{"paper_id":"24b0e450-2fc7-4447-ad90-5e069d1b14e7","body_text":"1 \n \nTitle: Addressing Socioeconomic Inequities in Children’s Cardiovascular Health via Positive 1 \nExperiences 2 \n 3 \nAuthors: Shuaijun Guo, PhD, 1,2 Rushani Wijesuriya, PhD, 2,3 David Burgner, PhD, 2,4,5,6 4 \nMeredith O’Connor, DEdPsych, 2,7,8 Sharon Goldfeld, FRACP , FAFPHM, PhD,1,2 Richard S 5 \nLiu, PhD,9,10 Naomi Priest, PhD,1,11,12 6 \n 7 \nAuthor affiliations:  8 \n1Centre for Community Child Health, Murdoch Children’s Research Institute, Melbourne, 9 \nAustralia.  10 \n2Department of Pediatrics, University of Melbourne, Melbourne, Australia. 11 \n3Clinical Epidemiology and Biostatistics Unit, Murdoch Children's Research Institute, Royal 12 \nChildren's Hospital, Melbourne, Australia 13 \n4Inflammatory Origins Group, Murdoch Children’s Research Institute, Royal Children's 14 \nHospital, Melbourne, Australia. 15 \n5Department of General Medicine, Royal Children’s Hospital, Melbourne, Australia. 16 \n6Department of Pediatrics, Monash University, Melbourne, Australia. 17 \n7Melbourne Children’s LifeCourse Initiative, Murdoch Children’s Research Institute, 18 \nMelbourne, Australia. 19 \n8Faculty of Education, University of Melbourne, Melbourne, Australia. 20 \n9Institute of Endocrinology and Diabetes, Children’s Hospital at Westmead, Sydney, 21 \nAustralia. 22 \n10School of Pediatrics and Child Health, University of New South Wales, Sydney, Australia. 23 \n11The Centre for Social Policy Research, Australian National University, Canberra, Australia. 24 \n12Indigenous Health Equity Unit, Melbourne School of Population and Global Health, 25 \nUniversity of Melbourne, Melbourne, Australia. 26 \n 27 \nCorresponding author: Dr Shuaijun Guo, Centre for Community Child Health, Murdoch 28 \nChildren’s Research Institute, Royal Children’s Hospital, Melbourne, VIC 3052, Australia. 29 \nEmail: jun.guo@mcri.edu.au.  30 \n 31 \nShort title: Reducing cardiovascular inequities in children 32 \n 33 \nEthical approval: The LSAC (ID 13-04) and CheckPoint (ID 14-26) methodologies were 34 \napproved by the Australian Institute of Family Studies Human Research Ethics Review Board, 35 \nand the CheckPoint additionally by The Royal Children's Hospital Melbourne Human 36 \nResearch Ethics Committee (33225D). This study was approved by the Royal Children’s 37 \nHospital Human Research Ethics Committee (ID 2019.170). 38 \n 39 \nConflict of Interest Disclosures:  The authors have indicated they have no conflicts of 40 \ninterest relevant to this article to disclose. 41 \n 42 \nFunding: This work is supported by the Victorian Government’s Operational Infrastructure 43 \nSupport Program. Dr Guo was supported by Murdoch Children’s Research Institute 44 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 16, 2025. ; https://doi.org/10.1101/2025.07.15.25331608doi: medRxiv preprint \nNOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice.\n\n2 \n \nPopulation Health Theme Funding for 2023. Prof Burgner is supported by an NHMRC 45 \nInvestigator Grant (1175744). Prof Goldfeld is supported by an NHMRC Investigator Grant 46 \n(2026263).  47 \n 48 \nRole of Funder: The funding sources had no role in the design and conduct of the study; 49 \ncollection, management, analysis, and interpretation of the data; preparation, review, or 50 \napproval of the manuscript; and decision to submit the manuscript for publication. 51 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 16, 2025. ; https://doi.org/10.1101/2025.07.15.25331608doi: medRxiv preprint \n\n3 \n \nAbbreviations 52 \nAHA American Heart Association \nB-cohort Birth cohort \nCVD Cardiovascular Disease \nCVH Cardiovascular Health \nHOPE Health Outcomes from Positive Experiences \nLE8 Life’s Essential 8 \nLSAC Longitudinal Study of Australian Children \nRR Risk Ratio \n 53 \nArticle Summary 54 \nWe explore the potential of positive childhood experience interventions to reduce 55 \nsocioeconomic inequities in children’s cardiovascular health.  56 \n 57 \nWhat’s Known on This Subject 58 \nSocioeconomic disadvantage is associated with poor cardiovascular health. Positive 59 \nchildhood experiences are emerging as protective factors, but their potential to reduce 60 \nsocioeconomic inequities in children’s cardiovascular health remains unexplored. 61 \n 62 \nWhat This Study Adds 63 \nPromoting positive experiences partially reduces socioeconomic inequities in children’s 64 \ncardiovascular health. An integrated and multi-faceted approach that tackles the diverse 65 \ndrivers of cardiovascular health is essential to achieve the maximum impact.  66 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 16, 2025. ; https://doi.org/10.1101/2025.07.15.25331608doi: medRxiv preprint \n\n4 \n \nContributors’ Statement:  67 \nDr Shuaijun Guo conceptualized and designed the study, carried out data analyses, drafted the 68 \ninitial manuscript, and critically reviewed and revised the manuscript. 