Publications
163 results found
Rodriguez-Martinez A, Zhou B, Sophiea MK, et al., 2020, 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, The Lancet, Vol: 396, Pages: 1511-1524, ISSN: 0140-6736
SummaryBackgroundComparable 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.MethodsFor 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.FindingsWe 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
Carrillo-Larco RM, 2020, COVID-19 data sources in Latin America and the Caribbean, Travel Medicine and Infectious Disease, Vol: 38, Pages: 1-3, ISSN: 1477-8939
Carrillo Larco R, Bennett JE, Di Cesare M, et al., 2020, The contribution of specific non-communicable diseases to the achievement of the Sustainable Development Goal 3.4 in Peru, PLoS One, Vol: 15, ISSN: 1932-6203
BackgroundNon-communicable diseases (NCDs) have received political attention and commitment, yet surveillance is needed to measure progress and set priorities. Building on global estimates suggesting that Peru is not on target to meet the Sustainable Development Goal 3.4, we estimated the contribution of various NCDs to the change in unconditional probability of dying from NCDs in 25 regions in Peru.MethodsUsing national death registries and census data, we estimated the unconditional probability of dying between ages 30 and 69 from any and from each of the following NCDs: cardiovascular, cancer, diabetes, chronic respiratory diseases and chronic kidney disease. We estimated the contribution of each NCD to the change in the unconditional probability of dying from any of these NCDs between 2006 and 2016.ResultsThe overall unconditional probability of dying improved for men (21.4%) and women (23.3%). Cancer accounted for 10.9% in men and 13.7% in women of the overall reduction; cardiovascular diseases also contributed substantially: 11.3% in men) and 9.8% in women. Consistently in men and women and across regions, diabetes moved in the opposite direction of the overall reduction in the unconditional probability of dying from any selected NCD. Diabetes contributed a rise in the unconditional probability of 3.6% in men and 2.1% in women.ConclusionsAlthough the unconditional probability of dying from any selected NCD has decreased, diabetes would prevent Peru from meeting international targets. Policies are needed to prevent diabetes and to strengthen healthcare to avoid diabetes-related complications and delay mortality.
Cohorts Consortium of Latin America and the Caribbean CC-LAC, Carrillo Larco R, Gregg EW, et al., 2020, Cohort profile: The Cohorts Consortium of Latin America and the Caribbean (CC-LAC), International Journal of Epidemiology, Vol: 49, Pages: 1437-1437g, ISSN: 0300-5771
NCD Countdown 030 collaborators, Bennett JE, Kontis V, et al., 2020, NCD countdown 2030: pathways to achieving sustainable development goal target 3.4, The Lancet, Vol: 396, Pages: 918-934, ISSN: 0140-6736
The Sustainable Development Goal (SDG) target 3.4 is to reduce premature mortality from non-communicable diseases (NCDs) by a third by 2030 relative to 2015 levels, and to promote mental health and wellbeing. We used data on cause-specific mortality to characterise the risk and trends in NCD mortality in each country and evaluate combinations of reductions in NCD causes of death that can achieve SDG target 3.4. Among NCDs, ischaemic heart disease is responsible for the highest risk of premature death in more than half of all countries for women, and more than three-quarters for men. However, stroke, other cardiovascular diseases, and some cancers are associated with a similar risk, and in many countries, a higher risk of premature death than ischaemic heart disease. Although premature mortality from NCDs is declining in most countries, for most the pace of change is too slow to achieve SDG target 3.4. To investigate the options available to each country for achieving SDG target 3.4, we considered different scenarios, each representing a combination of fast (annual rate achieved by the tenth best performing percentile of all countries) and average (median of all countries) declines in risk of premature death from NCDs. Pathways analysis shows that every country has options for achieving SDG target 3.4. No country could achieve the target by addressing a single disease. In at least half the countries, achieving the target requires improvements in the rate of decline in at least five causes for women and in at least seven causes for men to the same rate achieved by the tenth best performing percentile of all countries. Tobacco and alcohol control and effective health-system interventions—including hypertension and diabetes treatment; primary and secondary cardiovascular disease prevention in high-risk individuals; low-dose inhaled corticosteroids and bronchodilators for asthma and chronic obstructive pulmonary disease; treatment of acute cardiovascular diseases
Carrillo-Larco RM, Altez-Fernandez C, Ravaglia S, et al., 2020, COVID-19 and Guillain-Barre Syndrome: a systematic review of case reports [version 2; peer review: 2 approved], Wellcome Open Research, Vol: 5, ISSN: 2398-502X
Background: Guillain-Barre Syndrome (GBS) is a neurological autoimmune disease that can lead to respiratory failure and death. Whether COVID-19 patients are at high risk of GBS is unknown. Through a systematic review of case reports, we aimed to summarize the main features of patients with GBS and COVID-19. Methods: Without any restrictions, we searched MEDLINE, Embase, Global Health, Scopus, Web of Science and MedXriv (April 23 rd, 2020). Two reviewers screened and studied titles, abstracts and reports. We extracted information to characterize sociodemographic variables, clinical presentation, laboratory results, treatments and outcomes. Results: Eight reports (n=12 patients) of GBS and COVID-19 were identified; one was a Miller Fisher case. The age ranged between 23 and 77 years, and there were more men (9/102). GBS symptoms started between 5 and 24 days after those of COVID-19. The protein levels in cerebrospinal fluid samples ranged between 40 and 193 mg/dl. None of the cerebrospinal fluid samples tested positive for COVID-19. Six patients debuted with ascendant weakness and three with facial weakness. Five patients had favourable evolution, four remained with relevant symptoms or required critical care and one died; the Miller Fisher case had successful resolution. Conclusions: GBS is emerging as a disease that may appear in COVID-19 patients. Although limited, preliminary evidence appears to suggest that GBS occurs after COVID-19 onset. Practitioners and investigators should have GBS in mind as they look after COVID-19 patients and conduct research on novel aspects of COVID-19. Comparison with GBS patients in the context of another viral outbreak (Zika), revealed similarities and differences that deserves further scrutiny and epidemiological studies.
