The female organism undergoes changes during menopause resulting from a gradual decrease in estrogen production that increases several health risks. Considering these risks, we selected 6 micronutrients, the intake of which we will evaluate. We assume that women living in a city environment, mostly in apartments, will show a higher intake of micronutrients. We also examine whether the choice of shopping place influences the intake of selected minerals or energy intake.

Statistical analysis was carried out using MS Excel 2010 (Los Angeles, CA, USA) in combination with XLSTAT (Version 2019.3.1). Mean, standard deviation, minimum and maximum, and median were calculated. Statistical significance was determined using a two-sample t-test when comparing subgroups of the population and a paired t-test when comparing the nutritional intake of the entire population during a workday and weekend. Differences at p <0.05 were considered significant.

Significant adverse effects on the intake of basic nutrients and energy were observed on workdays and non-workdays, for which all participants provided a weekend day (Table 1).

On weekdays, women tend to receive lower amounts of total energy, protein, carbohydrates, and fats compared to a weekend day. According to the calculated mean values, the recommended daily allowance (RDA) (57 g) was met only for protein intake, both on weekdays (62.89 ±27.33 g) and over the weekend (75.47 ±25.76 g).

We observed that the average values of the monitored group did not meet the RDA guideline (MHSR, 2015), which are 8800 kJ of energy, 306 g of carbohydrates, and 72 g of fats. At the same time, there are obvious differences in the intake of the selected minerals on a workday and weekend day.

Haines et al. (2003) described high energy intake from alcoholic beverages over the weekend, especially on Saturday, in the 19 – 50 age group, as did An (2016) and Jahns et al. (2017). In addition to alcohol, energy intake was also increased by the increase in the proportion of fats in the weekend diet, which was richer than during workdays by an average of 115 kcal (481.28 kJ).

Haines et al. (2003) observed similar results as the study of An (2016), which examined the differences in the nutrition of 11 646 adults over 18 years in the United States during workdays and weekends. In comparison with the average values on workdays and on Saturday, the weekend intake was increased, especially in the case of total energy, by 181.04 kcal, approximately 757.5 kJ. Food quality on Saturday was lower than on other monitored days.

Jahns et al. (2017) also found a higher energy intake of macronutrients over the weekend in a population of middle-aged women (49.4 ±5.8 years). In 75% of these women, they noticed increased energy intake by an average of 158 kcal (661.23 kJ) over the weekend. The increase in intake was provided mainly by carbohydrates, as in our results. The least variable nutrient were fats; their intake was very similar during the week, contrary to our results. In our research, we observed very small differences in protein intake.

From our results, on workdays, the recommended nutritional quantities of protein intake were met only in 56.67% of cases, and those of fat intake in 6.67% of cases in a population of thirty. None of the participants from the observed group met the recommended intake of energy and carbohydrates. Weekend intake was higher for all four endpoints (Tables 1), with recommended energy intake met by 23.33%, protein intake by 73.33%, carbohydrates intake by 16.67%, and fat intake by 40.0% of the participants.

Several authors (Haines et al., 2003; Ruopeng, 2016; Jahns et al., 2017) have observed lower nutritional quality of the diet over weekends – reduced intake of fruits, vegetables, and fiber, and increased consumption of fast food. Our results, on the other hand, show better nutritional status over the weekend, especially in terms of total energy, carbohydrate, and fat intake, but participants also received higher amounts of almost all minerals (except Cu and Se). Based on the average intake of the selected nutrients, we find that the intake of micronutrients over the weekend is almost the same as on weekdays. The biggest differences were in the intake of energy, carbohydrates, and fats, which is explained by the fact that during the weekend, the participants had time to consume more meals per day compared to a workday (average of 4.5 meals on a weekend day; an average of 4.1 on a workday). Of those involved, 53% received at least one meal more during the weekend than on weekdays.

Urbanization interacts with several key determinants of food consumption. It is believed that the self-production of food is not very common in urbanized areas, which also affects dietary habits (Cockx, Colen and De Weerdt, 2018).

From the monitored population of 30 women, 13 women lived in a village and the remaining 17 lived in a city. Based on average values of the group (Table 2), intake of minerals, zinc, copper, selenium, and chromium were met in both groups of women, even exceeding the recommended amounts given in the RDA guideline (MHSR, 2015).

In the “urban” group, we observed that the average BMI was higher than in the “rural” group, mainly because most overweight (>25 kg.m^-2) and obese (>30 kg.m^-2) women lived in the city (Table 3). Although BMI above 30 kg.m^-2 was observed only in 2 participants in our study, several studies of women of similar age categories show the prevalence of higher BMI in urban women, often in association with waist circumference (≥88 cm) (Okop, Levitt and Puoane, 2015; Rothman et al., 2018). In addition, Okop, Levitt and Puoane, (2015) reported a higher proportion of excessive body fat in urban women (47.6 ±11% body fat) compared with women living in rural areas (44.10 ±10% body fat), differences in BMI parameters (34.7 ±9 and 31.4 ±8 for city and village, respectively), and waist circumference (100.1 ±16 cm in the city and 93.7 ±17 cm in the village). The percentage of women in the 35 – 49 age group (n = 429) with high measured endpoints was 10% higher for BMI, 6% higher for waist circumference, and 4% higher in the urban group compared to the rural. Conversely, Trivedi et al. (2015) are critical of the rural group in the American population, in which they observed a higher prevalence of obesity due to poor eating habits and lower physical activity. The prevalence of female obesity was 33.4% in the rural area and 28.2% in the urban area (p <0.01). The nutritional risk factors associated with an increased risk of obesity were lower fruit consumption, higher protein intake (mainly from meat and beans), and skipping breakfast.

