Summary
Background
Fractures related to osteoporosis and low bone mineral density lead to substantial morbidity, mortality, and cost to individuals and health systems. Here we present the most up-to-date global, regional, and national estimates of the contribution of low bone mineral density to the burden of fractures from falls and additional categories of injuries from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021.
Methods
The burden of low bone mineral density was estimated from 1990 to 2020 in terms of years lived with disability (YLDs), disability-adjusted life years (DALYs), and deaths, for individuals aged 40 years and older, using data from population-based studies from 48 countries or territories (169 unique sources). Mean standardised femoral neck bone mineral density values were estimated by GBD location, age, and sex by meta-regression. Based on a separate meta-analysis of population-based studies from nine countries (12 unique sources), we also estimated the pooled relative risk of fractures per unit decrease in bone mineral density (g/cm2). The population-attributable fraction for low bone mineral density was calculated by comparing the observed distributions of standardised femoral neck bone mineral density to an age-specific and sex-specific counterfactual distribution, defined as the 99th percentile of five rounds of the National Health and Nutrition Examination Survey in the USA, by 5-year age group and sex. Hospital and emergency department data were used to derive the incidence of fractures for six categories of injury (road injuries, other transport injuries, falls, non-venomous animal contact, exposure to mechanical forces, and physical interpersonal violence) using ICD codes. Deaths due to fractures were estimated as the proportion of in-hospital deaths due to the specified injury causes for which a fracture (nature of injury code) was more severe than the cause of injury code. YLDs and DALYs attributable to low bone mineral density by cause of injury were also determined according to previous GBD methods.
Findings
In 2020, 8·32 million (95% UI 5·58–10·84) YLDs, 17·2 million (14·1–20·2) DALYs, and 477 000 (411 000–536 000) deaths were attributable to low bone mineral density globally in individuals aged 40 years and older. Between 1990 and 2020, global YLDs, DALYs, and deaths attributable to low bone mineral density increased by 91·8% (88·5–95·1), 89·8% (81·5–99·0), and 127·1% (108·5–144·5), respectively. Over this period, the age-standardised global rates of YLDs, DALYs, and deaths attributable to low bone mineral density showed modest decreases. In 2020, falls accounted for 76·2% (95% UI 74·2–78·3) of YLDs, 65·2% (62·9–67·6) of DALYs, and 71·0% (67·4–72·8) of deaths attributable to low bone mineral density, and road injuries largely accounted for the remaining amount: 12·4% (11·1–13·6) of YLDs, 24·6% (22·5–27·1) of DALYs, and 23·1% (21·6–26·2) of deaths. As a proportion of all fall-related burden, low bone mineral density accounted for 26·6% (23·2–28·7) of YLDs, 25·6% (22·1–27·4) of DALYs, and 40·6% (35·4–44·0) of deaths in 2020. Of all road injury-related burden, 12·6% (10·8–13·5) of YLDs, 6·3% (5·4–6·9) of DALYs, and 8·9% (7·6–9·6) of deaths were attributable to low bone mineral density. In men, road injuries accounted for the largest proportion of DALYs attributable to low bone mineral density in those aged 40–59 years and the largest proportion of deaths in those aged 40–64 years. In women, road injuries were the leading cause of DALYs attributable to low bone mineral density in those aged 40–44 years and the leading cause of deaths attributable to low bone mineral density in those aged 40–54 years. In older age groups among both men and women, falls were the leading cause of the burden attributable to low bone mineral density.
Interpretation
Low bone mineral density is a crucial modifiable risk factor for fractures, which are an important cause of morbidity and mortality particularly in ageing populations. This analysis highlights low bone mineral density as a cause of health loss not just from falls, but also from road injuries.
Funding
Gates Foundation.
Research in context.
