Advances in population surveillance for physical activity and sedentary behavior : reliability and validity of time use surveys

Many countries conduct regular national time use surveys, some of which date back as far as the 1960s. Time use surveys potentially provide more detailed and accurate national estimates of the prevalence of sedentary and physical activity behavior than more traditional self-report surveillance systems. In this study, the authors determined the reliability and validity of time use surveys for assessing sedentary and physical activity behavior. In 2006 and 2007, participants (n = 134) were recruited from work sites in the Australian state of New South Wales. Participants completed a 2-day time use diary twice, 7 days apart, and wore an accelerometer. The 2 diaries were compared for test-retest reliability, and comparison with the accelerometer determined concurrent validity. Participants with similar activity patterns during the 2 diary periods showed reliability intraclass correlations of 0.74 and 0.73 for nonoccupational sedentary behavior and moderate/vigorous physical activity, respectively. Comparison of the diary with the accelerometer showed Spearman correlations of 0.57-0.59 and 0.45-0.69 for nonoccupational sedentary behavior and moderate/vigorous physical activity, respectively. Time use surveys appear to be more valid for population surveillance of nonoccupational sedentary behavior and health-enhancing physical activity than more traditional surveillance systems. National time use surveys could be used to retrospectively study nonoccupational sedentary and physical activity behavior over the past 5 decades.

Comparison of surveys used to measure physical activity

Objective To compare the level of agreement in results obtained from four physical activity (PA) measurement instruments that are in use in Australia and around the world. Methods 1,280 randomly selected participants answered two sets of PA questions by telephone. 428 answered the Active Australia (AA) and National Health Surveys, 427 answered the AA and CDC Behavioural Risk Factor Surveillance System surveys (BRFSS), and 425 answered the AA survey and the short International Physical Activity Questionnaire (IPAQ). Results Among the three pairs of survey items, the difference in mean total PA time was lowest when the AA and NHS items were asked (difference=24) (SE:17) minutes, compared with 144 (SE:21) mins for AA/BRFSS and 406 (SE:27) mins for AA/IPAQ). Correspondingly, prevalence estimates for 'sufficiently active' were similar for AA and NHS (56% and 55% respectively), but about 10% higher when BRFSS data were used, and about 26% higher when the IPAQ items were used, compared with estimates from the AA survey. Conclusions The findings clearly demonstrate that there are large differences in reported PA times and hence in prevalence estimates of 'sufficient activity' from these four measures. Implications It is important to consistently use the same survey for population monitoring purposes. As the AA survey has now been used three times in national surveys, its continued use for population surveys is recommended so that trend data ever a longer period of time can be established.

Test-retest reliability of physical activity measures used in Australian population surveys

PURPOSE Accurate monitoring of prevalence and trends in population levels of physical activity is fundamental to the planning of health promotion and disease-prevention strategies. Test-retest reliability (repeatability) was assessed for four self-report measures of physical activity commonly used in population surveys: the Active Australia survey (AA, N=356), the short form of the International Physical Activity Questionnaire (IPAQ-S, N=104), the physical activity items in the Behavioral Risk Factor Surveillance System (BRFSS, N=127) and the physical activity items in the Australian National Health Survey (NHS, N=122). METHODS Percent agreement and Kappa statistics were used to assess the reliability of classification of activity status (where ‘active’= 150 minutes of activity per week) and sedentariness (where ‘sedentary’ = reporting no physical activity). Intraclass correlations (ICCs) were used to assess agreement on minutes of activity reported for each item of each survey and on total minutes reported in each survey. RESULTS Percent agreement scores for both activity status and sedentariness were very good on all four instruments. Overall the percent agreement between repeated surveys was between 73% (NHS) and 87% (IPAQ) for the criterion measure of achieving 150 minutes per week, and between 77% (NHS) and 89% (IPAQ) for the criterion of being sedentary. Corresponding Kappa statistics ranged from 0.46 (NHS) to 0.61 (AA) for activity status and from 0.20 (BRFSS) to 0.52 (AA) for sedentariness. For the individual items ICCs were highest for walking (0.45 to 0.56) and vigorous activity (0.22 to 0.64) and lowest for the moderate questions (0.16 to 0.44). CONCLUSION All four measures provide acceptable levels of test-retest reliability for assessing both activity status and sedentariness, and moderate reliability for assessing total minutes of activity. Supported by the Australian Commonwealth Department of Health and Ageing.

