Skip to main content
. Author manuscript; available in PMC: 2023 Jul 1.
Published in final edited form as: Am J Prev Med. 2022 Jul;63(1 Suppl 1):S18–S27. doi: 10.1016/j.amepre.2022.02.013

Table 3.

ORs From Logistic Regression Models Predicting Obesity, 1996 to 2016 (N=8,059; Observations=36,122)

Variable Models
1 2 3 4 5 6 7 8 9 10 11 12 13
Net worth shock 0.97 (0.04) 0.96 (0.04)
Savings shock 1.00 (0.03) 1.00 (0.04)
Housing shock 0.94 (0.05) 0.94 (0.05)
Property shock 0.95 (0.04) 0.95 (0.04)
Indebted 1.05 (0.05) 1.05 (0.05)
Housing debt 1.00 (0.13) 0.97 (0.13)
Property debt 1.33*** (0.09) 1.29*** (0.08)
Unsecured debt 1.21*** (0.04) 1.20*** (0.04)
Bankruptcy 1.43*** (0.11) 1.43*** (0.11)
Chapter 7 1.44*** (0.15) 1.44*** (0.15)
Chapter 13 1.40** (0.17) 1.41** (0.17)
Model fit
 AIC 33,188 33,188 33,187 33,186 33,187 33,188 33,168 33,146 33,167 33,175 33,180 33,169 33,119
 AIC0 – AICM −2 −2 −1 0 −1 −2 19 40 20 11 6 18 67

Notes: Boldface indicates statistical significance (*p<0.05; **p<0.01; ***p<0.001 [2-tailed tests]). Robust SEs are in parentheses. Every model included lagged obesity, age, age squared, and the socioeconomic and demographic controls listed in Table 1. AIC0 – AICM denotes the differences between a model that excludes all financial stressors (AIC0) and models with a single financial stressor included (AICM).