Generalized Additive Models For Location, Scale And Shape Research Articles

Prediction of deciduous teeth eruption in Brazilian children: A cross-sectional study nested in a prospective birth cohort (BRISA)

BackgroundDental eruption is part of a set of children´s somatic growth phenomena. The worldwide accepted human dental eruption chronology is still based on a small sample of European children. However, evidence points to some population variations with the eruption at least two months later in low-income countries, and local standards may be useful. So, this study aimed to predict deciduous teeth eruption from 12 months of age in a Brazilian infant population.MethodsWe developed a cross-sectional study nested in four prospective cohorts – the Brazilian Ribeirão Preto and São Luís Cohort Study (BRISA) – in a sample of 3,733 children aged 12 to 36 months old, corrected by gestational age. We made a reference curve with the number of teeth erupted by age using the Generalized Additive Models for location, scale, and shape (GAMLSS) technique. The explanatory variable was the corrected children´s age. The dependent variable was the number of erupted teeth, by gender, evaluated according to some different outcome distributional forms. The generalized Akaike information criterion (GAIC) and the model residuals were used as the model selection criterion.ResultsThe Box-Cox Power Exponential method was the GAMLSS model with better-fit indexes. Our estimation curve was able to predict the number of erupted deciduous teeth by age, similar to the real values, in addition to describing the evolution of children’s development, with comparative patterns. There was no difference in the mean number of erupted teeth between the sexes. According to the reference curve, at 12 months old, 25% of children had four erupted teeth or less, while 75% had seven or fewer and 95% had 11 or fewer. At 24 months old, 5% had less than 12, and 75% had 18 or more. At 36 months old, around 50% of the population had deciduous dentition completed (20 teeth).ConclusionThe adjusted age was an important predictor of the number of erupted deciduous teeth. This outcome can be a variable incorporated into children’s growth and development curves, such as weight and height curves for age to help dentists and physicians in the monitoring the children’s health.

Influence of large-scale climate indices and regional meteorological elements on drought characteristics in the Luanhe River Basin

Frequent drought disasters have significant impacts on socio-economic and ecosystems, and it is crucial to explore the propagation characteristics of drought for disaster prevention and mitigation. In this paper, based on 0.25° × 0.25° grid-point Meteorological hydrological and large-scale climate factor data, the start-to-start, peak-to-peak, and end-to-end drought propagation times, and the periods and rates of drought development and recovery were estimated for 11 regions in the Luanhe River Basin under stationary and non-stationary conditions. The Generalized Additive Model for Location, Scale and Shape (GAMLSS) framework was used to construct stationary and non-stationary models to capture the stationary and non-stationary drought characteristics respectively, and then the drought development and recovery patterns, and drought propagation times were assessed. The results showed that under the influence of climate factors, severe drought events occurred in most study areas, the duration of meteorological drought was prolonged by 0.1–0.6 months, and the peak intensity was increased by about 0.05. The severity of hydrological drought increased by 0.2–0.8, and the peak intensity decreased by 0.1–0.2. The rate of development and recovery of hydrological drought was accelerated by 0.1–0.2 per month. The propagation time of start-to-start was shortened by 0.2 months, and the propagation time of end-to-end was extended by 1–2 months. These mean that water resource control authorities need to propose responses to droughts more quickly.

MODELING PNEUMONIA CASES IN TODDLERS IN INDONESIA USING GENERALIZED ADDITIVE MODEL FOR LOCATION, SCALE, AND SHAPE (GAMLSS) WITH LOESS SMOOTHING

Pneumonia is an acute respiratory infectious disease that is the primary death cause due to infection in children worldwide, including Indonesia. Pneumonia case modeling is necessary to predict the incidence, especially pneumonia in toddlers. In this study, case modeling using the Generalized Additive Model for Location, Scale, and Shape (GAMLSS) method with LOESS smoothing to determine the model form and the factors influencing pneumonia cases in toddlers in Indonesia in 2021. The research results obtained indicate that with the Inverse Gaussian distribution, the model form for the location parameter is  9,719 + 0,013 + 0,001 + 0,031 and for the scale parameter is  -10,897 + 0,125. The resulting model is accurate and suitable for use because the model residuals follow a normal distribution. Along with factors that influence pneumonia cases in toddlers in Indonesia are the percentage of babies receiving exclusive breastfeeding (), population density (), and the percentage of toddlers receiving measles immunization ().

