Matching Items (27)
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Description

Disparities in healthy food access are well documented in cross-sectional studies in communities across the United States. However, longitudinal studies examining changes in food environments within various neighborhood contexts are scarce. In a sample of 142 census tracts in four low-income, high-minority cities in New Jersey, United States, we examined

Disparities in healthy food access are well documented in cross-sectional studies in communities across the United States. However, longitudinal studies examining changes in food environments within various neighborhood contexts are scarce. In a sample of 142 census tracts in four low-income, high-minority cities in New Jersey, United States, we examined the availability of different types of food stores by census tract characteristics over time (2009–2017). Outlets were classified as supermarkets, small grocery stores, convenience stores, and pharmacies using multiple sources of data and a rigorous protocol. Census tracts were categorized by median household income and race/ethnicity of the population each year. Significant declines were observed in convenience store prevalence in lower- and medium-income and majority black tracts (p for trend: 0.004, 0.031, and 0.006 respectively), while a slight increase was observed in the prevalence of supermarkets in medium-income tracts (p for trend: 0.059). The decline in prevalence of convenience stores in lower-income and minority neighborhoods is likely attributable to declining incomes in these already poor communities. Compared to non-Hispanic neighborhoods, Hispanic communities had a higher prevalence of small groceries and convenience stores. This higher prevalence of smaller stores, coupled with shopping practices of Hispanic consumers, suggests that efforts to upgrade smaller stores in Hispanic communities may be more sustainable.

ContributorsOhri-Vachaspati, Punam (Author) / DeWeese, Robin (Author) / Acciai, Francesco (Author) / DeLia, Derek Michael, 1969- (Author) / Tulloch, David (Author) / Tong, Daoqin (Author) / Lorts, Cori (Author) / Yedidia, Michael J., 1946- (Author)
Created2019-07-03
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Description

Introduction

The US Preventive Services Task Force recommends that all patients be screened for obesity and, if needed, be provided weight-loss advice. However, the prevalence of such advice is low and varies by patient demographics. This study aimed to describe the determinants of receiving weight-loss advice among a sample with

Introduction

The US Preventive Services Task Force recommends that all patients be screened for obesity and, if needed, be provided weight-loss advice. However, the prevalence of such advice is low and varies by patient demographics. This study aimed to describe the determinants of receiving weight-loss advice among a sample with a high proportion of low-income, racial/ethnic minority individuals.

Methods

Data were collected from a telephone survey of 1,708 households in 2009 and 2010 in 5 cities in New Jersey. Analyses were limited to 1,109 overweight or obese adults. Multivariate logistic regression determined the association of participants’ characteristics with receiving weight-loss advice from their health care provider. Two models were used to determine differences by income and insurance status.

Results

Of all overweight or obese respondents, 35% reported receiving advice to lose weight. Receiving advice was significantly associated with income in multivariate analysis. Compared with those with an income at or below 100% of the federal poverty level (FPL), those within 200% to 399% of the FPL had 1.60 higher odds of receiving advice (P = .02), and those with an income of 400% or more of the FPL had 1.73 higher odds of receiving advice (P = .03). The strength of the association did not change after adjusting for health insurance.

Conclusion

Income is a significant predictor of whether or not overweight or obese adults receive weight-loss advice after adjustment for demographic variables, health status, and insurance status. Further work is needed to examine why disparities exist in who receives weight-loss advice. Health care providers should provide weight-loss advice to all patients, regardless of income.

ContributorsLorts, Cori (Author) / Ohri-Vachaspati, Punam (Author)
Created2016-10-06
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Description
PURPOSE: The aim of this study was to determine if the linear and nonlinear components of the energy expenditure-walking speed relationship are influenced by body mass index (BMI; kg/m2). The secondary aims were to determine if the relationship was influenced by age, height, and sex. METHODS: Subjects (n=182)

