https://orcid.org/0009-0004-1987-3706
Figures
Abstract
Drinking water access and water and food insecurity have been linked to mental well-being, but few studies have comprehensively assessed potential pathways linking these associations. Understanding these mediation pathways is particularly important among pregnant women, as prenatal stress and poor mental well-being have been shown to negatively impact fetal development. In this study, we address this gap by analyzing the relationships between drinking water source and water and food insecurity with mental well-being amongst pregnant women living in low-income, urban neighborhoods of Beira, Mozambique. Data for this cross-sectional analysis were collected among third-trimester, pregnant women (n = 740) from February 2021 through October 2022 as part of a matched cohort study. Validated, cross-cultural measures of mental well-being and household water and food insecurity were administered in the survey. Drinking water source was determined by presence of a household drinking water source on-premises. We used logistic regression to characterize the associations between drinking water source, water and food insecurity, and mental well-being and causal mediation analysis to determine mediation by food and water insecurity along these pathways. We found evidence that water insecurity (OR 1.44; 95%CI 1.02, 2.02) and food insecurity (OR 2.27; 95%CI 1.57, 3.34) were individually associated with adverse mental well-being. Drinking water source was not associated with mental well-being (OR 1.00; 95%CI 0.71, 1.39), water insecurity (OR 0.86; 95%CI 0.60, 1.24), or food insecurity (OR 1.02; 95%CI 0.71, 1.47). Food insecurity may also mediate the relationship between water insecurity and mental well-being (ACME 0.05; 95%CI 0.02, 0.07; ADE 0.04; 95%CI -0.04, 0.13). Our findings support growing literature that water and food insecurity are important to mental well-being, a key aspect of overall health. Further research is needed to confirm causality along these pathways and determine specific mechanisms through which these interactions take place.
Citation: O’Brien LA, Snyder JS, Garn JV, Kann R, Júnior A, McGunegill S, et al. (2024) Water, food, and mental well-being: Associations between drinking water source, household water and food insecurity, and mental well-being of low-income pregnant women in urban Mozambique. PLOS Water 3(6): e0000219. https://doi.org/10.1371/journal.pwat.0000219
Editor: Sonia Ferdous Hoque, University of Oxford, UNITED KINGDOM
Received: January 2, 2024; Accepted: May 11, 2024; Published: June 20, 2024
Copyright: © 2024 O'Brien et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: Deidentified data and analysis code can be accessed on our project OSF (Open Science Framework) site upon publication at this link: https://osf.io/e96wd/.
Funding: This work was supported by National Institute of Allergy and Infectious Diseases (NIAID) Grant #R01AI130163 (KL, MF, JG). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Approximately one-third of the global urban population currently faces water scarcity, and this proportion is expected to grow to almost half by 2050, aided by increasing urbanization [1]. Population growth in expanding towns and cities often outpaces the rate of infrastructure development, leaving unplanned and overcrowded settlements without sufficient water and sanitation infrastructure [2]. Food insecurity is also increasing alongside urbanization due to food system adjustments and intra-urban, income-based disparities [3, 4]. While inadequate drinking water and food access have implications on individual physical health [5, 6], growing evidence has also identified linkages between water and food access and mental health [6–12]. The World Health Organization (WHO) defines health as “a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity” [13]. Mental well-being is an integral part of overall health, and thus it is necessary to consider its role when determining the impact of water access on overall health and quality of life.
The burdens of household water management and the toll of mental health are not equally distributed; domestic water supply responsibilities—and the corresponding increased mental load—are disproportionately allocated to women and girls [7, 14–23]. When clean, piped water is not available at the household in sufficient quantity, household members, predominantly women, sacrifice time, money, energy, and water quality to secure water from alternate sources [9, 24]. Engaging in water gathering activities can increase one’s risk for infection and disease, physical injuries, and decreased mental well-being [9, 23–27]. For example, in a low-income, urban area of Bolivia, stressful water-related experiences were associated with increased negative emotional impacts for household heads, and female household heads had both a higher responsibility for water-related housework and a greater degree of related emotional distress than male household heads [14, 15].
