Association between early maternal depression and child growth: A group-based trajectory modeling analysis

Pineros Leano, Maria Fernanda

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https://hdl.handle.net/2142/101332 Copy

Description

Title

Association between early maternal depression and child growth: A group-based trajectory modeling analysis

Author(s)

Pineros Leano, Maria Fernanda

Issue Date

2018-04-17

Director of Research (if dissertation) or Advisor (if thesis)

Liechty, Janet M.

Doctoral Committee Chair(s)

Liechty, Janet M.

Committee Member(s)

• Tabb-Dina, Karen
• Donovan, Sharon
• Musaad , Salma

Department of Study

School of Social Work

Discipline

Social Work

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• Childhood obesity
• Maternal depression
• Group-Based Trajectory Modeling Analysis

Abstract

Childhood overweight and obesity have become a primary social and public health concern. Over the past 30 years, rates of childhood overweight and obesity in the United States have increased dramatically from 6% to 32%. Childhood obesity is also a health equity issue: overweight and obesity disproportionately affect more low-income and minority children than White and middle class children. A potential risk factor of interest is maternal depression. To date, there are mixed findings available on the association between maternal depression and childhood obesity development. To address these gaps in the literature, this study used innovative statistical techniques to explore: 1) The association between maternal depression at age 1 and/or age 3 and childhood obesity longitudinally; 2) The association between child-level factors (sleep, television viewing, outdoor play, and dietary intake) and at-risk growth trajectories from birth to age 9; 3) The association between clan-level factors (maternal involvement and breastfeeding duration) and at-risk growth trajectories from birth to age 9; 4) Differences in growth trajectory solutions by race/ethnicity; and 5) Common and unique risk factors that predict at-risk growth among children from different racial/ethnic groups. This study used data from the Fragile Families Child Well Being Study (FFCWS) to investigate the research questions. FFCWS is a national dataset that has information on 4,898 women from predominantly non-marital, low-income, minority groups in the United States. This study used information collected at the birth of the child (wave 1) through age 9 (wave 5). The analytic sample consisted of 3,500 mother-children dyads. Group-based trajectory modeling, general linear models, and multivariable logistic regression were used to test the different research questions in the full sample and the stratified sample by race/ethnicity. The results indicated that there was no association between maternal depression and childhood obesity development in this sample of low-income and mostly minority participants. Only maternal pre-pregnancy BMI and number of biological children were significant predictors of at-risk growth trajectories in the full sample. It was also found that there group-trajectory solutions were different based on race/ethnicity. Specifically, a three-group trajectory solution was found for the full sample and for the sample of White children. Among the samples of Black and Latino children, a two-group trajectory solution was found. The most worrisome results were found among Latino children who showed a rapid BMI z-score increase from birth until age 5, which placed them at an increased risk of overweight/obesity during early childhood. Also, child-level and clan-level factors were found to be associated differently with at-risk group membership by race/ethnicity. Suggestions for designing childhood obesity prevention interventions based on research are discussed. Implications for theory, policy, and future research are identified.

Graduation Semester

2018-05

Type of Resource

text

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http://hdl.handle.net/2142/101332

Copyright and License Information

Copyright 2018 Maria Fernanda Piñeros Leaño

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