1) 814.7 (514.8) 115 (118.7) 24 (26) 200 (230)Overweight/obese 138(33.3%) 587.6 (254.6) 17.14 (8.5) 20.3 (13.2) 8.6 (6.6) 88.4 (40.2) 42.4 (29) 9.5 (19.6) 5 (2.9) 816.1 (437.5) 96.5 (104.5) 20.5 (25) 272.2 (237.7)

Family TypeOne Parent 58 (12.9%) 638.5 (249.7) 19.2 (13.3) 19 (10.9) 8.1 (5.1) 102.9 (38.9) 52.3 (27.2) 10.9 (16.9) 5.6 (3.3) 877.2 (622.3) 97.5 (109.8) 22.8 (34.7) 350 (220.8)Two Parent 392(87.1%) 580.4 (270.5) 17.9 (10.4) 19.9 (13.8) 8.3 (6.3) 86.7 (43.3) 41.5 (31.2) 9.5 (22.4) 5.3 (4.1) 806.9 (457) 106 (122) 22.5 (26.5) 202.7 (213)

Figures in bold were statistically significant values for nutrient and food group intake between demographic factorChildren aged 10/11 consumed more fat than children aged 8/9 (22.24g vs. 18.93g)Children aged 8/9 consumed more SSBs than children aged 10/11 (138.95ml vs. 91.79ml)The analysed sample reporting mean lunchtime nutrient intake included only plausible reporters (n=471, 65.1%)The analysed sample reporting food group intakes included plausible reporters and food group consumers only. The population samples are as follows;o 303 (44.5%) participants, who provided a food diary, were included in the analysis as they were fruit consumers and plausible reporterso 130 (19.1%) participants, who provided a food diary, were included in the analysis as they were vegetable consumers and plausible reporters.o 209 (30.7%) participants, who provided a food diary, were included in the analysis as they were SSB consumers and plausible reporters.N; the number of non-DEIS participants where plausible information on nutrient intake was available, by each demographic factorIQR; the interquartile range of intakeThe median and IQR values were used to assess the dietary quality of school lunch against demographic characteristics, food group intakes were taken only from the consumers of each food471 plausible DEIS children reported their gender and were included in the above analysis471 plausible DEIS children reported their age and were included in the above analysis466 plausible DEIS children reported their BMI and were included in the above analysis415 of the DEIS children’s parents reported their BMI and were included in the above analysis450 of the DEIS children’s parents reported their marital status and were included in the above analysis

34

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A multivariate analysis of nutrient intake and dietary quality is outlined in table 10. The OR

calculated for lunchtime nutrient intake indicated that DEIS populations were less likely to

meet the SFT recommendations for lunchtime protein, carbohydrate and DF intakes, while in

contrast, non-DEIS populations were less likely to meet the SFT recommendations for

lunchtime fat, SF, TS and sodium intakes, when adjusted for gender, age parental education

and BMI. Insignificant results were found between school DEIS status and lunchtime energy,

and AS intake. However, when the model was further adjusted for physical activity (PA), the

odds of DEIS population groups meeting the SF lunchtime standards compared to non-DEIS

groups were no longer statistically significant (p=0.074), however other nutrients remained

significant (table10).

Similar to the univariate model (table 7), the OR calculated for lunchtime dietary quality

taking various confounders into consideration indicated that DEIS groups were less likely to

meet the SFT recommendations for F&V compared to non-DEIS groups (table 10) as non-

DEIS groups were less likely to meet the SFT recommendations for SSB intake compared to

their counterparts in DEIS schools. However, each association was insignificant in the

multivariate model (table 10).

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Table 10, a multivariate logistic regression model reporting the odds ratio (OR) and 95% confidence interval (95% CI) for lunchtime nutrient and food group intake among 8-11 year old children attending DEIS22 and non-DEIS23 primary schools, Co. Cork. The test showed the likelihood24 of a particular group to meet the nutrient and food group recommendations25 in comparison to their counterparts.26

Energy27 Protein28 Fat29 SF30 Carbohydrate31 Sugar32 AS33 DF34 Sodium35 Fruit3637 Vegetables38 SSB3940

OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CI

Model 141

DEIS 0.6 0.3-1.1 0.5 0.3-0.8 1.6 1.1-2.3 1.4 1.01-2.02 0.5 0.3-0.7 2.5 1.7-3.5 0.8 0.5-1.2 0.5 0.4-0.7 1.9 1.3-2.8 0.95 0.55-1.6 0.8 0.26-2.5 1.1 0.9-1.5

