. Author manuscript; available in PMC: 2021 Jun 1.

Published in final edited form as: Pediatr Nephrol. 2020 Jan 29;35(6):1085–1096. doi: 10.1007/s00467-020-04470-1

Table 3.

Multivariate modeling by sequential addition of potential confounders

	Race + chronic	Race + chronic + age + urban	Race + chronic + age + urban + insurance + gender
Health insurance
Medicaid	Reference	Reference	Reference
No insurance	14.4 (12.7, 16.2)^****	12.9 (11.3, 14.6)^****	11.8 (10.2, 13.4)^****
Private insurance	3.4 (2.8, 4.0)^****	3.4 (2.9, 4.0)^****	2.8 (2.3, 3.4)^****
Other	6.7 (4.8, 8.5)^****	6.4 (4.5, 8.3)^****	5.7 (3.8, 7.6)^****
Gender
Female	–	Reference	Reference
Male	–	7.3 (6.7, 7.9)^****	6.8 (6.2, 7.4)^****
Race/ethnicity
Caucasian	–	–	Reference
African-American	–	–	2.5 (1.7, 3.3)^****
Hispanic	–	–	1.7 (0.9, 2.5)^****
Asian/Pacific Islander	–	–	4.5 (2.9, 6.0)^****
Native American	–	–	0.7 (− 2.1, 3.5)
Other	–	–	1.4 (0.3, 2.5)^*

Risk differences per 1000 hospitalizations presented with 95% confidence intervals in parentheses

Race=race/ethnicity; Chronic=chronic illnesses; Age=age in years; Urban=household urbanization

Italics indicates ideal set of confounders to evaluate according to DAG depicted in Fig. 1. Additional confounders are shown for comparison but may potentially introduce additional bias

p-value < 0.05; **< 0.01; ***< 0.001; ****< 0.0001