Quantifying spatial ignorance in the effort to collect terrestrial fauna in Namibia, Africa

Effective conservation efforts and predictions of future impacts on biodiversity depend heavily on publicly available information about species distributions. However, data on species distributions is often patchy, especially in many countries of the Global South where resources for biological surveys have been historically limited. In this study, we use biodiversity ignorance scores to quantify and visualize gaps and biases in biodiversity data for Namibia, with a focus on five terrestrial taxa at a spatial scale of 10 x 10 km. We model the relationship between ignorance scores and socio-geographical variables using generalized additive models for location, scale and shape (GAMLSS). Our findings demonstrate that despite a high volume of occurrence records available on the Global Biodiversity Information Facility (GBIF), publicly available knowledge of Namibia's terrestrial biodiversity remains very limited, with large areas contributing few or no records for key taxa. The exception is birds that have benefitted from a massive influx of data from the citizen science platform eBird. Our study also highlights the importance of citizen science initiatives for biodiversity knowledge and reinforces the usefulness of ignorance scores as a simple intuitive indicator of the relative availability and distribution of species occurrence records. However, further research, biological surveys, and renewed efforts to make existing data held by museums and other institutions widely available are still necessary to enhance biodiversity data coverage in countries with patchy data.

Wildlife Roadkill Driven by Hydrological Regime in a Subtropical Wetland

This study explored the role of the hydrological regime as a trigger factor for wildlife roadkill along a 22 km road crossing the Taim Wetland, a Ramsar site of international importance in South Brazil. The north–south crossing of BR-471, a federal highway, causes fatalities to numerous animals due to collisions with vehicles. An 11-year long-term time series study encompassing monthly roadkill incidents, water level, and rainfall was analyzed by considering three different periods related to a Wildlife Protection System (WPS): (i) 3 initial years before the WPS implementation (BWPS); (ii) 4 intermediate years after the WPS implementation (AWPS), which includes fences, fauna tunnels, cattle guard stocks, bumps, and speed control; (iii) 4 final years during partial destruction of the WPS (PDWPS). A pseudo-2D full hydrodynamic cell model was employed to fill missing water level data. The model had a good to very good performance (NSE: 0.73 to 0.87; R2: 0.79 to 0.90). The relationship between roadkill incidents and the WPS periods (BWPS, AWPS, and PDWPS) was modeled using Generalized Additive Models for Location, Scale, and Shape (GAMLSS), considering rainfall and water level as predictor variables. The analysis revealed a higher incidence of wildlife roadkill in BWPS compared to AWPS and PDWPS, suggesting the effectiveness of the implemented measures. Critical season and interplay between water levels, rainfall, and the roadkill were assessed. Mammals was the most common roadkill class identified (~92%), followed by reptiles (13%) and birds (2%), with no change in these percentual in the BWPS, AWPS, and PDWPS. Among mammals, capybara (Hydrochoerus hydrochaeris) and coypu (Myocastor coypu) were the most frequent victims (~93% of mammals). Winter, followed by autumn, recorded the highest number of roadkill incidents (>60%), and this pattern remained consistent during the three periods. While rainfall did not emerge as a determining variable for roadkill, water levels above certain thresholds (>3.3 m) drastically diminished the effectiveness of the WPS, mainly due to fauna tunnel submersion. These findings offer valuable insights for enhancing wildlife conservation strategies in this protected area by incorporating hydrological information providing a baseline for designing WPS in similar environments.