Model 242

DEIS 0.6 0.3-1.1 0.5 0.3-0.8 1.6 1.1-2.3 1.4 1.01-2.02 0.5 0.4-0.7 2.4 1.4-3.4 0.8 0.5-1.2 0.5 0.4-0.8 1.9 1.2-2.8 0.95 0.55-1.6 0.82 0.3-2.58 1.1 0.9-1.5

Model 343

DEIS 0.6 0.3-1.2 0.5 0.3-0.8 1.5 1.1-2.2 1.4 1.0-2.0 0.5 0.4-0.7 2.35 1.6-3.4 0.8 0.5-1.2 0.5 0.4-0.7 1.8 1.2-2.7 0.96 0.55-1.7 0.8 0.5-1.1 1.1 0.9-1.5

22 Data was analysed from 210 DEIS children out of the total sample of 389 as they were not under reporters23 Data was analysed from 471 non-DEIS children out of the total sample of 686 as they were not under reporters24 If OR>1, DEIS schools were more likely to meet the nutrient and food group recommendation compared to non-DEIS schools25 The recommendations used in the present report were taken from 19. School Food Trust. A guide to introducing the Government’s food-based and nutrient-based standards for school lunches 2007 [cited 2015 21 April]. Available from: http://www.childrensfoodtrust.org.uk/assets/sft_nutrition_guide.pdf. For each nutrient except TS, which was attained from 20. European Food Safety Authority. Review of labelling reference intake values: "Scientific Opinion of the Panel on Dietetic Products, Nutrition and Allergies on a request from the Commission related to the review of labelling reference intake values for selected nutritional elements". The EFSA Journal. 2009(1008,):1-14. Upper limits were decided upon for protein and carbohydrate intakes. Lower limits were decided upon for fat and sodium intakes using the standard deviation of the mean.26 The results highlighted in bold were statistically significant (p<0.05)27 The recommended energy lunchtime intake was 503-557 kcal28 The recommended lunchtime protein intake was 7.5-47.25g 29 The recommended lunchtime fat intake was 2.53-20.6g30 The recommended lunchtime SF intake was <=6.5g31 The recommended lunchtime carbohydrate intake was 70.6-217.11g32 The recommended lunchtime TS intake was <=30g33 The recommended lunchtime AS intake was <=15.5g34 The recommended lunchtime DF intake was >=4.2g35 The recommended lunchtime intake was 0-499mg36 The recommended lunchtime F&V intake was 65g each37 413 (38.96%) participants in total were included in the analysis as they were fruit consumers and plausible reporters, 113 (29.8%) were from the DEIS group whilst 303 (44.5%) were from the non-DEIS population.38 174 (16.42%) participants in total were included in the analysis as they were vegetable consumers and plausible reporters, 44 (11.6%) were from the DEIS group whilst 130 (19.1%) were from the non-DEIS population.39 There is no set SSB recommendation, as they offer no nutritional benefit to the consumer. 40In total, 330 (31.12%) of the participants who provided a food diary were included in the analysis as they were vegetable consumers and plausible reporters, 209 (30.7%) were from the DEIS group whilst 121 (31.9%) were from the non-DEIS population. In total 394 (37.2%) plausible reporters who provided a food diary, met the SSB recommendations by being non-consumers at lunchtime, 132 (34.8%) were from the DEIS group whilst 262 (38.47%) were from the non-DEIS population41 Model 1 was adjusted for gender, age and parental education42 Model 2 was adjusted for gender, age, parental education and BMI43 Model 3 was adjusted for gender, age, parental education, BMI and whether physical activity recommendations were met

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Chapter 5: DiscussionUsing Irish representative data, the present study examined for the first time the nutrient

intake and the dietary quality of school lunch in 8-11 year old children attending DEIS and

non-DEIS primary schools in county Cork, Ireland.

One of the key findings from the study was that the school lunch quality in DEIS and non-

DEIS schools followed a similar pattern. Imbalances in nutrient intake were noted in both

groups for saturated fat (SF), total sugar (TS) and sodium (19, 20), however, lunchtime

intakes for protein, fat, carbohydrate, added sugar (AS) and dietary fibre (DF) were met in

both population groups (19). Mean lunchtime energy intakes were above the School Food

Trust (SFT) recommendations in non-DEIS schools (19) while DEIS groups had mean

intakes within the recommended range (19). Mean sodium were classified as poor in both

DEIS and non-DEIS schools. In fact, levels were so high that they also surpassed 733.3mg,

the tolerable upper intake level (51), which is the highest daily intake level identified as being

associated with no increased health risk (51). In similar motion, there were no major

differences in the dietary quality of school lunch between DEIS and non-DEIS primary

school children. Both groups consumed sufficient amount of fruit products however

imbalances in vegetable and SSB lunchtime according to the SFT guidelines (19). There were

no significant differences in the dietary intakes between DEIS and non-DEIS primary

schools.

