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Article

Total Water Intake and Beverage Variety in Older Adults: A Cross-Sectional Study on Social Capital and Quality of Life in Greece

by
Aleks Pepa
1,
Olga Malisova
2,
Ioanna Apostolaki
1,3,
Emmanuella Magriplis
1,
Chrysavgi Galanaki
1,
Alexandros Chamos
1,
Maria G. Grammatikopoulou
4 and
Maria Kapsokefalou
1,*
1
Department of Food Science and Human Nutrition, Agricultural University of Athens, 75 Iera Odos Str., GR-11855 Athens, Greece
2
Department of Food Science and Technology, University of Patras, G Seferi 2, 30100 Agrinio, Greece
3
Department of Social Medicine, Faculty of Medicine, University of Crete, GR-71003 Heraklion, Greece
4
Immunonutrition Unit, Department of Rheumatology & Clinical Immunology, University of Thessaly, Larissa University Hospital, GR-41223 Larissa, Greece
*
Author to whom correspondence should be addressed.
Beverages 2025, 11(5), 132; https://doi.org/10.3390/beverages11050132
Submission received: 1 July 2025 / Revised: 25 July 2025 / Accepted: 27 August 2025 / Published: 4 September 2025
Browse Figure
Versions Notes

Abstract

Older adults face unique challenges related to hydration, particularly within the context of psychosocial determinants. This study aimed to examine the associations between total water intake (TWI), beverage variety, social capital, and health-related quality of life. We hypothesized that their ability to access, purchase, prepare, and drink a variety of beverages towards optimal TWI is affected by their physical/mental health and social support. To test the hypothesis, a cross-sectional design was implemented. We evaluated TWI, social capital, and Health-Related Quality Of Life, using the Water Balance Questionnaire, Social Capital Questionnaire, and SF-36, respectively, in 890 free-living participants (49.6% male), aged >65 years, recruited in Metropolitan Athens and Crete, Greece. TWI, 80% from beverages, was 2.6 ± 0.7 L in men and 2.4 ± 0.8 L in women and was associated with beverage variety (4.1 ± 1.0 in men, 3.9 ± 1.1 in women). Social capital, mental health, and variety of beverages were significant predictors of TWI; for each increased unit of the aforementioned predictors, TWI increased to 9.1, 6.8, and 183.5 mL, respectively. Spatial and gender differences were observed in social capital score and its components and in Health-Related Quality Of Life and its components, thus reflecting differences in social support and in functional health, plausibly linked to barriers/enablers to TWI. These findings highlight the potential importance of addressing psychosocial factors to support hydration in older adults.

1. Introduction

Older adults are vulnerable to dehydration, attributed to age-related changes in physiology, psychology, physical and cognitive abilities, and lifestyle [1,2,3,4]. As individuals age, there is a natural decline in total body water content and a diminished sensation of thirst, which can impair fluid intake regulation [5,6]. Additionally, renal function declines with age, reducing the kidneys’ ability to concentrate urine and conserve water, thereby increasing the risk of dehydration [7,8]. Cognitive impairments, such as dementia, further exacerbate the risk, as they can hinder an individual’s ability to recognize and respond to thirst cues [9,10,11]. Moreover, medications commonly prescribed to older adults, including diuretics and laxatives, can lead to increased fluid loss [12]. Lifestyle factors, such as reduced mobility and social isolation, may also limit access to fluids and contribute to inadequate hydration [13,14].
The consequences of dehydration in the elderly are significant. Even mild dehydration can impair cognitive functions, particularly attention and executive function, which are critical for daily activities [3,14,15]. Chronic dehydration has been associated with increased risks of urinary tract infections, kidney stones, constipation, and falls [16,17,18,19]. Furthermore, studies have linked inadequate hydration to accelerated cognitive decline and increased mortality rates [2,13,20].
Despite the clear risks, dehydration remains a common issue among older adults. A systematic review and meta-analysis estimated that approximately 20–30% of community-dwelling older individuals experience low-intake dehydration, with higher prevalence observed among those with multiple chronic conditions [4,20]. This highlights the need for targeted interventions to promote adequate hydration in this population.
Understanding the multifaceted causes and consequences of dehydration in older adults is essential for developing effective prevention and management strategies [1,2]. Barriers and facilitators to the process of daily hydration through the selection of beverages and foods must be identified and fully understood [21,22,23]. It appears that beyond individual physiological and cognitive factors, broader social determinants such as social capital may also influence hydration behaviors in older adults, shaping access to care, support for daily needs, and overall health practices through social networks and community engagement. Social capital refers to the networks, trust, and norms that facilitate cooperation within communities [24,25,26]. We hypothesized that in older adults, the ability to access, purchase, prepare, and drink a variety of beverages mainly depends on their (a) health and (b) social interaction. This paper aims to explore the physiological, cognitive, and lifestyle factors contributing to dehydration in the elderly and thus, indirectly, to identify potential interventions to mitigate this pervasive health issue.
Adequate nutrition is not only vital for maintaining hydration but also plays a pivotal role in preventing and healing pressure ulcers in frail older adults, especially those receiving care in community settings where nutritional monitoring may be inconsistent [27]. In post-conflict environments, community health workers serve as essential bridges between vulnerable populations and fragmented health systems, offering culturally sensitive care that can improve hydration and nutrition outcomes among older adults [28]. Empowering community health workers and accountability through clear accountability structures enhances their ability to advocate for the hydration and nutritional needs of older adults, ensuring that care delivery is both equitable and responsive [29].
The primary aim of this study was to examine the relationship between total water intake, beverage variety, and psychosocial factors such as social capital and mental health in older adults in Greece. The secondary aim was to explore potential implications for health promotion and care planning. The objective of the present study was to (a) define associations with variety in beverage intake, water intake from beverages, and total water intake, as well as physical and mental health scores, and (b) to assess social capital among older adults living in different geographical settings (the island of Crete and metropolitan Athens).

