Consistently Bounding Parameter Values with One Instrument and Two Endogenous Explanatory Variables: With an Application to the Effect of Fast-Food Availability on Obesity

2009 ◽  
Author(s):  
Richard A. Dunn
Keyword(s):  
Food Availability ◽  
Fast Food ◽  
Explanatory Variables ◽  
Parameter Values

scholarly journals Food Insecurity, Diet Quality, Home Food Availability, and Health Risk Behaviors Among Emerging Adults: Findings From the EAT 2010–2018 Study

2020 ◽  
Vol 110 (9) ◽  
pp. 1422-1428 ◽  
Author(s):  
Nicole Larson ◽  
Melissa N. Laska ◽  
Dianne Neumark-Sztainer
Keyword(s):  
Food Insecurity ◽  
Emerging Adults ◽  
Food Availability ◽  
Diet Quality ◽  
Fast Food ◽  
Health Risk Behaviors ◽  
Food Literacy ◽  
Home Food ◽  
Home Food Availability

Objectives. To examine emerging adults’ experiences of food insecurity in relation to measures of diet quality, food literacy, home food availability, and health behaviors. Methods. We used EAT 2010–2018 (Eating and Activity over Time) study data on 1568 participants who completed surveys as adolescents in 2009 to 2010 and follow-up surveys in 2017 to 2018 (mean age = 22.0 ±2.0 years; 58% female). At baseline, participants were recruited from 20 urban schools in Minneapolis–St Paul, Minnesota. Food insecurity was defined by emerging adult report of both eating less than they thought they should and not eating when hungry because of lack of money. Results. The prevalence at follow up of experiencing food insecurity in the past year was 23.3% among emerging adults. Food insecurity was associated with poorer diet quality (e.g., less vegetables and whole grains, more sugar-sweetened drinks and added sugars), lower home availability of healthy foods, skipping breakfast, frequently eating at fast-food restaurants, binge eating, binge drinking, and substance use (all P < .01). Conclusions. Assistance programs and policies are needed to address food insecurity among emerging adults and should be coordinated with other services to protect health.

scholarly journals Unhealthy Lifestyle Associated with Higher Intake of Sugar-Sweetened Beverages among Malaysian School-Aged Adolescents

2019 ◽  
Vol 16 (15) ◽  
pp. 2785 ◽  
Author(s):  
Wan Ying Gan ◽  
Siti Fathiah Mohamed ◽  
Leh Shii Law
Keyword(s):  
Physical Activity ◽  
Sleep Quality ◽  
Food Availability ◽  
Fast Food ◽  
Negative Impact ◽  
Daily Consumption ◽  
Sugar Sweetened Beverages ◽  
Sweetened Beverages ◽  
Home Food ◽  
Home Food Availability

High consumption of sugar-sweetened beverages (SSBs) among adolescents has turned into a global concern due to its negative impact on health. This cross-sectional study determined the amount of SSB consumption among adolescents and its associated factors. A total of 421 adolescents aged 13.3 ± 1.3 years (41.8% males, 58.2% females) completed a self-administered questionnaire on sociodemographic characteristics, physical activity, screen-viewing behavior, sleep quality, frequency of eating at fast food restaurants, home food availability, peer social pressure, parenting practice, and SSB consumption. Weight and height were measured. Results showed that the mean daily consumption of SSBs among adolescents was 1038.15 ± 725.55 mL. The most commonly consumed SSB was malted drink, while the least commonly consumed SSB was instant coffee. The multiple linear regression results revealed that younger age (β = −0.204, p < 0.001), higher physical activity (β = 0.125, p = 0.022), higher screen time (β = 0.147, p = 0.007), poorer sleep quality (β = 0.228, p < 0.001), and unhealthy home food availability (β = 0.118, p = 0.032) were associated with a higher SSB intake. Therefore, promoting a healthy lifestyle may help to reduce the excessive consumption of SSBs among adolescents.

scholarly journals Selection Without Exclusion

Econometrica ◽  
2020 ◽  
Vol 88 (3) ◽  
pp. 1007-1029
Author(s):  
Bo E. Honoré ◽  
Luojia Hu
Keyword(s):  
Line Segment ◽  
Sample Selection ◽  
Selection Model ◽  
Sharp Bounds ◽  
One Dimensional ◽  
Explanatory Variables ◽  
Sample Selection Model ◽  
Full Structure ◽  
Exclusion Restrictions ◽  
Parameter Values

It is well understood that classical sample selection models are not semiparametrically identified without exclusion restrictions. Lee (2009) developed bounds for the parameters in a model that nests the semiparametric sample selection model. These bounds can be wide. In this paper, we investigate bounds that impose the full structure of a sample selection model with errors that are independent of the explanatory variables but have unknown distribution. The additional structure can significantly reduce the identified set for the parameters of interest. Specifically, we construct the identified set for the parameter vector of interest. It is a one‐dimensional line segment in the parameter space, and we demonstrate that this line segment can be short in practice. We show that the identified set is sharp when the model is correct and empty when there exist no parameter values that make the sample selection model consistent with the data. We also provide non‐sharp bounds under the assumption that the model is correct. These are easier to compute and associated with lower statistical uncertainty than the sharp bounds. Throughout the paper, we illustrate our approach by estimating a standard sample selection model for wages.

scholarly journals Parameter Choice, Stability and Validity for Robust Cluster Weighted Modeling

