1,721,144 research outputs found
Comparing Food Desert and Non-Food Desert Residents by Key Socio-Demographic Variables, Distance to supermarkets, Supermarket Type by Price, Diet Quality and Obesity in King County, Washington
Full text linkThesis (Master's)--University of Washington, 2012The causes of obesity are multi-factorial; however, decreased access to healthy and affordable foods has emerged as an important factor. Areas where access to healthy and affordable foods is limited are known as food deserts. Although the definition of food deserts has evolved since the term was coined in the early 1990s, it is currently defined by the USDA using distance and income as the main criteria and census tracts as the geographic unit. A new web-based tool called the USDA Food Desert Locator was developed in 2011 to identify food desert census tracts across the U.S. using the USDA definition. This study utilizes information from the USDA Food Desert Locator to enhance a secondary data analysis of the Seattle Obesity Study (SOS). The overall goal of this study is to describe and compare the socioeconomic status (SES) of participants enrolled in the Seattle Obesity Study (SOS), a large county based study of food cost, access and quality. This study will also analyze the effects of residing in a food desert on measures of diet quality and obesity measures such as body mass index (BMI) among SOS participants. This is a secondary data analysis of the SOS. Briefly, the SOS is a 2007 cross-sectional telephone survey that was modeled on the CDC's Behavioral Risk Factor Surveillance System (BRFSS). The data was collected within King County, Washington in 2007 and 2008. Data for 2,001 participants was collected. The SOS survey captured extensive data on food and eating, along with demographic factors and physical measures including height and weight. Food deserts were determined using the USDA Food Desert Locator tool. Seventeen census tracts were identified and used to filter SOS participants within King County, Washington. This study analyzed individual level data to ascertain relationships between food desert residence and SES, supermarket type by price, diet quality and obesity. Results show that residing in a food desert is not the key factor associated with obesity, but that SES as defined by income and education are. Solving issues surrounding access to healthy fruits and vegetables may not be as easy as previously thought. Building a new supermarket in food deserts may solve issues of access relating to distance, but it may not solve the socioeconomic challenges facing food desert residents
Patterns of obesogenic neighborhood features and residential property values
No full textThesis (Master's)--University of Washington, 2012Obesity is a growing problem in the United States, and past research has investigated ways in which neighborhood characteristics may influence obesity prevalence. However, studying features of the obesogenic neighborhood can be difficult because of the need for complex multilevel analyses. Using data from the Seattle Obesity Study, a cross-sectional study of socioeconomic disparities in diet and health based on a representative sample of 2,001 adult residents of King County, WA, we examined property value as a new metric for capturing aspects of the built environment. We used regression analyses to examine the associations between property value and 22 total self-reported access to neighborhood amenities and perception of neighborhood characteristic variables, and further investigated the association between these neighborhood features and BMI. Eight of the 11 access to amenities variables and ten of the 11 neighborhood perception variables were associated with property values (p<0.001). The largest difference in property values due to access to amenities was associated with access to a convenience store (100,000 higher property value) and trusting the people in the neighborhood ($90,000 higher property value). We further found that the association between neighborhood features and BMI depended on gender. The data provide evidence that, because of its ability to capture complex information about the built environment, neighborhood perceptions, and socioeconomic status in a single metric, property values can be of great use in epidemiology studies
District Market: A Pilot Marketing Study
No full textThesis (Master's)--University of Washington, 2013placeholde
Socioeconomic Disparities in Health: The Role of Diet Cost
