Predictors of Daily Mobility of Adults in Peri-Urban South India

Indoor air pollution and airway health

Because of the disproportionate amount of time that people spend indoors and the complexities of air pollutant exposures found there, indoor air pollution is a growing concern for airway health. Both infiltration of outdoor air pollution into the indoor space and indoor sources (such as smoke from tobacco products, cooking or heating practices and combustion of associated fuels, and household materials) contribute to unique exposure mixtures. Although there is substantial literature on the chemistry of indoor air pollution, research focused on health effects is only beginning to emerge and remains an important area of need to protect public health. We provide a review of emerging literature spanning the past 3 years and relating indoor air exposures to airway health, with a specific focus on the impact of either individual pollutant exposures or common combustion sources on the lower airways. Factors defining susceptibility and/or vulnerability are reviewed with consideration for priority populations and modifiable risk factors that may be targeted to advance health equity.

Household concentrations and female and child exposures to air pollution in peri-urban sub-Saharan Africa: measurements from the CLEAN-Air(Africa) study

BACKGROUND

Relatively clean cooking fuels such as liquefied petroleum gas (LPG) emit less fine particulate matter (PM2·5) and carbon monoxide (CO) than polluting fuels (eg, wood, charcoal). Yet, some clean cooking interventions have not achieved substantial exposure reductions. This study evaluates determinants of between-community variability in exposures to household air pollution (HAP) across sub-Saharan Africa.

METHODS

In this measurement study, we recruited households cooking primarily with LPG or exclusively with wood or charcoal in peri-urban Cameroon, Ghana, and Kenya from previously surveyed households. In 2019-20, we conducted monitoring of 24 h PM2·5 and CO kitchen concentrations (n=256) and female cook (n=248) and child (n=124) exposures. PM2·5 measurements used gravimetric and light scattering methods. Stove use monitoring and surveys on cooking characteristics and ambient air pollution exposure (eg, walking time to main road) were also administered.

FINDINGS

The mean PM2·5 kitchen concentration was five times higher among households cooking with charcoal than those using LPG in the Kenyan community (297 μg/m3, 95% CI 216-406, vs 61 μg/m3, 49-76), but only 4 μg/m3 higher in the Ghanaian community (56 μg/m3, 45-70, vs 52 μg/m3, 40-68). The mean CO kitchen concentration in charcoal-using households was double the WHO guideline (6·11 parts per million [ppm]) in the Kenyan community (15·81 ppm, 95% CI 8·71-28·72), but below the guideline in the Ghanaian setting (1·77 ppm, 1·04-2·99). In all communities, mean PM2·5 cook exposures only met the WHO interim-1 target (35 μg/m3) among LPG users staying indoors and living more than 10 min walk from a road.

INTERPRETATION

Community-level variation in the relative difference in HAP exposures between LPG and polluting cooking fuel users in peri-urban sub-Saharan Africa might be attributed to differences in ambient air pollution levels. Thus, mitigation of indoor and outdoor PM2·5 sources will probably be critical for obtaining significant exposure reductions in rapidly urbanising settings of sub-Saharan Africa.

FUNDING

UK National Institute for Health and Care Research.

Systematic review of best practices for GPS data usage, processing, and linkage in health, exposure science and environmental context research

Global Positioning System (GPS) technology is increasingly used in health research to capture individual mobility and contextual and environmental exposures. However, the tools, techniques and decisions for using GPS data vary from study to study, making comparisons and reproducibility challenging.

OBJECTIVES

The objectives of this systematic review were to (1) identify best practices for GPS data collection and processing; (2) quantify reporting of best practices in published studies; and (3) discuss examples found in reviewed manuscripts that future researchers may employ for reporting GPS data usage, processing and linkage of GPS data in health studies.

DESIGN

A systematic review.

DATA SOURCES

Electronic databases searched (24 October 2023) were PubMed, Scopus and Web of Science (PROSPERO ID: CRD42022322166).

ELIGIBILITY CRITERIA

Included peer-reviewed studies published in English met at least one of the criteria: (1) protocols involving GPS for exposure/context and human health research purposes and containing empirical data; (2) linkage of GPS data to other data intended for research on contextual influences on health; (3) associations between GPS-measured mobility or exposures and health; (4) derived variable methods using GPS data in health research; or (5) comparison of GPS tracking with other methods (eg, travel diary).

DATA EXTRACTION AND SYNTHESIS

We examined 157 manuscripts for reporting of best practices including wear time, sampling frequency, data validity, noise/signal loss and data linkage to assess risk of bias.