Water insecurity is defined as “the inability to access and benefit from adequate, reliable and safe water for well-being and a healthy life” [28]. A household’s level of water insecurity may be influenced, but not solely defined, by their water supply source. For example, the presence of a piped water source on a household’s premises has been associated with reducing, although not eliminating, household water insecurity [29]. Mental well-being effects of household water insecurity often include increased levels of anxiety, depression, and psychosocial distress, especially in women [30–34]. Thus, reducing household water insecurity through improving access to a drinking water source may have the potential to reduce adverse well-being beyond a reduction in ingestion of enteric pathogens.
Similar to water insecurity, food insecurity has been associated with adverse mental health indicators such as anxiety, depression, and frequency of negative emotions [6, 35–37]. Associations between food insecurity and mental health outcomes have also been found specifically in pregnant women across many settings [38–41]. The relationship between food insecurity and water insecurity is well-established [31]. Evidence from 27 sites in low- and middle-income countries suggests that the most plausible directionality of the relationship is that water insecurity is a driver of food insecurity [31]. As illustrated by a community intervention that installed household piped water sources at some households in a Kenyan village, those with piped water reported reduced water insecurity and increased water expenditure savings, and a majority spent those savings on food [29].
Quantifying the relationships between drinking water improvements and less tangible outcomes such as mental well-being and water and food insecurity experiences can inform programs and policies that facilitate health equity, particularly for women and children. Prioritizing mental well-being during pregnancy is critical, as the rates of depressive symptoms have been reported to be higher during pregnancy when compared to rates observed before pregnancy [42]. Further, prenatal stress, anxiety, and overall poor mental well-being have been associated with negative impacts on fetal and child development [43–46], so efforts to improve mental well-being during pregnancy can be understood as important preventative interventions for the developing child.
The relationships between drinking water source, water and food insecurity, and mental well-being are complex and intrinsically interrelated. Prior work in this area has established individual linkages between these factors [6, 8, 29–37], without assessing the interactions between more than two factors among pregnant women at a time. We carried out a comprehensive and simultaneous study of these relationships, using validated, cross-cultural indicators to explore the relationships between drinking water source, water and food insecurity, and mental well-being amongst pregnant women in low-income, urban neighborhoods of Beira, Mozambique. This area has experienced concerns related to water and food access recently, alongside potentially elevated levels of common mental health disorders [47–49]. This backdrop underlines the relevance and importance of exploring these relationships here. In this study, we investigated the following questions: (1) Are household drinking water source, water insecurity, and food insecurity each independently associated with prenatal mental well-being? (2) Is there potential mediation by water or food insecurity between drinking water source and prenatal mental well-being? (3) Is there potential mediation by food insecurity between water insecurity and prenatal mental well-being?
Methods
We conducted a cross-sectional analysis to evaluate the associations of drinking water source and water and food insecurity with mental well-being amongst pregnant women in Beira, Mozambique. We used data collected from a matched cohort study titled “PAASIM (Pesquisa Sobre o Acesso à Água e a Saúde Infantil em Moçambique—Research on Access to Water and Children’s Health in Mozambique).” The PAASIM study was designed to assess the health impacts of piped water supply on young children in low-income, urban neighborhoods of Beira, Mozambique; the study protocol contains additional details of the study [50]. Briefly, this prospective matched cohort study follows mother-child dyads from late pregnancy through 12 months of age to examine the impact of water system improvements on acute and chronic health outcomes in children.