69 \n 70 \nDr Rushani Wijesuriya conceptualized and designed the study, carried out data analyses, and 71 \ncritically reviewed and revised the manuscript. 72 \n 73 \nDrs Meredith O’Connor, Richard Liu, Profs David Burgner, and Sharon Goldfeld 74 \nconceptualized and designed the study, and critically reviewed and revised the manuscript for 75 \nimportant intellectual content. 76 \n 77 \nProf Naomi Priest conceptualized and designed the study, critically reviewed and revised the 78 \nmanuscript for important intellectual content and supervised Dr Guo. 79 \n 80 \nAll authors approved the final manuscript as submitted and agreed to be accountable for all 81 \naspects of the work. 82 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 16, 2025. ; https://doi.org/10.1101/2025.07.15.25331608doi: medRxiv preprint \n\n5 \n \nAbstract 83 \nObjectives: Socioeconomic disadvantage leads to poor cardiovascular health and this 84 \nrelationship may be mediated by positive childhood experiences. This study aimed to 85 \nestimate the extent to which promoting positive experiences could reduce socioeconomic 86 \ninequities in children’s cardiovascular health. 87 \n 88 \nMethods: Data source: The Longitudinal Study of Australian Children Child Health 89 \nCheckPoint (N=1874). Exposure: Maternal education (low/medium/high) as a key indicator 90 \nof family socioeconomic position during pregnancy. Outcome: Cardiovascular health (11-12 91 \nyears) (poor/good) quantified by four health behaviors and four health factors. Mediator: 92 \nMultiple positive experiences ( ≥ 2/<2) indicated by positive parenting, supportive 93 \nrelationships, environments, and high social engagement (2-11 years). We conducted a causal 94 \nmediation analysis using an interventional effects approach, adjusting for childhood adversity 95 \nand other potential confounders.   96 \n 97 \nResults: Children with low (risk difference=4.9%, 95% CI=-3.2%, 13.0%) or medium (risk 98 \ndifference=5.6%, 95% CI=-1.2%, 12.5%) maternal education had a higher risk of poor 99 \ncardiovascular health compared to those with high maternal education. Causal mediation 100 \nanalysis estimated that increasing the levels of positive experiences in children with low or 101 \nmedium maternal education to be like their high maternal education peers could reduce these 102 \nrisk differences by 1.0% (95% CI= -0.8%,1.5%) and 0.5% (95% CI=-0.5%, 1.5%) respectively, 103 \nreducing cardiovascular inequities by 20.4% and 8.9%. 104 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 16, 2025. ; https://doi.org/10.1101/2025.07.15.25331608doi: medRxiv preprint \n\n6 \n \n 105 \nConclusions: Targeted policy interventions that promote positive experiences are potential 106 \nopportunities to reduce socioeconomic inequities in children’s cardiovascular health. 107 \nHowever, such interventions should be considered within a broader and multipronged 108 \napproach that includes addressing socioeconomic disadvantage itself and other socially 109 \ndistributed drivers of cardiovascular diseases to achieve the maximum impact. 110 \n 111 \nKeywords: maternal education, positive experiences, health inequities, cardiovascular health, 112 \nlongitudinal, children, interventional effects113 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 16, 2025. ; https://doi.org/10.1101/2025.07.15.25331608doi: medRxiv preprint \n\n7 \n \nINTRODUCTION  114 \nCardiovascular disease (CVD) is the leading cause of mortality globally, accounting for 32% 115 \nof all deaths in 2020. 1 The economic burden of CVD is substantial, with global costs 116 \nestimated at US$1 trillion in 2030. 2 Socioeconomic disadvantage is a well-established 117 \ndeterminant of CVD, contributing to differences in the incidence and mortality of CVD. 3 118 \nAddressing socioeconomic inequities in CVD is a priority of governments worldwide. 119 \nEvidence suggests that more than 80% of CVD can be prevented or modified in early life by 120 \nfollowing healthy lifestyles and addressing risk factors such as high blood pressure and 121 \ndiabetes.4  122 \n 123 \nThe American Heart Association (AHA) introduced the concept of ideal cardiovascular health 124 \n(CVH) in 2010, 5 which refers to not merely the absence of CVD but the presence of 125 \nfavorable health behaviors (e.g., no smoking, healthy diet, regular physical activity) and 126 \nhealth factors (e.g., normal body mass index, healthy blood pressure and lipid levels). These 127 \ncomponents were updated in 2022 to reflect the Life’s Essential 8 (LE8). 6 This paradigm 128 \nrepresents a shift in cardiovascular research from a deficit-focus approach to a 129 \nstrengths-based approach.5 Monitoring CVH at the population level over the life course is 130 \nessential for identifying CVH disparities and informing targeted interventions. 