Dataset Information

Identifying and mitigating risks for agricultural injury associated with obesity.

ABSTRACT: In some occupational contexts overweight and obesity have been identified as risk factors for injury. The purpose of this study was to examine this hypothesis within farm work environments and then to identify specific opportunities for environmental modification as a preventive strategy. Data on farm-related injuries, height and weight used to calculate body mass index (BMI), and demographic characteristics were from the Phase 2 baseline survey of the Saskatchewan Farm Injury Cohort; a large cross-sectional mail-based survey conducted in Saskatchewan, Canada from January through May 2013. Multivariable logistic regression was used to examine associations between BMI and injury. Injury narratives were explored qualitatively. Findings were inconsistent and differed according to gender. Among women (n = 927), having overweight (adjusted OR: 2.94; 95% CI: 1.29 to 6.70) but not obesity (1.10; 95% CI: 0.35 to 3.43) was associated with an increased odds of incurring a farm-related injury. No strong or statistically significant effects were observed for men (n = 1406) with overweight or obesity. While injury-related challenges associated with obesity have been addressed in other occupational settings via modification of the worksite, such strategies are challenging to implement in farm settings because of the diversity of work tasks and associated hazards. We conclude that the acute effects of overweight in terms of injury do require consideration in agricultural populations, but these should also be viewed with a differentiation based on gender.

SUBMITTER: King N

PROVIDER: S-EPMC4929122 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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Identifying and mitigating risks for agricultural injury associated with obesity.

King Nathan N Janssen Ian I Hagel Louise L Dosman James J Lawson Joshua J Trask Catherine C Pickett William W

Preventive medicine reports 20160607

In some occupational contexts overweight and obesity have been identified as risk factors for injury. The purpose of this study was to examine this hypothesis within farm work environments and then to identify specific opportunities for environmental modification as a preventive strategy. Data on farm-related injuries, height and weight used to calculate body mass index (BMI), and demographic characteristics were from the Phase 2 baseline survey of the Saskatchewan Farm Injury Cohort; a large cr ...[more]

PMID: 27413685

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Project description:OBJECTIVES:To apply spinal cord injury (SCI) specific waist circumference (WC) cutoff point to identify risks of 1) obesity, 2) metabolic syndrome (MetS), 3) cardiovascular disease (CVD). METHODS:Thirty-six men with chronic SCI underwent anthropometric measurements, dual-energy x-ray absorptiometry (DXA), and magnetic resonance imaging (MRI) to measure total and regional adiposity. An SCI specific WC cutoff point of 86.5 cm was applied to the existing general population criteria. Pearson chi-square (?2) analyses tested the difference in the number of participants classified as obese using the SCI specific cutoff point compared to the general population criteria. Sensitivity and specificity analyses relative to percentage body fat mass and visceral adipose tissue was used to assess classification performance of this cutoff point. The interrater reliability for three definitions of MetS was assessed using Cohen's Kappa (?) values. Linear regression analyses were utilized to propose SCI specific Framingham Coronary Heart Disease Risk Score (FRS) cutoff value. RESULTS:Using SCI specific WC cutoff point of 86.5 cm, 36% of participants were classified as obese compared to only 3% when using WC of 102 cm (P < 0.001). Relative to percentage body fat mass, the general population WC cutoff point of 102 cm had a sensitivity of 6.3% and specificity of 100% both which changed to 68.8% and 90%, respectively, with a SCI specific cutoff point of 86.5 cm. Similar results were obtained when using visceral adipose tissue as a reference. The Kappa (?) values improved substantially after using SCI specific criteria (0.95 ± 0.05) compared to the general population criteria (0.47 ± 0.28) for three definitions of MetS. The SCI specific FRS cutoff value of 6 was predicted after applying a WC cutoff of 86.5 cm. CONCLUSIONS:Using the existing general population criteria underestimated persons with SCI who are at risk of developing obesity, MetS, and CVD. The recommended SCI specific criteria are likely to distinguish those at risks of developing comorbidities and allow healthcare providers to intervene in a timely manner.

