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December 27, 2012

More evidence against Richard Lynn's Italian "IQ" study. The achievement test scores he used to "measure" intelligence have since improved dramatically in Southern Italy, which is rapidly catching up to the North.

Recent results of international assessment programs (e.g., PISA) have shown a large difference in high school students' performance between northern and southern Italy. On this basis, it has been argued that the discrepancy reflects differences in average intelligence of the inhabitants of regions and is associated with genetic factors (Lynn, 2010a, 2012). This paper provides evidence in contrast to this conclusion by arguing that the use of PISA data to make inferences about regional differences in intelligence is questionable, and in any case, both PISA and other recent surveys on achievement of North and South Italy students offer some results that do not support Lynn's conclusions. In particular, a 2006-2009 PISA data comparison shows a relevant decrease in the North-South difference in only three years, particularly evident in the case of a single region (Apulia). Other large surveys (including INVALSI-2011) offer different results; age differences suggest that schooling could have an important role.

October 29, 2012

The good news is there's a new study on population structure in Italy. The bad news is that it's not very well done. The authors failed to sample populations from elsewhere in Southern Europe (like Iberia and the Balkans), which Italians are most related to in other studies, and they didn't collect 4-grandparental information on each individual, resulting in several outliers apparently with recent origins in different parts of the country. They also describe genetic components that are probably very old and have a wide distribution as "Northern European ancestry" and "Middle Eastern ancestry" as if they came from modern populations. Besides all that, the results aren't too surprising.

According to the study, Italians have similar proportions of the same genetic components, varying slightly from North to South, but distinct from both Northern/ Central Europe and the Middle East/North Africa. The island of Sardinia is unique in having an excess amount of one of those components.

In terms of PCA, Italians plot expectedly according to geography between the Western and Eastern Mediterranean (the authors say "France" and "the Middle East" because of the lack of Southern European reference samples), with Sardinians out to the side.

The position of the Italian population samples suggests that genetic distances between these populations and other European and Middle East populations has a good correlation with geographic distances. At the same time, Sardinia was confirmed to be a genetic "outlier".

[...]

The relative position of the samples reflected their geographic location: the close correlation between PC and geography was previously reported by several authors. When compared to other European populations, Sardinia was confirmed to be a genetic "outlier", whereas the Northern Italian population was genetically close to the French population, and the Southern Italians had some similarities with other Mediterranean populations such as those from Middle East. Unfortunately, lack of data from other relevant reference populations from the South-East Europe, e.g. from the Balkan peninsula, made it impossible to fully analyze the extent of the Eastern contribution in Italian populations.

Our main goal was to investigate the genetic structure of the Italian population considering four main macro-areas (Northern, Central, Southern Italy and Sardinia). We carried out PC analysis on the Italian samples and plotted the eigenvectors 1 and 2 in Figure 2. Most samples fell within a main cluster which seems to be indicative of Italian peninsula individuals. The first PC divided Italian populations in two clusters, one for Sardinia and the other for the remaining three Italian macro-areas. The Sardinian population is highly dispersed along the first eigenvector.

The second PC divided Italian mainland population into two clusters, with a certain degree of overlapping between Northern and Central Italy, and a separate cluster for Southern Italy, suggesting that genetic variation is generally continuous rather than discrete, at least within Italian mainland.

The overlap of Northern and Central Italy, and the gap between Central and Southern Italy, is explained by the uneven distribution of the samples.

ADMIXTURE analysis confirms that there was no clear separation between Northern and Central Italy, at least as considered as macro-areas. Additional comparison of the distribution of pair-wise identity-by-state within each of the four populations and ADMIXTURE analysis clarified that this is not an artifact of the PC analysis. However, the PC and ADMIXTURE analysis results could be due to the sparse geographical coverage of our samples, especially for the Central and Northern macro-areas. In fact, many of the individuals (N = 413) in the North Italian sample analyzed in this study were from Piedmont — a North West Italian region that has historically been affected by intense migration. At the same time, many individuals in the Central Italy macro-area (113 samples) are settled in Tuscany, an administrative region which is at the border with northern regions.

Within each macro-area, there isn't much substructure, meaning that a Sicilian, e.g., is not particularly differentiated from a Campanian or a Puglian.

A finer view of the Italian substructure, can be seen in Figure S2 where the hidden population structure within the Italian dataset is appreciable. Subjects are labeled by municipality, or in the case of the Sardinian samples, by the main linguistic area. In this figure we can appreciate the lack of clustering at the municipality level, also within Sardinia. Individuals seem to cluster within the main macro-area, but the geographic patterning is less obvious for the municipality (or in the case of Sardinia, linguistic) division, and in our opinion this pattern indicates no substructure within regions among municipalities, while the structuring between regions can be easily detected. It is also possible to appreciate a certain genetic homogeneity within Sardinia.

