| Literature DB >> 31125371 |
Åsa Grauman1, Mats G Hansson1, Arvid Puranen2, Stefan James3, Jorien Veldwijk4,5.
Abstract
BACKGROUND: Understanding of how cardiovascular risk information influence individuals is critical for the practice of risk assessment and the management of patients with cardiovascular disease.Entities:
Mesh:
Year: 2019 PMID: 31125371 PMCID: PMC6534302 DOI: 10.1371/journal.pone.0217247
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Fig 1Study process.
Characteristics of participants presented as total distribution and divided by exposure groups.
Continuous variables are expressed as mean (SD), categorical as percentages.
| N = 434 | Total | Not referred | Referred toPrimary care | Referred to hospital | |
|---|---|---|---|---|---|
| Age | 58.0 (4.4) | 57.7 (4.3) | 58.3 (4.6) | 59.1 (4.0) | |
| Gender ( | 53.0% | 55.5% | 49.4% | 42.6% | |
| Education | Primary school | 6.7% | 6.0% | 5.7% | 13.0% |
| High school | 43.1% | 39.9% | 50.6% | 44.4% | |
| University | 50.2% | 54.1% | 43.7% | 42.6% | |
| Born in Sweden | Yes | 90.1% | 87.2% | 94.3% | 98.1% |
| Health literacy | Sufficient | 62.0% | 66.4% | 65.1% | 57.7% |
| Problematic | 30.4% | 30.4% | 30.1% | 36.5% | |
| In-adequate | 3.5% | 3.0% | 4.8% | 5.8% | |
| Numeracy | 3.9 (0.8) | 3.9 (0.8) | 3.8 (0.9) | 3.8 (1.0) | |
| Hypertension | 22.1% | 20.4% | 23.0% | 31.5 | |
| High cholesterol | 11.3% | 9.3% | 8.0% | 25.9% | |
| Diabetes | 3.7% | 3.2% | 2.3% | 7.4% | |
| CVD | 6.0% | 5.0% | 6.9% | 11.1% | |
| Multiple risk factors | 2 | 16.6% | 15.2% | 18.6% | 20.4% |
| 3 or 4 | 8.4% | 7.2% | 5.8% | 18.5% | |
| Family history of myocardial infarction | 24.7% | 22.6% | 31.0% | 26.4% | |
| General health | Bad | 1.6% | 1.4% | 2.3% | 1.9% |
| Somewhat good | 15.2% | 12.8% | 19.5% | 16.7% | |
| Good | 34.6% | 33.5% | 37.9% | 37.0% | |
| Very good | 35.0% | 37.7% | 26.4% | 38.9% | |
| Excellent | 13.6% | 14.6% | 13.8% | 5.6% | |
| Self-perceived stress | Low | 81.3% | 82.1% | 79.3% | 79.6% |
| High | 18.8% | 17.9% | 20.7% | 20.4% | |
| HADS Anxiety | Borderline case | 11.1% | 9.6% | 10.8% | 17.3% |
| Case | 6.5% | 7.4% | 3.6% | 3.8% | |
| HADS Depression | Borderline case | 5.8% | 5.5% | 6.0% | 3.8% |
| Case | 2.6% | 3.3% | 1.2% | 1.9% | |
| Abdominal obesity | 49.8% | 45.2% | 55.2% | 61.1% | |
| Smoker | 7.0% | 7.9% | 8.1% | - |
a Treated or diagnosed before participating in SCAPIS
bAccording to the cutoffs for Hospital Anxiety and Depression Scale
cWaist circumference >87 cm for woman, >101 for men.
Differences in psychological factors at baseline and after three months.
| Psychological factors | N | Baseline | Three months | |
|---|---|---|---|---|
| Mean(SD) | Mean(SD) | |||
| Worry about experiencing a myocardial infarction | Total | 408 | 1.6 (.7) | 1.7 (.7) |
| Not referred | 266 | 1.6 (.7) | 1.6 (.7) | |
| Referred PHCC | 82 | 1.6 (.6) | 1.7 (.6) | |
| Referred hospital | 52 | 1.8 (.7) | 2.0 (.8) | |
| SF-12 PCS | Total | 418 | 50.7 (7.7) | 50.5 (7.5) |
| Not referred | 271 | 50.9 (7.4) | 50.9 (7.0) | |
| Referred PHCC | 84 | 50.7 (8.3) | 50.1 (8.0) | |
| Referred hospital | 53 | 49.6 (8.5) | 49.3 (7.5) | |
| SF-12 MCS | Total | 418 | 51.8 (9.1) | 51.1 (10.3) |
| Not referred | 271 | 51.8 (9.0) | 51.5 (9.6) | |
| Referred PHCC | 84 | 52.0 (8.6) | 51.5 (10.0) | |
| Referred hospital | 53 | 52.0 (9.1) | 49.6(11.0) | |
| HADS Anxiety score | Total | 416 | 4.4 (3.5) | 4.5 (3.6) |
| Not referred | 271 | 4.4 (3.6) | 4.4 (3.6) | |
| Referred PHCC | 83 | 4.0 (3.1) | 4.0 (3.2) | |
| Referred hospital | 52 | 4.7 (3.1) | 5.4 (3.4) | |
| HADS Depression score | Total | 416 | 3.3 (2.9) | 3.3 (2.9) |
| Not referred | 271 | 3.3 (3.1) | 3.2 (2.9) | |
| Referred PHCC | 83 | 3.2 (2.6) | 3.4 (2.7) | |
| Referred hospital | 52 | 3.6 (2.4) | 3.8 (2.9) |
*P>0.05
**P>0.01
AN = 343
Data collected in Uppsala, Sweden, 2017.
