Summary Background Comparable global data on health and nutrition of school-aged children and adolescents are scarce. We aimed to estimate age trajectories and time trends in mean height and mean body-mass index (BMI), which measures weight gain beyond what is expected from height gain, for school-aged children and adolescents. Methods For this pooled analysis, we used a database of cardiometabolic risk factors collated by the Non-Communicable Disease Risk Factor Collaboration. We applied a Bayesian hierarchical model to estimate trends from 1985 to 2019 in mean height and mean BMI in 1-year age groups for ages 5–19 years. The model allowed for non-linear changes over time in mean height and mean BMI and for non-linear changes with age of children and adolescents, including periods of rapid growth during adolescence. Findings We pooled data from 2181 population-based studies, with measurements of height and weight in 65 million participants in 200 countries and territories. In 2019, we estimated a difference of 20 cm or higher in mean height of 19-year-old adolescents between countries with the tallest populations (the Netherlands, Montenegro, Estonia, and Bosnia and Herzegovina for boys; and the Netherlands, Montenegro, Denmark, and Iceland for girls) and those with the shortest populations (Timor-Leste, Laos, Solomon Islands, and Papua New Guinea for boys; and Guatemala, Bangladesh, Nepal, and Timor-Leste for girls). In the same year, the difference between the highest mean BMI (in Pacific island countries, Kuwait, Bahrain, The Bahamas, Chile, the USA, and New Zealand for both boys and girls and in South Africa for girls) and lowest mean BMI (in India, Bangladesh, Timor-Leste, Ethiopia, and Chad for boys and girls; and in Japan and Romania for girls) was approximately 9–10 kg/m 2 . In some countries, children aged 5 years started with healthier height or BMI than the global median and, in some cases, as healthy as the best performing countries, but they became progressively less healthy compared with their comparators as they grew older by not growing as tall (eg, boys in Austria and Barbados, and girls in Belgium and Puerto Rico) or gaining too much weight for their height (eg, girls and boys in Kuwait, Bahrain, Fiji, Jamaica, and Mexico; and girls in South Africa and New Zealand). In other countries, growing children overtook the height of their comparators (eg, Latvia, Czech Republic, Morocco, and Iran) or curbed their weight gain (eg, Italy, France, and Croatia) in late childhood and adolescence. When changes in both height and BMI were considered, girls in South Korea, Vietnam, Saudi Arabia, Turkey, and some central Asian countries (eg, Armenia and Azerbaijan), and boys in central and western Europe (eg, Portugal, Denmark, Poland, and Montenegro) had the healthiest changes in anthropometric status over the past 3·5 decades because, compared with children and adolescents in other countries, the...
From 1985 to 2016, the prevalence of underweight decreased, and that of obesity and severe obesity increased, in most regions, with significant variation in the magnitude of these changes across regions. We investigated how much change in mean body mass index (BMI) explains changes in the prevalence of underweight, obesity, and severe obesity in different regions using data from 2896 population-based studies with 187 million participants. Changes in the prevalence of underweight and total obesity, and to a lesser extent severe obesity, are largely driven by shifts in the distribution of BMI, with smaller contributions from changes in the shape of the distribution. In East and Southeast Asia and sub-Saharan Africa, the underweight tail of the BMI distribution was left behind as the distribution shifted. There is a need for policies that address all forms of malnutrition by making healthy foods accessible and affordable, while restricting unhealthy foods through fiscal and regulatory restrictions.
Objective: Antenatal care (ANC) utilization remains a challenge in efforts to reduce maternal mortality and improve maternal health in Uganda. This study aimed to identify perceived barriers to utilization of ANC services in a rural post-conflict area in northern Uganda. Methods: A qualitative study using in-depth interviews and focus group discussions of seventeen participants (pregnant women, health workers and a traditional birth attendant). The study was informed through a phenomenological approach to capture perceived barriers to utilization of ANC. The study was carried out in post-conflict Awach sub-county, Gulu District, northern Uganda. Data was analyzed using inductive conventional content analysis. Results: The main perceived barriers to ANC utilization were identified as: poor quality of care including poor attitude of health workers; socio-cultural practices not being successfully aligned to ANC; and lack of support from the husband including difficulties in encouraging him to attend ANC. Additionally, institutional structures and procedures at the health centers in terms of compulsory HIV testing and material requirements and transportation were perceived to prevent some pregnant women from attending ANC. Conclusions: Identifying local barriers to ANC utilization are important and should be considered when planning ANC programs. We propose that future efforts should focus on how to ensure a good patient-provider relationship and perceived quality of care, and further how to improve inter-spousal communication and sensitization of husbands for increased involvement in ANC. We recommend more research on how socio-cultural context can meaningfully be aligned to ANC to improve maternal health and reduce maternal mortality.
Background Multimorbidity is an increasing public health concern and is associated with a range of further adverse outcomes. Identification of disease patterns as well as characteristics of populations affected by multimorbidity is important for prevention strategies to identify those at risk. Aim The aim of the study was to identify and describe demographic characteristics of multimorbidity classes in three age groups (16-44 years, 45-64 years, and 65+ years). Methods Based on register information on 47 chronic diseases and conditions, we used latent class analysis to identify multimorbidity classes in a random sample of the Danish population (n = 470,794). Information on sociodemographic characteristics (age, sex, region of origin, educational level, employment status, and marital status) was obtained from registers and linked to the study population. Age-and sex-adjusted multinomial logistic regression models were used to examine associations between multimorbidity classes and sociodemographic characteristics. Results We identified seven classes among individuals in the age groups 45-64 years and 65+ years and five classes in the age group 16-44 years. Overall, the classes were similar in the three age groups, but varied in size, i.e. the class 'No or few diseases' was larger in the younger age group. The class 'Many diseases' (a class with both somatic diseases and mental illnesses) was only seen in individuals aged 45-64 years and 65+ years. There were social inequalities in odds of belonging to the multimorbidity classes compared to the healthier class. These social inequalities varied but were especially strong in the classes named 'Many diseases' and 'Mental illness, epilepsy'.
Abstractobjective To determine the prevalence of adult malnutrition and associated risk factors in a postconflict area of northern Uganda.methods A cross-sectional community survey was performed from September 2011 to June 2013. All registered residents in Gulu Health and Demographic Surveillance System aged 15 years and older were considered eligible. Trained field assistants collected anthropometric measurements (weight and height) and administered questionnaires with information on sociodemographic characteristics, food security, smoking and alcohol. Nutritional status was classified by body mass index.results In total, 2062 men and 2924 women participated and were included in the analyses. The prevalence of underweight was 22.3% for men and 16.0% for women, whereas the prevalence of overweight was 1.5% for men and 7.6% for women. In men, underweight was associated with younger (15-19 years) and older age (>55 years) (P < 0.001), being divorced/separated [odds ratio (OR) = 1.91 (95% confidence interval (CI): 1.21-2.99] and smoking (OR = 2.13, 95% CI: 1.67-2.73). For women, underweight was associated with older age (P < 0.001) and hungry-gap rainy season (May-July) (OR = 1.33, 95% CI: 1.04-1.69). Widowed or divorced/separated women were not more likely to be underweight. No association was found between education, alcohol consumption or food security score and underweight.conclusions Our findings are not in line with the conventional target groups in nutritional programmes and highlight the importance of continuous health and nutritional assessments of all population groups that reflect local social determinants and family structures.
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