Secular Trends of Adult Population and Their Impacts in Industrial Design and Ergonomics

Abstract

Significant increase in 25 anthropometric variables of the Slovak and Czech population in time are defined in the paper. A total of 691 respondents from Slovakia and 688 from the Czech Republic were analyzed. Arithmetic means and standard deviations to characterize the anthropometric variables and their variation were defined and compared. Subsequently, quantiles of the selected anthropometric measurements of the adult male and female population in individual countries in the year 2004 and newly determined quantiles in the year 2018 were calculated and compared. Following the results, the fact that secular trend has stabilized and differences in population between individual countries have minimized over the course of the last 14 years can be stated.

1. Introduction

At the present time, human comfort in the school, work, or home environment is at the center of attention. Therefore, the focus must be put on the most common activities done at work, at school, or in free time. Ergonomics deals with the relation between a man and his/her environment, the main aim of ergonomics is to adapt to human possibilities and needs [1]. When designing and assessing office spaces or workplaces in general, a man must be taken into consideration as a primary factor determining the production of working tools and furniture [2]. Application of anthropometric data appropriate for the intended population can result in reducing the sickness absence, increasing the productivity in the workplace, or developing mental abilities [3]. Improving the physical and mental health, reducing the risk of fatigue can contribute to employee wellbeing. The size of the workplace corresponding with the body measurements of intended users can be considered one of the important rules of ergonomics [4,5]. Therefore, designing the optimal workplace, including furniture, working tools, and equipment follows the measurement of the target population [6]. Incorrect design of the workplace, ignoring the anthropometric data can cause mental discomfort [7], physical tiredness, and can affect the human health in a negative way [8]. Therefore, anthropometric data are an essential condition for designing safe, comfortable, and effective equipment and tools and workplace management [9]. Economic impact and employee health are two indicators that must be met when ergonomics is applied.

Slow and continuous changes associated with growth and development of the human body of consecutive generations compared to previous generations are described using the secular trend. Studies conducted in many countries showed progressive development of the human height of adults as well as children and teenagers. The trends were connected with fast weight gain. Secular changes resulted from the interaction between genes and environmental factors [10,11]. In many developed countries, trends started to slow down [12,13,14,15]. Differences in body measurements between a person’s sex, ethnic groups can result in difficulties in designing furniture [16,17]. Although there is no system satisfying all people [18] and a person’s sex, basic human measurements must be discussed [19,20]. So, anthropometry must be taken into account. Knowledge of basic anthropometric variables of employees is considered an essential condition [19,21]. Anthropometric data are one of basic factors in designing machines, hand tools, and working environment [22,23,24]. Human body measurements, like body weight, height, circumferences, length and width of limbs are included in anthropometry [25]. The great effort aimed at developing an anthropometric database covering various groups of people can be seen in many countries [26,27]. In developed countries with ergonomics research and practice widespread, researchers have collected anthropometric data of various population segments for a long time [28,29,30]. Due to the constant development of the secular trend over the years, anthropometric data must be updated [31,32] and regular population measurements must be carried out [22,33,34].

Following the split of the former Czech and Slovak Federal Republic in the year 1993, we decided to find out if there are changes/differences in selected anthropometric variables of the Czech and Slovak population. Analyzed years (2004 and 2018) are compared, men and women individually.

The main objective of the study is to determine the importance of the changes in the anthropometric measurements of the Slovak and Czech population and, following the measured data, to find out if the secular trend in the case of analyzed countries is stabilized or continues to grow, and presentation of a new data collecting.

2. Materials and Methods

Empirical measurements of selected anthropometric variables of the current population in Slovakia were carried out in the year 2004. The sample consisted of 204 men and 143 women. While in 2018, the sample consisted of 183 men and 161 women, students of twelve Slovak universities. In the Czech Republic, the sample consisted of adult students of seventeen Czech universities. The data were collected in the year 2004 and the students were at a similar age. Their numbers were: 186 men and 119 women. In the year 2018, the sample consisted of 158 men and 225 women. This study was approved by the research ethics Committee in Slovakia and also in the Czech Republic. The measurements were conducted systematically and their number depended on the number of students measured during individual years. Anthropometric measurements were carried out in the morning while standing, sitting, with no shoes, and at the vertical wall. In a standing position, the body of students had to be relaxed, with legs close to each other and heels positioned close to the wall, they had to look straight ahead so that his/her head is in the Frankfurt horizontal plane, which ensures the desired position of the vertex landmark (the highest point on the top of the head) [35]. The anthropometer and measuring tape with the accuracy of 0.01 m was used to measure the variables. The body weight was measured using a standardized medical scale with the accuracy of 0.1 kg. Twenty-five variables which can be used in accordance with hygiene rules and ergonomics in designing optimal workplace and work environment were introduced.

Measured selected data were described by arithmetic means $\stackrel{\leftharpoonup }{x}$ and standard deviations sx, defining the size and variation of anthropometric variables of two samples selected from two populations—Slovak and Czech women (men). Relative differences dif % were calculated for both characteristics of each selected parameter following the formula:

$$dif\%=\frac{{\overline{x}}_1-{\overline{x}}_2}{\frac{{\overline{x}}_1+{\overline{x}}_2}{2}}\mathrm{or}dif\%=\frac{s_{x1}-s_{x2}}{\frac{s_{x1}+s_{x2}}{2}},$$

(1)

where index 1 used in the sample arithmetic mean and the standard deviation was for the Slovak female (male) population, and index 2 for the Czech female (male) population. Differences in the arithmetic means were tested using the T-test for independent samples at the level of significance of 5% and differences in the standard deviations were tested using the F-test at the level of significance of 5%. The statistical significance of differences in sample arithmetic means and standard deviations of individual analyzed anthropometric variables was examined in order to eliminate the fact that the determined differences in descriptive characteristics were only due to the sampling error.