2. Materials and Methods

2.1. Ethical Permission

The study protocol was designed in line with the Declaration of Helsinki and the principles of research on human subjects and was reviewed and approved by the Ethical Committee of the Agricultural University of Athens (181-14/02/2014). Before entering the study, all participants were informed of the aims and procedures of the study and were asked to provide informed consent. All data were collected via personal one-on-one interviews and were treated with confidentiality, according to the ethical clearance provided by the Ethics Committee.

2.2. Study Participants

Older adults (age > 65 years) were recruited from day-care centers via invitation at Social Structures for the Elderly (KAPI) in an urban and a rural area in Greece, namely the area of metropolitan Athens (several municipalities) and the Municipality of Minoa in Crete, by trained field researchers, in collaboration with local municipal services, who enrolled eligible participants. Exclusion criteria included inability to communicate, cognitive impairment, lack of knowledge of the Greek language, current hospitalization, and medical conditions that could affect fluid balance, such as renal insufficiency, urinary tract infections, or other acute illnesses. Out of 1200 invited, 890 agreed to participate (49.6% male), specifically 454 from Athens and 436 from Crete. Participation rate reached 70%, while 30 participants withdrew for personal reasons, despite having provided prior consent. Trained personnel collected all information via interviews (Figure 1).

2.3. Socio-Demographic Parameters

Collected demographics included gender, age, educational level, marital status, number of children, employment status, number of people cohabiting the same house, car ownership, annual income, smoking habits, and health problems (recorded as known diagnoses of medical conditions). Anthropometric data were self-reported and included weight and height. Body Mass Index (BMI) was calculated from these data for each participant.
The characteristics of the sample are presented in Table 1.

2.4. Water and Beverage Intake

For estimating TWI and water intake from beverages, the Water Balance Questionnaire (WBQ) was employed [30]. The WBQ embeds a food and beverage frequency questionnaire and allows collecting information on the variety and number of beverages consumed. The WBQ has been previously used in older adults in Greece [31].
In order to score variety in beverage consumption, beverages were categorized into eight groups: water (tap or bottled), fruit juice, caloric soft drinks, diet soft drinks, milk, alcohol, tea/coffee, and other beverages. The sum of tap and bottled water intake was used to calculate drinking water consumption. The variety score was calculated as the sum of all beverages consumed from the eight distinct categories, with a minimum value of “0” and a maximum value of “8” [31,32,33]. TWI was calculated from the moisture content of the consumed foods and the total beverage intake and includes all sources of water, i.e., drinking water, water from beverages, and water from food.

2.5. Social Capital Analysis

For scoring individual social capital, the Social Capital Questionnaire (SCQ) [34] was employed. The social capital questionnaire has been translated and validated for the Greek population (SCQ-G) in the past [35]. The SCQ-G comprises 36 questions in total organized in six subscales: Participation in the Local Community, Feelings of Safety, Family/Friends Connections, Value of Life and Social Agency, Tolerance of Diversity, and Work Connections. In the present study, the four questions from the subscale Work Connections and one additional question from the subscale Value of Life and Social Agency related to employment status were excluded, given that almost half of the participants were not working during the time of the study [35]. This tool was chosen due to its cultural relevance and existing validation in the Greek context. Scores were calculated as simple sums of items, with equal weighting across subscales; in detail, each question has a 4-point scale reflecting the frequency of occurrence (1, not at all, no, never; 2, rarely, sometimes; 3, probably yes, often, much; 4, very much, frequently). Higher scores in each question indicate higher social capital. A score for each separate subscale is derived by adding the scores of the questions of each subscale; a total score by adding all scores is also estimated [35].

2.6. Statistical Analysis

Results are presented as mean ± sd for the normally distributed variables and median (P25–P75) for the skewed ones. Normality was tested using the probability–probability plot (P–P plot) and histograms. Differences were assessed with the t-test for the normally distributed variables and the Mann–Whitney U-test for the skewed ones. Significance level was set at 5%. A multiple linear regression analysis was performed to examine whether beverage variety, mental and physical health (MCS, PCS), social capital, and sociodemographic factors significantly predicted total water intake (TWI). Independent variables included beverage variety score, social capital score, MCS, PCS, BMI, age, income, gender, and car ownership. The Enter method was used to enter all predictors simultaneously, and missing data were handled via listwise deletion. Key linear regression assumptions were assessed and met: normality of residuals (via histograms and P–P plots), linearity and homoscedasticity (via scatterplots of standardized residuals), and absence of multicollinearity (all VIFs < 1.4). Interaction terms were excluded due to limited scope and statistical power. Bonferroni correction was applied for multiple comparisons, and models were adjusted for age, gender, education, and marital status. Analyses were performed using SPSS version 26 (SPSS Inc., Chicago, IL, USA), with statistical significance set at α = 0.05. Assumptions for linear regression were assessed as follows: Normality of residuals was tested using histograms and P–P plots; linearity and homoscedasticity were verified through scatterplots of standardized predicted versus residual values. Multicollinearity was ruled out based on Variance Inflation Factors (VIFs), all of which were below 1.4.

