Prevalence and Correlates of Double and Triple Burden of Malnutrition Among Children and Adolescents in India: The Comprehensive National Nutrition Survey.

BACKGROUND: Limited information on the co-prevalence of undernutrition, micronutrient deficiencies, overnutrition, and abnormal levels of noncommunicable disease biomarkers at the same time in children and adolescents in India hinders efforts to comprehensively address their health. OBJECTIVES: This study aimed to examine the prevalence and correlates of double burden of malnutrition (DBM) and triple burden of malnutrition (TBM) among children and adolescents (5-19 y) to inform policies and programs. METHODS: A total of 17,599 children (5-9 y) and 16,184 adolescents (10-19 y) with available biomarker data from the Comprehensive National Nutrition Survey were included. Malnutrition was defined based on either undernutrition based on anthropometry, overnutrition/abnormal metabolic markers, and anemia/micronutrient deficiency. DBM was defined as the coexistence of any 2 forms of malnutrition. DBM+ was defined as the coexistence of undernutrition and/or micronutrient deficiency along with overnutrition. TBM was defined as having the coexistence of all 3 forms of malnutrition. The prevalence of DBM, DBM+, and TBM was estimated accounting for probabilistic selection. We used mixed-effect binomial regression to determine correlates of DBM/TBM in children and adolescents separately. RESULTS: The prevalence of DBM, DBM+, and TBM was 50.8%, 37.2%, and 14.4%, respectively, in children and 53.4%, 36.1%, and 12.7%, respectively, in adolescents. The prevalence of DBM+ was significantly higher in girls compared to in boys in the 5-9 y age group. In children, being in a disadvantaged caste group, having a lower wealth index, having inadequate diet diversity, having no maternal schooling, and having a recent history of acute illness were associated with DBM. In adolescents, being in a disadvantaged caste group, maternal occupation, and lower paternal age were correlated with DBM. A similar set of variables was associated with TBM in both age groups. CONCLUSIONS: The prevalence of DBM and TBM is substantial in children and adolescents in India and varies across states. Socioeconomic factors and acute illness were the main correlates for DBM and TBM.

Childhood adversities characterize the heterogeneity in the brain pattern of individuals during neurodevelopment.

BACKGROUND: Several factors shape the neurodevelopmental trajectory. A key area of focus in neurodevelopmental research is to estimate the factors that have maximal influence on the brain and can tip the balance from typical to atypical development. METHODS: Utilizing a dissimilarity maximization algorithm on the dynamic mode decomposition (DMD) of the resting state functional MRI data, we classified subjects from the cVEDA neurodevelopmental cohort (n = 987, aged 6-23 years) into homogeneously patterned DMD (representing typical development in 809 subjects) and heterogeneously patterned DMD (indicative of atypical development in 178 subjects). RESULTS: Significant DMD differences were primarily identified in the default mode network (DMN) regions across these groups (p < 0.05, Bonferroni corrected). While the groups were comparable in cognitive performance, the atypical group had more frequent exposure to adversities and faced higher abuses (p < 0.05, Bonferroni corrected). Upon evaluating brain-behavior correlations, we found that correlation patterns between adversity and DMN dynamic modes exhibited age-dependent variations for atypical subjects, hinting at differential utilization of the DMN due to chronic adversities. CONCLUSION: Adversities (particularly abuse) maximally influence the DMN during neurodevelopment and lead to the failure in the development of a coherent DMN system. While DMN's integrity is preserved in typical development, the age-dependent variability in atypically developing individuals is contrasting. The flexibility of DMN might be a compensatory mechanism to protect an individual in an abusive environment. However, such adaptability might deprive the neural system of the faculties of normal functioning and may incur long-term effects on the psyche.

Estimation of Hydration and Density of Fat-Free Mass in Indian Children Using a 4-Compartment Model: Implications for the Estimation of Body Composition Using 2-Compartment Models.

