Multidimensional Child Deprivation in Ireland: A New Child Rights-Informed Approach

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This study uses longitudinal data from the Growing Up in Ireland study on a cohort of children born in 2008. The child rights framework was applied to identify six dimensions of child deprivation: nutrition, access to healthcare, protection from violence, access to information, leisure, and housing. Combining these dimensions into an index of child deprivation at ages 9 and 13 shows that household income poverty alone is insufficient for identifying deprived children. However, low income remains a statistically significant predictor of child deprivation. Notably, transitions into multidimensional deprivation were more prevalent than transitions into the lowest income bracket over time. Children whose mothers were single or had a lower level of education were more likely to experience multidimensional deprivation at ages 9 and 13. At age 13, girls were at a higher risk of deprivation than boys. Overall, this study highlights the potential of rights-informed multidimensional deprivation indices to identify areas of deprivation that are less dependent on household income. The study indicates the advantages of using child-centred indices over household-level measures when suggesting policy interventions to combat child deprivation in higher-income countries. Multidimensional deprivation Child poverty Child rights Ireland Inequalities Figures Figure 1 1. Introduction Experiencing deprivation during childhood has been linked to poor educational, health, and life satisfaction outcomes (e.g. Dickerson & Popli, 2018 ; Griggs & Walker, 2008 ; Knies, 2022 ; Raphael, 2011 ). However, research conducted using child-centred deprivation indices demonstrates that low household income is not always associated with child deprivation, and conversely that high household income is not always associated with an absence of child deprivation (e.g. Chzhen et al., 2018 ; Main & Bradshaw, 2012 ). The objectives of this study are therefore twofold. First, we develop a child-centred multidimensional deprivation index, using the United Nations Convention on the Rights of the Child (UNCRC) (1989) as a guide at the indicator selection stage. Secondly, we use this index to gain a new perspective on the association between household income and multidimensional child deprivation in higher income countries. This study examines the degree of overlap between children who experience multidimensional deprivation and those who live in low-income households. It uses two waves of data from the Growing Up in Ireland study (GUI) ‘08 Cohort. Ireland provides a suitable high-income research setting, having the second highest GDP per capita in the European Union in 2024 according to Eurostat (2025a). Despite the country’s high-income status, the Irish Economic and Social Research Institute (ESRI) have reported that a fifth of children in Ireland are experiencing material deprivation for two consecutive years (Roantree et al., 2024 , 2025 ). In 2025 they reported that 19.6% of children were in income-poor households, after taking housing costs into account (Roantree et al., 2025 ). Furthermore, Ireland’s current official child poverty measure, proposed by Maître et al. ( 2006 ), relies on a combination of equivalised disposable household income and deprivation measured at household-level. While the current measure provides a strong tool in predicting child-specific deprivation (C. T. Whelan & Maître, 2012 ), its household-based and adult-centric nature has been criticised for its omission of child-specific deprivation items (Kerrins et al., 2011 ; Madden, 2022 ). 2. Literature Review 2.1 Child-Centred Deprivation Indices A large international literature exists on the development of child-centred deprivation indices, representing a variety of methodological and conceptual approaches. Some studies adopt a participatory approach, consulting with children themselves at the indicator development stage. This results in indices that are truly child-centred and child rights-informed. It aligns with the Lundy ( 2007 ) model of meaningful child participation, which asserts the importance of affording children Space, Voice, Audience and Influence in matters affecting them, in accordance with Article 12 of the UNCRC. For instance, Main & Bradshaw ( 2012 ) employed a participatory approach to develop a child deprivation index in England. They conducted focus-groups with children aged 8–14 to determine which deprivation indicators best reflected their necessities in their own view. They found that there were non-deprived children living in income-poor households and vice-versa. Similarly, Sollis ( 2019 ) developed a deprivation index based on ARACY’s (Australian Research Alliance for Children and Youth) nest framework. ARACY identified dimensions of child well-being in Australia by interviewing over 3,700 children, young people, and experts. Sollis ( 2019 ) found that at each point in time, those living in monetary poverty were more likely to be deprived across two or more dimensions. These studies provide strong examples of child-centred indices, since children were consulted in their development. However, many studies cannot work with children directly due to time and resource constraints. As a result, alternative methodologies to elicit child-centred and rights-informed deprivation indices have emerged. One such methodology is UNICEF’s Multiple Overlapping Deprivation Analysis (MODA) framework (de Neubourg et al., 2013 ). The MODA approach separates the child deprivation and poverty, grounding poverty in a lack of income. By using the child as the unit of analysis, MODA considers the position of children as dependents within households and avoids overlooking deprived children who live in households that are not income-poor (UNICEF, 2020 ). Additionally, MODA recommends the use of the UNCRC as a guide in identifying dimensions and indicators of deprivation within the data employed (de Neubourg et al., 2013 ). Several notable studies have employed the MODA framework in their analyses. Chzhen et al. ( 2018 ) used the MODA framework in their analysis of child deprivation among adolescents in 37 European countries. They used the UNCRC to identify six dimensions of deprivation in data from the 2013/14 Health Behaviour in School-aged Children study: nutrition, perceived health, school environment, protection from peer violence, family environment and access to information. They found that while single dimensions of deprivation did not relate closely with national wealth and income inequality, deprivation in three or more dimensions was associated with income inequality. Similarly, Chzhen & Ferrone ( 2017 ) used MODA’s child rights-based approach to develop a deprivation index and operationalise it using Expanded Household Budget Survey data collected in 2011 in Bosnia and Herzegovina. They identified seven dimensions of deprivation and used it to analyse data for children aged 5–15. Household consumption informed the development of a monetary poverty line, rather than income. Findings indicated that children in consumption poor households were more likely to be deprived in every dimension, although the overlap between monetary poverty and multidimensional deprivation was only moderate. Overall, the MODA framework allowed both studies to develop child-centred deprivation indices without directly eliciting children’s opinions. The differing contexts of their studies illustrate the advantage of the UNCRC’s international applicability, regardless of individual countries’ economic statuses. However, it is of note that these studies used cross-sectional data, rather than longitudinal data. Using an early child development framework, Kazakova et al. ( 2024 ) constructed a child-centred and dynamic deprivation index for children in early childhood using longitudinal data from the Étude longitudinale française depuis l’enfance. While the study identified dimensions of deprivation which remained constant over time, indicators changed to capture children's changing needs through early childhood. Kazakova et al. ( 2024 ) notably decided to weight deprivation items. This set the study’s approach aside from other rights-informed methodologies like MODA, which advises against the use of weights to avoid passing value judgements on different aspects of child well-being (de Neubourg et al., 2013 ). They found that around 43% of multidimensionally deprived children were also income poor, on average across all waves, while 23% of income poor children were also deprived. This study was novel in its incorporation of young children’s changing needs over time into a single deprivation measure. However, while its dynamic items are reflective of a child rights perspective, they did not explicitly link them with the UNCRC. 2.2 The Irish Context 2.2.1 The Official Measure and Definition of Poverty in Ireland Ireland’s official measure of poverty, first proposed by Maître et al. ( 2006 ), uses an eleven-item deprivation list in conjunction with equivalised disposable household income. Deprivation items pertain to the household’s ability to afford food, clothing, to keep the home warm, to participate in social events, and other socially perceived necessities. According to the measure, households who cannot afford two or more of the eleven deprivation items are experiencing “enforced deprivation”, while those who have a nominal equivalised disposable income below 60% of the median are “at risk of poverty”. Households who are both at risk of poverty and experiencing enforced deprivation are in “consistent poverty”. Nationally representative data is collected annually by the Central Statistics Office for the Survey on Income and Living Conditions (SILC) and used to determine the proportion of the population falling into each of the three categories. Ireland’s combination of low income and deprivation measures places it among several other high-income countries that rely on household-level measures to gauge poverty levels. Similar measures are used in the UK (Francis-Devine, 2025 ), as well as at the EU level (Eurostat, 2025b). The Irish measure’s use of deprivation items acknowledges the inadequacy of income alone in capturing poverty and recognises the need for a multidimensional approach (Maître et al., 2006 ). However, Kerrins et al. ( 2011 ) argue that the sole inclusion of indicators which are adult-centred and captured at household-level leads to an “imprecise picture of child poverty” (p.7) and the erasure of children’s experiences. They emphasise that the current measure neither provides insight into what items poor children in Ireland lack, nor considers that resources may not be shared equally within households. A wealth of research has demonstrated that resources are often not distributed equally between children in the same households (e.g. Akresh et al., 2012 ; Kaul, 2018 ; Main, 2018 ; Sivadasan & Xu, 2021 ). Furthermore, Kazakova et al. ( 2024 ) suggest that indicators of child deprivation should change over time to remain relevant to children’s changing needs and experiences. The current Irish measure, and household-level measures more broadly, cannot capture these critical aspects of child poverty. In contrast, Whelan & Maître ( 2012 ) argued in favour of the current Irish measure. They analysed 2009 EU-SILC data, which included a list of child-centred deprivation items in addition to the standard household list. They found that just 3 percent of children were deprived according only to the child-specific list and argue that using this measure alone would exclude children who live in deprived households but do not experience child-specific deprivation. However, even EU-SILC child-centred deprivation data is collected from an adult household representative and assumes that if one child is lacking an item in a household, all children in the household lack that item (Guio et al., 2018 ). These deprivation items were intended for use across the EU and therefore are not necessarily relevant to the specific needs and experiences of Irish children. Overall, while the current measure may be a strong predictor of child deprivation according to EU-SILC data, its household and adult-centric nature cannot capture significant elements of child deprivation. 2.2.2 Studies of Child Poverty in Ireland Deprivation indices have long formed part of the poverty literature in Ireland, with Layte et al. ( 2000 ) acknowledging the problematic nature of relying on relative income-poverty measures where living conditions are rapidly changing. Nolan ( 2000 ) employed a list of household deprivation items to compare levels of child deprivation with household income using Irish data collected in 1994 and 1997. He found that low income alone is not sufficient in explaining exclusion due to a lack of resources. Furthermore, Nolan ( 2000 ) acknowledges that while low income and deprivation do not overlap perfectly, sustained low income is a good indicator of need which can help policymakers identify children in need of support. Since the adoption of the official Irish poverty measure, much of the research on child poverty in Ireland has employed SILC or EU-SILC data (e.g. Children’s Rights Alliance, 2024 ; Regan & Maître, 2020 ; Russell et al., 2025 ; C. T. Whelan & Maître, 2012 ). However, some use data from the Growing Up in Ireland study (GUI), a nationally representative longitudinal cohort study of Irish children. Some studies which employ GUI data also gauge deprivation using the 11-item list included in the national measure. Such studies have provided insights into the socioeconomic predictors of child poverty (Maître et al., 2021 ), as well as its impact on children’s mental health (Gibbons et al., 2023 ) and cognitive ability (Li & Chzhen, 2024 ). Meanwhile, Williams et al. ( 2014 ) developed a list of multidimensional indicators of child deprivation distinct from the official list of deprivation items and tested it on data from the ’98 Cohort at age 9. Their study used just one cross-section of GUI data and focused on the debate surrounding the use of multidimensional deprivation indices, and the methods used in operationalising them. Williams et al. ( 2014 ) included household income in their index as a dimension of deprivation. Similarly, Madden ( 2022 ) developed a multidimensional child deprivation index and employed it using GUI data. The index contained just three dimensions and included family income/resources as a dimension of deprivation. Unlike Williams et al. ( 2014 ), however, Madden ( 2022 ) employed three waves of data collected from the ’98 Cohort. 2.3 Theoretical Background This study is underpinned by a relative conceptualisation of poverty. Peter Townsend’s ( 1979 ) defined individuals as poor when: “Their resources are so seriously below those commanded by the average individual that they are, in effect, excluded from ordinary living patterns, customs and activities” (p. 31). He emphasised that an individual’s ability to participate in the society in which they live is determined by the resources available to them. Therefore, poverty is grounded in a lack of resources relative to other members of society. To operationalise this definition, Townsend ( 1979 ) employed both deprivation indices and income measures. He included separate deprivation items for children and adults, and items which are captured at both individual and household levels. Townsend’s work therefore acknowledges that children’s needs differ from those of adults, and that poverty is characterised by a lack of resources extending beyond finances alone. This study conceptualises deprivation as multidimensional and argues that it is best measured at the individual level. De Neubourg et al. ( 2013 ) recognise that capturing child poverty at the individual child level makes children’s specific needs visible. Using the UNCRC as a guide at indicator selection allows for the identification of these needs, while also acknowledging that poverty denies children their internationally enshrined rights (Gordon et al., 2003 ). Employing the UNCRC in indicator development also offers two further advantages. Firstly, De Neubourg et al. ( 2013 ) note that the UNCRC is useful in constructing indicators which are important to any child’s development, regardless of their socio-economic status, culture, or country of residence. Therefore, the child-rights approach allows for the selection of context-specific deprivation indicators, in line with a relative conceptualisation of poverty, that remain grounded in the needs of all children, regardless of context. Secondly, since the UNCRC aims to protect children in all aspects of their lives, it elicits ecological and multidimensional concepts of child well-being (Ben-Arieh, 2008 ). It therefore allows for the identification of children’s needs across all dimensions of their lives. 3. Methodology 3.1 Growing Up in Ireland Data and Sample This study uses data from the GUI ’08 study, a nationally representative cohort study of children born in Ireland in 2007/8. The GUI’s provision of extensive information on cohort members and their families makes it well-suited to the study of multidimensional child deprivation. The study includes questions on different areas of children’s lives, many of which reflect rights enshrined in the UNCRC. The study includes interviews with primary and secondary caregivers, teachers, and the children themselves. For brevity, this text will refer to primary caregivers as mothers. We use data from Waves 5 (2017/18, age 9) and 6 (2021/22, age 13) of the GUI ’08 study. These waves encompass the most recently available longitudinal data on children in Ireland, capturing important educational transitions (i.e. from primary to secondary school) and developmental changes (from middle childhood to adolescence). Furthermore, Wave 6 took place amid the Covid-19 pandemic, a period of economic hardship and psychological strain for many people (Madden, 2024 ; Smyth & Murray, 2022 ). Initially, the GUI ’08 study included over 11,000 households. Participants were randomly selected from the Child Benefit Register. Wave 5 comprised 8,032 children, while Wave 6 included 6,655 children. This study focuses on the subset of children who participated in both waves. We used the longitudinal analysis weight provided in the GUI researcher microdata files to statistically account for non-random panel attrition and systematic non-response. We then excluded cases with missing data for any of the key variables to be used in our analyses, amounting to approximately 10% (614 cases). Our analytic sample consists of 5,442 children, corresponding to 10,884 observations. 3.2 Indicators and Dimensions Table 1 shows the deprivation indicators selected at each wave, categorised by dimension. It includes the deprivation threshold used and respondent from whom responses were collected for each indicator. Using the UNCRC as a guide, we identify six dimensions in the data: nutrition, access to healthcare, protection from violence, access to information, leisure and housing. Since de Neubourg (2013) classifies children aged 5–16 as falling into the same life-cycle stage (school-age), we aim to use the same indicators of deprivation for children at ages 9 and 13. However, inconsistencies in the variables available at each wave mean indicators are not identical between waves. Each dimension is composed of exactly two indicators. We take the union approach, meaning that if a child is deprived according to at least one of two indicators in a dimension they are considered deprived in that dimension. Chzhen et al. ( 2018 ) acknowledge that the union approach is consistent with a child rights framework, given that an absence of deprivation in one indicator in a dimension does not compensate for the presence of deprivation in another. Each indicator and dimension is coded so that “1” indicates deprivation and “0” indicates a lack of deprivation. We define the deprivation rate as the percentage of children deprived in at least one dimension, and the multidimensional deprivation rate as the percentage of children deprived in two or more dimensions. 3.2.1 Nutrition Article 24 of the UNCRC calls for access to “adequate nutritious foods”. The role of nutrition in child development for school-aged children is widely acknowledged. Florence et al. ( 2008 ) found that schoolchildren with a lower quality diet were significantly more likely to perform poorly academically. Equally, breakfast is understood as vital to adequate nutrition. A systematic literature review by Adolphus et al. ( 2016 ) found that for children, breakfast consumption was associated with better performance on tasks that required attention, executive function and memory. We classify children who do not consume fruit and vegetables at least once a day as deprived. GUI survey questions surrounding children’s food consumption vary slightly between Waves 5 and 6 (see Table 1 ). At age 9, we combined three variables regarding consumption of fruit and vegetables in the 24 hours before the interview into one dichotomous indicator variable: a child is deprived if they have consumed no fruit, cooked vegetables, or raw vegetables in the last 24 hours. At 13, a child as deprived if they usually consume no fruit or vegetables in a day. We classify children who do not usually eat before school as deprived of breakfast at age 9, and children who have breakfast less than once a week or never as deprived at age 13. It is notable that at age 9 the respondent for the breakfast indicator was the child’s mother, while at 13 the respondent was the child. Additionally, breakfast is the most skipped meal, particularly among adolescents (Adolphus et al., 2016 ). Therefore, particularly at 13, children may choose to skip breakfast. Furthermore, Pastore et al. ( 1996 ) found that girls were significantly more likely to skip breakfast than boys. This finding is mirrored in the sample data at age 13, where 8% of girls report eating breakfast “Less than once a week/Never”, compared to 3% of boys (Table 2 ). Nonetheless, since breakfast skipping has been associated with health-compromising behaviours in adolescents (Keski-Rahkonen et al., 2003 ), breakfast remains a valid indicator of child deprivation. 3.2.2 Access to Healthcare Access to healthcare is crucial to child wellbeing. Article 24 of the UNCRC recognises the right of the child to access “facilities for the treatment of illness and rehabilitation of health”. Crowley ( 2018 ) notes that dental neglect is recognised as a child protection issue, yet their survey found that 62% of Irish public healthcare service dentists reported seeing neglected dentitions at least once a week in their clinics. We classify a child as deprived if their mother reports that they never (or never/almost never at 13) visit the dentist. Although GUI collects data on how frequently mothers consult with a general practitioner (GP) on their child’s health, 48% (at age 9) and 62% (at age 13) said that they had not consulted with a GP over the last year. As GP visits are more common among those with symptoms, a child’s access to healthcare services may be more accurately reflected by their possession of a means-tested medical card (entitling them to free healthcare) or private insurance coverage. Connolly and Wren ( 2017 ) found that, in Ireland, people without free primary care or private insurance were more likely to report an unmet healthcare need. We created an indicator variable where a child is considered deprived if they possess neither a medical card nor private insurance. 3.2.3 Protection from Violence Protection from violence is enshrined in Article 19 of the UNCRC. Mills et al. ( 2004 ) found that bullying was significantly associated with depression and suicidal ideation in their analysis of data collected from Irish schoolchildren. Similarly, Callaghan et al. ( 2019 ) found that victims of bullying were significantly more likely to report low life satisfaction, poor health, and psychological and somatic symptoms. We consider children who have recently experienced bullying as deprived. Although the timeframe of the indicators varies between the ages 9 and 13, i.e. in the last year vs in the last 3 months, both capture a child’s recent experience of bullying. The second indicator in this dimension relates to parental discipline. UNICEF ( 2025 ) refers to shouting or yelling at a child as a form of psychological aggression. Similarly, Miller-Perrin et al. ( 2009 ) suggest that psychological aggression may be more important than physical violence toward children in predicting psychological outcomes. We classify a child as deprived if their mother regularly/always (age 9) or always (age 13) shouts at them when they misbehave. The respondent for this indicator was the mother at age 9 but the child at age 13. 