The objective of this review was to assess the impact of lifestyle interventions (including dietary interventions, physical activity, behavioral therapy, or any combination of these interventions) to prevent and manage childhood and adolescent obesity. We conducted a comprehensive literature search across various databases and grey literature without any restrictions on publication, language, or publication status until February 2020. We included randomized controlled trials and quasi-experimental studies from both high income countries (HIC) and low-middle-income countries (LMICs). Participants were children and adolescents from 0 to 19 years of age. Studies conducted among hospitalized children and children with any pre-existing health conditions were excluded from this review. A total of 654 studies (1160 papers) that met the inclusion criteria were included in this review. A total of 359 studies targeted obesity prevention, 280 studies targeted obesity management, while 15 studies targeted both prevention and management. The majority of the studies (81%) were conducted in HICs, 10% of studies were conducted in upper middle income countries, while only 2% of the studies were conducted in LMICs. The most common setting for these interventions were communities and school settings. Evidence for the prevention of obesity among children and adolescents suggests that a combination of diet and exercise might reduce the BMI z-score (MD: −0.12; 95% CI: −0.18 to −0.06; 32 studies; 33,039 participants; I² 93%; low quality evidence), body mass index (BMI) by 0.41 kg/m² (MD: −0.41 kg/m²; 95% CI: −0.60 to −0.21; 35 studies; 47,499 participants; I² 98%; low quality evidence), and body weight (MD: −1.59; 95% CI: −2.95 to −0.23; 17 studies; 35,023 participants; I² 100%; low quality evidence). Behavioral therapy alone (MD: −0.07; 95% CI: −0.14 to −0.00; 19 studies; 8569 participants; I² 76%; low quality evidence) and a combination of exercise and behavioral therapy (MD: −0.08; 95% CI: −0.16 to −0.00; 9 studies; 7334 participants; I² 74%; low quality evidence) and diet in combination with exercise and behavioral therapy (MD: −0.13; 95% CI: −0.25 to −0.01; 5 studies; 1806 participants; I² 62%; low quality evidence) might reduce BMI z-score when compared to the control group. Evidence for obesity management suggests that exercise only interventions probably reduce BMI z-score (MD: −0.13; 95% CI: −0.20 to −0.06; 12 studies; 1084 participants; I² 0%; moderate quality evidence), and might reduce BMI (MD: −0.88; 95% CI: −1.265 to −0.50; 34 studies; 3846 participants; I² 72%) and body weight (MD: −3.01; 95% CI: −5.56 to −0.47; 16 studies; 1701 participants; I² 78%; low quality evidence) when compared to the control group. and the exercise along with behavioral therapy interventions (MD: −0.08; 95% CI: −0.16 to −0.00; 8 studies; 466 participants; I² 49%; moderate quality evidence), diet along with behavioral therapy interventions (MD: −0.16; 95% CI: −0.26 to −0.07; 4 studies; 329 participants; I² 0%; moderate quality evidence), and combination of diet, exercise and behavioral therapy (MD: −0.09; 95% CI: −0.14 to −0.05; 13 studies; 2995 participants; I² 12%; moderate quality evidence) also probably decreases BMI z-score when compared to the control group. The existing evidence is most favorable for a combination of interventions, such as diet along with exercise and exercise along with behavioral therapy for obesity prevention and exercise alone, diet along with exercise, diet along with behavioral therapy, and a combination of diet, exercise, and behavioral therapy for obesity management. Despite the growing obesity epidemic in LMICs, there is a significant dearth of obesity prevention and management studies from these regions.

Pakistan has alarmingly high numbers of maternal mortality along with suboptimal care-seeking behaviour. It is essential to identify the barriers and facilitators that women and families encounter, when deciding to seek maternal care services. This study aimed to understand health-seeking patterns of pregnant women in rural Sindh, Pakistan. A qualitative study was undertaken in rural Sindh, Pakistan as part of a large multi-country study in 2012. Thirty three focus group discussions and 26 in-depth interviews were conducted with mothers [n = 173], male decision-makers [n = 64], Lady Health Workers [n = 64], Lady Health Supervisors [n = 10], Women Medical Officers [n = 9] and Traditional Birth Attendants [n = 7] in the study communities. A set of a priori themes regarding care-seeking during pregnancy and its complications as well as additional themes as they emerged from the data were used for analysis. Qualitative analysis was done using NVivo version 10. Women stated they usually visited health facilities if they experienced pregnancy complications or danger signs, such as heavy bleeding or headache. Findings revealed the importance of husbands and mothers-in-law as decision makers regarding health care utilization. Participants expressed that poor availability of transport, financial constraints and the unavailability of chaperones were important barriers to seeking care. In addition, private facilities were often preferred due to the perceived superior quality of services. Maternal care utilization was influenced by social, economic and cultural factors in rural Pakistani communities. The perceived poor quality care at public hospitals was a significant barrier for many women in accessing health services. If maternal lives are to be saved, policy makers need to develop processes to overcome these barriers and ensure easily accessible high-quality care for women in rural communities. NCT01911494

