Early Adiposity Rebond in Moroccan Children: Prevalence and Determinants

 

K Tahiri1, Z Abidli2, J El Turk2, A Amri1, F Elarabi1, Z Hannoun1, A Bour1

1Ibn Tofail University, Faculty of Sciences, Kenitra, Morocco.

2Faculty of Health Sciences, International University of Casablanca, Morocco.

*Corresponding Author E-mail: zakaria.abidli@uit.ac.ma.

 

ABSTRACT:

Background: Childhood obesity is a real public health problem Q, Its incidence is rapidly increasing in developing countries. According to the literature review, early rebound fat is associated with obesity and non-communicable diseases, our objective is therefore to determine the risk factors for early rebound fat in a population of Moroccan children. Material and methods: This retrospective epidemiological study lasted 12 months in 2018. The study involved 200 mother-child couples seen for consultation in an urban health centre at Salé city. Data were collected from a survey on the living conditions of the first 1000 days of life of the children studied and completed by anthropometric measurements, as well as information from mothers and children health books. Results: The average age of the children is 42.3±18.9 months with a sex ratio towards females (46% male versus 54% female). In terms of the internal reliability of the survey, the value of the calculated Cronbach index is acceptable (α = 0.7). We have established that mothers who have practiced artificial breastfeeding or gave birth by cesarean and nursing mothers who took oral contraceptives are of a higher-risk of having a child with an early adiposity rebond compared to other categories, with an odds-ration respectively [Odds-Ratio = 4; IC  95% [2,15-7,45]; P-value = 0,000]; [Odds-Ratio =4. 7; 95% CI [2.46-9.08]; P-value=0.000] and ERA [Odds-Ratio =2.3; 95% CI [1.46-4.34]; P-value=0.000]. Conclusion: Early rebound of adiposity is apredictor of obesity with a whole range of possible cardiovascular and metabolic complications.

 

KEYWORDS: Early, Adiposityre bound, Children, Prevalence, Determinant, Morocco.

 

 


INTRODUCTION:

During the growth period, the body mass index (BMI), which is used as an indication of obesity, follows a trajectory characterized by a rapid increase during the first year of life, then a decrease to reach its nadir around the age of 6 years. Thereafter, BMI increases again throughout childhood, and this second increase is called the rebound in adiposity. It was first reported in 1984 by Rolland-Cachera et al, who found a relationship between the age of fat rebound and final adiposity1. Several studies have identified early rebound of adiposity (ERA) as a predictive marker of obesity later in childhood, adolescence and adulthood2-3. According to the World Health Organization, childhood obesity is one of the most serious public health problems of the 21st century.

 

The problem is global and regularly affects many low- and middle-income countries, particularly in urban areas. Prevalence has increased at an alarming rate.  Globally, in 2016, the number of overweight children under five years of age is estimated at more than 41 million. Nearly half of all overweight children under five lived in Asia and a quarter in Africa4. The rebound in adiposity, which we know is strongly associated with obesity, has recently been the subject of research. The early rebound in adiposity is traditionally known to have a close link with noncommunicable diseases. For this reason, our objective is to determine the risk factors for ERA in a population of Moroccan children.

 

MATERIAL AND METHODS:

This retrospective epidemiological study lasted 12 months in 2018. The study involved 200 mother-child couples seen in consultation in an urban health centre in Sale. Data were collected from a questionnaire on the living conditions of the first 1000 days of life of the children studied and completed by anthropometric measurements, as well as information from the child's health book (birth weight, growth curves, stay in resuscitation, type of lactation, antibiotic therapy, etc) and of the mother (conditions during pregnancy, evolution of weight, etc.). The statistical methodology was based on two axes: descriptive and analytical. In the first part, we calculated the frequencies and characteristics of each variable studied that could give a general idea of the participants. The results were expressed as percentages for the qualitative variables and as a mean± standard deviation for the quantitative variables. 

 

Then, in a second step, we used the Chi-square test (χ˛) to determine whether there is a significant relationship between the variables studied.

 

To determine the internal reliability of our questionnaire, we calculated Cronbach's alpha. An alpha between 0.6 and 0.8 is acceptable for an exploratory study5-6.

 

RESULTS:

This is a sample of 200 mothers and children. The average age of the children is 42.3±18.9 months with a sex ratio in favour of the female sex (46% male versus 54% female). In terms of the internal reliability of the questionnaire, the value of the calculated Cronbach's index is acceptable (α = 0.7).

 

 In light of this result, we can already provide the internal reliability of our questionnaire adapted to the Moroccan context. Concerning fat rebound, we noted that 32% (n=67) of the children had an early fat rebound (ERP) (Figure 1), with a highly significant difference between the two modalities (Chi-square: 21.23; P-value <0.001).