When verifying the identity of two sample means of two basic samples, the null hypothesis H₀ is tested: ${\mu }_1={\mu }_2$, where we state that arithmetic means of anthropometric variables of two basic samples—Slovak and Czech population—are the same. Standard testing criteria are used for testing the identity of arithmetic means under conditions when samples from different populations are independent and the population variability is assumed not to be the same:

$$t=\frac{{\overline{x}}_1-{\overline{x}}_2}{\sqrt{\frac{s_{x_1}^2}{n_1}+\frac{s_{x_1}^2}{n_2}}}.$$

(2)

Quantiles of investigated anthropometric variables were determined by non-parametric way through value ordering according the size. Subsequently, the relative order $i\%=i/n$ of each value was calculated, where is an order of the value in the arranged row and n is a sample size. Quantiles were obtained by linear interpolation between the values arranged in the row, where the relative order of the 1st value was i % lower and the 2nd value was higher than quantile expressed in %. Empirical quantiles were computed this way in the case of each investigated anthropometric variable. Therefore, the table of current characteristics of individual parameters in 2018 comparable to 2004 for the male and female population in the Slovak and Czech Republic was compiled. Relative differences in central characteristics, i.e., medians or the 50 percent quantile, were calculated in order to assess the changes in the values of investigated parameters:

$$dif\%=\frac{(m_{present}-m_{last})}{m_{last}}.100\%,$$

(3)

where m_present was median of the year 2018 and m_last was median of the year 2004 were compared to each other.

Considering the fact that the nature of both compared investigations was selective, testing the statistical significance of determined differences must be done in order to confirm the significance of changes in the values of the investigated parameters. The following median test was done:

$${\chi }^2={\displaystyle \sum _{j=1}^2\left[\frac{{(n_j-n/2)}^2}{n/2}\right]},$$

(4)

where n_j was the number of respondents of the actual sample set with the higher values associated with the parameter (j = 1) or lower values (j = 2) than the value of median and n/2 was the expected frequency of values higher or lower than the value of median, provided that the compared median were equal. The final part of the test was done following the comparison of the value of testing criterion ${\chi }^2$ with the critical value ${\chi }_{1\%(f)}^2=6.63$ determined for the number of degrees of freedom $f=1$. When the testing criterion ${\chi }^2$ is bigger than the critical value ${\chi }_{1\%(1)}^2$, determined difference in medians is considered proven with the 99% reliability and vice versa.

3. Results

Gathered data from measurements in the year 2004 and 2018 associated with the male and female population in the Czech and Slovak Republic are mentioned in

Table 1. Basic characteristics of anthropometric variables and their variation in the Slovak and Czech female population in the year 2004.

Anthropometric Variables	Arith. Means SR CZ		Dif. in %	t-Test	Standard Deviation SR CZ		Dif. in %	F-Test
1. body weight in kg	59.3	61.4	−3.5	−2.024	7.8	8.8	−12.0	1.273
2. height	168.6	168.0	0.4	0.735	6.3	6.8	−7.6	1.165
3. eye height	157.4	156.6	0.5	0.895	6.7	7.6	−12.6	1.287
4. shoulder height	141.5	141.2	0.2	0.304	7.9	8.0	−1.3	1.025
5. elbow height	108.2	107.7	0.5	0.673	6.1	5.9	3.3	1.069
6. fingertip height	66.4	65.9	0.8	0.908	4.1	4.7	−13.6	1.314
7. vertical reach	209.9	208.5	0.7	1.224	9.0	9.4	−4.3	1.091
8. shoulder breadth (bideltoid)	41.3	41.2	0.2	0.292	3.1	2.4	25.5	1.668
9. chest depth	32.0	29.5	8.1	3.222	4.3	7.5	−54.2	3.042
10. upper limb length	78.1	77.3	1.0	1.168	5.3	5.7	−7.3	1.157
11. span	164.9	165.1	−0.1	−0.184	8.7	8.8	−1.1	1.023
12. sitting height	88.2	88.8	−0.7	−0.978	5.0	4.9	2.0	1.041
13. sitting eye height	76.9	77.3	−0.5	−0.553	5.2	6.3	−19.1	1.468
14. sitting elbow height	25.6	27.2	−6.1	−2.631	3.9	5.6	−35.8	2.062
15. shoulder-elbow length	34.8	34.5	0.9	0.906	2.5	2.8	−11.3	1.254
16. knee height	52.8	52.3	1.0	1.155	3.7	3.3	11.4	1.257
17. vertical reach (sit)	127.2	125.7	1.2	1.849	6.7	6.4	4.6	1.096
18. elbow fingertip length	43.7	43.3	0.9	1.134	2.5	3.1	−21.4	1.538
19. buttock popliteal length	56.2	55.4	1.4	1.340	4.3	5.2	−18.9	1.462
20. buttock heel length	101.4	98.6	2.8	2.748	6.5	9.4	−36.5	2.091
21. forward grip reach (sit)	77.8	77.6	0.3	0.237	5.7	7.8	−31.1	1.873
22. hand breadth	9.6	9.6	0.0	0.00	0.7	1.3	−60.0	3.449
23. hand length	17.9	17.8	0.6	0.587	1.2	1.5	−22.2	1.563
24. foot breadth	9.4	9.1	3.2	1.117	1.0	1.1	−9.5	1.210
25. foot length	24.2	24.2	0.0	0.00	1.7	1.8	−5.7	1.121
	Av. difference:		0.5		Av. difference:		−13.6

Note: differences and testing criteria in bold are significant at the level of significance = 5%. Source: Author’s compilation.

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Table 2. Basic characteristics of anthropometric variables and their variation in the Slovak and Czech female population in the year 2018.

