Dietary Glycemic Index, Dietary Glycemic Load, Blood Lipids, and Coronary Heart Disease

Objective. To examine the associations of dietary glycemic index (GI) and dietary glycemic load (GL) with blood lipid concentrations and coronary heart disease (CHD) in nondiabetic participants in the Health Worker Cohort Study (HWCS). Materials and Methods. A cross-sectional analysis was performed, using data from adults who participated in the HWCS baseline assessment. We collected information on participants' socio-demographic conditions, dietary patterns and physical activity via self-administered questionnaires. Dietary GI and dietary GL were measured using a validated food frequency questionnaire. Anthropometric and clinical measurements were assessed with standardized procedures. CHD risk was estimated according to the sex-specific Framingham prediction algorithms. Results. IIn the 5,830 individuals aged 20 to 70 who were evaluated, dietary GI and GL were significantly associated with HDL-C, LDL-C, LDL-C/HDL-C ratio, and triglycerides serum levels. Subjects with high dietary GI have a relative risk of 1.56 (CI 95%; 1.13–2.14), and those with high dietary GL have a relative risk of 2.64 (CI 95%; 1.15–6.58) of having an elevated CHD risk than those who had low dietary GI and GL. Conclusions. Our results suggest that high dietary GI and dietary GL could have an unfavorable effect on serum lipid levels, which are in turn associated with a higher CHD risk

Dietary patterns in Mexican preschool children are associated with stunting and overweight

OBJECTIVE To evaluate the association between dietary patterns, stunting, and overweight among Mexican preschoolers. METHODS This study was conducted with anthropometric (weight, height/length), sociodemographic (age, gender, education level of household head, socioeconomic status, country region and area, ethnicity, and beneficiary of social programs), and dietary data (Semiquantitative-food frequency questionnaire) on children aged from 1 to 4 years collected from the Mexican National Health and Nutrition Survey-2012. Dietary patterns were derived by principal components analysis. The association between dietary patterns, stunting, and overweight was assessed by prevalence ratios (PR), estimated by Poisson regression. RESULTS In total, 1,112 preschoolers (mean age 3.06 years, SD = 1.08 years; 48.8% females) were included in the study; 11.9% of whom presented stunting, and 6.7% overweight. We identified four dietary patterns: Fruits and Vegetables [F&V], Western [W], Traditional [T], and Milk and Liquids [M&L]. Considering the lowest tertile of each dietary pattern as reference, the prevalence of stunting was 2.04 times higher [95%CI: 1.17–3.56] among children in the highest tertile of the “F&V” pattern. The prevalence of stunting was lower among children in the highest tertile of the “W” pattern [PR = 0.48; 95%CI: 0.27–0.85]. Overweight was negatively associated with the “F&V” dietary pattern [PR = 0.37; 95%CI: 0.16–0.85 for its highest tertile], and children whose consumption was mostly equivalent to the “T” pattern showed higher prevalence of stunting [PR = 1.74; 95%CI: 1.01–3.00]. CONCLUSIONS The prevalence of stunting and overweight in a nationwide sample of Mexican preschoolers was associated with dietary patterns

Differences in the relation between bone mineral content and lean body mass according to gender and reproductive status by age ranges

