Are environmental area characteristics at birth associated with overweight and obesity in school-aged children? Findings from the SLOPE (Studying Lifecourse Obesity PrEdictors) population-based cohort in the south of England

Spatial-temporal evolution of overweight and obesity among Chinese adolescents from 2016 to 2020

This study examines the spatial-temporal evolution of overweight and obesity among Chinese adolescents aged 14-17. Data from five national surveys conducted between 2016 and 2020 were analyzed to determine distribution patterns and trends. Results showed that overweight and obesity exhibit spatial clustering, with greater severity in the north and less severity in the south. The issue has spread from the northeast to the southwest of Mainland China. Using a local autocorrelation model, the regions were divided into a northern disease cold spot area (Inner Mongolia) and a southern disease hot spot area (Guangxi). Over the past five years, overweight rates among Chinese adolescents have not been effectively curbed, but obesity has shown some success in control and reversal until 2019. Future efforts should focus on the spatial-temporal pattern of disease spread, targeting hotspot areas and abnormal values for regional synergy and precise prevention and control.

PM2.5 constituents associated with childhood obesity and larger BMI growth trajectory: A 14-year longitudinal study

BACKGROUND

The association of specific PM2.5 chemical constituents with childhood overweight or obesity (OWOB) remain unclear. Furthermore, the long-term impacts of PM2.5 exposure on the trajectory of children's body mass index (BMI) have not been explored.

METHODS

We conducted a longitudinal study among 1,450,830 Chinese children aged 6-19 years from Beijing and Zhongshan in China during 2005-2018 to examine the associations of PM2.5 and its chemical constituents with incident OWOB risk. We extracted PM2.5 mass and five main component exposure from Tracking Air Pollution in China (TAP) dataset. Cox proportional hazards models were applied to quantify exposure-response associations. We further performed principal component analysis (PCA) to handle the multi-collinearity and used quantile g-computation (QGC) approach to analyze the impacts of exposure mixtures. Additionally, we selected 125,863 children with at least 8 physical examination measurements and combined group-based trajectory models (GBTM) with multinomial logistic regression models to explore the impacts of exposure to PM2.5 mass and five constituents on BMI and BMI Z-score trajectories during 6-19 years.

RESULTS

We observed each interquartile range increment in PM2.5 exposure was significantly associated with a 5.1 % increase in the risk of incident OWOB (95 % confidence Interval [CI]: 1.036-1.066). We also found black carbon, sulfate, organic matter, often linked to fossil combustion, had comparable or larger estimates of the effect (HR = 1.139-1.153) than PM2.5. Furthermore, Exposure to PM2.5 mass, sulfate, nitrate, ammonium, organic matter and black carbon was significantly associated with an increased odds of being in a larger BMI trajectory and being assigned to persistent OWOB trajectory.

CONCLUSIONS

Our findings provide evidence that the constituents mainly from fossil fuel combustion may have a perceptible influence on increased OWOB risk associated with PM2.5 exposure in China. Moreover, long-term exposure to PM2.5 contributes to an increased odds of being in a lager BMI and a persistent OWOB trajectories.

Early-life exposure to residential black carbon and childhood cardiometabolic health

BACKGROUND

Early life exposure to air pollution, such as particulate matter ≤2.5 μm (PM2.5), may be associated with obesity and adverse cardiometabolic health outcomes in childhood. However, the toxicity of PM2.5 varies according to its chemical composition. Black carbon (BC) is a constituent of PM2.5, but few studies have examined its impact on childhood cardiometabolic health. Therefore, we examined relationships between prenatal and early childhood exposure to BC and markers of adiposity and cardiometabolic health in early childhood.

METHODS

This study included 578 mother-child pairs enrolled in the Healthy Start study (2009-2014) living in the Denver-metro area. Using a spatiotemporal prediction model, we assessed average residential black carbon levels during pregnancy and in the year prior to the early childhood follow-up visit at approximately 5 years old. We estimated associations between prenatal and early childhood BC and indicators of adiposity and cardiometabolic biomarkers in early childhood (mean 4.8 years; range, 4.0, 8.3), using linear regression.

