Racism and health and wellbeing among children and youth-An updated systematic review and meta-analysis.

BACKGROUND: Evidence of racism's health harms among children and youth is rapidly increasing, though attention to impacts on physical health and biomarker outcomes is more emergent. We performed a systematic review of recent publications to examine the association between racism and health among children and youth, with a meta-analysis of the specific relationships between racism and physical health and biomarkers. METHODS: We conducted a systematic literature search using four databases: Medline, PsycINFO, PubMed, and ERIC. Four inclusion criteria were used to identify eligible studies: (1) exposure was experiences of racism, (2) outcome was health and wellbeing, (3) quantitative methods were used to estimate the association between racism and health outcomes, and (4) the effect size of associations between racism and health and wellbeing was reported for participants aged 0-24 years. Correlation coefficients were used to report the pooled effect size for each outcome indicator. RESULTS: There were 463 eligible studies included in the screening process, with 42 studies focusing on physical health or biomarker outcomes. Random-effects meta-analysis found minimal to moderate positive associations between racism and C-reactive protein, Interleukin 6, body mass index (BMI), obesity, systolic blood pressure, salivary cortisol, asthma, and somatic symptoms. There were marginal positive associations between racism and Tumour Necrosis Factor-α, cortisol collected via saliva, urine and hair, BMI-z score, and diastolic blood pressure, with imprecise estimates and wide confidence intervals. CONCLUSIONS: Racism is associated with negative physical health and biomarker outcomes that relate to multiple physiological systems and biological processes in childhood and adolescence. This has implications for health and wellbeing during childhood and adolescence and future chronic disease risk. Collective and structural changes to eliminate racism and create a healthy and equitable future for all children and youth are urgently required.

Prevalence and Determinants of Food Allergy in the Era of Early Allergen Introduction: the EarlyNuts Population-Based Study.

BACKGROUND: Infant feeding guidelines in Australia changed in 2016 to recommend introducing common allergy-causing foods by age 1 year to prevent food allergy. Although most Australian infants now eat peanut and egg by age 6 months, some still develop food allergy despite the early introduction of allergens. OBJECTIVES: To describe the prevalence of food allergy in a cohort recruited after introducing the nationwide allergy prevention recommendations; identify characteristics of infants who developed allergy despite early introduction of allergens; and estimate the causal effect of modifiable exposures on food allergy prevalence and whether this differed between infants who were introduced to allergens before or after age 6 months. METHODS: We recruited a population-based sample of 12-month-old infants in Melbourne, Australia. Infants had skin prick tests to four foods and parents completed questionnaires. Infants with evidence of sensitization were offered oral food challenges. Prevalence estimates were adjusted using inverse probability weighting. RESULTS: In a cohort of infants (n = 1,420) in which nearly all infants had been introduced to common allergens such as egg, milk, and peanut by age 1 year, the prevalence of food allergy remained high at 11.3% (95% CI, 9.6-13.4). Infants who developed food allergy despite introduction of the allergen by age 6 months were more likely to have Asian-born parents. Early-onset moderate or severe eczema was associated with an increased odds of food allergy irrespective of whether allergens were introduced before or after age 6 months. Among infants who were introduced to peanut at age 6 months or earlier, antibiotic use by age 6 months was associated with an increased odds of peanut allergy (adjusted odds ratio = 6.03; 95% CI, 1.15-31.60). CONCLUSIONS: In a cohort in which early allergen introduction was common, the prevalence of food allergy remained high. Infants who developed food allergy despite introduction of the respective allergen by age 6 months were more likely to have had Asian parents and early-onset eczema. New interventions are needed for infants with a phenotype of food allergy that is not amenable to early allergen introduction.

The effects of adverse and positive experiences on cardiovascular health in Australian children.

