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Vol. 69. Issue 1.
Pages 4-14 (January 2022)
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Vol. 69. Issue 1.
Pages 4-14 (January 2022)
Original article
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The association between modifiable lifestyle behaviour in Latin-American schoolchildren with abdominal obesity and excess weight. A comparison of Chile and Colombia
Asociación entre comportamientos de estilo de vida modificables con obesidad abdominal y exceso de peso en preescolares latinoamericanos. Análisis entre Chile y Colombia
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Felipe Caamaño-Navarretea, Iris Paola Guzmán-Guzmánb, Constanza Palomino-Deviac, Felipe Augusto Reyes-Oyolac, Rocío Bustos-Barahonad, Daniel Jerez-Mayorgae, Pedro Delgado-Floodyf,
Corresponding author
pedro.delgado@ufrontera.cl

Corresponding author.
a Faculty of Education, Universidad Católica de Temuco, Chile
b Faculty of Chemical-Biological Sciences, Universidad Autónoma de Guerrero, Guerrero, Mexico
c Faculty of Education Sciences, Universidad de Tolima, Colombia
d Faculty of Health, School of Kinesiology, Universidad Santo Tomás, Valdivia, Chile
e Faculty of Rehabilitation Sciences, Universidad Andres Bello, Santiago, Chile
f Department of Physical Education, Sport, and Recreation, Universidad de La Frontera, Temuco, Chile
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Tables (5)
Table 1. Sociodemographic characteristics of the study sample.
Table 2. Comparison of anthropometric and physical characteristics of the study sample.
Table 3. Prevalence of abdominal obesity according to sex and country.
Table 4. Lineal correlation between WC and WtHR with physical factors in Latin-American preschool children.
Table 5. Association between abdominal obesity and lifestyle in Latin-American preschool children.
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Abstract
Objective

The purpose was to determine the association of lifestyle (i.e., Mediterranean diet [MD] adherence, physical activity [PA], screen time [ST]) and fitness with abdominal obesity (AO) and excess weight in the Chilean and Colombian schoolchildren.

Research methods & procedures

This cross-sectional study included 969 schoolchildren, girls (n=441, 5.24±0.80 years old) and boys (n=528, 5.10±0.78 years old) from Chile (n=611) and Colombia (n=358). The body mass index (BMI), waist circumference (WC), waist-to-height ratio (WtHR), MD adherence, PA, ST and cardiorespiratory fitness (CRF) were evaluated. The association of AO and anthropometric variables with lifestyle was estimated through multiple linear regression. To determine the association between AO and lifestyle, a logistic regression and the inclusion of odds ratios (ORs) with 95% confidence intervals (CIs) were used.

Results

Worse CRF in Chilean children were positively correlated with WC. Excess weight in Chilean and Colombian children was positively associated with an unhealthy lifestyle. In Chilean children unhealthy lifestyle was also associated with AO based on WC85th percentile and AO based on WtHR85th percentile. In Chilean children, excess weight (BMI85th percentile) was positively associated with poor MD adherence.

Conclusion

AO and excess weight were associated with an unhealthy lifestyle in Latin-American schoolchildren. Interventions to reduce the prevalence of AO should include promoting healthier lifestyle choices (i.e., increasing PA after school, reducing ST and improving CRF).

Keywords:
Nutritional level
Physical activity
Resistance endurance
Abdominal obesity
Resumen
Objetivo

El propósito fue determinar la asociación del estilo de vida (es decir, adherencia a la dieta mediterránea [DM], actividad física [AF], tiempo frente a la pantalla [TP]) y aptitud física con obesidad abdominal (OA) y exceso de peso en escolares chilenos y colombianos.

Métodos y procedimientos de investigación

Este estudio transversal incluyó a 969 escolares, niñas (n=441; 5,24±0,80años) y niños (n=528; 5,10±0,78años) de Chile (n=611) y Colombia (n=358). Se evaluaron el índice de masa corporal (IMC), la circunferencia de la cintura (CC), la relación cintura-altura (RCE), la adherencia a la DM, la AF, la TP y la aptitud cardiorrespiratoria (CRF). La asociación de OA y variables antropométricas con el estilo de vida se estimó mediante regresión lineal múltiple. Para determinar la asociación entre OA y estilo de vida se utilizó una regresión logística y la inclusión de odds ratios (OR) con intervalos de confianza (IC) del 95%.

Resultados

Menor CRF en los niños chilenos se correlacionó positivamente con la CC. El exceso de peso en preescolares chilenos y colombianos se asoció positivamente con un mal estilo de vida (3-5años). Además, en los niños chilenos de 3 a 5años un mal estilo de vida se asoció con AO basado en CC ≥percentil 85 y OA basado en RCE ≥percentil 85. En los niños chilenos, el exceso de peso (IMC ≥percentil 85) se asoció positivamente con una mala adherencia a la DM.

Conclusión

La OA y el exceso de peso se asociaron con un mal estilo de vida en preescolares latinoamericanos. Las intervenciones para reducir la prevalencia de OA deben incluir la promoción de un estilo de vida saludable (es decir, aumentar la AF después de la escuela, reducir el TP y mejorar la CRF).

Palabras clave:
Nivel nutricional
Actividad física
Resistencia
Obesidad abdominal
Full Text
Introduction

The prevalence of childhood obesity is reaching epidemic proportions all over the world even among preschool children,1 and has been declared a global public health problem.2 Childhood obesity has become one of the major concerns in recent years due to its association with future health problems.3 Obesity is a global phenomenon in both developed and undeveloped countries. However, as Mazza and Kovalskys have noted, there is little information regarding this issue in Latin America.4 The high prevalence of obesity in Latin America is basically caused by important changes in food habits and PA patterns and by other sociocultural factors (i.e., a lower educational and socioeconomic level), which have produced a nutritional transition process.5

Likewise, abdominal obesity (AO) is a major clinical and public health issue compared with generalized obesity in children, as AO (i.e., central obesity) is more strongly correlated with cardiometabolic risk (CMR)6 and seems to have increased during the last few decades.7 Moreover, it has been reported that AO in children increases CMR factors such as dyslipidaemia, hypertension and hyperglycaemia.6 Likewise, AO predicts a wide range of adverse health outcomes such as diabetes and cardiovascular diseases.8 Thus, more attention should be paid in epidemiological studies to AO in children, while identifying modifiable lifestyle behaviour linked to AO is necessary for developing preventive strategies.