 

 

Figure 1: Distribution of children according to the precocity of adipose rebound. (Chi-square: 21.23; P-value<0.001).

 

In our study, links between sociodemographic, prenatal, postnatal and clinical variables and early fat rebound were established. Regarding the educational level of the mothers, we noted that all university educated mothers have children with normal adipose rebound, while participants with a high school education or less have children with significant early adipose rebound, with an overall R2 determination coefficient of 77%.

 

 

Figure 2: Distribution of fat rebound by maternal education level.

 

We found a significant relationship between fat rebound and monthly household income (Chi-square=5.52; P-value<0.05), 62.2% of participants with a monthly income above 500€ (5500DH) have children with early fat rebound (ERA). Concerning the determinants related to the course of pregnancy, we noted a significant link between the fatty rebound and the number of ANC (P-value<0.05). Indeed, the more the number of pre-natal consultations increases, the more the probability of having a child with ERA decreases (Figure 3).

 

 

Figure 3: Distribution of fat rebound by number of visits.

 

Maternal weight at the beginning of pregnancy and ERA re highly related (P-value<0.05). Similarly, we noted a significant association between maternal diabetes and fat rebound. Indeed, 50% of diabetic mothers had children with ERA. Maternal infections during pregnancy and ERA are also correlated. With regard to obstetrical parameters, we noted that 92% of preterm infants had a fat mass that rebounded early.


 

Figure 4: Distribution of fat rebound according to maternal infections.

 

Table 1 : Risk factors for ERA in children in our population.

Variables

Fatty rebound

Chi-square

P-value

OR

CI95%

Early

Normal

Type of mother's diet

Wrong (Reference)

3

2

1.54

0.221n.s

3

[0.49-18.4]

Healthy

64

131

Type of breast feeding

Artificial (Reference)

44

43

20.15

0.000***

4

[2.15-7.45]

Maternal

23

90

Route of Childbirth

Caesarean (Reference)

50

51

23.46

0.000***

4.7

[2.46-9.08]

Normal

17

82

Birth weight

Hypotrophy (Reference)

8

4

5.28

0.020*

3.9

[1.31-13.48. 34]

Other

64

125

Take the pill

Yes (Reference)

40

51

8.19

0.050*

2.3

[1.31-4. 34]

No

27

82

OR: Odds ratio (OR); CI: confidence interval ;*** Highly significant; n.s: Is not significant

 


In order to highlight the risk factors for early fat rebound in children, we studied the effect of the type of diet, type of breastfeeding, route of delivery and pill intake.

 

According to the table, we have noted that mothers who have practised artificial breastfeeding are 4 times more likely to have a child with ERA [Odds-Ratio =4; 95% CI [2.15-7.45]; P-value=0.000], similarly, mothers who have given birth by caesarean section are 5 times more likely to have a child with ERA [Odds-Ratio =4. 7; 95% CI [2.46-9.08]; P-value=0.000], in fact, we also noted that breastfeeding mothers who took the pill were twice as likely to have a child with ERA [Odds-Ratio =2.3; 95% CI [1.46-4.34]; P-value=0.000]. Concerning children, we noted that hypotrophy accelerates ERA, with a risk of 4 times more likely to have a child with ERA than other categories of ERA [Odds-Ratio =3.9; 95% CI [1.31-13.84]; P-value<0.000].

 

DISCUSSION:

It is now proven that ERA is a predictive factor for the occurrence of obesity in adolescents and young adults7-8.  This obesity is predictive of the occurrence of metabolic diseases, such as type II diabetes whose incidence decreases inversely with age, metabolic syndrome9-10, high blood pressure, dyslipidemia, cardiovascular disease, sleep apnea syndrome and other diseases. It increases the risk of certain cancers, joint diseases such as osteoarthritis10-11. Complications associated, in particular, with diabetes and cardiovascular disease cause the death of at least 2.8 million people worldwide each year12. This is why we proposed to study the different determinants of PAR among the living conditions of the first 1000 days, a precious window of opportunity or very first day for the child and the adult to come, all the more so as to our knowledge there is no similar study in the Arabic-speaking or Moroccan context, according to the great scientific research databases such as: Science direct, Scopus, web of sciences and PubMed. Different factors and mechanisms have been proposed that prove to accelerate the occurrence of EAR during the first thousand days.

 

We found a ERA in 32% of the children studied, which is transposable to the European samples and lower than the results of the Chilean and Japanese studies13-14. We were able to establish a relationship between low household income and ERA. This is in agreement with the results of an American study in North Carolina15, while an English study refuted it16.

