Introduction

Lifestyle factors contributing to childhood obesity include a high-calorie diet and low levels of physical activity (PA) or physical inactivity among children [1, 2]. Children’s lifestyle choices are greatly influenced by their mothers [3, 4]. A growing body of evidence suggests that maternal lifestyle before or during pregnancy contributes to adverse offspring outcomes at birth [5] and the risk of obesity in offspring [6,7,8,9,10]. In addition, maternal behaviors such as smoking, alcohol consumption, unhealthy dietary pattern, and physical inactivity during pregnancy are also associated with offspring’s body mass index (BMI) [8,9,10,11,12].

The Developmental Origins of Health and Disease theory highlights the importance of the early-life environment, including maternal diet and lifestyle factors, on offspring health [13]. Thus optimization of maternal diet and lifestyle behaviors during critical windows of development, such as during pregnancy, may positively impact on offspring future health trajectory. Familial associations may influence offspring growth and development outcomes through shared lifestyle and social environments [13], including diet, heritable genetic, and epigenetic mechanisms [14], and for maternal lines in particular, intra-uterine and mitochondrial pathways [15]. We have recently shown that maternal line dietary quality appears to influence fetal growth, whereas paternal line dietary quality appears to influence postnatal growth [16].

The Healthy Lifestyle Score (HLS) comprising low-risk lifestyle-related factors, such as high diet quality, never smoking, moderate or vigorous PA, moderate alcohol consumption, and healthy BMI, with higher scores indicating a healthier lifestyle, has been evaluated in different populations [17,18,19,20,21]. The impact of individual and combined lifestyle factors, through HLS, on a range of health outcomes has been examined with significant beneficial effects being reported including a reduction in premature mortality and longer life expectancy [17]. Furthermore, reduced risk of primary cardiovascular disease (CVD) was identified in a Spanish population when comparing those with the highest HLS (greatest adherence to a healthy lifestyle) to those with the lowest HLS [18]. Moreover, it has been suggested that relative to individual healthy lifestyle components a composite HLS comprising a combination of multiple behaviors/factors may provide stronger protection against metabolic syndrome in Puerto Rican adults [19].

Adherence to an overall healthy lifestyle before or during pregnancy is strongly associated with reduced risk of offspring obesity in childhood, adolescence, and early adulthood compared with offspring of women who did meet any of the low-risk factors [20, 21]. A HLS in early pregnancy has been linked with greater offspring birth weight in males but lower birth weight among female offspring [5]. However little data regarding maternal associations between a composite HLS and both birth outcomes and offspring growth during childhood exist. Thus our objective was to investigate associations between a maternal HLS derive from dietary quality, smoking, alcohol intake, PA and BMI, and adverse offspring birth outcomes and childhood obesity at 5 and 9 years of age in the Lifeways Cross-Generation Cohort Study.

Methods

Participants

The Lifeways Cross-Generation Cohort Study is a prospective family study that has been described in detail elsewhere [22, 23]. The study objectives were to document health status, diet, and lifestyle in the family members and to establish patterns and links across generations. Briefly, 1124 mothers were initially recruited by a midwife during their first antenatal visit in two maternity hospitals in the Republic of Ireland between 2001 and 2003. A cohort of 1094 live infants were born to these mothers including 12 sets of twins (n = 1082 mothers). Anthropometric measures were available from 585 children at 5.4 years and 298 children at 9.8 years on average. Six hundred sixty-five mothers with available lifestyle factors, including diet based on HEI score, were included in this study. Three hundred sixty-one and 196 mothers with available healthy lifestyle factors at 5 and 9 year follow-up were also included in the study (Supplementary Table S4). The participant flow chart is shown in Supplementary Fig. S1.

