Next Article in Journal
Dietary Factors Influencing the Intensity of Low-Grade Inflammation in Obesity
Previous Article in Journal
Beyond the Scales: A Qualitative Study on the Biopsychosocial Impacts of Time-Restricted Eating in Free-Living Individuals
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Obesities
Volume 5
Issue 1
10.3390/obesities5010011
obesities-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Trend in the Prevalence of Overweight, Obesity, and Body Fat Distribution in Children and Adolescents in Northwestern Argentina Between 1982 and 2019

by
Delia B. Lomaglio
1,2,* and
Rosario E. Pacheco Agüero
1,2
1
Regional Institute of Sociocultural Studies (IRES), UNCA-CONICET, Catamarca 4700, Argentina
2
Center for Biological Anthropology Studies (CEABi), FACEN-UNCA, Catamarca 4700, Argentina
*
Author to whom correspondence should be addressed.
Obesities 2025, 5(1), 11; https://doi.org/10.3390/obesities5010011
Submission received: 2 January 2025 / Revised: 23 January 2025 / Accepted: 13 February 2025 / Published: 21 February 2025
Browse Figures
Versions Notes

Abstract

:
The aim of this work was to analyze the trend of overweight, obesity, and body fat distribution of children and adolescents in Catamarca, northwest Argentina, in the last four decades. A data series obtained between 1982 and 2019 in the province of Catamarca was analyzed. The sample of 5596 individuals (46.41% female), between 5 and 14 years old, was grouped into four decades: 1980, 1990, 2000, and 2010. The categories of overweight and obesity, based on body mass index (BMI), were defined from the international reference IOTF. The fat distribution was defined according to the subscapular tricipital index (STI). Between 1980 and 2010, BMI increased by 2.35 kg/m2, overweight varied between 13.9% and 21.0%, and obesity varied between 3.4% and 19.2%. The centralized fat distribution varied from 3.9% in 1990 to 27.3% in 2010. In the cohort analysis, and after forty years, an increase in excess weight and body fat centralization was observed in children and adolescents in Catamarca. This trend was inversely proportional to the indicators of unsatisfied basic needs (UBN). It can be concluded that improvements in economic, educational, and housing conditions were not reflected in a better nutritional status.

1. Introduction

Obesity and overweight, characterized by excessive fat accumulation [1], have become widespread and difficult-to-address issues. In recent decades, the rise in overweight and obesity has been associated with the so-called “nutritional transition,” which is itself related to two other transitions: epidemiological and demographic. This transition refers to the replacement of traditional foods with processed and ultra-processed products [2,3]. Such changes suggest a potential determinant of obesity in children and adolescents [4]. However, excess fat is as important as its distribution in the body. This is crucial because numerous studies have established the significance of fat distribution, particularly trunk or centralized fat, in the increased risk of cardiometabolic diseases such as type II diabetes, hypertension, metabolic syndrome, among others [5].
Overweight and obesity conditions can easily be estimated at both individual and population levels using anthropometric indices, among which the most universally accepted, due to its ease of use and low cost, is the body mass index (BMI). BMI relates an individual’s weight to their height. However, this index does not indicate how excess body fat is distributed. Other indirect techniques, such as those using subcutaneous skinfold measurements, can be applied in this regard. Among them, the ratio of the subscapular to triceps skinfolds, known as the subscapular-to-triceps index (STI) [6], provides information about fat accumulation at the trunk or peripheral levels.
The rising trend in overweight and obesity has also been associated, either concomitantly or causally, with socioeconomic conditions, poverty, and other quality-of-life factors such as education level, access to digital media, and increasingly sedentary lifestyles in modern societies. These factors constitute risk elements for non-communicable chronic diseases (NCDs). These conditions can emerge in early stages of development and persist into adulthood, even independently of BMI, a general measure of adiposity that may not reflect excess body fat, a condition known as latent obesity [7]. Such conditions have detrimental health implications, as well as significant healthcare costs. Therefore, it is essential to evaluate the trends in overweight, obesity, and fat distribution prevalence, particularly in childhood and early adolescence, stages during which dietary habits are established [8].
Such associations have been reported globally since the 2000s [9,10], as well as in Latin America in general [11,12] and Argentina in particular [13]. Specifically, Argentina’s northwest (NOA) has historically shown the highest levels of vulnerability in terms of poverty, education, and employment indicators, conditions shared with the northeastern region (NEA). In this context, in 2018, NOA had the highest prevalence of overweight and ranked second among Argentina’s five regions (NOA, NEA, Center, Cuyo, and Patagonia) for obesity prevalence [14]. Additionally, a recent review highlights that Argentine children and adolescents exhibit high overweight and obesity prevalence rates, with increases over the past 20 years [15], alongside significant territorial asymmetries [16].
In Argentina, the unsatisfied basic needs (UBN) method, used in several Latin American countries to measure multidimensional or structural poverty, was first applied in the 1980 national census. This concept is based on minimum well-being thresholds that must be met by fulfilling basic material needs and allows for the description of structural poverty through five essential quality-of-life indicators: BN1: inadequate housing; BN2: lack of sanitation; BN3: overcrowding; BN4: school absenteeism; and BN5: lack of economic sustainability. Households are classified as having UBN if they meet at least one of these indicators [17]. UBN measurement has been conducted periodically in each national census since 1980.
The objective of this study was to evaluate the trends in body mass index, overweight and obesity prevalence, and centralized fat distribution in children and adolescents from the capital of Catamarca Province, northwest Argentina, over a 40-year period, and to analyze the possible association with the percentage of UBN reported in the 1980, 1991, 2001, and 2010 censuses.