BACKGROUND: Accurate methods are needed to measure body fat mass (FM), particularly in South Asian children who are thought to have greater adiposity for a given body size. The accuracy of simple 2-compartment (2C) models of measuring FM depends on the primary measurement of the fat free mass (FFM) and the validity of assumed constants for FFM hydration and density. These have not been measured in this particular ethnic group. OBJECTIVES: To measure FFM hydration and density in South Indian children using a 4-compartment (4C) model and to compare FM estimates from this 4C-model with 2C-model-based estimates from hydrometry and densitometry, using literature-reported FFM hydration and density in children. METHODS: This study included 299 children (45% boys), aged 6-16 y from Bengaluru, India. Total body water (TBW), bone mineral content (BMC), and body volume were measured using deuterium dilution, dual-energy X-ray absorptiometry, and air displacement plethysmography, respectively, to calculate the FFM hydration and density, and the FM using 4C and 2C models. The agreement between FM estimates from 2C and 4C models was also evaluated. RESULTS: Mean FFM hydration and density were 74.2% ± 2.1% and 71.4% ± 2.0% and 1.095 ± 0.008 kg/L and 1.105 ± 0.008 kg/L in boys and girls respectively, which were significantly different from published values. Using the presently estimated constants, the mean hydrometry-based FM (as % body weight) estimates decreased by 3.5% but increased by 5.2% for densitometry-based 2C methods. When 2C-FM (using previously reported FFM hydration and density) were compared with 4C-FM estimates, the mean difference was -1.1 ± 0.9 kg for hydrometry and 1.6 ± 1.1 kg for densitometry. CONCLUSIONS: Previously published constants of hydration and density of FFM may induce errors of -12% to +17% in FM (kg) when using different 2C models in comparison to the 4C models in Indian children. J Nutr 20xx;x:xx.

Comparison of Anemia Screening Methods Using Paired Venous Samples in Women of Reproductive Age in Southern India.

BACKGROUND: Anemia is an important public health problem, and accurate estimates may inform policy and programs. Although hemoglobin (Hb) assessment of venous blood via automated hematology analyzers (AHAs) is recommended, most population-based surveys estimate anemia prevalence based on analysis of capillary blood via portable hemoglobinometers. OBJECTIVES: We aimed to evaluate screening methods for hemoglobin and anemia assessment using paired venous samples. METHODS: Participants were women 15-40 y who were not pregnant or lactating. Paired venous whole blood samples (n = 896) were analyzed for hemoglobin (Hb) via portable hemoglobinometer (HemoCue 301) and Coulter Counter AHA. Anemia and severe anemia were defined as Hb <12.0g/dL and <8.0 g/dL, respectively. Bland-Altman methods were used to assess the level of agreement for Hb results (mean difference, SD of differences, limits of agreement). Diagnostic accuracy parameters (sensitivity, specificity, positive predictive value, negative predictive value, accuracy) were calculated to evaluate HemoCue performance compared to the AHA reference, overall and by sociodemographic, nutritional, and metabolic characteristics. RESULTS: The estimated anemia prevalence was significantly lower via HemoCue vs. AHA (36.3% compared with 41.6%; P value < 0.0001). The HemoCue had 84.4% accuracy for anemia screening and 98.8% for severe anemia, compared to the AHA reference. The HemoCue had 74.8% sensitivity and 91.2% specificity, compared to AHA. HemoCue sensitivity was higher in women with iron deficiency [serum ferritin (SF) <15.0 µg/L: 81.6% compared with SF ≥15.0 µg/L: 41.3%], and lower in women with metabolic risk factors, including overweight [BMI ≥25.0 kg/m2: 63.9% vs. BMI <25.0 kg/m2: 78.8%], or elevated CRP (>1.0 mg/L: 67.2% vs. ≤1.0 mg/L: 82.9%), trunk fat (>35%: 62.7% vs. ≤35%: 80.1%), or whole-body fat (>35%: 63.9% vs. ≤35%: 80.3%). CONCLUSIONS: Findings suggest that women with anemia may be incorrectly identified as not anemic via portable hemoglobinometer, and anemia prevalence may be underestimated at the population level.This study was registered at clinicaltrials.gov as NCT04048330.

Risk clustering and psychopathology from a multi-center cohort of Indian children, adolescents, and young adults.

