# Intermarriage and COVID-19 mortality among immigrants. A population-based cohort study from Sweden

Siddartha Aradhya, Maria Brandén, Sven Drefahl, Ognjen Obucina, Gunnar Andersson, Mikael Rostila, Eleonora Mussino, Sol Pía Juárez

► To cite this version:

Siddartha Aradhya, Maria Brandén, Sven Drefahl, Ognjen Obucina, Gunnar Andersson, et al.. Inter-marriage and COVID-19 mortality among immigrants. A population-based cohort study from Sweden. BMJ Open, 2021, 11 (9), pp.e048952 (1-8). 10.1136/bmjopen-2021-048952. hal-03334283

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# BMJ Open Intermarriage and COVID-19 mortality among immigrants. A population-based cohort study from Sweden

Siddartha Aradhya,¹ Maria Brandén,¹,² Sven Drefahl,¹ Ognjen Obućina,³ Gunnar Andersson,¹ Mikael Rostila,⁴ Eleonora Mussino,¹ Sol Pía Juárez⁵

**To cite:** Aradhya S, Brandén M, Drefahl S, et al. Intermarriage and COVID-19 mortality among immigrants. A population-based cohort study from Sweden. *BMJ Open* 2021;11:e048952. doi:10.1136/bmjopen-2021-048952

► Prepublication history and additional supplemental material for this paper are available online. To view these files, please visit the journal online. (http://dx.doi.org/10.1136/bmjopen-2021-048952).

Received 19 January 2021
Accepted 28 July 2021

## ABSTRACT

**Objectives** To evaluate the role of language proficiency and institutional awareness in explaining excess COVID-19 mortality among immigrants.

**Design** Cohort study with follow-up between 12 March 2020 and 23 February 2021.

**Setting** Swedish register-based study on all residents in Sweden.

**Participants** 3 963 356 Swedish residents in co-residential unions who were 30 years of age or older and alive on 12 March 2020 and living in Sweden in December 2019.

**Outcome measures** Cox regression models were conducted to assess the association between different constellations of immigrant-native couples (proxy for language proficiency and institutional awareness) and COVID-19 mortality and all other causes of deaths (2019 and 2020). Models were adjusted for relevant confounders.

**Results** Compared with Swedish-Swedish couples (1.18 deaths per thousand person-years), both immigrants partnered with another immigrant and a native showed excess mortality for COVID-19 (HR 1.43; 95% CI 1.29 to 1.58 and HR 1.24; 95% CI 1.10 to 1.40, respectively), which translates to 1.37 and 1.28 deaths per thousand person-years. Moreover, similar results are found for natives partnered with an immigrant (HR 1.15; 95% CI 1.02 to 1.29), which translates to 1.29 deaths per thousand person-years. Further analysis shows that immigrants from both high-income and low-income and middle-income countries (LMIC) experience excess mortality also when partnered with a Swede. However, having a Swedish-born partner is only partially protective against COVID-19 mortality among immigrants from LMIC origins.

**Conclusions** Language barriers and/or poor institutional awareness are not major drivers for the excess mortality from COVID-19 among immigrants. Rather, our study provides suggestive evidence that excess mortality among immigrants is explained by differential exposure to the virus.

International evidence has shown that immigrants and ethnic minorities are disproportionately at risk of severe COVID-19 complications and death.¹⁻¹³ In the context of an ongoing pandemic, an effort to understand the causes for why some groups are more affected is a public health priority.¹⁴⁻¹⁷

## Strengths and limitations of this study

► This study uses total population data with all deaths (from COVID-19 and other causes) in Sweden from 12 March 2020 to 23 February 2021.

► We identified the origin of co-resident couples to evaluate the role of language proficiency and institutional awareness (eg, healthcare system) in explaining excess COVID-19 mortality among immigrants.

► We compare COVID-19 mortality with all other causes of death during the pandemic and all-cause mortality 1 year prior to evaluate the relative impact of the pandemic within each group.

► The analyses do not include information on occupation, however the most vulnerable individuals are beyond retirement age.

Among these groups, excess mortality has been suggested to be the result of differential exposure (eg, high-risk occupations or overcrowded accommodation), susceptibility (eg, pre-existing conditions) and language barriers and access to healthcare.¹⁸⁻²⁰ Recent studies, however, suggest that immigrants and minorities maintain an excess mortality even after controlling for socioeconomic status and housing conditions.³,²¹ Yet there is paucity of evidence on the role of language barriers and institutional awareness in explaining the COVID-19 excess mortality experienced by immigrants.

Sweden took a distinct approach to dealing with the COVID-19 pandemic as compared with other Western countries by not implementing lock downs or mask mandates and instead relied largely on recommendations. The authorities justified implementing a relatively less rigid approach by arguing that Swedes have a high level of trust in their institutions and as such follow governmental recommendations.²²,²³ The strategy relied primarily on public health advice (regarding hygiene routines, social distancing and suspension from work, school or daycare in case of minor

<figure><img src="image_2.png" /></figure>

### Check for updates

© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.

¹Stockholm University
Demography Unit (SUDA),
Department of Sociology,
Stockholm University,
Stockholm, Sweden

²The Institute for Analytical
Sociology (IAS), Linköping
University, Linköping, Sweden

³Institut national d'études
démographiques (INED),
Aubervilliers, France

⁴Department of Public Health
Sciences, Stockholm University,
Stockholm, Sweden

**Correspondence to**
Dr Sol Pía Juárez;
sol.juarez@su.se
symptoms) *in lieu* of mandates which are not permitted under Swedish law.²² The effectiveness of the adopted strategy strongly depends on the ability of all members of the society to understand the recommendations, which is a basic condition for their adherence. Under this ratio-nale, it is unsurprising that excess mortality observed among immigrants²⁴—especially concentrated among those with more distant origins—could be interpreted as a consequence of lower adherence to recommendations and/or related factors.

More specifically, it has been argued that immigrants may, as a result of inadequate language proficiency and institutional awareness, have a poor understanding of the healthcare system and of the recommendations during the COVID-19 pandemic putting them at higher risk of exposure and vulnerability to the virus. Analysing inter-married immigrants present a unique opportunity to generate evidence for this explanation.

