Association between Biochemical Parameters, Especially Hydration Status and Dietary Patterns, and Metabolic Alterations in Polish Adults with Metabolic Syndrome

Abstract

It is important to understand which factors are central to the development of metabolic syndrome as the burden of the condition increases (MetS). The aim of this study was to search for associations between the frequency of non-alcoholic beverage consumption (FFQ), blood pressure, anthropometric measurements, biochemical parameters related to health and hydration status, and the number of MetS components in 290 adults diagnosed with metabolic disorders. Blood pressure and anthropometric measurements: body weight (BW), height (H), waist circumference (WC), handgrip strength (HGS), and total body water (TBW) were measured. Blood and urine samples were collected. We observed the highest frequency of consumption of tea drinks in women with four MetS components and fruit and vegetable juices in men with five MetS components. The highest systolic blood pressure (SBP) and BMI were found with five MetS components and the lowest TBW with three MetS components in both sexes. The lowest uric acid and urea were observed in women with three MetS components, while the lowest pH with five MetS components and the highest urine-specific gravity (USG) with four MetS components were observed in men. These findings highlight the need to focus on elucidating the relationship between diet, including beverage consumption, blood pressure, anthropometric measurements and biochemical parameters, and health and hydration status in adults with metabolic disorders in further research.

1. Introduction

Metabolic syndrome (MetS) can be defined as a part of linked metabolic factors such as overweight, obesity, hypertension, low high-density lipoprotein cholesterol (HDL-C), and elevated triglyceride (TG) or glucose levels. Results from epidemiological studies confirm the growing problem associated with MetS, and it is estimated that MetS may affect up to 20–35% of the global adult population [1,2]. According to Regufe et al. [3], factors influencing the development of MetS are demographic factors—age, body mass index, various socio-economic factors, and diet. The most rapid increase in MetS has been observed in populations in developing countries, associated with sedentary lifestyles, low socioeconomic status, smoking, and unhealthy dietary habits, including the consumption of beverages as a source of water for adequate hydration [2,3,4,5].

Water is a very important substance for the human body and performs many vital functions. It is a component of all cells and body fluids and provides the environment for all biochemical reactions in the body. “Euhydration” is the proper state of hydration of the body resulting from the correct water balance in the body. Dehydration can lead to negative physiological and exercise outcomes because it is the result of a complete lack of water in the body [6,7]. Therefore, it is important to ensure adequate fluid intake throughout the day and to understand the importance of body hydration for good human health, as even mild dehydration is an undesirable state [8,9,10]. Inadequate water intake is a major health problem because it is associated with many adverse health outcomes, including MetS, as well as urolithiasis, constipation, asthma, cardiovascular disease, and some cancers, although the causal relationship is not clear [11,12,13].

Inappropriate hydration, as assessed by urinary biomarkers, was associated with increased BMI and overweight or obesity in adults. This association suggests that water, as an essential nutrient, may deserve a greater focus in weight management research and clinical strategies. Obesity is known to be associated with several comorbidities, including type 2 diabetes, hypertension, coronary heart disease, arterial disease, and several types of cancer [14,15,16]. High blood pressure is a major risk factor for cardiovascular disease. It is the leading cause of increasing morbidity and mortality worldwide. Emerging evidence suggests an association between blood pressure and hydration status. Fluid retention is a major contributor to essential hypertension and adversely affects the cardiovascular system [17,18,19]. This is of concern as cardiovascular disease is the leading cause of death worldwide.

Therefore, the aim of this study was to search for associations between the frequency of consumption of non-alcoholic beverages, blood pressure, anthropometric measurements, blood and urine biochemical analyses related to hydration and health status, and the number of MetS components in adults diagnosed with metabolic disorders.

2. Materials and Methods

2.1. Study Design and Participants

This convenience-sampled cross-sectional study was conducted among 290 participants, 170 women and 120 men, aged 18–70 years. The study group was recruited from patients being treated at the Metabolic Diseases Outpatient Clinic of the Czerniakowski Hospital in Warsaw for diagnosed metabolic disorders. These were adults with at least one of the following diagnoses: diabetes, hypertension, overweight/obesity, circulatory failure, hypertension, hyperglycemia, and/or dyslipidemia. The participants were mainly from Warsaw but also from other towns and cities in Poland. The observational study was conducted from May 2017 to February 2020 in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of the Faculty of Human Nutrition and Consumer Sciences, Warsaw University of Life Sciences, Warsaw, Poland, on 11 April 2017 (Resolution No. 04p/2017).

Inclusion criteria were Caucasian, aged 18–70 years, diagnosed with at least one metabolic disorder, and able to sign an informed consent form to participate in the study. Exclusion criteria were inability to give consent to participate in the study, diagnosed with acute or chronic renal failure, cancer, irritable bowel syndrome, use of corticosteroids, diuretics or other medications that could affect the results of this study, vomiting, diarrhea or fever in the last 3 days or being confined to a bed or chair, pregnant or breastfeeding, and missing or incomplete participant data. Due to the BIA measurement, people with endoprosthesis or a pacemaker, stent, or metal suture in their heart/blood vessels were also excluded. Detailed information on sample recruitment and the methods and procedures used have been published previously [20].

2.2. Sociodemographic, Lifestyle, and Health Data

The survey method was used to collect general information about the respondents. Respondents were asked about age (continuous variable), sex (women or men), level of education (primary/vocational, secondary/‘I study’, or higher), place of residence (village, town, or city), self-reported economic status (very poor/poor, average, or very good), self-reported physical activity (no/low or moderate/high), and self-reported health status (poor, average, or good/very good).