Dietary intake assessment

Habitual dietary intakes of the women during the first trimester of pregnancy were assessed using a validated 149-item semi quantitative food frequency questionnaire (SQFFQ), which has been validated for use in the Irish population [24]. Participants were asked about their average consumption frequency (9 levels, from ‘never or less than once per month’ to ‘6+ per day’) of each food items during the first 12–16 weeks of pregnancy. The daily quantities of food intakes were then derived by multiplying the frequencies per day by standard portion sizes [25]. Daily energy and nutrient intakes were computed for each participant using an in-house software program (FFQ Software Ver 1.0; developed by the National Nutrition Surveillance Centre, School of Public Health, Physiotherapy and Sports Science, University College Dublin, Belfield, Dublin 4, Ireland) based on the McCance and Widdowson Food Tables [25].

In 2007–2008, when the children averaged 5 years of age, mothers were asked to repeat the health assessment questionnaire, including reported dietary intake, and to provide information also on their child’s health status, including dietary intake. Mothers responded for themselves on the same SQFFQ as earlier and again reported habitual diet for the previous year. The SQFFQ containing 52 food and drink items used for assessment of children’s diet was comparatively different and adapted from the UK National Diet and Nutrition Survey of 4.5-year-old children [26].

Maternal HLS

Our HLS included five lifestyle-related factors: diet, smoking, PA, alcohol consumption, and BMI. Diet quality was assessed with the Healthy Eating Index (HEI)-2015, the latest update diet quality index of the US Department of Agriculture [27]. The HLS of this study is a modified version of Li et al. [17]. We defined a healthy diet as a diet score in the top 40%. For smoking, we defined low risk as never smoking and the high risk as current smoking. For PA, we classified low risk as >20 min/day of combined moderate or vigorous activities (MVPA) at least 5 days per week and high risk as <20 min/day of MVPA. We defined low-risk alcohol consumption as non or moderate alcohol consumption (5–15 g/d for women) and high risk as heavy alcohol consumption (>15 g/day for women). A pre-pregnancy BMI in the range of 18.5–24.9 kg/m2 was considered as a healthy BMI. For each low-risk factor, the participant received a score of 1. If the participant did not meet the criterion, the participant was classified as high risk for that factor and received a score of 0. The sum of these 5 scores provided a total number of low-risk factors of 0, 1, 2, 3, 4, or 5, with higher scores indicating a healthier lifestyle [17].

Offspring outcomes assessment

Information on birth outcomes and infant sex were abstracted from linked hospital records. Adverse birth outcomes included low birth weight (LBW) and macrosomia, which were defined based on standard clinical cut-offs (BW < 2500 g and BW > 4000 g for LBW and macrosomia, respectively), while pre-term birth, delivery before 37 completed weeks of gestation; and post-term birth, delivery at and after 42 completed weeks of gestation [28, 29]. The children’s BMI and WC measurements at 5 and 9 years old were collected by trained researchers using standardized techniques and tools [30]. Height was measured using the Leicester portable height measure (Chasmors Ltd, London); weight by using Tanita Digital Weighing Scale (Chasmors Ltd, London); and WC was measured using a body tape with clear plastic slider (Chasmors Ltd, London) [30]. Further detailed information on the anthropometric measurements of the study’s participants has been previously published [30]. BMI was derived using the formula weight/height2 (kg/m2). Overweight and obesity in the children at age 5 and 9 were defined according to the International Obesity Task Force sex-for-age-BMI cut-offs [31]. Children with a BMI ≥ 95th percentile for age and sex were classified with obesity; those with a BMI ≥ 85th but <95th percentile for age and sex were classified as overweight [31]. A combined overweight/obesity group was additionally generated to increase sample size and statistical power of the analysis. Central obesity was defined as having age- and sex-standardized WC of over 90th percentile based on the 1990 British reference [32].

Covariates

At recruitment, mothers provided information on age, self-reported height and pre-pregnancy weight, socioeconomic status (household’s total net income per week) (proxied by eligibility to the General Medical Services Scheme, a robust indicator of social disadvantage in Ireland) [33], and highest education attainment (tertiary or no tertiary education). Maternal educational level, when pregnant (categorized as up to secondary studies and university studies), was used as a proxy of maternal socioeconomic position. Pre-pregnancy BMI was subsequently derived. Alcohol intake and cigarette smoking during pregnancy also were ascertained using the same questionnaire (current smokers/drinkers and women who have smoked/consumed alcohol in < three months’ time prior to recruitment were classified as exposed) and heavy alcohol consumption was defined as >15 g/day for women. MVPA (>20 min/day) was calculated at least 5 days per week of combined MVPA and marital status (married, cohabiting, single, separated, or divorced) were also reported. Child’s diet quality was assessed with HEI-2015. These covariates were chosen for their influence on the score and similarly to other previous studies [17,18,19,20,21,22,23].