3.2.4 Access to Information The right to “seek, receive and impart information” is enshrined in Article 13 of the UNCRC. Similarly, Article 17 recognises the right of the child to access “information […] from a diversity of national and international sources”. Internet access represents an important facet of access to information. Hurwitz & Schmitt ( 2020 ) found that middle childhood digital skill (measured by parent’s rating of children’s ability to find information on the web at age 11) was significantly positively associated with school performance. Internet access was also of significant value for children in the sample at age 13, since the educational repercussions of the Covid-19 pandemic were exacerbated by a lack of internet access (Coleman, 2021 ). We deem a child deprived if they do not have access to the internet at home via an electronic device. The second indicator of access to information is access to age-appropriate books. It is a robust predictor of students’ academic language comprehension (Heppt et al., 2022 ). A child is therefore classified as deprived if their mother reports that they have 0 to 10 age-appropriate books at home. It is of note that at age 9 the variable we employ mentions library books, while at 13 it does not. Nonetheless, responses to both questions reflect a lack of books at home. 3.2.5 Leisure Article 31 of the UNCRC recognises the right of the child to rest and leisure, and to participate in “recreational activities appropriate to the age of the child”. The benefits of extracurricular activities for children are widely acknowledged. Gerber ( 1996 ) found that it was positively related to academic achievement. Furthermore, O’Donnell et al. ( 2024 ) found that for adolescents, participation in extracurricular activities can promote wellbeing, with those from lower socioeconomic backgrounds experiencing the greatest positive effects. We classify a child as deprived if they do not participate in any extracurricular activities. The second indicator in the leisure dimension is access to green space. McCormick ( 2017 ) found that it was associated with a range of benefits for children’s mental well-being, including improved overall mental-health and cognitive development. The indicators we employ for access to green space differ somewhat between the two waves, but they capture the availability of parks and play spaces in the local area (see Table 1 ). 3.2.6 Housing Article 27 of the UNCRC recognises the child’s right to “a standard of living adequate for the child’s […] development”, explicitly mentioning that State Parties should provide material assistance with “housing”. The UNCRC thereby recognises that adequate housing is essential for children’s development and well-being. Although this dimension is by default measured at household-level rather than at the child level, we argue its inclusion is important due to both its recognition in the UNCRC and Ireland’s ongoing housing crisis. An extensive review found that living in damp accommodation was linked to a range of physical health conditions in children including asthma and eczema (Hock et al., 2024 ). The first indicator of housing conditions therefore relates to poor physical conditions in the home such as damp. Reynolds-Salmon et al. ( 2024 ) found that children’s locomotor and personal-social development are negatively affected by living in a crowded home. As such, the second indicator of housing conditions classifies a child as deprived if their mother reports their home to be too small. Table 1 Deprivation Dimensions and Indicators Age 9 (Wave 5) Age 13 (Wave 6) Dimension Indicator Question(s) Deprivation Threshold Resp-ondent Indicator Question(s) Deprivation Threshold Resp-ondent Nutrition In the last 24 hours has Child had fresh fruit? / In the last 24 hours has Child had cooked vegetables? / In the last 24 hours has Child had raw vegetables or salad? Deprived if answered “Not at all” to each question. M How many portions of fruit or vegetables would Child usually have in a day? Deprived if answered “None.” M Does child usually have something to eat before going to school? Deprived if answered “No.” M How often do you have breakfast (either at home or at school)? Deprived if answered “Less than once a week/Never.” C Access to Healthcare Which of the following best describes how regularly child visits the dentist? Deprived if answered “Never/ Almost Never.” M Which of the following best describes how regularly Child visits the dentist? Deprived if answered “Never.” M Is child covered by a medical card? / Is child covered by private medical insurance? Deprived if answered “No” to both questions M Is Child covered by a medical card? / Is Child covered by private medical insurance? Deprived if answered “No” to both questions M Protection from Violence Has child been victim of bullying in last year? Deprived if answered “Yes.” M Has child been a victim of bullying in last 3 months? Deprived if answered “Yes.” M How often do you do the following when child misbehaves? - Shout or yell at him/her? Deprived if answered “Regularly/ Always”. M When you misbehave, how often do your parents shout at you? Deprived if answered “Always”. C Table 1 Continued Access to Information Do you have a computer, iPad, smartphone, or other gadget at home that you can use to access the internet? Deprived if answered “No.” C Does Study Child have access to the internet through a smartphone, tablet, laptop or other computer? Deprived if answered “No.” M About how many children’s books does child have access to in your home now, including any library books? Would you estimate: Deprived if answered “None”, or “Less than 10.” M How many books (including e-books) does Study Child have access to in the home? Deprived if answered “None”, or “1 to 10.” M Leisure During an average week, does child participate in… Team sports / Individual sports / Drama classes / Arts and craft / Youth club / Religious club/group/ Music/dance / Scouts/guides/ boy's brigade/ girl's brigade / Other activities? Deprived if answered “No” to all. M How often do you play sports with a coach or instructor, or as part of an organised team? / How often do you take part in dance lessons? / How often do you take part in art, crafts, drama or music lessons, clubs or rehearsals? / How often do you take part in clubs or groups (e.g. Guides, Scouts, youth club, community, church groups)? Deprived if answered “Less often or never” to all. C There are safe parks, playgrounds and play spaces in this area. Deprived if answered “Strongly disagree.” M Is there a park, beach or green space within 2 kilometres of home Deprived if answered “No.” M Housing Accommodation: Poor conditions in the home (damp, drafts, leaks etc.) Deprived if answered “Yes.” M Leaking roof/ damp walls /rot in windows or door frames - Problems with your accommodation Deprived if answered “Yes.” M Accommodation: Too small Deprived if answered “Yes.” M Too small, not enough space - Problems with your accommodation Deprived if answered “Yes.” M Note : The above table details the indicator questions, deprivation criteria, and respondent used for each wave of GUI data. Respondent abbreviations are as follows: M = Mother and C = Child. Data : Growing Up in Ireland Survey ’08 Cohort, 2017/18 and 2021/22. 3.3 Data Analysis All data analyses were performed using STATA Version 18 (StataCorp LLC, College Station, Texas, USA). All analyses were weighted using the longitudinal weight provided with GUI data. First, we tabulated the shares of children deprived on each indicator and dimension at 9 and 13. Then we counted the number of dimensions each child was deprived on and created binary deprivation and multidimensional deprivation variables which return “1” to indicate deprivation/multidimensional deprivation and “0” to indicate lack of deprivation were generated for ages 9 and 13. Multidimensional deprivation is defined as being deprived on two or more dimensions. We then estimated deprivation rates at each age. Next, we analysed the relationship between income and multidimensional deprivation at each age. We used income data provided by GUI in the form of equivalised net annual household income quintiles. This allowed for meaningful comparison between five broad household income categories, considering household size and structure. In the sample there were 426 missing income values at age 9, and 505 at age 13. Rather than excluding these observations, we recoded missing values into a category and included them in our analysis to maximise the analytic sample. We first examined the relationship between household income and deprivation by cross-tabulating income quintiles with multidimensional deprivation status and determining the shares of multidimensionally deprived children within each quintile for each wave. Next, we ran logistic regression models, first regressing multidimensional deprivation status on equivalised household income quintile. We then added controls for child’s gender, maternal age, couple family vs lone parent family, mother’s highest level of educational attainment, and mother’s employment situation. Appendix A reports the distribution of independent variables used in logistic regression. Findings are reported as average marginal effects to allow for comparison between models. Finally, we analysed transition probabilities to gauge mobility into and out of multidimensional deprivation, and the lowest income quintile, over time. 4. Findings 4.1 Deprivation Across Indicators and Dimensions 4.1.1 Deprivation Across Indicators Table 2 reports the percentage of children deprived on each indicator at each wave. At age 9, one in five children did not possess a medical card or private health insurance (21%). A similar proportion (21%) had a recent experience of bullying. In contrast, just 1% of children were regularly/always shouted at by their mothers. However, the respondent for this question was the child’s mother. Small shares of children also went without breakfast (2%) or lived in poor physical conditions (2%) at age 9. Aged 13, children were most likely to be deprived of a medical card or private health insurance, with over one fifth (22%) of children not possessing either. A large share (17%) of children also had limited access to books at home at 13. The indicators on which children were least like to be deprived at 13 were dentist visits (0.06%) and internet access at home (0.06%). Table 2 Share (%) of Children Deprived on Each Indicator. Indicator Deprived at age 9 (%) Deprived at age 13 (%) Fruit and vegetables 6.50 4.29 Breakfast 2.26 5.56 Dentist visits 5.63 0.06 Medical card/private health insurance 20.78 22.43 Recent experience of bullying 21.30 9.80 Mother shouts when child misbehaves 1.37 5.88 Internet access via a gadget at home 8.16 0.06 Books at home 8.83 16.92 Participation in extracurriculars 8.51 14.26 Access to green space 8.33 8.51 Physical condition of home 2.26 8.07 Home sufficiently spacious 10.35 13.18 Note: N= 5,442. Data was collected in 2017/18 for children at age 9 and 2021/22 for children at age 13. Results are weighted using the longitudinal survey weight provided with GUI data. Data : Growing Up in Ireland Survey ’08 Cohort, 2017/18 (Wave 5) and 2021/22 (Wave 6). 4.1.2 Deprivation Across Dimensions Table 3 reports the percentage of children deprived on each dimension at each wave. At 9, the highest rate of deprivation was observed on access to healthcare, with just over a quarter of children (25%) lacking access. A similarly high rate was observed on protection from violence (22%). Children were least likely to be deprived on nutrition, with just 8% of children deprived on this dimension at 9. At age 13, slightly under a quarter (23%) of children had limited access to healthcare. A similarly high rate of deprivation was observed on leisure at age 13, with just over a fifth (21%) of children experiencing deprivation on this dimension. Almost one fifth (19%) of children were in inadequate accommodation at this wave. As at age 9, children were least likely to experience nutritional deprivation at 13, with 9% of children deprived on this dimension. Between waves, changes occurred in the prevalence of deprivation in some dimensions. The rate of deprivation in protection from violence decreased by approximately 7% between waves. Meanwhile, the proportions of children experiencing deprivation in the leisure and housing dimensions were greater at age 13 than at age 9. The prevalence of deprivation in the nutrition, access to healthcare, and access to information dimensions remained similar between waves. However, since the survey items used to construct indicators varied between waves, we do not know whether these represent real changes or are artefacts of measurement. Table 3 Share (%) of Children Deprived on Each Dimension. Dimension Deprived at age 9 (%) Deprived at age 13 (%) Nutrition 8.47 8.97 Access to Healthcare 25.12 22.85 Protection from Violence 22.11 14.58 Access to Information 16.33 17.39 Leisure 15.74 21.38 Housing 10.94 18.65 Note: N= 5,442. Data was collected in 2017/18 for children at age 9 and 2021/22 for children at age 13. Results are weighted using the longitudinal survey weight provided with GUI data. Data : Growing Up in Ireland Survey ’08 Cohort, 2017/18 (Wave 5) and 2021/22 (Wave 6). 4.1.3 Multidimensional Deprivation Figure 1 shows the distribution of the number of dimensions children are deprived in at each wave. No child experienced deprivation on all 6 dimensions at ages 9 or 13. At both ages, comparable shares of children experienced no deprivation (36% at 9 and 34% at 13) or just one dimension (38% at 9 and 37% at 13). The multidimensional deprivation rate was 26% at age 9 and 29% at age 13. In the next section, we direct our attention to multidimensional rather than single-dimension deprivation to capture the intensity of deprivation experienced. 4.2 Cross-sectional analysis of multidimensional deprivation and household income 4.2.1 Distribution of multidimensional deprivation across income quintiles. First, we report on the distribution of multidimensional deprivation across household income quintiles at ages 9 and 13. Table 4 documents crosstabulations of equivalised household income quintile with multidimensional deprivation status at each wave. The similar distribution of the sample across income quintiles at both ages suggests that missing values were relatively evenly distributed across income quintiles. However, the analytic sample may be slightly skewed towards households of a higher socioeconomic status, since the lowest income quintile is slightly underrepresented in both waves. Results presented in Table 4 suggest that low income and multidimensional deprivation do not overlap perfectly at ages 9 or 13. At both ages, multidimensional deprivation was not concentrated in any one income quintile, although the lowest shares of deprived children lived in households whose income fell into the highest two income quintiles. At age 9, 17% of children were multidimensionally deprived but not in the lowest income quintile. Similarly, one fifth of children experienced multidimensionally deprivation at 13 but were not in the lowest income quintile. Of those in the lowest income quintile, 63% were not multidimensionally deprived at age 9, and 64% at age 13. Overall, although smaller shares of children in higher-income households experienced multidimensional deprivation, not all multidimensionally deprived children lived in low-income households. Table 4 Share (%) of Multidimensionally Deprived Children by Income Quintile. Age 9 Age 13 Income quintile Deprived (%) Not Deprived (%) Total (%) Deprived (%) Not Deprived (%) Total (%) 1 st 6.29 10.74 17.04 6.31 11.1 17.41 2 nd 5.95 13.6 19.55 6.38 11.85 18.23 3 rd 4.62 13.91 18.52 5.65 12.4 18.05 4 th 4.01 14.26 18.27 4.75 13.11 17.86 5 th 2.55 14.55 17.11 3.08 15.07 18.15 Missing 2.29 7.23 9.52 2.63 7.67 10.30 Total (%) 25.71 74.29 100 28.8 71.2 100 Note: N =5,442. 1 st income quintile refers to the lowest equivalised net income quintile and so forth. Data was collected in 2017/18 for children at age 9 and 2021/22 for children at age 13. Results are weighted using the longitudinal survey weight provided with GUI data. Data : Growing Up in Ireland Survey ’08 Cohort, 2017/18 (Wave 5) and 2021/22 (Wave 6). 4.2.2 Logistic Regression of Multidimensional Deprivation Status on Income Quintile Table 5 reports average marginal effects from logistic regression of multidimensional deprivation status on equivalised household income quintile. Regression coefficients are reported in Appendix B. Logistic regression was performed with and without socio-demographic controls. Logistic regression of multidimensional deprivation status on equivalised household income quintile, excluding sociodemographic controls, allowed us to examine the degree of overlap between low income and multidimensional deprivation. At age 9, those in the lowest income quintile were 22 percentage points (p<0.001) more likely to experience multidimensional deprivation on average, compared to those in the highest quintile, all else being equal. Similarly, everything else being equal, the probability of multidimensional deprivation was 16 points higher (p<0.001), on average, for children in the second-lowest income quintile relative to those in the highest. There were statistically significant, although smaller, differences between the third and fourth income quintiles and the top quintile. This suggests a strong association between low household income and multidimensional deprivation. However, the overlap between multidimensional deprivation and low income was imperfect. Similar average marginal effects were observed at 13, when not controlling for sociodemographic predictors. As at age 9, the largest difference (19 points, p<0.001) was observed between the lowest and highest income quintile. However, there was just one point decrease (from 19 points to 18 points), on average, between the first and second income quintiles in the probability of being multidimensionally deprived relative to the highest income quintile, everything else held constant. Therefore, on average, there was less variation in the probability of experiencing multidimensional deprivation relative to the highest income quintile between the poorest and second poorest income quintiles at age 13 than at age 9, everything else being held constant. As at age 9, the size of average marginal effects decreased as income quintile increased at 13, and all average marginal effects were statistically significant. Like at age 9, all else being equal, while those in lower income quintiles had a higher probability of experiencing deprivation, on average, at 13 the overlap between low income and multidimensional deprivation was imperfect. Average marginal effects from logistic regression of multidimensional deprivation status on equivalised household income quintile including sociodemographic controls are also reported in Table 5. At age 9, all else being equal, after including controls, being in a higher income quintile was still associated with a lower probability of experiencing multidimensional deprivation, on average, relative to the richest quintile. However, overall, the size and statistical significance of average marginal effects decreased in income quintile, on average, after controlling for sociodemographic predictors, everything else held constant. The average marginal effect associated with being in the fourth income quintile was not statistically significant. All else equal, those in the lowest income quintile had a 10 point (p<0.01) higher probability of experiencing multidimensional deprivation, on average, than those in the highest quintile. Everything being held constant, those in the lowest income quintile therefore remained the most at risk of experiencing multidimensional deprivation, on average, relative to those in the highest quintile. At age 13, including controls also resulted in reduced, less statistically significant average marginal effects in income quintile. However, unlike at age 9, all else being equal, the magnitude of average marginal effects was similar across income quintiles, on average, relative to the highest income quintile. The largest differences were observed for the first and second income quintiles, with children in these groups having, on average, a 10 point (p<0.01) greater probability of experiencing multidimensional deprivation compared to those in the richest quintile, all else being equal. Meanwhile children in the third quintile had a 9 point (p<0.01) greater probability of multidimensional deprivation, on average, than those in the highest income bracket, everything else being constant. Therefore, on average, being in a lower income quintile was still associated with a higher probability of experiencing multidimensional deprivation than being in the highest quintile, after controlling for sociodemographic predictors at age 13. However, since the size of average marginal effects associated with each income quintile did not greatly decrease as income quintile increased, the probability of multidimensional deprivation did not decline sharply between income quintiles when controlling for predictors. Statistically significant differences were observed for maternal educational attainment and family status at 9 and 13. All else being constant, the probability of being multidimensionally deprived was greater for children whose mother had lower levels of educational attainment, relative to those whose mother had a postgraduate qualification, on average. Similarly, those whose mothers were single had a statistically significantly higher probability of being multidimensionally deprived, on average, all else being equal. At age 13, average marginal effects suggested that being a girl, having a younger mother, or a mother who was not in work, were also statistically significantly associated with a greater probability of experiencing multidimensional deprivation on average, everything else being held constant. Table 5 Average marginal effects from logistic regression of multidimensional deprivation status on income quintile. (1) (2) Age 9 Age 13 Age 9 Age 13 Income quintile (ref: 5 th quintile) 1 st 0.22*** 0.19*** 0.10** 0.10** 2 nd 0.16*** 0.18*** 0.08** 0.10** 3 rd 0.10*** 0.14*** 0.05* 0.09** 4 th 0.07** 0.10*** 0.05 0.07** Missing 0.09** 0.09** 0.05 0.05 Child’s gender (ref: Male) Female -0.02 0.04* Mother’s age group (ref: 50 or older) 20-39 years 0.08 0.17*** 40-49 years -0.02 0.04* Family status (ref: Couple family) Lone parent family 0.09** 0.06* Mother’s highest educational level (ref: Postgraduate) School 0.21*** 0.21*** Higher Education 0.07*** 0.11*** Mother’s employment status (ref: Employed) Studying/Training 0 0.10 Not in work -0.02 -0.05* N 5,442 5,442 5,442 5,442 Note: * p<0.05, ** p<0.01, *** p<0.001. The dependent variable in logistic regression (1) without controls and (2) with controls is a binary indicator variable for multidimensional deprivation status. Income category “ 1 s t ” denotes the lowest income quintile. Reference categories are included in brackets. Results are weighted using the longitudinal survey weight provided with GUI data. Data was collected in 2017/18 for children at age 9 and 2021/22 for children at age 13. Data : Growing Up in Ireland Survey ’08 Cohort, 2017/18 (Wave 5) and 2021/22 (Wave 6). 4.3 Income and Multidimensional Deprivation Dynamics Finally, since this study used longitudinal data, we examine transition probabilities into and out of multidimensional deprivation and the lowest income quintile over time. At age 9, 26% of children were multidimensionally deprived, and at 13, 29% were multidimensionally deprived. Children who were multidimensionally deprived at age 9 had a 51% chance of not being multidimensionally deprived at 13. Therefore, the probability of escaping multidimensional deprivation about the same as the probability of remaining deprived. However, those who were not multidimensionally deprived at 9 had a 22% chance of becoming deprived at 13. Almost 80% of children who were not multidimensionally deprived at age 9 remained non-deprived. Therefore, children who were not deprived at 9 had a much lower probability of experiencing deprivation at age 13 compared to those who experienced deprivation at 9. Meanwhile, children whose household income did not fall into the lowest quintile at age 9 had a 10% chance of entering this income bracket at age 13. Those who were in the lowest income quintile at age 9 had a 40% chance of being in a higher income quintile at 13, however just over half (51%) remained in the lowest income bracket. As such, children who lived in households whose equivalised net income fell into the lowest quintile were much more likely to remain in this quintile, than those in higher income brackets were to fall into the lowest quintile. 