131 \n 132 \nChildren’s CVH is shaped by the social environments where they live and develop across the 133 \nlife span.6,7 Socioeconomic inequities in CVH emerge as early as childhood. 7 Data from the 134 \n2013-2018 US National Health and Nutrition Examination Survey indicate that family 135 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 16, 2025. ; https://doi.org/10.1101/2025.07.15.25331608doi: medRxiv preprint \n\n8 \n \nincome is associated with differences in CVH indicators such as nicotine exposure, body 136 \nmass index, and diet among children aged 2 to 19 years. 8 These disparities are driven by an 137 \nunequal distribution of material resources as well as structural barriers that disproportionately 138 \naffect children from socioeconomically disadvantaged families. 6,8-10 Addressing CVH 139 \ninequities in children is likely to yield greater cost-effective benefits than interventions later 140 \nin life, given the cumulative impact of early life exposures on long-term health outcomes.8,11  141 \n 142 \nThe mechanisms linking socioeconomic disadvantage to CVH are complex, 12 including both 143 \nadverse and positive experiences. While childhood adversity (e.g., family violence, child 144 \nabuse) has been well-established as a risk factor of CVH, 13,14 positive childhood experiences 145 \nwarrant specific focus because they are valued by families and communities, and efforts to 146 \npromote positive experiences are considered highly acceptable, avoiding stigma and aligning 147 \nwith strengths-based practices and policies.15,16 Positive experiences refer to a range of events, 148 \nactivities, or situations that foster flourishing and better health outcomes.17 Although variably 149 \ndefined, emerging evidence suggests that positive experiences are associated with better 150 \nCVH,14,16,18-20 with possible pathways such as enhanced self-esteem and lower rates of 151 \nsubstance use.21 152 \n 153 \nCompared to CVH in adulthood, very few studies have explored CVH in childhood from a 154 \nlife course perspective.8,22 While there is increasing evidence showing the benefits of positive 155 \nexperiences, the extent to which promoting positive experiences would reduce socioeconomic 156 \ninequities in CVH remains unknown. To inform intervention opportunities and policy actions 157 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 16, 2025. ; https://doi.org/10.1101/2025.07.15.25331608doi: medRxiv preprint \n\n9 \n \non CVH improvement at the population level, we estimated the extent to which promoting 158 \npositive experiences could reduce socioeconomic inequities in children’s CVH. 159 \n 160 \nMETHODS 161 \nData source 162 \nWe drew on a subset of data from the birth cohort (B-cohort) of the Longitudinal Study of 163 \nAustralian Children (LSAC), which commenced in 2004 when children were aged 0-1 year 164 \n(n=5107). A two-stage clustered design was employed to select a sample that was broadly 165 \nrepresentative of the Australian child population except those living in remote areas. 23 166 \nChildren were followed up every two years. We drew data when children were aged 0-1 years 167 \n(Wave 1; n=5107), 2-3 years (Wave 2; n=4606), 4-5 years (Wave 3; n=4386), 6-7 years 168 \n(Wave 4; n=4242), 8-9 years (Wave 5; n=4085), 10-11 years (Wave 6; n=3764) and 11-12 169 \nyears (CheckPoint wave; n=1874). The CheckPoint wave was a one-off national-wide 170 \ncross-sectional physical health and biomarker module, nested between LSAC Waves 6 and 7.24 171 \nMultiple information sources were utilized, including parent interviews, parent-report and 172 \nchild-report questionnaires. 173 \n 174 \nDespite the requirement for children to attend multi-hour, in-person clinic assessments in the 175 \nCheckPoint wave, over 1,800 families participated, demonstrating a strong commitment and 176 \nwillingness to invest time and travel resources. We found that children who had lower 177 \nmaternal education, came from Aboriginal or ethnic minority backgrounds, and lived in low 178 \nsocioeconomic status neighborhoods were likely to be missed out (see Supplementary file 1).  179 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 16, 2025. ; https://doi.org/10.1101/2025.07.15.25331608doi: medRxiv preprint \n\n10 \n \n 180 \nMeasures 181 \nOur conceptual model (Figure 1) shows the hypothesized causal pathway from maternal 182 \neducation (during pregnancy) to children’s CVH (11-12 years), via positive experiences (2-11 183 \nyears) as an intervention target of interest, informed by current knowledge (see 184 \nSupplementary file 2). Figure 1 was used to guide the selection of measures and inform the 185 \nanalytic approach.  