A Population-Based Survey in Australia of Men’s and Women’s Perceptions of Genetic Risk and Predictive Genetic Testing and Implications for Primary Care

2011 ◽  
Vol 14 (6) ◽  
pp. 325-336 ◽  
Author(s):  
S. Taylor
Keyword(s):  
Primary Care ◽  
Genetic Testing ◽  
Genetic Risk ◽  
Population Based ◽  
Predictive Genetic Testing ◽  
Women’S Perceptions ◽  
Population Based Survey

scholarly journals Access to primary care and other health care use among western Canadians with chronic conditions: a population-based survey

CMAJ Open ◽  
2014 ◽  
Vol 2 (1) ◽  
pp. E27-E34 ◽  
Author(s):  
R. G. Weaver ◽  
B. J. Manns ◽  
M. Tonelli ◽  
C. Sanmartin ◽  
D. J. T. Campbell ◽  
...  
Keyword(s):  
Primary Care ◽  
Health Care ◽  
Chronic Conditions ◽  
Population Based ◽  
Health Care Use ◽  
Access To Primary Care ◽  
Population Based Survey

scholarly journals Design of a study to implement population-based risk assessment for hereditary cancer genetic testing in primary care

2020 ◽  
pp. 106257
Author(s):  
Deborah J. Bowen ◽  
Catharine Wang ◽  
Allison M. Cole ◽  
Barbara M. Norquist ◽  
Sarah Knerr ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Primary Care ◽  
Genetic Testing ◽  
Hereditary Cancer ◽  
Population Based ◽  
Cancer Genetic

Knowledge, Attitudes, and Practice Regarding Genetic Testing and Genetic Counselors in Jordan: A Population-Based Survey

2015 ◽  
Vol 24 (6) ◽  
pp. 1001-1010 ◽  
Author(s):  
Mamoun Ahram ◽  
Majd Soubani ◽  
Lana Abu Salem ◽  
Haneen Saker ◽  
Muayyad Ahmad
Keyword(s):  
Genetic Testing ◽  
Population Based ◽  
Genetic Counselors ◽  
Population Based Survey

scholarly journals Towards improving primary care: Considerations on a Sicilian population-based survey

2019 ◽  
Vol 8 (11) ◽  
pp. 3647 ◽  
Author(s):  
RoccoSalvatore Calabrò ◽  
Alfredo Manuli ◽  
MariaGrazia Maggio ◽  
Mariacristina De Cola ◽  
Daniele Tripoli ◽  
...  
Keyword(s):  
Primary Care ◽  
Population Based ◽  
Sicilian Population ◽  
Population Based Survey

Lipid metabolism genetic risk score interacts with the Brazilian Healthy Eating Index Revised and its components to influence the odds for dyslipidemia in a cross-sectional population-based survey in Brazil

2019 ◽  
Vol 25 (2) ◽  
pp. 119-126 ◽  
Author(s):  
Tatiane Mieko de Meneses Fujii ◽  
Marina Maintinguer Norde ◽  
Regina Mara Fisberg ◽  
Dirce Maria Lobo Marchioni ◽  
Marcelo Macedo Rogero
Keyword(s):  
Lipid Metabolism ◽  
Risk Score ◽  
Healthy Eating ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Population Based ◽  
Healthy Eating Index ◽  
Cross Sectional ◽  
The Relationship ◽  
Population Based Survey

Background: Dyslipidemia can be influenced by genetic and dietary risk factors. Aim: This study set out to investigate diet and genetic variations in Brazilian people in a cross-sectional population-based survey and to analyze the relationship between single nucleotide polymorphisms (SNPs) of genes involved in lipid metabolism and cardiometabolic-related phenotypes using a genetic risk score (GRS). Methods: We recruited 228 adults (mean age 36.5 years) who participated in the Health Survey of São Paulo (HS-SP), Brazil. Clinical and anthropometric parameters, as well as the interaction between the GRS and the Brazilian Healthy Eating Index Revised (BHEI-R) were evaluated. We analyzed the relationship between SNPs in APOA5 (rs662799), APOB (rs693, rs1367117), LDLR (rs688, rs5925) and LIPC (rs2070895, rs1800588) and cardiometabolic-related phenotypes using a GRS. Results: High-density lipoprotein cholesterol (HDLC) levels were associated with the BHEI-R ( p=0.026; β= −0.183) and with its SoFAAS component (solid fats, alcoholic beverages and added sugars) ( p=0.007; β=0.279). Non-HDL cholesterol levels were associated with the BHEI-R vegetable component ( p=0.015; β=0.002) and the meat, eggs and beans component ( p=0.003; β=0.007). Triacylglycerol levels were associated with the BHEI-R vegetable component ( p=0.027; β=0.003); the meat, eggs and beans component ( p=0.041; β=0.001); and the total protein component ( p=0.013; β=0.032). Significant effects were observed for the interactions between the GRS and both the BHEI-R oils component ( p=0.019) and the SoFAAS component ( p<0.001) on the dyslipidemia risk. Conclusions: The evaluation of dietary quality, especially fat quality, together with the lipid metabolism GRS could be a useful tool to manage cardiometabolic risk.

Sign in / Sign up

Export Citation Format

Share Document