RESULTS

We found higher early childhood BC was associated with higher percent fat mass, fat mass index, insulin, and homeostatic model assessment for insulin resistance (HOMA-IR), and lower leptin and waist circumference at approximately 5 years old, after adjusting for covariates. For example, per interquartile range (IQR) increase in early childhood BC (IQR, 0.49 μg/m3) there was 3.32% higher fat mass (95% CI; 2.05, 4.49). Generally, we did not find consistent evidence of associations between prenatal BC and cardiometabolic health outcomes in early childhood, except for an inverse association between prenatal BC and adiponectin, an adipocyte-secreted hormone typically inversely associated with adiposity.

CONCLUSIONS

Higher early childhood, but not in utero, ambient concentrations of black carbon, a component of air pollution, were associated with greater adiposity and altered insulin homeostasis at approximately 5 years old. Future studies should examine whether these changes persist later in life.

Prenatal maternal cortisol, stress and anxiety, and childhood obesity at 5 years: a nested case-control study

BACKGROUND

Paediatric obesity is a global public health issue. Prenatal maternal mental health is potentially implicated in the development of childhood obesity. This study examined associations between prenatal maternal cortisol, self-reported stress, anxiety and depression in the second trimester, and childhood overweight and obesity at 5 years of age.

METHODS

A nested case-control study was conducted using data from the Irish prospective longitudinal birth cohort SCOPE BASELINE. Cases were children with overweight or obesity, operationalised as having a BMI z-score above +2 standard deviations. Controls were children with a BMI z-score between -0.5 and 0.5 standard deviations at 5 years of age. Two to one matching by sex was conducted. Thirty-eight cases and 83 sex-matched controls were included. Maternal serum cortisol concentration and self-reported stress, anxiety and depression were measured at 15 ± 1 and 20 ± 1 weeks gestation. Conditional logistic regression analyses were conducted to examine associations between prenatal maternal cortisol and self-reported stress, anxiety and depression, and childhood overweight and obesity.

RESULTS

Despite some evidence for associations between anxiety and depression, and child BMI z-scores in univariate analyses, adjusted models indicated no associations between prenatal maternal stress (OR: 1.02, 95% CI: 0.94-1.12), anxiety (OR: 1.03, 95% CI: 0.97-1.09), depression (OR: 1.04, 95% CI: 0.91-1.19), or cortisol concentration (OR: 0.99, 95% CI: 0.99-1.00) and child BMI z-score.

CONCLUSION

Our findings do not provide support for associations between foetal exposure during the second trimester of pregnancy and maternal cortisol, stress and anxiety, and childhood overweight or obesity at 5 years of age.

Socio-economic correlates of childhood obesity in urban and rural England

OBJECTIVE

Physical access to food may affect diet and thus obesity rates. We build upon existing work to better understand how socio-economic characteristics of locations are associated with childhood overweight.

DESIGN

Using cross-sectional design and publicly available data, the study specifically compares rural and urban areas, including interactions of distance from supermarkets with income and population density.

SETTING

We examine cross-sectional associations with obesity prevalence both in the national scale and across urban and rural areas differing in household wealth.

PARTICIPANTS

Children in reception class (aged 4-5) from all state-maintained schools in England taking part in the National Child Measurement Programme (n 6772).

RESULTS

Income was the main predictor of childhood obesity (adj. R-sq=.316, p<.001), whereas distance played only a marginal role (adj. R-sq=.01, p<.001). In urban areas, distance and density correlate with obesity directly and conditionally. Urban children were slightly more obese, but the opposite was true for children in affluent areas. Association between income poverty and obesity rates was stronger in urban areas (7·59 %) than rural areas (4·95 %), the former which also showed stronger association between distance and obesity.

CONCLUSIONS

Obesogenic environments present heightened risks in deprived urban and affluent rural areas. The results have potential value for policy making as for planning and targeting of services for vulnerable groups.

Change in the food environment and measured adiposity in adulthood in the Christchurch Health and development birth cohort, Aotearoa, New Zealand: A birth cohort study

This study investigated associations between change in the food environment and change in measured body mass index (BMI) and waist circumference (WC) in the Christchurch Health and Development Study (CHDS) birth cohort. Our findings suggest that cohort members who experienced the greatest proportional change towards better access to fast food outlets had the slightly larger increases in BMI and WC. Contrastingly, cohort members who experienced the greatest proportional change towards shorter distance and better access to supermarkets had slightly smaller increases in BMI and WC. Our findings may help explain the changes in BMI and WC at a population level.