5. Discussion This study demonstrates the development of a child-centred multidimensional deprivation index using data for ages 9 and 13 from GUI’s ’08 cohort. Unlike other studies of child deprivation in Ireland, which have employed the national household-based measure of deprivation (e.g. Gibbons et al., 2023 ; Maître et al., 2021 ), this study’s measure operates at the individual child level. The child-rights approach elicits a deprivation index which is representative of children’s needs across several facets of their lives, while also representing their rights as enshrined in the UNCRC. The use of the UNCRC as a guide, and exclusion of income as a dimension of deprivation, sets this study aside from previous Irish studies using GUI data by Williams et al. ( 2014 ) and Madden ( 2022 ). Six dimensions of deprivation were identified: nutrition, access to healthcare, protection from violence, access to information, leisure, and housing. At both age 9 and 13, over one fifth of children did not have either private health insurance or a medical card. Although the high rates of deprivation observed on this indicator inflated deprivation rates, its inclusion was important given both the literature on its importance in meeting healthcare needs in Ireland (Connolly & Wren, 2017 ) and the recognition of access to healthcare in the UNCRC. The large shares of children deprived on this indicator at each wave underline a need for the introduction of free GP care for all children in Ireland. Since August 2023, all children under age 8 in Ireland have been entitled to a free GP visit card (Citizens Information, 2023 ). The findings of this study suggest that the inclusion of older children in this scheme would be highly beneficial. A large share of children were deprived on the bullying indicator (21%) at age 9. A seemingly smaller share of children had a recent experience of bullying at age 13 (10%), however this apparent change is likely reflective of the change in indicator timeframe between waves (see Table 1 ). Equally, it could be a result of the fact that adolescents often do not disclose instances of bullying or harassment (deLara, 2012 ). Nonetheless, deprivation rates at both 9 and 13 point toward the need for anti-bullying interventions in schools. A new child rights-informed anti-bullying initiative called Bí Cineálta comes into effect this 2025/26 school year in Ireland (Department of Education, 2024 ; Smyth & Darmody, 2025 ). The initiative centres the fostering of empathetic and inclusive environments within both primary and secondary schools. While its impact remains to be seen, its introduction is welcome given the particularly high rates of bullying observed amongst 9-year-olds in 2017/18 in this study. At 13 there were much higher shares of children deprived on the leisure and housing dimensions than at age 9. The increased exclusion from leisure observed at 13 could be reflective of the higher costs associated with meeting teenagers’ needs (Thornton et al., 2025 ). Meanwhile, the decline in housing conditions between waves could be driven by overcrowding, arising from the addition of new siblings to households. However, differences between deprivation indicators used at each wave mean we cannot know whether these findings represent real change over time or are artefacts of measurement. Similarly, differing indicators mean we cannot be certain if changes in the multidimensional deprivation rate between waves represent real shifts over time. The rate varied only slightly between waves (26% at age 9, 29% at age 13). Nonetheless, at both 9 and 13, over one quarter of children lacked two or more resources important to their wellbeing. This finding is stark, regardless of the figures’ comparability over time. Descriptive analysis demonstrated that the overlap between multidimensional deprivation and low household income was imperfect at both ages 9 and 13. This is in line with findings from previous Irish studies of child deprivation (e.g. Nolan, 2000 ; C. T. Whelan & Maître, 2012 ). Less variation in multidimensional deprivation rates within the lowest three income quintiles was observed at age 13 compared to at age 9. While levels of multidimensional deprivation decreased as income increased, deprivation rates did not decline sharply between any two income quintiles at either point in time. These results differ from findings of previous Irish studies. For instance, Whelan & Maître ( 2012 )found that being in the lowest income quintile was associated with a much greater risk of childhood deprivation (according to EU-SILC data) and basic deprivation (according to the Irish national measure). This suggests that rights-informed multidimensional deprivation measures may highlight areas of deprivation which are less dependent on household income, while remaining grounded in a lack of resources and opportunities. Logistic regression of multidimensional deprivation status on income quintile demonstrated that household income was a significant predictor of multidimensional deprivation. Therefore, while children experiencing multidimensional deprivation do not directly overlap with those who live in low-income households, income remains an important predictor of deprivation. Including controls in our model lead to decreased statistical significance and magnitude for average marginal effects in income quintile. At both 9 and 13, family status and maternal educational attainment were statistically significant predictors of deprivation. This aligns with Maître et al.’s ( 2021 ) findings. While at age 9, average marginal effects still decreased as income quintile increased, this pattern was not observed at age 13. While at age 9, multidimensional deprivation was more concentrated in lower income quintiles when controlling for sociodemographic predictors, this was not true at age 13. It may be a result of restrictions imposed during the Covid-19 pandemic. Restrictions impacted all areas of life for children in Ireland, irrespective of their families’ financial situations. For instance, restrictions affected all children’s ability to participate in extracurricular activities. While those in deprived areas were disproportionately affected by the pandemic (Whelan et al., 2023 ), its wider impact may explain the more even distribution of multidimensional deprivation at age 13. Further analysis is required to prove this hypothesis, however. Overall, while household income is a significant predictor of multidimensional deprivation in Ireland, the overlap between low household income and multidimensional deprivation is imperfect. As such, household income alone cannot identify multidimensionally deprived children. Our results align with findings from other studies using child-centred and rights-informed multidimensional deprivation measures in high-income national contexts (e.g. Chzhen et al., 2018 ; Kazakova et al., 2024 ; Sollis, 2019 ). At age 13, the study child’s gender, their family status, and their mother’s age, highest level of educational attainment, and employment status were all significant predictors of deprivation. Girls were at a greater risk of multidimensional deprivation than boys. This finding aligns with Chzhen et al.’s ( 2018 ) study of deprivation among adolescents in higher income countries, which found that girls had a higher risk of experiencing multidimensional deprivation in most countries included in the study. We can speculate as to why this was the case, although further analysis is required to prove the underlying reasons for gender differences. As discussed, girls were more likely to go without breakfast than boys (see section 3.2.1 ). Girls may also have been less likely to participate in extracurriculars than boys. For example, Woods et al. ( 2023 ) found that at post-primary level, girls in Ireland participated in sport less than boys. They also may have been more likely to report experience of bullying, in line Chzhen et al.’s ( 2018 ) findings. That girls were more likely to be deprived at 13 is an important finding from a child rights perspective, considering Article 2 of the UNCRC states that state parties shall “respect and ensure the rights set forth […] irrespective of the child’s […] sex”. This finding also points toward a need for further research into the divergent trajectories during adolescence that may explain these gendered wellbeing inequalities. Moreover, it highlights the importance of child-centred measures of deprivation in capturing between child differences that are lost in household-level measures. There were transitions both into and out of the lowest income quintile and multidimensional deprivation over time. Those who experienced deprivation at age 9 were more likely to continue to experience it at 13. Similarly, children in the lowest income bracket in the first wave were more likely to remain there, than children in other income brackets were to end up in the lowest bracket. These findings align with those from previous Irish studies. For instance, Sprong et al. ( 2023 ) found that in Ireland, those with a previous experience of material deprivation were more likely to remain deprived. It is also acknowledged in the international literature that those in lower income brackets face greater levels of economic instability, creating considerable barriers to upward economic mobility (e.g. Gangl, 2005 ). Nonetheless, children who were not deprived at age 9 faced a greater than 20% probability of experiencing deprivation at age 13. This highlights the potential effectiveness of preventative interventions, as well as targeted measures to meet immediate need. It is also possible that this is reflective of the wider effects of the Covid-19 pandemic, as discussed. This study points toward a number of policy implications. The deprivation index used in this study underlines the advantages of using measures which centre the child as the unit of analysis in high income national contexts. Child-centred measures capture between-child differences that household-level measures miss, and identify the specific items that deprived children lack. Supplementing existing household deprivation and income measures with child-specific deprivation indices at the national level would provide policy makers with comprehensive information on children’s personal and household circumstances. This data could be used to better target policy interventions in combatting and preventing child poverty and deprivation. Secondly, this study’s finding that not all multidimensionally deprived children live in low income households points towards the potential benefits of non-monetary policy interventions in Ireland and similar contexts. However, it is important to acknowledge that cash transfers are vital in reducing rates of child poverty and deprivation (Doorley et al., 2025 ). While non-monetary interventions cannot replace cash transfers, they may help meet children’s immediate needs as identified by child-centred deprivation indices. The dimensions of deprivation identified in this study highlight facets of child wellbeing in which non-monetary interventions could be effective in Ireland. For instance, as mentioned, the expansion of access to GP visit cards to all children would improve access to healthcare. Similarly, since girls were more likely to be deprived on the breakfast indicator at 13, the introduction of nutritional education programmes in secondary schools could help to bridge the gender divide in deprivation on this indicator. Keski-Rahkonen et al. ( 2003 ) found that breakfast skipping could be reduced with increased nutritional knowledge. Furthermore, while there is a well-documented need for greater supply of housing, and specifically affordable housing, in Ireland (Social Justice Ireland, 2024), other interventions could help improve accommodation conditions. For instance, increased legal oversight of rental accommodation quality, as well as more efficient services through which renters’ complaints can be rectified, would significantly improve the immediate need for better housing conditions. 6. Limitations This study has several limitations. Firstly, our approach to developing a child-centred deprivation index would be improved by ensuring all deprivation indicators emerged from survey questions answered by children. However, due to data availability and changes in respondent to survey items between waves of data collection this was not possible. Moreover, consulting with children to ensure that deprivation items reflected what they considered necessities would have enhanced our approach. Similar methods have been successfully employed by Main & Bradshaw ( 2012 ) and Sollis ( 2019 ). Since this was not possible due to time and resource constraints, using the UNCRC as a guide at the indicator selection stage allowed us to create a child rights-based index without eliciting children’s views. Secondly, since we selected deprivation items from existing GUI data, data availability limited our choice of possible items. For instance, large amounts of missing data in school principal-reported survey items informed our decision not to include deprivation items relating to children’s school environment. Additionally, there were several disparities in survey items used in the construction of indicators between waves of data collection, as detailed in the methodology section. While the use of disparate indicator variables between waves was avoided wherever possible, some differences could not be accounted for. For instance, mothers reported how often they shouted at study children at age 9, while children responded at 13. Details of all variables employed in the construction of indicators are included between Table 1 and the Supplementary Information. Finally, recoding missing values into a category within income quintile variables has implications for this study’s findings. Results may be skewed slightly towards households of higher socioeconomic status, which is important to bear in mind when interpreting findings. 7. Conclusion This study represents the first development of a child-centred deprivation index emerging from GUI data guided by the UNCRC. While net equivalised household income is a significant predictor of multidimensional deprivation, the overlap between low income and multidimensional deprivation is imperfect. Within the lowest income bracket 63% of children were not multidimensionally deprived at age 9, and 64% at age 13. Therefore, household income alone cannot identify multidimensionally deprived children in Ireland. Our findings suggest that child-rights informed measures may identify dimensions of deprivation which are less dependent on household income. The findings of this study point towards the need for non-monetary policy interventions in the prevention and reduction of multidimensional child deprivation in Ireland. Such interventions may be informed by dimensions of deprivation identified by this study. Although cash transfers are imperative in combatting child poverty and deprivation, non-monetary interventions can help meet children’s immediate needs. Girls being at a greater risk of multidimensional deprivation than boys at 13 highlights the problem with the official Irish poverty measure’s inability to capture between-child differences due its household-centred approach. This study also highlights a need for greater consistency in survey items between waves of GUI data to maximise researchers’ ability to use the rich dataset longitudinally. Finally, the findings of this study indicate potential areas for further research. These include investigation into girls’ greater risk of multidimensional deprivation compared to boys at 13, and the identification of children’s own views on which items best capture necessities of life in Ireland. It is imperative that governments in high income countries act on the increasing body of literature which suggests that household-level measures are not sufficient in capturing child poverty, and move toward supplementing them with child-centric rights-informed measures. Declarations Author Contribution C.O'H wrote the main manuscript text and prepared all figures and tables. Acknowledgement I would like to thank Dr Yekaterina Chzhen and Dr Nicole Kapelle for their very helpful comments on an earlier version of this paper. Data Availability This study used data from the Growing Up in Ireland Survey. All data is available from the Irish Social Science Data Archive at the following link:https://www.ucd.ie/issda/ References Adolphus, K., Lawton, C. L., Champ, C. L., & Dye, L. (2016). The Effects of Breakfast and Breakfast Composition on Cognition in Children and Adolescents: A Systematic Review. Advances in Nutrition (Bethesda, Md.) , 7 (3), 590S-612S. https://doi.org/10.3945/an.115.010256 Akresh, R., Bagby, E., de Walque, D., & Kazianga, H. (2012). Child Ability and Household Human Capital Investment Decisions in Burkina Faso. Economic Development and Cultural Change , 61 (1), 157–186. JSTOR. https://doi.org/10.1086/666953 Ben-Arieh, A. (2008). The Child Indicators Movement: Past, Present, and Future. Child Indicators Research , 1 (1), 3–16. https://doi.org/10.1007/s12187-007-9003-1 Callaghan, M., Kelly, C., & Molcho, M. (2019). Bullying and bystander behaviour and health outcomes among adolescents in Ireland. Journal of Epidemiology and Community Health , 73 (5), 416–421. https://doi.org/10.1136/jech-2018-211350 Children’s Rights Alliance. (2024). Child Poverty Monitor 2024 . https://childrensrights.ie/wp-content/uploads/2024/05/Child-Poverty-Monitor-2024-4.pdf Chzhen, Y., Bruckauf, Z., Toczydlowska, E., Elgar, F. J., Moreno-Maldonado, C., Stevens, G. W. J. M., Sigmundová, D., & Gariépy, G. (2018). Multidimensional Poverty Among Adolescents in 38 Countries: Evidence from the Health Behaviour in School-aged Children (HBSC) 2013/14 Study. Child Indicators Research , 11 (3), 729–753. https://doi.org/10.1007/s12187-017-9489-0 Chzhen, Y., & Ferrone, L. (2017). Multidimensional Child Deprivation and Poverty Measurement: Case Study of Bosnia and Herzegovina. Social Indicators Research , 131 (3), 999–1014. https://doi.org/10.1007/s11205-016-1291-8 Citizens Information. (2023). GP visit cards for children under 8 (Ireland). Citizensinformation.ie. https://www.citizensinformation.ie/en/health/medical-cards-and-gp-visit-cards/gp-visit-cards-for-under-8s/ Coleman, T. (2021). Digital divide in UK education during COVID-19 pandemic: Literature review. Cambridge Assessment Research Report . https://doi.org/10.17863/CAM.110826 Connolly, S., & Wren, M.-A. (2017). Unmet healthcare needs in Ireland: Analysis using the EU-SILC survey. Health Policy , 121 (4), 434–441. https://doi.org/10.1016/j.healthpol.2017.02.009 Crowley, E. (2018). The prevalence of neglected dentitions in children as perceived by HSE primary care dentists in Ireland. Journal of the Irish Dental Association , 64 (3), 139–144. de Neubourg, C., Chai, J., de Milliano, M., & Plavgo, I. (2013). Step-by-Step Guidelines to the Multiple Overlapping Deprivation Analysis (MODA) (UNICEF Office of Research Working Papers, WP-2012-10). deLara, E. W. (2012). Why Adolescents Don’t Disclose Incidents of Bullying and Harassment. Journal of School Violence , 11 (4), 288–305. https://doi.org/10.1080/15388220.2012.705931 Department of Education. (2024). Bí Cineálta: Procedures to Prevent and Address Bullying Behaviour for Primary and Post­-Primary Schools . https://oide.ie/wp-content/uploads/2024/06/Bi-Cinealta.pdf Dickerson, A., & Popli, G. (2018). The Many Dimensions of Child Poverty: Evidence from the UK Millennium Cohort Study. Fiscal Studies , 39 (2), 265–298. https://doi.org/10.1111/1475-5890.12162 Doorley, K., Sándorová, S., & Maître, B. (2025). The effect of child-related benefits on child poverty and deprivation in Ireland (No. 01; Budget Perspectives 2026). ESRI. https://doi.org/10.26504/BP202601 Eurostat. (2025a, March 27). Purchasing power parities and GDP per capita—Preliminary estimate . https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Purchasing_power_parities_and_GDP_per_capita_-_preliminary_estimate Eurostat. (2025b, April). Living conditions in Europe—Poverty and social exclusion . https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Living_conditions_in_Europe_-_poverty_and_social_exclusion Florence, M. D., Asbridge, M., & Veugelers, P. J. (2008). Diet quality and academic performance. The Journal of School Health , 78 (4), 209–215; quiz 239–241. https://doi.org/10.1111/j.1746-1561.2008.00288.x Francis-Devine, B. (2025). Poverty in the UK: Statistics . https://commonslibrary.parliament.uk/research-briefings/sn07096/ Gangl, M. (2005). Income Inequality, Permanent Incomes, and Income Dynamics: Comparing Europe to the United States. Work and Occupations , 32 (2), 140–162. https://doi.org/10.1177/0730888404274354 Gerber, S. B. (1996). Extracurricular activities and academic achievement. Journal of Research & Development in Education , 30 (1), 42–50. Gibbons, R. A., Sprong, S., & Chzhen, Y. (2023). Growing Up in the Great Recession: The Effects of Three Dimensions of Economic Well-being on Child Behavioral Difficulties from Ages 3 to 17. Journal of Youth and Adolescence , 52 (5), 1024–1038. https://doi.org/10.1007/s10964-022-01721-2 Gordon, D., Nandy, S., Pantazis, C., Pemberton, S., & Townsend, P. (2003). Child poverty in the developing world . The Policy Press. Griggs, J., & Walker, R. (2008). The costs of child poverty for individuals and society: A literature review . York Publishing Services for Joseph Rowntree Foundation. https://ora.ox.ac.uk/objects/uuid:820a69b6-a83e-47af-8e4b-ea3dd921655a Guio, A.-C., Gordon, D., Marlier, E., Najera, H., & Pomati, M. (2018). Towards an EU measure of child deprivation. Child Indicators Research , 11 (3), 835–860. https://doi.org/10.1007/s12187-017-9491-6 Heppt, B., Olczyk, M., & Volodina, A. (2022). Number of books at home as an indicator of socioeconomic status: Examining its extensions and their incremental validity for academic achievement. Social Psychology of Education , 25 (4), 903–928. https://doi.org/10.1007/s11218-022-09704-8 Hock, E. S., Blank, L., Fairbrother, H., Clowes, M., Cuevas, D. C., Booth, A., Clair, A., & Goyder, E. (2024). Exploring the impact of housing insecurity on the health and wellbeing of children and young people in the United Kingdom: A qualitative systematic review. BMC Public Health , 24 (1), 2453. https://doi.org/10.1186/s12889-024-19735-9 Hurwitz, L. B., & Schmitt, K. L. (2020). Can children benefit from early internet exposure? Short- and long-term links between internet use, digital skill, and academic performance. Computers & Education , 146 , 103750. https://doi.org/10.1016/j.compedu.2019.103750 Kaul, T. (2018). Intra-household allocation of educational expenses: Gender discrimination and investing in the future. World Development , 104 , 336–343. https://doi.org/10.1016/j.worlddev.2017.12.017 Kazakova, Y., Leturcq, M., & Panico, L. (2024). Multidimensional Child Deprivation: Constructing Longitudinal Indicators for the Early Childhood Period. Child Indicators Research , 17 (6), 2629–2669. https://doi.org/10.1007/s12187-024-10178-7 Kerrins, L., Greene, S., & Murphy, S. (2011). Going Without: Measuring Child Poverty and Social Exclusion in Ireland . Combat Poverty Agency. http://hdl.handle.net/10147/219871 Keski-Rahkonen, A., Kaprio, J., Rissanen, A., Virkkunen, M., & Rose, R. J. (2003). Breakfast skipping and health-compromising behaviors in adolescents and adults. European Journal of Clinical Nutrition , 57 (7), 842–853. https://doi.org/10.1038/sj.ejcn.1601618 Knies, G. (2022). Effects of Income and Material Deprivation on Children’s Life Satisfaction: Evidence from Longitudinal Data for England (2009-2018). Journal of Happiness Studies , 23 (4), 1469–1492. https://doi.org/10.1007/s10902-021-00457-3 Layte, R., Nolan, B., & Whelan, C. (2000). Ten: Poverty and affluence in Ireland: A comparison of income and deprivation approaches to the measurement of poverty. In Breadline Europe (pp. 203–222). Policy Press. https://doi.org/10.51952/9781447366584.ch010 Li, M., & Chzhen, Y. (2024). Parental investment or parenting stress? Examining the links between poverty and child development in Ireland. European Societies , 26 (4), 911–951. https://doi.org/10.1080/14616696.2023.2275592 Lundy, L. (2007). ‘Voice’ is not enough: Conceptualising Article 12 of the United Nations Convention on the Rights of the Child. British Educational Research Journal , 33 (6), 927–942. https://doi.org/10.1080/01411920701657033 Madden, D. (2022). The Dynamics of Multidimensional Poverty in a Cohort of Irish Children. Child Indicators Research , 15 (5), 1631–1671. https://doi.org/10.1007/s12187-022-09921-9 Madden, D. (2024). Mental health in Ireland during the Covid pandemic: Evidence from two longitudinal surveys. PloS One , 19 (3), e0279526. https://doi.org/10.1371/journal.pone.0279526 Main, G. (2018). Fair Shares and Families: A Child-Focused Model of Intra-Household Sharing. Childhood Vulnerability Journal , 1 (1), 31–49. https://doi.org/10.1007/s41255-019-00001-9 Main, G., & Bradshaw, J. (2012). A Child Material Deprivation Index. Child Indicators Research , 5 (3), 503–521. https://doi.org/10.1007/s12187-012-9145-7 Maître, B., Nolan, B., & Whelan, C. T. (2006). Reconfiguring the Measurement of Deprivation and Consistent Poverty in Ireland (Report No. 58; Policy Research Series). ESRI. https://doi.org/10.26504/prs58 Maître, B., Russell, H., & Smyth, E. (2021). The dynamics of child poverty in Ireland: Evidence from the Growing Up in Ireland survey (Report No. 121; ESRI Research Series). ESRI. https://doi.org/10.26504/rs121 McCormick, R. (2017). Does Access to Green Space Impact the Mental Well-being of Children: A Systematic Review. Journal of Pediatric Nursing , 37 , 3–7. https://doi.org/10.1016/j.pedn.2017.08.027 Miller-Perrin, C. L., Perrin, R. D., & Kocur, J. L. (2009). Parental physical and psychological aggression: Psychological symptoms in young adults. Child Abuse & Neglect , 33 (1), 1–11. https://doi.org/10.1016/j.chiabu.2008.12.001 Mills, C., Guerin, S., Lynch, F., Daly, I., & Fitzpatrick, C. (2004). The relationship between bullying, depression and suicidal thoughts/behaviour in Irish adolescents. Irish Journal of Psychological Medicine , 21 (4), 112–116. Cambridge Core. https://doi.org/10.1017/S0790966700008521 Nolan, B. (2000). Child Poverty in Ireland . Oak Tree Press in association with Combat Poverty Agency. O’Donnell, A. W., Redmond, G., Gardner, A. A., Wang, J. J. J., & Mooney, A. (2024). Extracurricular activity participation, school belonging, and depressed mood: A test of the compensation hypothesis during adolescence. Applied Developmental Science , 28 (4), 596–611. https://doi.org/10.1080/10888691.2023.2260745 Pastore, D. R., Fisher, M., & Friedman, S. B. (1996). Abnormalities in weight status, eating attitudes, and eating behaviors among urban high school students: Correlations with self-esteem and anxiety. Journal of Adolescent Health , 18 (5), 312–319. https://doi.org/10.1016/1054-139X(95)00321-I Raphael, D. (2011). Poverty in childhood and adverse health outcomes in adulthood. Maturitas , 69 (1), 22–26. https://doi.org/10.1016/j.maturitas.2011.02.011 Regan, M., & Maître, B. (2020). Child poverty in Ireland and the pandemic recession (No. 04; Budget Perspectives 2021). ESRI. https://doi.org/10.26504/bp202104 Reynolds-Salmon, R., Samms-Vaughan, M., Coore-Desai, C., Reece, J., & Pellington, S. (2024). Does household size matter? Crowding and its effects on child development. Psychology, Health & Medicine , 29 (6), 1165–1178. https://doi.org/10.1080/13548506.2024.2326867 Roantree, B., Maître, B., & Russell, H. (2024). Poverty, income inequality and living standards in Ireland: Fourth annual report [Report]. ESRI and Community Foundation Ireland. https://doi.org/10.26504/jr7 Roantree, B., Russell, H., Alamir, A., Griffin, M., Maître, B., & Mitchell, T. (2025). Poverty, income inequality and living standards in Ireland: Fifth annual report [Report]. ESRI and Community Foundation Ireland. https://doi.org/10.26504/jr14 Russell, H., Maître, B., Alamir, A., & Slevin, E. (2025). Child poverty on the island of Ireland (Report No. 199; ESRI Research Series). ESRI. https://doi.org/10.26504/rs199 Sivadasan, J., & Xu, W. (2021). Missing women in India: Gender-specific effects of early-life rainfall shocks. World Development , 148 , 105652. https://doi.org/10.1016/j.worlddev.2021.105652 Smyth, E., & Darmody, M. (2025). Experience of bullying and bullying behaviours in childhood and adolescence (Report No. 216; ESRI Research Series). ESRI. https://doi.org/10.26504/rs216 Smyth, E., & Murray, A. (2022). The effect of pandemic‐related economic disruption on young adolescents in Ireland. Children , 9 (7). https://doi.org/10.3390/children9071037 Social Justice Ireland. (2024, May 29). Addressing Ireland’s Housing Crisis: Urgent Policy Reforms Needed . https://www.socialjustice.ie/article/addressing-irelands-housing-crisis-urgent-policy-reforms-needed Sollis, K. (2019). Measuring Child Deprivation and Opportunity in Australia . ARACY. https://www.aracy.org.au/wp-content/uploads/2024/09/ARACY_Measuring_child_deprivation_and_opportunity_in_Australia.pdf Sprong, S., Gibbons, R. A., & Chzhen, Y. (2023). Divergent trajectories: Three dimensions of child poverty during the Great Recession in Ireland. Longitudinal and Life Course Studies , 14 (1), 128–137. https://doi.org/10.1332/175795921X16551460545543 Thornton, R., O’Carroll, N., McGovern, A., & Boylan, H. (2025). Minimum Essential Standard of Living 2025 . Vincentian MESL Research Centre. https://www.budgeting.ie/download/pdf/mesl_2025.pdf Townsend, P. (1979). Poverty in the United Kingdom: A Survey of Household Resources and Standards of Living . Penguin Books. UNICEF. (2020). Measuring and Monitoring Child Poverty- Position Paper . https://data.unicef.org/resources/measuring-and-monitoring-child-poverty/ UNICEF. (2025). Violent discipline. UNICEF DATA . https://data.unicef.org/topic/child-protection/violence/violent-discipline/ United Nations. (1989). United Nations Convention on the Rights of the Child . https://www.ohchr.org/sites/default/files/Documents/ProfessionalInterest/crc.pdf Whelan, A., Devlin, A., McGuinness, S., & Redmond, P. (2023). Pandemic unemployment and social disadvantage in Ireland (Report No. 163; ESRI Research Series). ESRI. https://doi.org/10.26504/rs163 Whelan, C. T., & Maître, B. (2012). Identifying Childhood Deprivation: How Well Do National Indicators of Poverty and Social Exclusion in Ireland Perform? The Economic and Social Review , 43 (2, Summer), 251–272. Williams, J., Murray, A., & Whelan, C. T. (2014). Multi-Dimensional Deprivation Among 9-Year-Olds in Ireland: An Analysis of the Growing Up in Ireland Survey. Child Indicators Research , 7 (2), 279–300. https://doi.org/10.1007/s12187-013-9215-5 Woods, C., Ng, K., Britton, U., McClelland, J. F., O’Keeffe, B., Sheikhi, A., McFlynn, P., Murphy, M., Goss, H., Behan, S., Philpott, C., Lester, D., Adamakis, M., Costa, J., Coppinger, T., Connolly, S., Belton, S., & O’Brien, W. (2023). Children’s Sport Participation and Physical Activity Study 2022 . Physical Activity for Health Research Centre, Department of Physical Education and Sport Sciences, University of Limerick, Limerick, Ireland, Sport Ireland and Healthy Ireland, Dublin, Ireland and Sport Northern Ireland, Belfast, Northern Ireland. https://doi.org/10.34961/RESEARCHREPOSITORY-UL.23609157 Additional Declarations No competing interests reported. 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Data was collected in 2017/18 for children at age 9 and 2021/22 for children at age 13. Results are weighted using the longitudinal survey weight provided with GUI data.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eData\u003c/em\u003e: Growing Up in Ireland Survey ’08 Cohort 2017/18 (Wave 5) and 2021/22 (Wave 6).\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7790955/v1/2006e60b036cb9c09202ab9a.png"},{"id":104250772,"identity":"a5a58f85-84ff-4ad4-8fe5-b34cb780d0ea","added_by":"auto","created_at":"2026-03-09 16:08:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1372333,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7790955/v1/3144e7db-23f2-41b6-a3f5-aac1f4ce9f51.pdf"},{"id":94489198,"identity":"491d512c-e9ef-4980-bb9e-535acd88b221","added_by":"auto","created_at":"2025-10-27 17:03:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":152399,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryInformation.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7790955/v1/ae8f66b2a00c809fcd21d02a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eMultidimensional Child Deprivation in Ireland: A New Child Rights-Informed Approach\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eExperiencing deprivation during childhood has been linked to poor educational, health, and life satisfaction outcomes (e.g. Dickerson \u0026amp; Popli, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Griggs \u0026amp; Walker, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Knies, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Raphael, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). However, research conducted using child-centred deprivation indices demonstrates that low household income is not always associated with child deprivation, and conversely that high household income is not always associated with an absence of child deprivation (e.g. Chzhen et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Main \u0026amp; Bradshaw, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The objectives of this study are therefore twofold. First, we develop a child-centred multidimensional deprivation index, using the United Nations Convention on the Rights of the Child (UNCRC) (1989) as a guide at the indicator selection stage. Secondly, we use this index to gain a new perspective on the association between household income and multidimensional child deprivation in higher income countries. This study examines the degree of overlap between children who experience multidimensional deprivation and those who live in low-income households. It uses two waves of data from the Growing Up in Ireland study (GUI) \u0026lsquo;08 Cohort.\u003c/p\u003e\u003cp\u003eIreland provides a suitable high-income research setting, having the second highest GDP per capita in the European Union in 2024 according to Eurostat (2025a). Despite the country\u0026rsquo;s high-income status, the Irish Economic and Social Research Institute (ESRI) have reported that a fifth of children in Ireland are experiencing material deprivation for two consecutive years (Roantree et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In 2025 they reported that 19.6% of children were in income-poor households, after taking housing costs into account (Roantree et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Furthermore, Ireland\u0026rsquo;s current official child poverty measure, proposed by Ma\u0026icirc;tre et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), relies on a combination of equivalised disposable household income and deprivation measured at household-level. While the current measure provides a strong tool in predicting child-specific deprivation (C. T. Whelan \u0026amp; Ma\u0026icirc;tre, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), its household-based and adult-centric nature has been criticised for its omission of child-specific deprivation items (Kerrins et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Madden, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e"},{"header":"2. Literature Review","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Child-Centred Deprivation Indices\u003c/h2\u003e\u003cp\u003eA large international literature exists on the development of child-centred deprivation indices, representing a variety of methodological and conceptual approaches. Some studies adopt a participatory approach, consulting with children themselves at the indicator development stage. This results in indices that are truly child-centred and child rights-informed. It aligns with the Lundy (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) model of meaningful child participation, which asserts the importance of affording children Space, Voice, Audience and Influence in matters affecting them, in accordance with Article 12 of the UNCRC. For instance, Main \u0026amp; Bradshaw (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) employed a participatory approach to develop a child deprivation index in England. They conducted focus-groups with children aged 8\u0026ndash;14 to determine which deprivation indicators best reflected their necessities in their own view. They found that there were non-deprived children living in income-poor households and vice-versa. Similarly, Sollis (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) developed a deprivation index based on ARACY\u0026rsquo;s (Australian Research Alliance for Children and Youth) nest framework. ARACY identified dimensions of child well-being in Australia by interviewing over 3,700 children, young people, and experts. Sollis (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) found that at each point in time, those living in monetary poverty were more likely to be deprived across two or more dimensions. These studies provide strong examples of child-centred indices, since children were consulted in their development.\u003c/p\u003e\u003cp\u003eHowever, many studies cannot work with children directly due to time and resource constraints. As a result, alternative methodologies to elicit child-centred and rights-informed deprivation indices have emerged. One such methodology is UNICEF\u0026rsquo;s Multiple Overlapping Deprivation Analysis (MODA) framework (de Neubourg et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The MODA approach separates the child deprivation and poverty, grounding poverty in a lack of income. By using the child as the unit of analysis, MODA considers the position of children as dependents within households and avoids overlooking deprived children who live in households that are not income-poor (UNICEF, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Additionally, MODA recommends the use of the UNCRC as a guide in identifying dimensions and indicators of deprivation within the data employed (de Neubourg et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSeveral notable studies have employed the MODA framework in their analyses. Chzhen et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) used the MODA framework in their analysis of child deprivation among adolescents in 37 European countries. They used the UNCRC to identify six dimensions of deprivation in data from the 2013/14 Health Behaviour in School-aged Children study: nutrition, perceived health, school environment, protection from peer violence, family environment and access to information. They found that while single dimensions of deprivation did not relate closely with national wealth and income inequality, deprivation in three or more dimensions was associated with income inequality. Similarly, Chzhen \u0026amp; Ferrone (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) used MODA\u0026rsquo;s child rights-based approach to develop a deprivation index and operationalise it using Expanded Household Budget Survey data collected in 2011 in Bosnia and Herzegovina. They identified seven dimensions of deprivation and used it to analyse data for children aged 5\u0026ndash;15. Household consumption informed the development of a monetary poverty line, rather than income. Findings indicated that children in consumption poor households were more likely to be deprived in every dimension, although the overlap between monetary poverty and multidimensional deprivation was only moderate. Overall, the MODA framework allowed both studies to develop child-centred deprivation indices without directly eliciting children\u0026rsquo;s opinions. The differing contexts of their studies illustrate the advantage of the UNCRC\u0026rsquo;s international applicability, regardless of individual countries\u0026rsquo; economic statuses. However, it is of note that these studies used cross-sectional data, rather than longitudinal data.\u003c/p\u003e\u003cp\u003eUsing an early child development framework, Kazakova et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) constructed a child-centred and dynamic deprivation index for children in early childhood using longitudinal data from the \u0026Eacute;tude longitudinale fran\u0026ccedil;aise depuis l\u0026rsquo;enfance. While the study identified dimensions of deprivation which remained constant over time, indicators changed to capture children's changing needs through early childhood. Kazakova et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) notably decided to weight deprivation items. This set the study\u0026rsquo;s approach aside from other rights-informed methodologies like MODA, which advises against the use of weights to avoid passing value judgements on different aspects of child well-being (de Neubourg et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). They found that around 43% of multidimensionally deprived children were also income poor, on average across all waves, while 23% of income poor children were also deprived. This study was novel in its incorporation of young children\u0026rsquo;s changing needs over time into a single deprivation measure. However, while its dynamic items are reflective of a child rights perspective, they did not explicitly link them with the UNCRC.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 The Irish Context\u003c/h2\u003e\u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\u003ch2\u003e2.2.1 The Official Measure and Definition of Poverty in Ireland\u003c/h2\u003e\u003cp\u003eIreland\u0026rsquo;s official measure of poverty, first proposed by Ma\u0026icirc;tre et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), uses an eleven-item deprivation list in conjunction with equivalised disposable household income. Deprivation items pertain to the household\u0026rsquo;s ability to afford food, clothing, to keep the home warm, to participate in social events, and other socially perceived necessities. According to the measure, households who cannot afford two or more of the eleven deprivation items are experiencing \u0026ldquo;enforced deprivation\u0026rdquo;, while those who have a nominal equivalised disposable income below 60% of the median are \u0026ldquo;at risk of poverty\u0026rdquo;. Households who are both at risk of poverty and experiencing enforced deprivation are in \u0026ldquo;consistent poverty\u0026rdquo;. Nationally representative data is collected annually by the Central Statistics Office for the Survey on Income and Living Conditions (SILC) and used to determine the proportion of the population falling into each of the three categories. Ireland\u0026rsquo;s combination of low income and deprivation measures places it among several other high-income countries that rely on household-level measures to gauge poverty levels. Similar measures are used in the UK (Francis-Devine, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), as well as at the EU level (Eurostat, 2025b).\u003c/p\u003e\u003cp\u003eThe Irish measure\u0026rsquo;s use of deprivation items acknowledges the inadequacy of income alone in capturing poverty and recognises the need for a multidimensional approach (Ma\u0026icirc;tre et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). However, Kerrins et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) argue that the sole inclusion of indicators which are adult-centred and captured at household-level leads to an \u0026ldquo;imprecise picture of child poverty\u0026rdquo; (p.7) and the erasure of children\u0026rsquo;s experiences. They emphasise that the current measure neither provides insight into what items poor children in Ireland lack, nor considers that resources may not be shared equally within households. A wealth of research has demonstrated that resources are often not distributed equally between children in the same households (e.g. Akresh et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Kaul, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Main, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sivadasan \u0026amp; Xu, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Furthermore, Kazakova et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) suggest that indicators of child deprivation should change over time to remain relevant to children\u0026rsquo;s changing needs and experiences. The current Irish measure, and household-level measures more broadly, cannot capture these critical aspects of child poverty.\u003c/p\u003e\u003cp\u003eIn contrast, Whelan \u0026amp; Ma\u0026icirc;tre (\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) argued in favour of the current Irish measure. They analysed 2009 EU-SILC data, which included a list of child-centred deprivation items in addition to the standard household list. They found that just 3 percent of children were deprived according \u003cem\u003eonly\u003c/em\u003e to the child-specific list and argue that using this measure alone would exclude children who live in deprived households but do not experience child-specific deprivation. However, even EU-SILC child-centred deprivation data is collected from an adult household representative and assumes that if one child is lacking an item in a household, all children in the household lack that item (Guio et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). These deprivation items were intended for use across the EU and therefore are not necessarily relevant to the specific needs and experiences of Irish children. Overall, while the current measure may be a strong predictor of child deprivation according to EU-SILC data, its household and adult-centric nature cannot capture significant elements of child deprivation.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003e2.2.2 Studies of Child Poverty in Ireland\u003c/h2\u003e\u003cp\u003eDeprivation indices have long formed part of the poverty literature in Ireland, with Layte et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) acknowledging the problematic nature of relying on relative income-poverty measures where living conditions are rapidly changing. Nolan (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) employed a list of household deprivation items to compare levels of child deprivation with household income using Irish data collected in 1994 and 1997. He found that low income alone is not sufficient in explaining exclusion due to a lack of resources. Furthermore, Nolan (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) acknowledges that while low income and deprivation do not overlap perfectly, sustained low income is a good indicator of need which can help policymakers identify children in need of support.\u003c/p\u003e\u003cp\u003eSince the adoption of the official Irish poverty measure, much of the research on child poverty in Ireland has employed SILC or EU-SILC data (e.g. Children\u0026rsquo;s Rights Alliance, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Regan \u0026amp; Ma\u0026icirc;tre, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Russell et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; C. T. Whelan \u0026amp; Ma\u0026icirc;tre, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). However, some use data from the Growing Up in Ireland study (GUI), a nationally representative longitudinal cohort study of Irish children. Some studies which employ GUI data also gauge deprivation using the 11-item list included in the national measure. Such studies have provided insights into the socioeconomic predictors of child poverty (Ma\u0026icirc;tre et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), as well as its impact on children\u0026rsquo;s mental health (Gibbons et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and cognitive ability (Li \u0026amp; Chzhen, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMeanwhile, Williams et al. (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) developed a list of multidimensional indicators of child deprivation distinct from the official list of deprivation items and tested it on data from the \u0026rsquo;98 Cohort at age 9. Their study used just one cross-section of GUI data and focused on the debate surrounding the use of multidimensional deprivation indices, and the methods used in operationalising them. Williams et al. (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) included household income in their index as a dimension of deprivation. Similarly, Madden (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) developed a multidimensional child deprivation index and employed it using GUI data. The index contained just three dimensions and included family income/resources as a dimension of deprivation. Unlike Williams et al. (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), however, Madden (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) employed three waves of data collected from the \u0026rsquo;98 Cohort.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Theoretical Background\u003c/h2\u003e\u003cp\u003eThis study is underpinned by a relative conceptualisation of poverty. Peter Townsend\u0026rsquo;s (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e1979\u003c/span\u003e) defined individuals as poor when: \u0026ldquo;Their resources are so seriously below those commanded by the average individual that they are, in effect, excluded from ordinary living patterns, customs and activities\u0026rdquo; (p. 31). He emphasised that an individual\u0026rsquo;s ability to participate in the society in which they live is determined by the resources available to them. Therefore, poverty is grounded in a lack of resources relative to other members of society. To operationalise this definition, Townsend (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e1979\u003c/span\u003e) employed both deprivation indices and income measures. He included separate deprivation items for children and adults, and items which are captured at both individual and household levels. Townsend\u0026rsquo;s work therefore acknowledges that children\u0026rsquo;s needs differ from those of adults, and that poverty is characterised by a lack of resources extending beyond finances alone.