Secular Trends in Height, Body Mass, and BMI among Girls in the Eastern Poland Region (1986-2021): Public Health Perspectives.

To examine the orientation, magnitude, and pace of secular trends in body height, weight, and body mass index (BMI) among Chinese urban students aged 7-18 years from 2000 to 2019. Data were extracted from Chinese urban students aged 7-18 years from the Chinese National Surveillance on Students' Constitution and Health in 2000, 2005, 2010, 2014, and 2019. The height, weight, and BMI of 548 419, 548 408, and 548 365 urban students aged 7-18 years, respectively, were tested. The mean differences across survey years were tested by one-way analysis of variance (ANOVA). The pace of secular trends is expressed as the change every 5 years between every two adjacent survey years. Height increments between 1.9 and 6.2 cm, weight increments between 2.7 and 8.6 kg, and BMI increments between 0.9 and 1.9 kg/m2 were observed in boys. For girls, height increments between 1.5 and 4.9 cm, weight increments between 2.2 and 6.0 kg, and BMI increments between 0.7 and 1.7 kg/m2 were observed. The pace of secular trends in height decreased in the last 5 years, and the secular trends in weight and BMI have accelerated in the last 9 years compared with the previous 10 years. Although the secular trend in height among Chinese urban students has slowed, it has not yet reached its genetic potential and continues to increase. The rapid increase in weight and BMI was a cause for concern. Our findings provide a basis for the future formulation of public health interventions in China.

What is already known about this subject Factors associated with children's body mass index (BMI) include parents' BMIs, birth weight, maternal smoking, sleep duration and television watching. Few studies have attempted to quantify either changes in the association between risk factors and BMI or the contribution of changes in the risk factors to increases in BMI over a generation. What this study adds The magnitude of the association between most risk factors and children's BMIs has not changed over a 29-year period. Increases in the population level of mothers' body mass index (BMI) explains ~20% of the increase in children's BMI whereas the smaller increase in fathers' BMI contributes only 6%. Maternal smoking, despite the decrease in prevalence, contributes ~17%. Using two cohorts born 29 years apart in Dunedin, New Zealand we aim to examine changes in risk factors and their associations with body mass index (BMI) at ages 3 and 7 years, and estimate their contribution to the secular changes in BMI at age 7 years. Birth weight and anthropometric measures at ages 3, 5 and 7 years were obtained for 974 participants in the Dunedin Multidisciplinary Health and Development Study (DMHDS), born in 1972-1973, and 241 in the Family Lifestyle, Activity, Movement and Eating Study (FLAME), born in 2001-2002. Information about maternal age, education and smoking in pregnancy, as well as breastfeeding, children's television time and time in bed, was obtained by questionnaire. The increase in BMI over the 29-year period was 0.84 (95% CI 0.61, 1.06) kg m(-2) at age 7. A 1-unit difference in the mother's BMI was associated with a 0.06 (0.03, 0.08) kg m(-2) difference in offspring in both studies; the 3.4 (2.8, 4.0) kg m(-2) increase in the mothers' BMIs accounts for a change of 0.19 kg m(-2) in the children's BMI. The much smaller generational increase in fathers' BMI (0.7 kg m(-2) ) correspondingly had a more limited effect on change in child BMI over time (0.06 kg m(-2) ). Although smoking in pregnancy decreased by 15% (8, 21) its association with BMI increased from 0.20 (-0.01, 0.42) in the DMHDS cohort to 1.24 (0.76, 1.71) kg m(-2) in the FLAME cohort, contributing 0.18 kg m(-2) to the increase in children's BMI. Societal factors such as higher maternal BMI and smoking in pregnancy contribute most to the secular increase in BMI, with changes in behavioural factors, including sleep and television viewing, having little effect in this setting.

