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BACKGROUND: Neurodevelopmental trajectories of preterm children may have changed due to changes in care and in society. We aimed to compare neurodevelopmental trajectories in early and moderately late preterm children, measured using the Developmental (D)-score, in two cohorts born 15 years apart. METHODS: We included early preterm and moderately late preterm children from two Dutch cohorts (LOLLIPOP, 2002-2003 and ePREM, 2016-2017). ePREM counterparts were matched to LOLLIPOP participants by gestational age and sex. D-score trajectories were summarized by a multilevel model with random intercepts and random slopes, and multigroup analyses were used to test if the intercepts and slopes differed across cohorts. RESULTS: We included 1686 preterm children (1071 moderately late preterm, 615 early preterm) from LOLLIPOP, and matched these with 1686 ePREM counterparts. The neurodevelopmental trajectories of the two cohorts were mostly similar. For early preterm children, we found no statistically significant differences. For moderately late preterm children, both the intercept (43.0 vs. 42.3, p < 0.001) and slope (23.5 vs. 23.9, p = 0.002) showed some, but only clinically minor, differences. CONCLUSION: Developmental trajectories, measured using the D-score, in the first four years of life are comparable and stable across a period of 15 years for both early and moderately late preterm children. IMPACT: Neurodevelopmental trajectories are similar for early and moderately late preterm children born 15 years apart and thus seem quite stable in time. The validated Developmental score visualizes these trajectories based on developmental milestone attainment Because of its stability over time, the Developmental score trajectory may aid clinicians in neurodevelopmental assessment of preterm children as this simplifies monitoring and interpretation, similar to a growth chart.
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BACKGROUND: Educational inequalities in major depressive disorder (MDD) pose a major challenge. Tackling this issue requires evidence on the long-term impact of intervening on modifiable factors, for example lifestyle and psychosocial factors. For this reason, we aimed to simulate the development of educational inequalities in MDD across the life course, and to estimate the potential impact of intervening on modifiable factors. METHODS: We used data from the prospective Dutch Lifelines Cohort Study to estimate the required input for a continuous-time microsimulation. The microsimulation allowed us to project the development of educational inequalities in MDD between ages 18 and 65, and to assess the potential benefit of intervening on quality of social contacts, health literacy and smoking. RESULTS: On average, an additional 19.1% of individuals with low education will ever experience MDD between ages 18 and 65 compared with those with high education. Additionally, individuals with low education generally will develop MDD 0.9 years earlier and spend 1.2 years more with MDD, than individuals with high education. Improving the quality of social contacts in individuals with low education produced the largest effect; it would reduce the inequalities in the prevalence, onset and duration of MDD by an average of 18.4%, 18.3% and 28.6%, respectively. CONCLUSIONS: Intervening on modifiable factors, particularly quality of social contacts, in individuals with low education could help reduce the estimated educational inequalities in MDD over the life course.
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Transtorno Depressivo Maior , Escolaridade , Humanos , Transtorno Depressivo Maior/epidemiologia , Adulto , Feminino , Pessoa de Meia-Idade , Prevalência , Masculino , Adolescente , Países Baixos/epidemiologia , Idoso , Adulto Jovem , Estudos Prospectivos , Estudos de Coortes , Fatores Socioeconômicos , Disparidades nos Níveis de Saúde , Fatores de Tempo , Simulação por ComputadorRESUMO
BACKGROUND: Educational inequalities in metabolic syndrome (MetS) are a growing public health concern. Intervening on modifiable factors may help reduce these inequalities, but there is a need for evidence on the long-term impact of intervening on these factors. Thus, we simulate the development of educational inequalities in MetS across the life course and assess the impact of intervening on the modifiable factors that contribute to these inequalities. METHODS: We used data from the prospective multigenerational Dutch Lifelines Cohort Study to estimate the required input for a continuous-time microsimulation. The microsimulation projects the development of educational inequalities in MetS between ages 18 and 65, and assesses the potential benefit of intervening on smoking, alcohol use, diet quality, and health literacy. FINDINGS: The likelihood of ever experiencing MetS between ages 18 and 65 varies from 32.5% among high educated women to 71.5% among low educated men. On average, 27.6% more individuals with low education will ever experience MetS between ages 18 and 65 compared to those with high education. Additionally, individuals with low education generally will develop MetS 2.3 years earlier, and will spend an extra 2.6 years with MetS, compared to individuals with high education. Changes to smoking behaviours in individuals with low education produced the largest effect; it would reduce inequalities in prevalence, timing and duration by an average of 7.5%, 9.5%, and 6.9%, respectively. CONCLUSIONS: Interventions targeting the modifiable factors included in this study, especially smoking, could help reduce the estimated educational inequalities in MetS over the life course.