Univariate analysis between nutrient intake and DEIS status confirmed that lunchtime

standards for TS (20) were met by less children from non-DEIS primary schools compared to

DEIS primary schools. Alternatively, the lunchtime standards for DF (19) were met by a

smaller proportion of DEIS participants compared to non-DEIS participants. As for the

dietary quality of school lunch, univariate analysis established that 8-11 year old children

attending DEIS were less likely to meet the SFT recommendations for lunchtime fruit

(p<0.0001) and vegetables (p=0.002) intake (19) compared to non-DEIS children of the same

age group. Conversely, those from non-DEIS groups were less likely to adequately consume

SSB compared to DEIS groups (19) however this was statistically insignificant (p=0.374).

Multivariate logistic regression analysis identified the impact confounding had on lunchtime

nutrient intake by 8-11 year old primary school children in DEIS and non-DEIS schools.

When adjusted for confounders such as gender, age, parental education and BMI, non-DEIS

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attenders were less likely to meet the recommended lunchtime standards for SF and sodium

(19). However when physical activity (PA) was taken into account, there were no longer any

statistical differences between the adequacy of SF intake and school level of deprivation, i.e.

DEIS vs. non-DEIS schools (p=0.074), whereas other lunchtime nutrient intakes remained

significant. Multivariate analysis additionally proved that when confounding was taken into

consideration no significant differences were found for F&V intake between DEIS and non-

DEIS schools. Thus, confounding had a strong influence on the F&V consumption in the

sample of DEIS and non-DEIS primary schools.

In agreement with previously published studies (8, 52), the present study found that the

nutritional intake and dietary quality of school lunch could be improved in primary school

children. Children attending non-DEIS schools, who consumed a packed lunch, had

considerably higher lunchtime intakes for energy, fat, carbohydrate, TS and DF. Similarly,

Gatenby et al, (52) noted that children who consumed a packed lunch had significantly

greater energy and fat lunchtime intakes compared to those consuming a school meal.

Gatenby also found that lunchtime sodium intakes were much lower for those who consumed

school meals in primary schools in areas of high and low affluence compared to those who

consumed a packed lunch in the same schools (52). This differed to the present study where

both DEIS schools, consuming a provided meal, and non-DEIS schools, consuming a packed

lunch had lunchtime sodium intakes much higher than what is recommended by the SFT. See

appendix table 3.1 for a broader representation of the results attained from the research

conducted by Gatenby. Relative to energy intake, lunchtime nutrient intake in both DEIS and

non-DEIS schools failed to comply with the recommended food energy standards for SF and

TS both over the full school day and at lunch. This inadequacy was mirrored by Walton et al,

(8) where a sample of primary level children were found to have exceeded 10 and 18%E for

SF and TS intake. However, this sample of primary school children had adequate intakes for

AS whereas research by Walton (8) did not. This could be due to Walton’s utilisation of a 7-

day food dairy rather than a 3-day representation similar to this report. Generally, 3-day food

diaries give a more accurate representation of food intake as reported intakes tend to decrease

with a broader recording period (53). See appendix table 3.2 for an in depth representation of

the results attained from the research conducted by Walton.

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Strengths & Limitations of the studyThe strengths and limitations of the present study merit consideration. One limitation is that

in involved the self-reporting of food intake by the children themselves, which may have led

to the high proportion of under-reporting. As energy under-reporting prevents the accuracy of

habitual food intake, under-reporters were excluded from the analysis. Therefore, there was a

reduction in sample size, thus less statistical power. Additionally, the data used to define

nutrient and food group intake was quite skewed, making the results difficult to interpret. One

of the strengths to the present study worth noting is that it is one of the first European studies

designed to collect in depth data on lifestyle, diet, and PA. This study collected objectively

measured physical activity data in free-living conditions over a 7-day period. Additionally,

the debriefed 3-day estimated food diaries used to provide comprehensive data on dietary

intake patterns and behaviours within the sample of 8-11 year old children.

Chapter 6: ConclusionIn conclusion, the key finding of the present study is that there are no substantial differences

in the nutrient intakes and dietary quality of school lunch between DEIS and non-DEIS, 8-11

year old children. Examination of nutrient intake at lunchtime has highlighted nutritional

imbalances for intakes of saturated fat (SF), total sugar (TS) and sodium in both school

categories (19, 20). Furthermore, mean lunchtime energy intakes exceeded the standard

school lunch guidelines in non-DEIS however DEIS schools met these standards (19).