BACKGROUND: Limited evidence suggests that positive experiences in childhood may promote cardiovascular health, providing additional opportunities for prevention and early intervention. This study aimed to examine the effects of adverse and positive experiences on cardiovascular health in late childhood. METHODS: Data sources: Longitudinal Study of Australian Children (N = 1874). EXPOSURES: Adverse and positive experiences assessed repeatedly (age 0-11 years). OUTCOMES: Cardiovascular health (high versus low or moderate) quantified by four health behaviors (diet, physical activity, cigarette smoking, and sleep) and four health factors (body mass index, non-high-density lipoprotein, blood pressure, and blood glucose) (age 11-12 years) as per the American Heart Association's Life's Essential 8 metrics. ANALYSES: Separate generalized linear models with log-Poisson links were used to estimate the effects of adverse and positive experiences on cardiovascular health, adjusting for confounders. RESULTS: Children exposed to multiple adverse experiences (≥ 2) were less likely to have high cardiovascular health (RR = 0.82, 95% CI = 0.67 to 1.02) than those not exposed. Children exposed to multiple positive experiences (≥ 2) were more likely to have high cardiovascular health (RR = 1.14, 95% CI = 0.94 to 1.38) than those not exposed. Stratified analyses suggested that exposure to multiple positive experiences might buffer the detrimental effects of multiple adverse experiences on cardiovascular health. CONCLUSIONS: Both adverse and positive experiences were found to be modestly associated with cardiovascular health in Australian children. Future research and practice should not only consider addressing childhood adversity but also use a strengths-based approach to promoting positive experiences to improve cardiovascular health.

Longitudinal peanut and Ara h 2 specific-IgE, -IgG4, and -IgG4/-IgE ratios are associated with the natural resolution of peanut allergy in childhood.

BACKGROUND: There are no studies of longitudinal immunoglobulin measurements in a population-based cohort alongside challenge-confirmed peanut allergy outcomes. Little is known about biomarkers for identifying naturally resolving peanut allergy during childhood. OBJECTIVES: To measure longitudinal trends in whole peanut and component Ara h 2 sIgE and sIgG4 in the first 10 years of life, in a population cohort of children with challenge-confirmed peanut allergy, and to determine whether peanut-specific immunoglobulin levels or trends are associated with peanut allergy persistence or resolution by 10 years of age. METHODS: One-year-old infants with challenge-confirmed peanut allergy (n = 156) from the HealthNuts study (n = 5276) were prospectively followed at ages 4, 6, and 10 years with questionnaires, skin prick tests, oral food challenges, and plasma total-IgE, sIgE and sIgG4 to peanut and Ara h 2. RESULTS: Peanut allergy resolved in 33.9% (95% CI = 25.3%, 43.3%) of children by 10 years old with most resolving (97.4%, 95% CI = 86.5%, 99.9%) by 6 years old. Decreasing Ara h 2 sIgE (p = .01) and increasing peanut sIgG4 (p < .001), Ara h 2 sIgG4 (p = .01), peanut sIgG4/sIgE (p < .001) and Ara h 2 sIgG4/sIgE (p < .001) from 1 to 10 years of age were associated with peanut allergy resolution. Peanut sIgE measured at 1 year old had the greatest prognostic value (AUC = 0.75 [95% CI = 0.66, 0.82]); however, no single threshold produced both high sensitivity and specificity. CONCLUSION: One third of infant peanut allergy resolved by 10 years of age. Decreasing sIgE and sIgG4 to peanut and Ara h 2 over time were associated with natural resolution of peanut allergy. However, biomarker levels at diagnosis were not strongly associated with the natural history of peanut allergy.

The Prevalence of IgE-Mediated Food Allergy and Other Allergic Diseases in the First 10 Years: The Population-Based, Longitudinal HealthNuts Study.

BACKGROUND: There are limited longitudinal data on the population prevalence of allergic conditions during childhood, and few studies have incorporated the reference standard oral food challenge to confirm food allergy. OBJECTIVE: To describe the population prevalence of IgE-mediated food allergy, eczema, asthma, and rhinitis at ages 6 and 10 years in Melbourne, Australia. METHODS: The HealthNuts study recruited 5,276 1-year-old infants in Melbourne, Australia, with repeat assessments at ages 6 and 10 years. At ages 6 and 10 years, carers completed a questionnaire on symptoms and doctor diagnosis of allergic conditions (International Study of Asthma and Allergies in Children). Children were invited to attend a clinic assessment including skin prick test, lung function tests, and oral food challenges when indicated. To minimize the impact of attrition bias, prevalence estimates among participants at ages 6 and 10 years were weighted to reflect characteristics of the whole cohort at recruitment. RESULTS: In total, 4,455 and 4,065 families participated at ages 6 and 10 years, respectively (84% and 77% of the original cohort). Of those, 73% and 55% of participants ages 6 and 10 years, respectively, completed clinical assessments. Overall, 36.5% (95% CI, 34.8-38.2) and 38.2% (95% CI, 36.5-40.1%) of 6- and 10-year-olds had at least one current allergic disease, and around one third of those had two or more allergic diseases. Food allergy occurred in 6.4% (95% CI, 5.6-7.2) of 6-year olds and 6.3% (95% CI, 5.5-7.2) of 10-year-olds. Among infants with challenge-confirmed food allergy in infancy, 45% had persistent disease at age 10 years. The prevalence of current diagnosed asthma at ages 6 and 10 years were 12.1% (95% CI, 10.9-13.3) and 13.1% (95% CI, 11.9-14.4), respectively, current eczema decreased slightly from 15.3% (95% CI, 14.1-19.7) at age 6 years to 12.9% (95% CI, 11.7-14.2) at age 10 years, and current rhinitis increased from 15.1% (95% CI, 13.9-16.5) at age 6 years to 25.0% (95% CI, 23.4-26.7) at age 10 years. CONCLUSIONS: Allergic diseases affect 40% of primary school-age children; one third have multiple allergic diagnoses. Challenge-confirmed food allergy prevalence remains high, and 45% of infants with food allergy have persistent disease to age 10 years.

Should I Take Aspirin? (SITA): randomised controlled trial of a decision aid for cancer chemoprevention.

BACKGROUND: Australian guidelines recommend that people aged 50-70 years consider taking low-dose aspirin to reduce their risk of colorectal cancer (CRC). AIM: To determine the effect of a consultation with a researcher before an appointment in general practice using a decision aid presenting the benefits and harms of taking low-dose aspirin compared with a general CRC prevention brochure on patients' informed decision making and low-dose aspirin use. DESIGN AND SETTING: Individually randomised controlled trial in six general practices in Victoria, Australia, from October 2020 to March 2021. METHOD: Participants were recruited from a consecutive sample of patients aged 50-70 years attending a GP. The intervention was a consultation using a decision aid to discuss taking aspirin to reduce CRC risk while control consultations discussed reducing CRC risk generally. Self-reported co-primary outcomes were the proportion of individuals making informed choices about taking aspirin at 1 month and on low-dose aspirin uptake at 6 months, respectively. The intervention effect was estimated using a generalised linear model and reported with Bonferroni-adjusted 95% confidence intervals (CIs) and P-values. RESULTS: A total of 261 participants (86% of eligible patients) were randomised into trial arms (n = 129 intervention; n = 132 control). Of these participants, 17.7% (n = 20/113) in the intervention group and 7.6% (n = 9/118) in the control group reported making an informed choice about taking aspirin at 1 month, an estimated 9.1% (95% CI = 0.29 to 18.5) between-arm difference in proportions (odds ratio [OR] 2.47, 97.5% CI = 0.94 to 6.52, P = 0.074). The proportions of individuals who reported taking aspirin at 6 months were 10.2% (n = 12/118) of the intervention group versus 13.8% (n = 16/116) of the control group, an estimated between-arm difference of -4.0% (95% CI = -13.5 to 5.5; OR 0.68 [97.5% CI = 0.27 to 1.70, P = 0.692]). CONCLUSION: The decision aid improved informed decision making but this did not translate into long-term regular use of aspirin to reduce CRC risk. In future research, decision aids should be delivered alongside various implementation strategies.

Infant food allergy phenotypes and association with lung function deficits and asthma at age 6 years: a population-based, prospective cohort study in Australia.