Evaluation of public hospital performance in Khanh Hoa Province : Vietnam in connection with patient and staff satisfaction surveys

This research aimed to develop a framework for performance evaluation of public hospitals in Vietnam that is culturally, socially, and politically appropriate. The research included both qualitative and quantitative methods and identified and validated novel instruments to measure patient satisfaction and job satisfaction of hospital staff and to determine a set of hospital indicators that reflect the quality of hospital performance. New models for understanding the determinants of patient and staff satisfaction were developed along with a new performance indicator framework for hospital performance. These instruments will now be applied to the evaluation of hospital services in Khanh Hoa Province, permitting longer term evaluation of their effectiveness in changing system wide performance and satisfaction.

Understanding Uncertainties in Non-Linear Population Trajectories: A Bayesian Semi-Parametric Hierarchical Approach to Large-Scale Surveys of Coral Cover

Recently, attempts to improve decision making in species management have focussed on uncertainties associated with modelling temporal fluctuations in populations. Reducing model uncertainty is challenging; while larger samples improve estimation of species trajectories and reduce statistical errors, they typically amplify variability in observed trajectories. In particular, traditional modelling approaches aimed at estimating population trajectories usually do not account well for nonlinearities and uncertainties associated with multi-scale observations characteristic of large spatio-temporal surveys. We present a Bayesian semi-parametric hierarchical model for simultaneously quantifying uncertainties associated with model structure and parameters, and scale-specific variability over time. We estimate uncertainty across a four-tiered spatial hierarchy of coral cover from the Great Barrier Reef. Coral variability is well described; however, our results show that, in the absence of additional model specifications, conclusions regarding coral trajectories become highly uncertain when considering multiple reefs, suggesting that management should focus more at the scale of individual reefs. The approach presented facilitates the description and estimation of population trajectories and associated uncertainties when variability cannot be attributed to specific causes and origins. We argue that our model can unlock value contained in large-scale datasets, provide guidance for understanding sources of uncertainty, and support better informed decision making

Recent surveys of bats (Mammalia: Chiroptera) from China. I. Rhinolophidae and Hipposideridae

We conducted surveys of bats in China between 1999 and 2007, resulting in the identification of at least 62 species. In this paper we present data on 19 species, comprising 12 species from the family Rhinolophidae and seven from the Hipposideridae. Rhinolophids captured were Rhinolophus affinis, R. ferrumequinum, R. lepidus, R. luctus, R. macrotis, R. siamensis, R. marshalli, R. rex, R. pearsonii, R. pusillus, R. sinicus and R. stheno. Because of extensive morphological similarities we question the species distinctiveness of R. osgoodi (may be conspecific with R. lepidus), R. paradoxolophus (which may best be treated as a subspecies of R. rex), R. huananus (probably synonymous with R. siamensis), and we are skeptical as to whether R. sinicus is distinct from R. thomasi. Hipposiderids captured were Hipposideros armiger, H. cineraceus, H. larvatus, H. pomona, H. pratti, Aselliscus stoliczkanus and Coelops frithii. Of these species, two rhinolophids (Rhinolophus marshalli and R. stheno) and one hipposiderid (Hipposideros cineraceus) represent new species records for China. We present data on species' ranges, morphology and echolocation call frequencies, as well as some notes on ecology and conservation status. China hosts a considerable diversity of rhinolophid and hipposiderid bats, yet threats to their habitats and populations are substantial.