RESULTS

We found that 6% of the studies did not disclose the GPS device model used, only 12.1% reported the per cent of GPS data lost by signal loss, only 15.7% reported the per cent of GPS data considered to be noise and only 68.2% reported the inclusion criteria for their data.

CONCLUSIONS

Our recommendations for reporting on GPS usage, processing and linkage may be transferrable to other geospatial devices, with the hope of promoting transparency and reproducibility in this research.

PROSPERO REGISTRATION NUMBER

CRD42022322166.

Challenges and opportunity in mobility among older adults - key determinant identification

BACKGROUND

Attention is focused on the health and physical fitness of older adults due to their increasing age. Maintaining physical abilities, including safe walking and movement, significantly contributes to the perception of health in old age. One of the early signs of declining fitness in older adults is limited mobility. Approximately one third of 70-year-olds and most 80-year-olds report restrictions on mobility in their apartments and immediate surroundings. Restriction or loss of mobility is a complex multifactorial process, which makes older adults prone to falls, injuries, and hospitalizations and worsens their quality of life while increasing overall mortality.

OBJECTIVE

The objective of the study is to identify the factors that have had a significant impact on mobility in recent years and currently, and to identify gaps in our understanding of these factors. The study aims to highlight areas where further research is needed and where new and effective solutions are required.

METHODS

The PRISMA methodology was used to conduct a scoping review in the Scopus and Web of Science databases. Papers published from 2007 to 2021 were searched in November 2021. Of these, 52 papers were selected from the initial 788 outputs for the final analysis.

RESULTS

The final selected papers were analyzed, and the key determinants were found to be environmental, physical, cognitive, and psychosocial, which confirms the findings of previous studies. One new determinant is technological. New and effective solutions lie in understanding the interactions between different determinants of mobility, addressing environmental factors, and exploring opportunities in the context of emerging technologies, such as the integration of smart home technologies, design of accessible and age-friendly public spaces, development of policies and regulations, and exploration of innovative financing models to support the integration of assistive technologies into the lives of seniors.

CONCLUSION

For an effective and comprehensive solution to support senior mobility, the determinants cannot be solved separately. Physical, cognitive, psychosocial, and technological determinants can often be perceived as the cause/motivation for mobility. Further research on these determinants can help to arrive at solutions for environmental determinants, which, in turn, will help improve mobility. Future studies should investigate financial aspects, especially since many technological solutions are expensive and not commonly available, which limits their use.

Smartphone Global Positioning System-Based System to Assess Mobility in Health Research: Development, Accuracy, and Usability Study

BACKGROUND

As global positioning system (GPS) measurement is getting more precise and affordable, health researchers can now objectively measure mobility using GPS sensors. Available systems, however, often lack data security and means of adaptation and often rely on a permanent internet connection.

OBJECTIVE

To overcome these issues, we aimed to develop and test an easy-to-use, easy-to-adapt, and offline working app using smartphone sensors (GPS and accelerometry) for the quantification of mobility parameters.

METHODS

An Android app, a server backend, and a specialized analysis pipeline have been developed (development substudy). Parameters of mobility by the study team members were extracted from the recorded GPS data using existing and newly developed algorithms. Test measurements were performed with participants to complete accuracy and reliability tests (accuracy substudy). Usability was examined by interviewing community-dwelling older adults after 1 week of device use, followed by an iterative app design process (usability substudy).

RESULTS

The study protocol and the software toolchain worked reliably and accurately, even under suboptimal conditions, such as narrow streets and rural areas. The developed algorithms had high accuracy (97.4% correctness, F₁-score=0.975) in distinguishing dwelling periods from moving intervals. The accuracy of the stop/trip classification is fundamental to second-order analyses such as the time out of home, as they rely on a precise discrimination between the 2 classes. The usability of the app and the study protocol was piloted with older adults, which showed low barriers and easy implementation into daily routines.

CONCLUSIONS

Based on accuracy analyses and users' experience with the proposed system for GPS assessments, the developed algorithm showed great potential for app-based estimation of mobility in diverse health research contexts, including mobility patterns of community-dwelling older adults living in rural areas.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1186/s12877-021-02739-0.