Anthropometric Variables	Arith. Means SR CZ		Dif. in %	t-Test	Standard Deviation SR CZ		Dif.	F-Test SR
1. body weight in kg	61.2	61.6	−0.7	−0.369	10.2	10.9	−6.6	1.142
2. height	167.1	167.3	−0.1	−0.310	6.5	5.9	9.7	1.214
3. eye height	157.3	156.2	0.7	1.696	6.2	6.4	−3.2	1.066
4. shoulder height	139.1	139.9	−0.6	−1.219	6.1	6.7	−9.4	1.206
5. elbow height	106.5	108.3	−1.7	−2.943	5.3	6.7	−23.3	1.598
6. fingertip height	65.3	66.6	−2.0	−2.479	4.4	5.9	−29.1	1.798
7. vertical reach	209.9	208.7	0.4	1.261	9.3	9.1	2.2	1.044
8. shoulder breadth (bideltoid)	41.1	41.9	1.9	−1.930	3.8	4.3	−12.3	1.280
9. chest depth	31.4	32.9	−4.7	−3.167	4	5.3	−28	1.756
10. upper limb length	78.0	76.7	1.7	2.221	4.7	6.8	−36.5	2.093
11. span	165.8	163.9	1.2	2.484	7.2	7.7	−6.7	1.144
12. sitting height	86.7	86.3	0.5	0.600	5.7	7.4	−26.0	1.685
13. sitting eye height	77.3	77.2	0.1	0.182	4.3	6.5	−40.7	2.285
14. sitting elbow height	26.9	27.2	−1.1	−0.906	2.6	3.9	−40.0	2.250
15. shoulder-elbow length	33.7	34.0	−0.9	−1.105	2.5	2.8	−11.3	1.254
16. knee height	52.1	52.4	−0.6	−0.647	4	5.1	−24.2	1.626
17. vertical reach (sit)	127.0	127.0	0.0	0	7.6	9.5	−22.2	1.563
18. elbow fingertip length	42.1	42.8	−1.6	−1.460	2.6	6.5	−85.7	6.250
19. buttock popliteal length	56.0	54.0	3.6	3.475	4.5	6.8	−40.7	2.283
20. buttock heel length	99.5	100.5	−1.0	−1.551	5.9	6.7	−12.7	1.290
21. forward grip reach (sit)	77.9	76.4	1.9	2.607	4.6	6.7	−37.2	2.121
22. hand breadth	9.8	9.6	2.1	1.303	1.1	1.9	−53.3	2.983
23. hand length	17.7	17.6	0.6	0.589	1.8	1.4	25.0	1.653
24. foot breadth	9.5	9.5	0.0	0	1.4	1.5	−6.9	1.148
25. foot length	24.2	24.4	−0.8	−3.358	1.4	1.5	−6.9	1.148
	Av. difference:		−0.2		Av. difference:		−21.0

Note: differences and testing criteria in bold are significant at the level of significance = 5%. Source: Author’s compilation.

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Table 3. Basic characteristics of anthropometric variables and their variation in the Slovak and Czech male population in the year 2004.

Anthropometric Variables	Arith. Means SR CZ		Dif. in %	t-Test	Standard Deviation SR CZ		Dif.	F-Test SR
1. body weight in kg	76.3	77.4	−1.4	−1.141	10.6	10.5	0.9	1.019
2. height	181.1	181.1	0.0	0.00	6.4	7.9	−21.0	1.524
3. eye height	170.0	169.7	0.2	0.414	6.6	7.6	−14.1	1.326
4. shoulder height	152.5	152.0	0.3	0.692	6.7	7.5	−11.3	1.253
5. elbow height	115.9	116.0	−0.1	−0.164	6.1	5.9	3.3	1.069
6. fingertip height	70.4	70.4	0.0	0.00	4.3	3.8	12.3	1.280
7. vertical reach	228.8	228.7	0.0	0.099	9.1	10.7	−16.2	1.383
8. shoulder breadth (bideltoid)	49.1	48.9	0.4	0.415	4.8	4.7	2.1	1.043
9. chest depth	36.1	30.1	18.1	9.096	4.1	8.1	−65.6	3.903
10. upper limb length	86.6	82.7	4.6	1.627	5.1	7.3	−35.5	2.049
11. span	181.7	181.8	−0.1	−0.128	8.1	7.3	10.4	1.231
12. sitting height	93.7	94.9	−1.3	−1.993	4.5	7.0	−43.5	2.420
13. sitting eye height	82.1	85.7	−4.3	−6.193	4.6	6.6	−35.7	3.414
14. sitting elbow height	25.2	25.5	−1.2	−0.846	3.6	3.4	5.7	1.121
15. shoulder-elbow length	37.9	38.8	−2.3	−2.271	2.6	4.8	−59.5	3.408
16. knee height	57.5	56.4	1.9	2.878	3.5	4.0	−13.3	1.306
17. vertical reach (sit)	138.5	138.5	0.0	0.00	6.2	8.3	−29.0	1.792
18. elbow fingertip length	48.3	48.1	0.4	0.503	3.0	4.6	−42.1	2.351
19. buttock popliteal length	59.5	56.5	5.2	5.161	4.6	6.6	−35.7	2.059
20. buttock heel length	109.7	105.6	3.8	4.937	7.2	9.0	−22.2	1.563
21. forward grip reach (sit)	86.4	82.4	4.7	5.438	5.9	8.2	−32.6	1.932
22. hand breadth	11.1	10.8	2.7	2.234	1.1	1.5	−30.8	1.860
23. hand length	19.3	19.4	−0.5	−0.453	1.9	2.4	−23.3	1.596
24. foot breadth	10.4	10.6	−1.9	−1.793	1.1	1.1	0.0	1.000
25. foot length	27.5	27.3	0.7	0.918	2.2	2.1	4.7	1.098
	Av. difference:		1.2		Av. difference:		−19.7

Note: differences and testing criteria in bold are significant at the level of significance α = 5%. Source: Author’s compilation.

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Table 4. Basic characteristics of anthropometric variables and their variation in the Slovak and Czech male population in the year 2018.