 

In addition, low maternal education was found to be a determinant in the occurrence of ERA in our group. The Americans also found the same trend15. With regard to gender, we did not find a significant association with ERA, as in other studies17. We were able to determine a relationship between maternal diabetes during pregnancy and ERA this was demonstrated by Georges et al. Maternal weight at the beginning of pregnancy is highly correlated with PAR. Several studies highlight the power of the link between maternal BMI and ERA18-19-20-21-22. A study by Johannes Hebebrand has shown a link with the BMI of both parents23. This is due to genetic factors in addition to family eating habits23. In our study, we found a relationship between maternal perpartum infections and ERA. In fact, fetal adipose tissue, in addition to adipocytes, contains inflammatory and other cells that react to infections by releasing adipokines that modulate various mechanisms such as inslion sensitivity and appetite24. We have also noted the influence of poor monitoring of fat and ERA, which can be justified by the resulting lack of hygieno-dietary advice on weight and glycemia that is given during prenatal consultations. In our study, children born by caesarean section had an odds-ratio of times more likely to have a ERA. Breastfeeding prevented the children in our sample from having ERA. This is demonstrated by several studies25-27. The mechanism of this protective effect can be explained by the fact that it involves reducing plasma insulin levels, thereby reducing fat storage and preventing the development of excessive early adiposity. In other words, breastfeeding protects children from insulin resistance28. We found a relationship between microprogestin-only pill use in breastfeeding mothers and PAR. This could be justified by the reduction in milk production caused by these pills, forcing mothers to use infant milks.

 

According to the literature review, there are several factors that influence PLAR such as maternal smoking during pregnancy18-19, screening time29, and early protein intake30-31 have been suggested to be related to the timing of fat rebound; however, there is some variation in the findings. Higher protein intake may stimulate the secretion of insulin and insulin-like growth factor-1, both of which accelerate growth and increase fat mass (FM)32.

 

CONCLUSION:

Early rebound of adiposity is a predictor of obesity with all its possible cardiovascular and metabolic complications.  It would be desirable that there are more field studies responding to our Arab, Mediterranean and countries in full nutritional transition context.

 

REFERENCE:

1.      Rolland-Cachera MF, Deheeger M, Bellisle F, Sempé M, Guilloud-Bataille M, Patois E. Adiposity rebound in children: a simple indicator for predicting obesity. Am J ClinNutr. 1984; 39:129-35.

2.      Eriksson JG, Forsén T, Tuomilehto J, Osmond C, Barker DJ. Early adiposity rebound in childhood and risk of type 2 diabetes in adult life. Diabetologia. 2003; 46:190-4.

3.      Williams S, Davie G, Lam F. Predicting BMI in young adults from childhood data using two approaches to modelling adiposity rebound. Int J ObesRelatMetabDisord. 1999; 23:348–54.

4.      World Health Organization. Global Strategy on Diet, Physical Activity and Health. Childhood overweight and obesity. 2017. Consulted January 23, 2020. Available on the: https://www.who.int/dietphysicalactivity/childhood/en/.

5.      Johnson RA, Wichern DW. Applied Multivariate Correspondence Analysis. 6th edition. Prentice-Hall, editors. USA: Upper Saddle River, NJ. 2007.

6.      Yves E, Pras B, Roux E. Market–Etudes et recherches en marketing. 2nded.Dunod, editors. France: Gestion Sup. 2003.

7.      Berenson GS, Srinivasan SR, Bao W, Newman WP, 3rd, Tracy RE, Wattigney WA. Association between multiple cardiovascular risk factors and atherosclerosis in children and young adults. The Bogalusa Heart Study. N Engl J Med. 1998; 338:1650-6.

8.      Raitakari OT, Juonala M, Viikari JS. Obesity in childhood and vascular changes in adulthood: insights into the Cardiovascular Risk in Young Finns Study. Int J Obes (Lond.) 2005; 29(2): S101–4.

9.      Cornier M, Dabelea D, Hernandez TL, Lindstrom R C, Steig AJ, Stob NR, Van Pelt RE, Wang H, Eckel RH. The Metabolic Syndrome. Endocr Rev, 2008; 29(7): 777–822.

10.    Koyama S, Go I, Kojima M, Shimura N, Sairenchi T, Arisaka O. Adiposity Rebound and the Development of Metabolic Syndrome. Pediatrics January, 2014; 133 (1): 114-119.

11.    Girardin JL, Zizi F,  Clark LT, Brown CD,  McFarlane SI. Obstructive Sleep Apnea and Cardiovascular Disease: Role of the Metabolic Syndrome and Its Components. J Clin Sleep Med, 2008; 4(3):261-272.

12.    World Health Organization. Rapport mondial sur le diabčte.2016. Consulted the January 24, 2020. Available on: https://apps.who.int/iris/bitstream/handle/10665/254648/9789242565256-fre.pdf; jsessionid=064D8FA724A548759CB2E1C10466AFBF?sequence=1

13.    González L, Corvalán C, Pereira A, Kain J, Garmendia ML, Uauy R. Early adiposity rebound is associated with metabolic risk in 7-year-old children. Int J Obes, 2014; 38(10):1299-304.

