Students may pick any epidemiological article to practice on the following questions ??? 1. Research objective and study rationale a. What is the p
Students may pick any epidemiological article to practice on the following questions
1. Research objective and study rationale
a. What is the primary research objective of this study?
b. What is the rationale for this objective (i.e., the reason(s) that this objective is important to achieve)?
c. In terms of public health importance and contribution to knowledge, how strong is the rationale for this study and how well is it presented by the authors (e.g., conceptual framework, supporting evidence, logic)?
d. How well grounded is the rationale in the published literature (biological, epidemiological)?
2. Key variables, measures, and data collection modes
a. What are the key variables and what are their roles (e.g., primary outcome [“disease”] or dependent variables, “exposure” or study factors, major potential confounders and other covariables)?
b. How are these variables defined and measured?
c. What are the major modes by which data are being collected? (e.g., self-administered questionnaire, interviewer-administered questionnaire, medical record review, biological specimens, etc.)
d. How suited are these variables, their definitions, their measurement methods, and the data collection modes for the objectives and rationale of this study? Would other ones have been better for meeting the objectives? If yes, which variables and/or methods and why?
3. Study conduct and quality control
a. How has the study population been recruited (e.g., patients in a clinic, volunteers to advertisements, random digit dialing, area sampling of households, etc.)? If different groups of participants are recruited through different mechanisms (e.g., cases and controls, exposed and unexposed), provide this information for each primary group).
b. What steps were taken to minimize non-participation and selective factors in recruitment? In retention? How effective were these steps?
c. How successful, overall, was the data collection? What major steps were taken to improve and
document the accuracy of the data collected?
4. Study design and study population
a. Identify the important design features of the study, such as its basic design, or architecture (e.g., case-control, cohort, etc.) and how the design is implemented (e.g., incident vs. prevalent cases, randomization by group, whether data are collected multiple times, what follow-up or any is involved, how follow-up if any is carried out, etc.])
b. Compared to other reasonable choices, what are the advantages and disadvantages of this study design and its features for the specific objective(s) or question(s) of this study?
c. What is the study population for this investigation?
d. What are the major eligibility criteria (inclusion and/or exclusion criteria)?
e. How suited is this choice of study population, including eligibility criteria, for the objectives of the study?
5. Data analysis
a. What are the primary data analysis strategies and/or methods used in the study (e.g., stratified analysis, mathematical modeling, graphical analysis)?
b. How are the primary variables coded for analysis? (e.g., as binary or dichotomous variables, in categories, as ordered categories, as counts, as continuous measures?)
c. What were the primary statistical parameters (measures) estimated in the data analysis (e.g., means, prevalences, incidences, incidence rate ratios, odds ratios, survival curves)?
d. How well suited is the choice of these parameters to the objectives of the study? Are there other parameters that you think should have been estimated?
e. How many participants are included in the primary analyses, and what percentage do they
constitute of the people who were eligible and selected for inclusion? Have a substantial number of observations been dropped from the analyses? Do drop-outs pose any limitations to the final conclusion?
f. How well do the authors deal with issues of multi-causation (e.g., measurement of and control for potentially confounding variables, investigation of important interactions)? Do the authors analyze the data separately in respect to a major variable to assess similarity or differences?
6. Findings
a. What are the main findings, including both those related to the primary study question(s) and other important results?
b. Are there particular results you regard as most important?
c. How well have the authors reported and presented their findings?
d. Are there additional results or analyses that you believe should have been reported, data that should have been shown?
e. Are extraneous results presented?
7. Potential concerns in interpreting the findings
a. How completely do the authors account for the disposition of all prospective members of the study population (e.g., persons sampled but not contacted, refusals, exclusions from analysis, etc.)
b. Does the study population seem to reflect the target population well? What sources of selection bias, if any, are likely to be a problem?
c. What are the major possible sources of bias and other threats to validity that are important for interpreting the findings?
d. How well did the authors discuss these threats to validity? Did the authors present them objectively, evaluate their likely importance, and provide evidence in support of that evaluation? Did the authors conduct any specific analyses to evaluate reliability, validity, selection bias, social desirability, or information bias? What were the results of these analyses?