The decrease in physical activity (PA) and the increase in sedentary behaviour in children have affected the development of healthy children.9 In this sense, a high amount of screen time (ST, the most popular sedentary behaviour) has been associated with a cluster of CMR factors10 such as AO in children.11 Additionally, PA has been indicated as an important factor in preventing CMR,12 and is a modifiable factor that is inversely associated with AO. Thus, if carried out from childhood, it can influence the adoption of an active lifestyle.13

Children's food habits represent one of the main determinant factors that influence the development of obesity.14 There is evidence that adherence to a Mediterranean diet (MD) is associated with positive effects on specific components of well-being.15 Likewise, children's food habits have an influence on health in later life,16 and may be protective factors for well-being in children. Nevertheless, there is a high prevalence of children aged 6–7 years with poor-to-moderate MD adherence.17 Additionally, better MD adherence in preschool children is associated with a lower risk of developing AO in children and adolescents.18

Another relevant factor is fitness in pre-schoolers. During childhood it has different health benefits, especially cardiorespiratory fitness (CRF), which is a basic component of a healthy lifestyle19 and is related to lower CMR.20 It has also been shown that overweight children with high CRF have a healthier cardiovascular profile.21 Moreover, higher levels of CRF substantially reduce CMR in adulthood, even among those with AO in childhood.22 Developing assessments of children's health-related physical fitness at an early stage is a priority,23 since improving physical fitness provides protection against CMR24 and is an important biomarker of health.25 The association between such modifiable behaviour as fitness and lifestyle (i.e., PA, ST and MD adherence) and obesity is well documented in children, but this association remains to be determined in Latin-American children. Therefore, the purpose of this study was to determine the association of lifestyle (i.e., MD adherence, PA and ST) and fitness with AO and excess weight in Chilean and Colombian schoolchildren.

MethodsStudy design and participants

This cross-sectional study included 969 children, girls (n=441, 5.27±0.71 years old) and boys (n=528, 5.14±0.82 years old) from Chile (n=611) and Colombia (n=358), selected by convenience sampling. Parents and guardians were informed about the study and provided signed written consent for participation. Additionally, all children gave their oral or written assent on the day of the assessment. The investigation complied with the 2013 Helsinki Declaration and was approved by the Ethics Committee (Doctoral Project, Jaen University and Local Ethics Committee).

The inclusion criteria were: (i) presenting informed consent of the parents and assent of the participant, (ii) belonging to educational centres and (iii) being between 3 and 7 years old. The exclusion criteria were having a musculoskeletal disorder or any other known medical condition, which might alter the participant's health and PA levels. Moreover, schoolchildren with physical, sensorial or intellectual disabilities were excluded.

Sociodemographic characteristics

An ad hoc sociodemographic questionnaire was used; information such as educational level, marital status and socioeconomic background (based on their socioeconomic self-perception) was collected from parents. Moreover, parents completed the information about the preschool children's PA and ST (Krece Plus test).

General obesity

The body mass index (BMI), calculated as the body mass divided by the square of the height in metres (kg/m2), was used to estimate the degree of obesity. Body mass (kg) was measured using a Tanita UM-028 scale (Tokyo, Japan); the children were weighed in their underclothes without shoes. Height (m) was estimated with a Seca® 214 stadiometer (Hamburg, Germany) that was graduated in mm. For the BMI, World Health Organization (WHO) curves were used to identify excess weight, according to sex and age.26

Abdominal obesity

Waist circumference (WC) was measured using a Seca® 201 tape measure (Hamburg, Germany) at the height of the umbilical scar.27 The waist-to-height ratio (WtHR) was obtained by dividing the WC by the height. To define AO, four aspects were considered: (i) WC in the 90th percentile of the sample study (≥65cm), (ii) WC85th percentile of the sample study (≥63cm), (iii) WtHR in the 90th percentile of the sample study (≥0.59) and (iv) WtHR85th percentile (≥0.57) of the sample study.28–30

Food habits

MD adherence of the children was assessed by the Krece Plus test,31 a tool for assessing eating patterns and their relationship with nutritional status based on the MD. The questionnaire has 15 items, and the format assesses a set of items about the food consumed in the diet. Each item has a score of +1 or −1, depending on whether it approximates the ideal of the MD. The maximum score is 11 points and the minimum −5. The total points are added, and according to the score, the nutritional status is classified as follows: (i) low nutritional level: ≤5; (ii) moderate nutritional level: 6–8; or (iii) high nutritional level: ≥9. This questionnaire has been used in Chilean schoolchildren.12

Physical activity patterns

Lifestyle was evaluated with the Krece Plus test,31 a quick questionnaire that classifies lifestyle according to the daily average of hours spent watching television or playing video games (h/day) and hours of PA after school per week (h/week). Classification is made according to the number of hours used for each point. The total points are added, and the person is classified as having: (i) good lifestyle (men: ≥9, women8), (ii) regular lifestyle (men: 6–8, women: 5–7) or (iii) bad lifestyle (men: ≤5, women: ≤4).

Physical fitness

For the evaluation of physical fitness, leg strength, CRF and handgrip strength were measured.

Lower-body explosive strength was assessed by a standing long jump test (SLJ).32 The SLJ has been used in preschool children33 and consists of jumping a distance with both feet at the same time. For this, the student stands behind the jump line, and with a foot separation equal to the width of their shoulders; the knees are then bent with the arms in front of the body and parallel to the ground. From this position, they swing their arms, push hard and jump as far as possible, making contact with the ground with both feet simultaneously and in a vertical position. This is done twice, and the best result is recorded.

Handgrip strength was used to measure upper body strength through a hand dynamometer (TKK 5101 Grip D; Takei, Tokyo, Japan). The test consists of holding a dynamometer in one hand and squeezing as tightly as possible without allowing the dynamometer to touch the body; force is applied gradually and continuously for a maximum of 3–5s.32 The test was performed twice, and the maximum score for each hand was recorded in kilograms. The average of the scores achieved by the left and right hands was used in the analysis. Higher scores indicate better performance.

