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THE IMPACT OF FOOD ADDITIVE INTAKE AND ALTERED GUT MICROBIOME ON PERINATAL HEALTH: DATA FROM 3 REGIONS IN CHINA FROM THE MOMMY COHORT
Date
May 21, 2024
Keywords: food additives, maternal gut microbiome, gestational diabetes mellitus, large for gestational age
Introduction: Accumulating evidence suggest that food additives can lead to altered gut microbiome composition. The impact of food additive intake on early life gut microbiome and prenatal health have not been explored. This study aimed to investigate the role of food additives on perinatal health using prospectively collected longitudinal mother-baby cohort in three cities in China with different levels of urbanization.
Materials & Methods: This is a sub-study of MOMmy (The MOther-infant Microbiota transmission and its link to long terM health of babY) cohort. A total of 2171 pregnant mothers from three regions/cities in China [(Hong Kong (HK)=Westernized, N=1544; Foshan (FS)=Transitioning, N=532; and Kunming (KM)=Chinese-traditional/rural), N=95] were recruited. Recent food additive intake (past 12 months) was collected at early pregnancy using a validated questionnaire and defined based on high (Q4) or normal (Q1-3) interquartile range in the study population. Past dietary score (PDS) assessed mothers' early-life dietary habits regarding processed food and food sources (A higher PDS indicates poorer dietary habits). The impact of food additive intake on maternal and post-partum clinical outcomes was assessed using questionnaires with obstetrics and gynaecology clinicians’ validation. Fecal microbiome composition in late pregnancy were assessed by shotgun metagenomic sequencing.
Results: Dietary habits and the consumption of food additives diverge amongst the three study sites. Pregnant mothers in Hong Kong, as the symbolic westernized city, had the highest mean annual food additives intake levels (Fig 1A). Regionally, the demographics and lifestyle that related to current food additive intake varied (Fig 1B).
Maternal total food additive intake was associated with an increased risk of Gestational Diabetes Mellitus (GDM) and Large for Gestational Age (LGA) risks in the infants. There was dietary-region specific impact on the maternal gut microbiome. The metric multidimensional scaling showed the KM women had the most distinguishable gut microbiome composition compared to other two regions, and FS subjects have the lowest PDS. Among all the potential microbiome related co-variates, geography/region was the major factor that shaped gut microbiome, followed by PDS, and a diagnosis of GDM.
Conclusion: Our findings highlighted that maternal food additive intake were associated with unfavourable health outcomes in babies, possibly through altered gut microbiome. Further mechanistic studies are warranted to dissect the effect of maternal food additive intake on microbiome functional pathways and outcomes.
Acknowledgment: MOMmy was supported by InnoHK, The Government of Hong Kong, Special Administrative Region of the People’s Republic of China.
Introduction: Accumulating evidence suggest that food additives can lead to altered gut microbiome composition. The impact of food additive intake on early life gut microbiome and prenatal health have not been explored. This study aimed to investigate the role of food additives on perinatal health using prospectively collected longitudinal mother-baby cohort in three cities in China with different levels of urbanization.
Materials & Methods: This is a sub-study of MOMmy (The MOther-infant Microbiota transmission and its link to long terM health of babY) cohort. A total of 2171 pregnant mothers from three regions/cities in China [(Hong Kong (HK)=Westernized, N=1544; Foshan (FS)=Transitioning, N=532; and Kunming (KM)=Chinese-traditional/rural), N=95] were recruited. Recent food additive intake (past 12 months) was collected at early pregnancy using a validated questionnaire and defined based on high (Q4) or normal (Q1-3) interquartile range in the study population. Past dietary score (PDS) assessed mothers' early-life dietary habits regarding processed food and food sources (A higher PDS indicates poorer dietary habits). The impact of food additive intake on maternal and post-partum clinical outcomes was assessed using questionnaires with obstetrics and gynaecology clinicians’ validation. Fecal microbiome composition in late pregnancy were assessed by shotgun metagenomic sequencing.
Results: Dietary habits and the consumption of food additives diverge amongst the three study sites. Pregnant mothers in Hong Kong, as the symbolic westernized city, had the highest mean annual food additives intake levels (Fig 1A). Regionally, the demographics and lifestyle that related to current food additive intake varied (Fig 1B).
Maternal total food additive intake was associated with an increased risk of Gestational Diabetes Mellitus (GDM) and Large for Gestational Age (LGA) risks in the infants. There was dietary-region specific impact on the maternal gut microbiome. The metric multidimensional scaling showed the KM women had the most distinguishable gut microbiome composition compared to other two regions, and FS subjects have the lowest PDS. Among all the potential microbiome related co-variates, geography/region was the major factor that shaped gut microbiome, followed by PDS, and a diagnosis of GDM.
Conclusion: Our findings highlighted that maternal food additive intake were associated with unfavourable health outcomes in babies, possibly through altered gut microbiome. Further mechanistic studies are warranted to dissect the effect of maternal food additive intake on microbiome functional pathways and outcomes.
Acknowledgment: MOMmy was supported by InnoHK, The Government of Hong Kong, Special Administrative Region of the People’s Republic of China.
Figure 1. Overview of food additives intake among three study sites. (A) Data collection time points, sample size, and mean regional food additives intake (g/year) (B) Univariable analysis (linear regression) to identify the baseline characteristics that are related to current food additives intake. ^Reference groups: Pre-pregnancy BMI (Normal weight); Educational level (high school or below); Working status (full-time job); Dietary habits (Vegetable < meat); Weekly P.E. (no regular physical exercise). P-value label: .:<0.1, *:<0.05, **:<0.01, ***:<0.001.
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