Demystifying LMS and BCPE methods of centile estimation for growth and other health parameters

Indrayan, Abhaya

doi:10.1007/s13312-014-0310-6

Cited by 37 publications

(38 citation statements)

References 11 publications

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“…Using height, weight, age and sex data for each individual, WHZs were calculated using the age-, sex-and indicator-specific lambda-musigma values from the 2006 WHO Child Growth Standards 10,57 . The lambda-musigma methodology allows for Gaussian z score calculations and comparisons to be applied to skewed, non-Gaussian distributions 58 . A child was classified as overweight or wasted if their weight-for-height/length was more than two s.d.…”

Section: Data Surveys and Child Anthropometry Data We Extracted Indmentioning

confidence: 99%

Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017

Kinyoki

Schutte

Ross

et al. 2020

Nat Med

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A double burden of malnutrition occurs when individuals, household members or communities experience both undernutrition and overweight. Here, we show geospatial estimates of overweight and wasting prevalence among children under 5 years of age in 105 low- and middle-income countries (LMICs) from 2000 to 2017 and aggregate these to policy-relevant administrative units. Wasting decreased overall across LMICs between 2000 and 2017, from 8.4% (62.3 (55.1–70.8) million) to 6.4% (58.3 (47.6–70.7) million), but is predicted to remain above the World Health Organization’s Global Nutrition Target of <5% in over half of LMICs by 2025. Prevalence of overweight increased from 5.2% (30 (22.8–38.5) million) in 2000 to 6.0% (55.5 (44.8–67.9) million) children aged under 5 years in 2017. Areas most affected by double burden of malnutrition were located in Indonesia, Thailand, southeastern China, Botswana, Cameroon and central Nigeria. Our estimates provide a new perspective to researchers, policy makers and public health agencies in their efforts to address this global childhood syndemic.

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Section: Data Surveys and Child Anthropometry Data We Extracted Indmentioning

confidence: 99%

Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017

Kinyoki

Schutte

Ross

et al. 2020

Nat Med

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“…Two major statistical challenges involve making these curves: finding different percentiles at each age and achieving smoothness of the estimated percentile curves over age (9). For percentile estimation at each age group, the approach taken by others involves statistical modeling using methods such as generalized linear modeling or generalized additive models for location, scale, and shape (10) to estimate the parameters of a predefined probability distribution thought to best describe the data and from this estimate derive the percentiles.…”

Section: Discussionmentioning

confidence: 99%

“…For each age group distribution, we directly calculated the cumulative distribution function and compared these to fitted standard distributions (Figures 1F,G) (1, 2, 9–13). Gaussian and Logistic estimates were derived using regression based on maximum likelihood estimates.…”

Section: Methodsmentioning

confidence: 99%

Heart Rate and Blood Pressure Centile Curves and Distributions by Age of Hospitalized Critically Ill Children

et al. 2017

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Heart rate (HR) and blood pressure (BP) form the basis for monitoring the physiological state of patients. Although norms have been published for healthy and hospitalized children, little is known about their distributions in critically ill children. The objective of this study was to report the distributions of these basic physiological variables in hospitalized critically ill children. Continuous data from bedside monitors were collected and stored at 5-s intervals from 3,677 subjects aged 0–18 years admitted over a period of 30 months to the pediatric and cardiac intensive care units at a large quaternary children’s hospital. Approximately 1.13 billion values served to estimate age-specific distributions for these two basic physiological variables: HR and intra-arterial BP. Centile curves were derived from the sample distributions and compared to common reference ranges. Properties such as kurtosis and skewness of these distributions are described. In comparison to previously published reference ranges, we show that children in these settings exhibit markedly higher HRs than their healthy counterparts or children hospitalized on in-patient wards. We also compared commonly used published estimates of hypotension in children (e.g., the PALS guidelines) to the values we derived from critically ill children. This is a first study reporting the distributions of basic physiological variables in children in the pediatric intensive care settings, and the percentiles derived may serve as useful references for bedside clinicians and clinical trials.

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“…Centile curves were constructed for each sex between the ages of 0–29 years using Generalized Additive Models for Location Scale and Shape ( GAMLSS )(Rigby and Stasinopoulos, 2005). For height weight and BMI, ages up to 29 were included to anchor curves and avoid edge effects (Indrayan, 2014). For weight-for-height, ages up to 20 were included, and dummy cases with values below the lowest height measurement were added to weight-for-height models to reduce edge effects.…”

Section: Methodsmentioning

confidence: 99%

Growth references for Tsimane forager‐horticulturalists of the Bolivian Amazon

Blackwell

Urlacher

Beheim

et al. 2016

American J Phys Anthropol

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Objectives Growth standards and references currently used to assess population and individual health are derived primarily from urban populations, including few individuals from indigenous or subsistence groups. Given environmental and genetic differences, growth may vary in these populations. Thus, there is a need to assess whether international standards are appropriate for all populations, and to produce population specific references if growth differs. Here we present and assess growth references for the Tsimane, an indigenous population of Bolivian forager-horticulturalists. Methods Mixed cross-sectional/longitudinal anthropometrics (9,614 individuals; 30,118 observations; ages 0–29 years) were used to generate centile curves and Lambda-Mu-Sigma (LMS) tables for height-for-age, weight-for-age, body mass index (BMI)-for-age, and weight-for-height (WFH) using Generalized Additive Models for Location Shape and Scale (GAMLSS). Velocity curves were generated using SuperImposition by Translation and Rotation (SITAR). Tsimane ≤5 years were compared World Health Organization (WHO) standards while those >5 years were compared to WHO school age references. All ages were compared to published references for Shuar forager-horticulturalists of the Ecuadorian Amazon. Results Tsimane growth differs from WHO values in height and weight, but is similar for BMI and WFH. Tsimane growth is characterized by slow height velocity in childhood and early adolescent peak height velocity at 11.3 and 13.2 years for girls and boys. Tsimane growth patterns are similar to Shuar, suggesting shared features of growth among indigenous South Americans. Conclusions International references for BMI-for-age and WFH are likely appropriate for Tsimane, but differences in height-for-age and weight-for-age suggest Tsimane specific references may be useful for these measures.

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Demystifying LMS and BCPE methods of centile estimation for growth and other health parameters

Cited by 37 publications

References 11 publications

Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017

Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017

Heart Rate and Blood Pressure Centile Curves and Distributions by Age of Hospitalized Critically Ill Children

Growth references for Tsimane forager‐horticulturalists of the Bolivian Amazon

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