To compare obese with normal and overweight type 2 diabetic patients regarding body mass index (BMI) and cardiovascular risk factors, and to analyse changes in weight versus risk factors. A cross-sectional study of 44 042 type 2 patients, and a 6-year prospective study of 4468 type 2 patients. Obese patients (BMI > or = 30 kg m(-2)), 37% of all patients, had high frequencies of hypertension (88%), hyperlipidaemia (81%) and microalbuminuria (29%). Only 11% had blood pressure <130/80 mmHg. Their ratio of triglycerides to HDL cholesterol was considerably elevated, whilst the mean total and LDL cholesterol were similar as in normal weight subjects. Obese patients had elevated odds ratios for hypertension, hyperlipidaemia and microalbuminuria: 2.1, 1.8 and 1.4 in the cross-sectional study, similarly confirmed in the prospective 6-year study. BMI was an independent predictor of these risk factors (P < 0.001), although only slightly associated with HbA1c and not with total or LDL cholesterol. A change in BMI during the prospective study was related to a change in HbA1c in patients treated with diet and oral hypoglycaemic agents (OHAs) but not with insulin. In all patients, an increase in BMI was related to the development of hypertension, and a change in BMI to change in blood pressure, also mostly confirmed when treated with diet, OHAs or insulin. The high frequencies of risk factors in obese type 2 patients implies an increased risk of cardiovascular disease and the need for therapeutic measures. The paradox that hypoglycaemic treatment accompanied by weight gain may increase cardiovascular risk factors seems to be verified here concerning hypertension but not concerning microalbuminuria.

Background/Objectives: Secular trends in children’s physical development are important indicators of population health, nutritional status, and socioeconomic conditions. This study aimed to assess long-term changes in the height, weight, Body Mass Index (BMI), and nutritional status of boys from Eastern Poland between 1986 and 2021. Methods: Anthropometric data were collected from 13,172 boys aged 8, 13, and 17 years at five time points (1986, 1996, 2006, 2016, and 2021). Standardized measurement protocols were used throughout the study. The BMI was calculated and categorized using international cut-off points for age and gender. Secular changes in the height, weight, and Body Mass Index (BMI) were analyzed using an analysis of variance (ANOVA) with post hoc tests, and differences in dietary categories were assessed using chi-square tests (p ≤ 0.05). Results: The height, weight, and BMI increased significantly across all ages. The largest height gain was seen in 13-year-olds, while the greatest BMI increase occurred between 2016 and 2021. The overweight and obesity prevalence rose sharply by an average of 21.70% across age groups, with the normal BMI prevalence decreasing by 18.41%. The underweight prevalence declined, especially among adolescents; however, this likely reflects a general upward shift in the BMI rather than a true nutritional improvement. Conclusions: Strong secular trends are evident, influenced by global and local socioeconomic factors, including Poland’s EU accession and the COVID-19 pandemic. While an increased height suggests better living standards, the rising overweight and obesity rates indicate emerging health risks. Due to the lack of direct lifestyle and socioeconomic data, further research incorporating these factors and the pubertal BMI variability is needed to clarify underlying causes. Targeted regional strategies promoting healthy diets, physical activity, and lifestyles are urgently required.

To assess the prevalence of obesity and changes in body mass index (BMI) distribution between 1989 and 1999 in 5-y-old children, and to study the influence of parental socioeconomic status on these parameters. Two cohorts of children in the final year of nursery school (in the city of Lille, France) were enrolled in 1989 (705 children: mean age=5.6+/-0.4 y) and 1999 (1258 children: mean age=5.6+/-0.5 y). Weight and height were measured, and data about parental occupation were collected during a school medical examination. International Obesity Task Force cutoff points were used to define overweight and obesity. Parental occupation was classified into four categories. The prevalence of obesity increased from 1.8 to 4.9%, and the prevalence of overweight rose from 9.6 to 16.9%. Mean-difference plots allowed qualitative comparisons of the BMI distribution between the surveys: for children from the highest social classes, there was no change in BMI; for children from intermediate classes, there was a up-shift only in the upper part of the distribution with the heaviest children becoming heavier still; finally, for children from the lowest class, there was an increase in BMI across the entire population. This study of the changes in BMI distribution gives greater insight into the 'obesity epidemic'. Our results show the influence of an interaction between genetic and environmental factors. The increase in BMI in the upper part of the distribution suggests that this is a population with a high degree of susceptibility, whereas the increase in BMI across the whole population in the lowest social class suggests a strong influence of the environment on this group and thus the necessity of appropriate, preventive measures.

Inter-individual inequality in BMI: An analysis of Indonesian Family Life Surveys (1993–2007)

This study assessed the change in body mass index (BMI) distribution among 18- or 19-year-olds over 24 years. It also investigated parallel changes in the distribution of birth weight and in the association between birth weight and later risk of overweight and/or obesity. Parental educational variations in the trends and associations were explored. The study used data on 606,832 male military conscripts enlisted between 1985 and 2008. Quantile regression was used to assess the temporal change in BMI and birth weight distribution. The association between birth weight and overweight and/or obesity at age 18 or 19 years was quantified by using logistic regression. Increases in BMI over time were found namely in the 90th, 95th, 97th, and 99th percentiles. Socioeconomic differences in this increase were documented in the 75th to 97th percentiles. The distribution of birth weight and the association between birth weight and the risk of overweight and/or obesity at age 18 or 19 years remained stable over time. The difference in the increase in BMI between low and high percentiles indicates the limited role of mean BMI in reflecting population changes. The results suggest a need to focus on those with low socioeconomic position in the upper ends of the BMI distribution to combat increasing disparities in obesity-related outcomes.

