Screening, prevalence, treatment and control of kidney disease in patients with type 1 and type 2 diabetes in low-to-middle-income countries (2005–2017): the International Diabetes Management Practices Study (IDMPS)

Diabetes is the leading cause of kidney disease worldwide. There is limited information on screening, treatment and control of kidney disease in patients with diabetes in low-to-middle-income countries (LMICs).Fil: Mbanya, Jean Claude. Université de Yaoundé ; CamerúnFil: Aschner, Pablo. Hospital Universitario San Ignacio; Colombia. Pontificia Universidad Javeriana; ColombiaFil: Gagliardino, Juan Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Endocrinología Experimental y Aplicada. Universidad Nacional de La Plata. Facultad de Ciencias Médicas. Centro de Endocrinología Experimental y Aplicada; ArgentinaFil: Ilkova, Hasan. İstanbul S. Zaim Üniversitesi; TurquíaFil: Lavalle, Fernando. Universidad Autónoma de Nuevo Leon, Facultad de Medicina; MéxicoFil: Ramachandran, Ambady. India Diabetes Research Foundation; IndiaFil: Chantelot, Jean Marc. Sanofi; FranciaFil: Chan, Juliana C. N.. Prince of Wales Hospital; Chin

Association of serum leptin and adiponectin with anthropomorphic indices of obesity, blood lipids and insulin resistance in a Sub-Saharan African population

Abstract Background There is little data on the metabolic effects of adipokines in sub-Saharan African populations. This study aimed to explore the potential relationship of leptin and adiponectin, with obesity, plasma lipids and insulin resistance in a Cameroonian population. Methods We enrolled 167 men and 309 women aged ≥18 years from the general population in Cameroon. Data were collected on waist circumference (WC), body mass index (BMI), waist-to-hip ratio (WHR), body fat (BF%), fasting blood glucose, plasma lipids, adiponectin, leptin, insulin and homeostasis model for assessment of insulin resistance (HOMA-IR). Pearson’s correlation and multiple stepwise linear regression analyses were used to determine correlates of leptin and adiponectin serum levels. Results The prevalence of obesity was higher in women compared to men (p < 0.0001), and Central obesity which is more prevalent particularly in women (WC = 42.4 %, WHR = 42.3 %), is almost for 90 % comparable to %BF (42.7 %). Adiponectin negatively with BMI (r = −0.294, p < 0.0001), WC (r = −0.294, p < 0.0001), %BF (r = −0.122, p = 0.028), WHR (r = −0.143, p = 0.009), triglycerides (r = −0.141, p = 0.011), HOMA-IR (r = −0.145, p = 0.027) and insulin (r = −0.130, p = 0.048). Leptin positively correlated with BMI (r = 0.628), WC (r = 0.530), BF% (r = 0.720), (all p < 0.0001); with DBP (r = 0.112, p = 0.043), total cholesterol (r = 0.324, p < 0.0001), LDL-cholesterol (r = 0.298, p < 0.0001), insulin (r = 0.320, p < 0.001 and HOMA-IR (r = 0.272, p < 0.0001). In multiple stepwise regression analysis, adiponectin was negatively associated with WC (β = −0.38, p = 0.001) and BF% (β = 0.33, p < 0.0001), while leptin was positively associated with BF% (β = 0.60, p < 0.0001), total cholesterol (β = 0.11, p = 0.02) and HOMA-IR (β = 0.11, p = 0.02). When controlled for gender, HOMA-IR was found significantly associated to adiponectin (β = 0.13, p = 0.046), but not BF%, while the association previously found between leptin and HOMA-IR disappeared; BMI and WC were significantly associated with leptin (β = 0.18, p = 0.04 & β = 0.19, p = 0.02 respectively). Conclusion This study, which includes a population who was not receiving potentially confounding medications, confirms the associations previously observed of adiponectin with reduced adiposity especially central adiposity and improved insulin sensitivity. Confirmatory associations were also observed between leptin and obesity, blood lipids and insulin resistance for the first time in an African population. Gender was significant covariate interacting with insulin sensitivity/insulin resistance and obesity indexes associations in this population

Persistent poor glycaemic control in individuals with type 2 diabetes in developing countries: 12 years of real-world evidence of the International Diabetes Management Practices Study (IDMPS)

We evaluated the secular trend of glycaemic control in individuals with type 2 diabetes in developing countries, where data are limited. Erratum in Correction to: Persistent poor glycaemic control in individuals with type 2 diabetes in developing countries: 12 years of real-world evidence of the International Diabetes Management Practices Study (IDMPS). Aschner P, Gagliardino JJ, Ilkova H, Lavalle F, Ramachandran A, Mbanya JC, Shestakova M, Chantelot JM, Chan JCN. Diabetologia. 2020 May;63(5):1088-1089. doi: 10.1007/s00125-020-05118-3.Fil: Aschner, Pablo. Pontificia Universidad Javeriana; ColombiaFil: Gagliardino, Juan Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Endocrinología Experimental y Aplicada. Universidad Nacional de La Plata. Facultad de Ciencias Médicas. Centro de Endocrinología Experimental y Aplicada; ArgentinaFil: Ilkova, Hasan. İstanbul Üniversitesi; TurquíaFil: Lavalle, Fernando. universidad Autónoma de Nueva León; MéxicoFil: Ramachandran, Ambady. India Diabetes Research Foundation; IndiaFil: Mbanya, Jean Claude. Université de Yaoundé I; CamerúnFil: Shestakova, Marina. Endocrinology Research Center Moscow; RusiaFil: Chantelot, Jean Marc. Sanofi; FranciaFil: Chan, Juliana C. N.. The Chinese University of Hong Kong; Chin