Ethics statement
The study was approved by the Mozambique National Bio-Ethics Committee for Health (Ref: 105/CNBS/20) and the Institutional Review Board of Emory University (IRB#: CR001-IRB00098584, Atlanta, GA). In addition, we obtained permissions from local authorities, namely Beira municipality and municipal district administrations from study neighborhoods included in the study. Credential letters were issued to be presented in all sub-neighborhoods and households visited. Additionally, courtesy meetings between the study team and city health department were held. Recruitment and consent of subjects took place at the households. Prior to enrollment, study staff fully explained and carried out the consent process and documented the procedure. Subjects provided written consent with a signature. In the case of illiteracy of the subject, study staff verbally summarized the material with the subject, and the participants were required to provide written consent by marking the document with a thumbprint.
Study site
Mozambique is considered a least developed country by the WHO/UNICEF Joint Monitoring Programme (JMP), and it has substantial progress to be made toward universal access to basic drinking water sources [51, 52]. In urban areas of Mozambique, 88% of the population has access to at least basic services, but only 65% of the urban population has an improved drinking water source on-premises. The people in the richest wealth quintile have access to basic drinking water services in urban areas at a proportion 1.8 times higher than the people in the poorest wealth quintile, indicating a significant wealth gap [51]. Over half of the urban population in Mozambique live in low-income, high-density neighborhoods where these wealth gaps are most evident [53].
Beira is the capital of the Sofala Province and is a rapidly growing port city with an estimated population of 600,000 people [54]. Its location on the coast has rendered it highly vulnerable to increasingly frequent cyclones and flooding, a trend driven by climate change [55]. Over 300,000 low-income residents inhabit neighborhoods that often occupy flood zones to the north and east of the planned city [49, 50]. These impoverished, densely populated neighborhoods have the most difficulty recovering from the cyclones and flooding, resulting in further stress being placed on their food systems and drinking water sources [56, 57].
As of December 2019, 48% of households in low-income neighborhoods in Beira reported having a household water connection, 42% used a neighbor’s piped water as their main source, and the remaining 12% used public tap, unprotected well, borehole, bottled water, or other sources. Satisfaction with water services in these low-income neighborhoods was found to be inversely proportional to the intermittency in water supply and the distance from a water main, but satisfaction was not associated with household connection status. Residents are able to request a household water connection to a piped water source and pay for water service through Water-Supply Asset Holding and Investment Fund (FIPAG) [55]. Projects are underway to improve piped water supply throughout Beira including the Water Service & Institutional Support (WASIS-II) project funded by the World Bank in 2016. It aims to increase access to improved water supply in Mozambique through investing with Mozambican public water institutions, including FIPAG [58].
Food insecurity is widespread in Beira, with over 70% of the population experiencing moderate to severe food insecurity. Residents primarily purchase their food at informal and formal markets. The infrastructure and supply chains of these urban markets were impacted by both cyclones and COVID-19, affecting the location, hours of operation, and availability and diversity of food [48].
The overall prevalence of common mental disorders measured by a research study in Beira was reported to be 24% among patients visiting large Ministry of Health facilities. This was slightly higher than the global average of 21%. The most common diagnosis was generalized anxiety disorder followed by major depressive disorder [47]. A vast majority of these cases go undiagnosed as the current mental healthcare system does not currently have sufficient capacity, but efforts to expand mental healthcare systems in Mozambique are currently ongoing [59, 60].
The PAASIM study’s primary aim is to determine the impact of ongoing water supply improvements on the enteric health of newborn infants in low-income neighborhoods [50, 61]. The neighborhoods chosen for the PAASIM study area comprised approximately 26,300 households, and we targeted recruitment of 900 pregnant women in the third trimester from low-income neighborhoods.
