Disparities in the potentially avoidable use of emergency services by citizenship: a two-year cross-sectional study in Italy

Disparities in the potentially avoidable use of emergency services by citizenship: a two-year cross-sectional study in Italy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Disparities in the potentially avoidable use of emergency services by citizenship: a two-year cross-sectional study in Italy Elvira Massaro, Alexander Domnich, Giancarlo Icardi, Andrea Orsi, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8680399/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background Avoidable emergency department (ED) access, though inconsistently defined and measured, is a major driver of both overcrowding and opportunity costs for healthcare systems. Among numerous factors associated with avoidable ED access, foreign citizenship has been increasingly recognized as an important predictor. Indeed, systemic and socioeconomic barriers may prevent foreign citizens from accessing primary healthcare, making the ED a primary entry point for medical advice. This study aimed to investigate disparities in avoidable ED visits among foreign and Italian citizens in Liguria, the oldest region in Europe in terms of population age. Methods In this cross-sectional study, all adult (≥ 18 years) ED visits registered in Liguria during 2023 and 2024 were eligible. Considering the lack of a standardized definition of avoidable ED visits, for the main analysis, we used both narrow (non-urgency only) and broad (non-urgency plus minor urgency) definitions based on the discharge severity codes. Entry priority codes assigned at triage were used in the sensitivity analysis. The effect of citizenship on avoidable access was quantified via logistic regression. After adjusting for confounders, interaction terms were tested to evaluate effect variations. Results Of 916,568 ED visits recorded during the study period, 14.08% involved foreign citizens. Across both definitions, foreign citizens were at higher risk ( P < 0.001) of potentially avoidable ED access, with the narrow definition showing a nearly two-fold increase (7.00% vs. 3.70%) and the broad definition similarly reflecting a significant disparity (67.88% vs. 54.71%). In the fully adjusted models, the odds ratio for foreign versus Italian citizenship was 1.628 (95% CI: 1.542–1.719) for the narrow outcome definition and 1.174 (95% CI: 1.143–1.205) for the broad definition of avoidable ED access. Furthermore, there was a significant ( P < 0.001) three-way interaction, indicating that the difference by citizenship was moderated by both sex and age, with younger foreign males being at the highest risk. These results were robust in the sensitivity analysis. Conclusion Foreign citizens, especially younger males, are at higher risk of avoidable ED access. To mitigate these disparities, policymakers should move beyond generalized approaches towards migrant-sensitive interventions tailored to specific socio-demographic intersections. Access to care Emergency department Avoidable visit Inappropriate access Immigration Migrants Healthcare disparities Italy Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Avoidable emergency department (ED) utilization arises when patients present with non-urgent conditions that do not risk clinical deterioration if treatment is postponed for hours or even days. Managing these low-acuity cases in an ED rather than in more appropriate outpatient settings results in misallocation of resources, leading to inflated healthcare expenditures, overcrowding, increased waiting times, and a lack of care continuity [ 1 ]. This concept is typically based on the assumption that a portion of ED utilization is preventable; however, the definition of avoidable ED access varies by healthcare system, as it is shaped by organizational structures, payment models, and the accessibility of alternative services [ 2 ]. Operationally, avoidable ED visits can be quantified using various algorithms, including methods based on triage and acuity scales [ 2 , 3 ], resource utilization (e.g., visits not requiring diagnostic tests or procedures) [ 4 ], ad hoc tools like the validated Emergency Department Avoidability Classification [ 5 ], and many other methods [ 3 ]. This inconsistency in definition leads to significant variability in the estimated frequency of avoidable ED visits; one systematic review reported a range of 8–62% of total visits [ 6 ], while another found a prevalence ranging from 10% to 90% [ 7 ]. Furthermore, terminology remains unstandardized, with literature also referring to “non-urgent” [ 6 ], “inappropriate” [ 7 ], and “primary care patient in ED” [ 3 ], among others. In this manuscript, we will use the term “avoidable ED access." Regardless of the specific definition applied, avoidable ED access imposes a heavy burden on healthcare systems and entails significant opportunity costs. For instance, research in Italy [ 8 ] suggests that the ED is significantly oversized to accommodate potentially avoidable visits, with only 29% of personnel costs attributed to treating truly urgent cases. Numerous factors correlate with avoidable ED access, including demographic and socioeconomic characteristics of patients, their beliefs and preferences, health literacy, and the accessibility of other health services [ 6 , 7 ]. Among these factors, immigration background and citizenship status have recently emerged as significant predictors of avoidable ED utilization, underscoring the persistent health disparities faced by communities experiencing high rates of international immigration [ 9 , 10 ]. Rising migration rates may burden public services, but the actual correlation between international immigration and increased pressure on emergency services is a subject of debate [ 10 ]. Nevertheless, foreign citizens often underutilize healthcare services due to a complex interplay of systemic and legal barriers and socioeconomic determinants. These barriers may result in a lack of access to primary healthcare. Consequently, the ED becomes the primary entry point for medical advice [ 9 ]. The evaluation of avoidable ED access among foreign and native populations may be considered as an indicator of the broader accessibility, quality, and inclusivity of the host country’s healthcare system. However, available evidence on this topic is limited and fragmented. The most recent (2024) systematic review [ 9 ] has identified only 23 studies comparing ED utilization between immigrant and host populations, of which only ten were specifically focused on avoidable ED access. The objective of this study was to explore patterns of avoidable ED access among foreign and Italian citizens and to identify potential disparities between these two groups. Methods Study design and setting This was a cross-sectional register-based study. The STROBE (strengthening the reporting of observational studies in epidemiology) checklist [ 11 ] was used as a reporting standard (see Additional file 1, Table S1 ). The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of Liguria Region (protocol n. 166/2024 of 6 June 2024, id 13819). The study was conducted in Liguria, a northern Italian region bordering France to the west. The region has one of Europe’s oldest populations, with 29.0% of its approximately 1.5 million residents aged ≥ 65 years as of 2024. A total of 155,646 residents (10.3% of the total population) did not hold Italian citizenship, a figure higher than the national average (8.9%). Notably, this non-Italian population is much younger, with only 7.2% aged ≥ 65 years. Half of the foreign citizens living in Liguria are nationals of just five countries: Albania (13.3%), Romania (13.3%), Morocco (9.7%), Ecuador (8.7%), and Bangladesh (6.1%) [ 12 ]. In Liguria, there are 17 EDs and first aid posts distributed across five local health units (LHUs). On the basis of clinical evaluation (vitals, signs, and symptoms) at triage, trained nurses assign all patients who enter the ED to one of five priority levels (henceforth referred to as “entry priority codes”): red (emergency, immediate access), orange (urgency, access within 15 min), blue (deferrable urgency, access within 60 min), green (minor urgency, access within 2 h), and white (non-urgency, access within 4 h) [ 13 ]. This scheme resembles a widely used 5-level emergency severity index (ESI), where ESI 1 is the highest priority [ 14 ]. A periodic reassessment of waiting patients may lead to updates of an initially assigned entry priority code. Upon completion of the patient’s care pathway, a final 5-level discharge severity code (critical, acute, deferrable urgency, minor urgency, non-urgency), which reflects the initial entry priority codes, is assigned by a physician to indicate the patient's final severity level [ 13 ]. Both code schemes are summarized in Fig. 1 . Discharge severity codes are not assigned to patients who left without being seen (LWBS). Data source and eligibility criteria Routinely collected, deidentified data for all ED attendances registered in Liguria throughout 2023 and 2024 were obtained from the Regional Health Authorities. Each record included patient demographics (age, sex, and citizenship), dates of ED access and discharge, entry priority code, discharge severity code, and the principal ED diagnosis, coded according to the ICD-9-CM (international classification of diseases, 9th revision, clinical modification) system. Ligurian ED data have been extensively used in previous research [ 15 , 16 ]. In this census-based study, the sample size was not determined a priori , and all consecutive ED visits recorded in the registry were eligible in order to reduce selection bias. The inclusion criteria were formulated as follows: individuals aged ≥ 18 years who accessed any ED or first aid post in Liguria between 1 January 2023 and 31 December 2024. No explicit exclusion criteria were set. Study outcome The study outcome was potentially avoidable ED access. As there is no universally accepted definition for avoidable ED visits [ 2 , 6 , 7 ], we adopted several definitions based on local regulatory frameworks, previous literature, and data availability. Specifically, the discharge severity codes were used for the main analysis. Here, potentially avoidable ED access was defined using both narrow (only non-urgency discharge severity codes) and broad (both non-urgency and minor urgency discharge severity codes) definitions. The narrow definition is expected to be more specific, while the broad definition is likely more sensitive. Previous studies used both narrow [ 17 , 18 ] and broad [ 19 ] definitions. For the sensitivity analysis, the outcome was based on the entry priority codes, which were analogously defined using narrow (only non-urgency white entry priority codes) and broad (both non-urgency white and minor urgency green entry priority codes) definitions. While entry priority codes may be less accurate than the final discharge severity codes, the analysis of the former allows for the inclusion of LWBS patients, for whom the discharge severity codes were unavailable. Figure 1 outlines the outcome definitions used. Study variables The primary independent variable was patient citizenship, dichotomized into Italian (reference category) and foreign. The latter category predominantly comprises legal residents holding a residence permit; however, it also encompasses some temporary visitors (e.g., tourists), undocumented migrants, and individuals born in Italy to foreign-born parents who have not yet acquired Italian citizenship. Since the database did not distinguish between the aforementioned types of foreign citizens, citizenship was defined based on the legal status recorded in the administrative registry at the time of the ED encounter. For exploratory purposes, foreign citizens were categorized into the following groups: European Union (EU)/European economic area (EEA)/United Kingdom (UK); Balkan non-EU; Russia and former Soviet States (non-EU); United States (US) and Canada; Latin America; Northern Africa and Western Asia; Sub-Saharan Africa; Central and Southern Asia; Eastern and South-Eastern Asia; Oceania; stateless individuals. The following variables were considered as potential confounders and effect modifiers: sex; age; year; access on weekend or public holidays; LHU; the major ICD-9-CM diagnostic blocks. All these variables, except for the ICD-9-CM diagnostic code unavailable for LWBS patients, were required entries and therefore there were no missing data. Statistical analysis Categorical variables were expressed as percentages with the exact Clopper-Pearson’s 95% confidence intervals (CIs), while the continuous variable of age was reported as mean with standard deviation (SD). Categorical and continuous variables were compared using the chi-square and t tests, respectively. The association between the potentially avoidable ED access and citizenship was reported by means of odds ratios (ORs) estimated via logistic regression. Covariates were added progressively, starting from an unadjusted model with no covariates, to conservatively (age and sex) and fully (all the predictors described earlier) adjusted models. Moreover, several interaction terms between citizenship and other covariates were tested and statistically significant terms were eventually retained. To facilitate interpretation of the interaction effects, the variable of age was mean-centered, and predicted probabilities of the potentially avoidable ED access according to citizenship, age, and sex were plotted. Model performance was compared by means of the Akaike information criterion (AIC), adjusted pseudo- R 2 , and C index. Data were analyzed in Excel v. 1808 (Microsoft, Redmond, WA, USA) and R v. 4.3.3 (R Foundation for Statistical Computing; Vienna, Austria) package rms [ 20 ]. Results Description of the study population During the study period, 916,568 ED visits (2023: 450,377; 2024: 466,191) were registered in Liguria (Fig. 1 ), of which 14.08% (95% CI: 14.02–14.15%) involved foreign citizens. For the entire cohort, the mean age of patients was 56.99 (SD 21.37) years, and 50.36% (95% CI: 50.29–50.44%) were female. About three-fourths (71.53%; 95% CI: 71.45–71.61%) of accesses occurred on weekdays, and the most frequent (23.69%; 95% CI: 23.61–23.77%) ED diagnostic block was “Injuries and poisonings” (ICD-9-CM: 800–999). As shown in Table 1 , Italian and foreign citizens differed significantly ( P < 0.001) across all