| Literature DB >> 33160326 |
Xiatong Ke1,2, Liang Zhang3,4, Zhong Li3,4, Wenxi Tang5,6.
Abstract
BACKGROUND: Shenzhen is characterized with the largest scale of migrant children among all the cities in China. Unequal access to health services among migrant and local children greatly affects health equity and has a profound impact on the quality of human capital. This study aimed to investigate differences in using community-based healthcare between local and migrant children and to identify the influencing factors in Futian District of Shenzhen.Entities:
Keywords: Community-based healthcare; Inequality; Influencing factor; Local child; Migrant child; Service utilization
Mesh:
Year: 2020 PMID: 33160326 PMCID: PMC7648970 DOI: 10.1186/s12889-020-09781-4
Source DB: PubMed Journal: BMC Public Health ISSN: 1471-2458 Impact factor: 3.295
Coding of the independent variables
| Variable | Assignment |
|---|---|
| Gender | Male = 1; female = 2 |
| Household registration | Local child = 1; migrant children = 2 |
| Family annual income | 0 to 0.15 million yuan = 1; 0.15 to 0.5 million yuan = 2; 0.5 to 1 million yuan = 3; more than 1 million yuan = 4 |
| Medical insurance of Child | Basic health insurance only =1; commercial insurance only =2; basic medical insurance + commercial insurance =3; no insurance or others = 4 |
| Occupation of the parents | white-collar workers =1; blue-collar workers =2; Mixed white−/blue-collar workers =3; others = 4 |
| Education level of the parents | Junior high school and below =1; Senior high school/ technical secondary school/ junior college = 2; Bachelor’s degree or above =3 |
| Marital status of the parents | Unmarried =1; married = 2; divorced = 3; widowed = 4 |
For parental occupation, white-collar workers included staff members of the government or other institutions, clerks, and related personnel, whereas blue-collar workers included laborers in the industries of agriculture, forestry, animal husbandry, fishing, and water conservancy, as well as production and transportation equipment operators. Mixed white−/blue-collar workers included professional and technical personnel, commercial workers, and service personnel
Fig. 1The age distribution of the local and migrant children
Demographic characteristics of the surveyed children by migration status
| Investigated factor | Local child ( | Migrate child ( | ||
|---|---|---|---|---|
| 0.470 | 0.493 | |||
| Male | 187 (53.89%) | 92 (57.14%) | ||
| Female | 160 (46.11%) | 69 (42.86%) | ||
| 41.619 | < 0.001 | |||
| Low (≤0.15 million yuan) | 60 (17.29%) | 63 (39.13%) | ||
| Medium (0.15–0.5 million yuan) | 211 (60.81%) | 90 (55.90%) | ||
| Medium to high (0.5–1 million yuan) | 67 (19.31%) | 6 (3.73%) | ||
| High (1 million yuan or higher) | 9 (2.59%) | 2 (1.24%) | ||
| 38.084 | < 0.001 | |||
| Basic health insurance only | 169 (48.70%) | 80 (49.69%) | ||
| Commercial insurance only | 39 (11.24%) | 8 (4.97%) | ||
| Basic medical insurance + commercial insurance | 101 (29.11%) | 24 (14.91%) | ||
| No insurance or others | 38 (10.95%) | 49 (30.43%) | ||
| 36.437 | < 0.001 | |||
| White-collar workers | 134 (38.62%) | 28 (17.39%) | ||
| Blue-collar workers | 22 (6.34%) | 6 (3.73%) | ||
| Mixed white−/blue-collar workers | 177 (51.01%) | 104 (64.60%) | ||
| Others | 14 (4.03%) | 23 (14.29%) | ||
| White-collar workers | 166 (47.84%) | 70 (43.48%) | 12.162 | 0.007 |
| Blue-collar workers | 26 (7.49%) | 6 (3.73%) | ||
| Mixed white−/blue-collar workers | 132 (38.04%) | 60 (37.27%) | ||
| Others | 23 (6.63%) | 25 (15.53%) | ||
| 100.268 | < 0.001 | |||
| Junior high school and below | 40 (11.53%) | 68 (42.24%) | ||
| Senior high school/ technical secondary school/ junior college | 102 (29.39%) | 68 (42.24%) | ||
| Bachelor’s degree or above | 205 (59.08%) | 25 (15.53%) | ||
| 80.931 | < 0.001 | |||
| Junior high school and below | 67 (19.31%) | 83 (51.55%) | ||
| Senior high school/ technical secondary school/ junior college | 116 (33.43%) | 61 (37.89%) | ||
| Bachelor’s degree or above | 164 (47.26%) | 17 (10.56%) | ||
| 1.075 | 0.783 | |||
| Unmarried | 13 (3.75%) | 5 (3.11%) | ||