Developmental adversities early in life are associated with later psychopathology. Clustering may be a useful approach to group multiple diverse risks together and study their relation with psychopathology. To generate risk clusters of children, adolescents, and young adults, based on adverse environmental exposure and developmental characteristics, and to examine the association of risk clusters with manifest psychopathology. Participants (n = 8300) between 6 and 23 years were recruited from seven sites in India. We administered questionnaires to elicit history of previous exposure to adverse childhood environments, family history of psychiatric disorders in first-degree relatives, and a range of antenatal and postnatal adversities. We used these variables to generate risk clusters. Mini-International Neuropsychiatric Interview-5 was administered to evaluate manifest psychopathology. Two-step cluster analysis revealed two clusters designated as high-risk cluster (HRC) and low-risk cluster (LRC), comprising 4197 (50.5%) and 4103 (49.5%) participants, respectively. HRC had higher frequencies of family history of mental illness, antenatal and neonatal risk factors, developmental delays, history of migration, and exposure to adverse childhood experiences than LRC. There were significantly higher risks of any psychiatric disorder [Relative Risk (RR) = 2.0, 95% CI 1.8-2.3], externalizing (RR = 4.8, 95% CI 3.6-6.4) and internalizing disorders (RR = 2.6, 95% CI 2.2-2.9), and suicidality (2.3, 95% CI 1.8-2.8) in HRC. Social-environmental and developmental factors could classify Indian children, adolescents and young adults into homogeneous clusters at high or low risk of psychopathology. These biopsychosocial determinants of mental health may have practice, policy and research implications for people in low- and middle-income countries.

Intraindividual double burden of malnutrition: The contribution of the infant gut microbiome.

The prevalence of the double burden of malnutrition in society is well known with the coexistence of undernutrition with an increase in overweight/obesity; this has been increasing globally with nutritional imbalances and infectious diseases being the major etiological factors. However, there is also the coexistence of inappropriate adiposity or metabolic dysfunction in an individual who appears currently undernourished by anthropometric standards (stunted or underweight); this is the intraindividual double burden of malnutrition. It could also occur in temporal sequence, as anthropometric overweight in an individual who has previously endured childhood under-nutrition. IIDBM has increased the risk for diet-related non-communicable diseases over the past few decades, as it tracks into adulthood, warranting an urgent need for intervention and prevention. While gut dysbiosis has been associated with various forms of malnutrition, the early life gut microbiome composition and its related metabolites and regulatory factors, are possibly linked to the development of inflammatory and metabolic conditions in IIDBM. The possible underlying physiological mechanisms are reviewed here, working through host dietary influences, gut microbial metabolites, host inflammation and metabolic dysregulation. When validated experimentally and tested through appropriately designed randomised, controlled trials, these mechanistic insights will likely lead to development of preventive strategies.

Central obesity in low BMI as a risk factor for COVID-19 severity in South Indians.

BACKGROUND AND OBJECTIVES: South Asians are known to have excess adiposity at a lower body mass index, with truncal fat accumulation. Whether this confers higher risk to develop severe COVID-19 is not known. This study evaluated body mass index, body fat mass and waist circumference as risk factors for COVID-19 severity and its progression, in South Asian adults. METHODS AND STUDY DESIGN: Details of COVID-19 patients (19-90 years) were obtained prospectively, along with weight, height, waist circumference and body fat mass assessed by bioelectrical impedance analysis. Binomial logistic and Poisson regression were performed to test associations between waist circumference, body fat mass and body mass index to evaluate the adjusted OR or relative risk for disease severity at admission and length of stay. RESULTS: After adjusting for age, sex, height and co-morbidities, body mass index >23 kg/m2 (adjusted OR 2.758, 95% CI 1.025, 7.427), waist circumference (adjusted OR 1.047, 95% CI 1.002, 1.093) and body fat mass (adjusted OR 1.111, 95% CI 1.013, 1.219) were associated with a significant risk for disease severity at admission, while only waist circumference (adjusted relative risk 1.004, 95% CI 1.001, 1.008), and body fat mass (adjusted relative risk 1.011, 95% CI 1.003, 1.018), were associated with a significantly longer length of stay. CONCLUSIONS: Body mass index, at a lower cut-off of >23 kg/m2, is a significant risk factor for COVID-19 disease severity in the group of patients studied. The waist circumference and body fat mass are also good indicators for both severity at admission and length of stay.

The Consortium on Vulnerability to Externalizing Disorders and Addictions (c-VEDA): an accelerated longitudinal cohort of children and adolescents in India.