Univariate analysis of lunchtime nutrition intakes for protein, carbohydrate and dietary fibre

(DF) found that non-DEIS schools had significantly higher proportions of adequate

consumers compared to DEIS attenders. On the other hand, those in the DEIS group had

significantly more adequate consumers for TS compared to their counterparts. Multivariate

analysis explained that the influence of various confounders including age, gender, parental

education and BMI impacted the nutrient intakes of the children. Lunchtime intakes for fat,

SF and sodium were found to have significantly more adequate consumers from DEIS

schools then it did for non-DEIS schools. Additionally, the inclusion of physical activity (PA)

attenuated results for meeting recommendation specifically the association between SF

intakes between school-types, was no longer deeming it as significant.

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Dietary quality analysis at lunchtime highlighted that in total, just over half the children

between 8 and 11 years old are consuming fruit (n=416, 57.46%44). Approximately one-

quarter were consuming vegetables (n=174, 24.03%) and just under half the population

consumed SSBs (n=330, 45.58%) at school lunch. From these food group consumers, there

were no statistical differences between the intakes of SSBs in DEIS and non-DEIS primary

schools. Children attending both DEIS and non-DEIS schools, categorised as fruit and

vegetable consumers, the majority of them met the recommendations for fruit (DEIS: n=113,

100%; non-DEIS: n=293, 96.7%) and vegetables (DEIS: n=34, 77.27%; non-DEIS=103,

79.23%) intake (19), though the recommendation was 65g for a portion at school. There were

no significant associations between the median adequacy intakes between school types.

However, when the influence of confounding was taken into account, 8-11 year old children

attending non-DEIS schools were found to have a higher likelihood of consuming adequate

amounts of fruit compared to those attending DEIS schools. The confounders that influenced

this association were gender, age, parental education, BMI and PA.

RecommendationsThe main recommendations are as follows; that the study is repeated using a larger sample

population from various areas in Ireland, not only county Cork. This is necessary to gain a

broader understanding of children’s school consumption in Ireland. Additionally, due to the

time constraints of the present study, it was not possible to analyse every nutrient consumed

by the children during their school lunch hours. As a result, just one micronutrient (sodium)

was analysed. Other micronutrients should be given attention and therefore further studies

should investigate intakes of vitamin C, B12, iron and vitamin D in the analysis.

Additionally, similar to this study, there is a need for the inclusion of confounders in dietary

analysis as many factors have to tendency to vary the quality of food intake.

Total word count for the full report: 7,705

44 The % of food group consumers (fruit, vegetables and SSBs) weans attained by finding the proportion of food group consumers in relation to the total sample of plausible energy reporters (n=724).

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of energy intake data using fundamental principles of energy physiology: 2. Evaluating the

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requirements. Washington: National Academies Press; 2006.

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Acknowledgements

The author would like to acknowledge with thanks the support received by the Department of

Public Health and Epidemiology in University College Cork over, the children who

participated in CCLaS and to the National Children’s Research Centre in Our Lady’s

Children’s Hospital, Crumlin for funding this study. Special thanks are given to; Janas

Harrington and Catherine Perry who supervised the analyses conducted throughout the study

period. Additionally, the author would like to acknowledge Celine Murrin, the project tutor as

well Shauni Fitzgerald and Fiona Riordan, who were also of great support over the time in

which the project was undertaken.

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Appendices

Appendix 1:

The following is the data management skills used during data analysis

The generation of variables for descriptive statistics

Mean lunchtime nutrient intakes were generated by the following process. First, weekdays

and weekend days were obtained. Following this the total amount of the particular nutrient

consumed at school was divided by the appropriate number of days the child completed the

diary for (three day diaries completed by the majority, n-1043 children). This calculation had

a condition taking into account whether there were any weekend days, i.e. if there was one

weekend day the total nutrient value was divided by two as there were two weekend days or

school days. A similar process was taken to generate the total daily nutrient intake. The total

nutrient intake on weekdays was divided by the diary day count, taking into account whether

there were any weekdays or not. Lunchtime nutrients were also presented as percentages.

These were defined by dividing the lunchtime nutrients by the total daily mean of the same

nutrient and multiplying by 100 e.g. (school sugar/ daily sugar)*100 The generated variables

helped analyse the nutritional quality of school lunches and the mean and standard deviation

(SD) of percentage intake were analysed. Using the same process, variables describing mean

lunchtime intakes, TDM as well as the mean lunchtime percentage of food items were

generated. These variables were also used in the analysis; however, due to the skewed data of

each food group, the median and the interquartile range (IQR) were analysed dissimilar to

nutrient analysis.

