Amani Siyam

Post-partum weight change patterns in the WHO Multicentre Growth Reference Study

The interplay of factors that affect post-partum loss or retention of weight gained during pregnancy is not fully understood. The objective of this paper is to describe patterns of weight change in the six sites of the World Health Organization (WHO) Multicentre Growth Reference Study (MGRS) and explore variables that explain variation in weight change within and between sites. Mothers of 1743 breastfed children enrolled in the MGRS had weights measured at days 7, 14, 28 and 42 post-partum, monthly from 2 to 12 months and bimonthly thereafter until 24 months post-partum. Height, maternal age, parity and employment status were recorded and breastfeeding was monitored throughout the follow-up. Weight change patterns varied significantly among sites. Ghanaian and Omani mothers lost little or gained weight post-partum. In Brazil, India, Norway and USA, mothers on average lost weight during the first year followed by stabilization in the second year. Lactation intensity and duration explained little of the variation in weight change patterns. In most sites, obese mothers tended to lose less weight than normal-weight mothers. In Brazil and Oman, primiparous mothers lost about 1 kg more than multiparous mothers in the first 6 months. In India and Ghana, multiparous mothers lost about 0.6 kg more than primiparas in the second 6 months. Culturally defined mother-care practices probably play a role in weight change patterns among lactating women. This hypothesis should stimulate investigation into gestational weight gain and post-partum losses in different ethnocultural contexts.

Comparison of the World Health Organization Growth Velocity Standards With Existing US Reference Data

OBJECTIVE: The goal of this study was to compare World Health Organization (WHO) growth velocity standards with reference data based on US children. METHODS: Comparisons were made between reference values for weight and length gains based on serial data from US children and the WHO child growth standards. We compared weight velocities for boys and girls for selected percentiles (5th, 25th, 50th, 75th, and 95th) for 1-month intervals from birth to 6 months, 2-month intervals up to 12 months, and 3-month intervals up to 24 months. For length, we compared 2-month intervals from birth to 6 months and 3-month intervals up to 24 months. RESULTS: WHO and US monthly weight increments were similar at the 5th percentile up to 3 months of age; values for other US percentiles were below the WHO percentiles ∼150 g on average. From 3 months onward, the US values converged to a narrow range of <100 g between estimated percentiles. Two- and 3-month weight gains showed similar variations. Differences between the WHO and US values were more pronounced at the lower end of the distribution. For length, medians were in closer agreement, but as occurred with weight, values at the outer US percentiles converged to a narrower range with increasing age compared with those of the WHO standards. CONCLUSIONS: There are important differences between the WHO standards and the reference values for growth velocity based on US data. The WHO values are a better tool for assessing growth velocity and making clinical decisions.

Elaboración de valores de referencia de la OMS para el crecimiento de escolares y adolescentes