Stats ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 602-615
Author(s):  
Andrea Cappozzo ◽  
Luis Angel García García Escudero ◽  
Francesca Greselin ◽  
Agustín Mayo-Iscar
Keyword(s):  
Statistical Inference ◽  
Robust Estimation ◽  
Final Solution ◽  
Parameter Choice ◽  
Subjective Judgment ◽  
Explanatory Variables ◽  
Weighted Model ◽  
Cluster A ◽  
Parameter Values ◽  
Robust Cluster

Statistical inference based on the cluster weighted model often requires some subjective judgment from the modeler. Many features influence the final solution, such as the number of mixture components, the shape of the clusters in the explanatory variables, and the degree of heteroscedasticity of the errors around the regression lines. Moreover, to deal with outliers and contamination that may appear in the data, hyper-parameter values ensuring robust estimation are also needed. In principle, this freedom gives rise to a variety of “legitimate” solutions, each derived by a specific set of choices and their implications in modeling. Here we introduce a method for identifying a “set of good models” to cluster a dataset, considering the whole panorama of choices. In this way, we enable the practitioner, or the scientist who needs to cluster the data, to make an educated choice. They will be able to identify the most appropriate solutions for the purposes of their own analysis, in light of their stability and validity.

Contributions of local-area fast-food availability and area-based weight and dietary norms to 10-year change in cardiometabolic risk

2014 ◽  
Vol 8 ◽  
pp. 15
Author(s):  
Suzanne J. Carroll ◽  
Catherine Paquet ◽  
Natasha J. Howard ◽  
Neil T. Coffee ◽  
Robert Adams ◽  
...  
Keyword(s):  
Food Availability ◽  
Fast Food ◽  
Cardiometabolic Risk ◽  
Local Area

scholarly journals Neighborhood fast food availability and fast food consumption

Appetite ◽  
2015 ◽  
Vol 92 ◽  
pp. 227-232 ◽  
Author(s):  
Nathalie Oexle ◽  
Timothy L. Barnes ◽  
Christine E. Blake ◽  
Bethany A. Bell ◽  
Angela D. Liese
Keyword(s):  
Food Consumption ◽  
Food Availability ◽  
Fast Food ◽  
Fast Food Consumption

Recent Advances in Spatial Interaction Modelling: An Application to the Forecasting of Shopping Travel

1987 ◽  
Vol 19 (2) ◽  
pp. 173-186 ◽  
Author(s):  
C M Guy
Keyword(s):  
Optimal Parameter ◽  
Spatial Interaction ◽  
Specific Model ◽  
Small Sample ◽  
Explanatory Variables ◽  
Interaction Modelling ◽  
Complex Models ◽  
Decay Parameters ◽  
Parameter Values ◽  
Specific Distance

A common problem in the use of singly-constrained spatial interaction shopping models has been that of finding optimal parameter values. This problem has been exacerbated where improvements to the model have involved extra parameters to be estimated. In this paper it is shown that calibration of quite complex models can be achieved through modification of the conventional ‘gravity’ model to a generalised linear model with Poisson error structure and logarithmic link function. Data on observed trips between fifteen residential zones and eighty-three shopping destinations in Cardiff are used to test several models through application of the GLIM computing package. Models involving extra explanatory variables, origin-specific distance-decay parameters, and competing-destinations terms are all shown to offer worthwhile improvements in performance over the conventional singly-constrained model. An individual-specific model is also tested for a small sample of shoppers. Finally, some comments are made concerning the relevance of the Cardiff findings and the wider significance of these methodological advances.

Abstract P266: The Local Food Environment and Obesity: A Systematic Review

Circulation ◽  
2015 ◽  
Vol 131 (suppl_1) ◽  
Author(s):  
Laura K Cobb ◽  
Lawrence J Appel ◽  
Manuel Franco ◽  
Jessica C Jones-Smith ◽  
Cheryl A Anderson
Keyword(s):  
Food Availability ◽  
Food Environment ◽  
Fast Food ◽  
Local Food ◽  
Grocery Stores ◽  
Food Environments ◽  
Study Quality ◽  
The Us ◽  
Relationship Of ◽  
The Relationship

Introduction: Numerous studies have explored the relationship of the local food environment and obesity. However, results have been inconsistent, and existing literature reviews have not taken into account study quality or the heterogeneity of measures of the local food environment. Methods: We used systematic keyword searches in Pubmed and Scopus to identify studies conducted in the US and Canada that assessed the relationship of obesity to the local availability of supermarkets, grocery stores, convenience stores, fast food restaurants or indices combining these measures. We developed a quality metric based on study design, exposure and outcome measurement and analysis, and then assigned each study a score. Results: We identified 71 studies representing 65 cohorts. Overall, study quality was low; 60 studies were cross-sectional. The approach to measuring local food environments varied: fast food availability was measured 31 ways in 44 studies. Associations between food outlet availability and obesity were predominantly null. In adults, we saw a trend among the non-null associations toward inverse associations between supermarket availability and obesity (22 inverse, 4 direct, 67 null) and direct associations between fast food and obesity (29 direct, 6 inverse, 71 null). In children, we saw robust direct associations between fast food availability and obesity in lower income populations only (12 direct, 7 null). In adults, indices made up of multiple types of outlets had resulted in the most consistent associations with obesity (18 expected, 23 null). Limiting analyses to higher quality studies did not affect results. Conclusions: We found limited evidence for associations between the local food environment and obesity. Quality issues, however, make causal inference difficult. Absent compelling direct evidence linking local food environments to obesity, policy makers will need to rely on other types of evidence as they address the environmental changes that contribute to the steep increase in obesity in the US.

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