The present study aims: (1) to explore the influence of lean mass (LM) on bone mineral content (BMC), (2) to investigate the pubertal influences on the BMC–LM relation, and (3) to perform Z-score charts of BMC–LM relation, stratified by gender and reproductive status categorized by age ranges. A cross-sectional analysis was conducted using 4001 healthy subjects between 7 and 90 years participating in the Health Workers Cohort Study. Of these, 720 participants were ≤ 19 years, 2417 were women ≥ 20 years, and 864 were men ≥ 20 years. Using Dual X-ray absorptiometry (DXA), we measured BMC and LM. Participants’ pubertal development was assessed according to Tanner’s stage scale. To describe BMC–LM relation, simple correlation coefficients were computed. To produce best-fit equations, an ANOVA test was conducted. Z-score graphs for the BMC–LM relation were obtained. In general, the BMC–LM correlations were linear and highly significant. For boys, curves were virtually parallel, with similar intercepts and a progressive displacement of values toward the upper-right region of the graph, for each Tanner subgroup. For girls, curves for Tanner 1-2 and 4-5 stages were parallel; but, in girls Tanner 4-5, the intercepts were significantly higher by about +300–400 g of BMC (P < 0.001). For postmenopausal women, the curve was parallel to that for the premenopausal but showed a lower intercept (P < 0.001). We provide DXA reference data on a well-characterized cohort of 4001 healthy subjects. These reference curves provide a reference value for the assessment and monitoring of bone health in all age groups included in the present study.Fil: Denova Gutiérrez, Edgar. Instituto Nacional de Salud Pública; MéxicoFil: Clark, Patricia. Hospital Infantil de México Federico Gómez. Unidad de Investigación en Epidemiología Clínica; México. Universidad Nacional Autónoma de México; MéxicoFil: Capozza, Ricardo Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina. Universidad Nacional de Rosario. Facultad de Ciencias Médicas. Centro de Estudios de Metabolismo Fosfocálcico; ArgentinaFil: Nocciolino, Laura Marcela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina. Universidad Nacional de Rosario. Facultad de Ciencias Médicas. Centro de Estudios de Metabolismo Fosfocálcico; ArgentinaFil: Ferretti, Jose Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina. Universidad Nacional de Rosario. Facultad de Ciencias Médicas. Centro de Estudios de Metabolismo Fosfocálcico; ArgentinaFil: Velázquez Cruz, Rafael. Instituto Nacional de Medicina Genómica México. Laboratorio de Genómica del Metabolismo Óseo; MéxicoFil: Rivera, Berenice. Universidad Nacional Autónoma de México; MéxicoFil: Cointry, Gustavo Roberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina. Universidad Nacional de Rosario. Facultad de Ciencias Médicas. Centro de Estudios de Metabolismo Fosfocálcico; ArgentinaFil: Salmerón, Jorge. Universidad Nacional Autónoma de México; México. Instituto Nacional de Salud Pública; Méxic

Dietary Inflammatory Index and Type 2 Diabetes Mellitus in Adults: The Diabetes Mellitus Survey of Mexico City

Diet and inflammation are both associated with type 2 diabetes mellitus (T2DM). In the present study, we aimed to assess the relation between the dietary inflammatory index (DII) and the presence of T2DM in Mexican adults participating in the Diabetes Mellitus Survey administered in Mexico City (DMS-MC). The study involved 1174 subjects (48.5% men) between 20–69 years of age. A validated semi-quantitative food frequency questionnaire was employed to evaluate dietary intake and to compute DII. The DII is based on scientific evidence about the association between dietary compounds and six established inflammatory biomarkers. Multivariate logistic regression models were used to estimate the odds ratios (ORs) and 95% confidence intervals (95% CIs) of DII in relation to T2DM. Our results suggest that subjects in the highest quintile of the DII had higher odds of T2DM (OR = 3.02; 95% CI: 1.39, 6.58; p = 0.005) compared to subjects in the lowest quintile of DII scores. Assessing possible effect modification, an association with T2DM was evident when comparing DII quintile 5 to quintile 1 for participants aged ≥ 55 years (OR = 9.77; 95% CI: 3.78, 25.50; p = 0.001). These results suggest that a pro-inflammatory diet is associated with significantly higher odds of T2DM among adult Mexicans

Dietary Glycemic Index, Dietary Glycemic Load, Blood Lipids, and Coronary Heart Disease

Objective. To examine the associations of dietary glycemic index (GI) and dietary glycemic load (GL) with blood lipid concentrations and coronary heart disease (CHD) in nondiabetic participants in the Health Worker Cohort Study (HWCS). Materials and Methods. A cross-sectional analysis was performed, using data from adults who participated in the HWCS baseline assessment. We collected information on participants&apos; socio-demographic conditions, dietary patterns and physical activity via self-administered questionnaires. Dietary GI and dietary GL were measured using a validated food frequency questionnaire. Anthropometric and clinical measurements were assessed with standardized procedures. CHD risk was estimated according to the sex-specific Framingham prediction algorithms. Results. IIn the 5,830 individuals aged 20 to 70 who were evaluated, dietary GI and GL were significantly associated with HDL-C, LDL-C, LDL-C/HDL-C ratio, and triglycerides serum levels. Subjects with high dietary GI have a relative risk of 1.56 (CI 95%; 1.13-2.14), and those with high dietary GL have a relative risk of 2.64 (CI 95%; 1.15-6.58) of having an elevated CHD risk than those who had low dietary GI and GL. Conclusions. Our results suggest that high dietary GI and dietary GL could have an unfavorable effect on serum lipid levels, which are in turn associated with a higher CHD risk

