Study Design and Data Source
This study was a secondary analysis of publicly available, cross-sectional data that was combined from the 2016 and 2017 National Survey of Children’s Health (NSCH). The data analyzed for the current study are available through the U.S. Census Bureau at https://www.census.gov/programs-surveys/nsch/data.html. The NSCH is a parent-reported survey about healthcare access and quality, educational experiences, parent and family health, and child health for a nationally-representative sample of children ages 0–17 years. The NSCH is sponsored by the Maternal and Child Health Bureau of the Health Resources and Services Administration, part of the U.S. Department of Health and Human Services. The 2016 and 2017 NSCH were conducted by the U.S. Census Bureau using web- or mail-based survey administration, with a telephone questionnaire assistance option. Questionnaires were available in English or Spanish. The overall weighted response rates were as follows: 40.7% for the 2016 NSCH and 37.4% for the 2017 NSCH.(27,28) Additional details about the NSCH methodology are available from the U.S. Census Bureau.(29,30)
In conducting this study, two parent advisors were continuously and regularly involved in the study’s conceptualization, design, and interpretation of results. Each parent advisor had a young child who was 2 to 3 years old that was born prematurely, and each advisor was involved on a family advisory committee for a neonatal intensive care unit (NICU) at a large academic medical center following their child’s discharge. The Institutional Review Board at Massachusetts General Hospital determined that this study was not human research and it was exempt from review.
Participants
The full study sample included 19,482 U.S. children ages 0–5 years. In the sample, 242 children were born very low birthweight (< 1,500 grams), 1,236 children were born low birthweight (1,500 to 2,499 grams), 969 children were born preterm but not low birthweight or very low birthweight, and 17,035 other children were not born very low birthweight, low birthweight, or preterm. Because children born preterm but not with low birthweight may be similarly prone to experience health risks as children born low birthweight (not very low birthweight) (3,31), we combined children born low birthweight and children born preterm not low birthweight or very low birthweight (n = 2,205) into one group (LBW/PTB) that was mutually exclusive from children born very low birthweight (VLBW) or other children. In both the 2016 and 2017 NSCH, parents were asked the following question to determine if children were born prematurely: “Was this child born more than 3 weeks before his or her due date?” To establish each child’s birthweight, parents were also asked: “How much did he or she weigh when born?” In alignment with the Centers for Disease Control and Prevention’s case definition (1), very low birthweight was defined as < 1,500 grams and low birthweight was defined as 1,500 to 2,499 grams for this study.
Measures
Healthcare access. Per past research about healthcare access and quality for child subgroups at high risk of health disparities (e.g., children with special health care needs, children with autism spectrum disorder) (1), we used the following three healthcare access measures: adequate health insurance, medical home, and developmental screening receipt. Adequate health insurance was a composite measure only assessed among children who were insured during the past 12-months. In the study sample, 635 children were uninsured. Adequate health insurance was determined by the following three subcomponents: health insurance benefits met the child’s needs (usually or always versus sometimes or never), coverage allowed the child to see needed providers (usually or always versus sometimes or never), and the child’s out-of-pocket health care expenses were reasonable (usually or always versus sometimes or never). To qualify as having adequate health insurance, children had usually or always on all three subcomponents. Medical home was also a composite measure based on 16 items about the following five subcomponents of care in the past 12-months: child had a personal doctor or nurse, usual source for sick care, family-centered care (e.g., doctors spent enough time with the child, doctors showed sensitivity to family values and customs), no problems getting needed referrals, and effective care coordination when needed (e.g., got all needed help with care coordination, satisfaction with communication among child’s doctor and other health care providers). To qualify as having a medical home, children needed to have had a personal doctor or nurse, usual source for sick care, and family-centered care. To have been considered as having a medical home, children additionally must have had no problems getting needed referrals and effective care coordination (if they reported needing these services). Additional documentation about this medical home measure is provided elsewhere.(36) Developmental screening receipt was assessed with a 3-item measure previously validated using NSCH data.(37) The developmental screening measure was only assessed for children who were ages 9 to 35 months, in alignment with national screening guidelines.(38) Children were considered to have had developmental screening if their parent indicated a doctor or other health care provider had given them or another caregiver a questionnaire about specific concerns or observations they had about their child’s development, communication, or social behaviors and if this questionnaire had two age-specific content areas regarding language development and social behavior in the past 12-months.