Multidisciplinary ecosystem to study lifecourse determinants and prevention of early-onset burdensome multimorbidity (MELD-B) - protocol for a research collaboration

Background

Most people living with multiple long-term condition multimorbidity (MLTC-M) are under 65 (defined as 'early onset'). Earlier and greater accrual of long-term conditions (LTCs) may be influenced by the timing and nature of exposure to key risk factors, wider determinants or other LTCs at different life stages. We have established a research collaboration titled 'MELD-B' to understand how wider determinants, sentinel conditions (the first LTC in the lifecourse) and LTC accrual sequence affect risk of early-onset, burdensome MLTC-M, and to inform prevention interventions.

Aim

Our aim is to identify critical periods in the lifecourse for prevention of early-onset, burdensome MLTC-M, identified through the analysis of birth cohorts and electronic health records, including artificial intelligence (AI)-enhanced analyses.

Design

We will develop deeper understanding of 'burdensomeness' and 'complexity' through a qualitative evidence synthesis and a consensus study. Using safe data environments for analyses across large, representative routine healthcare datasets and birth cohorts, we will apply AI methods to identify early-onset, burdensome MLTC-M clusters and sentinel conditions, develop semi-supervised learning to match individuals across datasets, identify determinants of burdensome clusters, and model trajectories of LTC and burden accrual. We will characterise early-life (under 18 years) risk factors for early-onset, burdensome MLTC-M and sentinel conditions. Finally, using AI and causal inference modelling, we will model potential 'preventable moments', defined as time periods in the life course where there is an opportunity for intervention on risk factors and early determinants to prevent the development of MLTC-M. Patient and public involvement is integrated throughout.

A conceptual framework for characterising lifecourse determinants of multiple long-term condition multimorbidity

Objective

Social, biological and environmental factors in early-life, defined as the period from preconception until age 18, play a role in shaping the risk of multiple long-term condition multimorbidity. However, there is a need to conceptualise these early-life factors, how they relate to each other, and provide conceptual framing for future research on aetiology and modelling prevention scenarios of multimorbidity. We develop a conceptual framework to characterise the population-level domains of early-life determinants of future multimorbidity.

Method

This work was conducted as part of the Multidisciplinary Ecosystem to study Lifecourse Determinants and Prevention of Early-onset Burdensome Multimorbidity (MELD-B) study. The conceptualisation of multimorbidity lifecourse determinant domains was shaped by a review of existing research evidence and policy, and co-produced with public involvement via two workshops.

Results

Early-life risk factors incorporate personal, social, economic, behavioural and environmental factors, and the key domains discussed in research evidence, policy, and with public contributors included adverse childhood experiences, socioeconomics, the social and physical environment, and education. Policy recommendations more often focused on individual-level factors as opposed to the wider determinants of health discussed within the research evidence. Some domains highlighted through our co-production process with public contributors, such as religion and spirituality, health screening and check-ups, and diet, were not adequately considered within the research evidence or policy.

Conclusions

This co-produced conceptualisation can inform research directions using primary and secondary data to investigate the early-life characteristics of population groups at risk of future multimorbidity, as well as policy directions to target public health prevention scenarios of early-onset multimorbidity.

What is the role of particulate matter 2.5 (PM2.5) on excess weight? A cross-sectional study in young Spanish people aged 2─14 years

PURPOSE

To assess the relationship between particulate matter 2.5 (PM2.5) levels and the prevalence of excess weight in a representative sample of Spanish young people aged 2─14 years.

METHODS

This was an ecological cross-sectional study using data from the 2017 wave of the Encuesta Nacional de Salud Española (ENSE), a nationally representative survey of the Spanish young and adult population. The final sample included 4378 young Spanish people (51.0% boys). The weight (kg) and height (cm) of the study participants were proxy-reported by parents or guardians. Excess weight was determined according to the age- and sex-criteria of the International Obesity Task Force. The PM_2.5 level was calculated as the annual monitoring data indicator for 2017 among the different regions in Spain. Logistic regression models were performed to estimate the relationships between PM_2.5 and weight.