186 \n 187 \nExposure (during pregnancy) 188 \nMaternal education at Wave 1 was used as a key indicator of socioeconomic resources in the 189 \nfamily environment during pregnancy, assuming maternal education did not change 190 \nsignificantly from pregnancy to just after birth. 25 In keeping with previous studies, 25 we 191 \ncategorized it into three groups: low (Year 12 or below); medium (Certificate I/II/III/IV or 192 \nAdvanced Diploma); and high (Bachelor’s degree or above).  193 \n 194 \nMediator (2-11 years) 195 \nInformed by the Health Outcomes from Positive Experiences (HOPE) framework 26 and 196 \nprevious validation work, 17 we quantified overall positive experiences using 17 indicators, 197 \neach mapping to one of the four domains of positive experiences prospectively collected from 198 \n2 to 11 years: (1) positive parenting practice; (2) trusting and supportive relationships; (3) 199 \nsupportive neighborhood and home learning environments; and (4) social engagement and 200 \nenjoyment (see Supplementary file 3). Each indicator was first dichotomized (yes/no) using 201 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 16, 2025. ; https://doi.org/10.1101/2025.07.15.25331608doi: medRxiv preprint \n\n11 \n \nthe top quartile to indicate the presence of exposure to a positive experience at each wave. 17 202 \nNext, we summed the number of positive experiences at each wave for each domain and 203 \ndichotomized this count at ‘two or more’ to indicate multiple positive experiences in each 204 \ndomain at each wave. To measure multiple positive experiences across four domains at each 205 \nwave, we summed the number of positive experiences at each wave and dichotomized this 206 \ncount at ‘two or more’ at each wave. Finally, to measure multiple positive experiences over 207 \nthe follow-up period (2-11 years), we summed the number of positive experiences across 208 \nthese waves and dichotomized this count at ‘two or more’, given that a cluster of positive 209 \nexperiences is likely to have a cumulative benefit on health.27  210 \n 211 \nOutcome (11-12 years) 212 \nWe quantified CVH at 11-12 years using the LE8 metrics, including four health behaviors 213 \n(diet, physical activity, cigarette smoking, and sleep) and four health factors (body mass 214 \nindex, non-high-density lipoprotein, blood pressure, and blood glucose). For each child, each 215 \nof the LE8 metrics was scored on a scale of 0 to 100 (see Supplementary file 4). We then 216 \ncalculated an overall CVH score, using the average value across all eight metrics. According 217 \nto the AHA recommendation, 6 we dichotomized the overall CVH score using “0 to 79” to 218 \nindicate children with poor CVH. 219 \n 220 \nConfounders 221 \nBaseline confounders (at birth). We posited four baseline confounders: child’s sex 222 \n(male/female), child’s ethnicity (Anglo or European/minoritized ethnic group/Indigenous), 223 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 16, 2025. ; https://doi.org/10.1101/2025.07.15.25331608doi: medRxiv preprint \n\n12 \n \nchild’s disability status (yes/no), and neighborhood socioeconomic status (top 75% - not 224 \ndisadvantaged/bottom 25% - disadvantaged) assessed by the Socioeconomic Indexes for 225 \nAreas of Relative Socioeconomic Advantage and Disadvantage.28 Due to the possible overlap 226 \nbetween maternal education and neighbourhood socioeconomic status, we conducted 227 \nsensitivity analyses by removing neighborhood socioeconomic status as a baseline 228 \nconfounder . 229 \n 230 \nIntermediate confounder (0-1 year). We posited four intermediate confounders: gestational 231 \nage in weeks (<37 weeks/ ≥ 37 weeks), maternal age at childbirth (<27 years/ ≥  27 years), 232 \nfamily composition (single parent/two parents), and multiple childhood adversities (<2/ ≥ 2) 233 \nmeasured by parent legal problems, family violence, household member mental illness, 234 \nhousehold member substance abuse, harsh parenting, parental separation, unsafe 235 \nneighborhood, and family member death (see Supplementary file 3).27  236 \n 237 \nStatistical analysis 238 \nThe analytic sample consisted of all children who attended CheckPoint (N=1874). Participant 239 \ncharacteristics were summarized overall and by maternal education, using descriptive 240 \nstatistics. Preliminary analyses were first conducted to confirm whether data were consistent 241 \nwith the expected associations depicted in Figure 1. Specifically, generalized linear models 242 \nwith a log-Poisson link were used to examine unadjusted and confounder-adjusted 243 \nassociations between exposure, mediator and outcome. Descriptive analyses and preliminary 244 \nanalyses were conducted using Stata 18.0.  245 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 16, 2025. ; https://doi.org/10.1101/2025.07.15.25331608doi: medRxiv preprint \n\n13 \n \n 246 \nIn all analyses, we ignored the clustering due to postcodes as the correlations between the 247 \noutcome measures within the postcodes were negligible (intra-cluster correlation= 0.0005). 