No full textThesis (Ph.D.)--University of Washington, 2014Numerous studies have linked diet quality to all-cause mortality. Diet cost has been implicated as an important determinant of diet quality and has been linked to many of the dietary patterns and scores related to adverse health outcomes, such as weight gain, type 2 diabetes mellitus (T2DM), cardiovascular disease (CVD) and all-cause mortality. However, few prospective studies have evaluated whether diet cost is associated with these adverse health outcomes. Therefore, this body of work sought to elucidate the relationship between diet cost and adverse health outcomes, while also examining the extent to which diet cost explains the association between socioeconomic status (SES) and health. To address these aims, we used data on post-menopausal women (ages 49-64 years) included in the Women's Health Initiative (WHI). Participants' daily diet cost was estimated by linking a national food price database developed by the United States Department of Agriculture was linked to the participants' food frequency questionnaire. The four outcomes of this study were weight gain, T2DM, CVD and all-cause mortality. Adjusted linear regression models were used to evaluate the association between diet cost and weight change, whereas Cox proportional hazards regression models were used to evaluate the association between diet cost and T2DM, CVD and all-cause mortality. To evaluate the extent by which diet cost explained the socioeconomic (income/education) gradient in outcomes, we evaluated the percent difference in the diet-cost adjusted income/education coefficients to the coefficients from models without the diet cost term. The association between diet cost and diet cost was evaluated in 10,807 women from the control arm of the Dietary Modification (DM-C) trial. For weight change, a 50% increase in diet costs was associated with excess weight gain of 0.33 kg (95% CI 0.06, 0.59) over up-to seven years of follow-up, though the association was modified by weight change prior to baseline. Among women who previously gained weight or were weight stable there was no significant association between diet cost and weight change. For women who previously lost weight, a 50% increase in diet cost was associated with excess weight gain of 0.87 kg (95% CI 0.34, 1.40). Given the unexpected direction of the association between diet cost and weight change subsequent SES-mediation analyses were not conducted. Over eight years of follow-up 2,174 new cases of T2DM were observed among 47,683 women from the DM-C and Observational Study (OS). A 50% increase in diet costs was associated with a 14% reduced risk of T2DM (hazard ratio [HR] 0.86; 95% CI 0.78, 0.94). In regression calibration models that incorporated estimated diet costs from the 4DFR, a 50% increase in diet cost was associated with a 22% reduced risk of diabetes (HR 0.78; 95% CI 0.67, 0.90). A strong social gradient in diabetes risk was observed for both education and income, with individuals of lower SES having an elevated risk of being diagnosed with T2DM. In mediation analyses, diet costs explained 15-19% (p<0.05 for all mediation analyses) of the association between income/education and T2DM. With eight years of follow-up 1,208 cardiovascular events were observed among 42,632 women from the DM-C and OS. A 50% increase in diet costs was associated with a 19% reduced risk of CVD (HR 0.81; 95% CI 0.72, 0.92). In regression calibration models, a 50% increase in energy-adjusted diet costs was associated with a 28% reduced risk of CVD (HR 0.72; 95% CI 0.58, 0.88). A strong social gradient in CVD risk was observed for both education and income, whereby individuals of lower SES experienced an elevated risk of CVD. In mediation analyses, diet costs explained 12-19% (p<0.008 for all mediation analyses) of social gradient in CVD. Over 12 years of follow-up, 2,055 deaths were observed among 49,336 women from the DM-C and OS. Among the entire population, diet cost was not significantly associated with mortality (HR for 50% increase diet cost: 0.95; 95% CI 0.87, 1.04). When restricting the analysis to healthy never smokers, a 50% increase in diet costs was associated with a non-significant 15% reduced risk of death (HR 0.85; 95% CI 0.70, 1.03). Given the lack of a main effect between diet cost and mortality, subsequent SES-mediation analyses were not conducted. This is the first systematic evaluation of the association between diet cost and adverse health outcomes in the United States. Contrary to the original hypothesis, higher diet costs were not associated with decreased weight gain. For T2DM and CVD, a significant inverse association between diet costs and risk of these outcomes was observed, and for mortality, there a suggestion of an association between higher diet costs and reduced mortality risk among healthy never smokers, but this association was not statistically significant. Diet cost accounted for 12-19% of the association between income/education and T2DM and CVD. The positive results observed for T2DM and CVD should be compared to results from other studies. Examining upstream factors associated with adverse health, including diet costs, expands our understanding of socioeconomic disparities in health, while also unpacking the consequences of the contemporary food environment on disease risk
Eating well and paying less: a positive deviance study
