**1. Introduction**

Very good health and maintaining high level of psychophysical fitness are the main factors that determine the effectiveness and reliability of duties and tasks performed by Border Guard officers. The main tasks include border protection and the control of border traffic [1]. Some of the border guard's duties are performed in diverse geographical conditions, such as the sea area or mountains, thus maintaining a healthy condition and psychophysical fitness are crucial. Changing circumstances, i.e., during the deployment period, may lead to modification of dietary habits and exercise routine, for example with a negative effect on body composition and physical performance [2]. Thus, it is very important to maintain good nutritional status which mainly depends on diet and physical activity.

Optimizing nutrition strategies to support health and performance is important, especially for physically active people [3] as well as tactical personnel [4]. The recommendations, for example position stands developed by the International Society of Sports Nutrition,

**Citation:** Anyzewska, A.; Łakomy, R.; ˙ Lepionka, T.; Maculewicz, E.; Szarska, E.; Tomczak, A.; Bolczyk, I.; Bertrandt, J. Association between Diet, Physical Activity and Nutritional Status of Male Border Guard Officers. *IJERPH* **2022**, *19*, 5305. https://doi.org/10.3390/ ijerph19095305

Academic Editor: Lauri O. Byerley

Received: 25 March 2022 Accepted: 26 April 2022 Published: 27 April 2022

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**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

such as nutrient timing [5], protein and exercise [6] can be also applied as some of the nutrition recommendations for uniformed forces. Nevertheless, the basic principles of healthy diet and implementing a balance and diverse diet with high nutritional density are crucial, especially considering the poor dietary habits observed in these populations [4,7–10]. Diet quality, eating styles, and macronutrient composition influence body composition [11]. Too low an energy intake can lead to weight loss, especially a decrease in muscle mass, or decrease in bone density, which may negatively affect psychophysical performance, prolong recovery time and increase injury risk [2,12]. On the other hand, too high an energy intake may cause weight gain, and thus indirectly increase the risk of obesity that might result in difficulties in fulfilling service tasks. These abnormalities might be also the reason for early service eliminations because of health concerns.

The second factor that significantly affects body composition is physical activity. It not only leads to increasing physical performance and muscle mass, but also, as the most variable component of daily energy expenditure, determines energy balance [13]. Lifelong exercise delays the onset of 40 chronic diseases, such as coronary (ischemic) heart diseases, hypertension, obesity, insulin resistance, metabolic syndrome, osteoporosis, depression, and anxiety [14]. The evidence for the notion of "exercise is medicine" is strong, and physical activity has been used in both the prevention and treatment strategies for various diseases [15]. It is also an interaction between physical activity and other factors, for example diet and genetics that increases disease risk factors.

Since physical inactivity is considered as the biggest public health problem of the 21st century [16], the growing trend of people with overweight and obesity is also observed in the general population [17,18], as well as among uniformed service officers [19–25]. According to the last study, the prevalence of overweight and obesity in the Polish Army Forces (50% and 17% of men) [10] is similar to that in the general population of Poland (52% and 16% of men) [18]. Border guard officers, like other uniformed services, attend physical education classes and are obligated to complete annual physical fitness test [26,27]. Nevertheless, it has been observed that not all of border guard officers attend sport classes [28–30]. It has been shown that both occupational and leisure time physical activity are associated with body composition in police officers [31], thus it is necessary to assess the level of physical activity including both physical activity during work and physical activity as sport and leisure time.

Proper diet, regular physical activity, and thus nutritional status are extremely important for uniformed forces, affecting their physical fitness and their suitability for service. However, the literature on these associations between lifestyle factors and body composition among tactical personnel is relatively scarce, especially there has been a lack of research carried out among border guard officers. Therefore, the aim of the study was to verify the correlations between dietary habits, physical activity level and selected nutritional status indicators: body mass index (BMI), fat mass index (FMI), visceral fat level (VFL), bone mineral density (BMD T-score) and muscle mass index (MMI) in border guard officers from Poland.

#### **2. Materials and Methods**

The study was carried out with the participation of 169 male border guard officers from Poland. Informed consent was obtained from all subjects involved in the study. The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the Military Institute of Hygiene and Epidemiology (1/XXI/2016).