The global burden of disease attributable to externalizing disorders such as alcohol misuse calls urgently for effective prevention and intervention. As our current knowledge is mainly derived from high-income countries such in Europe and North-America, it is difficult to address the wider socio-cultural, psychosocial context, and genetic factors in which risk and resilience are embedded in low- and medium-income countries. c-VEDA was established as the first and largest India-based multi-site cohort investigating the vulnerabilities for the development of externalizing disorders, addictions, and other mental health problems. Using a harmonised data collection plan coordinated with multiple cohorts in China, USA, and Europe, baseline data were collected from seven study sites between November 2016 and May 2019. Nine thousand and ten participants between the ages of 6 and 23 were assessed during this time, amongst which 1278 participants underwent more intensive assessments including MRI scans. Both waves of follow-ups have started according to the accelerated cohort structure with planned missingness design. Here, we present descriptive statistics on several key domains of assessments, and the full baseline dataset will be made accessible for researchers outside the consortium in September 2019. More details can be found on our website [cveda.org].

A series of five population-specific Indian brain templates and atlases spanning ages 6-60 years.

Anatomical brain templates are commonly used as references in neurological MRI studies, for bringing data into a common space for group-level statistics and coordinate reporting. Given the inherent variability in brain morphology across age and geography, it is important to have templates that are as representative as possible for both age and population. A representative-template increases the accuracy of alignment, decreases distortions as well as potential biases in final coordinate reports. In this study, we developed and validated a new set of T1w Indian brain templates (IBT) from a large number of brain scans (total n = 466) acquired across different locations and multiple 3T MRI scanners in India. A new tool in AFNI, make_template_dask.py, was created to efficiently make five age-specific IBTs (ages 6-60 years) as well as maximum probability map (MPM) atlases for each template; for each age-group's template-atlas pair, there is both a "population-average" and a "typical" version. Validation experiments on an independent Indian structural and functional-MRI dataset show the appropriateness of IBTs for spatial normalization of Indian brains. The results indicate significant structural differences when comparing the IBTs and MNI template, with these differences being maximal along the Anterior-Posterior and Inferior-Superior axes, but minimal Left-Right. For each age-group, the MPM brain atlases provide reasonably good representation of the native-space volumes in the IBT space, except in a few regions with high intersubject variability. These findings provide evidence to support the use of age and population-specific templates in human brain mapping studies.

Metabolic Availability of Lysine in Milk and a Vegetarian Cereal-Legume Meal Determined by the Indicator Amino Acid Oxidation Method in Indian Men.

BACKGROUND: Lysine rich foods such as milk and legumes serve as important food additions to the lysine deficient cereal-based diets of vegetarian populations in low- and middle-income countries (LMICs) to alleviate the risk of quality corrected dietary protein inadequacy. Dietary protein quality can be determined by estimating the metabolic availability (MA) of lysine. OBJECTIVES: The study aimed to estimate the MA of lysine in spray-dried cow milk powder (SMP), heat-treated spray-dried cow milk powder (HSMP), and a habitually consumed cereal-legume based vegetarian meal (VM), using the indicator amino acid oxidation (IAAO) slope-ratio method. METHODS: The MA of lysine in SMP, HSMP, and VM was estimated in 7 healthy young men aged 19-24 y with BMI of 21.5 ± 0.5 kg/m2 in a repeated measures design. The IAAO response slopes with 2 graded lysine intakes (10.5 and 15.0 mg·kg-1·d-1) from the SMP and VM were compared with the response slope generated with 3 graded crystalline lysine intakes (6.0, 10.5, and 15.0 mg·kg-1·d-1) at the subrequirement level. To produce HSMP, pasteurized cow milk was heat treated and spray dried. The MA of lysine in HSMP was tested at a single level of lysine intake (15 mg·kg-1·d-1). A total of 8 IAAO experiments were conducted on each participant in randomized order. The IAAO slopes were estimated using a linear mixed-effect regression model. RESULTS: The MA of lysine in SMP, HSMP, and VM was 91.9%, 69.9%, and 86.6% respectively. CONCLUSIONS: Heat treatment reduced the MA of lysine by 22% in HSMP compared with SMP in healthy Indian adults. The lysine MA estimates can be used to optimize lysine limited cereal-based diets, with the addition of appropriately processed legumes and milk powder, to meet the protein requirement. This trial was registered at Clinical Trials Registry of India (http://ctri.nic.in) as CTRI/2019/08/020568.

The Thin But Fat Phenotype is Uncommon at Birth in Indian Babies.