Evidence before this study
Low bone mineral density is a reliably measurable and modifiable risk factor for fractures at the hip, spine, and other skeletal sites. Low bone mineral density is acknowledged as a risk factor for fractures related to falls and minor trauma, but few studies to date have explored the relationship between bone mineral density and major non-fall-related injuries. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) analyses low bone mineral density as a risk factor that directly contributes to quantifiable disease burden from fractures. For GBD 2015 we searched PubMed for population-based studies reporting femoral neck bone mineral density measured by dual-energy x-ray absorptiometry from Jan 1, 1980, to Dec 31, 2015, using the search terms (osteoporosis OR osteopenia OR osteopaenia OR bone mineral density OR radiolucency) AND (prevalen* OR inciden* OR cross-sectional OR cross sectional OR epidemi* OR survey OR population-based OR population based OR population study OR population sample OR cohort OR follow-up OR follow up OR longitudinal OR regist* OR data collection). Additional studies encountered opportunistically during data review were added for GBD 2016, 2017, 2019, and 2021. In parallel, a systematic search of PubMed done for GBD 2019 and updated for GBD 2021 identified studies published from Jan 1, 2010, to Dec 31, 2020, reporting the relative risk of hip or non-hip fracture per change in bone mineral density, using the search terms (bone mineral density[title/abstract] OR bone mineral densities[title/abstract]) OR bone density[Mesh]) AND (mean[title/abstract] OR average[title/abstract]) AND risk[Mesh]) AND fracture[title/abstract]).
Added value of this study
This synthesis provides updated and comprehensive estimates of the global burden from fractures attributable to low bone mineral density from 1990 to 2020, and quantifies the contribution of six categories of injury (falls, road injuries, other transport injuries, exposure to mechanical forces, animal contact, and interpersonal violence) in men and women aged 40 years and older. An increase in burden related to low bone mineral density was observed, with a nearly two-times increase in years lived with disability and disability-adjusted life-years and a greater than two-times increase in deaths attributable to low bone mineral density. Among the types of injury, road injuries were the largest contributor to burden attributable to low bone mineral density among middle-aged men, and a main contributor among middle-aged women. In older individuals, falls represented the predominant cause of burden attributable to low bone mineral density.
Implications of all the available evidence
Low bone mineral density is an important predictor of fracture that is modifiable by existing prevention and treatment interventions. Strengthened policy and implementation strategies are needed to improve the uptake of evidence-based injury and fracture prevention approaches and to promote lifestyle strategies, to support bone health across the life-course.
Introduction
Fractures related to osteoporosis represent a substantial burden and economic cost for societies across the world, and a steady increase in incidence is forecast over the coming decades.1, 2 In addition to the pain, functional impairment, and mortality risks associated with a fracture in the short term, the lasting consequences of bone fractures include chronic pain, permanent disability, and long-term institutionalisation.3, 4 A study of the Danish National Hospital Discharge Registry showed that 1 year after a hip fracture event, cumulative mortality was 37·1% in men and 26·4% in women, compared with 9·9% in men and 9·3% in women in the general population.5 In the USA, approximately half of individuals who have osteoporotic fractures (also known as fragility fractures) never regain their pre-fracture level of physical function, and many lose their independence, requiring long-term care.6 Furthermore, estimates show that fragility fractures lead to higher costs for individuals and health-care systems than other common disabling disorders such as myocardial infarction, stroke, Parkinson's disease, and rheumatoid arthritis.7, 8
Cost-effective strategies exist for the identification and treatment of individuals with low bone mineral density who are at high risk of fracture,9, 10 yet there is little awareness regarding these strategies among health professionals, public health institutions, and the general population, as highlighted in a report of EU countries.7 Low bone mineral density has been consistently shown to predict fragility fractures at the hip and other sites.11 Standard methods to measure bone mineral density exist using dual-energy x-ray absorptiometry (DXA), allowing for the comparison of values between different populations, and the establishment of diagnostic and treatment thresholds.12, 13
We previously estimated the burden of falls attributable to low bone mineral density in persons aged 50 years and older as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2010.14 In this updated and expanded analysis of the GBD 2021 dataset, which encompasses data from 1990 to 2020, we estimate the burden—including years lived with disability (YLDs), disability-adjusted life years (DALYs), and mortality—attributable to low bone mineral density in people aged 40 years and older in the setting of falls, road injuries and other transport injuries, exposure to mechanical forces, animal contact, and interpersonal violence.
Methods
Overview
This Article was produced as part of the GBD Collaborator Network and in accordance with the GBD Protocol. This study adheres to the GATHER statement15 and follows the comparative risk assessment methodology used in the GBD, as previously described.14, 16 Briefly, by this methodology, the burden due to a risk factor is compared to a hypothetical counterfactual exposure level that would result in the lowest attributable burden, referred to as the theoretical minimum risk exposure level (TMREL; appendix 1 p 1).14, 16 Full details of the methods are included in appendix 1 (pp 14–31).
