Cigarette smoking is the leading preventable cause of cancer mortality and accounts for more than 30% of all cancer deaths in the United States. Despite warnings about its adverse health effects, the prevalence of smoking is still high among US persons, especially among adolescents and young adults. Most adult smokers initiated smoking before age 18 years and developed tobacco dependence during their young adulthood. Adolescent and young adult smoking remains one of the most challenging public health issues. Smoking behaviors are highly-heritable and also influenced by environments. Although genetic and other individual risk factors of smoking have been well established, only few studies examined neighborhood effects on adolescent and young adult smoking. While gene-environment interactions on smoking have been widely evaluated, the environment has been focused typically on individual- or family-level factors. No studies have investigated the interaction between adverse neighborhood conditions and genetic risk factors on smoking. In a multilevel framework, the examination of overall geographic variation in smoking behaviors, geographic heterogeneity of genetic influences on smoking, and effect modification of neighborhood disadvantages on smoking will be able to significantly facilitate improving tobacco control and the intervention in smoking cessation. Genetic alterations combined with neighborhood deprivation could prioritize the target population of the intervention through subdividing the risk levels (risk stratification) and refining prevention choices. Therefore, using the Missouri Adolescent Female Twin Study (MOAFTS) data, we will explore the hypothesis that neighborhood environments modify the influence of genetic predispositions on cigarette smoking among adolescents and young adults.
Three specific aims will be addressed: (1) Quantify the small-area geographic variation in adolescent and young adult smoking;(2) Identify neighborhood characteristics that are associated with adolescent and young adult smoking;and (3) Prospectively assess if genetic influences on smoking outcomes vary across distinct neighborhood environments. We will develop neighborhood measures based on area-level data and link them to the MOAFTS data after gecoding the residential addresses of study subjects to prospectively assess the independent and interactive effects of neighborhood environment with genetic predispositions on adolescent and young adult smoking. This award will allow the applicant to gain advanced skills in research methodology and behavioral genetics of smoking behaviors. The findings from the proposed study will provide important support to further investigate gene-neighborhood interplay on smoking through the R01 mechanism. The training and research experience obtained during this award, in combination with the excellence and expertise of his mentoring team (Drs. Mario Schootman, Andrew Heath, Pamela Madden, and Graham Colditz), will promote applicant's transition to an independent academic researcher in smoking prevention and tobacco control.

Public Health Relevance

Cigarette smoking is the leading preventable cause of cancer incidence and mortality while the smoking prevalence remains high among adolescents and young adults in the United States. To more effectively improve smoking prevention and tobacco control, it is crucial to accurately assess the interactive effects of neighborhood environments and individual genetic predispositions on smoking behavior which is highly- heritable and influenced by environments.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Academic/Teacher Award (ATA) (K07)
Project #
1K07CA178331-01
Application #
8568297
Study Section
Subcommittee G - Education (NCI)
Program Officer
Perkins, Susan N
Project Start
2013-07-01
Project End
2018-06-30
Budget Start
2013-07-01
Budget End
2014-06-30
Support Year
1
Fiscal Year
2013
Total Cost
$132,216
Indirect Cost
$9,794
Name
Washington University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
068552207
City
Saint Louis
State
MO
Country
United States
Zip Code
63130
Waldron, Mary; Bucholz, Kathleen K; Lian, Min et al. (2017) Single Motherhood, Alcohol Dependence, and Smoking During Pregnancy: A Propensity Score Analysis. J Stud Alcohol Drugs 78:745-753
Ratnapradipa, Kendra L; Lian, Min; Jeffe, Donna B et al. (2017) Patient, Hospital, and Geographic Disparities in Laparoscopic Surgery Use Among Surveillance, Epidemiology, and End Results-Medicare Patients With Colon Cancer. Dis Colon Rectum 60:905-913
Lian, Min; Struthers, James; Liu, Ying (2016) Statistical Assessment of Neighborhood Socioeconomic Deprivation Environment in Spatial Epidemiologic Studies. Open J Stat 6:436-442
Schootman, M; Nelson, E J; Werner, K et al. (2016) Emerging technologies to measure neighborhood conditions in public health: implications for interventions and next steps. Int J Health Geogr 15:20
Lian, Min; Madden, Pamela A; Lynskey, Michael T et al. (2016) Geographic Variation in Maternal Smoking during Pregnancy in the Missouri Adolescent Female Twin Study (MOAFTS). PLoS One 11:e0153930
Madubata, Chinwe C; Liu, Ying; Goodman, Melody S et al. (2016) Comparing treatment and outcomes of ductal carcinoma in situ among women in Missouri by race. Breast Cancer Res Treat 160:563-572
Heath, Andrew C; Lessov-Schlaggar, Christina N; Lian, Min et al. (2016) Research on Gene-Environment Interplay in the Era of ""Big Data"". J Stud Alcohol Drugs 77:681-3
Liu, Ying; Schloemann, Derek T; Lian, Min et al. (2015) Accelerated partial breast irradiation through brachytherapy for ductal carcinoma in situ: factors influencing utilization and risks of second breast tumors. Breast Cancer Res Treat 151:199-208
Lian, Min (2015) Statistical Significance of Geographic Heterogeneity Measures In Spatial Epidemiologic Studies. Open J Stat 5:46-50
Lian, Min; PĂ©rez, Maria; Liu, Ying et al. (2014) Neighborhood socioeconomic deprivation, tumor subtypes, and causes of death after non-metastatic invasive breast cancer diagnosis: a multilevel competing-risk analysis. Breast Cancer Res Treat 147:661-70