Narrative reviews of paediatric NAFLD quote prevalences in the general population that range from 9% to 37%; however, no systematic review of the prevalence of NAFLD in children/adolescents has been ...conducted. We aimed to estimate prevalence of non-alcoholic fatty liver disease (NAFLD) in young people and to determine whether this varies by BMI category, gender, age, diagnostic method, geographical region and study sample size.
We conducted a systematic review and meta-analysis of all studies reporting a prevalence of NAFLD based on any diagnostic method in participants 1-19 years old, regardless of whether assessing NAFLD prevalence was the main aim of the study.
The pooled mean prevalence of NAFLD in children from general population studies was 7.6% (95%CI: 5.5% to 10.3%) and 34.2% (95% CI: 27.8% to 41.2%) in studies based on child obesity clinics. In both populations there was marked heterogeneity between studies (I2 = 98%). There was evidence that prevalence was generally higher in males compared with females and increased incrementally with greater BMI. There was evidence for differences between regions in clinical population studies, with estimated prevalence being highest in Asia. There was no evidence that prevalence changed over time. Prevalence estimates in studies of children/adolescents attending obesity clinics and in obese children/adolescents from the general population were substantially lower when elevated alanine aminotransferase (ALT) was used to assess NAFLD compared with biopsies, ultrasound scan (USS) or magnetic resonance imaging (MRI).
Our review suggests the prevalence of NAFLD in young people is high, particularly in those who are obese and in males.
Experiencing multiple adverse childhood experiences (ACEs) is a risk factor for many adverse outcomes. We explore associations of ACEs with educational attainment and adolescent health and the role ...of family and socioeconomic factors in these associations.
Using data from the Avon Longitudinal Study of Parents and Children (ALSPAC), a prospective cohort of children born in southwest England in 1991-1992, we assess associations of ACEs between birth and 16 years (sexual, physical, or emotional abuse; emotional neglect; parental substance abuse; parental mental illness or suicide attempt; violence between parents; parental separation; bullying; and parental criminal conviction, with data collected on multiple occasions between birth and age 16) with educational attainment at 16 years (n = 9,959) and health at age 17 years (depression, obesity, harmful alcohol use, smoking, and illicit drug use; n = 4,917). We explore the extent to which associations are robust to adjustment for family and socioeconomic factors (home ownership, mother and partner's highest educational qualification, household social class, parity, child's ethnicity, mother's age, mother's marital status, mother's depression score at 18 and 32 weeks gestation, and mother's partner's depression score at 18 weeks gestation) and whether associations differ according to socioeconomic factors, and we estimate the proportion of adverse educational and health outcomes attributable to ACEs or family or socioeconomic measures. Among the 9,959 participants (49.5% female) included in analysis of educational outcomes, 84% reported at least one ACE, 24% reported 4 or more ACEs, and 54.5% received 5 or more General Certificates of Secondary Education (GCSEs) at grade C or above, including English and Maths. Among the 4,917 participants (50.1% female) included in analysis of health outcomes, 7.3% were obese, 8.7% had depression, 19.5% reported smoking, 16.1% reported drug use, and 10.9% reported harmful alcohol use. There were associations of ACEs with lower educational attainment and higher risk of depression, drug use, and smoking. For example, odds ratios (ORs) for 4+ ACEs compared with no ACEs after adjustment for confounders were depression, 2.4 (1.6-3.8, p < 0.001); drug use, 3.1 (2.1-4.4, p < 0.001); and smoking, 2.3 (1.7-3.1, p < 0.001). Associations with educational attainment attenuated after adjustment but remained strong; for example, the OR after adjustment for confounders for low educational attainment comparing 4+ ACEs with no ACEs was 2.0 (1.7-2.4, p < 0.001). Associations with depression, drug use, and smoking were not altered by adjustment. Associations of ACEs with harmful alcohol use and obesity were weak. For example, ORs for 4+ ACEs compared with no ACEs after adjustment for confounders were harmful alcohol use, 1.4 (0.9-2.0, p = 0.10) and obesity, 1.4 (0.9-2.2, p = 0.13) We found no evidence that socioeconomic factors modified the associations of ACEs with educational or health outcomes. Population attributable fractions (PAFs) for the adverse educational and health outcomes range from 5%-15% for 4+ ACEs and 1%-19% for low maternal education. Using data from multiple questionnaires across a long period of time enabled us to capture a detailed picture of the cohort members' experience of ACEs; however, a limitation of our study is that this resulted in a high proportion of missing data, and our analyses assume data are missing at random.
