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Lack of in-home piped water and reported consumption of sugar-sweetened beverages among adults in rural Alaska

Published online by Cambridge University Press:  24 September 2019

Emily Mosites*
Affiliation:
Arctic Investigations Program, Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Anchorage, Alaska
Sara Seeman
Affiliation:
Arctic Investigations Program, Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Anchorage, Alaska
Andrea Fenaughty
Affiliation:
Section of Chronic Disease Prevention and Health Promotion, Division of Public Health, Alaska Department of Health and Social Services, Anchorage, Alaska
Karol Fink
Affiliation:
Section of Chronic Disease Prevention and Health Promotion, Division of Public Health, Alaska Department of Health and Social Services, Anchorage, Alaska
Laura Eichelberger
Affiliation:
National Tribal Water Center, Division of Environmental Health and Engineering, Alaska Native Tribal Health Consortium, Anchorage, Alaska
Peter Holck
Affiliation:
Clinical and Research Services, Alaska Native Tribal Health Consortium, Anchorage, Alaska
Timothy K Thomas
Affiliation:
Clinical and Research Services, Alaska Native Tribal Health Consortium, Anchorage, Alaska
Michael G Bruce
Affiliation:
Arctic Investigations Program, Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Anchorage, Alaska
Thomas W Hennessy
Affiliation:
Arctic Investigations Program, Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Anchorage, Alaska
*
*Corresponding author: Email Lwx7@cdc.gov
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Abstract

Objective:

To assess whether a community water service is associated with the frequency of sugar-sweetened beverages (SSB) consumption, obesity, or perceived health status in rural Alaska.

Design:

We examined the cross-sectional associations between community water access and frequency of SSB consumption, body mass index categories, and perceived health status using data from the 2013 and 2015 Alaska Behavioral Risk Factor Surveillance System (BRFSS). Participants were categorized by zip code to ‘in-home piped water service’ or ‘no in-home piped water service’ based on water utility data. We evaluated the univariable and multivariable (adjusting for age, household income and education) associations between water service and outcomes using log-linear survey-weighted generalized linear models.

Setting:

Rural Alaska, USA.

Subjects:

Eight hundred and eighty-seven adults, aged 25 years and older.

Results:

In unadjusted models, participants without in-home water reported consuming SSB more often than participants with in-home water (1·46, 95 % CI: 1·06, 2·00). After adjustment for potential confounders, the effect decreased but remained borderline significant (1·29, 95 % CI: 1·00, 1·67). Obesity was not significantly associated with water service but self-reported poor health was higher in those communities without in-home water (1·63, 95 % CI: 1·05, 2·54).

Conclusions:

Not having access to in-home piped water could affect behaviours surrounding SSB consumption and general perception of health in rural Alaska.

Type
Research paper
Copyright
© The Authors 2019

According to the World Health Organization, 29 % of people in the world did not have access to safely managed drinking water in 2015(1). In low- and middle-income countries, lack of access to improved water sources and sanitation has been associated with infectious disease and poor child growth(Reference Wolf, Pruss-Ustun and Cumming2,Reference Hossain, Choudhury and Adib Binte Abdullah3) . Even in the United States, some areas do not have full coverage of in-home piped water. In 2017, at least 15 % of occupied housing units in rural Alaska lacked in-home plumbing(4). The lack of access to piped water service is a particular problem in remote communities that are reachable only by airplane or boat. In these communities, not having piped water has been associated with added risk of numerous infectious diseases, including respiratory hospitalizations in children, skin infections, gastrointestinal infections, and invasive pneumococcal disease(Reference Thomas, Ritter and Bruden5Reference Bulkow, Singleton and DeByle7). In addition to infectious diseases, there may be additional unknown health risks associated with not having access to in-home drinking water. Studies in other regions have found associations between inadequate water supply and stress(Reference Wutich and Ragsdale8) musculoskeletal injuries(Reference Geere, Bartram and Bates9) and gastric cancer risk(Reference Eichelberger, Murphy and Etemadi10).