An attempt to correct the underestimation of inequality measures in cross-survey imputation through generalized additive models for location, scale and shape

This paper contributes to the debate on ways to improve the calculation of inequality measures in developing countries experiencing severe budget constraints. Linear regression-based survey-to-survey imputation techniques (SSITs) are most frequently discussed in the literature. These are effective at estimating predictions of poverty indicators but are much less accurate with inequality indicators. To demonstrate this limited accuracy, the first part of the paper review and discuss the SSITs. The paper proposes a method for overcoming these limitations based on a Generalized Additive Models for Location, Scale and Shape (GAMLSS). Before to apply this method to Moroccan data with the aim to analyze the relation between poverty and climate changes a simulation is carried out to compare classical SSIT and SSIT based on GAMLSS.

In vivo marker of brainstem myelin is associated to quantitative sleep parameters in healthy young men

The regional integrity of brain subcortical structures has been implicated in sleep–wake regulation, however, their associations with sleep parameters remain largely unexplored. Here, we assessed association between quantitative Magnetic Resonance Imaging (qMRI)-derived marker of the myelin content of the brainstem and the variability in the sleep electrophysiology in a large sample of 18-to-31 years healthy young men (N = 321; ~ 22 years). Separate Generalized Additive Model for Location, Scale and Shape (GAMLSS) revealed that sleep onset latency and slow wave energy were significantly associated with MTsat estimates in the brainstem (pcorrected ≤ 0.03), with overall higher MTsat value associated with values reflecting better sleep quality. The association changed with age, however (MTsat-by-age interaction—pcorrected ≤ 0.03), with higher MTsat value linked to better values in the two sleep metrics in the younger individuals of our sample aged ~ 18 to 20 years. Similar associations were detected across different parts of the brainstem (pcorrected ≤ 0.03), suggesting that the overall maturation and integrity of the brainstem was associated with both sleep metrics. Our results suggest that myelination of the brainstem nuclei essential to regulation of sleep is associated with inter-individual differences in sleep characteristics during early adulthood. They may have implications for sleep disorders or neurological diseases related to myelin.

Reference values for body composition in healthy urban Mexican children and adolescents.

Given the increasing incidence of chronic degenerative diseases related to changes in tissues, the availability of diagnostic tools with greater accuracy in the estimation of body composition (BC) has become necessary. Interpreting the BC values of individuals requires reference data obtained from a healthy population with the same ethnicity, to identify individuals at risk for the development of negative health outcomes. Generate reference values (RV) of body composition (BC) for Mexican children and adolescents. This was an urban-population-based cross-sectional study of healthy Mexican children and adolescents. BC estimations by anthropometry, multifrequency bioimpedance analysis (MF-BIA) and dual-energy X-ray absorptiometry (DXA) where used to create sex- and age-specific RV by means of generalized additive models for location, scale and shape (GAMLSS). We assessed 2104 subjects, and after confirming a clinically and metabolically healthy status, we measured 1659 subjects aged 5-20 years, [806 females (49%) and 853 males (51%)] by anthropometry, MF-BIA and DXA to create sex- and age- smoothed reference centiles, lambda (L), mu (M), and sigma (S) values. We also built sex- and age-smoothed graphic curves for each variable of interest. We present valid RV and curves for BC variables estimated by anthropometry, MF-BIA and DXA from clinically and metabolically healthy urban Mexican children and adolescents. These RV are different from those reported for other populations, and therefore, should be used for clinical and research purposes involving urban Mexican children and adolescents.

Growth patterns of young achondroplasia patients in Korea and predictability of neurosurgical procedures

