5 resultados para food preparation

em DigitalCommons@The Texas Medical Center


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Existing literature examining the association between occupation and asthma has not been adequately powered to address this question in the food preparation or food service industries. Few studies have addressed the possible link between occupational exposure to cooking fumes and asthma. This secondary analysis of cohort study data aimed to investigate the association between adult-onset asthma and exposure to: (a) cooking fumes at work or (b) longest-held employment in food preparation or food service (e.g. waiters and waitresses, food preparation workers, non-restaurant food servers, etc.). Participants arose from a cohort of Mexican-American women residing in Houston, TX, recruited between July 2001 and June 2007. This analysis used Cox proportional-hazards regression to estimate the hazard ratio of adult-onset asthma given the exposures of interest, adjusting for age, BMI, smoking status, acculturation, and birthplace. We found a strong association between adult-onset asthma and occupational exposure to cooking fumes (hazard ratio [HR] = 1.77; 95% confidence interval [CI], 1.15, 2.72), especially in participants whose longest-held occupation was not in the food-related industry (HR = 2.12; 95% CI, 1.21, 3.60). In conclusion, adult-onset asthma is a serious public health concern for food industry workers. ^

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Recent data have shown that the percentage of time spent preparing food has decreased during the past few years, and little information is know about how much time people spend grocery shopping. Food that is pre-prepared is often higher in calories and fat compared to foods prepared at home from scratch. It has been suggested that, because of the higher energy and total fat levels, increased consumption of pre-prepared foods compared to home-cooked meals can lead to weight gain, which in turn can lead to obesity. Nevertheless, to date no study has examined this relationship. The purpose of this study is to determine (i) the association between adult body mass index (BMI) and the time spent preparing meals, and (ii) the association between adult BMI and time spent shopping for food. Data on food habits and body size were collected with a self-report survey of ethnically diverse adults between the ages of 17 and 70 at a large university. The survey was used to recruit people to participate in nutrition or appetite studies. Among other data, the survey collected demographic data (gender, race/ethnicity), minutes per week spent in preparing meals and minutes per week spent grocery shopping. Height and weight were self-reported and used to calculate BMI. The study population consisted of 689 subjects, of which 276 were male and 413 were female. The mean age was 23.5 years, with a median age of 21 years. The fraction of subjects with BMI less than 24.9 was 65%, between 25 and 29.9 was 26%, and 30 or greater was 9%. Analysis of variation was used to examine associations between food preparation time and BMI. ^ The results of the study showed that there were no significant statistical association between adult healthy weight, overweight and obesity with either food preparation time and grocery shopping time. Of those in the sample who reported preparing food, the mean food preparation time per week for the healthy weight, overweight, and obese groups were 12.8 minutes, 12.3 minutes, and 11.6 minutes respectively. Similarly, the mean weekly grocery shopping for healthy, overweight, and obese groups were 60.3 minutes per week (8.6min./day), 61.4 minutes (8.8min./day), and 57.3 minutes (8.2min./day), respectively. Since this study was conducted through a University campus, it is assumed that most of the sample was students, and a percentage might have been utilizing meal plans on campus, and thus, would have reported little meal preparation or grocery shopping time. Further research should examine the relationships between meal preparation time and time spent shopping for food in a sample that is more representative of the general public. In addition, most people spent very little time preparing food, and thus, health promotion programs for this population need to focus on strategies for preparing quick meals or eating in restaurants/cafeterias. ^