Within the field of immigrant integration, intermar-riage has been considered the ultimate stage of accul-turation²⁵⁻²⁷ and is, both, a marker of and facilitator for integration. Marrying a native is strongly related to language abilities, knowledge of the host country's insti-tutions and social practices as well as the ethnic compo-sition of one's social circle. As a result, intermarriage reflects the narrowing of sociocultural distance between ethnic Swedes and immigrants, which renders it an ideal measure to evaluate the role of understanding and aware-ness of recommendations from Swedish authorities as explanations for the excess COVID-19 mortality among immigrants.

If understanding and awareness of recommendations (language *in primis*) explain the excess mortality, immigrants partnered with a Swede and, in particular, Swedes partnered with an immigrant should have similar mortality to Swedes partnered with a Swede. To this end, the aim of this study is to examine the association between sociocultural integration and COVID-19 mortality by examining

native-immigrant couple dyads—a well-regarded measure that has been shown to be a marker and facilitator of integration.

## METHODS

### Study population

An observational cohort study was conducted using Swedish register data. The study includes all Swedish residents who were 30 years of age or older and were cohabiting with another adult who was at least 30 years of age and alive on 12 March 2020, residing in Sweden in December 2019 (n=4 019 418). This age restriction was established to ensure co-resident individuals were family members and not flat mates. The follow-up period was 12 March 2020 up until 23 February 2021. We excluded individuals who had not lived in Sweden in the two prior years (n=40 515), because they could not be linked to all records of data. In addition, we excluded individuals with missing data on country of birth (n=142) and income (n=15 405) of either partner. The final study population consists of 3 963 356 individuals (18.5% immigrants) (figure 1).

### Patient and public involvement

No patient was involved.

### Data

We use information from several Swedish administra-tive registers linked through personal identity numbers that are unique to each person with legal residence in Sweden. Data on deaths were retrieved from the Cause of Death Register. Socioeconomic and demographic variables (income, education, number of children and region of residence) were drawn from the Longitudinal Integrated Database for Health Insurance and Labour Market Studies (LISA), and residential information (type and crowdedness of the dwelling) were drawn from the

<figure><img src="image_3.png" /><figcaption>**Figure 1** Selection flow and final sample.</figcaption></figure>
Dwelling Register. All covariates in our study are time-
constant and either measured at the end of 2019 (all
variables at the household and neighbourhood level) or
2018 (highest education attained, sum of the individual
net incomes of the two co-resident adults, total number
of individuals in the household under 30). Information
on age, sex, country of birth and immigrant density in the
neighbourhood stem from the Total Population Register.
It is important to note that all individuals registered in
Sweden are entitled to healthcare access.

Study variables

COVID-19 mortality was identified by the Swedish National Board of Health and Welfare (Socialstyrelsen), the agency responsible for the Cause of Death Register. COVID-19 mortality was identified using the following International Classification of Diseases (ICD) codes for the underlying cause of death: U07.1 (3915 deaths), U07.2 (127 deaths) and B34.2 (2 deaths); for 522 more deaths ICD codes U07.1, U07.2 or B34.2 were listed as contributing causes of death, excluding mortality from all other causes of death (30374 deaths). Given the timeliness of the data, the assignment of the underlying cause of death should be understood as preliminary.

Immigrant-native couple types were created by
combining information from the Dwelling and the
Total Population Registers to create the couple type
which include two individuals of at least 30 years of age
co-residing in the same household. The variable is clas-
sified into the following four ego-partner categories
using information on country of birth: (i) native-native,
(ii) native-immigrant, (iii) immigrant-native and (iv)
immigrant-immigrant. We chose (i) native-native couples
as the reference group for our analyses as they (a) consti-
tute the largest category among all groups considered and
(b) represent the institutional awareness and language of
the host population from which we expect other groups
to deviate. We further disaggregated the groups by immi-
grant's origins defined according to the World Bank clas-
sification based on the Gross National Incomes per capita
using the WB Atlas method²⁸ as high-income countries
(HIC) and low-income and middle-income countries
(LMIC).

We derived individual income and calculated the sum
of the two partners' net incomes (household), categorised
into tertiles based on all adult residents of Sweden. We
derived education data from Swedish Educational Regis-
ters and categorise our population into four categories:
those with primary schooling, secondary schooling, post-
secondary education and those with missing information
on education. Missing information on education is gener-
ally very low but 88% of those with missing education are
immigrants. We additionally performed multiple imputa-
tion to test how the missing values for education impact
our results (see online supplemental appendix figure S1).
In addition, we dropped all missing categories to assess
whether the distributions of covariates were affected by
missing values (see online supplemental appendix table

S1). From the Swedish Dwelling Register, we accessed information on size of the dwelling and a unique dwelling code which enables us to link individuals who live together in a household and determine co-residence. In addition to define couples, we use this information to create: the number of individuals per square metre in the household (with a separate category for a small group of individuals, due to missing information on square metres in some detached houses), the number of individuals living in the household under the age of 30 and dwelling type (multi-family, single family or care home). We include in our model also the share of immigrants in the local neighbourhood, DeSO (a smaller subdivision of administrative areas based on demographic characteristics produced by the Swedish administrative statistics).

Statistical analysis

We conducted Cox proportional hazards regressions (using age as the timescale) to estimate HR and 95% CI for the association between immigrant-native couple type and COVID-19 mortality. Individuals exited the study by (1) dying between 12 March 2020 and 23 February 2021, or (2) being alive on 23 February 2021. We estimated two separate regressions estimating the cause-specific hazard of dying from COVID-19, right-censoring all individuals that die from other causes and (2) the cause-specific hazard of dying from other causes than COVID-19, right-censoring all individuals that die from COVID-19. In addition, we conducted Cox regressions for dying from all causes of death that occurred between 12 March 2019 and 23 February 2020 (31 653 deaths)—the same period we observe COVID-19 deaths 12 contiguous months prior to the start of the pandemic. Since mortality from COVID-19 and other causes of deaths during the study window are not fully independent of each other, our estimates for all-cause mortality between 12 March 2019 and 23 February 2020 were used to evaluate the robustness of our estimates for mortality during the pandemic. In addition, the comparison between all-cause mortality 1 year prior and mortality from causes other than COVID-19 during the pandemic, by immigrant-native couple type, will allow us to examine whether the latter has a distinctive role in relation to the pandemic.

