Article Read the article on the impact of maternal prenatal smoking on the development of childhood overweight in school-aged children (Link attached). Is

Article Read the article on the impact of maternal prenatal smoking on the development of childhood overweight in school-aged children (Link attached). Is

Click here to Order a Custom answer to this Question from our writers. It’s fast and plagiarism-free.

Article Read the article on the impact of maternal prenatal smoking on the development of childhood overweight in school-aged children (Link attached). Is the article quantitative, qualitative, or something else? State the study design, research question, and the strength and limitations of the study. Can the study results be generalized? Why or why not? 

1page 

at least 2 references The impact of maternal prenatal smoking on the
development of childhood overweight in
school-aged children
L. Wang1, H. M. Mamudu2 and T. Wu1,3
1Department of Biostatistics and Epidemiology, College of Public Health, East Tennessee State University, Johnson City, TN, USA;
2Department of Health Services Management and Policy, College of Public Health, East Tennessee State University, Johnson City,
TN, USA; 3Department of Family Medicine, James H. Quillen College of Medicine, East Tennessee State University, Johnson City,
TN, USA

Received 6 March 2012; revised 10 July 2012; accepted 24 August 2012

What is already known about this subject
• Maternal smoking during pregnancy likely increase the

risk of childhood overweight.
• Childhood overweight is influenced by socioeconomic

characteristics of mothers.
• Characteristics of child at birth determine the likelihood

of overweight.

What this study adds
• Children of mothers who smoked 1 year before birth

(including pregnancy) were likely to be overweight during
school ages than those of mothers who never smoked.

• Confirmation that socioeconomic characteristics of
mothers influence the likelihood of childhood overweight
during school age.

• Smoking cessation should be targeted at mothers 1 year
before birth to improve their health status and that of
offspring.

Summary
Objectives: To examine associations between maternal smoking and overweight among school-aged
children and also identify mothers and offspring characteristics that affect children’s weight.

Methods: We used data from the National Institute of Child Health and Human Development (NICHD)
Study of Early Child Care and Youth Development (SECCY). Childhood overweight was defined as having
Body Mass Index (BMI) of 85th percentile or above. Smoking patterns among mothers were assessed by
questioning smoking behaviour 1 year before birth of the target child: never or ever smoking. Standardized
procedures were used to measure height and weight. Descriptive statistics and generalized estimating
equations (GEE) were used for the analysis.

Results: Descriptive results showed that children of mothers who smoked anytime within 1 year before
birth were more likely to be overweight and have higher BMI percentile averages. GEE results showed that
children of mothers who were ever smokers 1 year before birth were more likely to be overweight (OR = 1.39,
95% CI: 1.01, 1.94) and have higher BMI percentile averages (b = 4.46, P = 0.036) from grades 1 through
6 than those of mothers who were never smokers. Additionally, the level of mother’s education and birth
weight were significantly associated with childhood overweight.

Conclusions: Confirmed relationships between maternal smoking and overweight among school-aged
children have important implications for public health policy because this evidence can be used to enhance
smoking cessation 1 year before birth to improve the health status of mothers and offspring.

Keywords: Childhood overweight, longitudinal study, maternal prenatal smoking, risk factor.

Address for correspondence: Dr L Wang, Department of Biostatistics and Epidemiology, East Tennessee State University, PO Box
70259, Johnson City, TN 37614, USA. E-mail: wangl2@etsu.edu
© 2012 The Authors
Pediatric Obesity © 2012 International Association for the Study of Obesity. Pediatric Obesity 8, 178–188

PEDIATRICOBESITY ORIGINALRESEARCH doi:10.1111/j.2047-6310.2012.00103.x
O

R
IG

IN
A

L
R

E
S

E
A

R
C

H

Introduction

The prevalence of overweight and obesity has been
increasing worldwide and has emerged as a global
public health issue (1), thus leading to efforts to iden-
tify the root causes of the problem. Data from the
National Health and Nutrition Examination Survey
(NHANES) in the United States indicate that the
prevalence of adult overweight and obesity was
34.4% in 2008 (2) and 35.7% in 2010 (3). The data
also show that the prevalence of overweight and
obesity among school-aged children between 6 and
11 years of age in 2008 was 35.5% and 19.6%,
respectively (4). The rate of prevalence of obesity in
children between 2 and 19 years of age (16.9%)
remained steady between 2008 and 2010 despite
efforts to reduce it (5). For this reason, the obesity rate
31% in 2010 in the United States is expected to reach
over 42% by 2030 if drastic efforts are not taken to
identify the sources and interventions for it (6).

Overweight and obesity among children in the
United States has increased dramatically over the
past three decades to reach epidemic proportions.
Obesity in children aged two years and older has at
least doubled in the last 25 years and tripled in the
past 30 years (7). The dramatic increase in childhood
overweight and obesity has resulted in ‘childhood’
diseases that were once thought of as primarily
‘adult’ diseases, such as type II diabetes (8), hyper-
tension, hyperlipidemia, high cholesterol levels and
abnormal glucose tolerance (9,10). Additionally, over-
weight children and adolescents often have psycho-
social problems, including compromised health
related to quality of physical, emotional and social
well-being (11–14). Moreover, obese children are
least desired to be friended by peers (15) and more
likely to be bullied (16), which leads to a poor self-
image that persists into adulthood (17). Thus, over-
weight or obesity is not only a health problem but
also a social problem. However, the age at which
overweight and obesity starts is not obvious, thus
demanding investigation into the sources of the
problem for early intervention.

Previous studies have identified socioeconomic,
demographic and environmental determinants of
overweight and obesity (1,18). Increasing studies on
populations in places, such as Japan (19), Europe
(20), Canada (21) and the United States (22) have
turned to the lifestyle of mothers that impact foetal
programming and lead to overweight or obesity in
childhood (and adulthood). A key marker for child-
hood (and adult) obesity is maternal smoking (1,23–
26). This relationship is due to a number of possible
reasons, including intrauterine malnutrition (27) and

toxic effects of cigarette smoke (28) that may result in
elevated concentration of cortisol in the cord blood
(29). All these metabolic mechanisms may have an
adverse impact on foetal programming and could
negatively impact the weight of offspring (30). Thus,
maternal smoking does not only lead to low birth
weight (31), but it is also related to catching up
growth in childhood that leads to overweight and
obesity (32,33). Despite this increasing evidence,
studies about the effects of whether or not the
mother had ever smoked within the entire year
before birth on the weight status of offspring are
sparse. Therefore, this study analyzes effects of
mothers’ smoking status within 1 year before birth
on overweight of school-aged children in the United
States using longitudinal cohort data. Simultane-
ously, the study identifies maternal and offspring
characteristics that impact the weight of offspring
during school ages. While the study helps to identify
mothers’ behaviours that impact the weight of
offspring, it provides useful information for under-
standing foetal programming and suggests that
the year before the birth may be an important period
for intervention to prevent childhood overweight.
This study may contribute to targeting maternal
smoking behaviour before birth and its adverse
outcome as an integral part of efforts to prevent the
obesity rate in the country from reaching 42% by
2030 (6).

Materials and methods
Data source and participants

Since 1991, the National Institute of Child Health and
Human Development (NICHD) Study of Early Child
Care and Youth Development (SECCYD) has been
conducted at 10 research hospitals across the
United States. Detailed recruitment and selection
procedures have been published in a previous
study (34) and http://www.nichd.nih.gov/research/
supported/seccyd/overview.cfm.