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Educação em Saúde , Desigualdades de Saúde , Síndrome Metabólica , Determinantes Sociais da Saúde , Síndrome Metabólica/epidemiologia , Fatores de Tempo , Prevalência , Estudos Prospectivos , Humanos , Masculino , Feminino , Adolescente , Adulto Jovem , Adulto , Pessoa de Meia-Idade , IdosoRESUMO
BACKGROUND: Parental health literacy may explain the relationship between parental socioeconomic status (SES) and paediatric metabolic syndrome (MetS). For this reason, we assessed to what extent parental health literacy mediates the relationships between parental SES and paediatric MetS. METHODS: We used data from the prospective multigenerational Dutch Lifelines Cohort Study. Our sample consisted of 6683 children with an average follow-up of 36.2 months (SD 9.3) and a mean baseline age of 12.8 years (SD 2.6). We used natural effects models to assess the natural direct, natural indirect and total effects of parental SES on MetS. RESULTS: On average, an additional 4 years of parental education, e.g. university instead of secondary school, would lead to continuous MetS (cMetS) scores that were 0.499 (95% confidence interval (CI): 0.364-0.635) units lower, which is a small effect (d: 0.18). If parental income and occupational level were 1 SD higher, on average cMetS scores were 0.136 (95% CI: 0.052-0.219) and 0.196 (95% CI: 0.108-0.284) units lower, respectively; these are both small effects (d: 0.05 and 0.07, respectively). Parental health literacy partially mediated these pathways; it accounted for 6.7% (education), 11.8% (income) and 8.3% (occupation) of the total effect of parental SES on paediatric MetS. CONCLUSIONS: Socioeconomic differences in paediatric MetS are relatively small, the largest being by parental education. Improving parental health literacy may reduce these inequalities. Further research is needed into the mediating role of parental health literacy on other socioeconomic health inequalities in children.
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Letramento em Saúde , Síndrome Metabólica , Humanos , Criança , Síndrome Metabólica/epidemiologia , Estudos de Coortes , Estudos Prospectivos , Classe Social , Pais , Fatores SocioeconômicosRESUMO
BACKGROUND: There is no consensus regarding the definition of pediatric metabolic syndrome (MetS). This study assessed the impact of alternative definitions on the prevalence, children identified, and association with socioeconomic status (SES). METHODS: Data were from the prospective multigenerational Dutch Lifelines Cohort Study. At baseline, 9754 children participated, and 5085 (52.1%) with average follow-up of 3.0 (SD = 0.75) years were included in the longitudinal analyses; median ages were 12 (IQR = 10-14) and 14 years (IQR = 12-15), respectively. We computed MetS prevalence according to five published definitions and measured the observed proportion of positive agreement. We used logistic regression to assess the SES-MetS association, adjusted for age and sex. Longitudinal models were also adjusted for baseline MetS. RESULTS: MetS prevalence and positive agreement varied between definitions, from 0.7 to 3.0% and from 0.34 (95% CI: 0.28; 0.41) to 0.66 (95% CI: 0.58; 0.75) at baseline, respectively. We consistently found a socioeconomic gradient; in the longitudinal analyses, each additional year of parental education reduced the odds of having MetS by 8% (95% CI: 1%; 14%) to 19% (95% CI: 7%; 30%). CONCLUSIONS: Alternative MetS definitions had differing prevalence estimates and agreed on 50% of the average number of cases. Additionally, regardless of the definition, low SES was a risk factor for MetS. IMPACT: Little is known about the impact of using different definitions of pediatric metabolic syndrome on study results. Our study showed that the choice of pediatric metabolic syndrome definition produces very different prevalence estimates. We also showed that the choice of definition influences the socioeconomic gradient. However, low socioeconomic status was consistently a risk factor for having pediatric metabolic syndrome. In conclusion, studies using different definitions of metabolic syndrome could be reasonably compared when investigating the association with socioeconomic status but not always validly when comparing prevalence studies.
