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Evaluation of being overweight/obese and related sociodemographic factors in 0-5 year age group in Turkey: Turkey Demographic Health Survey 2013 advanced analysis

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Background/aim: To determine risk factors of overweightness/obesity in children aged 0-5 years in the Turkish population. Materials and methods: We made advanced analysis using the Turkey Demographic Health Survey (TDHS) 2013 female database, in which data from children aged under five years and their mothers are included. Analyses were performed using weight for height index data. The children were divided into two groups by age as 0–23 months and 24–59 months. Results: The analysis comprised 2196 children aged under 5 years. Several factors were associated with an increase in overweightness/ obesity of children aged under 5 years. Overweight/obesity in children aged 0-23 months was associated with several factors such as age (12–23 months) (OR: 2.89 CI: 1.62-5.13), high birth weight (OR: 2.36 CI: 1.26-4.44), maternal obesity (OR: 2.09 CI: 1.33-3.27), and maternal smoking (OR: 2.07, CI: 1.28-3.33). Overweightness/obesity in children aged 24–59 months was associated with several factors such as education level of the mother (OR: 2.27, CI: 1.08-4.75), consanguineous marriage (OR: 2.86, CI: 1.83-4.47), and which region of Turkey the family lives in (OR: 2.79, CI: 1.53-5.08). Conclusion: Our results from the TDHS 2013 showed several risk factors of children overweight/obesity. Determining obesity risk factors, monitoring obese children/adults, and providing a multidisciplinary approach to the treatment and prevention of obesity will be useful for the future.
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879
http://journals.tubitak.gov.tr/medical/
Turkish Journal of Medical Sciences
Turk J Med Sci
(2019) 49: 879-887
© TÜBİTAK
doi:10.3906/sag-1808-3
Evaluation of being overweight/obese and related sociodemographic factors in 0-5 year
age group in Turkey: Turkey Demographic Health Survey 2013 advanced analysis
Asiye UĞRAŞ DİKMEN1,2,*, Hande KONŞUK ÜNLÜ2, Lütye Hilal ÖZCEBE2
1Public Health Department, Gazi University Medicine Faculty, Ankara, Turkey
2Public Health Department, Hacettepe University Medicine Faculty, Ankara, Turkey
* Correspondence: asiyeud@gmail.com
1. Introduction
Obesity is a medical condition dened by the World
Health Organization (WHO) as abnormal or excessive fat
accumulation that presents a risk to health (1). In 2006, the
WHO started to use weigth for height index and weight
for age index values in the classication of overweightness
and obesity according to growth standards for the 0 to 59
months age group. According to these growth standards,
overweight is dened as over 2 standard deviations or over
the 97th percentile value, and obesity is dened as above 3
standard deviations or the 99th percentile value (2,3).
Childhood overweightness/obesity is one of the most
severe public health problems of the 21st century. e
prevalence of overweightness/obesity in childhood has
increased steadily to alarming levels, and an epidemic
approach has begun to be used. is epidemic, described
in the childhood age group, concerns the entire world.
It is known that 42 million children worldwide under
the age of 5 years in 2010 were overweight and obese
(4). It is estimated that in 2025, a total of 70 million
children aged under 5 years will be aected if the trend of
increasing overweightness/obesity continues in children
(5). Overweight/obese children are also more likely to
become overweight/obese during adulthood. In children
with this risk, noncommunicable diseases, particularly
diabetes mellitus and cardiovascular diseases, increased
psychosocial health problems, increased risk of middle-
aged deaths, and lower success rates in education and
workplaces were observed (6).
Overweightness and obesity in children are also
important problems for the Turkish population. Despite
this, there has been limited research to reveal the factors
associated with the incidence of overweightness/obesity in
Turkey. e Turkey Demographic Health Survey (TDHS)
is one of the critical studies that showed overweightness/
underweightness in children aged under ve years in
2013, and the percentage over the 2 standard deviations
according to height in the 0–5 years age group was 10.9%
Background/aim: To determine risk factors of overweightness/obesity in children aged 0-5 years in the Turkish population.
Materials and methods: We made advanced analysis using the Turkey Demographic Health Survey (TDHS) 2013 female database, in
which data from children aged under ve years and their mothers are included. Analyses were performed using weight for height index
data. e children were divided into two groups by age as 0–23 months and 24–59 months.
Results: e analysis comprised 2196 children aged under 5 years. Several factors were associated with an increase in overweightness/
obesity of children aged under 5 years. Overweight/obesity in children aged 0-23 months was associated with several factors such as
age (12–23 months) (OR: 2.89 CI: 1.62-5.13), high birth weight (OR: 2.36 CI: 1.26-4.44), maternal obesity (OR: 2.09 CI: 1.33-3.27), and
maternal smoking (OR: 2.07, CI: 1.28-3.33). Overweightness/obesity in children aged 24–59 months was associated with several factors
such as education level of the mother (OR: 2.27, CI: 1.08-4.75), consanguineous marriage (OR: 2.86, CI: 1.83-4.47), and which region
of Turkey the family lives in (OR: 2.79, CI: 1.53-5.08).
Conclusion: Our results from the TDHS 2013 showed several risk factors of children overweight/obesity. Determining obesity risk
factors, monitoring obese children/adults, and providing a multidisciplinary approach to the treatment and prevention of obesity will
be useful for the future.
Key words: Childhood obesity, pediatric obesity, overweight, Turkey
Received: 01.08.2018 Accepted/Published Online: 13.04.2019 Final Version: 18.06.2019
Research Article
is work is licensed under a Creative Commons Attribution 4.0 International License.