3. Results

3.1. Water and Beverage Intake and Variety

TWI, and its components, namely water from beverages, from drinking water (tap and bottled), and from foods, are reported in Table 2, presenting values in men and in women, and at the two sites of the study in order to observe gender and spatial differences. TWI was 2543 (2057–3058) in men and 2322 (1838–2813) in women. Approximately 80% of TWI was from beverages. Gender differences were apparent in TWI and its components (p ≤ 0.001); with the exception of water from foods, no differences were observed. There were no differences in TWI in older adults living in Athens and in Crete; however, water from beverages and water from foods was lower in Crete, while water from drinking water was higher (p ≤ 0.001).
The beverage variety score was 4.1 ± 1.0 in men and 3.9 ± 1.1 in women; women in Athens and in Crete scored lower in variety compared to men (p ≤ 0.001), but there was no difference in beverage variety in Athens and in Crete.

3.2. Social Capital

Social capital scores per gender and per area of residence are presented in Table 3. Men exhibited higher feelings of safety and family and friend bonds compared to women in the total sample (p ≤ 0.001 for all) and at each site. The total social capital score was higher among men inhabiting Athens compared to women, whereas the sense of local community was higher among women living in Crete compared to men. Between areas, the sense of local community and tolerance of diversity was higher in Athens compared to Crete (p ≤ 0.001 and p ≤ 0.05, respectively), whereas in the latter, the feeling of safety was higher (p ≤ 0.001).

3.3. Health-Related Quality of Life

The distinct SF-36 components per gender and per area of residence are presented in Table 4. Higher scores were reported for components of SF-36 physical functioning, bodily pain, social functioning, and mental health were observed among men in the total sample, compared to the women (p ≤ 0.001) [36]. Vitality, as well as physical and mental health summaries, was also higher among men participants compared to women (p ≤ 0.02, p ≤ 0.008, and p ≤ 0.002, respectively). In Crete, men demonstrated increased social functioning and physical health compared to women (p ≤ 0.001 for all), whereas in Athens, men also scored higher in role emotional compared to women (p ≤ 0.05). In both sites, female participants reported reduced bodily pain, vitality, mental health, and mental health summary compared to the men. When pooled gender samples were compared from each site, components of SF-36 role physical, role emotional, general health, vitality, physical and mental health summaries (p ≤ 0.001 for all), as well as mental health (p ≤ 0.05), were greater in Athens compared to Crete.

3.4. Correlations Between Study Variables

In the total sample, social capital was positively correlated with physical and mental health (rho = 0.195, rho = 0.240, p ≤ 0.001 for both). Weak positive correlations were observed between beverage variety and water intake from beverages (rho = 0.234, p ≤ 0.001) and TWI (rho = 0.260, p ≤ 0.001). In addition, water from beverages demonstrated a strong positive correlation with TWI (rho = 0.972, p ≤ 0.001).
A multiple linear regression model was used to predict TWI based on the social capital score, physical health, mental health, beverage variety, age, gender, BMI, car, and income. The final model used was significant [F(9,n=874) = 11.226, p ≤ 0.001], with an R2 of 0.094. Social capital, mental health, and variety of beverages were significantly associated with higher TWI, and for each increased unit of the aforementioned predictors, TWI increased to 9.1, 6.8, and 183.5 mL, respectively (Table 5). Beverage variety (β = 0.253, p < 0.001), mental health (β = 0.091, p = 0.007), and social capital (β = 0.103, p = 0.003) were independently and positively associated with total water intake. These findings suggest that beverage variety had the strongest association and psychosocial and behavioral factors play a role in hydration behavior among older adults.
Although 95% confidence intervals for standardized beta coefficients were not available from SPSS output, the reported effect sizes reflect small-to-moderate associations, with beverage variety showing the strongest predictive value for TWI.
Regarding the consumption of water from beverages, including drinking water, a regression equation was calculated [F(9,n=874) = 8.890, p ≤ 0.001], with an R2 of 0.074. Social capital, mental health, beverage variety, and gender were predictors; for each unit increase of those predictors, water intake from beverages increased to 7.4, 6.6, 149.6, and 127.4 mL, respectively.
When participants’ gender was accounted for, among women, beverage variety was predicted by age and car ownership (β = 0.037, p ≤ 0.001 and β = 0.254, p ≤ 0.044), a finding lacking from the men’s sample. As per area, in the Athenian population, social capital, physical health, and gender were significant predictors, while in the Cretan sample, age and gender were demonstrated to be significant predictors.
All regression models were adjusted for sociodemographic confounders, including age, gender, education, and marital status.