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Síndrome Metabólica/metabolismo , Classe Social , Adolescente , Adulto , Criança , Pré-Escolar , Humanos , Lactente , Recém-Nascido , Síndrome Metabólica/epidemiologia , Pessoa de Meia-Idade , Prevalência , Estudos ProspectivosRESUMO
BACKGROUND: Socioeconomic inequalities contribute to childhood overweight. Identifying mediators could help reduce these inequalities. OBJECTIVE: We assessed to what extent and how parental health literacy and health behaviours mediate the relationship between parental socioeconomic status and childhood overweight. METHODS: Data were taken from the multigenerational prospective Dutch Lifelines Cohort Study. We included 6683 children, baseline age 9.8 years (SD = 2.6), with an average follow-up of 36.2 months (SD = 9.3). Overweight was defined using age- and sex-specific cut-offs. Three indicators of socioeconomic status were included: education, income and occupation. We assessed the mediating role of parental health literacy and health behaviours (smoking, diet, physical activity and alcohol) using causal mediation. RESULTS: Four additional years of education and an SD-increase in both income and occupation decreased the odds of childhood overweight by 42%, 12% and 20%, respectively. Only parental smoking independently mediated the relationship of both education (6.6%) and occupation (5.7%) with overweight. Parental health behaviours jointly explained 8.4% (education), 19.4% (income) and 9.8% (occupation) per relationship. Lastly, adding parental health literacy explained 10.8% (education), 27.4% (income) and 13.3% (occupation) of these relationships. CONCLUSIONS: We found large socioeconomic inequalities in childhood overweight. Remarkably, parental smoking was a key mediator. Therefore, prevention targeting smoking may reduce socioeconomic inequalities in childhood overweight.
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Comportamentos Relacionados com a Saúde , Letramento em Saúde , Pais , Obesidade Infantil , Fatores Socioeconômicos , Humanos , Feminino , Masculino , Letramento em Saúde/estatística & dados numéricos , Criança , Pais/psicologia , Obesidade Infantil/epidemiologia , Obesidade Infantil/prevenção & controle , Estudos Prospectivos , Países Baixos/epidemiologia , Classe Social , Exercício FísicoRESUMO
BACKGROUND: The COVID-19 pandemic may have a differential impact on mental health based on an individual's capital, i.e. resources available to maintain and enhance health. We assessed trajectories of depression and anxiety symptoms, and their association with different elements of capital. METHODS: Data on 65,854 individuals (mean baseline age = 50·4 (SD = 12·0) years) from the Lifelines COVID-19 cohort were used. Baseline mental health symptoms were on average measured 4.7 (SD = 1·1) years before the first COVID-19 measurement wave, and subsequent waves were (bi)weekly (March 30âAugust 05, 2020). Mental health symptom trajectories were estimated using a two-part Latent Class Growth Analysis. Class membership was predicted by economic (education, income, and occupation) and person capital (neuroticism, poor health condition, and obesity) FINDINGS: Most individuals were unlikely to report symptoms of depression (80·6%) or anxiety (75·9%), but stable-high classes were identified for both conditions (1·6% and 6·7%, respectively). The stable-high depression class saw the greatest increase in symptoms after COVID, and the stable-high anxiety class reported an increase in the probability of reporting symptoms after COVID. At the first COVID-measurement, the mean number of symptoms increased compared to baseline (depression:4·7 vs 4·1; anxiety:4·3 vs 4·2); the probability of reporting symptoms also increased (depression:0·96 vs 0·65; anxiety:0·92 vs 0·70). Membership in these classes was generally predicted by less capital, especially person capital; odds ratios for person capital ranged from 1·10-2·22 for depression and 1·08-1·51 for anxiety. INTERPRETATION: A minority of individuals, possessing less capital, reported an increase in symptoms of depression or anxiety after COVID. FUNDING: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
