Cross-sectional interactions between quality of the physical and social environment and self-reported physical activity in adults living in income-deprived communities

Sawyer, Alexia; Jones, Russell; Ucci, Marcella; Smıth, Lee; Kearns, Ade; Fisher, Abi

doi:10.1371/journal.pone.0188962

Cited by 20 publications

(19 citation statements)

References 37 publications

(44 reference statements)

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“…3 ). This confirms previous studies which found that LDA gave an under-estimate of clay with a clay threshold < 2 µm 4 , 5 , 7 , 22 , 23 , but disputes the proposed clay threshold of < 8 µm with LDA analyses 5 , 11 . Taubner et al 6 also found an ~ 20% clay over-estimate using the < 8 µm threshold.…”

Section: Discussionsupporting

confidence: 87%

“…An additional explanation for this discrepancy in findings on the ideal clay threshold could be related to the pre-treatment of samples to remove OC in the afore-mentioned LDA studies 4 , 5 , 7 , 22 . In the present study, the absolute accuracy of the clay estimate with the LDA was very good for soils with < 3% OC and a < 4 µm threshold, even without OC removal (Fig.…”

Section: Discussionmentioning

confidence: 92%

“…It should also be kept in mind that the sieve-pipette technique can over-estimate the clay proportion 3 , 4 . Likewise, Fisher et al 22 found no significant effects of OC removal on clay detection in soils which generally had < 5% OC, and the only effects were seen in podsol soils from pasture systems with large contents of particulate labile carbon. Beuselinck et al 8 found no significant effect of OC removal on clay detection.…”

Section: Discussionmentioning

confidence: 96%

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A comparison of soil texture measurements using mid-infrared spectroscopy (MIRS) and laser diffraction analysis (LDA) in diverse soils

Thomas

Hernández-Allica

Dunham

et al. 2021

Sci Rep

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Spectroscopic methods for the determination of soil texture are faster and cheaper than the standard methods, but how do the results compare? To address this question, laser diffraction analysis (LDA) and mid-infrared spectroscopy (MIRS) analysis have been compared to conventional sieve-pipette measurements of texture in diverse European and Kenyan soils. To our knowledge this comparison between LDA and MIRS has not been made previously. It has used soils with a broad range of organic carbon (OC) contents to investigate whether, as in other techniques, clay-OC aggregation affects the estimation of clay with MIRS. The MIRS predictions of clay content were much better than the LDA measurements, but both techniques gave good measurements of sand content. The MIRS over-estimated clay at low clay content and under-estimated at high clay content (calibration set R2 = 0.83). The LDA over-estimated clay by ~ 60% (calibration set R2 = 0.36), indicating that the widely used clay threshold of < 8 µm was too high, and < 4 µm was found to be more accurate. In samples with < 5% OC content, both the LDA and MIRS gave very good clay predictions (R2 = 0.88 and 0.81, respectively). But in predictions of clay content in samples with > 5% OC the LDA under-estimated (R2 = < 0.1) and MIRS over-estimated (R2 = 0.34) clay content. In soils with OC removed, the MIRS prediction of clay content improved, indicating interference between over-lapping spectral regions for organic and mineral constituents. Unlike granulometric measurements of texture such as the LDA, MIRS analysis is not subject to the limitations imposed by the shape and density of particles. It was concluded that in typical agricultural soils with < 5% OC and < 60% clay content, both techniques could be used for cheap, fast and reliable estimates of soil texture.

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Section: Discussionsupporting

confidence: 87%

Section: Discussionmentioning

confidence: 92%

Section: Discussionmentioning

confidence: 96%

See 1 more Smart Citation

A comparison of soil texture measurements using mid-infrared spectroscopy (MIRS) and laser diffraction analysis (LDA) in diverse soils

Thomas

Hernández-Allica

Dunham

et al. 2021

Sci Rep

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“…Both studies are supported by findings of previous literature, indicating that social support is a strong determinant of physical activity participation (15). Social cohesion and safety are associated with increased odds of walking (OR = 1.78; 95% CI, 1.56–2.03) and moderate physical activity (OR = 1.93; 95% CI, 1.65–2.27) in a population-based study in the United Kingdom (16). Our findings extend those results to strength training specifically.…”

Section: Discussionmentioning

confidence: 99%

Associations Between Neighborhood Social Cohesion and Physical Activity in the United States, National Health Interview Survey, 2017

Quinn

Mody

et al. 2019

Prev. Chronic Dis.