2.3. Non-Alcoholic Beverage Consumption Data

Dietary habits were assessed using a food frequency questionnaire (FFQ) adapted from the validated Dietary Habits and Nutrition Beliefs Questionnaire KomPAN [21,22,23]. Beverage consumption data were collected using a food frequency questionnaire (FFQ) (0—never; 1—<1 serving/month; 2—1–3 servings/month; 3—1–2 servings/week; 4—3–4 servings/week, 5—5 servings/week; 6—1 serving/day; 7—≥2 servings/day). Information was collected from the respondents on the frequency of consumption of non-alcoholic beverages, i.e., tea, coffee, milk, fermented milk drinks (natural or flavored), mineral water (carbonated or non-carbonated), juices (fruit, vegetable, or fruit and vegetable), non-carbonated fruit drinks, fruit nectars, sweetened carbonated drinks, tea drinks, cola drinks, energy drinks, and isotonic drinks. Subjects completed the FFQ in the presence of the same person—a well-trained dietician and hospital staff member. This was the basis for eliminating errors and standardizing the procedure for completing the questionnaire by all respondents. In addition, direct contact with the dietitian helped to clarify any doubts about how to complete the questionnaire.

2.4. Dietary Patterns

Dietary patterns (DPs) were distinguished using k-means analysis and included the frequency of consumption of 17 non-alcoholic beverages: tea, coffee, milk, fermented milk drinks (natural or flavored), mineral water (carbonated or non-carbonated), juices (fruit, vegetable, or fruit and vegetable), non-carbonated fruit drinks, fruit nectars, sweetened carbonated drinks, tea drinks, cola drinks, energy drinks, and isotonic drinks. Four dietary patterns were created: (1) ProHealthy, characterized by the highest frequency of consumption of coffee, milk, natural fermented milk drinks, still mineral water, and vegetable juices; (2) Sweet, characterized by the highest frequency of consumption of flavored fermented milk drinks, fruit juice, still fruit drinks, fruit nectars, sweetened carbonated drinks, tea drinks, cola drinks, energy drinks, and isotonic drinks and the lowest frequency of consumption of tea, coffee, natural fermented milk drinks, and fruit and vegetable juices; (3) Prudent, characterized by the highest frequency of consumption of tea, carbonated mineral water, and vegetable juice and the lowest frequency of consumption of fruit and vegetable juice; (4) Low Sweet, characterized by the lowest frequency of consumption of milk, fruit juice, non-carbonated fruit drinks, fruit nectars, sweetened carbonated drinks, tea drinks, cola drinks, energy drinks, and isotonic drinks.

2.5. Anthropometric Measurements

During the study, selected anthropometric measurements were collected, such as body weight (BW), height (H), waist circumference (WC), and arm grip strength (HGS). All anthropometric measurements were performed according to standard procedures with the participation of qualified researchers. Measurements were taken in light clothing and without shoes. Mean values were calculated from the two measurements taken [24]. BW was measured to the nearest 0.1 kg using an electronic digital scale (SECA 799, Hamburg, Germany), while H was measured using a stadiometer and recorded to the nearest 0.1 cm (SECA 220, Hamburg, Germany).

BMI was classified according to WHO adult standards: BMI < 18.5 kg/m² was interpreted as underweight, 18.5–24.9 kg/m²—normal body weight, 25.0–29.9 kg/m²—overweight, 30.0–34.9 kg/m²—first-degree obesity, 35.0–39.9 kg/m²—second-degree obesity, and BMI ≥ 40.00 kg/m² was interpreted as third-degree obesity [25]. WC was measured with a non-stretchable and tensile-resistant tape that provided constant tension (SECA 201, Hamburg, Germany). HGS (kg) was measured to the nearest 0.5 kg at maximum effort using a hydraulic hand dynamometer (SAEHAN Corporation, Masan, Changwon, Republic of Korea). A rest period of approximately 2 min was allowed between each HGS measurement [26].

2.6. BIA Measurements

Individual total body water (TBW in % and L) was assessed using a Tanita portable, single-frequency (50 kHz), eight-point analyzer (Tanita BC-418 MA, Tanita Co., Tokyo, Japan) according to BIA measurement procedures. BIA was performed under standardized conditions according to the manufacturer’s protocol [27].

2.7. Blood Pressure Measurements

Systolic and diastolic blood pressures were measured with the patient in a seated position using a standardized automatic sphygmomanometer SureSigns VM6 Cardiac Monitor (Philips Medical Systems, 3000 Minuteman Road, Andover, MA 01810, USA) after a 10 min rest period. Three readings were taken 2 min apart and the average of the last 2 readings was recorded. The cuff was adjusted according to the circumference of the arm and placed on the middle third of the upper arm. The patient was seated comfortably, without crossing their legs, with their arm resting on a table at heart level. The patient was relaxed, had an empty bladder, and had not recently smoked or taken any stimulants. Reference values for blood pressure were <130 mmHg systolic blood pressure (SBP) and <85 mmHg diastolic blood pressure (DBP) in women and men [28,29].

2.8. Biochemical Analysis

Blood samples for glucose, triglycerides (TG), high-density cholesterol (HDL-C), hematocrit (HCT), uric acid, sodium (Na), potassium (K), creatinine, urea, and serum osmolality (Sosm) were obtained from the ulnar vein between 7 and 9 am after an overnight fast (10–12 h) using standard techniques. Blood was centrifuged at 5000 rpm for 10 min at 4 °C and stored frozen (−80 °C) for subsequent analysis. All biochemical analyses were performed by a certified laboratory using standard methods with accepted reference values for glucose: 70–99 mg/dL in women and men, TG: <150 mg/dL in women and men, HDL-C: >40 mg/dL in men and >50 mg/dL in women, HCT: 37–47% in women and 40–54% in men, uric acid: 2.7–6.1 mg/dL in women and 3.7–8.0 mg/dL in men, Na: 132–146 mmol/L in women and men, K: 3.5–5.5 mmol/L in women and men, creatinine: 0.6–1.1 mg/dL in women and 0.7–1.3 mg/dL in men, and urea: 10–50 mg/d [30,31,32,33,34,35].

