scholarly journals Estimating salt consumption in 49 low-and middle-income countries: Development, validation and application of a machine learning model

2021 ◽  
Author(s):  
Wilmer Cristobal Guzman-Vilca ◽  
Manuel Castillo-Cara ◽  
Rodrigo M Carrillo-Larco
Keyword(s):  
Machine Learning ◽  
Salt Intake ◽  
Population Based ◽  
Urine Samples ◽  
Middle Income ◽  
Spot Urine ◽  
Salt Consumption ◽  
Middle Income Countries ◽  
Model Based ◽  
Low And Middle Income

Background: Global targets to reduce salt intake have been proposed but their monitoring is challenged by the lack of population-based data on salt consumption. We developed a machine learning (ML) model to predict salt consumption based on simple predictors, and applied this model to national surveys in low- and middle-income countries (LMICs).<br /><br />Methods: Pooled analysis of WHO STEPS surveys. We used 19 surveys with spot urine samples for the ML model derivation and validation; we developed a supervised ML regression model based on: sex, age, weight, height, systolic and diastolic blood pressure. We applied the ML model to 49 new STEPS surveys to quantify the mean salt consumption in the population.<br /><br />Results: The pooled dataset in which we developed the ML model included 45,152 people. Overall, there were no substantial differences between the observed (8.1 g/day (95% CI: 8.0-8.2 g/day)) and ML-predicted (8.1 g/day (95% CI: 8.1-8.2 g/day)) mean salt intake (p= 0.065). The pooled dataset where we applied the ML model included 157,699 people; the overall predicted mean salt consumption was 8.1 g/day (95% CI: 8.1-8.2 g/day). The countries with the highest predicted mean salt intake were in Western Pacific. The lowest predicted intake was found in Africa. The country-specific predicted mean salt intake was within reasonable difference from the best available evidence.<br /><br />Conclusions: A ML model based on readily available predictors estimated daily salt consumption with good accuracy. This model could be used to predict mean salt consumption in the general population where urine samples are not available.

scholarly journals Development, validation and application of a machine learning model to estimate salt consumption in 54 countries

eLife ◽  
2022 ◽  
Vol 11 ◽  
Author(s):  
Wilmer Cristobal Guzman-Vilca ◽  
Manuel Castillo-Cara ◽  
Rodrigo M Carrillo-Larco
Keyword(s):  
Machine Learning ◽  
Salt Intake ◽  
Population Level ◽  
American Samoa ◽  
Population Based ◽  
Urine Samples ◽  
Spot Urine ◽  
Salt Consumption ◽  
Model Based ◽  
Machine Learning Model

Global targets to reduce salt intake have been proposed but their monitoring is challenged by the lack of population-based data on salt consumption. We developed a machine learning (ML) model to predict salt consumption at the population level based on simple predictors and applied this model to national surveys in 54 countries. We used 21 surveys with spot urine samples for the ML model derivation and validation; we developed a supervised ML regression model based on: sex, age, weight, height, systolic and diastolic blood pressure. We applied the ML model to 54 new surveys to quantify the mean salt consumption in the population. The pooled dataset in which we developed the ML model included 49,776 people. Overall, there were no substantial differences between the observed and ML-predicted mean salt intake (p<0.001). The pooled dataset where we applied the ML model included 166,677 people; the predicted mean salt consumption ranged from 6.8 g/day (95% CI: 6.8-6.8 g/day) in Eritrea to 10.0 g/day (95% CI: 9.9-10.0 g/day) in American Samoa. The countries with the highest predicted mean salt intake were in Western Pacific. The lowest predicted intake was found in Africa. The country-specific predicted mean salt intake was within reasonable difference from the best available evidence. A ML model based on readily available predictors estimated daily salt consumption with good accuracy. This model could be used to predict mean salt consumption in the general population where urine samples are not available.

scholarly journals Mean Dietary Salt Intake in Vanuatu: A Population Survey of 755 Participants on Efate Island

Nutrients ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 916
Author(s):  
Katherine Paterson ◽  
Nerida Hinge ◽  
Emalie Sparks ◽  
Kathy Trieu ◽  
Joseph Alvin Santos ◽  
...  
Keyword(s):  
Salt Intake ◽  
Urine Samples ◽  
World Health ◽  
Dietary Salt ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Middle Income ◽  
Dietary Salt Intake ◽  
Spot Urine ◽  
Salt Consumption

