Using the Moving to Opportunity Experiment to Investigate the Long-Term Impact of Neighborhoods on Healthcare Use by Specific Clinical Conditions and Type of Service

Figures & data

Table 1. Baseline characteristics of the matched MTO study population.^a

	Adult sample (Age ≥18 at randomization)		Child sample (Age <18 at randomization)
	Voucher groups N = 2,849	Control group N = 1,293	Voucher groups N = 6,287	Control group N = 2,882
Age—median (Q1, Q3)^b	32 (27, 38)	32 (26, 38)	8 (4, 12)	7 (4, 11)
Race—no. (%)^c
Black	1789/2800 (64)	821/1266 (65)	4067/6148 (66)	1797/2796 (64)
White	208/2800 (7)	103/1266 (8)	391/6148 (6)	207/2796 (7)
Other	803/2800 (29)	342/1266 (27)	1690/6148 (27)	792/2796 (28)
Hispanic ethnicity—no. (%)^c	890/2800 (32)	397/1293 (31)	1875/6148 (30)	935 (33)
Sex—no. (%)
Female^d	2793 (98)	1255 (97)	3132 (50)	1415 (49)
Male	56 (2)	38 (3)	3155 (50)	1467 (51)
Study site—no. (%)
Baltimore, MD	355 (12)	156 (12)	895 (14)	394 (14)
Boston, MA	607 (21)	309 (24)	1197 (19)	661 (23)
Chicago, IL	543 (19)	192 (15)	1440 (23)	462 (16)
Los Angeles, CA	571 (20)	345 (27)	1325 (21)	775 (27)
New York, NY	773 (27)	291 (23)	1430 (23)	590 (20)
Never married—no. (%)	1729 (63)	801 (64)
Age <18 at first childbirth	700 (26)	302 (25)
Employed^e	705 (26)	309 (25)
Enrolled in school^e	461 (17)	204 (16)
High school diploma^e	1065 (37)	468 (36)
GED certificate^e	210 (18)	238 (18)
Neighborhood poverty years 1–3 —mean (SD)^f	37 (15)	47 (13)	37 (15)	47 (14)
Years of all-payer/Medicaid hospitalization. data —median (Q1, Q3)^g	13 (11, 18)	14 (11, 18)	13 (11, 18)	14 (11, 18)
Years of all-payer/Medicaid Emergency department data —median (Q1, Q3)^h	11 (1, 16)	11 (0, 16)	13 (3, 17)	13 (2, 17)
Years of Medicaid data (hospitalization, ED, and outpatient) —median (Q1, Q3)	7 (3, 11)	6 (3, 11)	9 (5, 13)	9 (5, 13)

Note. ^aNumbers are unweighted data. Percentages were calculated with sample weights accounting for changes in random-assignment ratios across randomized study groups and for subsample interviews. Percentages include imputed values. Omnibus chi-square tests failed to reject the null hypothesis that baseline characteristics are the same between study groups (P = .73 for adults, P = .11 for children).

^bImputed age at randomization in whole years.

^cRace categories do not sum to the total number because of missing data. The other race category includes American Indians, Asian/Pacific Islanders, and other races. A Hispanic person could be a member of any race.

^dThis reflects the high proportion of female-headed households and preferential selection of female respondents in other households.

^eEmployment and current education status at baseline were self-reported by each adult head of household in the year of randomization. Being employed is defined as working either full-time or part-time for pay.

^fThis measure is based on the proportion of households in a census tract with total family income below the federal poverty line, weighted by the amount of time a participant lived in each census tract.

^gFor the all-payer hospitalization samples from California, New York, and Massachusetts, this is the number of years potentially in the data, incorporating deaths. For the Medicaid hospitalization samples from Illinois and Maryland, this is the number of years actually enrolled in Medicaid. For the 56,462 adult person-years in the hospitalization analyses, 46,159 (82%) were from the all-payer data and 10,303 (18%) were from the Medicaid data. Of the person-years of adult Medicaid data, 7,450 (72%) were full-year enrollment and 5,182 (50%) were managed care. For the 127,300 person-years of hospitalization data for children at the time of randomization, 96,510 (76%) were from the all-payer hospitalization data and 30,790 (24%) were from the Medicaid data. Of the person-years of children Medicaid hospitalization data, 23,897 (78%) were full-year enrollment and 18,043 (59%) were managed care.