This study demonstrates associations between ACEs and lower educational attainment and higher risks of depression, drug use, and smoking that remain after adjustment for family and socioeconomic factors. The low PAFs for both ACEs and socioeconomic factors imply that interventions that focus solely on ACEs or solely on socioeconomic deprivation, whilst beneficial, would miss most cases of adverse educational and health outcomes. This interpretation suggests that intervention strategies should target a wide range of relevant factors, including ACEs, socioeconomic deprivation, parental substance use, and mental health.
Previous research has demonstrated a graded relationship between the number of Adverse Childhood Experiences reported (an ACE score) and child outcomes. However, ACE scores lack specificity and ...ignore the patterning of adversities, which are informative for interventions. The aim of the present study was to explore the clustering of ACEs and whether this clustering differs by gender or is predicted by poverty. Data on 8,572 participants of the Avon Longitudinal Study of Parents and Children (ALSPAC) were used. ALSPAC is a regionally representative prenatal cohort of children born between 1991 and 1992 in the Avon region of South-West England. ACEs included parental divorce, death of a close family member, interparental violence, parental mental health problems, parental alcohol misuse, parental drug use, parental convictions, and sexual, emotional, and physical abuse, between birth and 19 years. Latent class analysis was used to derive ACE clusters and associations between poverty, gender, and the derived classes tested using multinomial logistic regression. Five latent classes were identified: “Low ACEs” (55%), “Parental separation and mother’s mental health problems” (18%), “Parental mental health problems, convictions and separation” (15%), “Abuse and mental health problems” (6%), and “Poly adversity” (6%). Death of a close family member and sexual abuse did not cluster with other adversities. The clustering did not differ by gender. Poverty was strongly related to both individual ACEs and clusters. These findings demonstrate that ACEs cluster in specific patterns and that poverty is strongly related to this. Therefore, reducing child poverty might be one strategy for reducing ACEs.
Background: Although cohort members tend to be healthy and affluent compared with the whole population, some studies indicate this does not bias certain exposure-outcome associations. It is less ...clear whether this holds when socioeconomic position (SEP) is the exposure of interest. Methods: As an illustrative example, we use data from the Avon Longitudinal Study of Parents and Children. We calculate estimates of maternal education inequalities in outcomes for which data are available on almost the whole cohort (birth weight and length, breast-feeding, preterm birth, maternal obesity, smoking during pregnancy, educational attainment). These are calculated for the full cohort (n~12,000) and in restricted subsamples defined by continued participation at age 10 years (n~7,000) and age 15 years (n~5,000). Results: Loss to follow-up was related both to SEP and outcomes. For each outcome, loss to follow-up was associated with underestimation of inequality, which increased as participation rates decreased (eg, mean birth-weight difference between highest and lowest SEP was 116 g 95% confidence interval = 78 to 153 in the full sample and 93 g 45 to 141 and 62 g 5 to 119 in those attending at ages 10 and 15 years, respectively). Conclusions: Considerable attrition from cohort studies may result in biased estimates of socioeconomic inequalities, and the degree of bias may worsen as participation rates decrease. However, even with considerable attrition (>50%), qualitative conclusions about the direction and approximate magnitude of inequalities did not change among most of our examples. The appropriate analysis approaches to alleviate bias depend on the missingness mechanism.
Mediation analysis seeks to explain the pathway(s) through which an exposure affects an outcome. Traditional, non-instrumental variable methods for mediation analysis experience a number of ...methodological difficulties, including bias due to confounding between an exposure, mediator and outcome and measurement error. Mendelian randomisation (MR) can be used to improve causal inference for mediation analysis. We describe two approaches that can be used for estimating mediation analysis with MR: multivariable MR (MVMR) and two-step MR. We outline the approaches and provide code to demonstrate how they can be used in mediation analysis. We review issues that can affect analyses, including confounding, measurement error, weak instrument bias, interactions between exposures and mediators and analysis of multiple mediators. Description of the methods is supplemented by simulated and real data examples. Although MR relies on large sample sizes and strong assumptions, such as having strong instruments and no horizontally pleiotropic pathways, our simulations demonstrate that these methods are unaffected by confounders of the exposure or mediator and the outcome and non-differential measurement error of the exposure or mediator. Both MVMR and two-step MR can be implemented in both individual-level MR and summary data MR. MR mediation methods require different assumptions to be made, compared with non-instrumental variable mediation methods. Where these assumptions are more plausible, MR can be used to improve causal inference in mediation analysis.