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BackgroundIndividual social support is positively related to physical activity participation. However, less is known about how neighborhood-level social structures relate to physical activity participation.MethodsWe analyzed 2017 National Health Interview Survey data for adult participants who completed all questions on physical activity and neighborhood cohesion (N = 23,006). Each cohesion question was binary coded (cohesion or not) and used as a predictor individually and for a composite score measuring total social cohesion. We used linear regression to estimate minutes of moderate aerobic activity, and we used logistic regression to estimate the odds of meeting aerobic guidelines (≥150 min/wk), strength guidelines (≥2 d/wk of muscle strengthening exercises), or both guidelines, predicted by the 5 definitions of cohesion (composite cohesion and the 4 questions separately). Models were adjusted for sex, age, race/ethnicity, family-income-to-poverty ratio, education, nativity, language, and neighborhood tenure.ResultsRespondents who reported having more social cohesion had 45.0 more minutes of aerobic activity and increased odds of meeting aerobic, strength, and combined guidelines (odds ratio [OR] = 1.22, OR = 1.13, and OR = 1.14, respectively; P < .01 for all). Reporting having availability of help when needed, neighbors to count on, trustworthy neighbors, and close-knit neighbors all resulted in increased odds of meeting aerobic guidelines but not increased odds for meeting strength guidelines in the latter 3 components or combined guidelines for the latter 2 components.ConclusionsHaving neighborhood social cohesion or select individual components of neighborhood cohesion are positively related to meeting aerobic, strength, and combined guidelines.

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“…Several recent studies have examined associations between social cohesion and both PA and obesity [52•, 63, 59-61]. Higher levels of social cohesion were associated with increased leisure-time PA in low SES neighborhoods [64]. Yuma-Guerrero and colleagues demonstrated that social cohesion mediated the association between neighborhood SES (β=−0.18 between SES and social cohesion, p<0.05) and PA (β=0.10 between social cohesion and PA; p<0.05), in a fully-adjusted model, including age, race/ethnicity, marital status, number of children in the home, depression, and obesity [61].…”

Section: The Role Of Neighborhood Social Environment Factors In Pa Anmentioning

confidence: 99%

Neighborhood Social Environment and Cardiovascular Disease Risk

Tamura

Langerman

Ceasar

et al. 2019

Curr Cardiovasc Risk Rep

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Purpose of review: Limited physical activity (PA) and obesity are two primary risk factors for cardiovascular disease (CVD). Within a socio-ecological framework, neighborhood social environment may play a key role in influencing PA and obesity. However, the mechanisms underlying this relationship remain ambiguous. Our goals in this review are: (1) to summarize findings from the recent studies on neighborhood social environment in relation to PA and obesity as CVD risk factors, and (2) to briefly describe several innovative approaches to assessing neighborhood social environment. Recent findings: Almost all recent studies assessed neighborhood social environment around residential areas. There were consistent associations between neighborhood social environment and PA and obesity, with some exceptions (indicating null associations or paradoxical associations). However, a focus on residential social environment may limit results because these studies did not account for any exposures occurring away from individuals’ homes. Additionally, the majority of studies utilized a cross-sectional design, which limits our ability to make inferences regarding the causality of the association between social environment and PA or obesity as CV risk factors. Summary: The majority of the studies on neighborhood social environment characterized factors around residential areas and assessed participant activity via self-reported surveys. Future research should leverage tools to account for the spatial mismatch between environmental exposures and outcomes by using global positioning systems, ecological momentary assessments, virtual neighborhood audits, and simulation modeling. These approaches can overcome major limitations by tracking individuals’ daily activity and real-time perceptions of neighborhood social environments linked to CVD events.

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Cross-sectional interactions between quality of the physical and social environment and self-reported physical activity in adults living in income-deprived communities

Cited by 20 publications

References 37 publications

A comparison of soil texture measurements using mid-infrared spectroscopy (MIRS) and laser diffraction analysis (LDA) in diverse soils

A comparison of soil texture measurements using mid-infrared spectroscopy (MIRS) and laser diffraction analysis (LDA) in diverse soils

Associations Between Neighborhood Social Cohesion and Physical Activity in the United States, National Health Interview Survey, 2017

Neighborhood Social Environment and Cardiovascular Disease Risk

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