248 \nWe also did not incorporate the CheckPoint sampling weights in the analyses, 29 as the 249 \nincorporation of sampling weights appropriately in the causal mediation approach used below 250 \nis still an ongoing area of research.  251 \n 252 \nCausal mediation analysis 253 \nWe then conducted a casual mediation analysis using an interventional effects approach to 254 \nanswer the causal question of interest:30,31 what would be the reduction in risk of poor CVH if 255 \nwe could offer effective interventions that promote positive childhood experiences among 256 \nchildren with low or medium maternal education?  As well-defined interventions that can 257 \ncollectively address the composite measure of positive experiences are not available in the 258 \ncommunity, we examined the question by conceptualizing hypothetical interventions that 259 \nmap to a ‘target trial’.32  260 \n 261 \nWe first estimated the confounder-adjusted absolute difference in the risk of poor CVH in 262 \nchildren with low or medium maternal education compared to their high maternal education 263 \npeers, separately, using g-computation.30,31 These adjusted differences provided estimates of 264 \nthe overall CVH inequities that we sought to reduce.  265 \n 266 \nNext we evaluated the reduction in risk of poor CVH that would be achieved by a 267 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 16, 2025. ; https://doi.org/10.1101/2025.07.15.25331608doi: medRxiv preprint \n\n14 \n \nhypothetical intervention that would shift the distribution of the positive experiences in 268 \nchildren with low or medium maternal education, to be similar to that in children with high 269 \nmaternal education, using an extended g-computation estimation procedure (see 270 \nSupplementary file 5).32 This provided estimates of the absolute risk differences achieved if 271 \nwe could offer an intervention that promotes positive experiences among children with low or 272 \nmedium maternal education.  273 \n 274 \nThe difference between the initial overall CVH inequities and the reduction in risk achieved 275 \nby the hypothetical intervention provides an estimate of CVH inequities that would remain 276 \nafter the hypothetical intervention. We also report the relative reductions in the gap achieved 277 \nfor children with low or moderate maternal education using these estimates (i.e. reduction in 278 \nrisk of poor CVH achieved by the hypothetical intervention as a ratio of existing 279 \nsocioeconomic inequities in CVH). Standard error estimates were computed using a bootstrap 280 \nprocedure. All mediation analyses were implemented using R Statistical Software 4.3.1 using 281 \nR package medRCT.33,34 282 \n 283 \nMissing data 284 \nIn the analytic sample, the percentage of missing data across any of the study variables was 285 \n59%. We used multiple imputation by chained equations to reduce bias due to incomplete 286 \nrecords, under the missing at random assumption. 35,36 Imputations of incomplete variables 287 \nwere carried out at the composite level where applicable rather than at the item level due to 288 \nconvergence not being achieved. The imputation model included all study variables and four 289 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 16, 2025. ; https://doi.org/10.1101/2025.07.15.25331608doi: medRxiv preprint \n\n15 \n \nauxiliary variables (birth weight, GlycA, family income, and parents’ disability status) as well 290 \nas all two-way interactions amongst exposure, mediator, outcome, and confounders. 37 Based 291 \non the percentage of missing data,36 we produced 60 imputed datasets and used Rubin’s rules 292 \nto obtain the final imputed estimates of interest. 38 Results using multiply imputed data are 293 \nshown for preliminary analyses and causal mediation analyses.  294 \n 295 \nRESULTS 296 \nSample characteristics 297 \nParticipant characteristics are summarized in Table 1. At 11-12 years, around half (53.6%) of 298 \nchildren had poor CVH. A larger proportion of children with low or medium maternal 299 \neducation had poor CVH compared with their high maternal education peers (low: 55.0%, 300 \nmedium: 57.4%, high: 50.5%). At 2-11 years, a larger proportion of children with low or 301 \nmedium maternal education had fewer positive experiences (low: 63.4%, medium: 55.3%), 302 \ncompared with those with high maternal education (high: 51.3%). 