Soc Indic Res DOI 10.1007/s11205-014-0731-6
Children’s Wellbeing in East and Southeast Asia: A Preliminary Comparison Esther Yin-Nei Cho
Accepted: 7 August 2014 Ó Springer Science+Business Media Dordrecht 2014
Abstract Much progress has been made recently in expanding the literature on international comparison of children’s wellbeing. Nevertheless, most studies are skewed toward western or European countries, with the Asian nations rarely included. The purpose of this study is to fill the gap by conducting an exploratory comparison of children’s wellbeing in East and Southeast Asian countries. A multidimensional approach is adopted by analyzing material wellbeing, health, educational wellbeing, behavior, environment, and psychosocial wellbeing, together with their associated components and indicators. All countries are ranked according to their overall child wellbeing indices, including and excluding the dimension of psychosocial wellbeing. The results show that Japan, Korea, and Singapore perform best while Malaysia, Vietnam, Thailand, and Indonesia do less well in terms of children’s wellbeing. Various issues, including the paucity of data, are discussed as items to be considered in the agenda for future research. Keywords Children’s wellbeing East and Southeast Asia Cross-national comparison Child indicators Ranking approach
1 Introduction Cross-national comparisons of children’s wellbeing have been conducted for more than a decade, starting in the late 1990s. Considerable progress has been made in identifying how it can be conceptualized, measured, and analyzed. Comparative studies of children’s
Electronic supplementary material The online version of this article (doi:10.1007/s11205-014-0731-6) contains supplementary material, which is available to authorized users. E. Y.-N. Cho (&) Department of Social Work, Hong Kong Baptist University, 10/F, Academic and Administration Building, Baptist University Road Campus, Kowloon Tong, Hong Kong e-mail:
[email protected]
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wellbeing are of great value. Not only can they provide trend information to monitor children’s status in individual countries, they also serve as benchmark for countries to compare their performance with that of others (Phipps 2006). However, such comparative studies on children’s wellbeing are focused almost on western or European countries, targeting the Organization for Economic Cooperation and Development (OECD), European Union, and Central and Eastern European nations (Bradshaw et al. 2007; Dijkstra 2009; Heshmati et al. 2008; OECD 2009; Richardson et al. 2008; UNICEF 2007; UNICEF Office of Research 2013). It is seldom for Asian countries to be included in comparison studies. As OECD members, only Japan and Korea have ever been included in those western studies (UNICEF 2007; OECD 2009; UNICEF Office of Research 2013). One study examines the situation of children in Central Asia (Menchini et al. 2009). Another study by Lau and Bradshaw (2010) covers Asian countries in the Pacific Rim, yet it suffers from data inconsistencies which make effective comparison difficult. Data for comparison comes from a wide range of years. For example, indicators of child wellbeing under the domain of living environment are obtained from the year of 2001, 2006, and 2008. Data is also missing for different countries under different components or domains of child wellbeing. There is missing data for eight out of 13 countries, for instance, in certain components under the domain of subjective wellbeing. Comparison of the overall child wellbeing could be particularly problematic when the overall child wellbeing indices are constructed based on such data. The Child Development Index (CDI), which was launched in 2008 to assess children’s development worldwide, also covers the Asian nations (Cobham et al. 2012). However, its emphasis is on the most basic threats to child survival. Reliance on the three indicators which make up the CDI, namely child mortality, nutrition, and access to primary education, may not be sufficient to describe the quality of life of children in the developed world. In fact, current discussion and measurement of child wellbeing has already begun shifting its emphasis from basic survival to more multifaceted development needs (Ben-Arieh et al. 2001; Ben-Arieh 2008). Such an emphasis may be reflected in how children’s wellbeing can be defined, as ‘‘the realization of children’s rights and the fulfillment of the opportunity for every child to be all she or he can be in the light of a child’s abilities, potential and skills’’ (Bradshaw et al. 2007:8). Therefore, children’s wellbeing in Asia is still largely excluded from the current body of knowledge. To fill this gap in the literature, the purpose of this study is to compare children’s wellbeing in East and Southeast Asian regions based on best available data. As one of the initial steps in extending the global picture toward the east, this study attempts to align with existing work by employing similar dimensions and indicators of child wellbeing, and the most frequently used analytical method. However, due to a paucity of data, it is not possible for this work to include all the indicators and it should therefore be considered as a preliminary study. The following sections highlight the accomplishments and challenges in existing work, compare selected countries in East and Southeast Asia using the ranking method, and discuss the implications for future research.