No full textThesis (Master's)--University of Washington, 2014<bold>Background/Objective</bold>: Past studies have shown that healthier diets tend to cost more. This study identified groups of positive deviants (PD) who are able to achieve healthier diets at lower cost, and characterize them by socio-demographics, dietary components, and food attitudes. <bold>Subjects/Methods</bold>: The Seattle Obesity Study (SOS) was a cross-sectional study based on a representative sample of 1266 adults of King County, WA, conducted in 2008-09. Socio-demographic and attitudinal variables were obtained through telephone survey. Dietary intake data were obtained using a food frequency questionnaire (FFQ). Diet cost was calculated based on retail prices for FFQ component foods. Healthy Eating Index-2005 (HEI), mean adequacy ratio (MAR), and energy density (ED) were used as three measures of diet quality. <bold>Results</bold>: Higher diet cost is associated with being female, aged 50-64, a college graduate or higher, and having annual household income $100,000 or more. 66 HEI positive deviants, 73 MAR positive deviants, and 33 ED positive deviants were identified who had higher diet quality at lower cost. Compared to other individuals, PD varied by gender, age, race, education, income, marital status and perceived importance of eating foods that are healthy, inexpensive and convenient. Regardless of cost, individuals with high diet quality had similar HEI component scores. However, PD were able to achieve the same high HEI at lower cost. Their diet was constituted by more fruits, vegetables, whole grains, and milk, and less saturated fats, solid fats, alcohol, and added sugars (SoFAAS). <bold>Conclusions</bold>: One way to achieve high diet quality at low cost is by choosing less expensive forms of fruits and vegetables--such as apples and carrots instead of strawberries and kale. Increasing intake of healthful food components that are less expensive, such as whole grains, meats and beans is another way to achieve a healthier diet at lower cost. Strategies to improve diet quality at low cost should also include techniques to increase the perception that it is important that food be healthy, and to improve the accuracy of self-assessments of diet quality
Validating Smartphone- and Computer-based Technologies with GPS for Activity Tracking
No full textThesis (Master's)--University of Washington, 2018The space in which we live and complete our daily activities such as shopping, eating, and working is known as the activity space. Measuring activity space can provide insights into the relation between built environment and health outcomes. Historically, geospatial research in public health was conducted using paper-and-pencil travel logs. It has since moved to Global Positioning System (GPS)-enabled instruments and to computer-assisted interviews. The purpose of this study was to validate a newly developed computer-assisted instrument, Karma, against a traditionally used GPS instrument and a smartphone-based application, MapMyRun (MMR), to study activity space. 12 participants, recruited in the spring of 2018, were asked to collect data using the three instruments over the same three days. Four primary outcome variables were tested for each participant-day (n=29): dwell point count, active dwell duration (in minutes), travel time (in minutes), and track length (in kilometers). Statistically significant correlations were observed for active dwell duration, travel time and track length from Karma with both GPS (satellite-based instrument) and MMR (smartphone-based instrument). The only exception was the dwell point count variable that did not show significant correlation between Karma and GPS. Additional analyses suggested slightly different travel patterns for food shopping days vs. non-food shopping days and for weekends vs. weekdays. Limited sample size did not allow further stratified analyses. Despite a small sample size, the present findings suggest potential use of Karma to measure activity space in lieu of GPS instruments. Further studies are needed to test the use of Karma with a larger sample size and in population segments that depend on modes of transportation other than car for their primary travel
The influence of state minimum wage increases on health and behavior
No full textThesis (Ph.D.)--University of Washington, 2020Low and minimum wage work, prevalent in the United States, is a key driver of both income inequality and income-driven health disparities. Cities and states have increasingly moved to adopt higher minimum wages with the goal of closing the income gap and improving the economic well-being of their residents. Over the last decade, academics and policymakers alike have been interested in the influence of higher wage policies on health and behavior. To date the emerging evidence has been mixed and varies depending on the populations or outcomes under study. Few studies have evaluated the longitudinal relation between higher minimum wages and health or changes in behavior. Moreover, no prior study has explored whether this relation is modified by individual economic circumstances. We used the 1999 to 2017 biannual waves of the Panel Study of Income Dynamics to examine the association between minimum wage and health (obesity, hypertension, fair or poor self-reported health, and moderate psychological distress) and behavior (smoking, drinking, and physical