Individually experienced heat stress among elderly residents of an urban slum and rural village in India

The elderly are one of the most vulnerable groups to heat-related illnesses and mortality. In tropical countries like India, where heat waves have increased in frequency and severity, few studies have focused on the level of stress experienced by the elderly. The study presented here included 130 elderly residents of Kolkata slums and 180 elderly residents of rural villages about 75 km south of Kolkata. It used miniature monitoring devices to continuously measure temperature, humidity, and heat index experienced during everyday activities over 24-h study periods, during hot summer months. In the Kolkata slum, construction materials and the urban heat island effect combined to create hotter indoor than outdoor conditions throughout the day, and particularly at night. As a result, elderly slum residents were 4.3 times more likely to experience dangerous heat index levels (≥ 45°C) compared to rural village elderly. In both locations, the median 24-h heat indexes of active elderly were up to 2°C higher than inactive/sedentary elderly (F = 25.479, p < 0.001). Among Kolkata slums residents, there were no significant gender differences in heat exposure during the day or night, but in the rural village, elderly women were 4 times more likely to experience dangerous heat index levels during the hottest times of the day compared to elderly men. Given the decline in thermoregulatory capacity associated with aging and the increasing severity of extreme summer heat in India, these results forecast a growing public health challenge that will require both scientific and government attention.

Freedom of Movement and Adolescent Sexual Violence in India

This study assesses associations between freedom of movement and sexual violence, both in marriage and outside of marriage, among a representative sample of adolescents in India. We analyzed data from girls aged 15 to 19 years (n = 9,593) taken from India's nationally representative National Family Health Survey 2015-2016. We defined freedom of movement using three items on whether girls could go unaccompanied to specified locations; we summated responses and categorized them as restricted, or unrestricted. We used multivariable regression to assess associations between restricted movement and nonmarital violence, and with marital sexual violence among ever-married girls. Results show that only 2% of girls reported nonmarital sexual violence, among married and unmarried girls; 6% of married girls reported marital sexual violence. Most girls (78%) reported some restriction in movement. Restricted movement was negatively associated with nonmarital sexual violence (adjusted odds ratio [AOR] = 0.52, 95% confidence interval [CI] = [0.31, 0.87], p = .01) but positively associated with marital sexual violence (AOR = 3.87, 95% CI = [1.82, 8.25], p < .001). Further analyses highlight that the observed association with nonmarital sexual violence was specific to urban and not rural girls. These findings reveal that approximately one in 30 adolescent girls in India has been a victim of sexual violence. Restricted movement is associated with lower risk for nonmarital sexual violence for urban adolescent girls, possibly due to lower exposure opportunity. Married girls with restricted movement have higher odds of marital sexual violence, possibly because these are both forms of control used by abusive husbands. Freedom of movement is a human right that should not place girls at greater risk for nonmarital violence or be used as a means of control by abusive spouses. Social change is needed to secure girls' safety in India.

GPS-based built environment measures associated with adult physical activity

Studies often rely on home locations to access built environment (BE) influences on physical activity (PA). We use GPS and accelerometer data collected for 288 individuals over a two-week period to examine eight GPS-derived BE characteristics and moderate-to-vigorous PA (MVPA) and light-to-moderate-vigorous PA (LMVPA). NDVI, parks, blue space, pedestrian-orientated intersections, and population density were associated with increased odds of LMVPA and MVPA, while traffic air pollution and noise were associated with decreased odds of LMVPA and MVPA. Associations varied by population density and when accounting for multiple BE measures. These findings provide further information on where individuals choose to be physically active.

Demographic and behavioural drivers of intra-urban mobility of migrant street children and youth in Kampala, Uganda

While research on the nexus of migration and wellbeing of individuals has gained recognition in recent years, far less attention has been devoted to intra-urban mobility especially among the urban poor young populations. We assess the drivers of intra-urban mobility using a random sample of 412 migrant street children and youth in Kampala city, Uganda. This paper draws from a larger cross-sectional survey of circular migration and sexual and reproductive health choices among street children in Kampala, Uganda. We define 'migrants' as street children and youth with a rural-urban migration experience and 'intra-urban mobility' as the number of places stayed in or moved since migrating to the city, measured on a continuous scale. More than half (54.37%) of the migrant street children and youth had lived in two or more places since migrating to the city. Multivariate negative binomial regression analysis reveals migrant street children and youth's intra-urban mobility to be associated with gender (aIRR = 0.71, 95%CI 0.53-0.96), sex work (aIRR = 1.38, 95%CI 1.01-1.88), a daily income of one USD or more (aIRR = 1.57, 95%CI 1.16-2.13) and duration of stay in the city (aIRR = 1.54, 95%CI 1.17-2.01). Other drivers of intra-urban mobility included availability of causal work, personal safety and affordability of rental costs. Our findings suggest the need for urban housing and health policies to take into account street children and youth's intra-urban mobility and its drivers. Future research on all drivers of street children and youth's intra-urban mobility and its linkage with their health outcomes is recommended.