Study design
Data were gathered from the PAASIM study’s enrollment survey. Structured household surveys were conducted at enrollment of pregnant mothers (February 19th, 2021 to October 7th, 2022). We used the surveys to collect information about the participants’ individual and household demographics, drinking water source, household water insecurity, household food insecurity, and maternal mental well-being. Active recruitment occurred through identification of pregnant women in the 2020 population-based survey, lists of pregnant women visiting local health centers for prenatal care, and study staff visiting under-enrolled sub-neighborhoods throughout the recruitment period [50]. During a recruitment visit, pregnant women were assessed for the following study eligibility criteria: (1) 18 years or older; (2) in third trimester of pregnancy (at least 27 weeks pregnant); (3) resides in enrolled study neighborhood; (4) not planning to move within the next 12 months; (5) carrying a singleton birth; and (6) consents to take part in the study. The enrollment survey was conducted during recruitment if the consenting participant was at least 31 weeks pregnant, otherwise, a follow-up visit was scheduled to complete the survey. In some instances, the child was born before the scheduled enrollment visit took place or the pregnancy was lost. For this sub-study, we limited our analysis to those with data collected during a prenatal enrollment visit and those with complete data on measures of mental well-being and household water and food insecurity. Of 897 pregnant participants enrolled in the study, 740 met eligibility criteria and had complete data (Fig 1).
The exclusion criteria of “incomplete data” indicates that an eligible participant refused to answer one or more of the questions used for the validated scales.
Primary outcome variable
Mental well-being was assessed using the WHO-5 Well-being Index [62], a well-established, globally validated index measure. The English and Portuguese versions of the questionnaire are published online [63]. It uses five non-invasive questions to determine the participant’s subjective psychological well-being. Each question asks the participant how often within the past two weeks, ranging from “at no time” (0) to “all of the time” (5), they related to a given statement of positive well-being. Question scores are added together and multiplied by 25. An overall score of 100 indicates the best possible well-being, and a score of 0 indicates the worst possible well-being. This scale score will be assessed as a binary variable, with scores of 50 or less indicating adverse mental well-being. This cut-off point is recommended when screening for clinical depression and is in accordance with recent literature [62].
Predictor variables
Drinking water source was categorized as a binary variable (no source on-premises vs source on-premises). ‘On-premises’ was defined as the presence of a drinking water source on a household’s premises (within the property boundaries of their primary residence and not owned or controlled by neighbors) [64]. Participants provided information on the main source of drinking water for members of the household and the location of the drinking water source (i.e., inside or outside of the household’s compound), determined by their response to the survey question: “What is the main source of drinking water for members of your household?” This question was derived from indicators outlined by WHO/UNICEF JMP [65]. Those that indicated their source was “piped water into the dwelling” or “piped water to yard/plot” were designated as having a drinking water source on-premises. Those that indicated their source was piped water from a neighbor, piped water from a public tap/standpipe, bottled water, a tubewell/borehole, or an unprotected well were designated as having no drinking water source on-premises.
Water insecurity was assessed using the Household Water Insecurity Experiences (HWISE) Scale [28]. The scale was developed and validated to provide a consistent tool for evaluating lived experiences of household water insecurity across different cultural and ecological settings. The scale uses twelve questions that ask the participant how often within the past four weeks, ranging from “never” (0) to “always” (3), they or anyone in their household had a water insecurity experience. An overall score of 36 indicates the highest possible level of water insecurity. This was assessed as a binary variable, where scores at or above 12 indicate household water insecurity and scores less than 12 indicate household water security [66]. For the remainder of this paper, we refer to household water insecurity as “water insecurity.” The specific questions and further details of the scale are available in the user guide [67].
Food insecurity was assessed using the Household Food Insecurity Access Scale (HFIAS) [68]. The scale uses eight questions to determine how often within the past four weeks they or anyone in their household had a food insecurity experience. The answer scale ranges from “No” (0) to “Often” (3). A score of 27 indicates the highest possible level of food insecurity. For HFIAS, there has not been an established standard cutoff point. However, an HFIAS indicator guide provided conditional equations to determine if the respondent was “food secure,” “mildly insecure,” “moderately insecure,” or “severely insecure.” Upon completing exploratory data analyses comparing continuous versus binary classifications of HFIAS, we concluded that a binary variable classifying “food secure” and “mildly insecure” as "secure" and “moderately insecure” and “severely insecure” as “insecure” produced results similar to HFIAS represented on a continuous scale. The presentation of moderate and severe food insecurity together aligns with reporting by the Food and Agriculture Organization of the United Nations [69]. For the remainder of this paper, we refer to household food insecurity as “food insecurity.” The specific questions and further details of the scale are available in the user guide [68].
