Effects of a community-based approach of food and psychosocial stimulation on growth and development of severely malnourished children in Bangladesh: a randomised trial.

BACKGROUND/OBJECTIVE: Psychosocial stimulation (PS) and food supplementation (FS) improve development of malnourished children. This study evaluates the effects of a community-based approach of PS and FS on growth and development of severely malnourished children. SUBJECTS/METHODS: Severely underweight hospitalised children aged 6-24 months (n = 507) were randomly allocated on discharge to five groups: (i) PS, (ii) FS, (iii) PS+FS, (iv) clinic-control and (v) hospital-control. PS included play sessions and parental counselling on child development. This was done at each fortnightly follow-up visit, that is, every second week, for 6 months at community clinics. FS included distribution of cereal-based food packets (150-300 kcal/day) for 3 months. All groups received medical care, micronutrient supplementation, health-education and growth monitoring. Children's development was assessed using revised version of Bayley Scales of Infant Development at baseline and after 3 and 6 months of intervention. Anthropometry was measured using standard procedure. RESULTS: Comparing groups with any stimulation with those with no stimulation there was a significant effect of stimulation on children's mental development index (group*session interaction P = 0.037, effect size = 0.37 s.d.) and weight-for-age Z-score (group*session interaction P = 0.02, effect size=0.26 s.d.). Poor levels of development and nutritional status were sustained, however, due to their initial very severe malnutrition. There was no effect on motor development and linear growth. CONCLUSION: Children receiving any stimulation showed a significant benefit to mental development and growth in weight. More intensive intervention with longer duration is needed to correct their poor developmental levels and nutritional status

Integrating an early childhood development programme into Bangladeshi primary health-care services: an open-label, cluster-randomised controlled trial

BACKGROUND: Poor development in young children in developing countries is a major problem. Child development experts are calling for interventions that aim to improve child development to be integrated into health services, but there are few robust evaluations of such programmes. Previous small Bangladeshi trials that used individual play sessions with mothers and their children (at home or in clinics), which were predominantly run by employed women, found moderate improvements on child development. We aimed to integrate an early childhood development programme into government clinics that provide primary health care and to evaluate the effects of this intervention on child cognition, language, and motor development, growth, and behaviour in a subsample of the children. METHODS: In this open-label cluster-randomised controlled trial, we recruited individuals from community clinics in Narsingdi district, Bangladesh. These clinics were randomly selected from a larger sample of eligible clinics, and they were assigned (1:1) to either deliver an intervention of 25 sessions, in which mothers of eligible children were shown how to support their child's development through play and interactions, or to deliver no intervention (control group). Participants were underweight children, defined as a weight-for-age Z score of -2 SDs of the WHO standard, who were aged 5-24 months and who lived near the clinic (defined as a walk of less than 30 min). Government health workers ran these sessions at the clinics as part of their routine work, and mothers and children attended fortnightly in pairs (instead of individual weekly home visits that were specified in the original programme). A subsample of children from each clinic was randomly selected for impact evaluation, and these children were assessed on the Bayley Scales of Infant and Toddler Development for their cognitive, language, and motor performance and for their behaviour with Wolke's ratings, before and after implementation of the intervention. The primary outcomes were the performance of this evaluation subsample on the Bayley and Wolke scales and their anthropometric measurements (weight, length or height, and head circumference) after 1 year of the intervention. This study is registered with ClinicalTrials.gov, number NCT02208531. FINDINGS: Between Nov 29, 2014, and April 30, 2015, 12 054 children in 90 clinics were screened, and between six and 25 underweight children were enrolled from each clinic. From the 2423 (20%) underweight children, we excluded 656 (27%) children who lived more than 30-min walking distance from the community clinics, and 30 (1%) children whose mothers did not consent to participate. We therefore enrolled 1737 (72%) children from these 90 clinics. After randomisation, the control group clinics included 878 (51%) children (who all received no intervention) and the intervention group clinics included 859 (49%) children (who all received the child development programme sessions). Eight children from each clinic (360 [41%] children from the control group clinics and 358 [42%] children from the intervention group clinics) were randomly selected for inclusion in the evaluation subsample. Between Feb 24, 2016, and Sept 7, 2016, 344 (96%) children in control group clinics and 343 (96%) children in intervention group clinics were assessed for the primary outcome. 16 (5%) children in the control group clinics and 15 (4%) children in the intervention group clinics did not provide all data and were not included in final analyses. An intention-to-treat analysis showed that the intervention significantly improved children's cognition (effect size 1·3 SDs, 95% CI 1·1 to 1·5; p=0·006), language (1·1 SDs, 0·9 to 1·2; p=0·01), and motor composite scores (1·2 SDs, 1·0 to 1·3; p=0·006) and behaviour ratings (ranging from 0·7 SDs, 0·5 to 0·9; p=0·02; to 1·1 SDs, 1·0 to 1·2; p=0·007), but the intervention had no significant effect on growth (p values ranged from 0·05 to 0·74). Three (1%) children in the intervention group died, but their deaths were not related to the intervention. INTERPRETATION: The extent and range of benefits of our intervention are encouraging. Health workers ran most of the sessions effectively and attendance was good, which is promising for scale-up of the intervention model. However, researchers trained and supervised the health workers, and the next step will be to determine whether the Bangladeshi ministry of health can perform these tasks. In future programmes, more attention needs to be paid to the nutrition of the children. FUNDING: Grand Challenges Canada (Saving Brains)