\u003c/p\u003e\u003cp\u003eThis study conceptualises deprivation as multidimensional and argues that it is best measured at the individual level. De Neubourg et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) recognise that capturing child poverty at the individual child level makes children\u0026rsquo;s specific needs visible. Using the UNCRC as a guide at indicator selection allows for the identification of these needs, while also acknowledging that poverty denies children their internationally enshrined rights (Gordon et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Employing the UNCRC in indicator development also offers two further advantages. Firstly, De Neubourg et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) note that the UNCRC is useful in constructing indicators which are important to any child\u0026rsquo;s development, regardless of their socio-economic status, culture, or country of residence. Therefore, the child-rights approach allows for the selection of context-specific deprivation indicators, in line with a relative conceptualisation of poverty, that remain grounded in the needs of all children, regardless of context. Secondly, since the UNCRC aims to protect children in all aspects of their lives, it elicits ecological and multidimensional concepts of child well-being (Ben-Arieh, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). It therefore allows for the identification of children\u0026rsquo;s needs across all dimensions of their lives.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Methodology","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Growing Up in Ireland Data and Sample\u003c/h2\u003e\u003cp\u003eThis study uses data from the GUI \u0026rsquo;08 study, a nationally representative cohort study of children born in Ireland in 2007/8. The GUI\u0026rsquo;s provision of extensive information on cohort members and their families makes it well-suited to the study of multidimensional child deprivation. The study includes questions on different areas of children\u0026rsquo;s lives, many of which reflect rights enshrined in the UNCRC. The study includes interviews with primary and secondary caregivers, teachers, and the children themselves. For brevity, this text will refer to primary caregivers as mothers.\u003c/p\u003e\u003cp\u003eWe use data from Waves 5 (2017/18, age 9) and 6 (2021/22, age 13) of the GUI \u0026rsquo;08 study. These waves encompass the most recently available longitudinal data on children in Ireland, capturing important educational transitions (i.e. from primary to secondary school) and developmental changes (from middle childhood to adolescence). Furthermore, Wave 6 took place amid the Covid-19 pandemic, a period of economic hardship and psychological strain for many people (Madden, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Smyth \u0026amp; Murray, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eInitially, the GUI \u0026rsquo;08 study included over 11,000 households. Participants were randomly selected from the Child Benefit Register. Wave 5 comprised 8,032 children, while Wave 6 included 6,655 children. This study focuses on the subset of children who participated in both waves. We used the longitudinal analysis weight provided in the GUI researcher microdata files to statistically account for non-random panel attrition and systematic non-response. We then excluded cases with missing data for any of the key variables to be used in our analyses, amounting to approximately 10% (614 cases). Our analytic sample consists of 5,442 children, corresponding to 10,884 observations.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Indicators and Dimensions\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the deprivation indicators selected at each wave, categorised by dimension. It includes the deprivation threshold used and respondent from whom responses were collected for each indicator. Using the UNCRC as a guide, we identify six dimensions in the data: nutrition, access to healthcare, protection from violence, access to information, leisure and housing. Since de Neubourg (2013) classifies children aged 5\u0026ndash;16 as falling into the same life-cycle stage (school-age), we aim to use the same indicators of deprivation for children at ages 9 and 13. However, inconsistencies in the variables available at each wave mean indicators are not identical between waves.\u003c/p\u003e\u003cp\u003eEach dimension is composed of exactly two indicators. We take the union approach, meaning that if a child is deprived according to at least one of two indicators in a dimension they are considered deprived in that dimension. Chzhen et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) acknowledge that the union approach is consistent with a child rights framework, given that an absence of deprivation in one indicator in a dimension does not compensate for the presence of deprivation in another. Each indicator and dimension is coded so that \u0026ldquo;1\u0026rdquo; indicates deprivation and \u0026ldquo;0\u0026rdquo; indicates a lack of deprivation. We define the deprivation rate as the percentage of children deprived in at least one dimension, and the multidimensional deprivation rate as the percentage of children deprived in two or more dimensions.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\u003ch2\u003e3.2.1 Nutrition\u003c/h2\u003e\u003cp\u003eArticle 24 of the UNCRC calls for access to \u0026ldquo;adequate nutritious foods\u0026rdquo;. The role of nutrition in child development for school-aged children is widely acknowledged. Florence et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) found that schoolchildren with a lower quality diet were significantly more likely to perform poorly academically. Equally, breakfast is understood as vital to adequate nutrition. A systematic literature review by Adolphus et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) found that for children, breakfast consumption was associated with better performance on tasks that required attention, executive function and memory.\u003c/p\u003e\u003cp\u003eWe classify children who do not consume fruit and vegetables at least once a day as deprived. GUI survey questions surrounding children\u0026rsquo;s food consumption vary slightly between Waves 5 and 6 (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). At age 9, we combined three variables regarding consumption of fruit and vegetables in the 24 hours before the interview into one dichotomous indicator variable: a child is deprived if they have consumed no fruit, cooked vegetables, or raw vegetables in the last 24 hours. At 13, a child as deprived if they usually consume no fruit or vegetables in a day.\u003c/p\u003e\u003cp\u003eWe classify children who do not usually eat before school as deprived of breakfast at age 9, and children who have breakfast less than once a week or never as deprived at age 13. It is notable that at age 9 the respondent for the breakfast indicator was the child\u0026rsquo;s mother, while at 13 the respondent was the child. Additionally, breakfast is the most skipped meal, particularly among adolescents (Adolphus et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Therefore, particularly at 13, children may choose to skip breakfast. Furthermore, Pastore et al. (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e1996\u003c/span\u003e) found that girls were significantly more likely to skip breakfast than boys. This finding is mirrored in the sample data at age 13, where 8% of girls report eating breakfast \u0026ldquo;Less than once a week/Never\u0026rdquo;, compared to 3% of boys (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Nonetheless, since breakfast skipping has been associated with health-compromising behaviours in adolescents (Keski-Rahkonen et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), breakfast remains a valid indicator of child deprivation.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\u003ch2\u003e3.2.2 Access to Healthcare\u003c/h2\u003e\u003cp\u003eAccess to healthcare is crucial to child wellbeing. Article 24 of the UNCRC recognises the right of the child to access \u0026ldquo;facilities for the treatment of illness and rehabilitation of health\u0026rdquo;. Crowley (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) notes that dental neglect is recognised as a child protection issue, yet their survey found that 62% of Irish public healthcare service dentists reported seeing neglected dentitions at least once a week in their clinics. We classify a child as deprived if their mother reports that they never (or never/almost never at 13) visit the dentist.\u003c/p\u003e\u003cp\u003eAlthough GUI collects data on how frequently mothers consult with a general practitioner (GP) on their child\u0026rsquo;s health, 48% (at age 9) and 62% (at age 13) said that they had not consulted with a GP over the last year. As GP visits are more common among those with symptoms, a child\u0026rsquo;s access to healthcare services may be more accurately reflected by their possession of a means-tested medical card (entitling them to free healthcare) or private insurance coverage. Connolly and Wren (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) found that, in Ireland, people without free primary care or private insurance were more likely to report an unmet healthcare need. We created an indicator variable where a child is considered deprived if they possess neither a medical card nor private insurance.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003ch2\u003e3.2.3 Protection from Violence\u003c/h2\u003e\u003cp\u003eProtection from violence is enshrined in Article 19 of the UNCRC. Mills et al. (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) found that bullying was significantly associated with depression and suicidal ideation in their analysis of data collected from Irish schoolchildren. Similarly, Callaghan et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) found that victims of bullying were significantly more likely to report low life satisfaction, poor health, and psychological and somatic symptoms. We consider children who have recently experienced bullying as deprived. Although the timeframe of the indicators varies between the ages 9 and 13, i.e. in the last year vs in the last 3 months, both capture a child\u0026rsquo;s recent experience of bullying.\u003c/p\u003e\u003cp\u003eThe second indicator in this dimension relates to parental discipline. UNICEF (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) refers to shouting or yelling at a child as a form of psychological aggression. Similarly, Miller-Perrin et al. (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) suggest that psychological aggression may be more important than physical violence toward children in predicting psychological outcomes. We classify a child as deprived if their mother regularly/always (age 9) or always (age 13) shouts at them when they misbehave. The respondent for this indicator was the mother at age 9 but the child at age 13.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\u003ch2\u003e3.2.4 Access to Information\u003c/h2\u003e\u003cp\u003eThe right to \u0026ldquo;seek, receive and impart information\u0026rdquo; is enshrined in Article 13 of the UNCRC. Similarly, Article 17 recognises the right of the child to access \u0026ldquo;information [\u0026hellip;] from a diversity of national and international sources\u0026rdquo;. Internet access represents an important facet of access to information. Hurwitz \u0026amp; Schmitt (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) found that middle childhood digital skill (measured by parent\u0026rsquo;s rating of children\u0026rsquo;s ability to find information on the web at age 11) was significantly positively associated with school performance. Internet access was also of significant value for children in the sample at age 13, since the educational repercussions of the Covid-19 pandemic were exacerbated by a lack of internet access (Coleman, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). We deem a child deprived if they do not have access to the internet at home via an electronic device.\u003c/p\u003e\u003cp\u003eThe second indicator of access to information is access to age-appropriate books. It is a robust predictor of students\u0026rsquo; academic language comprehension (Heppt et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). A child is therefore classified as deprived if their mother reports that they have 0 to 10 age-appropriate books at home. It is of note that at age 9 the variable we employ mentions library books, while at 13 it does not. Nonetheless, responses to both questions reflect a lack of books at home.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003e3.2.5 Leisure\u003c/h2\u003e\u003cp\u003e Article 31 of the UNCRC recognises the right of the child to rest and leisure, and to participate in \u0026ldquo;recreational activities appropriate to the age of the child\u0026rdquo;. The benefits of extracurricular activities for children are widely acknowledged. Gerber (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1996\u003c/span\u003e) found that it was positively related to academic achievement. Furthermore, O\u0026rsquo;Donnell et al. (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) found that for adolescents, participation in extracurricular activities can promote wellbeing, with those from lower socioeconomic backgrounds experiencing the greatest positive effects. We classify a child as deprived if they do not participate in any extracurricular activities.\u003c/p\u003e\u003cp\u003eThe second indicator in the leisure dimension is access to green space. McCormick (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) found that it was associated with a range of benefits for children\u0026rsquo;s mental well-being, including improved overall mental-health and cognitive development. The indicators we employ for access to green space differ somewhat between the two waves, but they capture the availability of parks and play spaces in the local area (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\u003ch2\u003e3.2.6 Housing\u003c/h2\u003e\u003cp\u003eArticle 27 of the UNCRC recognises the child\u0026rsquo;s right to \u0026ldquo;a standard of living adequate for the child\u0026rsquo;s [\u0026hellip;] development\u0026rdquo;, explicitly mentioning that State Parties should provide material assistance with \u0026ldquo;housing\u0026rdquo;. The UNCRC thereby recognises that adequate housing is essential for children\u0026rsquo;s development and well-being. Although this dimension is by default measured at household-level rather than at the child level, we argue its inclusion is important due to both its recognition in the UNCRC and Ireland\u0026rsquo;s ongoing housing crisis.\u003c/p\u003e\u003cp\u003eAn extensive review found that living in damp accommodation was linked to a range of physical health conditions in children including asthma and eczema (Hock et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The first indicator of housing conditions therefore relates to poor physical conditions in the home such as damp. Reynolds-Salmon et al. (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) found that children\u0026rsquo;s locomotor and personal-social development are negatively affected by living in a crowded home. As such, the second indicator of housing conditions classifies a child as deprived if their mother reports their home to be too small.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDeprivation Dimensions and Indicators\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eAge 9 (Wave 5)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003eAge 13 (Wave 6)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDimension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIndicator Question(s)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDeprivation Threshold\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eResp-ondent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eIndicator Question(s)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDeprivation Threshold\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eResp-ondent\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eNutrition\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIn the last 24 hours has Child had fresh fruit? / In the last 24 hours has Child had cooked vegetables? / In the last 24 hours has Child had raw vegetables or salad?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDeprived if answered \u0026ldquo;Not at all\u0026rdquo; to each question.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHow many portions of fruit or vegetables would Child usually have in a day?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDeprived if answered \u0026ldquo;None.\u0026rdquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDoes child usually have something to eat before going to school?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDeprived if answered \u0026ldquo;No.\u0026rdquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHow often do you have breakfast (either at home or at school)?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDeprived if answered \u0026ldquo;Less than once a week/Never.\u0026rdquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eAccess to Healthcare\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWhich of the following best describes how regularly child visits the dentist?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDeprived if answered \u0026ldquo;Never/\u003c/p\u003e\u003cp\u003eAlmost Never.\u0026rdquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eWhich of the following best describes how regularly Child visits the dentist?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDeprived if answered \u0026ldquo;Never.\u0026rdquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIs child covered by a medical card? / Is child covered by private medical insurance?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDeprived if answered \u0026ldquo;No\u0026rdquo; to both questions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eIs Child covered by a medical card? / Is Child covered by private medical insurance?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDeprived if answered \u0026ldquo;No\u0026rdquo; to both questions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eProtection from\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eViolence\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHas child been victim of bullying in last year?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDeprived if answered \u0026ldquo;Yes.\u0026rdquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHas child been a victim of bullying in last 3 months?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDeprived if answered \u0026ldquo;Yes.\u0026rdquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHow often do you do the following when child misbehaves? - Shout or yell at him/her?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDeprived if answered \u0026ldquo;Regularly/ Always\u0026rdquo;.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eWhen you misbehave, how often do your parents shout at you?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDeprived if answered \u0026ldquo;Always\u0026rdquo;.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003eContinued\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eAccess to Information\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDo you have a computer, iPad, smartphone, or other gadget at home that you can use to access the internet?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDeprived if answered \u0026ldquo;No.\u0026rdquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eDoes Study Child have access to the internet through a smartphone, tablet,\u0026nbsp;laptop\u0026nbsp;or other computer?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDeprived if answered \u0026ldquo;No.\u0026rdquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAbout how many children\u0026rsquo;s books\u0026nbsp;does\u0026nbsp;child have access to in your home now, including any library books? Would you estimate:\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDeprived if answered \u0026ldquo;None\u0026rdquo;,\u0026nbsp;or \u0026ldquo;Less than 10.\u0026rdquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHow many books (including e-books) does Study Child have access to in the home?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDeprived if answered \u0026ldquo;None\u0026rdquo;,\u0026nbsp;or \u0026ldquo;1 to 10.\u0026rdquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eLeisure\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDuring an average week, does child\u0026nbsp;participate\u0026nbsp;in\u0026hellip; Team sports / Individual sports / Drama classes / Arts and craft / Youth club / Religious club/group/ Music/dance / Scouts/guides/ boy's brigade/ girl's brigade / Other activities?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDeprived if answered \u0026ldquo;No\u0026rdquo; to all.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHow often do you play sports with a coach or instructor, or as part of an organised team? / How often do you take part in dance lessons? / How often do you take part in art, crafts, drama or music lessons,\u0026nbsp;clubs\u0026nbsp;or rehearsals? / How often do you take part in clubs or groups (e.g. Guides, Scouts,\u0026nbsp;youth club, community, church groups)?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDeprived if answered \u0026ldquo;Less often or never\u0026rdquo; to all.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThere are safe parks, playgrounds and play spaces in this area.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDeprived if answered \u0026ldquo;Strongly disagree.\u0026rdquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eIs there a park,\u0026nbsp;beach\u0026nbsp;or green space within 2 kilometres of home\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDeprived if answered \u0026ldquo;No.\u0026rdquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eHousing\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAccommodation: Poor conditions in the home (damp, drafts, leaks etc.)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDeprived if answered \u0026ldquo;Yes.\u0026rdquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLeaking roof/ damp walls /rot in windows or door frames - Problems with your accommodation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDeprived if answered \u0026ldquo;Yes.\u0026rdquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAccommodation: Too small\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDeprived if answered \u0026ldquo;Yes.\u0026rdquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eToo small, not enough space - Problems with your accommodation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDeprived if answered \u0026ldquo;Yes.\u0026rdquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eNote\u003c/em\u003e:\u0026nbsp;The above table details the indicator questions, deprivation criteria, and respondent used for each wave of GUI data. Respondent abbreviations are as follows: M\u0026thinsp;=\u0026thinsp;Mother and C\u0026thinsp;=\u0026thinsp;Child.\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cem\u003eData\u003c/em\u003e: Growing Up in Ireland Survey \u0026rsquo;08 Cohort, 2017/18 and 2021/22.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Data Analysis\u003c/h2\u003e\u003cp\u003eAll data analyses were performed using STATA Version 18 (StataCorp LLC, College Station, Texas, USA). All analyses were weighted using the longitudinal weight provided with GUI data. First, we tabulated the shares of children deprived on each indicator and dimension at 9 and 13. Then we counted the number of dimensions each child was deprived on and created binary deprivation and multidimensional deprivation variables which return \u0026ldquo;1\u0026rdquo; to indicate deprivation/multidimensional deprivation and \u0026ldquo;0\u0026rdquo; to indicate lack of deprivation were generated for ages 9 and 13. Multidimensional deprivation is defined as being deprived on two or more dimensions. We then estimated deprivation rates at each age.\u003c/p\u003e\u003cp\u003eNext, we analysed the relationship between income and multidimensional deprivation at each age. We used income data provided by GUI in the form of equivalised net annual household income quintiles. This allowed for meaningful comparison between five broad household income categories, considering household size and structure. In the sample there were 426 missing income values at age 9, and 505 at age 13. Rather than excluding these observations, we recoded missing values into a category and included them in our analysis to maximise the analytic sample. We first examined the relationship between household income and deprivation by cross-tabulating income quintiles with multidimensional deprivation status and determining the shares of multidimensionally deprived children within each quintile for each wave.\u003c/p\u003e\u003cp\u003eNext, we ran logistic regression models, first regressing multidimensional deprivation status on equivalised household income quintile. We then added controls for child\u0026rsquo;s gender, maternal age, couple family vs lone parent family, mother\u0026rsquo;s highest level of educational attainment, and mother\u0026rsquo;s employment situation. Appendix A reports the distribution of independent variables used in logistic regression. Findings are reported as average marginal effects to allow for comparison between models.