CRF was assessed using the 100m×20m test, inspired by the spatial structure of the Léger test.34 The 100m×20m test has been used in preschool children and has been validated.35 Its design takes into account the age of the children, the rules being very simple and the test enjoyable to perform. The materials required are a tape measure to mark the distances of the runway (20m), two boxes, five balloons and a stopwatch. It is a 20m shuttle test, in which participants have to move five balloons from box A, located at one extreme, to box B, located at the opposite extreme. The total distance covered is 200m, timed from the signal “Go” until the participant deposits the last balloon. It is unimportant whether or not the balloon enters the box. If dropped, the participant has to pick it up and continue moving. Supervisors indicate that the balloon has to be held with both hands. Only one attempt is made and running and walking are allowed. The result is recorded in seconds with one decimal place, a slower time indicating a poorer performance.

Statistical analysis

Statistical analyses were performed using STATA V.13.0. (StataCorp, College Station, TX, USA). Normal distribution was tested using the Kolmogorov–Smirnov test. For continuous variables, values were presented as means and standard deviations (SDs), whereas for categorical variables, data were presented as proportions. Differences between groups were determined using one-way ANOVA and the χ2 test. The association of AO and anthropometric variables with lifestyle was estimated through multiple linear regression. To determine the association between AO and lifestyle, a logistic regression and the inclusion of odds ratios (ORs) with 95% confidence intervals (CIs) were used. Values of P<0.05 were considered statistically significant.

ResultsSociodemographic antecedents

There were no significant differences between the proportion of girls and boys or the parents’ antecedents (i.e., marital status, study level and socioeconomic background) in the comparison between Chilean and Colombian children (Table 1).

Table 1.

Sociodemographic characteristics of the study sample.

  Chile(n=611)  Colombia(n=358)  P-value 
Sex
Girls  277 (45.3)  164 (45.8)  0.88 
Boys  334 (54.7)  194 (54.2)   
Age, y (5–95th)  5 (4–6)  5 (4–6)  0.26 
Age category
3–5 years old  400 (64.1)  211 (61.2)  0.36 
6–7 years old  224 (35.9)  134 (38.8)   
Parents information
Socioeconomic background n (%)
Low/middle low  248 (40.6)  136 (38)  0.59 
Middle  345 (56.5)  208 (58.1)   
Middle high/high  18 (2.9)  14 (3.9)   
Study level n (%)
Primary  112 (18.3)  67 (18.7)  0.95 
Secondary  237 (38.8)  141 (39.4)   
University  262 (42.9)  150 (41.9)   
Marital status n (%)
Single  190 (31.1)  98 (27.4)  0.57 
Married  271 (44.3)  163 (45.5)   
Divorced  94 (15.4)  64 (17.9)   
Widow  56 (9.2)  33 (9.2)   

The data shown represent n (proportions). P<0.05 considered statistically significant.

Comparison between sexes in Chilean vs. Colombian preschool children

According to the anthropometric parameters, the boys in Chile had a higher BMI (P<0.001), WC (P<0.001) and WtHR (P<0.001) than the Colombian children. In relation to fitness, Chilean children presented better results in the ‘10×20’ resistance test than Colombian children (P<0.001). However, regarding handgrip strength the Chilean children had worse results than the Colombian children (P=0.007). For lifestyle, Chilean children presented higher MD adherence (P=0.040), hours of PA after school per week (P<0.001) and ST per day (P<0.001) than Colombian children. Chilean girls had higher WC (P<0.001) than Colombian girls; likewise, they had better results in the 10×20 resistance test (P<0.001). For lifestyle, the Chilean girls had higher levels of moderate and high MD adherence (P=0.040), hours of PA after school per week (P<0.001) and ST per day than Colombian girls (P<0.001) (Table 2).

Table 2.

Comparison of anthropometric and physical characteristics of the study sample.

  Chilen=611Colombian=358P value  P value 
  Girls (ABoys (BGirls (CBoys (DA×CA×B°  B×DC×D° 
Age (y)  5 (4–5)  6 (4–6)  5 (4–5)  6 (4–7)  0.76<0.001°  0.07<0.001° 
Body mass (kg)  19 (14–27.2)  21.4 (16–33)  19.0 (14–25)  21.35 (17.3–31.9)  0.43<0.001°  0.61<0.001° 
Size (m)  1.13 (0.99–1.29)  1.13 (1.0–1.34)  1.11 (0.99–1.2)  1.17 (1.06–1.32)  <0.0010.79°  <0.001<0.001° 
BMI (kg/m2)  14.9 (9.7–22.5)  17 (12.0–22.6)  15.4 (11.6–19.9)  15.7 (13–20.6)  0.05<0.001°  <0.0010.07° 
WC (cm)  59 (50.7–66)  58 (51–66)  56.1 (50–67)  55.5 (50–65.5)  <0.0010.06°  <0.0010.21° 
WtHR (WC/size)  0.52 (0.43–0.63)  0.51 (0.43–0.59)  0.50 (0.44–0.62)  0.47 (0.40–0.58)  0.200.08°  <0.001<0.001 
Fitness
SJT (cm)  82 (46–114.5)  83 (43–117)  83 (39–117)  82 (49–116)  0.800.65  0.980.83° 
Speed 20m (s)  6 (4.8–7.6)  6.02 (4.7–7.7)  6.3 (4.8–7.5)  5.9 (4.5–7.8)  0.200.80°  0.400.05° 
Resistance 10×20 (s)  75.6 (63.5–95.4)  75.0 (66–95)  84.8 (60–112)  90 (60–120)  <0.0010.58°  <0.001<0.001 
Handgrip strength (kg)  5.7 (2–8)  5.5 (2.0–8.2)  6 (2–11.8)  6 (2–17.3)  0.0010.35°  0.0070.80 
Lifestyle
MD adherence (−5 to 11)  5 (−2 to 9)  5 (−2 to 9)  3 (−1 to 9)  3 (−1 to 8)  0.390.52°  0.0400.50° 
Mediterranean diet adherence0.040.47°  0.0030.70° 
Low MD  229 (57.3)  151 (67.4)  151 (67.4)  96 (71.6)     
Moderate MD  143 (35.7)  61 (27.2)  61 (27.2)  32 (23.9)     
High MD  28 (7.0)  12 (5.4)  12 (5.4)  6 (4.5)     
PA after school (h/week)  3 (1–5)  3 (1–5)  3 (0–5)  2 (0–5)  <0.0010.91°  <0.0010.14° 
ST (h/day)  4 (1–4)  4 (1–5)  3 (1–5)  2 (1–4)  <0.0010.99°  <0.0010.75° 
Lifestyle (PA+ST)<0.0010.051°  0.340.10° 
Bad PA  252 (63.0)  125 (59.2)  106 (47.3)  78 (58.2)     
Regular PA  111 (27.8)  75 (35.55)  108 (48.2)  53 (39.5)     
Good PA  37 (9.2)  11 (5.2)  10 (4.5)  3 (2.24)     

The quantitative variables shown median (percentiles 5–95), qualitative variables represent n (proportions). P<0.05 considered statistically significant. BMI=body max index, WC=waist circumference, WtHR=waist-to-height ratio, SLJ=standing long jump test, MD=Mediterranean diet, PA=physical activity, ST=screen time.

