IQ is a very good measure of intelligence -efficiency of the central nervous system- the validity of the measure is corroborated in many ways. Here is a summary.

2. Social IQ Correlations
2.1 National/Racial IQs Predict Success in Math and Science
2.2 IQ Predicts Salary
2.3 IQ Predicts Education Level
2.4 IQ Predicts Socioeconomic Status
2.5 IQ Predicts Trainability
2.6 IQ Predicts Job Proficiency
2.7 IQ and Violent Behavior
2.8 National/Racial IQ Predict PISA Scores
2.9 IQ at 13 Predicts of Many Subsequent Achievements
2.10 National IQ, Predictive of GDP/Capita from 1500 to 2000 (See « National I.Q and Economy« )
2.11 National IQ, Predictive of Life Expectancy (See « National I.Q and Economy« )
2.12 Nation IQ, Highly Predictive of Index of Human Development (See « National I.Q and Economy« )


1.Biological IQ Correaltions

1.1 Head Size

Head size is an imperfect estimate of brain size. The correlation between IQ and head size is +0.2.

1.2 Brain Size

Brain size is correlated +0,45 with IQ. The brain size distribution is, like general intelligence (g), Gaussian (bell curve, figure 1 below).

A +0.45 correlation between general intelligence (= IQ) and brain size means that:

1. An increase of 1 SD in brain size (about 120 grams in mass) increases IQ of an average of 0.45 SD (7 IQ points).

2. IQs of 115 (1SD above average) have an average brain size 0.45 SD above average (about 55 grams more in mass).


Figure 1: Cranial capacity in African-Americans (red) and Europeans (white).

This correlation is not limited to homo sapiens: mice with bigger brains are smarter and find their way more quickly in a labyrinth.
University students, whose average IQ is significantly higher than the national average, have a bigger brain (as a mean).

Among university students, those finishing with distinction have a bigger brain and those finishing with great distinction have a bigger brain than those finishing with distinction. This is simply predictable by the intelligence-brain size positive correlation.

Figure 2: Cranial Capacity of Cambridge Students Aged 19 to 24, by Grade.

General Population < University Students < Distinction < Grande Distinction

Some cranial capacities of famous geniuses …


It should be noted that exceptionally intelligent individuals can be found with a below average brain size, the correlation is not 1 (the french writer Anatole France for example had a brain of less than 1kg and the composer Smetana had also a below average brain size).

How to understand a +0.45 correlation between general intelligence and brain size?

Imagine a safe filled with jewelry and bank notes of 5-10-20-50-100-200-500 euros. In the blind, you take with the help of a small shovel of say 1200ml full content from this chest. You repeat the operation 10 times. With the help of a larger 1400ml shovel, you blindly perform 10 shots in the safe.

What do you notice?
1. On average, the value of an intake of 1400ml is greater than that of 1200ml.
2. This is not true in all cases: it is possible that a 1200 ml take is very valuable, simply because it is very dense in 500 notes and jewels, for example. Conversely a catch of 1400ml can be of little value because more dense in notes of 5 and 10 euros.

Brain size distribution in a European male population and associated mean IQ.

Mean IQ distribution in a European male population and associated mean brain size

1.3 Myopia (+0,25) et Hyperopia (Negative Correlation)

Myopics have an IQ of about 7.5 points above the average. Myopia is homozygous recessive. The myopia genes seems to be on chromosome 11. The eyes are extensions of the brain. It seems that the myopia genes modulate both brain size and eyes size. Myopic people have a brain and eyes bigger than average. This is the characteristic of myopia: The eyes are too big so that the picture is formed at the front of the retina, which must be corrected by biconcave glasses.
Heterozygote carriers of a single gene of myopia are not myopics and are not wearing glasses, but they have some intellectual gain, of lesser amplitude than the homozygous myopia.

Conversely, hyperopia (eyes too small) is correlated negatively with intelligence.