8. Conclusions, implications, and recommendations
ff. What are the primary conclusions? Are they stated clearly?
a. How well are they supported by the findings and discussion?
b. How directly do the conclusions relate to the primary study objective and rationale?
c. How well did the authors address implications of their study and/or give insightful recommendations for next steps.
9. Overview of strengths and limitations
a. What were the key strengths of this study in regard to its objective and accomplishments?
b. Has the study taken advantage of new methodology?
c. Do these strengths or new methodology advance the field? How?
d. What were the key limitations of this study in regard to its objective(s) and
accomplishments?
e. Are these limitations shared by other studies of this topic?
f. What would be needed to overcome these limitations?
10. Linkage with previous knowledge
a. How well did the authors compare their results to the findings from other relevant studies?
How well did the authors discuss reasons for differences between previous findings and their own?
b. How well did the authors evaluate the evidence concerning the study objective or question in regard to possible biological or other mechanisms that could account for their findings and other criteria for causal inference (for this question, please ignore concerns about bias)?
c. How relevant and responsive to the study rationale was this discussion?
d. In what ways, if any, have the authors advanced previous knowledge?
Early Life Exposures
Parental smoking during pregnancy and the risk
of gestational diabetes in the daughter
Wei Bao,1,2 Karin B Michels,3,4,5 Deirdre K Tobias,6,7 Shanshan Li,1
Jorge E Chavarro,3,4,7 Audrey J Gaskins,7 Allan A Vaag,8
Frank B Hu3,4,7 and Cuilin Zhang1*
1Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child
Health and Human Development, Rockville, MD, USA, 2Department of Epidemiology, University of Iowa
College of Public Health, Iowa City, IA, USA, 3Department of Epidemiology, Harvard T.H. Chan School of
Public Health, Boston, MA, USA, 4Channing Division of Network Medicine, 5Department of Obstetrics,
Gynecology and Reproductive Biology, 6Division of Preventive Medicine, Brigham and Women’s
Hospital and Harvard Medical School, Boston, MA, USA, 7Department of Nutrition, Harvard T.H. Chan
School of Public Health, Boston, MA, USA and 8Department of Endocrinology, Rigshospitalet,
Copenhagen, Denmark
*Corresponding author. Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy
Shriver National Institute of Child Health and Human Development, National Institutes of Health, 6100 Executive Blvd,
Rockville, MD 20852, USA. E-mail: [email protected]
The abstract of this study was included in poster presentation at the American Heart Association’s EPI/Lifestyle2015
Scientific Sessions (March 3–6, 2015, Baltimore, MD).
Accepted 19 November 2015
Abstract
Background: Fetal exposure to parental smoking may have long-term impact on the de-
velopment of disease in adulthood. We examined the association of parental smoking
during pregnancy with risk of gestational diabetes mellitus (GDM) in the daughter.
Methods: We included 15 665 singleton pregnancies from 10 152 women in the Nurses’
Health Study II cohort whose mothers participated in the Nurses’ Mothers’ Cohort Study.
Data on maternal and paternal smoking during pregnancy and associated covariates
were recalled by the mothers. GDM diagnosis was self-reported by the daughters
and was validated by medical record review in a previous study. We used log-binomial
models with generalized estimating equations to estimate relative risks (RRs) and 95%
confidence intervals (CIs).
Results: We observed a positive association between maternal heavy smoking during
pregnancy and risk of GDM in the daughter. The multivariable-adjusted RRs (95% CIs) of
GDM among women whose mothers did not smoke during pregnancy, continued smoking
1–14, 15–24, and�25 cigarettes/day were 1.00 (reference), 1.05 (0.81–1.35), 1.27 (0.95–1.70) and 1.98 (1.18–3.30), respectively (P for trend¼0.01). Further adjustment for the women’s perinatal variables, adult-life characteristics and body mass index during various periods
of life modestly attenuated the association. No association was observed between pater-
nal smoking during the pregnancy period and risk of GDM in the daughter.
Published by Oxford University Press on behalf of International Epidemiological Association 2016.
