| Literature DB >> 35719667 |
Laura Terragni1, Alessio Rossi2, Monica Miscali3, Giovanna Calogiuri4,5.
Abstract
Background: Most studies on immigrant health focus on immigrant groups coming from extra-European and/or low-income countries. Little attention is given to self-rated health (SRH) in the context EU/EEA migration. To know more about health among European immigrants can provide new insights related to social determinants of health in the migration context. Using the case of Italian immigrants in Norway, the aim of this study was to (i) examine the levels of SRH among Italian immigrants in Norway as compared with the Norwegian and the Italian population, (ii) examine the extent to which the Italian immigrant perceived that moving to Norway had a positive or negative impact on their SRH; and (iii) identify the most important factors predicting SRH among Italian immigrants in Norway.Entities:
Keywords: Italian immigrants; acculturation; health literacy; healthy immigrant effect; intra-European migration; machine learning; new mobilities; self-rated health
Mesh:
Year: 2022 PMID: 35719667 PMCID: PMC9198252 DOI: 10.3389/fpubh.2022.837728
Source DB: PubMed Journal: Front Public Health ISSN: 2296-2565
Predictors of Self-rated health included in the machine learning analysis.
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Descriptive statistics of Self-rated health, perceived impact of moving, and other information about the health and living conditions of Italian immigrants in Norway (oversampled dataset, n = 531).
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| Age, M ± SD | 40.54 ± 10.78 |
| Gender, % | |
| Man | 60.45% |
| Woman | 39.55% |
| Educational level, % | |
| Primary or lower | 4.71% |
| High school | 33.90% |
| B.A. degree | 10.73% |
| M.A. degree or equivalent | 33.33% |
| Doctoral degree | 17.33% |
| Region of residence, % | |
| All other regions | 43.50% |
| Oslo & Akeshus | 56.50% |
| Occupational situation, % | |
| Unemployed | 4.90% |
| Student | 2.64% |
| Occasional occupation | 2.45% |
| Self-employed | 7.16% |
| Hired by the piece | 7.34% |
| Term contract | 26.18% |
| Permanent contract | 47.08% |
| Other | 2.26% |
| Satisfaction with occupation % | |
| Unemployed | 6.09% |
| Unsatisfactory | 14.00% |
| Satisfactory but not consistent with educational background | 19.68% |
| Satisfactory and consistent with educational background | 36.51% |
| Highly satisfied with occupation | 23.73% |
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| Empowerment relative to health behaviors, Median [Q1–3] (1–4 scale) | 3 ( |
| Empowerment relative to communication, M ± SD (1–4 scale) | 3 [3] |
| Health literacy, M ± SD (total score) | 35.34 ± 3.91 |
| Trust in the health system, Median [Q1–3] (1–10 scale) | 6 [4–7] |
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| Healthy food habits, Median [Q1–3] (1–4 scale) | 3 [2–4] |
| Nature restoration, Median [Q1–3] (1–4 scale) | 2 [1–4] |
| Tobacco usage, % | |
| No | 79.47% |
| Yes, occasionally | 13.37% |
| Yes, regularly | 7.16% |
| Weekly physical activity, % | |
| No regular physical activity | 23.16% |
| <2.5 h/week | 23.16% |
| Between 2.5 and 5 h/week | 33.33% |
| 5 h/week or more | 20.34% |
| Contacts with Italian relatives, % | |
| Never/ < once a year | 0.75% |
| About once a year | 1.32% |
| Some times a year | 5.84% |
| About once a month | 11.68% |
| About once a week | 47.27% |
| Almost every day | 33.15% |
| Contact with good friends, % | |
| Never/ < once a year | 1.32% |
| About once a year | 2.45% |
| Some times a year | 22.98% |
| About once a month | 27.31% |
| About once a week | 36.53% |
| Almost every day | 9.42% |
| Living alone, % “Yes” | 41.30% |
| Living with children, % “Yes” | 25.24% |