Anthropometric Variables	Arith. Means SR CZ		Dif. in %	t-Test	Standard Deviation SR CZ		Dif.	F-Test SR
1. body weight in kg	79.8	80.2	−0.5	−0.294	12.8	12.3	4.0	1.083
2. height	181.5	180.6	0.5	1.170	6.3	7.7	−20.0	1.494
3. eye height	171.1	168.5	1.5	3.036	6.2	8.6	−32.4	1.924
4. shoulder height	152.2	151.9	0.2	0.369	6.1	8.5	−32.9	1.942
5. elbow height	115.3	115.8	−0.4	−0.703	6.6	6.5	1.5	1.031
6. fingertip height	72.3	71.3	1.4	1.742	4.9	5.6	−13.3	1.306
7. vertical reach	229.9	224.8	2.2	4.699	9.5	10.4	−9.0	1.198
8. shoulder breadth (bideltoid)	47.6	48.2	−1.3	−1.007	5.8	5.2	10.9	1.244
9. chest depth	35.4	36.7	−3.6	−2.375	4.3	5.6	−26.3	1.696
10. upper limb length	84.3	82.5	2.2	2.813	5.1	6.5	−24.1	1.624
11. span	181.8	178.4	1.9	3.982	7.7	8.0	−3.8	1.079
12. sitting height	93.1	93.2	−0.1	−0.217	4.8	3.7	25.9	1.683
13. sitting eye height	83.4	84.7	−1.5	−2.146	4.6	6.3	−31.2	1.876
14. sitting elbow height	29.0	27.2	6.4	5.036	2.4	3.9	−47.6	2.641
15. shoulder-elbow length	36.3	37.5	−3.3	−3.114	2.4	4.3	−56.7	3.210
16. knee height	57.2	57.0	0.4	0.455	3.6	4.4	−20.0	1.494
17. vertical reach (sit)	138.0	138.6	−0.4	−0.648	7.8	9.1	−15.4	1.361
18. elbow fingertip length	44.7	47.0	−5.0	−3.612	2.7	7.6	−95.1	7.923
19. buttock popliteal length	59.2	56.8	4.1	3.824	3.7	7.1	−63.0	3.682
20. buttock heel length	107.4	107.0	0.4	0.542	5.4	7.8	−36.4	2.086
21. forward grip reach (sit)	84.3	82.4	2.3	2.843	5.0	7.0	−33.3	1.960
22. hand breadth	11.1	11.0	0.9	0.610	1.4	1.6	−13.3	1.306
23. hand length	19.3	18.9	2.1	2.018	1.6	2.0	−22.2	1.563
24. foot breadth	10.5	10.4	1.0	0.679	1.0	1.6	−46.2	2.560
25. foot length	27.1	27.4	−1.1	−1.063	2.2	2.9	−27.5	1.738
	Av. difference:		0.4		Av. difference:		−25.1

Note: differences and testing criteria in bold are significant at the level of significance α = 5%. Source: Author’s compilation.

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Table 5. Comparison of the original (the year 2004) and actual (the year 2018) quantiles of selected anthropometric variables of the female population in the Slovak Republic.

Quantiles	1%		5%		50%		95%		99%		Dif.	Chi2
Anthropometric Variables	Orig.	Act.	Orig.	Act.	Orig.	Act.	Orig.	Act.	Orig.	Act.	Med.	Test
1. body weight in kg	40	45	47	47	59	60	73	79	82	90	1.695	0.770
2. height	150	152	158	155	169	168	178	177	182	181	−0.592	6.000
3. eye height	135	145	146	148	158	158	167	168	172	169	0.000	0.007
4. shoulder height	123	127	128	129	141	139	153	150	164	153	−1.418	13.740
5. elbow height	94	94	99	98	107	107	117	116	130	117	0.000	0.026
6. fingertip height	57	53	60	58	66	65	73	72	76	73	−1.515	6.338
7. vertical reach	184	190	195	196	210	210	223	226	227	228	0.000	0.000
8. shoulder breadth (bideltoid)	34	33	36	35	41	41	47	47	49	50	0.000	0.000
9. chest depth	21	23	24	25	32	31	38.5	38	40	40	−3.125	6.827
10. upper limb length	56	68	70	70	78	78	88	85	89	88	0.000	0.026
11. span	126	150	150	153	165	166	177	178	184	180	0.606	2.456
12. sitting height	72	75	79	80	89	87	95	95	97	97	−2.247	26.638
13. sitting eye height	59	66	68	70	77	78	84	85	88	87	1.299	0.947
14. sitting elbow height	16	22	19	23	25	27	33	31	37	33	8.000	50.939
15. shoulder−elbow length	28	26	31	30	35	34	39	37	41	39	−2.857	30.676
16. knee height	41	43	46	46	53	52	59	59	62	62	−1.887	9.000
17. vertical reach (sit)	114	92	116	115	127	128	137	138	142	140	0.787	2.532
18. elbow fingertip length	35	36	40	38	44	42	48	46	49	47	−4.545	45.623
19. buttock popliteal length	43	47	49	48	56	56	62	63	65	66	0.000	0.113
20. buttock heel length	78	84	92	89	101	100	111	108	116	111	−0.990	4.390
21. forward grip reach (sit)	56	68	70	70	78	78	87	85	91	88	0.000	0.028
22. hand breadth	8	7	8	8	10	10	11	11	11	12	0.000	11.239
23. hand length	15	15	16	15.5	18	17.5	20	20	21	21	−2.778	0.014
24. foot breadth	10	7	9	8	10	9	9	12	10	13	−10.000	15.680
25. foot length	23	20.5	25	22	24	24	24	26.5	25.5	27	0.000	2.888

Note: median differences significant at the level of significance 1% are in bold. Source: Author’s compilation.