2. Materials and Methods

2.1. Study Area and Design

The province of Catamarca is located in northwest Argentina (NOA) and, together with the northeast (NEA), forms the Gran Norte region. It borders Salta to the north, Tucumán and Santiago del Estero to the east, Córdoba to the southeast, La Rioja to the south, and Chile to the west, with the boundary marked by the Andean watershed. Catamarca covers an area of 102,602 km2, with a population of 429,562 inhabitants, accounting for 0.92% of Argentina’s total population. The Capital City, San Fernando del Valle de Catamarca, is located in the southeastern sector of the Capital Department at an average altitude of 519 meters above sea level, covering an area of 399 km2 and housing 186,947 inhabitants [18].
A cross-sectional retrospective study was conducted on children and adolescents aged 5 to 14 years from the Capital City of Catamarca, based on proprietary datasets from 12 series collected between 1982 and 2019. These datasets were generated within the framework of various research projects approved and funded by the Ministry of Health of Catamarca (1982 and 1983 series), the National University of Catamarca (1993, 1995, 2008, 2009, and 2010 series), and the National Agency for Scientific and Technological Promotion (2011, 2012, 2013, 2014, and 2019 series). Anthropometric measurements were obtained for all series. Sampling was non-probabilistic and convenience-based.
Inclusion criteria for children and adolescents included the following: (1) individuals of both sexes; (2) attending public primary and secondary schools in Catamarca’s capital; (3) availability of informed consent from parents or guardians; (4) participants’ own assent and willingness; and (5) attendance at school on the day anthropometric data were collected. Exclusion criteria included the following: (1) manifest diseases potentially affecting results or nutritional status; and (2) being outside the specified age range.
Data collection was conducted in public schools managed by the province of Catamarca. All projects had authorization from the relevant ministerial authorities. Before collecting anthropometric measurements, informed consent from legal guardians and assent from minors were obtained.
From each series, recorded data included weight, height, triceps, and subscapular skinfolds (the latter measured starting in the 1993 series). All measurements were performed by trained personnel using standardized equipment, following the recommendations of the Practical Human Biology [19]. The total sample for this study included 5,596 individuals (46.4% females).

2.2. UBN Indicators

Unsatisfied basic needs (UBN) indicators were obtained from Argentina’s population and housing censuses for 1980, 1991, 2001, and 2010 [20].

2.3. Statistical Processing

Data were digitized into a spreadsheet, grouping the series by decades: 1980s, 1990s, 2000s, and 2010s. Statistical analysis was performed using IBM SPSS version 23.0 for Windows [21].
Body mass index (BMI) was calculated using Quetelet’s equation: weight (kg)/height (m2). The subscapular-to-triceps index (STI) was derived from the ratio of subscapular (mm)/triceps (mm) skinfolds. BMI was categorized according to IOTF international references [22] to determine overweight and obesity prevalence. STI was categorized to estimate trunk (STI > 1) or peripheral (STI ≤ 1) fat distribution. Ages were grouped as follows: children (5–9 years) and adolescents (10–14 years).
The Kolmogorov–Smirnov test was used to verify data normality. Descriptive statistics (mean, 95% CI) were calculated for continuous variables, while prevalences (%, 95% CI) were calculated for discrete variables.
Trends in BMI over decades were analyzed using linear regression, with BMI as the dependent variable and decades, sex, and age group as independent variables. Prevalence trends were assessed using the chi-square test for trend and Cramer’s V test to evaluate effect size or association strength, using the following criteria: ≤0.2 = weak; 0.2–≤0.6 = moderate; >0.6 = strong. All analyses were performed with a 95% confidence level. A p-value of less than 0.05 was considered statistically significant to determine associations.