AimsThere is limited information on changes in body mass index (BMI) due to the COVID-19 pandemic among persons of migrant origin. The aim of the present study was to examine factors associated with changes in BMI among the general- and migrant-origin populations in Finland.MethodsLongitudinal data to explore individual-level changes in self-reported BMI among migrant-origin persons (N = 3313) were obtained from the FinMonik Survey conducted in 2018 and the MigCOVID Survey conducted 2020–2021. Data for the general population reference group were obtained from the FinHealth 2017 Study conducted 2017–2018 and its follow-up conducted in 2020 (N = 2982). Logistic regression was applied to examine whether age, sex, education, economic activity, length of residence in Finland, language skills, smoking, alcohol usage, sleep, physical activity, snacking, and fruit and vegetable consumption were associated with an increase or decrease in BMI. A change in BMI was defined as a 5% or greater increase or decrease.ResultsTwenty-seven per cent of the migrant-origin population experienced an increase in BMI, while 14% had a decrease in BMI. These results corresponded to figures observed among the general population in Finland (27% and 14%). Persons of migrant origin who were other than students or employed faced greater odds of an increase in BMI of at least 5% (OR = 1.71). In the general population, an increase in BMI of at least 5% had greater odds of occurring among women (OR = 1.61), those who were other than students or employed (OR = 1.68), those who increased their alcohol intake (OR = 1.64), those who increased their snacking (OR = 1.40) and decreased their fruit and vegetable intake (OR = 1.85).ConclusionsMost examined factors applied differently to general- and migrant-origin populations and by migrant-origin group. These differences must be considered when planning future public health promotion efforts, particularly those during crisis situations.

We wanted to evaluate the predictive value of percentage change in antenatal maternal body mass index (BMI) as it relates to macrosomia, as well as to compare change in pregnancy BMI with existing weight gain guidelines. We analyzed data from 6 months of consecutive deliveries, focusing on first visit (first trimester) BMI, last visit (37 weeks or later) BMI, and fetal birth weight. Using regression and chi(2) analyses, we evaluated the relationship between change in BMI and macrosomia. Of the 238 consecutive deliveries, we were able to analyze data from 186, of which 15.6% (n = 29) of the infants were macrosomic. Among macrosomic infants, 86.2% (25/29) of their mothers had a 25% or greater increase in BMI compared with 6.6% (10/157) of mothers of normal-weight infants (P <.001), for a relative risk 13.5% (95% confidence interval [CI], 7.3%-25.1%). Percentage change in BMI of 25% or greater had a sensitivity of 86.2% (95% CI, 68.3%-96.1%), a specificity of 93.6% (95% CI, 88.6%-96.9%), a positive predictive value of 71.4% (95% CI, 53.7%-85.4%), and a negative predictive value 97.4% (95% CI, 93.4%-99.3%) for macrosomia. Logistic regression adjusted for maternal age, race, parity, and gravidity showed that those women whose BMI increased 25% or greater were more than 200 times more likely (odds ratio [OR] = 219.3; 95% CI, 38.8-1,238.6; P <.001) to give birth to a macrosomic infant. Further adjusting for initial BMI strengthened the association (OR=1,062.4; 95% CI, 83.2-13,572.2; P < 001). Regardless of weight gain, when compared with Institute of Medicine weight gain recommendations, change in BMI or 25% or greater was associated with macrosomia (P <.001). Independent of initial pregnancy BMI or absolute weight gain, an increase in maternal BMI of 25% or greater during pregnancy is highly predictive of macrosomia.