Non-communicable diseases are responsible for 63% of global deaths, with a higher burden in low- and middle-income countries. Hypertension is the leading cause of cardiovascular-disease-related deaths worldwide, and approximately 1.7 million deaths are directly attributable to excess salt intake annually. There has been little research conducted on the level of salt consumption amongst the population of Vanuatu. Based on data from other Pacific Island countries and knowledge of changing regional diets, it was predicted that salt intake would exceed the World Health Organization’s (WHO) recommended maximum of 5 g per day. The current study aimed to provide Vanuatu with a preliminary baseline assessment of population salt intake on Efate Island. A cross-sectional survey collected demographic, clinical, and urine data from participants aged 18 to 69 years in rural and urban communities on Efate Island in October 2016 and February 2017. Mean salt intake was determined to be 7.2 (SD 2.3) g/day from spot urine samples, and 5.9 (SD 3.6) g/day from 24-h urine samples, both of which exceed the WHO recommended maximum. Based on the spot urine samples, males had significantly higher salt intake than females (7.8 g compared to 6.5 g; p < 0.001) and almost 85% of the population consumed more than the WHO recommended maximum daily amount. A coordinated government strategy is recommended to reduce salt consumption, including fiscal policies, engagement with the food industry, and education and awareness-raising to promote behavior change.

scholarly journals Predictors of Contemporary under-5 Child Mortality in Low- and Middle-Income Countries: A Machine Learning Approach

2021 ◽  
Vol 18 (3) ◽  
pp. 1315
Author(s):  
Andrea Bizzego ◽  
Giulio Gabrieli ◽  
Marc H. Bornstein ◽  
Kirby Deater-Deckard ◽  
Jennifer E. Lansford ◽  
...  
Keyword(s):  
Machine Learning ◽  
Child Mortality ◽  
Learning Approach ◽  
Unique Contribution ◽  
Middle Income ◽  
Middle Income Countries ◽  
Country Level ◽  
Machine Learning Approach ◽  
Operational Information ◽  
Low And Middle Income

Child Mortality (CM) is a worldwide concern, annually affecting as many as 6.81% children in low- and middle-income countries (LMIC). We used data of the Multiple Indicators Cluster Survey (MICS) (N = 275,160) from 27 LMIC and a machine-learning approach to rank 37 distal causes of CM and identify the top 10 causes in terms of predictive potency. Based on the top 10 causes, we identified households with improved conditions. We retrospectively validated the results by investigating the association between variations of CM and variations of the percentage of households with improved conditions at country-level, between the 2005–2007 and the 2013–2017 administrations of the MICS. A unique contribution of our approach is to identify lesser-known distal causes which likely account for better-known proximal causes: notably, the identified distal causes and preventable and treatable through social, educational, and physical interventions. We demonstrate how machine learning can be used to obtain operational information from big dataset to guide interventions and policy makers.

scholarly journals Suicide prevention in low- and middle-income countries: part perceptions, partial solutions

2017 ◽  
Vol 211 (5) ◽  
pp. 264-265 ◽  
Author(s):  
K. S. Jacob
Keyword(s):  
Public Health ◽  
Suicide Prevention ◽  
Cause Of Death ◽  
Population Based ◽  
Personal Distress ◽  
Public Health Perspective ◽  
Middle Income ◽  
Common Cause ◽  
Middle Income Countries ◽  
Low And Middle Income

SummarySuicide, a common cause of death in many low- and middle-income countries, has often been viewed through a medical/psychiatric lens. Such perspectives medicalise social and personal distress and suggest individual and medication-based treatments. This editorial argues for the need to examine suicide from a public health perspective and suggests the need for population-based social and economic interventions.

Cancer control-planning and monitoring population-based systems

2009 ◽  
Vol 95 (5) ◽  
pp. 568-578 ◽  
Author(s):  
Joe B Harford ◽  
Brenda K Edwards ◽  
Ambakumar Nandakumar ◽  
Paul Ndom ◽  
Riccardo Capocaccia ◽  
...  
Keyword(s):  
Cancer Control ◽  
Population Based ◽  
Middle Income ◽  
Cancer Risk Factors ◽  
Middle Income Countries ◽  
Care Services ◽  
Aging Populations ◽  
Global Health Issue ◽  
Palliative Care Services ◽  
Low And Middle Income