This work is written by US Government employees and is in the public domain in the US. 160
International Journal of Epidemiology, 2016, 160–169
doi: 10.1093/ije/dyv334
Advance Access Publication Date: 9 January 2016
Original article
D ow
nloaded from https://academ
ic.oup.com /ije/article-abstract/45/1/160/2363826 by U
niversity of Texas at Tyler user on 10 February 2020
Conclusions: Maternal heavy smoking (�25 cigarettes/day) during pregnancy was associ- ated with higher risk of gestational diabetes in the daughter. Further studies are warranted
to confirm our findings and to elucidate the underlying mechanisms.
Key words: Gestational diabetes mellitus, maternal smoking during pregnancy
Introduction
The developmental origins of health and disease hypothesis,
or ‘Barker hypothesis’,1 continues to fuel research interest in
examining the health consequences of in utero exposures.
Maternal smoking during pregnancy represents a common
deleterious fetal exposure in many populations.2–4 The
short-term effects of maternal smoking during pregnancy on
multiple adverse pregnancy and perinatal outcomes, includ-
ing fetal growth restriction and low birthweight, have long
been recognized and established.5 Maternal smoking during
pregnancy has also been associated with an increased risk of
obesity during childhood and adulthood in some, although
not all, studies.6–10 There is limited evidence regarding the
long-term impact of fetal exposure to maternal smoking on
the risk of chronic disease in adulthood, which emerges as a
new focus of research interests.11
Gestational diabetes mellitus (GDM) is a common preg-
nancy complication characterized by glucose intolerance,
with onset or first recognition during pregnancy.12 GDM is
not only associated with short-term adverse perinatal out-
comes,13 but also related to long-term metabolic risk in both
mothers and their children.12,14,15 Thus, it is crucial to iden-
tify modifiable risk factors that may contribute to the preven-
tion of GDM in current and subsequent generations.
Animal studies have suggested that fetal exposure to maternal
smoking may lead to impaired glucose metabolism by alter-
ing pancreatic islet development and inducing beta cell apop-
tosis.16,17 In addition, epidemiological studies, although still
limited, suggest that maternal smoking during pregnancy
may increase the risk of diabetes in adulthood.18,19 However
the association, in particular the dose-response relation, be-
tween fetal exposure to maternal smoking and risk of GDM
is not well established. Moreover, no previous study has
examined the association between fetal exposure to paternal
smoking, a major source of maternal passive smoking, and
subsequent risk of GDM. In this study, we aimed to examine
the dose-response relation of maternal and/or paternal smok-
ing during pregnancy with risk of GDM in the daughter.
Methods
Study population
The Nurses’ Health Study II (NHSII) is an ongoing prospect-
ive cohort study of 116 430 female nurses aged 24–44 years
at study inception in 1989. The participants receive a biennial
questionnaire regarding lifestyle behaviours, anthropometric
variables and disease outcomes. In 2001, mothers of the
NHSII participants were invited to complete a questionnaire
regarding their nurse daughter. Details about the Nurses’
Mothers’ Cohort Study have been described elsewhere.20 We
included NHSII participants in the current analyses if they re-
ported at least one singleton pregnancy lasting greater than 6
months between 1989 and 2001 and their mothers partici-
pated in the Nurses’ Mothers’ Cohort Study and reported
data on pregnancy and perinatal variables associated with
the nurse daughter. The NHSII participants were excluded if
they had been adopted, were missing information on mater-
nal smoking or had type 2 diabetes reported in 1989 or be-
fore GDM. Figure 1 depicts the flowchart of study
participants. This study has been approved by the Partners
Human Research Committee (Boston, MA), with partici-
pants’ consent implied by the return of the completed
questionnaires.
Assessment of parental smoking
We used information on parental smoking during pregnancy
from the 2001 Nurses’ Mothers’ Cohort Study question-
naire.21 The mothers reported whether they ever smoked
cigarettes during pregnancy with the nurse daughter, the
number of cigarettes (i.e. 1–14, 15–24, 25–34 or� 35) they
Key Messages
• This study examined the association of parental smoking during pregnancy with risk of gestational diabetes in the
daughter among 15 665 singleton pregnancies from 10 152 women in the Nurses’ Health Study II cohort whose moth-
ers participated in the Nurses’ Mothers’ Cohort Study.