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Table 6. Comparison of the original (the year 2004) and actual (the year 2018) quantiles of selected anthropometric variables of the female population in the Czech Republic.

Quantiles	1%		5%		50%		95%		99%		Dif.	Chi2
Anthropometric Variables	Orig.	Act.	Orig.	Act.	Orig.	Act.	Orig.	Act.	Orig.	Act.	Med.	Test
1. body weight in kg	40	44	50.8	48	60	60	80	84	85	95	0.00	0.019
2. height	152	151	156	157	168	167	178	176	182	180	−0.595	2.556
3. eye height	135	136	142	146	157	157	167	166	172	170	0.00	0.485
4. shoulder height	123	122	130	129	140.5	140	150	150	163	153	−0.356	3.240
5. elbow height	94	95	98	99	107	108	116	120	123	133	0.935	5.113
6. fingertip height	52	53	60	59	65	66	73	80	76	85	1.538	6.879
7. vertical reach	184	182	191	195	209	208	222	225	226	230	−0.478	0.667
8. shoulder breadth (bideltoid)	36	26	37	36	41	42	46	48	47	52	2.439	4.063
9. chest depth	13	23	15	26	31	32	40	39	48	45	3.226	23.592
10. upper limb length	64	60	68	66	78	76	87	84	89	90	−2.564	25.411
11. span	143	142	150	150	165	164	179	177	184	180	−0.606	3.733
12. sitting height	74	60	81	70	89	88	97	94	100	96	−1.124	13.520
13. sitting eye height	59	52	65	65	77	78	88	86	89	89	1.299	6.231
14. sitting elbow height	13	20	19	21	27	27	37	35	44	37	0.00	0.184
15. shoulder-elbow length	25	24	30	29	35	34	38	38	40	39	−2.957	12.287
16. knee height	41	34	47	45	52	53	58	60	60	64	1.923	1.383
17. vertical reach (sit)	115	106	116	115	126	127	136	136	139	173	0.794	2.283
18. elbow fingertip length	34	10	37	34	44	43	48	48	49	65	−2.273	12.571
19. buttock popliteal length	39	26	46	40	56	55	62	62	65	66	−1.786	4.698
20. buttock heel length	75	82	77	90	100	100	111	111	116	116	0.00	0.043
21. forward grip reach (sit)	56	40	66	66	77	77	94	84	98	88	0.00	0.123
22. hand breadth	7	5	8	8	9.5	10	11	11	14	19	5.263	0.751
23. hand length	14	13	16	15	18	18	20	20	21	21	0.00	15.461
24. foot breadth	6	6	7	8	9	9	11	11	12	15	0.00	35.797
25. foot length	19	20	21	22	24	24	27	27	28	28	0.00	16.427

Note: median differences significant at the level of significance 1% are in bold. Source: Author’s compilation.

,

Table 7. Comparison of the original (the year 2004) and actual (the year 2018) quantiles of selected anthropometric variables of the male population in the Slovak Republic.

Quantiles	1%		5%		50%		95%		99%		Dif.	Chi2
Anthropometric Variables	Orig.	Act.	Orig.	Act.	Orig.	Act.	Orig.	Act.	Orig.	Act.	Med.	Test
1. body weight in kg	54	56	61	62	75	79	94	105	101	109	5.333	8.989
2. height	168	168	171	172	181	182	192	193	197	197	0.522	0.575
3. eye height	152	158	159	162	170	171	181	182	184	184	0.588	5.097
4. shoulder height	135	139	142	142	153	152	163	163	167	167	−0.654	5.097
5. elbow height	101	102	106	105	116	116	126	125.5	131	131	0.000	0.479
6. fingertip height	60.8	61	63	64	70	72	78	81	80	80	2.857	36.274
7. vertical reach	206	208	214	215	230	230	243	245	250	250	0.000	0.051
8. shoulder breadth (bideltoid)	41	39	43	40	48	47	58	59	65	65	−2.083	8.494
9. chest depth	27	22	30	29	36	35	42	43	50	50	−2.778	8.399
10. upper limb length	70	73	78	76	87	84	94	92	95	95	−3.448	22.092
11. span	165	168	169	170	181	181	194	196	197	197	0.000	0.006
12. sitting height	81	80	85	85	94	93	100	100	104	104	−1.064	2.162
13. sitting eye height	71	70	73	76	83	84	89	91	93	93	1.205	6.244
14. sitting elbow height	17	24	20	25	25	29	31.5	33	35	35	16.00	147.438
15. shoulder-elbow length	30	30	33	32	38	36	42	40	43	43	−5.263	47.676
16. knee height	49	48	51	52	57	57	62	63	65	65	0.000	0.025
17. vertical reach (sit)	124	117	127	123	138	139	149	150	151	151	0.725	0.691
18. elbow fingertip length	40	35	42	40	48	45	53	49	54	54	−6.250	125.885
19. buttock popliteal length	42	49	52	52	60	60	67	65	71	71	0.000	2.299
20. buttock heel length	90	90	98	99	109	108	122	117	127	127	0.917	15.060
21. forward grip reach (sit)	72	73	77	76	86	84	96	92	98	98	−2.326	11.126
22. hand breadth	8	8	9.5	9	11	11	13	13	14	14	0.000	0.525
23. hand length	10	15	17	17	19	19	22	22.5	23	23	0.000	5.565
24. foot breadth	8	8	9	9	10	10.5	12	12	14	14	5.000	43.932
25. foot length	22	19	24	24	28	27	31	30	34	34	−3.571	27.980

Note: median differences significant at the level of significance 1% are in bold. Source: Author’s compilation.

and

Table 8. Comparison of the original (the year 2004) and actual (the year 2018) quantiles of selected anthropometric variables of the male population in the Czech Republic.

Quantiles	1%		5%		50%		95%		99%		Dif.	Chi2
Anthropometric Variables	Orig.	Act.	Orig.	Act.	Orig.	Act.	Orig.	Act.	Orig.	Act.	Med.	Test
1. body weight in kg	53	60	61	62	75	78	98	102	100	115	4.000	8.333
2. height	157	163	170	168	180	180	194	193	200	198	0.000	0.170
3. eye height	148	145	157	152	169	169	183	181	188	186	0.000	0.026
4. shoulder height	134	134	140	137	152	151	166	169	167	173	−0.658	2.160
5. elbow height	102	101	107	106	115	116	127	125	128	131	0.870	2.423
6. fingertip height	63	60	64	64	70	71	78	81	79	87	1.429	7.615
7. vertical reach	202	202	210	208	227	224	248	241	252	247	−1.322	5.227
8. shoulder breadth (bideltoid)	40	38	42	40	48	47	58	59	59	62	−2.083	0.986
9. chest depth	15	22	18	28	30	37	42	45	45	48	23.333	100.192
10. upper limb length	64	65	71	68	83	83	94	92	99	95	0.000	0.027
11. span	166	156	170	162	182	179	194	190	196	194	−1.648	18.603
12. sitting height	80	83	82	87	94	93	108	99	115	101	−1.064	12.930
13. sitting eye height	73	68	75	75	86	83	99	96	100	99	−3.488	10.987
14. sitting elbow height	19	20	20	21	25	27	33	34	33	35	8.000	41.667
15. shoulder-elbow length	30	30	34	32	38	38	55	43	57	46	0.000	7.688
16. knee height	45	47	50	50	56	57	62	64	66	68	1.786	5.444
17. vertical reach (sit)	116	120	125	127	139	138	153	149	156	177	−0.719	2.703
18. elbow fingertip length	36	15	40	33	48	48	55	55	59	65	0.000	0.111
19. buttock popliteal length	41	38	44	42	58	57	64	67	68	69	−1.724	0.676
20. buttock heel length	84	90	89	95	107	107	120	120	124	126	0.000	0.059
21. forward grip reach (sit)	65	65	70	69	81	83	97	92	101	96	2.469	6.649
22. hand breadth	7	8	9	9	11	11	13	13	15	15	0.000	0.604
23. hand length	9	14	17	15	19	19	23	21	23	23	0.000	0.984
24. foot breadth	8	7	9	8	10	10	13	13	14	15	0.000	12.374
25. foot length	21.5	21	24	24	27	27	30	32	32	36	0.000	0.197

Note: median differences significant at the level of significance 1% are in bold. Source: Author’s compilation.

. In the first part, 25 anthropometric measurements associated with individual variables are elaborated and in the second part, there are results providing data to compare original and calculated quantiles in individual countries.

Table 1 shows the fact that in the case of the female population in the Slovak and Czech Republic in 2004, there is no significant difference in the investigated variables, i.e., anthropometric measurements in the Slovak and Czech population. Average relative difference in arithmetic means of all investigated variables was almost equal 0, individual relative differences were too slight in the range between ± 2% and their signs fluctuated randomly. Some exceptions could be seen. Body weight was the first one. The weight of Czech women was 3.5% bigger than Slovak women despite the fact that the height of both Slovak and Czech women is almost the same. The variables chest depth could be considered another exception. In the case of the Slovak population, the value of this variables was approximately 8% higher in comparison to the Czech population. This finding was interesting as the weight of Slovak women was lower than the weight of Czech women. Further exceptions can be seen in the variables sitting elbow height. The value of the Czech population was 6% higher than the value of the Slovak population. Buttock hell length, foot breadth were exceptions as well. The values of variables of the Slovak women are 2% higher than the Czech ones. Comparing the variability of measured values of the selected anthropometric variables, the fact that the variability of the values of the Czech selective sample was greater in most cases can be seen. Average relative difference in compared standard deviations of all 25 anthropometric variables was 13.6%, i.e., the variability of the values of the Czech population was approximately 14% greater. The sign of significant difference is negative, it confirms the greater variability of data in the Czech population. The same situation can be seen in the case of variables where the significant difference $s_x$ was not confirmed and most signs were negative as well.

Following the actual data associated with the female population shown in Table 2 confirmed the findings that the average relative difference in arithmetic means of all investigated variables is almost equal to 0, individual relative differences were very small, ranging between ± 2%, and their signs were random. Significant difference can be seen in the case of two variables—chest depth (the value of Czech women was by 4.7% higher than Slovak women). It can correspond with the weight which was greater in the case of Czech women. When comparing this variable, the bigger difference was in arithmetic means in 2004 but in a different country. A more significant difference can be seen in the case of the variable buttock popliteal length (the value of the Slovak population was by almost 4% higher than the Czech female population). This value of the Slovak women is higher despite the fact that Slovak women were smaller than Czech ones in 2018, even though the percentage was low. When comparing the variability of measured values of selected anthropometric variables, the fact that similar to the year 2004, the variability of the values in the Czech selective sample was higher in most cases can be seen. Significant difference was observed in the case of average relative difference in compared standard deviations in all 25 anthropometric variables and its value was −21%. In the case of 13 variables, the sign of significant difference is negative, i.e., the variability of data in the Czech population was greater, similar to the year 2004. The same situation can be seen in the case of variables where the significant difference was not confirmed and most signs were negative as well.

Table 3 shows that the values of investigated anthropometric variables of the male population differed significantly. The value of average relative difference of arithmetic means of all investigated variables was 1. 2% and in the case of more than half of the observed variables, the relative differences were in the range between ± 2%and their signs fluctuated randomly negative. However, individual relative differences differed significantly. Significant difference can be seen in the case of the variable chest depth with the 18% difference between Slovak and Czech arithmetic mean, whereby the values of the Slovak population are higher. It can be considered an interesting finding as the difference between the weight of the Slovak and Czech male population was not so big, the weight of the Czech population was even greater. Further significant difference can be seen in the case of the variables: upper limb length, buttock popliteal length, buttock heel length, forward grip reach. The values of the Slovak male population were higher by more than 3% in all variables. The next significant difference was observed in the case of the variables sitting eye height with the higher values by approximately 4% measured in the Czech population. When observing the variability, the fact that the value of the average relative difference of standard deviations in all investigated variables was −19.7%, i.e., similarly to the female population, the variability was bigger in most investigated variables in the Czech population. The number of significantly different variables was 17 with the negative sign in 16 cases.