→ Positive genetic correlation between intelligence and myopia
→ Negative genetic correlation between intelligence and hyperopia

http://blog.intelligence-humaine.com/q-i-moyen-des-myopes-emmetropes-et-hypermetropes/

Deary I. et al. (2018) « What genome-wide association studies reveal about the association between intelligence and physical health, illness, and mortality ».

Sorjonen K. et al. (2017) « Réfractive state, intelligence, education, and Lord’s paradox » Intelligence, Volume 61, pp. 115–119.

Karlsonn J.L. (2009) « Major Intelligence Gene Tied to Myopia: A Review ».

1.4 Brain Electrochemical Activity 

IQ is correlated:
-with the complexity of the waves at the EEG.
-with the alpha waves frequency.


Evoked potentials recorded with EEG.
The score used is the length of the first 4 brain waves E1 to E4 (figure below)This score is smaller in bright individuals and higher in less intelligent individuals.

In other words: the information transmission is faster in bright people and less in less intelligent individuals.


 


1.5 Brain Glucose Metabolic Rate

-> The main brain energy source is glucose.

-> For the same cognitive task, high IQ brains consume less glucose while low IQ brains conume more glucose.

Correlation of -0.7 to -0.8 between IQ and GMR (glucose metabolic rate)

-> For the same task, high IQ brains operate at lower glucose regime while lower IQ brains arrive more quickly at saturation.

-> Higher IQ brains are more effective.

-> Analogy with a computer:

-a weak computer arrives more quickly to saturation of its processor.

-a more powerful computer is more efficient, it processes identical information using less of its system resources.

If now we subjectively calibrate a difficulty level, for example to succeed a cognitive task in 75 percent of cases what will be defined as a difficult task:

With a success rate of 75%:

-Low IQ brains can perform a less complicated task, for example retain 6 digits.

-Higher IQ brains manage to perform a more complicated task, for example holding 7 digits.

In this case, IQ is correlated positively with GMR, mean that higher IQ brains can reach higher glucose metabolic rates, if needed.

Analogy with a computer:

-If a less powerfull computer runs at 80 percent of its capacity (threshold subjectively fixed as « difficult task »), it will accomplish a smaller task, achieve a lower processor speed and consume less.

-When a more powerfull computer runs at 80 percent of its capacity (subjectively referred to as a « difficult task »), it will accomplish more difficult tasks because it is able to achieve higher processor speed by consuming more.

-> for the same objective task, higher IQ brains consume less -> more effective brains.

-> for a task judged subjectively difficult, higher IQs perform more complex tasks, are able to reach a higher processing power by metabolizing more glucose (higher GMR) -> They are able to climb higher in their GMR -> more powerful brains


1.6 et 1.7 Vitesse de conduction nerveuse (nerfs périphériques et nerfs crâniens)

Correlation of +0.4 between nerve conduction velocity and IQ.

 

1.8 Simple Reaction Time (SRT)

Reaction time is correlated with IQ, as both are signs of efficiency of the central nervous system.

Reaction times are measured as follows: Someone is placed in front of a small lamp that will light. Whenever he does, he simply presses the button in front of him as quickly as possible.

It is a sign of the efficiency of the nervous system since it is in a way a basic treatment of informations. Reaction times are measured in milliseconds.

Below, simple reaction times: green IQ < or = 130, purple IQ > or = 160.

Below: SRT for normal IQs and IQs below average.
Lower IQs have longer reaction times with greater variance (SDRT), since from time to time they produce much slower reaction times, which increases the mean and the variance.

Simple reaction times are faster between 20 and 30 years, in agreement with the highest intelligence and the highest brain size of this period of life (see FAQ intelligence).

1.9 Brain pH, a Biochemical IQ Correlate

-> Higher pH increases conduction velocity
-> pH variations also modulate the activity of many receptors and neurotransmitters

1.10 Finesse of the Auditive Spectrum (Finer Ability to Distinguish Nearer Sounds Frequencies, Proportional to IQ)

Surprising as it may seem, there is a positive correlation between IQ and fineness of the auditory spectrum, ie the ability to distinguish closer sound tones. These tests are performed as follows: sounds of different frequencies are emitted. Gradually, we bring the sounds closer by asking the subjects to designate the higher sound. Correlation between g and the fineness of the auditory spectrum underscores the ubiquity of g in all brain processes and allows us to understand why all major composers, for example, were individuals with IQ around 165 (Cox).