Statistical analysis

Maternal and offspring characteristics were first summarized according to the number of healthy lifestyle factors and examined using Jonckheere test for continuous variables or χ2 test for categorical variables. Relationships between maternal HLS and individual HLS components with risk of adverse offspring birth outcomes and childhood adiposity outcomes were examined using multivariable analyses (logistic regression for binary offspring outcomes). The groups compared were 0–2 healthy lifestyle factors grouped, 3 and 4 factors relative to those with 5 healthy lifestyle factors. Potential confounders and covariates included in our analyses were maternal socioeconomic status, education and marital status, smoking and alcohol intake during pregnancy, diet quality, PA, age at recruitment, pre-pregnancy BMI, and child sex. Sensitivity analyses were performed restricting to 533 mother–child pairs for whom we have child dietary data at age 5 with additional adjustment for child dietary quality (HEI) and child PA (derived from parental reports of childhood factors at the year 5 follow-up including time spent outdoors, time spent viewing television). In addition, we conducted analyses excluding mothers diagnosed with gestational diabetes (abstracted from obstetric record). Missing covariates information was imputed using 20 multiple imputation datasets [34]. The mothers missing covariates information: maternal age (n = 52); pre-pregnancy BMI (n = 188); education status (n = 24); smoking (n = 16); alcohol intake (n = 98); economic status (n = 110); marital status (n = 9); PA (n = 123). All statistical analyses were conducted using SPSS® version 24.0 (IBM Corp., Armonk, NY, USA). Statistical significance was defined as two-sided P value < 0.05.

Results

Characteristics of the study population

Table 1 shows the characteristics of the Lifeways mothers and their offspring included in this study according to the maternal HLS. Higher number of maternal healthy lifestyle factors were associated with higher maternal age at recruitment (p < 0.05), education status, and household income (both p < 0.001). Offspring birth weight, length, and head circumference were positively associated with the number of maternal healthy lifestyle factors (p < 0.001), whereas child BMI and incidence of overweight/obesity at age 5 and 9 were negatively associated with the maternal HLS (p < 0.05). Maternal HLS was also inversely associated with offspring WC and abdominal obesity at age 9 (p = 0.05).

Table 1 Characteristics of the study population according to the number of healthy lifestyle factorsa.
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Maternal HLS, individual HLS components, and offspring birth outcomes

In multivariable adjusted logistic regression models (Supplementary Table S1), a lower overall HLS was associated with increased risk of LBW (OR: 1.15, 95% CI: 1.02–2.76, p trend = 0.04) and lower likelihood of macrosomia (OR:0.86, 95% CI:0.19–0.99, p trend = 0.025) (Fig. 1a). Individual HLS components revealed that poor maternal dietary quality, smoking, and alcohol intake were associated with increased risk of LBW (OR: 1.61, 95% CI: 1.01–7.85, p = 0.04, OR: 2.54, 95% CI: 1.26–5.12, p = 0.02 and OR: 2.30, 95%CI: 1.01–5.26, p = 0.03, respectively). Likelihood of macrosomia was greater among mothers with a pre-pregnancy BMI in the range with obesity (OR:2.18,95% CI: 1.23–3.85, p = 0.04) (Table 2).

Fig. 1: Associations between maternal healthy lifestyle score and risk of adverse offspring birth outcomes and childhood overweight and obesity.
figure 1

a Multivariable analyses between maternal HLS and risk of offspring low birth weight and macrosomia. b Multivariable analyses between maternal HLS and risk of offspring childhood overweight and obesity at age 5 and 9. Values were ORs (markers) and 95% CIs (capped vertical lines) from generalized estimating equations (for offspring birth outcomes and overweight and obesity at age 5 and 9) and logistic regression with reference to 5 healthy lifestyle factors. 0–2: 0, 1, 2 grouped components. *p < 0.05.