^hFor the all-payer ED samples from California, New York, and Massachusetts, this is the number of years potentially in the data, incorporating deaths. For the Medicaid ED samples from Illinois and Maryland, this is the number of years actually enrolled in Medicaid. For the 39,981 adult person-years in the ED analyses, 23,287 (58%) were from the all-payer data and 16,694 (42%) were from the Medicaid data. Of the person-years of adult Medicaid data, 12,438 (31%) were full-year enrollment and 33,094 (83%) were managed care. For the 95,469 person-years of ED data for children at the time of randomization, 49,028 (51%) were from the all-payer ED data and 46,441(49%) were from the Medicaid ED data. Of the person-years of children Medicaid ED data, 36,362 (38%) were full-year enrollment and 78,814 (83%) were managed care.

Figure 1. Inpatient hospitalizations and ED visits based on primary diagnosis among voucher groups versus control group.

Note. Mean hospitalizations and emergency department (ED) visits represent counts per 100 person-years and were estimated from intercept-only negative binomial regression models, with an offset term for the total months of available data for a person-year and survey sample weights to account for varying sample probabilities over the accrual period. Incidence rate ratios are expressed as the voucher groups relative to the control group and were derived from negative binomial regression models for the count of hospitalizations or ED visits with the person-year as the unit of observation and adjustments made for the set of covariates described in the text. The models included survey sample weights to account for varying sampling probabilities over the accrual period and accounted for the family unit by clustering all standard errors by family. The size of each square point is proportional to the number of person-years of data available. Diabetes, obesity, and hypertension are not included for children because of their low prevalence.

*Adjusted p values represent the lowest false discovery rate threshold at which the test could be considered significant, using the Benjamini–Hochberg procedure to keep the false discovery rate to less than 1 out of 8, corresponding to the number of comparisons per group of analyses for adults, and 1 out of 5, corresponding to the number of comparisons per group of analyses for children; an adjusted p value is statistically significant if < .125 for adults and if < .20 for children

Figure 2. Type of service utilization among voucher groups versus control groups.

Note. Mean types of service utilization represent counts per 100 person-years and were estimated from intercept-only negative binomial regression models with an offset term for the total months of available data for a person-year and survey sample weights to account for varying sample probabilities over the accrual period. Incidence rate ratios are expressed as the voucher groups relative to the control group and were derived from negative binomial regression models, with an offset term indicating the total months of available data for the person and adjustments made for the set of covariates described in the text. The models included survey sample weights to account for varying sampling probabilities over the accrual period and accounted for the family unit by clustering all standard errors by family. The size of each square point is proportional to the number of person-years of data available.

*Adjusted p values represent the lowest false discovery rate threshold at which the test could be considered significant, using the Benjamini–Hochberg procedure to control the false discovery rate to less than 1 of 11, corresponding to the number of comparisons per group of analyses; an adjusted p value is statistically significant if <.09

Table 2. Housing/neighborhood-sensitive hospitalizations and emergency department (ED) visits based on all diagnostic codes among voucher groups vs. control group^a: adults and children

	Voucher mean^b	Control mean^b	Incidence rate ratio^c (95% CI)	p value	Adjusted p value^d
Adult hospitalizations^e
All-cause visits^f	14.63	15.17	0.96 [0.85, 1.09]	.53	.79
Asthma	2.90	2.75	1.06 [0.81, 1.39]	.66	.79
Respiratory illness	1.85	1.61	1.08 [0.80, 1.46]	.61	.79
Injury	0.65	0.66	0.98 [0.75, 1.29]	.90	.90
Mental health	2.76	2.94	0.93 [0.66, 1.31]	.69	.79
Diabetes	3.61	4.24	0.79 [0.58, 1.08]	.14	.79
Obesity	1.87	2.06	0.91 [0.71, 1.16]	.44	.79
Hypertension	5.96	6.36	0.94 [0.77, 1.16]	.57	.79
Adult ED visits^e
All-cause visits^f	58.02	61.12	0.95 [0.87, 1.05]	.34	.45
Asthma	3.03	2.95	1.02 [0.76, 1.37]	.90	.90
Respiratory illness	4.10	4.48	0.89 [0.74, 1.07]	.21	.34
Injury	5.62	6.55	0.86 [0.76, 0.98]	.02	.05
Mental health	2.36	2.47	0.88 [0.57, 1.38]	.59	.67
Diabetes	3.45	4.98	0.60 [0.43, 0.84]	.003	.02
Obesity	0.36	0.63	0.57 [0.37, 0.87]	.01	.04
Hypertension	5.77	6.84	0.86 [0.71, 1.03]	.10	.20
Child hospitalizations^e,g
All-cause visits^f	6.73	7.82	0.84 [0.73, 0.97]	.02	.12
Asthma	0.94	1.38	0.74 [0.54, 1.01]	.06	.16
Respiratory illness	0.32	0.39	0.83 [0.59, 1.17]	.29	.39
Injury	0.53	0.57	0.96 [0.76, 1.20]	.70	.73
Mental health	0.74	1.02	0.75 [0.58, 0.97]	.03	.12
Diabetes	0.22	0.24	0.91 [0.53, 1.56]	.73	.73
Obesity	0.39	0.48	0.79 [0.60, 1.04]	.10	.20
Hypertension	0.21	0.27	0.73 [0.48, 1.11]	.14	.22
Child ED visits^e,g
All-cause visits^f	40.12	41.14	0.97 [0.90, 1.04]	.36	.87
Asthma	2.19	1.97	1.07 [0.84, 1.36]	.56	.87
Respiratory illness	3.08	3.02	1.01 [0.88, 1.16]	.87	.87
Injury	6.36	6.77	0.95 [0.87, 1.05]	.31	.87
Mental health	2.95	2.74	1.12 [0.84, 1.50]	.43	.87
Diabetes	0.28	0.26	0.89 [0.49, 1.60]	.69	.87
Obesity	0.20	0.22	0.94 [0.63, 1.42]	.78	.87
Hypertension	0.38	0.41	0.87 [0.57, 1.32]	.52	.87

