Suchergebnisse

Objectives Examine differences in perceptions of tap water (TW) and bottled water (BW) safety and TW taste and their associations with plain water (PW) and sugar-sweetened beverage (SSB) intake. Design Quantitative, cross-sectional study. Setting United States. Subjects 4,041 U.S. adults (≥18 years) in the 2018 SummerStyles survey data. Measures Outcomes were intake of TW, BW, PW (tap and bottled water), and SSB. Exposures were perceptions of TW and BW safety and TW taste (disagree, neutral, or agree). Covariates included sociodemographics. Analysis We used chi-square analysis to examine sociodemographic differences in perceptions and multivariable logistic regressions to estimate adjusted odds ratios (AOR) for consuming TW ≤ 1 cup/day, BW > 1 cup/day, PW ≤ 3 cups/day, and SSB ≥ 1 time/day by water perceptions. Results One in 7 (15.1%) of adults did not think their home TW was safe to drink, 39.0% thought BW was safer than TW, and 25.9% did not think their local TW tasted good. Adults who did not think local TW was safe to drink had higher odds of drinking TW ≤ 1 cup/day (AOR = 3.12) and BW >1 cup/day (AOR = 2.69). Adults who thought BW was safer than TW had higher odds of drinking TW ≤1 cup/day (AOR = 2.38), BW > 1 cup/day (AOR = 5.80), and SSB ≥ 1 time/day (AOR = 1.39). Adults who did not think TW tasted good had higher odds of drinking TW ≤ 1 cup/day (AOR = 4.39) and BW > 1 cup/day (AOR = 2.91). Conclusions Negative perceptions of TW safety and taste and a belief BW is safer than TW were common and associated with low TW intake. Perceiving BW is safer than TW increased the likelihood of daily SSB intake. These findings can guide programs and services to support water quality to improve perceptions of TW safety and taste, which might increase TW intake and decrease SSB intake.

Purpose: To examine factors associated with frequency of plain water (ie, tap, bottled, and unflavored sparkling water) intake among US high school students. Design: Quantitative, cross-sectional study. Setting: The 2017 national Youth Risk Behavior Survey data. Subjects: US high school students with plain water intake data (N = 10 698). Measures: The outcome was plain water intake. Exposure variables were demographics, academic grades, and behavioral characteristics. Analysis: We used logistic regression to estimate adjusted odds ratios (aOR) and 95% confidence intervals (CIs) for factors associated with infrequent plain water intake (<3 vs ≥3 times/day). Results: Overall, 48.7% of high school students reported drinking plain water <3 times/day. Factors associated with infrequent plain water intake were younger age (≤15 years; aOR = 1.20, CI = 1.05-1.37); earning mostly D/F grades (aOR = 1.37, CI = 1.07-1.77); consuming regular soda 1 to 6 times/week (aOR = 1.92, CI = 1.67-2.20) or ≥1 time/day (aOR = 3.23, CI = 2.65-3.94), sports drinks 1 to 6 times/week (aOR = 1.30, CI = 1.14-1.49), milk <2 glasses/day (aOR = 1.51, CI = 1.31-1.73), fruits <2 times/day (aOR = 1.92, CI = 1.66-2.22), and vegetables <3 times/day (aOR = 2.42, CI = 2.04-2.89); and being physically active ≥60 minutes/day on <5 days/week (aOR = 1.83, CI = 1.60-2.08). Students with obesity were less likely to have infrequent water intake (aOR = 0.63, CI = 0.53-0.74). Conclusions: Infrequent plain water intake was associated with younger age, poor academic grades, poor dietary behaviors, and physical inactivity. These findings can inform intervention efforts to increase water intake to promote healthy lifestyles among adolescents.

INTRODUCTION: Recent legislation requires public and charter schools in California to test drinking water for lead. Our objective was to describe 1) results from this testing program in the context of other available water safety data and 2) factors related to schools and water utilities associated with access to safe drinking water in schools. METHODS: Our study focused on a random sample of 240 California public and charter schools. We used multivariable logistic regression, accounting for clustering of tested water sources in schools, to examine school-level factors associated with failure to meet lead-testing deadlines and any history of water utility noncompliance. RESULTS: Of the 240 schools, the majority (n = 174) tested drinking water for lead. Of the schools tested, 3% (n = 6) had at least 1 sample that exceeded 15 parts per billion (ppb) (California action level) and 16% (n = 28) exceeded 5 ppb (bottled water standard). Suburban schools had lower odds of being served by noncompliant water systems (OR = 0.17; CI, 0.05–0.64; P = .009) than city schools. Compared with city schools, rural schools had the highest odds of not participating in the water testing program for lead (OR = 3.43; CI, 1.46–8.05; P = .005). Hallways and common spaces and food services areas were the most frequent school locations tested; one-third of all locations sampled could not be identified. CONCLUSION: In our study, geography influenced access to safe drinking water in schools, including both water utility safety standards and school lead-testing practices. Considerations for improving the implementation of state lead-testing programs include establishing priority locations for sampling, precisely labeling samples, and developing well-defined testing and reporting protocols.