4. Discussion

The present study highlights that among older adults, total water intake (TWI) is significantly influenced by social capital, mental health, and beverage variety. Beverage variety itself was associated with age, gender, and social capital, suggesting interconnected pathways that affect hydration behaviors. Notably, spatial and gender disparities were evident, with differences observed between older adults residing in metropolitan Athens and those living on the island of Crete. These differences were reflected not only in levels of social capital but also in the types and quantities of beverages consumed, underscoring the importance of environmental and socio-demographic factors in shaping hydration-related behaviors in aging populations.
With regard to the volume of water consumed by the older adults inhabiting Athens and Crete, it appears that both genders reached the adequate intake values suggested by the European Food Safety Authority (EFSA) [37] for men and women (2.5 and 2.0 L, respectively). Similar levels of intake were observed among older adults inhabiting Athens and Crete. However, other studies suggest that older adults are at risk for insufficient fluid intake and are encouraged to drink more [38]; research from countries like Sweden, the Netherlands, the Czech Republic, Slovenia, Spain, and the UK recorded water intakes below the adequate intake threshold [39,40,41,42,43,44,45,46]. According to O’Connor et al. [47], older men in Ireland failed to meet the EFSAs adequate volume intakes compared to women. These low fluid intakes are the epiphenomenon of aging-related altered physiology, including thirst perception [48], physical limitations (i.e., reduced mobility) [49], social isolation, depression, or other illnesses [20]. In parallel, with older adults demonstrating significant deficiencies in hydration health literacy [50], the reduced water intakes reported in these studies may reflect participants’ limited hydration knowledge. On the other hand, in Poland, 70% of older adults met the reference values [49]; older data from the UK suggest a nearly similar TWI to the EFSA reference values [51], whereas in Spain, the majority of independently living elderly consumed adequate amounts of fluids [42]. More recently, adequate mean daily intake was reported among a sample of Greek-born Australians [52]. Based on the present findings corroborated by previous research on the Greek population [32,33,53], it appears that in Greece, inhabitants tend to consume greater fluid intakes compared to other countries [43,54]. According to Muñoz and Wininger [55], models explaining hydration should account for the environment. Thus, the aforementioned finding might be the result of climate, acculturation to increased drinking volumes from a younger age, and the abundance of free drinking water available in most parts of the country.
In lieu of the aforementioned assumption, differences in the source of water intake were observed among older adults inhabiting metropolitan Athens compared to those living on the island of Crete. The first consumed more beverages and bottled water, whereas the latter reported a greater tap and drinking water intake. The quality of drinking water is easily influenced by natural and anthropogenic factors, including industry. This issue may explain spatial differences in the source of water intake observed among older adults inhabiting metropolitan Athens compared to those living on the island of Crete. Moreover, in Crete, the availability of water of better tap quality might also be the driving force behind the observed increased intake.
In the present study, water from beverages, including drinking water, contributed to the TWI at approximately 80%, a finding in agreement with the consumption reported by the NHANES 2005–2010 [56] and the estimated adequate intakes suggested by the EFSA [37]. Similar observations were recorded for men and women living either in Athens or Crete. In other populations, water intake from beverages may be different; for example, in Irish elder individuals, water intake from beverages contributed to the TWI at approximately 63% [47].
In our sample, TWI and water from beverages, including drinking water, were predicted from beverage variety and social capital. Beverage variety is an important factor associated with water intake [43]. Herein, we adopted a system for scoring variety, which takes into consideration eight different categories of hot and cold beverages, including drinking water. Adopting a similar scoring system from studies in adults living in the UK showed that greater variety scores were linked with increased water intake [57]. Furthermore, a scoring system analogous to the one used herein has been applied to determine the pattern of beverage variety of older French adults and was associated with increased TWI [58]. Gibson and associates [51] stated that the results from the secondary analysis of the NDNS 2000/2001 indicate a positive correlation between beverage variety and TWI. We observed that older adults’ beverage variety was positively correlated with TWI and water intake from beverages for all participants as well as in the samples from Athens and Crete. The same association between beverage variety and TWI has also been observed among older adults in Spain [43]. Given that an inverse age-related gradient is reported to exist in total beverage and water intake [59], assuring a social support network for older adults appears to be another means of ameliorating fluid intake and avoiding dehydration in this population [60].
Although older adults tend to be involved to a greater degree in their communities compared to younger ones [61], social interactions and connections demonstrate a decline through the course of life, being influenced by work careers and labor market particularities, memberships, and family ties [62]. Globally, gender differences exist in the components of social capital given the different life trajectories of both genders and the different gender perceptions regarding individual social capital components, including safety, value of life, social and family interactions, etc. [63,64,65,66]. In the present sample, women in both sites reported a lower feeling of safety as compared to the men, indicating that gender characteristics might augment the feeling of safety among men. Moreover, women reported fewer family and friend bonds as a possible result of a lack of career or having to stay at home and raise their children during earlier years [67]. Individuals with greater work experience demonstrate expanded social networks accumulated during their careers [68,69]. In parallel, these social capital components are also influenced by the place of residence, with the Cretan sample reporting greater safety as compared to the Athenian one. It is also of interest to highlight that men achieved a greater social capital score compared to women, although, between study sites, a similar total social capital score was observed.
Regarding the social capital, it was shown that as the level of socialization increased, i.e., the social capital score was elevated, older individuals had better chances to achieve the recommended intake of water and increase beverage variety. According to Durkheim’s classic social integration theory [70,71], the conceptual model ties social capital to health outcomes first at a macro level (political state, culture, socioeconomic status (SES), etc.) and secondly at a micro level (social support and engagement, etc.), both influencing health through physiological, psychological, and behavioral pathways [63]. Moreover, social capital is the quality of life [72] and collective efficacy [73] and, by inference, the potential aid that older adults might employ to improve accessibility to purchasing foods and drinks.
In different subgroups of the sample, social capital, age, and car ownership were predictors of the beverage variety score, indicating the complex mechanisms driving beverage variety among older adults. Car ownership, in particular, was an important factor affecting beverage variety among Cretan women. In rural and semi-rural areas like Crete, owning a car is important for transportation, socializing, and purchasing food commodities. Thus, in the Cretan sample, car ownership appears to be an asset aiding social capital among older women, which, in turn, might explain its effect on beverage variety. In parallel, social capital and SES have both been linked to the health and health-related behaviors of older adults [74]. Given that nearly half (45.4%) of the women participants herein were widowers, owning a car is an SES indicator that may undoubtedly increase social interactions and ameliorate quality of life.
With regard to the physical and mental health domains, the sample’s mean perceived scores were suboptimal (close to the average), with similarly average scores also being observed in both site [75]. However, based on the findings, mental health was more strongly associated with beverage variety and TWI as compared to physical health. This corroborates the plethora of research suggesting that adequate hydration is an important component of mental health among older adults, as depressed individuals tend to be dehydrated [76,77].
Moreover, social capital is also intertwined with mental health. The effect of the environment and social capital is so strong that twins’ studies indicate that cognitive social capital can even suppress a genetic predisposition for developing depression [78]. Among older adults, weak social capital has been associated with depression [74], which, in turn, has been shown to reduce water intake [79]. Poor mental health constitutes an important challenge in older age, and herein it is shown that mental health can predict both water intake and beverage variety. The combination of low fluid intake and compromised mental health appears to perpetuate a vicious cycle of dehydration among older adults [80]. Research on cohort and randomized controlled trials indicates that suboptimal fluid intake affects cognition and mental health, and in turn, poor mental health also deteriorates the level of hydration and the stimulus of thirst [81,82,83]. To battle this vicious cycle, Lindeman [1,2,38] suggested encouraging older adults to increase their fluid intake. In parallel, data from the Czech Republic reported lower hydration levels among non-exercising older adults [45], identifying exercise as an additional means to stimulate thirst and water intake in this age group. Conceptually, social capital may influence hydration through behavioral and structural mechanisms, as outlined in Berkman and Glass’s social integration model [71]. This framework proposes that social ties and support networks shape individual health behaviors—including fluid intake—via social norms; emotional support; and tangible resources. In older adults, such networks may facilitate or hinder access to beverages, promote hydration awareness, and shape routine consumption patterns.
Second, the reliance on self-reported data and structured questionnaires, rather than objective measurements (e.g., biomarkers of hydration, direct fluid intake tracking), may introduce recall bias or social desirability bias, potentially affecting the accuracy of the findings. Future studies should incorporate objective methods to validate self-reported intake and health status.
Additionally, this study did not explore the detailed composition of consumed beverages, such as the intake of sugary drinks, caffeinated beverages, or alcohol, nor did it assess their caloric contribution or potential health implications. Given the growing public health concern over sugar-sweetened beverages and alcohol consumption in older populations, this remains a critical area for further investigation.
The regression model demonstrated acceptable fit and met all major assumptions, including normality, homoscedasticity, and absence of multicollinearity. Standardized effect sizes suggest that beverage variety plays a moderately strong role in predicting water intake, while mental health and social capital have smaller but meaningful effects. These findings underscore the multifactorial nature of hydration behavior in older adults.
As to implications for clinical and community practice, strategies to improve hydration in older adults should consider social and mental health dimensions. Programs that promote social engagement, community participation, and accessible beverage options may support hydration. Public health campaigns could integrate hydration messaging into broader wellness initiatives, particularly within municipal care settings.
Despite statistical adjustment for key confounders, residual confounding from unmeasured variables (e.g., medication use, dietary patterns) may influence the associations and should be considered when interpreting results.
Regarding this study population, although the sample size was adequate and included participants from both metropolitan and rural settings, the use of a convenience sampling method may limit the generalizability of the findings. Participants may not be fully representative of the broader elderly population in Greece or in similar cultural settings. Therefore, caution is advised when extrapolating the results to other populations. Future research should aim to recruit larger, randomized, and more diverse samples to enhance representativeness and external validity.
Future research should adopt longitudinal designs to explore the directionality of the observed associations and incorporate objective hydration biomarkers for validation. Additionally, studies should evaluate the types and composition of beverages consumed—such as sugar-sweetened or caffeinated drinks—to assess their contribution to both hydration and broader health outcomes.
Limitations of the study: The present study has several limitations that should be acknowledged. First, its cross-sectional design limits the ability to draw causal inferences. While associations between beverage variety, health indicators, and total water intake (TWI) were identified, the study cannot determine the directionality or causality of these relationships. In addition, the sample size was modest and restricted to older adults attending day-care centers, which may limit the generalizability of the findings. The reliance on self-reported anthropometric and dietary data may also introduce measurement bias. Although predictors were entered simultaneously in a single model, and the model was statistically significant, we acknowledge the potential for Type I error due to multiple comparisons across several predictor variables. This limitation should be taken into account when interpreting the associations. Future research should employ longitudinal or intervention-based designs, include more diverse populations, and consider the use of objective hydration biomarkers to strengthen causal interpretations and applicability.