Personal exposure to particulate matter in peri-urban India: predictors and association with ambient concentration at residence

Scalable exposure assessment approaches that capture personal exposure to particles for purposes of epidemiology are currently limited, but valuable, particularly in low-/middle-income countries where sources of personal exposure are often distinct from those of ambient concentrations. We measured 2 × 24-h integrated personal exposure to PM_2.5 and black carbon in two seasons in 402 participants living in peri-urban South India. Means (sd) of PM_2.5 personal exposure were 55.1(82.8) µg/m³ for men and 58.5(58.8) µg/m³ for women; corresponding figures for black carbon were 4.6(7.0) µg/m³ and 6.1(9.6) µg/m³. Most variability in personal exposure was within participant (intra-class correlation ~20%). Personal exposure measurements were not correlated (R_spearman < 0.2) with annual ambient concentration at residence modeled by land-use regression; no subgroup with moderate or good agreement could be identified (weighted kappa ≤ 0.3 in all subgroups). We developed models to predict personal exposure in men and women separately, based on time-invariant characteristics collected at baseline (individual, household, and general time-activity) using forward stepwise model building with mixed models. Models for women included cooking activities and household socio-economic position, while models for men included smoking and occupation. Models performed moderately in terms of between-participant variance explained (38-53%) and correlations between predictions and measurements (R_spearman: 0.30-0.50). More detailed, time-varying time-activity data did not substantially improve the performance of the models. Our results demonstrate the feasibility of predicting personal exposure in support of epidemiological studies investigating long-term particulate matter exposure in settings characterized by solid fuel use and high occupational exposure to particles.

Personal exposure to particulate air pollution and vascular damage in peri-urban South India

OBJECTIVE

Air pollution is a leading preventable risk factor for cardiovascular diseases. Previous studies mostly relied on concentrations at residence, which might not represent personal exposure. Personal air pollution exposure has a greater variability compared with levels of ambient air pollution, facilitating evaluation of exposure-response functions and vascular pathophysiology. We aimed to evaluate the association between predicted annual personal exposure to PM2.5 and black carbon (BC) and three vascular damage markers in peri-urban South India.

METHODS

We analyzed the third wave of the APCAPS cohort (2010-2012), which recruited participants from 28 villages. We used predicted personal exposure to PM2.5 and BC derived from 610 participant-days of 24 h average gravimetric PM2.5 and BC measurements and predictors related to usual time-activity. Outcomes included carotid intima-media thickness (CIMT), carotid-femoral pulse wave velocity (cf-PWV) and augmentation index (AIx). We fit linear mixed models, adjusting for potential confounders and accounting for the clustered data structure. We evaluated nonlinear associations using generalized additive mixed models.

RESULTS

Of the 3017 participants (mean age 38 years), 1453 (48%) were women. The average PM2.5 exposure was 51 µg/m3 (range 13-85) for men, and 61 µg/m3 (range 40-120) for women, while the average BC was 4 µg/m3 (range 3-7) for men and 8 µg/m3 (range 3-22) for women. A 10 μg/m3 increase of PM2.5 was positively associated with CIMT (0.026 mm, 95% CI 0.014, 0.037), cf-PWV (0.069 m/s, 95% CI 0.008, 0.131) and AIx (0.8%, 95% CI 0.3, 1.3) among men. The exposure-response function for PM2.5 and AIx among men showed non-linearity, particularly within the exposure range dominated by tobacco smoking and occupational exposures. Both PM2.5 and BC were positively associated with AIx among women (0.6%, 95% CI 0.2, 1.0, per 10 μg/m3 PM2.5; 0.5%, 95% CI 0.1, 0.8, per 2 μg/m3 BC).

CONCLUSIONS

Personal exposure to particulate matter was associated with vascular damage in a peri-urban population in South India. Personal exposure to particulate matter appears to have gender-specific effects on the type of vascular damage, potentially reflecting differences in sources of personal exposure by gender.

Validating a GPS-based approach to detect health facility visits against maternal response to prompted recall survey

Introduction

Common approaches to measure health behaviors rely on participant responses and are subject to bias. Technology-based alternatives, particularly using GPS, address these biases while opening new channels for research. This study describes the development and implementation of a GPS-based approach to detect health facility visits in rural Pune district, India.