Overweight and obesity in children aged 3-13 years in urban Cameroon:a cross-sectional study of prevalence and association with socio-economic status

BACKGROUND: Childhood overweight/obesity is increasing rapidly in developing countries. There is a need to provide more evidence on its burden in sub-Saharan Africa, and to identify associated factors in order to set preventive measures. We aimed to determine the prevalence of overweight/obesity and assess its association with the socioeconomic status in nursery and primary school children in urban Cameroon. METHODS: In this cross-sectional study, we included by multi-staged cluster random sampling 1343 children from high (HSES, n = 673) and low (LSES, n = 670) socioeconomic status schools in Douala. Parent/child demographic data were collected, and children’s anthropometric parameters were measured using validated methods. The World Health Organization body mass index-for-age reference curves were used. RESULTS: The prevalence of overweight/obesity was 12.5% (13.2% in girls, 11.8% in boys). The risk of overweight/obesity was 2.40 (95% CI 1.70, 3.40) higher in HSES children compared to LSES after adjusting for age and gender. However this association was attenuated to 1.18 (95% CI 0.59, 2.35) once adjustment had been made for a range of potential confounders. CONCLUSIONS: Overweight/obesity is relatively common in sub-Saharan African children and prevalence is associated with HSES. However, this association may be mediated by sweet drink consumption, passive means of travel to school and not doing sport at school. We suggest that these potentially modifiable behaviors may be effective targets for obesity prevention. Further studies should specifically focus on unhealthy behaviors that mediate overweight/obesity as well as other non communicable diseases in children. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40608-017-0146-4) contains supplementary material, which is available to authorized users

Trends in obesity and diabetes across Africa from 1980 to 2014: an analysis of pooled population-based studies

Background: The 2016 Dar Es Salaam Call to Action on Diabetes and Other non-communicable diseases (NCDs) advocates national multi-sectoral NCD strategies and action plans based on available data and information from countries of sub-Saharan Africa and beyond. We estimated trends from 1980 to 2014 in age-standardized mean body mass index (BMI) and diabetes prevalence in these countries, in order to assess the co-progression and assist policy formulation. Methods: We pooled data from African and worldwide population-based studies which measured height, weight and biomarkers to assess diabetes status in adults aged ≥ 18 years. A Bayesian hierarchical model was used to estimate trends by sex for 200 countries and territories including 53 countries across five African regions (central, eastern, northern, southern and western), in mean BMI and diabetes prevalence (defined as either fasting plasma glucose of ≥ 7.0 mmol/l, history of diabetes diagnosis, or use of insulin or oral glucose control agents). Results: African data came from 245 population-based surveys (1.2 million participants) for BMI and 76 surveys (182 000 participants) for diabetes prevalence estimates. Countries with the highest number of data sources for BMI were South Africa (n = 17), Nigeria (n = 15) and Egypt (n = 13); and for diabetes estimates, Tanzania (n = 8), Tunisia (n = 7), and Cameroon, Egypt and South Africa (all n = 6). The age-standardized mean BMI increased from 21.0 kg/m2 (95% credible interval: 20.3–21.7) to 23.0 kg/m2 (22.7–23.3) in men, and from 21.9 kg/m2 (21.3–22.5) to 24.9 kg/m2 (24.6–25.1) in women. The age-standardized prevalence of diabetes increased from 3.4% (1.5–6.3) to 8.5% (6.5–10.8) in men, and from 4.1% (2.0–7.5) to 8.9% (6.9–11.2) in women. Estimates in northern and southern regions were mostly higher than the global average; those in central, eastern and western regions were lower than global averages. A positive association (correlation coefficient ≃ 0.9) was observed between mean BMI and diabetes prevalence in both sexes in 1980 and 2014. Conclusions: These estimates, based on limited data sources, confirm the rapidly increasing burden of diabetes in Africa. This rise is being driven, at least in part, by increasing adiposity, with regional variations in observed trends. African countries’ efforts to prevent and control diabetes and obesity should integrate the setting up of reliable monitoring systems, consistent with the World Health Organization’s Global Monitoring System Framework

Cardiovascular disease, chronic kidney disease, and diabetes mortality burden of cardiometabolic risk factors from 1980 to 2010: A comparative risk assessment

