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Additional file 1. Supplementary figure 1

Additional file 2: Supplemental Table 1. LUR models for air pollutant concentration assessment.

Additional file 5: Supplemental Table 4. The association between exposure to indoor air pollutants during pregnancy with birth anthropometrics in a-indoor subset group.

Additional file 3: Supplemental Table 2. Correlation between air pollutants concentration at the measurement sites.

Additional file 2. Supplementary figure 2

Additional file 3. Supplementary tables

Protocol for a scoping review to to i) describe the current practice of process evaluation in the scale-up of complex interventions, and ii) work towards a conceptual framework that can be used as a guiding document for future process evaluations of scale-up initiatives.

Supplemental Material for Multimorbidity of communicable and non-communicable diseases in low- and middle-income countries: A systematic review by Lucy Kaluvu, Asogwa Ogechukwa, Anna Marza Florensa, Catherine Kyobutungi, Naomi S Levitt, Daniel Boateng, and Kerstin Klipstein-Grobusch in Journal of Multimorbidity and Comorbidity

Additional file 1: Table S1. Scoring and definition of components of Cardiovascular Health Index.

Additional file 2: Figure S1. Kernel density of mean distribution number of ideal cardiovascular health metrics (0–14) by AWI-Gen study countries. Figure S2. Kernel density of mean CIMT distribution in μm by AWI-Gen study countries. Figure S3. The linear association between CVH score and CIMT in the combined AWI-Gen population. Figure S4. The linear association between CVH score and CIMT in the combined four participating countries of the AWI-Gen study.

Understanding the association between maternal metabolic conditions in pregnancy and the risk of childhood overweight, a growing concern in sub-Saharan Africa (SSA), helps to identify opportunities for childhood obesity prevention. To assess the association between hyperglycaemia first detected in pregnancy (HFDP) (gestational diabetes mellitus [GDM] and diabetes in pregnancy [DIP]) and child obesity and adiposity in pre-school-aged children in South Africa, independently of maternal BMI. Measurement of anthropometry and fat mass index (FMI) by the deuterium dilution method was done for 102 3–6-year-old children born to mothers with HFDP and 102 HFDP-unexposed children. Hierarchical regression analysis and generalised structural equation modelling (GSEM) were performed. The prevalence of overweight/obesity was 10.5% and 11.1% in children exposed to GDM and DIP, respectively, and 3.9% in the HFDP-unexposed group. Log-transformed FMI was significantly higher in the DIP-exposed group (β = 0.166, 95% CI = 0.014–0.217 p= .026), but not when adjusting for maternal pregnancy BMI (β = 0.226, 95% CI = 0.003–0.015, p = .004). GSEM showed significant total effects of maternal BMI and birth weight on FMI/BMI. Maternal pregnancy BMI seems to play a greater role in the development of childhood adiposity than maternal hyperglycaemia, requiring further research and identifying maternal BMI as a relevant prevention target in our setting.

Additional file 1: Supplementary methods: Additional details for handling missing data and evaluating predictive performance of models. Table S1: Search strategy for pre-eclampsia prediction models. Table S2: Predictors evaluated in the models externally validated in the IPPIC-UK cohorts. Table S3: Prediction models and equations identified from the literature search. Table S4: Study level characteristics of IPPIC-UK cohorts. Table S5: Patient characteristics of IPPIC-UK cohorts. Table S6: Number and proportion missing for each predictor in each cohort used for external validation. Table S7: Risk of bias assessment of the IPPIC-UK cohorts using the PROBAST tool. Table S8: Summary of linear predictor values and predicted probabilities for each model in each cohort. Table S9: Predictive performance statistics for models in the individual IPPIC-UK cohorts. Table S10: Predictive performance statistics for models in nulliparous women in all cohorts and in the POP cohort. Fig. S1: Decision curves for early pre-eclampsia models in SCOPE, UPBEAT and POP. Fig. S2: Decision curves for late pre-eclampsia models in SCOPE, Allen 2017, UPBEAT and POP.

Additional file 1: Table S1. Baseline characteristics of all BRAVO participants.

Additional file 1.

Hypertension perception questionnaire. This is the questionnaire used for the quantitative part in this study (PDF 44 kb)

Table S1. Association of SES category by maternal education and maternal and perinatal outcomes for pregnant women in Accra, Ghana. Table S2. Association of SES category by paternal education and maternal and perinatal outcomes for pregnant women in Accra, Ghana. Table S3. Association of SES category by employment and maternal and perinatal outcomes for pregnant women in Accra, Ghana (DOCX 31 kb)

Study guids focus group discussions. This is the study guide used by the moderators during the focus group discussions (PDF 67 kb)

Full search strategy and list of synonyms. (DOCX 19Â kb)

The review aimed to synthesize available evidence of the level of knowledge of and perceptions towards cardiovascular diseases and risk factors in sub-Saharan Africa.