In brief, of a total of 8986 mothers that gave birth in
the research hospitals during sampling periods in
1991, 5416 (60%) agreed to be telephoned in 2
weeks. The exclusion criteria for mother–baby dyads
included mothers younger than 18 years, those that
did not speak English, did not agree with the 2-week
phone call, had history of substance abuse and the
baby had medical complications. Additional exclu-
sion criteria were neighbourhoods unsafe for teams
of researchers to visit, families living in the same
location for less than 1 year and families living too far
away from the research site (more than 1 h drive)
(35). These criteria were used to screen out very low

Maternal smoking and childhood overweight | 179

O
R

IG
IN

A
L

R
E

S
E

A
R

C
H

© 2012 The Authors
Pediatric Obesity © 2012 International Association for the Study of Obesity. Pediatric Obesity 8, 178–188

birth weight, premature or sick infants. Guided by the
mothers’ plans to return to work or school within a
year after delivery (in the ratio of 3:1:1 – full-time
workers: part-time workers: non-workers), the con-
ditionally random sampling, a sketch-based sam-
pling technique, that includes the advantages of both
sketching and random sampling (36) was designed
to provide sufficient data to allow for some statistical
adjustments to reflect characteristics of the base
sample. The sampling technique was used to ensure
that single-parent, low-maternal education and
minority distributional targets were met while con-
tinuing to select cases at random (37). Data from the
Hospital Recruitment and Gestational Age forms
were entered into a database at the Data Coordinat-
ing Center (DCC). Conditional random calling lists
were then generated by the DCC. A sample of 3015
(56%) mothers was selected from the 5416 mothers
who agreed to be telephoned in 2 weeks. Of these
3015 mothers in the sample, 1526 were available for
the interview at 1 month age of the child. Of the 1526
mothers, 1364 (89.4%) finished the interview and
became study participants in 1991. At 24 months
interview after birth, two people, a visit coordinator/
examiner and camera operator, conducted the labo-
ratory visit. The visit coordinator/examiner was
responsible for greeting the family, explaining each
procedure to the mother and administering the pro-
cedures; and the operator served as operator of the
video camera. Mothers were asked to recall their
prenatal smoking habits. In this study, we restricted
children with measure of body mass index (BMI) at
one or more time points (grades 1, 3 or 6) and those
whose mothers were not missing information on their
smoking behaviours within 1 year before birth to get
our analytic sample (1041). Phase I (1991–1994),
phase II (1995–2000) and phase III (2000–2005) of
the SECCYD data were used in the analysis. The
attrition rate for the study sample was 20.1%.

The Institutional Review Board of East Tennessee
State University approved this study.

Variables
Childhood overweight status

The key outcome variable was BMI percentile, which
was calculated according to the U.S. Centers for
Disease Control and Prevention’s (CDC) age and
gender-specific growth charts (38). The CDC’s
nomenclature defined overweight for a child as a BMI
(defined as weight in kilograms divided by squared
height in meters) equal to or greater than the 85th
percentile. As such, the outcome variable in this
study, childhood overweight status, was measured

as a dichotomized variable (BMI � 85th percentile
or normal weight, BMI � 85th percentile or over-
weight). Standardized procedures were used to
measure height and weight during the interviews by
NICHD SECCY staff. Height was measured with chil-
dren standing without shoes, feet together and their
backs against a calibrated 7-foot measuring stick.
Weight was measured using a physician’s 2-beam
scale. Scales were calibrated monthly using certified
calibration weights. Weight was measured with chil-
dren in minimal clothing and recorded twice, each
time to the nearest 0.25 pound (0.1 kg). This NICHD
SECCY study followed the same children from birth
through grades 1 (2000), 3 (2002) and 6 (2005). We
used data on BMI values from when the children
were in these grades as outcome variables.

Maternal prenatal smoking

Mother’s smoking status within 1 year before the
birth (1990) of the target child were assessed retro-
spectively with ‘The year before my child was born’
question (39), which consisted of two items measur-
ing mother’s smoking behaviour shortly before and
during pregnancy. Because of the small sample size
(1041) and study purposes, mother’s smoking status
was divided into two categories, never smoking and
ever smoking within 1 year before the birth of target
child.

