Objective Although dual-energy X-ray absorptiometry
(DEXA) is the preferred method to estimate adiposity,
body mass index (BMI) is often used as a proxy.
However, the ability of BMI to measure adiposity change
among youth is poorly evidenced. This study explored
which metrics of BMI change have the highest
correlations with different metrics of DEXA change.
Methods Data were from the Quebec Adipose and
Lifestyle Investigation in Youth cohort, a prospective
cohort of children (8–10 years at recruitment) from
Québec, Canada (n=557). Height and weight were
measured by trained nurses at baseline (2008) and
follow-up (2010). Metrics of BMI change were raw
(ΔBMIkg/m2), adjusted for median BMI (ΔBMIpercentage)
and age-sex-adjusted with the Centers for Disease
Control and Prevention growth curves expressed as
centiles (ΔBMIcentile) or z-scores (ΔBMIz-score). Metrics of
DEXA change were raw (total fat mass; ΔFMkg), per cent
(ΔFMpercentage), height-adjusted (fat mass index; ΔFMI)
and age-sex-adjusted z-scores (ΔFMz-score). Spearman’s
rank correlations were derived.
Results Correlations ranged from modest (0.60) to strong
(0.86). ΔFMkg correlated most highly with ΔBMIkg/m2
(r = 0.86), ΔFMI with ΔBMIkg/m2 and ΔBMIpercentage
(r = 0.83–0.84), ΔFMz-score with ΔBMIz-score (r = 0.78), and
ΔFMpercentage with ΔBMIpercentage (r = 0.68). Correlations
with ΔBMIcentile were consistently among the lowest.
Conclusions In 8–10-year-old children, absolute or per
cent change in BMI is a good proxy for change in fat mass
or FMI, and BMI z-score change is a good proxy for FM
z-score change. However change in BMI centile and
change in per cent fat mass perform less well and are not
recommended.
Objective Although dual-energy X-ray absorptiometry
(DEXA) is the preferred method to estimate adiposity,
body mass index (BMI) is often used as a proxy.
However, the ability of BMI to measure adiposity change
among youth is poorly evidenced. This study explored
which metrics of BMI change have the highest
correlations with different metrics of DEXA change.
Methods Data were from the Quebec Adipose and
Lifestyle Investigation in Youth cohort, a prospective
cohort of children (8–10 years at recruitment) from
Québec, Canada (n=557). Height and weight were
measured by trained nurses at baseline (2008) and
follow-up (2010). Metrics of BMI change were raw
(ΔBMIkg/m2), adjusted for median BMI (ΔBMIpercentage)
and age-sex-adjusted with the Centers for Disease
Control and Prevention growth curves expressed as
centiles (ΔBMIcentile) or z-scores (ΔBMIz-score). Metrics of
DEXA change were raw (total fat mass; ΔFMkg), per cent
(ΔFMpercentage), height-adjusted (fat mass index; ΔFMI)
and age-sex-adjusted z-scores (ΔFMz-score). Spearman’s
rank correlations were derived.
Results Correlations ranged from modest (0.60) to strong
(0.86). ΔFMkg correlated most highly with ΔBMIkg/m2
(r = 0.86), ΔFMI with ΔBMIkg/m2 and ΔBMIpercentage
(r = 0.83–0.84), ΔFMz-score with ΔBMIz-score (r = 0.78), and
ΔFMpercentage with ΔBMIpercentage (r = 0.68). Correlations
with ΔBMIcentile were consistently among the lowest.
Conclusions In 8–10-year-old children, absolute or per
cent change in BMI is a good proxy for change in fat mass
or FMI, and BMI z-score change is a good proxy for FM
z-score change. However change in BMI centile and
change in per cent fat mass perform less well and are not
recommended.
การแปล กรุณารอสักครู่..
Objective Although dual-energy X-ray absorptiometry
(DEXA) is the preferred method to estimate adiposity,
body mass index (BMI) is often used as a proxy.
However, the ability of BMI to measure adiposity change
among youth is poorly evidenced. This study explored
which metrics of BMI change have the highest
correlations with different metrics of DEXA change.
Methods Data were from the Quebec Adipose and
Lifestyle Investigation in Youth cohort, a prospective
cohort of children (8–10 years at recruitment) from
Québec, Canada (n=557). Height and weight were
measured by trained nurses at baseline (2008) and
follow-up (2010). Metrics of BMI change were raw
(ΔBMIkg/m2), adjusted for median BMI (ΔBMIpercentage)
and age-sex-adjusted with the Centers for Disease
Control and Prevention growth curves expressed as
centiles (ΔBMIcentile) or z-scores (ΔBMIz-score). Metrics of
DEXA change were raw (total fat mass; ΔFMkg), per cent
(ΔFMpercentage), height-adjusted (fat mass index; ΔFMI)
and age-sex-adjusted z-scores (ΔFMz-score). Spearman’s
rank correlations were derived.
Results Correlations ranged from modest (0.60) to strong
(0.86). ΔFMkg correlated most highly with ΔBMIkg/m2
(r = 0.86), ΔFMI with ΔBMIkg/m2 and ΔBMIpercentage
(r = 0.83–0.84), ΔFMz-score with ΔBMIz-score (r = 0.78), and
ΔFMpercentage with ΔBMIpercentage (r = 0.68). Correlations
with ΔBMIcentile were consistently among the lowest.
Conclusions In 8–10-year-old children, absolute or per
cent change in BMI is a good proxy for change in fat mass
or FMI, and BMI z-score change is a good proxy for FM
z-score change. However change in BMI centile and
change in per cent fat mass perform less well and are not
recommended.
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