Stephanie T. Lanza|Brittany L. Rhoades|Mark T. Greenberg|Martha J. Cox
Modeling multiple risks during infancy to predict quality of the caregiving environment: Contributions of a person-centered approach
Pennsylvania State University|Pennsylvania State University|Pennsylvania State University|University of North Carolina at Chapel Hill
primary goal study compare several variablecentered personcentered methods modeling multiple risk factors infancy predict quality caregiving environments six months age nine risk factors related family demographics maternal psychosocial risk assessed children two months old explored understudied population children born lowincome nonurban communities pennsylvania north carolina n 1047 risk factors 1 single unpartnered parent status 2 marital status 3 mothers age first child birth 4 maternal education 5 maternal reading ability 6 poverty status 7 residential crowding 8 prenatal smoking exposure 9 maternal depression compared conclusions drawn using bivariate approach multiple regression analysis cumulative risk index latent class analysis lca risk classes derived using lca provided intuitive summary multiple risks organized within individuals compared methods five risk classes married lowrisk married lowincome cohabiting multiproblem single lowincome single lowincomeeducation lca findings illustrated association particular family configurations infants caregiving environment quality varied across race site discussion focuses value personcentered models analysis understand complexities prediction multiple risk factors