Covariates

The main covariates, which encompassed maternal
characteristics, were collected at the 1 month of
child age interview. These covariates include mater-
nal age, education (bachelor’s degree or above, less
than a bachelor’s degree), living status (living single,
not living single), poverty (above poverty line, i.e.
$6932 for a single person and $8797 for a family of
two in 1991 (40), at or below poverty line) and breast-
feeding status (breastfeeding, not breastfeeding).
Other covariates involved offspring characteristics,
such as sex, ethnicity and birth weight. Child sex and
ethnicity were recorded at 1 month after birth. The
sample sizes for individual ethnic minority groups
were not large enough to allow separate subgroups’
analyses, thus, this study categorized ethnicity into
Whites, Blacks, or Others. Child’s birth weight in
grams was obtained from medical chart as a con-
tinuous variable.

Statistical analysis

We analyzed these data using univariate (frequen-
cies and percentages), bivariate (chi-square and

180 | L. Wang et al.
O

R
IG

IN
A

L
R

E
S

E
A

R
C

H

© 2012 The Authors
Pediatric Obesity © 2012 International Association for the Study of Obesity. Pediatric Obesity 8, 178–188

t-test) and multivariate (Generalized Estimating
Equations [GEE] ) statistics. In the bivariate analysis,
while the chi-square test was used to determine
whether there is any association between categori-
cal variables, the student t-test was used to deter-
mine whether there is any difference in the means of
continuous variables between two groups. Using
chi-square test and student t-test, we compared
maternal and child’s characteristics in our analytic
sample (n = 1041) with those excluded due to
incomplete data on childhood overweight in school
ages and maternal smoking status within 1 year
before the birth (n = 323). We then compared mater-
nal and child’s characteristics with dichotomous
maternal smoking status (never smoker vs. ever
smoker) within 1 year before the birth in our analytic
sample. Additionally, to describe the distribution of
overweight status in the two groups at three meas-
ures, we examined the distribution of mean BMI per-
centiles and proportions of overweight children by
maternal smoking status (never smoker vs. ever
smoker) within 1 year before the birth at grades 1, 3
and 6, respectively. Finally, we used GEE for the
multivariate analysis because, in comparison with
traditional regression analysis at one time point
(cross-sectional), it considers all repeated measure-
ments of the health outcomes by accounting for
their dependency (41,42). More specifically, classical
analyses such as regression do not consider the
pattern across time, and are not adequate to
address changes in mean response over time. In this
longitudinal study, the independence assumption
was not satisfied because children were measured
at multiple follow-up time points. For this reason, the
correlation of data within each child could be close
and should not be ignored. The GEE was used to
address this issue through the use of ‘working cor-
relation’ structure to account for the within-subject
correlation of response on dependent variables of
different distributions (41). In other words, GEE
models were used to account for within-subject
correlation across three time points (grades 1, 3
and 6) of measurements for categorical (childhood
overweight status) and continuous (BMI percentile)
variables. While 74.4 % of children had BMI meas-
urements at all three time points, 89.4 % had BMI
measurements at least at two time points. In this
longitudinal study, the missing BMI percentiles were
assumed to be missing at random, which was regu-
larly used to address missing data in longitudinal
data analysis (43). First-order auto-regression [AR(1)]
was used as the working correlation matrix for per-
forming the GEE to account for correlations among
repeated measurements in the BMI. Statistical sig-

nificance was defined as having a P-value �0.05 for
two-tailed testing. All data analyses were performed
using PASW version 18.0 statistical software (IBM
SPSS, Chicago, Illinois).