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UĞRAŞ DİKMEN et al. / Turk J Med Sci
(3). In a study conducted in Turkey in 2014, 8.5% of
children aged between 0–5 years were reported as obese,
and 17.9% were considered overweight (7).
Many factors cause overweightness and obesity
problems in children. In dierent studies, it was found
that factors such as sedentary lifestyle, high birth weight,
obesity history in the family (overweight mother), smoking
around the children, low or high-income level, low or high
education level, and inadequate breastfeeding were eective
in overweightness/obesity (8). In the childhood age group,
especially in children aged younger than 12 years, drug
treatment is not recommended for overweightness and
obesity treatment, and surgical procedures are considered
as a last resort in unresolved cases. erefore, it is necessary
to take preventive measures by determining the related
risk factors in the rst four years of life, which is the basis
for ghting childhood obesity (9,10).
Childhood obesity is a serious problem because of its
high frequency, its impact on many aspects of the adult
population. However, it’s a preventable health problem
with short and long-term interventions. When taking
into consideration the rising rate of the childhood obesity
in the world, it is thought that countrywide research is
regional and does not adequately reect risk factors in
a country as a whole. In TDHS 2013, overweightness/
obesity data were presented for the rst time in children.
e identication of the risk factors will guide both the
prevention of obesity and similar studies because there are
dierences in risk factors among societies. e purpose of
this study was to assess overweightness/obesity in the 0-5
years (0-59 months) age group and related factors based
on the TDHS 2013 data.
2. Materials and methods
is study is a secondary data analysis of the 2013 database
of the TDHS, which is conducted every ve years by
Hacettepe University Institute of Population Studies (3).
e TDHS 2013 database, which is open to general use,
was obtained from the Hacettepe University Institute of
Population Studies. Data from children aged under ve
years were included in the TDHS 2013. e database of
women was also evaluated within the scope of the study.
Mothers of children aged 0 to 59 months were selected
from the TDHS womens database. As the analysis was
done through the womens database, younger children
aged 0–59 months of women with more than one child
were included in the study and the nal analysis was
performed with 2196 children.
Analyses were performed using weight for height
index data. According to the recommendation of the
WHO (3), children with +2 standard deviations were
considered overweight/obese. e overweight/obese data
in the database are presented as Z-scores; values over
+200 correspond to +2 standard deviations. Obesity of
the mother was considered as BMI ≥ 30 kg/m2 (3). In the
analysis of the risk factors from the TDHS 2013 female
database, data related with only children under the age
of ve years and women’s data related to overweightness/
obesity in children (e.g., household income level, parental
education status, type of residence, mother tongue) were
used. Figure shows the ow diagram of the study.
2.1. Statistical analysis
Statistical analysis was performed using the “Complex
Samples” module in IBM SPSS version 23.0 (IBM Corp,
Armonk, NY, USA) because a weighted, multi-stage,
stratied cluster sampling approach was used in the
TDHS-2013 study. e children were divided into two
groups by age as 0–23 months and 24–59 months. All
analyses were performed for each age group. For the study
sample characteristics, categorical variables are reported
as frequencies and weighted percentages. Chi-square
tests were conducted to examine dierences between
obesity status of child and other categorical variables. If
the result of the Chi-square test was found as statistically
signicant, standardized residual values were examined to
determine which variables caused the dierences. In each
child age group, binary logistic regression was constructed
to identify the relationship between child overweight/
obesity status and the following explanatory variables:
sex of child, age group of child, size of child at birth,
still breastfeeding, obesity status of mother, education
level of mother, education level of father, smoking status
of mother, parents related, level of income, region, and
type of residence.” In the backward model, variables were
included as independent variables if they were signicant
between 0.05–0.20 level or were found as signicant
according to Chi-square test. While performing multiple
logistic regression, the listwise deletion method was used
to handle missing observations. P value below 0.05 was
accepted as signicant.
3. Results
Sociodemographic features (age, sex) and nutrition-related
features (birth weight, birth order, and breastfeeding-
related characteristics) of overweight/obese children
are presented in Table 1. e frequency of obesity in
children aged 12–23 months and then 6–11 months
were signicantly higher than in other ages (P < 0.001).
e frequency of obesity was found to be signicantly
higher in children who were above average birth weight
(P = 0.003) among those aged 0 to 23 months. e same
relationship was found statistically signicant in the 24–59
months age group (P = 0.033). ere was no relationship
among birth order, the status of being breastfed aer
delivery, giving sugary water, giving formula, giving milk
other than breast milk, and bottle-feeding and obesity. e
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UĞRAŞ DİKMEN et al. / Turk J Med Sci
frequency of obesity was found to be signicantly lower in
children who were still being breastfed among those aged
0 to 23 months.
e descriptive characteristics of parents of obese
children are shown in Table 2. In the 0–23 months age
group, there was no relationship between maternal age,
parental consanguinity, mother tongue, and obesity. In
children aged 24 to 59 months, obesity was found to be
higher only in consanguineous marriages; there was no
dierence in terms of other parental features. In contrast,
in children aged 0–23 months, obesity was associated with
many parental characteristics. Higher educational level of
the mother, maternal smoking, and the mother’s obesity
were associated with obesity of children. In addition, a
lower education level of the father and higher welfare level
of parents were associated with obesity in the children.
Table 3 presents area and region distrubition of obesity.
Although there was found no dierence between regions
in children aged 0 to 23 months, the frequency of obesity
was found higher in children from urban areas. In children
aged 24 to 59 months, the least amount of obesity was in
the Eastern Anatolian region and highest in the Middle
Anatolian region. ere was no dierence in the frequency
of obesity according to settlement.
