Age-Period-Cohort Analysis of Obesity and Overweight in Iranian Children and Adolescents

Background Recent studies suggest that Systemic lupus erythematosus (SLE) mortality rates in Spain are decreasing. However, SLE mortality in Spain has been poorly studied. The purpose of study is to assess the temporal trends of mortality rates in the Spanish population with SLE from 1980 to 2018. Methods Death records and mid-year population data were collected from the National Statistics Institute. Age-standardized mortality rates were calculated for overall population and for each sex and age group. Significant changes in mortality trends were identified by Joinpoint regressions. Also, an Age-period-cohort (APC) and Potential Years of Life Lost (PYLL) analysis was carried out to know the burden of SLE disease. Results The overall SLE mortality rates in Spain has experimented an increased through the last 39 years. Mortality rates from the period 1980–1984 was 0.83 per 1.000.000 inhabitants, reaching the value to 1.77 cases per 1.000.000 from the period 2014–2018. A decreasing trend has been observed since 1999. Conclusions SLE mortality rate has increased in Spain between 1980 and 1999, with a sustained decrease up to our days.

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“…Cohort effect reflects variability in trends in subjects who born at the same year and because of that undergo comparable life experiences. 10,11…”

Section: Introductionmentioning

confidence: 99%

Trends in mortality from lupus in Spain from 1980 to 2018

Hernández‐Rodríguez

Durán‐Romero

Jiménez

et al. 2020

Lupus

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“…Alternatively, differences between longitudinal and cross-sectional effects of age may be due to the biasing effects of selective dropouts (21). In our study, as mentioned previously, there was no selection bias in dropouts (30); therefore, cohort or period effects are probable and for a more accurate assessment, an Age-Period-Cohort (APC) study is recommended (26).…”

Section: Discussionmentioning

confidence: 56%

“…To distinguish the longitudinal effect from the cross-sectional effect of age, longitudinal studies in which individuals are measured repeatedly through time are required. A limited number of studies separated longitudinal and cross-sectional effects of age (19,20,22,26,27).…”

Section: Introductionmentioning

confidence: 99%

Assessing longitudinal and cross-sectional effects of age on adult obesity in an Iranian population: results from a large population-based cohort study

Alhossaini

Kazemnejad

Zayeri

et al. 2020

Preprint

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BackgroundObesity is a significant risk factor for noncommunicable diseases, and it is related to many adverse health consequences. The risk of obesity commonly changes with age, which is called a longitudinal (aging) effect. Also, individuals enter the study of the same age have similar living conditions that may influence their obesity risk in a particular way; this is a cross-sectional effect.ObjectiveTo assess the cross-sectional and longitudinal effects of age, using a Marginal Logistic Regression (MLR) model.MethodsIn the current study, we used the information of individuals who had participated in the Isfahan Cohort Study (ICS). Participants were a large group of Iranian adults over 35 years of age in 2001, who lived in the central region of Iran. They were followed up for 12 years. Repeated measurements of obesity were obtained in 2001, 2007, and 2013. The Marginal Logistic Regression model including the effects of the age at baseline and its difference with current age, is used.ResultsFrom 2001 to 2013, the percentage of obesity in men and women has raised from 13% to 18% and from 31% to 44%, respectively. Both cross-sectional and longitudinal effects of age were significantly associated with the odds ratio of obesity. There was a rise in the probability of obesity for individuals with baseline age 35 to 60 and a decline for the older ones. Furthermore, the odds of obesity had about 2% increase (on average) by each year of aging, regardless of the baseline age.ConclusionThe high frequency of obese individuals and its fast growth has been a serious public health issue among Iranians adults aged 35-60 years, especially in women. To better understand the effect of age on obesity and identify the related factors, both cross-sectional and longitudinal effects of age should be considered.

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“…We postulated that old Korean women who survived the Korean War had experienced a delayed onset of menarche due to the stressful circumstances, despite most having sufficient body weight to initiate the menstrual cycle [61]. In contrast, in the younger generations, social pressure to maintain a low or normal body weight may have contributed to an overall lower average young adulthood BMI, compared to older women [62,63]. Individual socioeconomic factors may also confound the association between the timing of menarche.…”

Section: Plos Onementioning

confidence: 99%

Causal relationship between the timing of menarche and young adult body mass index with consideration to a trend of consistently decreasing age at menarche

et al. 2021

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Younger age at menarche (AAM) is associated with higher body mass index (BMI) for young women. Considering that continuous trends in decreasing AAM and increasing BMI are found in many countries, we attempted to assess whether the observed negative association between AAM and young adult BMI is causal. We included 4,093 women from the Korean Genome and Epidemiology Study (KoGES) and Healthy twin Study (HTS) with relevant epidemiologic data and genome-wide marker information. To mitigate the remarkable differences in AAM across generations, we converted the AAM to a generation-standardized AAM (gsAAM). To test causality, we applied the Mendelian randomization (MR) approach, using a genetic risk score (GRS) based on 14 AAM-associated single nucleotide polymorphisms (SNPs). We constructed MR models adjusting for education level and validated the results using the inverse-variance weighted (IVW), weighted median (WM), MR-pleiotropy residual sum and outliers test (MR-PRESSO), and MR-Egger regression methods. We found a null association using observed AAM and BMI level (conventional regression; -0.05 [95% CIs -0.10–0.00] per 1-year higher AAM). This null association was replicated when gsAAM was applied instead of AAM. Using the two-stage least squares (2SLS) approach employing a univariate GRS, the association was also negated for both AAM and gsAAM, regardless of model specifications. All the MR diagnostics suggested statistically insignificant associations, but weakly negative trends, without evidence of confounding from pleiotropy. We did not observe a causal association between AAM and young adult BMI whether we considered the birth cohort effect or not. Our study alone does not exclude the possibility of existing a weak negative association, considering the modest power of our study design.

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Age-Period-Cohort Analysis of Obesity and Overweight in Iranian Children and Adolescents

Cited by 9 publications

References 24 publications

Trends in mortality from lupus in Spain from 1980 to 2018

Trends in mortality from lupus in Spain from 1980 to 2018

Assessing longitudinal and cross-sectional effects of age on adult obesity in an Iranian population: results from a large population-based cohort study

Causal relationship between the timing of menarche and young adult body mass index with consideration to a trend of consistently decreasing age at menarche

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