• We demonstrated that maternal heavy smoking (�25 cigarettes/day) during pregnancy was associated with higher risk of gestational diabetes in the daughter. We did not observe an association between paternal smoking during
pregnancy and risk of gestational diabetes in the daughter.
International Journal of Epidemiology, 2016, Vol. 45, No. 1 161
D ow
nloaded from https://academ
ic.oup.com /ije/article-abstract/45/1/160/2363826 by U
niversity of Texas at Tyler user on 10 February 2020
smoked daily during pregnancy, whether they quit smoking
during pregnancy, and if so, in which trimester. In a separ-
ate validation study, the validity of recalled maternal smok-
ing during pregnancy was found to be high in the National
Collaborative Perinatal Project (sensitivity¼0.86, specifi- city¼0.94).22 We categorized maternal smoking as: never smoked; quit smoking in first trimester of pregnancy; con-
tinued smoking 1–14 cigarettes/day during pregnancy; con-
tinued smoking 15–24 cigarettes/day during pregnancy; and
continued smoking 25 or more cigarettes/day during preg-
nancy. We also asked the mothers whether the nurse’s father
ever smoked during pregnancy and the number of cigarettes
he smoked. We categorized paternal smoking as: never
smoked; smoked 1–14 cigarettes/day during pregnancy;
smoked 15–24 cigarettes/day during pregnancy; and
smoked 25 or more cigarettes/day during pregnancy.
Previous studies based on the same cohort as the current
analysis have found maternal smoking during pregnancy be
associated with an increased risk of overweight and obesity
in the daughter across adolescence and adult life.7
Ascertainment of gestational diabetes
The NHSII participants (i.e. the daughters) reported preva-
lent GDM in 1989 and incident GDM on each biennial
questionnaire through 2001. GDM was not ascertained
after the 2001 questionnaire in the NHSII cohort, because
the majority of NHSII participants had passed reproduct-
ive age by then. In a previous validation study among a
subgroup of the NHSII cohort, 94% of GDM self-reports
were confirmed by medical records.23 In a random sample
of parous women without GDM, 83% reported a glucose
screening test during pregnancy and 100% reported fre-
quent prenatal urine screenings, suggesting a high level of
GDM surveillance in this cohort.23
Covariates assessment
Covariates for maternal, paternal and perinatal characteris-
tics were obtained from the Nurses’ Mothers’ Cohort Study.
The 2001 Nurses’ Mothers’ Cohort Study questionnaire re-
quested data on the daughter’s gestational age at birth, birth-
weight and breastfeeding status, maternal and paternal age
at birth of the daughter, educational level, occupation and
home ownership at the time of the daughter’s birth, maternal
height, maternal pre-pregnancy weight, weight gain during
pregnancy (< 10, 10–14, 15–19, 20–29, 30–40, > 40
pounds; to convert pounds into kilograms, multiply pounds
by the conversion factor 0.453592.), paternal weight, pater-
nal height, maternal consumption of alcoholic beverages dur-
ing pregnancy, and the occurrence of maternal pregnancy
Nurses’ Health Study II cohort (n = 116 430)
Inclusion criteria: pregnancy ≥ 6 months 1989-2001 (NHSII)
(n = 10 862)
Exclusion criteria: • Nurses were adopted (NMS): n = 34 • Missing data on parental smoking (NMS): n = 643 • T2DM at baseline or before GDM (NHSII): n = 6 • Missing main questionnaire (NHSII): n = 33 • Missing data on the daughters’ smoking status
(NHSII): n = 76
Analytical population (n = 10 152)
Mothers participated in the Nurses’ Mothers’ Cohort Study
(n = 35 794)
Figure 1. The flowchart of study participants. Exclusion criteria are not mutually exclusive and individual reasons may not total the number of
excluded participants. GDM denotes gestational diabetes mellitus; NHSII, Nurses’ Health Study II; NMS, Nurses’ Mothers’ Cohort Study; T2DM, type
2 diabetes mellitus.
162 International Journal of Epidemiology, 2016, Vol. 45, No. 1
D ow
nloaded from https://academ
ic.oup.com /ije/article-abstract/45/1/160/2363826 by U
niversity of Texas at Tyler user on 10 February 2020
complications (gestational diabetes and preeclampsia) during
the pregnancy of the daughter.