Fat and sodium are generally considered as unhealthy however both are required for

maintaining healthy growth and development. Thus, for fat, this researcher with consultation

with supervisor decided a lower limit of intake. The normal/Gaussian distribution guided

these decisions therefore what 68% of the population were consuming was considered a

guideline with +/-1 standard deviation (SD) of the mean as the upper and lower limits of

intake. Thus, fat guidelines were set as 2.53-20.6g per school day intake. For sodium,

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children who consumed <0mg were not considered to be meeting recommendations setting

the standard sodium lunchtime intake between 0-499 mg.

Logical upper limits for healthier nutrients (protein and carbohydrate) were also set. In this

case it was assumed that 99.9% of the sample population were eating a desirable amount of

said nutrients. The reason for allowing a larger margin was due to health benefits of their

consumption in large amounts. Thus, after multiplying mean lunchtime intakes by 3 SDs the

recommended range was concluded to be within 7.5-47.27 and 70.6 -217.11g/school lunch

for protein and carbohydrate respectively.

For the remaining nutrients and dietary groups, no upper for healthier nutrients or lower for

unhealthier nutrients were decided on other than what was given in the SFT report. This was

because consuming less SF, sugar and AS would not cause any health defects as well as

consuming more DF, fruit and vegetables being more beneficial to the host rather than toxic.

As a result, binary variables were generated setting the lunchtime intake guidelines at <=6.5g

of SF, <=30g of sugar, <=15.5g of AS, >=4.2g DF and >=10.55g for F&V.

A new variable was created for SSBs, which transformed the data for these variables from a

continuous to a categorical form using the ‘xtile’ command. This divided the data into five

different quintiles from the lowest to the highest intake values. A cross tabulation between

DEIS status and the newly created quintile variable was performed. A chi square test was also

carried out during the cross tabulation in order to determine the significant.

Recoding old variables into new variables

The original DEIS variable was re-coded in order to give two categories of DEIS status

(DEIS or non-DEIS) rather than three (non-DEIS, level one DEIS or level two DEIS). Family

type of each child was generated by re-coded. Thus, the six categories of marital status

(single, married, cohabiting, separated, divorced, widowed) were transformed into two family

type situations, one parent (single, separated, divorced, widowed) or two parents (married or

cohabiting). Due to the low number of parents who described their child’s current health

status as “sometimes quite ill” and “almost always unwell”, the source variable was re-coded

so that the above suggestions could merge together. Thus, the variable for ‘current health

status’ was re-coded from “very healthy, no problems”, “healthy, a few minor problems”,

“sometimes quite ill” and “almost always unwell” to “great” “average” and “poor”. A similar

procedure was used in order to define the health status of the children’s parents. Similarly,

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the data for the options “fair” and “poor” were merged due to the small number of

participants in each. However the categories “excellent” and “very good” were also merged

to keep the categories defining the health status of the children and their parents standardised.

Therefore, the options for health status from the questionnaire (“excellent”, “very good”,

“good”, “fair” and “poor”) become “great” “average” and “poor” in the present report. A low

number of participants, both the children and their parents, were found to be in the

‘underweight’ and ‘obese’ category for BMI status. Thus, the source variable for parent and

child BMI was re-coded to merge those who were underweight with those within the

‘normal’ BMI range. Likewise, all participants who were ‘obese; were included with those

who were defined as ‘overweight’. Parental education was a four category variable coded as

1=3rd level education, 2=post-secondary education, 3=higher secondary education and

4=lower secondary education or lower. In order to analyse whether there were statistical

differences in nutrient intake and the dietary quality of school lunch based on age group, the

variable for age was re-coded from a four-category variable of each age of the participants

(8,9,10 and 11) to generate a binary variable. The binary variable generated (8/9 and 10/11)

described whether older or younger children in each school had significantly higher/lower

intakes of each nutrient and food group.

As the recommendation for SSBs is 0ml at lunchtime, non-consumers were classified as

meeting the recommendations. Re-coding was additionally used to generate a binary variable

that defined whether the children were SSB consumers or non-consumers, from the

continuous variable describing the children’s intake. This clarified whether the children met

the SFT guidelines or not. Rather than giving a strict range for SSB intake in primary school

children, the SFT suggested limiting their consumption completely within the school hours.

Thus, it was the consumers and non-consumers we were interested in for the analysis.