BACKGROUND: Indian babies are hypothesized to be born thin but fat. This has not been confirmed with precise measurements at birth. If it is true, it could track into later life and confer risk of noncommunicable diseases (NCDs). OBJECTIVES: Primarily, to accurately measure percentage of body fat (%BF) and body cell mass (BCM) in Indian babies with normal birth weight, compare them across different gestational ages and sex, and test the hypothesis of the thin but fat phenotype in Indian babies. Secondarily, to examine the relation between body weight and body fat in Indian babies. METHODS: Term newborns (n = 156) weighing ≥2500 g, from middle socioeconomic status mothers were recruited in Bengaluru, India, and their anthropometry, %BF (air displacement plethysmography), and BCM (whole-body potassium counter) were measured. Maternal demography and anthropometry were recorded. The mean %BF and its dispersion were compared with earlier studies. The relation between newborn %BF and body weight was explored by regression analysis. RESULTS: Mean birth weight was 3.0 ± 0.3 kg, with mean %BF 9.8 ± 3.5%, which was comparable to pooled estimates of %BF from published studies (9.8%; 95% CI: 9.7, 10.0; P > 0.05). Appropriate-for-gestational age (AGA) babies had higher %BF (1.8%) compared to small-for-gestational age (SGA) babies (P < 0.01). Mean %BCM of all babies at birth was 35.4 ± 10.5%; AGA babies had higher %BCM compared to SGA babies (7.0%, P < 0.05). Girls in comparison to boys had significantly higher %BF and lower %BCM. Body weight was positively associated with %BF. CONCLUSION: Indian babies with normal birth weight did not demonstrate the thin but fat phenotype. Body weight and fat had positive correlation, such that SGA babies did not show a preservation of their %BF. These findings will have relevance in planning optimal interventions during early childhood to prevent NCDs risk in adult life.

Consortium on Vulnerability to Externalizing Disorders and Addictions (cVEDA): A developmental cohort study protocol.

BACKGROUND: Low and middle-income countries like India with a large youth population experience a different environment from that of high-income countries. The Consortium on Vulnerability to Externalizing Disorders and Addictions (cVEDA), based in India, aims to examine environmental influences on genomic variations, neurodevelopmental trajectories and vulnerability to psychopathology, with a focus on externalizing disorders. METHODS: cVEDA is a longitudinal cohort study, with planned missingness design for yearly follow-up. Participants have been recruited from multi-site tertiary care mental health settings, local communities, schools and colleges. 10,000 individuals between 6 and 23 years of age, of all genders, representing five geographically, ethnically, and socio-culturally distinct regions in India, and exposures to variations in early life adversity (psychosocial, nutritional, toxic exposures, slum-habitats, socio-political conflicts, urban/rural living, mental illness in the family) have been assessed using age-appropriate instruments to capture socio-demographic information, temperament, environmental exposures, parenting, psychiatric morbidity, and neuropsychological functioning. Blood/saliva and urine samples have been collected for genetic, epigenetic and toxicological (heavy metals, volatile organic compounds) studies. Structural (T1, T2, DTI) and functional (resting state fMRI) MRI brain scans have been performed on approximately 15% of the individuals. All data and biological samples are maintained in a databank and biobank, respectively. DISCUSSION: The cVEDA has established the largest neurodevelopmental database in India, comparable to global datasets, with detailed environmental characterization. This should permit identification of environmental and genetic vulnerabilities to psychopathology within a developmental framework. Neuroimaging and neuropsychological data from this study are already yielding insights on brain growth and maturation patterns.

Breastfeeding and childhood obesity: A 12-country study.

This study aimed to examine the association between breastfeeding and childhood obesity. A multinational cross-sectional study of 4,740 children aged 9-11 years was conducted from 12 countries. Infant breastfeeding was recalled by parents or legal guardians. Height, weight, waist circumference, and body fat were obtained using standardized methods. The overall prevalence of obesity, central obesity, and high body fat were 12.3%, 9.9%, and 8.1%, respectively. After adjustment for maternal age at delivery, body mass index (BMI), highest maternal education, history of gestational diabetes, gestational age, and child's age, sex, birth weight, unhealthy diet pattern scores, moderate-to-vigorous physical activity, sleeping, and sedentary time, exclusive breastfeeding was associated with lower odds of obesity (odds ratio [OR] 0.76, 95% confidence interval, CI [0.57, 1.00]) and high body fat (OR 0.60, 95% CI [0.43, 0.84]) compared with exclusive formula feeding. The multivariable-adjusted ORs based on different breastfeeding durations (none, 1-6, 6-12, and > 12 months) were 1.00, 0.74, 0.70, and 0.60 for obesity (Ptrend = .020) and 1.00, 0.64, 047, and 0.64 for high body fat (Ptrend = .012), respectively. These associations were no longer significant after adjustment for maternal BMI. Breastfeeding may be a protective factor for obesity and high body fat in 9- to 11-year-old children from 12 countries.

