Economic globalization, inequality and body mass index:a cross-national analysis of 127 countries

This article investigates to what extent the worldwide increase in body mass index (BMI) has been affected by economic globalization and inequality. We used time-series and longitudinal cross-national analysis of 127 countries from 1980 to 2008. Data on mean adult BMI were obtained from the Global Burden of Metabolic Risk Factors of Chronic Diseases Collaborating Group. Globalization was measured using the Swiss Economic Institute (KOF) index of economic globalization. Economic inequality between countries was measured with the mean difference in gross domestic product per capita purchasing power parity in international dollars. Economic inequality within countries was measured using the Gini index from the Standardized World Income Inequality Database. Other covariates including poverty, population size, urban population, openness to trade and foreign direct investment were taken from the World Development Indicators (WDI) database. Time-series regression analyses showed that the global increase in BMI is positively associated with both the index of economic globalization and inequality between countries, after adjustment for covariates. Longitudinal panel data analyses showed that the association between economic globalization and BMI is robust after controlling for all covariates and using different estimators. The association between economic inequality within countries and BMI, however, was significant only among high-income nations. More research is needed to study the pathways between economic globalization and BMI. These findings, however, contribute to explaining how contemporary globalization can be reformed to promote better health and control the global obesity epidemic. © 2013 Copyright Taylor and Francis Group, LLC.

Using macroscopic entanglement to close the detection loophole in Bell-inequality tests

We consider a Bell-like inequality performed using various instances of multiphoton entangled states to demonstrate that losses occurring after the unitary transformations used in the nonlocality test can be counteracted by enhancing the size of such entangled states. In turn, this feature can be used to overcome detection inefficiencies affecting the test itself: a slight increase in the size of such states, pushing them towards a more macroscopic form of entanglement, significantly improves the state robustness against detection inefficiency, thus easing the closing of the detection loophole. Differently, losses before the unitary transformations cause decoherence effects that cannot be compensated using macroscopic entanglement.

Slavery, Education, and Inequality

We investigate the effect of slavery on the current level of income inequality across US counties. We find that a larger proportion of slaves over population in 1860 persistently increases inequality, and in particular inequality across races. We also show that a crucial
channel of transmission from slavery to racial inequality is human capital accumulation, i.e., current inequality is primarily influenced by slavery through the unequal educational attainment of blacks and whites. Finally, we provide suggestive evidence that the underlying links run through the political exclusion of former slaves and the resulting negative influence on the local provision of education.

Drivers of inequality in disability-free expectancy at birth and age 85 across space and time in Great Britain

Background: Although mortality and health inequalities at birth have increased both geographically and in socioeconomic terms, little is known about inequalities at age 85, the fastest growing sector of the population in Great Britain (GB).

Aim: To determine whether trends and drivers of inequalities in life expectancy (LE) and disability-free life expectancy (DFLE) at age 85 between 1991 and 2001 are the same as those at birth.

Methods: DFLE at birth and age 85 for 1991 and 2001 by gender were calculated for each local authority in GB using the Sullivan method. Regression modelling was used to identify area characteristics (rurality, deprivation, social class composition, ethnicity, unemployment, retirement migration) that could explain inequalities in LE and DFLE.

Results: Similar to values at birth, LE and DFLE at age 85 both increased between 1991 and 2001 (though DFLE increased less than LE) and gaps across local areas widened (and more for DFLE than LE). The significantly greater increases in LE and DFLE at birth for less-deprived compared with more-deprived areas were still partly present at age 85. Considering all factors, inequalities in DFLE at birth were largely driven by social class composition and unemployment rate, but these associations appear to be less influential at age 85.

Conclusions: Inequalities between areas in LE and DFLE at birth and age 85 have increased over time though factors explaining inequalities at birth (mainly social class and unemployment rates) appear less important for inequalities at age 85.

Helping the most vulnerable out of the poverty trap and reducing inequality: Policies, strategies, and services for individuals with Autism Spectrum Disorder, including intellectual and neurodevelopmental disabilities: Benchmarking Autism Services Efficacy: BASE Project (Volume 3) Secondary Data analysis

1) Executive Summary
Legislation (Autism Act NI, 2011), a cross-departmental strategy (Autism Strategy 2013-2020) and a first action plan (2013-2016) have been developed in Northern Ireland in order to support individuals and families affected by Autism Spectrum Disorder (ASD) without a prior thorough baseline assessment of need. At the same time, there are large existing data sets about the population in NI that had never been subjected to a secondary data analysis with regards to data on ASD. This report covers the first comprehensive secondary data analysis and thereby aims to inform future policy and practice.
Following a search of all existing, large-scale, regional or national data sets that were relevant to the lives of individuals and families affected by Autism Spectrum Disorder (ASD) in Northern Ireland, extensive secondary data analyses were carried out. The focus of these secondary data analyses was to distill any ASD related data from larger generic data sets. The findings are reported for each data set and follow a lifespan perspective, i.e., data related to children is reported first before data related to adults.
Key findings:
Autism Prevalence:
Of children born in 2000 in the UK,
• 0.9% (1:109) were reported to have ASD, when they were 5-year old in 2005;
• 1.8% (1:55) were reported to have ASD, when they were 7-years old in 2007;
• 3.5% (1:29) were reported to have ASD, when they were 11-year old in 2011.
In mainstream schools in Northern Ireland
• 1.2% of the children were reported to have ASD in 2006/07;
• 1.8% of the children were reported to have ASD in 2012/13.