5. Conclusions

Among older adults, beverage variety, mental health, and social capital are positively associated with greater fluid intake. In our hypothesis, health and social capital may be viewed as key assets for achieving better hydration. However, barriers to adequate hydration include structural limitations such as restricted mobility and transportation options and psychosocial challenges like reduced social support, isolation, or cognitive decline. Older individuals with high levels of social capital may be more likely to overcome these barriers and enhance their access to beverages by utilizing both personal and community resources. These findings underscore the importance of prioritizing future interventions that promote beverage variety, address psychosocial and environmental barriers, and evaluate health outcomes in relation to social capital. Community-based programs that focus on hydration education, beverage accessibility, and social support could complement nutritional strategies and support healthier aging and integrate psychosocial components, including fostering social participation, ensuring accessible beverage choices, and delivering hydration education within community care settings.

Author Contributions

Conceptualization, M.K., A.P. and O.M.; methodology, M.K., A.P., I.A., O.M., C.G. and A.C.; formal analysis, A.P. and E.M.; writing—original draft preparation, A.P., O.M. and M.G.G.; writing—review and editing, A.P., O.M. and M.K. All authors have read and agreed to the published version of the manuscript.

Funding

The first author of this research (A.P.) received a studentship award grant from the European Hydration Institute (EHI).

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethical Committee of the Agricultural University of Athens (protocol code: 181-14/02/2014 and date of approval: 14 February 2014).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author. (the data are not publicly available due to privacy and ethical restrictions).

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
TWITotal Water Intake
WBQWater Balance Questionnaire
SF36Short Form Health Survey
SCQSocial Capital Questionnaire
SCQ-GSocial Capital Questionnaire-Greek
BMIBody Mass Index
IQRInterquartile Range
EFSAEuropean Food Safety Authority

