Change in BMI Distribution over a 24‐Year Period and Associated Socioeconomic Gradients: A Quantile Regression Analysis

Gebremariam, Mekdes Kebede; Arah, Onyebuchi A.; Lien, Nanna; Næss, Øyvind; Ariansen, Inger; Kjøllesdal, Marte Karoline Råberg

doi:10.1002/oby.22133

Cited by 8 publications

(4 citation statements)

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“…at the lower-or upper-tails) [10]. Quantile regression facilitates assessment across continuous distributions; evidence suggests larger inequalities at the upper-tail of the body mass index (BMI) distribution [11,12]. Secondly, MVPA distributions are not typically normally distributed but are characterised by excess zeros (persons not doing any) and positive skewness (high MVPA for a small number of highly active adults) [13], with each aspect potentially having different determinants [14].…”

Section: (Continued From Previous Page)mentioning

confidence: 99%

Inequalities in participation and time spent in moderate-to-vigorous physical activity: a pooled analysis of the cross-sectional health surveys for England 2008, 2012, and 2016

Scholes

Mindell

2020

BMC Public Health

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Background Evidence is unclear on whether inequalities in average levels of moderate-to-vigorous physical activity (MVPA) reflect differences in participation, differences in the amount of time spent active, or both. Using self-reported data from 24,882 adults (Health Survey for England 2008, 2012, 2016), we examined gender-specific inequalities in these separate aspects for total and domain-specific MVPA. Methods Hurdle models accommodate continuous data with excess zeros and positive skewness. Such models were used to assess differences between income groups in three aspects: (1) the probability of doing any MVPA, (2) the average hours/week spent in MVPA, and (3) the average hours/week spent in MVPA conditional on participation (MVPA-active). Inequalities were summarised on the absolute scale using average marginal effects (AMEs) after confounder adjustment. Results Inequalities were robust to adjustment in each aspect for total MVPA and for sports/exercise. Differences between adults in high-income versus low-income households in sports/exercise MVPA were 2.2 h/week among men (95% confidence interval (CI): 1.6, 2.8) and 1.7 h/week among women (95% CI: 1.3, 2.1); differences in sports/exercise MVPA-active were 1.3 h/week (95% CI: 0.4, 2.1) and 1.0 h/week (95% CI: 0.5, 1.6) for men and women, respectively. Heterogeneity in associations was evident for the other domains. For example, adults in high-income versus low-income households were more likely to do any walking (men: 13.0% (95% CI: 10.3, 15.8%); women: 10.2% (95% CI: 7.6, 12.8%)). Among all adults (including those who did no walking), the average hours/week spent walking showed no difference by income. Among those who did any walking, adults in high-income versus low-income households walked on average 1 h/week less (men: − 0.9 h/week (95% CI: − 1.7, − 0.2); women: − 1.0 h/week (95% CI: − 1.7, − 0.2)). Conclusions Participation and the amount of time that adults spend in MVPA typically favours those in high-income households. Monitoring inequalities in MVPA requires assessing different aspects of the distribution within each domain. Reducing inequalities in sports/exercise requires policy actions and interventions to move adults in low-income households from inactivity to activity, and to enable those already active to do more. Measures to promote walking should focus efforts on reducing the sizeable income gap in the propensity to do any walking.

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Section: (Continued From Previous Page)mentioning

confidence: 99%

Inequalities in participation and time spent in moderate-to-vigorous physical activity: a pooled analysis of the cross-sectional health surveys for England 2008, 2012, and 2016

Scholes

Mindell

2020

BMC Public Health

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“…Similar findings have been observed in other studies in the UK, Spain, Norway and the USA (among men). 12–15 Across the literature, there appears to be evidence for a phenomenon that does not seem to have been explicitly noted nor explained—in the minority of cases where the outcome distribution is explicitly investigated, associations between a myriad of risk factors and BMI are progressively larger at the upper ends of the BMI distribution. This includes genetic factors, 16 , 17 behavioural factors (physical activity, sedentary behaviour and diet 18 , 19 ), and family factors (maternal BMI or exercise).…”

Section: Introductionmentioning

confidence: 99%

Determinants of the population health distribution: an illustration examining body mass index