| Living with partner, % “Yes” | 67.32% |
| Trust in people, Median [Q1–3] (1–10 scale) | 5 [6, 7] |
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| Perceived impact on food habit, % | |
| I don't know | 4.12% |
| Negative impact | 51.37% |
| No impact | 36.08% |
| Positive impact | 8.43% |
| Perceived impact on physical activity, % | |
| I don't know | 0% |
| Negative impact | 22.04% |
| No impact | 37.76% |
| Positive impact | 40.20% |
| Perceived impact on social relationships, % | |
| I don't know | 2.53% |
| Negative impact | 72.6% |
| No impact | 21.21% |
| Positive impact | 3.31% |
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| Belief about futurea, % | |
| Live in Norway for a short period | 6.03% |
| Move back to Italy when I'll be old | 31.45% |
| Move in some other country | 23.73% |
| Spend the rest of my life in Norway | 25.24% |
| I don't know | 13.56% |
| Identifying as an immigrant, % | |
| I don't know | 2.32% |
| No | 18.34% |
| In part | 48.26% |
| Yes | 31.08% |
| Identifying as a Norwegian, % | |
| I always identify as an Italian | 54.42% |
| I predominantly identify as an Italian | 37.15% |
| I identify as Italian and a Norwegian in equal extents | 8.03% |
| I predominantly identify as a Norwegian | 0.40% |
| I always identify as a Norwegian | 0.00% |
| Italian friends, % | |
| None | 18.64% |
| < half | 38.23% |
| About half | 19.96% |
| >half | 20.34% |
| All of them | 2.82% |
| Language proficiency, % | |
| Very poor | 13.37% |
| Poor | 23.16% |
| Intermediate | 27.68% |
| Good | 22.79% |
| Very good | 12.99% |
| Years of permanence in Norway, M ± SD | 8.75 ± 7.78 |
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| Moved alone, % “Yes” | 69.63% |
| Moved with family, % “Yes” | 29.38% |
| Moved with others, % “Yes” | 1.69% |
| Moved for family-related reasons, % “Yes” | 26.74% |
| Moved for job-related reasons, % “Yes” | 43.31% |
| Moved for other reasons, % “Yes” | 15.63% |
| Worse (total) | 30.89% |
| Very bad | 0.38% |
| Bad | 6.78% |
| Neither bad, not good | 23.73% |
| Better (total) | 69.11% |
| Good | 57.06% |
| Very good | 12.05% |
| Perceived impact of migration on SRH, % | |
| I don't know | 6.10% |
| Negative impact | 22.76% |
| No impact | 55.08% |
| Positive impact | 16.06% |
[a] Belief about the future is here presented as it was assessed in the questionnaire, but it was dichotomize for the purpose of the Machine learning analysis (0 = “Plan to move again/I don't know” and 1 = “Spend the rest of one's life in Norway”) (oversampled dataset, n = 531).
Figure 1Self-rated health among Norwegians, Italians, and Italian immigrants living in Norway.
Accuracy of the machine learning models predicting Self-rated health (SRH).
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| DTC | 75.05 ± 2.08 | 74.44 ± 2.31 | 74.61 ± 2.14 | 74.44 ± 2.31 |
| RFC | 83.04 ± 2.74 | 83.06 ± 2.66 | 82.04 ± 3.10 | 83.07 ± 2.66 |
| LR | 69.31 ± 2.50 | 71.31 ± 2.13 | 69.31 ± 2.45 | 71.31 ± 2.13 |
| XGB | 78.95 ± 2.61 | 79.50 ± 2.26 | 78.84 ± 2.69 | 79.50 ± 2.26 |
| ADA | 74.28 ± 2.30 | 75.19 ± 2.19 | 74.18 ± 2.35 | 75.19 ± 2.19 |
| Dummy | 56.18 ± 1.59 | 56.13 ± 2.67 | 56.07 ± 2.03 | 56.13 ± 2.67 |
*Metrics referring to the weighted values about the two classes.
Model with the highest prediction goodness.
DTC, Decision Tree Classifier; RFC, Random Forest Classifier; LR, Logistic Regression; XGB, eXtreme Gradient Boosting classifier; ADA, Adaptive Boosting classifier.
Figure 2Importance (expressed as SHAP values) of the relevant variables predicting SRH among Italian immigrants in Norway, according to the RFC model. Red bars refer to the negative influence of the independent variables on the dependent one, while the green one refers to a positive influence.