Two models were estimated: (1) a simple model with age
as the time scale adjusted for sex and (2) the same model
with further adjustments. In the latter analysis, we adjust
for education, neighbourhood immigrant density and
region of residence fixed-effects that are confounders, as
well as factors that are on the causal pathway that have
been previously used to explain the excess mortality of
immigrants (ie, number of individuals in the household
below the age of 30 years, dwelling type, square metres
per person in the dwelling, household income). In addi-
tion, we conducted two sensitivity analyses. One in which
we examined the partner's origin among Swedish-migrant
partnerships (HIC or LMIC) to check whether patterns
are consistent across groups and, a second, in which we
excluded all individuals born in Sweden with at least one
foreign-born parent. All analyses were conducted using Stata Statistical Software: Release 16 (StataCorp, College Station, Texas, USA).

## RESULTS

During the 3759610 person-years of observation, 4564 COVID-19 deaths occurred in our study population between 12 March 2020 and 23 February 2021. Table 1 shows the distribution of population at risk and deaths by all covariates. In our population, 6.09% of individuals are in immigrant-native couples. Native-native couples show the lowest deaths per thousand person-years (1.18/1000), whereas all other couple types show higher death rates of COVID-19 mortality (approximately 1.3–1.4 per thousand person-years). Of the study population, 6.55% of COVID-19 deaths were attributed to native-immigrant mixed couples and 14.04% to immigrant-immigrant couples.

Figure 2 displays mortality risks from COVID-19, all other causes of death during the pandemic and all-causes of death 1 year prior across couple types with native-native as the reference (see online supplemental appendix table S2 for estimates). Panel A presents models adjusted for age and sex and panel B presents the estimates including adjustments. In A, individuals in immigrant-immigrant couples show the highest HR of dying from COVID-19 (HR 2.47; 95% CI 2.27 to 2.69) and those in native-native couples the lowest (reference group) while natives (HR 1.40; 95% CI 1.25 to 1.58) and immigrants (HR 1.50; 95% CI 1.33 to 1.69) in mixed couples showed intermediate mortality levels. All causes of death in the year prior to the pandemic and all other causes of death during the pandemic show little differences between couple constellations. After adjustments (panel B), differences across groups attenuate, but the gradient in COVID-19 mortality remains. Individuals in immigrant-immigrant couples still display the highest HR of dying from COVID-19 relative to the reference group (HR 1.43; 95% CI 1.29 to 1.58), followed by those in immigrant-native couples (HR 1.24; 95% CI 1.10 to 1.40) and native-immigrant couples (HR 1.15; 95% CI 1.02 to 1.29). It is important to note that there is no statistically significant difference in the risk of COVID-19 mortality between immigrant-native and immigrant-immigrant couples. An opposite gradient is observed with respect to all-cause mortality in the year prior to the pandemic and all other causes of death during the pandemic, with immigrant-immigrant couples displaying the lowest mortality.

Figure 3 is an extension of figure 2 disaggregating the immigrant population by income level of their country of birth (see online supplemental appendix table S3 for estimates). In panel A, there are elevated HRs across all origin groups relative to native-native couples. Immigrants in LMIC-immigrant couples display the highest HR relative to the reference group (HR 3.60; 95% CI 3.25 to 3.99) followed by those in LMIC-native couples (HR 1.91; 95% CI 1.42 to 2.57). Natives in native-immigrant

couples, where HIC and LMIC have been pooled (HR 1.41; 95% CI 1.25 to 1.58), HIC-native (HR 1.44; 95% CI 1.27 to 1.64) and immigrants in HIC-immigrant (HR 1.54; 95% CI 1.34 to 1.77) couples display relatively similar HRs. After adjustment (panel B), all groups with an immigrant still display higher HRs relative to native-native couples, but at a lower level. LMIC-immigrant couples experience a particularly strong reduction in their HRs (HR 1.84; 95% CI 1.62 to 2.09). Compared with LMIC-native couples, their HR remains slightly higher (HR 1.35; 95% CI 1.00 to 1.82). We also find that HIC-native (HR 1.23; 95% CI 1.08 to 1.40) and HIC-immigrant (HR 1.11; 95% CI 0.97 to 1.28) couples display higher HRs relative to the reference group.

Sensitivity analyses showed that disaggregating the origin of immigrants in native-immigrant partnerships (online supplemental appendix figure S2) and excluding second-generation Swedes from the Swedish-born population (online supplemental appendix figure S3) produce no further differentials in mortality risks.

## DISCUSSION

Our study shows that immigrants have excess COVID-19 mortality regardless of the origin of their partner, where having a Swedish-born partner is only partially protective against COVID-19 mortality among immigrants from LMIC. These findings challenge hypotheses that poor language proficiency and institutional awareness are major contributing factors explaining the excess mortality from COVID-19 among immigrants.

Language has been considered a vital component of integration and relevant for accessing information for other types of medical treatments and health outcomes.²⁹ Given that the COVID-19 pandemic is a unique occurrence that was accompanied by a global diffusion of information, one can argue that even those with presumably little Swedish proficiency have been exposed to recommendations offered in their native languages from either public health officials from their countries of origin or via other international channels. In fact, the information that they may have received from international sources may be more relevant for specific immigrant populations, for example, how to best protect oneself when observing cultural or religious practice. At the same time, the Swedish authorities have translated information to other languages, although not culturally adapted. However, in the first stage of the pandemic, the authorities were delayed in releasing information in all languages and, at least in Stockholm, we found no group differences among intermarried groups and immigrant-immigrant couples (see online supplemental appendix figure S4). This highlights how language is no straightforward factor in mitigating the burden of COVID-19 on immigrant populations.