As shown in Table 4, the eects of dierent variables on
obesity frequency were determined. In the model, which
was constructed for children in the 0–23 months age group
and in children aged over 1 year, the frequency of obesity
was found as 2.8 times high compared with babies in
their rst 6 months. Obesity was 2.3 times more frequent
in children with high birth weight than in children with
low birth weight. e frequency of obesity was twice as
high in children with obese mothers and twice as high in
children with smoking mothers. In the model, which was
constructed for children over 2 years old, the frequency of
obesity was 2.8 times higher in children whose parents had
a consanguineous marriage than in children whose parents
were not in a consanguineous marriage. In addition, the
frequency of obesity was 2.7 times higher in children
living in the western and middle regions than the children
living in the eastern region.
4. Discussion
Overweightness and obesity are considered to be a
worldwide epidemic, the prevalence of which has
dramatically increased among children during the last
decades (11). e prevalence of overweightness and
obesity varies across countries and years of study. e
national prevalence obesity of United States of America
was found as 7.2% in 1988, 13.9% in 2004, and 9.4% in
2014 (12). e prevalence of obesity in preschool children
in China was reported as 3.9% in 1992 and 5.4% in 2002
(13). In Brazil, the prevalence of obesity increased from
6.7% to 9.3% in children aged under ve years (14). In a
study in Kuwait, the prevalence of preschool obesity was
found as 8.2% (15). Similar ndings were also obtained
Figure. Flow diagram of the study.
Cases attained
Excluded
(n=7550)
Study population
TDHS-2013 Female Database
N=9746
Not having a child under the age of 5
n=6881
Missing both height and weight data
n=27
Missing height or weight data
n=608
Incompatible height/weight data
n=34
TDHS-2013 Women’s
Database
N=2196
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UĞRAŞ DİKMEN et al. / Turk J Med Sci
Table 1. Overweight/obesity status of children aged 0–59 months by sociodemographic and nutrition-related
characteristics, Turkey, 2012.
0–23 months old
overweight/obese children
24–59 months old
overweight/obese children
%1n2P %1n2P
Sex
Boy 14.6 536 0.446 11,4 636 0.204
Girl 12.8 511 8,8 513
Months
0-5 months 6.4* 213
<0.0016-11 months 11.9 301
12-23 months 17.7* 533
24-36 months 12.3 451
0.22437-48 months 9.2 378
49-59 months 8.7 320
Birth weight
Low 9.5 250
0.003
5.1* 266
0.033 Normal 13.5 635 11.9 692
High 22.1* 156 10.9 190
Birth order
1st child 15.0 298
0.627
13.0 285
0.112
2nd-3rd child 13.4 554 10.1 647
4th-5th child 14.7 127 6.7 135
6th+ child 9.7 68 4.1 82
Breastfeeding aer delivery
Immediately 15.0 597
0.220
10.0 639
0.588
In an hour 10.9 57 12.4 63
Aer an hour 11.1 255 8.7 325
Aer a week 16.8 119 15.0 99
Never --- 18 12.5 2
Still breastfeeding
No 18.0* 338 0.030 10.2 1056 0.923
Yes 12.2 686 10.7 68
Taking milk except for breast milk in the rst three days AD
No 14.3 1012 0.143 10.3 1119 0.402
Yes --- 15 --- 6
Giving formula in the rst three days AD
No 14.0 757 0.962 9.8 907 0.479
Yes 14.2 270 11.6 218
Giving sugar water in the three days AD
No 14.2 976 0.537 10.2 1066 0.923
Yes 11.2 51 9.6 59
Bottle-feeding before the interview night
No 13.5 474 0.845 9.1 780 0.106
Yes 14.0 573 12.6 368
1Row percentage of overweight/obesity status.
2Total unweighted counts. AD: Aer delivery.
*Statistically signicant cells
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UĞRAŞ DİKMEN et al. / Turk J Med Sci
in a comprehensive study that used data from 450 cross-
sectional surveys from 144 countries (16). In that study,
the prevalence of childhood overweightness and obesity in
pre-chool children was reported as 4.2% in 1990 and 6.7%
in 2010. ese studies suggest that childhood obesity tends
to increase. e prevalence of overweightness and obesity
in children aged under ve years was found as 10.9%–
17.9% in Turkey (6, 7). According to TDHS 2013 ndings,
Table 2. e descriptive characteristics of parents of overweight/obese children, Turkey, 2012.
0–23 months old overweight/
obese children
24–59 months old overweight/
obese children
%1n2P %1n2P
Maternal age (years)
15-19 9.8 51
0.706
22.2 5
0.542
20-29 13.7 584 11.3 446
30-39 14.5 384 10.0 592
40-49 11.5 28 6.7 106
Status of mother education
No education 8.5 161 4.2 150
0.133
Elementary school 10.9 366 11.8 532
Secondary school 16.8 409 10.3 351
High school and above 17.4* 111 0.015 10.0 116
Status of father education
No education 19.9 45
0.002
6.0 43
0.501
Elementary school 8.4* 394 8.8 440
Secondary school 16.7 441 11.1 495
High school and above 16.7 165 12.6 167
Welfare level
Poor 10.3 565 8.3 569
0.117 Normal 13.2 204 9.2 239
Rich 18.6* 278 0.012 13.0 341
Consanguineous marriage
Yes 13.9 313 0.938 15.7* 297 0.002
No 13.7 733 8.5 852
Mother tongue of parents
Turkish 14.3 676
0.179
11.2 842
0.258
Kurdish 12.4 314 8.4 266
Arabic 5.4 46 --- 26
Others 36.9 11 --- 15
Maternal smoking status
Smoking 24.3* 178 <0.001 11.0 260 0.657
Not smoking 11.3 869 9.9 888
Status of mother obesity
Obese 21.6* 148 0.003 9.8 154 0.840
Not obese 12.3 888 10.4 988
1Row percentage.