Introduction: Recent legislation requires public and charter schools in California to test drinking water for lead. Our objective was to describe 1)results from this testing program in the context of other available water safety data and 2) factors related to schools and water utilities associated with access to safe drinking water in schools. Methods Our study focused on a random sample of 240 California public and charter schools. We used multivariable logistic regression, accounting for clustering of tested water sources in schools, to examine school-level factors associated with failure to meet lead-testing deadlines and any history of water utility noncompliance. Results: Of the 240 schools, the majority (n = 174) tested drinking water for lead. Of the schools tested, 3% (n = 6) had at least 1 sample that exceeded 15 parts per billion (ppb) (California action level) and 16% (n = 28) exceeded 5 ppb (bottled water standard). Suburban schools had lower odds of being served by noncompliant water systems (OR = 0.17; CI, 0.050.64; P =.009) than city schools. Compared with city schools, rural schools had the highest odds of not participating in the water testing program for lead (OR = 3.43; CI, 1.468.05; P =.005). Hallways and common spaces and food services areas were the most frequent school locations tested; one-third of all locations sampled could not be identified. Conclusion: In our study, geography influenced access to safe drinking water in schools, including both water utility safety standards and school lead-testing practices. Considerations for improving the implementation of state lead-testing programs include establishing priority locations for sampling, precisely labeling samples, and developing well-defined testing and reporting protocols. ; Published version

Objective To examine factors associated with water filter use (WFU) for drinking tap water at home and its association with consuming plain water and sugar-sweetened beverages (SSBs). Design Quantitative, cross-sectional study. Setting The 2018 SummerStyles survey data. Subjects U.S. adults (≥18 years; N=4042). Measures Outcomes were intake of plain water (tap/bottled water) and SSBs. Exposure was WFU (yes, no, not drinking tap water at home). Covariates included sociodemographics, weight status, Census regions, and home ownership status. Analysis We used multivariable logistic regressions to estimate adjusted odds ratios (AOR) and 95% confidence interval (CI) for consuming tap water, bottled water, or total plain water >3 cups/day (vs. ≤3 cups) and SSBs ≥1 time/day (vs. <1 time) by WFU. Results Overall, 36% of adults reported using a filter for drinking tap water at home; 14% did not drink tap water at home. Hispanics had significantly higher odds of using a water filter (AOR=1.50, 95% CI=1.14-1.98) vs non-Hispanic White. Factors significantly associated with lower odds of WFU were lower education (AOR=.69, 95% CI=.55-.86 for ≤high school; AOR=.78, 95% CI=.64-.95 for some college, vs college graduate), not being married (AOR=.81, 95% CI=.66-.98, vs married/domestic partnership), and lower household income (AOR=.68, 95% CI=.68-.90 for <$35,000, vs ≥$100,000). Using a water filter was associated with higher odds of drinking >3 cups/day of tap water (AOR=1.33, 95% CI=1.13-1.56) and lower odds of SSBs ≥1 time/day (AOR=.76, 95% CI=.62-.92). Not drinking tap water at home was associated with higher odds of drinking >3 cups/day bottled water (AOR=3.46, 95% CI=2.70-4.44). Conclusions WFU was associated with higher tap water intake and lower SSB intake among U.S. adults. WFU was higher among Hispanics, but lower among those with lower education and income and not married adults. Although WFU was associated with healthful beverage habits, additional considerations for WFU may include source water quality, oral health, cost, and proper use.

Algorithms are not to be regarded as a technical structure but as a social phenomenon - they embed themselves, currently still very subtle, into our political and social system. Algorithms shape human behavior on various levels: they influence not only the aesthetic reception of the world but also the well-being and social interaction of their users. They act and intervene in a political and social context. As algorithms influence individual behavior in these social and political situations, their power should be the subject of critical discourse - or even lead to active disobedience and to the need for appropriate tools and methods which can be used to break the algorithmic power