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Beverages 11 00132 g001
Figure 1. Study flow diagram.
Figure 1. Study flow diagram.
Beverages 11 00132 g001
Table 1. Participant characteristics.
Table 1. Participant characteristics.
Participant CharacteristicsValue
Inhabitants of Athens/Crete (n) 454/436
Gender (men/women n)441/449
Age (years)75.6 ± 6.6
Marital status (married/widower/divorced/never married) (%)65.7/30.1/2.5/1.7
Educational tier (primary/secondary/tertiary/professional school) (%)65.4/26.1/5.5/2.9
Profession (pensioner/farmer/private employee/housewife/other) (%)92.7/0.9/0.1/0.1/6.1/0.1
Annual income (<10 k€/10–20 k€/20–40 k€/>40 k€) (%)59.0/34.5/5.8/0.7
Home ownership (%)85.4
BMI (male/female)27.6 ± 3.6/28.7 ± 4.5
Table 2. Total Water Intake, observed as water from beverages, from drinking water (tap and bottled), and from foods, among older adult men and women, inhabitants of metropolitan Athens and Crete.
Table 2. Total Water Intake, observed as water from beverages, from drinking water (tap and bottled), and from foods, among older adult men and women, inhabitants of metropolitan Athens and Crete.
Water Intake and Beverage VarietyMen
(n = 441)		Women
(n = 449)		AthensCreteTotal
Men
(n = 190)		Women
(n = 264)		Men
(n = 251)		Women
(n = 185)		Athens
(n = 454)		Crete
(n = 436)
TWI (mL)2543 (2057–3058)2322 (1838–2813) ***2661 ± 8002389 (1974–2851) *2551 ± 6972298 ± 828 ***2466 (2006–2981)2444 ± 765
Water from beverages and drinking water (mL) ‡2025 (1597–2593)1865 (1408–2365) ***1943 (1528–2471)1889 (1482–2362)2145 ± 7051850 ± 799 ***1911 (1514–2403)1958 (1481–2521)
Water from beverages (mL) †595 (411–805)514 (361–745) ***669 (476–882)554 (411–810) **559 (402–724)466 (297–658) ***622 (430–830)514 (361–695) ###
Drinking water (tap + bottled) (mL)1440 (960–1920)1200 (840–1680) ***1200 (960–1680)1200 (960–1680)1440 (960–2160)1200 (720–1680) ***1200 (960–1680)1400 (960–1920) ###
Water from foods (mL)435 (360–574)470 (375–567)560 (438–718)491 (403–599) ***383 (338–453)424 (339–533) ***516 (421–665)395 (338–491) ###
Beverage variety (n)4 (4–5)4 (3–5) ***5 (4–5)4 (3–5) ***4 (4–5)4 (3–4) ***4 (3–5)4 (3–5)
4.4 ± 1.03.9 ± 1.14.5 ± 1.14.0 ± 1.14.3 ± 0.93.8 ± 1.04.2 ± 1.14.1 ± 1.0
Results are presented as median with the respective IQR for skewed variables or as mean ± standard deviation for normally distributed variables. Significance was tested with the Mann–Whitney U-test for skewed variables or the t-test for normally distributed variables; IQR: interquartile range; TWI: Total water intake; † Excluding drinking water; ‡ Including drinking water; * Significantly different compared to men (*** p ≤ 0.001; ** p ≤ 0.01; * p ≤ 0.05); # Significantly different compared to inhabitants of the Athens metropolitan area (### p ≤ 0.001).
Table 3. Frequencies of social capital scores and score components among older adult men and women, inhabitants of metropolitan Athens and Crete.
Table 3. Frequencies of social capital scores and score components among older adult men and women, inhabitants of metropolitan Athens and Crete.
Social Capital Questionnaire (SCQ) Scores and ComponentsMen
(n = 441)		Women
(n = 449)		AthensCreteTotal
Men
(n = 190)		Women
(n = 264)		Men
(n = 251)		Women
(n = 185)		Athens
(n = 454)		Crete
(n = 436)
%n%n%n%n%n%n%n%n
Total SCQ score (%, n)Low7.93513.6616.31215.9429.22310.31911.9549.642
Average81.035776.434380.015273.919581.720580.014876.434781.0353
High11.14910.04513.72610.2279.2239.71811.7539.441
SCQ Value of life score (%, n)Low80.735671.332076.814665.917483.721078.914670.532081.7356
Average8.83914.36411.12116.7447.21810.82014.3658.738
High7.93513.6616.31215.942922310.31911.9549.642
Total score (31–124) †
SCQ scores components		 74 (68–80)73 (67–79)74 (69–80)72.0 ± 9.5 *74 (68–80)75 (69–79.5)73 (67–79)75 (68–79.8)
Local community (12–48) †21 (18–23)21 (19–24)21 (19–25)21 (19–24)20 (18–22)21 (19–23) **21 (29–24)20 (18–23) ###
Safety (2–8) †6 (4–7)4 (3–6) ***5 (4–6)4 (3–5) ***6 (5–7)6 (4–7) ***4 (3–6)6 (5–7) ###
Family and friends bonds (2–8) †4 (4–5)4 (3–5) ***5 (4–5)4 (3–5) **4 (3–5)4 (3–5) ***4 (3–5)4 (3–5)
Tolerance diversity (2–8) †4 (3–5)4 (3–5)4 (3–6)4 (3–5)4 (3–4)4 (3–5)4 (3–5)4 (3–4) #
Value of life (11–44) †32 (30–35)33 (30–36)32 (30–35)33 (30–36)32 (30–35)33 (30–36)33 (30–36)33 (30–35)