BACKGROUND: Food allergy is considered a precursor to asthma in the context of the atopic march, but the relationship between infant food allergy phenotypes and lung function and asthma in childhood is unclear. We aimed to examine the association between food sensitisation and challenge-confirmed food allergy in infancy, as well as persistent and resolved food allergy up to age 6 years, and the risk of lung function deficits and asthma at age 6 years. METHODS: The longitudinal, population-based HealthNuts cohort study in Melbourne, VIC, Australia, recruited 5276 infants children aged 1 year who attended council-run immunisation sessions between Sept 28, 2007, and Aug 5, 2011. At age 1 year, all children completed skin prick testing to four food allergens (egg, peanut, sesame, and either shrimp or cow's milk) and an oral food challenge (egg, peanut, and sesame) at the Royal Children's Hospital in Melbourne. Parents completed questionnaires about their infant's allergy history, demographic characteristics, and environmental exposures. At age 6 years, children were invited for a health assessment that included skin prick testing for ten foods (milk, egg, peanut, wheat, sesame, soy, shrimp, cashew, almond, and hazelnut) and eight aeroallergens (alternaria, cladasporum, house dust mite, cat hair, dog hair, bermuda grass, rye grass, and birch mix), oral food challenges, and lung function testing by spirometry. Questionnaires completed by parents (different to those completed at age 1 year) captured the child's allergy and respiratory history and demographics. We investigated associations between food allergy phenotypes (food-sensitised tolerance or food allergy; and ever, transient, persistent, or late-onset food allergy), lung function spirometry measures (forced expiratory volume in 1 sec [FEV1] and forced vital capacity [FVC] z-scores, FEV1/FVC ratio, forced expiratory flow at 25% and 75% of the pulmonary volume [FEF25-75%], and bronchodilator responsiveness), and asthma using regression methods. Only children with complete data on the exposure, outcome, and confounders were included in models. Infants without food sensitisation or food allergy at age 1 year and 6 years served as the reference group. FINDINGS: Of 5276 participants, 3233 completed the health assessment at age 6 years and were included in this analysis. Food allergy, but not food-sensitised tolerance, at age 1 year was associated with reduced FEV1 and FVC (aß -0·19 [95% CI -0·32 to -0·06] and -0·17 [-0·31 to -0·04], respectively) at age 6 years. Transient egg allergy was associated with reduced FEV1 and FVC compared with never having egg allergy (-0·18 [95% CI -0·33 to -0·03] and -0·15 [-0·31 to 0·00], respectively), whereas persistent egg allergy was not (FEV1 -0·09 [-0·48 to 0·31]; FVC -0·20 [-0·62 to 0·21]). Transient peanut allergy was associated with reduced FEV1 and FVC (FEV1 aß -0·37 [-0·79 to 0·04] and FVC aß -0·55 [-0·98 to -0·12]), in addition to persistent peanut allergy (FEV1 aß -0·30 [-0·54 to -0·06] and FVC aß-0·30 [-0·55 to -0·05]), and late-onset peanut allergy (FEV1 aß -0·62 [-1·06 to -0·18] and FVC aß-0·49 [-0·96 to -0·03]). Estimates suggested that food-sensitised tolerance and food allergy were associated with reduced FEF25-75%, although some estimates were imprecise. Food allergy phenotypes were not associated with an FEV1/FVC ratio. Late-onset peanut allergy was the only allergy phenotype that was possibly associated with increased risk of bronchodilator responsiveness (2·95 [95% CI 0·77 to 11·38]). 430 (13·7%) of 3135 children were diagnosed with asthma before age 6 years (95% CI 12·5-15·0). Both food-sensitised tolerance and food allergy at age 1 year were associated with increased asthma risk at age 6 years (adjusted odds ratio 1·97 [95% CI 1·23 to 3·15] and 3·69 [2·81 to 4·85], respectively). Persistent and late-onset peanut allergy were associated with higher asthma risk (3·87 [2·39 to 6·26] and 5·06 [2·15 to 11·90], respectively). INTERPRETATION: Food allergy in infancy, whether it resolves or not, is associated with lung function deficits and asthma at age 6 years. Follow-up studies of interventions to prevent food allergy present an opportunity to examine whether preventing these food allergies improves respiratory health. FUNDING: National Health & Medical Research Council of Australia, Ilhan Food Allergy Foundation, AnaphylaxiStop, the Charles and Sylvia Viertel Medical Research Foundation, the Victorian Government's Operational Infrastructure Support Program.

The impact of strict lockdowns on the mental health and well-being of people living in Australia during the first year of the COVID-19 pandemic.

BACKGROUND: There are limited longitudinal studies on the effects of the COVID-19 pandemic on mental health and well-being, including the effects of imposed restrictions and lockdowns. AIMS: This study investigates how living in a pandemic, and related lockdowns and restrictions, affected the mental health of people living in Australia during the first year of the COVID-19 pandemic. METHOD: A total of 875 people living in Australia participated in a longitudinal survey from 27 May to 14 December 2020. This time period includes dates that span pre-, during and post-wave 2 lockdowns in Australia, with strict and sustained public health measures. Linear mixed models were fitted to investigate the effect of lockdown on depression and anxiety symptoms. RESULTS: Symptoms of depression and anxiety improved over time, during and after lockdowns. More adverse mental health symptoms were observed for people with a history of medical or mental health problems, caring responsibilities, more neurotic personality traits or less conscientiousness, and for people who were younger. People who reported being more conscientious reported better mental health. CONCLUSIONS: Despite notoriously strict lockdowns, participants did not experience a deterioration of mental health over time. Results suggest a lack of significant adverse effects of lockdown restrictions on mental health and well-being. Findings highlight cohorts that could benefit from targeted mental health support and interventions, so that public policy can be better equipped to support them, particularly if future strict public health measures such as lockdowns are being considered or implemented for the COVID-19 pandemic and other disasters.