Presence and severity of adhesions by number of previous cesarean section. (DOCX 10Â kb)

Patient satisfaction questionnaire adapted for patients in the study. (PDF 90Â kb)

Sampling of study participants. (PDF 95Â kb)

Table of definition of terms used in the article. (PDF 97Â kb)

Associations of adhesion groups by score and classification. (DOCX 15Â kb)

Associations of adhesion groups by score and classification. (DOCX 15Â kb)

Baseline characteristics of participating women by adhesion group. (DOCX 14Â kb)

Presence and severity of adhesions by number of previous cesarean section. (DOCX 10Â kb)

Baseline characteristics of participating women by adhesion group. (DOCX 14Â kb)

Innovative approaches in the HIV programme leveraged for NCDs in the ICDM model by the NDoH in South Africa. (PDF 89 kb)

Patient satisfaction questionnaire-18 developed by Ware et al. (PDF 285Â kb)

Table showing the checklist for scoring provider adherence to antenatal guidelines. (DOCX 20 kb)

Describes characteristics of the women. (PDF 117Â kb)

Age-standardised prevalence of overweight (BMIâ Ľ25 kg/m2) by locality in men (A) and women (B). Error bars are 95% confidence intervals. (DOC 137 kb)

Probability of abdominal obesity (waist circumference, men: >102 cm, women: >88 cm) by age in men (A) and women (B). (DOC 34 kb)

Script of antenatal clinic health talk. (DOC 23 kb)

Quality assessment for individual studies. (DOCX 136Â kb)

SPIRIT 2013 Checklist: recommended items to address in a clinical trial protocol and related documents. (PDF 964Â kb)

Additional file 2: Table S2. Title: Estimated means with 95% confidence intervals per outcome. Description of data: This table presents estimates of the means for each treatment group at 4 follow-up measurements based on a linear mixed model with correction for age, sex, site of inclusion (South-Africa, Uganda or India), body mass index and viral load at baseline (see â Methodsâ for details).

Flow chart of inclusion of RODAM study participants in analysis. (DOC 40 kb)

Additional file 1: Table S1. Title: Laboratory methods. Description of data: this table includes details on the measurement methods of lipids, glucose, insulin, HIV viral load and CD4+ cell count.

Search strategy. (DOCX 78Â kb)

SPIRIT 2013 Checklist: recommended items to address in a clinical trial protocol and related documents. (PDF 964Â kb)

Probability of obesity (BMIâ Ľ30kg/m2) by age in men (A) and women (B). (DOC 33 kb)

Probability of type 2 diabetes by age in men (A) and women (B). (DOC 34 kb )

Search strategy. (DOCX 78Â kb)

Funder: NIHR School for Primary Care Research; doi: http://dx.doi.org/10.13039/501100013374, BACKGROUND: Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk during pregnancy is required to plan management. Although there are many published prediction models for pre-eclampsia, few have been validated in external data. Our objective was to externally validate published prediction models for pre-eclampsia using individual participant data (IPD) from UK studies, to evaluate whether any of the models can accurately predict the condition when used within the UK healthcare setting. METHODS: IPD from 11 UK cohort studies (217,415 pregnant women) within the International Prediction of Pregnancy Complications (IPPIC) pre-eclampsia network contributed to external validation of published prediction models, identified by systematic review. Cohorts that measured all predictor variables in at least one of the identified models and reported pre-eclampsia as an outcome were included for validation. We reported the model predictive performance as discrimination (C-statistic), calibration (calibration plots, calibration slope, calibration-in-the-large), and net benefit. Performance measures were estimated separately in each available study and then, where possible, combined across studies in a random-effects meta-analysis. RESULTS: Of 131 published models, 67 provided the full model equation and 24 could be validated in 11 UK cohorts. Most of the models showed modest discrimination with summary C-statistics between 0.6 and 0.7. The calibration of the predicted compared to observed risk was generally poor for most models with observed calibration slopes less than 1, indicating that predictions were generally too extreme, although confidence intervals were wide. There was large between-study heterogeneity in each model's calibration-in-the-large, suggesting poor calibration of the predicted overall risk across populations. In a subset of models, the net benefit of using the models to inform clinical decisions appeared small and limited to probability thresholds between 5 and 7%. CONCLUSIONS: The evaluated models had modest predictive performance, with key limitations such as poor calibration (likely due to overfitting in the original development datasets), substantial heterogeneity, and small net benefit across settings. The evidence to support the use of these prediction models for pre-eclampsia in clinical decision-making is limited. Any models that we could not validate should be examined in terms of their predictive performance, net benefit, and heterogeneity across multiple UK settings before consideration for use in practice. TRIAL REGISTRATION: PROSPERO ID: CRD42015029349 .

Background: West African immigrants in Europe are disproportionally affected by metabolic conditions compared to European host populations. Nutrition transition through urbanisation and migration may contribute to this observations, but remains to be characterised. Objective: We aimed to describe the dietary behaviour and its socio-demographic factors among Ghanaian migrants in Europe and their compatriots living different Ghanaian settings. Methods: The multi-centre, cross-sectional RODAM (Research on Obesity and Diabetes among African Migrants) study was conducted among Ghanaian adults in rural and urban Ghana, and Europe. Dietary patterns were identified by principal component analysis. Results: Contributions of macronutrient to the daily energy intake was different across the three study sites. Three dietary patterns were identified. Adherence to the ‘mixed’ pattern was associated with female sex, higher education, and European residency. The ‘rice, pasta, meat, and fish’ pattern was associated with male sex, younger age, higher education, and urban Ghanaian environment. Adherence to the ‘roots, tubers, and plantain’ pattern was mainly related to rural Ghanaian residency. Conclusion: We observed differences in food preferences across study sites: in rural Ghana, diet concentrated on starchy foods; in urban Ghana, nutrition was dominated by animal-based products; and in Europe, diet appeared to be highly diverse.

Quality assessment for individual studies. (DOCX 136Â kb)

Additional file 3: Table S3. Title: Generalized linear mixed models. Description of data: generalized linear mixed models for the outcomes total cholesterol, HDL cholesterol, LDL cholesterol, triglycerides, glucose, insulin, HOMA-IR and Framingham risk score.

Additional file 2: Table S2. Title: Estimated means with 95% confidence intervals per outcome. Description of data: This table presents estimates of the means for each treatment group at 4 follow-up measurements based on a linear mixed model with correction for age, sex, site of inclusion (South-Africa, Uganda or India), body mass index and viral load at baseline (see â Methodsâ for details).