\u003c/p\u003e\u003cp\u003eFinally, we analysed transition probabilities to gauge mobility into and out of multidimensional deprivation, and the lowest income quintile, over time.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Findings","content":"\u003cp\u003e\u003cstrong\u003e4.1 Deprivation Across Indicators and Dimensions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.1.1 Deprivation Across Indicators\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 2 reports the percentage of children deprived on each indicator at each wave. At age 9, one in five children did not possess a medical card or private health insurance (21%). A similar proportion (21%) had a recent experience of bullying. In contrast, just 1% of children were regularly/always shouted at by their mothers. \u0026nbsp;However, the respondent for this question was the child\u0026rsquo;s mother. Small shares of children also went without breakfast (2%) or lived in poor physical conditions (2%) at age 9.\u003c/p\u003e\n\u003cp\u003eAged 13, children were most likely to be deprived of a medical card or private health insurance, with over one fifth (22%) of children not possessing either. A large share (17%) of children also had limited access to books at home at 13. The indicators on which children were least like to be deprived at 13 were dentist visits (0.06%) and internet access at home (0.06%).\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"538\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 416px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eShare (%) of Children Deprived on Each Indicator.\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 317px;\"\u003e\n \u003cp\u003eIndicator\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003eDeprived at\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;age 9 (%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003eDeprived at \u0026nbsp;\u003c/p\u003e\n \u003cp\u003eage 13 (%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 317px;\"\u003e\n \u003cp\u003eFruit and vegetables\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e6.50\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e4.29\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 317px;\"\u003e\n \u003cp\u003eBreakfast\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e2.26\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e5.56\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 317px;\"\u003e\n \u003cp\u003eDentist visits\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e5.63\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e0.06\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 317px;\"\u003e\n \u003cp\u003eMedical card/private health insurance\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e20.78\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e22.43\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 317px;\"\u003e\n \u003cp\u003eRecent experience of bullying \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e21.30\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e9.80\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 317px;\"\u003e\n \u003cp\u003eMother shouts when child misbehaves\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e1.37\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e5.88\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 317px;\"\u003e\n \u003cp\u003eInternet access via a gadget at home\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e8.16\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e0.06\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 317px;\"\u003e\n \u003cp\u003eBooks at home\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e8.83\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e16.92\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 317px;\"\u003e\n \u003cp\u003eParticipation in extracurriculars\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e8.51\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e14.26\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 317px;\"\u003e\n \u003cp\u003eAccess to green space\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e8.33\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e8.51\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 317px;\"\u003e\n \u003cp\u003ePhysical condition of home \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e2.26\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e8.07\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 317px;\"\u003e\n \u003cp\u003eHome sufficiently spacious\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e10.35\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp; 13.18\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 538px;\"\u003e\n \u003cp\u003e\u003cem\u003eNote:\u0026nbsp;\u003c/em\u003eN= 5,442. Data was collected in 2017/18 for children at age 9 and 2021/22 for children at age 13. Results are weighted using the longitudinal survey weight provided with GUI data.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eData\u003c/em\u003e: Growing Up in Ireland Survey \u0026rsquo;08 Cohort, 2017/18 (Wave 5) and 2021/22 (Wave 6).\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e4.1.2 Deprivation Across Dimensions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 3 reports the percentage of children deprived on each dimension at each wave. At 9, the highest rate of deprivation was\u0026nbsp;observed\u0026nbsp;on access to healthcare, with just over a quarter of children (25%) lacking access. A similarly high rate was\u0026nbsp;observed\u0026nbsp;on protection from violence (22%). Children were least likely to be deprived on nutrition, with just 8% of children deprived on this dimension at 9.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;At age 13, slightly under a quarter (23%) of children had limited access to healthcare. A similarly high rate of deprivation was observed on leisure at age 13, with just over a fifth (21%) of children experiencing deprivation on this dimension. Almost one fifth (19%) of children were in inadequate accommodation at this wave. As at age 9, children were least likely to experience nutritional deprivation at 13, with 9% of children deprived on this dimension.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBetween waves, changes occurred in the prevalence of deprivation in some dimensions. The rate of deprivation in protection from violence decreased by approximately 7% between waves. Meanwhile, the proportions of children experiencing deprivation in the leisure and housing dimensions were greater at age 13 than at age 9. The prevalence of deprivation in the nutrition, access to healthcare, and access to information dimensions remained similar between waves. However, since the survey items used to construct indicators varied between waves, we do not know whether these represent real changes or are artefacts of measurement.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"538\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 455px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eShare (%) of Children Deprived on Each Dimension.\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 318px;\"\u003e\n \u003cp\u003eDimension\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003eDeprived at\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eage 9 (%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003eDeprived at\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eage 13 (%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 318px;\"\u003e\n \u003cp\u003eNutrition\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e8.47\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e8.97\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 318px;\"\u003e\n \u003cp\u003eAccess to Healthcare\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e25.12\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e22.85\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 318px;\"\u003e\n \u003cp\u003eProtection from Violence\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e22.11\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e14.58\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 318px;\"\u003e\n \u003cp\u003eAccess to Information\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e16.33\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e17.39\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 318px;\"\u003e\n \u003cp\u003eLeisure\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e15.74\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e21.38\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 318px;\"\u003e\n \u003cp\u003eHousing\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e10.94\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e18.65\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 538px;\"\u003e\n \u003cp\u003e\u003cem\u003eNote:\u0026nbsp;\u003c/em\u003eN= 5,442. Data was collected in 2017/18 for children at age 9 and 2021/22 for children at age 13. Results are weighted using the longitudinal survey weight provided with GUI data.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eData\u003c/em\u003e: Growing Up in Ireland Survey \u0026rsquo;08 Cohort, 2017/18 (Wave 5) and 2021/22 (Wave 6).\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e4.1.3 Multidimensional Deprivation\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 1 shows the distribution of the number of dimensions children are deprived in at each wave. No child experienced deprivation on all 6 dimensions at ages 9 or 13. At both ages, comparable shares of children experienced no deprivation (36% at 9 and 34% at 13) or just one dimension (38% at 9 and 37% at 13). \u0026nbsp;The multidimensional deprivation rate was 26% at age 9 and 29% at age 13. \u0026nbsp;In the next section, we direct our attention to multidimensional rather than single-dimension deprivation to capture the intensity of deprivation experienced.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.2 Cross-sectional analysis of multidimensional deprivation and household income \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.2.1 Distribution of multidimensional deprivation across income quintiles.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFirst, we report on the distribution of multidimensional deprivation across household income quintiles at ages 9 and 13. Table 4 documents crosstabulations of equivalised household income quintile with multidimensional deprivation status at each wave. The similar distribution of the sample across income quintiles at both ages suggests that missing values were relatively evenly distributed across income quintiles. However, the analytic sample may be slightly skewed towards households of a higher socioeconomic status, since the lowest income quintile is slightly underrepresented in both waves. Results presented in Table 4 suggest that low income and multidimensional deprivation do not overlap perfectly at ages 9 or 13. At both ages, multidimensional deprivation was not concentrated in any one income quintile, although the lowest shares of deprived children lived in households whose income fell into the highest two income quintiles. At age 9, 17% of children were multidimensionally deprived but not in the lowest income quintile. Similarly, one fifth of children experienced multidimensionally deprivation at 13 but were not in the lowest income quintile. Of those in the lowest income quintile, 63% were not multidimensionally deprived at age 9, and 64% at age 13. Overall, although smaller shares of children in higher-income households experienced multidimensional deprivation, not \u003cem\u003eall\u003c/em\u003e multidimensionally deprived children lived in low-income households.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"604\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;4\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 510px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eShare (%) of Multidimensionally Deprived Children by Income Quintile.\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eAge 9\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 247px;\"\u003e\n \u003cp\u003eAge 13\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;Income\u0026nbsp;\u003c/p\u003e\n \u003cp\u003equintile\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eDeprived (%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eNot\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eDeprived (%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eTotal (%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eDeprived (%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eNot \u0026nbsp;\u003c/p\u003e\n \u003cp\u003eDeprived (%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eTotal (%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cem\u003e1\u003csup\u003est\u003c/sup\u003e\u0026nbsp;\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e6.29\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e10.74\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e17.04\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e6.31\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e11.1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e17.41\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cem\u003e2\u003csup\u003end\u003c/sup\u003e\u0026nbsp;\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e5.95\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e13.6\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e19.55\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e6.38\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e11.85\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e18.23\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cem\u003e3\u003csup\u003erd\u003c/sup\u003e\u0026nbsp;\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e4.62\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e13.91\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e18.52\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e5.65\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e12.4\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e18.05\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cem\u003e4\u003csup\u003eth\u003c/sup\u003e\u0026nbsp;\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e4.01\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e14.26\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e18.27\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e4.75\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e13.11\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e17.86\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cem\u003e5\u003csup\u003eth\u003c/sup\u003e\u0026nbsp;\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e2.55\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e14.55\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e17.11\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e3.08\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e15.07\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e18.15\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cem\u003eMissing\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e2.29\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e7.23\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e9.52\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e2.63\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e7.67\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e10.30\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eTotal (%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e25.71\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e74.29\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e28.8\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e71.2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 604px;\"\u003e\n \u003cp\u003e\u003cem\u003eNote:\u0026nbsp;\u003c/em\u003e N =5,442. 1\u003csup\u003est\u003c/sup\u003e income quintile refers to the lowest equivalised net income quintile and so forth. Data was collected in 2017/18 for children at age 9 and 2021/22 for children at age 13. Results are weighted using the longitudinal survey weight provided with GUI data.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eData\u003c/em\u003e: Growing Up in Ireland Survey \u0026rsquo;08 Cohort, 2017/18 (Wave 5) and 2021/22 (Wave 6).\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e4.2.2 Logistic Regression of Multidimensional Deprivation Status on Income Quintile \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 5 reports average marginal effects from logistic regression of multidimensional deprivation status on equivalised household income quintile. Regression coefficients are reported in Appendix B. Logistic regression was performed with and without socio-demographic controls.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLogistic regression of multidimensional deprivation status on equivalised household income quintile, excluding sociodemographic controls, allowed us to examine the degree of overlap between low income and multidimensional deprivation. At age 9, those in the lowest income quintile were 22 percentage points (p\u0026lt;0.001) more likely to experience multidimensional deprivation on average, compared to those in the highest quintile, all else being equal. Similarly, everything else being equal, the probability of multidimensional deprivation was 16 points higher (p\u0026lt;0.001), on average, for children in the second-lowest income quintile relative to those in the highest. There were statistically significant, although smaller, differences between the third and fourth income quintiles and the top quintile. This suggests a strong association between low household income and multidimensional deprivation. However, the overlap between multidimensional deprivation and low income was imperfect. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSimilar average marginal effects were observed at 13, when not controlling for sociodemographic predictors. As at age 9, the largest difference (19 points, p\u0026lt;0.001) was observed between the lowest and highest income quintile. However, there was just one point decrease (from 19 points to 18 points), on average, between the first and second income quintiles in the probability of being multidimensionally deprived relative to the highest income quintile, everything else held constant. Therefore, on average, there was less variation in the probability of experiencing multidimensional deprivation relative to the highest income quintile between the poorest and second poorest income quintiles at age 13 than at age 9, everything else being held constant. As at age 9, the size of average marginal effects decreased as income quintile increased at 13, and all average marginal effects were statistically significant. Like at age 9, all else being equal, while those in lower income quintiles had a higher probability of experiencing deprivation, on average, at 13 the overlap between low income and multidimensional deprivation was imperfect.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAverage marginal effects from logistic regression of multidimensional deprivation status on equivalised household income quintile including sociodemographic controls are also reported in Table 5. At age 9, all else being equal, after including controls, being in a higher income quintile was still associated with a lower probability of experiencing multidimensional deprivation, on average, relative to the richest quintile. However, overall, the size and statistical significance of average marginal effects decreased in income quintile, on average, after controlling for sociodemographic predictors, everything else held constant. The average marginal effect associated with being in the fourth income quintile was not statistically significant. All else equal, those in the lowest income quintile had a 10 point (p\u0026lt;0.01) higher probability of experiencing multidimensional deprivation, on average, than those in the highest quintile. Everything being held constant, those in the lowest income quintile therefore remained the most at risk of experiencing multidimensional deprivation, on average, relative to those in the highest quintile. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;At age 13, including controls also resulted in reduced, less statistically significant average marginal effects in income quintile. However, unlike at age 9, all else being equal, the magnitude of average marginal effects was similar across income quintiles, on average, relative to the highest income quintile. The largest differences were observed for the first and second income quintiles, with children in these groups having, on average, a 10 point (p\u0026lt;0.01) greater probability of experiencing multidimensional deprivation compared to those in the richest quintile, all else being equal. Meanwhile children in the third quintile had a 9 point (p\u0026lt;0.01) greater probability of multidimensional deprivation, on average, than those in the highest income bracket, everything else being constant. Therefore, on average, being in a lower income quintile was still associated with a higher probability of experiencing multidimensional deprivation than being in the highest quintile, after controlling for sociodemographic predictors at age 13. However, since the size of average marginal effects associated with each income quintile did not greatly decrease as income quintile increased, the probability of multidimensional deprivation did not decline sharply between income quintiles when controlling for predictors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eStatistically significant differences were\u0026nbsp;observed\u0026nbsp;for maternal educational attainment and family status at 9 and 13.\u0026nbsp;All else being constant, the probability of being multidimensionally deprived was greater for children\u0026nbsp;whose mother had lower\u0026nbsp;levels\u0026nbsp;of educational attainment,\u0026nbsp;relative\u0026nbsp;to\u0026nbsp;those\u0026nbsp;whose mother had a postgraduate qualification, on average. Similarly, those whose mothers were single had a statistically significantly higher probability of being multidimensionally deprived, on average, all else being equal. At age 13, average marginal effects suggested that being a girl, having a younger mother, or a mother who was not in work, were also statistically significantly associated with a greater probability of experiencing multidimensional deprivation on average, everything else being held constant.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"594\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;5\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 501px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAverage marginal effects from logistic regression of multidimensional deprivation status on income quintile.