RESULTS

Compared to young people located in regions with low levels of PM_2.5, those reporting greater odds for excess weight were found in regions with medium PM_2.5 (OR = 1.23; 95% CI, 1.02-1.49) and high PM_2.5 (OR = 1.35; 95% CI, 1.11-1.64) after adjusting for several sociodemographic, lifestyle and environmental covariates.

CONCLUSIONS

The prevalence of excess weight in young people was positively associated with PM_2.5 levels in Spain. This finding supports the hypothesis that air pollution exposure can result in excess weight in the young population, which, in turn, might lead to the development of metabolic disorders. From a socioecological perspective, a practical need to take environmental factors into consideration is important to address unhealthy weight in Spanish young people.

Greenspace and health outcomes in children and adolescents: A systematic review

An increasing body of evidence has linked greenspace and various health outcomes in children and adolescents, but the conclusions were inconsistent. For this review, we comprehensively summarized the measurement methods of greenspace, resultant health outcomes, and potential mechanisms from epidemiological studies in children and adolescents (aged ≤19 years). We searched for studies published and indexed in MEDLINE and EMBASE (via Ovid) up to April 11, 2022. There were a total of 9,291 studies identified with 140 articles from 28 countries finally assessed and included in this systematic review. Over 70% of the studies were conducted in highly urbanised countries/regions, but very limited research has been done in low-and middle-income countries and none in Africa. Measures of greenspace varied. Various health outcomes were reported, including protective effects of greenspace exposure on aspects of obesity/overweight, myopia, lung health, circulatory health, cognitive function, and general health in children and adolescents. The associations between greenspace exposure and other health outcomes were inconsistent, especially for respiratory health studies. We pooled odds ratios (OR) using random-effects meta-analysis for health outcomes of asthma (OR = 0.94, 95%CI: 0.84 to 1.06), allergic rhinitis (OR = 0.95; 95% CI: 0.73 to 1.25), and obesity/overweight (OR = 0.91, 95%CI: 0.84 to 0.98) with per 0.1 unit increase in normalized difference in vegetation index (NDVI). These associations have important implications for the assessment and management of urban environment and health in children and adolescents.

Physiology of the Weight-Reduced State and Its Impact on Weight Regain

Obesity is a chronic disease characterized by long duration, slow progression, and periods of remission and relapses. Despite the development of effective medical and surgical interventions and millions of people conducting tremendous personal efforts to manage their weight every year, recidivism remains a significant barrier to attaining long-term weight maintenance. This review aimed to explain the underlying physiology of the weight-reduced state including changes in energy balance, adipose tissue, genetic, environmental, and behavioral factors that may predispose individuals to weight regain following weight loss.

Exposure to ultrafine particles and childhood obesity: A cross-sectional analysis of the Seven Northeast Cities (SNEC) Study in China

BACKGROUND

Studies on the obesogenic effect of air pollution on children have been mixed and sparse. Moreover, due to insufficient air monitoring, few studies have investigated the role of more tiny but unregulated particles (ambient particles with a diameter of 0.1 μm or less, ultrafine particles).

OBJECTIVE

We sought to explore the associations between long-term exposure to ambient ultrafine particles (UFPs) and childhood obesity in Chinese children.

METHODS

In this cross-sectional study, we randomly recruited 47,990 children, aged 6-18 years, from seven cities in Northeastern China between 2012 and 2013. Child age- and sex-specific z-scores for body mass index (BMI Z-score) and weight status were generated using the World Health Organization growth reference. Four-year average concentrations of UFPs and airborne particulates of diameter ≤ 1 μm (PM₁), ≤2.5 μm (PM_2.5), and ≤10 μm (PM₁₀) were estimated at home, using neural network simulated WRF-Chem model and spatiotemporal model, respectively. Confounder-adjusted generalized linear mixed models examined the associations between air pollution and BMI Z-score and the prevalence of childhood obesity.