activity) in working-age adults, both employed and unemployed. We used a difference-in-difference-in-differences model using modified Poisson regression to evaluate the association between a $1 increase in minimum wage (current and 2-year lagged) among adults with a high school education or less in the full sample and across racial/ethnic and gender strata. We also used a difference-in-differences regression restricted to those with a high school education or less to determine whether employment instability, as measured by prior-year weeks of unemployment and years of tenure the current employer, modified the influence of minimum wage on obesity and moderate psychological distress. These evaluations of potential effect measure modification were conducted in the full sample and stratified by gender. All models were adjusted for a full set of individual and state-level covariates. We also used state and year fixed effects and cluster robust standard errors to account for within state correlations. No association between minimum wage increases and health or health behavior was observed in the overall sample of working-age adults, employed and unemployed. Subgroup models suggested a marginal reduction in obesity risk (RR = 0.82, 95% CI = 1.03, 1.50) and a marginal increase in daily cigarette consumption (RR = 1.10, 95% CI = 1.01, 1.19) in non-Hispanic White men. Higher obesity risk was found in non-Hispanic White women (RR = 1.35, 95% CI = 1.12, 1.64) associated with 2-year lagged minimum wage. Both higher current (RR = 0.73, 95% CI = 0.54, 1.00) and 2-year lagged minimum wage (RR = 0.75, 95% CI = 0.56, 1.00) were also marginally associated with a reduced risk of moderate psychological distress in non-Hispanic White women. Higher current (RR = 1.19, 95% CI 1.02, 1.40) minimum wage was associated with an increased risk of fair or poor self-reported health in women of color. Estimates were robust to restriction to workers employed hourly at baseline. We also found imprecise but suggestive evidence that prior-year unemployment, but not duration of employment, may modify the relation between minimum wage, obesity, and moderate psychological distress with the greatest risk in those exposed to both high minimum wages and greater unemployment. While no relation was observed between minimum wage and health or behaviors overall, these results are suggestive of potential heterogeneity across race/ethnicity and gender strata. Our findings with respect to modification by employment instability highlight the importance of considering the economic circumstances of individuals when evaluating the relation between social and income policies, such as the minimum wage, and health
Trends in Prices of Fresh vs. Ultra-Processed foods: Analyses of Seattle-King County Prices from 2004-16.
No full textThesis (Master's)--University of Washington, 2017-03Introduction: The availability of safe, affordable, nutrient-rich food for purchase is a key component of food equity. However, foods higher in nutrients and lower in energy tend to be associated with higher per- calorie costs. By contrast, foods with lower nutrient content and higher energy density generally cost less. Many of the lower cost foods are processed rather than fresh. This study explored the temporal profile of food prices in Seattle King county (2004-2016) by food group and by level of processing. Methods: Food prices were obtained for 379 food and beverage items from a Food Frequency Questionnaire (FFQ) provided by the Fred Hutchinson Cancer Research Center. Price data for King County were collected in 2-year cycles over 13-year period (2004-2016). In 2016 data were collected for 3 different counties in Washington State (2016). Prices data were used to generate prices per 100 g and per 100 kcal, edible portion of food. Analyses were conducted to determine whether fresh foods increased in price more than did processed and ultra-processed foods. The cross-sectional county comparisons followed the same criteria, using prices from a single cycle (2016). Prices and availability data were collected in July and August in King, Pierce, and Yakima counties in Washington State. Some items were re-collected for clarification in November. The prices were collected from the following supermarkets in King County: Safeway Inc., Quality Food Centers (QFC), and Albertsons, Pierce County: Safeway Inc., and Fred Meyer's, and Yakima County: Safeway Inc. and Fred Meyer’s. Item cost was defined by Shelf Price, Unit Price, and Price per pound or Price per pint. The independent variables were 7 food group categorizations, and 4 food processing categories. The dependent variables were /100 Kcal of food. Statistical analyses and descriptive statistics through STATA were used to compare the 2014 and 2016 prices and the 13-year time trends by food group and food processing classifications. Results: The price of the market basket of foods increased from 2004 to 2016. The food group category Fish/Poultry/Seafood was consistently the highest priced group out of the 7 total. The food processing category Fresh was consistently the most expensive classification for /100 Kcal. Foods with a higher energy density, more processed, were less expensive than food with lower energy density, less processed. Discussion: Fresher, less energy dense foods are important for healthy diets. Many studies have shown price to be a significant factor in consumers purchasing habits, and an intervention to encourage or discourage the consumption of certain foods and beverage items. The trends in food prices for both food group and food processing classifications are important for understanding future changes for policy, education, and the prevention of chronic disease