Bernabe-Ortiz A, Carrillo Larco R, 2020, Longitudinal association between food frequency and changes in body mass index: a prospective cohort study, BMJ Open, Vol: 10, ISSN: 2044-6055
Objectives Analysing data of the Young Lives Study in Peru, we aimed at assessing the association between daily food frequency and body mass index (BMI) changes between 2006 and 2016.Design Secondary analysis of a prospective ongoing cohort study.Setting 20 sentinel sites in Peru.Participants Children enrolled in the younger cohort of the Young Lives Study. We used information from the second (2006–2007), third (2009–2010), fourth (2013–2014) and fifth (2016–2017) rounds of the younger cohort in Peru.Primary and secondary outcomes BMI as well as BMI-for-age z-score, both as numerical variables.Results Data from 1948 children, mean age 4.3 (SD: 0.3) years and 966 (49.6%) women were included at baseline. In multivariable model, lower food consumption frequency was associated with increased BMI and BMI-for-age z-scores: children reporting <4 times of food consumption per day had a greater increase in BMI (β=0.39; 95% CI 0.17 to 0.62) and BMI-for-age z-score (β=0.07; 95% CI 0.01 to 0.13) compared with those reporting 5 per day. Results were consistent for those reporting exactly eating 4 times per day (β for BMI=0.16; 95% CI 0.02 to 0.30 and β for BMI-for-age z-score=0.05; 95% CI 0.01 to 0.09).Conclusions Children who eat <5 times per day, gain more BMI compared with those who eat ≥5 times. Parents should receive information to secure adequate nutrition for their children, both in terms of quality and quantity.
Carrillo Larco R, 2020, Intermediate hyperglycaemia and 10-year mortality in resource-constrained settings: The PERU Migrant Study, Diabetic Medicine, Vol: 37, Pages: 1519-1527, ISSN: 0742-3071
AimTo determine whether intermediate hyperglycaemia, defined by fasting plasma glucose and HbA1c criteria, is associated with mortality in a 10‐year cohort of people in a Latin American country.MethodsAnalysis of the PERU MIGRANT Study was conducted in three different population groups (rural, rural‐to‐urban migrant, and urban). The baseline assessment was conducted in 2007/2008, with follow‐up assessment in 2018. The outcome was all‐cause mortality, and the exposure was intermediate hyperglycaemia, using three definitions: (1) impaired fasting glucose, defined according to American Diabetes Association criteria [fasting plasma glucose 5.6–6.9 mmol/l (100–125 mg/dl)]; (2) prediabetes defined according to American Diabetes Association criteria [HbA1c levels 39–46 mmol/mol (5.7–6.4%)]; and (3) prediabetes defined according to the International Expert Committee criteria [HbA1c levels 42–46 mmol/mol (6.0–6.4%)]. Crude and adjusted hazard ratios and 95% CIs were estimated using Cox proportional hazard models.ResultsAt baseline, the mean (sd) age of the study population was 47.8 (11.9) years and 52.5% of the cohort were women. The study cohort was divided into population groups as follows: 207 people (20.0%) in the rural population group, 583 (59.7%) in the rural‐to‐urban migrant group and 198 (20.3%) in the urban population group. The prevalence of intermediate hyperglycaemia was: 6%, 12.9% and 38.5% according to the American Diabetes Association impaired fasting glucose definition, the International Expert Committee HbA1c‐based definition and the American Diabetes Association HbA1c‐based definition, respectively, and the mortality rate after 10 years was 63/976 (7%). Intermediate hyperglycaemia was associated with all‐cause mortality using the HbA1c‐based definitions in the crude models [hazard ratios 2.82 (95% CI 1.59–4.99) according to the American Diabetes Association and 2.92 (95% CI 1.62–5.28) according to the Interna
Werneck AO, Baldew S-S, Miranda JJ, et al., 2020, The South American Physical Activity and Sedentary Behavior Network (SAPASEN), Global Health Promotion, Vol: 27, Pages: 171-176, ISSN: 1757-9759
The present article describes the South American Physical Activity and Sedentary Behavior Network, which was designed to provide ongoing transnational empirical evidence about physical activity and sedentary behavior in South America. The first goal of this initiative was to form a representative body of researchers and policy makers from all South American countries (Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, Guyana, Paraguay, Peru, Suriname, Uruguay and Venezuela) to establish priorities and targets for the short, medium and long term. Examples are given of connecting physical activity and sedentary data from existing surveys in several of the partner countries. The main objective of the South American Physical Activity and Sedentary Behavior Network will be to impact policies on physical activity and sedentary behavior in South America according to the singularities of each country or region. By encouraging an inclusive and collaborative effort, we expect that the South American Physical Activity and Sedentary Behavior Network will support the connection between researchers from South America as well as provide a better comprehension of the epidemiology of physical activity and sedentary behavior regionally.