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COVID-19 , Adulto , Ansiedade/epidemiologia , Ansiedade/psicologia , COVID-19/epidemiologia , Estudos de Coortes , Depressão/epidemiologia , Depressão/psicologia , Humanos , Pessoa de Meia-Idade , Pandemias , SARS-CoV-2RESUMO
BACKGROUND: Diabetes mellitus, particularly type 2 diabetes, is a major public health burden globally. Diabetes is known to be associated with several comorbidities in high-income countries. However, our understanding of these associations in low- and middle-income countries (LMICs), where the epidemiological transition is leading to a growing dual burden of non-communicable and communicable disease, is less clear. We therefore conducted an umbrella review to systematically identify, appraise and synthesise reviews reporting the association between diabetes and multiple key comorbidities in LMICs. METHODS: We searched Medline, Embase, Global Health, and Global Index Medicus from inception to 14 November 2020 for systematic reviews, with or without meta-analyses, of cohort, case-control or cross-sectional studies investigating the associations between diabetes and cardiovascular disease (CVD), chronic kidney disease (CKD), depression, dengue, pneumonia, and tuberculosis within LMICs. We sought reviews of studies focused on LMICs, but also included reviews with a mixture of high-income and at least two LMIC studies, extracting data from LMIC studies only. We conducted quality assessment of identified reviews using an adapted AMSTAR 2 checklist. Where appropriate, we re-ran meta-analyses to pool LMIC study estimates and conduct subgroup analyses. RESULTS: From 11 001 articles, we identified 14 systematic reviews on the association between diabetes and CVD, CKD, depression, or tuberculosis. We did not identify any eligible systematic reviews on diabetes and pneumonia or dengue. We included 269 studies from 29 LMICs representing over 3 943 083 participants. Diabetes was positively associated with all comorbidities, with tuberculosis having the most robust evidence (16 of 26 cohort studies identified in total) and depression being the most studied (186 of 269 studies). The majority (81%) of studies included were cross-sectional. Heterogeneity was substantial for almost all secondary meta-analyses conducted, and there were too few studies for many subgroup analyses. CONCLUSIONS: Diabetes has been shown to be associated with several comorbidities in LMICs, but the nature of the associations is uncertain because of the large proportion of cross-sectional study designs. This demonstrates the need to conduct further primary research in LMICs, to improve, and address current gaps in, our understanding of diabetes comorbidities and complications in LMICs.
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Países em Desenvolvimento , Diabetes Mellitus Tipo 2 , Estudos Transversais , Humanos , Pobreza , Revisões Sistemáticas como AssuntoRESUMO
We assessed to what extent parental depression and parenting style mediate the relationships between different measures of parental socioeconomic status (SES) and both depression and metabolic syndrome (MetS) in adolescents, and whether sex moderates these mechanisms. Data were from the prospective multigenerational Dutch Lifelines Cohort Study. Our sample consisted of 1217 adolescents with an average follow-up of 33.3 (SD = 7.33) months and a median baseline age of 13 (IQR:13-14) years. We used structural equation models to assess the direct and indirect effects of SES on baseline and changes at follow-up in both depression and MetS, and to assess moderation by sex. For each additional year of education, continuous MetS scores were 0.098 (95%CI: 0.020; 0.184) units lower at baseline and decreased 0.079 (95%CI: 0.004; 0.158) units at follow-up. No other direct or indirect effects of SES were found, and there was no moderation by sex. Additionally, warmer parenting style was generally associated with more favorable outcome scores. Therefore, improving parenting style may improve health for all adolescents. However, in this study parental depression and parenting style did not account for adolescent socioeconomic health inequalities. This may be partly due to good access to social services within the Netherlands.