Estimates, trends, and drivers of the global burden of type 2 diabetes attributable to PM<inf>2·5</inf> air pollution, 1990–2019: an analysis of data from the Global Burden of Disease Study 2019

Background: Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM2·5 originating from ambient and household air pollution. Methods: We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM2·5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure–response curve from the extracted relative risk estimates using the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM2·5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM2·5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals. Findings: In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM2·5 exposure, with an estimated 3·78 (95% uncertainty interval 2·68–4·83) deaths per 100 000 population and 167 (117–223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13·4% (9·49–17·5) of deaths and 13·6% (9·73–17·9) of DALYs due to type 2 diabetes were contributed by ambient PM2·5, and 6·50% (4·22–9·53) of deaths and 5·92% (3·81–8·64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South America. Since 1990, the attributable burden has increased by 50%, driven largely by population growth and ageing. Globally, the impact of reductions in household air pollution was largely offset by increased ambient PM2·5. Interpretation: Air pollution is a major risk factor for diabetes. We estimated that about a fifth of the global burden of type 2 diabetes is attributable PM2·5 pollution. Air pollution mitigation therefore might have an essential role in reducing the global disease burden resulting from type 2 diabetes. Funding: Bill & Melinda Gates Foundation

Mapping development and health effects of cooking with solid fuels in low-income and middle-income countries, 2000–18: a geospatial modelling study

Background: More than 3 billion people do not have access to clean energy and primarily use solid fuels to cook. Use of solid fuels generates household air pollution, which was associated with more than 2 million deaths in 2019. Although local patterns in cooking vary systematically, subnational trends in use of solid fuels have yet to be comprehensively analysed. We estimated the prevalence of solid-fuel use with high spatial resolution to explore subnational inequalities, assess local progress, and assess the effects on health in low-income and middle-income countries (LMICs) without universal access to clean fuels. Methods: We did a geospatial modelling study to map the prevalence of solid-fuel use for cooking at a 5 km × 5 km resolution in 98 LMICs based on 2·1 million household observations of the primary cooking fuel used from 663 population-based household surveys over the years 2000 to 2018. We use observed temporal patterns to forecast household air pollution in 2030 and to assess the probability of attaining the Sustainable Development Goal (SDG) target indicator for clean cooking. We aligned our estimates of household air pollution to geospatial estimates of ambient air pollution to establish the risk transition occurring in LMICs. Finally, we quantified the effect of residual primary solid-fuel use for cooking on child health by doing a counterfactual risk assessment to estimate the proportion of deaths from lower respiratory tract infections in children younger than 5 years that could be associated with household air pollution. Findings: Although primary reliance on solid-fuel use for cooking has declined globally, it remains widespread. 593 million people live in districts where the prevalence of solid-fuel use for cooking exceeds 95%. 66% of people in LMICs live in districts that are not on track to meet the SDG target for universal access to clean energy by 2030. Household air pollution continues to be a major contributor to particulate exposure in LMICs, and rising ambient air pollution is undermining potential gains from reductions in the prevalence of solid-fuel use for cooking in many countries. We estimated that, in 2018, 205 000 (95% uncertainty interval 147 000–257 000) children younger than 5 years died from lower respiratory tract infections that could be attributed to household air pollution. Interpretation: Efforts to accelerate the adoption of clean cooking fuels need to be substantially increased and recalibrated to account for subnational inequalities, because there are substantial opportunities to improve air quality and avert child mortality associated with household air pollution. Funding: Bill & Melinda Gates Foundation

Global, regional, and national burden of osteoarthritis, 1990–2020 and projections to 2050: a systematic analysis for the Global Burden of Disease Study 2021