Covariates related to the daughters’ characteristics were
obtained from the NHSII questionnaires. The 1989 NHSII
questionnaire assessed the daughters’ age, height, race/ethni-
city and family history of diabetes at baseline. The daugh-
ters’ weight at 18 years old and current weight, parity, and
smoking status (including the number of cigarettes per day)
were self-reported from the 1989 NHSII questionnaire and
were updated with data from each biennial questionnaire
cycle. Self-reported weight was highly correlated with meas-
ured weight (r¼0.97) in a previous validation study.24
Body mass index (BMI) was computed as weight in kilo-
grams divided by height in metres squared. Dietary intake
was collected every 4 years since 1991 using a previously
validated semi-quantitative food frequency question-
naire.25–27 To assess the overall diet quality of the partici-
pants, we derived a diet score, the Alternate Healthy Eating
Index 2010 (AHEI-2010) for each participant, as previously
described.28 The overall AHEI-2010 ranged from 0 to 110
points, with a higher score indicating a better diet quality.
Physical activity was ascertained in 1989, 1991, 1997 and
2001 by frequency of engaging in common recreational
activities, from which metabolic equivalent (MET)-hours
per week were derived. The questionnaire-based estimates
of total physical activity correlated well with detailed activ-
ity diaries in a previous validation study (r¼0.56).29
Cumulative average of physical activity, total energy intake
and AHEI-2010 score were calculated for each individual at
each time period throughout the follow up, to reduce
within-subject variation and represent long-term habitual
diet and physical activity.30
Statistical analysis
We used log-binomial models with generalized estimating
equations to estimate the relative risks (RRs) and 95% confi-
dence intervals (CIs) of GDM for maternal and paternal
smoking, separately and jointly. Generalized estimating equa-
tions allowed us to account for correlations among repeated
observations (pregnancies) contributed by a single participant
(i.e. the nurse daughter). In the multivariable regression mod-
els, we adjusted for: age and race/ethnicity of the daughters
(Model 1); and additionally for maternal and paternal vari-
ables including maternal and paternal age at time of daugh-
ter’s birth, maternal pre-pregnancy BMI, paternal BMI,
maternal weight gain during pregnancy, maternal pregnancy
complications (gestational diabetes, preeclampsia) and mater-
nal alcohol consumption during pregnancy (Model 2); for the
daughters’ perinatal variables including gestational age at
birth, birthweight, and breastfeeding status (Model 3); for
the daughters’ adult life variables including parity, family
history of diabetes, cigarette smoking, total energy intake,
overall diet quality (i.e. Alternate Healthy Eating Index) and
physical activity (Model 4); for the daughters’ BMI at 18
years old (Model 5); and for the daughters’ pre-pregnancy
BMI (Model 6). We mutually adjusted for maternal and pa-
ternal smoking during pregnancy in all these models. Wald
tests were used to assess the differences between maternal
and paternal associations. The daughters’ BMI and other
adult life covariates were updated during the follow-up.
When categorizing each categorical covariate, we created a
category for missing data. We considered Model 3–Model 6
as sensitivity analyses, because the daughter’s perinatal vari-
ables, adult-life variables and adulthood BMI in these models
are potential intermediates or explanatory variables for the
associations of maternal and paternal smoking during preg-
nancy with the risk of GDM. Tests for linear trend were per-
formed across the categories of the number of cigarettes
smoked for mothers who continued to smoke throughout
pregnancy, with non-smoking during pregnancy as the refer-
ence group (for maternal smoking, the test for trend excluded
the category of mothers who quit smoking during preg-
nancy). Statistical analyses were performed using the SAS
statistical software version 9.2 (SAS Institute Inc., Cary, NC)
and the Stata statistical software version 14.0 (StataCorp LP,
College Station, TX).
Results
We included 15 665 singleton pregnancies from 10 152
women in the Nurses’ Health Study II cohort whose mothers
participated in the Nurses’ Mothers’ Cohort Study. Of them,
736 GDM pregnancies were documented. Characteristics of
mothers, fathers and daughters are shown in Table 1 accord-
ing to maternal smoking status during pregnancy. Mothers
who smoked more frequently during pregnancy were more
likely to consume alcoholic beverages during the pregnancy.
