Diet, obesity and adipokines play important roles in diabetes and CVD; yet, limited studies have assessed the relationship between diet and multiple adipokines. This cross-sectional study assessed associations between diet, adiposity and adipokines in Mexican Americans. The cohort included 1128 participants (age 34·7±8·2 years, BMI 29·5±5·9 kg/m2, 73·2 % female). Dietary intake was assessed by 12-month food frequency questionnaire. Adiposity was measured by BMI, total percentage body fat and percentage trunk fat using dual-energy X-ray absorptiometry. Adiponectin, apelin, C-reactive protein (CRP), dipeptidyl peptidase-4 (DPP-IV), IL-1β, IL-1ra, IL-6, IL-18, leptin, lipocalin, monocyte chemo-attractant protein-1 (MCP-1), resistin, secreted frizzled protein 4 (SFRP-4), SFRP-5, TNF-α and visfatin were assayed with multiplex kits or ELISA. Joint multivariate associations between diet, adiposity and adipokines were analysed using canonical correlations adjusted for age, sex, energy intake and kinship. The median (interquartile range) energy intake was 9514 (7314, 11912) kJ/d. Overall, 55 % of total intake was accounted for by carbohydrates (24 % from sugar). A total of 66 % of the shared variation between diet and adiposity, and 34 % of diet and adipokines were explained by the top canonical correlation. The diet component was most represented by sugar-sweetened beverages (SSB), fruit and vegetables. Participants consuming a diet high in SSB and low in fruits and vegetables had higher adiposity, CRP, leptin, and MCP-1, but lower SFRP-5 than participants with high fruit and vegetable and low SSB intake. In Mexican Americans, diets high in SSB but low in fruits and vegetables contribute to adiposity and a pro-inflammatory adipokine profile.

Site properties and weed species abundance are known to vary spatially across fields. The extent to which they covary is not well understood. The objective of this research was to assess how canonical correlation analysis could be used to identify associations among site properties and weed species abundance within an agricultural field. A farmer-managed field rotated between Zea mays and Glycine max in Boone County, IA, was grid-sampled for site properties in 1992 and for weed species abundance between 1994 and 1997. Twelve site properties were considered in relation to five weed species that were identified and counted after all weed control operations were completed. Site properties such as total nitrogen, Bray-1 P, percent organic carbon, and texture were spatially variable. Weed species abundance was also spatially variable such that most weeds were found in patches and much of the field was weed-free. Canonical correlation analysis identified one to four significant correlations between linear combinations of site properties and weed species abundance. The first and second pairs of linear combinations explained the majority of variation in the data and were used to identify associations among site properties and weed species abundance. In years with Z. mays, the first pair of linear combinations described an association between herbicide activity and weed presence, and the second described topography and soil texture associations with weed presence. In years with G. max, the single observed association described a link between soil texture and presence of Setaria species and Polygonum coccineum. Several consistent associations were identified across years, indicating that site properties can influence weed abundance. However, annual variation in the associations may be attributed to differences in agronomic and weed management practices for each crop, as well as temporal weather variation influencing weed abundance from year to year. This multivariate technique is an important tool to identify associations between site properties and weed abundance that could help explain observed patchy patterns of weed abundance. These associations are an important first step in the generation of hypotheses to be tested at the whole field scale.

Identification of associations between site properties and weed species abundance led to the generation of hypotheses as to why weed populations occur where they do, or do not, in agricultural fields. The objective of this research was to use a multivariate statistical technique, canonical correlation analysis, to identify the associations. Two continuous Zea mays production fields under center-pivot irrigation in the central Platte River Valley of Nebraska were grid-sampled between 1994 and 1997 for nine site properties and six to seven weed species. Weed species were identified and counted just prior to postemergence weed control in two adjacent quadrats (1 by 0.38 m) at each grid sampling point. These quadrats represented untreated weed populations emerging between crop rows and treated populations that survived preemergence herbicide banded within the crop row. Canonical correlation analysis identified one to five significant correlations between linear combinations of site properties and weed species abundance depending on field site, years, and between- vs. on-crop row weed populations. The first pair of linear combinations consistently described an association that separated weed species across a gradient of topography and soil type. The second pair of linear combinations described associations between weed species and soil fertility. In all cases, it was hypothesized that management practices strongly interacted with site properties to create the observed associations with weed populations. Other hypothesized mechanisms for weed patchiness include patchiness in available soil moisture that would influence weed seed germination, emergence, and seedling growth. Additional variation in plant-available preemergence herbicide concentration across the field site would vary weed control efficacy. Another mechanism would be variation in soil fertility that affects the growth, reproduction, and competitive ability of both the crop and the weed.