* Significantly different compared to men (*** p ≤ 0.001; ** p ≤ 0.01); # Significantly different compared to inhabitants of the Athens metropolitan area (### p ≤ 0.001; # p ≤ 0.05); † Highlights the specific categories of the SC score.
Table 4. Health-Related Quality Of Life in older adult men and women living in metropolitan Athens and in Crete, evaluated with the SF-36 questionnaire and reported per component of SF-36.
Table 4. Health-Related Quality Of Life in older adult men and women living in metropolitan Athens and in Crete, evaluated with the SF-36 questionnaire and reported per component of SF-36.
SF-36 ComponentsMen
(n = 441)		Women
(n = 449)		AthensCreteTotal
Men
(n = 190)		Women
(n = 264)		Men
(n = 251)		Women
(n = 185)		Athens
(n = 454)		Crete
(n = 436)
Physical Functioning70 (50–90)60 (40–80) ***,a70 (45–85)65 (45–80) d75 (50–95)50 (35–75) ***65 (45–80) e65 (40–85)
Role-Physical69 (44–94)69 (44–94)75 (50–100)81 (50–100)63 (38–88)63 (44–82)75 (50–100)63 (39–81) ###
Bodily Pain72 (51–100)61 (41–74) ***74 (51–100)61 (41–84) ***64 (51–84)61 (41–72) ***62 (41–100)62 (42–74)
General Health57 (42–72)57 (40–72)62 (47–75)65 (48–77)52 (40–67)4 ± 22 **62 (47–76)50 (35–67) ###
Vitality63 (50–75)63 (44–75) *69 (50–88)69 (50–81) *63 (50–75)56 (44–69) **69 (50–81)56 (50–69) ###
Social Functioning88 (63–100)75 (50–100) ***88 (63–100) c88 (-50–100)88 (75–100)75 (50–100) ***88 (50–100) f75 (63–100)
Role-Emotional75 (42–100)75 (42–100)92 (65–100)83 (50–100) *58 (33–100)58 (25–92)92 (58–100)58 (33–92) ###
Mental Health75 (60–85)65 (45–80) ***70 (59–85)65 (45–80) ***75 (65–85)65 (50–80) ***70 (50–80)70 (55–85) #
Physical Health Summary47 (40–53 b)45 (38–52) **,a48 (42–53) c46 ± 9 d47 (39–53)42 ± 9 ***48 (40–53) g45 (37–52) ###
Mental Health Summary50 (43–56 b)48 (38–56) **,a54 (45–57) c50 (39–57) **,d48 (42–54)45 ± 11 **52 (42–57) g47 (40–54) ###
Results are presented as median with the respective 1st and 3rd interquartile ranges for skewed variables or as mean ± standard deviation for normally distributed variables (in italics). Significance was tested with the Mann–Whitney U-test for skewed variables or the t-test for normally distributed variables; IQR: Interquartile range; SF-36: Short form 36 questionnaire. Total water intake; * Significantly different compared to men (*** p ≤ 0.001; ** p ≤ 0.01; * p ≤ 0.05); # Significantly different compared to inhabitants of Athens metropolitan area (### p ≤ 0.001); a n = 448; b n = 439; c n = 188; d n = 263; e n = 453; f n = 452; g n = 451.
Table 5. Multiple linear regression analyses of social capital and Health-Related Quality Of Life components on TWI and beverage variety.
Table 5. Multiple linear regression analyses of social capital and Health-Related Quality Of Life components on TWI and beverage variety.
TWIWater Intake from
Beverages ‡		Beverage Variety
(Total Sample)		Beverage Variety
(Athenians)		Beverage Variety
(Cretans)
β95% CIβ95% CIβ95% CIβ95% CIβ95% CI
SCQ total score9.1 **3.2 to 15.07.4 *1.6 to 13.10.01 *0.0 to 0.020.02 ***0.01 to 0.03−0.002−0.014 to 0.01
Physical Health Summary−1.9−7.9 to 3.9−1.0−6.7 to 4.6−0.002−0.01 to 0.006−0.02 **−0.03 to -0.0040.006−0.005 to 0.017
Mental Health Summary6.8 **1.9 to 11.76.6 **1.8 to 11.3−0.001−0.01 to 0.01−0.01−0.02 to 0.0010.004−0.006 to 0.014
Beverage variety183.5 ***136.1 to 230.9149.6 ***104 to 195.2- - -
Age0.4−8.1 to 9.0 −1.4 −9.6 to 6.80.02 ***0.01 to 0.030.020.00 to 0.040.019 *0.002 to 0.035
Gender110−4.7 to 224.6127.4 *17.1 to 237.60.4 ***0.3 to 0.60.4 ***0.2 to 0.70.455 ***0.245 to 0.665
BMI2.9−9.3 to 15.21.5−10.2 to 13.3−0.006−0.02 to 0.01−0.01−0.04 to 0.0120.001−0.021 to 0.023
Car ownership−109.3−226.3 to 7.6−71.7−184.2 to 40.70.11−0.06 to 0.3−0.02−0.26 to 0.220.213−0.011 to 0.437
Income12.3−69.6 to 94.1−56.5−135.1 to 22.20.1−0.06 to 0.17−0.006−0.17 to 0.160.052−0.118 to 0.222
BMI, Body Mass Index; CI, confidence interval; SCQ, Social Capital Questionnaire; TWI, total water intake; β, beta coefficient; ‡ Including drinking water; Statistically significant (*** p ≤ 0.001; ** p ≤ 0.01; * p ≤ 0.05).
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Pepa, A.; Malisova, O.; Apostolaki, I.; Magriplis, E.; Galanaki, C.; Chamos, A.; Grammatikopoulou, M.G.; Kapsokefalou, M. Total Water Intake and Beverage Variety in Older Adults: A Cross-Sectional Study on Social Capital and Quality of Life in Greece. Beverages 2025, 11, 132. https://doi.org/10.3390/beverages11050132