The actual data associated with the Slovak and Czech male population are shown in Table 4. The values of investigated variables of the male population were not significantly different. The value of the average relative difference of arithmetic means of all investigated variables was 0.4 and individual relative differences were very small, ranging between ± 2%, and their signs fluctuated randomly. Significant differences can be seen in the case of five anthropometric variables: chest depth, shoulder-elbow length, elbow fingertip length, with the values of all investigated variables higher by more than 3% in the Czech male population. More significant difference in the values of the Slovak and Czech population was observed in the case of the variables sitting elbow height and buttock popliteal length with the differences bigger by more than 4%. Following the analysis of the actual values of the male population, the fact that the variability of investigated variables in the Czech population was significantly greater could be seen. Average relative difference of standard deviations in all investigated variables (−25.1%) was by 5.4% bigger in comparison to the year 2004 in the male population. The number of significant different variables was 20 with the negative sign besides one.

Table 5 shows the comparison of original and actual quantiles of the Slovak female population. In the case of the first most significant variable body weight, there was no significant change observed over the course of 14 years (1.7%). In the case of the second very significant variable height, a decrease in the value by −0.6% could be seen. When comparing individual percentiles of this variable, an increase only in 1st was observed. In the case of other percentiles, there was a decrease. In the case of the next variable, there was no change observed during the analyzed time. There are several increases and decreases in the variable corresponding with individual percentiles. There was no change observed in the case of further variables, elbow height, upper limb length, shoulder breadth, vertical reach. More significant changes occurred only in the case of two variables—sitting elbow height with an increase of 8% and foot breadth with a decrease of −10% observed. The final test showed that in the variables like shoulder height, chest depth, sitting height, sitting elbow height, shoulder-elbow length, knee height, elbow fingertip length, forward grip reach, hand breadth, and foot breadth, the values of testing criterion were higher than the critical value, i.e., the difference in medians was considered proven.

The development of the female population in the Czech Republic over the course of 14 years is given in Table 6. Interesting results in changes of the body weight can be seen. In the case of the 1st percentile, there was an increase of 4 kg, but in the case of 5th percentile, there was a decrease of almost 3 kg. The development of height in individual percentiles was variable as well. In the case of the 1st percentile, a decrease of 1 cm occurred, but in 99th percentile, there was a decrease of 2 cm. When evaluating the variable eye height, the development of original and actual quantiles in individual percentiles was similar in the variable fingertip height, showing more significant development with an increase from the 5th percentile. Considerable increase in this variable by 7 cm occurred in 95th percentile and in 99th percentile there was an increase by 2 percent more. Interesting values could be seen in the case of the variable buttock heel length. There was no change observed in 50th, 95^th, and 99th percentiles over the course of 14 years. A considerable decrease could be seen in the variable forward grip reach, mainly in 95th percentile—the value of original quantile was 94 cm and the value of actual quantile was 84 cm. Minimal change between individual percentiles was in the variables hand length, foot breadth, and foot length. Changes occurred, an increase or a decrease by up to 3 cm. The final test proved the difference in medians of 9 variables with 99% reliability.

Table 7 shows the differences between original and actual quantiles of the male population in the Slovak Republic. The development of body weight of men is a little bit more significant in comparison to the female population. An increase in individual percentiles is at least 1 kg and up to 11 kg. In the case of the second important variable—height, there were no significant changes in individual percentiles observed. Maximal change was only by 1 cm. In almost all variables, only the minimal difference can be seen over the course of 14 years. The final test showed that the differences in medians in the case of 13 variables were not proven with 99% reliability. It means that individual values of the testing criterion were not higher than the critical value. On the contrary, critical values exceeded in 12 variables, i.e., the investigated difference was considered proven.

The development of the male population in the Czech Republic over the course of 14 years is mentioned in Table 8. The most considerable increase in body weight was observed in the 99th percentile, there was an increase in the value by 5 kg. In the case of height, there were only minimal changes during the time of investigation, there was a decrease in height mentioned in some quantiles. In the case of the variable chest depth with an increase of 7 cm, the most significant change in medians was confirmed when the final test occurred. When observing 25 variables, several increases or decreases in values of medians can be seen. During final testing, the value of testing criterion exceeded the critical value in 9 variables, i.e., the difference in medians was considered proven with 99% reliability.

4. Discussion

Secular trends have been documented in many countries since the 19th century [36,37,38,39,40]. Height increases were registered in southern Europe [41,42]. Hauspie et al. (1997) [43] found secular trends in Europe during the last decades of the 20th century ranging from 3 mm/decade in Scandinavia to 30 mm/decade in parts of southern and eastern Europe.

Although height in the Netherlands [44] and Scandinavia appears to be close to a plateau, the increase is likely to continue for some decades to come in southern Europe [45]. The existence of secular trends can be considered a global phenomenon [9,46,47,48]. In this regard, our research complements a number of other studies carried out in the recent past in Slovakia and various neighboring countries. Comparing the results of our research to the results of other research studies is difficult for a variety of reasons, such as the different sample sizes, specific measurement methods, demographic coverage, ethnic mix, or health status of the participants.

Regarding the Czech population, Reference [46] confirmed an acceleration in the growth of the average body height and weight from 1955 in young men aged 18–25, and this trend has been slowing down since the 1980s. Vignerová et al. (2006) [49] registered that the average height of 13-year-old Czech boys has increased by 19.4 cm, and the average height of Czech girls has increased by 18.3 cm since 1895.