variables considered, except for the calendar year ( P = 0.21). Specifically, males predominated among foreign citizens (53.68% vs. 46.32%), whereas the opposite pattern was observed among Italians (48.97% male vs. 51.03% female). Foreign citizens were on average 18.62 (95% CI: 18.53–18.72) years younger than their Italian counterparts. Similarly, significant differences were observed in the distribution of weekend accesses, diagnostic codes, and LHUs. Most (59.74%) foreign patients originated from three geographic areas, namely Northern Africa/Western Asia, EU/EEA/UK, and Latin America (Table 1 ). Table 1 Main characteristics of the study population; Liguria (Italy), 2023–2024 ( N = 916,568) Characteristic Level Citizenship, n (%) P a Italian ( N = 787,503) Foreign ( N = 129,065) Year 2023 386,749 (49.11) 63,628 (49.30) 0.21 2024 400,754 (50.89) 65,437 (50.70) Sex Male 385,675 (48.97) 69,287 (53.68) < 0.001 Female 401,828 (51.03) 59,778 (46.32) Age, years Mean (SD) 59.61 (21.07) 40.99 (21.37) < 0.001 18–44 203,919 (25.89) 82,812 (64.16) < 0.001 45–64 230,414 (29.26) 35,025 (27.14) 65–74 112,668 (14.31) 7177 (5.56) ≥ 75 240,502 (30.54) 4051 (3.14) Local health unit (LHU) LHU 1 108,108 (13.73) 18,944 (14.68) < 0.001 LHU 2 167,951 (21.33) 21,285 (16.49) LHU 3 317,951 (40.37) 58,398 (45.25) LHU 4 79,243 (10.06) 10,031 (7.77) LHU 5 114,250 (14.5) 20,407 (15.81) Weekend or holiday access No 562,326 (71.41) 93,278 (72.27) < 0.001 Yes 225,177 (28.59) 35,787 (27.73) Emergency department diagnosis (ICD-9-CM) Infectious (001–139) 11,997 (1.52) 1919 (1.49) < 0.001 Neoplasms (140–239) 1379 (0.18) 171 (0.13) Endocrine (240–279) 5981 (0.76) 564 (0.44) Blood (280–289) 6512 (0.83) 508 (0.39) Mental (290–319) 23,670 (3.01) 4075 (3.16) Nervous/sense (320–389) 58,204 (7.39) 8637 (6.69) Circulatory (390–459) 51,522 (6.54) 3286 (2.55) Respiratory (460–519) 36,818 (4.68) 5248 (4.07) Digestive (520–579) 41,718 (5.30) 7444 (5.77) Genitourinary (580–629) 21,554 (2.74) 3654 (2.83) Pregnancy (630–679) 12,024 (1.53) 5252 (4.07) Skin (680–709) 10,445 (1.33) 2412 (1.87) Musculoskeletal (710–739) 44,017 (5.59) 8151 (6.32) Signs/symptoms (780–799) 134,571 (17.09) 19,888 (15.41) Injuries/poisonings (800–999) 191,310 (24.29) 25,821 (20.01) Other/unspecified 135,781 (17.24) 32,035 (24.82) Citizenship (geographic area) EU/EEA/UK – 25,566 (19.81) – Balkans (non-EU) – 17,594 (13.63) Russia and former USSR – 7114 (5.51) Northern Africa/Western Asia – 28,359 (21.97) Sub-Saharan Africa – 10,172 (7.88) Central/Southern Asia – 12,486 (9.67) Eastern/South-Eastern Asia – 2507 (1.94) Oceania – 285 (0.22) Latin America – 23,179 (17.96) US & Canada – 1390 (1.08) Stateless – 413 (0.32) a Independent t test was used for the continuous variable of age, and chi-square test was used for all other categorical variables EEA European economic area, EU European Union, ICD-9-CM international classification of diseases 9th revision clinical modification, LHU local health unit, SD standard deviation, UK , United Kingdom, USSR Union of Soviet Socialist Republics, US United States Effects of citizenship on avoidable emergency department access Of the initial 916,568 ED accesses with an assigned entry priority code, 57,362 (6.26%; 95% CI: 6.21–6.31%) records belonged to LWBS patients. Therefore, data on the discharge severity code were available for 859,206 patients. Notably, the proportion of foreign citizens among LWBS patients was higher than in the overall population (25.85%; 95% CI: 25.49–26.21%) (Fig. 1 ). Italian and foreign citizens showed significantly ( P < 0.001) different distributions of discharge severity codes (Fig. 2 ). According to the narrow definition (non-urgency codes only), the potentially avoidable ED access rate was about twice as high among foreign citizens compared to Italian citizens (3.70% vs. 7.00%), with a crude OR of 1.961 (95% CI: 1.911–2.012). Potentially avoidable ED access proxied by the broad definition (both non-urgency and minor urgency codes) also showed a higher rate among foreign citizens (54.71% vs. 67.88%), but the effect size dropped (crude OR = 1.750; 95% CI: 1.727–1.773). Similar findings emerged when the entry priority codes were considered for the definition of potentially avoidable ED access. As shown in Fig. 2 , compared with the discharge severity codes, the entry priority codes showed a significant decrease in minor urgency green codes, which was associated with an increase in all other color codes. In this sensitivity analysis, foreign citizens showed a higher likelihood of inappropriate ED access proxied by both narrow (4.40% vs. 9.97%) and broad (41.58% vs. 54.22%) definitions. The corresponding crude ORs were 2.403 (95% CI: 2.353–2.455) and 1.664 (95% CI: 1.644–1.684), respectively. When stratified by geographic area of citizenship, a large variation of potentially avoidable ED access was observed (Fig. 3 ). For example, considering discharge severity codes and narrow outcome definition, the highest proportion of potentially avoidable ED visits was registered among citizens of Central and Southern Asia (7.44%), while this figure was lowest among individuals coming from EU/EEA/UK (4.56%). When the outcome was broadly defined, the highest proportion was recorded for stateless individuals (77.74%) and the lowest for Americans and Canadians (61.30%). Importantly, the rate of potentially avoidable ED access for every foreign geographic area exceeded that of Italian citizens (Fig. 3 ). To adjust for potential confounders, a multivariable logistic regression analysis was conducted (Table 2 ). Although both parsimoniously (Model 1) and fully adjusted (Model 2) models produced similar effect sizes, a larger number of covariates was generally associated with a better model fit and discrimination indices (see Additional file 1, Tables S2–S5). In the fully adjusted model, compared to Italian citizens, foreign ones had 63% higher odds (OR = 1.625; 95% CI: 1.580–1.671) of potentially avoidable ED access, narrowly defined according to the discharge severity codes. For the broad definition, the increase in the odds was 17% (OR = 1.172; 95% CI: 1.155–1.190). However, there was a significant ( P < 0.001) three-way interaction between citizenship, sex, and age (Model 3). While foreign citizenship remained a strong independent predictor of avoidable ED access, the significant interaction term suggests that the disparity between foreign and Italian citizens is moderated by both sex and age (Table 2 , Fig. 4 ). Specifically, foreign citizens consistently showed higher predicted probabilities of potentially avoidable ED access than Italians across the entire lifespan, with foreign males showing the highest risk. Although there was a steady decline in the predicted probability of avoidable ED access, the risk for foreign citizens declined more slowly. The disparities between groups were most pronounced for the narrow definition of potentially avoidable ED access. The sensitivity analysis based on entry priority codes produced consistent estimates (Table 2 , Fig. 4 ). Full modeling results relative to both main and sensitivity analyses are reported in Additional file 1, Tables S2–S5. Table 2 Multivariable logistic regression analysis of the association between foreign citizenship and potentially avoidable emergency department access; Liguria (Italy), 2023–2024 Variable/parameter Model 1 a Model 2 b Model 3 c b (SE) OR (95% CI) b (SE) OR (95% CI) b (SE) OR (95% CI) Main analysis : Narrow definition (non-urgency codes only) at discharge (N = 859,206) Citizenship (foreign vs. Italian) 0.455 (0.014)*** 1.577 (1.535–1.620) 0.485 (0.014)*** 1.625 (1.580–1.671) 0.487 (0.028)*** 1.628 (1.542–1.719) Sex (male vs. female) 0.099 (0.011)*** 1.104 (1.080–1.128) 0.070 (0.011)*** 1.073 (1.050–1.097) 0.036 (0.013)*** 1.036 (1.011–1.062) Age (1-year increase) d –0.012 (0.000)*** 0.988 (0.987–0.988) –0.010 (0.000)*** 0.990 (0.989–0.990) –0.012 (0.000)*** 0.988 (0.987–0.988) Citizenship × sex – – – – 0.158 (0.038)*** 1.171 (1.086–1.262) Citizenship × age – – – – 0.009 (0.001)*** 1.009 (1.007–1.012) Sex × age – – – – 0.003 (0.001)*** 1.003 (1.002–1.004) Citizenship × sex × age – – – – –0.006 (0.002)*** 0.994 (0.991–0.998) Main analysis : Broad definition (both non-urgency and minor urgency codes) at discharge (N = 859,206) Citizenship (foreign vs. Italian) 0.090 (0.007)*** 1.094 (1.079–1.110) 0.159 (0.008)*** 1.172 (1.155–1.190) 0.160 (0.014)*** 1.174 (1.143–1.205) Sex (male vs. female) –0.048 (0.005)*** 0.953 (0.945–0.962) –0.025 (0.005)*** 0.975 (0.966–0.985) –0.052 (0.005)*** 0.949 (0.939–0.959) Age (1-year increase) d –0.025 (0.000)*** 0.975 (0.975–0.975) –0.023 (0.000)*** 0.977 (0.977–0.977) –0.025 (0.000)*** 0.975 (0.975–0.975) Citizenship × sex – – – – 0.124 (0.020)*** 1.132 (1.089–1.176) Citizenship × age – – – – 0.007 (0.001)*** 1.007 (1.005–1.008) Sex × age – – – – 0.003 (0.000)*** 1.003 (1.003–1.004) Citizenship × sex × age – – – – –0.004 (0.001)*** 0.996 (0.994–0.998) Sensitivity analysis : Narrow definition (non-urgency white codes only) at entry (N = 916,568) Citizenship (foreign vs. Italian) 0.648 (0.011)*** 1.911 (1.869–1.955) 0.630 (0.012)*** 1.877 (1.834–1.921) 0.561 (0.025)*** 1.752 (1.670–1.839) Sex (male vs. female) 0.282 (0.010)*** 1.326 (1.302–1.352) 0.263 (0.010)*** 1.301 (1.276–1.326) 0.173 (0.011)*** 1.189 (1.163–1.216) Age (1-year increase) d –0.013 (0.000)*** 0.987 (0.987–0.988) –0.009 (0.000)*** 0.991 (0.991–0.992) –0.011 (0.000)*** 0.989 (0.988–0.990) Citizenship × sex – – – – 0.341 (0.032)*** 1.407 (1.321–1.498) Citizenship × age – – – – 0.013 (0.001)*** 1.013 (1.011–1.015) Sex × age – – – – 0.002 (0.001)*** 1.002 (1.001–1.003) Citizenship × sex × age – – – – –0.006 (0.001)*** 0.994 (0.991–0.997) Sensitivity analysis : Broad definition (both non-urgency white and minor urgency green codes) at entry (N = 916,568) Citizenship (foreign vs. Italian) 0.068 (0.006)*** 1.071 (1.057–1.084) 0.125 (0.007)*** 1.133 (1.117–1.148) 0.102 (0.013)*** 1.108 (1.080–1.137) Sex (male vs. female) 0.018 (0.004)*** 1.018 (1.009–1.027) 0.023 (0.005)*** 1.023 (1.013–1.033) –0.011 (0.005)* 0.989 (0.979–0.999) Age (1-year increase) d –0.025 (0.000)*** 0.975 (0.975–0.976) –0.023 (0.000)*** 0.978 (0.977–0.978) –0.025 (0.000)*** 0.975 (0.975–0.976) Citizenship × sex – – – – 0.236 (0.019)*** 1.266 (1.221–1.313) Citizenship × age – – – – 0.008 (0.001)*** 1.008 (1.007–1.009) Sex × age – – – – 0.004 (0.000)*** 1.004 (1.004–1.005) Citizenship × sex × age – – – – –0.002 (0.001)** 0.998 (0.996–0.999) a Conservatively adjusted model for age and sex only; b Fully adjusted model without interaction terms; c Fully adjusted model with interaction terms; d Age was mean-centered; *** P < 0.001, ** P < 0.01, * P < 0.05 CI confidence interval, OR odds ratio, SE standard error Discussion This study investigated the impact of citizenship on potentially avoidable ED utilization in Liguria, where demographic shifts exert significant pressure on healthcare resources. Our findings indicate that foreign citizens face a higher risk of potentially avoidable ED utilization, particularly for the lowest-priority codes. Importantly, this relationship is moderated by sex and age; a significant three-way interaction reveals that younger foreign males are the most frequent users of ED services for non-urgent issues, suggesting that the effect of citizenship is highly dependent on demographic intersections. These results highlight the need for targeted interventions rather than broad, one-size-fits-all policies. Our main finding reveals disparities in how foreign and Italian citizens use ED services in Liguria: the former group showed up to 75% increased odds of potentially avoidable ED access. With a mean population age of 52.3 years, which is the highest in Europe [ 21 ], the regional healthcare system is heavily burdened. Considering that the foreign population is much younger, a higher likelihood of using ED services for non-urgent conditions indicates a deficit in primary care accessibility for foreign citizens. Immigrants are known to face financial, legal, socio-cultural, and other barriers to healthcare access; the key barriers include inadequate language proficiency, cultural issues, poor health literacy, and limited access to information. Financial aspects, lack of mobility affecting older and disabled immigrants, and gender issues may further compromise access to primary care [ 22 ]. Despite foreign citizens making up 14% of total ED visits, which is higher than the officially registered foreign population in Liguria [ 12 ], foreign LWBS patients accounted for approximately 26%. Together, these findings suggest that while a higher proportion of foreign citizens may lack a registered general practitioner (GP) or struggle to book appointments (i.e., limited access to primary care), they may also have a misunderstanding of how triage waiting times function for non-urgent issues, which may be further exacerbated by limited language proficiency (i.e., systemic barriers within the ED). Policymakers should focus on strengthening primary care accessibility by expanding and promoting access to outpatient clinics with extended hours; simplifying the administrative process for foreign citizens to register with a GP upon arrival; enhancing multichannel educational campaigns in multiple languages; and implementing targeted outreach through employers in sectors with high foreign labor. Within the ED, deploying cultural mediators and multilingual digital kiosks to explain triage color codes, as well as enhancing the fast-track model for low-acuity patients, is advisable. Furthermore, to ensure long-term success, these efforts should be supported by digital integration between ED and primary care records. The second major finding of this study is that the effect of citizenship is moderated by sex and age, with foreign males, especially those of younger age, being at the highest risk of potentially avoidable ED access. This risk was particularly pronounced for the lowest priority codes. In Italy, immigrant males outnumber females in younger age groups, whereas the opposite occurs in the older age groups. For example, in Liguria, foreign men are about four years younger than foreign women [ 12 ]. Young foreign males have a higher propensity of being employed in high-risk jobs and consequently are at higher risk of work-related injuries, including non-urgent ones [ 23 ]. Moreover, it has also been suggested that the lower use of ED services among women may be related to the fact