BackgroundAchondroplasia is an autosomal dominant disorder mainly affecting bony growth, typically resulting in markedly short stature. From a neurosurgical viewpoint, patients sometimes develop spinal cord compression at the narrowed foramen magnum and hydrocephalus. This study aims to construct growth references for height, weight, and head circumference (HC) of young achondroplasia patients in Korea and to evaluate the predictability of the necessity and timing of neurosurgical procedures through growth patterns.MethodsGrowth data were collected from achondroplasia patients who visited our institution between January 2002 and August 2022. First, we constructed percentile growth curves of height, weight, and HC for the patients under 3 years of age with the generalized additive model for location, scale, and shape (GAMLSS). Second, the growth patterns of the patients with hydrocephalus who underwent neurosurgical procedures such as foramen magnum decompression (FMD) and ventriculoperitoneal (VP) shunt were analyzed.ResultsThere were 125 achondroplasia patients, including 67 males and 58 females. Among 125 patients, 46 underwent FMD, and 5 underwent VP shunt. As short stature and macrocephaly were typical characteristics of achondroplasia, the height of achondroplasia was lower than that of the general population, and HC in achondroplasia showed accelerated growth postnatally. There were no significant changes in HC in hydrocephalus patients before they underwent neurosurgical procedures. The influence of hydrocephalus on the growth patterns of HC in achondroplasia seemed insignificant.ConclusionGrowth references for height, weight, and HC in young achondroplasia patients were constructed. It is the first report of growth patterns of achondroplasia in Korea. Unlike other pediatric patients, the diagnosis of hydrocephalus and the necessity of neurosurgical procedures are hard to be predicted with HC in achondroplasia. Neuroimaging should be considered for achondroplasia patients with neurological symptoms.

Impacts of Air Pollution and Thermal Discomfort in Hospitalizations for Multiple Sclerosis in Sao Paulo, Brazil

Multiple sclerosis (MS) is an autoimmune, neurological, and demyelinating disease of unknown etiology. Neuroinflammation caused by the disease has been associated with air pollution as well as bioclimatic conditions. The aim of this study was to investigate the impacts of air pollution and human thermal discomfort on hospitalizations for multiple sclerosis in Sao Paulo, Brazil, from 2008 to 2015. Generalized Additive Model for Location Scale and Shape (GAMLSS) with Zero Inflated Poisson was used to relate multiple sclerosis hospitalizations in three age groups (less than 30 years old, between 30 and 50 years old, and more than 50 years old) and gender (female and male) with atmospheric pollutants PM10, SO2, NO2, NO, and NOx and thermal discomfort. The results showed that the exposure to an increase of 1 µg/m3 in SO2 concentration is highly associated with a 10% increase of the risk of MS hospitalization (95% CI: 2–21%) in female patients and a 7.5% (95% CI: 1.5–16%) increase in male patients. PM10 and NO were associated with increased MS risk only for female patients, mainly aged between 30 and 50 years old (2% and 1% increase in hospitalizations, respectively). The cold discomfort was also associated with MS hospitalization, mainly in males (2% increase in hospitalizations; 95% IC: 1–3%). These results are important, since there are few studies that relate air pollution and thermal discomfort with hospitalizations for multiple sclerosis in Brazil.

Reference Values for Birth Weight in Relation to Gestational Age in Poland and Comparison with the Global Percentile Standards.

Percentiles of birth weight by gestational age (GA) are an essential tool for clinical assessment and initiating interventions to reduce health risks. Unfortunately, Poland lacks a reference chart for assessing newborn growth based on the national population. This study aimed to establish a national reference range for birth weight percentiles among newborns from singleton deliveries in Poland. Additionally, we sought to compare these percentile charts with the currently used international standards, INTERGROWTH-21 and WHO. All singleton live births (n = 3,745,239) reported in Poland between 2010 and 2019 were analyzed. Using the Lambda Mu Sigma (LMS) method, the Generalized Additive Models for Location Scale, and Shape (GAMLSS) package, smoothed percentile charts (3-97) covering GA from 23 to 42 weeks were constructed. The mean birth weight of boys was 3453 ± 540 g, and this was higher compared with that of girls (3317 ± 509 g). At each gestational age, boys exhibited higher birth weights than girls. The weight range between the 10th and 90th percentiles was 1061 g for boys and 1016 g for girls. Notably, the birth weight of Polish newborns was higher compared to previously published international growth standards. The reference values for birth weight percentiles established in this study for Polish newborns differ from the global standards and are therefore useful for evaluating the growth of newborns within the national population. These findings hold clinical importance in identifying neonates requiring postbirth monitoring.