Prevalence of obesity in Chilean vs. Colombia preschool children

In Chilean girls, excess weight was present in 36.5%, of which 21.3% fell into the obesity category, while 9.1% of Colombian girls were obese. Similarly, 39.5% of Chilean boys had excess weight, of which 27.2% were obese, while 13.9% of Colombian boys were obese (Fig. 1).

Figure 1.

Prevalence of obesity according to sex. Cl=Chile, Col=Colombia.

(0.14MB).

In relation to AO, more Chilean girls (24.2% vs. 7.9%, P<0.001) and boys (18.3% vs. 10.3%, P=0.0014) had a higher AO based on WC85th percentile (≥ 63cm) than their Colombian peers. Assessing AO based on WtHR85th percentile (≥ 0.57), more Chilean girls (25.3% vs. 7.3%) had AO than Colombian girls and Chilean boys (25.3% vs. 17.1%, P=0.013) (Table 3).

Table 3.

Prevalence of abdominal obesity according to sex and country.

  Chilen=611Colombian=358P value
  Girlsn=277  Boysn=334  Girlsn=164  Boysn=194  A×CA×B°  B×DC×D° 
  (A(B(C(D   
AO by WC 90th percentile (≥65cm)0.0060.20°  0.250.43° 
AO  41 (14.8)  38 (11.38)  10 (6.1)  16 (8.25)     
Non-AO  236 (85.2)  296 (88.62)  154 (93.9)  178 (91.75)     
AO by WC 85th percentile (≥63cm)<0.0010.073°  0.0140.43° 
AO  67 (24.2)  61 (18.3)  13 (7.9)  20 (10.3)     
Non-AO  210 (75.8)  273 (81.7)  151 (92.1)  174 (89.7)     
AO by WtHR 90th percentile(≥0.59 ratio)0.0030.035°  0.730.11° 
AO  43 (15.52)  33 (9.88)  10 (6.1)  21 (10.82)     
Non-AO  234 (84.48)  301 (90.1)  154 (93.9)  173 (89.2)     
AO by WtHR 85th percentile (≥0.57 ratio)<0.0010.013°  0.520.024° 
AO  70 (25.3)  57 (17.1)  12 (7.3)  29 (15.0)     
Non-AO  207 (74.7)  277 (82.9)  152 (92.7)  165 (85.0)     

Data represent n (proportions), P value determined by Chi2. P<0.05 was considered statistically significant. AO=abdominal obesity. WC=waist circumference, WtHR=waist-to-height ratio.

Linear correlation between abdominal obesity markers and lifestyle

Worse results in the 10×20 resistance test (i.e., CRF) in Chilean girls and boys were positively correlated with WC (girls, r=0.34, P<0.001; boys, r=0.26, P<0.001) and WtHR (girls, r=0.27, P<0.001; boys r=0.22, P<0.001). PA after school was inversely correlated with WC in girls (r=−0.15, P=0.009) and boys (r=−0.23, P<0.001). In Colombian girls (r=0.20, P=0.009) and boys (r=0.24, P<0.001), MD adherence was positively correlated with WC. ST was positively correlated with WC in Chilean girls (r=0.23, P<0.001) and boys (r=0.24, P<0.001). The same relation was found in Colombian girls and boys (r=0.16, P=0.030 and r=0.16, P=0.040, respectively) (Table 4).

Table 4.

Lineal correlation between WC and WtHR with physical factors in Latin-American preschool children.

  ChileColombia
WC (cm)^WHtR (ratio)  Girlsr* (P value)  Boysr* (P value)  Girlsr* (P value)  Boysr* (P value) 
Age (y)  −0.05 (0.35)−0.05 (0.32) ^  −0.07 (0.17)−0.07 (0.15) ^  −0.15 (0.04)−0.49 (<0.001)^  0.006 (0.92)−0.31 (<0.001) ^ 
BMI (kg/m2)  0.15 (0.01)0.44 (<0.001)  0.06 (0.21)0.24 (<0.001) ^  −0.07 (0.33)0.04 (0.59)^  0.01 (0.85)0.24 (<0.001) ^ 
WtHR (WC/size)  0.71 (<0.001)−^  0.69 (<0.001)−^  0.73 (<0.001)−^  0.73 (<0.001)−^ 
BMI percentile  0.14 (0.019)0.42 (<0.001) ^  0.05 (0.30)0.22 (<0.001) ^  −0.07 (0.33)0.05 (0.48)^  0.006 (0.92)0.23 (0.001) ^ 
Fitness
SJT (cm)  −0.01 (0.84)−0.06 (0.28) ^  −0.04 (0.37)−0.01 (0.80) ^  0.11 (0.15)0.18 (0.01)^  0.001 (0.98)0.02 (0.68)^ 
Speed 20m (s)  0.09 (0.10)0.13 (0.029) ^  −0.05 (0.29)−0.01 (0.80) ^  0.01 (0.86)−0.03 (0.62)^  −0.15 (0.03)−0.20 (0.004)^ 
Resistance 10×20 (s)  0.34 (<0.001)0.27 (<0.001) ^  0.26 (<0.001)0.22 (<0.001) ^  0.007 (0.92)−0.08 (0.28) ^  0.01 (0.87)0.01 (0.85)^ 
Handgrip strength (kg)  0.09 (0.12)0.04 (0.49) ^  −0.01 (0.83)−0.02 (0.64) ^  0.04 (0.55)0.13 (0.07)^  0.003 (0.95)−0.02 (0.72)^ 
Lifestyle
MD adherence (−5 to 11)  0.006 (0.91)−0.05 (0.34) ^  0.05 (0.27)0.05 (0.28) ^  0.20 (0.009)0.20 (0.008) ^  0.24 (<0.001)0.10 (0.14)^ 
PA after school (h/week)  −0.15 (0.009)−0.08 (0.16) ^  −0.23 (<0.001)−0.18 (<0.001) ^  0.05 (0.46)0.04 (0.53)^  0.007 (0.91)0.08 (0.23)^ 
ST (h/day)  0.23 (<0.001)0.14 (0.01) ^  0.24 (<0.001)0.17 (0.001) ^  0.16 (0.03)0.12 (0.11)^  0.14 (0.04)0.04 (0.54)^ 