303 \n 304 \nAssociations between socioeconomic disadvantage, positive experiences, and poor CVH 305 \nChildren with low or medium maternal education had a higher risk of poor CVH and fewer 306 \npositive experiences than their high maternal education peers, after adjusting for baseline 307 \nconfounders (Table 2). Children who had fewer positive experiences had a higher risk (risk 308 \nratio (RR)=1.17; 95% CI=1.00, 1.36) of poor CVH than those who had two or more positive 309 \nexperiences, after adjusting for all confounders and maternal education. These findings 310 \nconfirm the hypothesized associations depicted in Figure 1. 311 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 16, 2025. ; https://doi.org/10.1101/2025.07.15.25331608doi: medRxiv preprint \n\n16 \n \n 312 \nThe extent to which intervening on positive experiences could reduce socioeconomic 313 \ninequities in poor CVH  314 \nUsing the interventional effects approach, we estimated an absolute difference of 4.9% (95% 315 \nCI: -3.2%, 13.0%) and 5.6% (95% CI: -1.2%, 12.5%) in the prevalence of poor CVH in 316 \nchildren with low and medium maternal education when compared with their high maternal 317 \neducation peers. If we were able to intervene to effectively increase the levels of positive 318 \nexperiences amongst children with low maternal education to be equivalent to their high 319 \nmaternal education peers, we could potentially reduce this absolute risk difference by 1% (95% 320 \nCI: -0.8%, 1.5%). This translates to a relative reduction of 20.4% of socioeconomic inequities 321 \n(Table 3). Similarly, hypothetical interventions that promote positive experiences amongst 322 \nchildren with medium maternal education to be like their high maternal education peers, 323 \ncould potentially reduce the absolute risk difference by 0.5% (95% CI: -0.5%, 1.5%), leading 324 \nto a relative reduction of 8.9% of socioeconomic inequities. After the hypothetical 325 \ninterventions, 3.9% and 5.1% absolute socioeconomic difference in CVH would remain 326 \nrespectively among children with low and medium maternal education. 327 \n 328 \nResults from the sensitivity analysis omitting the neighborhood socioeconomic status showed 329 \nthat promoting positive experiences in children with low and medium maternal education to 330 \nbe like their high maternal education peers could reduce the absolute risk difference by 1.2% 331 \nand 0.6% respectively (see Supplementary file 6). 332 \n  333 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 16, 2025. ; https://doi.org/10.1101/2025.07.15.25331608doi: medRxiv preprint \n\n17 \n \nDISCUSSION 334 \nUsing prospective data from a national birth cohort, we estimated the potential reduction of 335 \nsocioeconomic inequities in children’s CVH if we could offer effective interventions to 336 \npromote positive experiences among children with low or medium maternal education to be 337 \nequivalent to their high maternal education peers. Our findings suggest a positive effect of 338 \npositive experiences to reduce socioeconomic inequities in CVH, especially in children with 339 \nlow maternal education. 340 \n 341 \nConsistent with previous findings, 21,39-41 we found that children with more positive 342 \nexperiences had lower risk of poor CVH, after controlling childhood adversity and other 343 \nconfounders. We build on existing evidence by evaluating the potential benefit of a 344 \nhypothetical intervention on positive experiences to reduce socioeconomic inequities in 345 \nchildren’s CVH. Children with medium maternal education (5.6%) show a slightly greater 346 \nabsolute risk difference with their high maternal education peers than the low maternal 347 \neducation group (4.9%). However, promoting positive experiences appears to reduce a larger 348 \nproportion of inequity among children with low maternal education. The greater benefit 349 \nobserved for children with low maternal education likely reflects the well-documented social 350 \ngradient in CVH, 7 where children from more disadvantaged families benefit more from 351 \ninterventions. Our estimates show that promoting positive experiences could reduce CVH 352 \ninequities by up to 20.4%, highlighting the potential value of investing in positive 353 \nexperiences as a key intervention target. These reductions in childhood are likely to 354 \naccumulate and translate to substantial social and health benefits in adulthood.25  355 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 16, 2025. ; https://doi.org/10.1101/2025.07.15.25331608doi: medRxiv preprint \n\n18 \n \n 356 \nSocioeconomic disadvantage can influence CVH through multiple interrelated pathways, 357 \nincluding positive experiences as examined here, and other mediators such as childhood 358 \nadversity, limited resources and healthcare access. 