Prior studies in clinical settings have shown that access to a medical interpreter is associated with better health access and outcomes.²⁹ Although we cannot test this
<table><caption>Table 1 Description of the study population, number, proportion of deaths and death rates</caption><thead><tr><th rowspan="2"></th><th colspan="2">Total</th><th colspan="2">COVID-19</th><th colspan="2">Other cause of death</th><th rowspan="2">Exposure time in years</th><th rowspan="2">COVID-19 deaths per 1000 years</th></tr><tr><th>N at 12 March 2020</th><th>%</th><th>Deaths 12 March 2020-23 February 2021</th><th>%</th><th>Deaths 12 March 2020-23 February 2021</th><th>%</th></tr></thead><tbody><tr><td colspan="9"><strong>Couple type</strong></td></tr><tr><td>Native-native</td><td>2984648</td><td>75.31</td><td>3330</td><td>72.96</td><td>24846</td><td>81.80</td><td>2830382</td><td>1.18</td></tr><tr><td>Native-immigrant</td><td>245124</td><td>6.18</td><td>299</td><td>6.55</td><td>1739</td><td>5.73</td><td>232563</td><td>1.29</td></tr><tr><td>Immigrant-native</td><td>241185</td><td>6.09</td><td>294</td><td>6.44</td><td>1507</td><td>4.96</td><td>228949</td><td>1.28</td></tr><tr><td>Immigrant-immigrant</td><td>492399</td><td>12.42</td><td>641</td><td>14.04</td><td>2282</td><td>7.51</td><td>467716</td><td>1.37</td></tr><tr><td colspan="9"><strong>Couple type, detailed</strong></td></tr><tr><td>Native-native</td><td>2984648</td><td>75.31</td><td>3330</td><td>72.96</td><td>24846</td><td>81.80</td><td>2830382</td><td>1.18</td></tr><tr><td>Native-immigrant</td><td>245124</td><td>6.18</td><td>299</td><td>6.55</td><td>1739</td><td>5.73</td><td>232563</td><td>1.29</td></tr><tr><td>HIC-native</td><td>140281</td><td>3.54</td><td>249</td><td>5.46</td><td>1294</td><td>4.26</td><td>132929</td><td>1.87</td></tr><tr><td>HIC-immigrant</td><td>121148</td><td>3.06</td><td>215</td><td>4.71</td><td>1170</td><td>3.85</td><td>114765</td><td>1.87</td></tr><tr><td>LMIC-native</td><td>100904</td><td>2.55</td><td>45</td><td>0.99</td><td>213</td><td>0.70</td><td>96020</td><td>0.47</td></tr><tr><td>LMIC-immigrant</td><td>371251</td><td>9.37</td><td>426</td><td>9.33</td><td>1112</td><td>3.66</td><td>352951</td><td>1.21</td></tr><tr><td colspan="9"><strong>Sex</strong></td></tr><tr><td>Man</td><td>1992097</td><td>50.26</td><td>3145</td><td>68.91</td><td>19003</td><td>62.56</td><td>1887523</td><td>1.67</td></tr><tr><td>Woman</td><td>1971259</td><td>49.74</td><td>1419</td><td>31.09</td><td>11371</td><td>37.44</td><td>1872087</td><td>0.76</td></tr><tr><td colspan="9"><strong>Education</strong></td></tr><tr><td>Primary</td><td>589969</td><td>14.89</td><td>1810</td><td>39.66</td><td>11495</td><td>37.84</td><td>555860</td><td>3.26</td></tr><tr><td>Secondary</td><td>1687832</td><td>42.59</td><td>1732</td><td>37.95</td><td>12069</td><td>39.73</td><td>1601553</td><td>1.08</td></tr><tr><td>Postsecondary</td><td>1651905</td><td>41.68</td><td>900</td><td>19.72</td><td>6420</td><td>21.14</td><td>1570393</td><td>0.57</td></tr><tr><td>Missing</td><td>33650</td><td>0.85</td><td>122</td><td>2.67</td><td>390</td><td>1.28</td><td>31804</td><td>3.84</td></tr><tr><td colspan="9"><strong>Household income (tertile)</strong></td></tr><tr><td>Lowest</td><td>1289265</td><td>32.53</td><td>3544</td><td>77.65</td><td>22358</td><td>73.61</td><td>1216124</td><td>2.91</td></tr><tr><td>Middle</td><td>1336367</td><td>33.72</td><td>625</td><td>13.69</td><td>5008</td><td>16.49</td><td>1270568</td><td>0.49</td></tr><tr><td>Highest</td><td>1337724</td><td>33.75</td><td>395</td><td>8.65</td><td>3008</td><td>9.90</td><td>1272918</td><td>0.31</td></tr><tr><td colspan="9"><strong>Housing type</strong></td></tr><tr><td>Multifamily</td><td>1283364</td><td>32.38</td><td>2248</td><td>49.26</td><td>11797</td><td>38.84</td><td>1216054</td><td>1.85</td></tr><tr><td>Single-family</td><td>2662463</td><td>67.18</td><td>1930</td><td>42.29</td><td>16946</td><td>55.79</td><td>2527860</td><td>0.76</td></tr><tr><td>Care home</td><td>17529</td><td>0.44</td><td>386</td><td>8.46</td><td>1631</td><td>5.37</td><td>15696</td><td>24.59</td></tr><tr><td colspan="9"><strong>Number of people under 30 in the household</strong></td></tr><tr><td>0</td><td>2079106</td><td>52.46</td><td>4244</td><td>92.99</td><td>28211</td><td>92.88</td><td>1965558</td><td>2.16</td></tr><tr><td>1</td><td>614976</td><td>15.52</td><td>180</td><td>3.94</td><td>1191</td><td>3.92</td><td>585276</td><td>0.31</td></tr><tr><td>2</td><td>870872</td><td>21.97</td><td>85</td><td>1.86</td><td>647</td><td>2.13</td><td>829379</td><td>0.10</td></tr><tr><td>3+</td><td>398402</td><td>10.05</td><td>55</td><td>1.21</td><td>325</td><td>1.07</td><td>379397</td><td>0.14</td></tr><tr><td colspan="9"><strong>m²/person in the household (crowdedness)</strong></td></tr><tr><td>0-</td><td>325441</td><td>8.21</td><td>325</td><td>7.12</td><td>1463</td><td>4.82</td><td>309194</td><td>1.05</td></tr><tr><td>20-</td><td>814282</td><td>20.55</td><td>464</td><td>10.17</td><td>2809</td><td>9.25</td><td>774226</td><td>0.60</td></tr><tr><td>30-</td><td>913084</td><td>23.04</td><td>1240</td><td>27.17</td><td>7232</td><td>23.81</td><td>865941</td><td>1.43</td></tr><tr><td>40-</td><td>1127740</td><td>28.45</td><td>1662</td><td>36.42</td><td>11264</td><td>37.08</td><td>1068381</td><td>1.56</td></tr><tr><td>60-</td><td>750691</td><td>18.94</td><td>861</td><td>18.87</td><td>7468</td><td>24.59</td><td>711339</td><td>1.21</td></tr><tr><td>Missing</td><td>32118</td><td>0.81</td><td>12</td><td>0.26</td><td>138</td><td>0.45</td><td>30530</td><td>0.39</td></tr><tr><td colspan="9"><strong>Share immigrants in DeSO (%)</strong></td></tr><tr><td>0-</td><td>1306913</td><td>32.97</td><td>958</td><td>20.99</td><td>9358</td><td>31.40</td><td>1240219</td><td>0.77</td></tr><tr><td>0.10-</td><td>943691</td><td>23.81</td><td>972</td><td>21.30</td><td>7318</td><td>24.09</td><td>895256</td><td>1.09</td></tr><tr><td>0.15-</td><td>659303</td><td>16.63</td><td>858</td><td>18.80</td><td>5003</td><td>16.47</td><td>625400</td><td>1.37</td></tr><tr><td>0.20-</td><td>556222</td><td>14.03</td><td>765</td><td>16.76</td><td>4575</td><td>15.06</td><td>527391</td><td>1.45</td></tr></tbody></table>