2 Total unweighted count.
*Statistically signicant cells.
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UĞRAŞ DİKMEN et al. / Turk J Med Sci
one out of every ten children was overweight/obese (6).
In the Childhood Obesity Surveillance Initiative-Turkey
(COSI-TR) study, the prevalence of obesity was found as
22.5% in children aged 7–8 years (17). It is thought that
if obesity/overweightness is not prevented, it will increase
later in Turkey. Identied risk factors should be considered
for the prevention of overweightness/obesity. e aim
of this study was to determine factors associated with
overweightness/obesity.
Many studies have reported a positive association
between high birth weight and obesity in older children and
adults (18–21). Also, similar results were found in children
aged up to 7 years (22, 23). A systematic review conducted
by Martins et al. (over 20 studies) in 2016 showed that
there was a positive association between birth weight and
childhood obesity (22). Our research also supports this
nding. In the present study, the frequency of obesity was
2.3 times more frequent in children with high birth weight
than in children with low birth weight. ese results were
interpreted that obesity became a chronic process if obese
children with high birth size were not treated. Besides,
studies have reported that low birth weight was protective
against the development of obesity (23).
e WHO recommends exclusive breastfeeding in the
rst six months, then breastfeeding to 24 months with
a supplementary diet. In children aged 0–23 months,
a higher prevalence of obesity was found in those who
were not breastfed. Breastfeeding is a protective factor for
obesity of early childhood (24). Armstrong et al. reported
that breastfeeding reduced the risk of childhood obesity in
a study conducted with 32,200 children aged 39–42 months
(24). It is thought that adherence to the recommendations
of the WHO regarding breastfeeding would reduce the
prevalence of obesity.
Many factors related to mothers have been associated
with obesity in children. Lamerz et al. reported a strong
relationship between mother’s high educational status
and obesity in children. However, Fitzgibbon et al. (2005
and 2006) found no statistically signicant relationship
between the mother’s education and the prevalence
of obesity in children aged under 60 months (25, 26).
On the contrary, Felisbino-Mendes et al. reported that
there was a positive relationship between the level of
maternal education and obesity in children aged under
60 months. e frequency of obesity increased as the
mother’s education level increased (27). In our study,
there was a dierence in childhood obesity related with
the mother’s education levels; it was observed that the
frequency of obesity increased as the mother’s education
level increased. is situation may be associated with
an increase in the socioeconomic level of the family due
to the increase in the education level of the mother. As
the socioeconomic level increases, unhealthy diets may
also increase. In addition, this may be related to the fact
that highly-educated mothers perceive their children as
overweight. Baugchum et al. emphasized that preventing
obesity/overweightness in preschool children could not
succeed without understanding their mother’s perception
of the problem when treating the obesity problem (28).
Prenatal exposure to tobacco can lead to life-long eects as
a result of DNA methylation (29). Von Kries et al. reported
that smoking during pregnancy caused childhood obesity
by aecting babies in utero (30). Also, mothers who smoke
may also be less likely to monitor their children’s health. e
Table 3. Regional and area distribution of overweightness/obesity, Turkey, 2012.
0–23 months old
overweight/obese children
24–59 months old
overweight/obese children
%1n2P %1n2P
Regions
West 16.5 187
0.105
12.3 254
0.001
South 16.1 167 6.4 160
Middle 15.3 171 13.7 217
North 11.2 130 10.4 179
East 8.2 392 5.2* 339
Residence
Urban 15.2 755
0.007
10.3 829 0.880
Rural 8.2* 292 10.0 320
1Row percentage.
2 Total unweighted count.
*Statistically signicant cells.
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UĞRAŞ DİKMEN et al. / Turk J Med Sci
results of our study support a rising prevalence of obesity
in children whose mothers smoke (31). Another factor
related to maternal characteristics about childhood obesity
is maternal obesity status. Maternal obesity increases the
risk that children will become obese/overweight (32). e
ndings of our study support this nding. A number of
mechanisms could be responsible for the links between
childhood obesity and maternal obesity. Sloboda and
Vickers reported that obesity of the mother might transfer
to the child via nonMendelian mechanisms (33). Lesseur
et al. reported that the obese mother might be eective by
disrupting the leptin DNA methylation in the child (34).
e family characteristics (lifestyle, traditional behavior,
and health behaviors) in which children live can inuence
children’s behaviors and health outcomes. ere is a need
for more research in this area.
Table 4. Various independent factors associated with childhood overweight/obesity, Turkey, 2012.
0–23 months old children1,2 24–59 months old children3,4
OR CI P OR CI P
Age group (months)
0-5 months Ref.
<0.001
6-11 months 1.933 0.947-3.948
12-23 months 2.891 1.628-5.133
Birth weight
Low Ref.
0.022
Normal 1.382 0.853-2,239
High 2.368 1.263-4.440
Status of mother obesity
Obese 2.092 1.338-3.272 0.001
Not obese Ref.
Status of mother education
No education Ref.
