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Brown acknowledges the support of USAID and NASA Grants funding research on food security and environmental change. Shively acknowledges the research assistance of Celeste Sununtnasuk and support provided by the Bureau of Economic Growth, Agriculture and Trade, US Agency for International Development through the Global Nutrition Collaborative Research Support Program (Grants AID-OAA-10-00005 and AID-OAA-10-00006). The opinions expressed herein are those of the authors and do not necessarily reflect the views of the sponsoring agency.
To explore further the paradigm that nutrition can modulate toxicological insults, and to identify the potential implications of this paradigm for risk assessment of environmental pollutants and human health, the University of Kentucky Superfund Research Center invited experts from the fields of nutritional sciences, medicine, public health, and environmental toxicology, as well as scientists from the U.S. EPA National Center for Environmental Assessment, to participate in a workshop titled “Nutrition and Chemical Toxicity: Implications in Risk Assessment.” In a previous commentary (), we stated how nutrition can be used to modulate toxicological events associated with exposure to hazardous substances. Here we expand on this reasoning, and on a growing body of evidence supporting its validity, to explore new ways of incorporating nutrition within the paradigm of risk assessment. Thus, this recent meeting focused on nutrition as a modulator of environ-mental toxicity and on the need to consider nutrition (diet) as a component of risk assessment methodologies. Presentations highlighted studies that suggest that nutrition can be a potential modulator of diseases associated with exposure to environ-mental stressors. However, critical questions remain. For example, to what extent can health risks associated with exposure to environ-mental pollutants be reduced or improved through healthy nutrition? Can nutrition be a critical component in redefining methodologies used in risk assessment? That is, can nutrition (or dietary practices) be considered either a stressor or a buffer of cumulative risk from exposure to environmental pollutants?
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Many persistent environmental pollutants, including polychlorinated biphenyls (PCBs), brominated flame retardants, and organometallic compounds, can accumulate in the body. In addition, these persistent organic pollutants can generate free radicals, which in turn can trigger proinflammatory signaling pathways and associated inflammatory diseases, including atherosclerosis, diabetes, and hypertension (; ; ). B.H.’s laboratory has conducted extensive research over the years to study the effects of PCBs on the early pathology of atherosclerosis, with a particular focus on vascular endothelial cell function. These studies have shown that an increase in cellular oxidative stress and an imbalance in antioxidant status are critical events in PCB-mediated induction of inflammatory genes and endothelial cell dysfunction (reviewed by ). The research team also found that specific dietary fats can further compromise endothelial dysfunction induced by selected PCBs by further adding to a cellular oxidative and inflammatory insult. Importantly, study data suggest that antioxidant nutrients, such as vitamin E and dietary flavonoids, as well as a high ratio of omega-3 to omega-6 fatty acids, can protect against endothelial cell damage mediated by these persistent organic pollutants (; ; ). Recent data further suggest that membrane lipid rafts such as caveolae may play a major role in the regulation of PCB-induced inflammatory signaling in endothelial cells, as well as in protective mechanisms of dietary-derived polyphenols such as quercetin and the green tea catechin epigallocatechin-gallate (; ). These studies provide strong evidence that healthy nutrition can protect against proinflammatory environmental stressors. However, human studies are needed to confirm such therapeutic effects of protective nutrients. In the same context, it is important to be mindful that long-term effects of excessive antioxidant intake in the form of supplements have been questioned (; ). In addition, a multitude of bioactive food components occur in the food supply, and some of these bioactive constituents likely share the same molecular targets. Thus, continued research and a greater understanding of nutrition science will be needed to optimize any dietary intervention in order to reduce health risks associated with exposure to environmental pollutants. Evolving studies suggest that the interaction of toxicants and nutrients occurs throughout the body, and that the consequences of tissue damage by environmental pollutants can be significant. For example, a review of the National Health and Nutrition Examination Survey (NHANES) found that PCB, lead, and mercury exposures were associated with elevated blood levels of alanine aminotransferase (ALT), a marker for nonalcoholic fatty liver disease (). Interestingly, high-fructose diets also can induce non-alcoholic fatty livers or steatohepatitis, which was accompanied by a multi-fold increase in blood ALT levels (). Nonalcoholic steatohepatitis is usually associated with obesity, but it also has been reported in lean individuals exposed to industrial chemicals, such as vinyl chloride (). Taken together, these studies suggest that the involvement of similar and possibly additive liver pathologies can be induced by both environmental pollutants and certain dietary components.
