Relevance of the Sustainable Development Goals (SDGs) to Adolescent Health Measurement: A Systematic Mapping of the SDG Framework and Global Adolescent Health Indicators.

PURPOSE: To assess the relevance of the Sustainable Development Goals (SDGs) framework for adolescent health measurement, both in terms of age disaggregation and different health domains captured, and how the adolescent health indicators recommended by the Global Action for Measurement of Adolescent Health (GAMA) can complement the SDG framework. METHODS: We conducted a desk review to systematically map all 248 SDG indicators using the UN metadata repository in three steps: 1) age-related mandates for SDG reporting; 2) linkages between the SDG indicators and priority areas for adolescent health measurement; 3) comparison between the GAMA indicators and the SDG framework. RESULTS: Of the 248 SDG indicators, 35 (14%) targeted an age range overlapping with adolescence (10-19 years) and 33 (13%) called for age disaggregation. Only one indicator (3.7.2 "adolescent birth rate") covered the entire 10-19 age range. Almost half (41%) of the SDG indicators were directly related to adolescent health, but only 33 of those (13% of all SDG indicators) overlapped with the ages 10-19, and 15 (6% of all SDG indicators) explicitly mandated age disaggregation. Among the 47 GAMA indicators, five corresponded to existing SDG indicators, and eight were adolescent-specific age adaptations. Several GAMA indicators shed light on aspects not tracked in the SDG framework, such as obesity, mental health, physical activity, and bullying among 10-19-year-olds. DISCUSSION: Adolescent health cannot be monitored comprehensively with the SDG framework alone. The GAMA indicators complement this framework via age-disaggregated adaptations and by tracking aspects of adolescent health currently absent from the SDGs.

Priority Indicators for Adolescent Health Measurement - Recommendations From the Global Action for Measurement of Adolescent Health (GAMA) Advisory Group.

PURPOSE: This article describes the selection of priority indicators for adolescent (10-19 years) health measurement proposed by the Global Action for Measurement of Adolescent health advisory group and partners, building on previous work identifying 33 core measurement areas and mapping 413 indicators across these areas. METHODS: The indicator selection process considered inputs from a broad range of stakeholders through a structured four-step approach: (1) definition of selection criteria and indicator scoring; (2) development of a draft list of indicators with metadata; (3) collection of public feedback through a survey; and (4) review of the feedback and finalization of the indicator list. As a part of the process, measurement gaps were also identified. RESULTS: Fifty-two priority indicators were identified, including 36 core indicators considered to be most important for measuring the health of all adolescents, one alternative indicator for settings where measuring the core indicator is not feasible, and 15 additional indicators for settings where further detail on a topic would add value. Of these indicators, 17 (33%) measure health behaviors and risks, 16 (31%) health outcomes and conditions, eight (15%) health determinants, five (10%) systems performance and interventions, four (8%) policies, programmes, laws, and two (4%) subjective well-being. DISCUSSION: A consensus list of priority indicators with metadata covering the most important health issues for adolescents was developed with structured inputs from a broad range of stakeholders. This list will now be pilot tested to assess the feasibility of indicator data collection to inform global, regional, national, and sub-national monitoring.

A Scoping Review of Adolescent Health Indicators.

PURPOSE: A host of recent initiatives relating to adolescent health have been accompanied by varying indicator recommendations, with little stakeholder coordination. We assessed currently included adolescent health-related indicators for their measurement focus, identified overlap across initiatives, and determined measurement gaps. METHODS: We conducted a scoping review to map the existing indicator landscape as depicted by major measurement initiatives. We classified indicators as per 33 previously identified core adolescent health measurement areas across five domains and by age groups. We also identified indicators common across measurement initiatives even if differing in details. RESULTS: We identified 413 indicators across 16 measurement initiatives, with most measuring health outcomes and conditions (162 [39%]) and health behaviors and risks (136 [33%]); followed by policies, programs, and laws (49 [12%]); health determinants (44 [11%]); and system performance and interventions (22 [5%]). Age specification was available for 221 (54%) indicators, with 51 (23%) focusing on the full adolescent age range (10-19 years), 1 (<1%) on 10-14 years, 27 (12%) on 15-19 years, and 142 (64%) on a broader age range including adolescents. No definitional information, such as numerator and denominator, was available for 138 indicators. We identified 236 distinct indicators after accounting for overlap. CONCLUSION: The adolescent health measurement landscape is vast and includes substantial variation among indicators purportedly assessing the same concept. Gaps persist in measuring systems performance and interventions; policies, programs, and laws; and younger adolescents' health. Addressing these gaps and harmonizing measurement is fundamental to improve program implementation and accountability for adolescent health globally.

A call for standardised age-disaggregated health data.

