http://politiken.dk/indland/ECE1941066/samfundets-svage-skal-tilgodeses-i-sundhedsvaesnet/

Med andre ord ønsker foreningen, at politikerne i højere grad tænker social ulighed ind i de kliniske retningslinjer, så sundhedsvæsnet bliver bedre til at omfavne alle behov.

»Nogle kroniske patienter er meget opmærksomme på symptomer på forværring af deres sygdomme og henvender sig til egen læge af sig selv. Andre skal følges helt anderledes tæt, fordi de ikke har ressourcerne til selv at opsøge hjælp«, siger Jette Dam-Hansen.

Hun henviser til tal fra Region Hovedstaden, der viser, at 27 procent af borgere med kort uddannelse lider af tre eller flere langvarige sygdomme. Det tilsvarende tal for borgere med lang uddannelse er fem procent.

De er ekke nået nyt at dær er sammenhæng mællem disse. Forskere har fornylit dærfor fået dæn idé at dær er en gæneral fitness fakotor, lissom at dær er en gæneral entælligæns faktor, g.

Jaj sitérer bl.a.:

Abstract
We recently found positive correlations between human general intelligence and three key indices of semen quality, and hypothesized that these correlations arise through a phenotype-wide ‘general fitness factor’ reflecting overall mutation load.  In this addendum we consider some of the biochemical pathways that may act as targets for pleiotropic mutations that disrupt both neuron function and sperm function in parallel. We focus especially on the inter-related roles of polyunsaturated fatty acids, exocytosis, and receptor signaling.

In a recent paper we reported a positive association between general intelligence and semen quality in male humans. Specifically, in a sample of 425 Vietnam-era veterans, we found positive correlations between a g factor (representing general intelligence, extracted from factor analysis of five well-validated cognitive tests) and three independent measures of semen quality: sperm concen- tration (r = 0.15, p = 0.002), sperm count (r = 0.19, p = 0.001) and sperm motility (r = 0.14, p = 0.002). None of these correla- tions were mediated by age, body mass index, combat experience in Vietnam, use of alcohol, tobacco, marijuana or hard drugs or days of sexual abstinence before collection of the semen sample. We argued that although these correlations were small in magni- tude, they might be theoretically important for understanding the evolutionary genetics of human phenotypic variation.

From an adaptationist viewpoint, there is little reason to expect a correlation in functional efficiency between two such disparate traits: intelligence depends mainly on brain function and neural development, whereas semen quality depends mainly on testicular function and spermatogenesis. Nonetheless, we hypothesized that there may be pervasive positive correlations among the functional efficiencies of many organ systems because different organs are influenced by overlapping sets of genes. Since most genes are pleio- tropic (affecting several traits in parallel), most mutations are likely to have pleiotropic effects in disrupting several traits in parallel. Potentially, such pleiotropic mutations could produce positive genetic correlations in the functional efficiencies of different organ systems, yielding positive phenotypic correlations in different components of fitness, such as intelligence and fertility.

Abstract
We suggest that an over-arching ‘fitness factor’ (an index of general genetic quality that predicts survival and reproductive success) partially explains the observed associations between health outcomes and intelligence. As a proof of concept, we tested this idea in a sample of 3654 US Vietnamveterans aged 31–49 who completed five cognitive tests (fromwhich we extracted a g factor), a detailed medical examination, and self-reports concerning lifestyle health risks (such as smoking and drinking). As indices of physical health, we aggregated ‘abnormality counts’ of physician-assessed neurological, morphological, and physiological abnormalities in eight categories: cranial nerves, motor nerves, peripheral sensory nerves, reflexes, head, body, skin condition, and urine tests. Since each abnormality was rare, the abnormality counts showed highly skewed, Poisson-like distributions. The correlation matrix amongst these eight abnormality counts formed only a weak positive manifold and thus yielded only a weak common factor. However, Poisson regressions showed that intelligence was a significant positive predictor of six of the eight abnormality counts, even controlling for diverse lifestyle covariates (age, obesity, combat and toxin exposure owing to service in Vietnam, and use of tobacco, alcohol, marijuana, and hard drugs). These results give preliminary support for the notion of a superordinate fitness factor above intelligence and physical health, which could be further investigated with direct genetic assessments of mutation load across individuals.

Abstract
Just as body symmetry reveals developmental stability at the morphological level, general intelligence may reveal developmental stability at the level of brain development and cognitive functioning. These two forms of developmental stability may overlap by tapping into a “general fitness factor.” If so, then intellectual tests with higher g-loadings should show higher correlations with a composite measure of body symmetry. We tested this prediction in 78 young males by measuring their left–right symmetry at 10 body points, and by administering five cognitive tests with diverse g-loadings. As predicted, we found a significant (z=3.64, p<0.003) relationship between each test’s rank order g-loading and its body symmetry association. We also found a substantial correlation (r=0.39, p<0.01) between body symmetry and our most highly g-loaded test (Ravens Advanced Progressive Matrices). General intelligence is apparently a valid indicator of general developmental stability and heritable fitness, which may partly explain its social and sexual attractiveness.

Noen forskere har endda foreslået præsis de som læerne forslår i dæn danske artikel.

The present data have a number of interesting applications. One is derived from the field of cognitive epidemiology—a relatively new field of study that examines intelligence-health associations (Deary, 2009). In our current study, Table 1 and Table 2 show that there is a difference in educational level for MCI and AD in both the ADNI (χ21 = 79.2; p = 2.2 × 10−16) and CHS-CS (χ21 = 4.0; p = 0.05) cohorts, with the AD group having a smaller percentage of subjects with more than 12 years of education. This could suggest a hypothetical causal chain whereby a lower educational level is associated with poorer skills for choosing healthy behaviors leading to higher BMI values and lower brain volumes. Clearly, whether or not an individual chooses healthy behaviors depends on many factors — including access to exercise, education, and other cultural factors. General intelligence may also be a contributing factor.

Specifically, general intelligence has been found to contribute to overall educational achievement (Deary et al., 2007). It is unfortunate that a measure of intelligence was not consistently collected in both the datasets analyzed here, as intelligence is the best single predictor of achieved educational level (Deary et al., 2007). This hypothetical causal chain could show that poorer intellectual function leads to a lower level of educational attainment, which may be associated with poorer skills for choosing healthy behaviors, higher BMI values, and thus lower brain volumes. Interestingly, intelligence is itself positively correlated with brain volume (Luders et al., 2009b and McDaniel, 2005).

If this line of reasoning is correct, cognitive epidemiology may provide some insight for public policy (Lubinski, 2009). We have shown that obesity may modify the risk for cognitive impairment because of the link to compromised brain structure. Thus, when proposing behaviors for controlling body fat content, the population distribution of intelligence should also be considered as the relationship between general intelligence and healthy outcomes has been established (Arden et al., 2009 and Lubinski, 2009). Preventing obesity requires healthy behaviors that may already be more evident in better educated people, so healthcare systems may have greater success by developing targeting messages to populations with poorer access to education, or poorer educational attainment. [min æmfase]