RESULT

We found that UFPs exposure was associated with greater childhood BMI Z-score and a higher likelihood of obesity. Compared with the lowest quartile, higher quartiles of UFPs were associated with greater odds for obesity prevalence in children (i.e., the adjusted OR was 1.25; 95 % CI, 1.12-1.39; 1.43; 95 % CI, 1.27-1.61; and 1.41; 95 % CI, 1.25-1.58 for the second, third, and fourth quartile, respectively). Similar associations were observed for PM₁, PM_2.5, and PM₁₀, and were greater in boys and children living close to roadways.

CONCLUSIONS

Long-term UFPs exposure was associated with a greater likelihood of childhood obesity, and stronger associations on BMI Z-score were observed in boys and children living close to roadways. This study indicates that more attention should be paid to the health effects of UFPs, and routinely monitoring of UFPs should be considered.

Exposure to outdoor and indoor air pollution and risk of overweight and obesity across different life periods: A review

Due to the highly evolved industrialization and modernization, air quality has deteriorated in most countries. As reported by the World Health Organization (WHO), air pollution is now considered as one of the major threats to global health and a principal risk factor for noncommunicable diseases. Meanwhile, the increasing worldwide prevalence of overweight and obesity is attracting more public attentions. Recently, accumulating epidemiological studies have provided evidence that overweight and obesity may be partially attributable to environmental exposure to air pollution. This review summarizes the epidemiological evidence for the correlation between exposure to various outdoor and indoor air pollutants (mainly particulate matter (PM), nitrogen oxides (NO_x), ozone (O₃), and polycyclic aromatic hydrocarbons (PAHs)) and overweight and obesity outcomes in recent years. Moreover, it discusses the multiple effects of air pollution during exposure periods throughout life and sex differences in populations. This review also describes the potential mechanism underlying the increased risk of obesity caused by air pollution, including inflammation, oxidative stress, metabolic imbalance, intestinal flora disorders and epigenetic modifications. Finally, this review proposes macro- and micro-measures to prevent the negative effects of air pollution exposure on the obesity prevalence.

Multidisciplinary Treatment for Childhood Obesity: A Two-Year Experience in the Province of Naples, Italy

Childhood obesity must be faced through an integrated multi-level preventive approach. This study was aimed at assessing the adherence and the outcomes of an outpatient service for childhood obesity treatment activated in the province of Naples, Italy, throughout a 2-year follow-up period. At first visit (T0), weight, height, waist circumference, and body composition of children were assessed, together with sociodemographic features and physical activity levels of children and parents. Anthropometric and body composition parameters of children were measured at 6 ± 3 months (T1) and 12 ± 3 months (T2). A total of 451 non-related children who accessed the service were analyzed: 220 (48.7%) of them returned at least once (attrition rate 51.3%). Returner outpatients showed higher age (p = 0.046) and father’s educational level (p = 0.041) than non-returner ones. Adherence to the treatment was found to be related to father’s (Rho = 0.140, p = 0.005) and mother’s (Rho = 0.109, p = 0.026) educational level. All the outcomes improved between T0 and T1 (p < 0.001), while only body mass index (BMI) decreased significantly at T2. Changes in BMI-SDS were associated with baseline value (OR 0.158, 95%CI 0.017−0.298, p = 0.029). The multidisciplinary approach seems to be promising to treat childhood obesity in this geographic context. Lower parents’ educational level should be considered as an attrition determinant.

Global association between atmospheric particulate matter and obesity: A systematic review and meta-analysis

BACKGROUND

Among various air pollutants, particulate matter (PM) is the most harmful and representative pollutant. Although several studies have shown a link between particulate pollution and obesity, the conclusions are still inconsistent.

METHODS

We conducted a systematic review and meta-analysis to pool the effect of PM exposure on obesity. Five databases (including PubMed, Web of Science, Scopus, Embase, and Cochrane) were searched for relevant studies up to Jan 2022. Adjusted risk ratio (RR) with corresponding 95% confidence interval (CI) were retrieved from individual studies and pooled with random effect models by STATA software. Besides, we tested the stability of results by Egger's test, Begg's test, funnel plot, and using the trim-and-fill method to modify the possible asymmetric funnel graph. The NTP-OHAT guidelines were followed to assess the risk of bias. Then the GRADE was used to evaluate the certainty of evidence.

