Physical activity derived from questionnaires and wrist-worn accelerometers: comparability and the role of demographic, lifestyle, and health factors among a population-based sample of older adults

Chantal M Koolhaas,1 Frank JA van Rooij,1 Magda Cepeda,1 Henning Tiemeier,1–3 Oscar H Franco,1 Josje D Schoufour1 1Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands; 2Department of Child and Adolescent Psychiatry, Erasmus Medical Center, Rotterdam, The Netherlands; 3Department of Psychiatry, Erasmus Medical Center, Rotterdam, The Netherlands Background: Agreement between questionnaires and accelerometers to measure physical activity (PA) differs between studies and might be related to demographic, lifestyle, and health characteristics, including disability and depressive symptoms.Methods: We included 1,410 individuals aged 51–94 years from the population-based Rotterdam Study. Participants completed the LASA Physical Activity Questionnaire and wore a wrist-worn accelerometer on the nondominant wrist for 1 week thereafter. We compared the Spearman correlation and disagreement (level and direction) for total PA across levels of demographic, lifestyle, and health variables. The level of disagreement was defined as the absolute difference between questionnaire- and accelerometer-derived PA, whereas the direction of disagreement was defined as questionnaire PA minus accelerometer PA. We used linear regression analyses with the level and direction of disagreement as outcome, including all demographic, lifestyle, and health variables in the model.Results: We observed a Spearman correlation of 0.30 between questionnaire- and accelerometer-derived PA in the total population. The level of disagreement (ie, absolute difference) was 941.9 (standard deviation [SD] 747.0) minutes/week, and the PA reported by questionnaire was on average 529.4 (SD 1,079.5) minutes/week lower than PA obtained by the accelerometer. The level of disagreement decreased with higher educational levels. Additionally, participants with obesity, higher disability scores, and more depressive symptoms underestimated their self-reported PA more than their healthier counterparts.Conclusion: We observed large differences in PA time derived from the LASA Physical Activity Questionnaire and the wrist-worn accelerometer. Differences between the methods were related to body-mass index, level of disability, and presence of depressive symptoms. Future studies using questionnaires and/or accelerometers should account for these differences. Keywords: physical activity, questionnaire, accelerometer, disagreement, elderl

Objective measures of activity in the elderly: Distribution and associations with demographic and health factors

Little is known about the distribution of activity over the full 24-hour spectrum in late old age and its association with demographic and health factors. Therefore, we aimed to evaluate the distribution of physical activity (PA), sedentary behavior, and sleep, and associated factors in the elderly population.This work was supported by a Netherlands Organization for Scientific Research grant (017.106.370) awarded to HT. The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University Rotterdam; Netherlands Organization for the Health Research and Development; the Research Institute for Diseases in the Elderly; the Ministry of Education, Culture and Science; the Ministry for Health, Welfare and Sports; and the European Commission. O.H.F. works in ErasmusAGE, a center for aging research across the life course funded by Nestlé Nutrition (Nestec Ltd.), Metagenics Inc., and AXA. The work of SB was supported by UK Medical Research Council [MC_UU_12015/3]

Dietary patterns and changes in frailty status: the Rotterdam study

Prevention, Population and Disease management (PrePoD)Public Health and primary car

Dietary patterns and changes in frailty status: the Rotterdam study

Purpose: To determine the associations between a priori and a posteriori derived dietary patterns and a general state of health, measured as the accumulation of deficits in a frailty index. Methods: Cross-sectional and longitudinal analysis embedded in the population-based Rotterdam Study (n = 2632) aged 45 years. Diet was assessed at baseline (year 2006) using food frequency questionnaires. Dietary patterns were defined a priori using an existing index reflecting adherence to national dietary guidelines and a posteriori using principal component analysis. A frailty index was composed of 38 health deficits and measured at baseline and follow-up (4 years later). Linear regression analyses were performed using adherence to each of the dietary patterns as exposure and the frailty index as outcome (all in Z-scores). Results: Adherence to the national dietary guidelines was associated with lower frailty at baseline (β −0.05, 95% CI −0.08, −0.02). Additionally, high adherence was associated with lower frailty scores over time (β −0.08, 95% CI −0.12, −0.04). The PCA revealed three dietary patterns that we named a “Traditional” pattern, high in legumes, eggs and savory snacks; a “Carnivore” pattern, high in meat and poultry; and a “Health Conscious” pattern, high in whole grain products, vegetables and fruit. In the cross-sectional analyses adherence to these patterns was not associated with frailty. However, adherence to the “Traditional” pattern was associated with less frailty over time (β −0.09, 95% CI −0.14, −0.05). Conclusion: No associations were found for adherence to a “healthy” pattern or “Carnivore” pattern. However, Even in a population that is relatively young and healthy, adherence to dietary guidelines or adherence to the Traditional pattern could help to prevent, delay or reverse frailty levels

Statistical model for earthquake economic loss estimation using GDP and DPI: a case study from Iran

As earthquakes can result in multi-dimensional negative consequences such as human loss and building damage, the ability to make accurate economic loss estimations immediately after the occurrence is crucial. Unfortunately, in many earthquake-stricken countries such as Iran, governments are often unable to quickly or accurately assess post-earthquake losses. The aim of this paper, therefore, is to extend the model developed by Chan et al. (Nat Hazards 17:269–283, 1998) to two independent variables to develop an earthquake economic loss estimation method based on the economic and socio-economic indices gross domestic product (GDP) and disposable personal income (DPI) and a seismic hazard probability function. A global cell map is also considered to assess the GDP and DPI based on the population in each cell affected by the earthquake. In the final stage, using the Modified Mercalli Intensity Scale, 18 earthquake damaged areas in Iran are taken as case study to estimate the economic losses using the new model presented in this paper