Both groups met the requirements for the recommended intake of phosphorus ingested – the intake exceeded the RDA by more than 200 mg. However, in the case of calcium, the intake was almost 400 mg below the RDA in both groups. Women living in the village environment received a higher amount of Ca, which is surprising given that the intake of other minerals was lower than in the urban group. However, on average, this amount was still insufficient, and less than 30 mg higher than that of the women from the city district. Rothman et al. (2018), in their study of 452 women (aged 45 to 54 years), observed a higher intake of milk and dairy products (Ca sources) in the diet of the urban population compared to the rural population and assumed that calcium intake is directly proportional to the consumption of these foods. They refer to an insufficient intake of these foods and thus calcium as a risk factor in the development and progression of osteoporosis.

Average zinc intake was elevated almost 2.5 to 3 times the recommended daily dosage, which may be counterproductive and may disrupt the homeostasis of the body. However, the mean value was not within the range of 50 – 300 mg.d^-1, and therefore we assume that chronic toxicity manifestations of this element should not be present (EFSA, 2006). The dietary intake of copper according to the RDA guideline (MHSR, 2015) is 900 μg and 1.6 mg according to the Mountberry nutritional software used; therefore, the values obtained from the nutritional records of the population were optimal. Again, we observed a higher intake of both elements in the group of participants living in the city.

Ilow et al. (2011) also reported lower zinc intake in urban areas, although our average values were 3 to 4 times higher than those reported, mainly attributed to the size of our sample (n = 30) and the sample size of Ilow et al. (2011) (n = 2572). However, copper intake in their study was higher in rural areas by an average of 0.1 mg, while we observe a higher intake of 0.25 mg in the urban population. In both cases, copper intake exceeds the recommended daily quantities.

A phenomenon similar to that of zinc intake is also observed for selenium intake. The urban part of the population receives a higher amount than women living in the village, and the intake is 2 – 3 times higher than recommended by the Ministry of Health. If the participants consistently received that much selenium, as in the case of zinc, their organisms could be damaged. Chromium intake only slightly exceeds the recommended intake in women living in a village and can be said to be optimal compared to Cr intake in the city where we observe a slightly higher average intake value. Nutritional intake is again higher in the urban group.

Similar findings were present in the Polish population, with higher Se intake in cities (77.3 ±31.3 μg per day) compared with rural areas (72.9 ±23.6 μg per day). The authors attributed the size of the standard deviation to different numbers of participants (n = 1786 for the urban population and n = 786 for the rural population) (Ilow et al., 2011).

The differences in the diets can be explained by the fact that urban areas are characterized by a significantly different food supply environment, affecting the availability and price of food. The possibilities of eating away from home or buying semi-finished or ready-made meals are more prevalent and more diverse in urban areas because there are mini-markets, supermarkets, and fast-food chains with easy availability of food (Cockx. Colen and De Weerdt, 2018).

The participant group comprised of 16 women living in a family house with a garden and 14 living in an apartment. The average intake of minerals was similar to the previous criterion of evaluation, namely that the intake of all selected micronutrients was sufficient except for calcium, intake of which was deficient in both groups regardless of the type of housing (Table 3).

We observed a higher intake of Ca in participants living in a family house with a difference of over 100 mg. Six women from this group achieved the recommended intake, but none received more than 1000 mg twice or more in 3 monitored days. In the group of women living in apartments, we have seen such values only in 4 women, also only one day from the three-day nutritional protocol. Phosphorus intake was met according to RDA limits but may be of concern due to low calcium intake. The calcium to phosphorus intake ratio in the "family house" group was 1:1.58, while in the "apartment" group the Ca:P ratio was 1:1.45. EFSA (2015) reports an optimal Ca:P ratio of 1.4:1 to 1.9:1 and may therefore be a risk factor at a later age or after menopause, particularly in relation to osteoporosis.

The mean value of Zn intake was 27.60 ±11.57 mg in the group of women living in apartments and 24.40 ±12.52 mg in family houses. The actual intake was more than triple the RDA, but this amount should not cause any health risks according to EFSA (2006).

Comparing the intake of copper in both groups, we can see that the individual average received quantities are higher than those stated by the MHSR (2015) in the RDA for SR, therefore, the intake was sufficient. However, according to the limits in Mountberry software, which recommends an intake of 1.6 mg Cu per day for the selected age group, intake would be inadequate, especially in the “family house” group.