Covariates
Covariates were considered in each model. Because hydrological seasons have the potential to affect water insecurity, seasonality was included as a covariate [70]. The month that the survey was administered in was used to determine the seasonality, with November through April being the hot, rainy season and May through October being the cool, dry season [71]. The primary household wage earner was included as a binary variable (the participant is the primary wage earner versus not). Wealth score, or socio-economic status (SES), was included as a continuous variable. Respondents answered ten standardized questions from the Simple Poverty Scorecard Poverty-Assessment Tool Mozambique, including questions on household size, materials, and assets [72]. Each question’s answer choices correspond with a point total, and points are summed over all ten questions into a poverty score. The age of the participant (continuous), number of living children (discrete), participant’s level of education (dichotomous; completed secondary school or above versus completed some secondary school and below), and the impact of preexisting, chronic health conditions and previous infectious diseases (dichotomous; one or more relevant conditions is present versus none) were also included as covariates.
Statistical analyses
Regression models were created to determine the relationships between drinking water source, water insecurity, food insecurity, and mental well-being, as displayed in Fig 2, using R statistical software (RStudio v. 4.3.1) [73]. All models adjusted for the seasonality, SES, age, education completed, and previous diagnosis of an infectious disease, a priori selected based on their relevance and univariate relationships to the main predictor and outcome variables (S1 Table).
The relationships evaluated are (question 1) drinking water source, water insecurity, and food insecurity with mental well-being, (question 2) potential mediation (mediation indicated by dotted line) of water and food insecurity on the relationship between drinking water source and mental well-being and (question 3) potential mediation of food insecurity on the relationship between water insecurity and mental well-being.
We assessed if water and food insecurity, represented on continuous scales, were associated with mental well-being score to determine the consistency of the chosen binary cutoff points. The continuous models produced highly similar results to the binary representations (S2 and S3 Tables). We use binary versions of water and food insecurity for homogeneity in statistical estimates (odds ratios) and, for cohesion in reporting, designate the presence of drinking water source, water security, food security, and positive mental well-being as the model reference levels.
For question 1, each predictive factor (drinking water source, water insecurity, and food insecurity) was investigated individually for its direct relationship with mental well-being using binary general linear model (GLM) frameworks. Estimates were reported in the form of odds ratios with their corresponding confidence intervals and p values, assessed at the 0.05 alpha level.
To ensure suitability for the mediation analyses of questions 2 and 3, we first looked at whether there was a direct effect using binary general linear model (GLM) frameworks. One model was created between the predictor and the outcome and one between the predictor and the mediator. Criteria were met to continue forward with mediation analysis if direct effects in both models were present, or a direct effect between the predictor and outcome was not present but an effect between the predictor and mediator was present. However, if direct effects were not present in either model, mediation analysis was not possible [74]. Based on the individual pathway GLMs, mediation relationships were assessed using the “mediation” R package [75]. The “mediation” package uses a causal mediation analysis approach that provides causal effect estimates and is recommended for use in correct interpretation of mediation effects in structural equation models. The significance of the mediation analysis indirect effect was tested with bootstrapping procedures, computing 1000 bootstrapped samples.
The directionality of the mediation analysis in question 3 was derived from previous evidence of a temporal relationship where water insecurity and food insecurity where water insecurity had a predictive effect on food insecurity, but there were no predictive effects in the reverse [31, 76].
Results
The composition of the 740 pregnant women included in our analysis is shown in Table 1. The surveys were conducted in a relatively even distribution between the cool, dry season (44%) and the hot, rainy seasons (56%). A majority of our participants reported positive well-being (64%) and water security (75%); however, a majority also reported not having a drinking water source on-premises (65%) and being food insecure (74%) (Table 1). 174 participants reported to be both water insecure and food insecure (24%), 371 participants reported to be food insecure only (50%), and 11 reported to be water insecure only (1.5%).
Question 1: Associations of household drinking water source, water insecurity, and food insecurity with prenatal mental well-being
We found no evidence of a direct association between having an off-premises drinking water source and adverse mental well-being (OR 1.00; 95%CI 0.71, 1.39; Table 2). Water insecure households had 1.44 higher odds (OR 1.44; 95%CI 1.02, 2.02; Table 2) of adverse mental well-being, compared to water secure households. Food secure households had 2.27 higher odds (OR 2.27; 95%CI 1.57, 3.34; Table 2) of adverse mental well-being, compared to food secure households.
Question 2: Potential mediation of water and food insecurity on the relationship between drinking water source and prenatal mental well-being
We found no association between having an off-premises drinking water source and water insecurity (OR 0.86; 95%CI 0.60, 1.24; Table 3), nor between having an off-premises drinking water source and food insecurity (OR 1.02; 95%CI 0.71, 1.47; Table 3) (S4 Table). Mediation analysis by water insecurity and food insecurity as an intermediate between drinking water and mental well-being could not take place due to lack of associations between the predictor and outcome and predictor and mediators.
Question 3: Potential mediation of food insecurity on the relationship between water insecurity and mental well-being
The association between water insecurity and mental well-being was mediated by food insecurity. Water insecurity was associated with adverse mental well-being (path c; total effect) when the effects of food insecurity were not taken into account (OR 1.44; 95%CI 1.02, 2.02; Table 2, Fig 3). We found associations between water insecurity and food insecurity (path a) (OR 8.40; 95%CI 4.62, 16.90; Fig 3) and food insecurity and mental well-being (path b) (OR 2.17; 95%CI 1.48, 3.23; Fig 3). When food insecurity was included in the model of the association of water insecurity and mental well-being, there was no direct effect of water insecurity on mental well-being (path c’) (OR 1.18; 95%CI 0.83, 1.69; Fig 3) (S5 Table). The presence of indirect effects (ACME 0.04; 95%CI 0.02, 0.07) but no direct effects (ADE 0.04; 95%CI -0.04, 0.12) calculated through causal mediation analysis indicate the presence of full mediation. Over half of the relationship between water insecurity and mental well-being was due to the indirect path through food insecurity (PM 0.54; 95%CI 0.14, 3.10).
The figure shows odds ratios with 95% confidence intervals (*p<0.05, **p<0.001).
Discussion
The relationships between drinking water source, water and food insecurity, and mental well-being are complex and intrinsically linked. In this study, we evaluated these relationships in a single context for pregnant women in an urban, low-income setting, and we first found a strong association between food insecurity and decreased mental well-being. Water insecurity was also found to be related to mental well-being, but the relationship may be entirely mitigated by the effects of food insecurity on mental well-being and of water insecurity on food insecurity. The presence of a drinking water source on- or off-premises in this urban, low-income setting did not appear to have an impact on other factors. This study adds to the growing literature that supports the influence of water and food insecurity on mental health—an important component of overall well-being—and extends beyond the physical implications associated with exposure to enteropathogens.
We found a strong association between food insecurity and mental well-being. Food insecurity was highly prevalent; 74% of the women in our study population reported having moderate or severe food insecurity. This percentage aligns with the average prevalence of moderate and severe food insecurity among the adult female population in all of Mozambique from 2020 to 2022, which was 75.4%, as measured by the Food Insecurity Experience Scale (FIES) [69]. Participants with moderate to severe food insecurity were over two times as likely to have adverse mental well-being compared to those with no or mild food insecurity. This relationship is consistent with existing literature [6, 8, 35–40, 77, 78], and it is especially acute as our population consisted of pregnant women. Consequences of poor mental well-being in pregnant mothers include potential negative impacts on the fetus such as reduced fetal weight gain, head and abdominal growth, increased fetal distress, abnormalities, preterm birth, and even increased rates of fetal death [43–45, 79–81]. Over 70% of our pregnant participants already had other children which brings up the potential role of “maternal nutritional buffering.” This concept highlights that mothers will often reduce their own food intake in order to provide their children with more nutrition in periods of food insecurity [82]. Undernutrition during pregnancy can have severe effects such as anemia, hemorrhage, and death in mothers, and fetal growth and developmental delays in the child [83]. Our findings support that action plans to improve maternal mental well-being would likely benefit from incorporating strategies to reduce food insecurity among pregnant mothers, resulting in the prevention of adverse fetal and child development outcomes [8, 84].
