Another study looking into the urban-nature effect issue takes a different tack than those I’ve previously reported on, that look at the attention-refreshing benefits of natural environments.

In this study, a rural African people living in a traditional village were compared with those who had moved to town. Participants in the first experiment included 35 adult traditional Himba, 38 adolescent traditional Himba (mean age 12), 56 adult urbanized Himba, and 37 adolescent urbanized Himba. All traditional Himba had had little contact with the Western world and only spoke their native language; all adult urbanized Himba had grown up in traditional villages and only moved to town later in life (average length of time in town was 6 years); all adolescent urbanized Himba had grown up in town the town and usually attended school regularly.

The first experiments assessed the ability to ignore peripheral distracting arrows while focusing on the right or left direction of a central arrow.

There was a significant effect of urbanization, with attention being more focused (less distracted) among the traditional Himba. Traditional Himba were also slower than urbanized Himba — but note that there was substantial overlap in response times between the two groups. There was no significant effect of age (that is, adolescents were faster than adults in their responses, but the effect of the distracters was the same across age groups), or a significant interaction between age and urbanization.

The really noteworthy part of this, was that the urbanization effect on task performance was the same for the adults who had moved to town only a few years earlier as for the adolescents who had grown up and been educated in the town. In other words, this does not appear to be an educational effect.

The second experiment looked at whether traditional Himba would perform more like urbanized Himba if there were other demands on working memory. This was done by requiring them to remember three numbers (the number words in participants’ language are around twice as long as the same numbers in English, hence their digit span is shorter).

While traditional Himba were again more focused than the urbanized in the no-load condition, when there was this extra load on working memory, there was no significant difference between the two groups. Indeed, attention was de-focused in the traditional Himba under high load to the same degree as it was for urbanized Himba under no-load conditions. Note that increasing the cognitive load made no difference for the urbanized group.

There was also a significant (though not dramatic) difference between the traditional and urbanized Himba in terms of performance on the working memory task, with traditional Himba remembering an average of 2.46/3 digits and urbanized Himba 2.64.

Experiment 3 tested the two groups on a working memory task, a standard digit span test (although, of course, in their native language). Random sequences of 2-5 digits were read out, with the participant being required to say them aloud immediately after. Once again, the urbanized Himba performed better than the traditional Himba (4.32 vs 3.05).

In other words, the problem does not seem to be that urbanization depletes working memory, rather, that urbanization encourages disengagement (i.e., we have the capacity, we just don’t use it).

In the fourth experiment, this idea was tested more directly. Rather than the arrows used in the earlier experiments, black and white faces were used, with participants required to determine the color of the central face. Additionally, inverted faces were sometimes used (faces are stimuli we pay a lot of attention to, but inverting them reduces their ‘faceness’, thus making them less interesting).

An additional group of Londoners was also included in this experiment.

While urbanized Himba and Londoners were, again, more de-focused than traditional Himba when the faces were inverted, for the ‘normal’ faces, all three groups were equally focused.

Note that the traditional Himba were not affected by the changes in the faces, being equally focused regardless of the stimulus. It was the urbanized groups that became more alert when the stimuli became more interesting.

Because it may have been a race-discrimination mechanism coming into play, the final experiment returned to the direction judgment, with faces either facing left or right. This time the usual results occurred – the urbanized groups were more de-focused than the traditional group.

In other words, just having faces was not enough; it was indeed the racial discrimination that engaged the urbanized participants (note that both these urban groups come from societies where racial judgments are very salient – multicultural London, and post-apartheid Namibia).

All of this indicates that the attention difficulties that appear so common nowadays are less because our complex environments are ‘sapping’ our attentional capacities, and more because we are in a different attentional ‘mode’. It makes sense that in environments that contain so many more competing stimuli, we should employ a different pattern of engagement, keeping a wider, more spread, awareness on the environment, and only truly focusing when something triggers our interest.

Organophosphate pesticides are the most widely used insecticides in the world; they are also (according to WHO), one of the most hazardous pesticides to vertebrate animals. While the toxic effects of high levels of organophosphates are well established, the effects of long-term low-level exposure are still controversial.

A meta-analysis involving 14 studies and more than 1,600 participants, reveals that the majority of well-designed studies undertaken over the last 20 years have found a significant association between low-level exposure to organophosphates and impaired cognitive function. Impairment was small to moderate, and mainly concerned psychomotor speed, executive function, visuospatial ability, working memory, and visual memory.

In a large Mayo Clinic study, self-reported diet was found to be significantly associated with the risk of seniors developing mild cognitive impairment or dementia over a four-year period.

