Modeling multiple risks during infancy to predict quality of the caregiving environment: Contributions of a person-centered approach

https://doi.org/10.1016/j.infbeh.2011.02.002Get rights and content

Abstract

The primary goal of this study was to compare several variable-centered and person-centered methods for modeling multiple risk factors during infancy to predict the quality of caregiving environments at six months of age. Nine risk factors related to family demographics and maternal psychosocial risk, assessed when children were two months old, were explored in the understudied population of children born in low-income, non-urban communities in Pennsylvania and North Carolina (N = 1047). These risk factors were (1) single (unpartnered) parent status, (2) marital status, (3) mother's age at first child birth, (4) maternal education, (5) maternal reading ability, (6) poverty status, (7) residential crowding, (8) prenatal smoking exposure, and (9) maternal depression. We compared conclusions drawn using a bivariate approach, multiple regression analysis, the cumulative risk index, and latent class analysis (LCA). The risk classes derived using LCA provided a more intuitive summary of how multiple risks were organized within individuals as compared to the other methods. The five risk classes were: married low-risk; married low-income; cohabiting multiproblem; single low-income; and single low-income/education. The LCA findings illustrated how the association between particular family configurations and the infants’ caregiving environment quality varied across race and site. Discussion focuses on the value of person-centered models of analysis to understand complexities of prediction of multiple risk factors.

Highlights

► Nine risk factors for poor quality caregiving environment explored using four methods. ► Compared bivariate approach, regression, cumulative risk, latent class analysis. ► Five risk classes identified, from married low-risk to single low-income/education. ► Latent class analysis provided more intuitive and useful summary of multiple risks.

Section snippets

Modeling multiple risks during infancy: contributions of a person-centered approach

The identification of risk factors for early cognitive and behavioral development is important because a risk-focused approach provides a framework for understanding etiology as well as targeting at-risk individuals in order to improve developmental outcomes (Catalano and Hawkins, 1996, Hawkins et al., 1992). Historically, different methods have been used to model risk, each providing a somewhat different framework for understanding the risks associated with children's outcomes. However, most

Procedure

The Family Life Project (FLP) is a community-based study of developmental processes and outcomes in non-urban families. The study population is drawn from Eastern North Carolina (the counties of Sampson, Wayne and Wilson) and Central Pennsylvania (the counties of Blair, Cambria and Huntington). These two regions were chosen because they represent two of four major non-urban geographic areas of the US with high poverty rates (Dill, 1999). Specifically, the counties in North Carolina and

Bivariate analysis of risk factors

Table 2 displays the bivariate relations between the total HOME score and the individual risk factors, site-ethnicity group, and the risk factor by site-ethnicity group interaction. Each risk factor was a significant negative predictor of HOME scores. The amount of risk associated with each of the first seven risk factors was significant (p < .0001 for each), although the interaction term for each of these risk factors with site-ethnicity was not significant, indicating that risk did not vary

Discussion

Risk-focused research can inform our understanding regarding selection of risk subgroups to be targeted for use of limited prevention funds. This study provides a unique opportunity to compare and contrast different methodologies. Interestingly, the percent of variance in the quality of caregiving environment was nearly identical across all multivariate methods (multiple regression, cumulative risk index, and LCA), ranging from approximately 32–35%. Thus, the methods are essentially equivalent

Conclusions

Despite these limitations, a person-centered framework provides unique insight into common profiles of risk in the population under study. The identification of key subgroups of family configurations which place children at highest risk, as opposed to key individual risk factors, provides a more holistic understanding of the ways in which multiple risks converge within individuals’ lives and together predict an adverse outcome. The LCA approach revealed the importance of both the quantity of

Acknowledgements

Data collection for The Family Life Project was funded by NIH/NICHD Grant Number P01HD39667 with co-funding from NIDA. This research was supported by NIDA Grant Numbers R03DA023032 and P50DA010075. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute on Drug Abuse or the National Institutes of Health. We would like to thank Mildred Maldonado-Molina, Michael Cleveland and Bethany Bray for providing feedback on an

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