1.11 Finesse of the Visual Spectrum (Finer Ability to Distinguish Nearer Sounds Frequencies, Proportional to IQ)

There is also a positive correlation between IQ and the fineness of the visual spectrum, ie the ability to distinguish closer colors. These tests are performed as follows: different color frequencies are presented. Gradually, we bring the colors together by asking the subjects to designate the two colors and the border between them.

The higher the IQ, the more individuals are able to distinguish nearby color tones.

1.12 Auditory and Visual Inspection Time (measuring the speed of processing sensory information)

« Inspection time » measures the speed of processing visual or auditory information. These measures are correlated +0.7 with IQ.

In this type of test, two bars of unequal length appear on the screen for a short period of time (in milliseconds). We then asks the participant which was the longest bar, the one on the right or the one on the left?

Higher IQs process visual or auditory information more quickly. They have smaller inspection times.


1.13 Erythrocyte Sedimentation Rate

ESR (erythrocyte sedimentation rate) is an indirect measure of inflammation level. Several studies have already shown an inverse association between level of inflammation and intelligence. A high ESR is also a prognostic factor for cardiovascular disorders later in life.

IQ is categorized by decile (decile 1 = mean IQ of 81, decile 2 = IQ of 87, decile 3 = IQ of 92, decile 4 = IQ of 96, decile 5 = IQ of 100, decile 6 = IQ of 104, decile 7 = I.Q of 108, decile 8 = IQ of 113, decile 9 = IQ of 119)

« Association between erythrocyte sedimentation rate and IQ in Swedish males aged 18–20 » Brain, Behavior, and Immunity 24 (2010) 868–873.


1.14 Baseline Pupil Size

Smarter individuals have a larger pupil, even in a « basic », passive condition.

This would be related to the activity of the locus coeruleus (LC) and the noradrenergic system (LC-NS for Locus Coeruleus Norepinephrin System). Pupil size is generally a good estimate of LC activity. LC, which has projections throughout the brain and central nervous system, releases norepinephrine which facilitates the capture of important sensory information and the suppression of responses to small stimuli.

A LC-NS deficiency leads to cognitive impairment and attention.

Below, pupil size versus Q.I (factor g).


Reference: Tsukahara J.S et al. (2016) « The relationship between baseline pupil size and intelligence », Cognitive Psychology 91, 109–123.

1.15 Telomere Lenght

There is a positive correlation between telomere length and intelligence. Intelligent individuals age more slowly, which explains their higher life expectancy. Low intelligence is very clearly a risk factor for accelerated aging.

A, B, C, E, F: Telomere size for tertile 1, 2 and 3 (tertile 1 = best results) at different intelligence tests.
D: Size of the telomeres according to reaction times. Smarter individuals have a faster reaction time.

Figure 1: Biological age at age 38 according to intelligence (in SD) in early childhood

Reference:
Kingma E.M., De Jonge P., Van der Harst P., Ormel J. and Rosmalen J.G.M. (2012) The association between intelligence and telomere length: A longitudinal population based study PLoS One. 7(11): e49356.

Valdes A.M., Deary I.J., Gardner J., Kimura M., Lu X., Spector T.D., Aviv A. and Cherkas L.F., (2010) Leukocyte telomere length is associated with cognitive performance in healthy women, Neurobiol Aging. 31(6): 986–992.