Continued
<table><caption>**Table 1** Continued</caption><thead><tr><th rowspan="2"></th><th colspan="2">Total</th><th colspan="2">COVID-19</th><th colspan="2">Other cause of death</th><th rowspan="2">Exposure time in years</th><th rowspan="2">COVID-19 deaths per 1000 years</th></tr><tr><th>N at 12 March 2020</th><th>%</th><th>Deaths 12 March 2020-23 February 2021</th><th>%</th><th>Deaths 12 March 2020-23 February 2021</th><th>%</th></tr></thead><tbody><tr><td>0.30-</td><td>349 234</td><td>8.81</td><td>637</td><td>13.96</td><td>2896</td><td>9.53</td><td>331 065</td><td>1.92</td></tr><tr><td>0.50-</td><td>147 993</td><td>3.73</td><td>374</td><td>8.19</td><td>1044</td><td>3.44</td><td>140 278</td><td>2.67</td></tr><tr><td>Total</td><td>3 963 356</td><td>100.0</td><td>4564</td><td>100.0</td><td>30 374</td><td>100.0</td><td>3 759 610</td><td>1.21</td></tr></tbody></table>

HIC, high-income country; LMIC, low-income and middle-income country.

aspect directly, our study shows that immigrants partnered with Swedes are slightly protected with respect to COVID-19 mortality. This suggests that lower language barriers may indeed be relevant with respect to interacting with the healthcare system. To the best of our knowledge, however, we are unaware of any additional provisions provided to non-Swedish speakers at hospitals or clinics during the pandemic.

In addition to disentangling the role of language barriers and lack of understanding of the healthcare system and recommendations in explaining the excess COVID-19 mortality among immigrants, our study provides suggestive evidence that the main explanation is differential exposure to the virus and not susceptibility.²⁰ Although it is true that Swedes partnered with a Swede show the lowest mortality, those partnered with an immigrant experience higher COVID-19 mortality. Given that Swedes do not experience language barriers or lack institutional awareness and that biological susceptibility cannot be transmitted between partners, Swedes partnered with immigrants are likely to be at either higher exposure to the virus or impacted by the social susceptibility of their partner. Swedes in mixed partnerships may be exposed to similar social environments and/or risk factors as immigrants thus placing them at a higher risk of

exposure as compared to Swedes partnered with another Swede. For example, they may have more transnational contacts or are impacted by some of the same social risk factors as immigrants. Moreover, the higher mortality experienced by natives partnered with immigrants could be related to the disadvantages faced by the immigrant partner either via discrimination or a higher exposure to the pandemic (eg, having a frontline or precarious occupation). Although this type of exposure in mixed partnerships might not be at the same level as for immigrants partnered with another immigrant (as our results with a gradient in mortality suggests).

In this study, immigrants in different family constellations show higher levels of COVID-19 deaths than the majority of natives, after adjustment for a wide range of individual-level and contextual-level factors, including education, income, housing conditions and neighbourhood immigrant density. This set of adjustments also partly accounts for a number of socially patterned chronic health conditions and comorbidities, for example, insulin resistance, hypertension, smoking and obesity, which have been suggested as risk factors for severe cases of COVID-19.¹⁷

This study has a number of contributions and strengths, First, this is the only study to date to examine

<figure><img src="image_4.png" /><figcaption>**Figure 2** HRs for the risk of dying from COVID-19, other causes of death during the pandemic, and all-cause mortality in the year prior to the pandemic by couple dyad. Model A is adjusted for age and sex only and model B includes full adjustment (reference group: native-native couples).</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>**Figure 3** HRs for the risk of dying from COVID-19, other causes of death during the pandemic and all-cause mortality in the year prior to the pandemic by couple dyad disaggregated by low-income and middle-income countries (LMIC) and high-income countries (HIC) immigrants. Model A is adjusted for age and sex only and model B includes full adjustment (reference group: native-native couples).</figcaption></figure>

sociocultural integration as the mechanism behind the disproportionate burden that COVID-19 has placed on immigrant communities, by comparing the mortality of native-native, immigrant-native and immigrant-immigrant couples in Sweden. A major strength of our study is that we have complete coverage of the total population and all deaths in Sweden from the start of the pandemic until February 2021 for both COVID-19 and remaining causes of death. Thus, our analysis does not suffer from selection into our study population. We have similar high-quality data for the year prior to the pandemic, which allows for an unbiased comparison of mortality patterns between the 2 years. The comparison between couple types with respect to mortality from all other causes during the pandemic and all-cause mortality in the year prior strengthens our findings as it demonstrates that the excess mortality from COVID-19 is observed in couples that show no excess mortality from other causes before and during the pandemic.

