Research Objective. To evaluate one of the first implemented provisions of the Patient Protection and Affordable Care Act (ACA), which permits young adults up to age 26 to enroll as dependents on a parent's private health plan. Nearly one-in-three young adults lacked coverage before the ACA. Study Design, Methods, and Data. Data from the Current Population Survey 2005 -2011 are used to estimate linear probability models within a difference-in-differences framework to estimate how the ACA affected coverage of eligible young adults compared to slightly older adults. Multivariate models control for individual characteristics, economic trends, and prior state-dependent coverage laws. Principal Findings. This ACA provision led to a rapid and substantial increase in the share of young adults with dependent coverage and a reduction in their uninsured rate in the early months of implementation. Models accounting for prior state dependent expansions suggest greater policy impact in 2010 among young adults who were also eligible under a state law. Conclusions and Implications. ACA-dependent coverage expansion represents a rare public policy success in the effort to cover the uninsured. Still, this policy may have later unintended consequences for premiums for alternative forms of coverage and employer-offered rates for young adult workers. Key Words. Health care reform, health insurance regulation, health policy, health economics One of the first implemented provisions of the Patient Protection and Affordable Care Act (ACA) permits young adults aged up to 26 years to obtain health insurance as dependents on a parent's private health plan. This provision recognized that young adults are the age group most likely to lack health insurance. In 2009, the year before the ACA-dependent coverage expansion, 31.4 percent of adults in the targeted age range, 19-25 years old, lacked coverage, nearly double the national rate (DeNavas-Walt, Proctor, and Smith 2011).
. Linear probability models are used to obtain difference-in-differences estimates of the impact of dependent coverage expansions in 19 early-adopting states on young adults' insurance status. The models also address possible policy endogeneity due to the nonrandom enactment of expansion policies across states. Principal Findings. State young adult dependent coverage policies yielded small increases in dependent coverage ranging from 1.52 percentage points for all young adults to 3.84 percentage points for those ages 19-25 residing with parents. These increases were largely offset by declines in employer-sponsored insurance (ESI) in the young adults' own name. No significant impact on young adult uninsured rates was observed. Conclusions and Implications. Adult dependent coverage expansions have had a relatively small impact on enrollment as an ESI dependent and appear to have the unintended consequence of reducing ESI policyholder coverage. This policy did not achieve a reduction in uninsured rates as policy makers had intended. Federal reform efforts to expand dependent coverage are likely to be more successful because reform will be accompanied by subsidies and enrollment mandates.
Objective The Social Ecological Model (SEM) has been used to describe the aetiology of childhood obesity and to develop a framework for prevention. The current paper applies the SEM to data collected at multiple levels, representing different layers of the SEM, and examines the unique and relative contribution of each layer to children’s weight status. Design Cross-sectional survey of randomly selected households with children living in low-income diverse communities. Setting A telephone survey conducted in 2009–2010 collected information on parental perceptions of their neighbourhoods, and household, parent and child demographic characteristics. Parents provided measured height and weight data for their children. Geocoded data were used to calculate proximity of a child’s residence to food and physical activity outlets. Subjects Analysis based on 560 children whose parents participated in the survey and provided measured heights and weights. Results Multiple logistic regression models were estimated to determine the joint contribution of elements within each layer of the SEM as well as the relative contribution of each layer. Layers of the SEM representing parental perceptions of their neighbourhoods, parent demographics and neighbourhood characteristics made the strongest contributions to predicting whether a child was overweight or obese. Layers of the SEM representing food and physical activity environments made smaller, but still significant, contributions to predicting children’s weight status. Conclusions The approach used herein supports using the SEM for predicting child weight status and uncovers some of the most promising domains and strategies for childhood obesity prevention that can be used for designing interventions.
Background Understanding determinants of high consumption of sugar-sweetened beverages (SSB), a highly prevalent obesogenic behavior, will help build effective customized public health interventions. Objective To identify child and parent lifestyle and household demographic factors predictive of high SSB consumption frequency in children from low-income, ethnically diverse communities that may help inform public health interventions. Design Cross-sectional telephone household survey. Participants/Setting 717 boys and 686 girls 3–18 years old from the New Jersey Childhood Obesity Study living in five low-income cities (Camden, New Brunswick, Newark, Trenton, and Vineland). The adult most knowledgeable about household food shopping completed a questionnaire over the telephone inquiring about their and their child’s dietary and physical activity habits, and household-, parent-, and child-level demographics. Main outcome measures Child’s SSB consumption frequency. Statistical analysis performed Multivariate ordered logit models were designed to investigate a variety of variables hypothesized to affect the frequency of SSB consumption. Exploratory stratified analyses by race, gender, and age were also conducted. Results Eight percent of our study participants never consumed SSBs, 45% consumed SSBs at least once per day, and 23% consumed twice or more per day. SSB consumption was higher among children 12–18 vs. 3–5 years (p<0.0001), of non-Hispanic black vs. non-Hispanic white race/ethnicity (p=0.010), who were moderate fast food consumers vs. never consumers (p=0.003), and those whose parents were high vs. low SSB consumers (p<0.0001). Living in a non-English speaking household (p=0.030), having a parent with a college or higher education vs. less than high school (p=0.003), and having breakfast 6–7 days/week vs. never to ≤ twice/week were associated with lower SSB consumption (p=0.001). Conclusions We identified a number of household-, parental-, and child-level predictors of SSB consumption, which varied by race, gender and age, useful for building customized interventions targeting certain behaviors in ethnically diverse, low-income children.
Objectives Conflicting findings on associations between food and physical activity (PA) environments and children’s weight status demand attention in order to inform effective interventions. We assess relationships between the food and PA environments in inner-city neighborhoods and children’s weight status and address sources of conflicting results of prior research. Methods Weight status of children ages 3–18 was assessed using parent-measured heights and weights. Data were collected from 702 children living in four low-income cities in New Jersey between 2009 and 2010. Proximity of a child’s residence to a variety of food and PA outlets was measured in multiple ways using geo-coded data. Multivariate analyses assessed the association between measures of proximity and weight status. Results Significant associations were observed between children’s weight status and proximity to convenience stores in the 1/4 mile radius (OR = 1.9) and with presence of a large park in the 1/2 mile radius (OR = 0.41). No associations were observed for other types of food and PA outlets. Conclusions Specific aspects of the food and PA environments are predictors of overweight and obese status among children, but the relationships and their detection are dependent upon aspects of the geospatial landscape of each community.
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