The average Se intake in the "apartment" group was more than three times the RDA. For women living in a family home, we also see a higher daily intake, but to a lesser extent. Selenium intake is high throughout the population regardless of assessment criteria, which may have an adverse effect on the cardiovascular system, as reported by Grotto et al. (2018) and Vinceti et al. (2019). Grotto et al. (2018) reported that high intake induces changes in blood pressure: an increase in systolic blood pressure. Their experiments were performed in mice which they had been feeding increased amounts of selenium for 85 days via drinking water (2 and 6 mg.L^-1) in the form of sodium selenite; the first changes in blood pressure were observed after 42 days. Although several authors report 400 μg a day as a critical intake of Se in humans, and according to the recorded average values, the respondents' health should not be in danger, we do not recommend a multiple increase in the intake of this mineral.

According to the RDA, the intake of chromium is adequate in both groups, with a more optimal value in the “family house” group, where the difference from RDA is on average 1.01 μg, while in women living in apartments, the actual intake exceeds RDA by less than 23%. Overall, we note that the intake of Cr and Cu shows the most optimal values in relation to the recommended daily allowances set by the Ministry of Health of the Slovak Republic (MHSR, 2015).

We can see from Table 3 that the intake of all nutritional parameters was higher in women living in apartments. Cockx. Colen and De Weerdt (2018) suggest that smaller living space and a lack of storage and cooking facilities could contribute to increased dependence on foods that require less or no preparation. This phenomenon may encourage more frequent shopping and more varied food choices, depending on the individual's current preferences.

Several studies point out that the choice of grocery store affects food intake and nutritional composition. We anticipated that total energy intake would be higher in the supermarket group, due to the increased availability of semi-prepared foods and ready-made meals that tend to contain more salt, saturated and trans-fatty acids, and sugar (Albuquerque et al., 2018).

Most women (18) reported different sources of food than the supermarket, which included local producers, vendors, farmers, or their food production. The second group consisted of women (12) who identified supermarkets as their only food source – they did not buy food in other establishments.

We observed that the intake of minerals, except Ca, is higher in the group buying food in several stores of local farmers and producers or growing and producing the food themselves (Table 4). In this group we also see a better ratio of calcium to phosphorus intake, numbering 1:1.43 compared with 1:1.64 in the supermarket only group. From this point of view, women buying only in supermarkets could be at a higher risk of breaching bone homeostasis. Regardless of the Ca: P ratio, calcium is deficient in the diet of the participants of both groups. This is not true of phosphorus intake, which seems excessive compared to RDA in both groups and reaches 141.57% of RDA in the supermarket group and 131.97% RDA in the “different food source” group.

Zinc intake is excessive in both subgroups but is significantly higher in women shopping at the supermarket. Zinc, due to its role in the human body, is nowadays one of the elements by which food, for example, breakfast cereals or flour, is fortified, especially to prevent its deficiency in the body (Brown, Hambidge and Ranum, 2010; Shah et al., 2016). The likelihood of availability of such enriched foods in local farm shops is lower than in the supermarkets. Again, the average amounts received are within the range recommended in the RDA and Mountberry (0.9 – 1.6 mg per day), leading us to conclude that the diet intake is optimal.

The amounts of selenium and chromium received from the diet were met in terms of the recommended daily intakes in both groups. Again, as with most previous micronutrients, higher quantities were received by women shopping in the supermarket.

In our representative sample of women, it was not confirmed that the choice of food source had an impact on the intake of the micronutrients monitored, as the differences between the groups are slight and statistically inconclusive (Table 4). These findings are consistent with Cummins, Flint and Matthews (2014), who reported that they did not find significant changes in endpoints when changing the typical grocery shopping place in the American population. However, Liese et al. (2017) noted the relationship between BMI and the primary grocery store. Their research involved 459 respondents (80% women), with 61% listing a supermarket as their primary point of purchase. Their results pointed to an interesting association: higher BMI values of 2.6 kg.m^-2 were found in people who regularly and primarily shopped in large stores (supermarkets) and discount halls compared to shoppers in small local operations.

In the group of women shopping in supermarkets, we observed a slightly higher energy intake compared to the second group, but the nutrient intake did not change significantly, which may mean that these participants received more low-nutrient but high-energy foods. This, according to Cohen et al. (2015), can reflect in changes in body weight and consequently an increase in BMI. More frequent consumption of such foods is also helped by the marketing strategies of the producer or retailer: lower price, bigger packaging, and advantageous offers (2 in 1). Based on the results (Table 4) we can say that the choice of food source does not play a significant role in the intake of minerals. We observe minor abnormalities in the intake of macronutrients, but given the uneven distribution of the population with a higher number of participants on the mixed food source side (n = 18) than on the supermarket side only (n = 12), we conclude that these differences are due only to the food preferences of the women.

Several strengths and limitations exist in the current study. We focused strictly on the intake of selected nutrients and did not consider physical activity, which may increase the body's need for some nutrients. Another limitation might be the sample size. On the other hand, the strength of the study is the age group and the quality of the obtained nutritional data. Collected 3-day dietary records were responsibly filled by participants and we completed the dietary records with an interview about used groceries and food processing.