3. Results

Table 1 shows the sample composition by decade. In each decade, the number of individuals represents approximately 3% of the population aged 5 to 14 years in the capital of Catamarca, according to census data.

3.1. Body Mass Index

The mean BMI with 95% confidence intervals by decade and sex is shown in Table 2.
BMI shows significant differences across decades in both sexes. In the 5-to-9-year-old age group, significant differences were observed in the period 1990–2000 in boys (p = 0.029) and girls (p = 0.003) and in the period 2000–2010 only in boys (p = 0.008). In the 10-to-14-year-old age group, significant differences were observed across all decades in boys: 1980–1990 (p = 0.024), 1990–2000, and 2000–2010 (p = 0.000). In girls, significant differences were observed only in the periods 1980–1990 (p = 0.005) and 1990–2000 (p = 0.004) (Figure 1).
Linear regression analysis suggests that BMI differences are mainly influenced by age (t = 22.875; p = 0.000) and decade (t = 3.228; p = 0.001), while sex has no significant effect (t = 0.766; p = 0.444) (Table 3).

3.2. Overweight, Obesity, and Centralized Fat Distribution

Prevalences by decade, sex, and age group are shown in Table 4. In boys from both age groups, significant positive trends were observed in the prevalence of overweight, obesity, and centralized fat distribution. In girls, significant differences were only observed for obesity and centralized fat distribution in both age groups.
The strongest effect size across decades was observed for centralized fat distribution (Cramér’s V = 0.285), followed by obesity (Cramér’s V = 0.215), indicating a moderate effect in both cases. Overweight, on the other hand, showed a weak effect (Cramér’s V = 0.070), with significant differences in boys (p = 0.000) but not in girls (p = 0.089).
Figure 2 shows the trend in the increase in overweight and obesity from 1980 to 2010. Overweight and obesity appear to slow down in girls starting in the 1990s and 2000s, respectively. In boys, the trend is linear and continuous for both overweight and obesity.
Centralized adiposity was present in both overweight and obese children between 1990 and 2010. Among obese children, it increased from 2% to 51.7%, and among overweight children, it increased from 4.6% to 26.6%.
During the analyzed decades, households with UBN decreased from 28.8% in 1980 to 8.6% in 2010. The decline in UBN indicators was accompanied by an increase in excess weight and centralized fat distribution.