The biological fathers of the daughters whose mothers
smoked during pregnancy were also more likely to smoke
during the pregnancy. Women who were exposed to frequent
maternal smoking during pregnancy had a lower birthweight,
were less likely to be breastfed and were heavier and more
likely to smoke in adulthood.
We observed a dose-response relation between in utero
exposure to maternal smoking and risk of GDM (Table 2).
After adjustment for the daughter’s age, race/ethnicity and
maternal and paternal variables, the RRs (95% CIs) of GDM
among women whose mothers did not smoke during preg-
nancy or continued smoking 1–14, 15–24 or � 25 cigarettes/ day were 1.00 (reference), 1.05 (0.81–1.35), 1.27
(0.95–1.70) and 1.98 (1.18–3.30), respectively (P for
trend¼0.02). Further adjustment for the daughter’s perinatal variables and adult life variables, including pre-pregnancy
International Journal of Epidemiology, 2016, Vol. 45, No. 1 163
D ow
nloaded from https://academ
ic.oup.com /ije/article-abstract/45/1/160/2363826 by U
niversity of Texas at Tyler user on 10 February 2020
BMI, only slightly changed the association. No association
was observed between paternal smoking during pregnancy
and the risk of GDM (Table 3). Wald tests showed suggestive
statistical evidence that the maternal smoking associations
may differ from the paternal smoking associations with
GDM risk (P¼0.10). We further examined the joint effect of both maternal and paternal smoking during pregnancy on
the risk of GDM. Women whose mother or both parents
smoked during pregnancy � 15 cigarettes/day had a higher risk of GDM (RR 1.43, 95% CI 1.11–1.85), compared with
women whose parents did not smoke during pregnancy or
smoked < 15 cigarettes/day (Supplementary Figure 1, avail-
able as Supplementary data at IJE online).
In an analysis on the joint effect of maternal smoking
during pregnancy and the participants’ smoking during
adulthood, we found that the women who smoked < 15
cigarettes/day and whose mothers smoked � 15 cigarettes/ day during pregnancy had an RR (95% CI) of 1.28 (1.00–
1.64) for GDM, compared with neither the mothers nor
the participants smoking � 15 cigarettes/day (Figure 2). We also performed a stratified analysis according to the
daughters’ own smoking status. Among the daughters who
never smoked, the adjusted RRs (95% CIs) of GDM were
1.30 (0.79–2.13), 0.94 (0.67–1.32), 1.13 (0.77–1.65) and
2.15 (1.19–3.88) for the daughters whose mothers smoked
but quit smoking in the first trimester, continued smoking
Table 1. Age-standardized maternal, paternal, and the daughter’s characteristics by maternal smoking status during pregnancya
Maternal cigarette smoking during pregnancy
Non-smoker Quit smoking in
the first trimester
Continued smoking
1–14 cigarettes/day
Continued
smoking 15–24
cigarettes/day
Continued smoking
�25 cigarettes/day
Number of participants 7478 373 1369 793 139
Maternal characteristics
Age at daughter’s birth (years) 26.68 (4.83) 25.33 (4.34) 26.39 (4.75) 26.23 (4.66) 26.90 (4.65)