Multiple linear regression analysis of differences between referral groups three months after risk assessment, adjusting for diagnosis of coronary artery stenosis, age and health literacy.
| Model 1 | CI for Beta | Adj. R square | Model 2 | CI for Beta | Adj. R square | |||
|---|---|---|---|---|---|---|---|---|
| Lower | Upper | Lower | Upper | |||||
| 0.40 | 0.43 | |||||||
| Worry at baseline | 0.62 | 0.56 | 0.72 | 0.64 | 0.56 | 0.72 | ||
| Referral to hospital | 0.10 | 0,05 | 0,36 | 0.05 | -0.06 | 0.26 | ||
| Referral to PHCC | 0.01 | -0.11 | 0.16 | 0.02 | -0.13 | 0.14 | ||
| Coronary artery stenosis | 0.15 | 0.28 | 0.88 | |||||
| Age | -0.03 | -0.02 | 0.01 | |||||
| Health literacy | 0.04 | -0.05 | 0.18 | |||||
| 0.38 | 0.39 | |||||||
| MCS baseline | 0.61 | 0.58 | 0.75 | 0.61 | 0.58 | 0.75 | ||
| Referral to hospital | -0.10 | -4.83 | -0.60 | -0.07 | -4.31 | 0.16 | ||
| Referral to PHCC | -0.01 | -2.02 | 1.71 | 0.00 | -1.88 | 1.90 | ||
| Coronary artery stenosis | -0,08 | -8.23 | -0.28 | |||||
| Age | 0.04 | -0.09 | 0.26 | |||||
| Health literacy | -0.06 | -2.82 | 0.35 | |||||
| 0.43 | 0.43 | |||||||
| SF-12 P baseline | ,654 | ,547 | ,685 | 0.65 | 0.55 | 0.68 | ||
| Referral to hospital | -,018 | -1,878 | 1,131 | 0.000 | -1,60 | 1,60 | ||
| Referral to PHCC | -,016 | -1,609 | 1,040 | -0.01 | -1.52 | 1.14 | ||
| Coronary artery stenosis | -0.05 | -4.99 | 1.10 | |||||
| Age | -0.02 | -0.15 | 0.10 | |||||
| Health literacy | -0.01 | -1.37 | 0.92 | |||||
| 0.56 | 0.56 | |||||||
| HADS A at baseline | 0.72 | 0.69 | 0.82 | 0.74 | 0.69 | 0.82 | ||
| Referral to hospital | 0.07 | 0.03 | 1.33 | 0.04 | -0.24 | 1.14 | ||
| Referral to PHCC | -0.03 | -0.85 | 0.29 | -0.03 | -0.90 | 0.27 | ||
| Coronary artery stenosis | 0.08 | 0.14 | 2.71 | |||||
| Age | -0.02 | -0.07 | 0.03 | |||||
| Health literacy | 0.02 | -0.34 | 0.63 | |||||
| 0.54 | 0.54 | |||||||
| HADS D at baseline | 0.74 | .67 | .80 | 0.73 | 0.66 | 0.80 | ||
| Referral to hospital | 0.05 | -0.13 | .94 | 0.05 | -0.18 | 0.96 | ||
| Referral to PHCC | 0.02 | -0.36 | 0.58 | 0.02 | -0.37 | 0.60 | ||
| Coronary artery stenosis | 0.02 | -0.82 | 1.32 | |||||
| Age | -0.5 | -0.08 | 0.01 | |||||
| Health literacy | 0.02 | -0.25 | 0.55 | |||||
*p<0.05
**p<0.01
Data from SCAPIS research participants. Men and woman 50–64 years old. Data collected in Uppsala, Sweden, 2017. N = 434
ASufficient health literacy compared to problematic or in-adequate health literacy