Data represent r*=Pearson correlation coefficient (P value), P<0.05 considered statistically significant. BMI=body mass index, WC=waist circumference, WtHR=waist-to-height ratio, SLJ=standing long jump test, MD=Mediterranean diet, PA=physical activity, ST=screen time.

Association of variables with abdominal obesity

Excess weight in Chilean (OR: 1.73, 95%CI: 1.1–2.73, P=0.018) and Colombian children (OR: 1.83, 95%CI: 0.96–3.47, P=0.06) was positively associated with bad lifestyle. In Chilean children, a bad lifestyle was also associated with AO based on WC in the 90th percentile (OR: 2.36, 95%CI: 1.22–4.54, P=0.010), AO based on WC85th percentile (OR: 1.74, 95%CI: 1.04–2.9, P=0.032) and AO based on WtHR85th percentile (OR: 1.75, 95%CI: 1.06–2.89, P=0.028). Moreover, in Colombian children, low MD adherence was inversely associated with AO based on WC85th percentile (OR: 0.44, 95%CI: 0.23–0.84, P=0.010). By contrast, in Chilean children, excess weight – a BMI85th percentile – was positively associated with bad MD adherence (OR: 1.43, 95%CI: 1.0–2.05, P=0.04) (Table 5).

Table 5.

Association between abdominal obesity and lifestyle in Latin-American preschool children.

  Chilen=611Colombian=358
  4–5 years old  6–7 years old  4–5 years old  6–7 years old 
  OR (CI95%) P value  OR (CI95%) P value  OR (CI95%) P value  OR (CI95%) P value 
Bad lifestyle (PA+ST)
EW-BMI85th  1.73 (1.1–2.73), 0.018  1.14 (0.65–2.0), 0.63  1.83 (0.96–3.47), 0.06  1.60 (0.70–3.65), 0.25 
AO by WC 90th  2.36 (1.22–4.54), 0.010  3.31 (1.05–10.4), 0.04  1.65 (0.60–4.5), 0.32  6.42 (0.77–53.2), 0.08 
AO by WC 85th  1.74 (1.04–2.90), 0.032  1.69 (0.77–3.7), 0.18  1.69 (0.69–4.1), 0.25  3.53 (0.73–17.0), 0.11 
AO by WtHR 90th  1.66 (0.91–3.04), 0.09  1.73 (0.55–5.37), 0.34  1.23 (0.53–2.84), 0.62  1.46 (0.25–8.26), 0.66 
AO by WtHR 85th  1.75 (1.06–2.89), 0.028  0.89 (0.40–1.99), 0.78  1.21 (0.56–2.62), 0.61  3.08 (0.63–15.1), 0.16 
Low MD adherence
EW- BMI ≥85th  1.43 (1.0–2.05), 0.04  0.86 (0.56–1.30), 0.48  1.27 (0.72–2.26), 0.39  0.97 (0.48–1.97), 0.95 
AO by WC 90th  1.33 (0.83–2.14), 0.22  1.17 (0.56–2.44), 0.65  0.49 (0.24–1.01), 0.056  0.53 (0.19–1.46), 0.22 
AO by WC 85th  1.01 (0.69–1.46), 0.95  0.97 (0.56–1.67), 0.91  0.44 (0.23–0.84), 0.010  0.42 (0.17–1.06), 0.06 
AO by WtHR 90th  1.25 (0.79–1.98), 0.33  0.57 (0.26–1.22), 0.15  0.72 (0.37–1.39), 0.33  0.61 (0.17–2.15), 0.44 
AO by WtHR 85th  1.08 (0.74–1.57), 0.67  0.82 (0.45–1.49), 0.53  0.63 (0.34–1.15), 050  0.37 (0.14–0.95), 0.040 

The data shown represent OR, (95%CI), P-value. The OR was adjusted by sex. AO=abdominal obesity, WC=waist circumference, WtHR=waist to height ratio, EW=excessive weight.

Discussion

The purpose of this study was to determine the association of lifestyle (i.e., MD adherence, PA and ST) and fitness with AO and excess weight in Chilean and Colombian children. The main results were: (i) in Chilean and Colombian children, AO was associated with a poor lifestyle, (ii) ST was positively correlated with WC in Chilean and Colombian preschool children, and (iii) worse CRF results (10×20 test) were positively correlated with WC and WtHR in Chilean girls and boys, but not in Colombian children.

In the present study, we found a higher prevalence of AO in Chilean girls (25.3%), than boys and Colombian girls. In a study conducted in 5231 Greek children, the prevalence of AO did not differ between boys and girls at the age of 7 (25.2% and 25.3% respectively), while at the age of 9 more boys than girls had AO (33.2% and 28.2%, respectively).36 In another study evaluating 1433 Portuguese children (6–12 years old), the prevalence of AO based on the measurement of WC was similar in girls and boys; however, according to WtHR, boys had a higher prevalence than girls.37 Another investigation reported a high prevalence of AO in children between 3 and 10 years old, where 30.5% of the children had AO.38 Evidence of the prevalence of AO in children is worrying, as it is a risk factor for cardiovascular diseases and cancer in adults.39 Another study reported that those presenting high WC values are more likely to have hypertension, diabetes, dyslipidaemia and CMR compared with those with normal WC values.40