Cancer is a growing global health issue, and many countries are ill-prepared to deal with their current cancer burden let alone the increased burden looming on the horizon. Growing and aging populations are projected to result in dramatic increases in cancer cases and cancer deaths particularly in low- and middle-income countries. It is imperative that planning begin now to deal not only with those cancers already occurring but also with the larger numbers expected in the future. Unfortunately, such planning is hampered, because the magnitude of the burden of cancer in many countries is poorly understood owing to lack of surveillance and monitoring systems for cancer risk factors and for the documentation of cancer incidence, survival and mortality. Moreover, the human resources needed to fight cancer effectively are often limited or lacking. Cancer diagnosis and cancer care services are also inadequate in low-and middle-income countries. Late-stage presentation of cancers is very common in these settings resulting in less potential for cure and more need for symptom management. Palliative care services are grossly inadequate in low- and middle-income countries, and many cancer patients die unnecessarily painful deaths. Many of the challenges faced by low- and middle-income countries have been at least partially addressed by higher income countries. Experiences from around the world are reviewed to highlight the issues and showcase some possible solutions.

scholarly journals Early Detection of CKD: Implications for Low-Income, Middle-Income, and High-Income Countries

2020 ◽  
Vol 31 (9) ◽  
pp. 1931-1940 ◽  
Author(s):  
Marcello Tonelli ◽  
James A. Dickinson
Keyword(s):  
Early Detection ◽  
Low Income ◽  
Population Based ◽  
Case Finding ◽  
High Income ◽  
Opportunity Costs ◽  
Middle Income ◽  
Middle Income Countries ◽  
Use Of Resources ◽  
Low And Middle Income

CKD is common, costly, and associated with adverse health outcomes. Because inexpensive treatments can slow the rate of kidney function loss, and because CKD is asymptomatic until its later stages, the idea of early detection of CKD to improve outcomes ignites enthusiasm, especially in low- and middle-income countries where renal replacement is often unavailable or unaffordable. Available data and prior experience suggest that the benefits of population-based screening for CKD are uncertain; that there is potential for harms; that screening is not a wise use of resources, even in high-income countries; and that screening has substantial opportunity costs in low- and middle-income countries that offset its hypothesized benefits. In contrast, some of the factors that diminish the value of population-based screening (such as markedly higher prevalence of CKD in people with diabetes, hypertension, and cardiovascular disease, as well as high preexisting use of kidney testing in such patients) substantially increase the appeal of searching for CKD in people with known kidney risk factors (case finding) in high-income countries as well as in low- and middle-income countries. For both screening and case finding, detection of new cases is the easiest component; the real challenge is ensuring appropriate management for a chronic disease, usually for years or even decades. This review compares and contrasts the benefits, harms, and opportunity costs associated with these two approaches to early detection of CKD. We also suggest criteria (discussed separately for high-income countries and for low- and middle-income countries) to use in assessing when countries should consider case finding versus when they should consider foregoing systematic attempts at early detection and focus on management of known cases.

scholarly journals Early-life conditions and older adult health in low- and middle-income countries: a review

2012 ◽  
Vol 4 (1) ◽  
pp. 10-29 ◽  
Author(s):  
M. McEniry
Keyword(s):  
Heart Disease ◽  
Older Adult ◽  
Early Life ◽  
Population Based ◽  
Adult Health ◽  
Middle Income ◽  
Middle Income Countries ◽  
Life Conditions ◽  
Early Life Conditions ◽  
Low And Middle Income

Population aging and subsequent projected large increases in chronic conditions will be important health concerns in low- and middle-income countries. Although evidence is accumulating, little is known regarding the impact of poor early-life conditions on older adult (50 years and older) health in these settings. A systematic review of 1141 empirical studies was conducted to identify population-based and community studies in low- and middle-income countries, which examined associations between early-life conditions and older adult health. The resulting review of 20 studies revealed strong associations between (1) in utero/early infancy exposures (independent of other early life and adult conditions) and adult heart disease and diabetes; (2) poor nutrition during childhood and difficulties in adult cognition and diabetes; (3) specific childhood illnesses such as rheumatic fever and malaria and adult heart disease and mortality; (4) poor childhood health and adult functionality/disability and chronic diseases; (5) poor childhood socioeconomic status (SES) and adult mortality, functionality/disability and cognition; and (6) parental survival during childhood and adult functionality/disability and cognition. In several instances, associations remained strong even after controlling for adult SES and lifestyle. Although exact mechanisms cannot be identified, these studies reinforce to some extent the importance of early-life environment on health at older ages. Given the paucity of cohort data from the developing world to examine hypotheses of early-life conditions and older adult health, population-based studies are relevant in providing a broad perspective on the origins of adult health.

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