PURPOSE: The aim of this study was to determine if the linear and nonlinear components of the energy expenditure-walking speed relationship are influenced by body mass index (BMI; kg/m2). The secondary aims were to determine if the relationship was influenced by age, height, and sex. METHODS: Subjects (n=182) walked at 2, 3, and 4 mph for six minutes each with oxygen consumption (V̇O2; ml/kg/min) and measured via indirect calorimetry and converted to energy expenditure (EE; W/kg). Because of the curvilinear change in metabolic rate with increase in walking speed, polynomial random coefficient regression (PRCR) was employed to produce a model which captures the slope of change. Individual level linear and quadratic coefficients were analyzed for relationships with BMI, age, height, and sex. RESULTS: The net V̇O2 regression formula for walking was 1.79(x-3)2+4.97(x-3)+9.32 where x is speed in mph. BMI was modestly correlated with the quadratic coefficients (r = 0.15 to 0.17, p = 0.02 to 0.04) but not the linear coefficients (r =0.02- 0.07, p = 0.36-0.78) for V̇O2 and EE. There was no difference in coefficients between normal BMI (18.5-<25.0 kg/m2), overweight (25-<30.0 kg/m2) and obese (>30.0 kg/m2) groups (H = 1.5-4.0, p = 0.13-0.48). Delta V̇O2 for 2-3 mph, 3-4 mph, and 2-4 mph were not correlated with BMI (r = -0.02 - 0.13, p = 0.11 - 0.41). Height was inversely correlated with the linear and quadratic coefficients (r = -0.32 to -0.14, p = 0.09). Age was not correlated to coefficients (r = -0.16 to 0.32, p = 0.06-0.44). The coefficients for sex were not different after controlling for height in ANCOVA (F(1,179)=0.3-2.9, p >0.09). Age was not correlated to coefficients (r = -0.16 to –0.32, p = 0.06-0.44). CONCLUSION: Although BMI had a modest relationship with the quadratic coefficient, it explained less than 3% of the variance in V̇O2 or EE. Combined with the absence of a delta V̇O2 or a linear component, BMI does not influence the energy expenditure-walking speed relationship. Height explained up to 9% of the variance in the coefficients and eliminated apparent sex differences. Age was not related to the coefficients.
ContributorsBeaumont, Joshua S (Author) / Gaesser, Glenn A (Thesis advisor) / Angadi, Siddhartha S (Thesis advisor) / Adams, Marc A (Committee member) / Dickinson, Jared M (Committee member) / Peterson, Daniel S (Committee member) / Arizona State University (Publisher)
Created2023
Description

In March 2020, the COVID-19 pandemic triggered a sudden and severe economic downturn. Between February and May 2020, the number of unemployed individuals rose by more than 14 million, resulting in an unprecedented increase in the unemployment rate, which went from 3.8% in February to 14.4% in April. Even though unemployment

In March 2020, the COVID-19 pandemic triggered a sudden and severe economic downturn. Between February and May 2020, the number of unemployed individuals rose by more than 14 million, resulting in an unprecedented increase in the unemployment rate, which went from 3.8% in February to 14.4% in April. Even though unemployment has declined in recent months, with some individuals returning to work, the rate is still much higher than it was one year ago (7.9% in September 2020 vs. 3.5% in September 2019). Further, as of September 2020, there are 19.4 million persons unable to work due to the pandemic, as well as 6.3 million persons working only part time even though they would prefer to work more.

Created2020-11
Description

The coronavirus (COVID-19) pandemic has affected employment and food security globally and in the United States. To understand the impacts of COVID-19 on food security in Arizona, a representative survey of Arizona households was launched online from July 1 to August 10, 2020. This brief provides an overview of changes

The coronavirus (COVID-19) pandemic has affected employment and food security globally and in the United States. To understand the impacts of COVID-19 on food security in Arizona, a representative survey of Arizona households was launched online from July 1 to August 10, 2020. This brief provides an overview of changes in food security rate, perceived worries and challenges about food security, as well as behavioral changes and strategies adopted since the pandemic. Additional briefs from the Arizona survey covering topics on economic consequences, food access, and participations in food assistance programs during the pandemic are also available.