2 An Overview of Major Accomplishments and Challenges Although the comparison of children’s wellbeing is a relatively recent development, it has been a topic of research in this area for around two decades. The literature can be briefly reviewed in terms of its major accomplishments and remaining challenges. The former include making children a visible population with explicit measures of their wellbeing,
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transcending boundaries to promote cross-national understanding, and expanding the use of appropriate tools for conducting comparisons. The challenges include data comparability and national coverage. 2.1 Making Children a Visible Population Children became more visible as a group when their wellbeing started to receive separate attention and specific monitoring in the late 1970s. This period can be considered the beginning of the child indicators movement. The movement followed its antecedent, the social indicators movement, which first emerged in the 1960s with Bauer’s (1966) Social Indicators, when policymakers began calling for statistical indicators to be used to track social change and monitor the impact of policy. Along with the gradual understanding that childhood should be considered as a life stage in and of itself (Ben-Arieh 2008), the development of child indicators helped to further underscore the significance of children as a unique population. Rather than being regarded as mere members of households or offspring of adult parents, children’s wellbeing in their own right can be uniquely defined and measured. An evolving process has ensued, in which the emphasis on defining and measuring children’s wellbeing has shifted over time. The characteristics of those shifts are discussed in detail by Ben-Arieh et al. (2001) and Ben-Arieh (2008). In short, the focus of work on children’s wellbeing and the choice of suitable indicators have changed from basic survival needs to promotion of child development, from negative to positive outcomes, from wellbecoming to wellbeing, from limited to multidimensional indicators, and from children as passive objects to children as active subjects. 2.2 Transcending Boundaries for Cross-National Understanding Another accomplishment of this strand of research is that the study of children’s wellbeing has transcended locality or national boundaries to enable cross-national comparisons. Early work focused on single geographical areas or nations (Ben-Arieh et al. 2001), but since the late 1990s, more research has been directed towards international comparisons (Ben-Arieh 1999; Ben-Arieh and Wintersberger 1997; Ben-Arieh and Goerge 2001; Bradshaw et al. 2007; Heshmati et al. 2008; Dijkstra 2009; Richardson et al. 2008; UNICEF 2007; UNICEF Office of Research 2013; Lau and Bradshaw 2010; Cho 2014). Such international comparisons allow internal performance to be benchmarked such that individual countries can gauge their performance by comparing it with that of other nations with similar characteristics (Phipps 2006). This may draw the attention of policymakers and persuade them to make policy changes to improve outcomes for children. Accompanying the introduction of the cross-boundary study came a change in the research agenda. Early work was primarily social-service oriented, focusing on topics such as daycare, health, or housing (Ben-Arieh et al. 2001). To enable comparability across countries, more recent studies have adopted a multidimensional framework in which children’s wellbeing is conceptualized along different dimensions, each represented by one of a variety of indicators. Despite slight discrepancies between individual studies, the dimensions that have generally been included are material wellbeing, health and safety, education, behaviors and risks, housing, subjective wellbeing, relationships, and civic participation (Bradshaw et al. 2007; UNICEF 2007; Heshmati et al. 2008; Richardson et al. 2008; Dijkstra 2009; OECD 2009; UNICEF Office of Research 2013; Lau and Bradshaw
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2010; Cho 2014). A range of 21–51 indicators, depending on the dimensions included, are generally employed in these studies. The results of such work vary, but a pattern has clearly emerged in which children in the Nordic countries tend to fare better than others. Based on the work of UNICEF (2007), children in the Netherlands and Sweden do best whereas those in the US and UK are worst off. The Netherlands, Sweden, Norway, Spain, and Denmark are at the top and the UK and the Russian Federation are at the bottom of the league table, according to Heshmati et al. (2008). Another report suggests that Iceland and Sweden rank highly while Greece and Mexico score poorly (OECD 2009). The Nordic countries continued to perform well and the US poorly in another recent study (UNICEF Office of Research 2013). In another analysis, the Nordic countries plus a mix of the continental European and Anglo-Saxon nations are identified as the leaders in children’s wellbeing while the US, Latvia, Lithuania, and Romania are the laggards (Cho 2014). 