6,7 Given this complexity, no single 359 \nintervention will fully close the socioeconomic gap in children’s CVH. The residual 360 \ninequities that persist after the hypothetical intervention on positive experiences suggest that 361 \na multi-faceted and stacked approach is needed to address both upstream and downstream 362 \nfactors of CVH.42 363 \n 364 \nStrengths and limitations 365 \nThis study utilizes a national birth cohort that captured resourceful data on social, 366 \nenvironmental, and physical measures longitudinally. We also used the target trial framework 367 \nto provide clarity in the study design (e.g., eligibility criteria, treatment strategies). However, 368 \nsome limitations should be noted: (1) Selection bias: Although we conducted multiple 369 \nimputation to reduce selection bias due to missing data in the sample, we were unable to 370 \naccount for the CheckPoint sampling weights in the analysis, meaning that some selection 371 \nbias might remain and limit the generalisability of our findings; (2) Measurement bias: We 372 \nused maternal education as a single measure of family socioeconomic position, which may 373 \nunderestimate the influence of socioeconomic disadvantage on the outcome. In addition, 374 \nmeasurement errors may exist for parent-report or self-report measures, particularly with 375 \nrespect to the mediator and the outcome; and (3) Confounding bias: Despite adjusting for a 376 \nrange of potential confounders, residual or unmeasured confounding (e.g., racism, cultural 377 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 16, 2025. ; https://doi.org/10.1101/2025.07.15.25331608doi: medRxiv preprint \n\n19 \n \nnorms, policy environment) remains a possibility. 378 \n 379 \nImplications for future research and practice 380 \nOur findings suggest that enhancing positive experiences has the potential to reduce 381 \nsocioeconomic inequities in children’s CVH. This study reinforces the importance of 382 \nstrengths-based approaches in epidemiolocal research that examine the positive health assets 383 \nthat allow populations to thrive, including in the face of adversity. 43,44 We focused on a 384 \nnegative outcome in the present study; it is worthwhile to consider using a positive outcome 385 \nin future to check whether results are consistent. It would be also interesting to explore the 386 \npotential benefits of intervening on each type of positive experience to reduce socioeconomic 387 \ninequities in each CVH component. 21 Future work may also consider exploring the potential 388 \nbenefits in other countries and populations such as First Nations children.  389 \n 390 \nThe Australian Government’s Early Years Strategy  highlights the importance of a 391 \nstrengths-based approach, leveraging positive resources to support children in reaching their 392 \noptimal health. 15 The hypothetical intervention in our study that would be capable of 393 \nachieving an increase from “fewer than two” to “two or more” positive experiences remains 394 \nundetermined (i.e., what the intervention is in practice and how to deliver it is not specified). 395 \nCurrently, there is increasing attention to programs targeting positive experiences to improve 396 \nchildren’s health, such as the Healthy Communities Study in the US 45 and the Kids Building 397 \nFuture Healthy Mission  in Australia. 46 It is likely to achieve the maximum impact by 398 \ncombining strategies that promote positive experiences with a multi-faceted and sustained 399 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 16, 2025. ; https://doi.org/10.1101/2025.07.15.25331608doi: medRxiv preprint \n\n20 \n \napproach that considers other fundamental drivers of CVH inequities.  400 \n 401 \nCONCLUSIONS 402 \nThis study demonstrates that positive experiences partially mediate the relationship between 403 \nsocioeconomic disadvantage and poor CVH among Australian children. While promoting 404 \npositive experiences has the potential to reduce socioeconomic inequities in CVH, addressing 405 \nsocioeconomic disadvantage itself and other socially distributed drivers of CVD remain 406 \nimperative to achieve the maximum impact. 407 \n . 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The Healthy Communities Study: Its 533 \nRationale, Aims, and Approach. Am J Prev Med . Oct 2015;49(4):615-23. 534 \ndoi:10.1016/j.amepre.2015.06.029 535 \n46. Victorian Health Promotion Foundation. Kids Building Future Healthy. VicHealth. 20 536 \nDecember 2024, Accessed 25 May, 2023. 537 \nhttps://www.vichealth.vic.gov.au/programs-and-projects/campaigns-initiatives/future-healthy-538 \nminecraft 539 \n540 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 16, 2025. ; https://doi.org/10.1101/2025.07.15.25331608doi: medRxiv preprint \n\n27 \n \n 541 \nFigure 1. Directed acyclic graph depicting the assumed causal model conceptualizing the 542 \npathway from maternal education to children’s cardiovascular health via positive childhood 543 \nexperiences. 544 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 16, 2025. ; https://doi.org/10.1101/2025.07.15.25331608doi: medRxiv preprint \n\n28 \n \nTable 1. Descriptive information for all study variables in our sample (N=1874). Observed 545 \ndata are shown. 