Ambulatory blood pressure as risk factor for long-term kidney function decline in the general population: a distributional regression approach

The results of randomized controlled trials are unclear about the long-term effect of blood pressure (BP) on kidney function assessed as the glomerular filtration rate (GFR) in persons without chronic kidney disease or diabetes. The limited duration of follow-up and use of imprecise methods for assessing BP and GFR are important reasons why this issue has not been settled. Since a long-term randomized trial is unlikely, we investigated the association between 24-h ambulatory BP (ABP) and measured GFR in a cohort study with a median follow-up of 11 years. The Renal Iohexol Clearance Survey (RENIS) cohort is a representative sample of persons aged 50 to 62 years without baseline cardiovascular disease, diabetes, or kidney disease from the general population of Tromsø in northern Norway. ABP was measured at baseline, and iohexol clearance at baseline and twice during follow-up. The study population comprised 1589 persons with 4127 GFR measurements. Baseline ABP or office BP components were not associated with the GFR change rate in multivariable adjusted conventional regression models. In generalized additive models for location, scale, and shape (GAMLSS), higher daytime systolic, diastolic, and mean arterial ABP were associated with a slight shift of the central part of the GFR distribution toward lower GFR and with higher probability of GFR < 60 mL/min/1.73 m2 during follow-up (p < 0.05). The use of a distributional regression method and precise methods for measuring exposure and outcome were necessary to detect an unfavorable association between BP and GFR in this study of the general population.

Applicability of the Global Lung Function Initiative prediction equations in Hong Kong Chinese children.

This study aimed to assess the applicability of the Global Lung Function Initiative (GLI) prediction equations for spirometry in Hong Kong childrenand to develop prediction equations based on the Generalized Additive Models for Location, Scale, and Shape (GAMLSS) modeling. Healthy Chinese children and adolescents aged 6-17 years old were recruited from randomly selected schools to undergo spirometry. The measurements were transformed to z-score according to the GLI-2012 equations for South East(SE) Asians and the GLI-2022 global race-neutral equations. Prediction equations for spirometric indices were developed with GAMLSS modeling to identify predictors. A total of 886 children (477 boys) with a mean age of 12.5 years (standard deviation [SD]3.3 years) were included. By the GLI-2012 SE Asian equations, positive mean z-scores were observed in forced expiratory volume in 1 s(FEV1 )(boys: 0.138 ± SD 0.828;girls: 0.206 ± 0.823) and forced vital capacity(FVC) (boys: 0.160 ± 0.930;girls: 0.310 ± 0.895) in both sexes. Negative mean z-scores were observed in FEV1 /FVC ratio (boys: -0.018 ± 0.998; girls: -0.223 ± 0.897). In contrast, negative mean z-scores in FEV1 and FVC, and positive mean z-scores in FEV1 /FVC were observed when adopting the GLI-2022 race-neutral equations. The mean z-scores were all within the range of ±0.5. By GAMLSS models, age and height were significant predictors for all four spirometric indices, while weight was an additional predictor for FVC and FEV1 . Our study provided data supporting the applicability of the GLI prediction equations in Hong Kong Chinese children. The GLI-2012 equations may underestimate FEV1 and FVC, while the GLI-2022 equations may overestimate the parameters, but the differences lie within the physiological limits. By GAMLSS modeling, weight was an additional predictor for FVC and FEV1 .

Robust gradient boosting for generalized additive models for location, scale and shape

AbstractDue to the increasing complexity and dimensionality of data sources, it is favorable that methodological approaches yield robust results so that corrupted observations do not jeopardize overall conclusions. We propose a modelling approach which is robust towards outliers in the response variable for generalized additive models for location, scale and shape (GAMLSS). We extend a recently proposed robustification of the log-likelihood to gradient boosting for GAMLSS, which is based on trimming low log-likelihood values via a log-logistic function to a boundary depending on a robustness constant. We recommend a data-driven choice for the involved robustness constant based on a quantile of the unconditioned response variable and investigate the choice in a simulation study for low- and high-dimensional data situations. The versatile application possibilities of robust gradient boosting for GAMLSS are illustrated via three biomedical examples—including the modelling of thyroid hormone levels, spatial effects for functional magnetic resonance brain imaging and a high-dimensional application with gene expression levels for cancer cell lines.