2.3 Expanding the Use of Appropriate Tools for Comparison The most frequently used tool for comparing children’s wellbeing is the ranking method (Bradshaw et al. 2007; UNICEF 2007; OECD 2009) which has recently been complemented by the use of the clustering approach (Cho 2014). In the ranking method, the individual scores for the indicators of wellbeing are aggregated into component and then dimensional scores. Usually, the ranks of the dimensional scores are averaged to obtain the overall country ranking, resulting in a league table to identify countries who lead and who lag behind. Heshmati et al. (2008) and Dijkstra (2009) use more sophisticated techniques to augment the ranking method, such as weighting each component before aggregation. However, their results show that the ranking approach without weighting is equally accurate and robust (Dijkstra 2009). While ranking with league tables provides an easy means of comparison, it may conceal other, useful information. The clustering approach, in which countries are classified into groups based on their similarities and differences according to the dimensions of children’s wellbeing, has been suggested as a means to complement the ranking method (Cho 2014). Although no individual ranking of countries exists, the clusters imply a ranking from the best to the worst performance. Profile characteristics of each cluster in terms of the dimensions of children’s wellbeing can also be identified. Including more information of this kind may open up more possibilities for further analysis, such as examining the underlying dynamics of the clustering pattern to yield policy proposals for improving children’s wellbeing (Cho 2014). 2.4 Comparability of Data and Coverage of Countries The biggest challenge in comparing children’s wellbeing is the issue of data comparability. Carrying out a comparison between countries requires the relevant data to be available and up to date. However, there is often a problem with full data not being available for all countries. A total of 51, 40, 21, and 26 indicators are used by Bradshaw et al. (2007), UNICEF (2007), OECD (2009), and UNICEF Office of Research (2013), respectively. Such inconsistency could be in part due to unavailable data for some of the countries included. While the data used could be survey or administrative in nature, and not specifically intended for use in monitoring children’s wellbeing, the selection of indicators in a study is often data-driven as a result. The timeliness of data also makes comparability challenging. Timing of data collection could vary for different sources, so the age of the
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most up to date data available may be different for different indicators. For instance, data from the Programme for International Student Assessment (PISA) used for measuring educational indicators is collected every 3 years while data from the Health Behavior in School-Aged Children Survey used to measure behaviors and risks indicators is collected every 4 years. Moreover, the coverage of countries is also an issue. As discussed above, Asian countries are largely omitted in the current literature. This may be because they have been given insufficient research attention, but the difficulty of comparing data may also be a hurdle to their inclusion.
3 Methods Based on the available data, this study compares the wellbeing of children in 11 countries or cities in East and Southeast Asia; China, Hong Kong, Indonesia, Japan, Korea, Macau, Malaysia, Singapore, Taiwan, Thailand, and Vietnam. With some variations, the adoption of dimensions, components, and indicators of children’s wellbeing, as well as the analytical method, are chosen to be compatible with the existing literature. 3.1 Data and Variables This study uses six dimensions of children’s wellbeing, namely material wellbeing, health, educational wellbeing, behavior, environment, and psychosocial wellbeing, based on a recent study (UNICEF Office of Research 2013) with some modifications. In previous work, the dimension of material wellbeing has comprised the components monetary and material deprivation. However, data for child poverty, which indicates monetary deprivation, is unavailable for most countries since they do not report child poverty statistics. This study thus only retains the component of material deprivation, measured by two indicators; item deprivation rate and books deprivation rate. The dimension of health comprises health at birth, indicated by infant mortality rate and low birth weight, and preventive health services, measured by immunization rates. A third component, childhood mortality, is not included due to a lack of relevant data. Thirdly, educational wellbeing is composed of two components, achievement and participation. Achievement is measured by PISA scores. Participation is measured by preprimary and secondary school gross enrollment ratios. A third indicator, NEET (not in education, employment, or training) for participation is not included as data are not available. The fourth dimension is behaviors. In previous work, this has been conceptualized as behaviors and risks, made up of the components of risk behaviors, health behaviors, and exposure to violence. Since there are no data on health behaviors and exposure to violence, this study retains the component of risk behaviors, measured by the rates of smoking and adolescent fertility. The fifth dimension is environment, which in existing work is comprised of housing and environment. Without data on housing problems, in this study this dimension is made up of the component of environmental safety, which is represented by homicide rate and air quality. Finally, psychosocial wellbeing is represented by the component of relationship with peers at school, which is further indicated by how children feel about themselves in relation to their peers. Self-assessment of peer relationship is a form of subjective wellbeing, which is treated differently in various studies. Some consider subjective wellbeing