The 2030 Sustainable Development Goals agenda calls for health data to be disaggregated by age. However, age groupings used to record and report health data vary greatly, hindering the harmonisation, comparability, and usefulness of these data, within and across countries. This variability has become especially evident during the COVID-19 pandemic, when there was an urgent need for rapid cross-country analyses of epidemiological patterns by age to direct public health action, but such analyses were limited by the lack of standard age categories. In this Personal View, we propose a recommended set of age groupings to address this issue. These groupings are informed by age-specific patterns of morbidity, mortality, and health risks, and by opportunities for prevention and disease intervention. We recommend age groupings of 5 years for all health data, except for those younger than 5 years, during which time there are rapid biological and physiological changes that justify a finer disaggregation. Although the focus of this Personal View is on the standardisation of the analysis and display of age groups, we also outline the challenges faced in collecting data on exact age, especially for health facilities and surveillance data. The proposed age disaggregation should facilitate targeted, age-specific policies and actions for health care and disease management.

Global and regional levels and trends of child and adolescent morbidity from 2000 to 2016: an analysis of years lost due to disability (YLDs).

INTRODUCTION: Non-fatal health loss makes a substantial contribution to the total disease burden among children and adolescents. An analysis of these morbidity patterns is essential to plan interventions that improve the health and well-being of children and adolescents. Our objective was to describe current levels and trends in the non-fatal disease burden from 2000 to 2016 among children and adolescents aged 0-19 years. METHODS: We used years lost due to disability (YLD) estimates in WHO's Global Health Estimates to describe the non-fatal disease burden from 2000 to 2016 for the age groups 0-27 days, 28 days-11 months, 1-4 years, 5-9 years, 10-14 years and 15-19 years globally and by modified WHO region. To describe causes of YLDs, we used 18 broad cause groups and 54 specific cause categories. RESULTS: In 2016, the total number of YLDs globally among those aged 0-19 years was about 130 million, or 51 per 1000 population, ranging from 30 among neonates aged 0-27 days to 67 among older adolescents aged 15-19 years. Global progress since 2000 in reducing the non-fatal disease burden has been limited (53 per 1000 in 2000 for children and adolescents aged 0-19 years). The most important causes of YLDs included iron-deficiency anaemia and skin diseases for both sexes, across age groups and regions. For young children under 5 years of age, congenital anomalies, protein-energy malnutrition and diarrhoeal diseases were important causes of YLDs, while childhood behavioural disorders, asthma, anxiety disorders and depressive disorders were important causes for older children and adolescents. We found important variations between sexes and between regions, particularly among adolescents, that need to be addressed context-specifically. CONCLUSION: The disappointingly slow progress in reducing the global non-fatal disease burden among children and adolescents contrasts starkly with the major reductions in mortality over the first 17 years of this century. More effective action is needed to reduce the non-fatal disease burden among children and adolescents, with interventions tailored for each age group, sex and world region.

Effective coverage measurement in maternal, newborn, child, and adolescent health and nutrition: progress, future prospects, and implications for quality health systems.

Intervention coverage-the proportion of the population with a health-care need who receive care-does not account for intervention quality and potentially overestimates health benefits of services provided to populations. Effective coverage introduces the dimension of quality of care to the measurement of intervention coverage. Many definitions and methodological approaches to measuring effective coverage have been developed, resulting in confusion over definition, calculation, interpretation, and monitoring of these measures. To develop a consensus on the definition and measurement of effective coverage for maternal, newborn, child, and adolescent health and nutrition (MNCAHN), WHO and UNICEF convened a group of experts, the Effective Coverage Think Tank Group, to make recommendations for standardising the definition of effective coverage, measurement approaches for effective coverage, indicators of effective coverage in MNCAHN, and to develop future effective coverage research priorities. Via a series of consultations, the group recommended that effective coverage be defined as the proportion of a population in need of a service that resulted in a positive health outcome from the service. The proposed effective coverage measures and care cascade steps can be applied to further develop effective coverage measures across a broad range of MNCAHN services. Furthermore, advances in measurement of effective coverage could improve monitoring efforts towards the achievement of universal health coverage.

Global trends in insufficient physical activity among adolescents: a pooled analysis of 298 population-based surveys with 1·6 million participants.