July 5, 2012

Ancient DNA analysis reveals that Ötzi the Iceman clusters with modern Southern Europeans and closest to Italians (the orange "Europe S" dots in the plots below), especially those from the island of Sardinia. Other Italians pull away toward Southeastern and Central Europe consistent with geography and some post-Neolithic gene flow from those areas (e.g. Italics, Greeks, Etruscans, Celts), but despite that and centuries of history, they're still very similar to their prehistoric ancestor.

The first analysis was to determine if the Iceman's autosomal DNA shows an affinity to any specific population or if he remains an outlier among contemporary samples. We intersected...his genome with the population reference sample consisting of more than 1,300 Europeans...125 individuals from seven North African populations ranging from Egypt to Morocco...and 20 Qatari samples from the Arabian Peninsula. When plotting the Iceman's genotype along the first two major axes of variation in Principal Component space (PC1 versus PC2), PC1 is driven by a north-to-south gradient differentiating North Africans from Europeans, and PC2 aligns individuals along north-to-south gradient within Europe (Fig. 3a). The Iceman clusters nearest to southern European samples, suggesting no greater genetic affinity with the North African or Middle Eastern components of variation than present day southern Europeans (Fig. 3a).

When considering only European populations, however, we observe that the Iceman clusters closest with five outlier contemporary samples from south-western Europe. In particular, the Iceman abuts the Italian samples originating from geographically isolated regions such as Sardinia (Fig. 3b). Analysis of a larger set of samples, including Sardinians from HGDP across a smaller subset of SNPs, further supports the clustering of the Iceman with samples from Sardinia based on autosomal SNPs (Fig. 3f). [...] The affinity of the Iceman's genome to modern Sardinian groups may reflect relatively recent common ancestry between the ancient Sardinian and Alpine populations, possibly due to the diffusion of Neolithic peoples.

June 7, 2012

This is part of a new Google project to bring UNESCO World Heritage Sites to life and make them available to people across the globe. So far there are 21 Italian sites listed from all over the country (you can learn about the rest at the World Heritage Centre's website). Click on the names below to explore each site further.

March 9, 2012

Here's yet another critique of Richard Lynn's work on Italian IQ. After reiterating the main arguments against his initial study, it focuses on data included in his reply to the first round of criticism, exposing the usual questionable methods we've come to expect from him, and providing new evidence that there are no significant differences in intelligence between north and south.

1.2. Differences in achievement not in intelligence

Lynn's (2010a) estimate of IQ was based on the 2006 British PISA (Program for International Student Assessment), an internationally standardized assessment administered to 15 year olds in schools, that found higher scores for students in northern Italy when compared to students in the south. PISA tests, however, were developed to measure achievement and not intelligence. In fact, the aim of PISA is to measure "how far students near the end of compulsory education have acquired some of the knowledge and skills that are essential for full participation in society"....

Nevertheless, Lynn (2010a) uses achievement tests as "proxies for intelligence" (p. 95) adopting the logic that educational attainment and intelligence are highly correlated (from r=0.5 to r=1.0) across nations (Lynn & Meisenberg, 2010; Lynn & Mikk, 2007). However, in his studies it is not clear what kind of IQ tests have been used, and the other factors affecting achievement such as school quality, sociocultural level, and so on, are not controlled.

1.3. Correlation relationships discussed as causality relationships

It is widely known and accepted that a correlation coefficient describes the degree of relationship between two variables. However, two variables may correlate highly, but they may be different from each other. It is also possible that changes in the variables being studied are influenced by some other unobserved variable. Finally, correlation does not assume causality.

Against such universally shared methodological rules, Lynn (2010a) discusses association among variables as if they are equivalent or in a simple unilinear causal relationship.

[...]

1.5. Measuring intelligence using unvalidated tests

In his more recent paper, Lynn (2010b) reports further evidence of the lower IQs of southern Italians. The first is the report of an intelligence test given to a sample of 50,000 individuals who self-administered the test over the internet on www.sitozero.it. This is a commercial site with an inadequate description of the psychological tests used, with a considerable amount of advertisements and without any control of scientific and methodological issues. We do not consider these non-scientific data to be suitable for making assumptions about IQs.

