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Assessment of circannual variation in relative weight among children in Wisconsin using electronic health records
Author(s) -
Bhutani Surabhi,
Schoeller Dale,
Kloke John,
Hanrahan Lawrence
Publication year - 2016
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.30.1_supplement.276.3
Subject(s) - demography , medicine , psychological intervention , obesity , weight gain , standard score , childhood obesity , body weight , pediatrics , overweight , statistics , mathematics , sociology , psychiatry
Objective Summer weight gain (June through August inclusive) has been repeatedly reported in children. This has recently led to the development and implementation of multiple interventions to address the child's summer environment. Most reports on summer weight gain are mainly based on measures of BMI at the beginning (Sept./Oct.) and end of the school season (May/June), and are the only time points used to demonstrate the success of school based obesity prevention interventions. Basing the relative weight outcome on just two measures may be risky and therefore data on the time course of this weight gain in children is necessary. Thus, the objective of this study was to investigate circannual pattern in childhood weight status. Method We analyzed cross‐sectional height and weight data from de‐identified electronic medical records of 225,607 children (5–17yr) collected between 2007–2012 from South Central Wisconsin. The average monthly BMI and BMI z‐score were calculated and categorized by age, sex, and minority status. Results Averaged across ages, the BMI z‐scores increased during the school year (Sept. – May) by 0.03±0.4 z‐score (P<0.05), but decreased from May to June by 0.08±0.4 z‐score (p<0.01) and then increased from Aug. to Sept. by 0.06±0.4 units (p<0.01). The BMI z‐scores for males were slightly higher than for females and both displayed similar and distinctive differences between May and June and averages being greater beginning in July or Aug. When categorized by race/ethnicity, the BMI z‐scores during July were lowest than those of Sept‐May for Non‐Hispanic White population. Non‐Hispanic Blacks had the lowest BMI z‐score at the beginning of the school year (Sept.) while Hispanics had the lowest BMI z‐score at the end of summer (Aug.). Conclusion Our analysis is consistent with summer weight gain findings from other studies showing a slightly lower BMI z‐score during the school year (Sept. to beginning of June) and higher BMI z‐score during the summer (beginning of Jun to Sept). This pattern would probably be interpreted as a successful intervention by the school followed by regression during the summer, even if there is no effect of the intervention per se. But this also raises issues about adequacy of 2 measures of z‐scores for school evaluations due to lower BMI z‐scores in summer period. We suggest taking additional measures at least in Dec. and March so that a time trend analysis can be performed. An alternate approach might be to move the assessment months to Oct and April. Moreover, a longitudinal study is required to confirm the circannual pattern we observed using cross‐sectional data.