Urine for assessment of urine-specific gravity (USG), pH, and urine osmolality (Uosm) was collected in the morning, with the first fraction discarded. Urine samples collected in this way were secured (labelled) and stored frozen (−20 °C) for subsequent analysis. USG and pH were performed by a certified laboratory using standard methods with accepted reference values for USG: 1.010–1.030 g/cm³ and pH: 5.0–7.5 [36].

Uosm and Sosm osmolality were determined using a freezing point osmometer (cryoscopic method) (Marcel OS3000 osmometer, Warsaw, Poland). Uosm greater than 800 mOsm/kg is considered dehydrated, while values less than 800 mOsm/kg indicate normal hydration status [37,38]. A Sosm of 275 to <295 mOsm/kg indicates euhydration, 295–300 mOsm/kg mild dehydration, and >300 mOsm/kg dehydration [36].

2.9. Metabolic Syndrome

According to the definitions of Panel III of the National Cholesterol Education Program for the Treatment of Adults (NCEP ATP III) [31] and the diagnostic criteria established in 2009 [30], MetS can be recognized when any three of the following criteria are present: WC (cm) ≥ 80 in women or ≥94 in men, glucose (mg/dL) ≥ 100, TG (mg/dL) ≥ 150, HDL-C (mg/dL) < 50 in women or <40 in men, and blood pressure (mmHg) ≥ 130 SBP or ≥85 DBP. It was also assumed that if the patient was taking medication for this constituent (MetS criterion), it would be assigned to the invalid constituent status.

2.10. Statistical Analysis

All the statistical analyses were conducted using STATISTICA 13.3 computer software (TIBCO Software Inc., StatSoft, Palo Alto, CA, USA) with a signification level fixed at 0.05. The normality of distribution was examined using the Shapiro–Wilk test. Results are presented as mean and standard deviation (SD) for continuous or data sample proportion (%) for categorical data. Sex and the number of MetS components were the basis for the division into study groups—MetS 3, MetS 4, and MetS 5. Differences between groups were tested using the Pearson’s chi-squared test (categorical data), the Mann–Whitney U test (continuous data, for two groups), or the Kruskal–Wallis test (continuous data, for more than two groups). The partial correlation between biochemical analysis, anthropometric measurements, and the number of MetS components was explored using the Spearman correlation test.

3. Results

3.1. Study Group Characteristics

There were 170 women and 120 men in the study group. The mean age of the participants was 55.2 years. Considering the components of the MetS, 190 of the participants had three MetS components, 70 had four MetS components, and 30 had five MetS components. There were statistically significant differences between the subgroups. There was a significantly higher percentage of women with three MetS components compared to men. A significantly higher percentage of women with three MetS components had higher education (42%) or moderate/higher physical activity (38%) (

Table 1. Study population characteristics by sex and MetS components.

	Women (n = 170)							Men (n = 120)
	MetS 3 (n = 119)		MetS 4 (n = 33)		MetS 5 (n = 18)			MetS 3 (n = 71)		MetS 4 (n = 37)		MetS 5 (n = 12)
Variable	n	%	n	%	n	%	p-Value	n	%	n	%	n	%	p-Value
Age (years)		50.1 ± 14.1		55.9 ± 11.0		61.3 ± 7.2	0.012 1		53.1 ± 12.9		55.6 ± 10.8		54.1 ± 11.7	0.989 1
Education (%)
primary/vocational	21	18	5	15	3	17		15	21	13	35	7	58
secondary/‘I study’	48	40	23	70	10	55	0.031 2	31	44	13	35	1	8	0.055 2
higher	50	42	5	15	5	28		25	35	11	30	4	34
Place of residence (%)
village	12	10	0	0	1	6		12	17	1	3	0	0
town	18	15	7	21	2	11	0.328 2	8	11	7	19	3	25	0.093 2
city	89	75	26	79	15	83		51	72	29	78	9	75
Health status—self-assessment (%)
poor	17	14	11	33	3	17		10	14	7	19	1	8
average	75	63	17	52	13	72	0.107 2	40	56	20	54	10	84	0.411 2
good/very good	27	23	5	15	2	11		21	30	10	27	1	8
Physical activity—self-assessment (%)
now/low	81	68	28	85	17	95	0.017 2	55	77	25	68	10	83	0.413 2
moderate/high	38	32	5	15	1	5		16	23	12	32	2	17
Economic status—self-assessment (%)
very poor/poor	12	10	3	9	4	22		4	6	6	16	1	8
average	66	56	23	70	9	50	0.302 2	35	49	13	35	9	75	0.078 2
good/very good	41	34	7	21	5	28		32	45	18	49	2	17
BMI (kg/m2)		28.06 ± 7.74 26.00 a		33.35 ± 7.40 32.70 b		35.31 ± 7.91 34.3 b	0.001 1		28.51 ± 5.19 28.20 a		32.64 ± 5.47 31.50 b		35.02 ± 6.24 34.30 b	0.009 1
BMI (%)
<18.5 (kg/m2)	9	8	0	0	0	0		2	3	0	0	0	0
18.5–24.9 (kg/m2)	44	37	4	12	2	11		18	25	0	0	0	0
25.0–29.9 (kg/m2)	23	19	6	18	2	11		24	34	14	38	3	25
30.0–34.9 (kg/m2)	19	16	10	30	6	33	0.009 2	19	27	13	35	3	25	0.011 2
35.0–39.9 (kg/m2)	13	11	6	18	3	17		8	11	4	11	4	33
≥40.0 (kg/m2)	11	9	7	22	5	28		0	0	6	16	2	17
DPs (%)
ProHealthy	58	49	13	40	8	45		17	24	11	29	2	17
High Sweet	7	6	3	9	0	0	0.855 2	16	23	8	22	4	33	0.855 2
Prudent	22	18	7	21	4	22		16	23	10	27	2	17
Low Sweet	32	27	10	30	6	33		22	30	8	22	4	33

MetS, metabolic syndrome; BMI, body mass index; DPs, dietary patterns; ^a,b, different letters indicate significant differences at p ≤ 0.05; ¹, the Kruskal–Wallis test; ², the Pearson chi-squared test.

). The highest percentage of participants with normal body weight was found among adults with three MetS components (37% in women and 25% in men), while those with five MetS components had a higher incidence of obesity (≥30 kg/m²) compared to other components. However, there were no significant differences in place of residence, health status, economic status, and DPs according to the number of MetS components in women and men.

3.2. Frequency of Non-Alcoholic Beverage Consumption and Dietary Patterns

Table 2. Frequency of consumption of selected non-alcoholic beverages and dietary patterns by sex and MetS components.

Variable	Women (n = 170)			p-Value	Men (n = 120)			p-Value
	MetS 3 (n = 119)	MetS 4 (n = 33)	MetS 5 (n = 18)		MetS 3 (n = 71)	MetS 4 (n = 37)	MetS 5 (n = 12)
Tea	6.3 ± 1.1	6.5 ± 1.6	6.3 ± 1.5	0.849	6.2 ± 1.5	6.9 ± 1.3	5.5 ± 1.1	0.516
Coffee	5.4 ± 1.5	4.8 ± 1.5	5.2 ± 1.9	0.302	4.8 ± 1.0	3.9 ± 0.9	4.1 ± 1.2	0.174
Milk	3.8 ± 1.9	3.2 ± 1.0	3.9 ± 1.1	0.524	3.2 ± 0.8	3.6 ± 0.7	1.9 ± 0.2	0.199
Natural fermented milk drinks	3.6 ± 1.3	3.9 ± 1.2	4.6 ± 1.1	0.238	3.5 ± 0.9	3.7 ± 0.7	2.9 ± 0.4	0.662
Flavoured fermented milk drinks	1.1 ± 0.5	0.6 ± 0.2	0.9 ± 0.4	0.275	0.7 ± 0.4	0.5 ± 0.2	0.8 ± 0.4	0.824
Carbonated mineral water	2.0 ± 0.6	1.9 ± 0.3	2.1 ± 0.4	0.964	3.6 ± 0.7	3.5 ± 0.8	3.3 ± 0.6	0.986
Non-carbonated mineral water	5.8 ± 1.2	5.2 ± 1.5	2.9 ± 1.7	0.313	4.8 ± 1.6	4.9 ± 1.7	5.5 ± 1.4	0.811
Fruit juices	1.6 ± 0.3	1.4 ± 0.3	1.8 ± 0.5	0.814	1.4 ± 0.1	1.6 ± 0.3	1.1 ± 0.6	0.618
Vegetable juices	0.9 ± 0.3	1.0 ± 0.4	1.4 ± 0.6	0.481	0.6 ± 0.2	1.4 ± 0.3	0.7 ± 0.4	0.580
Fruit and vegetable juices	1.6 ± 0.3	1.4 ± 0.4	1.8 ± 0.5	0.653	1.4 ± 0.3	1.9 ± 0.5	2.3 ± 0.6	0.036
Fruit nectars	0.5 ± 0.2	0.5 ± 0.3	0.2 ± 0.1	0.823	0.4 ± 0.2	0.6 ± 0.3	0.2 ± 0.1	0.517
Non-carbonated fruit drinks	0.6 ± 0.4	0.3 ± 0.1	0.2 ± 0.1	0.552	0.3 ± 0.1	0.7 ± 0.4	1.1 ± 0.7	0.316
Sweetened carbonated drinks	0.4 ± 0.2	0.5 ± 0.3	0.2 ± 0.1	0.795	1.0 ± 0.5	1.1 ± 0.7	0.7 ± 0.4	0.239
Tea drinks	1.3 ± 0.1	1.8 ± 0.3	1.2 ± 0.1	0.048	0.6 ± 0.4	0.5 ± 0.2	0.3 ± 0.2	0.930
Cola drinks	0.8 ± 0.3	1.3 ± 0.4	0.9 ± 0.3	0.092	2.0 ± 0.6	1.0 ± 0.5	3.0 ± 0.9	0.114
Energy drinks	0.2 ± 0.1	0.3 ± 0.1	0.2 ± 0.1	0.402	0.7 ± 0.4	0.3 ± 0.1	0.6 ± 0.3	0.608
Isotonic drinks	0.2 ± 0.1	0.2 ± 0.1	0.2 ± 0.1	0.592	0.9 ± 0.3	0.5 ± 0.2	0.8 ± 0.3	0.207
Dietary patterns (%)
ProHealthy	49	39	44		24	30	17
High Sweet	6	9	0	0.856	23	22	33	0.758
Prudent	19	21	22		23	27	17
Low Sweet	26	31	34		30	21	33