Schaefer J.D.  et al. (2016) Early-life intelligence predicts midlife biological age. The Journals of Gerontology: Series B, Volume 71, Issue 6, 17 Pages 968–977,


2.Social IQ Correaltions

2.1. National/Racial IQs Predict Success in Mathematics and Science

Nations IQ
Math & Science1964-86
Math 1994 Age 10 Math 1994 Age 14 Science 1994
Age 10
Science 1994
Age 14
East Asia 105 56.60 604 606 561 568
China 103 59.28
Hong Kong 107 56.93 587 588 533 522
Japan 105 60.65 597 605 574 571
Singapore 103 56.51 625 643 547 607
South Korea 109 56.21 611 607 597 565
Taiwan 105 56.28
Europe 98 52.84 545 530 549 532
Australie 98 48.13 546 530 562 545
Austria 100 559 539 565 558
Belgium 99 53.25 546 511
Britain 100 53.98 513 506 551 552
Bulgarie 93 59.28 565
Canada 99 47.57 532 527 549 531
Czech Rep 98 567 564 557 574
Denmark 98 53.48 478
Finland 99 48.76
France 98 54.15 538 498
Germany 98 59.03 531
Greece 92 492 484 497
Hungary 98 53.85 548 537 532 554
Iceland 101 474 487 505 494
Ireland 93 47.59 550 527 539 538
Italy 102 44.59
Lithuanie 90 477 476
Netherlands 101 56.84 577 541 557 560
New Zeeland 99 52.44 499 508 531 525
Norway 100 49.60 502 503 530 527
Portugal 95 50.28 475 454 480 480
Romania 94 486
Russie 97 538
Spain 98 49.40 487 517
Slovakia 96 547 544
Slovenia 96 552 541 546 560
Sweden 100 47.41 535
Switzerland 101 57.17 545 ?
United States 98 43.43 545 500 534
South America 86 30.10 385 411
Brazil 86 33.91
Chile 89 26.30
Colombia 84 385 411
South & SE Asia 86 39.83 490 474 473 470
Cyprus 85 502 474 475 463
Indic 82 21.63
Iran 84 20.75 429 428 416 470
Israel 95 51.29 531 522 505 524
Jordan 84 39.38
Kuwait 86 400 392 401 430
Philippines 86 34.35
Thailand 91 39.83 490 522 473 525
Turkey 90 41.52
Africa 69 32.00 354 326   326
Mozambique 64 24.26 ?
Nigeria 69 34.15 ?
South Africa 72 354 326 326
Swaziland 68 32.00
Correlations

with IQ

0.81 0.85 0.89 0.81 0.82

2.2 IQ Predicts Salaries

Table 3. 1. Correlations between IQ and earnings

Country Number Sex Age Age r Reference
1 Netherlands 835 M 12 43 0.17 Dronkers, 1999
2 Netherlands 819 M 12 53 0.19 Dronkers, 1999
3 Netherlands 350 F 12 43 0.03 Dronkers, 1999
4 Netherlands 237 F 12 53 0.19 Dronkers, 1999
5 Norway 1,082 M/F 18 0.33 Tambs et al., 1989
6 Sweden 346 M 10 25 0.08 Fagerlind, 1975
7 Sweden 460 M 10 30 0.22 Fagerlind, 1975
8 Sweden 631 M 10 35 0.34 Fagerlind, 1975
9 Sweden 707 M 10 43 0.40 Fagerlind, 1975
10 Sweden 312 M 20 25 0.10 Fagerlind, 1975
1 1 Sweden 410 M 20 30 0.22 Fagerlind, 1975
12 Sweden 532 M 20 35 0.43 Fagerlind, 1975
13 Sweden 585 M 20 43 0.50 Fagerlind, 1975
14 USA M 18 30 0.31 Duncan, 1968
15 USA 345 M 19 0.15 Hause, 1971
16 USA 345 M 24 0.29 Hause, 1971
17 USA 345 M 29 0.45 Hause, 1971
18 USA 345 M 34 0.49 Hause, 1971
19 USA 4,388 M 17 25 0.26 Hauser et al., 1973
20 USA-whites 24,812 M 18 30 0.24 Brown & Reynolds, 1975
21 USA-whites 24,812 M 18 36 0.33 Brown & Reynolds, 1975
27 USA-blacks 4,008 M 18 30 0.08 Brown & Reynolds, 1975
23 USA-blacks 4,008 M 18 36 0.13 Brown & Reynolds, 1975
24 USA 12,686 M/F 18 30 0.37 Murray, 1998
25 USA 1,943 M/F 18 30 0.35 Rowe et al., 1998
26 USA M 12 45 0.53 Judge et al., 1999
27 USA-whites 3,484 M 19 37 0.36 Nyborg & Jensen, 2001
28 USA-blacks 493 M 19 37 0.37 Nyborg & Jensen, 2001
29 USA 1,448 M 17 27 0.22 Murnane et al., 2001

