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Abstract
Understanding the distribution and variation in inflammatory markers is crucial for
advancing our knowledge of inflammatory processes and evaluating their clinical utility
in diagnosing and monitoring acute and chronic disease.
1H NMR spectroscopy of blood plasma and serum was applied to measure a composite panel
of inflammatory markers based on acute phase glycoprotein signals (GlycA and GlycB)
and sub-regions of the lipoprotein derived Supramolecular Phospholipid Composite signals
(SPC
1, SPC
2 and SPC
3) to establish normal ranges in two healthy, predominantly white cohorts from Australia
(n = 398) and Spain (n = 80; ages 20–70 years). GlycA, GlycB, SPC
1 and SPC
3 were not significantly impacted by age or sex, but SPC
2 (an HDL-related biomarker) was significantly higher in women across all age ranges
by an average of 33.7%. A free-living Australian population cohort (n = 3945) was
used to explore the relationship of BMI with the panel of inflammatory markers. The
glycoprotein signals were directly associated with BMI with GlycB levels being significantly
higher for women in all BMI classes. Conversely, SPC
2 was found to be inversely associated with BMI and differed significantly between
the sexes at each BMI category (normal weight
p = 3.46x10
-43, overweight
p = 3.33x10
-79, obese
p = 2.15x10
-64). SPC
1 and SPC
3 were markedly less affected by BMI changes. Given the significant association between
SPC
2 and sex, these data suggest that men and women should be modelled independently for
NMR-determined inflammatory biomarkers, or that data should be corrected for sex.
Summary Background Global development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017. Methods The causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries—Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODEm), to generate cause fractions and cause-specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised. Findings At the broadest grouping of causes of death (Level 1), non-communicable diseases (NCDs) comprised the greatest fraction of deaths, contributing to 73·4% (95% uncertainty interval [UI] 72·5–74·1) of total deaths in 2017, while communicable, maternal, neonatal, and nutritional (CMNN) causes accounted for 18·6% (17·9–19·6), and injuries 8·0% (7·7–8·2). Total numbers of deaths from NCD causes increased from 2007 to 2017 by 22·7% (21·5–23·9), representing an additional 7·61 million (7·20–8·01) deaths estimated in 2017 versus 2007. The death rate from NCDs decreased globally by 7·9% (7·0–8·8). The number of deaths for CMNN causes decreased by 22·2% (20·0–24·0) and the death rate by 31·8% (30·1–33·3). Total deaths from injuries increased by 2·3% (0·5–4·0) between 2007 and 2017, and the death rate from injuries decreased by 13·7% (12·2–15·1) to 57·9 deaths (55·9–59·2) per 100 000 in 2017. Deaths from substance use disorders also increased, rising from 284 000 deaths (268 000–289 000) globally in 2007 to 352 000 (334 000–363 000) in 2017. Between 2007 and 2017, total deaths from conflict and terrorism increased by 118·0% (88·8–148·6). A greater reduction in total deaths and death rates was observed for some CMNN causes among children younger than 5 years than for older adults, such as a 36·4% (32·2–40·6) reduction in deaths from lower respiratory infections for children younger than 5 years compared with a 33·6% (31·2–36·1) increase in adults older than 70 years. Globally, the number of deaths was greater for men than for women at most ages in 2017, except at ages older than 85 years. Trends in global YLLs reflect an epidemiological transition, with decreases in total YLLs from enteric infections, respiratory infections and tuberculosis, and maternal and neonatal disorders between 1990 and 2017; these were generally greater in magnitude at the lowest levels of the Socio-demographic Index (SDI). At the same time, there were large increases in YLLs from neoplasms and cardiovascular diseases. YLL rates decreased across the five leading Level 2 causes in all SDI quintiles. The leading causes of YLLs in 1990—neonatal disorders, lower respiratory infections, and diarrhoeal diseases—were ranked second, fourth, and fifth, in 2017. Meanwhile, estimated YLLs increased for ischaemic heart disease (ranked first in 2017) and stroke (ranked third), even though YLL rates decreased. Population growth contributed to increased total deaths across the 20 leading Level 2 causes of mortality between 2007 and 2017. Decreases in the cause-specific mortality rate reduced the effect of population growth for all but three causes: substance use disorders, neurological disorders, and skin and subcutaneous diseases. Interpretation Improvements in global health have been unevenly distributed among populations. Deaths due to injuries, substance use disorders, armed conflict and terrorism, neoplasms, and cardiovascular disease are expanding threats to global health. For causes of death such as lower respiratory and enteric infections, more rapid progress occurred for children than for the oldest adults, and there is continuing disparity in mortality rates by sex across age groups. Reductions in the death rate of some common diseases are themselves slowing or have ceased, primarily for NCDs, and the death rate for selected causes has increased in the past decade. Funding Bill & Melinda Gates Foundation.