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Table 2 Maternal individual healthy lifestyle score components and risk of adverse offspring birth outcomesa.
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Maternal HLS, individual HLS components, and offspring weight status at 5 and 9 years

In multivariable adjusted logistic regression models (Supplementary Table S1), a lower overall HLS was associated with increased risk of overweight/obesity at age 5 (OR: 1.18, 95% CI: 1.01–1.29, p trend = 0.02) and at age 9 (OR: 1.21, 95% CI: 1.01–7.93, p trend = 0.04) (Fig. 1b). No significant associations were found between maternal HLS and childhood obesity at age 5 and 9 (Supplementary Table S1). Smoking during pregnancy was also linked to greater risk of childhood overweight/obesity (OR:1.91, 95% CI: 1.01–3.61, p = 0.04 at age 5 and OR: 2.14, 95% CI: 1.01–4.11, p = 0.03 at age 9) (Table 3), with childhood obesity at 5 years (OR: 2.48, 95% CI: 1.00–6.99, p = 0.03) (Table 4) and with childhood obesity and central obesity (WC > 90th) at 9 years (OR:2.59, 95% CI: 1.33–4.95, p = 0.02 and OR: 2.09, 95% CI: 1.05–7.14, p = 0.01, respectively). However, these latter associations were attenuated in the fully adjusted model (Tables 4 and 5). Maternal obesity (based on pre-pregnancy BMI) was associated with increased likelihood of childhood overweight/obesity (combined) at age 5 and 9 (OR: 2.19, 95% CI: 1.01–5.08, p = 0.03 and OR: 3.89, 95% CI: 1.00–10.59, p = 0.04, respectively) (Table 3) and to a greater extent with childhood obesity at age 5 and 9 (OR: 4.12, 95% CI: 1.36–12.50, p = 0.03 and OR: 3.52, 95% CI: 1.17–10.59, p = 0.02, respectively) (Table 4). Results from sensitivity analyses restricted to mother–child pairs with child dietary data at age 5 suggest that individual HLS component (maternal BMI and smoking) and overall HLS associations with childhood outcomes were attenuated following additional adjustment for childhood dietary quality and PA (data collected at 5 year follow-up) (Supplementary Tables S2 and S3).

Table 3 Maternal individual healthy lifestyle score components and risk of offspring overweight and obesity at 5 and 9 yearsa.
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Table 4 Maternal individual healthy lifestyle score components and risk of offspring obesity at 5 and 9 yearsa.
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Table 5 Maternal individual healthy lifestyle score components and risk of offspring central obesity (WC > 90th) at 5 and 9 yearsa.
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Discussion

Regarding birth outcomes, several maternal lifestyle behaviors during early pregnancy have been associated with offspring birth weight [5]. Healthy diet, such as adherence to the HEI, not smoking, and moderate alcohol intake have individually been associated with greater offspring birth weight [16, 35] similar with our findings. Smoking during pregnancy results in decreased vascularization of the placenta, reducing fetal oxygen supply, and growth [36]. Maternal malnutrition and anemia have been associated with altered levels of growth hormones in cord blood at birth and risk of LBW [37, 38], which could partially explain our results but these results come from studies in a population of India where maternal malnutrition is more frequent than in Western countries such as Ireland. On the other hand, in a US study, greater maternal dietary quality (determined by the alternative HEI score) during pregnancy was not significantly associated with offspring birth weight [39]. A meta-analysis of randomized controlled trials of lifestyle interventions for pregnant women of normal BMI did not find an association with offspring macrosomia or LBW [40]. Study differences such as sample size, timing of the assessment of maternal diet quality/lifestyle during 3rd trimester [39] (which may be more relevant for offspring adiposity development than the first trimester when they were assessed in our study), population differences (only 3 of the 12 studies were in Europe) [41,42,43], and restriction to normal BMI range in other study [40], may partially explain the contradictory results of our study.