Methods

Participants were mothers of under-five year old children within the Vadu Demographic Surveillance area. Participants received GPS-enabled smartphones pre-installed with a location-aware application to continuously record and transmit participant location data to a central server. Data were analyzed to identify health facility visits according to a parameter-based approach, optimal thresholds of which were calibrated through a simulation exercise. Lists of GPS-detected health facility visits were generated at each of six follow-up home visits and reviewed with participants through prompted recall survey, confirming visits which were correctly identified. Detected visits were analyzed using logistic regression to explore factors associated with the identification of false positive GPS-detected visits.

Results

We enrolled 200 participants and completed 1098 follow-up visits over the six-month study period. Prompted recall surveys were completed for 694 follow-up visits with one or more GPS-detected health facility visits. While the approach performed well during calibration (positive predictive value (PPV) 78%), performance was poor when applied to participant data. Only 440 of 22 251 detected visits were confirmed (PPV 2%). False positives increased as participants spent more time in areas of high health facility density (odds ratio (OR) = 2.29, 95% confidence interval (CI) = 1.62-3.25). Visits detected at facilities other than hospitals and clinics were also more likely to be false positives (OR = 2.78, 95% CI = 1.65-4.67) as were visits detected to facilities nearby participant homes, with the likelihood decreasing as distance increased (OR = 0.89, 95% CI = 0.82-0.97). Visit duration was not associated with confirmation status.

Conclusions

The optimal parameter combination for health facility visits simulated by field workers substantially overestimated health visits from participant GPS data. This study provides useful insights into the challenges in detecting health facility visits where providers are numerous, highly clustered within urban centers and located near residential areas of the population which they serve.

Land-Use Change and Cardiometabolic Risk Factors in an Urbanizing Area of South India: A Population-Based Cohort Study

BACKGROUND

Land-use changes in city fringes due to urbanization can lead to a reduction of greenspace that may reduce its associated health benefits.

OBJECTIVES

We evaluated the association between changes in residential surrounding built-up land use and cardiometabolic risk factors in an urbanizing peri-urban area of south India and explored the mediating roles of air pollution, physical activity, and stress in these associations.

METHODS

We analyzed data on 6,039 adults from the third follow-up of the Andhra Pradesh Children and Parent Study (APCAPS) cohort (2010-2012). We generated trajectories of change in residential surrounding built-up land use (buffer areas) from 1995-2009 (stable, slow increase, fast increase) using remote sensing data and image classification methods. We estimated associations between built-up land use trajectories and natural log-transformed blood pressure, waist circumference, triglycerides, fasting glucose, and non-high-density lipoprotein (non-HDL) cholesterol using linear mixed models. We accounted for multiple mediators and the multilevel structure of the data in mediation analyses.

RESULTS

We observed positive associations between a fast increase in built-up land use within 300m of the home and all cardiometabolic risk factors. Compared with participants with stable trajectories, those with the largest increase in built-up land use had 1.5% (95% CI: 0.1, 2.9) higher systolic blood pressure, 2.4% (95% CI: 0.6, 4.3) higher diastolic blood pressure, 2.1% (95% CI: 0.5, 3.8) higher waist circumference, and 1.6% (95% CI: -0.6, 3.8) higher fasting glucose in fully adjusted models. Associations were positive, but not statistically significant, for triglycerides, fasting glucose, and non-HDL cholesterol. Physical activity and ambient particulate matter ≤2.5μm in aerodynamic diameter (PM2.5) partially mediated the estimated associations. Associations between fast build-up and all cardiometabolic risk factors except non-HDL cholesterol were stronger in women than men.

DISCUSSION

Increases in built-up land use surrounding residences were consistently associated with higher levels of cardiometabolic risk factors. Our findings support the need for better integration of health considerations in urban planning in rapidly urbanizing settings. https://doi.org/10.1289/EHP5445.

Identifying predictors of personal exposure to air temperature in peri-urban India