Introduction The need to develop an appropriate single growth reference for the screening, surveillance and monitoring of school-aged children and adolescents has been stirred by two contemporary events: the increasing public health concern over childhood obesity (1) and the April 2006 release of the WHO Child Growth Standards for preschool children based on a prescriptive approach. (2) As countries proceed with the implementation of growth standards for children under 5 years of age, the gap across all centiles between these standards and existing growth references for older children has become a matter of great concern. It is now widely accepted that using descriptive samples of populations that reflect a secular trend towards overweight and obesity to construct growth references results inadvertently in an undesirable upward skewness leading to an underestimation of overweight and obesity, and an overestimation of undernutrition. (3) The reference previously recommended by WHO for children above 5 years of age, i.e. the National Center for Health Statistics (NCHS)/WHO international growth reference, (4) has several drawbacks. (5) In particular, the body mass index-for-age reference, developed in 1991, (6) only starts at 9 years of age, groups data annually and covers a limited percentile range. Many countries pointed to the need to have body mass index (BMI) curves that start at 5 years and permit unrestricted calculation of percentile and z-score curves on a continuous age scale from 5 to 19 years. The need to harmonize growth assessment tools conceptually and pragmatically prompted an expert group meeting in January 2006 to evaluate the feasibility of developing a single international growth reference for school-aged children and adolescents. (7,8) The experts agreed that appropriate growth references for these age groups should be developed for clinical and public health applications. They also agreed that a multicentre study, similar to the one that led to the development of the WHO Child Growth Standards for 0 to 5 years, would not be feasible for older children, as it would not be possible to control the dynamics of their environment. Therefore, as an alternative, the experts suggested that a growth reference be constructed for this age group using existing historical data and discussed the criteria for selecting the data sets. WHO subsequently initiated a process to identify existing data sets from various countries. This process resulted in an initial identification of 115 candidate data sets from 45 countries, which were narrowed down to 34 data sets from 22 countries that met the inclusion criteria developed by the expert group. However, after further review, even these most promising studies showed great heterogeneity in methods and data quality, sample size, age categories, socioeconomic status of participating children and various other factors critical to growth curve construction. Therefore, it was unlikely that a growth reference constructed from these heterogeneous data sets would agree with the WHO Child Growth Standards at 5 years of age for the different anthropometric indicators needed (i.e. height-for-age, weight-for-age and BMI-for-age). In consequence, WHO proceeded to reconstruct the 1977 NCHS/WHO growth reference from 5 to 19 years, using the original sample (a non-obese sample with expected heights), supplemented with data from the WHO Child Growth Standards (to facilitate a smooth transition at 5 years), and applying the state-of-the-art statistical methods (9,10) used to develop standards for preschool children, that is, the Box-Cox power exponential (BCPE) method with appropriate diagnostic tools for the selection of best models. The purposes of this paper are to report the methods used to reconstruct the 1977 NCHS/WHO growth reference, to compare the resulting new curves (the 2007 WHO reference) with the 1977 NCHS/WHO charts, and to describe the transition at 5 years of age from the WHO standards for under-fives to these new curves for school-aged children and adolescents. …

Health workforce indicators: let's get real

Health workforce indicators?1 Those should be easy. We just need to count the numbers entering from training institutions or through re-entry, the numbers working, and the numbers exiting. If we know where these people work, we have the distribution of health workers within a country, and if we also have information on their competencies, responsiveness and productivity, we can know about their performance.

Health workforce metrics pre- and post-2015: a stimulus to public policy and planning

BackgroundEvidence-based health workforce policies are essential to ensure the provision of high-quality health services and to support the attainment of universal health coverage (UHC). This paper describes the main characteristics of available health workforce data for 74 of the 75 countries identified under the ‘Countdown to 2015’ initiative as accounting for more than 95% of the world’s maternal, newborn and child deaths. It also discusses best practices in the development of health workforce metrics post-2015.MethodsUsing available health workforce data from the Global Health Workforce Statistics database from the Global Health Observatory, we generated descriptive statistics to explore the current status, recent trends in the number of skilled health professionals (SHPs: physicians, nurses, midwives) per 10 000 population, and future requirements to achieve adequate levels of health care in the 74 countries. A rapid literature review was conducted to obtain an overview of the types of methods and the types of data sources used in human resources for health (HRH) studies.ResultsThere are large intercountry and interregional differences in the density of SHPs to progress towards UHC in Countdown countries: a median of 10.2 per 10 000 population with range 1.6 to 142 per 10 000. Substantial efforts have been made in some countries to increase the availability of SHPs as shown by a positive average exponential growth rate (AEGR) in SHPs in 51% of Countdown countries for which there are data. Many of these countries will require large investments to achieve levels of workforce availability commensurate with UHC and the health-related sustainable development goals (SDGs). The availability, quality and comparability of global health workforce metrics remain limited. Most published workforce studies are descriptive, but more sophisticated needs-based workforce planning methods are being developed.ConclusionsThere is a need for high-quality, comprehensive, interoperable sources of HRH data to support all policies towards UHC and the health-related SDGs. The recent WHO-led initiative of supporting countries in the development of National Health Workforce Accounts is a very promising move towards purposive health workforce metrics post-2015. Such data will allow more countries to apply the latest methods for health workforce planning.