Such research provides insight into our evolutionary diet, and also reveals why any comparative "proof" that ignores intelligence and the significant impact of brain size on metabolic requirements is logically dubious.
Life cycle and energy requirements
Parker  analyzes intelligence and encephalization from the perspective of life history strategy (LHS) theory, a branch of behavioral ecology.
General setting. We selected existing cohort studies of mortality and chronic diseases in Europe based on their potential to quantify relationships between long-term exposure and health response. Cohorts were eligible to participate in the analysis of BP and hypertension if the following data were available: a) BP values, measured according to the World Health Organization (WHO) Multinational MONItoring of trends and determinants in CArdiovascular Diseases (MONICA) protocol () or a study-specific standard; b) information on BPLM use; and c) long-term residential TRAP concentrations at the residence, assessed with the ESCAPE land use regression (LUR) model.
"An uncooked vegan diet shifts the profile of human fecal microflora: computerized analysis of direct stool sample gas-liquid chromatography profiles of bacterial cellular fatty acids."
Peltonen R, Ling WH, Hanninen O, Eerola E.
1992 Nov; vol. 58, pp. 3660-6. Also see comment in: 1993 Aug; vol. 59, pp. 2763-4.
Note to readers with disabilities: EHP has provided a table of contents summarizing the Supplemental Material for this article (see below) so readers with disabilities may determine whether they wish to access the full, nonconformant Supplemental Material. If you need assistance accessing journal content, please contact . Our staff will work with you to assess and meet your accessibility needs within 3 working days.
(The above is adapted from Leonard and Robertson .) An understanding of Kleiber's Law is important to several of the discussions in this paper. A key observation to note about relative brain size when averaged across species is that the equation for how brain size varies in proportion to body size uses an exponential scaling factor almost identical to the one used in the equation for how an organism's basal metabolic rate (BMR) varies with body size, i.e.
This study has several limitations. We used exposures based on the baseline home address as a proxy for actual exposures over time. However, a number of studies have also demonstrated that land-use regressions, such as the one used here, are quite robust to historical changes (; ; ). Our inability to incorporate changes in residence during the study period would have induced further exposure misclassification. Another limitation is that we were not able to adjust our analyses of NO2 (due to violations in the required assumptions) and the traffic proximity and volume measures (due to a lack of data in the validation study) for measurement error. The high β12σ2 for NO2 is likely attributable to the presence of indoor sources or low air exchange rates, which have been consistently observed in other studies (; ; ; ; ). Given the differences in measurement error for PM2.5 and BS, it is not possible to determine the potential magnitude error that would be observed for NO2. We are also not able to quantify the impact of indoor sources of NO2 on lung cancer risk. Therefore, our NO2 associations should be treated with caution and interpreted only as the ambient effects of these exposures. Last, as with all studies, residual confounding is a concern. Our study was not able to update potential confounders, such as smoking or diet, after baseline, and we were missing information on potential confounders such as secondhand smoke and occupation for around 10% of the study participants.
Finally, although residual confounding cannot be excluded, it is not likely to have occurred in our study. Individual-level potential confounders, such as smoking and other lifestyle factors, are not available for Medicare enrollees, as these data are collected largely for utilization and cost statistics and not for epidemiological analyses. We did, however, select a study design that did not allow potential confounders that varied across cities, or long-term trends, to affect our estimates. Moreover, we adjusted for age, race, sex, and SES, as well as for any prior cardiopulmonary admission and severity of disease. In addition, chronic PM2.5-mortality studies using Medicare data have yielded very similar results to studies that adjusted for more individual-level confounders (; ).
To our knowledge, this has been the first large-scale, multi-site epidemiologic study to examine the association between air pollution and hospital admissions due to the most common neurodegenerative diseases. We observed statistically significant, positive associations between long-term PM2.5 city-wide exposures and PD, AD, and dementia, supporting our hypothesis. In light of our limitations, our results should be viewed as preliminary; our findings provide the basis for further exploration in large epidemiologic studies with validated outcomes and more detailed information on potential individual-level confounders. Such studies are of crucial importance, as the implications for public health are tremendous, especially given the anticipated increase in life expectancy.
We detected significant effect heterogeneity in the estimates across cities for all outcomes. This finding could be partially attributed to the large number of cities and participants in our study, which provided ample power to detect heterogeneity even across the smallest differences in estimates. It is also likely that other factors contributed to this heterogeneity. For example, particle composition has been shown to modify the association between long-term exposure to air pollution and other outcomes, such as mortality (). Nevertheless, it should be noted that the majority of the estimates across cities were positive and many of those were significantly so (–), indicating that this heterogeneity only reflected differences across harmful estimates.
Based on existing knowledge of possible nonlinear relationships for age, BMI, pack-years of smoking, and wine consumption (where available), the corresponding terms were entered as linear and squared, centered on the mean.
That is, diet would have been an important hurdle--or limiting factor--to surmount in providing the necessary physiological basis for brain enlargement to occur within the context of whatever those other primary selective pressures might
The significance of Leonard and Robertson's research [1992, 1994] lies in their analysis of energy metabolism, which reveals the paradox: How do humans meet the dramatically higher energy needs of our brains, without a corresponding increase in RMR (which is related to our body size)?
Even though the direct epidemiologic evidence linking PM2.5 exposure to neurodegenerative diseases is sparse, toxicological studies have been published proposing several potential biological pathways (; ). One potential pathway, for instance, is through oxidative stress: air pollution exposures have been repeatedly linked to oxidative stress (; ; ; ). Furthermore, several studies reported evidence suggesting that oxidative stress plays a key pathogenic role in AD (; ; ; ). Inflammation has also been related to both air pollution exposure and neurodegeneration (). Both short- and long-term exposure to PM2.5 has been linked to increases in blood inflammatory markers (; ). Inflammatory processes are thought to play an important role in the pathogenesis of both PD () and AD ().