Characterizing personal exposure to air temperature is critical to understanding exposure measurement error in epidemiologic studies using fixed-site exposure data and to identify strategies to protect public health. To date, no study evaluating personal air temperature in the general population has been conducted in a low-and-middle income country. We used data from the CHAI study consisting of 50 adults monitored in up to six non-consecutive 24 h sessions in peri-urban south India. We quantified the agreement and association between fixed-site ambient and personal air temperature, and identified predictors of personal air temperature based on housing assessment, self-reported, GPS, remote sensing, and wearable camera data. Mean (SD) daytime (6 am-10 pm) average personal air temperature was 31.2 (2.6) °C and mean nighttime (10 pm-6 am) average temperature was 28.8 (2.8) °C. Agreement between average personal air and fixed-site ambient temperatures was limited, especially at night when personal air temperatures were underestimated by fixed-site temperatures (MBE = -5.6 °C). The proportion of average personal nighttime temperature variability explained by ambient fixed-site temperatures was moderate (R²_mar = 0.39); daytime associations were stronger for women (R²_mar = 0.51) than for men (R²_mar = 0.3). Other predictors of average nighttime personal air temperature included residential altitude, ceiling height, and household income. Predictors of average daytime personal air temperature included roof materials, GPS-tracked altitude, time working in agriculture (for women), and time travelling (for men). No biomass cooking, urban heat island, or greenspace effects were identified. R²_mar between ambient fixed-site and personal air temperature indicate that ambient fixed-site temperature is only a moderately useful proxy of personal air temperature in the context of peri-urban India. Our findings suggest that people living in houses at lower altitude, with lower ceiling height and asbestos roofing sheets might be more vulnerable to heat. We also identified households with higher income, women working in agriculture and men with long commutes as disproportionately exposed to high temperatures.

Association between ambient and household air pollution with carotid intima-media thickness in peri-urban South India: CHAI-Project

BACKGROUND

Evidence linking ambient air pollution with atherosclerosis is lacking from low- and middle-income countries. Additionally, evidence regarding the association between household air pollution and atherosclerosis is limited. We evaluated the association between ambient fine particulate matter [particulate matter with an aerodynamic diameter of ≤2.5 µm (PM2.5)] and biomass fuel use on carotid intima-media thickness (CIMT), a surrogate of atherosclerosis, in India.

METHODS

We analysed the third follow-up of the Andhra Pradesh Children and Parent Study cohort (2010-2012), which recruited participants from 28 peri-urban villages. Our primary outcome was mean CIMT, measured using a standardized protocol. We estimated annual average PM2.5 outdoors at residence using land-use regression. Biomass cooking fuel was self-reported. We fitted a within-between linear-mixed model adjusting for potential confounders.

RESULTS

Among 3278 participants (48% women, mean age 38 years), mean PM2.5 was 32.7 [range 24.4-38.2] µg/m3, and 60% used biomass. After confounder adjustment, we observed positive associations between within-village variation in PM2.5 and CIMT in all participants [1.79%, 95% confidence interval (CI), -0.31 to 3.90 per 1  µg/m3 of PM2.5] and in men (2.98%, 95% CI, 0.23-5.72, per 1  µg/m3 of PM2.5). Use of biomass cooking fuel was associated with CIMT in all participants (1.60%, 95% CI, -0.46 to 3.65), especially in women with an unvented stove (6.14%, 95% CI, 1.40-10.89). The point-estimate for the PM2.5 association was larger in sub-groups with higher cardiometabolic risk profile.

CONCLUSIONS

Ambient and household air pollution were positively associated with CIMT in a peri-urban population of India, although with limited precision for some estimates. We observed differences in the association between ambient and household air pollution and CIMT by gender.

Analysis of the Association between Running Performance and Game Performance Indicators in Professional Soccer Players

Running performance (RP) and game performance indicators (GPI) are important determinants of success in soccer (football), but there is an evident lack of knowledge about the possible associations between RP and GPI. This study aimed to identify associations between RP and GPI in professional soccer players and to compare RP and GPI among soccer playing positions. One hundred one match performances were observed over the course of half of a season at the highest level of national competition in Croatia. Players (mean ± SD, age: 23.85 ± 2.88 years; body height: 183.05 ± 8.88 cm; body mass: 78.69 ± 7.17 kg) were classified into five playing positions (central defenders (n = 26), full-backs (n = 24), central midfielders (n = 33), wide midfielders (n = 10), and forwards (n = 8). RP, as measured by global positioning system, included the total distance covered, distance covered in five speed categories (walking, jogging, running, high-speed running, and maximal sprinting), total number of accelerations, number of high-intensity accelerations, total number of decelerations, and number of high-intensity decelerations. The GPI were collected by the position-specific performance statistics index (InStat index). The average total distance was 10,298.4 ± 928.7 m, with central defenders having the shortest and central midfielders having the greatest covered distances. The running (r = 0.419, p = 0.03) and high-intensity accelerations (r = 0.493, p = 0.01) were correlated with the InStat index for central defenders. The number of decelerations of full-backs (r = −0.43, p = 0.04) and the distance covered during sprinting of forwards (r = 0.80, p = 0.02) were associated with their GPI obtained by InStat index. The specific correlations between RP and GPI should be considered during the conditioning process in soccer. The soccer training should follow the specific requirements of the playing positions established herein, which will allow players to meet the game demands and to perform successfully.