#### *2.1. Eating Meals, Food Consumption Frequency Assessment and Dietary Patterns*

A two-part questionnaire was used to assess diet. The first part contained questions about the regularity of eating five meals with three possible answers to choose: every day, not every day, never. The second part was the evaluated 61-item food frequency questionnaire (FFQ) [32], slightly modified by adding two new categories of answers in this questionnaire, as in an earlier study [9].

Border guard officers were asked, included in the FFQ, how often they had consumed 61 food products in the past 12 months. For each product they could choose one of the eight answers regarding food consumption frequency: 1—never or almost never, 2—once a quarter or less often, 3—once a month or less often, 4—a few times a month, 5—once a week, 6—several times a week, 7—every day, 8—several times a day.

Reported frequencies were calculated into daily frequencies (time/day), as follows: never or almost never—0.003 (1/365), once a quarter or less often—0.01 (4/365), once a month or less often—0.03 (1/30), a few times a month—0.08 (2.5/30), once a week—0.14 (1/7), several times a week—0.57 (4/7), every day—1, several times a day—2. Converted frequencies were also summed within the main food groups, that were identified as:

	- Converted frequencies of the main food groups were used to obtain dietary patterns.

#### *2.2. Physical Activity Assessment*

A long-form International Physical Activity Questionnaire (IPAQ) was used to assess physical activity level [33]. Officers were asked to answer 27 questions about physical activity during work/job, transportation, homework, house maintenance, and caring for family, recreation, sport, and leisure-time, as well as time spent sitting. Then results were calculated as metabolic equivalent (MET-minutes/week) according to the scoring protocol [34].

#### *2.3. Nutritional Status Assessment*

The TANITA HR-001 stadiometer (Tanita Corporation, Tokyo, Japan) was used to measure height. The head was aligned in the Frankfort horizontal plane [35]. Body weight and body composition (fat mass, visceral fat level, muscle mass) were evaluated using the TANITA MC-780 analyzer (Tanita Corporation, Tokyo, Japan). All measurements were performed in accordance with the procedures from the instruction manuals. Three additional indicators were calculated: body mass index (BMI), fat mass index (FMI) and muscle mass index (MMI):

BMI = body weight/height<sup>2</sup> [kg/m2],

FMI = fat mass/height<sup>2</sup> [kg/m2],

MMI = muscle mass/ height<sup>2</sup> [kg/m2].

The scale of BMI classification reported by the World Health Organization (WHO) [36] and the scale of FMI described by Kelly et al. [37] were accepted.

Bone mineral density (BMD) was measured in the forearm bone of the nondominant hand, using Dual Energy X-ray Absorptiometry (DEXA) densitometric method, with an EXA 3000 analyzer (OsteoSys, Seoul, Korea). The results were interpreted in accordance with the WHO standards for BMD T-score: osteoporosis: BMD T-score ≤ −2.5, osteopenia: −2.5 < BMD T-score ≤ −1.0, standard: BMD T-score > −1.0 [38].

#### *2.4. Statistical Analysis*

The PS IMAGO PRO (IBM SPSS Statistics, Armonk, NY, USA) program was used for all statistical analyses. Shapiro–Wilk test was used to verify the compatibility of variable distribution with normal distribution. Due to noncompliance of analyzed variables with normal distribution, Spearman's correlation was conducted to assess the associations among dietary habits, physical activity and five nutritional status indicators (BMI, FMI, VFL, BMD T-score, and MMI). Two dietary patterns were identified using the K-means cluster analysis. Input variables were converted to standardized scores. Logistic regression was used to assess the relationship between excess fat mass and potential risk factors. For all analysis the significant level of α = 0.05 was assumed.

## **3. Results**

The study was conducted among 169 male border guard officers aged 37 ± 6 years. The average length of service was 13 ± 7 years. About 1/3 of the subjects lived in a city of over 100 thousand inhabitants (32%), 35% in a city of up to 100 thousand inhabitants, and the rest lived in the country (33%). Almost 3/4 of officers were higher educated (71%), while others were secondary educated (29%). Nearly 2/3 of subjects assessed the physical level of work as light (27%) or performed while sitting (38%). According to 30% of officers, their work was moderate, and for others it was hard (5%).

#### *3.1. Eating Meals, Food Consumption Frequency and Dietary Patterns*

The meals that were most often eaten every day were dinner (84%), breakfast (83%) and supper (66%) (Table 1). Lunch was eaten every day only by 30%, afternoon snack by 18%, and supper by 66% of officers.

**Table 1.** Frequency of eating meals by border guard officers.


Fruits (all types) were eaten every day by only 30% of subjects, out of which barely 3% ate them several times a day (Table S1). About half of officers (51%) ate fruits several times a week. The most common fruits consumed were apples and pears (eaten more than once a week by 61% of subjects), and bananas (eaten more than once a week by 43% of subjects), while avocado, olives and other tropical fruits (not including kiwi fruit and citrus) were the least often consumed. Vegetables (all types) were eaten every day by only 32% of officers, including 3% of them who ate these products several times a day. Almost half of subjects (49%) ate vegetables several times a week. Tomatoes were the most often consumed vegetable (eaten more than once a week by 73% of officers), while leafy green vegetables and crucifers were the least often consumed (eaten more than once a week by 31% and 33 % of officers). So-called dark bread (wholemeal or with grains) was eaten every day by only 26%, while so-called white bread by 33%. Most of the officers consumed all dairy products, as well as eggs, less than daily. Meat products, especially high-quality cold-cuts and sausages were much more popular than fish—both lean and oily fish were eaten less than once a week by most of the officers (69% and 75%). Although nuts were more popular than grains, only 21% and 10% of subjects ate these products more than once a week. Sweets were more popular than salty snacks. More than half of officers (53%) never or almost never consumed energy drinks, while sweetened sodas such as beer were consumed more than once a week by 23% and 28% of subjects. Two major dietary patterns were identified using the K-means cluster analysis. The first one Dietary pattern 1—was a more healthy and more varied diet, while Dietary pattern 2 was a less healthy and less varied diet. Barely 24% of border guard officers were classified in the more healthy diet group (Dietary pattern 1). The differences between these two dietary patterns are described in Table 2.


**Table 2.** The frequency of food consumption by dietary pattern groups.


**Table 2.** *Cont*.

U Mann–Whitney Test \* *p* < 0.05; \*\* *p* < 0.01. X—average; SD—standard deviation; Me—median.

#### *3.2. Physical Activity*

Based on the IPAQ, the average total physical activity equaled 17,255 ± 14,152 (median: 13,692) MET-minutes per week (Table 3). The largest part of physical activity was job-related physical activity (39%). Housework, house maintenance, caring for family accounted for 22%, transportation for 20%, and recreation, sport and leisure-time physical activity for 19% of the total value of physical activity. Taking into consideration the intensity level, walking counted for 38%, moderate physical activity for 36%, and intensive physical activity for 26% of the total value of physical activity. According to the IPAQ classification, 93% officers were characterized by a high and 7% by a moderate level of physical activity. The mean time spent in the sitting position on weekdays was 4.8 ± 2.8 (median: 4.0) hours a day, and on weekends it was 3.9 ± 2.3 (median: 4.0) hours a day, however the result values ranged from 0.5 up to 14.5 h a day.


**Table 3.** Physical Activity according to the long-form International Physical Activity Questionnaire (IPAQ).

X—average; SD—standard deviation; Me—median; IRQ—interquartile range.

#### *3.3. Nutritional Status*

Nutritional status indicators varied among the examined border guard officers (Table 4). Body weight ranged from 62.5 to 114.9 kg and height ranged from 165.6 to 199.3 cm. According to the BMI classification, normal weight was observed in only 32% of officers, while 67% officers were overweight (53%) or obese (14%). However, normal fat was found in 54% of officers, and excess fat in 39%. Additionally, in the group with BMI higher than 25 kg/m2, 58% of the officers were normal fat, and only 42% were classified as excess fat. Almost all of participants (96%) had a healthy level of visceral fat, according to the Tanita classification. Sufficient bone mineral density was observed in 87% of the subjects, osteopenia—12%, and osteoporosis—1%.

**Table 4.** Anthropometry and nutritional status.


X—average; SD—standard deviation; Me—median; BMI—body mass index; FMI—fat mass index; MMI—muscle mass index; VFL—visceral fat level; BMD T-score—bone mineral density expressed in relation to a reference population in standard deviation units.