Integrating field survey data with satellite image data to improve shallow water seagrass maps : the role of AUV and snorkeller surveys

Repeatable and accurate seagrass mapping is required for understanding seagrass ecology and supporting management decisions. For shallow (< 5 m) seagrass habitats, these maps can be created by integrating high spatial resolution imagery with field survey data. Field survey data for seagrass is often collected via snorkelling or diving. However, these methods are limited by environmental and safety considerations. Autonomous Underwater Vehicles (AUVs) are used increasingly to collect field data for habitat mapping, albeit mostly in deeper waters (>20 m). Here we demonstrate and evaluate the use and potential advantages of AUV field data collection for calibration and validation of seagrass habitat mapping of shallow waters (< 5 m), from multispectral satellite imagery. The study was conducted in the seagrass habitats of the Eastern Banks (142 km2), Moreton Bay, Australia. In the field, georeferenced photos of the seagrass were collected along transects via snorkelling or an AUV. Photos from both collection methods were analysed manually for seagrass species composition and then used as calibration and validation data to map seagrass using an established semi-automated object based mapping routine. A comparison of the relative advantages and disadvantages of AUV and snorkeller collected field data sets and their influence on the mapping routine was conducted. AUV data collection was more consistent, repeatable and safer in comparison to snorkeller transects. Inclusion of deeper water AUV data resulted in mapping of a larger extent of seagrass (~7 km2, 5 % of study area) in the deeper waters of the site. Although overall map accuracies did not differ considerably, inclusion of the AUV data from deeper water transects corrected errors in seagrass mapped at depths to 5 m, but where the bottom is visible on satellite imagery. Our results demonstrate that further development of AUV technology is justified for the monitoring of seagrass habitats in ongoing management programs.

Being Thrifty on a $100K Wage: Austerity in Family Finances

Understanding how families manage their finances represents a highly important research agenda given the recent economic climate of debt and uncertainty. To have a better understanding of the economics in domestic settings, it is very important to study the ways money and financial issues are collaboratively handled within families. Using an ethnographic approach, we studied the everyday financial practices of fifteen middle-income families. Our preliminary results show that there is a strong tendency to live frugally; that, people apply various and creative mechanisms to minimize their expenses and save money seemingly irrespectively of their income. To this end we highlight some implications for designing technologies to support household financial practices.

Clustering acoustic events in environmental recordings for species richness surveys

Environmental acoustic recordings can be used to perform avian species richness surveys, whereby a trained ornithologist can observe the species present by listening to the recording. This could be made more efficient by using computational methods for iteratively selecting the richest parts of a long recording for the human observer to listen to, a process known as “smart sampling”. This allows scaling up to much larger ecological datasets. In this paper we explore computational approaches based on information and diversity of selected samples. We propose to use an event detection algorithm to estimate the amount of information present in each sample. We further propose to cluster the detected events for a better estimate of this amount of information. Additionally, we present a time dispersal approach to estimating diversity between iteratively selected samples. Combinations of approaches were evaluated on seven 24-hour recordings that have been manually labeled by bird watchers. The results show that on average all the methods we have explored would allow annotators to observe more new species in fewer minutes compared to a baseline of random sampling at dawn.

Automating marine mammal detection in aerial images captured during wildlife surveys: A deep learning approach

Aerial surveys conducted using manned or unmanned aircraft with customized camera payloads can generate a large number of images. Manual review of these images to extract data is prohibitive in terms of time and financial resources, thus providing strong incentive to automate this process using computer vision systems. There are potential applications for these automated systems in areas such as surveillance and monitoring, precision agriculture, law enforcement, asset inspection, and wildlife assessment. In this paper, we present an efficient machine learning system for automating the detection of marine species in aerial imagery. The effectiveness of our approach can be credited to the combination of a well-suited region proposal method and the use of Deep Convolutional Neural Networks (DCNNs). In comparison to previous algorithms designed for the same purpose, we have been able to dramatically improve recall to more than 80% and improve precision to 27% by using DCNNs as the core approach.