Background: High blood pressure, blood glucose, serum cholesterol, and BMI are risk factors for cardiovascular diseases and some of these factors also increase the risk of chronic kidney disease and diabetes. We estimated mortality from cardiovascular diseases, chronic kidney disease, and diabetes that was attributable to these four cardiometabolic risk factors for all countries and regions from 1980 to 2010. Methods: We used data for exposure to risk factors by country, age group, and sex from pooled analyses of population-based health surveys. We obtained relative risks for the effects of risk factors on cause-specific mortality from meta-analyses of large prospective studies. We calculated the population attributable fractions for each risk factor alone, and for the combination of all risk factors, accounting for multicausality and for mediation of the effects of BMI by the other three risks. We calculated attributable deaths by multiplying the cause-specific population attributable fractions by the number of disease-specific deaths. We obtained cause-specific mortality from the Global Burden of Diseases, Injuries, and Risk Factors 2010 Study. We propagated the uncertainties of all the inputs to the final estimates. Findings: In 2010, high blood pressure was the leading risk factor for deaths due to cardiovascular diseases, chronic kidney disease, and diabetes in every region, causing more than 40% of worldwide deaths from these diseases; high BMI and glucose were each responsible for about 15% of deaths, and high cholesterol for more than 10%. After accounting for multicausality, 63% (10·8 million deaths, 95% CI 10·1-11·5) of deaths from these diseases in 2010 were attributable to the combined effect of these four metabolic risk factors, compared with 67% (7·1 million deaths, 6·6-7·6) in 1980. The mortality burden of high BMI and glucose nearly doubled from 1980 to 2010. At the country level, age-standardised death rates from these diseases attributable to the combined effects of these four risk factors surpassed 925 deaths per 100 000 for men in Belarus, Kazakhstan, and Mongolia, but were less than 130 deaths per 100 000 for women and less than 200 for men in some high-income countries including Australia, Canada, France, Japan, the Netherlands, Singapore, South Korea, and Spain. Interpretation: The salient features of the cardiometabolic disease and risk factor epidemic at the beginning of the 21st century are high blood pressure and an increasing effect of obesity and diabetes. The mortality burden of cardiometabolic risk factors has shifted from high-income to low-income and middle-income countries. Lowering cardiometabolic risks through dietary, behavioural, and pharmacological interventions should be a part of the global response to non-communicable diseases. Funding: UK Medical Research Council, US National Institutes of Health. © 2014 Elsevier Ltd

Contributions of mean and shape of blood pressure distribution to worldwide trends and variations in raised blood pressure: A pooled analysis of 1018 population-based measurement studies with 88.6 million participants

© The Author(s) 2018. Background: Change in the prevalence of raised blood pressure could be due to both shifts in the entire distribution of blood pressure (representing the combined effects of public health interventions and secular trends) and changes in its high-blood-pressure tail (representing successful clinical interventions to control blood pressure in the hypertensive population). Our aim was to quantify the contributions of these two phenomena to the worldwide trends in the prevalence of raised blood pressure. Methods: We pooled 1018 population-based studies with blood pressure measurements on 88.6 million participants from 1985 to 2016. We first calculated mean systolic blood pressure (SBP), mean diastolic blood pressure (DBP) and prevalence of raised blood pressure by sex and 10-year age group from 20-29 years to 70-79 years in each study, taking into account complex survey design and survey sample weights, where relevant. We used a linear mixed effect model to quantify the association between (probittransformed) prevalence of raised blood pressure and age-group- and sex-specific mean blood pressure. We calculated the contributions of change in mean SBP and DBP, and of change in the prevalence-mean association, to the change in prevalence of raised blood pressure. Results: In 2005-16, at the same level of population mean SBP and DBP, men and women in South Asia and in Central Asia, the Middle East and North Africa would have the highest prevalence of raised blood pressure, and men and women in the highincome Asia Pacific and high-income Western regions would have the lowest. In most region-sex-age groups where the prevalence of raised blood pressure declined, one half or more of the decline was due to the decline in mean blood pressure. Where prevalence of raised blood pressure has increased, the change was entirely driven by increasing mean blood pressure, offset partly by the change in the prevalence-mean association. Conclusions: Change in mean blood pressure is the main driver of the worldwide change in the prevalence of raised blood pressure, but change in the high-blood-pressure tail of the distribution has also contributed to the change in prevalence, especially in older age groups

Height and body-mass index trajectories of school-aged children and adolescents from 1985 to 2019 in 200 countries and territories: a pooled analysis of 2181 population-based studies with 65 million participants

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/m2. 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, they had a much larger gain in height than they did in BMI. The unhealthiest changes—gaining too little height, too much weight for their height compared with children in other countries, or both—occurred in many countries in sub-Saharan Africa, New Zealand, and the USA for boys and girls; in Malaysia and some Pacific island nations for boys; and in Mexico for girls. Interpretation The height and BMI trajectories over age and time of school-aged children and adolescents are highly variable across countries, which indicates heterogeneous nutritional quality and lifelong health advantages and risks