In Chilean and Colombian children, excess weight (i.e., overweight and obesity) and AO was associated with a bad lifestyle (i.e., low PA after school and high ST). In accordance with our results, a study conducted in Canadian preschool children reported that a healthy lifestyle such as good PA patterns and low sedentary behaviour is significantly associated with healthy BMI z-scores but not with WC.41 Similarly, a longitudinal study demonstrated that an unhealthy lifestyle (i.e., bad food habits and high ST) is associated with high body fat in preschool girls.42 On the other hand, a recent study reported that BMI and WC are not associated with lifestyle (i.e., PA and sedentary behaviour) in preschool children,43 results in discordance with ours. In addition, childhood obesity has re-focused attention on the importance of a healthy lifestyle (i.e., PA and ST) in this age group.44 In this context, another study conducted in school age children and adolescents concluded that obesity in childhood and adolescence should be considered a health problem in Latin American countries.4

In the present study, we found that ST is positively related to WC in Chilean and Colombian children. In accordance with our results, it has been reported that those preschool children exhibiting more sedentary behaviour such as ST are more likely to have more AO.45 Moreover, Wuan et al.46 reported that preschool children who do not meet the ST guidelines are at higher risk for overweight and obesity. Similarly, Li et al.47 reported that ST is independently associated with childhood obesity. In accordance with our results, it has been demonstrated that ST increases the BMI, BMI z-score and AO in European preschool children.48

In the present study, we found that worse CRF (i.e., a slow time in test 10×20) was positively correlated with WC and WtHR in Chilean girls and boys, but not in Colombian children. Another study reported that higher CRF is associated with lower AO in Spanish preschool children.49 Similarly, Martínez et al.50 reported a significant association of the 20m shuttle run test (i.e., CRF) with the BMI and WC in preschool children. Additionally, it has been reported that free fat mass is associated with better CRF in preschool children.51 A longitudinal study reported that a high CRF at 4.5 years old is associated with better corporal composition at 5.5 years old in preschool children.52 Finally, further investigation is needed with the aim of clarifying the effects of physical fitness at preschool age on later health outcomes.52

In Chilean children, AO was positively associated with low MD adherence; by contrast, in Colombian children, low MD adherence had an inverse association with AO. It has been reported that high MD adherence is related to lower WC49 and associated with a lower risk of preschoolers developing overweight, obesity and AO in the future.18 Therefore, MD adherence is a relevant modifiable factor to be targeted in educational strategies aiming to prevent central obesity.49 The evidence shows that Chile has the appropriate characteristics for developing MD adherence. Also, MD adherence is a key tool to protect health and is not exclusive to the countries of the Mediterranean basin. It should be a target of community based interventions to promote health.53

Limitations

The limitations of the present study include those inherent to its transversal character. Another limitation is the self-reporting of parents in relation to the children's PA and food habits, which could mean that these data are underestimated or overestimated. We recognize the need to investigate possible longitudinal effects and to clarify the direction of the associations and carry out interventions in children's lifestyle.

The strengths of this study are that we examined several variables that affect children's development and have contributed to a better understanding of the serious problem of bad lifestyle in Latin-American children.

Conclusion

Chilean children have a higher prevalence of AO than their Colombian peers. Moreover, AO and excess weight are associated with a poor lifestyle in children of both countries, and are related to worse CRF results. Therefore, interventions to reduce the prevalence of AO should include promoting a healthy lifestyle (i.e., increasing PA after school, reducing ST and improving CRF) in Latin-American children. Strategies for preventing and reducing children's AO, through an accessible, economical and worldwide effort, should be considered as aids in the development of healthy habits and behaviour in schoolchildren.

Authors’ contributions

FC-N and PD-F contributed to the conception, organization and oversight of the study, the drafting of the analysis plan, writing the original manuscript draft and final approval of the version to be published. DJ-M, CP-V, RB-R and AR-O contributed to writing the original manuscript draft and final approval of the version to be published. IPG-G drafted the analysis plan, wrote the original manuscript draft and gave final approval of the version to be published.

Funding

This research received no external funding.

Conflicts of interest

The authors declare no conflict of interest.

Acknowledgments

The authors thank the teachers, parents, students and the schools (education centres) that participated in the research.