Economic Deprivation:
• Families of children with autism (CWA) were 9%-18% worse off per week than families of children not on the autism spectrum (COA).
• Between 2006-2013 deprivation of CWA compared to COA nearly doubled as measured by eligibility for free school meals (from near 20 % to 37%)
• In 2006, CWA and COA experienced similar levels of deprivation (approx. 20%), by 2013, a considerable deprivation gap had developed, with CWA experienced 6% more deprivation than COA.
• Nearly 1/3 of primary school CWA lived in the most deprived areas in Northern Ireland.
• Nearly ½ of children with Asperger’s Syndrome who attended special school lived in the most deprived areas.

Unemployment:
• Mothers of CWA were 6% less likely to be employed than mothers of COA.
• Mothers of CWA earned 35%-56% less than mothers of COA.
• CWA were 9% less likely to live in two income families than COA.

Health:
• Pre-diagnosis, CWA were more likely than COA to have physical health problems, including walking on level ground, speech and language, hearing, eyesight, and asthma.
• Aged 3 years of age CWA experienced poorer emotional and social health than COA, this difference increased significantly by the time they were 7 years of age.
• Mothers of young CWA had lower levels of life satisfaction and poorer mental health than mothers of young COA.
Education:
• In mainstream education, children with ASD aged 11-16 years reported less satisfaction with their social relationships than COA.
• Younger children with ASD (aged 5 and 7 years) were less likely to enjoy school, were bullied more, and were more reluctant to attend school than COA.
• CWA attended school 2-3 weeks less than COA .
• Children with Asperger’s Syndrome in special schools missed the equivalent of 8-13 school days more than children with Asperger’s Syndrome in mainstream schools.
• Children with ASD attending mainstream schooling were less likely to gain 5+ GCSEs A*-C or subsequently attend university.



Further and Higher Education:
• Enrolment rates for students with ASD have risen in Further Education (FE), from 0% to 0.7%.
• Enrolment rates for students with ASD have risen in Higher Education (HE), from 0.28% to 0.45%.
• Students with ASD chose to study different subjects than students without ASD, although other factors, e.g., gender, age etc. may have played a part in subject selection.
• Students with ASD from NI were more likely than students without ASD to choose Northern Irish HE Institutions rather than study outside NI.

Participation in adult life and employment:
• A small number of adults with ASD (n=99) have benefitted from DES employment provision over the past 12 years.
• It is unknown how many adults with ASD have received employment support elsewhere (e.g. Steps to Work).
•
Awareness and Attitudes in the General Population:
• In both the 2003 and 2012 NI Life and Times Survey (NILTS), NI public reported positive attitudes towards the inclusion of children with ASD in mainstream education (see also BASE Project Vol. 2).

Gap Analysis Recommendations:
This was the first comprehensive secondary analysis with regards to ASD of existing large-scale data sets in Northern Ireland. Data gaps were identified and further replications would benefit from the following data inclusion:
• ASD should be recorded routinely in the following datasets:
o Census;
o Northern Ireland Survey of Activity Limitation (NISALD);
o Training for Success/Steps to work; Steps to Success;
o Travel survey;
o Hate crime; and
o Labour Force Survey.
• Data should be collected on the destinations/qualifications of special school leavers.
• NILT Survey autism module should be repeated in 5 years time (2017) (see full report of 1st NILT Survey autism module 2012 in BASE Project Report Volume 2).
• General public attitudes and awareness should be assessed for children and young people, using the Young Life and Times Survey (YLT) and the Kids Life and Times Survey (KLT); (this work is underway, Dillenburger, McKerr, Schubolz, & Lloyd, 2014-2015).
 

Helping the most vulnerable out of the poverty trap and reducing inequality: Policies, strategies, and services for individuals with Autism Spectrum Disorder, including intellectual and neurodevelopmental disabilities: BASE Project Report (Volume 2) NILT Survey Autism Module

The primary purpose of the BASE Project was to establish how to help individuals with Autism Spectrum Disorder out of poverty by promoting social inclusion. In order to achieve this, a range of methodologies were utilised that aimed to provide a baseline against which the effect of the Autism Act (NI) 2011 and the associated Autism Strategy (2013-2020) and Action Plans can be measured. The BASE Project is reported in 5 volumes. Volume 2 reports on the analysis of the autism module of the Northern Ireland Life and Times (NILT) Survey that assessed public awareness, attitudes, knowledge, and projected behaviours with regard to individuals with ASD (all primary data and technical reports are available at www.ark.ac.uk/nilt/).