Multiple imputation approaches for handling incomplete three-level data with time-varying cluster-memberships.

Three-level data arising from repeated measures on individuals clustered within higher-level units are common in medical research. A complexity arises when individuals change clusters over time, resulting in a cross-classified data structure. Missing values in these studies are commonly handled via multiple imputation (MI). If the three-level, cross-classified structure is modeled in the analysis, it also needs to be accommodated in the imputation model to ensure valid results. While incomplete three-level data can be handled using various approaches within MI, the performance of these in the cross-classified data setting remains unclear. We conducted simulations under a range of scenarios to compare these approaches in the context of an acute-effects cross-classified random effects substantive model, which models the time-varying cluster membership via simple additive random effects. The simulation study was based on a case study in a longitudinal cohort of students clustered within schools. We evaluated methods that ignore the time-varying cluster memberships by taking the first or most common cluster for each individual; pragmatic extensions of single- and two-level MI approaches within the joint modeling (JM) and the fully conditional specification (FCS) frameworks, using dummy indicators (DI) and/or imputing repeated measures in wide format to account for the cross-classified structure; and a three-level FCS MI approach developed specifically for cross-classified data. Results indicated that the FCS implementations performed well in terms of bias and precision while JM approaches performed poorly. Under both frameworks approaches using the DI extension should be used with caution in the presence of sparse data.

Evaluation of approaches for accommodating interactions and non-linear terms in multiple imputation of incomplete three-level data.

Three-level data structures arising from repeated measures on individuals clustered within larger units are common in health research studies. Missing data are prominent in such studies and are often handled via multiple imputation (MI). Although several MI approaches can be used to account for the three-level structure, including adaptations to single- and two-level approaches, when the substantive analysis model includes interactions or quadratic effects, these too need to be accommodated in the imputation model. In such analyses, substantive model compatible (SMC) MI has shown great promise in the context of single-level data. Although there have been recent developments in multilevel SMC MI, to date only one approach that explicitly handles incomplete three-level data is available. Alternatively, researchers can use pragmatic adaptations to single- and two-level MI approaches, or two-level SMC-MI approaches. We describe the available approaches and evaluate them via simulations in the context of three three-level random effects analysis models involving an interaction between the incomplete time-varying exposure and time, an interaction between the time-varying exposure and an incomplete time-fixed confounder, or a quadratic effect of the exposure. Results showed that all approaches considered performed well in terms of bias and precision when the target analysis involved an interaction with time, but the three-level SMC MI approach performed best when the target analysis involved an interaction between the time-varying exposure and an incomplete time-fixed confounder, or a quadratic effect of the exposure. We illustrate the methods using data from the Childhood to Adolescence Transition Study.

Evaluation of approaches for multiple imputation of three-level data.

BACKGROUND: Three-level data arising from repeated measures on individuals who are clustered within larger units are common in health research studies. Missing data are prominent in such longitudinal studies and multiple imputation (MI) is a popular approach for handling missing data. Extensions of joint modelling and fully conditional specification MI approaches based on multilevel models have been developed for imputing three-level data. Alternatively, it is possible to extend single- and two-level MI methods to impute three-level data using dummy indicators and/or by analysing repeated measures in wide format. However, most implementations, evaluations and applications of these approaches focus on the context of incomplete two-level data. It is currently unclear which approach is preferable for imputing three-level data. METHODS: In this study, we investigated the performance of various MI methods for imputing three-level incomplete data when the target analysis model is a three-level random effects model with a random intercept for each level. The MI methods were evaluated via simulations and illustrated using empirical data, based on a case study from the Childhood to Adolescence Transition Study, a longitudinal cohort collecting repeated measures on students who were clustered within schools. In our simulations we considered a number of different scenarios covering a range of different missing data mechanisms, missing data proportions and strengths of level-2 and level-3 intra-cluster correlations. RESULTS: We found that all of the approaches considered produced valid inferences about both the regression coefficient corresponding to the exposure of interest and the variance components under the various scenarios within the simulation study. In the case study, all approaches led to similar results. CONCLUSION: Researchers may use extensions to the single- and two-level approaches, or the three-level approaches, to adequately handle incomplete three-level data. The two-level MI approaches with dummy indicator extension or the MI approaches based on three-level models will be required in certain circumstances such as when there are longitudinal data measured at irregular time intervals. However, the single- and two-level approaches with the DI extension should be used with caution as the DI approach has been shown to produce biased parameter estimates in certain scenarios.