Adverse family impact. We used five adverse family impact measures, which have been commonly used in relevant, past research.(17,19,33) Two of these measures were related to family financial and/or employment impacts including if the family spent $1,000 or more on out-of-pocket medical expenses for the child during the past 12-months and if a parent or other family member stopped working or cut down on hours working because of the child’s health or health condition(s) during the past 12-months. Parental aggravation was a composite measure derived from the following three items: parent felt the child is difficult to care for, parent felt that the child does things that bother them, and parent felt angry with the child. All of the parental aggravation items were assessed for the past month and included a five-point response scale (never, rarely, sometimes, usually, always). Parents were defined as having often experienced parental aggravation during the past month if they indicated usually or always for any of the three measure items. Overall maternal and paternal health status not being excellent were similarly measured using two items: one item about the mother’s or father’s overall physical health status and one item about the mother’s or father’s overall mental health status. Each item was rated on a five-point scale (poor, fair, good, very good, excellent). Maternal and paternal health were both considered to be not excellent, if either physical or mental health status was reported to be poor, fair, good, or very good.
Covariates. Child and family characteristics that have established linkages with prematurity status, healthcare access, and/or adverse family impact and were available in the 2016 and 2017 NSCH were selected as covariates.(24,26,39,40) Covariates included the child’s age (years), sex (male or female), race and ethnicity (white and non-Hispanic, Hispanic, black and non-Hispanic, other race and non-Hispanic), parent’s nativity (born in the U.S. or not born in the U.S.), primary household language (English or Spanish/other language), highest parent education level (high school or less versus more than high school), family structure (two married parents, two unmarried parents, single mother, other family structure), household income level defined according to the family poverty ratio, health insurance coverage (private only, public only, private and public, uninsured or unspecified), and region of residence (Northeast, Midwest, South, West). In addition, the child’s special health care needs status was assessed by the Children with Special Health Care Needs (CSHCN) Screener.(41) Other covariates included current presence of one or more of 27 chronic conditions (e.g., asthma, developmental delay, speech and language disorder), number of adverse childhood experiences (e.g., parent divorced or separated, parent died), and family resiliency (i.e., family talks together about what to do when facing a problem, works together to solve a problem, knows the family has strengths to draw on when the family faces a problem, and stays hopeful even in difficult times when the family faces problems).
Statistical Analysis
Characteristics of U.S. children ages 0–5 years were first compared by prematurity status using chi-square tests and multinomial logistic regression for categorical variables and linear regression for continuous age. Both unadjusted and adjusted differences in healthcare access and adverse family impact were examined by prematurity status by estimating relative risk. We included all covariates that differed by prematurity status at a p <.10 level in the multivariable regression models used to compute adjusted differences in healthcare access and adverse family impact. To determine associations of healthcare access with adverse family impact among children born prematurely, propensity score weighting was used to estimate the average treatment effect of each healthcare access measure in relationship to each adverse family impact.(42) These relative risk models, with adverse family impact as the dependent variable and healthcare access as the main independent variable of interest, also adjusted for parent nativity, household language, health insurance coverage, household income level, CSHCN status, one or more chronic condition(s), and family resiliency. Family structure was omitted from the maternal and paternal health models due to possible collinearity with the dependent variable. Post-hoc, we additionally performed bivariate analyses to examine associations between certain healthcare access measure subcomponents and three of the adverse family impact measures. All analyses incorporated strata and weighting to produce nationally representative estimates.(30) Weights were adjusted for multi-year analysis.(43) Family poverty ratio was analyzed in a multiple imputation framework.(44) We used a conventional alpha level of.05 to determine statistical significance. All analyses were performed in Stata version 15.(45)