The New Jersey Childhood Obesity Study was designed to provide vital information for planning, implementing, and evaluating interventions aimed at preventing childhood obesity in five New Jersey municipalities: Camden, Newark, New Brunswick, Trenton, and Vineland. These five communities are being supported by the Robert Wood Johnson Foundation’s New Jersey Partnership for Healthy Kids program to plan and implement policy and environmental change strategies to prevent childhood obesity. Effective interventions for addressing childhood obesity require community-specific information on

who is most at risk and on contributing factors that can be addressed through tailored interventions that meet the needs of the community. Based on comprehensive research, a series of reports are being prepared for each community to assist in planning effective interventions.

The main components of the study were:

• A household telephone survey of 1700 families with 3–18 year old children,

• De-identified heights and weights measured at public schools,

• Assessment of the food and physical activity environments using objective data.

This report presents the results from the household survey. Reports based on school body mass index (BMI) data and food and physical activity environment data are available at www.cshp.rutgers.edu/childhoodobesity.htm.

The New Jersey Childhood Obesity Study was designed to provide vital information for planning, implementing, and evaluating interventions aimed at preventing childhood obesity in five New Jersey municipalities: Camden, Newark, New Brunswick, Trenton, and Vineland. These five communities are being supported by the Robert Wood Johnson Foundation’s New Jersey Partnership for Healthy Kids program to plan and implement policy and environmental change strategies to prevent childhood obesity. Effective interventions for addressing childhood obesity require community-specific information on

who is most at risk and on contributing factors that can be addressed through tailored interventions that meet the needs of the community. Based on comprehensive research, a series of reports are being prepared for each community to assist in planning effective interventions.

The main components of the study were:

• A household telephone survey of 1700 families with 3–18 year old children,

• De-identified heights and weights measured at public schools,

• Assessment of the food and physical activity environments using objective data.

This report presents the results from the household survey. Reports based on school body mass index (BMI) data and food and physical activity environment data are available at www.cshp.rutgers.edu/childhoodobesity.htm.

The New Jersey Childhood Obesity Study was designed to provide vital information for planning, implementing, and evaluating interventions aimed at preventing childhood obesity in five New Jersey municipalities: Camden, Newark, New Brunswick, Trenton, and Vineland. These five communities are being supported by the Robert Wood Johnson Foundation’s New Jersey Partnership for Healthy Kids program to plan and implement policy and environmental change strategies to prevent childhood obesity. Effective interventions for addressing childhood obesity require community-specific information on

who is most at risk and on contributing factors that can be addressed through tailored interventions that meet the needs of the community. Based on comprehensive research, a series of reports are being prepared for each community to assist in planning effective interventions.

The main components of the study were:

• A household telephone survey of 1700 families with 3–18 year old children,

• De-identified heights and weights measured at public schools,

• Assessment of the food and physical activity environments using objective data.

This report presents the results from the household survey. Reports based on school body mass index (BMI) data and food and physical activity environment data are available at www.cshp.rutgers.edu/childhoodobesity.htm.

The New Jersey Childhood Obesity Study was designed to provide vital information for planning, implementing, and evaluating interventions aimed at preventing childhood obesity in five New Jersey municipalities: Camden, Newark, New Brunswick, Trenton, and Vineland. These five communities are being supported by the Robert Wood Johnson Foundation’s New Jersey Partnership for Healthy Kids program to plan and implement policy and environmental change strategies to prevent childhood obesity. Effective interventions for addressing childhood obesity require community-specific information on

who is most at risk and on contributing factors that can be addressed through tailored interventions that meet the needs of the community. Based on comprehensive research, a series of reports are being prepared for each community to assist in planning effective interventions.

The main components of the study were:

• A household telephone survey of 1700 families with 3–18 year old children,

• De-identified heights and weights measured at public schools,

• Assessment of the food and physical activity environments using objective data.

This report presents the results from the household survey. Reports based on school body mass index (BMI) data and food and physical activity environment data are available at www.cshp.rutgers.edu/childhoodobesity.htm.

The New Jersey Childhood Obesity Study was designed to provide vital information for planning, implementing, and evaluating interventions aimed at preventing childhood obesity in five New Jersey municipalities: Camden, Newark, New Brunswick, Trenton, and Vineland. These five communities are being supported by the Robert Wood Johnson Foundation’s New Jersey Partnership for Healthy Kids program to plan and implement policy and environmental change strategies to prevent childhood obesity. Effective interventions for addressing childhood obesity require community-specific information on

who is most at risk and on contributing factors that can be addressed through tailored interventions that meet the needs of the community. Based on comprehensive research, a series of reports are being prepared for each community to assist in planning effective interventions.

The main components of the study were:

• A household telephone survey of 1700 families with 3–18 year old children,

• De-identified heights and weights measured at public schools,

• Assessment of the food and physical activity environments using objective data.

This report presents the results from the household survey. Reports based on school body mass index (BMI) data and food and physical activity environment data are available at www.cshp.rutgers.edu/childhoodobesity.htm.

Background:
Many pharmaceutical drugs are known to be ineffective or have negative side effects in a substantial proportion of patients. Genomic advances are revealing that some non-synonymous single nucleotide variants (nsSNVs) may cause differences in drug efficacy and side effects. Therefore, it is desirable to evaluate nsSNVs of interest in their ability to modulate the drug response.

Results:
We found that the available data on the link between drug response and nsSNV is rather modest. There were only 31 distinct drug response-altering (DR-altering) and 43 distinct drug response-neutral (DR-neutral) nsSNVs in the whole Pharmacogenomics Knowledge Base (PharmGKB). However, even with this modest dataset, it was clear that existing bioinformatics tools have difficulties in correctly predicting the known DR-altering and DR-neutral nsSNVs. They exhibited an overall accuracy of less than 50%, which was not better than random diagnosis. We found that the underlying problem is the markedly different evolutionary properties between positions harboring nsSNVs linked to drug responses and those observed for inherited diseases. To solve this problem, we developed a new diagnosis method, Drug-EvoD, which was trained on the evolutionary properties of nsSNVs associated with drug responses in a sparse learning framework. Drug-EvoD achieves a TPR of 84% and a TNR of 53%, with a balanced accuracy of 69%, which improves upon other methods significantly.

Conclusions:
The new tool will enable researchers to computationally identify nsSNVs that may affect drug responses. However, much larger training and testing datasets are needed to develop more reliable and accurate tools.