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as a different topic which deserves separate attention. Others include it in the analysis while noting that it comprises various elements, such as relationships with parents and peers, life satisfaction, and self-reported health status. Table 1 shows the links between the dimensions, components, and indicators, as well as the definition for each indicator. A major difficulty facing this study is the scarcity of data for various indicators, such as child poverty or housing condition. Therefore, not all the potentially useful indicators could be included. Some popular measures, such as those for health, can be found in existing databases, but data for certain countries is missing. It is thus necessary to search for relevant data within local government reports for individual countries. The sources of data used in this study are shown in the third column of Table 1. The online addresses of those data sources are given in Appendix 1. Appendix 2 presents the raw data for each indicator. 3.2 Analysis This study applies the ranking method of comparing children’s wellbeing. This involves various steps. Firstly, all indicator scores are converted into standardized scores. Some standardized indicator scores are reverse coded so that they all run in the same direction, with the highest positive scores meaning the most favorable conditions. Secondly, all standardized indicator scores under each component are summed and averaged to obtain the component scores. Similarly, all component scores under each dimension are summed and averaged to arrive at the dimension scores. An overall index is then computed by averaging the aggregate of all the dimension scores. Consequently, the overall indices could be ranked to show which countries lead or lag behind in children’s wellbeing.
4 Findings 4.1 Comparing Indicators and Dimensions of Children’s Wellbeing Figure 1 compares the dimension of material wellbeing across countries. In terms of item deprivation, Korea, Singapore, and Hong Kong have the lowest rates whereas Indonesia has the highest. As for books deprivation, Korea is the least deprived whereas Macau, Indonesia, and Vietnam are the most deprived. The dimension score represents the overall performance of material wellbeing. Korea fares best and Indonesia the worst. The health dimension has two components, as noted earlier. The ranking for health at birth is illustrated in Fig. 2. Hong Kong and Indonesia have the lowest and highest infant mortality rates, respectively. China and Malaysia have the lowest and highest proportion of babies born with low birth weight, respectively. Looking at the component of preventive health services, shown in Fig. 3, most countries fare similarly in terms of immunization rates, with Hong Kong having the highest and Indonesia lagging behind all the other countries. As a whole, most countries do reasonably well in terms of health indicators, with Hong Kong and Korea the best performers and Indonesia the worst. Turning to the dimension of educational wellbeing, Fig. 4 presents the results for the achievement component. The majority of countries have an average score across different subjects of well over 500, but China performs noticeable better than the others. Indonesia and Malaysia have much lower average scores than the other countries. The component of participation is illustrated in Fig. 5. In terms of preprimary school gross enrollment ratio, Korea has the highest and Taiwan the lowest. Singapore has the highest secondary school
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Definition of indicator
Immunization rates: Percentages of children under two who received vaccination against measles, polio, and DPT3 (diphtheria, pertussis, and tetanus)
Low birth weight: Percentage of babies weighing below 2.5 kg at birth
Achievement
PISA score: Average score in PISA (Programme for International Student Assessment) tests of reading, mathematics, and science literacy for 15-year-olds
2009 2011 2011
*Department of Health (2010) [Hong Kong]; *Servic¸os de Sau´de (2012) [Macau]; *Department of Health (2011) [Taiwan]
2012
2011
Global Health Observatory Data Repository, World Health Organization; other reports*
PISA Database, OECD
2011 2011 2011 2011
2011
*The World Factbook 2011, Central Intelligence Agency (2011) [Macau] UNdata, United Nations Statistics Division; other reports* *Department of Health (2013) [Hong Kong]; *Servic¸os de Sau´de (2012) [Macau]; *Ministry of Health and Welfare (2013) [Taiwan]
2011
Statistical Database System, Asia Development Bank; other report*
2012
PISA Database, OECD
Books deprivation rate: Percentage of children aged 15 reporting less than 10 books at home
Infant mortality rate: Number of deaths per 1,000 of infants under 12 months old
