Staying under the Radar? Immigration Effects on Overdose Deaths and the Impact of Sanctuary Jurisdictions
Abstract
:1. Introduction
2. Literature Review
2.1. Immigration, Crime, and Drug Use
2.2. Reasons Immigration Could Increase Overdose Deaths
2.3. Reasons Immigration Could Decrease Overdose Deaths
2.4. Sanctuary Jurisdictions
2.5. The Current Study: Systems Avoidance, Immigrant Revitalization, and Sanctuary Status
3. Materials and Methods
3.1. Dependent Variables
3.2. Independent Variables
3.3. Control Variables
3.4. Analysis
4. Results
4.1. Descriptive Statistics
4.2. Multivariate Analysis
5. Discussion
Limitations and Directions for Future Research
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
1 | Overdose death data were calculated based on an individual’s county of residence. These data were then aggregated to the MSA-level using a crosswalk file. Overdose death counts were based on underlying death codes following CDC categorizations and prior research [89,90]: overdose, X40 to X44, X60 to X64, X85, and Y10 to Y14. |
2 | Coefficients were slightly larger using % Latinx foreign born than overall % foreign born for all groups, but significance levels were unchanged. |
3 | There is no standard definition of a sanctuary area. We use a conservative approach and only count those areas with formalized sanctuary resolutions in place as having sanctuary status. However, we conducted additional analyses using a sanctuary variable that included all MSAs that reported non-cooperation with ICE in 2015 that could be located (even without formal resolutions). Results did not change substantively. |
4 | MSAs containing large sanctuary cities, such as San Francisco, were almost all coded as having sanctuary status while mixed status areas where it was unclear how much of the MSA was covered by sanctuary policies were excluded. Most areas with sanctuary policies were coded as sanctuary MSAs due to the tendency for these policies to be enacted in large cities or counties (see [16]). However, for 10 MSAs, coverage of sanctuary policies were unclear or the sanctuary policy in question did not cover at least half the total population included in the MSA. |
5 | For information on sanctuary data sources, see FAIR US https://www.fairus.org/sites/default/files/2017-08/Sanctuary_Policies_Across_America_Report.pdf (accessed on 18 March 2023), Center for Immigration Studies https://cis.org/Map-Sanctuary-Cities-Counties-and-States (accessed on 18 March 2023, and Ohio Jobs and Justice PAC http://ojjpac.org/sanctuary.asp (accessed on 18 March 2023). |
6 | Indices were created with the “alpha” command in Stata, and were not standardized given the consistent measurement between indicators. Alternate indices (standardized alpha and factors using principal components analysis) were also examined in supplemental analyses. Results were consistent regardless of how the indices were created, though the effects of disadvantage had slightly stronger effects when using principal components analysis. |
7 | Because there was a concern that this may be a function of fewer White residents naturally resulting from a larger % of Latinx foreign-born residents, supplemental analysis was also run controlling for total non-Latinx White population rather than total population, which revealed that controlling for this only made the % Latinx foreign-born effect stronger (supplemental analysis not shown, available upon request). |