Results
Of the 1041 mothers, 812 (78%) were never smokers
and 229 (22%) were ever smokers. The characteris-
tics of the study sample were shown in Table 1. The
mean age of the mothers was about 29 years, and the
majority of them had less than a bachelor’s degree
(60.6%), were not living single (87.2%), were above
the poverty line (82.1%; $6932 for a single and $8865
for a family of two in 1991 (37)) and were breastfeed-
ing (62%). With respect to the offspring, half of them
were males (50.4%), more often white (81.5%) and
had a mean birth weight of 3503.2 grams. Compared
with mothers in the analytic sample (n = 1041),
mothers in the excluded sample due to incomplete
data (n = 323) were more likely to smoke within 1 year
before birth (P = 0.002), have younger ages
(P < 0.0001), have lower education (P < 0.0001), living single (P = 0.001), at or below poverty line (P < 0.0001) and breastfeed (P < 0.0001). With respect to child's sex, ethnicity and birth weight, there were no difference between analytic and excluded samples. Table 2 shows that compared to never smokers, ever smokers were more likely to be seen in mothers who had younger age (P < 0.0001), were less edu- cated than bachelor's degree (P < 0.0001), living single (P < 0.0001), at or below poverty level (P = 0.001) and not breastfeeding (P < 0.0001). The distribution of mean BMI percentile and pro- portions of overweight children described by mater- nal smoking status within 1 year before the birth and at the time of assessment were reported in Table 3. Generally, the proportion of childhood overweight (25.0%, 31.2% and 33.7% at grades 1, 3 and 6, respectively) and mean BMI percentile increased with increases in the level of school grade, suggesting a positive relationship between grade level and weight. Additionally, children of mothers who were ever smokers were more likely to be overweight than those of mothers who did not smoke (30.3% vs. 23.5%, 37.1% vs. 29.6%, 41.4% vs. 31.6% at grades 1, 3 and 6, respectively), and on average, have higher BMI percentiles. GEE results after adjusting for the covariates were reported in Table 4, which showed that maternal smoking within 1 year before birth was significantly associated with childhood overweight. That is, chil- dren of mothers who were ever smokers were more Maternal smoking and childhood overweight | 181 O R IG IN A L R E S E A R C H © 2012 The Authors Pediatric Obesity © 2012 International Association for the Study of Obesity. Pediatric Obesity 8, 178–188 likely to be overweight (OR = 1.39, 95% CI: 1.01, 1.94) and have higher BMI percentile (b = 4.46, P = 0.036) from grades 1 through 6 than children of mothers who were never smokers during the year before the birth. Additionally, two covariates, mater- nal education and birth weight of offspring were sig- nificantly associated with childhood overweight. In this respect, children of mothers with less than a bachelor degree were more likely to be overweight (OR = 1.41, 95% CI: 1.05, 1.91) and children with higher birth weight (in kilograms) were also likely to be overweight (OR = 1.99, 95% CI: 1.52, 2.61). All other covariates were not significant. Discussion Tobacco use during pregnancy is a major public health issue due to the negative effects on both the mother and offspring (4). While maternal prenatal smoking is known to be linked with negative health effects on offspring, such as low birth weight (31), evidence of its effects on the weight of offspring is still sparse. Our study investigated effects of whether the mother had ever smoked within 1 year before the birth of the target child on the weight of the child during school ages. Consistent with the existing lit- erature that linked smoking during pregnancy with Table 1 Comparison of maternal and child characteristics of the study sample in the analytic sample with those not included due to incomplete data Analytic sample* Not in analytic sample† P Overall [n (%)] 1041 (76.3) 323 (23.7) Maternal characteristics Smoking status 1 year before birth‡ 0.002 Ever smoker 229 (22.0) 50 (33.8) Never smoker 812 (78.0) 98 (66.2) Age§ Mean age at delivery, years (SD) 28.6 (5.5) 26.5 (5.7) <0.0001 Education‡ Bachelor's degree or