0.018
Elementary school 2.276 1.089-4.757
Secondery school 1.387 0.593-3.241
High school and higher 0.884 0.323-2.423
Maternal smoking status
Smoking 2.071 1.287-3.334 0.003
Not smoking Ref.
Consanguineous marriage
Yes 2.865 1.835-4.472 <0.001
No Ref.
Regions
West 2.776 1.486-5.186
0.001
South 1.346 0.683-2.654
Middle 2.796 1.538-5.085
North 1.823 0.926-3.591
East Ref.
1Percentage of correct classication: 85.9%.
2Adjusted for sex of child, still breastfeeding, status of mother education, status of father education,consanguineous
marriage, welfare level, regions and residence.
3Percentage of correct classication: 89.7%.
4Adjusted for sex of child, age group (months), birth weight, status of mother obesity, status of father education, maternal
smoking status, welfare level and residence.
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UĞRAŞ DİKMEN et al. / Turk J Med Sci
ere are a limited number of studies in the literature
about the level of childrens father’s education and its
relationship with childhood obesity. A recent study
by Savaşhan et al. in 2015 reported that there was no
relationship between father’s education and obesity in
school aged children (35). In contrast, Sarrafzadegan et
al. observed that higher levels of education of the father
were associated with obesity (36). In our study, there was
no linear correlation between the father’s education level
and frequency of obesity.
A systemic study showed no clear relationship between
socioeconomic level and childhood overweightness/
obesity (37). On the contrary, Vitolo et al. reported
that a high socioeconomic level was associated with
overweightness in children aged under ve years (38).
e results of our study are consistent with those of
Vitolo et al. is may be caused by children with higher
socioeconomic levels consuming high-calorie food and
avoiding physically challenging tasks.
Joens-Matre et al. suggested that there were rural-
urban dierences in obesity of children and adolescent
(39). In the literature, there are no consistent ndings that
residence factors are a risk for obesity in children aged 0-5
years. In this age group, dierent studies have reported that
obesity is more common in both urban and rural areas (7,
40). De Arruda Moreira et al. reported that children aged
under ve years did not dier in urban and rural regions
concerning overweightness and obesity (23). In the present
study, urban residence was found higher in children
aged 0-2 years, whereas it was found similar in children
aged 2-5 years. Despite the fact that high education was
more common in the urban residence group, the rural-
urban dierence in the development of overweightness/
obesity cannot be solely explained by the dierences in
the educational level of parents. e educational level
of the father and mother were not parallel in our study.
is result may be due to urbanization; the diculty of
accessing places for physical activity and easier access to
high-calorie foods. Also, we found that obesity increased
as the level of income increased in children aged 0 to 2
years. e fact that the welfare of the people living in the
city is better could explain this situation.
In conclusion, further analysis found that child
characteristics, parents’ characteristics and type of
residence were eective on childhood obesity in Turkey. It
would be benecial to identify obesity risk factors, monitor
obese patients, and present a multidisciplinary approach to
the treatment and prevention of obesity. Both family and
health professionals may make important contributions to
treatment and prevention of obesity. Obtaining accurate
information about obesity by parents may be possible
through health education. ere is a need for further
studies to identify the environmental and cultural factors
associated with overweightness/obesity.
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... Globally over 38 million children under the age of 5 years are affected [5][6][7]. Children are classified as overweight or obese if their weight-for-height is greater than two or three standard deviations above the age specific median as defined by the World Health Organization (WHO) [7,8]. Previously, childhood obesity was thought to be a problem of high-income countries, but low-and middle-income countries are now registering higher proportions of overweight and obese children [7,9]. ...
... Obesity arises from a complex interaction between behavioral, metabolic, environmental, and socioeconomic determinants ranging from changing food systems and reduced physical activity to indiscriminate marketing that promotes obesogenic foods [6,[11][12][13]. In addition, childhood obesity has been attributed to other risk factors such as high birth weight, maternal obesity, maternal smoking, consanguineous marriage, and poor breastfeeding practices [8,[14][15][16]. Similarly, the risk of overweight or obesity has been shown to be more prevalent among children attending affluent primary schools as compared to those in rural public schools [17,18]. ...
... Furthermore, overweight and obese children have higher risk of early chronic diseases onset, such as diabetes, dyslipidemias, cardiovascular diseases and some cancers [6,10,20]. Additionally, they are reported to have lower educational attainment because of poor psychosocial wellbeing [6,8], higher costs to health systems, and greater financial burden to households [6]. ...
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Background Childhood obesity is an emerging public health problem globally. Although previously a problem of high-income countries, overweight and obesity is on the rise in low- and middle-income countries. This paper explores the factors associated with childhood obesity and overweight in Uganda using data from the Uganda Demographic and Health Survey (UDHS) of 2016. Methods We used Uganda Demographic and Health Survey (UDHS) 2016 data of 4338 children less than 5 years. Multistage stratified sampling was used to select study participants and data were collected using validated questionnaires. Overweight and obesity were combined as the primary outcome. Children whose BMI z score was over two were considered as overweight while those with a BMI z score greater than three were considered as obese. We used multivariable logistic regression to determine factors associated with obesity and overweight among children under 5 years of age in Uganda. Results The prevalence of overweight and obesity was 5.0% (217/4338) (95% CI: 4.3–5.6), with overweight at 3.9% (168/4338: 95% CI: 3.2–4.3) and obesity at 1.1% (49/4338: 95% CI: 0.8–1.5). Mother’s nutritional status, sex of the child, and child’s age were associated with childhood obesity and overweight. Boys were more likely to be overweight or obese (aOR = 1.81; 95% CI 1.24 to 2.64) compared to girls. Children who were younger (36 months and below) and those with mothers who were overweight or obese were more likely to have obesity or overweight compared to those aged 49–59 months and those with underweight mothers respectively. Children from the western region were more likely to be overweight or obese compared to those that were from the North. Conclusion The present study showed male sex, older age of the children, nutritional status of the mothers and region of residence were associated with obesity and overweight among children under 5 years of age.