Case definition and input data
The case definition for bone mineral density refers to bone mineral density measured at the femoral neck by DXA in g/cm2. A systematic review was done for GBD 2010 to identify all population-based studies published from Jan 1, 1980, to Dec 31, 2010, reporting femoral neck bone mineral density (mean [SD]) measured by DXA.14 This search was last updated during GBD 2015, but with each successive round of the GBD up to GBD 2021, new sources suggested by collaborators within the GBD Network or identified in the Global Health Data Exchange database by GBD librarians (keywords: bone mineral density or osteoporosis) have been included. All sources up to GBD 2021 are available online in the GBD 2021 Sources Tool. Details of the search strategy, databases, inclusion and exclusion criteria, risk of bias assessment, and data extraction have been described previously.14, 16 All mean (SD) values for femoral neck bone mineral density from eligible studies, measured using DXA systems from different manufacturers, were extracted and standardised by international conversion formulas to mean standardised femoral neck bone mineral density and standardised SD.17 Mean standardised femoral neck bone mineral density values were estimated as a continuous parameter for each GBD location, age, and sex, from 1990 to 2020 using DisMod-MR 2.1 (Disease Modelling Meta-Regression; version 2.1), a Bayesian meta-regression tool developed specifically for the GBD.18 DisMod-MR 2.1 was chosen due to its ability to leverage information across locations, years, and heterogeneous age groups to generate estimates when data are sparse or missing. Estimates were generated for 204 countries and territories and for the GBD regions and super-regions. Age was modelled in 5-year intervals starting from 40–44 years, with the final category covering ages 95 years and older. Estimates were modelled up to 2020 to align with other papers in a recent musculoskeletal series by GBD collaborators.19
Defining the TMREL for low bone mineral density
To select counterfactual exposure levels of bone mineral density, defined as the exposure level with no or very low exposure to low bone mineral density, the TMREL was taken as the 99th percentile of the femoral neck bone mineral density values (mean [SD]), by 5-year age groups (from age 40–44 years up to ≥95 years) and sex, from five different cycles (years 1988–94, 2005–06, 2007–08, 2009–10, and 2013–14) of the US National Health and Nutrition Examination Survey,20, 21, 22, 23, 24 as the most broadly accepted standard international reference. Low bone mineral density exposure was defined as the difference between the mean bone mineral density of a population and the TMREL at the same age and sex. This meant that low bone mineral density exposure in a population was quantified as the amount by which the population's mean bone mineral density fell below the TMREL for the same age and sex. If the mean bone mineral density was higher than the TMREL, the exposure was considered zero.
Risk estimation
To establish the relationship between low bone mineral density and fracture risk we conducted a meta-analysis. A systematic review originally conducted for GBD 2019 and updated for GBD 2021 identified six studies that reported fracture risk per SD of bone mineral density.25, 26, 27, 28, 29, 30 Specifically, studies were eligible for inclusion if they: included representative, population-based longitudinal data; reported femoral neck bone mineral density measured by DXA as the exposure variable; reported relative risk of fractures per change in bone mineral density (most often captured as the per 1 SD decrease in bone mineral density); and included fractures (including type of fractures) as an outcome of interest. These studies were supplemented with six additional studies31, 32, 33, 34, 35, 36 meeting criteria for inclusion (from a larger meta-analysis of 12 studies that previously estimated the relative risk of fragility fracture associated with low bone mineral density11). The relationship between low bone mineral density and fracture risk was subsequently modelled using a meta-regression–Bayesian, regularised, trimmed meta-analysis.37 Relative risks were estimated separately for hip and non-hip fractures (appendix 1 p 2).
Estimate projections
The attributable burden of fractures due to low bone mineral density was calculated by comparing the observed distribution of standardised femoral neck bone mineral density to the counterfactual distribution for each age group, sex, location, year, and cause according to the following formula, as described previously:14
where PAFoasgt represents the population attributable fraction for outcome o (ie, hip or non-hip fracture), age group a, sex s, location g, and year t; RRo (x) is the relative risk at exposure level x for outcome o with the lowest observed exposure as l and the highest as u; Pasgt(x) is the exposure at level x for age group a, sex s, location g, and year t; TMRELas is the TMREL for age group a and sex s.