Table 3.3. Effects of IQ on earnings

Country Number Sex Age Age % Effect on Reference
1 USA 692 M 12  15 Crouse, 1979
2 USA 1,774 M 25-64 25-64  19 Bishop, 1989
3 USA 1,593 M 15-18 19-34  17 Neal & Johnson, 1996
4 USA 1,446 F 15-18 19-32  23 Neal & Johnson, 1996
5 USA 1,448 M 17 27  19 Murnane et al., 2001
6 USA 2,959 M 17 35  11 Zax & Rees, 2002
7 USA 2,264 M 17 53  21 Zax & Rees, 2002
8 Sweden 3,404 M 12 34  10 Zetterberg, 2004
9 Sweden 3,277 F 12 34 11 Zetterberg, 2004

2.3. IQ Predicts Educational Attainment

Table 3.4. Correlations between intelligence and educational attainment

  Country

N

Age

Age

Subject

r

Reference

1 Canada

208

13

13

General

0.55

Gagne & St. Pefi~-2002

2 England

85

5

16

English

0.62

Yule et al., 1982

3 England

85

5

16

Math

0.72

Yule et al., 1982

4 Great Britain 8,699

11

21

Years

0.70

Thienpont & Verleye, 2003

5 Great Britain 20,000

11

16

GCSE

0.74

Deary, 2004

6 N. Ireland

701

16

16

GCSE

0.65

Lynn et al., 1984

7 N. Ireland

451

16

23

Level

0.40

Cassidy & Lynn, 1991

8 Norway 1,082

18

18

Years

0.50

Tambs et al., 1989

9 Sweden

570

20

20

Years

0.53

Fagerlind, 1975

10 USA

General

0.71

Walberg, 1984

11 USA

455

13

13

Reading

0.68

Lloyd & Barenblatt, 1984

12 USA

18

18

Math

0.66

Lubinski & Humphreys, 1996

13 USA 1,943

17

31

Yeats

0.63

Rowe et al., 1998

14 USA 3,484

19

37

Yeats

0.59

Nyborg & Jensen, 2001

15 USA-blacks

493

19

37

Yeats

0.41

Nyborg & Jensen, 2001

16 Switzerland

82

11

11

Math

0.45

Tewes, 2003

2.4. IQ Predicts Socioeconomic Status

Table 3.5. Correlations between intelligence and socioeconomic status

  Country

N

Sex

Age

Age

r

Reference

1 Britain

5,038

M

11

42

0.39

Nettle, 2003

2 N. Ireland

451

M/F

16

23

0.24

Cassidy & Lynn, 1991

3 Norway

1,082

M

18

 