•There is a reliance on ACE scores and single adversity approaches in ACEs research.•We compare ACE scores, individual ACEs and latent class analysis (LCA) for early life inflammation.•LCA identified ...four clusters. ‘Maternal mental health problems’ was associated with lower CRP for girls.•IL-6 was higher for parental divorce and lower for emotional abuse, paternal mental health problems, parental offending and alcohol misuse.•Associations between paternal mental health problems and emotional abuse with lower IL-6 were only seen for boys.
Adverse childhood experiences (ACEs) have been associated with poorer health across the life course. Previous studies have used cumulative risk scores (ACE scores) or individual ACEs but these two approaches have important shortcomings. ACE scores assume that each adversity is equally important for the outcome of interest and the single adversity approach assumes that ACEs do not co-occur. Latent class analysis (LCA) is an alternative approach to operationalising ACEs data, identifying groups of people co-reporting similar ACEs. Here we apply these three approaches for ACEs operationalisation with inflammation in childhood with the aim of identifying particular ACEs or ACE combinations that are particularly associated with higher inflammation in early life.
Using data from the Avon Longitudinal Study of Parents and Children (ALSPAC) we compare ACE scores, single adversities and LCA-derived ACE clusters in their relationships with Interleukin-6 at age 9 (n = 4935) and C-Reactive Protein (CRP) at age 9 (n = 4887). ACEs included were parental separation/divorce, parental alcohol problems, parental mental health problems, parental offending, inter-parental violence, parental drug misuse, and physical, emotional and sexual abuse.
Two thirds of the sample reported at least one ACE. Mother’s mental health problems was the most frequently reported ACE (32.3 %). LCA identified four ACE classes – ‘Low ACEs’ (81.1 %), ‘Maternal mental health problems’ (10.3 %), ‘Maternal mental health problems and physical abuse’ (6.3 %) and ‘Parental conflict, mental health problems and emotional abuse’ (2.4 %). Parental separation/divorce was associated with higher IL-6. Parental alcohol problems, paternal mental health problems, parental convictions and emotional abuse were associated with lower levels of IL-6. Associations for paternal mental health problems and emotional abuse were only observed for boys. ACE score and LCA-derived ACE classes were not associated with differences in IL-6. Girls in the ‘Maternal mental health problems’ cluster had lower CRP levels.
Specific adversities and adversity combinations are important for differences in childhood inflammation. Some associations were only observed for girls or boys.
The prevalence of obesity has increased in the United Kingdom, and reliably measuring the impact on quality of life and the total healthcare cost from obesity is key to informing the ...cost-effectiveness of interventions that target obesity, and determining healthcare funding. Current methods for estimating cost-effectiveness of interventions for obesity may be subject to confounding and reverse causation. The aim of this study is to apply a new approach using mendelian randomisation for estimating the cost-effectiveness of interventions that target body mass index (BMI), which may be less affected by confounding and reverse causation than previous approaches.
We estimated health-related quality-adjusted life years (QALYs) and both primary and secondary healthcare costs for 310,913 men and women of white British ancestry aged between 39 and 72 years in UK Biobank between recruitment (2006 to 2010) and 31 March 2017. We then estimated the causal effect of differences in BMI on QALYs and total healthcare costs using mendelian randomisation. For this, we used instrumental variable regression with a polygenic risk score (PRS) for BMI, derived using a genome-wide association study (GWAS) of BMI, with age, sex, recruitment centre, and 40 genetic principal components as covariables to estimate the effect of a unit increase in BMI on QALYs and total healthcare costs. Finally, we used simulations to estimate the likely effect on BMI of policy relevant interventions for BMI, then used the mendelian randomisation estimates to estimate the cost-effectiveness of these interventions. A unit increase in BMI decreased QALYs by 0.65% of a QALY (95% confidence interval CI: 0.49% to 0.81%) per year and increased annual total healthcare costs by £42.23 (95% CI: £32.95 to £51.51) per person. When considering only health conditions usually considered in previous cost-effectiveness modelling studies (cancer, cardiovascular disease, cerebrovascular disease, and type 2 diabetes), we estimated that a unit increase in BMI decreased QALYs by only 0.16% of a QALY (95% CI: 0.10% to 0.22%) per year. We estimated that both laparoscopic bariatric surgery among individuals with BMI greater than 35 kg/m2, and restricting volume promotions for high fat, salt, and sugar products, would increase QALYs and decrease total healthcare costs, with net monetary benefits (at £20,000 per QALY) of £13,936 (95% CI: £8,112 to £20,658) per person over 20 years, and £546 million (95% CI: £435 million to £671 million) in total per year, respectively. The main limitations of this approach are that mendelian randomisation relies on assumptions that cannot be proven, including the absence of directional pleiotropy, and that genotypes are independent of confounders.