RESULTS

26 studies were included in this meta-analysis. 19 studies have shown that PM_2.5 can increase the risk of obesity per 10 μg/m³ increment (RR: 1.159, 95% CI: 1.111-1.209), while 15 studies have indicated that PM₁₀ increase the risk of obesity per 10 μg/m³ increment (RR: 1.092, 95% CI: 1.070-1.116). Besides, 5 other articles with maternal exposure showed that PM_2.5 increases the risk of obesity in children (RR: 1.06, 95% CI: 1.02-1.11). And we explored the source of heterogeneity by subgroup analysis, which suggested associations between PM and obesity tended to vary by region, age group, participants number, etc. The analysis results showed publication bias and other biases are well controlled, but most certainties of the evidence were low, and more research is required to reduce these uncertainties.

CONCLUSION

Exposure to PM_2.5 and PM₁₀ with per 10 μg/m³ increment could increase the risk of obesity in the global population.

Environmental and Socioeconomic Factors for Gastric Cancer in 14 Counties of the Huai River Basin from 2014 to 2018

To explore the potential relationship between environmental and socioeconomic factors and the risk of gastric cancer (GC) in the Huai River Basin, the GC incidence rate (GIR) and GC mortality rate (GMR) data from 2014 to 2018 in 14 counties of the Huai River Basin were collected from the Chinese Cancer Registration Annual Report. Environmental and socioeconomic parameters were collected through the Statistical Yearbook. The 14 counties were classified into three groups with low, moderate, and high risk of GC according to the point density of environmental factors (PDF) and index of socioeconomic factors (ISF). Significant differences in GIR and GMR were found among the counties with PDF (χ² = 21.36, p < 0.01) and ISF (χ² = 11.37, p < 0.05) levels. Meanwhile, significant differences in mortality rate were observed among counties with different PDF (χ² = 11.25, p < 0.01) and ISF (χ² = 18.74, p < 0.01), and the results showed that the ISF and PDF were increased while the GIR and GMR were decreased. Meanwhile, there was a lag effect between them, and we used two models to explore the lag effects between ISF, PDF and GIR and GMR; the coefficient influence between the ISF lag phase and GIR was −2.9768, and the coefficient influence between PDF and the lag phase on the GIR was −0.9332, and there were both significant impact when there was a probability of more than 95%. The results showed that the higher the ISF and PDF that lags in one stage, the more GIR was reduced, while the impact of the ISF and PDF on lag stage on mortality was not obvious. We used differential GMM to test the results, and also research results were relatively robust. Overall, GIR and GMR decreased with increasing point density of environmental factors and index of socioeconomic factors.

The built environment as determinant of childhood obesity: A systematic literature review

We evaluated the epidemiological evidence on the built environment and its link to childhood obesity, focusing on environmental factors such as traffic noise and air pollution, as well as physical factors potentially driving obesity-related behaviors, such as neighborhood walkability and availability and accessibility of parks and playgrounds. Eligible studies were (i) conducted on human children below the age of 18 years, (ii) focused on body size measurements in childhood, (iii) examined at least one built environment characteristic, (iv) reported effect sizes and associated confidence intervals, and (v) were published in English language. A z test, as alternative to the meta-analysis, was used to quantify associations due to heterogeneity in exposure and outcome definition. We found strong evidence for an association of traffic-related air pollution (nitrogen dioxide and nitrogen oxides exposure, p < 0.001) and built environment characteristics supportive of walking (street intersection density, p < 0.01 and access to parks, p < 0.001) with childhood obesity. We identified a lack of studies that account for interactions between different built environment exposures or verify the role and mechanism of important effect modifiers such as age.

Maternal smoking behaviour across the first two pregnancies and small for gestational age birth: Analysis of the SLOPE (Studying Lifecourse Obesity PrEdictors) population-based cohort in the South of England