Qualitative research has shown that individuals experiencing water scarcity may conserve water by consuming sugar-sweetened beverages (SSB)(Reference Sarkar, Hanrahan and Hudson11). SSB are defined as any beverage with added caloric sweetener, including regular soda, sweetened juices (e.g. Tang or Kool-Aid), sweet tea and sports/energy drinks(12,13) . In the United States, 30·1 % of respondents report consuming at least one SSB per day, with the prevalence ranging from under 20 % in some states in the northeast to over 40 % in the southeast(Reference Park, Xu and Town14). In several large and repeated studies, frequent consumption of SSB has been associated with obesity, cardiovascular disease, metabolic disorders, dental decay, and other chronic conditions(Reference Ruanpeng, Thongprayoon and Cheungpasitporn15Reference Bernabe, Vehkalahti and Sheiham18).

In rural Alaska, studies have found that over 50 % of adults consume sugar sweetened beverages at least once per week(Reference Elwan, Schweinitz and Wojcicki19). However, to our knowledge, the association between lack of water access and SSB consumption has not been studied quantitatively. In this analysis of Behavioral Risk Factor Surveillance System (BRFSS) and water utility data, we evaluated whether rural Alaska residents in communities without an in-home piped water service reported different frequencies of SSB consumption compared with residents of communities with an in-home service. We also assessed if residents without an in-home piped water service had a different prevalence of health outcomes that could be related to SSB consumption, including obesity or self-reported poor health.

Methods

Study population

Rural Alaska spans a large geographic area with a population of approximately 240 000 people. Communities are often geographically isolated and can only be reached by boat, aeroplane, or snowmobile. Food and other supplies can be gathered through subsistence activities (such as hunting) or through air or boat cargo. Larger communities (called ‘hub towns’) serve as transportation and administrative centres for surrounding smaller communities. For this analysis, data were restricted to those participants who lived in communities that were not externally accessible by the state-wide road system or the Alaska Marine Highway ferry system and were not hub towns.

Water access is variable in these remote areas. Some households have piped water from a centralized treated water source while some have piped water from wells. Communities without piped water from either of these sources may have a closed haul system, where water is hauled to, and sewage is hauled away from, the house. Other communities have a community clean water access point where individuals haul their own water to their house. In these areas, households usually self-haul limited amounts of water in 19–121 L (5–32 gallon) containers by hand or with the assistance of a sled, wheelbarrow or vehicle. Families often supplement this treated water with water from traditional sources such as springs, tundra ponds, and rainwater(Reference Eichelberger20,Reference Ritter, Lopez and Goldberger21) .

Measures

We used self-reported SSB consumption and chronic disease measures from the BRFSS, for years 2013 and 2015. The BRFSS is a telephone survey that gathers data about the health behaviours of adults across the United States(22). In Alaska, rural areas are oversampled to enhance the adequacy of sample size for analysis. BRFSS participants are required to be 18 years of age or older. In this analysis, data were restricted to participants aged 25 years or older because education level was a confounder of interest, and this question is only answered by those who are 25 years or older. Answers to the following questions were used as outcomes(23):

‘During the past 30 d, how often did you drink regular soda or pop that contains sugar? Do not include diet soda or diet pop.’

‘During the past 30 d, how often did you drink sugar-sweetened fruit drinks (such as Kool-Aid and lemonade), sweet tea, and sports or energy drinks (such as Gatorade and Red Bull)? Do not include 100 % fruit juice, diet drinks, or artificially sweetened drinks.’

‘Would you say that in general your health is (Options: Excellent, Very good, Good, Fair, Poor)?’

A weekly estimate of the frequency of SSB consumption was calculated according to the BRFSS data usage recommendations(Reference Park and Pan24). Participants were assigned weight categories (neither overweight nor obese (BMI < 25 kg/m2), overweight (25 < BMI < 30 kg/m2), or obese (BMI > 30 kg/m2)) based on BMI calculated from participant-reported height and weight. Other variables of interest included reported annual household income (<$25 000, $25 000–$49 000, or >$50 000), formal education level (less than high school, high school graduate, or some college or higher), race, and age (in years).

