DESIGN: GWG trajectories were identified using the latent class growth model. Binary logistic regression was performed to examine the associations between adverse pregnancy outcomes and these trajectories.
SETTING: Negeri Sembilan, Malaysia.
PARTICIPANTS: Two thousand one hundred ninety-three pregnant women.
RESULTS: Three GWG trajectories were identified: 'Group 1 - slow initial GWG but followed by drastic GWG', 'Group 2 - maintaining rate of GWG at 0·58 kg/week' and 'Group 3 - maintaining rate of GWG at 0·38 kg/week'. Group 1 had higher risk of postpartum weight retention (PWR) (adjusted OR (AOR) 1·02, 95 % CI 1·01, 1·04), caesarean delivery (AOR 1·03, 95 % CI 1·01, 1·04) and having low birth weight (AOR 1·04, 95 % CI 1·02, 1·05) compared with group 3. Group 2 was at higher risk of PWR (AOR 1·18, 95 % CI 1·16, 1·21), preterm delivery (AOR 1·03, 95 % CI 1·01, 1·05) and caesarean delivery (AOR 1·02, 95 % CI 1·01, 1·03), but at lower risk of having small-for-gestational-age infants (AOR 0·97, 95 % CI 0·96, 0·99) compared with group 3. The significant associations between group 1 and PWR were observed among non-overweight/obese women; between group 1 and caesarean delivery among overweight/obese women; group 2 with preterm delivery and caesarean delivery were only found among overweight/obese women.
CONCLUSIONS: Higher GWG as well as increasing GWG trajectories was associated with higher risk of adverse pregnancy outcomes. Promoting GWG within the recommended range should be emphasised in antenatal care to prevent the risk of adverse pregnancy outcomes.
METHODS: This was a prospective cohort study of 452 pregnant women recruited from 3 health clinics in a southern state of Peninsular Malaysia. PA levels at the first, second, and third trimester were assessed using the Pregnancy Physical Activity Questionnaire. GDM was diagnosed at 24-28 weeks of gestation following the Ministry of Health Malaysia criteria. Group-based trajectory modeling was used to identify PA trajectories. Three multivariate logistic models were used to estimate the odds of trajectory group membership and GDM.
RESULTS: Two distinct PA trajectories were identified: low PA levels in all intensity of PA and sedentary behavior (Group 1: 61.1%, n = 276) and high PA levels in all intensity of PA as well as sedentary behavior (Group 2: 38.9%, n = 176). Moderate and high intensity PA decreased over the course of pregnancy in both groups. Women in group 2 had significantly higher risk of GDM in two of the estimated logistic models. In all models, significant associations between PA trajectories and GDM were only observed among women with excessive gestational weight gain in the second trimester.
CONCLUSIONS: Women with high sedentary behavior were significantly at higher risk of GDM despite high PA levels by intensity and this association was significant only among women with excessive GWG in the second trimester. Participation in high sedentary behavior may outweigh the benefit of engaging in high PA to mitigate the risk of GDM.
SUBJECTS/METHODS: This study included 259 pregnant women within the Seremban Cohort Study (SECOST). Blood samples at < 14 weeks of gestation were drawn to determine serum 25(OH)D levels. GDM diagnosis was made at 24 to 32 weeks of gestation using a standard procedure. Association between serum vitamin D and GDM was tested using binary logistic regression.
RESULTS: Nearly all women (90%) had mild (68.3%) or severe (32.2%) vitamin D deficiency (VDD). Non-GDM women with mild VDD had a significantly higher mean vitamin D intake than GDM women with mild VDD (t = 2.04, p < 0.05). Women with higher early pregnancy serum vitamin D levels had a greater risk of GDM. However, this significant association was only identified among those with a family history of type 2 diabetes mellitus (T2DM) and in women with a body mass index indicating overweight or obese status.
CONCLUSIONS: The high prevalence of VDD in this sample of pregnant women underscores the need for effective preventive public health strategies. Further investigation of this unexpected association between serum vitamin D level and GDM risk in predominantly VDD pregnant women and the potential effects of adiposity and family history of T2DM on that association is warranted.
METHODS: A mapping population of 112 F1 individuals from a cross of Deli dura and Serdang pisifera was used in this study. GBS libraries were constructed using the double digestion method with HindIII and TaqI enzymes. Reduced representation libraries (RRL) of 112 F1 progeny and their parents were sequenced and the reads were mapped against the E. guineensis reference genome. To construct the oil palm genetic linkage map, informative SNP and InDel markers were used to discover significant DNA regions associated with the traits of interest. The nine traits of interest in this study were fresh fruit bunch (FFB) yield, oil yield (OY), oil to bunch ratio (O/B), oil to dry mesocarp ratio (O/DM) ratio, oil to wet mesocarp ratio (O/WM), mesocarp to fruit ratio (M/F), kernel to fruit ratio (K/F), shell to fruit ratio (S/F), and fruit to bunch ratio (F/B).
RESULTS: A total of 2.5 million SNP and 153,547 InDel markers were identified. However, only a subset of 5,278 markers comprising of 4,838 SNPs and 440 InDels were informative for the construction of a genetic linkage map. Sixteen linkage groups were produced, spanning 2,737.6 cM for the maternal map and 4,571.6 cM for the paternal map, with average marker densities of one marker per 2.9 cM and one per 2.0 cM respectively, were produced. A QTL analysis was performed on nine traits; however, only QTL regions linked to M/F, K/F and S/F were declared to be significant. Of those QTLs were detected: two for M/F, four for K/F and one for S/F. These QTLs explained 18.1-25.6% of the phenotypic variance and were located near putative genes, such as casein kinase II and the zinc finger CCCH domain, which are involved in seed germination and growth. The identified QTL regions for M/F, K/F and S/F from this study could be applied in an oil palm breeding program and used to screen palms with desired traits via marker assisted selection (MAS).
METHODS AND ANALYSIS: A total of 294 eligible participants will be recruited and allocated into 3 groups comprising of mHealth intervention alone, mHealth intervention integrated with personal medical nutrition therapy and a control group. Pretested structured questionnaires are used to obtain the respondents' personal information, anthropometry data, prenatal knowledge, physical activity, psychosocial well-being, dietary intake, quality of life, sleep quality and GWG. There will be at least three time points of data collection, with all participants recruited during their first or second trimester will be followed up prospectively (after 3 months or/and after 6 months) until delivery. Generalised linear mixed models will be used to compare the mean changes of outcome measures over the entire study period between the three groups.
ETHICS AND DISSEMINATION: Ethical approvals were obtained from the ethics committee of human subjects research of Universiti Putra Malaysia (JKEUPM-2022-072) and medical research & ethics committee, Ministry of Health Malaysia: NMRR ID-22-00622-EPU(IIR). The results will be disseminated through journals and conferences targeting stakeholders involved in nutrition research.
TRIAL REGISTRATION NUMBER: Clinicaltrial.gov ID: NCT05377151.