Joint associations between weekday and weekend physical activity or sedentary time and childhood obesity.

OBJECTIVE: To evaluate the single and joint associations of objectively measured moderate-to-vigorous physical activity (MVPA) and sedentary time on week and weekend days with obesity in children from 12 countries across all inhabited continents. METHODS: A multinational, 12-country cross-sectional study of 5779 children aged 9-11 years was conducted. Time spent in MVPA and sedentary behaviors was assessed by waist-worn accelerometry. Logistic regression was used to examine the independent and joint associations of MVPA and sedentary time on weekdays and weekend with the odds of obesity. RESULTS: After adjustment for all confounding factors, the odds ratios (ORs) of childhood obesity were the highest among children with a low level of MVPA on both weekdays and weekend (OR 4.67), high among children with a high level of MVPA on weekdays and a low level of MVPA on weekend (OR 1.99) and high among children with a low level of MVPA on weekdays and a high levels of MVPA on weekend (OR 2.20), compared to those with a high level of MVPA on both weekdays and weekend. Similarly, the ORs of childhood obesity were significantly higher among children with a high level of sedentary time on both weekdays and weekend (OR 1.87) compared with those with low levels of sedentary time on both weekdays and weekend. CONCLUSIONS: Lower levels of MVPA or higher levels of sedentary time on either weekdays or weekend were associated with increased odds of obesity in 9-11 year old children in 12 countries.

Body composition techniques.

Body composition is known to be associated with several diseases, such as cardiovascular disease, diabetes, cancers, osteoporosis and osteoarthritis. Body composition measurements are useful in assessing the effectiveness of nutritional interventions and monitoring the changes associated with growth and disease conditions. Changes in body composition occur when there is a mismatch between nutrient intake and requirement. Altered body composition is observed in conditions such as wasting and stunting when the nutritional intake may be inadequate. Overnutrition on the other hand leads to obesity. Many techniques are available for body composition assessment, which range from simple indirect measures to more sophisticated direct volumetric measurements. Some of the methods that are used today include anthropometry, tracer dilution, densitometry, dual-energy X-ray absorptiometry, air displacement plethysmography and bioelectrical impedance analysis. The methods vary in their precision and accuracy. Imaging techniques such as nuclear magnetic resonance imaging and computed tomography have become powerful tools due to their ability of visualizing and quantifying tissues, organs, or constituents such as muscle and adipose tissue. However, these methods are still considered to be research tools due to their cost and complexity of use. This review was aimed to describe the commonly used methods for body composition analysis and provide a brief introduction on the latest techniques available.

Health-Related Quality of Life and Lifestyle Behavior Clusters in School-Aged Children from 12 Countries.

OBJECTIVE: To evaluate the relationship between children's lifestyles and health-related quality of life and to explore whether this relationship varies among children from different world regions. STUDY DESIGN: This study used cross-sectional data from the International Study of Childhood Obesity, Lifestyle and the Environment. Children (9-11 years) were recruited from sites in 12 nations (n = 5759). Clustering input variables were 24-hour accelerometry and self-reported diet and screen time. Health-related quality of life was self-reported with KIDSCREEN-10. Cluster analyses (using compositional analysis techniques) were performed on a site-wise basis. Lifestyle behavior cluster characteristics were compared between sites. The relationship between cluster membership and health-related quality of life was assessed with the use of linear models. RESULTS: Lifestyle behavior clusters were similar across the 12 sites, with clusters commonly characterized by (1) high physical activity (actives); (2) high sedentary behavior (sitters); (3) high screen time/unhealthy eating pattern (junk-food screenies); and (4) low screen time/healthy eating pattern and moderate physical activity/sedentary behavior (all-rounders). Health-related quality of life was greatest in the all-rounders cluster. CONCLUSIONS: Children from different world regions clustered into groups of similar lifestyle behaviors. Cluster membership was related to differing health-related quality of life, with children from the all-rounders cluster consistently reporting greatest health-related quality of life at sites around the world. Findings support the importance of a healthy combination of lifestyle behaviors in childhood: low screen time, healthy eating pattern, and balanced daily activity behaviors (physical activity and sedentary behavior). TRIAL REGISTRATION: ClinicalTrials.gov: NCT01722500.

Socioeconomic status and dietary patterns in children from around the world: different associations by levels of country human development?

BACKGROUND: Although 'unhealthy' diet is a well-known risk factor for non-communicable diseases, its relationship with socio-economic status (SES) has not been fully investigated. Moreover, the available research has largely been conducted in countries at high levels of human development. This is the first study to examine relationships among dietary patterns and SES of children from countries spanning a wide range of human development. METHODS: This was a multinational cross-sectional study among 9-11 year-old children (n = 6808) from urban/peri-urban sites across 12 countries. Self-reported food frequency questionnaires were used to determine the children's dietary patterns. Principal Components Analysis was employed to create two component scores representing 'unhealthy' and 'healthy' dietary patterns. Multilevel models accounting for clustering at the school and site level were used to examine the relationships among dietary patterns and SES. RESULTS: The mean age of participants in this study (53.7% girls) was 10.4 years. Largest proportions of total variance in dietary patterns occurred at the individual, site, and school levels (individual, school, site: 62.8%; 10.8%; 26.4% for unhealthy diet pattern (UDP) and 88.9%; 3.7%; 7.4%) for healthy diet pattern (HDP) respectively. There were significant negative 'unhealthy' diet-SES gradients in 7 countries and positive 'healthy' diet-SES gradients in 5. Within country diet-SES gradients did not significantly differ by HDI. Compared to participants in the highest SES groups, unhealthy diet pattern scores were significantly higher among those in the lowest within-country SES groups in 8 countries: odds ratios for Australia (2.69; 95% CI: 1.33-5.42), Canada (4.09; 95% CI: 2.02-8.27), Finland (2.82; 95% CI: 1.27-6.22), USA (4.31; 95% CI: 2.20-8.45), Portugal (2.09; 95% CI: 1.06-4.11), South Africa (2.77; 95% CI: 1.22-6.28), India (1.88; 95% CI: 1.12-3.15) and Kenya (3.35; 95% CI: 1.91-5.87). CONCLUSIONS: This study provides evidence of diet-SES gradients across all levels of human development and that lower within-country SES is strongly related to unhealthy dietary patterns. Consistency in within-country diet-SES gradients suggest that interventions and public health strategies aimed at improving dietary patterns among children may be similarly employed globally. However, future studies should seek to replicate these findings in more representative samples extended to more rural representation.

Maternal gestational diabetes and childhood obesity at age 9-11: results of a multinational study.

AIMS/HYPOTHESIS: The aim of this study was to examine the association between maternal gestational diabetes mellitus (GDM) and childhood obesity at age 9-11 years in 12 countries around the world. METHODS: A multinational cross-sectional study of 4740 children aged 9-11 years was conducted. Maternal GDM was diagnosed according to the ADA or WHO criteria. Height and waist circumference were measured using standardised methods. Weight and body fat were measured using a portable Tanita SC-240 Body Composition Analyzer. Multilevel modelling was used to account for the nested nature of the data. RESULTS: The prevalence of reported maternal GDM was 4.3%. The overall prevalence of childhood obesity, central obesity and high body fat were 12.3%, 9.9% and 8.1%, respectively. The multivariable-adjusted (maternal age at delivery, education, infant feeding mode, gestational age, number of younger siblings, child unhealthy diet pattern scores, moderate-to-vigorous physical activity, sleeping time, sedentary time, sex and birthweight) odds ratios among children of GDM mothers compared with children of non-GDM mothers were 1.53 (95% CI 1.03, 2.27) for obesity, 1.73 (95% CI 1.14, 2.62) for central obesity and 1.42 (95% CI 0.90, 2.26) for high body fat. The positive association was still statistically significant for central obesity after additional adjustment for current maternal BMI but was no longer significant for obesity and high body fat. CONCLUSIONS/INTERPRETATION: Maternal GDM was associated with increased odds of childhood obesity at 9-11 years old but this association was not fully independent of maternal BMI.

