The study was designed and implemented by the Research Center for Rural Health Services, Key Research Institute of Humanities & Social Sciences at Huazhong University of Science and Technology to understand the health service needs of Chinese residents and the factors influencing these needs, and to provide a basis for primary health services to better meet residents’ needs.
Before the survey, community investigators who administered the questionnaire were trained, and unified coding rules for the questionnaire and implementation steps for the survey were explained in detail.
For children younger than first-grade level (0–6 years of age), their parents or guardians completed the questionnaire on their behalf. Children at the second-grade level or higher (7–14 years of age) responded to the questionnaire themselves, with assistance from their parents or guardians. During questionnaire completion process, quality-control staff members were available to immediately clarify the questions to ensure the validity and reliability of the questionnaire.
For data entry, EpiData data-entry software was used by the community investigators and team members to create a database, and the accuracy of these data was checked to ensure the quality of the data input.
Shenzhen is one of China’s special economic zones, which were established as part of the country’s economic reforms and policy of opening to the world. Futian District, the central urban area and transportation hub in Shenzhen, has the largest population density in the city (35). The Shenzhen Statistical Yearbook 2019 reported that, at the end of 2018, Futian District had an area of 78.66 square kilometers and a residential population of 1.6337 million, 591,500 of whom were a “floating population” not included in the household registration system. Futian District’s gross domestic product in 2018 was 401.82592 billion yuan, and the total index of production was 107.4 (treating 2017 as 100). As of 2016, there were 10 streets (Yuanling, Nanyuan, Futian, Shatou, Meilin, Huafu, Xiangmihu, Lianhua, Huaqiangbei, and Fubao) and 94 communities in Futian District. In the survey used in the present study, the six streets in Futian District with the largest administrative areas and highest concentrations of floating population—namely, Meilin Street, Shatou Street, Xiangmihu Street, Futian Street, Lianhua Street, and Huafu Street—were selected. Two communities were then randomly selected from each of these six streets for the administration of a questionnaire survey.
Survey participants selected for this study were consistent with the definition of migrant children and adolescents in terms of age in the “Interim Measure of School Education for Temporary Migrant Children,” which was jointly issued by the State Education Committee and the Public Security Department in 1998. The study therefore collected data on local children and migrant children living in Futian District in Shenzhen who were aged 0–14 years. Migrant children were defined as children aged 0–14 who were registered as living in other cities and who had lived with their migrant parents in Shenzhen for more than half a year without changing their household registration (indicating that, officially, no migration had occurred). Local children were defined as children aged 0–14 years whose city of registration was consistent with their place of residence, meaning that both were Shenzhen.
In this study, health service utilization (the dependent variable) was operationalized as the utilization of the following services: physical examination, feeding guidance, development guidance, disease prevention guidance, injury prevention guidance, oral health guidance, and mental health guidance. For example, if the child had received a physical examination, the value of the dependent variable of physical examination utilization was coded as 1; otherwise, the variable was coded as 0.
The influencing factors included in this study included the child’s sex, age, household registration status, and enrollment in medical insurance, as well as annual family income and both father’s and mother’s occupation, education level, and marital status. The coding of each of these variables is shown in Table 1.
The questionnaire also included items on geographical medical accessibility, such as the type of medical institution located closest to the family’s home, the distance between the home and this medical institution, the type of transportation to the medical institution, and the time required to travel to the medical institution. There were also items on household expenditure, including annual family housing, food, and education expenditures. However, these items were not used in the present study for several reasons. First, because the survey respondents lived in communities with similar levels of economic development, each community was equipped with a similar level of community health service centers, so there was no variation in geographical medical accessibility among these respondents. Second, because child health management services are part of the national basic health services, these services are free to Chinese citizens through community health service centers; therefore, annual household expenditures would have no impact on the research results.
The data used in this study comes from the Survey of Health Service Needs of Chinese Residents in the New Era, a nationally representative, large-scale longitudinal survey project designed and implemented by Research Center for Rural Health Services of Humanities & Social Sciences at Huazhong University of Science and Technology. In this study, only extracted the data on child health management in the Futian District of Shenzhen.
SPSS, Version 24.0 was used to organize and analyze the data. Descriptive statistics were used to analyze the general demographic characteristics of the children and their parents. The chi-square test was used to analyze differences between migrant children and local children in terms of the use of basic public health services. Binary logistic regression was used to analyze the specific factors influencing the difference in the utilization of basic health services between migrant children and local children.
Forward and backward methods in binary logistic regression analysis and different algorithms can lead to different results. Backward analysis assumes that there are N independent or predictor variables and initially includes all of these variables in a regression analysis. Then, examining the independent variables with P-values > 0.05, the variable with highest P-value is discarded. This process is then repeated for the remaining N − 1 independent variables until only significant variables (P < 0.05) are included in the model. The forward algorithm, in contrast, carries out univariate regression analysis N times, conducting a separate univariate regression analysis for each independent variable. The variable with highest sum of squared is then selected and set as A, which is maintained in the regression model. Variable A and the remaining N − 1 independent variables are combined to form N − 1 two-variable regression models, and the process described above is repeated until the sum of squared of independent variable is no higher than that of the residual. Comparing the results of the two algorithms, the forward (conditional) algorithm was judged to be more suitable for the analysis of the present research model. Taking the utilization of a service as the dependent variable (yes = 1, no = 0), with the child’s sex, enrollment in medical insurance, and household registration as well as annual family income and parental education level, occupation, and marital status as independent variables, this study analyzed the specific factors affecting the utilization of child health management services. In the analysis of the results, the significance level of α = 0.05 was used, and applied two-tailed tests.