Multiscale temporal and spatiotemporal analysis of wheat blast infection‐like dynamics using vertical plant stratification, regression and Markov chain approaches

AbstractThe spatiotemporal progress of wheat blast (WB) epidemics within the plant canopy remains poorly known due to complex pathogen–host–environment interactions. Although deterministic methods are popular and useful, robust stochastic methods, such as generalized additive models for location, scale and shape (GAMLSS) and probability matrix or Markov transition model (MTM), have seldom been used to analyse plant disease epidemics. Hence, both methods were employed to derive valuable insights into WB epidemiology at the vertical canopy level. We conducted experiments in three climatic zones in Bolivia, using three wheat cultivars, with disease data corresponding to different canopy positions (lower, L; middle, M; flag leaf, F; and spike, S). Using WB severity data (AUDPC, progress rate and maximum severity [Kmax]), we implemented the GAMLSS and MTM to test our hypothesis that WB is affected by host resistance, location and canopy level. Results showed that the AUDPC, progress rate and Kmax differed across sites, cultivars and canopy positions. Clearly, L and M canopies showed a lower progress rate than F and S. The disease showed an ascending movement from L and M canopies to F and S across locations and cultivars. However, descending transitions also occurred from M to L early or F to M canopy later in the season. Both ascending and descending movements can arise at a single state or several recurrent states, indicating indirect evidence of autoinfection within the canopy before and after spike emergence. Our findings contribute knowledge to improve monitoring and managing WB.

Nonstationary flood and its influencing factors analysis in the Hanjiang River Basin, China

Due to the impact of climate change and human activities, flood disasters have occurred frequently in the Hanjiang River Basin (HRB) in recent years, and the stationary behavior of its flood fluctuation has been disrupted. In this study, we used Generalized Additive Models for Location, Scale, and Shape (GAMLSS) to analyze the nonstationary changes of annual maximum runoff in the HRB and its influencing factors. It has also been complemented with a stationary model for comparative analysis. We found that the annual maximum runoff has a significant decreasing trend. The top four factors influencing this runoff change are the local changes in precipitation and temperature, and the regional climate oscillations as reflected by the North Atlantic Oscillation index (NAO) and the Pacific North American Index (PNA). The nonstationary model had better simulation effect than the stationary model. The stationary model could not reflect the impact of explanatory variables on annual maximum runoff, while the nonstationary model could well analyze the impact of single and dual explanatory variables. The results of this study provide some new insights in support of flood prevention and control in the HRB.

A distributional regression approach to modeling the impact of structural and intermediary social determinants on communities burdened by tuberculosis in Eastern Amazonia – Brazil

BackgroundTuberculosis (TB) is a disease that is influenced by social determinants of health. However, the specific structural and intermediary determinants of TB in Eastern Amazonia remain unclear. Despite being rich in natural resources, the region faces significant challenges related to poverty, inequality, and neglected diseases. The objective of this study was to use mathematical modeling to evaluate the influence of structural and intermediary determinants of health on TB in Eastern Amazonia, Brazil.MethodsThis cross-sectional included all TB cases diagnosed and registered in the Notifiable Diseases Information System (SINAN) from 2001 to 2017. Data on social determinants were collected at the census tract level. The generalized additive model for location, scale, and shape (GAMLSS) framework was employed to identify the effect of social determinants on communities with a high TB prevalence. The Double Poisson distribution (DPO) was chosen, and inclusion of quadratic effects was tested.ResultsA total of 1730 individuals were diagnosed with TB and reported in SINAN during the analyzed period. The majority were female (59.3%), aged 31 to 59 years (47.6%), identified as blacks (67.9%), and had incomplete elementary education (46.6%). The prevalence of alcoholism was 8.6% and mental illness was 0.7%. GAMLSS analyses demonstrated that the risk of community incidence of TB is associated with the proportion of the population lacking basic sanitation, as well as with the age groups of 16–31 years and > 61 years.ConclusionsThe study highlights the strategic utility of GAMLSS in identifying high-risk areas for TB. Models should encompass a broader range of social determinants to inform policies aimed at reducing inequality and achieving the goals of the End TB strategy.

