A cross-sectional study on intestinal microbiota composition was performed on 230 healthy subjects at four European locations in France, Germany, Italy, and Sweden. The study participants were assigned to two age groups: 20 to 50 years (mean age, 35 years; n ‫؍‬ 85) and >60 years (mean age, 75 years; n ‫؍‬ 145). A set of 14 group-and species-specific 16S rRNA-targeted oligonucleotide probes was applied to the analysis of fecal samples by fluorescence in situ hybridization coupled with flow cytometry. Marked country-age interactions were observed for the German and Italian study groups. These interactions were inverse for the predominant bacterial groups Eubacterium rectale-Clostridium coccoides and Bacteroides-Prevotella. Differences between European populations were observed for the Bifidobacterium group only. Proportions of bifidobacteria were two-to threefold higher in the Italian study population than in any other study group, and this effect was independent of age. Higher proportions of enterobacteria were found in all elderly volunteers independent of the location. Gender effects were observed for the Bacteroides-Prevotella group, with higher levels in males than in females. In summary, age-related differences in the microbiota makeup were detected but differed between the study populations from the four countries, each showing a characteristic colonization pattern.

The developed method for detecting physical activity types showed a high sensitivity and specificity for sitting, standing, walking, running, walking stairs, and cycling in a standardized setting and for sitting posture during free living.

This study examined the ability of the Acti4 software for identifying physical activity types from accelerometers during free-living with different levels of movement complexity compared with video observations. Nineteen aircraft cabin cleaners with ActiGraph GT3X+ accelerometer at the thigh and hip performed one semi-standardised and two non-standardised sessions (outside and inside aircraft) with different levels of movement complexity during working hours. The sensitivity for identifying different activity types was 75.4-99.4% for the semi-standardised session, 54.6-98.5% outside the aircraft and 49.9-90.2% inside the aircraft. The specificity was above 90% for all activities, except 'moving' inside the aircraft. These findings indicate that Acti4 provides good estimates of time spent in different activity types during semi-standardised conditions, and for sitting, standing and walking during non-standardised conditions with normal level of movement complexity. The Acti4 software may be a useful tool for researchers and practitioners in the field of ergonomics, occupational and public health. Practitioner Summary: Being inexpensive, small, water-resistant and without wires, the ActiGraph GT3X+ by applying the Acti4 software may be a useful tool for long-term field measurements of physical activity types for researchers and practitioners in the field of ergonomics, occupational and public health.

Being inexpensive, small, water-resistant and without wires, ActiGraph GT3X+ seems to be a valid mean for direct long-term field measurements of arm and trunk inclinations when analysed by the Acti4 customised software.

Purpose: The purpose of this study was to investigate the face validity of the self-reported single item work ability with objectively measured heart rate reserve (%HRR) among blue-collar workers. Methods: We utilized data from 127 blue-collar workers (Female = 53; Male = 74) aged 18–65 years from the cross-sectional “New method for Objective Measurements of physical Activity in Daily living (NOMAD)” study. The workers reported their single item work ability and completed an aerobic capacity cycling test and objective measurements of heart rate reserve monitored with Actiheart for 3–4 days with a total of 5,810 h, including 2,640 working hours. Results: A significant moderate correlation between work ability and %HRR was observed among males (R = −0.33, P = 0.005), but not among females (R = 0.11, P = 0.431). In a gender-stratified multi-adjusted logistic regression analysis, males with high %HRR were more likely to report a reduced work ability compared to males with low %HRR [OR = 4.75, 95% confidence interval (95% CI) = 1.31 to 17.25]. However, this association was not found among females (OR = 0.26, 95% CI 0.03 to 2.16), and a significant interaction between work ability, %HRR and gender was observed (P = 0.03). Conclusions: The observed association between work ability and objectively measured %HRR over several days among male blue-collar workers supports the face validity of the single work ability item. It is a useful and valid measure of the relation between physical work demands and resources among male blue-collar workers. The contrasting association among females needs to be further investigated.

ObjectivesTo investigate the differences between a questionnaire-based and accelerometer-based sitting time, and develop a model for improving the accuracy of questionnaire-based sitting time for predicting accelerometer-based sitting time.Methods183 workers in a cross-sectional study reported sitting time per day using a single question during the measurement period, and wore 2 Actigraph GT3X+ accelerometers on the thigh and trunk for 1–4 working days to determine their actual sitting time per day using the validated Acti4 software. Least squares regression models were fitted with questionnaire-based siting time and other self-reported predictors to predict accelerometer-based sitting time.ResultsQuestionnaire-based and accelerometer-based average sitting times were ≈272 and ≈476 min/day, respectively. A low Pearson correlation (r=0.32), high mean bias (204.1 min) and wide limits of agreement (549.8 to −139.7 min) between questionnaire-based and accelerometer-based sitting time were found. The prediction model based on questionnaire-based sitting explained 10% of the variance in accelerometer-based sitting time. Inclusion of 9 self-reported predictors in the model increased the explained variance to 41%, with 10% optimism using a resampling bootstrap validation. Based on a split validation analysis, the developed prediction model on ≈75% of the workers (n=132) reduced the mean and the SD of the difference between questionnaire-based and accelerometer-based sitting time by 64% and 42%, respectively, in the remaining 25% of the workers.ConclusionsThis study indicates that questionnaire-based sitting time has low validity and that a prediction model can be one solution to materially improve the precision of questionnaire-based sitting time.

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Fragestellung: In Deutschland gibt es kaum aussagefähige Daten zum Alkoholkonsum bei älteren Menschen in Privathaushalten. Im Rahmen dieser Arbeit soll der Alkoholkonsum älterer, in Privathaushalten lebender Menschen untersucht werden. </p><p> Methodik: Am Robert Koch-Institut wurde der telefonische Gesundheitssurvey 2007 ohne Altersbeschränkung durchgeführt. Der Alkoholkonsum wurde mit dem AUDIT-C bei 2.503 Frauen und Männern im Alter ab 18 Jahren erhoben. In der Stichprobe waren 547 (22 %) der Personen 60 Jahre oder älter. </p><p> Ergebnisse: Die Auswertung ergab bei Frauen ab 70 Jahren eine Abnahme des durchschnittlichen Alkoholkonsums. Bei den Männern wurde lediglich eine Tendenz jedoch keine signifikante Abnahme im Alter gefunden. Bei Frauen wurde eine Zunahme des Alkoholkonsums mit steigender Sozialschicht gefunden. Tendenziell ist in den meisten Altersgruppen der Alkoholkonsum in der unteren Sozialschicht geringer. Im Alter ab 70 Jahren ist dieser Unterschied am stärksten ausgeprägt. Eine Unterteilung in Risikotrinker, moderate Trinker und Nietrinker zeigt eine Verdoppelung des Nietrinkens bei Frauen im Alter ab 70 Jahren, bei gleichzeitiger Abnahme des moderaten und riskanten Konsums. Bei den Männern hatte im Alter ab 70 das Nietrinken ebenfalls zugenommen, wobei diese Zunahme geringer ausfiel und somit die Häufigkeiten von moderatem und riskantem Konsum in dieser Altersgruppe nicht signifikant rückläufig waren. Riskanter Alkoholkonsum war bei den Frauen der unteren Sozialschicht seltener, bei den Männern zeigt sich dieser Unterschied zwischen den Sozialschichten nicht. </p><p> Schlussfolgerungen: Es wird resümiert, dass bei der Analyse des Alkoholkonsums älterer Menschen, Geschlecht, Alter, Sozialschicht und regionale Besonderheiten berücksichtigt werden sollten.