| Married | 330 (95.10%) | 155 (96.27%) | ||
| Divorced | 2 (0.58%) | 0 (0%) | ||
| Widowed | 2 (0.58%%) | 1 (0.62%) | ||
| 2.305 | 0.512 | |||
| Unmarried | 4 (1.15%) | 4 (2.48%) | ||
| Married | 332 (95.68%) | 150 (43.23%) | ||
| Divorced | 5 (1.44%) | 2 (1.24%) | ||
| Widowed | 6 (1.73%) | 5 (3.11%) |
Differences between local children and migrant children in the utilization of health services
| Basic child health management services | Overall | Household registration | |||
|---|---|---|---|---|---|
| Local children ( | Migrant children ( | ||||
| Physical examination | 477 (93.9%) | 333 (96.0%) | 144 (89.4%) | 8.170 | 0.004 |
| Feeding guidance | 369 (73.1%) | 261 (75.2%) | 108 (67.1%) | 3.662 | 0.056 |
| Development guidance | 364 (71.7%) | 269 (77.5%) | 95 (59.0%) | 18.562 | < 0.001 |
| Disease prevention guidance | 273 (53.7%) | 201 (57.9%) | 72 (44.7%) | 7.713 | 0.005 |
| Injury prevention guidance | 238 (46.9%) | 178 (51.3%) | 60 (37.3%) | 8.693 | 0.003 |
| Oral health guidance | 265 (52.2%) | 197 (56.8%) | 68 (42.2%) | 9.313 | 0.002 |
| Mental health guidance | 93 (18.1%) | 72 (20.7%) | 21 (13.0%) | 4.366 | 0.037 |
| None | 9 (1.8%) | 3 (0.9%) | 6 (3.7%) | 5.177 | 0.023 |
| Unclear | 11 (2.2%) | 3 (0.9%) | 8 (5.0%) | 8.745 | 0.003 |
None means that the child has never used the basic child health management services; Unclear means that the child cannot clear remember clearly whether they have used the basic child health management services
Binary logistic regression analysis of factors influencing the utilization of child health management services
| Variable | Standard error | Wald test | Df | Exp( | 95% confidence interval | ||
|---|---|---|---|---|---|---|---|
| Constant | 1.931 | 0.245 | 61.857 | 1 | < 0.001 | 6.895 | – |
| Educational level of the mother (control = junior high school and below) | |||||||
| Senior high school/ technical secondary school/ junior college | 1.419 | 0.482 | 8.652 | 1 | 0.003 | 4.134 | (1.606, 10.642) |
| Bachelor’s degree or above | 1.442 | 0.482 | 8.941 | 1 | 0.003 | 4.230 | (1.644, 10.888) |
| Constant | 1.238 | 0.129 | 92.6775 | 1 | < 0.001 | 3.449 | – |
| Household registration (control = local children) ( | |||||||
| Migrant children | −0.874 | 0.205 | 18.085 | 1 | < 0.001 | 0.417 | (0.279,0.624) |
| Constant | −0.298 | 0.195 | 2.353 | 1 | 0.125 | 0.742 | – |
| Educational level of the father (control = junior high school and below) ( | |||||||
| Senior high school/ technical secondary school/ junior college | 0.251 | 0.248 | 1.029 | 1 | 0.310 | 1.286 | (0.791,2.090) |
| Bachelor’s degree or above | 0.814 | 0.238 | 11.739 | 1 | 0.001 | 2.257 | (1.417,3.595) |
| Constant | −0.088 | 0.242 | 0.132 | 1 | 0.716 | 0.916 | – |
| Occupation of the father (control = White-collar workers) ( | |||||||
| Blue-collar workers | −0.288 | 0.413 | 0.487 | 1 | 0.485 | 0.750 | (0.334, 1.684) |
| Mixed white/blue-collar workers | −0.622 | 0.203 | 9.381 | 1 | 0.002 | 0.537 | (0.361, 0.799) |
| Others | −1.240 | 0.418 | 8.808 | 1 | 0.003 | 0.289 | (0.128, 0.656) |
| Annual family income (control = ≤0.15 million yuan) ( | |||||||
| 0.15–0.5 million yuan | 0.476 | 0.227 | 4.415 | 1 | 0.036 | 1.610 | (1.033, 2.511) |
| 0.5–1 million yuan | 0.485 | 0.308 | 2.474 | 1 | 0.116 | 1.624 | (0.888, 2.970) |
| 1 million yuan or higher | 2.997 | 1.071 | 7.822 | 1 | 0.005 | 20.016 | (2.451, 163.436) |
| Constant | 0.273 | 0.108 | 6.327 | 1 | 0.012 | 1.313 | – |
| Household registration (control = local children) ( | |||||||
| Migrant children | −0.586 | 0.193 | 9.220 | 1 | 0.002 | 0.557 | (0.381, 0.813) |
| Constant | −1.341 | 0.218 | 37.953 | 1 | < 0.001 | 0.262 | – |
| Gender (control = male) ( | |||||||
| Female | 0.606 | 0.235 | 6.673 | 1 | 0.010 | 1.833 | (1.157, 2.904) |
| Occupation of the father (control = White-collar workers) ( | |||||||
| Blue-collar workers | −0.244 | 0.498 | 0.240 | 1 | 0.625 | 0.784 | (0.295, 2.080) |
| Mixed white/blue-collar workers | −0.739 | 0.249 | 8.841 | 1 | 0.003 | 0.478 | (0.293, 0.777) |
| Others | −1.050 | 0.562 | 3.495 | 1 | 0.602 | 0.350 | (0.116, 1.052) |