Very interesting results regarding the secular trends in heights, weights, and body mass index (BMI) in young Romanian students aged 18–24 years were reported by Ioana et al. (2014) [50]. The authors registered secular growth stagnation for males and females in height accompanied by a significant increase in BMI values in accordance to overall European trends.

Similar to Slovakia and the Czech Republic, the results of other research from other geographical areas confirm the existence of a secular trend in different parts of the world: the US and North America [51,52,53,54,55,56]; northern Europe [57,58]; south and southeastern Europe [59,60,61,62,63]; western Europe [22,43,44,64] or Asia [19,65,66,67]. In addition, some globally oriented reviews support the idea of secular growth trends in the height of the human population during the 20th century [68].

Although some indications about the contemporary slowdown or stagnation of secular trends in heights (similar to the mentioned Romanian study) were reported for some regions and populations [9,69,70,71], the positive secular trend in central and eastern Europe probably still prevails.

Several possible explanations of the positive secular trend in Slovakia are possible. First of all, the current generation is affected by the events that have taken place over the last three decades in Slovakia (the fundamental change in political regime, entry of Slovakia to the European Union). The economic prosperity of the population resulting from economic and political changes (the purchasing power more than doubled compared to 1989), the influence, availability, and quality of diet, adherence to healthy lifestyle, or availability of vitamins and medicines all could also have an impact. In addition, the positive change in healthcare greatly impacts such trends.

Grasgruber et al. (2016) [72] in their worldwide reviews found that the most important factors affecting the heights in human populations is consumption of protein-rich food and the human development index (as the measure of society wealth) which are most strongly associated with tall statures. This issue is also dealt by authors Hermanussen and Scheffler (2016) [73]. Both factors were increased or improved in Slovakia, especially after the country’s entry into EU, due to favorable economic development.

Moreover, the social status and the achieved education—one of the factors influencing the development of body physical dimensions of the human population—were improved for many families in Slovakia [74].

5. Conclusions

When comparing the Slovak and Czech population 14 years ago and nowadays, there are observed minimal changes in 25 individual anthropometric variables. In Slovakia, in the case of the variable weight of the female population, there can be seen changes in individual percentiles. An increase in 1st, 95th, and 99th percentiles by 8 kg was observed. During the last 14 years, there was an increase in the 50th percentile by only 1 kg. Minimal change in height can be seen as well. In the case of the Czech female population, there was no change in weight and only minimal change in height during the investigation period. Further exceptions can be seen in the variables sitting elbow height. The value of the Czech woman was by 6% higher than the value of the Slovak woman. Buttock hell length, foot breadth were exceptions as well. The values of variables of the Slovak women are by 2% higher than the Czech ones in the year 2004. Significant difference can be seen in the case of the variable chest depth with the 18% difference between Slovak and Czech arithmetic mean, whereby the values of the Slovak men population are higher. Further significant difference can be seen in the case of the variables: upper limb length, buttock popliteal length, buttock heel length, forward grip reach. The values of the Slovak male population were higher by more than 3% in all variables in the year 2018. At the present time, the weight is especially affected by fashion trends, different dietary habits, or food availability. On the contrary, an increase in weight of the Slovak as well as Czech population was observed. It is difficult to define whether it is an obesity or a muscle growth. However, we supposed that participants in the research were mainly university students taking care of their health, interested in sport activities and a healthy lifestyle. According to the study of Bryn et al. (2001) [75], dealing with anthropometric changes in older Canadians, body weight and height decreases as people get older. Perissinotto et al. (2002) [76] also showed that the body weight of older generation of Italians decreased considerably.

Therefore, the first main strategic direction is to strengthen the demand for high-quality human factors/ergonomics by increasing awareness among powerful stakeholders of the value of high-quality by communicating with stakeholders, by building partnerships, and by educating stakeholders. The second main strategic direction is to strengthen the application of high-quality ergonomics factors by promoting the education of specialists, by ensuring high-quality standards of applications and specialists, and by promoting research excellence at universities and other organizations [77,78,79,80,81].

Moreover, knowledge of the basic anthropometric measurements of employees is also important for creating the right workplace layout in terms of optimal performance of employees as well as the safety and hygiene at work [73,82,83,84]. Results of this study can be applied in wooden [85,86,87,88] and metal furniture, but also in agglomerated wood products [89,90,91,92,93]. Langová et al. (2019) [5] showed that all legislation dealing with furniture design takes into account users’ weight of 110 kg. However, according to anthropometric studies, 150 kg is the weight of users that should be taken into account in the future. The size of beds should be extended to 105 cm × 200 cm with a load capacity up to 150 kg. Therefore, it is necessary to improve the existing standards for testing beds; new standards for people weighing over 150 kg must be developed [78]. Following the static analysis of the load-carrying capacity of chairs, it was found that the only suitable construction type for users with a higher weight is the construction with stretchers. The leg cross-section dimensions increased by 20% and the side rail dimensions increased by 25% in the cases when a user weighed 150 kg and the tenon dimensions were 10 mm × 60 mm × 30 mm [6].

Based on the results of the long-term research of anthropometric measurements of the Slovak adult population, it can be stated that the production cost of the furniture will be increase. With the change of dimensions for a specific type of furniture—single bed, it was necessary to consider the increase of the production costs. The dimensions we proposed are as follow (length = 230.5 cm; width = 102.3 cm, and height = 45.7 cm). Using the variator method for each group of indirect costs in the areas of supply, production, sales, distribution, and administrative overhead, the change in direct costs (+11.17 €) resulted in a change in overhead costs. Compared to the traditional absorption calculation, based on rate constancy, the minimum change in overhead costs (+8.4 €) was caused by eliminating the impact of the proportionality of fixed costs [94].

Therefore, it is necessary to regularly update and monitor the data on population anthropometric characteristics in the future.