The independent sample t test assumptions

First, the normality of data assumption was tested for. This was achieved by constructing a

histogram with a normal distribution plot, of the data for each nutrient/food group variable. If

the data appeared as normally distributed it was marked as plausible. However, after having

looked at the histograms, this assumption was verified by performing a two sample

Kolmogorov–Smirnov equality of distributions test. Such a test determined whether there

were any differences in the variables distribution between the two groups. If the significance

level was <0.05 it was concluded as appropriate for the running of a parametric test, i.e. an

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independent sample t test. The second assumption that was run in order to verify whether the

data was appropriate for parametric testing was the equality of variance test. In this case, a

box plot was constructed by DEIS status for each variable. If both box plots were

approximately the same size, assumptions to run the independent t test were met. The final

assumption looked at the independence of data in each group. This was the only assumption

that was fully met by the CCLaS data.

Logistic regression analysis was performed using three different regression models in order to

estimate the associations between nutrient and food group intake at school and DEIS status.

The dichotomous dependent variable (y) used in the analysis was ‘students meeting the

recommendations for school lunch’ (0=no, 1=yes). Four predictor values were used, gender

(X1), age (X2), parental education (X3), BMI (X4) and whether physical activity (PA)

recommendations were met or not in three different models (X5). The gender distribution was

higher for males (n=612; 57.79%) compared to females (n=447; 42.21%). The predictor was

coded as 1=males and 2=females. The ages of the sample population ranged from 8-11 years.

The mean age of the children was 9 years with a standard deviation of 0.7. The distribution

was higher for the higher levels of education. 31.34% (n=310 parents) were classified as

having received third level education. 31.65% (n=313 parents) were categorized as having

received post-secondary education. 22.65% (n=224 parents) were found to have completed a

higher secondary education. Finally, only 14.36% (n=142 parents) were classified as having

received lower second level education or less. The BMI predictor was coded as

1=overweight/obese and 0=underweight/normal weight. The BMI distribution was far from

even with 74.64% (n=786 children) being underweight or normal weight and 25.36%

(n=267) being overweight or obese. Whether PA recommendations were met by the children

every day of the week was also dichotomous variable coded as 1=yes and 0=no. Again, the

distribution was far from an equal division as only 23.81% (n=245 children) met their PA

recommendation for everyday of the week while as much as 76.19% (784 children) did not.

Model one examined the nutritional and food group intakes of the sample population of

children by DEIS status and was adjusted for X1, X2 and X3. Model two was adjusted for X1,

X2, X3 as well as X4. Finally model three was adjusted for each of the predictor variables.

Model 1: ln (ρ45/1-ρ) =β0+β1x1+β2x2+β3x3+error

45 ρ, the expected probability that the outcome is present

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Model 2: ln (ρ/1-ρ) =β0+β1x1+β2x2+β3x3+β4x4+error

Model3: ln (ρ/1-ρ) =β0+β1x1+β2x2+β3x3+ β4x4+ β5x5+error

Appendix 2The proportions of consumers and non-consumers for the assessed food foods (Fruit,

vegetables and sugar-sweetened beverages

Due to the data describing fruit, vegetable and sugar sweetened beverage (SSB) being highly

skewed, median values of intake were found as 0g among each population group. This made

school lunch dietary quality difficult to assess. Therefore, it was decided to exclude any non-

consumer for each food group and provide the median intake for each consumer. Below is a

representation of the non-consumers.

Table 2.1, the proportions of consumers and non-consumers for each food group in the analysis of school lunch dietary quality

Consumers Non-consumersTotal

(n=724)DEIS

(n=253)Non-DEIS

(n=471)Total

(n=724)DEIS

(n=253)Non-DEIS

(n=471)Food group N (%) P-valueFruit (g) 418 (57.7%) 113 (27.0%) 305 (73.0%) 306 (42.3%) 140 (45.6%) 166 (54.3%) <0.0001Veg (g) 174 (24.0%) 44 (25.3%) 130 (74.7%) 550 (76.0%) 209 (38.0%) 341 (62.0%) 0.002SSB (ml) 330 (45.6%) 121 (36.7%) 209 (63.3%) 394 (54.4%) 132 (33.5%) 262 (66.5%) 0.374

Plausible energy reporters only were included in the above analysisP-value, this represents the differences in the proportions of consumers and non-consumers of food-group intake between DEIS and non-DEIS status. The differences were assessed using a Wilcoxon rank signed test.