Individually, water insecurity, an expansion of the concept of water access, was found to have an association with adverse mental well-being. This individual association aligns with existing literature on the impact of water insecurity on stress, anxiety, depression, and other adverse mental well-being indicators [9, 26, 30–33]. However, that relationship was entirely mitigated, statistically, by the inclusion of food insecurity in the pathway. This pragmatically suggests that food insecurity may have a more direct relationship with mental well-being than water insecurity in our study population of pregnant women. There is limited evidence on the explanations for this mediation in the literature, but we hypothesize that this association may stem from the greater presence of food insecurity than water insecurity in this context. Three times as many participants were food insecure than water insecure, and few participants were water insecure but not food insecure. Our findings suggest that food insecurity may be a significantly larger stressor to our population than water insecurity, but the level of food insecurity and subsequent mental well-being impact can be exacerbated by water insecurity. This may account for the more direct influence on mental well-being by food insecurity.
The directional association found between water insecurity and food insecurity in the mediation analysis highlights the close ties between these basic material needs among pregnant women. Our findings confirm those from Collins et al. (2019) in which their pregnant and post-natal participants discussed that, during times when they needed to purchase water, they prioritized spending their money on water, and the remaining amount was spent on food [9]. Conversely, money savings from reduced water insecurity have been reported to be spent on more food [29]. Further understanding of the details in this association is likely to be highly context-dependent. In Beira, staple foods are xima (cornmeal) and rice, and both of these foods need sufficient water in order to cook thoroughly [85]. Interviews with low-income individuals in other countries revealed that when a household is lacking sufficient water, they may not be able to cook enough food [14, 86, 87]. Alternatively, they may buy other, potentially more expensive or less desirable, foods that are less reliant on water [86, 87]. Additional evidence could help inform which interventions are likely to alleviate food insecurity by accounting for the role water insecurity plays in individual communities. To address this, the HWISE Research Coordination Network has a current project, “WI>FI,” that is exploring under which specific conditions food insecurity is driven by water insecurity [88].
A similar mediation relationship has been established in Haiti, though food insecurity only accounted for partial mediation, noting that different mental well-being indicators, household water security measurements, and an abbreviated version of the HFIAS scale were used [8]. Their study population consisted of low-income, vulnerable households that were both female and male-headed whereas ours focused specifically on the also vulnerable population of low-income pregnant women. The authors specifically emphasized that their study would have benefited from a multidimensional and cross-cultural tool for household water insecurity, which our study has accordingly benefited from with the use of the recently validated HWISE scale. Nevertheless, their findings, and ours, support the notion that water insecurity may be a foundation from which other poverty-related stressors, for example food insecurity, and their mental well-being effects emerge [8]. Our mediation analysis did not show a direct effect of water insecurity on mental health, but that does not mean interventions to improve water insecurity would fail to impact mental well-being. The causal mediation findings—with the support of existing literature—can be interpreted to say that water insecurity may be a significant driver of food insecurity, which is subsequentially associated with mental well-being.