MetS, metabolic syndrome; p-value, the Kruskal–Wallis test; significant difference p ≤ 0.05.

shows the average frequency of consumption of selected non-alcoholic beverages and DPs according to the number of MetS components. The average frequency of consumption of selected beverages was as follows: tea, coffee, and still mineral water—several times a day; milk, natural fermented milk drinks, and carbonated mineral water—several times a week; fruit juices, fruit and vegetable juices, tea drinks, and cola drinks—several times a month. We found statistically significant differences between the frequency of tea consumption in women and fruit and vegetable juices in men and MetS components. We observed the highest frequency of consumption of tea drinks with four MetS components in women and fruit and vegetable juices with five MetS components in men. In addition, statistically significant differences were found between the frequency of consumption of milk (p = 0.021), carbonated mineral water (p = 0.026), sweetened carbonated drinks (p = 0.007), and cola drinks (p = 0.004), and sex with three MetS components. The DPs did not differ in the groups of women and men according to the number of MetS components. However, there was a tendency for the ProHealthy DP to dominate in women with four MetS components compared with men (p = 0.074).

3.3. Anthropometric Measurements, Biochemical Analysis, and MetS

Blood pressure, selected anthropometric measurements, and biochemical analyses of blood and urine according to sex and number of MetS components are shown in

Table 3. Blood pressure, selected anthropometric measurements, and biochemical analyses according to sex and components of MetS.

Variable	Women (n = 170)			p-Value	Men (n = 120)			p-Value
	MetS 3 (n = 119)	MetS 4 (n = 33)	MetS 5 (n = 18)		MetS 3 (n = 71)	MetS 4 (n = 37)	MetS 5 (n = 12)
Blood pressure and anthropometric measurements
SBP (mmHG)	129.7 ± 18.3 125.0 a	139.7 ± 15.9 137.0 b	149.2 ± 14.8 146.0 c	<0.001	129.4 ± 16.8 125.0 a	138.2 ± 17.3 138.0 b	150.1 ± 18.5 143.5 b	0.001
BMI (kg/m2)	28.05 ± 7.74 26.00 a	33.35 ± 7.40 32.7 b	35.31 ± 7.91 34.3 b	<0.001	28.51 ± 5.19 28.20 a	32.64 ± 5.47 31.50 b	35.02 ± 6.25 34.30 b	0.002
HGS (kg)	27.38 ± 7.02 28.00 a	26.85 ± 5.99 28.00 a	25.94 ± 7.04 27.00 a	0.705	43.8 ± 10.9 42.0 a	42.9 ± 10.9 41.0 a	41.8 ± 10.5 43.0 a	0.850
TBW (%)	47.59 ± 7.55 47.2 a	42.77 ± 5.63 41.5 b	42.34 ± 5.89 41.2 b	0.001	55.24 ± 6.13 55.20 a	51.62 ± 5.14 51.90 b	50.90 ± 4.95 50.75 b	0.002
TBW (L)	35.40 ± 5.23 35.60 a	37.14 ± 5.21 37.00 a	38.45 ± 5.37 37.15 a	0.063	49.02 ± 7.47 48.20 a	52.72 ± 7.76 51.40 a	54.75 ± 11.23 53.4 a	0.073
Blood
HCT (%)	38.35 ± 4.78 38.80 a	38.30 ± 5.16 38.80 a	38.89 ± 5.14 38.00 a	0.927	40.51 ± 6.51 41.20 a	40.37 ± 5.78 41.30 a	39.97 ± 6.65 40.70 a	0.922
Uric acid (mg/dL)	5.09 ± 1.63 5.20 a	6.00 ± 2.29 5.90 b	5.28 ± 1.39 5.80 b	0.050	6.05 ± 1.80 6.00 a	6.56 ± 2.29 6.20 a	6.53 ± 1.92 6.95 a	0.468
Na (mmol/L)	139.88 ± 3.59 140.00 a	139.93 ± 3.48 141.00 a	138.56 ± 2.57 139.00 a	0.086	138.49 ± 5.35 140.00 a	138.54 ± 4.93 139.00 a	139.58 ± 3.61 140.00 a	0.698
K (mmol/L)	4.23 ± 0.41 4.20 a	4.26 ± 0.38 4.20 a	4.50 ± 0.55 4.32 a	0.165	4.34 ± 0.50 4.30 a	4.35 ± 0.65 4.40 a	4.22 ± 0.32 4.16 a	0.725
Creatinine (mg/dL)	0.85 ± 0.53 0.70 a	0.95 ± 0.47 0.80 a	0.87 ± 0.34 0.80 a	0.201	1.05 ± 0.42 1.00 a	1.03 ± 0.42 1.00 a	1.39 ± 0.85 1.00 a	0.683
Urea (mg/dL)	35.1 ± 19.8 32.0 a	43.1 ± 21.4 40.0 b	43.3 ± 28.8 36.0 b	0.049	43.5 ± 27.4 36.0 a	40.8 ± 20.0 36.0 a	52.7 ± 40.9 37.0 a	0.883
Sosm (mOsm/kg)	286.16 ± 6.28 285.00 a	287.61 ± 6.38 287.00 a	285.72 ± 6.34 285.00 a	0.421	287.51 ± 4.99 287.00 a	287.11 ± 5.86 287.00 a	290.83 ± 4.84 291.00 a	0.076
Urine
Uosm (mOsm/kg)	536 ± 228 515	504 ± 221 471	479 ± 239 404	0.554	597 ± 258 577 a	498 ± 153 514 a	635 ± 281 745 a	0.080
pH	6.1 ± 0.70 6.0 a	6.0 ± 0.7 6.0 a	5.9 ± 0.6 6.0 a	0.648	6.1 ± 0.7 6.0 a	5.9 ± 0.7 6.0 a	5.6 ± 0.9 5.5 b	0.026
USG (g/cm3)	1.017 ± 0.015 1.015 a	1.019 ± 0.010 1.020 a	1.014 ± 0.008 1.010 a	0.133	1.017 ± 0.008 1.015 a	1.020 ± 0.008 1.020 a	1.015 ± 0.009 1.010 b	0.045