Despite its strengths, this study has also some limitations that are worth mentioning. Although the Swedish population registers hold high quality and have many advantages, they capture *de jure* rather than *de facto* characteristics of individuals. With respect to our measure of partnership, 82% of the couples in our data are either married or have shared children while the remaining 18% co-reside unmarried without common children. However, non-marital cohabitation is very common in Sweden, while flat-sharing is not,³⁰ and particularly among individuals above their 30s. It is therefore fair to assume that a substantive share in this remaining group is indeed cohabiting in an amorous relationship, a group that is often overlooked in international studies of health and mortality because of the lack of data. A final limitation is that we do not include information on occupation. Specifically, it has been hypothesised that immigrants are

more likely to work in 'frontline' occupations; however, recent research in Sweden has shown that occupational exposure is not a risk factor for COVID-19 mortality.³¹ Furthermore, it is worth noting that a majority of deaths are occurring among retired individuals with no attachment to the labour market.

In conclusion, our study shows that being partnered with a native does not close the gap in COVID-19 mortality with natives even after adjusting for a wide range of possible confounders on individual, couple and residential level. As such, these findings show that lack of awareness of the Swedish recommendations and language barriers are not major drivers for the excess COVID-19 mortality of immigrants. At the same time, the fact that Swedes partnered with immigrants also show excess mortality compared with Swedish couples, suggests that excess mortality among immigrants is explained by differential exposure to the virus.

**Acknowledgements** We thank Thomas Niedomysl of Region Halland, Petra Westin of the National Board of Health and Welfare and Simon Kurt of Statistics Sweden for their invaluable role in providing the data.

**Contributors** SA, MB and SJ conceived the study and were responsible for the planning. GA and MB provided the data. MB analysed the data. SA, SJ, SD, EM and MB designed the analysis with contributions from OO, MR, GA. SA, SJ, SD, EM, MB, OO and MR. GA contributed to the interpretation of the data. SA and SJ drafted the manuscript with substantive contributions from EM, SD, MB, OO, MR and GA. All authors approved the final version of the manuscript.

**Funding** The Swedish Research Council for Health, Working Life and Welfare (FORTE), grant numbers 2016-07115, 2016-07105, 2016-07128, 2019-00603, The Swedish Research Council (VR), grant number 2018-01825 and The Swedish Foundation for Humanities and Social Sciences (Riksbankens Jubileumsfond), grant M18-0214:1.

**Competing interests** None declared.

**Patient consent for publication** Not required.

**Ethics approval** This study was approved by the Central Ethical Review Board in 2020 (Dnr 2020-02199).
**Provenance and peer review** Not commissioned; externally peer reviewed.

**Data availability statement** This study is produced under the Swedish Statistics Act, where privacy concerns restrict the availability of register data for research. Aggregated data can be made available by the authors, conditional on ethical vetting. The authors access the individual-level data through Statistics Sweden's micro-online access system MONA.