Since there were no associations between age and BMI, FMI, BMD (t-score) and MMI, age was positively correlated with VFL (Table 5). The nutritional status indices were correlated with each other.


**Table 5.** Correlations between selected nutritional status indices.

Spearman's correlation; \*\* *p* < 0.01. BMI—body mass index; FMI—fat mass index; VFL—visceral fat level;BMD T-score—bone mineral density expressed in relation to a reference population in standard deviation units;MMI—muscle mass index.

#### *3.4. Associations among Diet, Physical Activity and Nutritional Status*

Twelve negative correlations between the main food groups consumption frequency and BMI (fruits, vegetables, and potatoes; seeds of legumes; dairy products and eggs; fats, nuts, and grains), FMI (fruits, vegetables, and potatoes; seeds of legumes; dairy products and eggs) VFL (fruits, vegetables, and potatoes; seeds of legumes; dairy products and eggs) and BMDT-score (fruits, vegetables, and potatoes; dairy products and eggs) were found (Table S2). Out of the selected 61 products negative correlations were observed between BMI and 18 products (fruits together—all type; other tropical fruits; bananas; sweet fruit preserves and candied fruits; vegetables—all types; yellow–orange vegetables; leafy green vegetables; fresh seeds of legumes and canned ones; potatoes in various forms; unrefined groats coarse; refined cereal grain; ready-to-eat breakfast cereal products; milk and milk drinks; butter; nuts; grains; honey; vegetable juices and vegetable-fruit ones). FMI negatively correlated with almost all of products from the first group, including fruits, vegetables, and potatoes (14 of 18), and with seeds of legumes, unrefined groats coarse; refined cereal grain; ready-to-eat breakfast cereal products; milk and milk drinks; lean fish; nuts; grains; honey; vegetable juices and vegetable-fruit ones. Positive correlation was observed only between FMI and sweetened sodas such as Fanta, Coca-Cola, Mirinda, Sprite. VFL negatively correlated with 20 out of 61 analyzed foods. The BMD T-score negatively correlated with six products (yellow–orange vegetables; tomatoes; potatoes; cottage cheese; eggs; honey).

It was found that officers with more healthy dietary habits (dietary pattern 1) had significantly lower BMI (*p* = 0.001), FMI (*p* < 0.001) and VFL (*p* < 0.001) than officers from the less healthy diet group (Table 6).

No associations between the total amount of physical activity and BMI, FMI, VFL, and BMD T-score were observed (Table 7). However, correlations were found between several categories of physical activity and BMI, FMI and VFL. Recreation, sport and leisuretime physical activity negatively correlated with BMI (Rho = −0.182; *p* = 0.018), FMI (Rho = −0.277; *p* < 0.001) and VFL (Rho= −0.228; *p* = 0.003), while waking negatively correlated only with BMI (Rho = −0.156; *p* = 0,043). Time spent sitting at the weekend positively correlated with FMI (Rho = 0.198; *p* = 0.014) and VFL (Rho = 0.172; *p* = 0.034). Only one correlation was found between muscle mass expressed as MMI and walking (Rho= −0.186; *p* = 0.015).


**Table 6.** Nutritional status indices and physical activity by dietary pattern groups.

U Mann–Whitney Test \* *p* < 0.05; \*\* *p* < 0.01. X—average; SD—standard deviation; Me—median; BMI—body mass index; FMI—fat mass index; VFL—visceral fat level; BMD T-score—bone mineral density expressed in relation to a reference population in standard deviation units; MMI—muscle mass index.

**Table 7.** Relationships between physical activity (IPAQ) and body mass index (BMI), fat mass index (FMI), visceral fat level (VFL) and bone mineral density (BMD T-score).


Spearman's correlation; \* *p* < 0.05; \*\* *p* < 0.01. BMI—body mass index; FMI—fat mass index; VFL—visceral fat level; BMD T-score—bone mineral density expressed in relation to a reference population in standard deviation units.

It was found that both dietary pattern (OR = 2.98) and physical activity: sport and recreation (OR = 0.57) are associated with the risk of excess fat mass (Table 8).


**Table 8.** Logistic regression model for excess fat mass index probability (*p* < 0.001).

B—regression coefficient; Dietary pattern: 1—more healthy, 2—less healthy.