... Childhood obesity and overweight are an emerging public health problem [1] affecting over 38 million children under the age of ve globally [1][2][3]. Children are classi ed as overweight or obese if their weightfor-height is greater than two or three standard deviations above the World Health Organization (WHO) child growth median [3,4]. Although childhood obesity was previously a problem of high-income countries, low-and middle-income countries have been registering more cases and this is contributing to the double burden of disease [3,5]. ...
... These drivers spurn changing food systems, reduced physical activity, and indiscriminate marketing that promotes obesogenic foods [1,6,7]. Equally, childhood obesity has been attributed to other risk factors such as high birth weight, maternal obesity, maternal smoking, consanguineous marriage, and poor breastfeeding [4,[8][9][10]. Similarly, overweight and obesity are more prevalent among children attending a uent primary schools compared to those in rural public schools [11,12]. ...
... Furthermore, overweight and obese children suffer higher risks of early chronic diseases onset, for example, diabetes, dyslipidemias, cardiovascular illnesses and some cancers [1,14,15]. Likewise, they are reported to have low educational attainment because of poor psychosocial wellbeing [1,4]. Childhood obesity also results in higher costs to health systems, and greater nancial burden to households [1]. ...
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Background: Childhood obesity is an emerging public health problem. Although previously a problem of high-income countries, low- and middle-income countries are now registering higher proportions of overweight and obese children. Studies in Africa have mainly focused on undernutrition among children. This paper explores the factors associated with childhood obesity and overweight in Uganda using data from the Uganda Demographic and Health Survey (UDHS) of 2016. Methods: We used Uganda Demographic and Health Survey (UDHS) 2016 data of 4,338 children less than five years. Multistage stratified sampling was used to select study participants and data were collected using validated questionnaires. We used multivariable logistic regression to determine factors associated with obesity and overweight among children under the age of five in Uganda. Results: The prevalence of overweight and obesity was 5.0% (217/4338) (95% CI: 4.3–5.6) with overweight at 3.9% (168/4338: 95% CI: 3.2–4.3) and obesity at 1.1% (49/4338: 95% CI: 0.8–1.5). Boys were more likely to be overweight or obese (adjusted odds ratio: aOR = 2.00; 95% CI 1.42–2.82) compared to girls. Furthermore, children from the Western region (aOR = 1.61; 95% CI 1.07–2.44) compared to those from the North, children below the age of 49 months and those with mothers who were overweight or obese (aOR = 3.36; 95% CI 1.53–7.34) were more likely to be obese or overweight compared to their counterparts who were above 48 months and those with underweight mothers respectively. Conclusion: The present study showed male sex, older age of the children, nutritional status of the mothers and region of residence were associated with overnutrition among under five children in Uganda.
... Hal tersebut sudah dikonfirmasi melalui penelitian tentang adanya korelasi yang signifikan antara status berat badan ibu dan atau ayah dengan ukuran pertumbuhan anak mereka saat usia sekolah 13 . Penelitian lain melaporkan bahwa obesitas pada masa kanak-kanak berkorelasi dengan faktor risiko lain seperti berat badan lahir tinggi, obesitas ibu, ibu yang merokok, perkawinan sedarah, dan praktik menyusui yang buruk [14][15][16][17] . ...
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This study aims to investigate the causal effect of obesity on the employment probability of women in Turkey via the instrumental variable approach by using data from the 2018 Turkey and Demographic Health Survey. Obesity prevalence in the area of living and the overweight status of the oldest child, which are the most common types of instruments seen in the literature, are used as instruments. Consistent with the OLS result, the 2SLS estimate indicates that obese women are statistically significantly less likely to be employed when the overweight status of the child is used as an instrument. On the other hand, the statistically significant effect of obesity disappears when the area level obesity prevalence is used as the instrument. In addition, obesity in women decreases the likelihood of employment in the services sector and full-time jobs and employment with social security. Although the results of this study do not indicate the source of the effect found, the presence of a causal relationship for women should not be ignored when the economic burden of obesity for Turkey is considered.
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Background and aim The world is experiencing an alarming increase in prevalence of childhood obesity. The aim of this study was to determine the demographic determinants of obesity and adherence to dietary and physical activity guidelines among children aged 4 to 6 years old in Behbahan city, southwest Iran, in 2016. Methods This cross-sectional study was conducted on 120 preschool children aged 4 to 6 years old in Behbahan city, southwest Iran, in 2016. Multi-stage random sampling was done. The weight and height of the children were measured with standard methods. The demographic and behavioral factors data were collected in self report questionnaires which were completed by the children’s mothers. The Chi-square test, Independent-samples t-tests, One-way analysis of variances and logistic regression analysis were used for data analysis. SPSS software (version 22) was employed. Results This study showed that 88.3% of the children did not meet the guideline of 5 servings per day of fruit and vegetables. Only 2.5% met the guideline of 60 minutes of structured physical activity every day. Sex and mother’s occupation status were associated with adhering to screen time guideline. This study found a significant difference in the mean of screen time between sexes. Boys were more likely to meet the screen time guideline. A significant association between adhering to physical activity guidelines and mother’s occupation status was revealed. Significant statistical relationship between demographic factors and BMI categories was not illustrated. Demographic covariates were not significantly related to adherence to dietary and physical activity guidelines. Conclusion In preventive programs of obesity among 4 to 6-year-old children key lifestyle behaviors and demographic factors need to be considered.