\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 27.1044%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 35.5219%;\"\u003e\n \u003cp\u003e(1)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 207px;\"\u003e\n \u003cp\u003e(2)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 27.1044%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17.6767%;\"\u003e\n \u003cp\u003eAge 9\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003eAge 13\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003eAge 9\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eAge 13\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 27.1044%;\"\u003e\n \u003cp\u003eIncome quintile \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(ref:\u0026nbsp;5\u003csup\u003eth\u0026nbsp;\u003c/sup\u003equintile)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17.6767%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 27.1044%;\"\u003e\n \u003cp\u003e\u003cem\u003e1\u003csup\u003est\u003c/sup\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17.6767%;\"\u003e\n \u003cp\u003e0.22***\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e0.19***\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0.10**\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.10** \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 27.1044%;\"\u003e\n \u003cp\u003e\u003cem\u003e2\u003csup\u003end\u003c/sup\u003e\u0026nbsp;\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17.6767%;\"\u003e\n \u003cp\u003e0.16***\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e0.18***\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0.08**\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.10** \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 27.1044%;\"\u003e\n \u003cp\u003e\u003cem\u003e3\u003csup\u003erd\u003c/sup\u003e\u0026nbsp;\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17.6767%;\"\u003e\n \u003cp\u003e0.10***\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e0.14***\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0.05*\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.09** \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 27.1044%;\"\u003e\n \u003cp\u003e\u003cem\u003e4\u003csup\u003eth\u003c/sup\u003e\u0026nbsp;\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17.6767%;\"\u003e\n \u003cp\u003e0.07**\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e0.10***\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0.05\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.07** \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 27.1044%;\"\u003e\n \u003cp\u003e\u003cem\u003eMissing\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17.6767%;\"\u003e\n \u003cp\u003e0.09**\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e0.09** \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0.05\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.05\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 27.1044%;\"\u003e\n \u003cp\u003e\u0026nbsp;Child\u0026rsquo;s gender \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(ref: Male)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.6767%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 27.1044%;\"\u003e\n \u003cp\u003e\u003cem\u003eFemale\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.6767%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e-0.02\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.04* \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 27.1044%;\"\u003e\n \u003cp\u003e\u0026nbsp;Mother\u0026rsquo;s age group \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(ref: 50 or older)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.6767%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 27.1044%;\"\u003e\n \u003cp\u003e\u003cem\u003e20-39 years\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.6767%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0.08\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.17***\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 27.1044%;\"\u003e\n \u003cp\u003e\u003cem\u003e40-49 years\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.6767%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.04*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 27.1044%;\"\u003e\n \u003cp\u003e\u0026nbsp;Family status\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(ref: Couple family)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.6767%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 27.1044%;\"\u003e\n \u003cp\u003e\u003cem\u003eLone parent family\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.6767%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0.09**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.06*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 27.1044%;\"\u003e\n \u003cp\u003e\u0026nbsp;Mother\u0026rsquo;s highest educational level\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(ref: Postgraduate)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.6767%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 27.1044%;\"\u003e\n \u003cp\u003e\u003cem\u003eSchool\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.6767%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0.21***\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.21***\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 27.1044%;\"\u003e\n \u003cp\u003e\u003cem\u003eHigher Education\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.6767%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0.07***\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.11***\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 27.1044%;\"\u003e\n \u003cp\u003e\u0026nbsp;Mother\u0026rsquo;s employment status\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(ref: Employed)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.6767%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 27.1044%;\"\u003e\n \u003cp\u003e\u003cem\u003eStudying/Training\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.6767%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.10\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 27.1044%;\"\u003e\n \u003cp\u003e\u003cem\u003eNot in work\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.6767%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e-0.02\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e-0.05* \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 27.1044%;\"\u003e\n \u003cp\u003e\u0026nbsp;N\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17.6767%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 5,442\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 5,442\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 5,442\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; 5,442\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 594px;\"\u003e\n \u003cp\u003e\u003cem\u003eNote:\u003c/em\u003e * p\u0026lt;0.05, ** p\u0026lt;0.01, *** p\u0026lt;0.001. The dependent variable in logistic regression (1) without controls and (2) with controls is a binary indicator variable for multidimensional deprivation status. Income category \u0026ldquo;\u003cem\u003e1\u003csup\u003es\u003c/sup\u003e\u003c/em\u003e\u003csup\u003et\u003c/sup\u003e\u0026rdquo; denotes the lowest income quintile. Reference categories are included in brackets. Results are weighted using the longitudinal survey weight provided with GUI data. Data was collected in 2017/18 for children at age 9 and 2021/22 for children at age 13. \u003cem\u003e\u0026nbsp;\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eData\u003c/em\u003e: Growing Up in Ireland Survey \u0026rsquo;08 Cohort, 2017/18 (Wave 5) and 2021/22 (Wave 6).\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e4.3 Income and Multidimensional Deprivation Dynamics\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFinally, since this study used longitudinal data, we examine transition probabilities into and out of multidimensional deprivation and the lowest income quintile over time. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAt age 9, 26% of children were multidimensionally deprived, and at 13, 29% were multidimensionally deprived. Children who were multidimensionally deprived at age 9 had a 51% chance of not being multidimensionally deprived at 13. Therefore, the probability of escaping multidimensional deprivation about the same as the probability of remaining deprived. However, those who were not multidimensionally deprived at 9 had a 22% chance of becoming deprived at 13. Almost 80% of children who were not multidimensionally deprived at age 9 remained non-deprived. Therefore, children who were not deprived at 9 had a much lower probability of experiencing deprivation at age 13 compared to those who experienced deprivation at 9.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMeanwhile, children whose household income did not fall into the lowest quintile at age 9 had a 10% chance of entering this income bracket at age 13. Those who were in the lowest income quintile at age 9 had a 40% chance of being in a higher income quintile at 13, however just over half (51%) remained in the lowest income bracket. As such, children who lived in households whose equivalised net income fell into the lowest quintile were much more likely to remain in this quintile, than those in higher income brackets were to fall into the lowest quintile.\u0026nbsp;\u003c/p\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eThis study demonstrates the development of a child-centred multidimensional deprivation index using data for ages 9 and 13 from GUI\u0026rsquo;s \u0026rsquo;08 cohort. Unlike other studies of child deprivation in Ireland, which have employed the national household-based measure of deprivation (e.g. Gibbons et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Ma\u0026icirc;tre et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), this study\u0026rsquo;s measure operates at the individual child level. The child-rights approach elicits a deprivation index which is representative of children\u0026rsquo;s needs across several facets of their lives, while also representing their rights as enshrined in the UNCRC. The use of the UNCRC as a guide, and exclusion of income as a dimension of deprivation, sets this study aside from previous Irish studies using GUI data by Williams et al. (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) and Madden (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSix dimensions of deprivation were identified: nutrition, access to healthcare, protection from violence, access to information, leisure, and housing. At both age 9 and 13, over one fifth of children did not have either private health insurance or a medical card. Although the high rates of deprivation observed on this indicator inflated deprivation rates, its inclusion was important given both the literature on its importance in meeting healthcare needs in Ireland (Connolly \u0026amp; Wren, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and the recognition of access to healthcare in the UNCRC. The large shares of children deprived on this indicator at each wave underline a need for the introduction of free GP care for all children in Ireland. Since August 2023, all children under age 8 in Ireland have been entitled to a free GP visit card (Citizens Information, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The findings of this study suggest that the inclusion of older children in this scheme would be highly beneficial.\u003c/p\u003e\u003cp\u003eA large share of children were deprived on the bullying indicator (21%) at age 9. A seemingly smaller share of children had a recent experience of bullying at age 13 (10%), however this apparent change is likely reflective of the change in indicator timeframe between waves (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Equally, it could be a result of the fact that adolescents often do not disclose instances of bullying or harassment (deLara, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Nonetheless, deprivation rates at both 9 and 13 point toward the need for anti-bullying interventions in schools. A new child rights-informed anti-bullying initiative called B\u0026iacute; Cine\u0026aacute;lta comes into effect this 2025/26 school year in Ireland (Department of Education, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Smyth \u0026amp; Darmody, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The initiative centres the fostering of empathetic and inclusive environments within both primary and secondary schools. While its impact remains to be seen, its introduction is welcome given the particularly high rates of bullying observed amongst 9-year-olds in 2017/18 in this study.\u003c/p\u003e\u003cp\u003eAt 13 there were much higher shares of children deprived on the leisure and housing dimensions than at age 9. The increased exclusion from leisure observed at 13 could be reflective of the higher costs associated with meeting teenagers\u0026rsquo; needs (Thornton et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Meanwhile, the decline in housing conditions between waves could be driven by overcrowding, arising from the addition of new siblings to households. However, differences between deprivation indicators used at each wave mean we cannot know whether these findings represent real change over time or are artefacts of measurement.\u003c/p\u003e\u003cp\u003eSimilarly, differing indicators mean we cannot be certain if changes in the multidimensional deprivation rate between waves represent real shifts over time. The rate varied only slightly between waves (26% at age 9, 29% at age 13). Nonetheless, at both 9 and 13, over one quarter of children lacked two or more resources important to their wellbeing. This finding is stark, regardless of the figures\u0026rsquo; comparability over time.\u003c/p\u003e\u003cp\u003eDescriptive analysis demonstrated that the overlap between multidimensional deprivation and low household income was imperfect at both ages 9 and 13. This is in line with findings from previous Irish studies of child deprivation (e.g. Nolan, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; C. T. Whelan \u0026amp; Ma\u0026icirc;tre, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Less variation in multidimensional deprivation rates within the lowest three income quintiles was observed at age 13 compared to at age 9. While levels of multidimensional deprivation decreased as income increased, deprivation rates did not decline sharply between any two income quintiles at either point in time. These results differ from findings of previous Irish studies. For instance, Whelan \u0026amp; Ma\u0026icirc;tre (\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)found that being in the lowest income quintile was associated with a much greater risk of childhood deprivation (according to EU-SILC data) and basic deprivation (according to the Irish national measure). This suggests that rights-informed multidimensional deprivation measures may highlight areas of deprivation which are less dependent on household income, while remaining grounded in a lack of resources and opportunities.\u003c/p\u003e\u003cp\u003eLogistic regression of multidimensional deprivation status on income quintile demonstrated that household income was a significant predictor of multidimensional deprivation. Therefore, while children experiencing multidimensional deprivation do not directly overlap with those who live in low-income households, income remains an important predictor of deprivation. Including controls in our model lead to decreased statistical significance and magnitude for average marginal effects in income quintile. At both 9 and 13, family status and maternal educational attainment were statistically significant predictors of deprivation. This aligns with Ma\u0026icirc;tre et al.\u0026rsquo;s (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) findings. While at age 9, average marginal effects still decreased as income quintile increased, this pattern was not observed at age 13. While at age 9, multidimensional deprivation was more concentrated in lower income quintiles when controlling for sociodemographic predictors, this was not true at age 13. It may be a result of restrictions imposed during the Covid-19 pandemic. Restrictions impacted all areas of life for children in Ireland, irrespective of their families\u0026rsquo; financial situations. For instance, restrictions affected all children\u0026rsquo;s ability to participate in extracurricular activities. While those in deprived areas were disproportionately affected by the pandemic (Whelan et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), its wider impact may explain the more even distribution of multidimensional deprivation at age 13. Further analysis is required to prove this hypothesis, however.\u003c/p\u003e\u003cp\u003eOverall, while household income is a significant predictor of multidimensional deprivation in Ireland, the overlap between low household income and multidimensional deprivation is imperfect. As such, household income alone cannot identify multidimensionally deprived children. Our results align with findings from other studies using child-centred and rights-informed multidimensional deprivation measures in high-income national contexts (e.g. Chzhen et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Kazakova et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Sollis, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAt age 13, the study child\u0026rsquo;s gender, their family status, and their mother\u0026rsquo;s age, highest level of educational attainment, and employment status were all significant predictors of deprivation. Girls were at a greater risk of multidimensional deprivation than boys. This finding aligns with Chzhen et al.\u0026rsquo;s (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) study of deprivation among adolescents in higher income countries, which found that girls had a higher risk of experiencing multidimensional deprivation in most countries included in the study. We can speculate as to why this was the case, although further analysis is required to prove the underlying reasons for gender differences. As discussed, girls were more likely to go without breakfast than boys (see section \u003cspan refid=\"Sec11\" class=\"InternalRef\"\u003e3.2.1\u003c/span\u003e). Girls may also have been less likely to participate in extracurriculars than boys. For example, Woods et al. (\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) found that at post-primary level, girls in Ireland participated in sport less than boys. They also may have been more likely to report experience of bullying, in line Chzhen et al.\u0026rsquo;s (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) findings. That girls were more likely to be deprived at 13 is an important finding from a child rights perspective, considering Article 2 of the UNCRC states that state parties shall \u0026ldquo;respect and ensure the rights set forth [\u0026hellip;] irrespective of the child\u0026rsquo;s [\u0026hellip;] sex\u0026rdquo;. This finding also points toward a need for further research into the divergent trajectories during adolescence that may explain these gendered wellbeing inequalities. Moreover, it highlights the importance of child-centred measures of deprivation in capturing between child differences that are lost in household-level measures.\u003c/p\u003e\u003cp\u003eThere were transitions both into and out of the lowest income quintile and multidimensional deprivation over time. Those who experienced deprivation at age 9 were more likely to continue to experience it at 13. Similarly, children in the lowest income bracket in the first wave were more likely to remain there, than children in other income brackets were to end up in the lowest bracket. These findings align with those from previous Irish studies. For instance, Sprong et al. (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) found that in Ireland, those with a previous experience of material deprivation were more likely to remain deprived. It is also acknowledged in the international literature that those in lower income brackets face greater levels of economic instability, creating considerable barriers to upward economic mobility (e.g. Gangl, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Nonetheless, children who were not deprived at age 9 faced a greater than 20% probability of experiencing deprivation at age 13. This highlights the potential effectiveness of preventative interventions, as well as targeted measures to meet immediate need. It is also possible that this is reflective of the wider effects of the Covid-19 pandemic, as discussed.\u003c/p\u003e\u003cp\u003eThis study points toward a number of policy implications. The deprivation index used in this study underlines the advantages of using measures which centre the child as the unit of analysis in high income national contexts. Child-centred measures capture between-child differences that household-level measures miss, and identify the specific items that deprived children lack. Supplementing existing household deprivation and income measures with child-specific deprivation indices at the national level would provide policy makers with comprehensive information on children\u0026rsquo;s personal \u003cem\u003eand\u003c/em\u003e household circumstances. This data could be used to better target policy interventions in combatting and preventing child poverty and deprivation.\u003c/p\u003e\u003cp\u003eSecondly, this study\u0026rsquo;s finding that not all multidimensionally deprived children live in low income households points towards the potential benefits of non-monetary policy interventions in Ireland and similar contexts. However, it is important to acknowledge that cash transfers are vital in reducing rates of child poverty and deprivation (Doorley et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). While non-monetary interventions cannot replace cash transfers, they may help meet children\u0026rsquo;s immediate needs as identified by child-centred deprivation indices.\u003c/p\u003e\u003cp\u003eThe dimensions of deprivation identified in this study highlight facets of child wellbeing in which non-monetary interventions could be effective in Ireland. For instance, as mentioned, the expansion of access to GP visit cards to all children would improve access to healthcare. Similarly, since girls were more likely to be deprived on the breakfast indicator at 13, the introduction of nutritional education programmes in secondary schools could help to bridge the gender divide in deprivation on this indicator. Keski-Rahkonen et al. (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) found that breakfast skipping could be reduced with increased nutritional knowledge. Furthermore, while there is a well-documented need for greater supply of housing, and specifically affordable housing, in Ireland (Social Justice Ireland, 2024), other interventions could help improve accommodation conditions. For instance, increased legal oversight of rental accommodation quality, as well as more efficient services through which renters\u0026rsquo; complaints can be rectified, would significantly improve the immediate need for better housing conditions.\u003c/p\u003e"},{"header":"6. Limitations","content":"\u003cp\u003eThis study has several limitations. Firstly, our approach to developing a child-centred deprivation index would be improved by ensuring all deprivation indicators emerged from survey questions answered by children. However, due to data availability and changes in respondent to survey items between waves of data collection this was not possible. Moreover, consulting with children to ensure that deprivation items reflected what they considered necessities would have enhanced our approach. Similar methods have been successfully employed by Main \u0026amp; Bradshaw (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) and Sollis (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Since this was not possible due to time and resource constraints, using the UNCRC as a guide at the indicator selection stage allowed us to create a child rights-based index without eliciting children\u0026rsquo;s views.\u003c/p\u003e\u003cp\u003eSecondly, since we selected deprivation items from existing GUI data, data availability limited our choice of possible items. For instance, large amounts of missing data in school principal-reported survey items informed our decision not to include deprivation items relating to children\u0026rsquo;s school environment. Additionally, there were several disparities in survey items used in the construction of indicators between waves of data collection, as detailed in the methodology section. While the use of disparate indicator variables between waves was avoided wherever possible, some differences could not be accounted for. For instance, mothers reported how often they shouted at study children at age 9, while children responded at 13. Details of all variables employed in the construction of indicators are included between Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and the Supplementary Information.\u003c/p\u003e\u003cp\u003eFinally, recoding missing values into a category within income quintile variables has implications for this study\u0026rsquo;s findings. Results may be skewed slightly towards households of higher socioeconomic status, which is important to bear in mind when interpreting findings.\u003c/p\u003e"},{"header":"7. Conclusion","content":"\u003cp\u003eThis study represents the first development of a child-centred deprivation index emerging from GUI data guided by the UNCRC. While net equivalised household income is a significant predictor of multidimensional deprivation, the overlap between low income and multidimensional deprivation is imperfect. Within the lowest income bracket 63% of children were \u003cem\u003enot\u003c/em\u003e multidimensionally deprived at age 9, and 64% at age 13. Therefore, household income alone cannot identify multidimensionally deprived children in Ireland. Our findings suggest that child-rights informed measures may identify dimensions of deprivation which are less dependent on household income. The findings of this study point towards the need for non-monetary policy interventions in the prevention and reduction of multidimensional child deprivation in Ireland. Such interventions may be informed by dimensions of deprivation identified by this study. Although cash transfers are imperative in combatting child poverty and deprivation, non-monetary interventions can help meet children\u0026rsquo;s immediate needs.