4. Discussion

This study estimated the prevalence of overweight, general obesity, and central obesity in schoolchildren aged 5 to 14 years from the capital of Catamarca, northwestern Argentina, between 1982 and 2019.
High percentages of obesity and centralized fat distribution were observed, with a positive trend of increases over the 40-year period. Obesity quadrupled in younger boys and increased sixfold in those older than 10 years. In girls, the increase ranged between five- and eightfold. Fat distribution increased by more than tenfold in boys and girls aged 5 to 9 years and approximately fivefold in the older group. Overweight also increased, although to a lesser extent, and changes in girls were not significant.
In the 1970s, the nutritional paradigm in Argentina focused on protein energy malnutrition and nutrient deficiencies, with overweight and obesity considered minor issues compared to complications related to undernutrition [23]. By the 1990s and early 2000s, the coexistence of conditions of deficit and excess—or “double burden of malnutrition”—emerged. As with other regions of Latin America and the world, excess weight in particular has become an increasingly common problem over the past decades [24,25,26].
Since then, trends in increasing overweight and obesity have, in recent years, been reported in global studies [9], in Latin America [11], as well as in European countries [27], Korea [28], the United States [29], and China [30], among others.
Data from the latest National Survey of Nutrition and Health, conducted in Argentina in 2019 [13], indicated that overweight and obesity are the most prevalent forms of malnutrition among children and adolescents. In individuals aged 5 to 17 years, excess weight reached a prevalence of 41.1% (20.7% overweight, 20.4% obesity), with regional differences. Moreover, these prevalences did not show statistically significant differences by sex, education level, healthcare coverage, or income quintiles. These results align with those obtained in our study for the last decade’s series (2010). The survey data also highlighted socioeconomic inequalities across Argentina and disparities in the prevalence of overweight and obesity.
Such regional differences were previously noted in the study by Kovalsky et al. [31] and later in the multicenter study by Oyhenart et al. [32], which analyzed schoolchildren from six Argentine provinces and identified a north–south clinal distribution of overweight and obesity, with the highest prevalence in Patagonia and the lowest in the NOA and NEA regions. These differences were linked to the varying social and health conditions of each province. Despite territorial differences, increases in overweight and obesity have been reported in several provinces with distinct environmental, socioeconomic, and cultural characteristics.
For instance, studies have documented increases in overweight and obesity in Corrientes [33], Buenos Aires [25], and Tucumán [34], among other provinces. Centralized adiposity has also increased in provinces like La Pampa [35].
The growing prevalence of overweight and obesity is evidently multifactorial. Among the main causes are changes in eating habits and lifestyle [36]. In Argentina, this trend has been observed in various cities and periods, as noted in studies comparing cohorts from Buenos Aires [37], Jujuy [38], La Pampa [39], and Puerto Madryn [40].
Our findings align with those of other authors, showing a nonlinear trend with an apparent deceleration in overweight and obesity among girls from the 1990s onward. In boys, however, both overweight and obesity exhibit a linear positive trend across all analyzed periods. Centralized adiposity, meanwhile, was higher in girls, with a linear trend in both sexes between 1990 and 2010.
The inverse relationship between UBN (unsatisfied basic needs) indicators and BMI indicates that as UBN decreases, BMI increases, along with the prevalence of overweight, obesity, and centralized fat distribution. In areas with high UBN, obesity was less prevalent. These observations were previously described in the NOA region for children under 5 years old during the first National Survey of Nutrition and Health [41].
Although the relationship between excess weight and socioeconomic status has been widely documented, no clear linear correlation has yet been established, as is the case with undernutrition. One could speculate that with lower structural poverty, both excess weight and central fat accumulation should decrease. However, the inverse relationship might be explained by economic constraints limiting access to, or choice of, an adequate, balanced diet, negatively impacting nutritional status. Conversely, better socioeconomic conditions (low UBN) might be associated with consumption patterns of foods high in fats and sugars. Additionally, it could be explained in the context of temporary poverty, for example, those related to natural disasters or socioeconomic crises, which lead to a decrease in or loss of purchasing power for the family breadwinner and unemployment. In these situations, families opt for more affordable foods, even if they have low nutritional quality [42].
This problem may be exacerbated by the lack of effective nutritional education, exposure to the marketing of ultra-processed foods, obesogenic environments, and the reduction of physical activity, increasingly replaced by excessive use of smartphones and computers, fostering sedentary habits. Unfortunately, the measures taken at the national and provincial levels are relatively recent and have been limited to isolated initiatives, rather than forming widespread policies. In this context, schools, as strategic spaces for the implementation of public policies, play a key role in addressing these challenges. In Catamarca, notable initiatives include the implementation of “healthy kiosks” in 2018, the introduction of nutritional education in 2022, and the launch of a digital nutrition education project aimed at adolescents in 2024, promoting interactive and accessible learning. These initiatives highlight the need for integrated efforts that combine curricular content, teacher training, and community participation to promote healthy habits and counter sedentary lifestyles. Sustained and well-implemented policies like these have great potential to generate lasting changes in nutritional education and foster healthier behaviors among children and adolescents.

Strengths and Limitations

This study’s strength lies in its inclusion of a broad sample of children and adolescents from a period before the obesity pandemic, enabling the evaluation of trends over four decades. However, it has significant limitations, including the absence of sufficient data to analyze the evolution of central adiposity between 1980 and 1990, as well as the lack of information on dietary habits and physical activity levels—key factors for a deeper interpretation of the results.

5. Conclusions

The children and adolescents analyzed in this study exhibited increased BMI values, along with a rise in the prevalence of malnutrition due to excess weight (overweight and obesity) and trunk fat accumulation. These trends were inversely associated with the unmet basic needs (UBN) indicator.
These findings suggest that improvements in multifactorial poverty conditions over the past four decades did not translate into better health outcomes related to excess weight. These results highlight the urgent need for public policies aimed at raising awareness of the risks of overweight and central adiposity while promoting healthy habits from an early age. Long-term policies that integrate nutrition education, school-based interventions, and community participation could play a crucial role in tackling childhood and adolescent obesity, ultimately improving health outcomes in the population.

Author Contributions

Conceptualization: D.B.L. and R.E.P.A.; methodology: D.B.L. and R.E.P.A.; validation: R.E.P.A. and D.B.L.; formal analysis: D.B.L. and R.E.P.A.; investigation: D.B.L.; resources: D.B.L. and R.E.P.A.; data curation: D.B.L.; writing—original draft preparation: D.B.L. and R.E.P.A.; writing—review and editing: D.B.L. and R.E.P.A.; visualization: D.B.L. and R.E.P.A.; supervision: D.B.L.; project administration: D.B.L.; funding acquisition: D.B.L. All authors have read and agreed to the published version of the manuscript.