Risk estimation for injuries
In view of the evidence showing the similar role of bone mineral density in both low-energy and high-energy trauma,38 the estimation of burden attributable to low bone mineral density included fractures from unintentional injuries (falls, non-venomous animal contact, and exposure to mechanical forces [an aggregate of two causes: unintentional firearms and other exposure to mechanical forces]), from transportation injuries, including road injuries (pedestrian road injuries, cyclist road injuries, motorcyclist road injuries, motor vehicle road injuries) and other transport injuries (eg, trains, ferries, and aeroplanes), and interpersonal violence (physical violence by other means than firearms). The six distinct categories evaluated in the present analyses were road injuries, other transport injuries, falls, animal contact, exposure to mechanical forces, and interpersonal violence.
Methods to estimate the incidence of and deaths due to each injury have been described in detail previously,39 with references for datasets available on the GBD 2021 Sources Tool. In summary, we utilised data from vital registration records, verbal autopsy, and police records for deaths, and from hospital and emergency or outpatient departments, insurance claims, and surveys that reported on injuries that warranted care for incidence. Death estimates were modelled with the Cause of Death Ensemble model tool,40 which selects an ensemble of mixed-effects or spatiotemporal Gaussian regression models of mortality rates or cause fractions. The hierarchical Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to estimate the incidence of each injury.18 Years of life lost (YLLs) were the product of the number of deaths and standard life expectancy at each age of death,41 and YLDs were the product of the disability weight corresponding to each ICD nature-of-injury code (N-code) and their probabilities of long-term and short-term impacts. DALYs were calculated as the sum of YLLs and YLDs.
There were two steps to estimate the fraction of fractures that were due to low bone mineral density for each injury. First, we estimated the fraction of each injury that resulted in a fracture. We calculated this across the six causes of injuries separately (by ICD external cause codes, E-codes) and then as a total. Briefly, we applied the ratio of fracture versus non-fracture injuries within each E-code. To derive these ratios, we used hospital and emergency department datasets with detailed diagnostic codes (ICD-9 and ICD-10) that were dual-coded with both the cause of injury (E-code; eg, falls or road injury) and nature of injury (N-code; eg, fracture or traumatic brain injury). We calculated the ratio of injuries attributable to fracture versus non-fracture injuries. These dual-coded data were available from 35 countries: Argentina, Brazil, Bulgaria, China, Chile, Colombia, Cyprus, Czech Republic, Denmark, Egypt, England, Estonia, Georgia, Hungary, Iceland, Iran, Italy, India, Kyrgyzstan, Latvia, Macedonia, Malta, Mauritius, Mexico, Mozambique, Netherlands, New Zealand, Norway, the Philippines, Portugal, Slovenia, Spain, Sweden, Uganda, the USA, and Zambia.39 Second, we applied this ratio to the population attributable fractions for fractures by E-code to quantify the magnitude of each burden measurement that resulted from low bone mineral density. We then aggregated the low bone mineral density-specific and total number of YLDs, DALYs, and deaths across E-codes to calculate the proportion of burden of each E-code that was due to low bone mineral density.
We observed that each cause of injury could result in multiple N-codes within each dataset, so we applied a series of logical and pragmatic decisions. First, we assumed that only hip fractures and some non-hip fractures, including vertebral, pelvic, and humeral fractures, were assumed to be potentially fatal. Second, we assigned the death to the fracture in the absence of a more severe injury code (N-code) that could better explain the death (ie, moderate to severe head trauma, spinal cord lesion, and intra-abdominal or thoracic organ damage).
For all measures, uncertainty was calculated by taking the final 100 draws from the posterior distribution. We report the 95% uncertainty intervals (UIs) as the 2·5th and 97·5th percentile values. Age-standardised rates and values were calculated with use of the GBD standard population.42 We provide detailed data on DALYs but not always on YLDs because, for low bone mineral density, YLDs are nearly equivalent to DALYs. This is due to the age structure of low bone mineral density, which primarily affects older adults who contribute few YLLs.