546 \n Frequency \n(%) \nMaternal education \nMissing \nHigh Medium Low  \nExposure      \nMaternal education      0 \nHigh  826 (44.1) - - -  \nMedium 619 (33.0) - - -  \nLow  429 (22.9) - - -  \nMediator      \nFewer positive experiences (<2)    464 (24.8) \nNo 631 (44.8) 313 (48.7) 206 (44.7) 112 (36.6)  \nYes 779 (55.2) 330 (51.3) 255 (55.3) 194 (63.4)  \nOutcome      \nCardiovascular health      815 (43.5) \nGood  491 (46.4) 251 (49.5) 146 (42.6) 94 (45.0)  \nPoor 568 (53.6) 256 (50.5) 197 (57.4) 115 (55.0)  \nBaseline confounders      \nChild's sex assigned at birth     0 \nFemale 919 (49.0) 412 (49.9) 295 (47.7) 212 (49.4)  \nMale 955 (51.0) 414 (50.1) 324 (52.3) 217 (50.6)  \nChild's ethnicity     0 \nAnglo or European 1616 (86.2) 696 (84.3) 551 (89.0) 369 (86.0)  \nMinoritized ethnic group 221 (11.8) 126 (15.3) 53 (8.6) 42 (9.8)  \nIndigenous 37 (2.0) 4 (0.5) 15 (2.4) 18 (4.2)  \nChild's disability status     0 \nNo 1785 (95.3) 792 (95.9) 582 (94.0) 411 (95.8)  \nYes 89 (4.7) 34 (4.1) 37 (6.0) 18 (4.2)  \nNeighbourhood socioeconomic status    0 \nNot disadvantaged 1322 (70.5) 658 (79.7) 411 (66.4) 253 (59.0)  \nDisadvantaged 552 (29.5) 168 (20.3) 208 (33.6) 176 (41.0)  \nIntermediate confounder      \nGestation age in weeks     13 (0.7) \n≥ 37 weeks 1746 (93.8) 782 (95.5) 568 (92.2) 396 (93.0)  \n<37 weeks 115 (6.2) 37 (4.5) 48 (7.8) 30 (7.0)  \nMaternal age at childbirth     0 \n≥ 27 1626 (86.8) 782 (94.7) 519 (83.8) 325 (75.8)  \n<27 248 (13.2) 44 (5.3) 100 (16.2) 104 (24.2)  \nFamily composition     0 \nTwo parents 1781 (95.0) 810 (98.1) 574 (92.7) 397 (92.5)  \nSingle parent 93 (5.0) 16 (1.9) 45 (7.3) 32 (7.5)  \nMultiple adversities (≥ 2)     170 (9.1) \nNo 1585 (93.0) 718 (94.6) 517 (92.3) 350 (90.9)  \nYes 119 (7.0) 41 (5.4) 43 (7.7) 35 (9.1)  \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 16, 2025. ; https://doi.org/10.1101/2025.07.15.25331608doi: medRxiv preprint \n\n29 \n \n 547 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 16, 2025. ; https://doi.org/10.1101/2025.07.15.25331608doi: medRxiv preprint \n\n30 \n \nTable 2. Generalized linear models examining the associations between maternal education, 548 \npositive childhood experiences, and poor cardiovascular health, using imputed data 549 \n(N=1874). 550 \n Risk ratio (95% CI) \nModel 1: \nUnadjusted \nModel 2: \nAdjusted for \nbaseline \nconfounders \nModel 3: \nAdjusted for \nbaseline and \nintermediate \nconfounders \nModel 4: \nAdjusted for \nbaseline, \nintermediate \nconfounders and \nmaternal \neducation \nAssociation with poor cardiovascular health \nLow maternal education \n(ref=high) 1.11 (0.92, 1.34) 1.09 (0.91, 1.32) - - \nMedium maternal education \n(ref=high) 1.11 (0.94, 1.30) 1.11 (0.94, 1.31) - - \nFewer positive experiences \n(ref=2 or more) 1.18 (1.01, 1.37) 1.17 (1.01, 1.36) 1.17 (1.00, 1.36) 1.17 (1.00, 1.36) \nAssociation with fewer positive experiences  \nLow maternal education \n(ref=high) 1.23 (1.05, 1.45) 1.19 (1.01, 1.41) - - \nMedium maternal education \n(ref=high) 1.10 (0.95, 1.28) 1.08 (0.93, 1.26) - - \nBaseline confounders controlled for were child’s sex, child’s ethnicity, child’s disability, and neighborhood 551 \nsocioeconomic status. Intermediate confounders controlled for were gestational age in weeks, maternal age at 552 \nchildbirth, family composition, and childhood adversity. CI, confidence interval; -, not applicable. 553 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 16, 2025. ; https://doi.org/10.1101/2025.07.15.25331608doi: medRxiv preprint \n\n31 \n \nTable 3. Results of evaluation of mediator interventions to close socioeconomic inequities in 554 \nchildren’s poor cardiovascular health (CVH) using the interventional effects approach, using 555 \nimputed data (N=1874). 556 \nGroup comparison  \nEstimate of \nabsolute risk \ndifference (%) \n95% CI \np \nvalue \nProportion of the \nsocioeconomic \ngap in poor CVH  \nLow versus high maternal education      \nExisting socioeconomic inequities in poor CVH (before \nintervening on positive childhood experiences)  4.9 (-3.2, 13.0) 0.23 100 \n  Reduction in inequities from intervening on positive \nchildhood experiences  1.0 (-0.8,2.8) 0.26 20.4 \n Remaining inequities  3.9 (-4.3,12.1) 0.35 79.6 \nMedium versus high maternal education      \nExisting socioeconomic inequities in poor CVH (before \nintervening on positive childhood experiences) 5.6 (-1.2,12.5) 0.10 100 \n  Reduction in inequities from intervening on positive \nchildhood experiences  0.5 (-0.5, 1.5) 0.32 8.9 \n Remaining inequities  5.1 (-1.8,12.1) 0.14 91.1 \n 557 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 16, 2025. ; https://doi.org/10.1101/2025.07.15.25331608doi: medRxiv preprint","source_license":"CC-BY-4.0","license_restricted":false}