Funding

This study was conducted within the framework of the research project approved and funded by the Universidad Nacional de Catamarca (UNCA); project code: 02/P232.

Institutional Review Board Statement

The approval of an ethics committee does not apply, as this study utilized existing databases and no new measurements were taken on human subjects.

Informed Consent Statement

Not applicable, since existing databases were used.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Acknowledgments

The authors would like to thank the Center for Biological Anthropology Studies of the Faculty of Exact and Natural Sciences of the National University of Catamarca for providing access to the anthropometric data series.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. WHO Obesity and Overweight [Internet]. 2024. Available online: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight (accessed on 20 December 2024).
  2. Popkin, B.M. The Nutrition Transition in Low-Income Countries: An Emerging Crisis. Nutr. Rev. 1994, 52, 285–298. [Google Scholar] [CrossRef] [PubMed]
  3. Laurentin, A.; Schnell, M.; Tovar, J.; Domínguez, Z.; Pérez, B.; López de Blanco, M. Transición alimentaria y nutricional: Entre la desnutrición y la obesidad. In Anales Venezolanos de Nutrición; Fundación Bengoa: Miranda, Venezuela, 2007; pp. 47–52. [Google Scholar]
  4. Neri, D.; Steele, E.M.; Khandpur, N.; Cediel, G.; Zapata, M.E.; Rauber, F.; Marrón-Ponce, J.A.; Machado, P.; da Costa Louzada, M.L.; Andrade, G.C.; et al. Ultraprocessed food consumption and dietary nutrient profiles associated with obesity: A multicountry study of children and adolescents. Obes. Rev. 2022, 23 (Suppl. S1), e13387. [Google Scholar] [CrossRef]
  5. Bose, K. Age Trends in Adiposity and Central Body Fat Distribution Among Adult White Men Resident in Peterborough, East Anglia, England. Coll. Antropol. 2002, 26, 179–186. [Google Scholar]
  6. Tanner, J.M.; Whitehouse, R.H. Revised standards for triceps and subscapular skinfolds in British children. Arch. Dis. Child. 1975, 50, 142–145. [Google Scholar] [CrossRef] [PubMed]
  7. Vážná, A.; Novák, J.M.; Daniš, R.; Sedlak, P. Adiposity and body fat distribution based on skinfold thicknesses and body circumferences in Czech preschool children, secular changes. PeerJ 2024, 12, e18695. [Google Scholar] [CrossRef] [PubMed]
  8. UNICEF La Nutrición en la Infancia Media y la Adolescencia. Prevención de la Malnutrición en Niños, Niñas y Adolescentes en Edad Escolar. [Internet]. 2023. Available online: https://www.unicef.org/es/nutricion-infancia-media-adolescencia (accessed on 19 December 2024).
  9. Wang, Y.; Lobstein, T. Worldwide trends in childhood overweight and obesity. Int. J. Pediatr. Obes. 2006, 1, 11–25. [Google Scholar] [CrossRef] [PubMed]
  10. NCD Risk Factor Collaboration (NCD-RisC). Worlwide trends in body mass index, underweight, overweight and obesity from 1975 to 2016: A pooled analysis of 2416 populationhased measurement studies in 128-9 million children, adolescents and adults. Lancet 2017, 390, 2627–2642. [Google Scholar] [CrossRef]
  11. Filozof, C.; González, C.; Sereday, M.; Mazza, C.; Braguinsky, J. Obesity prevalence and trends in Latin-American countries. Obes. Rev. 2008, 2, 99–106. [Google Scholar] [CrossRef] [PubMed]
  12. Corvalán, C.; Garmendia, M.L.; Jones-Smith, J.; Lutter, C.K.; Miranda, J.J.; Pedraza, L.S.; Popkin, B.M.; Ramirez-Zea, M.; Salvo, D.; Stein, A.D. Nutrition status of children in Latin America. Obes. Rev. 2017, 18, 7–18. [Google Scholar] [CrossRef]