Decomposition analysis
A Das Gupta decomposition analysis was done to determine the relative contributions of four factors to the change in absolute DALYs and deaths attributable to low bone mineral density between 1990 and 2020. These factors were population growth, population ageing, changes in exposure to low bone mineral density, and changes in risk-deleted injury (ie, injury-related DALY or death rate after removing the effect of low bone mineral density on overall rate).43
Role of the funding source
The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report.
Results
The current analysis is based on 169 unique sources (including some sources reporting bone mineral density in multiple countries) representing 48 countries or territories and all seven GBD super-regions for mean bone mineral density, and on 12 sources representing nine countries and three super-regions for the meta-analysis establishing the relationship between low bone mineral density and risk of fracture (appendix 1 p 3).
In 2020, 8·32 million (95% UI 5·58–10·84) YLDs, 17·2 million (14·1–20·2) DALYs, and 477 000 (411 000–536 000) deaths were attributable to low bone mineral density. From 1990 to 2020, age-standardised mean bone mineral density values in the global population remained stable in men (0·85 g/cm2 [0·82–0·87] in 1990 vs 0·87 g/cm2 [0·84–0·89] in 2020) and women (0·75 g/cm2 [0·73–0·77] in 1990 vs 0·76 g/cm2 [0·74–0·78]) in 2020 (figure 1A). In 2020, mean bone mineral density was lower in women than in men across all age strata. In women, mean bone mineral density decreased from 0·86 g/cm2 (0·78–0·94) at age 40–44 years to 0·65 g/m2 (0·60–0·70) at age 80–84 years (figure 1B). The lowest mean bone mineral density was observed in women aged 95 years and older, although the 95% UIs widened due to the smaller size of this age group. Similarly, in men, mean bone mineral density decreased from 0·95 g/cm2 (0·86–1·04) at age 40–44 years to 0·79 g/cm2 (0·73–0·87) at age 85–89 years. Global, region, and country or territory level mean bone mineral density data in 2020, including change from 1990, by sex for all ages combined, are shown in appendix 1 (pp 4–7).
Figure 1.
Bone mineral density values for the global population by sex
(A) Age-standardised mean bone mineral density values from 1990 to 2020. (B) Mean bone mineral density values in 2020 by 5-year age-strata. Shaded regions represent 95% UIs.
Between 1990 and 2020, global YLDs attributable to low bone mineral density increased by 91·8% (95% UI 88·5–95·1), DALYs increased by 89·8% (81·5–99·0), and deaths increased by 127·1% (108·5–144·5). After standardisation by age, global rates of YLDs, DALYs and deaths attributable to low bone mineral density showed modest decreases between 1990 and 2020 (–12·9% [–14·2 to –11·6] for YLDs, –12·7% [–16·5 to –8·6] for DALYs, and –4·0% [–10·9 to 3·5] for deaths; table).