Note. ^aAny diagnosis includes at least one corresponding ICD-9 or ICD-10 diagnosis code associated with the hospitalization or ED visit. This included up to 25 possible codes for the all-payer claims, up to 9 possible codes for the Medicaid hospitalization claims, and 2 possible codes for the Medicaid ED claims.

^bHospitalizations and ED visits are per 100 person-years. Means were estimated from intercept-only negative binomial regression models, with an offset term for the total months of available data for a person-year and survey sample weights to account for varying sample probabilities over the accrual period.

^cThese estimates compared the outcomes for everyone assigned to the voucher groups with the outcomes for everyone assigned to the control group, with adjustments made for the set of baseline covariates as described in the text. Incidence rate ratios were estimated from negative binomial models with an offset term indicating the total months of available data for the person. The models included survey sample weights to account for varying sampling probabilities over the accrual period and accounted for the family unit by clustering all standard errors by family.

^dAdjusted p values represent the lowest false discovery rate threshold at which the test could be considered significant, using the Benjamini–Hochberg procedure to control the false discovery rate to less than 1 out of 8, corresponding to the number of comparisons per group of analyses; an adjusted p value is statistically significant if <.125.

^eAdult age ≥18 at randomization; children <18 at randomization.

^fAll-cause visits refer to hospitalizations or ED visits for all diagnoses, including but not limited to the specific conditions in this analysis (asthma, respiratory illness, injury, mental health, diabetes, obesity, and hypertension).

Table 3. Inpatient hospitalizations and emergency department (ED) visits based on primary diagnosis: magnitudes are shown as associations with a 10-percentage-point decrease in neighborhood poverty

	Incidence rate ratio^a (95% CI)	p value	Adjusted p value^b
Adult hospitalizations^c
All-cause visits^d	0.97 [0.86, 1.09]	.60	.81
Asthma	0.95 [0.61, 1.47]	.81	.81
Respiratory illness	1.04 [0.76, 1.42]	.81	.81
Injury	1.25 [0.87, 1.79]	.23	.64
Mental health	0.81 [0.55, 1.21]	.31	.64
Diabetes	1.08 [0.73, 1.60]	.71	.81
Obesity	0.80 [0.51, 1.25]	.32	.64
Hypertension	0.81 [0.54, 1.20]	.29	.64
Adult ED visits^c
All-cause visits^d	0.97 [0.90, 1.06]	.53	.65
Asthma	1.14 [0.85, 1.54]	.37	.59
Respiratory illness	1.01 [0.84, 1.20]	.95	.95
Injury	0.91 [0.82, 1.02]	.12	.40
Mental health	1.11 [0.79, 1.56]	.57	.65
Diabetes	0.84 [0.64, 1.10]	.20	.40
Obesity	0.71 [0.43, 1.17]	.18	.40
Hypertension	0.84 [0.71, 1.01]	.06	.40
Child hospitalizations^c,e
All-cause visits^d	0.88 [0.80, 0.98]	.02	.10
Asthma	0.79 [0.52, 1.18]	.25	.42
Respiratory illness	1.00 [0.69, 1.44]	.99	.99
Injury	1.04 [0.86, 1.27]	.67	.84
Mental health	0.75 [0.56, 0.99]	.04	.10
Child ED visits^c,e
All-cause visits^d	0.98 [0.92, 1.04]	.55	.60
Asthma	1.08 [0.85, 1.36]	.54	.60
Respiratory illness	1.08 [0.96, 1.23]	.21	.60
Injury	0.97 [0.90, 1.05]	.51	.60
Mental health	1.07 [0.84, 1.37]	.60	.60