Carrillo Larco R, Benites-Moya CJ, Anza-Ramirez C, et al., 2020, A systematic review of population-based studies on Lipid profiles in Latin America and the Caribbean, eLife, Vol: 9, Pages: 1-13, ISSN: 2050-084X
We aimed to study time trends and levels of mean total cholesterol and lipid fractions, and dyslipidaemias prevalence in Latin America and the Caribbean (LAC).Systematic-review and meta-analysis of population-based studies in which lipid (total cholesterol [TC; 86 studies;168,553 people], HDL-Cholesterol [HDL-C; 84 studies;121,282 people], LDL-Cholesterol [LDL-C; 61 studies;86,854 people], and triglycerides [TG;84 studies;121,009 people]) levels and prevalences were laboratory-based. We used Scopus, LILACS, Embase, Medline and Global Health; studies were from 1964-2016. Pooled means and prevalences were estimated for lipid biomarkers from ≥2005.The pooled means(mg/dl) were 193for TC, 120 for LDL-C, 47 for HDL-C, and 139 for TG; no strong trends. The pooled prevalence estimates were 21% for high TC, 20% for high LDL-C, 48% for low HDL-C, and 21% for high TG; no strong trends. These results may help strengthen programs fordyslipidaemias prevention/management in LAC.
Villarreal-Zegarra D, Carrillo Larco R, Cabrera-Alva M, et al., 2020, Trends in the prevalence and treatment of depressive symptoms in Peru: a population-based study, BMJ Open, Vol: 10, ISSN: 2044-6055
Objectives: This study aimed to estimate the trends in the prevalence and treatment of depressive symptoms using nationally representative surveys in Peru from 2014-2018.Design:A secondary analysis was conductedusing five nationally representative surveys carried out consecutively in the years between 2014and 2018, including a total of 166,290 individuals. Setting:The study was conducted in Peru.Participants:Individuals, men and women, aged≥15 years who participatedin the selected surveys. Sampling was probabilistic using a two-stage approach.Main outcome measures:Two versions of the Patient Health Questionnaire (PHQ-9)that focused on the presence of depressive symptomswere administered(one in the last two-week and other in the last-year). Scores ≥15 were used as the cut-off point in both versions of the PHQ-9to define the presence of depressive symptoms. Also, the treatment rate was based on the proportion of individuals who had experienceddepressive symptoms in the last-yearandwho had self-reported having received specific treatment for these symptoms.The age-standardized prevalence was estimated.Results:A total of 161,061 participants were included. There was no evidence of a change in age-standardized prevalence rates of depressive symptoms at the two weeksprior to the point of data collection(2.6% in 2014 to 2.3% in 2018), or in the last-year (6.3% in2014 to 6.2% in 2018).Furthermore,no change was found in the proportion of depressive cases treated in the last-year(14.6% in 2014 to 14.4% in 2018). Rural areas and individuals with low-level of wealth had lower proportion of depressive cases treated.Conclusions:No changes in trends of rates of depressive symptoms or in the proportion of depressive cases treated were observed. This suggests the need to reduce the treatment gap considering social determinants associated with inequality in access to adequate therapy.
Blümel JE, Vallejo MS, Chedraui P, et al., 2020, Multimorbidity in a cohort of middle-aged women: Risk factors and disease clustering, Maturitas, Vol: 137, Pages: 45-49, ISSN: 0378-5122
ObjectiveWe aimed to evaluate which risk factors in middle-aged women are associated with higher risk of multimorbidity in older age.Study designWe conducted a prospective cohort study from 1990 to 1993 in Santiago de Chile, Chile among women aged 40–59 (at baseline). Diagnosed illnesses were retrieved from national health records in 2020.Main outcome measures: Clinical and laboratory evaluation was conducted.Results1066 women were followed-up for a mean of 27.8 years, after which 49.7% presented multimorbidity. These women, as compared with those without multimorbidity, were more likely at baseline to have had obesity (20.4% vs. 8.6%, p < 0.001); be post-menopause (47.2% vs. 40.5%; p < 0.03); have jobs that did not require a qualification (74.2% vs. 56.0%, p < 0.001); arterial hypertension (19.8% vs 14.4%, p < 0.018); lower HDL-cholesterol (51.3 ± 12.9 vs. 53.6±12.7 mg/dL, p < 0.005); and higher triglyceride levels (136.0 ± 65.0 vs. 127.0 ± 74.0 mg/dL, p = 0.028). Hypertension was associated in 22.0% of women with diabetes, in 20.9% with osteoarthritis and 14.0% with depression. Osteoarthritis was also associated with diabetes mellitus (8.3%) and depression (7.8%). Diabetes mellitus, in addition to hypertension and osteoarthritis, was associated with depression (6.4%). In a logistic regression model, we observed that obesity in middle-aged women was the strongest risk factor for multimorbidity in the elderly (OR: 2.48; 95% CI, 1.71–3.61), followed by having a job that did not require a qualification (OR: 2.18; 95% CI, 1.67–2.83) and having a low HDL-cholesterol level (OR: 1.31; 95% CI, 1.02–1.68).ConclusionsMultimorbidity was highly prevalent in this older female population. Obesity in middle-aged women was the strongest risk factor for multimorbidity at older age. These results are relevant for Chile and other countries with similar population profiles.