Obesity is the accumulation of abnormal or excessive fat that may interfere with the maintenance of an optimal state of health. The excess of macronutrients in the adipose tissues stimulates them to release inflammatory mediators such as tumor necrosis factor α and interleukin 6, and reduces production of adiponectin, predisposing to a pro-inflammatory state and oxidative stress. The increased level of interleukin 6 stimulates the liver to synthesize and secrete C-reactive protein. As a risk factor, inflammation is an imbedded mechanism of developed cardiovascular diseases including coagulation, atherosclerosis, metabolic syndrome, insulin resistance, and diabetes mellitus. It is also associated with development of non-cardiovascular diseases such as psoriasis, depression, cancer, and renal diseases. On the other hand, a reduced level of adiponectin, a significant predictor of cardiovascular mortality, is associated with impaired fasting glucose, leading to type-2 diabetes development, metabolic abnormalities, coronary artery calcification, and stroke. Finally, managing obesity can help reduce the risks of cardiovascular diseases and poor outcome via inhibiting inflammatory mechanisms.
Publisher:
Public Library of Science
(San Francisco, CA USA
)
ISSN
(Electronic):
1932-6203
Publication date
(Electronic):
6
January
2025
Publication date Collection: 2025
Volume: 20
Issue: 1
Electronic Location Identifier: e0311975
Affiliations
[1
]
Australian National Phenome Center and Center for Computational and Systems Medicine,
Health Futures Institute, Murdoch University, Perth, Western Australia, Australia
[2
]
School of Biomedical Sciences, University of Western Australia, Perth, Western Australia,
Australia
[3
]
PathWest Laboratory Medicine, Queen Elizabeth II Medical Centre, Perth, Western Australia,
Australia
[4
]
School of Population and Global Health, University of Western Australia, Perth, Western
Australia, Australia
[5
]
School of Medicine, University of Western Australia, Crawley, Western Australia, Australia
[6
]
Department of Endocrinology and Diabetes, Fiona Stanley Hospital, Murdoch, Western
Australia, Australia
[7
]
Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia,
Derio, Spain
[8
]
Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial
College London, London, United Kingdom
[9
]
Chemistry Department, Universidad del Valle, Cali, Colombia
[10
]
Institute of Global Health Innovation, Faculty of Medicine, Imperial College London,
London, United Kingdom
Catholic University of Brasilia, BRAZIL
Author notes
Competing Interests: The authors have declared that no competing interests exist.
This is an open access article distributed under the terms of the
Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided
the original author and source are credited.
History
Date
received
: 2
July
2024
Date
accepted
: 27
September
2024
Page count
Figures: 3,
Tables: 0,
Pages: 15
Funding
The author(s) received no specific funding for this work.
Categories
Subject:
Research Article
Subject:
Biology and Life Sciences
Subject:
Physiology
Subject:
Physiological Parameters
Subject:
Body Weight
Subject:
Body Mass Index
Subject:
Biology and Life Sciences
Subject:
Immunology
Subject:
Immune Response
Subject:
Inflammation
Subject:
Medicine and Health Sciences
Subject:
Immunology
Subject:
Immune Response
Subject:
Inflammation
Subject:
Medicine and Health Sciences
Subject:
Clinical Medicine
Subject:
Signs and Symptoms
Subject:
Inflammation
Subject:
Biology and Life Sciences
Subject:
Physiology
Subject:
Physiological Parameters
Subject:
Body Weight
Subject:
Obesity
Subject:
Medicine and Health Sciences
Subject:
Medical Conditions
Subject:
Inflammatory Diseases
Subject:
Research and analysis methods
Subject:
Spectrum analysis techniques
Subject:
NMR spectroscopy
Subject:
Biology and Life Sciences
Subject:
Biochemistry
Subject:
Lipids
Subject:
Phospholipids
Subject:
Biology and Life Sciences
Subject:
Biochemistry
Subject:
Proteins
Subject:
Lipoproteins
Subject:
Biology and Life Sciences
Subject:
Biochemistry
Subject:
Glycobiology
Subject:
Glycoproteins
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Data Availability All data files are open access available from the zenodo database (
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