We obtained 2016 water service data from the Alaska Infrastructure Programs, United States Environmental Protection Agency. BRFSS participants were categorized by zip code as having water piped to their home if their community had piped water either from a centralized water service or from wells. Participants were considered to not have piped water if their community had a closed haul system, a washeteria, or other community watering points where individuals bring their own water to their home(Reference Hickel, Dotson and Thomas25). Some zip codes included communities with differing water service status (‘mixed’ zip codes). For example, one zip code could include two small communities, one with an in-home piped water service and one without an in-home piped water service. In these instances, the zip code was attributed the water status of the community with the larger population.

All data were publically available.

Statistical analysis

We described participant demographics according to water service status based on their zip code. Reported percentages were survey-weighted according to the BRFSS weighting formula(26). Weights were provided in the BRFSS dataset. Before analysing the primary question, we developed a causal model to determine the minimum number of potential confounders in the relationship between residence in a community with piped water and SSB consumption. We used a survey-weighted log-linear generalized linear model (GLM) to compare the frequency of reported SSB consumption between participants in zip codes with and without an in-home piped water service. After assessing the univariable associations, we controlled for annual household income, formal education level, American Indian/Alaska Native race, and age. For the binary outcomes of obesity and fair/poor health, we used a survey-weighted log binomial GLM. After assessing univariable associations, we also controlled for age, sex, race, and income in the obesity analysis, and age, race, and income in the self-reported poor health analysis. Model outputs are expressed as exponentiated (exp) β, which we called a frequency ratio. A frequency ratio can be interpreted as the percentage higher or lower that one group reported drinking SSB per week compared with another group. Using α = 0·05, ratios were considered to be significant if the 95 % CI did not include 1. We conducted a sensitivity analysis by removing participants with mixed zip codes to identify whether these participants affected the model results. Data were analysed using SUDAAN (RTI International, NC).

Results

After excluding urban areas, hub communities, and communities on the state-wide road or marine highway system, 887 rural Alaskans over age 25 years participated in the 2013 and 2015 BRFSS. Slightly more participants were female (430, 52 %) and the mean age was 48 years. Of these participants, 733 (83 %) lived in 102 zip codes with piped water and 154 (17 %) lived in 28 zip codes without piped water. Among participants with in-home piped water, 43 % reported completing some college or higher education and 39 % reported household annual income of over $50 000 (Table 1). Among participants without in-home piped water, 27 % reported completing some college or higher education and 22 % reported household annual income of over $50 000 (Table 1).

Table 1 Characteristics of adult participants by in-home piped water access, rural Alaskaa, 2013 and 2015

Sum of data may not equal total due to missing values.

a Data were restricted to those participants who lived in communities that were not externally accessible by the state-wide road system or the Alaska Marine Highway ferry system and were not hub towns.

b SSB = Sugar-sweetened beverage.

Overall, 37 % of participants reported drinking SSB at least once per day, and participants reported drinking SSB a mean of 8·5 times per week. Participants in communities with in-home piped water reported a mean SSB consumption frequency of 7·8 times per week while participants in communities without in-home piped water reported a mean frequency of 12·5 times per week. Overall, those who reported higher frequency of SSB consumption were younger, had lower household income, and lower formal education (Table 2).

Table 2 Characteristics of adult participants by sugar-sweetened beverage consumption, rural Alaskaa, 2013 and 2015

Sum of data may not equal total due to missing values.

a Data were restricted to those participants who lived in communities that were not externally accessible by the state-wide road system or the Alaska Marine Highway ferry system and were not hub towns.

In the unadjusted model, respondents who lived in a community without in-home piped water reported consuming SSB 46 % more often than those who lived in a community with in-home piped water (unadjusted exp β 1·46, 95 % CI: 1·29, 1·67, P = 0·02). After adjustment for age, income, and education, the size of the effect decreased (adjusted exp β 1·29, 95 % CI: 1·00, 1·67, P = 0·05; Table 3).

Table 3 Generalized linear models of health outcomes and piped water service, rural Alaskaa, 2013 and 2015

a Data were restricted to those participants who lived in communities that were not externally accessible by the state-wide road system or the Alaska Marine Highway ferry system and were not hub towns.

b SSB = Sugar-sweetened beverage.

c Unweighted model sample size used in analysis.