above (%) 410 (39.4) 72 (22.4) Less than a bachelor's degree (%) 631 (60.6) 250 (77.6) Living status‡ 0.001 Living single (%) 133 (12.8) 65 (20.2) Not living single (%) 906 (87.2) 257 (79.8) Poverty level‡ <0.0001 At or below poverty line (%) 176 (17.9) 97 (33.2) Above poverty line (%) 805 (82.1) 195 (66.8) Breastfeeding status‡ <0.0001 Not breastfeeding (%) 396 (38.0) 191 (59.1) Breastfeeding (%) 645 (62.0) 132 (40.9) Offspring characteristics Sex‡ 0.096 Male (%) 525 (50.4) 180 (55.7) Female (%) 516 (49.6) 143 (44.3) Ethnicity‡ 0.099 Whites (%) 848 (81.5) 249 (77.1) Blacks (%) 123 (11.8) 53 (16.4) Others (%) 70 (6.7) 21 (6.5) Birth weight§ Mean birth weight, grams (SD) 3503.2 (511.4) 3445.5 (489.0) 0.332 *Subjected included in analytic sample (n = 1041). Of these, 1 was missing data on living single status, 60 were missing data on maternal poverty level. †Subjects excluded due to incomplete data on childhood overweight in school ages and children whose mothers were missing information on their smoking behaviours within 1 year before birth (n = 323). Of these, 2 were missing data on living single status, 31 were missing data on maternal poverty level, and 1 was missing data on maternal education. ‡Chi-square (c2) test was used for P-value. §T-test was used for P-value. 182 | L. Wang et al. O R IG IN A L R E S E A R C H © 2012 The Authors Pediatric Obesity © 2012 International Association for the Study of Obesity. Pediatric Obesity 8, 178–188 childhood overweight and obesity (1,23), our study discovered a higher prevalence of overweight among children of mothers who ever smoked within 1 year before the birth. After adjusting for covariates, GEE results showed that maternal smoking within 1 year before birth significantly increased the likelihood of overweight by 1.39 times, suggesting the need for smoking cessation programmes to encourage mothers to abstain from smoking at least a year before the birth of the target child. Although most of the covariates (maternal and off- spring characteristics) in our study were not signifi- cantly associated with childhood overweight, the two significant ones, the level of education and birth Table 2 Characteristics of the analytic sample by maternal smoking status* within 1 year before the birth (n = 1041) Never smoker Ever smoker P Overall [n (%)] 812 (78) 229 (22) Maternal characteristics Age† <0.0001 Mean age at delivery, years (SD) 29.1 (5.4) 26.8 (5.6) Education‡ <0.0001 Bachelor's degree or above (%) 372 (45.8) 38 (16.6) Less than bachelor's degree (%) 440 (50.2) 191 (83.4) Living status‡ <0.0001 Living single (%) 84 (10.4) 49 (21.4) Not living single (%) 726 (89.6) 180 (78.6) Poverty level‡ 0.001 At or below poverty line (%) 122 (15.8) 54 (26.1) Above poverty line (%) 652(84.2) 153 (73.9) Breastfeeding status‡ <0.0001 Not breastfeeding (%) 282 (34.7) 114 (49.8) Breastfeeding (%) 530 (65.3) 115 (50.2) Offspring characteristics Sex‡ 0.60 Male (%) 406 (50.0) 119 (52.0) Female (%) 406 (50.0) 110 (48.0) Ethnicity‡ 0.28 Whites (%) 662 (81.5) 186 (81.2) Blacks (%) 100 (12.3) 23 (10.0) Others (%) 50 (6.2) 20 (8.7) Birth weight† 0.01 Mean birth weight, grams (SD) 3524.9 (516.2) 3426.3 (487.4) Note: Number of missing observations: single = 2; poverty = 60. *Mothers were interviewed at children 24 months after birth for their smoking status within 1 year before the birth. †t test was used, the numbers indicate mean �standard deviation (SD). ‡chi-square ( c2) test was used, the numbers indicate percentage values. Table 3 Distribution of mean BMI-P* and proportions of overweight children by maternal prenatal smoking status† and time of assessment (n = 1041) Time Never smoker Ever smoker Total n BMI_P* Overweight‡ (%) n BMI_P* Overweight‡ (%) n BMI_P* Overweight‡ (%) Grade 1 756 61.9 23.5 208 65.6 30.3 964 62.7 25.0 Grade 3 706 63.8 29.6 197 67.8 37.1 903 64.7 31.2 Grade 6 693 62.3 31.6 186 69.7 41.4 879 63.9 33.7 *A standardized protocol to measure child's weight and height was used at all three times (grades 1, 3, 6). Body mass index (BMI) was calculated by [BMI = weight (kg)/height (m)2]. †Mothers were interviewed at children 24 months after birth for their smoking status within 1 year before the birth. ‡Overweight