Carrillo-Larco RM, Castillo-Cara M, 2020, Using country-level variables to classify countries according to the number of confirmed COVID-19 cases: An unsupervised machine learning approach [version 3; peerreview: 2 approved], Wellcome Open Research, Vol: 5, ISSN: 2398-502X
Background: The COVID-19 pandemic has attracted the attention of researchers and clinicians whom have provided evidence about risk factors and clinical outcomes. Research on the COVID-19 pandemic benefiting from open-access data and machine learning algorithms is still scarce yet can produce relevant and pragmatic information. With country-level pre-COVID-19-pandemic variables, we aimed to cluster countries in groups with shared profiles of the COVID-19 pandemic. Methods: Unsupervised machine learning algorithms (k-means) were used to define data-driven clusters of countries; the algorithm was informed by disease prevalence estimates, metrics of air pollution, socio-economic status and health system coverage. Using the one-way ANOVA test, we compared the clusters in terms of number of confirmed COVID-19 cases, number of deaths, case fatality rate and order in which the country reported the first case. Results: The model to define the clusters was developed with 155 countries. The model with three principal component analysis parameters and five or six clusters showed the best ability to group countries in relevant sets. There was strong evidence that the model with five or six clusters could stratify countries according to the number of confirmed COVID-19 cases (p<0.001). However, the model could not stratify countries in terms of number of deaths or case fatality rate. Conclusions: A simple data-driven approach using available global information before the COVID-19 pandemic, seemed able to classify countries in terms of the number of confirmed COVID-19 cases. The model was not able to stratify countries based on COVID-19 mortality data.
Carrillo-Larco R, Castillo-Cara M, 2020, Using country-level variables to classify countries according to the number of confirmed COVID-19 cases: An unsupervised machine learning approach [version 2; peerreview: 1 approved, 1 approved with reservations], Wellcome Open Research, Vol: 5, Pages: 1-21, ISSN: 2398-502X
Background: The COVID-19 pandemic has attracted the attention of researchers and clinicians whom have provided evidence about risk factors and clinical outcomes. Research on the COVID-19 pandemic benefiting from open-access data and machine learning algorithms is still scarce yet can produce relevant and pragmatic information. With country-level pre-COVID-19-pandemic variables, we aimed to cluster countries in groups with shared profiles of the COVID-19 pandemic. Methods: Unsupervised machine learning algorithms (k-means) were used to define data-driven clusters of countries; the algorithm was informed by disease prevalence estimates, metrics of air pollution, socio-economic status and health system coverage. Using the one-way ANOVA test, we compared the clusters in terms of number of confirmed COVID-19 cases, number of deaths, case fatality rate and order in which the country reported the first case. Results: The model to define the clusters was developed with 155 countries. The model with three principal component analysis parameters and five or six clusters showed the best ability to group countries in relevant sets. There was strong evidence that the model with five or six clusters could stratify countries according to the number of confirmed COVID-19 cases (p<0.001). However, the model could not stratify countries in terms of number of deaths or case fatality rate. Conclusions : A simple data-driven approach using available global information before the COVID-19 pandemic, seemed able to classify countries in terms of the number of confirmed COVID-19 cases. The model was not able to stratify countries based on COVID-19 mortality data.
NCD Risk Factor Collaboration NCD-RisC, 2020, Repositioning of the global epicentre of non-optimal cholesterol, Nature, Vol: 582, Pages: 73-77, ISSN: 0028-0836
High blood cholesterol is typically considered a feature of wealthy western countries1,2. However, dietary and behavioural determinants of blood cholesterol are changing rapidly throughout the world3 and countries are using lipid-lowering medications at varying rates. These changes can have distinct effects on the levels of high-density lipoprotein (HDL) cholesterol and non-HDL cholesterol, which have different effects on human health4,5. However, the trends of HDL and non-HDL cholesterol levels over time have not been previously reported in a global analysis. Here we pooled 1,127 population-based studies that measured blood lipids in 102.6 million individuals aged 18 years and older to estimate trends from 1980 to 2018 in mean total, non-HDL and HDL cholesterol levels for 200 countries. Globally, there was little change in total or non-HDL cholesterol from 1980 to 2018. This was a net effect of increases in low- and middle-income countries, especially in east and southeast Asia, and decreases in high-income western countries, especially those in northwestern Europe, and in central and eastern Europe. As a result, countries with the highest level of non-HDL cholesterol-which is a marker of cardiovascular risk-changed from those in western Europe such as Belgium, Finland, Greenland, Iceland, Norway, Sweden, Switzerland and Malta in 1980 to those in Asia and the Pacific, such as Tokelau, Malaysia, The Philippines and Thailand. In 2017, high non-HDL cholesterol was responsible for an estimated 3.9 million (95% credible interval 3.7 million-4.2 million) worldwide deaths, half of which occurred in east, southeast and south Asia. The global repositioning of lipid-related risk, with non-optimal cholesterol shifting from a distinct feature of high-income countries in northwestern Europe, north America and Australasia to one that affects countries in east and southeast Asia and Oceania should motivate the use of population-based policies and per
Carrillo-Larco R, Altez-Fernandez C, Ravaglia S, et al., 2020, COVID-19 and Guillain-Barre Syndrome: a systematic review of case reports, Wellcome Open Research, Vol: 5, Pages: 1-12, ISSN: 2398-502X
Background: Guillain-Barre Syndrome (GBS) is a neurological autoimmune disease that can lead to respiratory failure and death. Whether COVID-19 patients are at high risk of GBS is unknown. Through a systematic review of case reports, we aimed to summarize the main features of patients with GBS and COVID-19. Methods: Without any restrictions, we searched MEDLINE, Embase, Global Health, Scopus, Web of Science and MedXriv (April 23 rd , 2020). Two reviewers screened and studied titles, abstracts and reports. We extracted information to characterize sociodemographic variables, clinical presentation, laboratory results, treatments and outcomes. Results: Eight reports (n=12 patients) of GBS and COVID-19 were identified; one was a Miller Fisher case. Overall, the median age was 62.5 (interquartile range (IQR)=54.5-70.5) years, and there were more men (9/102). GBS symptoms started between 5 and 24 days after those of COVID-19. The median protein levels in cerebrospinal fluid samples was 101.5 mg/dl (IQR=51-145). None of the cerebrospinal fluid samples tested positive for COVID-19. Six patients debuted with ascendant weakness and three with facial weakness. Five patients had favourable evolution, four remained with relevant symptoms or required critical care and one died; the Miller Fisher case had successful resolution. Conclusions: GBS is emerging as a disease that may appear in COVID-19 patients. Although limited, preliminary evidence appears to suggest that GBS occurs after COVID-19 onset. Practitioners and investigators should have GBS in mind as they look after COVID-19 patients and conduct research on novel aspects of COVID-19. Comparison with GBS patients in the context of another viral outbreak (Zika), revealed similarities and differences that deserves further scrutiny and epidemiological studies.