References
[1]
M. Garrido-Miguel, I. Cavero-Redondo, C. Alvarez-Bueno, F. Rodriguez-Artalejo, L.A. Moreno, J.R. Ruiz, et al.
Prevalence and trends of overweight and obesity in European children from 1999 to 2016: a systematic review and meta-analysis.
JAMA Pediatr, 173 (2019), pp. e192430
[2]
C.L. Roth, V. Jain.
Rising obesity in children: a serious public health concern.
Indian J Pediatr, 85 (2018), pp. 461-462
[3]
T. Vanlancker, E. Schaubroeck, K. Vyncke, C. Cadenas-Sanchez, C. Breidenassel, M. Gonzalez-Gross, et al.
Comparison of definitions for the metabolic syndrome in adolescents. The HELENA study.
Eur J Pediatr, 176 (2017), pp. 241-252
[4]
C. Mazza, I. Kovalskys.
Epidemiología de la obesidad infantil en países de Latinoamérica.
Med Infant, 9 (2002), pp. 299-304
[5]
D.F. Pedraza.
Obesidad y pobreza: marco conceptual para su análisis en Latinoamérica.
Saúde e Sociedade, 18 (2009), pp. 103-117
[6]
R. Kelishadi, P. Mirmoghtadaee, H. Najafi, M. Keikha.
Systematic review on the association of abdominal obesity in children and adolescents with cardio-metabolic risk factors.
J Res Med Sci, 20 (2015), pp. 294-307
[7]
C.N. Katsagoni, G. Psarra, M. Georgoulis, K. Tambalis, D.B. Panagiotakos, L.S. Sidossis.
High and moderate adherence to Mediterranean lifestyle is inversely associated with overweight, general and abdominal obesity in children and adolescents: the MediLIFE-index.
[8]
F.C. Teixeira, F.E.F. Pereira, A.F. Pereira, B.G. Ribeiro.
Overweight, obesity and abdominal obesity and its association with cardiometabolic risk factors in Brazilian schoolchildren: a cross-sectional study.
Nutrition, (2020), pp. 110780
[9]
S.J. te Velde, F. Van Nassau, L. Uijtdewilligen, M.M. Van Stralen, G. Cardon, M. De Craemer, et al.
Energy balance-related behaviours associated with overweight and obesity in preschool children: a systematic review of prospective studies.
[10]
H. Wang, J. Zhong, R. Hu, B. Fiona, M. Yu, H. Du.
Prevalence of high screen time and associated factors among students: a cross-sectional study in Zhejiang, China.
BMJ Open, 8 (2018), pp. e021493
[11]
M.V. Nascimento-Ferreira, T. Rendo-Urteaga, A.C.F. De Moraes, L.A. Moreno, H.B. Carvalho.
Abdominal obesity in children: the role of physical activity sedentary behavior, and sleep time.
Nutr Prevent Treat Abdom Obes, (2019), pp. 81-94
[12]
P. Delgado-Floody, C. Alvarez, F. Caamaño-Navarrete, D. Jerez-Mayorga, P. Latorre-Román.
The influence of Mediterranean diet adherence, physical activity patterns and weight status on cardiovascular response to cardiorespiratory fitness test in Chilean schoolchildren.
Nutrition, (2020), pp. 110621
[13]
R.K. Kelly, R. Thomson, K.J. Smith, T. Dwyer, A. Venn, C.G. Magnussen.
Factors affecting tracking of blood pressure from childhood to adulthood: the childhood determinants of adult health study.
J Pediatr, 167 (2015),
[14]
D. Bundhun, S. Rampadarath, D. Puchooa, R. Jeewon.
Dietary intake and lifestyle behaviors of children in Mauritius.
[15]
R. Ferrer-Cascales, N. Albaladejo-Blázquez, N. Ruiz-Robledillo, V. Clement-Carbonell, M. Sánchez-SanSegundo, A. Zaragoza-Martí.
Higher adherence to the Mediterranean diet is related to more subjective happiness in adolescents: the role of health-related quality of life.
Nutrients, 11 (2019), pp. 698
[16]
J.J. Muros, C. Cofre-Bolados, D. Arriscado, F. Zurita, E. Knox.
Mediterranean diet adherence is associated with lifestyle, physical fitness, and mental wellness among 10-y-olds in Chile.
Nutrition, 35 (2017), pp. 87-92
[17]
A. Buja, G. Grotto, F. Brocadello, M. Sperotto, V. Baldo.
Primary school children and nutrition: lifestyles and behavioral traits associated with a poor-to-moderate adherence to the Mediterranean diet. A cross-sectional study.
Eur J Pediatrics, (2020), pp. 1-8
[18]
L. Notario-Barandiaran, D. Valera-Gran, S. Gonzalez-Palacios, M. Garcia-de-la-Hera, S. Fernández-Barrés, E. Pereda-Pereda, et al.
High adherence to a mediterranean diet at age 4 reduces overweight, obesity and abdominal obesity incidence in children at the age of 8.
Int J Obes, (2020), pp. 1-12
[19]
M. Jankowski, A. Niedzielska, M. Brzezinski, J. Drabik.
Cardiorespiratory fitness in children: a simple screening test for population studies.
Pediatr Cardiol, 36 (2015), pp. 27-32
[20]
A. Díez-Fernández, M. Sánchez-López, R. Mora-Rodríguez, B. Notario-Pacheco, C. Torrijos-Niño, V. Martínez-Vizcaíno.
Obesity as a mediator of the influence of cardiorespiratory fitness on cardiometabolic risk: a mediation analysis.
Diabetes Care, (2013),
[21]
J.L. Walker, T.D. Murray, J. Eldridge, J. Squires, G. William, P. Silvius, et al.
The Association between waist circumference and FITNESSGRAM® aerobic capacity classification in sixth-grade children.
Pediatr Exerc Sci, 27 (2015), pp. 488-493
[22]
M.D. Schmidt, C.G. Magnussen, E. Rees, T. Dwyer, A.J. Venn.
Childhood fitness reduces the long-term cardiometabolic risks associated with childhood obesity.
Int J Obes (Lond), 40 (2016), pp. 1134-1140
[23]
M. Lindgren, M. Aberg, M. Schaufelberger, D. Aberg, L. Schioler, K. Toren, et al.
Cardiorespiratory fitness and muscle strength in late adolescence and long-term risk of early heart failure in Swedish men.
Eur J Prev Cardiol, 24 (2017), pp. 876-884
[24]
R. Bustos-Barahona, P. Delgado-Floody, C. Martinez-Salazar.
Lifestyle associated with physical fitness related to health and cardiometabolic risk factors in Chilean schoolchildren.
Endocrinol Diabetes Nutr, (2020),
[25]
A. García-Hermoso, R. Ramírez-Campillo, M. Izquierdo.
Is muscular fitness associated with future health benefits in children and adolescents? A systematic review and meta-analysis of longitudinal studies.
[26]
M. de Onis, A.W. Onyango, E. Borghi, A. Siyam, C. Nishida, J. Siekmann.
Development of a WHO growth reference for school-aged children and adolescents.
Bull World Health Organ, 85 (2007), pp. 660-667
[27]
H. Schröder, L. Ribas, C. Koebnick, A. Funtikova, S.F. Gomez, M. Fíto, et al.
Prevalence of abdominal obesity in Spanish children and adolescents. Do we need waist circumference measurements in pediatric practice?.
[28]
C.A. Alves Junior, M.C. Mocellin, E.C.A. Gonçalves, D.A. Silva, E.B. Trindade.