2012
Year of data
PISA Database, OECD
Source of data
Item deprivation rate: Percentage of children aged 15 reporting less than five out of seven items at home. Items include: (1) a desk to study at, (2) a quiet place to study, (3) a computer for school work, (4) educational software, (5) an internet connection, (6) a dictionary, and (7) school textbooks
Dimension 3: educational wellbeing
Preventive health services
Health at birth
Dimension 2: health
Material deprivation
Dimension 1: material wellbeing
Component
Table 1 Components and indicators for each dimension of children’s wellbeing
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Adolescent fertility rate: Number of births per 1,000 girls aged 15–19 Smoking rate: Percentage of young people aged 13–15 who reported smoking at least one cigarette during the last 30 days
Homicide rate: Annual number of homicides per 100,000 population
Air pollution: Annual concentration of particulate matter smaller than 10 lm (annual PM 10 [lg/m3])
Safety
Air quality
Dimension 5: environment
Risk behaviors
2010
*Department of Health (2011) [Taiwan]
World Development Indicators, World Bank; other reports* *Environmental Protection Department (2011) [Hong Kong]; *Environmental Protection Administration (2011) [Taiwan]; *Air Quality Historical Data, The Macao Meteorological and Geophysical Bureau [Macau]
2010 2010 2010 2010
2008–2011 2006, 2009
2010
*WHO Report on the Global Tobacco Epidemic, World Health Organization (2013) [Japan];
United Nations Office on Drugs and Crime; other report* *United Nations Office on Drugs and Crime (2011) [Malaysia & Taiwan]
2009, 2010
*Global Tobacco Surveillance System Data, Center for Disease Controls and Prevention [Hong Kong & Macau];
World Development Indicators, World Bank; other reports* *Schwab (Ed.) (2013) [Singapore &Vietnam]; *Ministry of Education (2013) [Taiwan]
Secondary school gross enrollment ratio: Total enrollment in secondary education, regardless of age, expressed as a percentage of the population of official secondary education age
2011 2011 2010
2011 2012 2011 2011 2011 2010
World Development Indicators, World Bank; other reports* *Ministry of Education (2012) [Singapore]; *Ministry of Education (2013) [Taiwan]
Preprimary school gross enrollment ratio: Total enrollment in preprimary education, regardless of age, expressed as a percentage of the total population of official preprimary education age
World Development Indicators, World Bank; other report* *Ministry of Health and Welfare (2012) [Taiwan] Global Youth Tobacco Survey, World Health Organization; other reports*
Year of data
Source of data
Definition of indicator
Dimension 4: behaviors
Participation
Component
Table 1 continued
E. Y.-N. Cho
Definition of indicator
Peer relationship
Assessment of peer relationship: Percentages of children aged 15 who agree with the statement: ‘I feel like an outsider (or left out of things) at school.’ ‘I feel awkward and out of place in my school.’ ‘Other students seem to like me.’ ‘I feel happy at school.’ ‘I feel lonely at school.’
Dimension 6: psychosocial wellbeing
Component
Table 1 continued
PISA Database, OECD
Source of data
2012
Year of data
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Fig. 1 Dimension of material wellbeing
Fig. 2 Dimension of health and health at birth
gross enrollment ratio and Malaysia the lowest. Considering the dimension of educational wellbeing, Singapore and Korea fare best and Indonesia and Malaysia the worst. Figure 6 shows the dimension of behaviors, as represented by the component of risky behavior. The smoking and fertility rates of adolescents in Japan and Korea are lowest, but both rates are highest in Indonesia. Japan performs the best and Indonesia the worst in terms of this dimension. Environmental safety is the sole component of the environment dimension. Figure 7 shows that Hong Kong is the safest country and Indonesia the most dangerous based on
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Fig. 3 Dimension of health and preventive health services
Fig. 4 Dimension of educational wellbeing and achievement
homicide rate. In terms of air quality, Malaysia has the best while Indonesia and China have the worst. Taking both indicators together, Singapore provides the most favorable and Indonesia the least favorable physical environment for children. The analysis of the dimension of psychosocial wellbeing, represented by relationships with peers at school, is presented in Fig. 8. Vietnam has the lowest proportion of children agreeing to the negative self-evaluation statements about feeling like an outsider, feeling
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Fig. 5 Dimension of educational wellbeing and participation
Fig. 6 Dimension of behaviors and risk behaviors
awkward and out of place, and feeling lonely. Thailand has the highest proportion of children agreeing to these negative statements. Along with Indonesia, Thailand also has the highest proportion of children agreeing to the positive statements of feeling liked by others and feeling happy at school. Although Korea fares relatively well in terms of many other indicators, this is not the case for positive self-evaluation. In general, Vietnam scores the highest on psychosocial wellbeing and Thailand the lowest.