MetS, metabolic syndrome; SBP, systolic blood pressure; BMI, body mass index; HGS, handgrip strength of arm muscles; TBW, total body water; HCT, hematocrit; Na, sodium; K, potassium; Sosm, serum osmolality; Uosm, urine osmolality; USG, urine-specific gravity; ^a,b,c, different letters indicate significant differences at p ≤ 0.05; p-value, the Kruskal–Wallis test.

. Regardless of sex, SBP and BMI differed significantly and the highest values were observed in subgroups with five MetS components. However, TBW (%) was lowest in women and men with four and five MetS components. Furthermore, there were statistically significant differences in uric acid and urea levels in women, and in urine pH and USG in men, between each MetS subgroup. The lowest uric acid and urea were observed in women with three MetS components, while the lowest pH was observed in men with five MetS components and the highest USG in men with four MetS components. Moreover, in men, there was a tendency for the highest Uosm or Sosm to correlate with five MetS components. The analyses also revealed significant differences between women and men for the following parameters: HGS (p < 0.001), TBW (p < 0.001), HCT (p = 0.001), uric acid (p < 0.001), creatinine (p < 0.001), and urea (p = 0.014) with three MetS components.

Table 4. Partial Spearman correlation coefficients between the variables analyzed, adjusted for sex and age.

Variables	SBP	DBP	BMI	WC	HGS	TBW	HCT	Uric Acid	Na	K	Creatinine	Urea	Sosm	Uosm	pH	USG	MetS
Blood pressure and anthropometric measurements
SBP	1.000	0.576 ***	0.150 *	0.176 *	0.134 *	−0.095	−0.002	−0.002	0.074	0.019	−0.086	−0.027	0.066	0.026	0.082	−0.029	0.347 **
DBP	0.576 ***	1.000	0.267 *	0.258 *	0.152 *	−0.239 *	0.091	0.010	0.067	0.027	−0.190 *	−0.186 *	−0.057	0.020	0.079	0.050	0.247 *
BMI (km/m2)	0.150 *	0.267 *	1.000	0.891 ***	0.171 *	−0.833 ***	0.181 *	0.361 **	0.052	−0.001	0.022	0.032	0.079	0.168 *	−0.148 *	0.026	0.475 ***
WC	0.176 *	0.258 *	0.891 ***	1.000	0.187 *	−0.812 ***	0.141 *	0.396 **	0.062	−0.029	0.031	0.014	0.036	0.126 *	−0.133 *	0.054	0.553 ***
HGS	0.134 *	0.152 *	0.171 *	0.187 *	1.000	−0.173 *	0.122	0.092	0.158 *	0.045	0.060	−0.059	0.151 *	0.126	0.122	−0.071	0.073
TBW	−0.095	−0.239 *	−0.833 ***	−0.812 ***	−0.173 *	1.000	−0.186 *	−0.280 *	−0.068	0.011	−0.013	−0.000	−0.045	−0.170 *	0.039	−0.023	−0.414 ***
Blood
HCT	−0.002	0.091	0.181 *	0.141 *	0.122	−0.186 *	1.000	0.091	−0.012	0.084	−0.100	−0.127 *	−0.013	0.137 *	0.070	−0.018	0.118
Uric acid (mg/dL)	−0.002	0.010	0.361 **	0.396 **	0.092	−0.280 *	0.091	1.0000	0.127 *	−0.075	0.195 *	0.205 *	0.057	−0.017	−0.066	−0.008	0.170 *
Na (mmol/L)	0.074	0.067	0.052	0.062	0.158 *	−0.068	−0.012	0.127 *	1.000	−0.049	−0.081	−0.026	0.127 *	0.131 *	0.046	0.114	−0.022
K (mmol/L)	0.019	0.027	−0.001	−0.029	0.045	0.011	0.084	−0.075	−0.049	1.000	0.217 *	0.152 *	0.008	−0.053	−0.070	−0.014	0.052
Creatinine (mg/dL)	−0.086	−0.190 *	0.022	0.031	0.060	−0.013	−0.100	0.195 *	−0.081	0.217 *	1.000	0.796 ***	0.229 *	−0.173 *	−0.105	−0.114	0.053
Urea (mg/dL)	−0.027	−0.186 *	0.032	0.014	−0.059	−0.000	−0.127 *	0.205 *	−0.026	0.152 *	0.796 ***	1.000	0.223 *	−0.075	−0.101	−0.019	0.028
Sosm (mOsm/kg)	0.066	−0.057	0.079	0.036	0.151 *	−0.045	−0.013	0.057	0.127 *	0.008	0.229 **	0.223 *	1.000	0.077	−0.056	−0.131 *	0.043
Urine
Uosm (mOsm/kg)	0.026	0.020	0.168 *	0.126 *	0.126	−0.170 *	0.137 *	−0.017	0.131 *	−0.053	−0.173 *	−0.075	0.077	1.000	−0.052	0.166 *	−0.028
pH	0.082	0.079	−0.148 *	−0.133 *	0.122	0.039	0.070	−0.066	0.046	−0.070	−0.105	−0.100	−0.056	−0.052	1.000	−0.170 *	−0.143 *
USG (g/cm3)	−0.029	0.050	0.026	0.054	−0.071	−0.023	−0.018	−0.008	0.1149	−0.014	−0.114	−0.019	−0.131 *	0.166 *	−0.170 *	1.000	0.016
Other
MetS	0.347 **	0.247 *	0.475 ***	0.553 ***	0.073	−0.414 ***	0.118	0.170 *	−0.022	0.052	0.053	0.028	0.043	−0.028	−0.143 *	0.016	1.000
DPs	−0.071	−0.083	0.017	0.014	0.043	−0.014	−0.058	−0.003	0.058	−0.042	0.033	0.039	0.075	−0.059	−0.011	−0.073	0.018