Carrillo-Larco RM, Altez-Fernandez C, 2020, Anosmia and dysgeusia in COVID-19: a systematic review [version 1; peer review: 2 approved, 1 not approved], Wellcome Open Research, Vol: 5, ISSN: 2398-502X
Background: This systematic review had three aims: i) to determine the frequency of anosmia (or other smell disorders) and dysgeusia (or other taste disorders) in COVID-19 patients; ii) to determine whether anosmia or dysgeusia are independently associated with COVID-19 diagnosis; and iii) to determine whether anosmia or dysgeusia are prognostic factors for impaired outcomes among COVID-19 patients. Methods: On April 20 th, 2020, we search MEDLINE, Embase, Global Health, Scopus, Web of Science and MedXriv. We used terms related to COVID-19, smell and taste disorders. We selected case series, cross-sectional, case-control and cohort studies. We included studies with COVID-19 patients describing their symptoms; studies that compared smell and taste disorders between COVID-19 patients and otherwise healthy subjects; and studies comparing smell and taste disorders between COVID-19 severe and mild/moderate cases. Because of methodological heterogeneity and the limited number of results, a qualitative synthesis is presented. Results: From 31 reports, we selected six (n=2,757). Six studies reported the proportion of smell and taste disorders among COVID-19 patients. Two reports studied whether smell and taste disorders were independently associated with COVID-19 diagnosis. No reports studied the association with impaired outcomes among COVID-19 patients. The frequency of anosmia ranged between 22%-68%. The definition of taste disorders varied greatly, with dysgeusia present in 33% and ageusia in 20%. People who reported loss of smell and taste had six-fold higher odds of being COVID-19 positive; similarly, anosmia and ageusia were associated with 10-fold higher odds of COVID-19 diagnosis. Conclusions: The frequency of smell and taste disorders is as high as other symptoms, thus, at least anosmia for which the definition was more consistent, could be included in lists of COVID-19 symptoms. Although there is promising evidence, it is premature to conclude that smell and tast
Carrillo Larco R, Tudor Car L, Pearson-Stuttard J, et al., 2020, Machine learning health-related applications in low- and middle-income countries: A scoping review protocol, BMJ Open, Vol: 10, ISSN: 2044-6055
Introduction Machine learning (ML) has been used in bio-medical research, and recently in clinical and public health research. However, much of the available evidence comes from high-income countries, where different health profiles challenge the application of this research to low/middle-income countries (LMICs). It is largely unknown what ML applications are available for LMICs that can support and advance clinical medicine and public health. We aim to address this gap by conducting a scoping review of health-related ML applications in LMICs.Methods and analysis This scoping review will follow the methodology proposed by Levac et al. The search strategy is informed by recent systematic reviews of ML health-related applications. We will search Embase, Medline and Global Health (through Ovid), Cochrane and Google Scholar; we will present the date of our searches in the final review. Titles and abstracts will be screened by two reviewers independently; selected reports will be studied by two reviewers independently. Reports will be included if they are primary research where data have been analysed, ML techniques have been used on data from LMICs and they aimed to improve health-related outcomes. We will synthesise the information following evidence mapping recommendations.Ethics and dissemination The review will provide a comprehensive list of health-related ML applications in LMICs. The results will be disseminated through scientific publications. We also plan to launch a website where ML models can be hosted so that researchers, policymakers and the general public can readily access them.
Carrillo Larco R, Aparcana-Granda DJ, Mejia JR, et al., 2020, FINDRISC in Latin America: A systematic review of diagnosis and prognosis models, BMJ Open Diabetes Research and Care, Vol: 8, Pages: 1-7, ISSN: 2052-4897
Aim: To assess whether the FINDRISC, a risk score fortype 2 diabetes mellitus (T2DM), has been externally validated in Latin America and the Caribbean (LAC). Methods:We conducted a systematic review following the CHARMS framework. Reports were included if they validated or re-estimated the FINDRISCin population-based samples, health facilities or administrative data. Reports were excluded if they only studiedpatients or at-risk individuals. The search was conducted in Medline, Embase, Global Health, Scopus and LILACS. Risk of bias was assessedwith the PROBAST tool. Results:From 1,582 titles and abstracts, 4 (N=7,502) reports were included for qualitatively summary. All reports were from South America; there were slightly more women and themean age rangedfrom 29.5 to 49.7 years. Undiagnosed T2DM prevalence ranged from 2.6% to 5.1%. None of the studies conducted an independent external validation of the FINDRISC; conversely, they used the same (or very similar) predictors to fit a new model.None of the studies reported calibration metrics. The area under the receiver operating curve was consistently above 65.0%. All studies had high risk of bias.Conclusion:There has not been any external validation of the FINDRISCmodelin LAC. Selected reportsre-estimated the FINDRISC, though they have several methodologicallimitations. There is a need for big data to develop -or improve-T2DM diagnostic and prognostic models in LAC. This could benefit T2DM screening and early diagnosis.