Artemisinin derivatives versus quinine in treating severe malaria in children: a systematic review

<p>Abstract</p> <p>Background</p> <p>The efficacy of intravenous quinine, which is the mainstay for treating severe malaria in children, is decreasing in South East Asia and Africa. Artemisinin derivatives are a potential alternative to quinine. However, their efficacy compared to quinine in treating severe malaria in children is not clearly understood. The objective of this review was to assess the efficacy of parenteral artemisinin derivatives versus parenteral quinine in treating severe malaria in children.</p> <p>Methods</p> <p>All randomized controlled studies comparing parenteral artemisinin derivatives with parenteral quinine in treating severe malaria in children were included in the review. Data bases searched were: The Cochrane Central Register of Controlled Trials (The Cochrane Library Issue 4, 2007), MEDLINE (1966 to February 2008), EMBASE (1980 to February 2008), and LILACS (1982 to February 2008). Dichotomous variables were compared using risk ratios (RR) and the continuous data using weighted mean difference (WMD).</p> <p>Results</p> <p>Twelve trials were included (1,524 subjects). There was no difference in mortality between artemisinin derivatives and quinine (RR = 0.90, 95% CI 0.73 to 1.12). The artemisinin derivatives resolved coma faster than quinine (WMD = -4.61, 95% CI: -7.21 to -2.00, fixed effect model), but when trials with adequate concealment only were considered this differences disappeared. There was no statistically significant difference between the two groups in parasite clearance time, fever clearance time, incidence of neurological sequelae and 28^thday cure rate. One trial reported significantly more local reactions at the injection site with intramuscular quinine compared to artemether. None of the trials was adequately powered to demonstrate equivalence.</p> <p>Conclusion</p> <p>There was no evidence that treatment of children with severe malaria with parenteral artemisinin derivatives was associated with lower mortality or long-term morbidity compared to parenteral quinine. Future studies require adequately powered equivalence trial design to decide whether both drugs are equally effective.</p

Does health intervention improve socioeconomic inequalities of neonatal, infant and child mortality? Evidence from Matlab, Bangladesh

<p>Abstract</p> <p>Background</p> <p>Although there are wide variations in mortality between developed and developing countries, socioeconomic inequalities in health exist in both the societies. The study examined socioeconomic inequalities of neonatal, infant and child mortality using data from the Matlab Health and Demographic Surveillance System of the International Centre for Diarrhoeal Disease Research, Bangladesh (ICDDR,B).</p> <p>Methods</p> <p>Four birth cohorts (1983–85, 1988–90, 1993–95, 1998–00) were followed for five years for death and out-migration in two adjacent areas (ICDDR,B-service and government-service) with similar socioeconomic but differ health services. Based on asset quintiles, inequality was measured through both poor-rich ratio and concentration index.</p> <p>Results</p> <p>The study found that the socioeconomic inequalities of neonatal, infant and under-five mortality increased over time in both the ICDDR,B-service and government-service areas but it declined substantially for 1–4 years in the ICDDR,B- service area.</p> <p>Conclusion</p> <p>The study concluded that usual health intervention programs (non-targeted) do not reduce poor-rich gap, rather the gap increases initially but might decrease in long run if the program is very intensive.</p

Mapping inequalities in exclusive breastfeeding in low- and middle-income countries, 2000–2018