0.33

Tambs et al., 1989

4 Sweden

346

M

10

25

0.28

Fagerlind, 1975

5 Sweden

460

M

10

30

0.35

Fagerlind, 1975

6 Sweden

631

M

10

35

0.35

Fagerlind, 1975

7 Sweden

707

M

10

43

0.40

Fagerlind, 1975

8 Sweden

312

M

20

25

0.40

Fagerlind, 1975

9 Sweden

410

M

20

30

0.48

Fagerlind, 1975

10 Sweden

532

M

20

35

0.50

Fagerlind, 1975

11 Sweden

585

M

20

43

0.53

Fagerlind, 1975

12 USA

81,553

M

0.45

Stewart, 1947

13 USA

M

18

30

0.45

Duncan, 1968

14 USA

437

M

11

45

0.46

Baiema, 1968

15 USA

4,388

M

17

26

0.36

Sewell et al., 1970

16 USA

408

M

17

36

0.41

Sewell et al., 1980

17 USA

330

F

17

36

0.33

Sewell et al., 1980

18 USA

131

M

16

0.57

Waller, 1971

19 USA

170

M

13

0.50

Waller, 1971

20 USA

M

12

45

0.47

Judge et al., 1999

21 USA-whites

3,484

M

19

37

0.38

Nyborg & Jensen, 2001

22 USA-blacks

493

M

19

37

0.31

Nyborg & Jensen, 2001


2.5. IQ Predicts Trainability

Table 3.6. Correlations between intelligence and trainability

  Country Complexity

r

Reference

1 United States High

0.58

Hunter & Hunter, 1984

2 United States Medium

0.40

Hunter & Hunter, 1984

3 United States Low

0.25

Hunter & Hunter, 1984

4 United States Electronics

0.67

Hunter, 1986

5 United States Mechanical

0.62

Hunter, 1986

6 United States Technical

0.62

Hunter, 1986

7 United States Clerical

0.58

Hunter, 1986

8 United States Combat

0.45

Hunter, 1986

9 Europe High

0.29

Salgado et al., 2003

10 Europe Medium

0.29

Salgado et al., 2003

11 Europe Low

0.23

Salgado et al., 2003

2.6. IQ Predicts Job Proficiency

Table 3.7 Correlations between intelligence and job proficiency
 
Country
Complexity
r
Reference
1
United States
High
0.42
Ghiselli, 1966
2
United States
Medium
0.27
Ghiselli, 1966
3
United States
Low
0.15
Ghiselli, 1966
4
United States
High
0.57
Hunter & Hunter, 1984
5
United States
Medium
0.51
Hunter & Hunter, 1984
6
United States
Low-general
0.40
Hunter & Hunter, 1984
7
United States
Low-industriel
0.23
Hunter & Hunter, 1984
8
United States
All
0.51
Schmidt & Hunter, 1998
9
Europe
All
0.25
Salgado et al., 2003


2.7. IQ and Violence

A lower IQ is linearly associated with higher violence in the general population.


« Association between intelligence quotient and violence perpetration in the English general population », Cambridge University Press, 2018.

 

2.8. IQ Predicts PISA Scores

Nations National IQ Math 2000
Age 15
Science 2000
Age 15
Math 2003
Age 15
Albania 90 370 375
Argentina 93 380 395   –
Australia 98 533 525 524
Austria 100 515 520 506
Belgium 99 520 495 529
Brazil 86 330 375 356
Bulgaria 93 430 448  –
Canada 99 533 530 532
Chile 90 375 410  –
China (Macao) 105 527
Czech Republic 98 498 508 516
Denmark 98 514 515 514
Finland 99 536 540 544
France 98 517 500 511
Germant’ 99 490 480 503
Greece 92 447 455 445
Hong Kong 108 550 540 550
Hungary 98 488 498 490
Iceland 101 514 515 515
Indonesia 82 360 395 360
Ireland 93 503 510 503
Israel 95 435 438  –
Italy 102 457 475 466
Japan 105 557 550 534
Latvia 97 465 455 483
Luxembourg 100 446 445 493
Macedonia 91 370 400  –
Mexico 88 387 420 383
Netherlands 101 538
New Zealand 99 537 575 523
Norway 100 499 500  495
Peru 85 295 335  –
Poland 99 470 475  490
Portugal 95 452 455  466
Russia 97 480 455  468
Serbia 89  437
Slovakia 96  498
South Korea 106 547 550  542
Spain 98 476 485  485
Sweden 100 510 508  509
Switzerland 101 529 495  527
Thailand 91 430 440  417
Tunisia 83  359
Turkey 90  423
United Kingdom 100 529 535  –
United States 98 493 500  483
Uruguay 96  422
Correlations with IQ 0.876 0.833 0.871

 

2.9. IQ measured at 13, predictive of many subsequent achievements

These are children with an IQ > 140. These children were divided into 4 quintiles. The Q4 represents the top 25% of these children with IQ > 140. The Q1 represents the 25% of the « least talented » among these children. We note that even among the very talented children, IQ remains highly predictive.