  13. 2° Encuesta Nacional de Nutrición y Salud [Internet]. 2019. Available online: https://fagran.org.ar/wp-content/uploads/2020/01/Encuesta-nacional-de-nutricion-y-salud.pdf (accessed on 29 November 2024).
  14. Ministerio de Salud de la Nación. Análisis de Situación de Salud: República Argentina, 1st ed.; Ministerio de Salud de la Nación: Ciudad autónoma de Buenos Aires, Argentina, 2018. [Google Scholar]
  15. Lomaglio, D.B.; Pacheco Agüero, R.E. Effects of the nutrition transition in Argentinean children and adolescents: A narrative review of overweight and obesity prevalence between 2000 and 2021. J. Public Health Emerg. 2022, 6, 1–14. [Google Scholar] [CrossRef]
  16. Rovirosa, A.; Zapata, M. La alimentación en Argentina. In Una Mirada Desde Distintas Aprroximaciones, 1st ed.; CESNI: Ciudad autónoma de Buenos Aires, Argentina, 2021. [Google Scholar]
  17. Ministerio de Economía y Finanzas Públicas de la Nación. Necesidades Básicas Insatisfechas (NBI). Información Censal del año 2010. [Internet]. Available online: https://www.economia.gob.ar/dnap/economica/13.Informes_tematicos/NBIAmpliado_ene2014.pdf (accessed on 30 December 2014).
  18. INDEC Censo Nacional de Población. Hogares y Viviendas 2022: Resultados Provisionales; Instituto Nacional de Estadística y Censos: Loja, Ecuador, 2023. [Google Scholar]
  19. Weiner, J.; Lourie, J. Practical Human Biology; Academic Press: London, UK, 1981. [Google Scholar]
  20. Instituto Nacional de Estadística y Censos. Censo 2010 [Internet]. Available online: https://www.indec.gob.ar/indec (accessed on 25 May 2022).
  21. Nie, N.; Bent, D.; Hull, C. SPSS: Statistical Package for the Social Sciences; McGraw-Hill: New York, NY, USA, 1970. [Google Scholar]
  22. Cole, T.J.; Bellizzi, M.C.; Flegal, K.M.; Dietz, W.H. Establishing a standard definition for child overweight and obesity worldwide: International survey. Br. Med. J. 2000, 320, 1240. [Google Scholar] [CrossRef]
  23. Lomaglio, D. Transición nutricional y el impacto sobre el crecimiento y la composición corporal en el noroeste argentino (NOA). Nutr. Clín. Diet. Hosp. 2012, 32, 30–35. [Google Scholar]
  24. Cesani, M.F.; Luis, M.A.; Torres, M.F.; Castro, L.E.; Quintero, F.A.; Luna, M.E.; Bergel, M.L.; Oyhenart, E.E. Sobrepeso y obesidad en escolares de Brandsen en relación a las condiciones socioambientales de residencia. Arch. Argent. Pediatr. 2010, 108, 294–302. [Google Scholar]
  25. Szer, G.; Kovalskys, I.; De Gregorio, J. Prevalencia de sobrepeso, obesidad y su relación con hipertensión arterial y centralización del tejido adiposo en escolares. Arch. Argent. Pediatr. 2010, 108, 492–498. [Google Scholar]
  26. Padilla, I.S. Prevalencia de sobrepeso-obesidad y factores asociados con valor predictivo-preventivo en escolares de 6 a 11 años de Río Gallegos, Santa Cruz, Argentina. Salud Colect. 2011, 7, 377–388. [Google Scholar] [CrossRef]
  27. Buoncristiano, M.; Spinelli, A.; Williams, J.; Nardone, P.; Rito, A.I.; García-Solano, M.; Grøholt, E.K.; Gutiérrez-González, E.; Klepp, K.I.; Starc, G.; et al. Childhood overweight and obesity in Europe: Changes from 2007 to 2017. Obes. Rev. 2021, 22, e13226. [Google Scholar] [CrossRef]
  28. Kim, J.H.; Moon, J.S. Secular Trends in Pediatric Overweight and Obesity in Korea. J. Obes. Metab. Syndr. 2020, 29, 12–17. [Google Scholar] [CrossRef] [PubMed]
  29. Hu, K.; Staiano, A.E. Trends in Obesity Prevalence Among Children and Adolescents Aged 2 to 19 Years in the US From 2011 to 2020. JAMA Pediatr. 2022, 176, 1037–1039. [Google Scholar] [CrossRef] [PubMed]