ContributorsAcciai, Francesco (Author) / Yellow Horse, Aggie J. (Author) / Martinelli, Sarah (Author) / Josephson, Anna (Author) / Evans, Tom P. (Author) / Ohri-Vachaspati, Punam (Author)
Created2020-11
Description

The coronavirus (COVID-19) pandemic led to disruptions in the food supply and high rates of unemployment and under-employment, both in Arizona and nationally. These emergencies required food assistance programs to adapt quickly and in unprecedented ways by relaxing eligibility criteria, improvising on delivery modalities, and increasing benefits. To examine food assistance program

The coronavirus (COVID-19) pandemic led to disruptions in the food supply and high rates of unemployment and under-employment, both in Arizona and nationally. These emergencies required food assistance programs to adapt quickly and in unprecedented ways by relaxing eligibility criteria, improvising on delivery modalities, and increasing benefits. To examine food assistance program participation during the pandemic, we collected data from a representative sample of 620 Arizona households. The sample was drawn from across Arizona in July-August 2020 using an online survey. This brief provides the summary for participation in key food assistance programs, namely, the Supplementary Nutrition Assistance Program (SNAP), the Special Supplemental Program for Women Infants and Children (WIC), School Food Programs, and the emergency food assistance provided through food pantries.

ContributorsMartinelli, Sarah (Author) / Acciai, Francesco (Author) / Yellow Horse, Aggie J. (Author) / Josephson, Anna (Author) / Ohri-Vachaspati, Punam (Author)
Created2020-11
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Description

The epidemic of overweight and obesity and its multiple causes have captured the attention of researchers, program administrators, politicians, and the public alike. Recently, many stakeholder groups have started investigating the role that food and nutrition assistance programs play in the etiology of the problem and in identifying possible solutions.

The epidemic of overweight and obesity and its multiple causes have captured the attention of researchers, program administrators, politicians, and the public alike. Recently, many stakeholder groups have started investigating the role that food and nutrition assistance programs play in the etiology of the problem and in identifying possible solutions. As a result, policy changes have been recommended and implemented for programs such as the National School Lunch Program (NSLP) and the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) to improve the nutritional quality of foods they offer to their participants. The Supplemental Nutrition Assistance Program (SNAP) is also attracting attention as a potential vehicle to reduce the burden of obesity among its users. Because of the tough economic and political climate in which all federal programs currently operate, the need for making nutrition assistance programs more efficient and effective in addressing health and nutrition related problems affecting the country has never been greater.

This document proposes a set of strategies to improve the effectiveness and efficiency of SNAP. These strategies are based on a review of research literature, recommendations from expert groups, and the experiences of other communities and states. We include information that pertains to potential stakeholder arguments for and against each strategy, as well as the political feasibility, financial impact, and logistical requirements for implementation. We drew candidate strategies from the range of options that have been tested through research and from policies that have been implemented around the country. The order of strategies in this document is based on overall strength of supportive research, as well as political and implementation feasibility. The four proposed strategies are improving access to healthy foods to provide better choices, incentivizing the purchase of healthy foods, restricting access to unhealthy foods, and maximizing education to more effectively reach a larger population of SNAP participants.

Created2011
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Description

This brief summarizes the different types of food stores open in New Brunswick, New Jersey and in a one mile radius around the city during 2008 to 2014.

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Description

With more than 19 million confirmed COVID-19 cases across the United States1 and over 500,000 in Arizona as of December 2020, the ongoing pandemic has had devastating impacts on local, national, and global economies. Prior to the pandemic (February 2020), based on U.S. Bureau of Labor Statistics data, the unemployment rate

With more than 19 million confirmed COVID-19 cases across the United States1 and over 500,000 in Arizona as of December 2020, the ongoing pandemic has had devastating impacts on local, national, and global economies. Prior to the pandemic (February 2020), based on U.S. Bureau of Labor Statistics data, the unemployment rate in Arizona was 6.5%, compared to 4.9% at the national level.3 Since the beginning of the COVID-19 pandemic (March 2020), the United States has experienced striking increases in the unemployment rate, reaching 13.2% in April. Similarly, in Arizona, the unemployment rate jumped to over 13.5% in April. The unemployment rates have since declined both nationally and in Arizona but remain higher compared to February 2020. In November 2020 (the most recent data available), the national unemployment rate was 6.7%, while in Arizona the rate was 7.8%—the 10th highest unemployment rate among all U.S. states.

Created2020-12