The study involved 1,230 older adults (70-89) who completed a 128-item food-frequency questionnaire about their diet during the previous year. Of these, around three-quarters (937) showed no signs of cognitive impairment at the beginning of the study period, and were asked to return for follow-up cognitive assessments. These assessments took place every 15 months. After about four years, 200 (21%) had developed mild cognitive impairment (MCI) or dementia.

The likelihood of cognitive deterioration was significantly affected by the type of diet. Those with the highest carbohydrate intake were nearly twice as likely to develop cognitive impairment compared to those with the lowest carbohydrate consumption, and when total fat and protein intake were taken into account, they were 3.6 times likelier to develop impairment.

Those with the highest sugar intake were 1.5 times more likely to develop cognitive impairment.

But — a finding that will no doubt surprise many — those with the highest fat consumption were 42% less likely to develop cognitive impairment, compared to those with the lowest level of fats.

Less surprisingly, those with highest intake of protein had a reduced risk of 21%.

In other words, the worst diet you can have, if you want to keep your brain healthy, is one that receives most of its calories from carbohydrates and sugar, and relatively little from fats and protein.

The findings about carbs, sugar, and protein are consistent with other research. The finding regarding fats is somewhat more surprising. The inconsistency may lie in the type of fat. Research implicating high-fat diets as a risk factor in Alzheimer’s have used saturated fats. Diets high in olive oil, on the other hand, have been found to be beneficial.

It seems likely that the danger of carbs and too much sugar lies in the effects on glucose and insulin metabolism. Saturated fats also interfere with glucose metabolism. Alzheimer’s has sometimes been called Type 3 diabetes, because of its association with insulin problems.

Green tea is thought to have wide-ranging health benefits, especially in the prevention of cardiovascular disease, inflammatory diseases, and diabetes. These are all implicated in the development of age-related cognitive impairment, so it’s no surprise that regular drinking of green tea has been suggested as one way to help protect against age-related cognitive decline and dementia. A new mouse study adds to that evidence by showing how a particular compound in green tea promotes neurogenesis.

The chemical EGCG, (epigallocatechin-3 gallate) is a known anti-oxidant, but this study shows that it also has a specific benefit in increasing the production of neural progenitor cells. Like stem cells, these progenitor cells can become different types of cell.

Mice treated with EGCG displayed better object recognition and spatial memory than control mice, and this improved performance was associated with the number of progenitor cells in the dentate gyrus and increased activity in the sonic hedgehog signaling pathway (confirming the importance of this pathway in adult neurogenesis in the hippocampus).

The findings add to evidence that green tea may help protect against cognitive impairment and dementia.

A large long-running New Zealand study has found that people who started using cannabis in adolescence and continued to use it for years afterward showed a significant decline in IQ from age 13 to 38. This was true even in those who hadn’t smoked marijuana for some years.

The study has followed a group of 1,037 children born in 1972-73. At age 38, 96% of the 1004 living study members participated in the latest assessment. Around 5% were regularly smoking marijuana more than once a week before age 18 (cannabis use was ascertained in interviews at ages 18, 21, 26, 32, and 38 years, and this group was not more or less likely to have dropped out of the study).

This group showed an average decline in IQ of 8 points on cognitive tests at age 38 compared to scores at age 13. Such a decline was not found in those who began using cannabis after the age of 18. In comparison, those who had never used cannabis showed a slight increase in IQ. The effect was dose-dependent, with those diagnosed as cannabis dependent on three or more occasions showing the greatest decline.

While executive function and processing speed appeared to be the most seriously affected areas, impairment was seen across most cognitive domains and did not appear to be statistically significantly different across them.

The size of the effect is shown by a further measure: informants (nominated by participants as knowing them well) also reported significantly more attention and memory problems among those with persistent cannabis dependence. (Note that a decline of 8 IQ points in a group whose mean is 100 brings it down to 92.)

The researchers ruled out recent cannabis use, persistent dependence on other drugs (tobacco, alcohol, hard drugs), and schizophrenia, as alternative explanations for the effect. The effect also remained after years of education were taken into account.

The finding supports the view that the adolescent brain is vulnerable to the effects of marijuana, and that these effects are long-lasting and significant.

Some numbers for those interested: Of the 874 participants included in the analysis (those who had missed at least 3 interviews in the 25 years were excluded), 242 (28%) never used cannabis, 479 (55%) used it but were never diagnosed as cannabis-dependent, and 153 (17%) were diagnosed on at least one of the interviews as cannabis-dependent. Of these, 80 had been so diagnosed on only one occasion, 35 on two occasions, and 38 on three or more occasions. I note that the proportion of males was significantly higher in the cannabis-dependent groups (39% in never used; 49% in used but never diagnosed; 70%, 63%, 82% respectively for the cannabis-dependent).