Anthropometric indicators as body fat discriminators in children and adolescents: a systematic review and meta-analysis.
Adv Nutr, 8 (2017), pp. 718-727
[29]
R.W. Taylor, I.E. Jones, S.M. Williams, A. Goulding.
Evaluation of waist circumference, waist-to-hip ratio, and the conicity index as screening tools for high trunk fat mass, as measured by dual-energy X-ray absorptiometry, in children aged 3–19 y.
Am J Clin Nutr, 72 (2000), pp. 490-495
[30]
Y. Fujita, K. Kouda, H. Nakamura, M. Iki.
Cut-off values of body mass index, waist circumference, and waist-to-height ratio to identify excess abdominal fat: population-based screening of Japanese schoolchildren.
J Epidemiol, 21 (2011), pp. 191-196
[31]
L.S. Majem, L.R. Barba, J.A. Bartrina, C.P. Rodrigo, P.S. Santana, L.P. Quintana.
Obesidad infantil y juvenil en España Resultados del Estudio enKid (1998–2000).
Med Clin, 121 (2003), pp. 725-732
[32]
J.R. Ruiz, V. Espana Romero, J. Castro Pinero, E.G. Artero, F.B. Ortega, M. Cuenca, et al.
Bateria ALPHA-Fitness: test de campo para la evaluacion de la condicion fisica relacionada con la salud en ninos y adolescentes.
Nutr Hosp, 26 (2011), pp. 1210-1214
[33]
P. Román-Latorre, D. López Mora, M. Fernández-Sánchez, J. Salas-Sánchez, F. Moriana-Coronas, F. García-Pinillos.
Test–retest reliability of a field-based physical fitness assessment for children aged 3–6 years.
Nutr Hosp, 32 (2015), pp. 1683-1688
[34]
L.A. Leger, D. Mercier, C. Gadoury, J. Lambert.
The multistage 20 metre shuttle run test for aerobic fitness.
J Sports Sci, 6 (1988), pp. 93-101
[35]
P. Latorre-Román, D. Mora-López, F. García-Pinillos.
Feeding practices, physical activity, and fitness in Spanish preschoolers. Influence of sociodemographic outcome measures.
Arch Argent Pediatr, 114 (2016), pp. 441-447
[36]
M. Hassapidou, T. Tzotzas, E. Makri, I. Pagkalos, I. Kaklamanos, E. Kapantais, et al.
Prevalence and geographic variation of abdominal obesity in 7- and 9-year-old children in Greece; World Health Organization Childhood Obesity Surveillance Initiative 2010.
BMC Public Health, 17 (2017), pp. 126
[37]
D. Albuquerque, C. Nóbrega, H. Samouda, L. Manco.
Assessment of obesity and abdominal obesity among Portuguese children.
Acta Med Portug, 25 (2012), pp. 169-173
[38]
M.R. Melzer, I.M. Magrini, S.M. Domene, P.A. Martins.
Factors associated with abdominal obesity in children.
Revista paulista de pediatria: orgao oficial da Sociedade de Pediatria de Sao Paulo, 33 (2015), pp. 437-444
[39]
C. Zhang, K.M. Rexrode, R.M. van Dam, T.Y. Li, F.B. Hu.
Abdominal obesity and the risk of all-cause, cardiovascular, and cancer mortality: sixteen years of follow-up in US women.
Circulation, 117 (2008), pp. 1658-1667
[40]
I. Janssen, P.T. Katzmarzyk, R. Ross.
Body mass index, waist circumference, and health risk: evidence in support of current National Institutes of Health guidelines.
Arch Intern Med, 162 (2002), pp. 2074-2079
[41]
V. Carson, M.S. Tremblay, S.F.M. Chastin.
Cross-sectional associations between sleep duration, sedentary time, physical activity, and adiposity indicators among Canadian preschool-aged children using compositional analyses.
BMC Public Health, 17 (2017), pp. 848
[42]
C. Saldanha-Gomes, M. Marbac, M. Sedki, M. Cornet, S. Plancoulaine, M.A. Charles, et al.
Clusters of diet, physical activity, television exposure and sleep habits and their association with adiposity in preschool children: the EDEN mother-child cohort.
Int J Behav Nutr Phys Activity, 17 (2020), pp. 20
[43]
R. Wiersma, B.F. Haverkamp, J.H. van Beek, A.M. Riemersma, H.M. Boezen, N. Smidt, et al.
Unravelling the association between accelerometer-derived physical activity and adiposity among preschool children: a systematic review and meta-analyses.
Obes Rev, 21 (2020), pp. e12936
[44]
B.W. Timmons, P.-J. Naylor, K.A. Pfeiffer.
Physical activity for preschool children—how much and how?.
Appl Physiol Nutr Metab, 32 (2007), pp. S122-S134
[45]
J. Mota, S. Silva Dos Santos, A. Santos, A. Seabra, S. Vale.
Association between sedentary behavior time and waist-to-height ratio in preschool children.
Am J Hum Biol, 28 (2016), pp. 746-748
[46]
H. Guan, Z. Zhang, B. Wang, A.D. Okely, M. Tong, J. Wu, et al.
Proportion of kindergarten children meeting the WHO guidelines on physical activity, sedentary behaviour and sleep and associations with adiposity in urban Beijing.
BMC Pediatr, 20 (2020), pp. 70
[47]
L. Li, T. Shen, L.M. Wen, M. Wu, P. He, Y. Wang, et al.
Lifestyle factors associated with childhood obesity: a cross-sectional study in Shanghai, China.
BMC Res Notes, 8 (2015), pp. 6
[48]
S. Olafsdottir, C. Berg, G. Eiben, A. Lanfer, L. Reisch, W. Ahrens, et al.
Young children's screen activities, sweet drink consumption and anthropometry: results from a prospective European study.
Eur J Clin Nutr, 68 (2014), pp. 223-228
[49]
I. Labayen Goñi, L. Arenaza, M. Medrano, N. García, C. Cadenas-Sanchez, F.B. Ortega.
Associations between the adherence to the Mediterranean diet and cardiorespiratory fitness with total and central obesity in preschool children: the PREFIT project.
Eur J Nutr, 57 (2018), pp. 2975-2983
[50]
B. Martinez-Tellez, G. Sanchez-Delgado, C. Cadenas-Sanchez, J. Mora-Gonzalez, M. Martín-Matillas, M. Löf, et al.
Health-related physical fitness is associated with total and central body fat in preschool children aged 3–5 years.
Pediatric Obes, 11 (2016), pp. 468-474
[51]
P. Henriksson, C. Cadenas-Sanchez, M.H. Leppänen, C. Delisle Nyström, F.B. Ortega, J. Pomeroy, et al.
Associations of fat mass and fat-free mass with physical fitness in 4-year-old children: results from the MINISTOP trial.
[52]
P. Henriksson, M.H. Leppänen, H. Henriksson, C. Delisle Nyström, C. Cadenas-Sanchez, A. Ek, et al.
Physical fitness in relation to later body composition in pre-school children.
J Sci Med Sport, 22 (2019), pp. 574-579
[53]
M. Espinoza Montenegro, G. Echeverría Errazuriz.
La dieta mediterranea fuera de España: hábitos alimentarios en Chile, uno de los cinco ecosistemas mediterráneos en el mundo.
Dieta Mediterránea, (2014), pp. 155
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