SBP, systolic blood pressure; DBP, diastolic blood pressure; BMI, body mass index; WC, waist circumference; HGS, handgrip strength of arm muscles; TBW, total body water; HCT, hematocrit; Na, sodium; K, potassium; Sosm, serum osmolality; Uosm, urine osmolality; USG, urine-specific gravity; MetS, metabolic syndrome; DPs, dietary patterns; * p ≤ 0.05; ** p ≤ 0.01; *** p ≤ 0.001.

shows Spearman’s partial correlation coefficients with blood pressure, selected anthropometric measurements, biochemical analyses of blood and urine, the number of MetS components, and DPs, adjusted for age and sex. There was a positive correlation between MetS components and SBP (0.347, p ≤ 0.01), DBP (0.247, p ≤ 0.05), BMI (0.475, p ≤ 0.001), WC (0.553, p ≤ 0.001), and uric acid (0.170, p ≤ 0.05) and a negative correlation with TBW (−0.414, p < 0.001) and pH (−0.143, p ≤ 0.05). There was also a strong negative correlation between TBW and BMI (−0.833, p ≤ 0.001) and TBW and WC (−0.812, p ≤ 0.001) and a positive correlation between urea and creatinine (0.796, p ≤ 0.001). Based on correlations, DPs did not differ significantly according to hydration status as measured by different parameters.

4. Discussion

This study provides interesting insights into the associations between the frequency of consumption of non-alcoholic beverages, blood pressure, selected anthropometric measurements, biochemical analyses related to health and hydration status, and the number of MetS components in adults diagnosed with metabolic disorders. We observed the highest frequency of consumption of tea drinks in women with four MetS components and fruit and vegetable juices in men with five MetS components. We identified four DPs in the study group: ProHealthy, High Sweet, Prudent, and Low Sweet. The DPs did not differ in women and men according to the number of MetS components. However, we found a tendency for the ProHealthy DP to dominate in women compared to men. Moreover, SBP and BMI differed significantly, and the highest values were noted in subgroups with five MetS components. However, TBW was lowest in women and men with four and five MetS components. The lowest uric acid and urea were observed in women with three MetS components, whereas the lowest pH was observed in men with five MetS components and the highest USG was seen in men with four MetS components. In addition, there was a tendency for the highest Uosm or Sosm to be seen in men with five MetS components. Based on correlations, DPs did not differ significantly according to hydration status as measured by different parameters; however, we found a strong negative correlation between TBW and BMI and TBW and WC.

In our study, we showed that statistically, the highest percentages of participants with three MetS components were the youngest, women, and women with moderate/high physical activity, compared to participants with a different number of MetS components. Research shows that age and gender (male) are factors that significantly influence the likelihood of developing metabolic syndrome [39]. MetS used to affect adults and older people, but more recently, it is affecting an increasingly younger group of people, including children [40,41]. However, the most influential factors are poor diet and lack of physical activity. In our study, the vast majority of women with five MetS components reported no or low physical activity. The results of many previous studies show that regular moderate physical activity is recommended for the treatment of MetS, whereas low levels of physical activity may be a risk factor for the development of MetS [31].

Diet plays an important role in the prevention and treatment of adults diagnosed with metabolic disorders. Studies have shown that unhealthy behaviors are associated with a higher incidence of metabolic syndrome and healthier diets are associated with a lower risk of metabolic syndrome [42,43]. Our study showed the highest frequency of consumption of tea drinks in women with four MetS components and fruit and vegetable juices in men with five MetS components. Both tea drinks and fruit and vegetable juices contain sugar, and consumption of products with a high glycaemic index, such as sugar-sweetened beverages, is associated with rapid carbohydrate release, an increase in blood glucose concentration, and an increase in insulin secretion. This can lead to insulin resistance, which is associated with MetS. It seems that a desirable approach would be to modify diet, as this is one of the factors that may contribute to the development of MetS [44]. In addition to diet, another factor that may contribute to the development of MetS is lack of or low physical activity. As the results show, regular moderate physical activity is recommended in the treatment of MetS [31,45].