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Antibiotic therapy in hematologic patients, often weak and susceptible to a wide range of infections, particularly nosocomial infections derived from long hospitalization periods, is a challenging issue. This paper presents ESBL-producing strains isolated from such hematologic patients treated at the Amazon Hematology and Hemotherapy Foundation (HEMOAM) in the Brazilian Amazon Region to identify the ESBL genes carried by them as well as the susceptibility to 11 antimicrobial agents using the E-test method. A total of 146 clinical samples were obtained from July 2007 to August 2008, when 17 gram-negative strains were isolated in our institution. The most frequent isolates confirmed by biochemical tests and 16S rRNA sequencing were E. coli (8/17), Serratia spp. (3/17) and B.cepacia (2/17). All gram-negative strains were tested for extended-spectrum-beta-lactamases (ESBLs), where: (12/17) strains carried ESBL; among these, (8/12) isolates carried blaTEM, blaCTX-M, blaOXA, blaSHV genes, (1/12) blaTEM gene and (3/12) blaTEM, blaCTX-M, blaOXA genes. Antibiotic resistance was found in (15/17) of the isolates for tetracycline, (12/17) for ciprofloxacin, (1/17) resistance for cefoxitin and chloramphenicol, (1/17) for amikacin and (3/17) cefepime. This research showed the presence of gram-negative ESBL-producing bacteria infecting hematologic patients in HEMOAM. These strains carried the blaTEM, blaSHV, blaCTX-M and blaOXA genes and were resistant to different antibiotics used in the treatment. This finding was based on a period of 13 months, during which clinical samples from specific populations were obtained. Therefore, caution is required when generalizing the results that must be based on posological orientations and new breakpoints for disk diffusion and microdilution published by CLSI 2010.
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Background and aims: Infant and adult obesity is becoming a real public health concern in Romania, similar to other countries of the European Union. Maternal obesity and excessive weight gain during pregnancy are proven risk factors for the obesity of the child. The protective role of the breastfeeding against obesity has also been demonstrated. The most important issue is whether the choice of a milk formula with the right protein composition could or not protect the newborn from becoming a future obese infant and child. Our study aims to describe the characteristics of a group of macrosomic newborns, in relation to the mothers' weight gain during pregnancy, mode of delivery, birth weight, complications at birth, time of first feeding and type of feeding during maternity stay. Patients and methods: We conducted a retrospective study on 179 newborns with birth weights >4000 grams, born over a period of three months (March-May) in 6 large maternity hospitals in Romania. Results: the newborns had a mean gestational age of 39.5 weeks and a mean birth weight of 4195 grams. Male newborns were prevalent (74%). More than half were born by Cesarian section and had Apgar scores with a median of 9. Macrosomes are prone to complications at birth and in our study those were mainly hypoglycemia and birth trauma. Time at first feeding was 95 minutes (mean), with a high percentage of formula/mixed feeding (68%). Conclusion: Macrosomia itself attracts the risk of birth by cesarean section (54% of study group), birth trauma and a low rate of exclusive breast milk feeding (32% of study group) at discharge.
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Children from disadvantaged families including those from low socioeconomic backgrounds and Indigenous families have higher rates of obesity, making early intervention a priority. The aim of this study was to systematically review the literature to examine the effectiveness of interventions to prevent obesity or improve obesity related behaviours in children 0-5 years from socioeconomically disadvantaged or Indigenous families. Searches of major electronic databases identified articles published from 1993–2013 targeting feeding practices, anthropometric, diet, activity or sedentary behaviour outcomes. This was supplemented with snowballing from existing reviews and primary studies. Data extraction was undertaken by one author and cross checked by another. Quality assessments included both internal and external validity. Thirty-two studies were identified, with only two (both low quality) in Indigenous groups. Fourteen studies had a primary aim to prevent obesity. Mean differences between intervention and control groups ranged from -0.29 kg/m2 to -0.54 kg/m2 for body mass index (BMI) and -2.9 to -25.6% for the prevalence of overweight/obesity. Interventions initiated in infancy (under two years) had a positive impact on obesity related behaviours (e.g. diet quality) but few measured the longer-term impact on healthy weight gain. Findings amongst pre-schoolers (3–5 years) were mixed, with the more successful interventions requiring high levels of parental engagement, use of behaviour change techniques, a focus on skill building and links to community resources. Less than 10% of studies were high quality. Future studies should focus on improving study quality, including follow-up of longer-term anthropometric outcomes, assessments of cost effectiveness, acceptability in target populations and potential for implementation in routine service delivery. There is an urgent need for further research on effective obesity prevention interventions for Indigenous children. The findings from the growing body of intervention research focusing on obesity prevention amongst young children from socioeconomically disadvantaged families suggest intervention effects are modest but promising. Further high quality studies with longer term follow up are required. Trial registration PROSPERO Registration no: CRD42013006536.