\u003c/p\u003e\u003cp\u003eGirls being at a greater risk of multidimensional deprivation than boys at 13 highlights the problem with the official Irish poverty measure\u0026rsquo;s inability to capture between-child differences due its household-centred approach. This study also highlights a need for greater consistency in survey items between waves of GUI data to maximise researchers\u0026rsquo; ability to use the rich dataset longitudinally. Finally, the findings of this study indicate potential areas for further research. These include investigation into girls\u0026rsquo; greater risk of multidimensional deprivation compared to boys at 13, and the identification of children\u0026rsquo;s own views on which items best capture necessities of life in Ireland. It is imperative that governments in high income countries act on the increasing body of literature which suggests that household-level measures are not sufficient in capturing child poverty, and move toward supplementing them with child-centric rights-informed measures.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eC.O'H wrote the main manuscript text and prepared all figures and tables.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eI would like to thank Dr Yekaterina Chzhen and Dr Nicole Kapelle for their very helpful comments on an earlier version of this paper.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThis study used data from the Growing Up in Ireland Survey. All data is available from the Irish Social Science Data Archive at the following link:https://www.ucd.ie/issda/\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAdolphus, K., Lawton, C. L., Champ, C. L., \u0026amp; Dye, L. (2016). The Effects of Breakfast and Breakfast Composition on Cognition in Children and Adolescents: A Systematic Review. \u003cem\u003eAdvances in Nutrition (Bethesda, Md.)\u003c/em\u003e, \u003cem\u003e7\u003c/em\u003e(3), 590S-612S. https://doi.org/10.3945/an.115.010256\u003c/li\u003e\n\u003cli\u003eAkresh, R., Bagby, E., de Walque, D., \u0026amp; Kazianga, H. (2012). Child Ability and Household Human Capital Investment Decisions in Burkina Faso. \u003cem\u003eEconomic Development and Cultural Change\u003c/em\u003e, \u003cem\u003e61\u003c/em\u003e(1), 157\u0026ndash;186. JSTOR. https://doi.org/10.1086/666953\u003c/li\u003e\n\u003cli\u003eBen-Arieh, A. (2008). The Child Indicators Movement: Past, Present, and Future. \u003cem\u003eChild Indicators Research\u003c/em\u003e, \u003cem\u003e1\u003c/em\u003e(1), 3\u0026ndash;16. https://doi.org/10.1007/s12187-007-9003-1\u003c/li\u003e\n\u003cli\u003eCallaghan, M., Kelly, C., \u0026amp; Molcho, M. (2019). Bullying and bystander behaviour and health outcomes among adolescents in Ireland. \u003cem\u003eJournal of Epidemiology and Community Health\u003c/em\u003e, \u003cem\u003e73\u003c/em\u003e(5), 416\u0026ndash;421. https://doi.org/10.1136/jech-2018-211350\u003c/li\u003e\n\u003cli\u003eChildren\u0026rsquo;s Rights Alliance. (2024). \u003cem\u003eChild Poverty Monitor 2024\u003c/em\u003e. https://childrensrights.ie/wp-content/uploads/2024/05/Child-Poverty-Monitor-2024-4.pdf\u003c/li\u003e\n\u003cli\u003eChzhen, Y., Bruckauf, Z., Toczydlowska, E., Elgar, F. J., Moreno-Maldonado, C., Stevens, G. W. J. M., Sigmundov\u0026aacute;, D., \u0026amp; Gari\u0026eacute;py, G. (2018). Multidimensional Poverty Among Adolescents in 38 Countries: Evidence from the Health Behaviour in School-aged Children (HBSC) 2013/14 Study. \u003cem\u003eChild Indicators Research\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(3), 729\u0026ndash;753. https://doi.org/10.1007/s12187-017-9489-0\u003c/li\u003e\n\u003cli\u003eChzhen, Y., \u0026amp; Ferrone, L. (2017). Multidimensional Child Deprivation and Poverty Measurement: Case Study of Bosnia and Herzegovina. \u003cem\u003eSocial Indicators Research\u003c/em\u003e, \u003cem\u003e131\u003c/em\u003e(3), 999\u0026ndash;1014. https://doi.org/10.1007/s11205-016-1291-8\u003c/li\u003e\n\u003cli\u003eCitizens Information. (2023). \u003cem\u003eGP visit cards for children under 8\u003c/em\u003e (Ireland). Citizensinformation.ie. https://www.citizensinformation.ie/en/health/medical-cards-and-gp-visit-cards/gp-visit-cards-for-under-8s/\u003c/li\u003e\n\u003cli\u003eColeman, T. (2021). Digital divide in UK education during COVID-19 pandemic: Literature review. \u003cem\u003eCambridge Assessment Research Report\u003c/em\u003e. https://doi.org/10.17863/CAM.110826\u003c/li\u003e\n\u003cli\u003eConnolly, S., \u0026amp; Wren, M.-A. (2017). Unmet healthcare needs in Ireland: Analysis using the EU-SILC survey. \u003cem\u003eHealth Policy\u003c/em\u003e, \u003cem\u003e121\u003c/em\u003e(4), 434\u0026ndash;441. https://doi.org/10.1016/j.healthpol.2017.02.009\u003c/li\u003e\n\u003cli\u003eCrowley, E. (2018). The prevalence of neglected dentitions in children as perceived by HSE primary care dentists in Ireland. \u003cem\u003eJournal of the Irish Dental Association\u003c/em\u003e, \u003cem\u003e64\u003c/em\u003e(3), 139\u0026ndash;144.\u003c/li\u003e\n\u003cli\u003ede Neubourg, C., Chai, J., de Milliano, M., \u0026amp; Plavgo, I. (2013). \u003cem\u003eStep-by-Step Guidelines to the Multiple Overlapping Deprivation Analysis (MODA)\u003c/em\u003e (UNICEF Office of Research Working Papers, WP-2012-10).\u003c/li\u003e\n\u003cli\u003edeLara, E. W. (2012). Why Adolescents Don\u0026rsquo;t Disclose Incidents of Bullying and Harassment. \u003cem\u003eJournal of School Violence\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(4), 288\u0026ndash;305. https://doi.org/10.1080/15388220.2012.705931\u003c/li\u003e\n\u003cli\u003eDepartment of Education. (2024). \u003cem\u003eB\u0026iacute; Cine\u0026aacute;lta: Procedures to Prevent and Address Bullying Behaviour for Primary and Post\u0026shy;-Primary Schools\u003c/em\u003e. https://oide.ie/wp-content/uploads/2024/06/Bi-Cinealta.pdf\u003c/li\u003e\n\u003cli\u003eDickerson, A., \u0026amp; Popli, G. (2018). The Many Dimensions of Child Poverty: Evidence from the UK Millennium Cohort Study. \u003cem\u003eFiscal Studies\u003c/em\u003e, \u003cem\u003e39\u003c/em\u003e(2), 265\u0026ndash;298. https://doi.org/10.1111/1475-5890.12162\u003c/li\u003e\n\u003cli\u003eDoorley, K., S\u0026aacute;ndorov\u0026aacute;, S., \u0026amp; Ma\u0026icirc;tre, B. (2025). \u003cem\u003eThe effect of child-related benefits on child poverty and deprivation in Ireland\u003c/em\u003e (No. 01; Budget Perspectives 2026). ESRI. https://doi.org/10.26504/BP202601\u003c/li\u003e\n\u003cli\u003eEurostat. (2025a, March 27). \u003cem\u003ePurchasing power parities and GDP per capita\u0026mdash;Preliminary estimate\u003c/em\u003e. https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Purchasing_power_parities_and_GDP_per_capita_-_preliminary_estimate\u003c/li\u003e\n\u003cli\u003eEurostat. (2025b, April). \u003cem\u003eLiving conditions in Europe\u0026mdash;Poverty and social exclusion\u003c/em\u003e. https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Living_conditions_in_Europe_-_poverty_and_social_exclusion\u003c/li\u003e\n\u003cli\u003eFlorence, M. D., Asbridge, M., \u0026amp; Veugelers, P. J. (2008). Diet quality and academic performance. \u003cem\u003eThe Journal of School Health\u003c/em\u003e, \u003cem\u003e78\u003c/em\u003e(4), 209\u0026ndash;215; quiz 239\u0026ndash;241. https://doi.org/10.1111/j.1746-1561.2008.00288.x\u003c/li\u003e\n\u003cli\u003eFrancis-Devine, B. (2025). \u003cem\u003ePoverty in the UK: Statistics\u003c/em\u003e. https://commonslibrary.parliament.uk/research-briefings/sn07096/\u003c/li\u003e\n\u003cli\u003eGangl, M. (2005). Income Inequality, Permanent Incomes, and Income Dynamics: Comparing Europe to the United States. \u003cem\u003eWork and Occupations\u003c/em\u003e, \u003cem\u003e32\u003c/em\u003e(2), 140\u0026ndash;162. https://doi.org/10.1177/0730888404274354\u003c/li\u003e\n\u003cli\u003eGerber, S. B. (1996). Extracurricular activities and academic achievement. \u003cem\u003eJournal of Research \u0026amp; Development in Education\u003c/em\u003e, \u003cem\u003e30\u003c/em\u003e(1), 42\u0026ndash;50.\u003c/li\u003e\n\u003cli\u003eGibbons, R. A., Sprong, S., \u0026amp; Chzhen, Y. (2023). Growing Up in the Great Recession: The Effects of Three Dimensions of Economic Well-being on Child Behavioral Difficulties from Ages 3 to 17. \u003cem\u003eJournal of Youth and Adolescence\u003c/em\u003e, \u003cem\u003e52\u003c/em\u003e(5), 1024\u0026ndash;1038. https://doi.org/10.1007/s10964-022-01721-2\u003c/li\u003e\n\u003cli\u003eGordon, D., Nandy, S., Pantazis, C., Pemberton, S., \u0026amp; Townsend, P. (2003). \u003cem\u003eChild poverty in the developing world\u003c/em\u003e. The Policy Press.\u003c/li\u003e\n\u003cli\u003eGriggs, J., \u0026amp; Walker, R. (2008). \u003cem\u003eThe costs of child poverty for individuals and society: A literature review\u003c/em\u003e. York Publishing Services for Joseph Rowntree Foundation. https://ora.ox.ac.uk/objects/uuid:820a69b6-a83e-47af-8e4b-ea3dd921655a\u003c/li\u003e\n\u003cli\u003eGuio, A.-C., Gordon, D., Marlier, E., Najera, H., \u0026amp; Pomati, M. (2018). Towards an EU measure of child deprivation. \u003cem\u003eChild Indicators Research\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(3), 835\u0026ndash;860. https://doi.org/10.1007/s12187-017-9491-6\u003c/li\u003e\n\u003cli\u003eHeppt, B., Olczyk, M., \u0026amp; Volodina, A. (2022). Number of books at home as an indicator of socioeconomic status: Examining its extensions and their incremental validity for academic achievement. \u003cem\u003eSocial Psychology of Education\u003c/em\u003e, \u003cem\u003e25\u003c/em\u003e(4), 903\u0026ndash;928. https://doi.org/10.1007/s11218-022-09704-8\u003c/li\u003e\n\u003cli\u003eHock, E. S., Blank, L., Fairbrother, H., Clowes, M., Cuevas, D. C., Booth, A., Clair, A., \u0026amp; Goyder, E. (2024). Exploring the impact of housing insecurity on the health and wellbeing of children and young people in the United Kingdom: A qualitative systematic review. \u003cem\u003eBMC Public Health\u003c/em\u003e, \u003cem\u003e24\u003c/em\u003e(1), 2453. https://doi.org/10.1186/s12889-024-19735-9\u003c/li\u003e\n\u003cli\u003eHurwitz, L. B., \u0026amp; Schmitt, K. L. (2020). Can children benefit from early internet exposure? Short- and long-term links between internet use, digital skill, and academic performance. \u003cem\u003eComputers \u0026amp; Education\u003c/em\u003e, \u003cem\u003e146\u003c/em\u003e, 103750. https://doi.org/10.1016/j.compedu.2019.103750\u003c/li\u003e\n\u003cli\u003eKaul, T. (2018). Intra-household allocation of educational expenses: Gender discrimination and investing in the future. \u003cem\u003eWorld Development\u003c/em\u003e, \u003cem\u003e104\u003c/em\u003e, 336\u0026ndash;343. https://doi.org/10.1016/j.worlddev.2017.12.017\u003c/li\u003e\n\u003cli\u003eKazakova, Y., Leturcq, M., \u0026amp; Panico, L. (2024). Multidimensional Child Deprivation: Constructing Longitudinal Indicators for the Early Childhood Period. \u003cem\u003eChild Indicators Research\u003c/em\u003e, \u003cem\u003e17\u003c/em\u003e(6), 2629\u0026ndash;2669. https://doi.org/10.1007/s12187-024-10178-7\u003c/li\u003e\n\u003cli\u003eKerrins, L., Greene, S., \u0026amp; Murphy, S. (2011). \u003cem\u003eGoing Without: Measuring Child Poverty and Social Exclusion in Ireland\u003c/em\u003e. Combat Poverty Agency. http://hdl.handle.net/10147/219871\u003c/li\u003e\n\u003cli\u003eKeski-Rahkonen, A., Kaprio, J., Rissanen, A., Virkkunen, M., \u0026amp; Rose, R. J. (2003). Breakfast skipping and health-compromising behaviors in adolescents and adults. \u003cem\u003eEuropean Journal of Clinical Nutrition\u003c/em\u003e, \u003cem\u003e57\u003c/em\u003e(7), 842\u0026ndash;853. https://doi.org/10.1038/sj.ejcn.1601618\u003c/li\u003e\n\u003cli\u003eKnies, G. (2022). Effects of Income and Material Deprivation on Children\u0026rsquo;s Life Satisfaction: Evidence from Longitudinal Data for England (2009-2018). \u003cem\u003eJournal of Happiness Studies\u003c/em\u003e, \u003cem\u003e23\u003c/em\u003e(4), 1469\u0026ndash;1492. https://doi.org/10.1007/s10902-021-00457-3\u003c/li\u003e\n\u003cli\u003eLayte, R., Nolan, B., \u0026amp; Whelan, C. (2000). Ten: Poverty and affluence in Ireland: A comparison of income and deprivation approaches to the measurement of poverty. In \u003cem\u003eBreadline Europe\u003c/em\u003e (pp. 203\u0026ndash;222). Policy Press. https://doi.org/10.51952/9781447366584.ch010\u003c/li\u003e\n\u003cli\u003eLi, M., \u0026amp; Chzhen, Y. (2024). Parental investment or parenting stress? Examining the links between poverty and child development in Ireland. \u003cem\u003eEuropean Societies\u003c/em\u003e, \u003cem\u003e26\u003c/em\u003e(4), 911\u0026ndash;951. https://doi.org/10.1080/14616696.2023.2275592\u003c/li\u003e\n\u003cli\u003eLundy, L. (2007). \u0026lsquo;Voice\u0026rsquo; is not enough: Conceptualising Article 12 of the United Nations Convention on the Rights of the Child. \u003cem\u003eBritish Educational Research Journal\u003c/em\u003e, \u003cem\u003e33\u003c/em\u003e(6), 927\u0026ndash;942. https://doi.org/10.1080/01411920701657033\u003c/li\u003e\n\u003cli\u003eMadden, D. (2022). The Dynamics of Multidimensional Poverty in a Cohort of Irish Children. \u003cem\u003eChild Indicators Research\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e(5), 1631\u0026ndash;1671. https://doi.org/10.1007/s12187-022-09921-9\u003c/li\u003e\n\u003cli\u003eMadden, D. (2024). Mental health in Ireland during the Covid pandemic: Evidence from two longitudinal surveys. \u003cem\u003ePloS One\u003c/em\u003e, \u003cem\u003e19\u003c/em\u003e(3), e0279526. https://doi.org/10.1371/journal.pone.0279526\u003c/li\u003e\n\u003cli\u003eMain, G. (2018). Fair Shares and Families: A Child-Focused Model of Intra-Household Sharing. \u003cem\u003eChildhood Vulnerability Journal\u003c/em\u003e, \u003cem\u003e1\u003c/em\u003e(1), 31\u0026ndash;49. https://doi.org/10.1007/s41255-019-00001-9\u003c/li\u003e\n\u003cli\u003eMain, G., \u0026amp; Bradshaw, J. (2012). A Child Material Deprivation Index. \u003cem\u003eChild Indicators Research\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e(3), 503\u0026ndash;521. https://doi.org/10.1007/s12187-012-9145-7\u003c/li\u003e\n\u003cli\u003eMa\u0026icirc;tre, B., Nolan, B., \u0026amp; Whelan, C. T. (2006). \u003cem\u003eReconfiguring the Measurement of Deprivation and Consistent Poverty in Ireland\u003c/em\u003e (Report No. 58; Policy Research Series). ESRI. https://doi.org/10.26504/prs58\u003c/li\u003e\n\u003cli\u003eMa\u0026icirc;tre, B., Russell, H., \u0026amp; Smyth, E. (2021). \u003cem\u003eThe dynamics of child poverty in Ireland: Evidence from the Growing Up in Ireland survey\u003c/em\u003e (Report No. 121; ESRI Research Series). ESRI. https://doi.org/10.26504/rs121\u003c/li\u003e\n\u003cli\u003eMcCormick, R. (2017). Does Access to Green Space Impact the Mental Well-being of Children: A Systematic Review. \u003cem\u003eJournal of Pediatric Nursing\u003c/em\u003e, \u003cem\u003e37\u003c/em\u003e, 3\u0026ndash;7. https://doi.org/10.1016/j.pedn.2017.08.027\u003c/li\u003e\n\u003cli\u003eMiller-Perrin, C. L., Perrin, R. D., \u0026amp; Kocur, J. L. (2009). Parental physical and psychological aggression: Psychological symptoms in young adults. \u003cem\u003eChild Abuse \u0026amp; Neglect\u003c/em\u003e, \u003cem\u003e33\u003c/em\u003e(1), 1\u0026ndash;11. https://doi.org/10.1016/j.chiabu.2008.12.001\u003c/li\u003e\n\u003cli\u003eMills, C., Guerin, S., Lynch, F., Daly, I., \u0026amp; Fitzpatrick, C. (2004). The relationship between bullying, depression and suicidal thoughts/behaviour in Irish adolescents. \u003cem\u003eIrish Journal of Psychological Medicine\u003c/em\u003e, \u003cem\u003e21\u003c/em\u003e(4), 112\u0026ndash;116. Cambridge Core. https://doi.org/10.1017/S0790966700008521\u003c/li\u003e\n\u003cli\u003eNolan, B. (2000). \u003cem\u003eChild Poverty in Ireland\u003c/em\u003e. Oak Tree Press in association with Combat Poverty Agency.\u003c/li\u003e\n\u003cli\u003eO\u0026rsquo;Donnell, A. W., Redmond, G., Gardner, A. A., Wang, J. J. J., \u0026amp; Mooney, A. (2024). Extracurricular activity participation, school belonging, and depressed mood: A test of the compensation hypothesis during adolescence. \u003cem\u003eApplied Developmental Science\u003c/em\u003e, \u003cem\u003e28\u003c/em\u003e(4), 596\u0026ndash;611. https://doi.org/10.1080/10888691.2023.2260745\u003c/li\u003e\n\u003cli\u003ePastore, D. R., Fisher, M., \u0026amp; Friedman, S. B. (1996). Abnormalities in weight status, eating attitudes, and eating behaviors among urban high school students: Correlations with self-esteem and anxiety. \u003cem\u003eJournal of Adolescent Health\u003c/em\u003e, \u003cem\u003e18\u003c/em\u003e(5), 312\u0026ndash;319. https://doi.org/10.1016/1054-139X(95)00321-I\u003c/li\u003e\n\u003cli\u003eRaphael, D. (2011). Poverty in childhood and adverse health outcomes in adulthood. \u003cem\u003eMaturitas\u003c/em\u003e, \u003cem\u003e69\u003c/em\u003e(1), 22\u0026ndash;26. https://doi.org/10.1016/j.maturitas.2011.02.011\u003c/li\u003e\n\u003cli\u003eRegan, M., \u0026amp; Ma\u0026icirc;tre, B. (2020). \u003cem\u003eChild poverty in Ireland and the pandemic recession\u003c/em\u003e (No. 04; Budget Perspectives 2021). ESRI. https://doi.org/10.26504/bp202104\u003c/li\u003e\n\u003cli\u003eReynolds-Salmon, R., Samms-Vaughan, M., Coore-Desai, C., Reece, J., \u0026amp; Pellington, S. (2024). Does household size matter? Crowding and its effects on child development. \u003cem\u003ePsychology, Health \u0026amp; Medicine\u003c/em\u003e, \u003cem\u003e29\u003c/em\u003e(6), 1165\u0026ndash;1178. https://doi.org/10.1080/13548506.2024.2326867\u003c/li\u003e\n\u003cli\u003eRoantree, B., Ma\u0026icirc;tre, B., \u0026amp; Russell, H. (2024). \u003cem\u003ePoverty, income inequality and living standards in Ireland: Fourth annual report\u003c/em\u003e [Report]. ESRI and Community Foundation Ireland. https://doi.org/10.26504/jr7\u003c/li\u003e\n\u003cli\u003eRoantree, B., Russell, H., Alamir, A., Griffin, M., Ma\u0026icirc;tre, B., \u0026amp; Mitchell, T. (2025). \u003cem\u003ePoverty, income inequality and living standards in Ireland: Fifth annual report\u003c/em\u003e [Report]. ESRI and Community Foundation Ireland. https://doi.org/10.26504/jr14\u003c/li\u003e\n\u003cli\u003eRussell, H., Ma\u0026icirc;tre, B., Alamir, A., \u0026amp; Slevin, E. (2025). \u003cem\u003eChild poverty on the island of Ireland\u003c/em\u003e (Report No. 199; ESRI Research Series). ESRI. https://doi.org/10.26504/rs199\u003c/li\u003e\n\u003cli\u003eSivadasan, J., \u0026amp; Xu, W. (2021). Missing women in India: Gender-specific effects of early-life rainfall shocks. \u003cem\u003eWorld Development\u003c/em\u003e, \u003cem\u003e148\u003c/em\u003e, 105652. https://doi.org/10.1016/j.worlddev.2021.105652\u003c/li\u003e\n\u003cli\u003eSmyth, E., \u0026amp; Darmody, M. (2025). \u003cem\u003eExperience of bullying and bullying behaviours in childhood and adolescence\u003c/em\u003e (Report No. 216; ESRI Research Series). ESRI. https://doi.org/10.26504/rs216\u003c/li\u003e\n\u003cli\u003eSmyth, E., \u0026amp; Murray, A. (2022). The effect of pandemic‐related economic disruption on young adolescents in Ireland. \u003cem\u003eChildren\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e(7). https://doi.org/10.3390/children9071037\u003c/li\u003e\n\u003cli\u003eSocial Justice Ireland. (2024, May 29). \u003cem\u003eAddressing Ireland\u0026rsquo;s Housing Crisis: Urgent Policy Reforms Needed\u003c/em\u003e. https://www.socialjustice.ie/article/addressing-irelands-housing-crisis-urgent-policy-reforms-needed\u003c/li\u003e\n\u003cli\u003eSollis, K. (2019). \u003cem\u003eMeasuring Child Deprivation and Opportunity in Australia\u003c/em\u003e. ARACY. https://www.aracy.org.au/wp-content/uploads/2024/09/ARACY_Measuring_child_deprivation_and_opportunity_in_Australia.pdf\u003c/li\u003e\n\u003cli\u003eSprong, S., Gibbons, R. A., \u0026amp; Chzhen, Y. (2023). Divergent trajectories: Three dimensions of child poverty during the Great Recession in Ireland. \u003cem\u003eLongitudinal and Life Course Studies\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(1), 128\u0026ndash;137. https://doi.org/10.1332/175795921X16551460545543\u003c/li\u003e\n\u003cli\u003eThornton, R., O\u0026rsquo;Carroll, N., McGovern, A., \u0026amp; Boylan, H. (2025). \u003cem\u003eMinimum Essential Standard of Living 2025\u003c/em\u003e. Vincentian MESL Research Centre. https://www.budgeting.ie/download/pdf/mesl_2025.pdf\u003c/li\u003e\n\u003cli\u003eTownsend, P. (1979). \u003cem\u003ePoverty in the United Kingdom: A Survey of Household Resources and Standards of Living\u003c/em\u003e. Penguin Books.\u003c/li\u003e\n\u003cli\u003eUNICEF. (2020). \u003cem\u003eMeasuring and Monitoring Child Poverty- Position Paper\u003c/em\u003e. https://data.unicef.org/resources/measuring-and-monitoring-child-poverty/\u003c/li\u003e\n\u003cli\u003eUNICEF. (2025). Violent discipline. \u003cem\u003eUNICEF DATA\u003c/em\u003e. https://data.unicef.org/topic/child-protection/violence/violent-discipline/\u003c/li\u003e\n\u003cli\u003eUnited Nations. (1989). \u003cem\u003eUnited Nations Convention on the Rights of the Child\u003c/em\u003e. https://www.ohchr.org/sites/default/files/Documents/ProfessionalInterest/crc.pdf\u003c/li\u003e\n\u003cli\u003eWhelan, A., Devlin, A., McGuinness, S., \u0026amp; Redmond, P. (2023). \u003cem\u003ePandemic unemployment and social disadvantage in Ireland\u003c/em\u003e (Report No. 163; ESRI Research Series). ESRI. https://doi.org/10.26504/rs163\u003c/li\u003e\n\u003cli\u003eWhelan, C. T., \u0026amp; Ma\u0026icirc;tre, B. (2012). Identifying Childhood Deprivation: How Well Do National Indicators of Poverty and Social Exclusion in Ireland Perform? \u003cem\u003eThe Economic and Social Review\u003c/em\u003e, \u003cem\u003e43\u003c/em\u003e(2, Summer), 251\u0026ndash;272.\u003c/li\u003e\n\u003cli\u003eWilliams, J., Murray, A., \u0026amp; Whelan, C. T. (2014). Multi-Dimensional Deprivation Among 9-Year-Olds in Ireland: An Analysis of the Growing Up in Ireland Survey. \u003cem\u003eChild Indicators Research\u003c/em\u003e, \u003cem\u003e7\u003c/em\u003e(2), 279\u0026ndash;300. https://doi.org/10.1007/s12187-013-9215-5\u003c/li\u003e\n\u003cli\u003eWoods, C., Ng, K., Britton, U., McClelland, J. F., O\u0026rsquo;Keeffe, B., Sheikhi, A., McFlynn, P., Murphy, M., Goss, H., Behan, S., Philpott, C., Lester, D., Adamakis, M., Costa, J., Coppinger, T., Connolly, S., Belton, S., \u0026amp; O\u0026rsquo;Brien, W. (2023). \u003cem\u003eChildren\u0026rsquo;s Sport Participation and Physical Activity Study 2022\u003c/em\u003e. Physical Activity for Health Research Centre, Department of Physical Education and Sport Sciences, University of Limerick, Limerick, Ireland, Sport Ireland and Healthy Ireland, Dublin, Ireland and Sport Northern Ireland, Belfast, Northern Ireland. https://doi.org/10.34961/RESEARCHREPOSITORY-UL.23609157\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Multidimensional deprivation, Child poverty, Child rights, Ireland, Inequalities","lastPublishedDoi":"10.21203/rs.3.rs-7790955/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7790955/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDespite an increasing body of literature that conceptualises child poverty as distinct from household poverty, it is still commonly measured as the proportion of children living in low-income households. This study uses longitudinal data from the Growing Up in Ireland study on a cohort of children born in 2008. The child rights framework was applied to identify six dimensions of child deprivation: nutrition, access to healthcare, protection from violence, access to information, leisure, and housing. Combining these dimensions into an index of child deprivation at ages 9 and 13 shows that household income poverty alone is insufficient for identifying deprived children. However, low income remains a statistically significant predictor of child deprivation. Notably, transitions into multidimensional deprivation were more prevalent than transitions into the lowest income bracket over time. Children whose mothers were single or had a lower level of education were more likely to experience multidimensional deprivation at ages 9 and 13. At age 13, girls were at a higher risk of deprivation than boys. Overall, this study highlights the potential of rights-informed multidimensional deprivation indices to identify areas of deprivation that are less dependent on household income. The study indicates the advantages of using child-centred indices over household-level measures when suggesting policy interventions to combat child deprivation in higher-income countries.\u003c/p\u003e","manuscriptTitle":"Multidimensional Child Deprivation in Ireland: A New Child Rights-Informed Approach","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-26 00:33:31","doi":"10.21203/rs.3.rs-7790955/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ced405ee-6b7a-45b5-9f2d-3b9e093532ba","owner":[],"postedDate":"October 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-09T16:04:50+00:00","versionOfRecord":{"articleIdentity":"rs-7790955","link":"https://doi.org/10.1007/s12187-026-10347-w","journal":{"identity":"child-indicators-research","isVorOnly":false,"title":"Child Indicators Research"},"publishedOn":"2026-03-07 15:57:49","publishedOnDateReadable":"March 7th, 2026"},"versionCreatedAt":"2025-10-26 00:33:31","video":"","vorDoi":"10.1007/s12187-026-10347-w","vorDoiUrl":"https://doi.org/10.1007/s12187-026-10347-w","workflowStages":[]},"version":"v1","identity":"rs-7790955","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7790955","identity":"rs-7790955","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}