Integrating Kindergartener-Specific Questionnaires With Citizen Science to Improve Child Health

Jia, Peng

doi:10.3389/fpubh.2018.00236

Cited by 15 publications

(13 citation statements)

References 18 publications

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“…Recall bias may exist, as data were self-reported. The modern approaches of collecting data, such as smartphone-based applications, could be used in future longitudinal studies to collect data in a more frequent, real-time manner, probably improving the reliability of the measurements of social capital scales [66,67]. Second, more aspects of mental health, such as stress, should be measured in future in order to fully understand influences of social capital on mental health problems among older PLWH.…”

Section: Discussionmentioning

confidence: 99%

Association between social capital and mental health among older people living with HIV: the Sichuan Older HIV-Infected Cohort Study (SOHICS)

et al. 2020

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Background: Mental health problems are common among older people living with HIV and associated with poorer health outcomes. Social capital is an important determinant of mental health problems but under-studied in this population. This study investigated the association between social capital and mental health problems among older people living with HIV in China. Methods: The study was based on the baseline data of a cohort study investigating mental health among older people living with HIV in Sichuan, China during November 2018 to February 2019. Participants were people living with HIV aged ≥50 years living in Sichuan province. Stratified multi-stage cluster sampling was used to recruit participants from 30 communities/towns; 529 out of 556 participants being approached completed the face-to-face interview. Social capital was measured by two validated health-related social capital scales: the Individual and Family scale and the Community and Society scale. Presence of probable depression (CES-D-10 score ≥ 10) and probable anxiety (GAD-7 score ≥ 5) were used as dependent variables. Two-level logistic regression models were applied to examine the association between social capital and probable depression/anxiety. Results: The prevalence of probable depression and probable anxiety was 25.9% (137/529) and 36.3% (192/529), respectively. After adjusting for significant covariates, the individual/family level of social capital was inversely associated with both probable depression (odds ratios (OR): 0.89, 95% CI: 0.84-0.93, p < 0.001) and probable anxiety (OR: 0.90, 95% CI: 0.86-0.95, p < 0.001). The community/society level social capital was associated with probable depression (OR: 0.91, 95% CI: 0.84-0.99, p < 0.001) but not probable anxiety (p > 0.05).

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Section: Discussionmentioning

confidence: 99%

Association between social capital and mental health among older people living with HIV: the Sichuan Older HIV-Infected Cohort Study (SOHICS)

et al. 2020

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“…Second, the majority of the studies included were cross‐sectional with few longitudinal studies and RCTs. The increasing use of the advanced spatial and big data approaches will lead to more frequent measurement of food environments for longitudinal study designs and linkage to follow‐up health data 60–63 . Finally, none of the included studies examined the pathway from convenience store accessibility to childhood obesity through unhealthy dietary behaviors.…”

Section: Discussionmentioning

confidence: 99%

Association between access to convenience stores and childhood obesity: A systematic review

Xin

Zhao

et al. 2019

Obesity Reviews

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Summary Childhood obesity increases the risk of adulthood obesity and is associated with other adverse health outcomes later in life. It may be influenced by environmental characteristics of neighborhoods where children live, particularly dietary supply–related environmental factors. This study aimed to systematically review the evidence on the association between access to convenience stores and childhood obesity. We searched and filtered relevant literature in PubMed, Embase, Web of Science, and Cochrane Library published before 1 January 2019. Data on the basic characteristics of studies, measures of access to convenience stores, and associations of convenience stores with weight‐related behaviors and outcomes were extracted from 41 included studies. In general, the density of and proximity to convenience stores in children's residential and school neighborhoods were positively associated with unhealthy eating behaviors. However, their associations with children's weight status varied significantly by regions. The association between convenience store access and children's weight status was found to be negative in Canada, rather mixed in the United States and the United Kingdom, and not significant in East Asia. We suggest future research to clearly define the convenience store, better measure the access to convenience store, and also measure children's journey and food purchasing and consumption behaviors, to explain pathways from convenience store access to childhood obesity for designing effective interventions and policies.

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“…This paper provided a new approach for the rapid and accurate estimation of the human population at the regional scale. The integrated approach for population estimation has the potential to adopt more remote sensing data and new types of social sensing big data to estimate population in more flexible ways in the future, such as age-specific population estimation [59]. The values of multisource social sensing data in population estimation will be explored in future studies to further improve the accuracy of population mapping.…”

Section: Discussionmentioning

confidence: 99%

Population Mapping with Multisensor Remote Sensing Images and Point-Of-Interest Data

Yang

Zhao

et al. 2019

Remote Sensing

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Fine-resolution population distribution mapping is necessary for many purposes, which cannot be met by aggregated census data due to privacy. Many approaches utilize ancillary data that are related to population density, such as nighttime light imagery and land use, to redistribute the population from census to finer-scale units. However, most of the ancillary data used in the previous studies of population modeling are environmental data, which can only provide a limited capacity to aid population redistribution. Social sensing data with geographic information, such as point-of-interest (POI), are emerging as a new type of ancillary data for urban studies. This study, as a nascent attempt, combined POI and multisensor remote sensing data into new ancillary data to aid population redistribution from census to grid cells at a resolution of 250 m in Zhejiang, China. The accuracy of the results was assessed by comparing them with WorldPop. Results showed that our approach redistributed the population with fewer errors than WorldPop, especially at the extremes of population density. The approach developed in this study—incorporating POI with multisensor remotely sensed data in redistributing the population onto finer-scale spatial units—possessed considerable potential in the era of big data, where a substantial volume of social sensing data is increasingly being collected and becoming available.

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Integrating Kindergartener-Specific Questionnaires With Citizen Science to Improve Child Health

Cited by 15 publications

References 18 publications

Association between social capital and mental health among older people living with HIV: the Sichuan Older HIV-Infected Cohort Study (SOHICS)

Association between social capital and mental health among older people living with HIV: the Sichuan Older HIV-Infected Cohort Study (SOHICS)

Association between access to convenience stores and childhood obesity: A systematic review

Population Mapping with Multisensor Remote Sensing Images and Point-Of-Interest Data

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