**Supplemental material** This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

**Open access** This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.

ORCID iDs

Siddartha Aradhya http://orcid.org/0000-0003-3748-6270

Sol Pia Juárez http://orcid.org/0000-0001-9086-7588

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<table><caption>Supplementary table 1: Descriptive table displaying distributions of all covariables with and without missing in education and dwelling size.</caption><thead><tr><th></th><th>Study population (with missing education and dwelling size)</th><th>Study population (without missing education)</th><th>Study population (without missing dwelling size)</th></tr></thead><tbody><tr><td><strong>Couple dyads</strong></td><td></td><td></td><td></td></tr><tr><td>Native-native</td><td>75.31</td><td>75.86</td><td>75.25</td></tr><tr><td>Native-immigrant</td><td>6.18</td><td>6.21</td><td>6.19</td></tr><tr><td>Immigrant-native</td><td>6.09</td><td>5.99</td><td>6.09</td></tr><tr><td>Immigrant-immigrant</td><td>12.42</td><td>11.94</td><td>12.47</td></tr><tr><td><strong>Sex</strong></td><td></td><td></td><td></td></tr><tr><td>Man</td><td>50.26</td><td>50.21</td><td>50.26</td></tr><tr><td>Woman</td><td>49.74</td><td>49.79</td><td>49.74</td></tr><tr><td><strong>Education</strong></td><td></td><td></td><td></td></tr><tr><td>Primary</td><td>14.89</td><td>15.01</td><td>14.91</td></tr><tr><td>Secondary</td><td>42.59</td><td>42.95</td><td>42.58</td></tr><tr><td>Post-secondary</td><td>41.68</td><td>42.04</td><td>41.66</td></tr><tr><td>Missing</td><td>0.85</td><td></td><td>0.85</td></tr><tr><td><strong>Income HH disposable Inc (tertlies)</strong></td><td></td><td></td><td></td></tr><tr><td>1</td><td>32.53</td><td>32.22</td><td>32.58</td></tr><tr><td>2</td><td>33.72</td><td>33.85</td><td>33.73</td></tr><tr><td>3</td><td>33.75</td><td>33.93</td><td>33.69</td></tr><tr><td><strong>Housing type</strong></td><td></td><td></td><td></td></tr><tr><td>Multi-family dwelling</td><td>32.38</td><td>32.11</td><td>32.64</td></tr><tr><td>Single-family dwelling</td><td>67.18</td><td>67.47</td><td>66.91</td></tr><tr><td>Care home</td><td>0.44</td><td>0.42</td><td>0.45</td></tr><tr><td><strong># of individuals in the household</strong></td><td></td><td></td><td></td></tr><tr><td>2</td><td>52.46</td><td>52.47</td><td>52.50</td></tr><tr><td>3</td><td>15.52</td><td>15.50</td><td>15.53</td></tr><tr><td>4</td><td>21.97</td><td>22.02</td><td>21.93</td></tr><tr><td>5+</td><td>10.05</td><td>10.01</td><td>10.04</td></tr><tr><td><strong>Sqm per person</strong></td><td></td><td></td><td></td></tr><tr><td>0</td><td>8.21</td><td>8.08</td><td>8.28</td></tr><tr><td>-20</td><td>20.55</td><td>20.50</td><td>20.71</td></tr><tr><td>-30</td><td>23.04</td><td>23.04</td><td>23.23</td></tr><tr><td>-40</td><td>28.45</td><td>28.54</td><td>28.69</td></tr><tr><td>-60</td><td>18.94</td><td>19.03</td><td>19.10</td></tr><tr><td>Missing</td><td>0.81</td><td>0.81</td><td></td></tr><tr><td><strong>Immigrants in DeSO</strong></td><td></td><td></td><td></td></tr><tr><td>0</td><td>32.97</td><td>33.15</td><td>32.77</td></tr><tr><td>.1-</td><td>23.81</td><td>23.88</td><td>23.82</td></tr><tr><td>.15-</td><td>16.63</td><td>16.64</td><td>16.70</td></tr><tr><td>.2-</td><td>14.03</td><td>14.01</td><td>14.09</td></tr><tr><td>.3-</td><td>8.81</td><td>8.72</td><td>8.86</td></tr><tr><td>.5-</td><td>3.73</td><td>3.61</td><td>3.76</td></tr><tr><td><strong>Region of residence</strong></td><td></td><td></td><td></td></tr><tr><td>Stockholms län</td><td>21.11</td><td>21.01</td><td>21.13</td></tr></tbody></table>
<table><tr><td>Uppsala län</td><td>3.57</td><td>3.57</td><td>3.57</td></tr><tr><td>Södermanlands län</td><td>2.91</td><td>2.92</td><td>2.90</td></tr><tr><td>Östergötlands län</td><td>4.64</td><td>4.65</td><td>4.65</td></tr><tr><td>Jönköpings län</td><td>3.73</td><td>3.74</td><td>3.73</td></tr><tr><td>Kronobergs län</td><td>2.05</td><td>2.04</td><td>2.05</td></tr><tr><td>Kalmar län</td><td>2.60</td><td>2.60</td><td>2.60</td></tr><tr><td>Gotlands län</td><td>0.59</td><td>0.60</td><td>0.59</td></tr><tr><td>Blekinge län</td><td>1.68</td><td>1.68</td><td>1.67</td></tr><tr><td>Skåne län</td><td>13.24</td><td>13.20</td><td>13.24</td></tr><tr><td>Hallands län</td><td>3.59</td><td>3.60</td><td>3.59</td></tr><tr><td>Västra Götalands län</td><td>16.71</td><td>16.73</td><td>16.75</td></tr><tr><td>Värmlands län</td><td>2.89</td><td>2.88</td><td>2.89</td></tr><tr><td>Örebro län</td><td>2.95</td><td>2.96</td><td>2.95</td></tr><tr><td>Västmanlands län</td><td>2.74</td><td>2.74</td><td>2.75</td></tr><tr><td>Dalarnas län</td><td>2.95</td><td>2.96</td><td>2.93</td></tr><tr><td>Gävleborgs län</td><td>2.89</td><td>2.91</td><td>2.90</td></tr><tr><td>Västernorrlands län</td><td>2.56</td><td>2.57</td><td>2.56</td></tr><tr><td>Jämtlands län</td><td>1.29</td><td>1.30</td><td>1.28</td></tr><tr><td>Västerbottens län</td><td>2.75</td><td>2.76</td><td>2.73</td></tr><tr><td>Norrbottens län</td><td>2.56</td><td>2.57</td><td>2.54</td></tr></table>
<table><caption>Supplementary table 2: Regression results for the risk of dying from COVID-19, other causes of death during the pandemic, and all-cause mortality in the year prior to the pandemic by couple dyad</caption><thead><tr><th rowspan="3"></th><th colspan="6">Model 1: Figure 2A</th><th colspan="6">Model 2: Figure 2B</th></tr><tr><th colspan="2">COVID-19</th><th colspan="2">Other COD Mar 5, 2020- Feb 23, 2021</th><th colspan="2">All COD Mar 5, 2019 - Feb 23, 2020</th><th colspan="2">COVID-19</th><th colspan="2">Other COD Mar 5, 2020- Feb 23, 2021</th><th colspan="2">All COD Mar 5, 2019 - Feb 23, 2020</th></tr><tr><th>HR</th><th>95% CI</th><th>HR</th><th>95% CI</th><th>HR</th><th>95% CI</th><th>HR</th><th>95% CI</th><th>HR</th><th>95% CI</th><th>HR</th><th>95% CI</th></tr></thead><tbody><tr><td><strong>Partnership type</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Native-native</td><td>1.00</td><td>1.00<br>(1.25,)</td><td>1.00</td><td>1.00<br>(1.02,)</td><td>1.00</td><td>1.00<br>(1.05,)</td><td>1.00</td><td>1.00<br>(1.02,)</td><td>1.00</td><td>1.00<br>(0.98,)</td><td>1.00</td><td>1.00<br>(1.00,)</td></tr><tr><td>Native-immigrant</td><td>1.40</td><td>1.58)<br>(1.33,)</td><td>1.07</td><td>1.13)<br>(0.95,)</td><td>1.10</td><td>1.15)<br>(1.05,)</td><td>1.15</td><td>1.29)<br>(1.10,)</td><td>1.03</td><td>1.08)<br>(0.93,)</td><td>5</td><td>1.10)<br>(1.02,)</td></tr><tr><td>Immigrant-native</td><td>1.50</td><td>1.69)<br>(2.27,)</td><td>1.00</td><td>1.06)<br>(1.04,)</td><td>1.11</td><td>1.16)<br>(1.00,)</td><td>1.24</td><td>1.40)<br>(1.29,)</td><td>0.98</td><td>1.03)<br>(0.85,)</td><td>7</td><td>1.12)<br>(0.83,)</td></tr><tr><td>Immigrant-immigrant</td><td>2.47</td><td>2.69)</td><td>1.08</td><td>1.13)</td><td>1.04</td><td>1.09)</td><td>1.43</td><td>1.58)</td><td>0.90</td><td>0.94)</td><td>7</td><td>0.91)</td></tr><tr><td>Years under risk</td><td colspan="2">3,759,610</td><td colspan="2">3,759,610</td><td colspan="2">3,764,370</td><td colspan="2">3,759,610</td><td colspan="2">3,759,610</td><td colspan="2">3,764,370</td></tr><tr><td>N events</td><td colspan="2">4564</td><td colspan="2">30,374</td><td colspan="2">31,653</td><td colspan="2">4564</td><td colspan="2">30,374</td><td colspan="2">31,653</td></tr><tr><td>N</td><td colspan="2">3,963,356</td><td colspan="2">3,963,356</td><td colspan="2">3,966,345</td><td colspan="2">3,963,356</td><td colspan="2">3,963,356</td><td colspan="2">3,966,345</td></tr></tbody></table>