We found that SBP and BMI differed significantly and the highest values were observed in subgroups with five MetS components. However, TBW was lowest in women and men with four and five MetS components. Moreover, we observed a strong negative correlation between TBW and BMI and TBW and WC. As we know, MetS has been defined on the basis of the following risk factors, among others: hypertension and obesity, which are associated with increased WC parameters and BMI. Our study group consisted mainly of overweight and obese people, and there was a noticeable increase in the percentage of these people with MetS components. It was also shown that as MetS increased, TBW, measured by the impedance method, decreased in both women and men. In addition, in men, significant mild dehydration was found in the group of people with four MetS components, based on BIA, and a tendency towards the highest values of Uosm and Sosm (towards dehydration) in men with five MetS components. As the research shows, regardless of how the body’s hydration status was measured, i.e., impedance, Sosm, Uosm, or ultrasound, people with an elevated BMI were characterized by an inadequate hydration status [14,15,16,46,47]. However, they all suggest an association between hydration status and adiposity that should be considered in research and clinical contexts, despite these important differences between studies. Rosinger et al. [15] examined the role of obesity in the relationship between total water intake (from food and fluids) and urine osmolality in adults over 20 years of age. Their conclusion was that obesity is associated with water intake and hydration status. The researchers showed that obese adults may need to consume more water than adults who are underweight or of normal weight in order to achieve similar hydration gains, which may not be enough to meet their increased needs [15]. In our study, we did not assess food intake, but we can speculate that obese people may have consumed smaller amounts of food and water-rich products and may have been more likely to choose energy-dense products, as indicated by WC and BMI parameters. In turn, hypertension is associated with an increased risk of cardiovascular disease and is a leading cause of increasing morbidity and mortality worldwide. Fluid retention plays a role in the pathogenesis of primary hypertension. Furthermore, fluid retention is known to have adverse effects on the cardiovascular system independent of blood pressure levels. Mohammedin et al. [18] found a strong association between hypertension status and hydration parameters. Hypertensive subjects tended to have a lower percentage of total body water (bioimpedance value) than normotensive subjects. On the other hand, Dizdar et al. [48] found that 50 primary hypertensive patients in the negative hydration group had significantly lower blood pressure. Meanwhile, Billington et al. [49] found that antihypertensive treatment was safe in dehydrated patients, with no abrupt changes in blood pressure in 4011 patients with acute stroke and elevated systolic blood pressure. The above data may encourage further research into the relationship between hypohydration and the pathophysiology of cardiovascular disease. This finding should raise awareness of proper hydration, as hypohydration may be a causative factor in hypertension.

We observed that women with four or five MetS components had significantly higher uric acid and urea levels than women with three MetS components. Uric acid not only causes gout but can also contribute to the development of cardiovascular diseases such as hypertension, heart failure, coronary heart disease and death from cardiovascular causes, and chronic kidney disease. The concentration of uric acid in blood serum depends on the degree of glomerular filtration and the intensity of purine catabolism. Uric acid in the extracellular fluid exists as sodium salt at a concentration close to saturation, so as the concentration increases, it readily crystallizes as sodium urate and accumulates in the joints or kidneys. People with diabetes, high blood pressure, obesity, and an unhealthy lifestyle are particularly susceptible to elevated blood levels of uric acid. Some clinical studies suggest serum uric acid as a marker for the prevention of the more severe form of MetS [50,51]. Urea, the end product of protein metabolism, is composed of ammonia and carbon dioxide. In the urea cycle, proteins are broken down into amino acids, which are then broken down into keto acids and ammonia, which are toxic to the body. Ammonium ions are then transported to the liver, where they are converted to the less toxic urea. Urea is transported with the blood to the kidneys, where it is filtered and removed from the body with urine, while a small amount is excreted in sweat. The test is mainly used in patients who need to be diagnosed because of suspected kidney abnormalities, heart failure, or metabolic diseases. Elevated urea levels may also indicate dehydration [34,35,52]. Future research focusing on patients with elevated uric acid and urea levels and a high risk of cardiovascular disease seems justified and worth considering as part of biochemical testing, especially in people with overweight/obesity, hypertension, and diabetes. These people should also be advised to control their body weight and maintain adequate hydration, excluding sweetened and alcoholic beverages.

Strengths and Limitations

The relatively homogeneous group with MetS treated at the Metabolic Diseases Outpatient Clinic is the strength of our study. It is worth noting that the respondents did not come from all over Poland, but the study reflects the demographics and social diversity of the Polish population. Another strength was that the research was conducted face-to-face and not online. In case of doubt when filling in the questionnaire, the respondents could ask questions about points they did not understand, and the anthropometric measurements were carried out by a trained person and did not rely on the patient’s self-assessment. In addition, the innovative approach used in this study should be emphasized, as there are few studies in this area on people with metabolic disorders. We used several measurements to assess hydration, including TBW, Sosm, HCT, Na, K, Uosm, and USG, and to assess health status, including SBP, DBP, WC, BMI, uric acid, and urea.

There are several limitations to our study. First, our study sample was not large, and some may argue that it was not large enough to detect statistical significance. However, the sample size was in accordance with the guidelines set by the ethics committee. Secondly, due to the recruitment method used in the study, it was not possible to calculate the response rate and reasons for refusal. Therefore, it cannot be excluded that this study is aimed at a group of adults who are more likely to respond but included people with metabolic problems who came to the outpatient clinic. A certain limitation of the study was that the project plan did not include an assessment of the participants’ food consumption, so there is no information on food consumption that could be an additional source of water for the respondents. The frequency of non-alcoholic beverage consumption was collected using the FFQ method, which may introduce errors in actual beverage consumption; however, the FFQ is a well-established, validated, and widely used questionnaire. Another limitation was the use of a body composition device that could only measure total body water without the ability to measure intracellular and extracellular water; however, these measurements are planned in future studies.

5. Conclusions

Public health policy should take into account many parameters of biochemical analyses that facilitate the early diagnosis of MetS, including parameters of health and hydration status measured by different methods. As dehydration leads to a poorer quality of life, especially in people who are more susceptible to the condition, early diagnosis, understanding, treatment, and prevention are very important. Inadequate hydration may be an additional problem in people with metabolic syndrome. In this case, it is important to educate them not only about a rational diet but also about proper hydration. These results highlight the need for further research to clarify the relationship between diet, including beverage consumption, blood pressure, anthropometric measurements, biochemical analysis of health, and hydration status in patients with metabolic disorders.