BACKGROUND: Physical activity has many health benefits for young people. In 2018, WHO launched More Active People for a Healthier World, a new global action on physical activity, including new targets of a 15% relative reduction of global prevalence of insufficient physical activity by 2030 among adolescents and adults. We describe current prevalence and trends of insufficient physical activity among school-going adolescents aged 11-17 years by country, region, and globally. METHODS: We did a pooled analysis of cross-sectional survey data that were collected through random sampling with a sample size of at least 100 individuals, were representative of a national or defined subnational population, and reported prevalence of of insufficient physical activity by sex in adolescents. Prevalence had to be reported for at least three of the years of age within the 10-19-year age range. We estimated the prevalence of insufficient physical activity in school-going adolescents aged 11-17 years (combined and by sex) for individual countries, for four World Bank income groups, nine regions, and globally for the years 2001-16. To derive a standard definition of insufficient physical activity and to adjust for urban-only survey coverage, we used regression models. We estimated time trends using multilevel mixed-effects modelling. FINDINGS: We used data from 298 school-based surveys from 146 countries, territories, and areas including 1·6 million students aged 11-17 years. Globally, in 2016, 81·0% (95% uncertainty interval 77·8-87·7) of students aged 11-17 years were insufficiently physically active (77·6% [76·1-80·4] of boys and 84·7% [83·0-88·2] of girls). Although prevalence of insufficient physical activity significantly decreased between 2001 and 2016 for boys (from 80·1% [78·3-81·6] in 2001), there was no significant change for girls (from 85·1% [83·1-88·0] in 2001). There was no clear pattern according to country income group: insufficient activity prevalence in 2016 was 84·9% (82·6-88·2) in low-income countries, 79·3% (77·2-87·5) in lower-middle-income countries, 83·9% (79·5-89·2) in upper-middle-income countries, and 79·4% (74·0-86·2) in high-income countries. The region with the highest prevalence of insufficient activity in 2016 was high-income Asia Pacific for both boys (89·0%, 62·8-92·2) and girls (95·6%, 73·7-97·9). The regions with the lowest prevalence were high-income western countries for boys (72·1%, 71·1-73·6), and south Asia for girls (77·5%, 72·8-89·3). In 2016, 27 countries had a prevalence of insufficient activity of 90% or more for girls, whereas this was the case for two countries for boys. INTERPRETATION: The majority of adolescents do not meet current physical activity guidelines. Urgent scaling up of implementation of known effective policies and programmes is needed to increase activity in adolescents. Investment and leadership at all levels to intervene on the multiple causes and inequities that might perpetuate the low participation in physical activity and sex differences, as well as engagement of youth themselves, will be vital to strengthen the opportunities for physical activity in all communities. Such action will improve the health of this and future young generations and support achieving the 2030 Sustainable Development Goals. FUNDING: WHO.

Socioeconomic inequalities in risk factors for non communicable diseases in low-income and middle-income countries: results from the World Health Survey.

BACKGROUND: Monitoring inequalities in non communicable disease risk factor prevalence can help to inform and target effective interventions. The prevalence of current daily smoking, low fruit and vegetable consumption, physical inactivity, and heavy episodic alcohol drinking were quantified and compared across wealth and education levels in low- and middle-income country groups. METHODS: This study included self-reported data from 232,056 adult participants in 48 countries, derived from the 2002-2004 World Health Survey. Data were stratified by sex and low- or middle-income country status. The main outcome measurements were risk factor prevalence rates reported by wealth quintile and five levels of educational attainment. Socioeconomic inequalities were measured using the slope index of inequality, reflecting differences in prevalence rates, and the relative index of inequality, reflecting the prevalence ratio between the two extremes of wealth or education accounting for the entire distribution. Data were adjusted for confounding factors: sex, age, marital status, area of residence, and country of residence. RESULTS: Smoking and low fruit and vegetable consumption were significantly higher among lower socioeconomic groups. The highest wealth-related absolute inequality was seen in smoking among men of low- income country group (slope index of inequality 23.0 percentage points; 95% confidence interval 19.6, 26.4). The slope index of inequality for low fruit and vegetable consumption across the entire distribution of education was around 8 percentage points in both sexes and both country income groups. Physical inactivity was less prevalent in populations of low socioeconomic status, especially in low-income countries (relative index of inequality: (men) 0.46, 95% confidence interval 0.33, 0.64; (women) 0.52, 95% confidence interval 0.42, 0.65). Mixed patterns were found for heavy drinking. CONCLUSIONS: Disaggregated analysis of the prevalence of non-communicable disease risk factors demonstrated different patterns and varying degrees of socioeconomic inequalities across low- and middle-income settings. Interventions should aim to reach and achieve sustained benefits for high-risk populations.

Global physical activity levels: surveillance progress, pitfalls, and prospects.

To implement effective non-communicable disease prevention programmes, policy makers need data for physical activity levels and trends. In this report, we describe physical activity levels worldwide with data for adults (15 years or older) from 122 countries and for adolescents (13-15-years-old) from 105 countries. Worldwide, 31·1% (95% CI 30·9-31·2) of adults are physically inactive, with proportions ranging from 17·0% (16·8-17·2) in southeast Asia to about 43% in the Americas and the eastern Mediterranean. Inactivity rises with age, is higher in women than in men, and is increased in high-income countries. The proportion of 13-15-year-olds doing fewer than 60 min of physical activity of moderate to vigorous intensity per day is 80·3% (80·1-80·5); boys are more active than are girls. Continued improvement in monitoring of physical activity would help to guide development of policies and programmes to increase activity levels and to reduce the burden of non-communicable diseases.