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Background. The purpose of this study was to describe the risk factors and demographics of persons with salmonellosis and shigellosis and to investigate both seasonal and spatial variations in the occurrence of these infections in Texas from 2000 to 2004, utilizing time series analyses and the geographic information system digital mapping methods. ^ Methods. Spatial Analysis: MapInfo software was used to map the distribution of age-adjusted rates of reported shigellosis and salmonellosis in Texas from 2000–2004 by zip codes. Census data on above or below poverty level, household income, highest level of educational attainment, race, ethnicity, and urban/rural community status was obtained from the 2000 Decennial Census for each zip code. The zip codes with the upper 10% and lower 10% were compared using t-tests and logistic regression to determine whether there were any potential risk factors. ^ Temporal analysis. Seasonal patterns in the prevalence of infections in Texas from 2000 to 2003 were determined by performing time-series analysis on the numbers of cases of salmonellosis and shigellosis. A linear regression was also performed to assess for trends in the incidence of each disease, along with auto-correlation and multi-component cosinor analysis. ^ Results. Spatial analysis: Analysis by general linear model showed a significant association between infection rates and age, with young children aged less than 5 and those aged 5–9 years having increased risk of infection for both disease conditions. The data demonstrated that those populations with high percentages of people who attained a higher than high school education were less likely to be represented in zip codes with high rates of shigellosis. However, for salmonellosis, logistic regression models indicated that when compared to populations with high percentages of non-high school graduates, having a high school diploma or equivalent increased the odds of having a high rate of infection. ^ Temporal analysis. For shigellosis, multi-component cosinor analyses were used to determine the approximated cosine curve which represented a statistically significant representation of the time series data for all age groups by sex. The shigellosis results show 2 peaks, with a major peak occurring in June and a secondary peak appearing around October. Salmonellosis results showed a single peak and trough in all age groups with the peak occurring in August and the trough occurring in February. ^ Conclusion. The results from this study can be used by public health agencies to determine the timing of public health awareness programs and interventions in order to prevent salmonellosis and shigellosis from occurring. Because young children depend on adults for their meals, it is important to increase the awareness of day-care workers and new parents about modes of transmission and hygienic methods of food preparation and storage. ^

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In this study we sought to identify and understand feelings, benefits and barriers to making heart healthy behavioral changes by reviewing and analyzing participant responses to a follow-up telephone survey conducted as part of the HEART project (Health Education Awareness Research Team). Individuals who participated in HEART attended classes and received “Su Corazon, Su Vida” education. The HEART follow-up telephone survey was conducted only on those participants who were part of the experimental group. A total of 93 individuals from this group were successfully contacted for participation in the telephone survey after the classes ended. Quantitative data regarding ‘feelings’ and ‘difficulty making heart healthy behavioral changes’ were analyzed by calculating frequencies of each category of response for post-intervention weeks 9, 13, and 15. In addition, Wilcoxon rank-sum tests were conducted for post-intervention at weeks 9, 13, and 15 to measure associations between feelings and difficulties making heart healthy behavioral changes. Changes in responses over time for feelings and difficulties making heart healthy behavioral changes were looked at by counting differences in responses between pairs of follow up weeks. Qualitative responses to the survey were analyzed by categorizing content of responses under themes in order to identify factors related to feelings and difficulties making heart healthy behavioral changes. Telephone survey participants showed positive attitudes towards making nutritional and physical activity changes. Out of the 93 telephone survey respondents, 53 (57%) reported some type of physical activity change during the follow-up period while 46 (49%) reported specific changes in nutrition. Data from the “difficulty to making changes” responses were categorized under constructs from the Health Belief Model, perceived benefits and barriers. Overall, the barriers for physical activity were health issues, individual habits and time. Barriers to eating healthy were family support, individual habits, and knowledge. This study suggests that with respect to nutritional knowledge barriers, educational programs should explore other ways of teaching and familiarizing individuals with information sources that may be more appropriate for those populations not accustomed to them. For example, nutrition labels, portions, recipes, and use of photonovelas. Our findings of the barriers to changes in food preparation due to lack of family support may also suggest the need for the development of programs where influential partners or relatives are involved in order to create a more supportive environment which may provide more opportunity for change toward healthier lifestyle behaviors. Finally, the physical activity barriers found suggest that it may be beneficial to recommend appropriate exercises for those with specific health problems or those with time restrictions due to work or travel so that physical activity is not completely avoided.^

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Few, if any studies, have attempted to identify the specific environmental factors associated with the incidence of diarrheal disease and to rank these by their contribution to the total incidence of diarrheal illness. Potentially those factors with the greatest contribution are the variables on which intervention could be expected to have the greatest impact on the incidence of diarrhea.^ In 317 rural Egyptian households participating in a longitudinal study of diarrheal disease, selected environmental characteristics were observed and recorded on a questionnaire. Characteristics of the environment were classified into seven categories including water usage, proximity of animals to the house, waste management, food preparation area, toilet area, the household structure and hygiene. The variables from each of the seven major groupings most associated with the incidence of diarrhea in infants were selected through the application of stepwise multiple regression. Each area was then ranked by the portion of the incidence of diarrhea in infants that each composite group of area-specific variables alone would explain. The groups of household structure and water usage variables were found to be more associated with the incidence of diarrhea in infants than variables describing the toilet area, proximity to animals or others. It was also found that 24.7% of the total variance in incidence of diarrheal illness was explained by environmental variables. ^