8 | A second, less stringently defined sanctuary variable was created for supplemental analysis in which MSAs with any sanctuary policy (formal or informal) and declined detainer requests as reported by Fair U.S. and the Center for Immigration Studies were coded as sanctuaries. Results from the supplemental models did not change substantively. |
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Total | Sanctuary MSA | Non-Sanctuary MSA | ||||
---|---|---|---|---|---|---|
Mean (Rate) | SD | Mean (Rate) | SD | Mean (Rate) | SD | |
Dependent Variables | ||||||
Total overdose deaths | 153.98 (18.16) | 153.98 | 454.23 (19.54) | 451.51 | 106.33 (17.94) | 135.78 |
Latinx overdose deaths | 13.38 (7.80) | 32.31 | 45.43 (11.79) | 65.04 | 8.28 (7.17) | 19.05 |
White overdose deaths | 118.36 (21.80) | 177.40 | 322.25 (22.5) | 329.55 | 85.99 (21.69) | 109.25 |
Black overdose deaths | 17.70 (16.63) | 43.01 | 70.26 (26.09) | 94.11 | 9.36 (15.12) | 16.09 |
Independent Variables | ||||||
Latinx foreign-born | 4.47% | 5.56 | 5.99% | 4.90 | 4.23% | 5.63 |
Sanctuary status | 13.70% | |||||
Total population | 878,351 | 1,399,192 | 2,607,703 | 2,655,185 | 603,850.80 | 788,708 |
Opioid prescription rate | 51.76 | 45.04 | 20.18 | 17.40 | 56.78 | 46.05 |
Total uninsured | 79,656.17 | 141,910.20 | 199,533.50 | 266,897.80 | 60,627.95 | 98,111.44 |
Residential mobility | 0.16 | 3.67 | 14.57 | 3.14 | 16.17 | 3.71 |
Police presence per 100,000 | 233.77 | 156.77 | 257.34 | 171.35 | 230.02 | 154.37 |
Disadvantage Index-Total | 11.58 | 2.80 | 11.72 | 2.80 | 10.73 | 2.68 |
Unemployed | 6.54% | 1.72 | 6.55% | 1.77 | 6.49% | 1.33 |
Female headed household | 12.64% | 2.79 | 12.79% | 2.83 | 11.69% | 2.26 |
Population in poverty | 15.21% | 4.07 | 15.47% | 3.99 | 13.59% | 4.20 |
No high school diploma | 11.92% | 5.02 | 12.05% | 5.11 | 11.14% | 4.46 |
Disadvantage Index-Latinx | 20.50 | 4.17 | 19.71 | 3.62 | 20.63 | 4.24 |
Unemployed | 7.80% | 2.92 | 7.95% | 2.00 | 7.79% | 3.05 |
Female headed household | 19.42% | 5.98 | 19.78% | 5.18 | 19.36% | 6.10 |
Population in poverty | 24.45% | 6.60 | 21.72% | 5.50 | 24.88% | 6.67 |
No high school diploma | 30.34% | 9.99 | 29.39% | 7.88 | 30.50% | 10.29 |
Disadvantage Index-White | 8.03 | 1.62 | 6.76 | 1.51 | 8.23 | 1.53 |
Unemployed | 5.37% | 1.28 | 5.23% | 1.05 | 5.39% | 1.31 |
Female headed household | 8.45% | 1.62 | 7.36% | 1.48 | 8.63% | 1.58 |
Population in poverty | 10.82% | 3.00 | 9.04% | 3.11 | 11.11% | 2.89 |
No high school diploma | 7.46% | 2.78 | 5.42% | 1.82 | 7.78% | 2.77 |
Disadvantage Index-Black | 21.40 | 5.51 | 19.64 | 5.02 | 21.67 | 5.54 |
Unemployed | 11.83% | 4.11 | 11.87% | 3.20 | 11.82% | 4.25 |
Female headed household | 30.31% | 9.69 | 28.88% | 9.60 | 30.54% | 9.70 |
Population in poverty | 28.38% | 8.62 | 25.04% | 7.41 | 28.91% | 8.69 |
No high school diploma | 15.06% | 5.27 | 12.79% | 3.79 | 15.42% | 5.39 |
N = 292 | n = 40 | n = 252 |
Total | Latinx | Black | White | |||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Model 1 | Model 2 | Model 3 | Model 1 | Model 2 | Model 3 | Model 1 | Model 2 | Model 3 | Model 1 | Model 2 | Model 3 | |||||||||||||
b (SE) | IRR | b (SE) | IRR | b (SE) | IRR | b (SE) | IRR | b (SE) | IRR | b (SE) | IRR | b (SE) | IRR | b (SE) | IRR | b (SE) | IRR | b (SE) | IRR | b (SE) | IRR | b (SE) | IRR | |
% Latinx foreign-born | −0.028 *** (0.005) | 0.972 | −0.028 *** (0.005) | 0.972 | −0.028 *** (0.006) | 0.972 | 0.096 *** (0.014) | 1.100 | 0.093 *** (0.013) | 1.098 | 0.091 *** (0.014) | 1.095 | −0.037 *** (0.008) | 0.964 | −0.036 *** (0.009) | 0.964 | −0.036 *** (0.009) | 0.965 | −0.049 *** (0.005) | 0.953 | −0.049 *** (0.005) | 0.952 | −0.048 *** (0.005) | 0.953 |