In an unadjusted overall model, residence in a community without in-home piped water was not associated with obesity (adjusted exp β 1·22, 95 % CI: 0·81, 1·83, P = 0·36; Table 3). This did not change after adjustment for confounders. In unadjusted and adjusted models, participants in communities without in-home piped water were significantly more likely to report fair/poor general health (adjusted exp β 1·63, 95 % CI: 1·05, 2·54, P = 0·04).

Three zip codes with thirty-one participants were considered to have ‘mixed’ service. All three were coded as having in-home piped water based on the criteria listed above, but included some participants in communities with washeterias or watering points. In sensitivity analyses where we removed these zip codes, no meaningful changes were observed in the models described above (data not shown).

Discussion

Within the United States, rural Alaskans have the lowest access to an in-home piped water service and experience a concordantly high burden of infectious disease(Reference Hennessy, Ritter and Holman6). However, the burden of infectious disease might not capture the full picture of the outcomes of lack of water access within rural Alaska or elsewhere. We evaluated whether a lack of water service in rural Alaska was also associated with frequency of SSB consumption and chronic disease outcomes. We found that rural Alaskans who lived in communities without in-home piped water may consume SSB more frequently than those who lived in communities with an in-home piped water service. Our findings contribute to the growing literature on the non-infectious disease risk factors associated with inadequate access to reliable, clean, water within the home(Reference Wutich and Ragsdale8,Reference Geere, Bartram and Bates9,Reference Ennis-McMillan27) .

The linkage between lack of in-home water service and infectious disease risk in Alaska has been well described(Reference Bressler and Hennessy28). However, the relationship between in-home water service and SSB consumption is not well documented. There are several potential reasons that residents of communities without an in-home piped water service might drink SSB more often than those in communities with in-home piped water. Self-hauling water is time-consuming, and the amount brought into the home is often directly related to a household’s access to a vehicle and the presence of an able-bodied male household member(Reference Eichelberger29,Reference Eichelberger30) . If water is not easily accessible, people may decrease their water consumption and increase their consumption of other beverages. Recently, a quasi-experimental study in schools in New York City showed that providing accessible water jet dispensers led to decreases in student BMI, ostensibly due to the consumption of water rather than other beverages(Reference Schwartz, Leardo and Aneja31). However, more research is necessary to evaluate the precise reasons that residents of communities without an in-home piped water service consumed SSB more frequently than those in communities with in-home piped water.

In this analysis, frequency of SSB consumption was associated with age, household income, and education level. Other studies of SSB have found similar patterns, demonstrating that younger people, men, those with lower income, and those with less formal educational attainment are likely to drink SSB more frequently(Reference Park, Xu and Town14,Reference Bolt-Evensen, Vik and Stea32,Reference Mendy, Vargas and Payton33) . In rural Alaska, several factors could also influence the choice to drink SSB, regardless of water accessibility. For example, prior studies have shown that some residents in these communities distrust the safety of treated water and/or are not satisfied with its quality (including colour and taste)(Reference Eichelberger20,Reference Ritter, Lopez and Goldberger21) . Across the United States, trust of water sources has been shown to impact behaviour around water consumption, especially among minorities(Reference Javidi and Pierce34Reference Rosinger, Herrick and Wutich36). Therefore, rural residents might perceive that consuming beverages from bottles or cans is safer than consuming tap water. The use of sugar-sweetened mixes such as Tang could offer a more palatable way to consume treated water. Further, SSB may be cheaper than bottled water in these communities, possibly contributing to higher consumption.

Not having an in-home piped water service was not significantly associated with obesity in this analysis. Although the association between drinking SSB and obesity has been well-described in other contexts(Reference Ruanpeng, Thongprayoon and Cheungpasitporn15) there could be aspects of living in communities without piped water that are protective against weight gain. For example, in Yupik communities, hauling water is conducted primarily by men and boys and could serve as a form of physical activity(Reference Eichelberger20). Communities without piped water could also differ from those with piped water by other activities related to exercise and diet, such as the types and frequencies of hunting or other physically-demanding subsistence activities. Unfortunately we were not able to assess these other factors in the current analysis. Further research on obesity in communities without piped water is warranted.

Living in a community without in-home water was associated with a higher proportion of respondents reporting fair or poor general health in this analysis. This association could reflect that residents experienced a variety of poor health outcomes associated with lack of water access, including infectious diseases.

This analysis has a few limitations. First, these data sources are cross-sectional, which affects the interpretability of temporal associations. Second, there may be some misclassification of water service exposure on the individual level. For example, in communities that have a piped water system, some households might still use point water sources. Therefore, the exposure in this analysis only represents a community-wide exposure to water service infrastructure. Additionally, the BRFSS data are self-reported, so responses are subject to inaccuracies. For example, self-reported height and weight often result in an underestimate of obesity(Reference Yun, Zhu and Black37). However, we would not expect this underestimate to be differential between communities with and without piped water. Furthermore, the BRFSS requests information on the frequency of SSB consumption, but does not include an estimate of volume. Similarly, sugar-sweetened coffee drinks are not included in the measure. These issues could lead to a misrepresentation of the amount of SSB consumed, although we also do not expect this to be differential between communities. Additionally, although rural Alaska was oversampled in the BRFSS, the number of participants who were classified as living in a community without piped water was small. The small sample size likely resulted in insufficient power to detect some significant differences, and possibly the borderline significance in the overall result.

Confounding is an important consideration illuminated by this analysis. Respondents from communities with and without piped water were markedly different according to their reported demographics. Furthermore, the changes to the effect estimates after adjustment demonstrated that confounding by socio-economic status, age, and race existed in the association between piped water and drinking SSB. There may be residual confounding or additional confounding by other factors that were not measured. Accordingly, the associations seen here warrant further investigation in other datasets and prospective analyses.

Conclusions

Recent studies have shown that disparities exist across the United States in terms of clean tap water access and consumption(Reference Brooks, Gortmaker and Long38,Reference Stillo and MacDonald Gibson39) . Our analysis suggests that residents who lived in communities without in-home piped water may drink SSB more frequently than those who lived in communities with in-home piped water. Although lacking piped water was not significantly associated with obesity in this analysis, a higher frequency of SSB consumption could lead to a number of other chronic disease outcomes and may have contributed to the association between lack of water and reported poor health. Access to in-home clean water is a key component to maintain optimal health in rural Alaska.

Disclaimer

The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention/the Agency for Toxic Substances and Disease Registry. Use of trade names is for identification only and does not imply endorsement by the Public Health Service or by the US Department of Health and Human Services.

Acknowledgements

Acknowledgements: Not applicable. Financial support: This research received no specific grant from any funding agency, commercial or not-for-profit sectors. Conflicts of interest: None. Authorship: E.M., S.S., A.F., K.F., L.E., P.H., T.T., M.B. and T.H. conceptualized the study. S.S., A.F. and K.F. managed the study data. E.M., S.S. and P.H. conducted the analysis and wrote the manuscript. S.S., A.F., K.F., L.E., P.H., T.T., M.B. and T.H. reviewed and contributed to the manuscript. Ethics of human subject participation: Not applicable.