was defined as a BMI-for-age above the 85th percentile of the Centers for Disease Control and Prevention sex-specific BMI-for-age growth charts (35). BMI-P, body mass index percentile. Maternal smoking and childhood overweight | 183 O R IG IN A L R E S E A R C H © 2012 The Authors Pediatric Obesity © 2012 International Association for the Study of Obesity. Pediatric Obesity 8, 178–188 weight of offspring, need attention. While the evi- dence linking socioeconomic status of mother and overweight or obesity of children is still not obvious (21,44), it was discovered in our study that a mother not having a bachelor degree significantly increases the likelihood of childhood overweight by 1.41 times. This finding suggests that education, being a driving determinant of socioeconomic status, may be a predictor for increased risk of overweight among off- spring, especially as mothers with lower socioeco- nomic status tend to smoke more. On the issue of birth weight, our finding is consistent with the extant literature that higher birth weight is associated with overweight and obesity in childhood (45). This result suggests the importance of attending to nutritional needs of children born with higher BMIs. Lastly, results on breastfeeding are worthy of consideration as the evidence of its effects on childhood overweight and obesity is not conclusive (46,47). The results of our study suggest that breastfeeding is probably a protective practice for childhood overweight. In general, the findings in our study are consistent with previous epidemiological studies on the effects of maternal prenatal smoking on the overweight status of children (21) and our contribution to this literature pertains to the effect of mothers smoking within 1 year before the birth of the target child. Because our study assessed maternal smoking Table 4 Longitudinal analysis of mean BMI-P and over- weight status from grades 1 through 6 using GEE* (n = 1041) BMI-P† Overweight status‡ b SE P OR 95% CI P Maternal smoking status d Never smoker (reference) Ever smoker 4.46 2.12 0.036 1.39 1.01–1.94 0.047 Maternal characteristics Age Mean age at delivery, years -0.22 0.18 0.235 0.98 0.96–1.01 0.189 Education Bachelor's degree or above (reference) Less than bachelor's degree 2.25 1.95 0.249 1.41 1.05–1.91 0.025 Living status Not living single (reference) Living single 1.33 3.46 0.701 0.90 0.53–1.54 0.710 Poverty level Above poverty line (reference) At or below poverty line 1.88 2.72 0.490 0.93 0.62–1.39 0.72 Breastfeeding status Not breastfeeding (reference) Breastfeeding -3.10 1.85 0.093 0.78 0.59–1.04 0.087 Offspring characteristics Sex Females (reference) Males -0.41 1.66 0.805 1.06 0.82–1.37 0.672 Ethnicity Whites (reference) Blacks 5.63 3.02 0.062 1.48 0.94–2.32 0.087 Others 0.08 3.72 0.983 1.11 0.67–1.83 0.699 Birth weight (kg) 11.35 1.64 <0.0001 1.99 1.52–2.61 <0.0001 *Analysis of the GEE parameter estimates was based on the use of first order auto-regressive working correlation [AR(1)] structure, with BMI_P as continuous outcome and overweight as dichotomous outcome, respectively. †A standardized protocol to measure child's weight and height was used at all 3 times (grades 1, 3, 6). BMI was calculated by [BMI = weight (kg)/height (m)2]. ‡Overweight was defined as a BMI-for-age above the 85th percentile of the Centers for Disease Control and Prevention sex-specific BMI-for-age growth charts (35). dMothers were interviewed at children 24 months after birth for their smoking status within 1 year before the birth. BMI_P, body mass index percentile; CI, confidence interval; GEE, generalized estimating equations; OR, odds ratio; SE, standard error. 184 | L. Wang et al. O R IG IN A L R E S E A R C H © 2012 The Authors Pediatric Obesity © 2012 International Association …

Place your order now for a similar assignment and have exceptional work written by one of our experts, guaranteeing you an A result.

Need an Essay Written?

This sample is available to anyone. If you want a unique paper order it from one of our professional writers.

Get help with your academic paper right away

Quality & Timely Delivery

Free Editing & Plagiarism Check

Security, Privacy & Confidentiality