The Association between Frequency of Fast Food Restaurant Visits and Diet Quality
No full textThesis (Master's)--University of Washington, 2012Frequency of fast food restaurant visits has often been used as a marker of poor diet quality though this association has not been fully documented. This study explores the association between fast food frequency and socio-demographic characteristics, as well as several measures of overall diet quality, including the HEI-2005 score and its individual components. The relation between types of fast food restaurant most frequented and socio-demographic characteristics and diet quality is also characterized. Frequency was found to be positively associated with respondents who were younger, male, and of higher income, and negatively associated with diet quality. However, frequency alone may not be sufficient as a proxy for diet quality as these associations were not clear for all diet quality measures. "Coffee" type restaurants were preferentially visited by respondents who were younger, female, and of higher SES; "Burgers/Chicken" was preferred by older, male, and lower SES respondents. In general, diet quality was best for those who most frequent "Coffee" and lowest for respondents who prefer "Burgers/Chicken", suggesting that preferred fast food type may be indicative of dietary habits overall
Nutrient-Rich Foods in Western African Food Supply: Applying Nutrient Profiling Models to the FAO Food Composition Table for Western Africa (WAFCT 2019)
No full textThesis (Master's)--University of Washington, 2023Background: The Western Africa region faces a significant burden of malnutrition, including high rates of micronutrient deficiencies. Addressing this issue requires identifying and ensuring equitable access to local nutrient-dense foods. While nutrient profiling tools can serve for this purpose, most of them have been developed for high-income countries, requiring adaptation for the Western African context. Objective: This study aimed to adapt and apply nutrient profiling models to the FAO/INFOODS Food Composition Table for Western Africa (WAFCT) 2019. The goal was to identify locally available nutrient-dense foods across different food groups.Design: Analysis encompassed 909 WAFCT foods with complete data. The Nutrient-Rich Food (NRF) Index served as the nutrient density metric, employing three versions: two adapted for low- and middle-income countries (LMICs) (the NRF6.3 and NRF15.3), and the original NRF9.3, developed in a high-income country. The Carbohydrate Foods Quality Score (CFQS) assessed carbohydrate quality in 446 carbohydrate foods. Protein quality correction was conducted using the Protein Digestibility Corrected Amino Acid Score (PDCAAS) in 862 foods. Descriptive statistics, Pearson correlations, one-way ANOVAs, and independent and paired sample t-tests were employed for data analysis, with significance set at α=0.05. Results: Among food groups, vegetables obtained the highest NRF scores. African indigenous vegetables (AIV) demonstrated significantly higher nutrient density and protein content compared to non-indigenous vegetables. A considerable proportion (66.8%) of analyzed foods were classified as higher-quality carbohydrate foods. African indigenous grains (AIG) exhibited higher carbohydrate quality and nutrient density scores than non-indigenous grains, particularly when non-indigenous grains were unfortified. When utilizing nutrient profiling models specifically adapted for LMICs (NRF6.3 and NRF15.3), animal-sourced food groups attained higher nutrient density rankings compared to the ranking they obtained with the NRF9.3. Additionally, food groups had significant reductions in mean grams of protein per 100 grams of food after the PDCAAS adjustment; however, differences were most pronounced in plant-based foods. Conclusion: Adapting nutrient profiling tools to the West African context allowed the identification of local nutrient-dense foods. AIV and AIG were sources of priority micronutrients and higher-quality carbohydrates. Animal-sourced foods also played a crucial role in providing essential micronutrients of public health significance in Western Africa. Governments, public health institutions, and academic organizations in the region should work together to recognize the nutrient density of these foods, increase their accessibility and affordability, and promote their consumption through appropriate policies and programs
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