Assistive classification for improving the efficiency of avian species richness surveys

Avian species richness surveys, which measure the total number of unique avian species, can be conducted via remote acoustic sensors. An immense quantity of data can be collected, which, although rich in useful information, places a great workload on the scientists who manually inspect the audio. To deal with this big data problem, we calculated acoustic indices from audio data at a one-minute resolution and used them to classify one-minute recordings into five classes. By filtering out the non-avian minutes, we can reduce the amount of data by about 50% and improve the efficiency of determining avian species richness. The experimental results show that, given 60 one-minute samples, our approach enables to direct ecologists to find about 10% more avian species.

Frequency and precision of aerial surveys for kangaroo management

The appropriate frequency and precision for surveys of wildlife populations represent a trade-off between survey cost and the risk of making suboptimal management decisions because of poor survey data. The commercial harvest of kangaroos is primarily regulated through annual quotas set as proportions of absolute estimates of population size. Stochastic models were used to explore the effects of varying precision, survey frequency and harvest rate on the risk of quasiextinction for an arid-zone and a more mesic-zone kangaroo population. Quasiextinction probability increases in a sigmoidal fashion as survey frequency is reduced. The risk is greater in more arid regions and is highly sensitive to harvest rate. An appropriate management regime involves regular surveys in the major harvest areas where harvest rate can be set close to the maximum sustained yield. Outside these areas, survey frequency can be reduced in relatively mesic areas and reduced in arid regions when combined with lowered harvest rates. Relative to other factors, quasiextinction risk is only affected by survey precision (standard error/mean × 100) when it is >50%, partly reflecting the safety of the strategy of harvesting a proportion of a population estimate.

The influence of animal mobility on the assumption of uniform distances in aerial line-transect surveys

Line-transect distance sampling is a widely used method for estimating animal density from aerial surveys. Analysis of line-transect distance data usually relies on a requirement that the statistical distribution of distances of animal groups from the transect line is uniform. We show that this requirement is satisfied by the survey design if all other assumptions of distance sampling hold, but it can be violated by consistent survey problems such as responsive movement of the animals towards or away from the observer. We hypothesise that problems with the uniform requirement are unlikely to be encountered for immobile taxa, but might become substantial for species of high mobility. We test evidence for non-uniformity using double-observer distance data from two aerial surveys of five species with a spectrum of mobility capabilities and tendencies. No clear evidence against uniformity was found for crabeater seals or emperor penguins on the pack-ice in East Antarctica, while minor non-uniformity consistent with responsive movement up to 30 m was found for Adelie penguins. Strong evidence of either non-uniformity or a failure of the capture-recapture validating method was found for eastern grey kangaroos and red kangaroos in Queensland.

A comparison of mark-recapture distance-sampling methods applied to aerial surveys of eastern grey kangaroos

Aerial surveys of kangaroos (Macropus spp.) in Queensland are used to make economically important judgements on the levels of viable commercial harvest. Previous analysis methods for aerial kangaroo surveys have used both mark-recapture methodologies and conventional distance-sampling analyses. Conventional distance sampling has the disadvantage that detection is assumed to be perfect on the transect line, while mark-recapture methods are notoriously sensitive to problems with unmodelled heterogeneity in capture probabilities. We introduce three methodologies for combining together mark-recapture and distance-sampling data, aimed at exploiting the strengths of both methodologies and overcoming the weaknesses. Of these methods, two are based on the assumption of full independence between observers in the mark-recapture component, and this appears to introduce more bias in density estimation than it resolves through allowing uncertain trackline detection. Both of these methods give lower density estimates than conventional distance sampling, indicating a clear failure of the independence assumption. The third method, termed point independence, appears to perform very well, giving credible density estimates and good properties in terms of goodness-of-fit and percentage coefficient of variation. Estimated densities of eastern grey kangaroos range from 21 to 36 individuals km-2, with estimated coefficients of variation between 11% and 14% and estimated trackline detection probabilities primarily between 0.7 and 0.9.