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Fig. 7 Dimension of environment and safety and air quality. Asterisk value is multiplied by 10 for annual PM10
Based on these comparisons, it can be seen that children in Indonesia fare consistently poorly across most of the indicators. Indonesia is ranked at the bottom for all dimensions except psychosocial wellbeing. More economically advanced countries, such as Japan, Hong Kong, and Korea, are performing the best in terms of the indicators and dimensions of children’s wellbeing. Table 2 presents the overall index and dimension scores while Table 3 shows the overall ranking and ranking by dimension for the countries included in this study. 4.2 Overall Ranking of Children’s Wellbeing Referring to the right two columns of Table 2, an overall index for each country can be computed by taking all the dimension scores together. However, the discussion presented earlier has suggested that psychosocial wellbeing, as a type of subjective self-assessment, must be treated separately in an empirical analysis since it is conceptually different from the other dimensions in which the emphasis is on the objective assessment of the absence of deprivation (Bradshaw et al. 2013; Klocke et al. 2014). To address this issue, separate analyses were carried out with the dimension of psychosocial wellbeing included and excluded. The right two columns of Table 3 show the rankings of all countries according to the overall indices. It can be seen that there is only a slight variation in ranking for two of the countries when the dimension of psychosocial wellbeing is omitted; Malaysia ranks eighth and Vietnam ninth. However, Vietnam rises to eighth place above Malaysia when psychosocial wellbeing, in which it performs the best, is included. Japan, Korea, and Singapore are the top three nations whether or not the dimension of psychosocial wellbeing is included. Not only is Japan ranked first in the world in the CDI (Cobham et al. 2012), it is also the leader among the countries included in this study. Japan’s performance is particularly outstanding as it is in the top three in all dimensions of children’s wellbeing except health. Thailand and Indonesia are the worst performers in the
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Fig. 8 Dimension of psychosocial wellbeing
overall ranking. Indonesia fares particularly poorly, being consistently at the bottom of the league table in all dimensions except psychosocial wellbeing. As well as identifying the ranking of individual countries, a view of the overall indices presented in Table 3 may also offer some ideas about the extent of their differences. Japan, Korea, and Singapore are close to one another, with a small difference of 0.01 in overall index (psychosocial wellbeing excluded) between Japan and Korea. Likewise, China and Hong Kong are close counterparts, with a 0.01 and a 0.02 difference without and with psychosocial wellbeing, respectively. Taiwan and Macau lie approximately in the middle. Malaysia, Vietnam, Thailand, and Indonesia are relatively poor performers, but Indonesia is far behind the others, scoring around 1 and 1.2 points lower than the second-poorest performer, Thailand. Figure 9 illustrates the differences between the countries.
5 Discussion Based on these findings, various observations can be made which can also form the basis for a future research agenda. Firstly, there appears a tendency for the more economically advanced countries, such as Japan, Korea, and Singapore, to rank higher than the less economically developed countries, such as Malaysia, Thailand, and Indonesia. There are exceptions, such as Macau which has the highest gross domestic product (GDP) per capita of all the countries studied but only ranks seventh overall. However, there does not seem to be a strong relationship between GDP per capita and child wellbeing (UNICEF 2013). A simple correlation between GDP per capita and overall index was calculated in this study and the result was insignificant. But when the GDP per capita was log transformed, the logged GDP per capita was significantly correlated to the overall index including all dimensions (r = 0.62; p \ 0.05) and excluding psychosocial wellbeing (r = 0.64; p \ 0.05). This indicates that the relationship of GDP per capita and the child wellbeing
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0.14
0.01
0.19
0.09
-1.32
-0.62
-1.49
Malaysia
Vietnam
Thailand
Indonesia
0.17
-2.4
-0.10
-0.02
0.49
-0.52
0.69
0.50
Macau
0.28
Hong Kong
0.15
0.63
Taiwan
0.56
0.62
Singapore
Korea
China
0.69
1.20
Japan
0.55
-1.55
-0.47
-0.20
-1.27
0.28
0.05
0.50
0.54
0.85
0.71
-1.94
-1.05
0.01
-0.54
0.53
0.37
0.40
0.74
0.23
0.34
0.91
Behaviors
Environment
Psychosocial wellbeing
-1.70
-0.80
-0.17
0.80
0.05
-0.67
0.28
-0.22
1.06
0.36
1.00
0.04
-0.57
0.51
-0.29
-0.14
0.29
-0.01
0.12
-0.02
-0.15
0.22
-1.81
-0.55
-0.33
-0.20
0.07
0.08
0.43
0.44
0.57
0.65
0.66
Without psychosocial wellbeing
Educational wellbeing
Material wellbeing
Health
Overall index