Maternal smoking is established to cause adverse birth outcomes, but evidence considering maternal smoking change across successive pregnancies is sparse. We examined the association between self-reported maternal smoking during and between the first two pregnancies with the odds of small for gestational age (SGA) birth (<10th percentile) in the second infant. Records for the first two pregnancies for 16791 women within the SLOPE (Studying Lifecourse Obesity PrEdictors) study were analysed. This is a population-based cohort of prospectively collected anonymised antenatal and birth healthcare data (2003-2018) in Hampshire, UK. Logistic regression was used to relate maternal smoking change to the odds of SGA birth in the second infant. In the full sample, compared to never smokers, mothers smoking at the start of the first pregnancy had higher odds of SGA birth in the second pregnancy even where they stopped smoking before the first antenatal appointment for the second pregnancy (adjusted odds ratio (aOR) 1.50 [95% confidence interval 1.10, 2.03]). If a mother was not a smoker at the first antenatal appointment for either her first or her second pregnancy, but smoked later in her first pregnancy or between pregnancies, there was no evidence of increased risk of SGA birth in the second pregnancy compared to never smokers. A mother who smoked ten or more cigarettes a day at the start of both of her first two pregnancies had the highest odds of SGA birth (3.54 [2.55, 4.92]). Women who were not smoking at the start of the first pregnancy but who subsequently resumed/began smoking and smoked at the start of their second pregnancy, also had higher odds (2.11 [1.51, 2.95]) than never smokers. Smoking in the first pregnancy was associated with SGA birth in the second pregnancy, even if the mother quit by the confirmation of her second pregnancy.

Nature and Children's Health: A Systematic Review

CONTEXT

Daily outdoor play is encouraged by the American Academy of Pediatrics. Existing evidence is unclear on the independent effect of nature exposures on child health.

OBJECTIVE

We systematically evaluated evidence regarding the relationship between nature contact and children's health.

DATA SOURCES

The database search was conducted by using PubMed, Cumulative Index to Nursing and Allied Health Literature, PsychInfo, ERIC, Scopus, and Web of Science in February 2021.

STUDY SELECTION

We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. In all searches, the first element included nature terms; the second included child health outcome terms.

DATA EXTRACTION

Of the 10 940 studies identified, 296 were included. Study quality and risk of bias were assessed.

RESULTS

The strongest evidence for type of nature exposure was residential green space studies (n = 147, 50%). The strongest evidence for the beneficial health effects of nature was for physical activity (n = 108, 32%) and cognitive, behavioral, or mental health (n = 85, 25%). Physical activity was objectively measured in 55% of studies, and 41% of the cognitive, behavioral, or mental health studies were experimental in design.

LIMITATIONS

Types of nature exposures and health outcomes and behaviors were heterogenous. Risk of selection bias was moderate to high for all studies. Most studies were cross-sectional (n = 204, 69%), limiting our ability to assess causality.

CONCLUSIONS

Current literature supports a positive relationship between nature contact and children's health, especially for physical activity and mental health, both public health priorities. The evidence supports pediatricians in advocating for equitable nature contact for children in places where they live, play, and learn.

Monitoring of Excess Body Weight in Children in the Emergency Department of a Tertiary Pediatric Hospital in Bucharest, Romania

Introduction: Excess body weight in children has become a public health issue in most countries. The aim of our study was to determine the prevalence of overweight and obesity in children over two years of age who presented at the Emergency Department of a tertiary pediatric hospital in Bucharest, Romania. Methods: Between July and August 2018, we conducted a prospective study among children who presented at the Emergency Department of "Alessandrescu-Rusescu" National Institute for Mother and Child Health, Bucharest, Romania. We collected data on weight, height and blood pressure classified by age and gender. Results: A total of 335 children aged 2 to 18 years were included in our study. A quarter of them had above normal body mass index values, 7.5% were overweight and 18.5% obese. Also, when measuring blood pressure, we observed increased values in 29.3% (n=98) of them. Among children with excess body weight, nearly a half (49.4%, n=47) had higher than normal blood pressure values. Conclusions: Excess body weight in children has become a public health issue in most countries. The aim of our study was to determine the prevalence of overweight and obesity in children over two years of age who presented at the Emergency Department of a tertiary pediatric hospital in Bucharest, Romania.