Mendelian randomisation can be used to estimate the impact of interventions on quality of life and healthcare costs. We observed that the effect of increasing BMI on health-related quality of life is much larger when accounting for 240 chronic health conditions, compared with only a limited selection. This means that previous cost-effectiveness studies have likely underestimated the effect of BMI on quality of life and, therefore, the potential cost-effectiveness of interventions to reduce BMI.
Mitochondria are organelles responsible for converting glucose into energy. Mitochondrial DNA is exclusively maternally inherited. The role of mitochondrial DNA haplogroups in the aetiology of ...cardiometabolic disease risk is not well understood.
Sex-specific associations between common European mitochondrial DNA haplogroups (H, U, J, T, K, V, W, I and X) and trajectories of cardiometabolic risk factors from birth to 18 years were examined in a prospective cohort. Cardiometabolic risk factors measured from birth/mid-childhood to 18 years included body mass index (BMI), fat and lean mass, systolic and diastolic blood pressure, pulse rate, high-density lipoprotein cholesterol (HDL-c), non-HDL-c and triglycerides. Fractional polynomial and linear spline multilevel models explored the sex-specific association between haplogroups and risk factor trajectories.
Among a total of 7,954 participants with 79,178 repeated measures per outcome, we found no evidence that haplogroups U, T, J, K and W were associated with cardiometabolic risk factors compared to haplogroup H. In females, haplogroup V was associated with 4.0% (99% CI: -7.5, -0.6) lower BMI at age one but associations did not persist at age 18. Haplogroup X was associated with 1.3kg (99% CI: -2.5, -0.2) lower lean mass at age 9 which persisted at 18. Haplogroup V and X were associated with 9.3% (99% CI: -0.4, 19.0) and 16.4% (99% CI: -0.5,33.3) lower fat mass at age 9, respectively, although confidence intervals spanned the null and associations did not persist at 18. In males, haplogroup I was associated with 2.4% (99% CI: -0.5, 5.3) higher BMI at age 7; widening to 5.1% (99% CI: -0.5, 10.6) at 18 with confidence intervals spanning the null.
Our study demonstrated little evidence of sex-specific associations between mitochondrial DNA haplogroups and cardiometabolic risk factors.
Cardiovascular disease (CVD) is influenced by genetic and environmental factors. Childhood maltreatment is associated with CVD and may modify genetic susceptibility to cardiovascular risk factors. We ...used genetic and phenotypic data from 100,833 White British UK Biobank participants (57% female; mean age = 55.9 years). We regressed nine cardiovascular risk factors/diseases (alcohol consumption, body mass index BMI, low-density lipoprotein cholesterol, lifetime smoking behaviour, systolic blood pressure, atrial fibrillation, coronary heart disease, type 2 diabetes, and stroke) on their respective polygenic scores (PGS) and self-reported exposure to childhood maltreatment. Effect modification was tested on the additive and multiplicative scales by including a product term (PGS*maltreatment) in regression models. On the additive scale, childhood maltreatment accentuated the effect of genetic susceptibility to higher BMI (Peffect modification: 0.003). Individuals not exposed to childhood maltreatment had an increase in BMI of 0.12 SD (95% CI: 0.11, 0.13) per SD increase in BMI PGS, compared to 0.17 SD (95% CI: 0.14, 0.19) in those exposed to all types of childhood maltreatment. On the multiplicative scale, similar results were obtained for BMI though these did not withstand to Bonferroni correction. There was little evidence of effect modification by childhood maltreatment in relation to other outcomes, or of sex-specific effect modification. Our study suggests the effects of genetic susceptibility to a higher BMI may be moderately accentuated in individuals exposed to childhood maltreatment. However, gene*environment interactions are likely not a major contributor to the excess CVD burden experienced by childhood maltreatment victims.
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