Model 1 includes adjustments for sex; Model 2 includes adjustments for sex, household income, education, housing type, number of individuals in the household, m²/person in the household (crowdedness), share of immigrants in the neighborhood of residence, and region of residence
<table><caption>Supplementary table 3: Regression results for the risk of dying from COVID-19, other causes of death during the pandemic, and all-cause mortality in the year prior to the pandemic by couple dyad disaggregated by LMIC and HIC immigrants.</caption><caption>Model 3: Figure 3A</caption><thead><tr><th rowspan="3"></th><th colspan="2">COVID-19</th><th colspan="2">Other COD Mar 5, 2020- Feb 23, 2021</th><th colspan="2">All COD Mar 5, 2019 - Feb 23, 2020</th><th colspan="2">COVID-19</th><th colspan="2">Other COD Mar 5, 2020- Feb 23, 2021</th><th colspan="2">All COD Mar 5, 2019 - Feb 23, 2020</th></tr><tr><th>HR</th><th>95% CI</th><th>HR</th><th>95% CI</th><th>HR</th><th>95% CI</th><th>HR</th><th>95% CI</th><th>HR</th><th>95% CI</th><th>HR</th><th>95% CI</th></tr></thead><tbody><tr><th colspan="14" style="text-align: left; font-weight: bold;">Partnership type</th></tr><tr><td>Native-native</td><td>1.00</td><td>1.00<br>(1.25,)</td><td>1.00</td><td>1.00<br>(1.02,)</td><td>1.00</td><td>1.00<br>(1.05,)</td><td>1.00</td><td>1.00<br>(1.03,)</td><td>1.00</td><td>1.00<br>(0.98,)</td><td>1.00</td><td>1.00<br>(0.99,)</td></tr><tr><td>Native-immigrant</td><td>1.41</td><td>1.58)<br>(1.27,)</td><td>1.07</td><td>1.13)<br>(0.96,)</td><td>1.10</td><td>1.15)<br>(1.07,)</td><td>1.16</td><td>1.30)<br>(1.08,)</td><td>1.03</td><td>1.08)<br>(0.94,)</td><td>1.04</td><td>1.09)<br>(1.05,)</td></tr><tr><td>HIC-native</td><td>1.44</td><td>1.64)<br>(1.34,)</td><td>1.01</td><td>1.07)<br>(1.07,)</td><td>1.13</td><td>1.19)<br>(1.03,)</td><td>1.23</td><td>1.40)<br>(0.97,)</td><td>0.99</td><td>1.05)<br>(0.95,)</td><td>1.11</td><td>1.16)<br>(0.91,)</td></tr><tr><td>HIC-immigrant</td><td>1.54</td><td>1.77)<br>(1.42,)</td><td>1.13</td><td>1.20)<br>(0.83,)</td><td>1.09</td><td>1.16)<br>(0.84,)</td><td>1.11</td><td>1.28)<br>(1.00,)</td><td>1.01</td><td>1.07)<br>(0.74,)</td><td>0.97</td><td>1.02)<br>(0.74,)</td></tr><tr><td>LMIC-native</td><td>1.91</td><td>2.57)<br>(3.25,)</td><td>0.95</td><td>1.09)<br>(0.97,)</td><td>0.96</td><td>1.09)<br>(0.93,)</td><td>1.35</td><td>1.82)<br>(1.62,)</td><td>0.85</td><td>0.98)<br>(0.72,)</td><td>0.84</td><td>0.97)<br>(0.70,)</td></tr><tr><td>LMIC-immigrant</td><td>3.60</td><td>3.99)</td><td>1.03</td><td>1.10)</td><td>0.99</td><td>1.06)</td><td>1.84</td><td>2.09)</td><td>0.77</td><td>0.83)</td><td>0.75</td><td>0.81)</td></tr><tr><td>Years under risk</td><td colspan="2">3,759,610</td><td colspan="2">3,759,610</td><td colspan="2">3,764,370</td><td colspan="2">3,759,610</td><td colspan="2">3,759,610</td><td colspan="2">3,764,370</td></tr><tr><td>N events</td><td colspan="2">4564</td><td colspan="2">30,374</td><td colspan="2">31,653</td><td colspan="2">4564</td><td colspan="2">30,374</td><td colspan="2">31,653</td></tr><tr><td>N</td><td colspan="2">3,963,356</td><td colspan="2">3,963,356</td><td colspan="2">3,966,345</td><td colspan="2">3,963,356</td><td colspan="2">3,963,356</td><td colspan="2">3,966,345</td></tr></tbody></table>
Model 3 includes adjustments for sex; Model 4 includes adjustments for sex, household income, education, housing type, number of individuals in the household, m²/person in the household (crowdedness), share of immigrants in the neighborhood of residence, and region of residence
<figure><img src="image_6.png" /><figcaption>Supplementary figure 1: Hazard Ratios for the risk of dying from COVID-19 by couple dyad, including estimates from sensitivity analyses using multiple imputations to adjust for missing education and only complete cases</figcaption></figure>
<figure><img src="image_7.png" /><figcaption>Supplementary figure 2: Hazard Ratios for the risk of dying from COVID-19, other causes of death during the pandemic, disaggregating native-immigrant couples by partner origin. Model includes full adjustment (reference group: native-native couples) (N=3,229,772)</figcaption></figure>
<figure><img src="image_8.png" /><figcaption>Supplementary figure 3: Hazard Ratios for the risk of dying from COVID-19 by couple dyads excluding second generation immigrants. Model includes full adjustment (reference group: native-native couples) (N= 3,593,764)</figcaption></figure>
<figure><img src="image_9.png" /><figcaption>Supplementary figure 4: Hazard Ratios for (A) adjusted for age and sex only and (B) further adjusted associations between immigrant-native couple type (reference group: native-native couples), COVID-19 and all-cause mortality in 2020 in Stockholm, Sweden.</figcaption></figure>

Note: This figure is based on data on all COVID-19 deaths during the period from March 12, 2020 to May 7, 2020 (149,622 person-years of observation, and 1,587 deaths).