Bann

Fitzsimons

Johnson

2020

International Journal of Epidemiology

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Most epidemiological studies examine how risk factors relate to average difference in outcomes (linear regression) or odds of a binary outcome (logistic regression); they do not explicitly examine whether risk factors are associated differentially across the distribution of the health outcome investigated. This paper documents a phenomenon found repeatedly in the minority of epidemiological studies which do this (via quantile regression): associations between a range of established risk factors and body mass index (BMI) are progressively stronger in the upper ends of the BMI distribution. In this paper, we document this finding and provide illustrative evidence of it in the 1958 British birth cohort study. Associations of low childhood socio-economic position, high maternal weight, low childhood general cognition and adult physical inactivity with higher BMI are larger at the upper end of the BMI distribution, on both absolute and relative scales. For example, effect estimates for socio-economic position and childhood cognition were around three times larger at the 90th compared with 10th quantile, while effect estimates for physical inactivity were increasingly larger from the 50th to 90th quantiles, yet null at lower quantiles. We provide potential explanations for these findings and discuss implications. Risk factors may have larger causal effects among those in worse health, and these effects may not be discovered when health is only examined in average terms. In such scenarios, population-based approaches to intervention may have larger benefits than anticipated when assuming equivalent benefit across the population. Further research is needed to understand why effect estimates differ across the BMI outcome distribution and to investigate whether differential effects exist for other physical and mental health outcomes.

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“…Pero mientras la tendencia del sobrepeso se ha desacelerado de 2.5 a 2.4% por década, la tendencia de obesidad se ha acelerado de 3.3 a 5.4% por década. Esto significa que el número de niños obesos aumentó relativamente más que el de niños con sobrepeso, afectando los centilos más altos de la distribución del IMC (Gebremariam et al, 2018;Popkin y Slining, 2013).…”

Section: Discussionunclassified

Aceleración y estabilización: disparidad en la tendencia de obesidad en escolares de la provincia de La Pampa (Argentina) entre 1990 y 2016

2020

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A pesar de los esfuerzos de diversos organismos para reducir la obesidad, sólo algunos países desarrollados muestran una desaceleración o estabilización de su prevalencia. Este trabajo presenta las tendencias en el índice de masa corporal (IMC) y las prevalencias de sobrepeso (SP) y obesidad (OB) ocurridas en escolares entre 1990 y 2016, y su distribución socioeconómica. Se compararon tres encuestas transversales realizadas en 1990, 2005/07 y 2015/16 en escolares primarios de Santa Rosa (La Pampa, Argentina). Para estandarizar los valores de IMC y definir las categorías SP y OB se empleó la referencia International Obesity Task Force (IOTF). El tipo de escuela se empleó como medida de nivel socioeconómico (NSE). Para analizar la asociación entre las variables dependientes con año de encuesta, sexo y NSE se aplicaron modelos de regresión lineal (IMC) y logística (SP, OB). El cambio temporal en las prevalencias de SP y OB se evaluó mediante Chi- cuadrado de tendencia entre proporciones. IMC, SP y OB incrementaron significativamente en el periodo 1990-2016, resultando en un tercio de la población con exceso de peso. Entre 2005/07 y 2015/16 sólo hubo incrementos significativos en niños que asistían a escuelas públicas. Las tendencias fueron similares en varones y niñas. Se concluye que el estatus de peso en esta población escolar muestra un patrón de aumento no lineal pero continuo en los últimos 25 años, con una estabilización en los sectores de mayor NSE durante la última década.

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Change in BMI Distribution over a 24‐Year Period and Associated Socioeconomic Gradients: A Quantile Regression Analysis

Cited by 8 publications

References 36 publications

Inequalities in participation and time spent in moderate-to-vigorous physical activity: a pooled analysis of the cross-sectional health surveys for England 2008, 2012, and 2016

Inequalities in participation and time spent in moderate-to-vigorous physical activity: a pooled analysis of the cross-sectional health surveys for England 2008, 2012, and 2016

Determinants of the population health distribution: an illustration examining body mass index

Aceleración y estabilización: disparidad en la tendencia de obesidad en escolares de la provincia de La Pampa (Argentina) entre 1990 y 2016

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