Dataset Information

An age-period-cohort approach to studying long-term trends in obesity and overweight in England (1992-2019).

ABSTRACT:

Objective

This study aims to understand long-term trends in obesity and overweight in England by estimating life-course transitions as well as historical and birth cohort trends for both children and adults.

Methods

Data on individuals aged 5 to 85 years old from the Health Survey for England were used, covering the period 1992 to 2019 and birth cohorts born between 1909 and 2013. Individual BMI values were classified as healthy weight, overweight, or obesity. Trends were compared, and an age-period-cohort model was estimated using logistic regression and categorical age, period, and cohort groups.

Results

There was significant variation in age trajectories by birth cohorts for healthy weight and obesity prevalence. The odds of having obesity compared with a healthy weight increased consistently with age, increased throughout the study period (but faster between 1992 and 2001), and were higher for birth cohorts born between 1989 and 2008. The odds of having overweight showed an inverted U-shape among children, increased through adulthood, have been stable since 2012, and were considerably higher for the youngest birth cohort (2009-2013).

Conclusions

Younger generations with higher overweight prevalence coupled with increasing obesity prevalence with age suggest that obesity should remain a high priority for public health policy makers in England.

SUBMITTER: Opazo Breton M

PROVIDER: S-EPMC10947422 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

An age-period-cohort approach to studying long-term trends in obesity and overweight in England (1992-2019).

Opazo Breton Magdalena M Gray Laura A LA

Obesity (Silver Spring, Md.) 20230206 3

<h4>Objective</h4>This study aims to understand long-term trends in obesity and overweight in England by estimating life-course transitions as well as historical and birth cohort trends for both children and adults.<h4>Methods</h4>Data on individuals aged 5 to 85 years old from the Health Survey for England were used, covering the period 1992 to 2019 and birth cohorts born between 1909 and 2013. Individual BMI values were classified as healthy weight, overweight, or obesity. Trends were compared ...[more]

PMID: 36746761

Similar Datasets

Project description:BackgroundThis study explored the epidemiological trends in pelvic fracture (PF) in China from 1992 to 2021, analyze their relationships with age-period-cohort (APC) factors, and predict the trends of PF from 2022 to 2046.MethodsIncidence and years lived with disabilities (YLDs) of PF among sexes in China from 1992 to 2021 were obtained through the 2021 Global Burden of Disease (GBD) database. Trends in the incidence and YLDs were described, and a joinpoint regression model was used. The APC model was used to explore the effects of age, period, and cohort on the incidence and YLDs. Nordpred forecasted the incidence and YLDs in China from 2022 to 2046.ResultsIn 2021, there were an estimated 0.63 million incidence cases and 0.33 million of YLDs, respectively. The number and age-standardized rate (ASR) of incidence and YLDs were both gradually increased. The average annual percent change (AAPC) in incidence and YLDs for men were 0.26% and -0.17%, respectively. For women, the AAPC values for incidence and YLDs were -0.03% and -0.57% (p < 0. 001), respectively. The relative risk (RR) of PF increases with age, with the lowest risk in those aged 10-14 years for incidence and aged 1-4 for YLDs and the highest risk in those aged >95 years for incidence and aged 90-94 years for YLDs. The period effect showed a totally increase in the risk across the general, male, and female populations. Cohort effects indicated a totally significant decline for both incidence and YLDs. The predicted incidence and YLDs of PF in China from 2022 to 2046 showed an initial rise, followed by a decline, with 2029 and 2034 being the turning point for incidence and YLDs, respectively.ConclusionThe characteristics of pelvic fracture incidence and YLDs in China are complex. Thus, primary prevention measures must be strengthened. Raising awareness about osteoporosis prevention, enhancing public health education, and promoting good dietary and hygiene habits are appropriate preventive measures for PF in China.

Project description:BackgroundCystic echinococcosis (CE) is widespread globally but imposes a particularly heavy burden in Central Asia. Despite control measures, disease management remains suboptimal in this region. This study analyzed trends in CE incidence, mortality, and disability-adjusted life years (DALYs) from 1992 to 2021 in Central Asia; compared them with global data; and explored variations by gender, age group, and country to identify critical factors in disease control.MethodsUsing data from the Global Burden of Disease Study 2021 (GBD 2021), we analyzed long-term trends in the incidence, mortality, and DALY rates of CE in Central Asia. The joinpoint regression model was employed to calculate the annual percentage change (APC) and average APC (AAPC) to identify shifts in disease trends. Additionally, an age-period-cohort model was used to assess the impact of various age groups, periods, and birth cohorts on the disease burden.ResultsThe number of CE cases increased by 52.13% in Central Asia, while deaths decreased by 57.35%; DALYs decreased only slightly by 10.75%. From 1992 to 2021, CE incidence showed an increasing trend until 2010, then rapidly declined until 2015, and then gradually increased thereafter. The highest incidence rates were among middle-aged and older adult populations. Although mortality and DALY rates decreased across all age groups, the decline was less than the global trend. Gender analysis showed that the incidence rate was significantly higher in males than in females.ConclusionAlthough there have been improvements in the CE disease burden in some Central Asian countries, the overall burden remains significant. This study highlights the importance of considering gender, age, and country-specific disease burdens when formulating public health policies. Future research should continue to monitor these trends and explore targeted prevention strategies within diverse socioeconomic contexts, such as integrating regional socioeconomic factors and public health resources.

Project description:BackgroundIn England, 41% of children aged 10-11 years live with overweight or obesity. Identifying children at risk of developing overweight or obesity may help target early prevention interventions. We aimed to develop and externally validate prediction models of childhood overweight and obesity at age 10-11 years using routinely collected weight and height measurements at age 4-5 years and maternal and early-life health data.MethodsWe used an anonymised linked cohort of maternal pregnancy and birth health records in Hampshire, UK between 2003 and 2008 and child health records. Childhood body mass index (BMI), adjusted for age and sex, at 10-11 years was used to define the outcome of overweight and obesity (BMI ≥ 91st centile) in the models. Logistic regression models and multivariable fractional polynomials were used to select model predictors and to identify transformations of continuous predictors that best predict the outcome. Models were externally validated using data from the Born in Bradford birth cohort. Model performance was assessed using discrimination and calibration.ResultsChildhood BMI was available for 6566 children at 4-5 (14.6% overweight) and 10-11 years (26.1% overweight) with 10.8% overweight at both timepoints. The area under the curve (AUC) was 0.82 at development and 0.83 on external validation for the model only incorporating two predictors: BMI at 4-5 years and child sex. AUC increased to 0.84 on development and 0.85 on external validation on additionally incorporating maternal predictors in early pregnancy (BMI, smoking, age, educational attainment, ethnicity, parity, employment status). Models were well calibrated.ConclusionsThis prediction modelling can be applied at 4-5 years to identify the risk for childhood overweight at 10-11 years, with slightly improved prediction with the inclusion of maternal data. These prediction models demonstrate that routinely collected data can be used to target early preventive interventions to reduce the prevalence of childhood obesity.

Dataset Information

An age-period-cohort approach to studying long-term trends in obesity and overweight in England (1992-2019).

Objective

Methods

Results

Conclusions

Publications

An age-period-cohort approach to studying long-term trends in obesity and overweight in England (1992-2019).

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets