Developing Neck Circumference Growth Reference Charts for Pakistani Children and Adolescents Using the Lambda-Mu-Sigma (LMS) and Quantile Regression Method

• Objective: Neck circumference (NC) is currently used as an embryonic marker of obesity and its associated risks. But its use in clinical evaluations and other epidemiological purposes requires sex and age-specific standardized cut-offs which are still scarce for the Pakistani pediatric population. We therefore developed sex and age-specific growth reference charts for NC for Pakistani children and adolescents aged 2-18 years.Design: Cross-sectional multi-ethnic anthropometric survey (MEAS) study.Setting: Multan, Lahore, Rawalpindi and Islamabad.Participants: The dataset of 10,668 healthy Pakistani children and adolescents aged 2 to 18 years collected in MEAS were used. Information related to age, sex and NC were taken as study variables. The lambda-mu-sigma (LMS) and quantile regression (QR) methods were applied to develop growth reference charts for NC.Results: The 5th, 10th, 25th, 50th, 75th, 90th and 95th smoothed percentile values of NC were presented. The centile values showed that neck size increased with age in both boys and girls. During 8 and 14 years of age, girls were found to have larger NC than boys. A comparison of NC median (50th) percentile values with references from Iranian and Turkish populations reveals substantially lower NC percentiles in Pakistani children and adolescents compared to their peers in the reference population.Conclusion: The comparative results suggest that the uses of NC references of developed countries are inadequate for Pakistani children. A small variability between empirical centiles and centiles obtained by QR procedure recommends that growth charts should be constructed by QR as an alternative method.

Ämnesord

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Pediatrik (hsv//swe)

MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Pediatrics (hsv//eng)

Nyckelord

Growth charts

LMS Method

Neck circumference

Quantile regression

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