Objectives The objective of this review was to assess the impact of maternal preeclampsia or hyperglycemia on the body composition and cardiovascular health in the offspring. Study Design We conducted a systematic review utilizing PubMed, EBSCO, CINAHLPlus, Cochrane Library, and Web of Science to include all studies assessing the impact of preeclampsia/eclampsia and/or gestational/pregestational diabetes mellitus on the health of the offspring (children <10 years of age). The health measures included anthropometry, cardiac dimensions and function, and vascular function. We performed a meta-analysis using Review Manager software and computed net risk ratio (RR) with 95% confidence interval (CI) for dichotomous data and mean difference (MD) with 95% CI for continuous data. Results There were 6,376 studies in total, of which 45 were included in the review and 40 in the meta-analysis. The results demonstrated higher birth weight (MD: 0.12 kg; 95% CI: 0.06–0.18) and systolic and diastolic blood pressure (BP; MD: 5.98 mm Hg; 95% CI: 5.64–6.32 and MD: 3.27 mm Hg; 95% CI: 0.65–5.89, respectively) in the offspring of mothers with gestational diabetes compared to controls. In contrast, the offspring of mothers with preeclampsia had lower birth weight (MD: −0.41 kg; 95% CI: −0.7 to −0.11); however, they had increased systolic (MD: 2.2 mm Hg; 95% CI: 1.28–3.12) and diastolic BP (MD: 1.41 mm Hg; 95% CI: 0.3–2.52) compared to controls. There is lack of data to conduct a meta-analysis of cardiac morphology, functional, and vascular imaging parameters. Conclusion These findings suggest that the in-utero milieu can have a permanent impact on the body composition and vascular health of the offspring. Future work warrants multicenter prospective studies to understand the mechanism and the actual effect of exposure to maternal hyperglycemia and high BP on the cardiovascular health of the offspring and long-term outcomes. Key Points

Introduction Rheumatic heart diseases (RHDs) contribute significant morbidity and mortality globally. To reduce the burden of RHD, timely initiation of secondary prophylaxis is important. The objectives of this study are to determine the frequency of subclinical RHD and to train a deep learning (DL) algorithm using waveform data from the digital auscultatory stethoscope (DAS) in predicting subclinical RHD. Methods and analysis We aim to recruit 1700 children from a group of schools serving the underprivileged over a 12-month period in Karachi (Pakistan). All consenting students within the age of 5–15 years with no underlying congenital heart disease will be eligible for the study. We will gather information regarding sociodemographics, anthropometric data, history of symptoms or diagnosis of rheumatic fever, phonocardiogram (PCG) and electrocardiography (ECG) data obtained from DAS. Handheld echocardiogram will be performed on each study participant to assess the presence of a mitral regurgitation (MR) jet (>1.5 cm), or the presence of aortic regurgitation (AR) in any view. If any of these findings are present, a confirmatory standard echocardiogram using the World Heart Federation (WHF) will be performed to confirm the diagnosis of subclinical RHD. The auscultatory data from digital stethoscope will be used to train the deep neural network for the automatic identification of patients with subclinical RHD. The proposed neural network will be trained in a supervised manner using labels from standard echocardiogram of the participants. Once trained, the neural network will be able to automatically classify the DAS data in one of the three major categories—patient with definite RHD, patient with borderline RHD and normal subject. The significance of the results will be confirmed by standard statistical methods for hypothesis testing. Ethics and dissemination Ethics approval has been taken from the Aga Khan University, Pakistan. Findings will be disseminated through scientific publications and to collaborators. Article focus This study focuses on determining the frequency of subclinical RHD in school-going children in Karachi, Pakistan and developing a DL algorithm to screen for this condition using a digital stethoscope.

Background Children born small for gestational age (SGA) may experience more long-term neurodevelopmental issues than those born appropriate for gestational age (AGA). This study aimed to assess differences in the neurodevelopment of children born SGA or AGA within a periurban community in Pakistan. Methods This was a prospective cohort study in which study participants were followed from the pilot Doppler cohort study conducted in 2018. This pilot study aimed to develop a pregnancy risk stratification model using machine learning on fetal Dopplers. This project identified 119 newborns who were born SGA (2.4±0.4 kg) based on International Fetal and Newborn Growth Consortium standards. We assessed 180 children (90 SGA and 90 AGA) between 2 and 4 years of age (76% of follow-up rate) using the Malawi Developmental Assessment Tool (MDAT). Findings Multivariable linear regression analysis comparing the absolute scores of MDAT showed significantly lower fine motor scores (β: −0.98; 95% CI −1.90 to –0.06) among SGAs, whereas comparing the z-scores using multivariable logistic regression, SGA children had three times higher odds of overall z-scores ≤−2 (OR: 3.78; 95% CI 1.20 to 11.89) as compared with AGA children. Interpretation SGA exposure is associated with poor performance on overall MDAT, mainly due to changes in the fine motor domain in young children. The scores on the other domains (gross motor, language and social) were also lower among SGAs; however, none of these reached statistical significance. There is a need to design follow-up studies to assess the impact of SGA on child’s neurodevelopmental trajectory and school performance.