14.    Kato N, Isojima T, Yokoya S, Tanaka T, Ono A, Yokomichi H, Yamagata Z, Tanaka S, Matsubara H, Ishikuro M, Kikuya M, Chida S, Hosoya M, Kuriyama S, Kure S. Earlier BMI rebound and lower pre-rebound BMI as risk of obesity among Japanese preschool children. International Journal of Obesity, 2017; 42:52–58.

15.    Edward H, Sarah A. Marshall, Santiago S, Joseph AS, Cynthia KS, Thomas AA, PhD, Sara A. Determinants of Adiposity Rebound Timing in Children. J Pediatr, 2017; 184(2):151-156.

16.    Dorosty AR1, Emmett PM, CowinSd, Reilly JJ. Factors associated with early adiposity rebound. ALSPAC Study Team. Pediatrics, 2000;105(5):1115-8.

17.    Quandt SA, Trejo G, Suerken CK, Pulgar CA, Ip EH, Arcury TA. Diet quality among preschool-age children of Latino migrant and seasonal farmworkers in the United States. J Immigr Minor Health 2016; 18:50512.

18.    Hughes AR, Sherriff A, Ness AR, Reilly JJ. Timing of adiposity rebound and adiposity in adolescence. Pediatrics. 2014; 134: e1354–61.

19.    Williams SM, Goulding A. Patterns of growth associated with the timing of adiposity rebound. Obesity (Silver Spring) 2009; 17:335–41.

20.    Doi L, Williams AJ, Frank J. How has child growth around adiposity rebound altered in Scotland since 1990 and what are the risk factors for weight gain using the Growing Up in Scotland birth cohort 1? BMC Public Health. 2016; 16:1081.

21.    Toschke AM, von Kries R, Beyerlein A, Rückinger S. Risk factors for childhood obesity: shift of the entire BMI distribution vs. shift of the upper tail only in a cross-sectional study. BMC Public Health. 2008; 8:115.

22.    Ip EH, Marshall SA, Saldana S, Skelton JA, Suerken CK, Arcury TA, et al. Determinants of adiposity rebound timing in children. J Pediatr. 2017; 6(2); 184:151.

23.    Hebebrand J, HinneyA. Environmental and Genetic Risk Factors in Obesity. Child and adolescent psychiatric clinics of North America 18(1):83-94.

24.    Faucher P, Poitouab C. Physiopathology of obesity. Revue du Rhumatisme Monographies,2016, 83(1):6-12

25.    Madsen AL, Schack-Nielsen L, Larnkjaer A, Mřlgaard C, Michaelsen KF. Déterminants de la glycémie et de l'insuline chez des nourrissons danois ŕ terme de 9 mois en bonne santé; la cohorte SKOT. Diabet Med. 2010; 27 : 1350–7.

26.    Ravelli AC, van der Meulen JH, Osmond C, Barker DJ, Bleker OP. Alimentation du nourrisson et tolérance au glucose chez l'adulte, profil lipidique, tension artérielle et obésité. Arch Dis Child. 2000; 82 : 248–52.

27.    Oddy WH. Infant feeding and obesity risk in the child. Breastfeed Rev. 2012; 20:7–12.

28.    Jae Kang M. The adiposity rebound in the 21st century children: meaning for what? Korean J Pediatr. 2018 Dec; 61(12): 375–380.

29.    Dietz WH, Jr, Gortmaker SL. Do we fatten our children at the television set? Obesity and television viewing in children and adolescents. Pediatrics. 1985; 75:807–12.

30.    Rolland-Cachera MF, Deheeger M, Akrout M, Bellisle F. Influence of macronutrients on adiposity development: a follow up study of nutrition and growth from 10 months to 8 years of age. Int J Obes Relat Metab Disord. 1995; 19: 573–8

31.    Scaglioni S, Agostoni C, Notaris RD, Radaelli G, Radice N, Valenti M, et al. Early macronutrient intake and overweight at five years of age. Int J ObesRelatMetabDisord. 2000; 24:777–81.

32.    Karaolis-Danckert N, Buyken AE, Kulig M, Kroke A, Forster J, Kamin W, et al. How pre- and postnatal risk factors modify the effect of rapid weight gain in infancy and early childhood on subsequent fat mass development: results from the Multicenter Allergy Study 90. Am J ClinNutr. 2008; 87:1356–64.

 

 

Received on 12.05.2020           Modified on 15.07.2021

Accepted on 06.12.2021         © RJPT All right reserved

Research J. Pharm. and Tech. 2022; 15(6):2733-2736.

DOI: 10.52711/0974-360X.2022.00457