An overall healthy maternal lifestyle during pregnancy was associated with favorable offspring outcomes including reduced risk of LBW and childhood overweight and obesity at age 5 and 9. Offspring of women who adhered to five healthy lifestyle factors (a high quality diet, normal body weight, moderate to vigorous PA, non to moderate intake of alcohol, and non-smoking) had lower risk of incident overweight and obesity than children of mothers who did not adhere to any of the healthy lifestyle factors. Others studies reported similar findings on the associations of an overall maternal healthy lifestyle during pregnancy and reduced risk of offspring obesity in childhood compared with offspring of women who did meet any of the low-risk factors [20, 21] and with offspring birth weight [5]. These associations on our study were attenuated in sensitivity analysis in mothers–child pairs with child’s diet data and after adjusting for childhood factors at the year 5 follow-up (diet quality and PA) so these childs factors may be influencing this findings, although the reduced sample size in the sensitivity analysis may perhaps reduce the statistical power.

In our study maternal obesity and smoking were strongly associated with offspring obesity, in line with previous reports [11, 30, 44]. Animal model studies showed that maternal obesity could promote alteration of adipocyte morphology in the fetus that is related to the development of offspring obesity [45]. In humans, twofold greater risk of obesity in adulthood has been reported among offspring of mothers with obesity [44]. A large multicenter study documented that BMI of children exposed to maternal smoking was 0.08 greater than those who were not exposed [44]. Findings from another meta-analysis revealed that offspring of mothers who smoked during pregnancy had greater risk of obesity during childhood (2–18 years) than children of mothers who did not smoke [7]. Healthy maternal dietary pattern during pregnancy are associated with lower BMI and low risk of being overweight in offspring at age 6 in the Generation R cohort [8] but none of these associations remained significant after adjustment for sociodemographic and lifestyle factors. In keeping with that finding we did not find any association between maternal dietary quality, as determined by the HEI-2015 score, with offspring overweight and obesity at age 5 and 9, nor after adjusting for the lifestyle factors of mother and child, thus the influence of maternal dietary quality on childhood obesity remains unclear and requires further investigation. Moreover, physical inactivity during pregnancy was associated with an increased BMI in offspring at age 7–10 [9, 10] but we did not find any association of maternal PA with offspring obesity. Our findings are in line with results from examination of the Nurses’ Health Study and the Health Professionals Follow-up Study [20] and with a study of 802 mother–child dyads from Project Viva which reported that higher PA before and during mid-pregnancy was not associated with lower adiposity in mid-childhood [9]. Sensitivity analyses revealed that after adjustment for child dietary quality (HEI score) and PA at 5-year follow-up the maternal dietary quality and PA associations with offspring overweight and obesity remained practically unchanged, however, the associations with maternal smoking, BMI, and overall HLS were attenuated. Although the reduced sample size in the sensitivity analyses at age 5 and 9, which may also reduce statistical power, should be taken into consideration, these findings highlight the influence of childhood lifestyle factors on weight status.

In addition to individual factors parental and environmental factors are also important [1]. Previous investigation studies of the Lifeways cohort have shown a strong association between mother and offspring BMI [30] and infant birth weight across three generations of the same families [46]. Furthermore, healthy dietary patterns in the mothers were negatively associated with offspring overweight and obesity at age five years [47]. However, examination of paternal line smoking also revealed associations with offspring adiposity [48]. Second hand smoking could be another mechanism underlying the link between maternal smoking and offspring obesity [12]. Although higher effect estimates for maternal smoking and childhood obesity have been reported [49], suggestive of direct intra-uterine effects, it is likely that paternal smoking contributes to household exposure and indirectly to childhood obesity risk. Furthermore, the lack of any associations between maternal HEI and PA during pregnancy with offspring childhood obesity may not perhaps be too surprising considering that during childhood additional external factors to that of the family/home environment exist, such as school and neighborhood food and PA environments, which may influence a child’s PA and diet [50].