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Importance Previous analyses of obesity trends among children and adolescents showed an increase between 1988-1994 and 1999-2000, but no change between 2003-2004 and 2011-2012, except for a significant decline among children aged 2 to 5 years. Objectives To provide estimates of obesity and extreme obesity prevalence for children and adolescents for 2011-2014 and investigate trends by age between 1988-1994 and 2013-2014. Design, Setting, and Participants Children and adolescents aged 2 to 19 years with measured weight and height in the 1988-1994 through 2013-2014 National Health and Nutrition Examination Surveys. Exposures Survey period. Main Outcomes and Measures Obesity was defined as a body mass index (BMI) at or above the sex-specific 95th percentile on the US Centers for Disease Control and Prevention (CDC) BMI-for-age growth charts. Extreme obesity was defined as a BMI at or above 120% of the sex-specific 95th percentile on the CDC BMI-for-age growth charts. Detailed estimates are presented for 2011-2014. The analyses of linear and quadratic trends in prevalence were conducted using 9 survey periods. Trend analyses between 2005-2006 and 2013-2014 also were conducted. Results Measurements from 40 780 children and adolescents (mean age, 11.0 years; 48.8% female) between 1988-1994 and 2013-2014 were analyzed. Among children and adolescents aged 2 to 19 years, the prevalence of obesity in 2011-2014 was 17.0% (95% CI, 15.5%-18.6%) and extreme obesity was 5.8% (95% CI, 4.9%-6.8%). Among children aged 2 to 5 years, obesity increased from 7.2% (95% CI, 5.8%-8.8%) in 1988-1994 to 13.9% (95% CI, 10.7%-17.7%) (P < .001) in 2003-2004 and then decreased to 9.4% (95% CI, 6.8%-12.6%) (P = .03) in 2013-2014. Among children aged 6 to 11 years, obesity increased from 11.3% (95% CI, 9.4%-13.4%) in 1988-1994 to 19.6% (95% CI, 17.1%-22.4%) (P < .001) in 2007-2008, and then did not change (2013-2014: 17.4% [95% CI, 13.8%-21.4%]; P = .44). Obesity increased among adolescents aged 12 to 19 years between 1988-1994 (10.5% [95% CI, 8.8%-12.5%]) and 2013-2014 (20.6% [95% CI, 16.2%-25.6%]; P < .001) as did extreme obesity among children aged 6 to 11 years (3.6% [95% CI, 2.5%-5.0%] in 1988-1994 to 4.3% [95% CI, 3.0%-6.1%] in 2013-2014; P = .02) and adolescents aged 12 to 19 years (2.6% [95% CI, 1.7%-3.9%] in 1988-1994 to 9.1% [95% CI, 7.0%-11.5%] in 2013-2014; P < .001). No significant trends were observed between 2005-2006 and 2013-2014 (P value range, .09-.87). Conclusions and Relevance In this nationally representative study of US children and adolescents aged 2 to 19 years, the prevalence of obesity in 2011-2014 was 17.0% and extreme obesity was 5.8%. Between 1988-1994 and 2013-2014, the prevalence of obesity increased until 2003-2004 and then decreased in children aged 2 to 5 years, increased until 2007-2008 and then leveled off in children aged 6 to 11 years, and increased among adolescents aged 12 to 19 years.
Article
Aim: To describe the methods used to construct the WHO Child Growth Standards based on length/height, weight and age, and to present resulting growth charts. Methods: The WHO Child Growth Standards were derived from an international sample of healthy breastfed infants and young children raised in environments that do not constrain growth. Rigorous methods of data collection and standardized procedures across study sites yielded very high-quality data. The generation of the standards followed methodical, state-of-the-art statistical methodologies. The Box-Cox power exponential (BCPE) method, with curve smoothing by cubic splines, was used to construct the curves. The BCPE accommodates various kinds of distributions, from normal to skewed or kurtotic, as necessary. A set of diagnostic tools was used to detect possible biases in estimated percentiles or z-score curves. Results: There was wide variability in the degrees of freedom required for the cubic splines to achieve the best model. Except for length/height-for-age, which followed a normal distribution, all other standards needed to model skewness but not kurtosis. Length-for-age and height-for-age standards were constructed by fitting a unique model that reflected the 0.7-cm average difference between these two measurements. The concordance between smoothed percentile curves and empirical percentiles was excellent and free of bias. Percentiles and z-score curves for boys and girls aged 0-60 mo were generated for weight-for-age, length/height-for-age, weight-for-length/h eight (45 to 110 cm and 65 to 120 cm, respectively) and body mass index-for-age. Conclusion: The WHO Child Growth Standards depict normal growth under optimal environmental conditions and can be used to assess children everywhere, regardless of ethnicity, socio-economic status and type of feeding.
Article
Prenatal exposure to tobacco smoke has lifelong health consequences. Epigenetic signatures such as differences in DNA methylation (DNAm) may be a biomarker of exposure and, further, might have functional significance for how in utero tobacco exposure may influence disease risk. Differences in infant DNAm associated with maternal smoking during pregnancy have been identified. Here we assessed whether these infant DNAm patterns are detectible in early childhood, whether they are specific to smoking, and whether childhood DNAm can classify prenatal smoke exposure status. Using the Infinium 450K array, we measured methylation at 26 CpG loci that were previously associated with prenatal smoking in infant cord blood from 572 children, aged 3-5, with differing prenatal exposure to cigarette smoke in the Study to Explore Early Development (SEED). Striking concordance was found between the pattern of prenatal smoking associated DNAm among preschool aged children in SEED and those observed at birth in other studies. These DNAm changes appear to be tobacco-specific. Support vector machine classification models and 10-fold cross-validation were applied to show classification accuracy for childhood DNAm at these 26 sites as a biomarker of prenatal smoking exposure. Classification models showed prenatal exposure to smoking can be assigned with 81% accuracy using childhood DNAm patterns at these 26 loci. These findings support the potential for blood-derived DNAm measurements to serve as biomarkers for prenatal exposure.