Dimension scores of children’s wellbeing
Table 2 Overall index and dimension scores of children’s wellbeing
-1.50
-0.55
-0.19
-0.22
0.03
0.12
0.36
0.38
0.47
0.52
0.59
All dimensions
Children’s Wellbeing in East and Southeast Asia
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2
1
4
3
6
5
8
7
10
9
11
Japan
Korea
Singapore
China
Hong Kong
Taiwan
Macau
Malaysia
Vietnam
Thailand
Indonesia
6
11
4
8
10
9
5
1
3
7
2
3
11
9
8
10
6
7
5
4
1
2
11
10
8
9
3
5
4
2
7
6
1
Behaviors
Environment
Psychosocial wellbeing
11
10
7
3
6
9
5
8
1
4
2
5
11
1
10
8
2
6
4
7
9
3
11
10
9
8
7
6
5
4
3
2
1
Without psychosocial wellbeing
Educational wellbeing
Material wellbeing
Health
Overall ranking
Ranking by dimension of children’s wellbeing
Table 3 Overall ranking and ranking by dimension of children’s wellbeing
11
10
8
9
7
6
5
4
3
2
1
All dimensions
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Children’s Wellbeing in East and Southeast Asia
Fig. 9 Overall index and ranking of children’s wellbeing
index is not linear. The same magnitude of difference in GDP per capita is associated with a larger increase in the child wellbeing index in low- rather than high-income countries. Such a potential nonlinear association may be examined more closely by taking into account both Asian and non-Asian countries in further research. Secondly, subjective wellbeing does not necessarily relate positively to objective wellbeing. Counter-intuitively, Vietnam is ranked best in terms of psychosocial wellbeing while it does not fare particularly well in the other, objective dimensions. Similarly, Korea only ranks ninth in psychosocial wellbeing but performs well in other dimensions. It is perhaps plausible that there is a relationship between subjective and objective wellbeing, but it is not as direct as one may expect (Bradshaw et al. 2013). Children in a relatively deprived environment may report feeling happy, or vice versa, for many different reasons. It might be useful to explore both the mediating factors, which affect the strength of the relationship, and the moderating factors, which specify why it occurs, to develop our understanding of this. Nevertheless, a study of subjective wellbeing or its relationship with objective wellbeing may require separate attention to be paid to countries in different cultural regions, given that subjective wellbeing may well be culturally specific. For example, how the ideas of happiness and coping are conceptualized, and the particular routes for achieving satisfaction, may differ between individualistic and collectivist cultures. Thirdly, the results indicate that attention needs to be paid to the educational wellbeing of children in China and Taiwan. The PISA scores for China and Taiwan are based on the cities of Beijing and Taipei, as the national scores are not available. Thus, there could be a potential upward bias to the indicator of educational wellbeing in these countries as both Beijing and Taipei are considered to be relatively better developed areas. Analyses
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excluding China and Taiwan were also conducted and the other countries were found to follow the same ordering in terms of performance. Finally, it has to be emphasized that data limitations are a particularly big challenge to comparing children’s wellbeing in East and Southeast Asia. Although some databases, such as those maintained by the World Bank and United Nations, cover useful indicators, they only cover a proportion of countries in the region. Much effort is necessary to locate and obtain relevant data from local government reports in various countries. This study was therefore only able to include 11 countries or cities. Furthermore, many indicators used in previous child wellbeing studies are not available in the Asian region, so some components of children’s wellbeing cannot be included. For instance, the child poverty rate for the component of monetary deprivation, and information about eating breakfast, eating fruit, and exercising for the component of health behaviors, are not available. As well as comparing children’s wellbeing in East and Southeast Asia, it will be useful for further work to examine the factors that may associate with or explain such wellbeing. For example, the extent to which a country places child-focused objectives high on its national agenda may be partly represented by its financial commitment to child-focused policies or programs, as indicated by child-specific public expenditure. However, as yet, this kind of specific data is scarce in most of the countries studied. To advance the study of children’s wellbeing in East and Southeast Asia will accordingly require the barrier of data limitations to be overcome. In the long term, this will require international effort in the form of expanding the existing databases beyond nonAsian countries or initiating collaboration among child-focused academics or organizations in the region to enable the consistent collection and compilation of useful indicators.