Alae-Carew C, Scheelbeek P, Carrillo-Larco RM, et al., 2020, Analysis of dietary patterns and cross-sectional and longitudinal associations with hypertension, high BMI and type 2 diabetes in Peru, Public Health Nutrition, Vol: 23, Pages: 1009-1019, ISSN: 1368-9800
OBJECTIVE: To determine if specific dietary patterns are associated with risk of hypertension, type 2 diabetes mellitus (T2DM) and high BMI in four sites in Peru. DESIGN: We analysed dietary patterns from a cohort of Peruvian adults in four geographical settings using latent class analysis. Associations with prevalence and incidence of hypertension, T2DM and high BMI were assessed using Poisson regression and generalised linear models, adjusted for potential confounders. SETTING: Four sites in Peru varying in degree of urbanisation. PARTICIPANTS: Adults aged ≥35 years (n 3280). RESULTS: We identified four distinct dietary patterns corresponding to different stages of the Peruvian nutrition transition, reflected by the foods frequently consumed in each pattern. Participants consuming the 'stage 3' diet, characterised by high proportional consumption of processed foods, animal products and low consumption of vegetables, mostly consumed in the semi-urban setting, showed the highest prevalence of all health outcomes (hypertension 32·1 %; T2DM 10·7 %; high BMI 75·1 %). Those with a more traditional 'stage 1' diet characterised by potato and vegetables, mostly consumed in the rural setting, had lower prevalence of hypertension (prevalence ratio; 95 CI: 0·57; 0·43, 0·75), T2DM (0·36; 0·16, 0·86) and high BMI (0·55; 0·48, 0·63) compared with the 'stage 3' diet. Incidence of hypertension was highest among individuals consuming the 'stage 3' diet (63·75 per 1000 person-years; 95 % CI 52·40, 77·55). CONCLUSIONS: The study found more traditional diets were associated with a lower prevalence of three common chronic diseases, while prevalence of these diseases was higher with a diet high in processed foods and low in vegetables.
Carrillo-Larco RM, Castillo-Cara M, 2020, Using country-level variables to classify countries according to the number of confirmed COVID-19 cases: An unsupervised machine learning approach, Publisher: F1000 Research Ltd
<ns4:p><ns4:bold>Background: </ns4:bold>The COVID-19 pandemic has attracted the attention of researchers and clinicians whom have provided evidence about risk factors and clinical outcomes. Research on the COVID-19 pandemic benefiting from open-access data and machine learning algorithms is still scarce yet can produce relevant and pragmatic information. With country-level pre-COVID-19-pandemic variables, we aimed to cluster countries in groups with shared profiles of the COVID-19 pandemic.</ns4:p><ns4:p> <ns4:bold>Methods: </ns4:bold>Unsupervised machine learning algorithms (k-means) were used to define data-driven clusters of countries; the algorithm was informed by disease prevalence estimates, metrics of air pollution, socio-economic status and health system coverage. Using the one-way ANOVA test, we compared the clusters in terms of number of confirmed COVID-19 cases, number of deaths, case fatality rate and order in which the country reported the first case.</ns4:p><ns4:p> <ns4:bold>Results: </ns4:bold>The model to define the clusters was developed with 155 countries. The model with three principal component analysis parameters and five or six clusters showed the best ability to group countries in relevant sets. There was strong evidence that the model with five or six clusters could stratify countries according to the number of confirmed COVID-19 cases (p<0.001). However, the model could not stratify countries in terms of number of deaths or case fatality rate.</ns4:p><ns4:p> <ns4:bold>Conclusions</ns4:bold>: A simple data-driven approach using available global information before the COVID-19 pandemic, seemed able to classify countries in terms of the number of confirmed COVID-19 cases. The model was not able to stratify countries based on COVID-19 mortality data.</ns4:p>
Zafra-Tanaka JH, Tenorio-Mucha J, Villarreal-Zegarra D, et al., 2020, Cancer-related mortality in Peru: Trends from 2003 to 2016 (vol 15, e0228867, 2020), PLoS One, Vol: 15, Pages: 1-1, ISSN: 1932-6203
Carrillo Larco R, BernabeOrtiz A, 2020, Sodium and salt consumption in Latin America and the Caribbean: a systematic-review and meta-analysis of population-based studies and surveys, Nutrients, Vol: 12, ISSN: 2072-6643
Sodium/salt consumption is a risk factor for cardiovascular diseases. Although global targets to reduce salt intake have been established, current levels and trends of sodium consumption in Latin America and the Caribbean (LAC) are unknown. We conducted a systematic review and meta-analysis of population-based studies in which sodium consumption was analyzed based on urine samples (24 hour samples or otherwise). The search was conducted in Medline, Embase, Global Health, Scopus and LILACS. From 2350 results, 53 were studied in detail, of which 15 reports were included, providing evidence for 18 studies. Most studies were from Brazil (7/18) and six collected 24 hour urine samples. In the random effects meta-analysis, 12 studies (29,875 people) were analyzed since 2010. The pooled mean 24 hour estimated sodium consumption was 4.13 g/day (10.49 g/day of salt). When only national surveys were analyzed, the pooled mean was 3.43 g/day (8.71 g/day of salt); when only community studies were analyzed the pooled mean was 4.39 g/day (11.15 g/day of salt). Studies had low risk of bias. The estimated 24 hour sodium consumption is more than twice the World Health Organization recommendations since 2010. Regional organizations and governments should strengthen policies and interventions to measure and reduce sodium consumption in LAC.
