Analysing behavioural risk factor surveillance data by using spatially and temporally varying coefficient models

2015 ◽  
Vol 179 (1) ◽  
pp. 153-175 ◽  
Author(s):  
Shireen Assaf ◽  
Stefano Campostrini ◽  
Fang Xu ◽  
Carol Gotway Crawford
Keyword(s):  
Risk Factor ◽  
Surveillance Data ◽  
Varying Coefficient Models ◽  
Behavioural Risk Factor ◽  
Varying Coefficient ◽  
Risk Factor Surveillance

Population-based birth-defect and risk-factor surveillance: data from the Northern Netherlands

1996 ◽  
Vol 8 (3) ◽  
pp. 197-209 ◽  
Author(s):  
Martina C. Cornel ◽  
J. David Erickson ◽  
Muin J. Khoury ◽  
Levy M. James ◽  
Yecai Liu
Keyword(s):  
Risk Factor ◽  
Birth Defect ◽  
Population Based ◽  
Surveillance Data ◽  
Risk Factor Surveillance

Parsimonious Prediction Model for the Prevalence of Dental Visits in Chennai, India

2014 ◽  
Vol 8 (2) ◽  
pp. 86-90
Author(s):  
D Prabu ◽  
M Shylaja ◽  
RU Vidhya ◽  
S Manipal ◽  
A Ahmed ◽  
...  
Keyword(s):  
Risk Factor ◽  
Local Governments ◽  
Surveillance System ◽  
Tamil Nadu ◽  
Insurance Companies ◽  
Behavioural Risk Factor ◽  
Multivariable Logistic Regression Model ◽  
Cross Sectional ◽  
Dental Visits ◽  
Risk Factor Surveillance

ABSTRACT OBJECTIVE The aim of the study is to analyze the prevalence of dental visits within the last year in the Behavioural Risk Factor Surveillance System or BRFSS by the simple sociodemographic factors among the adults in 10 different areas of Chennai, Tamil Nadu. METHODS Cross sectional telephone survey (Behavioural Risk Factor Surveillance System) conducted among 500 adults. Data was collected based on a standardized questionnaire to determine the distribution of risk behaviours and health practices among non-institutionalized adults. A multivariable logistic regression model considers the complex sample design of the BRFSS was used to predict the prevalence of dental visits based on four non-clinic parsimonious variables. RESULTS Results showed that the adults with the High household income, Religion (Hindu), High Education(> High School Diploma), and marital status were associated with an annual dental visit with the odd ratios of 0.943, 1.161, 1.243, 0.876 respectively. Besant Nagar had the highest percentage (13%) of estimated annual users, while Redhills had the lowest percentage(8%). CONCLUSION Health promotion organizations, Local governments, Insurance companies, and organizations that administer public health programs will benefit by applying this model to the available nonclinical databases, and will be able to improve planning of dental health services and required dental workforce.

Mode of physical activity participation by body mass index: 2015 behavioural risk factor surveillance system

2018 ◽  
Vol 26 (2) ◽  
pp. 147-157 ◽  
Author(s):  
James R Churilla ◽  
Tammie M Johnson ◽  
M. Ryan Richardson ◽  
Bethany D Williams ◽  
Brandi S Rariden ◽  
...  
Keyword(s):  
Physical Activity ◽  
Body Mass Index ◽  
Risk Factor ◽  
Body Mass ◽  
Surveillance System ◽  
Physical Activity Participation ◽  
Activity Participation ◽  
Behavioural Risk Factor ◽  
Risk Factor Surveillance
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