  30. Dong, Y.H.; Chen, L.; Liu, J.Y.; Ma, T.; Zhang, Y.; Chen, M.M.; Zhong, P.L.; Shi, D.; Hu, P.J.; Li, J.; et al. Epidemiology and prediction of overweight and obesity among children and adolescents aged 7–18 years in China from 1985 to 2019. Chin. J. Prev. Med. 2023, 57, 11–19. [Google Scholar]
  31. Kovalskys, I.; Bay, L.; Rausch Herscovici, C.; Berner, E. Prevalencia de obesidad en una población de 10 a 19 años en la consulta pediátrica. Arch. Argent. Pediatr. 2003, 101, 441–447. [Google Scholar] [CrossRef]
  32. Oyhenart, E.E.; Dahinten, S.L.; Alba, J.; Alfaro Gómez, E.L.; Bejarano, I.; Cabrera, G.; Cesani Rossi, M.F.; Dipierri, J.E.; Forte, L.M.; Lomaglio, D.B.; et al. Estado nutricional infantojuvenil en seis provincias de Argentina: Variación regional. Rev. Argent. Antropol. Biol. 2008, 10, 1–62. [Google Scholar]
  33. Martínez, C.A.; Ibáñez, J.O.; Paterno, C.A.; Semenza, M.; Heitz, M.; Kriskovich, J. Sobrepeso y obesidad en niños y adolescentes de la Ciudad de Corrientes. Asociación con factores de riesgo cardiovascular. Medicina 2001, 61, 308–314. [Google Scholar] [PubMed]
  34. Cesani, M.F.; Garraza, M.; Zonta, M.L.; Torres, M.F.; Navazo, B.; Bergel Sanchís, M.L.; Luna, M.E.; Gauna, M.E.; Quintero, F.A. Changes in the prevalence of undernutrition, overweight and obesity in children and adolescents from Buenos Aires, Mendoza, and Misiones provinces (Argentina) over the last two decades. Am. J. Hum. Biol. 2022, 34, e23755. [Google Scholar] [CrossRef] [PubMed]
  35. Catalani, F.; Fraire, J.; Pérez, N.; Mazzola, M.; Martínez, A.M.; Mayer, M.A. Prevalencia de bajo peso, sobrepeso y obesidad en adolescentes escolarizados de la provincia de La Pampa. Arch. Argent. Pediatría 2016, 114, 154–158. [Google Scholar]
  36. Rivera, J.Á.; Cossío, T.G.; Pedraza, L.S.; Aburto, T.C.; Sánchez, T.G.; Martorell, R. Childhood and adolescent overweight and obesity in Latin America: A systematic review. Lancet Diabetes Endocrinol. 2014, 2, 321–332. [Google Scholar] [CrossRef] [PubMed]
  37. Guimarey, L.M.; Castro, L.E.; Torres, M.F.; Cesani Rossi, M.F.; Luis, M.A.; Quintero, F.A.; Oyhenart, E.E. Secular changes in body size and body composition in schoolchildren from La Plata City (Argentina). Anthropol. Anz. 2014, 71, 287–301. [Google Scholar] [CrossRef] [PubMed]
  38. Bustamante, M.J.; Alfaro, E.L.; Dipierri, J.E.; Román, M.D. Excess weight and thinness over two decades (1996–2015) and spatial distribution in children from Jujuy, Argentina. BMC Public Health 2021, 21, 196. [Google Scholar] [CrossRef]
  39. Orden, A.B.; Apezteguia, M.C.; Mayer, M.A. Aceleración y estabilización: Disparidad en la tendencia de obesidad en escolares de la provincia de La Pampa (Argentina) entre 1990 y 2016. Rev. Argent. Antropol. Biol. 2021, 23, 7–8. [Google Scholar] [CrossRef]
  40. Navazo, B.; Dahinten, S.L.; Oyhenart, E.E. Malnutrición y pobreza estructural. Comparación de dos cohortes de escolares de Puerto Madryn, Argentina. Rev. Salud Pública 2018, 20, 60–66. [Google Scholar] [CrossRef]
  41. ENNyS Encuesta Nacional de Nutrición y Salud. Documento de resultados [Internet]. Ministerio de Salud, Presidencia de la Nación, Argentina; 2007. Available online: https://cesni-biblioteca.org/ennys2/ (accessed on 29 November 2024).
  42. Aguirre, P. Aspectos socioantropológicos de la obesidad en la pobreza. In La Obesidad en la Pobreza: Un Nuevo reto Para la Salud Pública; OPS Publicación científica nº 576 OPS: Washington, DC, USA, 2000; pp. 13–25. [Google Scholar]
Obesities 05 00011 g001