Sanctuary status | 0.006 (0.071) | 1.006 | 0.062 (0.107) | 1.064 | 0.692 *** (0.161) | 1.997 | 0.528 (0.281) | 1.696 | 0.042 (0.121) | 1.043 | 0.120 (0.175) | 1.128 | −0.053 (0.074) | 0.948 | 0.027 (0.111) | 1.028 | ||||||||
Foreign born x Sanctuary status | −0.010 (0.014) | 0.990 | 0.027 (0.039) | 1.027 | −0.015 (0.024) | 0.985 | −0.015 (0.015) | 0.985 | ||||||||||||||||
Total population a | 1.165 *** (0.037) | 3.205 | 1.164 *** (0.038) | 3.203 | 1.154 *** (0.040) | 3.172 | 0.915 *** (0.105) | 2.498 | 0.837 *** (0.106) | 2.309 | 0.862 *** (0.113) | 2.368 | 1.453 *** (0.069) | 4.276 | 1.446 *** (0.071) | 4.247 | 1.430 *** (0.075) | 4.181 | 1.184 *** (0.038) | 3.267 | 1.190 *** (0.039) | 3.286 | 1.176 *** (0.041) | 3.241 |
Opioid prescription rate | 2.28E-4 (0.001) | 1.000 | 2.418E-4 (0.001) | 1.000 | 2.109E-4 (0.001) | 1.000 | −0.010 *** (0.003) | 0.990 | −0.010 *** (0.002) | 0.990 | −0.010 *** (0.002) | 0.990 | 0.002 (0.001) | 1.002 | 0.002 (0.001) | 1.002 | 0.002 (0.001) | 1.002 | −0.002 * (0.001) | 0.998 | −0.001 * (0.001) | 0.998 | −0.002 * (0.001) | 0.998 |
Residential mobiliity | −0.019 ** (0.007) | 0.981 | −0.019 ** (0.007) | 0.982 | −0.019 ** (0.007) | 0.981 | −0.017 (0.018) | 0.983 | 0.002 (0.018) | 1.002 | 0.004 (0.018) | 1.004 | −0.018 (0.013) | 0.982 | −0.017 (0.013) | 0.983 | −0.018 (0.013) | 0.982 | −0.020 ** (0.007) | 0.980 | −0.021 ** (0.007) | 0.979 | −0.021 ** (0.007) | 0.979 |
Disadvantage index b | 0.006 (0.011) | 1.006 | 0.006 (0.011) | 1.006 | 0.007 (0.011) | 1.007 | −0.007 (0.016) | 0.994 | 4.679E-4 (0.015) | 1.000 | 0.001 (0.015) | 1.001 | 0.053 *** (0.010) | 1.054 | 0.053 *** (0.010) | 1.054 | 0.052 *** (0.010) | 1.054 | 0.112 *** (0.019) | 1.118 | 0.110 *** (0.019) | 1.117 | 0.110 *** (0.019) | 1.117 |
Total uninsured | −9.260E-7 *** (0.000) | 1.000 | −9.270E-7 *** (0.000) | 1.000 | −8.390E-7 ** (0.000) | 1.000 | −3.600E-7 (0.000) | 1.000 | −2.69E-7 (0.000) | 1.000 | −4.440E-7 (0.000) | 1.000 | −3.870E07 (0.000) | 1.000 | −3.930E-7 (0.000) | 1.000 | −2.570E-7 (0.000) | 1.000 | −9.720E-7 *** (0.000) | 1.000 | −9.650E-7 *** (0.000) | 1.000 | −8.340E-7 ** (0.000) | 1.000 |
Police presence | −2.456E-4 (0.000) | 1.000 | −2.456 (0.000) | 1.000 | −2.454E-4 (0.000) | 1.000 | 1.405E-4 (0.000) | 1.000 | −1.649E-4 (0.000) | 1.000 | −1.734E-7 (0.000) | 1.000 | 0.001 *** (0.000) | 1.001 | 0.001 *** (0.000) | 1.001 | 0.001 *** (0.000) | 1.001 | −2.95E-4 (0.000) | 1.000 | −2.905E-4 (0.000) | 1.000 | −2.887E-4 (0.000) | 1.000 |
Constant | −10.333 *** (0.544) | 0.000 | −10.327 *** (0.548) | 0.000 | −10.210 *** (0.571) | 0.000 | −10.008 *** (1.624) | 0.000 | −9.483 (1.603) | 0.000 | −9.824 (1.680) | 0.000 | −18.222 *** (1.084) | 0.000 | −18.15278 *** (1.100) | 0.000 | −17.929 *** (1.154) | 0.000 | −11.4042 *** (0.572) | 0.000 | −11.450 *** (0.574) | 0.000 | −11.274 *** (0.598) | 0.000 |
Pseudo R2 | 0.208 *** | 0.208 *** | 0.209 *** | 0.201 *** | 0.211 *** | 0.211 *** | 0.259 *** | 0.259 *** | 0.259 *** | 0.206 *** | 0.206 *** | 0.206 *** |
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Pierce, K.; Sun, D.; Feldmeyer, B. Staying under the Radar? Immigration Effects on Overdose Deaths and the Impact of Sanctuary Jurisdictions. Societies 2023, 13, 135. https://doi.org/10.3390/soc13060135
Pierce K, Sun D, Feldmeyer B. Staying under the Radar? Immigration Effects on Overdose Deaths and the Impact of Sanctuary Jurisdictions. Societies. 2023; 13(6):135. https://doi.org/10.3390/soc13060135
Chicago/Turabian StylePierce, Kelly, Diana Sun, and Ben Feldmeyer. 2023. "Staying under the Radar? Immigration Effects on Overdose Deaths and the Impact of Sanctuary Jurisdictions" Societies 13, no. 6: 135. https://doi.org/10.3390/soc13060135