BackgroundTraditional linear regression analyses have detected increasing trends in the incidence of overweight/obesity among both genders in China. However, these previous regression analyses were limited in their ability to capture cross-distribution variations among effects. The objective of our study was to analyze the change in the body mass index (BMI) distribution of adults and investigated the relationships between the key covariates and the BMI distribution.MethodsWe used longitudinal data from the China Health and Nutrition Surveys (CHNS) in 1991, 1993, 1997, 2000, 2004, 2006, 2009, and 2011, with at least two waves of data collection. In total, 17,819 participants aged 18–60 years (N = 8587 men and 9232 women) were included in the final analysis with 48,900 observations. The lambda-mu-sigma (LMS) method was used to describe changes in the BMI distribution. Separate sex-stratified longitudinal quantile regression (QR) analyses were used to investigate changes in the BMI distribution over time.ResultsThe main characteristics of the BMI changes in both genders were that the curves shifted to the right and the distributions became wider. All of the BMI percentile curves tended to increase from 1991 to 2011, where the levels increased more in the higher percentiles. The QR analyses showed that these patterns remain consistent after adjusting for individual and community level factors. Physical activity (PA) had a negative association with BMI for both genders in all percentiles. Income and energy intake were associated with positive changes in male BMI in the upper percentile. Sedentary time had a positive association with female BMI in the middle percentile. Compared with less educated women, women with senior school education at 75th percentile had 0.951 kg/m2 lower BMIs.ConclusionsThis longitudinal quantile regression suggests that effects of different covariates worked differently across the BMI distribution. Since social and economic characteristics in China have underlined the significant disparities in many aspects, national strategies to tackle overweight/obesity should be tailored as appropriate for various segments.

Secular trends in height and weight are interesting because in middle- and low-income countries they are a marker for changes in population health. The present study aims to evaluate the secular trend in height and weight and body mass index (BMI) of Iranian children and adolescents aged 2-18 years old between 1990-1991 and 1999 and compare the magnitude of urban-rural differences during this period for the first time in an Asian country. Data from two national health surveys in 1990-1991 and 1999, of 22,349 and 25,196 weight and height measures of Iranian children and adolescents were used to study the trend and compare its difference in urban and rural children. Logarithmic transformation of weight, height and BMI was modelled as a polynomial in age for urban and rural boys and girls in each survey separately. The trend in urban and rural growth indexes (weight, height and BMI) and also the comparisons of urban-rural differences between two national surveys were tested in logarithmic scale using a weighted form of Z statistic for comparison of two means adjusted for age groups. Urban and rural boys and girls became taller and heavier (P≤ 0.02) with no change of BMI (P > 0.05) during the period. There was not any significant difference between the magnitudes of urban-rural difference between two surveys (P≥ 0.61). Although generally positive weight and height trend was observed among urban and rural residents, the magnitude of their differences was not changed.

Research efforts have focused mainly on trends in obesity among populations, or changes in mean body mass index (BMI), without consideration of changes in BMI across the BMI spectrum. Examination of age-specific changes in BMI distribution may reveal patterns that are relevant to targeting of interventions. Using a synthetic cohort approach (which matches members of cross-sectional surveys by birth year) we estimated population representative annual BMI change across two time periods (1980 to 1989 and 1995 to 2008) by age, sex, socioeconomic position and quantiles of BMI. Our study population was a total of 27349 participants from four nationally representative Australian health surveys; Risk Factor Prevalence Study surveys (1980 and 1989), the 1995 National Nutrition Survey and the 2007/8 National Health Survey. We found greater mean BMI increases in younger people, in those already overweight and in those with lower education. For men, age-specific mean annual BMI change was very similar in the 1980s and the early 2000s (P=0.39), but there was a recent slowing down of annual BMI gain for older women in the 2000s compared with their same-age counterparts in the 1980s (P<0.05). BMI change was not uniform across the BMI distribution, with different patterns by age and sex in different periods. Young adults had much greater BMI gain at higher BMI quantiles, thus adding to the increased right skew in BMI, whereas BMI gain for older populations was more even across the BMI distribution. The synthetic cohort technique provided useful information from serial cross-sectional survey data. The quantification of annual BMI change has contributed to an understanding of the epidemiology of obesity progression and identified key target groups for policy attention-young adults, those who are already overweight and those of lower socioeconomic status.