Bernabe-Ortiz A, Sal y Rosas VG, Ponce-Lucero V, et al., 2020, Effect of salt substitution on community-wide blood pressure and hypertension incidence, Nature Medicine, Vol: 26, Pages: 374-378, ISSN: 1078-8956
Replacement of regular salt with potassium-enriched substitutes reduces blood pressure in controlled situations, mainly among people with hypertension. We report on a population-wide implementation of this strategy in a stepped-wedge cluster randomized trial (NCT01960972). The regular salt in enrolled households was retrieved and replaced, free of charge, with a combination of 75% NaCl and 25% KCl. A total of 2,376 participants were enrolled in 6 villages in Tumbes, Peru. The fully adjusted intention-to-treat analysis showed an average reduction of 1.29 mm Hg (95% confidence interval (95% CI) (−2.17, −0.41)) in systolic and 0.76 mm Hg (95% CI (−1.39, −0.13)) in diastolic blood pressure. Among participants without hypertension at baseline, in the time- and cluster-adjusted model, the use of the salt substitute was associated with a 51% (95% CI (29%, 66%)) reduced risk of developing hypertension compared with the control group. In 24-h urine samples, there was no evidence of differences in sodium levels (mean difference 0.01; 95% CI (0.25, −0.23)), but potassium levels were higher at the end of the study than at baseline (mean difference 0.63; 95% CI (0.78, 0.47)). Our results support a case for implementing a pragmatic, population-wide, salt-substitution strategy for reducing blood pressure and hypertension incidence.
Zafra-Tanaka JH, Tenorio-Mucha J, Villarreal-Zegarra D, et al., 2020, Cancer-related mortality in Peru: Trends from 2003 to 2016, PLoS One, Vol: 15, ISSN: 1932-6203
OBJECTIVES: In the last decade, Latin American (LA) countries, like Peru, have undergone an epidemiological transition that has changed the pattern of oncological cases. Given that Peru's oncological pattern could illustrate those of other LA countries, we aimed at determining trends and changes in cancer-related mortality by age and sex in Peru between 2003 and 2016. METHODS AND RESULTS: A secondary data analysis using national deaths registries was conducted. Categories were created according to the 27 most frequent sites of presentation of cancer. We found that deaths attributed to cancer increased from 15.4% of all deaths in 2003 to 18.1% in 2016 (p<0.001). According to the cancer site, stomach cancer (19.1%) and lung cancer (11.5%) were the most frequent causes of death overall. In childhood (0 to 14 years), the two most frequent fatal cancers were leukemia (54.6% for boys and 53.5% for girls) and brain and nervous system tumors (19.4% for boys and 20.3% for girls). For teenagers and young male adults (15-49 years), stomach cancer (18.1%) and brain cancer (17.4%) were the leading causes of death; in their female counterparts, cervix uteri (20.0%) and breast cancer (16.1%) were the most mortal cancers. In adults (≥50 years), stomach (20.9% for men and 18.6% for women) and lung (12.7% for men and 10.4% for women) were the leading contributors to the burden of cancer deaths. CONCLUSIONS: Between the years 2003 and 2016, almost one fifth of deaths were attributed to cancer in Peru. Absolute and relative number of deaths due to cancer has increased in this period for both men and women; however, standardized mortality rates due to cancer have declined.
Carrillo Larco R, Pearson-Stuttard J, Bernabe-Ortiz A, et al., 2020, The Andean Latin-American burden of diabetes attributable to high body mass index: a comparative risk assessment, Diabetes Research and Clinical Practice, Vol: 160, Pages: 1-10, ISSN: 0168-8227
Background:Body mass index (BMI)has increased in Latin-America, but the implications for the diabetesburden havenot been quantified. We estimated the proportion and absolute number of diabetescasesattributable to high BMI in Bolivia, Ecuador and Peru(Andean Latin-America), with estimation of region-level indicators in Peru.Methods: Weestimated the population attributable fraction (PAF) of BMI ondiabetes(regardless of type 1 or 2)from 1980 to 2014, including the number of cases attributable to overweight (BMI 25-<30), class I (30-<35),class II (BMI 35-<40) and class III(BMI ≥40)obesity.We used age-and sex-specific prevalence estimates of diabetes and BMI categories(NCD-RisC and Peru’s DHS survey)combined with relative risks from population-based cohortsin Peru. Findings: Across Andean Latin-Americain 2014, there were 1,258,313diabetes cases attributable to high BMI: 209,855 in Bolivia, 367,440in Ecuadorand681,018in Peru. Between 1980-2010, the absolute proportion of diabetes cases attributable toclass I obesity increased the most (from 12.9% to 27.2%) across the region. The second greatest increase was for class II obesity (from 3.6% to 16.5%). There was heterogeneity in the fraction of diabetes cases attributable to high BMI by region in Peru, ascoastal regions hadthelargestfractions,andso did high-income regions. Interpretation: Over one milliondiabetes cases are attributable to high BMI in Andean Latin-America. Public health efforts should focus on implementing population-based interventions to reduce high BMI and to developfocused interventions targeted at those at highest risk of diabetes.