Background Osteoarthritis is the most common form of arthritis in adults, characterised by chronic pain and loss of mobility. Osteoarthritis most frequently occurs after age 40 years and prevalence increases steeply with age. WHO has designated 2021–30 the decade of healthy ageing, which highlights the need to address diseases such as osteoarthritis, which strongly affect functional ability and quality of life. Osteoarthritis can coexist with, and negatively effect, other chronic conditions. Here we estimate the burden of hand, hip, knee, and other sites of osteoarthritis across geographies, age, sex, and time, with forecasts of prevalence to 2050. Methods In this systematic analysis for the Global Burden of Disease Study, osteoarthritis prevalence in 204 countries and territories from 1990 to 2020 was estimated using data from population-based surveys from 26 countries for knee osteoarthritis, 23 countries for hip osteoarthritis, 42 countries for hand osteoarthritis, and US insurance claims for all of the osteoarthritis sites, including the other types of osteoarthritis category. The reference case definition was symptomatic, radiographically confirmed osteoarthritis. Studies using alternative definitions from the reference case definition (for example self-reported osteoarthritis) were adjusted to reference using regression models. Osteoarthritis severity distribution was obtained from a pooled meta-analysis of sources using the Western Ontario and McMaster Universities Arthritis Index. Final prevalence estimates were multiplied by disability weights to calculate years lived with disability (YLDs). Prevalence was forecast to 2050 using a mixed-effects model. Findings Globally, 595 million (95% uncertainty interval 535–656) people had osteoarthritis in 2020, equal to 7·6% (95% UI 6·8–8·4) of the global population, and an increase of 132·2% (130·3–134·1) in total cases since 1990. Compared with 2020, cases of osteoarthritis are projected to increase 74·9% (59·4–89·9) for knee, 48·6% (35·9–67·1) for hand, 78·6% (57·7–105·3) for hip, and 95·1% (68·1–135·0) for other types of osteoarthritis by 2050. The global age-standardised rate of YLDs for total osteoarthritis was 255·0 YLDs (119·7–557·2) per 100 000 in 2020, a 9·5% (8·6–10·1) increase from 1990 (233·0 YLDs per 100 000, 109·3–510·8). For adults aged 70 years and older, osteoarthritis was the seventh ranked cause of YLDs. Age-standardised prevalence in 2020 was more than 5·5% in all world regions, ranging from 5677·4 (5029·8–6318·1) per 100 000 in southeast Asia to 8632·7 (7852·0–9469·1) per 100 000 in high-income Asia Pacific. Knee was the most common site for osteoarthritis. High BMI contributed to 20·4% (95% UI –1·7 to 36·6) of osteoarthritis. Potentially modifiable risk factors for osteoarthritis such as recreational injury prevention and occupational hazards have not yet been explored in GBD modelling. Interpretation Age-standardised YLDs attributable to osteoarthritis are continuing to rise and will lead to substantial increases in case numbers because of population growth and ageing, and because there is no effective cure for osteoarthritis. The demand on health systems for care of patients with osteoarthritis, including joint replacements, which are highly effective for late stage osteoarthritis in hips and knees, will rise in all regions, but might be out of reach and lead to further health inequity for individuals and countries unable to afford them. Much more can and should be done to prevent people getting to that late stage

Estimates, trends, and drivers of the global burden of type 2 diabetes attributable to PM2.5 air pollution, 1990-2019 : An analysis of data from the Global Burden of Disease Study 2019

Background Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM2·5 originating from ambient and household air pollution. Methods We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM2·5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure–response curve from the extracted relative risk estimates using the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM2·5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM2·5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals. Findings In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM2·5 exposure, with an estimated 3·78 (95% uncertainty interval 2·68–4·83) deaths per 100 000 population and 167 (117–223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13·4% (9·49–17·5) of deaths and 13·6% (9·73–17·9) of DALYs due to type 2 diabetes were contributed by ambient PM2·5, and 6·50% (4·22–9·53) of deaths and 5·92% (3·81–8·64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South America. Since 1990, the attributable burden has increased by 50%, driven largely by population growth and ageing. Globally, the impact of reductions in household air pollution was largely offset by increased ambient PM2·5. Interpretation Air pollution is a major risk factor for diabetes. We estimated that about a fifth of the global burden of type 2 diabetes is attributable PM2·5 pollution. Air pollution mitigation therefore might have an essential role in reducing the global disease burden resulting from type 2 diabetes