Crop Cultivation Efficiency and GHG Emission: SBM-DEA Model with Undesirable Output Approach

Crop production relies on the use of natural resources and is a source of greenhouse gas (GHG) emissions. The present study uses survey data from 250 Polish farms to investigate the eco-efficiency of three main crops: winter wheat, winter triticale, and winter oilseed rape. First, the slack-based Data Envelopment Analysis (SBM-DEA) model with undesirable output (GHG emissions) was applied. In the next step, the Generalized Additive Model for Location, Scale and Shape (GAMLSS) was used to explain the efficiency scores. The calculated GHG emissions per hectare of crop were 1.9 tCO2e, 3.2 tCO2e, and 4.3 tCO2e for winter triticale, wheat, and oilseed rape, respectively. Fully efficient farms used significantly less fertilizer (13.6–29.3%) and fuel (16.6–25.3%) while achieving higher yields (14.4–23.2%) and lower GHG emissions per hectare (10.8–17.7%). In practice, this means that efficient farms had a 20–32% lower carbon footprint per kilogram of yield than inefficient farms, depending on the crop. It was also shown that increasing the size of the cultivated area contributed to improving efficiency scores, while no conclusive evidence was found for an influence of economic size or farm type on their performance. Weather conditions had a significant impact on the efficiency score. In general, higher temperatures and precipitation in spring had a positive effect on efficiency, while an opposite relationship was observed in summer.

The Establishment of the Cut-off Value of Weight-for-Height for Preschool Children in China and an Empirical Study on the Influence of Overweight and Obesity on Physical Performance.

We aimed to establish the cut-off value of weight-for-height for preschool children in China, and to explore the influence of overweight and obesity on the physical performance of preschool children. Data from 31 provinces in China monitored in 2010 and 2014, the standard deviation unit curves of WFH were established by using GAMLSS (generalized additive model for location, scale, and shape) method preschool children in China, and then the cut-off values of normal weight, overweight and obesity were divided. The research group tested 5 physical performance indicators of 5154 preschool children from April 2018 to June 2019 in Beijing and Zhejiang in China. We then compared physical performance differences between the normal-weight group and the overweight-obesity group. A smooth and effective standard deviation unit curve of WFH was established. The overweight and obesity of Chinese preschool children were at a high level. Being overweight and obese reduced preschool children's relative strength, speed, sensitivity, coordination, and balance ability, but did not reduce preschool children's flexibility. In general, the physical performance of preschool children in the normal weight group was better than that in the overweight and obesity group. It is suggested to use the WFH criteria in this study to evaluate overweight and obesity in Chinese preschool children, and strengthen physical activity and take in energy substances properly of preschool children, to control the spread of overweight and obesity, to improve physical performance level.

MULT: A new BMI reference to assess nutritional status of multi-ethnic children and adolescents.

To develop a new Body Mass Index (BMI) reference (MULT) based on longitudinal data of multi-ethnic populations and to compare it to international BMI references. The MULT BMI reference was constructed through the LMS method and the Generalized Additive Models for Location Scale and Shape (GAMLSS), with 81 310 observations of 17 505 subjects aged 0-22 years old, from the United Kingdom, Ethiopia, Peru, India, Vietnam, Brazil, and Portugal. Outlier values were removed based on weight z-scores (population level) and based on BMI z-scores using the linear mixed effects model (individual level). The MULT M, S and L curves were compared to the ones of the World Health Organization (WHO), Centers for Disease Control and Prevention (CDC), International Obesity Task Force (IOTF), and Dutch Growth Study (DUTCH). The MULT BMI percentile cutoffs for overweight and obesity were calculated using the adult BMI values of 25 and 30 kg/m2 at 17, 18, 19, and 20 years old. MULT presented the lowest mean BMI values for the ages 102-240 months for boys and 114-220 months for girls. MULT S values were similar to the WHO and IOTF for children under 60 months of age and the highest during puberty, while the L curve showed to be more symmetric than the other BMI references. The MULT BMI reference was constructed based on recent data of populations from 10 countries, being a good option to assess the nutritional status of multi-ethnic populations.