Improving wear time compliance with a 24-hour waist-worn accelerometer protocol in the International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE).

BACKGROUND: We compared 24-hour waist-worn accelerometer wear time characteristics of 9-11 year old children in the International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE) to similarly aged U.S. children providing waking-hours waist-worn accelerometer data in the 2003-2006 National Health and Nutrition Examination Survey (NHANES). METHODS: Valid cases were defined as having ≥4 days with ≥10 hours of waking wear time in a 24-hour period, including one weekend day. Previously published algorithms for extracting total sleep episode time from 24-hour accelerometer data and for identifying wear time (in both the 24-hour and waking-hours protocols) were applied. The number of valid days obtained and a ratio (percent) of valid cases to the number of participants originally wearing an accelerometer were computed for both ISCOLE and NHANES. Given the two surveys' discrepant sampling designs, wear time (minutes/day, hours/day) from U.S. ISCOLE was compared to NHANES using a meta-analytic approach. Wear time for the 11 additional countries participating in ISCOLE were graphically compared with NHANES. RESULTS: 491 U.S. ISCOLE children (9.92±0.03 years of age [M±SE]) and 586 NHANES children (10.43 ± 0.04 years of age) were deemed valid cases. The ratio of valid cases to the number of participants originally wearing an accelerometer was 76.7% in U.S. ISCOLE and 62.6% in NHANES. Wear time averaged 1357.0 ± 4.2 minutes per 24-hour day in ISCOLE. Waking wear time was 884.4 ± 2.2 minutes/day for U.S. ISCOLE children and 822.6 ± 4.3 minutes/day in NHANES children (difference = 61.8 minutes/day, p < 0.001). Wear time characteristics were consistently higher in all ISCOLE study sites compared to the NHANES protocol. CONCLUSIONS: A 24-hour waist-worn accelerometry protocol implemented in U.S. children produced 22.6 out of 24 hours of possible wear time, and 61.8 more minutes/day of waking wear time than a similarly implemented and processed waking wear time waist-worn accelerometry protocol. Consistent results were obtained internationally. The 24-hour protocol may produce an important increase in wear time compliance that also provides an opportunity to study the total sleep episode time separate and distinct from physical activity and sedentary time detected during waking-hours. TRIAL REGISTRATION: ClinicalTrials.gov NCT01722500 .

A model for presenting accelerometer paradata in large studies: ISCOLE.

BACKGROUND: We present a model for reporting accelerometer paradata (process-related data produced from survey administration) collected in the International Study of Childhood Obesity Lifestyle and the Environment (ISCOLE), a multi-national investigation of >7000 children (averaging 10.5 years of age) sampled from 12 different developed and developing countries and five continents. METHODS: ISCOLE employed a 24-hr waist worn 7-day protocol using the ActiGraph GT3X+. Checklists, flow charts, and systematic data queries documented accelerometer paradata from enrollment to data collection and treatment. Paradata included counts of consented and eligible participants, accelerometers distributed for initial and additional monitoring (site specific decisions in the face of initial monitoring failure), inadequate data (e.g., lost/malfunction, insufficient wear time), and averages for waking wear time, valid days of data, participants with valid data (≥4 valid days of data, including 1 weekend day), and minutes with implausibly high values (≥20,000 activity counts/min). RESULTS: Of 7806 consented participants, 7372 were deemed eligible to participate, 7314 accelerometers were distributed for initial monitoring and another 106 for additional monitoring. 414 accelerometer data files were inadequate (primarily due to insufficient wear time). Only 29 accelerometers were lost during the implementation of ISCOLE worldwide. The final locked data file consisted of 6553 participant files (90.0% relative to number of participants who completed monitoring) with valid waking wear time, averaging 6.5 valid days and 888.4 minutes/day (14.8 hours). We documented 4762 minutes with implausibly high activity count values from 695 unique participants (9.4% of eligible participants and <0.01% of all minutes). CONCLUSIONS: Detailed accelerometer paradata is useful for standardizing communication, facilitating study management, improving the representative qualities of surveys, tracking study endpoint attainment, comparing studies, and ultimately anticipating and controlling costs. TRIAL REGISTRATION: ClinicalTrials.gov: NCT01722500.