IntroductionResearch on the shift in children's Body Mass Index (BMI) distribution is limited and conditional mean models used in the previous research have limitations in capturing cross-distribution variations in effects. The objectives are to analyze the shift in Chinese children’s BMI distribution and to test the associations between BMI distribution and other factors.MethodsWe analyzed data collected from children 7–17 years old from the China Health and Nutrition Survey (CHNS) conducted in 1997, 2000, 2004, 2006, 2009 and 2011, from 2,814 participants with 6,799 observations. Longitudinal quantile regression (QR) was used to explore the effect of several factors on BMI trends in 2015.ResultsThe BMI curves shift to the right in boys and girls, with the distributions becoming wider, indicating a higher proportion of children have become overweight. The 5th, 15th, 50th, 85th and 95th BMI percentile curves all shifted upward from 1997 to 2011, and the higher percentiles had greater increases. The prevalence of overweight and obesity increased in boys and girls between 1997–2011, from 6.5% to 15.5% in boys and from 4.6% to 10.4% in girls. Energy intake and parents’ BMI levels had a positive association with children’s BMI. Per capita income was positively associated with changes in BMI only at the upper percentiles of the BMI distributions in boys. Increased physical activity was associated with decreased BMI in girls.ConclusionsChildren in China are becoming increasingly overweight. Energy intake, parental BMI, physical activity and early menarche age in girls are associated with elevated BMI in children.

There are well-documented global increases in mean body mass index (BMI) and prevalence of overweight (BMI ≥ 25.0 kg/m(2)) and obese (BMI ≥ 30.0 kg/m(2)). Previous analyses, however, have failed to report whether this weight gain is shared equally across the population. We examined the change in BMI across all segments of the BMI distribution in a wide range of countries, and assessed whether the BMI distribution is changing between cross-sectional surveys conducted at different time points. We used nationally representative surveys of women between 1991-2008, in 37 low- and middle-income countries from the Demographic Health Surveys ([DHS] n = 732,784). There were a total of 96 country-survey cycles, and the number of survey cycles per country varied between two (21/37) and five (1/37). Using multilevel regression models, between countries and within countries over survey cycles, the change in mean BMI was used to predict the standard deviation of BMI, the prevalence of underweight, overweight, and obese. Changes in median BMI were used to predict the 5th and 95th percentile of the BMI distribution. Quantile-quantile plots were used to examine the change in the BMI distribution between surveys conducted at different times within countries. At the population level, increasing mean BMI is related to increasing standard deviation of BMI, with the BMI at the 95th percentile rising at approximately 2.5 times the rate of the 5th percentile. Similarly, there is an approximately 60% excess increase in prevalence of overweight and 40% excess in obese, relative to the decline in prevalence of underweight. Quantile-quantile plots demonstrate a consistent pattern of unequal weight gain across percentiles of the BMI distribution as mean BMI increases, with increased weight gain at high percentiles of the BMI distribution and little change at low percentiles. Major limitations of these results are that repeated population surveys cannot examine weight gain within an individual over time, most of the countries only had data from two surveys and the study sample only contains women in low- and middle-income countries, potentially limiting generalizability of findings. Mean changes in BMI, or in single parameters such as percent overweight, do not capture the divergence in the degree of weight gain occurring between BMI at low and high percentiles. Population weight gain is occurring disproportionately among groups with already high baseline BMI levels. Studies that characterize population change should examine patterns of change across the entire distribution and not just average trends or single parameters.

BackgroundSince its independence in 1945, Indonesia has undergone rapid socioeconomic development. The fastest changes occurred in Java, which is the main island where more than half of the Indonesian population lives.ObjectiveThis study aimed to analyze the secular trend in the height of adults living in Java born between 1953 and 1995 by comparing their residence (rural, small city, or large city) and considering factors that contribute to adult height.MethodsThe analysis used the following data: birth year, body height, weight, body mass index, sex, educational attainment, share of household food expenditures, and residence of 20- to 40-year-old men and women collected by the Indonesia Family Life Survey (IFLS) waves 1 to 5. Multiple linear regression was conducted to analyze several factors that influence adult height. Significance was set at p < 0.05 with a 95% confidence interval (CI).ResultsThe study included 30,656 measurements of individuals born between 1953 and 1995 (54.9% female). Positive secular trends (95% CI) were observed for men and women: 1.3 (1.1–1.4) cm and 0.9 (0.8–1.0) cm per decade, respectively. Multiple linear regression analyses showed that, in addition to the year of birth, the adult height of both males and females was independently associated with level of education and share of household food expenditure. Stratifying the data into residence in rural areas, small cities, and large cities showed that education levels influenced the adult height of men and women living in all regions, whereas the influence of birth year and share of household food expenditure differed between areas and genders.ConclusionsWe observed positive secular trends in the height of adults living in Java who were born between 1953 and 1995. The birth year, educational attainment, and share of household food expenditure significantly influenced adult height. A higher education level was consistently associated with taller adult height in both men and women living in rural areas, small cities, and large cities.