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Appendix 3:

The similarities and dissimilarities of the present study to previous studies of similar principal

Table 3.1, the comparison between the lunchtime nutrient intakes46 found in the present report and the lunchtime nutrient content of school

meals and packed lunches in schools in areas of high and low affluence in a similar study by Gatenby et al, 2011 (52) compared to the school

food trust (SFT) guidelines (19)

McGann, 2015 Gatenby et al, 2011 Guideline of intake47

Total DEIS Non-DEIS Less affluent More affluentNutrient (School meal) (Packed lunch) School meal Packed lunch School meal Packed lunchEnergy (kcal) 580.08* (315.55) 543.93 (279.97)ǂ 599.49* (331.76) ǂ 367* (128) ǂ 760* (196) ǂ 398* (128) ǂ 638* (167) ǂ 503-557Protein (g) 17.84 (11.19) 16.91 (10.76) 18.35 (11.4) 21 (6.9) 18.9 (5.1) 20.8 (7.1) 18.9 (6.1) 7.5-47.25Total Fat (g) 19.45 (15.82) 17.59 (11.43) ǂ 20.44 (17.67) ǂ 7.4 (2.8) ǂ 30.8* (10.7) ǂ 8.1 (3.4) ǂ 28.9* (9.5) ǂ 2.53-20.6Saturated Fat (g) 8.16* (6.11) 7.79* (5.83) 8.36* (6.25) 2.8 (1.4) ǂ 12.6* (4.5) ǂ 2.8 (1.4) ǂ 11.7* (4.3) ǂ <=6.5Carbohydrate (g) 87.92 (49.22) 83.86 (51.77) ǂ 90.1 (47.7) ǂ 57.6* (23.9) ǂ 108.7 (28.7) ǂ 64.3* (1.7) ǂ 92.5 (22.4) ǂ 70.6-217.11Added Sugar (g) 10.96 (25.64) 12.99 (31.8) 9.86 (21.58) 7.0 (4.2) ǂ 35.9* (18.8) ǂ 11.9 (3.9) ǂ 25.7* (11.8) ǂ <=15.5Dietary Fibre (g) 5.0 (3.53) 4.36 (2.5) ǂ 5.36 (3.93) ǂ 2.8 * (1.7) ǂ 3.9 * (1.9) ǂ 3.2* (1.6) 3.7* (1.3) >=4.2

46 Results are presented as the mean (SD) of intake47 The guidelines used to compare the above lunchtime intakes were taken from the School Food Trust 19. School Food Trust. A guide to introducing the Government’s food-based and nutrient-based standards for school lunches 2007 [cited 2015 21 April]. Available from: http://www.childrensfoodtrust.org.uk/assets/sft_nutrition_guide.pdf.*Mean intakes were outside the SFT guidelinesǂ A statistical comparison between the nutrient intake from school meals and packed lunches in areas of high and low affluence (Gatenby) and between DEIS and non-DEIS primary schools analysed in the present study (p<=0.05).

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Sodium (mg) 828.1* (506.02) 827.28* (527.6) 828.55* (494.6) 334.7 (118) ǂ 1026.4* (287) ǂ

374.8 (140) ǂ 1010.1* (348) ǂ

0-499

Table 3.2, the comparison between the percentage energy (%E) for nutrient intake over the full school day and at school lunch found in the

present report and from a similar study by Walton et al, (8) compared to the Irish food-based dietary guidelines (19)

McGann, 2015 Walton et al, 2014 Guideline of intake48

Total DEIS Non-DEISNutrient Full day Lunchtime Full day Lunchtime Full day Lunchtime Full day LunchtimeTF49 (%E) 33.14 29.09 33.25 28.87 33.08 29.2 33.2 31.9 25-35SF50 (%E) 13.82* 12.41* 13.91* 12.77* 13.77* 12.2* 14.2* 13.7* <=10Carb51(%E) 58.81 61.41 59.17 61.73 58.62 61.24 52.6 55.6 45-65TS52 (%E) 25.41*ǂ 27.92*ǂ 24.58*ǂ 25.2*ǂ 25.86*ǂ 29.38*ǂ 24.1*ǂ 27.5*ǂ <=18AS53 (%E) 8.94 6.81 9.72 8.26 8.52 6.03 14* 16.6* <=10

48 There were no guidelines suggesting lunchtime sugar intake in the SFT report and therefore the 30g standard was taken from an EFSA report 20. European Food Safety Authority. Review of labelling reference intake values: "Scientific Opinion of the Panel on Dietetic Products, Nutrition and Allergies on a request from the Commission related to the review of labelling reference intake values for selected nutritional elements". The EFSA Journal. 2009(1008,):1-14. , by dividing the total day sugar recommendation by 3 to get approximately one-third of the recommended intake49 TF, total fat50 SF, saturated fat51 Carb, carbohydrate52 TS, total sugar53 AS, total sugar

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Appendix 4:The instruments used to measure the intake of saturated fat

Prior commencement of this report, the author was working on a systematic literature review

(SLR) which focused on the instruments used to accurately assess the intake of saturated fat

(SF) As a result, the consumption of SF was specially considered in the present report. The

SLR was one of many work packages included in the Determinants of Diet and Physical

activity (DEDIPAC) study. This work package was entitled “what are the assessment

methods used to determine dietary intakes of saturated fats in adults (>18 years) and children

in European countries, according to pan-European studies involving two or more European

countries”.