Exclusive breastfeeding (EBF)-giving infants only breast-milk for the first 6 months of life-is a component of optimal breastfeeding practices effective in preventing child morbidity and mortality. EBF practices are known to vary by population and comparable subnational estimates of prevalence and progress across low- and middle-income countries (LMICs) are required for planning policy and interventions. Here we present a geospatial analysis of EBF prevalence estimates from 2000 to 2018 across 94 LMICs mapped to policy-relevant administrative units (for example, districts), quantify subnational inequalities and their changes over time, and estimate probabilities of meeting the World Health Organization's Global Nutrition Target (WHO GNT) of ≥70% EBF prevalence by 2030. While six LMICs are projected to meet the WHO GNT of ≥70% EBF prevalence at a national scale, only three are predicted to meet the target in all their district-level units by 2030.This work was primarily supported by grant no. OPP1132415 from the Bill & Melinda Gates Foundation. Co-authors used by the Bill & Melinda Gates Foundation (E.G.P. and R.R.3) provided feedback on initial maps and drafts of this manuscript. L.G.A. has received support from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Brasil (CAPES), Código de Financiamento 001 and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) (grant nos. 404710/2018-2 and 310797/2019-5). O.O.Adetokunboh acknowledges the National Research Foundation, Department of Science and Innovation and South African Centre for Epidemiological Modelling and Analysis. M.Ausloos, A.Pana and C.H. are partially supported by a grant from the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project no. PN-III-P4-ID-PCCF-2016-0084. P.C.B. would like to acknowledge the support of F. Alam and A. Hussain. T.W.B. was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, funded by the German Federal Ministry of Education and Research. K.Deribe is supported by the Wellcome Trust (grant no. 201900/Z/16/Z) as part of his international intermediate fellowship. C.H. and A.Pana are partially supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project no. PN-III-P2-2.1-SOL-2020-2-0351. B.Hwang is partially supported by China Medical University (CMU109-MF-63), Taichung, Taiwan. M.Khan acknowledges Jatiya Kabi Kazi Nazrul Islam University for their support. A.M.K. acknowledges the other collaborators and the corresponding author. Y.K. was supported by the Research Management Centre, Xiamen University Malaysia (grant no. XMUMRF/2020-C6/ITM/0004). K.Krishan is supported by a DST PURSE grant and UGC Centre of Advanced Study (CAS II) awarded to the Department of Anthropology, Panjab University, Chandigarh, India. M.Kumar would like to acknowledge FIC/NIH K43 TW010716-03. I.L. is a member of the Sistema Nacional de Investigación (SNI), which is supported by the Secretaría Nacional de Ciencia, Tecnología e Innovación (SENACYT), Panamá. M.L. was supported by China Medical University, Taiwan (CMU109-N-22 and CMU109-MF-118). W.M. is currently a programme analyst in Population and Development at the United Nations Population Fund (UNFPA) Country Office in Peru, which does not necessarily endorses this study. D.E.N. acknowledges Cochrane South Africa, South African Medical Research Council. G.C.P. is supported by an NHMRC research fellowship. P.Rathi acknowledges support from Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, India. Ramu Rawat acknowledges the support of the GBD Secretariat for supporting the reviewing and collaboration of this paper. B.R. acknowledges support from Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal. A.Ribeiro was supported by National Funds through FCT, under the programme of ‘Stimulus of Scientific Employment—Individual Support’ within the contract no. info:eu-repo/grantAgreement/FCT/CEEC IND 2018/CEECIND/02386/2018/CP1538/CT0001/PT. S.Sajadi acknowledges colleagues at Global Burden of Diseases and Local Burden of Disease. A.M.S. acknowledges the support from the Egyptian Fulbright Mission Program. F.S. was supported by the Shenzhen Science and Technology Program (grant no. KQTD20190929172835662). A.Sheikh is supported by Health Data Research UK. B.K.S. acknowledges Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal for all the academic support. B.U. acknowledges support from Manipal Academy of Higher Education, Manipal. C.S.W. is supported by the South African Medical Research Council. Y.Z. was supported by Science and Technology Research Project of Hubei Provincial Department of Education (grant no. Q20201104) and Outstanding Young and Middle-aged Technology Innovation Team Project of Hubei Provincial Department of Education (grant no. T2020003). The funders of the study had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication. All maps presented in this study are generated by the authors and no permissions are required to publish them

Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950-2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019.

BACKGROUND: Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019. METHODS: 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10-14 and 50-54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed age-specific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. FINDINGS: The global TFR decreased from 2·72 (95% uncertainty interval [UI] 2·66-2·79) in 2000 to 2·31 (2·17-2·46) in 2019. Global annual livebirths increased from 134·5 million (131·5-137·8) in 2000 to a peak of 139·6 million (133·0-146·9) in 2016. Global livebirths then declined to 135·3 million (127·2-144·1) in 2019. Of the 204 countries and territories included in this study, in 2019, 102 had a TFR lower than 2·1, which is considered a good approximation of replacement-level fertility. All countries in sub-Saharan Africa had TFRs above replacement level in 2019 and accounted for 27·1% (95% UI 26·4-27·8) of global livebirths. Global life expectancy at birth increased from 67·2 years (95% UI 66·8-67·6) in 2000 to 73·5 years (72·8-74·3) in 2019. The total number of deaths increased from 50·7 million (49·5-51·9) in 2000 to 56·5 million (53·7-59·2) in 2019. Under-5 deaths declined from 9·6 million (9·1-10·3) in 2000 to 5·0 million (4·3-6·0) in 2019. Global population increased by 25·7%, from 6·2 billion (6·0-6·3) in 2000 to 7·7 billion (7·5-8·0) in 2019. In 2019, 34 countries had negative natural rates of increase; in 17 of these, the population declined because immigration was not sufficient to counteract the negative rate of decline. Globally, HALE increased from 58·6 years (56·1-60·8) in 2000 to 63·5 years (60·8-66·1) in 2019. HALE increased in 202 of 204 countries and territories between 2000 and 2019. INTERPRETATION: Over the past 20 years, fertility rates have been dropping steadily and life expectancy has been increasing, with few exceptions. Much of this change follows historical patterns linking social and economic determinants, such as those captured by the GBD Socio-demographic Index, with demographic outcomes. More recently, several countries have experienced a combination of low fertility and stagnating improvement in mortality rates, pushing more populations into the late stages of the demographic transition. Tracking demographic change and the emergence of new patterns will be essential for global health monitoring. FUNDING: Bill & Melinda Gates Foundation