that women perform more GP and specialist visits, and more phone consultations than men [ 23 ]. Additionally, foreign women in Italy are generally more educated than foreign men, as they hold higher percentages of high school and university degrees [ 24 ]. In turn, individuals with higher level of educational attainment are less likely to attend ED [ 25 ]. Regarding age, younger people may have a poorer understanding of the appropriate use of the ED, less knowledge of other health services available, and beliefs that the ED is the most appropriate place to receive care [ 26 ]. In summary, age and sex should be considered in any comprehensive strategy aimed at optimizing the use of emergency healthcare resources among foreign citizens. Comparison between our findings and previous literature is complicated by both between-study heterogeneity in the definition of avoidable ED visits [ 2 , 3 , 6 , 7 ] and sociodemographic peculiarities of Liguria [ 12 ]. A systematic review of 26 studies found that individual reports of non-urgent ED visits vary widely, ranging from 8% to 62% [ 6 ]. In our study, the narrow and broad definitions approach the lower and upper bounds of that interval, respectively. Other systematic reviews [ 9 , 10 ] highlighted that most available research converges to the idea that foreign citizens are at greater risk of avoidable ED visits. On the other hand, these reviews also pointed out a mixed pattern in the association between citizenship or immigrant status and the overall usage of ED services: some primary studies found higher usage among foreign population, other studies reported higher usage among the host population, while still other studies found no association [ 9 , 10 ]. Apart from the differences in methodology (including the key definitions of both avoidable ED access and foreign population), the heterogeneity in the effect direction and magnitude is also determined by the organization of healthcare system and patients’ entitlement to use these services across countries [ 10 ]. It is therefore more appropriate to compare our findings with a few prior surveys conducted in Italy. In a study conducted in nine Italian regions (2016–2017), the age-standardized ED visit rates for individuals aged < 65 years were consistently higher among immigrants compared to Italians [ 27 ]. Specifically, rates were approximately 20% higher for both immigrant males (371.8 vs. 309.2 per 1,000) and females (365.3 vs. 299.4 per 1,000). Furthermore, the proportion of non-urgent white triage codes was significantly higher in the immigrant population, reaching 16.3% in males and 13.8% in females, compared to 9.5% and 9.2% in their Italian counterparts, respectively [ 27 ]. Similarly, between 2007 and 2010, in Reggio Emilia (Northeast Italy), the standardized access ratios for non-urgent visits were 65% higher for immigrant males and 43% higher for immigrant females [ 28 ]. While our findings align with earlier research [ 27 , 28 ], direct comparability is still limited because those studies used the former 4-level priority coding system, whereas our analysis incorporates the subsequently introduced “deferrable urgency” category. Despite the large sample size, precise point estimates, and inclusion of all adult ED visits, which minimized selection bias, this study has several limitations. The first shortcoming concerns inherent weaknesses of the dataset used, as it was primarily designed for administrative rather than clinical purposes. Although the database has been used in previous research [ 15 , 16 ], the absence of a formal validation of the underlying data warehouse means that its predictive accuracy remains unknown. Consequently, information bias (e.g., coding errors) is likely, particularly regarding ICD-9-CM discharge diagnosis codes; however, errors in patient demographics are less likely as these are typically scanned from official documents. Second, as there is no universally recognized definition of avoidable ED access [ 2 , 3 , 6 , 7 ], we adopted both a narrow (more specific) and a broad (more sensitive) definition; the true prevalence likely lies between these two estimates. Third, our models may be subject to residual confounding. Some important variables, such as residence permit status, time since arrival in Italy, language proficiency, and socioeconomic status (SES) were unavailable in the registry. Indeed, the fully adjusted models explained only 25–27% of variance. For example, assuming a lower SES among foreign citizens compared to Italians, the inclusion of SES as a covariate would likely lead to an attenuation of the observed effect sizes, as a portion of the currently estimated risk would be attributed to economic deprivation rather than citizenship alone. Fourth, because the data were fully anonymized, the unit of analysis was the ED visit rather than the unique patient, and the models do not account for individual-level clustering. In this regard, frequent ED users with avoidable visits may be systematically different from other patients [ 29 ]. Fifth, although consistent with several studies [ 9 , 10 , 27 , 28 ], our results may lack full generalizability to international contexts with divergent healthcare frameworks, particularly those operating outside the Beveridge-style system. Finally, due to the cross-sectional nature of this study, our findings represent associations and do not imply a causal relationship between citizenship and avoidable ED utilization. Conclusions In conclusion, the disparities in potentially avoidable ED access identified in this study reflect broader systemic gaps in the integration of foreign citizens into the Italian National Health Service. The role of sex and age as key moderators of healthcare-seeking behavior underscores the necessity of a nuanced and intersectional approach to healthcare planning. Future strategies should prioritize the decentralization of non-urgent care and the enhancement of cultural mediation within both the ED and primary care settings to ensure that the healthcare system is prepared for the demographic realities of an increasingly diverse and aging population. While our study provides a robust empirical baseline for understanding the demographic drivers of healthcare utilization, further longitudinal and qualitative studies are needed to incorporate individual-level socio-economic data, such as employment type and income, to further disentangle the extent to which these healthcare disparities are driven by citizenship status versus economic deprivation. Abbreviations AIC Akaike information criterion CI Confidence interval ED Emergency department EEA European economic area ESI Emergency severity index EU European Union GP General practitioner ICD-9-CM International classification of diseases, 9th revision, clinical modification LHU Local health unit LWBS Left without being seen OR Odds ratio SD Standard deviation SE Standard error SES Socioeconomic status STROBE Strengthening the reporting of observational studies in epidemiology UK United Kingdom US United States USSR Union of Soviet Socialist Republics Declarations Ethics approval and consent to participate The study was approved by the Ethics Committee of Liguria Region (protocol n. 166/2024 of 6 June 2024, id 13819). Informed consent was waived for this retrospective anonymized study. Consent for publication Not applicable. Availability of data and materials Restrictions apply to the raw data supporting the study findings; these data are not publicly available due to their sensitive nature. Competing interests The authors declare no competing interests. Funding This research was unfunded. Authors' contributions EM, DP and GI conceived and designed the study. MA and DA facilitated the formal agreement and data acquisition from local health authorities. LM was responsible the data quality. EV and EV performed data analyses, interpreted the results, and drafted the manuscript. FA and AO supervised the project. GI, AO, FA, LM, MA, DA and DP critically revised the manuscript. All authors read and approved the final manuscript. Acknowledgements EVOSH Collaborators (Bruno Buonopane, Andrea Fiorano, Federico Grammatico, Francesca Marchini, Vincenzo Paolozzi, Irene Schenone). References Mayfield CA, Geraci M, de Hernandez BU, Dulin M, Eberth JM, Merchant AT. Ambulatory care, insurance, and avoidable emergency department utilization in North Carolina. Am J Emerg Med. 2021;46:225–32. https://doi.org/10.1016/j.ajem.2020.07.034. Parkinson B, Meacock R, Checkland K, Sutton M. Clarifying the concept of avoidable emergency department attendance. J Health Serv Res Policy. 2021;26(1):68–73. https://doi.org/10.1177/1355819620921894. Bezzina AJ, Smith PB, Cromwell D, Eagar K. Primary care patients in the emergency department: who are they? A review of the definition of the 'primary care patient' in the emergency department. Emerg Med Australas. 2005;17(5–6):472–9. https://doi.org/10.1111/j.1742-6723.2005.00779.x. Hsia RY, Niedzwiecki M. Avoidable emergency department visits: a starting point. Int J Qual Health Care. 2017;29(5):642–5. https://doi.org/10.1093/intqhc/mzx081. Strum RP, Mondoux S, Mowbray FI, Griffith LE, Worster A, Tavares W, et al. Validating the Emergency Department Avoidability Classification (EDAC): A cluster randomized single-blinded agreement study. PLoS One. 2024;19(1):e0297689. https://doi.org/10.1371/journal.pone.0297689. Uscher-Pines L, Pines J, Kellermann A, Gillen E, Mehrotra A. Emergency department visits for nonurgent conditions: systematic literature review. Am J Manag Care. 2013;19(1):47–59. Carret ML, Fassa AC, Domingues MR. Inappropriate use of emergency services: a systematic review of prevalence and associated factors. Cad Saude Publica. 2009;25(1):7–28. https://doi.org/10.1590/s0102-311x2009000100002. Cremonesi P, di Bella E, Montefiori M, Persico L. The robustness and effectiveness of the triage system at times of overcrowding and the extra costs due to inappropriate use of emergency departments. Appl Health Econ Health Policy. 2015;13(5):507–14. https://doi.org/10.1007/s40258-015-0166-5. Acquadro-Pacera G, Valente M, Facci G, Molla Kiros B, Della Corte F, Barone-Adesi F, et al. Exploring differences in the utilization of the emergency department between migrant and non-migrant populations: a systematic review. BMC Public Health. 2024;24(1):963. https://doi.org/10.1186/s12889-024-18472-3. Credé SH, Such E, Mason S. International migrants' use of emergency departments in Europe compared with non-migrants' use: a systematic review. Eur J Public Health. 2018;28(1):61-73. https://doi.org/10.1093/eurpub/ckx057. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. PLoS Med. 2007;4(10):e296. https://doi.org/10.1371/journal.pmed.0040296. Italian Institute of Statistics. Demography in numbers. 2026. https://demo.istat.it/?l=it. Accessed 22 January 2026. Italian Ministry of Health. National guidelines for the in-hospital triage. 2019. Available from: https://www.salute.gov.it/imgs/C_17_pubblicazioni_3145_allegato.pdf. Accessed 22 January 2026. Tomaino L, Roncarati I, Rodríguez-Mireles S, Rivas-Wagner E, López-Valcárcel BG, La Vecchia C, et al. Emergency department and COVID-19 pandemic stress test: A comparison between two European settings. Med Princ Pract. 2025;34(6):583–92. https://doi.org/10.1159/000546166. Trucchi C, Paganino C, Orsi A, Amicizia D, Tisa V, Piazza MF, et al. Hospital and economic burden of influenza-like illness and lower respiratory tract infection in adults ≥50 years-old. BMC Health Serv Res. 2019;19(1):585. https://doi.org/10.1186/s12913-019-4412-7. Piazza MF, Amicizia D, Paganino C, Marchini F, Astengo M, Grammatico F, et al. Has clinical and epidemiological varicella burden changed over time in children? Overview on hospitalizations, comorbidities and costs from 2010 to 2017 in Italy. Vaccines (Basel). 2021;9(12):1485. https://doi.org/10.3390/vaccines9121485. Afilalo J, Marinovich A, Afilalo M, Colacone A, Léger R, Unger B, et al. Nonurgent emergency department patient characteristics and barriers to primary care. Acad Emerg Med. 2004;11(12):1302–10. https://doi.org/10.1197/j.aem.2004.08.032. Lippi Bruni M, Mammi I, Ugolini C. Does the extension of primary care practice opening hours reduce the use of emergency services? J Health Econ. 2016;50:144–55. https://doi.org/10.1016/j.jhealeco.2016.09.011. Liguoro I, Beorchia Y, Castriotta L, Rosso A, Pedduzza A, Pilotto C, et al. Analysis of factors conditioning inappropriate visits in a paediatric emergency department. Eur J Pediatr. 2023;182(12):5427–37. https://doi.org/10.1007/s00431-023-05223-6. Harrell FE Jr. rms: Regression modeling strategies. R package version 8.1-0. 2025. 2025. https://cran.r-project.org/web/packages/rms/rms.pdf. Accessed 22 January 2026. Eurostat. Population structure indicators by NUTS 2 region. 2025. https://ec.europa.eu/eurostat/databrowser/view/DEMO_R_PJANIND2__custom_1446484/default/table?lang=en. Accessed 22 January 2026. Rosano A, Dauvrin M, Buttigieg SC, Ronda E, Tafforeau J, Dias S. Migrant's access to preventive health services in five EU countries. BMC Health Serv Res. 2017;17(1):588. https://doi.org/10.1186/s12913-017-2549-9. De Luca G, Ponzo M, Andrés AR. Health care utilization by immigrants in Italy. Int J Health Care Finance Econ. 2013;13(1):1–31. https://doi.org/10.1007/s10754-012-9119-9. Italian Institute of Statistics. Educational attainment and employment returns; year 2023. 2024. Available from: https://www.istat.it/wp-content/uploads/2024/07/REPORT-livelli-istruzione.pdf. Accessed 22 January 2026. Masseria C, Giannoni M. Equity in access to health care in Italy: a disease-based approach. Eur J Public Health. 2010;20(5):504–10. https://doi.org/10.1093/eurpub/ckq029. McHale P, Wood S, Hughes K, Bellis MA, Demnitz U, Wyke S. Who uses emergency departments inappropriately and when - a national cross-sectional study using a monitoring data system. BMC Med. 2013;11:258. https://doi.org/10.1186/1741-7015-11-258. Di Napoli A, Ventura M, Spadea T, Giorgi Rossi P, Bartolini L, Battisti L, et al. Barriers to accessing primary care and appropriateness of healthcare among immigrants in Italy. Front Public Health. 2022;10:817696. https://doi.org/10.3389/fpubh.2022.817696. Bonvicini L, Broccoli S, D'Angelo S, Candela S. Emergency room services utilization in the province of Reggio Emilia: a comparison between immigrants and Italians. Epidemiol Prev. 2011;35(5–6):259–66. Thompson C, Watson T, Schull MJ, Gronsbell J, Rosella LC. Sociodemographic and health behaviour of frequent, avoidable emergency department users in Ontario, Canada: A population-based descriptive study. West J Emerg Med. 2025;26(6):1622–39. https://doi.org/10.5811/westjem.46551. Additional Declarations No competing interests reported. Supplementary Files Additionalfile1.