Interdisciplinary work requires interdisciplinary teams, and without substantial efforts to integrate expertise across multiple disciplines, this work will not be possible. Effectively analyzing the impact of environmental change requires joint quantitative analysis of human health and nutrition, the environment and economic performance. This requires expertise across all sectors at the beginning of a study, and approaches that incorporate and ground-truth the most precise data collected at appropriate spatial and temporal scales. Creatively combining and validating existing data, and improving and coordinating the collection of future data, are research imperatives.
Many factors contribute to child nutrition outcomes. Some are more easily observed and measured than others. Going forward, researchers will need to find ways to incorporate variables such as food prices, food quality, time allocation and measures of isolation and risk. Expanding the set of explanatory variables including in these analyses will be critical to understanding the impact of an environmental stressor in a specific location. In addition, how vulnerable a community or household might be to a particular environmental extreme captured with satellite data may depend on the resilience of households and communities and their ability to draw resources from elsewhere. Adding these additional and nuanced features to datasets will be challenging, since they are often disparate in the spatial and temporal resolutions.
Differential impacts of annual seasonal hunger also have been documented anthropometrically on relatively fine spatial scales. Seasonal nutritional impacts on children differed significantly between two neighboring villages in Tanzania (Wandel and Holmboe-Ottesen ). Seasonality in food availability (Brown and de Beurs ; Husak et al. ) and in food prices and thus food access (Becquey et al. ; Devereux ; Sagn ) can have important impacts on food security outcomes, which vary depending on where an individual resides (Hillbruner and Egan ). Remote sensing science can provide links between season nutritional stress and land cover, and its differential response to climate variability at a resolution that can resolve differences in fields, communities and regions.
Remotely sensed data were incorporated in a study of agriculture and child nutrition outcomes in Nepal (Sununtnasuk ). In Nepal, sources of nutrition are often determined by local agricultural conditions because poor infrastructure, harsh terrain and high transportation costs frustrate efforts to redistribute food from food-surplus to food-deficit areas. NDVI measures were matched to data from the 2011 Nepal DHS. The combined data were used in a series of Probit regressions to evaluate whether interannual variability in weather and its impact on food production was correlated with a child’s probability of being stunted or wasted (Sununtnasuk ). The hypothesis motivating this analysis was that NDVI values might help to predict vegetation patterns which could translate to food availability and, ultimately, consumption patterns of household members (Sununtnasuk ).
In a Kenyan study, Grace et al. () examined the birth weights of infants, a health outcome that reflects a woman’s nutritional status during pregnancy. The retrospective nature of the DHS allowed the researchers to examine birth weights, as recalled by the mother, of her most recently born children. Birth weights were classified as healthy or low birth weight using the WHO cutoff value of 2,500 g. Community NDVI and local maize prices were associated with each birth for each of the 12 months preceding each birth—the preconception and pregnancy periods. NDVI served as a measure of food production (food availability) in the community, while maize prices, provided by the Famine Early Warning Systems Network and USAID, served as indicators of food availability. Maize price data were only available for a small selection of major markets in Kenya. Because the livelihood zone data provided by FEWS NET reflects the dominant strategy used to produce food and household income in an area and are constructed with attention to markets, these zones were used to group community clusters. In other words, all communities that were located within a specific livelihood zone were assumed to be subject to the same price patterns represented by those of the major markets in the zone. The researchers assumed that an increase in maize price in one livelihood zone would reduce access to one of the most important food items relied on by Kenya’s poor for all residents in that livelihood zone. This price increase would indicate a general reduction in food access of the populations most likely to face food insecurity (Grace et al. ).
A weight-for-height Z score is an inherently short-term indicator of acute food shortage or compromised health. In contrast, a height-for-age Z score is a longer-term indicator of chronic food shortage or compromised health. Because these nutrition indicators may reflect environmental conditions that prevailed during different time periods in the child’s history, it may prove advantageous during analysis to explicitly link remotely sensed data to nutrition-sensitive periods in the child’s life. Furthermore, if environmental outcomes are hypothesized to reflect agronomic conditions, such as growing conditions in a local area, it may be necessary to account for the crop calendar and relevant growing periods for the most commonly grown crops in the vicinity of a household.