| Literature DB >> 29976166 |
Elena S Rotarou1, Dikaios Sakellariou2.
Abstract
BACKGROUND: Preventive health services play a vital role in population health. However, access to such services is not always equitably distributed. In this article, we examine the barriers affecting utilisation rates of preventive health services, using Chile as a case study.Entities:
Keywords: Chile; Health inequality; Healthcare; Preventive health services; Private health provider; Public health provider
Mesh:
Year: 2018 PMID: 29976166 PMCID: PMC6034328 DOI: 10.1186/s12889-018-5763-4
Source DB: PubMed Journal: BMC Public Health ISSN: 1471-2458 Impact factor: 3.295
Demographic, socioeconomic, and health-related characteristics of the sample
| Parameter | 2015 | ||
|---|---|---|---|
| No preventive services (n, %) | Preventive services (n,%) | ||
| Sex | Male | 91,771 (47.1%) | 4415 (38.9%) |
| Female | 103,021 (52.9%) | 6925 (61.1%) | |
| Chi-square test | |||
| Cramer’s V | 0.037 | ||
| Zone | Urban | 151,961 (78.0%) | 8746 (77.1%) |
| Rural | 42,831 (22.0%) | 2594 (22.9%) | |
| Chi-square test | |||
| Cramer’s V | 0.005 | ||
| Age (mean, std. dev.) | 42.9 (18.5) | 67.0 (15.9) | |
| t-test | |||
| Point biserial correlation | −.286 | ||
| Married | 67,871 (34.8) | 5319 (46.9%) | |
| Living with or in a relationship | 31,351 (16.1%) | 921 (8.1%) | |
| Civil status | Separated, divorced, annulled | 13,043 (6.7%) | 905 (8.0%) |
| Widowed | 9958 (5.1%) | 2648 (23.4%) | |
| Single | 72,569 (37.3%) | 1547 (13.6%) | |
| Chi-square test | |||
| Cramer’s V | 0.202 | ||
| Nationality | Chilean | 191,779 (98.5%) | 11,263 (99.3%) |
| Foreigner | 3013 (1.6%) | 77 (0.7%) | |
| Chi-square test | |||
| Cramer’s V | −0.016 | ||
| Indigeneity | Not indigenous | 173,670 (89.2%) | 10,356 (91.3%) |
| Indigenous | 21,122 (10.8%) | 984 (8.7%) | |
| Chi-square test | |||
| Cramer’s V | −0.016 | ||
| Health system | FONASA | 159,586 (81.9%) | 10,092 (89.0%) |
| Armed forces | 4190 (2.2%) | 325 (2.9%) | |
| ISAPRE | 24,210 (12.4%) | 833 (7.4%) | |
| Out-of-pocket | 6806 (3.5%) | 90 (0.8%) | |
| Chi-square test | |||
| Cramer’s V | 0.052 | ||
| Health score | Bad | 13,036 (6.7%) | 1487 (13.1%) |
| Average | 67,685 (34.8%) | 5632 (50.0%) | |
| Good | 114,071 (58.6%) | 4221 (37.2%) | |
| Chi-square test | |||
| Cramer’s V | 0.102 | ||
| Disability | No disability | 175,756 (90.2%) | 8434 (74.4%) |
| With disability | 19,036 (9.8%) | 2906 (25.6%) | |
| Chi-square test | |||
| Cramer’s V | 0.117 | ||
| Employment | Employed | 103,565 (53.2%) | 3176 (28.0%) |
| Unemployed | 8423 (4.3%) | 156 (1.4%) | |
| Inactive | 82,804 (42.5%) | 8008 (70.6%) | |
| t-test | |||
| Cramer’s V | 0.130 | ||
| Equalised incomea (mean, std. dev.) | 528,348 (671,874) | 509,400 (549,153) | |
| t-test | |||
| Point biserial correlation | .006 | ||
| Education, (mean, std. dev.) | 10.6 (4.2) | 7.8 (4.9) | |
| t-test | |||
| Point biserial correlation | .151 | ||
a Chilean pesos (1 USD = 659 Chilean pesos, average July 2017)
Fig. 1Chilean adults (%) using preventive health services, 2000–2015
Results of logistic regressions using preventive services as dependent variable
| Variables | (1) | (2) | (3) |
|---|---|---|---|
| OR (95% CI) | OR (95% CI) | OR (95% CI) | |
| Sex (male as reference) | |||
| Female | 1.28*** | 1.17*** | 1.16*** |
| Geographical location (urban as reference) | |||
| Rural | .92*** | .90*** | .90*** |
| Age (years) | 1.07*** | 1.07*** | 1.07*** |
| Civil status (married as reference) | |||
| Living with or in a relationship | .87*** | .89** | .88** |
| Separated, divorced, annulled | .96 | 1.02 | 1.03 |
| Widowed | .94* | .94* | .94* |
| Single | .85*** | .84*** | .85*** |
| Indigeneity (not indigenous as reference) | |||
| Indigenous | 1.03 | 1.03 | 1.02 |
| Nationality (Chilean as reference) | |||
| Foreigner | .90 | .91 | .97 |
| Equalised income (log) | 1.11*** | 1.13*** | |
| Education (years) | .99*** | .99** | |
| Employment (employed as reference) | |||
| Unemployed | 1.04 | 1.06 | |
| Inactive | 1.40*** | 1.41*** | |
| Health self-assessment (bad as reference) | |||
| Neither good nor bad | 1.18*** | ||
| Good | 1.14** | ||
| Health provider (FONASA as reference) | |||
| Armed forces | .92 | ||
| ISAPRE | .89** | ||
| Out-of-pocket | .42*** | ||
| Disability (no as reference) | |||
| Yes | 1.04 | ||
| LR chi2 | 17,770.10 | 17,923.71 | 17,576.60 |
| Prob > chi2 | 0.0000 | 0.0000 | 0.0000 |
| McFadden R2 | 0.197 | 0.200 | 0.200 |
| Deviance | 72,250.482 | 71,762.361 | 70,243.872 |
| AIC | 72,270.482 | 71,790.361 | 70,283.872 |
| BIC | 72,373.157 | 71,934.053 | 70,488.597 |
* p < 0.05, ** p < 0.01, *** p < 0.001
Fig. 2Estimated probabilities for utilisation of preventive health services with health provider as predictor variable