Dataset Information

Longitudinal study of variation in body mass index in middle-aged UK females.

ABSTRACT: The importance of changing patterns of obesity in society and its implications for public health are well recognized. However, the adult life course of body mass index (BMI) changes in individuals over time is largely unknown and has mostly been extrapolated from cross-sectional studies. The present study examines individual specific variation of BMI during a 15-year follow-up period in a community-based sample of UK females. We attempted to establish whether there is a common, generalized pattern which captures variation in BMI over time. The participants of this study belong to a prospective population cohort of British women studied intensively since 1989: the Chingford Study. The sample originally consisted of 1,003 women aged 45-68 years, who were assessed annually for BMI during follow-up period. Polynomial regression models were used to assess longitudinal BMI variation. We observed a great stability in individual BMI variation during the follow-up period, reflected by high correlations between the baseline BMI and follow-up BMI 10 and 15 years later (r = 0.876, N = 810, and r = 0.824, N = 638, respectively). We also found that three different major age-related patterns in BMI could be clearly identified: no change in 30.6% in 58% it increased and in 11.4% it decreased with age. Thus, our data suggest that individual age-related changes in BMI are very different. Therefore, simply combining all individuals into groups by any other criteria (age, sex, etc.) and overlooking the distinctive patterns of BMI change may lead to biased inferences in epidemiologic and etiologic research of the future.

SUBMITTER: Livshits G

PROVIDER: S-EPMC3448995 | biostudies-literature | 2012 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Longitudinal study of variation in body mass index in middle-aged UK females.

Livshits Gregory G Malkin Ida I Williams Frances M K FM Hart Deborah J DJ Hakim Alan A Spector Timothy D TD

Age (Dordrecht, Netherlands) 20110819 5

The importance of changing patterns of obesity in society and its implications for public health are well recognized. However, the adult life course of body mass index (BMI) changes in individuals over time is largely unknown and has mostly been extrapolated from cross-sectional studies. The present study examines individual specific variation of BMI during a 15-year follow-up period in a community-based sample of UK females. We attempted to establish whether there is a common, generalized patte ...[more]

PMID: 21853263

Similar Datasets

Project description:BackgroundBody mass index (BMI) based on self-reported height and weight has been criticized as being biased because of an observed tendency for overweight and obese people to overestimate height and underestimate weight, resulting in higher misclassification for these groups. We examined the validity of BMI based on self-reported values in a sample of Norwegian women aged 44-64 years.MethodsThe study sample of 1,837 participants in the Norwegian Women and Cancer study self-reported height and weight, and then, within 1 year, either self-reported anthropometric again, or were measured by medical staff. Demographic and anthropometric were compared using t-tests and chi-square tests of independence. Misclassification of BMI categories was assessed by weighted Cohen's kappa and Bland-Altman plot.ResultsOn average, the two measurements were taken 8 months apart, and self-reported weight increased by 0.6 kg (P<0.05), and BMI by 0.2 kg/m(2) (P<0.05). The distribution of BMI categories did not differ between self-reported and measured values. There was substantial agreement between self-reported values and those measured by medical staff (weighted kappa 0.73). Under-reporting resulting in misclassification of BMI category was most common among overweight women (36%), but the highest proportion of extreme under-reporting was found in obese women (18% outside the 95% limits of agreement). The cumulative distribution curves for the measured and self-reported values closely followed each other, but measurements by medical staff were shifted slightly toward higher BMI values.ConclusionWhile there was substantial agreement between self-reported and measured BMI values, there was small but statistically significant under-reporting of weight and thus self-reported BMI. The tendency to under-report was largest among overweight women, while the largest degree of under-reporting was found in the obese group. Self-reported weight and height provide a valid ranking of BMI for middle-aged Norwegian women.

Project description:ObjectiveBody mass index (BMI) and stroke risk have been linked, but these findings are still debated. This study investigated the relationship between BMI and stroke risk in a middle-aged and elderly Chinese population.MethodsThis study used four waves of CHARLS data (2011, 2013, 2015, and 2018), including 12,161 participants. The CHARLS sample was obtained by multi-stage probability sampling and all participants were assessed by one-to-one interviews using a standardized questionnaire. We used a Cox proportional-hazards regression model to examine the relationship between BMI and stroke risk. We used Cox proportional hazards regression with cubic spline functions and smooth curve fitting to identify the non-linear relationship between them. A series of sensitivity analyses were also conducted.ResultsThe multivariate Cox proportional hazards regression model identified a positive association between BMI and stroke risk (HR=1.025, 95% CI: 1.010-1.040). We also found a non-linear relationship between BMI and stroke incidence, with an inflection point at 26.63 kg/m2 for BMI. Each 1 kg/m2 increase in BMI to the left of the inflection point was related to a 4.4% increase in stroke risk (HR=1.044, 95% CI: 1.019-1.069). We stratified individuals by gender to further investigate their association and found a particular non-linear relationship and saturation effect between BMI and stroke risk in men, with the inflection point at 25.94 kg/m2. Each 1 kg/m2 increase in BMI to the left of the inflection point was related to a 7.6% increase in stroke risk (HR=1.076, 95% CI 1.034-1.119). The association was linear in women, with each 1 kg/m2 increase in BMI associated with a 2.1% increase in stroke risk (HR=1.021, 95% CI 1.002, 1.040).ConclusionIn men, there was a specific non-linear association and saturation effect of BMI with stroke (inflection point of 25.94 kg/m2), while in women, there was none. When males had a BMI below 25.94 kg/m2, the risk of stroke was significantly and positively associated with BMI. By controlling BMI below 25.94 kg/m2 in men, a further decrease in BMI may promote a significant reduction in stroke risk.

Project description:There is evidence that insufficient sleep and more stressors are individually associated with poor metabolic health outcomes. Examining sleep and stressors jointly may account for greater variability in health outcomes; however, we know little about the combined effect of both insufficient sleep and more stressors on metabolic health. This study examined whether experiencing more stressors in response to insufficient sleep ("stressor reactivity to insufficient sleep") was associated with body mass index in middle-aged workers. One-hundred and twenty-seven participants (Mage = 45.24 ± 6.22 years) reported nightly sleep characteristics and daily stressors on 8 consecutive days. We collected height and weight measurements to calculate body mass index (kg m-2 ). On average, workers reported more stressors following nights with shorter-than-usual sleep duration or poorer-than-usual sleep quality (negative slope means higher stressor reactivity to insufficient sleep). When examining stressor reactivity to insufficient sleep with insufficient sleep represented by shorter-than-usual sleep duration, compared with those with average stressor reactivity to insufficient sleep (within ±½ SD; reference), workers with high stressor reactivity to insufficient sleep (≤-½ SD) had higher body mass index (B = 3.24, p < .05). The body mass index of these workers fell in the obese range. There was no difference in body mass index between workers with low stressor reactivity to insufficient sleep (≥+½ SD) and the reference group. When examining stressor reactivity to insufficient sleep with insufficient sleep represented by poorer-than-usual sleep quality, stressor reactivity to insufficient sleep was not significantly associated with body mass index. Results suggest that middle-aged workers with higher stressor reactivity to insufficient sleep duration may be at greater risk for obesity. Results may inform future studies on interventions for improving sleep and reducing stress in middle-aged workers.

Dataset Information

Longitudinal study of variation in body mass index in middle-aged UK females.

Publications

Longitudinal study of variation in body mass index in middle-aged UK females.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets