The Journal of nutrition · 2026
Persistent BMI and height deficits reflect structural and geographic inequities among adolescent girls in Nepal.
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Rai Anjana, Wraith Darren, Sendall Marguerite C, Cunningham Kenda, Adhikari Ramesh P, Saville Naomi, Nambiar Smita
Аннотация
BACKGROUND: Adolescence is a period of rapid growth; however, many adolescent girls experience suboptimal growth trajectories.
OBJECTIVES: This longitudinal study assessed changes in body mass index (BMI) and linear growth and associated factors among Nepali adolescent girls from 2017 to 2019.
METHODS: We analyzed panel data from 3 waves [2017 (n = 770), 2018 (n = 682), and 2019 (n = 618)] of never-married and nonpregnant girls aged 10 to 19 y in 2017. BMI-for-age difference (BMI-AD) and height-for-age difference (HAD), indicating deviation from World Health Organization (WHO) age- and sex-specific medians, were used to assess change over time. BMI-AD and conditional growth (calculated as residuals from regressions of 2018/2019 HAD on prior HAD and age) were used in the regression analyses to identify associated factors. Conditional growth reflects linear growth above or below what would be expected, based on prior height and age. We used descriptive statistics to assess change, and linear mixed-effects and ordinary least squares regression to identify factors associated with BMI-AD and conditional growth, respectively.
RESULTS: Findings confirmed that girls consistently had lower BMI (kg/m2) (- 1.78, -1.60, and -1.48, respectively in 2017, 2018, and 2019, respectively) and height relative to the WHO median for their age and sex (-10.3 cm, -10.2 cm, and -9.9 cm, respectively, in 2017, 2018, and 2019), with negligible improvements. Factors associated with higher BMI-AD were postmenarche status [0.98, 95% confidence interval (CI): 0.72, 1.25], higher education (0.11, 95% CI: 0.01, 0.21), and disadvantaged caste/ethnicity (0.48, 95% CI: 0.14, 0.83); in contrast, older age (-0.17, 95% CI: -0.27, -0.07), food insecurity (-0.31, 95% CI: -0.57, -0.06), and terai (-0.93, 95% CI: -1.45, -0.40) or hill (-0.57, 95% CI: -1.06, -0.08) residence were associated with lower BMI-AD. For conditional linear growth, older age (0.19 cm, 95% CI: 0.14 cm, 0.24 cm for 2018; 0.16 cm, 95% CI: 0.11 cm, 0.21 cm for 2019), and underweight (0.25 cm, 95% CI: 0.10 cm, 0.40 cm for 2018) predicted higher gains than expected given their prior height and age, whereas postmenarche status (-0.94 cm, 95% CI: -1.16 cm, -0.72 cm for 2018; -1.03 cm, 95% CI: -1.25 cm, -0.82 cm for 2019) and terai (-0.35 cm, 95% CI: -0.62 cm, -0.08 cm for 2018; -0.31 cm, 95% CI: -0.59 cm, -0.03 cm for 2019) hill (-0.25 cm, 95% CI: -0.48 cm, -0.02 cm for 2019) residence predicted lower growth than expected given their prior height and age.
CONCLUSIONS: The study highlights the need to address age-related nutrition, education, food insecurity, and geographic disparities to support healthy growth.
OBJECTIVES: This longitudinal study assessed changes in body mass index (BMI) and linear growth and associated factors among Nepali adolescent girls from 2017 to 2019.
METHODS: We analyzed panel data from 3 waves [2017 (n = 770), 2018 (n = 682), and 2019 (n = 618)] of never-married and nonpregnant girls aged 10 to 19 y in 2017. BMI-for-age difference (BMI-AD) and height-for-age difference (HAD), indicating deviation from World Health Organization (WHO) age- and sex-specific medians, were used to assess change over time. BMI-AD and conditional growth (calculated as residuals from regressions of 2018/2019 HAD on prior HAD and age) were used in the regression analyses to identify associated factors. Conditional growth reflects linear growth above or below what would be expected, based on prior height and age. We used descriptive statistics to assess change, and linear mixed-effects and ordinary least squares regression to identify factors associated with BMI-AD and conditional growth, respectively.
RESULTS: Findings confirmed that girls consistently had lower BMI (kg/m2) (- 1.78, -1.60, and -1.48, respectively in 2017, 2018, and 2019, respectively) and height relative to the WHO median for their age and sex (-10.3 cm, -10.2 cm, and -9.9 cm, respectively, in 2017, 2018, and 2019), with negligible improvements. Factors associated with higher BMI-AD were postmenarche status [0.98, 95% confidence interval (CI): 0.72, 1.25], higher education (0.11, 95% CI: 0.01, 0.21), and disadvantaged caste/ethnicity (0.48, 95% CI: 0.14, 0.83); in contrast, older age (-0.17, 95% CI: -0.27, -0.07), food insecurity (-0.31, 95% CI: -0.57, -0.06), and terai (-0.93, 95% CI: -1.45, -0.40) or hill (-0.57, 95% CI: -1.06, -0.08) residence were associated with lower BMI-AD. For conditional linear growth, older age (0.19 cm, 95% CI: 0.14 cm, 0.24 cm for 2018; 0.16 cm, 95% CI: 0.11 cm, 0.21 cm for 2019), and underweight (0.25 cm, 95% CI: 0.10 cm, 0.40 cm for 2018) predicted higher gains than expected given their prior height and age, whereas postmenarche status (-0.94 cm, 95% CI: -1.16 cm, -0.72 cm for 2018; -1.03 cm, 95% CI: -1.25 cm, -0.82 cm for 2019) and terai (-0.35 cm, 95% CI: -0.62 cm, -0.08 cm for 2018; -0.31 cm, 95% CI: -0.59 cm, -0.03 cm for 2019) hill (-0.25 cm, 95% CI: -0.48 cm, -0.02 cm for 2019) residence predicted lower growth than expected given their prior height and age.
CONCLUSIONS: The study highlights the need to address age-related nutrition, education, food insecurity, and geographic disparities to support healthy growth.