References

Progress on drinking water, sanitation, and hygiene: 2017 update and SDG baselines (2017) Geneva: WHO and UNICEF. Contract No.: License: CC BY-NC-SA 3.0 IGO.Google Scholar
Wolf, J, Pruss-Ustun, A, Cumming, Oet al. (2014) Assessing the impact of drinking water and sanitation on diarrhoeal disease in low- and middle-income settings: systematic review and meta-regression. Trop Med Int Health 19, 928942.CrossRefGoogle ScholarPubMed
Hossain, M, Choudhury, N, Adib Binte Abdullah, Ket al. (2017) Evidence-based approaches to childhood stunting in low and middle income countries: a systematic review. Arch Dis Child 102, 903909.CrossRefGoogle ScholarPubMed
Alaska Department of Health and Social Services (2017) Healthy Alaskans 2020 Scorecard. http://hss.state.ak.us/ha2020/assets/HA2020_Scorecard.pdf (accessed February 2018).Google Scholar
Thomas, TK, Ritter, T, Bruden, Det al. (2016) Impact of providing in-home water service on the rates of infectious diseases: results from four communities in Western Alaska. J Water Health 14, 132141.CrossRefGoogle ScholarPubMed
Hennessy, TW, Ritter, T, Holman, RCet al. (2008) The relationship between in-home water service and the risk of respiratory tract, skin, and gastrointestinal tract infections among rural Alaska natives. Am J Public Health 98, 20722078.CrossRefGoogle ScholarPubMed
Bulkow, LR, Singleton, RJ, DeByle, Cet al. (2012) Risk factors for hospitalization with lower respiratory tract infections in children in rural Alaska. Pediatrics 129, e1220e1227.CrossRefGoogle ScholarPubMed
Wutich, A & Ragsdale, K (2008) Water insecurity and emotional distress: coping with supply, access, and seasonal variability of water in a Bolivian squatter settlement. Soc Sci Med 67, 21162125.CrossRefGoogle Scholar
Geere, JA, Bartram, J, Bates, Let al. (2018) Carrying water may be a major contributor to disability from musculoskeletal disorders in low income countries: a cross-sectional survey in South Africa, Ghana and Vietnam. J Glob Health 8, 010406.CrossRefGoogle Scholar
Eichelberger, L, Murphy, G, Etemadi, Aet al. (2015) Risk of gastric cancer by water source: evidence from the Golestan case-control study. PloS one 10, e0128491.CrossRefGoogle ScholarPubMed
Sarkar, A, Hanrahan, M & Hudson, A (2015) Water insecurity in Canadian Indigenous communities: some inconvenient truths. Rural Remote Health 15, 3354.Google ScholarPubMed
Services. UDoHaH, Agriculture. UDo (2015) 2015–2020 Dietary Guidelines for Americans. UDoHaH.Google Scholar
Prevention. CfDCa (2017) Get the Facts: Sugar-Sweetened Beverages and Consumption. CfDCa. Available from: https://www.cdc.gov/nutrition/data-statistics/sugar-sweetened-beverages-intake.html.Google Scholar
Park, S, Xu, F, Town, Met al. (2016) Prevalence of sugar-sweetened beverage intake among adults--23 states and the district of Columbia, 2013. MMWR Morb Mortal Wkly Rep 65, 169174.CrossRefGoogle ScholarPubMed
Ruanpeng, D, Thongprayoon, C, Cheungpasitporn, Wet al. (2017) Sugar and artificially sweetened beverages linked to obesity: a systematic review and meta-analysis. QJM 110, 513520.CrossRefGoogle ScholarPubMed
Greenwood, DC, Threapleton, DE, Evans, CEet al. (2014) Association between sugar-sweetened and artificially sweetened soft drinks and type 2 diabetes: systematic review and dose-response meta-analysis of prospective studies. Br J Nutr 112, 725734.CrossRefGoogle ScholarPubMed
Schwingshackl, L, Schwedhelm, C, Hoffmann, Get al. (2017) Food groups and risk of hypertension: a systematic review and dose-response meta-analysis of prospective studies. Adv Nutr 8, 793803.CrossRefGoogle ScholarPubMed
Bernabe, E, Vehkalahti, MM, Sheiham, Aet al. (2014) Sugar-sweetened beverages and dental caries in adults: a 4-year prospective study. J Dent 42, 952958.CrossRefGoogle ScholarPubMed
Elwan, D, Schweinitz, P & Wojcicki, JM (2016) Beverage consumption in an Alaska Native village: a mixed-methods study of behaviour, attitudes and access. Int J Circumpolar Health 75, 29905.CrossRefGoogle Scholar
Eichelberger, L (2017) Household water insecurity and its cultural dimensions: preliminary results from Newtok, Alaska. Environ Sci Pollut Res Int 25, 3293832951.CrossRefGoogle ScholarPubMed