Note. ^aPoverty-based estimates show the association of a 10-percentage-point decrease in neighborhood poverty exposure with hospital/ED use from a two-stage modeling approach. The first-stage regression was an ordinary least squares model with the mean duration-weighted percentage of households in the census tract with incomes above the poverty line as the dependent variable, the study-group voucher indicators and the site and study-group voucher interactions as the main predictors, and the baseline characteristics and sites as controls. The second-stage regression uses the predicted duration-weighted percentage of families above the poverty line from years 1 through 3 since randomization as the key explanatory variable and the utilization count from years 4 through 21 since randomization as the dependent variable, adjusting for baseline covariates (described in the text). Incidence rate ratios were estimated from negative binomial models with an offset term indicating the total months of available data for the person. The models included survey sample weights to account for varying sampling probabilities over the accrual period and accounted for the family unit by clustering all standard errors by family.

^bAdjusted p values represent the lowest false discovery rate threshold at which the test could be considered significant, using the Benjamini–Hochberg procedure to control the false discovery rate to less than 1 out of 8, corresponding to the number of comparisons per group of analyses for adults, and 1 out of 5, corresponding to the number of comparisons per group of analyses for children; an adjusted p value is statistically significant if <.125 for adults and if <.20 for children.

^cAdult age ≥18 at randomization; children <18 at randomization.

^dAll-cause visits refer to hospitalizations or ED visits for all diagnoses, including but not limited to the specific conditions in this analysis (asthma, respiratory illness, injury, mental health, diabetes, obesity, and hypertension).

^eModel estimates for diabetes, obesity, and hypertension for children at randomization are not shown because of the low incidence of these specific outcomes.

Table 4. Magnitudes of the association with types of service as a 10-percentage-point decrease in neighborhood poverty⁺

	Incidence rate ratio^a (95% CI)	p value	Adjusted p value^b
Adults at randomization^c
Lab and X-ray	1.02 [0.94, 1.11]	.61	.94
Physicians	0.98 [0.91, 1.07]	.70	.94
Psychiatric services	0.85 [0.68, 1.05]	.13	.47
Outpatient hospital	0.96 [0.89, 1.05]	.39	.86
Dental	1.02 [0.95, 1.10]	.54	.94
Clinic	0.92 [0.82, 1.04]	.17	.47
Other services	0.99 [0.82, 1.19]	.91	.94
Transportation services	0.76 [0.60, 0.97]	.03	.33
Targeted case management	0.97 [0.63, 1.50]	.90	.94
DME/supplies	0.87 [0.74, 1.02]	.08	.44
Other practitioners	0.99 [0.85, 1.17]	.94	.94
Children at randomization^c
Lab and X-ray	0.97 [0.91, 1.03]	.32	.48
Physicians	0.98 [0.93, 1.03]	.44	.48
Psychiatric services	0.88 [0.76, 1.01]	.06	.20
Outpatient hospital	0.93 [0.86, 1.01]	.08	.20
Dental	1.03 [0.97, 1.08]	.37	.48
Clinic	0.86 [0.79, 0.94]	.001	.005
Other services	1.01 [0.84, 1.21]	.95	.95
Transportation services	0.91 [0.76, 1.10]	.34	.48
Targeted case management	1.07 [0.90, 1.27]	.42	.48
DME/supplies	0.71 [0.59, 0.84]	<.001	.001
Other practitioners	1.11 [0.99, 1.24]	.09	.20

^aPoverty-based estimates show the association of a 10-percentage-point decrease in neighborhood poverty exposure with utilization from a two-stage modeling approach. The first-stage regression was an ordinary least squares model with the mean duration-weighted percentage of households in the census tract with incomes above the poverty line as the dependent variable, the study-group voucher indicators and the site and study-group voucher interactions as the main predictors, and the baseline characteristics and sites as controls. The second-stage regression uses the predicted duration-weighted percentage of families above the poverty line from years 1 through 3 since randomization as the key explanatory variable and the utilization count from years 4 through 21 since randomization as the dependent variable, adjusting for baseline covariates (described in the text). Incidence rate ratios were estimated from negative binomial models with an offset term indicating the total months of available data for the person. The models included survey sample weights to account for varying sampling probabilities over the accrual period and accounted for the family unit by clustering all standard errors by family.

^bAdjusted p values represent the lowest false discovery rate threshold at which the test could be considered significant, using the Benjamini–Hochberg procedure to control the false discovery rate to less than 1 out of 11, corresponding to the number of comparisons per group of analyses; an adjusted p value is statistically significant if <.09.

^cAdult age ≥18 at randomization; children <18 at randomization.