Prepregnancy BMI (kg/m2) 21.41 (2.60) 21.00 (2.26) 20.88 (2.46) 21.09 (2.70) 21.24 (2.61)
Attended college (%) 40.21 47.11 43.04 40.89 46.57
Ever consumed alcoholic beverages
during pregnancy (%)
25.03 44.82 60.43 63.59 63.68
Pregnancy complicationsb (%) 4.03 4.26 3.90 3.84 3.44
Paternal characteristics
Age at daughter’s birth (years) 28.70 (4.78) 27.85 (4.68) 28.59 (4.67) 28.57 (4.64) 29.63 (4.52)
BMI at daughter’s birth (kg/m2) 23.80 (2.81) 23.86 (3.08) 23.78 (2.80) 23.72 (2.83) 23.40 (2.75)
Attended college (%) 45.90 54.68 51.51 48.45 57.90
Ever smoked during pregnancy (%) 44.61 71.72 73.86 78.26 74.26
Characteristics of the daughter in early life
Gestational age at birth (weeks) 39.42 (2.26) 39.55 (2.32) 39.32 (2.40) 39.12 (2.54) 39.25 (2.54)
Birthweight (g) 3358.28 (493.41) 3291.89 (491.44) 3176.63 (498.50) 3070.21 (514.39) 3056.42 (523.58)
Caucasian (%) 95.05 95.42 96.03 95.84 95.86
Breastfed during infancy (%) 43.46 47.81 32.07 34.65 23.07
Characteristics of the daughter
during adulthoodc
Age in 1989 (years) 30.62 (3.42) 30.57 (3.27) 30.85 (3.42) 30.33 (3.31) 30.40 (3.29)
BMI (kg/m2) 22.81 (3.93) 23.01 (4.01) 22.87 (3.64) 23.32 (4.13) 23.64 (4.66)
Nulliparous (%) 7.68 7.50 6.02 8.21 5.81
Family history of diabetes (%) 10.08 8.51 8.60 7.55 7.88
Current smoking (%) 6.54 11.06 10.86 11.36 10.95
Alcohol intake (g/day) 2.55 (4.67) 3.15 (4.79) 3.42 (5.74) 3.30 (5.66) 3.33 (6.12)
Physical activity (MET-h/week) 25.88 (36.49) 26.26 (38.56) 27.59 (37.17) 28.19 (44.22) 28.31 (34.78)
Total energy intake (kcal/day) 1882.42 (545.50) 1837.95 (522.48) 1871.40 (549.03) 1850.16 (540.46) 1873.85 (559.33)
AHEI-2010d 47.42 (10.67) 48.72 (10.70) 48.38 (11.09) 48.08 (10.56) 47.85 (10.75)
AHEI-2010 indicates Alternate Healthy Eating Index 2010; BMI, body mass index; MET, metabolic equivalent. aValues are means (standard deviations) for continuous variables and percentages for categorical variables and are standardized to age distribution of the
NHSII participants (i.e. the daughters). bMaternal pregnancy complications included gestational diabetes and preeclampsia. cAdulthood characteristics are provided for 1989, except diet information (i.e. total energy intake, alcohol intake and the derived alternate healthy eating
index) which was first collected in the Nurses’ Health Study II cohort in 1991. dAHEI-2010 was derived for each participant, as previously describe,28 to assess the overall diet quality of the participants.
164 International Journal of Epidemiology, 2016, Vol. 45, No. 1
D ow
nloaded from https://academ
ic.oup.com /ije/article-abstract/45/1/160/2363826 by U
niversity of Texas at Tyler user on 10 February 2020
T a b
le 2 . M
a te
rn a
l c ig
a re
tt e
s m
o k in
g d
u ri
n g
p re
g n
a n
c y
a n
d th
e ri
s k
o f
g e
s ta
ti o
n a
l d
ia b
e te
s in
th e
d a
u g
h te
r
M a te
rn a l c ig
a re
tt e
sm o k in
g d u ri
n g
p re
g n a n c y
P fo
r tr
e n d
d
N o n -s
m o k e r Q
u it
sm o k in
g in
th e
fi rs
t tr
im e st
e rC
o n ti
n u e d
sm o k in
g
1 – 1 4
c ig