Effect of Air Pollution on Obesity in Children: A Systematic Review and Meta-Analysis

Air pollution exposure has been identified as being associated with childhood obesity. Nevertheless, strong evidence of such an association is still lacking. To analyze whether air pollution exposure affects childhood obesity, we conducted a systematic review and meta-analysis utilizing the PRISMA guidelines. Of 7343 studies identified, eight studies that investigated the effects of air pollutant characteristics, including PM_2.5, PM₁₀, PM_coarse, PM_absorbance, NO_x, and NO₂, on childhood obesity were included. The polled effects showed that air pollution is correlated with a substantially increased risk of childhood obesity. PM_2.5 was found to be associated with a significantly increased risk (6%) of childhood obesity (OR 1.06, 95% CI 1.02–1.10, p = 0.003). In addition, PM₁₀, PM_{2.5absorbance}, and NO₂ appeared to significantly increase the risk of obesity in children (OR 1.07, 95% CI 1.04–1.10, p < 0.00; OR 1.23, 95% CI 1.06–1.43, p = 0.07; and OR 1.10, 95% CI 1.04–1.16, p < 0.001, respectively). PM_coarse and NO_x also showed trends towards being associated with an increased risk of childhood obesity (OR 1.07, 95% CI 0.95–1.20, p = 0.291, and OR 1.00, 95% CI 0.99–1.02, p = 0.571, respectively). Strong evidence was found to support the theory that air pollution exposure is one of the factors that increases the risk of childhood obesity.

Walkability indices and childhood obesity: A review of epidemiologic evidence

The lack of an active neighbourhood living environment can impact community health to a great extent. One such impact manifests in walkability, a measure of urban design in connecting places and facilitating physical activity. Although a low level of walkability is generally considered to be a risk factor for childhood obesity, this association has not been established in obesity research. To further examine this association, we conducted a literature search on PubMed, Web of Science and Scopus for articles published until 31 December 2018. The included literature examined the association between measures of walkability (e.g., walkability score and walkability index) and weight-related behaviours and/or outcomes among children aged under 18 years. A total of 13 studies conducted in seven countries were identified, including 12 cross-sectional studies and one longitudinal study. The sample size ranged from 98 to 37 460, with a mean of 4971 ± 10 618, and the age of samples ranged from 2 to 18. Eight studies reported that a higher level of walkability was associated with active lifestyles and healthy weight status, which was not supported by five studies. In addition to reviewing the state-of-the-art of applications of walkability indices in childhood obesity studies, this study also provides guidance on when and how to use walkability indices in future obesity-related research.

Predicting the risk of childhood overweight and obesity at 4-5 years using population-level pregnancy and early-life healthcare data

BACKGROUND

Nearly a third of children in the UK are overweight, with the prevalence in the most deprived areas more than twice that in the least deprived. The aim was to develop a risk identification model for childhood overweight/obesity applied during pregnancy and early life using routinely collected population-level healthcare data.

METHODS

A population-based anonymised linked cohort of maternal antenatal records (January 2003 to September 2013) and birth/early-life data for their children with linked body mass index (BMI) measurements at 4-5 years (n = 29,060 children) in Hampshire, UK was used. Childhood age- and sex-adjusted BMI at 4-5 years, measured between September 2007 and November 2018, using a clinical cut-off of ≥ 91st centile for overweight/obesity. Logistic regression models together with multivariable fractional polynomials were used to select model predictors and to identify transformations of continuous predictors that best predict the outcome.

RESULTS

Fifteen percent of children had a BMI ≥ 91st centile. Models were developed in stages, incorporating data collected at first antenatal booking appointment, later pregnancy/birth, and early-life predictors (1 and 2 years). The area under the curve (AUC) was lowest (0.64) for the model only incorporating maternal predictors from early pregnancy and highest for the model incorporating all factors up to weight at 2 years for predicting outcome at 4-5 years (0.83). The models were well calibrated. The prediction models identify 21% (at booking) to 24% (at ~ 2 years) of children as being at high risk of overweight or obese by the age of 4-5 years (as defined by a ≥ 20% risk score). Early pregnancy predictors included maternal BMI, smoking status, maternal age, and ethnicity. Early-life predictors included birthweight, baby's sex, and weight at 1 or 2 years of age.

CONCLUSIONS

Although predictive ability was lower for the early pregnancy models, maternal predictors remained consistent across the models; thus, high-risk groups could be identified at an early stage with more precise estimation as the child grows. A tool based on these models can be used to quantify clustering of risk for childhood obesity as early as the first trimester of pregnancy, and can strengthen the long-term preventive element of antenatal and early years care.