Figure 1. Mean BMI by sex and age group.
Figure 1. Mean BMI by sex and age group.
Obesities 05 00011 g001
Obesities 05 00011 g002
Figure 2. Trend of overweight and obesity by sex.
Figure 2. Trend of overweight and obesity by sex.
Obesities 05 00011 g002
Table 1. Sample composition.
Table 1. Sample composition.
DecadesBoysGirlsTotal
n (%)n (%)n (%)
1980676 (49.9)679 (50.1)1355 (100)
19901045 (58.2)752 (41.8)1797 (100)
2000690 (60.1)458 (39.9)1148 (100)
2010588 (45.4)708 (54.6)1296 (100)
Total2999 (53.6)2597 (46.4)5596 (100)
Table 2. Mean (95% CI) BMI by sex.
Table 2. Mean (95% CI) BMI by sex.
DecadesBoysGirlsp-Value
Mean95% CISEMean95% CISE
198016.7016.54–16.850.07816.7216.54–16.890.0880.875
199017.0916.93–17.250.08117.2217.00–17.450.1140.318
200018.2317.96–18.500.13617.8317.50–18.160.1670.062
201019.1518.78–19.510.18318.9818.64–19.320.1730.306
Table 3. BMI regression analysis.
Table 3. BMI regression analysis.
Coefficients a
Non–StandardizedStandardizedtSig.
BTypical Errorβ
(Constant)13.9620.954 14.6240.000
sex0.0700.0920.0100.7660.444
age group2.2670.0990.33022.8750.000
decades0.6160.1910.1763.2280.001
a. Dependent variable: BMI.
Table 4. Prevalence (% 95 CI) of overweight, obesity, and centralized fat distribution (Chi square trend).
Table 4. Prevalence (% 95 CI) of overweight, obesity, and centralized fat distribution (Chi square trend).
No. of ParticipantsOverweightp-ValueObesityp-ValueCentralized Fat Distributionp-Value
BoysPrevalence (95%CI)Prevalence (95%CI)Prevalence (95%CI)
Age 5–9
198041716..5 (12.9–20.1)0.0234.3 (2.3–6.2)0.000
199054913.4 (10.6–16.3)6.9 (4.7–9.0)2.0 (0.0–3.0)0.000
200030618.6 (14.2–23.0)17.3 (13.0–21.5)5.0 (1.0–9.0)
201031521.5 (17.0–26.1)16.8 (12.6–20.9)25.0 (16.0–33.0)
Age10–14
19802598.4 (5.0–11.9)0.0004.2 (1.7–6.7)0.000
199049616.9 (13.6–20.25.6 (3.6–7.6)6.0 (3.0–8.0)0.000
200038420.5 (16.5–24.6)14.3 (10.8–17.8)26.0 (19.0–33.0)
201027324.5 (19.4–29.6)28.5 (23.1–33.9)28.0 (20.0–37.0)
Girls
Age 5–9
198043713.9 (10.7–17.2)0.0901.8 (0.5–3.0)0.000
199041412.8 (9.5–16.0)4.1 (2.1–6.0)2.0 (0.0–3.0)0.000
200029617.9 (13.5–22.3)13.8 (9.8–17.8)10.0 (5.0–15.0)
201035217.0 (13.1–20.9)15.3 (11.5–19.1)24.0 (15.0–33.0)
Age 10–14
198024214.8 (10.3–19.3)0.1723.7 (1.3–6.1)0.000
199033821.3 (16.9–25.6)4.1 (2.0–6.2)6.0 (3.0–9.0)0.000
200016212.9 (7.7–18.1)12.9 (7.7–18.1)24.0 (17.0–31.0)
201035621.6 (17.3–25.9)17.9 (13.9–21.9)30.0 (26.0–36.0)
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Lomaglio, D.B.; Agüero, R.E.P. Trend in the Prevalence of Overweight, Obesity, and Body Fat Distribution in Children and Adolescents in Northwestern Argentina Between 1982 and 2019. Obesities 2025, 5, 11. https://doi.org/10.3390/obesities5010011

AMA Style

Lomaglio DB, Agüero REP. Trend in the Prevalence of Overweight, Obesity, and Body Fat Distribution in Children and Adolescents in Northwestern Argentina Between 1982 and 2019. Obesities. 2025; 5(1):11. https://doi.org/10.3390/obesities5010011

Chicago/Turabian Style

Lomaglio, Delia B., and Rosario E. Pacheco Agüero. 2025. "Trend in the Prevalence of Overweight, Obesity, and Body Fat Distribution in Children and Adolescents in Northwestern Argentina Between 1982 and 2019" Obesities 5, no. 1: 11. https://doi.org/10.3390/obesities5010011

APA Style

Lomaglio, D. B., & Agüero, R. E. P. (2025). Trend in the Prevalence of Overweight, Obesity, and Body Fat Distribution in Children and Adolescents in Northwestern Argentina Between 1982 and 2019. Obesities, 5(1), 11. https://doi.org/10.3390/obesities5010011

Article Metrics

Back to TopTop