Table.
Absolute numbers and age-standardised rates of DALYs and deaths attributable to low bone mineral density in 2020, and percentage change in age-standardised rates from 1990 to 2020, globally and by super-region, region, and country or territory
| Number of DALYs in 2020 | Age-standardised rate of DALYs per 100 000 in 2020 | Percentage change in age-standardised rate of DALYs per 100 000 from 1990 to 2020 | Number of deaths in 2020 | Age-standardised rate of deaths per 100 000 in 2020 | Percentage change in age-standardised rate of deaths per 100 000 from 1990 to 2020 | ||
|---|---|---|---|---|---|---|---|
| Global | 17 200 000 (14 100 000–20 200 000) | 207·6 (170·0–243·3) | −12·7 (−16·5 to −8·6) | 477 000 (411 000–536 000) | 6·0 (5·1–6·7) | −4·0 (−10·9 to 3·5) | |
| Central Europe, eastern Europe, and central Asia | 1 170 000 (878 000–1 460 000) | 190·6 (142·3–236·0) | −29·9 (−32·8 to −27·6) | 19 100 (16 200–21 200) | 3·1 (2·6–3·4) | −37·9 (−40·7 to −34·9) | |
| Central Asia | 97 300 (73 900–117 000) | 123·7 (94·3–148·3) | −31·5 (−34·9 to −28·6) | 1510 (1280–1690) | 2·2 (1·9–2·5) | −32·6 (−37·5 to −26·7) | |
| Armenia | 4100 (3270–4960) | 102·2 (82·0–123·5) | −44·8 (−47·8 to −42·4) | 78·8 (66·8–89·9) | 2·0 (1·7–2·2) | −40·8 (−46·7 to −34·9) | |
| Azerbaijan | 8160 (5920–10 000) | 81·1 (59·3–98·7) | −41·7 (−46·8 to −37·2) | 98·3 (77·4–119) | 1·2 (0·9–1·5) | −53·6 (−62·8 to −43·4) | |
| Georgia | 12 200 (9430–14 500) | 212·7 (164·5–255·0) | 8·9 (2·1 to 14·5) | 287 (237–324) | 4·5 (3·7–5·1) | 31·6 (17·8 to 43·3) | |
| Kazakhstan | 27 400 (21 400–33 200) | 149·2 (116·0–180·3) | −23·8 (−30·2 to −18·2) | 385 (321–449) | 2·3 (1·9–2·6) | −34·2 (−43·3 to −24·7) | |
| Kyrgyzstan | 6200 (5070–7430) | 120·5 (97·2–143·7) | −38·7 (−43·6 to −33·4) | 104 (86·7–123) | 2·2 (1·8–2·5) | −39·6 (−47·7 to −29·9) | |
| Mongolia | 5310 (4100–6510) | 183·1 (141·5–222·7) | 9·8 (−1·5 to 20·6) | 79·2 (63·2–100) | 3·1 (2·5–3·8) | −6·2 (−27·4 to 16·1) | |
| Tajikistan | 5560 (4250–6850) | 96·9 (74·2–118·1) | −41·1 (−46·5 to −35·2) | 76·8 (59·8–93·3) | 1·7 (1·3–2·1) | −38·8 (−50·7 to −23·6) | |
| Turkmenistan | 3550 (2590–4450) | 82·0 (59·8–102·2) | −37·2 (−44·1 to −31·6) | 45·2 (35·9–55·3) | 1·1 (0·9–1·3) | −49·0 (−57·6 to −37·9) | |
| Uzbekistan | 24 800 (18 800–30 300) | 104·0 (79·1–126·5) | −39·2 (−43·5 to −35·4) | 357 (298–417) | 2·0 (1·7–2·2) | −45·3 (−51·4 to −38·9) | |
| Central Europe | 431 000 (319 000–530 000) | 204·8 (151·3–252·6) | −38·7 (−42·4 to −35·7) | 8380 (7050–9410) | 3·8 (3·2–4·2) | −53·5 (−56·9 to −50·7) | |
| Albania | 6210 (4350–7930) | 150·6 (105·2–192·8) | −22·3 (−27·4 to −17·9) | 72·8 (58·5–90·2) | 1·8 (1·4–2·2) | −26·6 (−39·1 to −9·3) | |