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 20 Apr, 2026 Reviews received at journal 19 Apr, 2026 Reviewers agreed at journal 08 Apr, 2026 Reviews received at journal 18 Feb, 2026 Reviewers agreed at journal 11 Feb, 2026 Reviewers invited by journal 09 Feb, 2026 Editor invited by journal 28 Jan, 2026 Editor assigned by journal 27 Jan, 2026 Submission checks completed at journal 27 Jan, 2026 First submitted to journal 23 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8680399","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":589843775,"identity":"b1d34a22-9de4-4ad0-abd1-ccca85fd975f","order_by":0,"name":"Elvira Massaro","email":"","orcid":"","institution":"University of Genoa","correspondingAuthor":false,"prefix":"","firstName":"Elvira","middleName":"","lastName":"Massaro","suffix":""},{"id":589843779,"identity":"1c973b22-641e-4990-85b3-197f340644ea","order_by":1,"name":"Alexander Domnich","email":"","orcid":"","institution":"IRCCS Azienda Ospedaliera Metropolitana","correspondingAuthor":false,"prefix":"","firstName":"Alexander","middleName":"","lastName":"Domnich","suffix":""},{"id":589843781,"identity":"af079c61-0893-4ddd-83e7-df9862d62346","order_by":2,"name":"Giancarlo Icardi","email":"","orcid":"","institution":"University of Genoa","correspondingAuthor":false,"prefix":"","firstName":"Giancarlo","middleName":"","lastName":"Icardi","suffix":""},{"id":589843789,"identity":"f2480d2f-afe3-40fc-aa16-449a967e9f21","order_by":3,"name":"Andrea Orsi","email":"","orcid":"","institution":"University of Genoa","correspondingAuthor":false,"prefix":"","firstName":"Andrea","middleName":"","lastName":"Orsi","suffix":""},{"id":589843791,"identity":"bd210edf-8c33-4124-884f-5ad3f94b5e06","order_by":4,"name":"Filippo Ansaldi","email":"","orcid":"","institution":"University of Genoa","correspondingAuthor":false,"prefix":"","firstName":"Filippo","middleName":"","lastName":"Ansaldi","suffix":""},{"id":589843793,"identity":"d731c8f4-835e-4e9d-b7f1-2e6cc85ae0db","order_by":5,"name":"Lucia Martines","email":"","orcid":"","institution":"University of Genoa","correspondingAuthor":false,"prefix":"","firstName":"Lucia","middleName":"","lastName":"Martines","suffix":""},{"id":589843795,"identity":"13cf2fb3-026e-4834-99a8-c549b909f216","order_by":6,"name":"Matteo Astengo","email":"","orcid":"","institution":"IRCCS Azienda Ospedaliera Metropolitana","correspondingAuthor":false,"prefix":"","firstName":"Matteo","middleName":"","lastName":"Astengo","suffix":""},{"id":589843797,"identity":"60d36f47-6042-444d-b61e-d1ee250201ba","order_by":7,"name":"Daniela Amicizia","email":"","orcid":"","institution":"University of Genoa","correspondingAuthor":false,"prefix":"","firstName":"Daniela","middleName":"","lastName":"Amicizia","suffix":""},{"id":589843798,"identity":"88cb84a6-e329-4d37-abbb-1ef46154cb08","order_by":8,"name":"Donatella Panatto","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvUlEQVRIiWNgGAWjYBADOQYGxgYgLUGk+gMJDMYwLUTqAWpJbICyCWsxZz978PPHHzbpG243N7/4wGBRR1CLZU9essSBhLTcDXcOtlnOIMZhBgdyDIBaDuduuJHYZsxDlJbzb4x/ALWkG4C0/CFKy40cM5AtCUAtzY+JCjHLGW/MLM6kpRnOBNrC2GMgIdlASIs5f47xjQobG3m+G+mPP/yoqOMn7DAkNpsECpcYLcwfiNAwCkbBKBgFIxAAAOZAPnx37nknAAAAAElFTkSuQmCC","orcid":"","institution":"University of Genoa","correspondingAuthor":true,"prefix":"","firstName":"Donatella","middleName":"","lastName":"Panatto","suffix":""},{"id":589843804,"identity":"83dbaf27-3fde-4105-b687-f1220ded767c","order_by":9,"name":"EVOSH Collaborators","email":"","orcid":"","institution":"IRCCS Azienda Ospedaliera Metropolitana","correspondingAuthor":false,"prefix":"","firstName":"EVOSH","middleName":"","lastName":"Collaborators","suffix":""}],"badges":[],"createdAt":"2026-01-23 14:53:58","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8680399/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8680399/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102747690,"identity":"582d8805-c5fa-4d7f-adea-34e1038eadc2","added_by":"auto","created_at":"2026-02-16 09:05:14","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":62846,"visible":true,"origin":"","legend":"\u003cp\u003eSummary of entry priority codes, discharge severity codes, definitions of potentially avoidable emergency department access used in the main and sensitivity analyses and participant flow diagram\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLegend:\u003c/em\u003e At triage, all patients who enter the emergency department are assigned to one of five entry priority codes, where the white non-urgency code represents the lowest priority and the red emergency code represents the highest priority. At the end of the encounter, all patients who did not leave without being seen (LWBS) are assigned a 5-level discharge severity code, which resembles the initial entry priority code. Discharge severity codes were used for the main analysis, while the entry priority codes were used for the sensitivity analysis. Potentially avoidable emergency department access was defined using both narrow (non-urgency codes only) and broad (non-urgency plus minor urgency codes) definitions.\u003c/p\u003e","description":"","filename":"Binder11.png","url":"https://assets-eu.researchsquare.com/files/rs-8680399/v1/51a4603a92dc3a29ec8d14ef.png"},{"id":102606516,"identity":"4e51ac53-b3ce-4e86-8c72-ae63dee8e90a","added_by":"auto","created_at":"2026-02-13 14:04:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":87322,"visible":true,"origin":"","legend":"\u003cp\u003eDischarge severity codes and entry priority codes assigned during emergency department visits by Italian (inner ring) and foreign (outer ring) citizens, by year; Liguria (Italy), 2023–2024\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLegend:\u003c/em\u003e Sector colors correspond to the 5-level discharge severity codes and entry priority codes used in Italy: red (critical discharge/emergency), orange (acute discharge/urgency), blue (deferrable urgency), green (minor urgency), and white (non-urgency).\u003c/p\u003e","description":"","filename":"Binder12.png","url":"https://assets-eu.researchsquare.com/files/rs-8680399/v1/feea9079df490117fec06b90.png"},{"id":102606515,"identity":"7f7cf8f9-903a-4e4c-a91a-b005ca434860","added_by":"auto","created_at":"2026-02-13 14:04:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":227497,"visible":true,"origin":"","legend":"\u003cp\u003eProportions of severity codes and entry priority codes assigned during emergency department visits, by geographic area of citizenship; Liguria (Italy), 2023–2024\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLegend:\u003c/em\u003e The main analysis is based on the discharge severity codes, while the entry priority codes were used for the sensitivity analysis. Potentially avoidable emergency department access was defined using both narrow (non-urgency codes only) and broad (non-urgency plus minor urgency codes) definitions.\u003c/p\u003e","description":"","filename":"Binder13.png","url":"https://assets-eu.researchsquare.com/files/rs-8680399/v1/5344f0d68a33ae35bf777690.png"},{"id":102606517,"identity":"f72b5aa7-d382-4c20-975d-dfaa9f174c3c","added_by":"auto","created_at":"2026-02-13 14:04:28","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":48750,"visible":true,"origin":"","legend":"\u003cp\u003ePredicted probabilities of potentially avoidable emergency department access by citizenship, age, and sex; Liguria (Italy), 2023–2024\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLegend:\u003c/em\u003e The main analysis is based on the discharge severity codes, while the entry priority codes were used for the sensitivity analysis. Potentially avoidable emergency department access was defined using both narrow (non-urgency codes only) and broad (non-urgency plus minor urgency codes) definitions. Predicted probabilities were estimated from the fully adjusted models with interaction terms (Model 3) reported in Table 2 and Tables S2–S5, holding other variables at their reference level (year 2023, local health unit 1, access on workdays, ICD-9-CM category of infectious diseases).\u003c/p\u003e","description":"","filename":"Binder14.png","url":"https://assets-eu.researchsquare.com/files/rs-8680399/v1/52c8ef2d1c6fbb816af89c7b.png"},{"id":102750705,"identity":"71ca9543-7744-4f49-a9b1-481b289d8564","added_by":"auto","created_at":"2026-02-16 09:21:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1438741,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8680399/v1/e12ec5f6-71f7-4b03-bcbd-3cda2d02c90d.pdf"},{"id":102606524,"identity":"7683e84b-090a-4ba6-8364-aa8309865ce5","added_by":"auto","created_at":"2026-02-13 14:04:28","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":51871,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8680399/v1/9712f6105ab1cd97c11dba9d.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Disparities in the potentially avoidable use of emergency services by citizenship: a two-year cross-sectional study in Italy","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAvoidable emergency department (ED) utilization arises when patients present with non-urgent conditions that do not risk clinical deterioration if treatment is postponed for hours or even days. Managing these low-acuity cases in an ED rather than in more appropriate outpatient settings results in misallocation of resources, leading to inflated healthcare expenditures, overcrowding, increased waiting times, and a lack of care continuity [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. This concept is typically based on the assumption that a portion of ED utilization is preventable; however, the definition of avoidable ED access varies by healthcare system, as it is shaped by organizational structures, payment models, and the accessibility of alternative services [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Operationally, avoidable ED visits can be quantified using various algorithms, including methods based on triage and acuity scales [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], resource utilization (e.g., visits not requiring diagnostic tests or procedures) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], \u003cem\u003ead hoc\u003c/em\u003e tools like the validated Emergency Department Avoidability Classification [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], and many other methods [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This inconsistency in definition leads to significant variability in the estimated frequency of avoidable ED visits; one systematic review reported a range of 8\u0026ndash;62% of total visits [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], while another found a prevalence ranging from 10% to 90% [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Furthermore, terminology remains unstandardized, with literature also referring to \u0026ldquo;non-urgent\u0026rdquo; [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], \u0026ldquo;inappropriate\u0026rdquo; [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], and \u0026ldquo;primary care patient in ED\u0026rdquo; [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], among others. In this manuscript, we will use the term \u0026ldquo;avoidable ED access.\" Regardless of the specific definition applied, avoidable ED access imposes a heavy burden on healthcare systems and entails significant opportunity costs. For instance, research in Italy [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] suggests that the ED is significantly oversized to accommodate potentially avoidable visits, with only 29% of personnel costs attributed to treating truly urgent cases.\u003c/p\u003e \u003cp\u003eNumerous factors correlate with avoidable ED access, including demographic and socioeconomic characteristics of patients, their beliefs and preferences, health literacy, and the accessibility of other health services [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Among these factors, immigration background and citizenship status have recently emerged as significant predictors of avoidable ED utilization, underscoring the persistent health disparities faced by communities experiencing high rates of international immigration [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Rising migration rates may burden public services, but the actual correlation between international immigration and increased pressure on emergency services is a subject of debate [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Nevertheless, foreign citizens often underutilize healthcare services due to a complex interplay of systemic and legal barriers and socioeconomic determinants. These barriers may result in a lack of access to primary healthcare. Consequently, the ED becomes the primary entry point for medical advice [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe evaluation of avoidable ED access among foreign and native populations may be considered as an indicator of the broader accessibility, quality, and inclusivity of the host country\u0026rsquo;s healthcare system. However, available evidence on this topic is limited and fragmented. The most recent (2024) systematic review [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] has identified only 23 studies comparing ED utilization between immigrant and host populations, of which only ten were specifically focused on avoidable ED access. The objective of this study was to explore patterns of avoidable ED access among foreign and Italian citizens and to identify potential disparities between these two groups.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and setting\u003c/h2\u003e \u003cp\u003eThis was a cross-sectional register-based study. The STROBE (strengthening the reporting of observational studies in epidemiology) checklist [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] was used as a reporting standard (see Additional file 1, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of Liguria Region (protocol n. 166/2024 of 6 June 2024, id 13819).