6 Conclusion This is one of the earliest empirical studies to have set out to compare children’s wellbeing in East and Southeast Asia using a multidimensional approach. On the whole, Japan, Korea, and Singapore are the leaders while Malaysia, Vietnam, Thailand, and Indonesia are the lowest placed in the league table. Various topics, including the association between the income of countries and children’s wellbeing, the plausible relationship between subjective and objective wellbeing, and the issue of data limitations could be incorporated into the agenda for further research. Although the limited amount of data available means that this study may not be completely aligned with previous work on children’s wellbeing, in terms of the number of indicators and components, it has nonetheless filled a gap in our existing knowledge and moved the literature a step forward.
References Bauer, R. A. (Ed.). (1966). Social indicators. Cambridge, MA: MIT Press. Ben-Arieh, A. (1999). The international effort to measure and monitor the state of children: A summary and agenda for future. In A. B. Andrews & N. K. Kaufman (Eds.), Implementing the U.N. convention on the rights of the child: A standard of living adequate for development (pp. 33–46). Westport, CT: Praeger. Ben-Arieh, A. (2008). The child indicators movement: Past, present, and future. Child Indicators Research, 1, 3–16. Ben-Arieh, A., & Goerge, R. (2001). Beyond the numbers: How do we monitor the state of our children? Children and Youth Services Review, 23(8), 603–631.
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Children’s Wellbeing in East and Southeast Asia Ben-Arieh, A., Kaufman, H. N., Andrews, B. A., Goerge, R., Lee, B. J., & Aber, J. L. (2001). Measuring and monitoring children’s well-being. Dordrecht: Kluwer. Ben-Arieh, A., & Wintersberger, H. (1997). Monitoring and measuring the state of children: Beyond survival. Eurosocial Report No. 62. Vienna, Austria: European Centre for Social Welfare Policy and Research. Bradshaw, J., Hoelscher, P., & Richardson, D. (2007). An index of child well-being in the European Union. Social Indicators Research, 80, 133–177. Bradshaw, J., Martorano, B., Natali, L., & de Neubourg, C. (2013). Children’s subjective well-being in rich countries. Child Indicators Research, 6(4), 619–635. Cho, E. Y. N. (2014). A clustering approach to comparing children’s wellbeing across countries. Child Indicators Research, 7(3), 553–567. Cobham, A., Molina, N., & Garde, M. (2012). The child development index 2012: Progress, challenges and inequality. London: The Save the Children Fund. Dijkstra, T. (2009). Child well-being in rich countries: UNICEF’s ranking revisited, and new symmetric aggregating operators exemplified. Child Indicators Research, 2(3), 303–317. Heshmati, A., Tausch, A., & Bajalan, C. (2008). Measurement and analysis of child well-being in middle and high income countries. The European Journal of Comparative Economics, 5(2), 187–249. Klocke, A., Clair, A., & Bradshaw, J. (2014). International variation in child subjective well-being. Child Indicators Research, 7(1), 1–20. Lau, M., & Bradshaw, J. (2010). Child well-being in the Pacific Rim. Child Indicators Research, 3, 367–383. Menchini, L., Marnie, S., & Tiberti, L. (2009). Child well-being in Eastern Europe and Central Asia: A multidimensional approach. Innocenti working paper no. 2009-20. Florence, Italy: UNICEF Innocenti Research Centre. OECD. (2009). Doing better for children. Paris: Author. Phipps, S. (2006). Using indicators of child well-being at the international level. In A. Ben-Arieh & R. M. Goerge (Eds.), Indicators of children’s well-being: Understanding their role, usage and policy influence (pp. 83–90). Dordrecht: Springer. Richardson, D., Hoelscher, O., & Bradshaw, J. (2008). Child well-being in Central and Eastern European Countries (CEE) and the Commonwealth of Independent States (CIS). Child Indicators Research, 1, 211–250. UNICEF (2007). Child poverty in perspective: An overview of child well-being in rich countries. Innocenti report card 7. Florence: UNICEF Innocenti Research Centre. UNICEF Office of Research (2013). Child well-being in rich countries: A comparative overview. Innocenti report card 11. Florence: UNICEF Office of Research.
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