| Bosnia and Herzegovina | 7760 (5380–9900) | 135·7 (94·2–173·4) | −31·1 (−34·7 to −26·5) | 83·2 (58·6–104) | 1·5 (1·1–1·9) | −41·7 (−52·0 to −27·5) | |
| Bulgaria | 24 400 (17 300–30 900) | 182·4 (129·5–230·2) | −24·1 (−29·0 to −19·6) | 333 (283–386) | 2·4 (2·1–2·8) | −39·9 (−45·8 to −32·1) | |
| Croatia | 24 300 (18 500–29 400) | 267·1 (201·9–324·1) | −24·8 (−29·5 to −19·6) | 627 (517–730) | 6·5 (5·3–7·6) | −34·7 (−42·3 to −24·9) | |
| Czechia | 47 500 (35 400–57 800) | 224·5 (165·6–274·6) | −50·4 (−54·8 to −46·6) | 1090 (921–1250) | 4·8 (4·1–5·5) | −65·5 (−69·7 to −60·9) | |
| Hungary | 44 400 (33 200–54 400) | 227·1 (169·0–277·1) | −56·0 (−60·4 to −52·5) | 997 (804–1170) | 4·7 (3·8–5·6) | −72·3 (−76·0 to −68·9) | |
| Montenegro | 1710 (1240–2120) | 180·3 (130·4–224·7) | −12·3 (−19·1 to −5·2) | 27·3 (21·6–33·2) | 3·1 (2·5–3·8) | −4·9 (−22·8 to 25·4) | |
| North Macedonia | 4800 (3410–6030) | 161·4 (116·4–203·8) | 14·5 (4·9 to 22·4) | 75·4 (59·5–90·2) | 3·3 (2·5–4·0) | 72·1 (37·6 to 103·2) | |
| Poland | 142 000 (107 000–177 000) | 206·2 (154·6–256·2) | −35·8 (−39·6 to −32·2) | 2900 (2340–3360) | 3·9 (3·1–4·5) | −46·7 (−52·1 to −40·5) | |
| Romania | 68 400 (48 900–87 100) | 193·5 (138·2–246·3) | −34·2 (−38·9 to −30·5) | 1030 (851–1190) | 2·7 (2·3–3·2) | −41·2 (−48·4 to −34·9) | |
| Serbia | 24 100 (17 900–30 200) | 162·2 (121·7–203·6) | −25·5 (−31·0 to −20·0) | 393 (315–473) | 2·9 (2·3–3·5) | −35·5 (−45·7 to −22·4) | |
| Slovakia | 20 900 (15 200–26 400) | 229·9 (165·2–290·0) | −33·3 (−41·0 to −27·3) | 361 (300–444) | 4·0 (3·3–4·9) | −44·7 (−54·7 to −31·3) | |
| Slovenia | 13 800 (10 300–16 700) | 292·4 (215·9–355·5) | −29·4 (−34·1 to −25·3) | 391 (303–453) | 6·9 (5·4–8·0) | −20·2 (−30·8 to −10·8) | |
| Eastern Europe | 646 000 (480 000–812 000) | 195·0 (144·8–244·4) | −23·3 (−26·3 to −20·8) | 9170 (7580–10 300) | 2·7 (2·3–3·1) | −24·3 (−29·4 to −19·4) | |
| Belarus | 31 300 (23 000–39 300) | 202·9 (148·9–254·4) | −9·8 (−14·7 to −4·5) | 448 (374–520) | 2·8 (2·4–3·3) | −8·1 (−17·0 to 3·1) | |
| Estonia | 3860 (2770–4760) | 155·1 (111·2–191·5) | −48·7 (−51·7 to −45·0) | 68·9 (56·2–82·8) | 2·4 (2·0–2·9) | −50·4 (−56·6 to −42·9) | |
| Latvia | 6940 (5120–8430) | 187·3 (137·0–226·8) | −50·4 (−53·7 to −47·3) | 139 (116–165) | 3·3 (2·8–4·0) | −50·9 (−56·2 to −44·3) | |
| Lithuania | 11 500 (8440–14 000) | 208·2 (152·1–254·1) | −33·5 (−37·9 to −30·1) | 225 (184–263) | 3·6 (3·0–4·2) | −26·6 (−34·9 to −18·4) | |
| Moldova | 8250 (6220–10 300) | 145·1 (109·2–181·0) | −46·7 (−50·1 to −43·6) | 128 (104–149) | 2·2 (1·8–2·6) | −50·3 (−56·0 to −45·0) | |
| Russia | 455 000 (339 000–572 000) | 200·4 (149·1–251·3) | −20·2 (−24·0 to −16·9) | 6760 (5680–7660) | 2·9 (2·5–3·4) | −20·6 (−26·6 to −14·0) | |
| Ukraine | 130 000 (95 500–164 000) | 180·5 (133·6–226·9) | −29·4 (−34·8 to −23·9) | 1400 (1090–1720) | 1·9 (1·5–2·4) | −37·4 (−47·9 to −25·3) | |