The NILT (2012) survey first ever autism module (n=1204) offered a baseline against which the impact of new autism legislation, policies, and strategies can be measured. Key findings:

• 82% awareness: Most people in Northern Ireland are aware of autism (n=989).
• 50% of all participants knew someone with autism personally (n=606).

Of those who were aware of autism:
• 19% had a close family member with autism (n=186), and/or a friends/acquaintance (n=296), and/or a work colleague (n=79) with autism.
• Autism awareness was particularly low for those from ethnic minorities and those with no internet access.
• Awareness of autism specific legislation was low (20%).
• Good levels of knowledge about autism strengths and challenges, slight tendency to overestimate the occurrence of special talents.
• Prevalence of autism was underestimated (62% thought autism was much less prevalent than official figures or did not know).
• Fairly accurate perception about causes of autism, i.e., not caused by poor parenting (84%).
• Strong support for evidence-based behavioural interventions (77%), but confusion about interventions that are not evidence-based (64%).
• Strong positive attitudes towards children and adults in social, educational and employment settings.
• Autism not viewed as necessarily ‘lifelong’ (58%); support for independent living (78%), e.g., driving a car (83%).
• More business for employers who employ people with autism (12%).
• Strong support for families caring rather than residential care (64%).
• Confusion about service responsibility: education (26%) health (33%) or both (28%).

Given increasing prevalence rates of ASD it is important that the general population is aware of autism and able to respond responsibly to the associated strengths and challenges. The results of the NILT (2012) first ever autism module show that the general public was well aware of autism, had positive attitudes, and was relatively knowledgeable about the issues faced by individuals and families affected directly. However, there was a lack of clarity about responsibility for effective service delivery. The NILT results show that a shift in focus is necessary from ‘awareness raising campaigns’ to an approach that delivers clarity with regard to intervention and accountability.

War, food rationing, and socioeconomic inequality in Germany during the First World War

Germany experienced a devastating period during the First World War due to severely restricted import possibilities and a general shortage of foodstuffs. This study uses the heights of some 4,000 individuals who served during the Second World War to quantify biological living standards from the 1900s to the 1920s, and focuses primarily on socioeconomic inequality during this period. The results suggest that generally the upper social strata, measured by fathers' occupation, exhibited the tallest average height, followed by the middle and lower classes. These socioeconomic differences became more pronounced during the First World War when the rationing system provided a limited food supply. Wealthier individuals were able to purchase additional foodstuffs on black markets. Therefore, children from upper-class families experienced only a small decline in average height compared to their counterparts from the middle and lower social strata.

The influence of inequality on the standard of living: Worldwide anthropometric evidence from the 19th and 20th centuries

We provide empirical evidence on the existence of the Pigou–Dalton principle. The latter indicates that aggregate welfare is – ceteris paribus – maximized when incomes of all individuals are equalized (and therefore marginal utility from income is as well). Using anthropometric panel data on 101 countries during the 19th and 20th centuries, we determine that there is a systematic negative and concave relationship between height inequality and average height. The robustness of this relationship is tested by means of several robustness checks, including two instrument variable regressions. These findings help to elucidate the impact of economic inequality on welfare.

Estimating male and female height inequality

This study investigates the coefficient of variation (CV) of height of males and females as a measure of inequality. We have collected a data set on corresponding male and female height CVs from 124 populations, spanning the period between the 1840s and 1980s. The results suggest that the R2 between the two CVs is 0.39, with the male CV being greater, indicating higher plasticity.

Anthropometric within-country Inequality and the Estimation of Skill Premia with Anthropometric Indicators

Recently, a method to measure inequality has been proposed that is based on an- thropometric indicators. Baten (1999, 2000) argued that the coefficient of variation of human stature (henceforth ‘CV’) is correlated with overall inequality in a society, and that it can be used as indicator, especially where income inequality measures are lack- ing. This correlation has been confirmed in further analyses, for example by Pradhan et al. (2003), Moradi and Baten (2005), Sunder (2003), Guntupalli and Baten (2006), Blum (2010a), van Zanden et al. (2010), see also Figure 1 and Table 1. The idea is that average height reflects nutritional conditions during early childhood and youth. Since wealthier people have better access to food, shelter and medical resources, they tend to be taller than the poorer part of the population. Hence, the variation of height of a cer- tain cohort may be indicative of income distribution during the decade of their birth. The aim of this study is firstly to provide an overview of different forms of within- country height inequality. Previous studies on the aspects of height inequality are re- viewed. Inequalities between ethnic groups, gender, inhabitants of different regions and income groups are discussed. In the two final sections, we compare height CVs of anthropological inequality with another indicator of inequality, namely skill premia. We also present estimates of skill premia for a set of countries and decades for which “height CVs”, as they will be called in the following, are available.