Given the limitations of BMI and potential for misclassification of obesity, central obesity (determined by WC) was additionally examined. However, no significant maternal HLS associations were observed. This may be partly due to the other environmental factors [50] that can influence abdominal obesity in childhood. In addition, differences in anthropometric assessment measures must be taken into account. BMI does not estimate body composition or lean muscle or fat mass and WC does not take whole body fat distribution into account. Thus future studies would benefit from using dual energy X-ray absorptiometry to determine body composition [51].

Li et al. demonstrated the potential impact of adopting a healthy lifestyle (both individual and combined lifestyle factors of the HLS) on reducing premature mortality and prolonging life expectancy in American adults (30–80 years of age) [17]. The projected life expectancy at age 50 years was on average 14.0 years (95% CI, 11.8–16.2) longer among females with five low-risk factors compared with those with zero low-risk factors; for men, the difference was 12.2 years (95% CI, 10.1–14.2). Thus following an overall healthy lifestyle that comprises a combination of multiple healthful behaviors that included diet, PA and sedentary behaviors, smoking, alcohol intake, social support and network, and sleep, may provide stronger protection against metabolic syndrome [19]. Furthermore, a 78% relative reduction in the risk of primary CVD [18] and reducing premature mortality have been reported among those who adopted all five low-risk factors relative to individual components [17]. The literature is limited regarding the association of a composite maternal HLS in pregnancy and the offspring weight status follow-up [5, 20, 21]. Taken together with our findings these data highlight the need for further examination of healthy lifestyle behaviors and composite HLSs in longitudinal birth and family cohorts.

Strengths and limitations

Our study has many strengths; it is one of few birth cohorts worldwide to have detailed clinical, anthropometric, sociodemographic, and lifestyle data from mothers, collected at baseline and prospectively. The number of mother–child pairs was relatively large. A wide range of maternal lifestyle factors including dietary habits, smoking, alcohol intake, PA, and potential confounders including education level, marital status and household income were considered. A few limitations need to be noted. First, maternal diet in the first trimester was assessed, whereas third trimester diet may be more relevant for offspring adiposity [52]. However, previous studies indicate that dietary intakes and patterns do not change substantially during pregnancy [53]. We cannot exclude the possibility that unmeasured confounders, such as genetic and psychosocial factors, and others family factors, such as those of the fathers, may influence our observations. A validated subjective (IPAQ) or objective (accelerometer) measure of PA might be better in our study instead of the current. Gestational diabetes may influence birth weight, although we identified only 12 cases in the current investigation we excluded them from our analysis. Central obesity could be under estimated when children were 5 and 9 years old. In the current and previous analyses [48, 54], we used the 1990 British growth reference [32]. A comparative study of this and a later UK-WHO growth chart revealed that the newer chart was more likely to classify overweight and obesity [55]. However, as we have combined overweight and obese children this may have reduced any impact in terms of association with HLS. Residual confounding arising from imprecise measurement of dietary intake also should be considered. As a structured dietary assessment method, the use of a FFQ can introduce recall and reporting biases [56]. Differential follow-up, leading to varied numbers of missing data for certain variables, could potentially introduce bias to follow-up data. Only half of the cohort was included for year 5 outcomes analyses, and the numbers at age 9 are smaller, raising concern of potential selection bias. However, to increase the study’s statistical power, multiple imputation was used to handle missing covariate information, which may have increased the validity of estimates because the uncertainties of imputation have been taken into account [34]. Last, our study only examined maternal lifestyle, prospective research examining paternal lifestyle in the development of obesity in offspring is needed. Regarding generalizability of our findings, the Lifeways study was not designed to be representative of the general obstetric population in Ireland [22], though previous analyses suggest that mothers are comparable to the contemporary national health and lifestyles surveys undertaken at the time [23].

Conclusions

In conclusion, our findings suggest that maternal adherence to a healthy lifestyle during pregnancy, in particular having a high quality diet, not smoking and no/low alcohol intake in combination with a healthy pre-pregnancy BMI, is associated with reduced risk of adverse offspring birth outcomes and childhood obesity. Our findings highlight the importance of maternal choices regarding healthier lifestyle behaviors and the potential for multifactorial diet and lifestyle intervention strategies to improve offspring birth outcomes and childhood obesity.