AMA Style

Pepa A, Malisova O, Apostolaki I, Magriplis E, Galanaki C, Chamos A, Grammatikopoulou MG, Kapsokefalou M. Total Water Intake and Beverage Variety in Older Adults: A Cross-Sectional Study on Social Capital and Quality of Life in Greece. Beverages. 2025; 11(5):132. https://doi.org/10.3390/beverages11050132

Chicago/Turabian Style

Pepa, Aleks, Olga Malisova, Ioanna Apostolaki, Emmanuella Magriplis, Chrysavgi Galanaki, Alexandros Chamos, Maria G. Grammatikopoulou, and Maria Kapsokefalou. 2025. "Total Water Intake and Beverage Variety in Older Adults: A Cross-Sectional Study on Social Capital and Quality of Life in Greece" Beverages 11, no. 5: 132. https://doi.org/10.3390/beverages11050132

APA Style

Pepa, A., Malisova, O., Apostolaki, I., Magriplis, E., Galanaki, C., Chamos, A., Grammatikopoulou, M. G., & Kapsokefalou, M. (2025). Total Water Intake and Beverage Variety in Older Adults: A Cross-Sectional Study on Social Capital and Quality of Life in Greece. Beverages, 11(5), 132. https://doi.org/10.3390/beverages11050132

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