Moreover, Lynn (2010b) did not consider the calculation of IQs made by the authors, but rather he recalculated the IQ scores in light of the well known and controversial (Colom, Lluis-Font & Andrés-Pueyo, 2005) Flynn effect (2007), described as a general increase of intelligence scores over the world in the last 50 years. So, for instance, an IQ of 99 collected in 1960, was increased by 4 points considering the Flynn effect = 4 of the Italian IQ in the years 1960-79.

Such procedure is questionable, as also Hagan, Drogin, and Guilmette (2008) pointed out. Indeed, different studies demonstrated that the Flynn effect is concentrated in the lower half of the normal distribution or in undeveloped countries (Colom et al., 2005), whereas a possible stagnation of IQ scores in developed ones is currently under debate (Teasdale & Owen, 2005; 2008).

[...]

2. New evidence against the north-south differences in IQs

With the aim to contribute to the study of regional differences in IQs, we obtained two new sources of evidence based on the direct assessment of IQs in children of different Italian regions, using measures of intelligence that do not contain highly academic content.

[...]

Despite the minor differences between the studies, our results demonstrate quite clearly that raw scores [on Raven's Coloured Progressive Matrices] of children from Sicily are not lower than those [of children from the North and Central-South] reported by Cornoldi et al. (2010). On the contrary, they are sometimes higher. This result could be related to the fact that the children in our group were tested in group sessions, while children in Italian standardization scores (Belacchi et al., 2008) were tested both in group and individual administration. Belacchi et al. (2008), indeed, found mean raw scores significantly higher in group sessions administration than in individual administration. Moreover, the children in our group were selected for other research purposes, and did not include children with socio-cultural disadvantage or other type of behavioral or cognitive problems. The more extensive sample reported by Cornoldi et al. (2010), on the contrary, was collected with the aim of building norms, and it likely includes a more diverse sample of children coming from different urban and suburban areas, and showing different socio-cultural levels.

[...]

Naglieri et al. (submitted for publication) studied the differences between the psychometric qualities of the CAS [Cognitive Assessment System] for the Italian and US standardization samples. Although the goal of that study was not to make regional comparisons, they did report that there were no significant differences (F(1, 806)=2.19, p=.11) between the average CAS-Italian Full Scale standard scores (set at a mean of 100 and standard deviation of 15) for students from the northern (M=100.5; SD=13.2), central (M=101.2; SD=11.9), and southern (M=103.1; SD=11.6) regions of Italy. The mean standard scores for the students in the north were only slightly lower than the mean for those in the south (effect size=.21). These results suggest that a test of intelligence that measures basic neuropsychological processes, and does not include academically laden verbal and quantitative tests, yields small differences between the regional groups. These findings also amplify the importance of measuring intelligence directly when comparing groups and argue against using reading, math and science test scores as "proxies for intelligence" (Lynn, 2010a).

[...]

5. General conclusions

Our examination of intelligence test score differences between the north and south of Italy led to results that are very different from those reached by Lynn (2010a). Our results demonstrate that by using intelligence tests to assess differences in ability rather than using achievement scores as a proxy for intelligence, children from the south of Italy did not earn lower scores than those from the north of Italy. Rather, they were even higher in Raven's CPM. However, we see no advantage in claiming that children in the south are "more intelligent" than children in the north, because these groups are different on a number of variables (e.g., environmental factors, educational influences, composition of the samples) that influence differences in test scores. We also disagree with Lynn's genetically-centered explanation of intelligence which denotes a fixed conception not only about intelligence but also about learning.

February 21, 2012

Europeans have gotten heavier over the last decade, but within that context, Italy has among the lowest rates of overweight and obese people, especially the latter and especially women.

Among the 19 [European Union] Member States for which data are available, the proportion of overweight and obese people in the adult population varied in 2008/09 between 36.9 % and 56.7 % for women and between 51 % and 69.3 % for men.

For both women and men aged 18 years and over, the lowest shares of obesity in 2008/09 were observed in Romania (8.0 % for women and 7.6 % for men), Italy (9.3 % and 11.3 %), Bulgaria (11.3 % and 11.6 %) and France (12.7 % and 11.7 %). The highest proportions of obese women were recorded in the United Kingdom (23.9 %), Malta (21.1 %), Latvia (20.9 %) and Estonia (20.5 % in 2006), and of men in Malta (24.7 %), the United Kingdom (22.1 %), Hungary (21.4 %) and the Czech Republic (18.4 %).

January 17, 2012

Actress and singer born in Rome. Her father is an actor-director with roots in Basilicata and Puglia, and her mother (also an actress from Rome) is best known outside of Italy for playing Michael Corleone's Sicilian wife Apollonia in The Godfather.