Project description:Industrialization plays a vital role in the development of a country’s economy. However, it also adversely affects the environment by discharging various unwanted and harmful substances such as heavy metals into the surface and subsurface aquifers. The current research work investigates the identification, characterization, and evaluation of specific heavy metals in industrial wastewater (IWW) and different composite samples of soil and vegetables (onion, pumpkin, lady finger, and green pepper) collected from selected agricultural fields irrigated with canals fed IWW in Mingora city of Swat (Pakistan). Obtained results were compared with the tube well water irrigated soil and vegetables grown in it. Heavy metals accumulation was tested through wet digestion method and atomic absorption spectrophotometry (AAS). The metal transfer factor (MTF) of heavy metals from soil to vegetables was also determined along with the health index (HI) to assess the potential health risk of the metals towards consumers using Monte Carlo simulation technique. Analysis of water samples showed that the concentration in mg l-1 of heavy metals in IWW follows the trend Fe (6.72) > Cr (0.537) > Pb (0.393) > Co (0.204) > Mn (0.125) > Ni (0.121). Analysis of the soil samples irrigated with IWW followed the order of Fe (47.27) > Pb (2.92) > Cr (2.90) >Ni (1.02) > Mn (0.90) > Co (0.68) and Fe (17.12) > Pb (2.12) > Cr (2.03) >Ni (0.76) > Co (0.49) > Mn (0.23) irrigated with TWW. Heavy metals concentration values found in soil irrigated with IWW were higher than the soil irrigated with TWW. Similar trends were found for agricultural produces grown on soil irrigated with IWW and found higher than the normal allowable WHO limits, indicating higher possibilities of health risks if continuously consumed. MTF values were found higher than 1 for ladyfinger and green pepper for Pb intake and pumpkin for Mn intake. The current study suggests the continuous monitoring of soil, irrigation water and agricultural products to prevent heavy metals concentration beyond allowable limits, in the food chain. Thus, concrete preventive measures must be taken to reduce heavy metal accumulation through wastewater irrigation to protect both human and animal health in the study area of Mingora Swat Pakistan.

Project description:BackgroundLarge sample sets of whole genome sequencing with deep coverage are being generated, however assembling datasets from different sources inevitably introduces batch effects. These batch effects are not well understood and can be due to changes in the sequencing protocol or bioinformatics tools used to process the data. No systematic algorithms or heuristics exist to detect and filter batch effects or remove associations impacted by batch effects in whole genome sequencing data.ResultsWe describe key quality metrics, provide a freely available software package to compute them, and demonstrate that identification of batch effects is aided by principal components analysis of these metrics. To mitigate batch effects, we developed new site-specific filters that identified and removed variants that falsely associated with the phenotype due to batch effect. These include filtering based on: a haplotype based genotype correction, a differential genotype quality test, and removing sites with missing genotype rate greater than 30% after setting genotypes with quality scores less than 20 to missing. This method removed 96.1% of unconfirmed genome-wide significant SNP associations and 97.6% of unconfirmed genome-wide significant indel associations. We performed analyses to demonstrate that: 1) These filters impacted variants known to be disease associated as 2 out of 16 confirmed associations in an AMD candidate SNP analysis were filtered, representing a reduction in power of 12.5%, 2) In the absence of batch effects, these filters removed only a small proportion of variants across the genome (type I error rate of 3%), and 3) in an independent dataset, the method removed 90.2% of unconfirmed genome-wide SNP associations and 89.8% of unconfirmed genome-wide indel associations.ConclusionsResearchers currently do not have effective tools to identify and mitigate batch effects in whole genome sequencing data. We developed and validated methods and filters to address this deficiency.

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Identifying and mitigating risks for agricultural injury associated with obesity.

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Identifying and mitigating risks for agricultural injury associated with obesity.

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