Jiwani SS, Carrillo-Larco RM, Hernandez-Vasquez A, 2020, The shift of obesity burden by socioeconomic status between 1998 and 2017 in Latin America and the Caribbean: a cross-sectional series study (vol 7, pg 1644, 2019), The Lancet Global Health, Vol: 8, Pages: E340-E340, ISSN: 2214-109X
Correction to Lancet Glob Health 2019; 7: e1644–74
Jaime Miranda J, Carrillo-Larco RM, Ferreccio C, et al., 2020, Trends in cardiometabolic risk factors in the Americas between 1980 and 2014: a pooled analysis of population-based surveys, The Lancet Global Health, Vol: 8, Pages: E123-E133, ISSN: 2214-109X
BackgroundDescribing the prevalence and trends of cardiometabolic risk factors that are associated with non-communicable diseases (NCDs) is crucial for monitoring progress, planning prevention, and providing evidence to support policy efforts. We aimed to analyse the transition in body-mass index (BMI), obesity, blood pressure, raised blood pressure, and diabetes in the Americas, between 1980 and 2014.MethodsWe did a pooled analysis of population-based studies with data on anthropometric measurements, biomarkers for diabetes, and blood pressure from adults aged 18 years or older. A Bayesian model was used to estimate trends in BMI, raised blood pressure (systolic blood pressure ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg), and diabetes (fasting plasma glucose ≥7·0 mmol/L, history of diabetes, or diabetes treatment) from 1980 to 2014, in 37 countries and six subregions of the Americas.Findings389 population-based surveys from the Americas were available. Comparing prevalence estimates from 2014 with those of 1980, in the non-English speaking Caribbean subregion, the prevalence of obesity increased from 3·9% (95% CI 2·2–6·3) in 1980, to 18·6% (14·3–23·3) in 2014, in men; and from 12·2% (8·2–17·0) in 1980, to 30·5% (25·7–35·5) in 2014, in women. The English-speaking Caribbean subregion had the largest increase in the prevalence of diabetes, from 5·2% (2·1–10·4) in men and 6·4% (2·6–10·4) in women in 1980, to 11·1% (6·4–17·3) in men and 13·6% (8·2–21·0) in women in 2014). Conversely, the prevalence of raised blood pressure has decreased in all subregions; the largest decrease was found in North America from 27·6% (22·3–33·2) in men and 19·9% (15·8–24·4) in women in 1980, to 15·
Ruiz-Alejos A, Carrillo-Larco RM, Miranda JJ, et al., 2020, Skinfold thickness and the incidence of type 2 diabetes mellitus and hypertension: an analysis of the PERU MIGRANT study, Public Health Nutrition, Vol: 23, Pages: 63-71, ISSN: 1368-9800
OBJECTIVE: To determine the association between excess body fat, assessed by skinfold thickness, and the incidence of type 2 diabetes mellitus (T2DM) and hypertension (HT). DESIGN: Data from the ongoing PERU MIGRANT Study were analysed. The outcomes were T2DM and HT, and the exposure was skinfold thickness measured in bicipital, tricipital, subscapular and suprailiac areas. The Durnin-Womersley formula and SIRI equation were used for body fat percentage estimation. Risk ratios and population attributable fractions (PAF) were calculated using Poisson regression. SETTING: Rural (Ayacucho) and urban shantytown district (San Juan de Miraflores, Lima) in Peru. PARTICIPANTS: Adults (n 988) aged ≥30 years (rural, rural-to-urban migrants, urban) completed the baseline study. A total of 785 and 690 were included in T2DM and HT incidence analysis, respectively. RESULTS: At baseline, age mean was 48·0 (sd 12·0) years and 47 % were males. For T2DM, in 7·6 (sd 1·3) years, sixty-one new cases were identified, overall incidence of 1·0 (95 % CI 0·8, 1·3) per 100 person-years. Bicipital and subscapular skinfolds were associated with 2·8-fold and 6·4-fold risk of developing T2DM. On the other hand, in 6·5 (sd 2·5) years, overall incidence of HT was 2·6 (95 % CI 2·2, 3·1) per 100 person-years. Subscapular and overall fat obesity were associated with 2·4- and 2·9-fold risk for developing HT. The PAF for subscapular skinfold was 73·6 and 39·2 % for T2DM and HT, respectively. CONCLUSIONS: We found a strong association between subscapular skinfold thickness and developing T2DM and HT. Skinfold assessment can be a laboratory-free strategy to identify high-risk HT and T2DM cases.
Aedo S, Blümel JE, Carrillo-Larco RM, et al., 2020, Association between high levels of gynoid fat and the increase of bone mineral density in women, Climacteric, Vol: 23, Pages: 206-210, ISSN: 1369-7137
Introduction: In women, bone mineral density (BMD) is related to age, estrogenic action, and appendicular skeletal muscle mass (ASMM). The gynoid fat distribution is linked to estrogenic action.Objective: This study aimed to assess whether an increase of gynoid fat is associated with high BMD independent of age and ASMM.Methods: An observational study was performed in women aged between 20 and 79 years. Fat mass, ASMM, and BMD were measured with dual-energy X-ray absorptiometry. The binned scatterplots and multivariate linear regression models were used to study the relationship between hip BMD and age, height, android fat, gynoid fat, and ASMM.Results: Of 673 women invited, 596 accepted to participate. Their mean age was 55.4 ± 12.8 years, weight 63.4 ± 9.4 kg, height 1.61 ± 0.06 m, body mass index 24.54 ± 3.59 kg/m2, average hip BMD 0.914 ± 0.122 g/cm2, android fat 2.12 ± 0.83 kg, gynoid fat 4.54 ± 1.07 kg, and ASMM 15.15 ± 1.97 kg. The final regression model included age (linear coefficient -0.004; 95% confidence interval [CI]: -0.005 to -0.003; p < 0.001), ASMM (linear coefficient 0.013; 95% CI: 0.009 to 0.018; p < 0.001), and gynoid fat (linear coefficient 0.013; 95% CI: 0.005 to 0.022; p < 0.002).Conclusion: Gynoid fat is associated with BMD in the hip independently of age and ASMM.
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