\u003c/p\u003e \u003cp\u003eThe study was conducted in Liguria, a northern Italian region bordering France to the west. The region has one of Europe\u0026rsquo;s oldest populations, with 29.0% of its approximately 1.5\u0026nbsp;million residents aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years as of 2024. A total of 155,646 residents (10.3% of the total population) did not hold Italian citizenship, a figure higher than the national average (8.9%). Notably, this non-Italian population is much younger, with only 7.2% aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years. Half of the foreign citizens living in Liguria are nationals of just five countries: Albania (13.3%), Romania (13.3%), Morocco (9.7%), Ecuador (8.7%), and Bangladesh (6.1%) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn Liguria, there are 17 EDs and first aid posts distributed across five local health units (LHUs). On the basis of clinical evaluation (vitals, signs, and symptoms) at triage, trained nurses assign all patients who enter the ED to one of five priority levels (henceforth referred to as \u0026ldquo;entry priority codes\u0026rdquo;): red (emergency, immediate access), orange (urgency, access within 15 min), blue (deferrable urgency, access within 60 min), green (minor urgency, access within 2 h), and white (non-urgency, access within 4 h) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. This scheme resembles a widely used 5-level emergency severity index (ESI), where ESI 1 is the highest priority [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. A periodic reassessment of waiting patients may lead to updates of an initially assigned entry priority code. Upon completion of the patient\u0026rsquo;s care pathway, a final 5-level discharge severity code (critical, acute, deferrable urgency, minor urgency, non-urgency), which reflects the initial entry priority codes, is assigned by a physician to indicate the patient's final severity level [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Both code schemes are summarized in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Discharge severity codes are not assigned to patients who left without being seen (LWBS).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData source and eligibility criteria\u003c/h3\u003e\n\u003cp\u003eRoutinely collected, deidentified data for all ED attendances registered in Liguria throughout 2023 and 2024 were obtained from the Regional Health Authorities. Each record included patient demographics (age, sex, and citizenship), dates of ED access and discharge, entry priority code, discharge severity code, and the principal ED diagnosis, coded according to the ICD-9-CM (international classification of diseases, 9th revision, clinical modification) system. Ligurian ED data have been extensively used in previous research [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this census-based study, the sample size was not determined \u003cem\u003ea priori\u003c/em\u003e, and all consecutive ED visits recorded in the registry were eligible in order to reduce selection bias. The inclusion criteria were formulated as follows: individuals aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years who accessed any ED or first aid post in Liguria between 1 January 2023 and 31 December 2024. No explicit exclusion criteria were set.\u003c/p\u003e\n\u003ch3\u003eStudy outcome\u003c/h3\u003e\n\u003cp\u003eThe study outcome was potentially avoidable ED access. As there is no universally accepted definition for avoidable ED visits [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], we adopted several definitions based on local regulatory frameworks, previous literature, and data availability. Specifically, the discharge severity codes were used for the main analysis. Here, potentially avoidable ED access was defined using both narrow (only non-urgency discharge severity codes) and broad (both non-urgency and minor urgency discharge severity codes) definitions. The narrow definition is expected to be more specific, while the broad definition is likely more sensitive. Previous studies used both narrow [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] and broad [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] definitions. For the sensitivity analysis, the outcome was based on the entry priority codes, which were analogously defined using narrow (only non-urgency white entry priority codes) and broad (both non-urgency white and minor urgency green entry priority codes) definitions. While entry priority codes may be less accurate than the final discharge severity codes, the analysis of the former allows for the inclusion of LWBS patients, for whom the discharge severity codes were unavailable. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e outlines the outcome definitions used.\u003c/p\u003e\n\u003ch3\u003eStudy variables\u003c/h3\u003e\n\u003cp\u003eThe primary independent variable was patient citizenship, dichotomized into Italian (reference category) and foreign. The latter category predominantly comprises legal residents holding a residence permit; however, it also encompasses some temporary visitors (e.g., tourists), undocumented migrants, and individuals born in Italy to foreign-born parents who have not yet acquired Italian citizenship. Since the database did not distinguish between the aforementioned types of foreign citizens, citizenship was defined based on the legal status recorded in the administrative registry at the time of the ED encounter. For exploratory purposes, foreign citizens were categorized into the following groups: European Union (EU)/European economic area (EEA)/United Kingdom (UK); Balkan non-EU; Russia and former Soviet States (non-EU); United States (US) and Canada; Latin America; Northern Africa and Western Asia; Sub-Saharan Africa; Central and Southern Asia; Eastern and South-Eastern Asia; Oceania; stateless individuals.\u003c/p\u003e \u003cp\u003eThe following variables were considered as potential confounders and effect modifiers: sex; age; year; access on weekend or public holidays; LHU; the major ICD-9-CM diagnostic blocks. All these variables, except for the ICD-9-CM diagnostic code unavailable for LWBS patients, were required entries and therefore there were no missing data.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eCategorical variables were expressed as percentages with the exact Clopper-Pearson\u0026rsquo;s 95% confidence intervals (CIs), while the continuous variable of age was reported as mean with standard deviation (SD). Categorical and continuous variables were compared using the chi-square and \u003cem\u003et\u003c/em\u003e tests, respectively. The association between the potentially avoidable ED access and citizenship was reported by means of odds ratios (ORs) estimated via logistic regression. Covariates were added progressively, starting from an unadjusted model with no covariates, to conservatively (age and sex) and fully (all the predictors described earlier) adjusted models. Moreover, several interaction terms between citizenship and other covariates were tested and statistically significant terms were eventually retained. To facilitate interpretation of the interaction effects, the variable of age was mean-centered, and predicted probabilities of the potentially avoidable ED access according to citizenship, age, and sex were plotted. Model performance was compared by means of the Akaike information criterion (AIC), adjusted pseudo-\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e, and \u003cem\u003eC\u003c/em\u003e index.\u003c/p\u003e \u003cp\u003eData were analyzed in Excel v. 1808 (Microsoft, Redmond, WA, USA) and R v. 4.3.3 (R Foundation for Statistical Computing; Vienna, Austria) package rms [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eDescription of the study population\u003c/h2\u003e \u003cp\u003eDuring the study period, 916,568 ED visits (2023: 450,377; 2024: 466,191) were registered in Liguria (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), of which 14.08% (95% CI: 14.02\u0026ndash;14.15%) involved foreign citizens. For the entire cohort, the mean age of patients was 56.99 (SD 21.37) years, and 50.36% (95% CI: 50.29\u0026ndash;50.44%) were female. About three-fourths (71.53%; 95% CI: 71.45\u0026ndash;71.61%) of accesses occurred on weekdays, and the most frequent (23.69%; 95% CI: 23.61\u0026ndash;23.77%) ED diagnostic block was \u0026ldquo;Injuries and poisonings\u0026rdquo; (ICD-9-CM: 800\u0026ndash;999).\u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Italian and foreign citizens differed significantly (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) across all variables considered, except for the calendar year (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.21). Specifically, males predominated among foreign citizens (53.68% vs. 46.32%), whereas the opposite pattern was observed among Italians (48.97% male vs. 51.03% female). Foreign citizens were on average 18.62 (95% CI: 18.53\u0026ndash;18.72) years younger than their Italian counterparts. Similarly, significant differences were observed in the distribution of weekend accesses, diagnostic codes, and LHUs. Most (59.74%) foreign patients originated from three geographic areas, namely Northern Africa/Western Asia, EU/EEA/UK, and Latin America (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMain characteristics of the study population; Liguria (Italy), 2023\u0026ndash;2024 (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;916,568)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLevel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eCitizenship, \u003cem\u003en\u003c/em\u003e (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eItalian (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;787,503)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eForeign (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;129,065)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e386,749 (49.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63,628 (49.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e400,754 (50.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65,437 (50.70)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e385,675 (48.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69,287 (53.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e401,828 (51.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59,778 (46.32)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eAge, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.61 (21.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40.99 (21.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e203,919 (25.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82,812 (64.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45\u0026ndash;64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e230,414 (29.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35,025 (27.14)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65\u0026ndash;74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e112,668 (14.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7177 (5.56)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e240,502 (30.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4051 (3.14)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eLocal health unit (LHU)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLHU 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e108,108 (13.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18,944 (14.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLHU 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e167,951 (21.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21,285 (16.49)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLHU 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e317,951 (40.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58,398 (45.25)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLHU 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79,243 (10.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10,031 (7.77)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLHU 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e114,250 (14.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20,407 (15.81)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWeekend or holiday access\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e562,326 (71.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93,278 (72.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e225,177 (28.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35,787 (27.73)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"15\" rowspan=\"16\"\u003e \u003cp\u003eEmergency department diagnosis (ICD-9-CM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInfectious (001\u0026ndash;139)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11,997 (1.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1919 (1.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"15\" rowspan=\"16\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNeoplasms (140\u0026ndash;239)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1379 (0.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e171 (0.13)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEndocrine (240\u0026ndash;279)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5981 (0.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e564 (0.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlood (280\u0026ndash;289)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6512 (0.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e508 (0.39)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMental (290\u0026ndash;319)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23,670 (3.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4075 (3.16)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNervous/sense (320\u0026ndash;389)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58,204 (7.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8637 (6.69)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCirculatory (390\u0026ndash;459)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51,522 (6.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3286 (2.55)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRespiratory (460\u0026ndash;519)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36,818 (4.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5248 (4.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDigestive (520\u0026ndash;579)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41,718 (5.