a re
tt e s/
d a y
C o n ti
n u e d
sm o k in
g
1 5 – 2 4
c ig
a re
tt e s/
d a y
C o n ti
n u e d
sm o k in
g
‡ 2 5
c ig
a re
tt e s/
d a y
G D
M ca
se s/
p re
g n a n ci
es 5 2 2 /1
1 5 2 5
3 3 /5
5 9
9 5 /2
1 2 2
6 8 /1
2 3 8
1 8 /2
2 1
M o d el
1 : A
d ju
st ed
fo r
th e
d a u g h te
r’ s
a g e
a n d
ra ce
/e th
n ic
it y
1 .0
0 1 .2
6 (0
.8 4 – 1 .8
7 ) 1 .0
0 (0
.7 9 – 1 .2
8 )
1 .2
2 (0
.9 2 – 1 .6
2 )
1 .8
6 (1
.1 2 – 3 .0
9 )
0 .0
2
M o d el
2 : M
o d el
1 þ
a d d it
io n a ll y
a d ju
st ed
fo r
m a te
rn a l a n d
p a te
rn a l v a ri
a b le
sa 1 .0
0 1 .2
7 (0
.8 5 – 1 .8
9 ) 1 .0
5 (0
.8 1 – 1 .3
5 )
1 .2
7 (0
.9 5 – 1 .7
0 )
1 .9
8 (1
.1 8 – 3 .3
0 )
0 .0
1
M o d el
3 : M
o d el
2 þ
a d d it
io n a ll y
a d ju
st ed
fo r
th e
d a u g h te
r’ s
p er
in a ta
l v a ri
a b le
sb 1 .0
0 1 .2
5 (0
.8 4 – 1 .8
6 ) 1 .0
1 (0
.7 8 – 1 .3
0 )
1 .2
1 (0
.9 0 – 1 .6
3 )
1 .8
9 (1
.1 3 – 3 .1
5 )
0 .0
4
M o d el
4 : M
o d el
3 þ
a d d it
io n a ll y
a d ju
st ed
fo r
th e
d a u g h te
r’ s
a d u lt
-l if
e ch
a ra
ct er
is ti
cs c
1 .0
0 1 .2
8 (0
.8 7 – 1 .9
0 ) 1 .0
1 (0
.7 8 – 1 .3
0 )
1 .2
3 (0
.9 1 – 1 .6
5 )
1 .9
7 (1
.2 0 – 3 .2
4 )
0 .0
2
M o d el
5 : M
o d el
4 þ
a d d it
io n a ll y
a d ju
st ed
fo r
th e
d a u g h te
r’ s
B M
I a t
a g e
1 8
y ea
rs 1 .0
0 1 .2
7 (0
.8 6 – 1 .8
7 ) 1 .0
0 (0
.7 7 – 1 .2
8 )
1 .2
2 (0
.9 1 – 1 .6
4 )
1 .8
8 (1
.1 5 – 3 .0
7 )
0 .0
3
M o d el
6 : M
o d el
5 þ
a d d it
io n a ll y
a d ju
st ed
fo r
th e
d a u g h te
r’ s
m o st
re ce
n t
p re
-p re
g n a n cy
B M
I1 .0
0 1 .2
4 (0
.8 5 – 1 .8
1 ) 1 .0
0 (0
.7 8 – 1 .2
9 )
1 .1
7 (0
.8 8 – 1 .5
6 )
1 .8
5 (1
.1 2 – 3 .0
4 )
0 .0
5
P a te
rn a l sm
o k in
g d u ri
n g
p re
g n a n cy
w a s
a d ju
st ed
in a ll
th e
m o d el
s. a T
h e
m a te
rn a l a n d
p a te
rn a l v a ri
a b le
s in
cl u d ed
m a te
rn a l a n d
p a te
rn a l a g e
a t
ti m
e o f
th e
d a u g h te
r’ s
b ir
th , m
a te
rn a l p re
-p re
g n a n cy
b o d y
m a ss
in d ex
, p a te
rn a l b o d y
m a ss
in d ex
, m
a te
rn a l w
ei g h t
g a in
d u ri
n g
p re
g n a n cy
, m
a te
r-
n a l p re
g n a n cy
co m
p li ca
ti o n s
(g es
ta ti
o n a l d ia
b et
es , p re
ec la
m p si
a ),
a n d
m a te
rn a l co
n su
m p ti
o n
o f
a lc
o h o li c
b ev
er a g es
d u ri
n g
p r
Collepals.com Plagiarism Free Papers
Are you looking for custom essay writing service or even dissertation writing services? Just request for our write my paper service, and we'll match you with the best essay writer in your subject! With an exceptional team of professional academic experts in a wide range of subjects, we can guarantee you an unrivaled quality of custom-written papers.
Get ZERO PLAGIARISM, HUMAN WRITTEN ESSAYS
Why Hire Collepals.com writers to do your paper?
Quality- We are experienced and have access to ample research materials.
We write plagiarism Free Content
Confidential- We never share or sell your personal information to third parties.
Support-Chat with us today! We are always waiting to answer all your questions.