Assessing Older Adults' Daily Mobility: A Comparison of GPS-Derived and Self-Reported Mobility Indicators

Interest in global positioning system (GPS)-based mobility assessment for health and aging research is growing, and with it the demand for validated GPS-based mobility indicators. Time out of home (TOH) and number of activity locations (#ALs) are two indicators that are often derived from GPS data, despite lacking consensus regarding thresholds to be used to extract those as well as limited knowledge about their validity. Using 7 days of GPS and diary data of 35 older adults, we make the following three main contributions. First, we perform a sensitivity analysis to investigate how using spatial and temporal thresholds to compute TOH and #ALs affects the agreement between self-reported and GPS-based indicators. Second, we show how daily self-reported and GPS-derived mobility indicators are compared. Third, we explore whether the type and duration of self-reported activity events are related to the degree of correspondence between reported and GPS event. Highest indicator agreement was found for temporal interpolation (Tmax) of up to 5 h for both indicators, a radius (Dmax) to delineate home between 100 and 200 m for TOH, and for #ALs a spatial extent (Dmax) between 125 and 200 m, and temporal extent (Tmin) between 5 and 6 min to define an activity location. High agreement between self-reported and GPS-based indicators is obtained for TOH and moderate agreement for #ALs. While reported event type and duration impact on whether a reported event has a matching GPS event, indoor and outdoor events are detected at equal proportions. This work will help future studies to choose optimal threshold settings and will provide knowledge about the validity of mobility indicators.

Towards a comprehensive set of GPS-based indicators reflecting the multidimensional nature of daily mobility for applications in health and aging research

BACKGROUND

GPS tracking is increasingly used in health and aging research to objectively and unobtrusively assess individuals' daily-life mobility. However, mobility is a complex concept and its thorough description based on GPS-derived mobility indicators remains challenging.

METHODS

With the aim of reflecting the breadth of aspects incorporated in daily mobility, we propose a conceptual framework to classify GPS-derived mobility indicators based on their characteristic and analytical properties for application in health and aging research. In order to demonstrate how the classification framework can be applied, existing mobility indicators as used in existing studies are classified according to the proposed framework. Then, we propose and compute a set of selected mobility indicators based on real-life GPS data of 95 older adults that reflects diverse aspects of individuals' daily mobility. To explore latent dimensions that underlie the mobility indicators, we conduct a factor analysis.

RESULTS

The proposed framework enables a conceptual classification of mobility indicators based on the characteristic and analytical aspects they reflect. Characteristic aspects inform about the content of the mobility indicator and comprise categories related to space, time, movement scope, and attribute. Analytical aspects inform how a mobility indicator is aggregated with respect to temporal scale and statistical property. The proposed categories complement existing studies that often underrepresent mobility indicators involving timing, temporal distributions, and stop-move segmentations of movements. The factor analysis uncovers the following six dimensions required to obtain a comprehensive view of an older adult's daily mobility: extent of life space, quantity of out-of-home activities, time spent in active transport modes, stability of life space, elongation of life space, and timing of mobility.

CONCLUSION

This research advocates incorporating GPS-based mobility indicators that reflect the multi-dimensional nature of individuals' daily mobility in future health- and aging-related research. This will foster a better understanding of what aspects of mobility are key to healthy aging.

Ambient Particulate Air Pollution and Blood Pressure in Peri-urban India

BACKGROUND

Evidence linking long-term exposure to particulate air pollution to blood pressure (BP) in high-income countries may not be transportable to low- and middle-income countries. We examined cross-sectional associations between ambient fine particulate matter (PM2.5) and black carbon (BC) with BP (systolic [SBP] and diastolic [DBP]) and prevalent hypertension in adults from 28 peri-urban villages near Hyderabad, India.

METHODS

We studied 5531 participants from the Andhra Pradesh Children and Parents Study (18-84 years, 54% men). We measured BP (2010-2012) in the right arm and defined hypertension as SBP ≥130 mmHg and/or DBP ≥80 mmHg. We used land-use regression models to estimate annual average PM2.5 and BC at participant's residence. We applied linear and logistic nested mixed-effect models stratified by sex and adjusted by cooking fuel type to estimate associations between within-village PM2.5 or BC and health.