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7444 (5.77)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGenitourinary (580\u0026ndash;629)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21,554 (2.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3654 (2.83)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePregnancy (630\u0026ndash;679)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12,024 (1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5252 (4.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSkin (680\u0026ndash;709)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10,445 (1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2412 (1.87)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMusculoskeletal (710\u0026ndash;739)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44,017 (5.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8151 (6.32)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSigns/symptoms (780\u0026ndash;799)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e134,571 (17.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19,888 (15.41)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInjuries/poisonings (800\u0026ndash;999)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e191,310 (24.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25,821 (20.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther/unspecified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e135,781 (17.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32,035 (24.82)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"10\" rowspan=\"11\"\u003e \u003cp\u003eCitizenship (geographic area)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEU/EEA/UK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25,566 (19.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"10\" rowspan=\"11\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBalkans (non-EU)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17,594 (13.63)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRussia and former USSR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7114 (5.51)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNorthern Africa/Western Asia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28,359 (21.97)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSub-Saharan Africa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10,172 (7.88)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCentral/Southern Asia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12,486 (9.67)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEastern/South-Eastern Asia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2507 (1.94)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOceania\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e285 (0.22)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLatin America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23,179 (17.96)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUS \u0026amp; Canada\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1390 (1.08)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStateless\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e413 (0.32)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ea\u003c/sup\u003e Independent \u003cem\u003et\u003c/em\u003e test was used for the continuous variable of age, and chi-square test was used for all other categorical variables\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cem\u003eEEA\u003c/em\u003e European economic area, \u003cem\u003eEU\u003c/em\u003e European Union, \u003cem\u003eICD-9-CM\u003c/em\u003e international classification of diseases 9th revision clinical modification, \u003cem\u003eLHU\u003c/em\u003e local health unit, \u003cem\u003eSD\u003c/em\u003e standard deviation, \u003cem\u003eUK\u003c/em\u003e, United Kingdom, \u003cem\u003eUSSR\u003c/em\u003e Union of Soviet Socialist Republics, \u003cem\u003eUS\u003c/em\u003e United States\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEffects of citizenship on avoidable emergency department access\u003c/h3\u003e\n\u003cp\u003eOf the initial 916,568 ED accesses with an assigned entry priority code, 57,362 (6.26%; 95% CI: 6.21\u0026ndash;6.31%) records belonged to LWBS patients. Therefore, data on the discharge severity code were available for 859,206 patients. Notably, the proportion of foreign citizens among LWBS patients was higher than in the overall population (25.85%; 95% CI: 25.49\u0026ndash;26.21%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eItalian and foreign citizens showed significantly (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) different distributions of discharge severity codes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). According to the narrow definition (non-urgency codes only), the potentially avoidable ED access rate was about twice as high among foreign citizens compared to Italian citizens (3.70% vs. 7.00%), with a crude OR of 1.961 (95% CI: 1.911\u0026ndash;2.012). Potentially avoidable ED access proxied by the broad definition (both non-urgency and minor urgency codes) also showed a higher rate among foreign citizens (54.71% vs. 67.88%), but the effect size dropped (crude OR\u0026thinsp;=\u0026thinsp;1.750; 95% CI: 1.727\u0026ndash;1.773).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSimilar findings emerged when the entry priority codes were considered for the definition of potentially avoidable ED access. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, compared with the discharge severity codes, the entry priority codes showed a significant decrease in minor urgency green codes, which was associated with an increase in all other color codes. In this sensitivity analysis, foreign citizens showed a higher likelihood of inappropriate ED access proxied by both narrow (4.40% vs. 9.97%) and broad (41.58% vs. 54.22%) definitions. The corresponding crude ORs were 2.403 (95% CI: 2.353\u0026ndash;2.455) and 1.664 (95% CI: 1.644\u0026ndash;1.684), respectively.\u003c/p\u003e \u003cp\u003eWhen stratified by geographic area of citizenship, a large variation of potentially avoidable ED access was observed (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). For example, considering discharge severity codes and narrow outcome definition, the highest proportion of potentially avoidable ED visits was registered among citizens of Central and Southern Asia (7.44%), while this figure was lowest among individuals coming from EU/EEA/UK (4.56%). When the outcome was broadly defined, the highest proportion was recorded for stateless individuals (77.74%) and the lowest for Americans and Canadians (61.30%). Importantly, the rate of potentially avoidable ED access for every foreign geographic area exceeded that of Italian citizens (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo adjust for potential confounders, a multivariable logistic regression analysis was conducted (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Although both parsimoniously (Model 1) and fully adjusted (Model 2) models produced similar effect sizes, a larger number of covariates was generally associated with a better model fit and discrimination indices (see Additional file 1, Tables S2\u0026ndash;S5). In the fully adjusted model, compared to Italian citizens, foreign ones had 63% higher odds (OR\u0026thinsp;=\u0026thinsp;1.625; 95% CI: 1.580\u0026ndash;1.671) of potentially avoidable ED access, narrowly defined according to the discharge severity codes. For the broad definition, the increase in the odds was 17% (OR\u0026thinsp;=\u0026thinsp;1.172; 95% CI: 1.155\u0026ndash;1.190). However, there was a significant (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) three-way interaction between citizenship, sex, and age (Model 3). While foreign citizenship remained a strong independent predictor of avoidable ED access, the significant interaction term suggests that the disparity between foreign and Italian citizens is moderated by both sex and age (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Specifically, foreign citizens consistently showed higher predicted probabilities of potentially avoidable ED access than Italians across the entire lifespan, with foreign males showing the highest risk. Although there was a steady decline in the predicted probability of avoidable ED access, the risk for foreign citizens declined more slowly. The disparities between groups were most pronounced for the narrow definition of potentially avoidable ED access. The sensitivity analysis based on entry priority codes produced consistent estimates (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Full modeling results relative to both main and sensitivity analyses are reported in Additional file 1, Tables S2\u0026ndash;S5.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariable logistic regression analysis of the association between foreign citizenship and potentially avoidable emergency department access; Liguria (Italy), 2023\u0026ndash;2024\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable/parameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eModel 1 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eModel 2 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eModel 3 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eb\u003c/em\u003e (SE)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eb\u003c/em\u003e (SE)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eb\u003c/em\u003e (SE)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMain analysis\u003c/b\u003e: \u003cem\u003eNarrow definition (non-urgency codes only) at discharge (N\u0026thinsp;=\u0026thinsp;859,206)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCitizenship (foreign vs. Italian)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.455 (0.014)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.577 (1.535\u0026ndash;1.620)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.485 (0.014)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.625 (1.580\u0026ndash;1.671)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.487 (0.028)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.628 (1.542\u0026ndash;1.719)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (male vs. female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.099 (0.011)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.104 (1.080\u0026ndash;1.128)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.070 (0.011)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.073 (1.050\u0026ndash;1.097)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.036 (0.013)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.036 (1.011\u0026ndash;1.062)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (1-year increase) \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;0.012 (0.000)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.988 (0.987\u0026ndash;0.988)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;0.010 (0.000)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.990 (0.989\u0026ndash;0.990)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026ndash;0.012 (0.000)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.988 (0.987\u0026ndash;0.988)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCitizenship \u0026times; sex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.158 (0.038)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.171 (1.086\u0026ndash;1.262)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCitizenship \u0026times; age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.009 (0.001)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.009 (1.007\u0026ndash;1.012)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex \u0026times; age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.003 (0.001)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.003 (1.002\u0026ndash;1.004)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCitizenship \u0026times; sex \u0026times; age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026ndash;0.006 (0.002)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.994 (0.991\u0026ndash;0.998)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMain analysis\u003c/b\u003e: \u003cem\u003eBroad definition (both non-urgency and minor urgency codes) at discharge (N\u0026thinsp;=\u0026thinsp;859,206)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCitizenship (foreign vs. Italian)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.090 (0.007)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.094 (1.079\u0026ndash;1.110)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.159 (0.008)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.172 (1.155\u0026ndash;1.190)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.160 (0.014)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.174 (1.143\u0026ndash;1.205)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (male vs. female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;0.048 (0.005)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.953 (0.945\u0026ndash;0.962)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;0.025 (0.005)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.975 (0.966\u0026ndash;0.985)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026ndash;0.052 (0.005)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.949 (0.939\u0026ndash;0.959)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (1-year increase) \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;0.025 (0.000)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.975 (0.975\u0026ndash;0.975)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;0.023 (0.000)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.977 (0.977\u0026ndash;0.977)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026ndash;0.025 (0.000)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.975 (0.975\u0026ndash;0.975)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCitizenship \u0026times; sex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.124 (0.020)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.132 (1.089\u0026ndash;1.176)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCitizenship \u0026times; age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.007 (0.001)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.007 (1.005\u0026ndash;1.008)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex \u0026times; age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.003 (0.000)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.003 (1.003\u0026ndash;1.004)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCitizenship \u0026times; sex \u0026times; age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026ndash;0.004 (0.001)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.996 (0.994\u0026ndash;0.998)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSensitivity analysis\u003c/b\u003e: \u003cem\u003eNarrow definition (non-urgency white codes only) at entry (N\u0026thinsp;=\u0026thinsp;916,568)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCitizenship (foreign vs. Italian)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.648 (0.011)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.911 (1.869\u0026ndash;1.955)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.630 (0.012)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.877 (1.834\u0026ndash;1.921)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.561 (0.025)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.752 (1.670\u0026ndash;1.839)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (male vs. female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.282 (0.010)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.326 (1.302\u0026ndash;1.352)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.263 (0.010)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.301 (1.276\u0026ndash;1.326)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.173 (0.011)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.189 (1.163\u0026ndash;1.216)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (1-year increase) \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;0.013 (0.000)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.987 (0.987\u0026ndash;0.988)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;0.009 (0.000)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.991 (0.991\u0026ndash;0.992)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026ndash;0.011 (0.000)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.989 (0.988\u0026ndash;0.990)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCitizenship \u0026times; sex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.341 (0.032)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.407 (1.321\u0026ndash;1.498)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCitizenship \u0026times; age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.013 (0.001)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.013 (1.011\u0026ndash;1.015)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex \u0026times; age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.002 (0.001)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.002 (1.001\u0026ndash;1.003)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCitizenship \u0026times; sex \u0026times; age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026ndash;0.006 (0.001)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.994 (0.991\u0026ndash;0.997)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSensitivity analysis\u003c/b\u003e: \u003cem\u003eBroad definition (both non-urgency white and minor urgency green codes) at entry (N\u0026thinsp;=\u0026thinsp;916,568)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCitizenship (foreign vs. Italian)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.068 (0.006)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.071 (1.057\u0026ndash;1.084)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.125 (0.007)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.133 (1.117\u0026ndash;1.148)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.102 (0.013)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.108 (1.080\u0026ndash;1.137)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (male vs. female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.018 (0.004)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.018 (1.009\u0026ndash;1.027)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.023 (0.005)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.023 (1.013\u0026ndash;1.033)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026ndash;0.011 (0.005)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.989 (0.979\u0026ndash;0.999)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (1-year increase) \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;0.025 (0.000)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.975 (0.975\u0026ndash;0.976)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;0.023 (0.000)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.978 (0.977\u0026ndash;0.978)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026ndash;0.025 (0.000)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.975 (0.975\u0026ndash;0.976)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCitizenship \u0026times; sex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.236 (0.019)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.266 (1.221\u0026ndash;1.313)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCitizenship \u0026times; age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.008 (0.001)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.008 (1.007\u0026ndash;1.009)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex \u0026times; age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.004 (0.000)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.004 (1.004\u0026ndash;1.005)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCitizenship \u0026times; sex \u0026times; age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026ndash;0.002 (0.001)**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.998 (0.996\u0026ndash;0.999)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003ea\u003c/sup\u003e Conservatively adjusted model for age and sex only; \u003csup\u003eb\u003c/sup\u003e Fully adjusted model without interaction terms; \u003csup\u003ec\u003c/sup\u003e Fully adjusted model with interaction terms; \u003csup\u003ed\u003c/sup\u003e Age was mean-centered; *** \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, ** \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, * \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cem\u003eCI\u003c/em\u003e confidence interval, \u003cem\u003eOR\u003c/em\u003e odds ratio, \u003cem\u003eSE\u003c/em\u003e standard error\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study investigated the impact of citizenship on potentially avoidable ED utilization in Liguria, where demographic shifts exert significant pressure on healthcare resources. Our findings indicate that foreign citizens face a higher risk of potentially avoidable ED utilization, particularly for the lowest-priority codes. Importantly, this relationship is moderated by sex and age; a significant three-way interaction reveals that younger foreign males are the most frequent users of ED services for non-urgent issues, suggesting that the effect of citizenship is highly dependent on demographic intersections. These results highlight the need for targeted interventions rather than broad, one-size-fits-all policies.\u003c/p\u003e \u003cp\u003eOur main finding reveals disparities in how foreign and Italian citizens use ED services in Liguria: the former group showed up to 75% increased odds of potentially avoidable ED access. With a mean population age of 52.3 years, which is the highest in Europe [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], the regional healthcare system is heavily burdened. Considering that the foreign population is much younger, a higher likelihood of using ED services for non-urgent conditions indicates a deficit in primary care accessibility for foreign citizens. Immigrants are known to face financial, legal, socio-cultural, and other barriers to healthcare access; the key barriers include inadequate language proficiency, cultural issues, poor health literacy, and limited access to information. Financial aspects, lack of mobility affecting older and disabled immigrants, and gender issues may further compromise access to primary care [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Despite foreign citizens making up 14% of total ED visits, which is higher than the officially registered foreign population in Liguria [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], foreign LWBS patients accounted for approximately 26%. Together, these findings suggest that while a higher proportion of foreign citizens may lack a registered general practitioner (GP) or struggle to book appointments (i.e., limited access to primary care), they may also have a misunderstanding of how triage waiting times function for non-urgent issues, which may be further exacerbated by limited language proficiency (i.e., systemic barriers within the ED). Policymakers should focus on strengthening primary care accessibility by expanding and promoting access to outpatient clinics with extended hours; simplifying the administrative process for foreign citizens to register with a GP upon arrival; enhancing multichannel educational campaigns in multiple languages; and implementing targeted outreach through employers in sectors with high foreign labor. Within the ED, deploying cultural mediators and multilingual digital kiosks to explain triage color codes, as well as enhancing the fast-track model for low-acuity patients, is advisable. Furthermore, to ensure long-term success, these efforts should be supported by digital integration between ED and primary care records.\u003c/p\u003e \u003cp\u003eThe second major finding of this study is that the effect of citizenship is moderated by sex and age, with foreign males, especially those of younger age, being at the highest risk of potentially avoidable ED access. This risk was particularly pronounced for the lowest priority codes. In Italy, immigrant males outnumber females in younger age groups, whereas the opposite occurs in the older age groups. For example, in Liguria, foreign men are about four years younger than foreign women [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Young foreign males have a higher propensity of being employed in high-risk jobs and consequently are at higher risk of work-related injuries, including non-urgent ones [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Moreover, it has also been suggested that the lower use of ED services among women may be related to the fact that women perform more GP and specialist visits, and more phone consultations than men [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Additionally, foreign women in Italy are generally more educated than foreign men, as they hold higher percentages of high school and university degrees [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In turn, individuals with higher level of educational attainment are less likely to attend ED [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Regarding age, younger people may have a poorer understanding of the appropriate use of the ED, less knowledge of other health services available, and beliefs that the ED is the most appropriate place to receive care [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In summary, age and sex should be considered in any comprehensive strategy aimed at optimizing the use of emergency healthcare resources among foreign citizens.\u003c/p\u003e \u003cp\u003eComparison between our findings and previous literature is complicated by both between-study heterogeneity in the definition of avoidable ED visits [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] and sociodemographic peculiarities of Liguria [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. A systematic review of 26 studies found that individual reports of non-urgent ED visits vary widely, ranging from 8% to 62% [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In our study, the narrow and broad definitions approach the lower and upper bounds of that interval, respectively. Other systematic reviews [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] highlighted that most available research converges to the idea that foreign citizens are at greater risk of avoidable ED visits. On the other hand, these reviews also pointed out a mixed pattern in the association between citizenship or immigrant status and the overall usage of ED services: some primary studies found higher usage among foreign population, other studies reported higher usage among the host population, while still other studies found no association [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Apart from the differences in methodology (including the key definitions of both avoidable ED access and foreign population), the heterogeneity in the effect direction and magnitude is also determined by the organization of healthcare system and patients\u0026rsquo; entitlement to use these services across countries [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. It is therefore more appropriate to compare our findings with a few prior surveys conducted in Italy. In a study conducted in nine Italian regions (2016\u0026ndash;2017), the age-standardized ED visit rates for individuals aged\u0026thinsp;\u0026lt;\u0026thinsp;65 years were consistently higher among immigrants compared to Italians [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Specifically, rates were approximately 20% higher for both immigrant males (371.8 vs. 309.2 per 1,000) and females (365.3 vs. 299.4 per 1,000). Furthermore, the proportion of non-urgent white triage codes was significantly higher in the immigrant population, reaching 16.3% in males and 13.8% in females, compared to 9.5% and 9.2% in their Italian counterparts, respectively [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Similarly, between 2007 and 2010, in Reggio Emilia (Northeast Italy), the standardized access ratios for non-urgent visits were 65% higher for immigrant males and 43% higher for immigrant females [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. While our findings align with earlier research [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], direct comparability is still limited because those studies used the former 4-level priority coding system, whereas our analysis incorporates the subsequently introduced \u0026ldquo;deferrable urgency\u0026rdquo; category.