Ritter, TL, Lopez, ED, Goldberger, Ret al. (2014) Consuming untreated water in four southwestern Alaska Native communities: reasons revealed and recommendations for change. J Environ Health 77, 813.Google Scholar
Centers for Disease Control and Prevention. About BRFSS 2014. Available from: https://www.cdc.gov/brfss/about/index.htm.Google Scholar
Centers for Disease Control and Prevention. BRFSS Questionnaires 2013. Available from: https://www.cdc.gov/brfss/questionnaires/index.htm.Google Scholar
Park, S & Pan, L (2013) A Data User’s Guide to the BRFSS Sugar-Sweetened Beverage Questions: How to Analyze Consumption of Sugar-Sweetened Beverages. Centers for Disease Control and Prevention.Google Scholar
Hickel, KA, Dotson, A, Thomas, TKet al. (2017) The search for an alternative to piped water and sewer systems in the Alaskan Arctic. Environ Sci Pollut Res Int 25, 3287332880.CrossRefGoogle ScholarPubMed
Centers for Disease Control and Prevention (2013) BRFSS 2013 Survey Data and Documentation. Available from: https://wwwdev.cdc.gov/brfss/annual_data/annual_2013.html.Google Scholar
Ennis-McMillan, MC (2001) Suffering from water: social origins of bodily distress in a Mexican Community. Med Anthropol Q 15, 368390.CrossRefGoogle Scholar
Bressler, JM & Hennessy, TW (2018) Results of an Arctic Council survey on water and sanitation services in the Arctic. Int J Circumpolar Health 77, 1421368.CrossRefGoogle ScholarPubMed
Eichelberger, L (2010) Living in utility scarcity: energy and water insecurity in Northwest Alaska. Am J Public Health 100, 10101018.CrossRefGoogle ScholarPubMed
Eichelberger, LP (2011) Manufacturing Insecurity: Power, Water, Waste, and the Silences of Sustainability and Suffering in Northwest Alaska. ProQuest Dissertations Publishing. Tucson, AZ: University of Arizona.Google Scholar
Schwartz, AE, Leardo, M, Aneja, Set al. (2016) Effect of a school-based water intervention on child body mass index and obesity. JAMA Pediatr 170, 220226.CrossRefGoogle ScholarPubMed
Bolt-Evensen, K, Vik, FN, Stea, THet al. (2018) Consumption of sugar-sweetened beverages and artificially sweetened beverages from childhood to adulthood in relation to socioeconomic status - 15 years follow-up in Norway. Int J Behav Nutr Phys Act 15, 8.CrossRefGoogle ScholarPubMed
Mendy, VL, Vargas, R, Payton, Met al. (2017) Association between consumption of sugar-sweetened beverages and sociodemographic characteristics among Mississippi adults. Prev Chronic Dis 14, E137.CrossRefGoogle ScholarPubMed
Javidi, A & Pierce, G (2018) U.S. households’ perception of drinking water as unsafe and its consequences: examining alternative choices to the tap. Am Geophys Union 54, 610061013.Google Scholar
Pierce, G & Gonzalez, S (2016) Mistrust at the tap? Factors contributing to public drinking water (mis)perception across US households. Water Policy 19, 112.CrossRefGoogle Scholar
Rosinger, AY, Herrick, KA, Wutich, AYet al. (2018) Disparities in plain, tap and bottled water consumption among US adults: National Health and Nutrition Examination Survey (NHANES) 2007–2014. Public Health Nutr 21, 14551464.CrossRefGoogle ScholarPubMed
Yun, S, Zhu, BP, Black, Wet al. (2006) A comparison of national estimates of obesity prevalence from the behavioral risk factor surveillance system and the National Health and Nutrition Examination Survey. Int J Obes (2005) 30, 164170.CrossRefGoogle ScholarPubMed
Brooks, CJ, Gortmaker, SL, Long, MWet al. (2017) Racial/ethnic and socioeconomic disparities in hydration status among us adults and the role of tap water and other beverage intake. Am J Public Health 107, 13871394.CrossRefGoogle ScholarPubMed
Stillo, F & MacDonald Gibson, J (2017) Exposure to contaminated drinking water and health disparities in North Carolina. Am J Public Health 107, 180185.CrossRefGoogle ScholarPubMed
Figure 0

Table 1 Characteristics of adult participants by in-home piped water access, rural Alaskaa, 2013 and 2015

Figure 1

Table 2 Characteristics of adult participants by sugar-sweetened beverage consumption, rural Alaskaa, 2013 and 2015

Figure 2

Table 3 Generalized linear models of health outcomes and piped water service, rural Alaskaa, 2013 and 2015