As previously mentioned in the introduction, ‘dietary fat’ can provide some benefit in the diet

and should be consumed within a certain range. Similar to protein and carbohydrate, it is an

essential macronutrient needed by the human body for optimum growth and nutrition.

However, as stated, large amounts of fat are believed to have toxic effects, leading to weight

gain and development of non-communicable diseases (NCDs). As a result, it is necessary to

adequately assess the dietary intakes of fat, draw conclusions regarding its consumption and

determine the upper limit of its allowance.

Dietary fat is attainable exogenously in two forms, saturated and unsaturated. The European

Food Safety Authority (EFSA) refers to the different dietary fat subgroups, saturated and

unsaturated fat, as non-essential (NEFA) and essential fatty acids (EFA) respectively.

European studies completed by the World Health Organization (WHO) have defined

‘saturated fat’ (SF) as dense sources of energy, which is one of the major causes of obesity in

the European region. It is known that excess intakes of such fats can greatly contribute to the

development of NCDs, i.e. diabetes, cancer and many respiratory diseases. Moreover,

consumption of saturated fats can increase the concentration of LDL cholesterol in the body,

high levels of which can increase the likelihood of developing cardiovascular disease Due to

the widespread increase in obesity rates among Europe and the adverse effects associated

with high levels of saturated fat consumption, it is imperative that the intake of fat can be

accurately assessed using appropriate methodology.

Data sources and study selectionA systematic literature search for pan-European studies assessing the intake of SF was

conducted. Other than SF, broad terms were used to define its consumption in the literature

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search, for example, “dietary fat(s)”, “dietary fatty acid(s)”, “saturated fatty acid(s)”, “volatile

fatty acid(s)”, “non-essential fatty acid(s)”, “”trans fatty acid(s)”, “trans fat(s)”, “short chain

fatty acid”, “fatty acid(s)“animal fat(s)” or “lipid(s)”. Two authors RM and FR,

independently conducted a search of PubMed, EMBASE and web of Science databases using

such search terms as well as keywords that defined dietary intake including

diet/dietary/nutritional/nutrient/calorie/food/energy intake/consumption. Additionally, terms

such as eating behaviour/habits, energy intake and food habits were included as search terms

for dietary intake. As this was a pan-European study, search terms for European countries

were included in the literature search. All searches were limited to English-language and

literature published between 1990 to the present day of the literature search. Titles and

abstracts were independently screened by RM and FR. Studies were included if they assessed

the intake of SF within 2 or more European countries. For this assessment, participants were

required to be from a free-living or healthy population and therefore hospital-based

populations and studies, which focused on a specific diseased subgroup, (i.e. diabetic cohort)

or any fixed societal subgroups (i.e. pregnant women). Studies were only included if they

assessed SF intake at the individual level thus, studies that assessed the consumption of SF at

household level were excluded.

Data extraction and quality assessmentThe following step involved the extraction of valid information from the included articles.

This process of data extraction was carried in order to capture the following data: study

design, number and names of the European countries involved, sample size (total number for

each country), age range of the included population, the methods used and description (i.e.

the frequency categories for FFQs, the number of items which referred to SF, details of

nutrient intake assessment, details of portion estimation), mode of administration and details

of validation or reproducibility. For each of the sourced articles, information on the dietary

assessment methods of SF was recorded. One reviewer extracted the data for each study,

which was confirmed by the other reviewer.

The checklist used to assess the quality of this SLR was derived from the ‘Standard quality

assessment criteria for evaluating primary research papers and was reduced to the relevant

question: Have the methods been described/justified (i.e. has the method been validated,

tested for reliability and are details of this validation and/or reproducibility testing

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available?). Answering yes, no or partial to the above questions assessed each retained article.

The papers were marked according to the following guidelines.

1. Where articles referred to comprehensive validation and/or reproducibility studies they

were marked as ‘yes’ and were given 2 marks.

2. Where studies stated the method was validated and/or how, but did not refer to a separate

validation or reproducibility study that were marked as ‘partial’ and were given 1 mark.

3. Where studies made no mention of validation or reproducibility at all they were marked

as ‘no’ and were given a 0 mark.

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roisin mcgann_final report

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