RESULTS

Mean (SD) PM2.5 was 33 µg/m (2.7) and BC was 2.5 µg/m (0.23). In women, a 1 µg/m increase in PM2.5 was associated with 1.4 mmHg higher SBP (95% confidence interval [CI]: 0.12, 2.7), 0.87 mmHg higher DBP (95% CI: -0.18, 1.9), and 4% higher odds of hypertension (95% CI: 0%, 9%). In men, associations with SBP (0.52 mmHg; 95% CI: -0.82, 1.8), DBP (0.41 mmHg; 95% CI: -0.69, 1.5), and hypertension (2% higher odds; 95% CI: -2%, 6%) were weaker. No associations were observed with BC.

CONCLUSION

We observed a positive association between ambient PM2.5 and BP and hypertension in women. Longitudinal studies in this region are needed to corroborate our findings.

Activity spaces in studies of the environment and physical activity: A review and synthesis of implications for causality

Activity spaces are increasingly used to understand how people interact with their environment and engage in activity but their use may raise challenges regarding causal inference. We conducted a systematic review of findings and the methodological, analytical and conceptual issues relevant to causal inference. Studies were included if they comprised a spatial summary of locations visited, assessed any part of the causal pathway between the environment, physical activity and health, and used quantitative or qualitative methods. We searched seven electronic databases in January 2018 and screened 11910 articles for eligibility. Forty-seven studies were included for review. Studies answered research questions about features of or environmental features within activity spaces using a range of spatial and temporal summary techniques. The conceptual challenge of using activity spaces to strengthen causal inference was rarely considered, although some studies discussed circularity, temporality, and plausibility. Future studies should use longitudinal and experimental designs and consider the potential and actual use of spaces for physical activity, and their relationship with total levels of activity.

When, Where, and What? Characterizing Personal PM2.5 Exposure in Periurban India by Integrating GPS, Wearable Camera, and Ambient and Personal Monitoring Data

Evidence identifying factors that influence personal exposure to air pollutants in low- and middle-income countries is scarce. Our objective was to identify the relative contribution of the time of the day ( when?), location ( where?), and individuals' activities ( what?) to PM_2.5 personal exposure in periurban South India. We conducted a panel study in which 50 participants were monitored in up to six 24-h sessions ( n = 227). We integrated data from multiple sources: continuous personal and ambient PM_2.5 concentrations; questionnaire, GPS, and wearable camera data; and modeled long-term exposure at residence. Mean 24-h personal exposure was 43.8 μg/m³ (SD 24.6) for men and 39.7 μg/m³ (SD 12.0) for women. Temporal patterns in exposure varied between women (peak exposure in the morning) and men (more exposed throughout the rest of the day). Most exposure occurred at home, 67% for men and 89% for women, which was proportional to the time spent in this location. Ambient daily PM_2.5 was an important predictor of 24-h personal exposure for both genders. Among men, activities predictive of higher hourly average exposure included presence near food preparation, in the kitchen, in the vicinity of smoking, or in industry. For women, predictors of exposure were largely related to cooking.

Wearable camera-derived microenvironments in relation to personal exposure to PM2.5

Data regarding which microenvironments drive exposure to air pollution in low and middle income countries are scarce. Our objective was to identify sources of time-resolved personal PM_2.5 exposure in peri-urban India using wearable camera-derived microenvironmental information. We conducted a panel study with up to 6 repeated non-consecutive 24 h measurements on 45 participants (186 participant-days). Camera images were manually annotated to derive visual concepts indicative of microenvironments and activities. Men had slightly higher daily mean PM_2.5 exposure (43 μg/m³) compared to women (39 μg/m³). Cameras helped identify that men also had higher exposures when near a biomass cooking unit (mean (sd) μg/m³: 119 (383) for men vs 83 (196) for women) and presence in the kitchen (133 (311) for men vs 48 (94) for women). Visual concepts associated in regression analysis with higher 5-minute PM_2.5 for both sexes included: smoking (+93% (95% confidence interval: 63%, 129%) in men, +29% (95% CI: 2%, 63%) in women), biomass cooking unit (+57% (95% CI: 28%, 93%) in men, +69% (95% CI: 48%, 93%) in women), visible flame or smoke (+90% (95% CI: 48%, 144%) in men, +39% (95% CI: 6%, 83%) in women), and presence in the kitchen (+49% (95% CI: 27%, 75%) in men, +14% (95% CI: 7%, 20%) in women). Our results indicate wearable cameras can provide objective, high time-resolution microenvironmental data useful for identifying peak exposures and providing insights not evident using standard self-reported time-activity.