\u003c/p\u003e \u003cp\u003eDespite the large sample size, precise point estimates, and inclusion of all adult ED visits, which minimized selection bias, this study has several limitations. The first shortcoming concerns inherent weaknesses of the dataset used, as it was primarily designed for administrative rather than clinical purposes. Although the database has been used in previous research [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], the absence of a formal validation of the underlying data warehouse means that its predictive accuracy remains unknown. Consequently, information bias (e.g., coding errors) is likely, particularly regarding ICD-9-CM discharge diagnosis codes; however, errors in patient demographics are less likely as these are typically scanned from official documents. Second, as there is no universally recognized definition of avoidable ED access [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], we adopted both a narrow (more specific) and a broad (more sensitive) definition; the true prevalence likely lies between these two estimates. Third, our models may be subject to residual confounding. Some important variables, such as residence permit status, time since arrival in Italy, language proficiency, and socioeconomic status (SES) were unavailable in the registry. Indeed, the fully adjusted models explained only 25\u0026ndash;27% of variance. For example, assuming a lower SES among foreign citizens compared to Italians, the inclusion of SES as a covariate would likely lead to an attenuation of the observed effect sizes, as a portion of the currently estimated risk would be attributed to economic deprivation rather than citizenship alone. Fourth, because the data were fully anonymized, the unit of analysis was the ED visit rather than the unique patient, and the models do not account for individual-level clustering. In this regard, frequent ED users with avoidable visits may be systematically different from other patients [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Fifth, although consistent with several studies [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], our results may lack full generalizability to international contexts with divergent healthcare frameworks, particularly those operating outside the Beveridge-style system. Finally, due to the cross-sectional nature of this study, our findings represent associations and do not imply a causal relationship between citizenship and avoidable ED utilization.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, the disparities in potentially avoidable ED access identified in this study reflect broader systemic gaps in the integration of foreign citizens into the Italian National Health Service. The role of sex and age as key moderators of healthcare-seeking behavior underscores the necessity of a nuanced and intersectional approach to healthcare planning. Future strategies should prioritize the decentralization of non-urgent care and the enhancement of cultural mediation within both the ED and primary care settings to ensure that the healthcare system is prepared for the demographic realities of an increasingly diverse and aging population. While our study provides a robust empirical baseline for understanding the demographic drivers of healthcare utilization, further longitudinal and qualitative studies are needed to incorporate individual-level socio-economic data, such as employment type and income, to further disentangle the extent to which these healthcare disparities are driven by citizenship status versus economic deprivation.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAIC\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Akaike information criterion\u003c/p\u003e\n\u003cp\u003eCI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Confidence interval\u003c/p\u003e\n\u003cp\u003eED\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Emergency department\u003c/p\u003e\n\u003cp\u003eEEA\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;European economic area\u003c/p\u003e\n\u003cp\u003eESI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Emergency severity index\u003c/p\u003e\n\u003cp\u003eEU \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;European Union\u003c/p\u003e\n\u003cp\u003eGP\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;General practitioner\u003c/p\u003e\n\u003cp\u003eICD-9-CM\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;International classification of diseases, 9th revision, clinical modification\u003c/p\u003e\n\u003cp\u003eLHU\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Local health unit\u003c/p\u003e\n\u003cp\u003eLWBS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Left without being seen\u003c/p\u003e\n\u003cp\u003eOR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Odds ratio\u003c/p\u003e\n\u003cp\u003eSD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Standard deviation\u003c/p\u003e\n\u003cp\u003eSE\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Standard error\u003c/p\u003e\n\u003cp\u003eSES\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Socioeconomic status\u003c/p\u003e\n\u003cp\u003eSTROBE\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Strengthening the reporting of observational studies in epidemiology\u003c/p\u003e\n\u003cp\u003eUK\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;United Kingdom\u003c/p\u003e\n\u003cp\u003eUS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;United States\u003c/p\u003e\n\u003cp\u003eUSSR \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Union of Soviet Socialist Republics\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Ethics Committee of Liguria Region (protocol n. 166/2024 of 6 June 2024, id 13819). Informed consent was waived for this retrospective anonymized study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRestrictions apply to the raw data supporting the study findings; these data are not publicly available due to their sensitive nature.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was unfunded.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEM, DP and GI conceived and designed the study. MA and DA facilitated the formal agreement and data acquisition from local health authorities. LM was responsible the data quality. EV and EV performed data analyses, interpreted the results, and drafted the manuscript. FA and AO supervised the project. GI, AO, FA, LM, MA, DA and DP critically revised the manuscript.\u0026nbsp;All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEVOSH Collaborators (Bruno Buonopane, Andrea Fiorano, Federico Grammatico, Francesca Marchini, Vincenzo Paolozzi, Irene Schenone).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eMayfield CA, Geraci M, de Hernandez BU, Dulin M, Eberth JM, Merchant AT. Ambulatory care, insurance, and avoidable emergency department utilization in North Carolina. 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Acad Emerg Med. 2004;11(12):1302\u0026ndash;10. https://doi.org/10.1197/j.aem.2004.08.032.\u003c/li\u003e\n \u003cli\u003eLippi Bruni M, Mammi I, Ugolini C. Does the extension of primary care practice opening hours reduce the use of emergency services? J Health Econ. 2016;50:144\u0026ndash;55. https://doi.org/10.1016/j.jhealeco.2016.09.011.\u003c/li\u003e\n \u003cli\u003eLiguoro I, Beorchia Y, Castriotta L, Rosso A, Pedduzza A, Pilotto C, et al. Analysis of factors conditioning inappropriate visits in a paediatric emergency department. Eur J Pediatr. 2023;182(12):5427\u0026ndash;37. https://doi.org/10.1007/s00431-023-05223-6.\u003c/li\u003e\n \u003cli\u003eHarrell FE Jr. rms: Regression modeling strategies. R package version 8.1-0. 2025. 2025. https://cran.r-project.org/web/packages/rms/rms.pdf. Accessed 22 January 2026.\u003c/li\u003e\n \u003cli\u003eEurostat. Population structure indicators by NUTS 2 region. 2025. https://ec.europa.eu/eurostat/databrowser/view/DEMO_R_PJANIND2__custom_1446484/default/table?lang=en. Accessed 22 January 2026.\u003c/li\u003e\n \u003cli\u003eRosano A, Dauvrin M, Buttigieg SC, Ronda E, Tafforeau J, Dias S. Migrant\u0026apos;s access to preventive health services in five EU countries. BMC Health Serv Res. 2017;17(1):588. https://doi.org/10.1186/s12913-017-2549-9.\u003c/li\u003e\n \u003cli\u003eDe Luca G, Ponzo M, Andr\u0026eacute;s AR. Health care utilization by immigrants in Italy. Int J Health Care Finance Econ. 2013;13(1):1\u0026ndash;31. https://doi.org/10.1007/s10754-012-9119-9.\u003c/li\u003e\n \u003cli\u003eItalian Institute of Statistics. Educational attainment and employment returns; year 2023. 2024. Available from: https://www.istat.it/wp-content/uploads/2024/07/REPORT-livelli-istruzione.pdf. Accessed 22 January 2026.\u003c/li\u003e\n \u003cli\u003eMasseria C, Giannoni M. Equity in access to health care in Italy: a disease-based approach. Eur J Public Health. 2010;20(5):504\u0026ndash;10.\u0026nbsp;https://doi.org/10.1093/eurpub/ckq029.\u003c/li\u003e\n \u003cli\u003eMcHale P, Wood S, Hughes K, Bellis MA, Demnitz U, Wyke S. Who uses emergency departments inappropriately and when - a national cross-sectional study using a monitoring data system. BMC Med. 2013;11:258.\u0026nbsp;https://doi.org/10.1186/1741-7015-11-258.\u003c/li\u003e\n \u003cli\u003eDi Napoli A, Ventura M, Spadea T, Giorgi Rossi P, Bartolini L, Battisti L, et al. Barriers to accessing primary care and appropriateness of healthcare among immigrants in Italy. Front Public Health. 2022;10:817696. https://doi.org/10.3389/fpubh.2022.817696.\u003c/li\u003e\n \u003cli\u003eBonvicini L, Broccoli S, D\u0026apos;Angelo S, Candela S. Emergency room services utilization in the province of Reggio Emilia: a comparison between immigrants and Italians. Epidemiol Prev. 2011;35(5\u0026ndash;6):259\u0026ndash;66.\u003c/li\u003e\n \u003cli\u003eThompson C, Watson T, Schull MJ, Gronsbell J, Rosella LC. Sociodemographic and health behaviour of frequent, avoidable emergency department users in Ontario, Canada: A population-based descriptive study. West J Emerg Med. 2025;26(6):1622\u0026ndash;39.\u0026nbsp;https://doi.org/10.5811/westjem.46551.\u003cstrong\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Access to care, Emergency department, Avoidable visit, Inappropriate access, Immigration, Migrants, Healthcare disparities, Italy","lastPublishedDoi":"10.21203/rs.3.rs-8680399/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8680399/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAvoidable emergency department (ED) access, though inconsistently defined and measured, is a major driver of both overcrowding and opportunity costs for healthcare systems. Among numerous factors associated with avoidable ED access, foreign citizenship has been increasingly recognized as an important predictor. Indeed, systemic and socioeconomic barriers may prevent foreign citizens from accessing primary healthcare, making the ED a primary entry point for medical advice. This study aimed to investigate disparities in avoidable ED visits among foreign and Italian citizens in Liguria, the oldest region in Europe in terms of population age.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn this cross-sectional study, all adult (\u0026ge;\u0026thinsp;18 years) ED visits registered in Liguria during 2023 and 2024 were eligible. Considering the lack of a standardized definition of avoidable ED visits, for the main analysis, we used both narrow (non-urgency only) and broad (non-urgency plus minor urgency) definitions based on the discharge severity codes. Entry priority codes assigned at triage were used in the sensitivity analysis. The effect of citizenship on avoidable access was quantified via logistic regression. After adjusting for confounders, interaction terms were tested to evaluate effect variations.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf 916,568 ED visits recorded during the study period, 14.08% involved foreign citizens. Across both definitions, foreign citizens were at higher risk (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) of potentially avoidable ED access, with the narrow definition showing a nearly two-fold increase (7.00% vs. 3.70%) and the broad definition similarly reflecting a significant disparity (67.88% vs. 54.71%). In the fully adjusted models, the odds ratio for foreign versus Italian citizenship was 1.628 (95% CI: 1.542\u0026ndash;1.719) for the narrow outcome definition and 1.174 (95% CI: 1.143\u0026ndash;1.205) for the broad definition of avoidable ED access. Furthermore, there was a significant (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) three-way interaction, indicating that the difference by citizenship was moderated by both sex and age, with younger foreign males being at the highest risk. These results were robust in the sensitivity analysis.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eForeign citizens, especially younger males, are at higher risk of avoidable ED access. To mitigate these disparities, policymakers should move beyond generalized approaches towards migrant-sensitive interventions tailored to specific socio-demographic intersections.\u003c/p\u003e","manuscriptTitle":"Disparities in the potentially avoidable use of emergency services by citizenship: a two-year cross-sectional study in Italy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-13 14:04:21","doi":"10.21203/rs.3.rs-8680399/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-20T15:04:12+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-19T12:22:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"322187866665686467559980540112395208321","date":"2026-04-08T21:29:55+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-18T16:32:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"331887134858894969657513818481054286524","date":"2026-02-11T19:54:33+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-09T19:00:11+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-28T15:42:21+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-27T07:26:33+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-27T07:23:57+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2026-01-23T14:34:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ca62d814-70fd-4a98-9d94-7f3f623558e8","owner":[],"postedDate":"February 13th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-14T17:08:38+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-13 14:04:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8680399","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8680399","identity":"rs-8680399","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}