Other studies have included food insecurity as a confounder—rather than as a mediator—in the relationship between water insecurity and mental well-being, and they found an independent association between water insecurity and mental well-being was still present after the inclusion of food insecurity [26, 32, 33, 77]. Though water insecurity’s relationship with mental well-being was not fully reduced when food insecurity was controlled for in these studies, partial mediation by food insecurity could still be present. Further analyses in these studies would be needed to determine the alignment with our study findings, but we suggest that in future studies, researchers should consider food insecurity as a potential mediator in relation to water insecurity.
The lack of associations between drinking water source and other factors, contrary to our initial hypothesis, may be due to the limited variation in drinking water sources among our study population. A previously cited study in Kenya reported that having drinking water on-premises was associated with reduced water insecurity [29]. However, the site was in a rural village where approximately 40% of the community used the local lake as their main drinking water source. Meanwhile, over 90% of our participants had access to a piped water source on either their own or a neighbor’s household premises. An initial assessment of satisfaction with water services in our study area revealed no differences in satisfaction based on household water connection status [89]. The assessment of “satisfaction” conceptually pairs well with our results that drinking water supply on-premises does not show an impact on one’s water insecurity or mental well-being. Our results support the notion that water access is more complex than the proximal location of a drinking water source to one’s place of residence.
Our findings should be interpreted in the context of the study’s limitations. First, our study was cross-sectional, so we were only able to establish associations, not causality. The causal mediation analysis does support causality in the mediation pathway, but it cannot be used to establish causality on its own. Longitudinal studies on these relationships, ideally paired with interventions aimed at reducing water and food insecurity, would give a more conclusive understanding of these pathways. Second, our survey relied on self-reported responses and may therefore be subject to social desirability bias. Where possible, enumerators aimed to gain trust with participants and conduct surveys in safe locations to reduce the potential for bias. Given the requirement for the PAASIM study, this cross-sectional analysis utilizes data collected over 1.5 years, spanning both rainy and dry seasons. Though we controlled for seasonality in our analyses, the reliability and generalizability of our findings are reinforced by this extended data collection period. The validity and consistency of this data are also strengthened by the usage of cross-culturally validated scales to measure water insecurity, food insecurity, and mental well-being.
Conclusion
Mental well-being is a key component of overall health and quality of life, especially for pregnant women. This study has described the interactions between drinking water source, water and food insecurity, and mental well-being of pregnant women in a low-income, urban context. The identified mediation relationship between water insecurity, mental well-being, and food insecurity suggests that approaches that aim to improve the mental well-being of women would likely be most effective when using holistic methods that reduce both water and food insecurity, considering the strong association between these two insecurities. Future research should aim to establish causality along these relationships and determine the specific mechanisms through which these interactions take place in varying contexts. Understanding these relationships is imperative to developing targeted interventions and policies that improve mental well-being through the reduction of poverty-related stressors.
Supporting information
S1 Table. Univariate associations of demographic characteristics with each predictor and outcome variable.
https://doi.org/10.1371/journal.pwat.0000219.s001
(DOCX)
S2 Table. Full logistic models using binary factors of drinking water source, water insecurity, and food insecurity with mental well-being (question 1).
https://doi.org/10.1371/journal.pwat.0000219.s002
(DOCX)
S3 Table. Full logistic models using continuous scales of HWISE and HFIAS scores with mental well-being.
https://doi.org/10.1371/journal.pwat.0000219.s003
(DOCX)
S4 Table. Full logistic model of off-premises drinking water source with water insecurity, food insecurity, and mental well-being for assessing mediation suitability (question 2).
https://doi.org/10.1371/journal.pwat.0000219.s004
(DOCX)
S5 Table. Full logistic model of water insecurity with food insecurity for assessing mediation (question 3).
https://doi.org/10.1371/journal.pwat.0000219.s005
(DOCX)
Acknowledgments
The authors would like to thank our study participants, who generously gave their time to participate in our survey. We thank the WE Consult field team (Genifa Banze, Gizela Brito, Isabel Chiquel, Marcelo Fernandes, Ligia Jorge, Gerson de Melo, Mario Mungoi, and Ricardina Timoteo) who captured these data.
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