Abstract：
There are persistent ethnic gaps in uptake of child healthcare services in New Zealand (NZ), despite increasing policy to promote equitable access. We examined ethnic differences in the uptake of immunisation and primary healthcare services at different ages and quantified the contribution of relevant explanatory factors, in order to identify potential points of intervention.
We used data from the Growing Up in New Zealand birth cohort study, including children born between 2009 and 2010. Econometric approaches were used to explore underlying mechanisms behind ethnic differences in service uptake. Multivariable regression was used to adjust for mother, child, household, socioeconomic, mobility, and social factors. Decomposition analysis was used to assess the proportion of each ethnic gap that could be explained, as well as the main drivers behind the explained component. These analyses were repeated for four data time-points.
Six thousand eight hundred twenty-two mothers were enrolled during the antenatal survey, and children were followed up at 9-months, 2-years and 4-years. In univariable models, there were ethnic gaps in uptake of immunisation and primary care services. After adjusting for covariates in multivariable models, compared to NZ Europeans, Asian and Pacific children had higher timeliness and completeness of immunisation at all time-points, while indigenous Māori had lower timeliness of first-year vaccines despite high intentions to immunise. Asian and Pacific mothers were less likely to have their first-choice lead maternity caregiver (LMC) than NZ Europeans mothers, and Māori and Asian mothers were less likely to be satisfied with their general practitioner (GP) at 2-years. Healthcare utilisation was strongly influenced by socio-economic, mobility and social factors including ethnic discrimination. In decomposition models comparing Māori to NZ Europeans, the strongest drivers for timely first-year immunisations and GP satisfaction (2-years) were household composition and household income. Gaps between Pacific and NZ Europeans in timely first-year immunisations and choice of maternity carer were largely unexplained by factors included in the models.
Ethnic gaps in uptake of child healthcare services vary by ethnicity, service, and time-point, and are driven by different factors. Addressing healthcare disparities will require interventions tailored to specific ethnic groups, as well as addressing underlying social determinants and structural racism. Gaps that remain unexplained by our models require further investigation.
We used data from the Growing Up in New Zealand birth cohort study, including children born between 2009 and 2010. Econometric approaches were used to explore underlying mechanisms behind ethnic differences in service uptake. Multivariable regression was used to adjust for mother, child, household, socioeconomic, mobility, and social factors. Decomposition analysis was used to assess the proportion of each ethnic gap that could be explained, as well as the main drivers behind the explained component. These analyses were repeated for four data time-points.
Six thousand eight hundred twenty-two mothers were enrolled during the antenatal survey, and children were followed up at 9-months, 2-years and 4-years. In univariable models, there were ethnic gaps in uptake of immunisation and primary care services. After adjusting for covariates in multivariable models, compared to NZ Europeans, Asian and Pacific children had higher timeliness and completeness of immunisation at all time-points, while indigenous Māori had lower timeliness of first-year vaccines despite high intentions to immunise. Asian and Pacific mothers were less likely to have their first-choice lead maternity caregiver (LMC) than NZ Europeans mothers, and Māori and Asian mothers were less likely to be satisfied with their general practitioner (GP) at 2-years. Healthcare utilisation was strongly influenced by socio-economic, mobility and social factors including ethnic discrimination. In decomposition models comparing Māori to NZ Europeans, the strongest drivers for timely first-year immunisations and GP satisfaction (2-years) were household composition and household income. Gaps between Pacific and NZ Europeans in timely first-year immunisations and choice of maternity carer were largely unexplained by factors included in the models.
Ethnic gaps in uptake of child healthcare services vary by ethnicity, service, and time-point, and are driven by different factors. Addressing healthcare disparities will require interventions tailored to specific ethnic groups, as well as addressing underlying social determinants and structural racism. Gaps that remain unexplained by our models require further investigation.
摘要：
背景：新西兰（NZ）在儿童医疗保健服务的吸收方面存在持续的种族差距，尽管加强了促进公平获取的政策。我们研究了不同年龄段在免疫接种和初级保健服务方面的种族差异，并量化了相关解释因素的贡献，以确定潜在的干预点。
方法：我们使用了来自新西兰出生队列研究的数据，包括2009年至2010年出生的孩子。计量经济学方法被用来探索服务吸收方面种族差异背后的潜在机制。多变量回归用于校正母亲，孩子,家庭,社会经济,移动性,和社会因素。分解分析用于评估可以解释的每个种族差距的比例，以及解释组件背后的主要驱动因素。对四个数据时间点重复这些分析。
结果：在产前调查中纳入了六千八百二十二名母亲，孩子们在9个月时接受了随访，2年和4年。在单变量模型中，在接受免疫接种和初级保健服务方面存在种族差距。在多变量模型中调整协变量后，与新西兰欧洲人相比，亚洲及太平洋儿童在所有时间点的免疫接种及时性和完整性更高，而土著毛利人的第一年疫苗的及时性较低，尽管有很高的免疫意愿。与新西兰欧洲人的母亲相比，亚洲和太平洋地区的母亲不太可能拥有首选的主要产妇照顾者（LMC），毛利人和亚裔母亲在2年时对全科医生（GP）感到满意的可能性较小。医疗保健利用率受到社会经济、流动性和社会因素，包括种族歧视。在将毛利人与新西兰欧洲人进行比较的分解模型中，及时进行第一年免疫接种和全科医生满意度(2年)的最强驱动因素是家庭构成和家庭收入.太平洋和新西兰欧洲人在及时进行第一年免疫接种和选择产妇护理人员方面的差距在很大程度上无法由模型中包含的因素来解释。
结论：儿童保健服务的人口差距因种族而异，服务,和时间点，并且是由不同的因素驱动的。解决医疗保健差距将需要针对特定种族群体的干预措施，以及解决潜在的社会决定因素和结构性种族主义。我们的模型无法解释的差距需要进一步调查。
方法：我们使用了来自新西兰出生队列研究的数据，包括2009年至2010年出生的孩子。计量经济学方法被用来探索服务吸收方面种族差异背后的潜在机制。多变量回归用于校正母亲，孩子,家庭,社会经济,移动性,和社会因素。分解分析用于评估可以解释的每个种族差距的比例，以及解释组件背后的主要驱动因素。对四个数据时间点重复这些分析。
结果：在产前调查中纳入了六千八百二十二名母亲，孩子们在9个月时接受了随访，2年和4年。在单变量模型中，在接受免疫接种和初级保健服务方面存在种族差距。在多变量模型中调整协变量后，与新西兰欧洲人相比，亚洲及太平洋儿童在所有时间点的免疫接种及时性和完整性更高，而土著毛利人的第一年疫苗的及时性较低，尽管有很高的免疫意愿。与新西兰欧洲人的母亲相比，亚洲和太平洋地区的母亲不太可能拥有首选的主要产妇照顾者（LMC），毛利人和亚裔母亲在2年时对全科医生（GP）感到满意的可能性较小。医疗保健利用率受到社会经济、流动性和社会因素，包括种族歧视。在将毛利人与新西兰欧洲人进行比较的分解模型中，及时进行第一年免疫接种和全科医生满意度(2年)的最强驱动因素是家庭构成和家庭收入.太平洋和新西兰欧洲人在及时进行第一年免疫接种和选择产妇护理人员方面的差距在很大程度上无法由模型中包含的因素来解释。
结论：儿童保健服务的人口差距因种族而异，服务,和时间点，并且是由不同的因素驱动的。解决医疗保健差距将需要针对特定种族群体的干预措施，以及解决潜在的社会决定因素和结构性种族主义。我们的模型无法解释的差距需要进一步调查。