| High income | 4 260 000 (3 210 000–5 270 000) | 191·6 (143·1–236·7) | −15·7 (−17·8 to −14·1) | 107 000 (86 600–121 000) | 4·0 (3·3–4·5) | −12·8 (−17·6 to −9·9) | |
| Australasia | 126 000 (93 400–158 000) | 239·3 (175·3–301·6) | −3·1 (−5·6 to −0·7) | 3040 (2470–3480) | 5·0 (4·1–5·7) | 23·7 (14·9 to 35·8) | |
| Australia | 106 000 (78 900–133 000) | 238·4 (175·3–300·5) | 0·9 (−2·0 to 4·1) | 2620 (2120–3010) | 5·1 (4·1–5·8) | 30·4 (19·7 to 44·4) | |
| New Zealand | 20 000 (14 500–25 200) | 242·7 (174·4–304·6) | −18·8 (−20·8 to −16·4) | 424 (343–497) | 4·5 (3·7–5·2) | −3·2 (−9·8 to 4·3) | |
| High-income Asia Pacific | 622 000 (454 000–788 000) | 133·2 (96·1–167·4) | −32·7 (−36·0 to −30·7) | 13 100 (10 300–15 300) | 2·2 (1·8–2·5) | −32·3 (−39·8 to −27·3) | |
| Brunei | 632 (477–756) | 209·0 (158·6–246·0) | −30·1 (−36·9 to −23·8) | 9·38 (8·01–10·6) | 4·8 (4·1–5·6) | −26·0 (−38·0 to −8·7) | |
| Japan | 426 000 (312 000–540 000) | 113·8 (81·9–143·7) | −31·9 (−34·1 to −30·7) | 9700 (7530–11 300) | 1·8 (1·5–2·1) | −27·8 (−35·4 to −23·4) | |
| Singapore | 9280 (6440–11 700) | 114·3 (79·7–144·7) | −30·3 (−36·8 to −26·0) | 104 (90–115) | 1·4 (1·2–1·5) | −50·8 (−54·7 to −47·3) | |
| South Korea | 186 000 (137 000–233 000) | 203·9 (149·5–255·1) | −44·7 (−51·4 to −40·4) | 3290 (2600–3890) | 3·8 (3·0–4·5) | −50·3 (−65·2 to −40·1) | |
| High-income North America | 1 410 000 (1 070 000–1 710 000) | 219·8 (167·4–267·5) | 11·1 (7·6 to 14·1) | 35 000 (29 000–39 400) | 5·0 (4·2–5·6) | 50·1 (42·4 to 55·2) | |
| Canada | 152 000 (115 000–187 000) | 204·2 (154·2–252·9) | −0·6 (−3·3 to 3·1) | 4530 (3700–5280) | 5·4 (4·5–6·3) | 18·0 (9·8 to 26·5) | |
| Greenland | 227 (181–278) | 367·4 (295·7–442·5) | −16·7 (−25·8 to −8·5) | 6·11 (4·32–7·61) | 12·0 (8·2–15·1) | −10·2 (−28·8 to 10·8) | |
| USA | 1 250 000 (956 000–1 520 000) | 221·2 (168·7–268·6) | 12·1 (8·4 to 15·6) | 30 500 (25 300–34 200) | 5·0 (4·2–5·5) | 53·3 (45·2 to 58·3) | |
| Southern Latin America | 142 000 (108 000–173 000) | 169·2 (128·4–205·9) | −16·3 (−19·7 to −13·7) | 2710 (2280–2960) | 3·1 (2·6–3·4) | −24·4 (−27·9 to −21·7) | |
| Argentina | 84 200 (64 100–102 000) | 155·6 (118·4–188·9) | −19·7 (−22·7 to −17·1) | 1510 (1280–1660) | 2·7 (2·3–3·0) | −30·9 (−34·8 to −27·8) | |
| Chile | 47 500 (35 800–58 100) | 194·4 (146·4–237·4) | −12·8 (−18·1 to −8·5) | 942 (785–1060) | 3·9 (3·2–4·3) | −19·6 (−24·5 to −13·9) | |
| Uruguay | 10 500 (8090–12 900) | 193·0 (146·9–236·8) | −11·5 (−14·0 to −9·0) | 250 (209–280) | 3·9 (3·3–4·3) | −3·7 (−8·5 to 2·8) | |
| Western Europe | 1 970 000 (1 470 000–2 430 000) | 200·0 (148·2–247·9) | −21·1 (−23·9 to −19·4) | 52 700 (42 300–60 500) | 4·4 (3·5–5·0) | −24·8 (−29·1 to −21·8) | |
| Andorra | 460 (332–577) | 301·6 (218·0–375·7) | 4·4 (−8·8 to 13·4) | 7·64 (5·81–9·75) | 4·5 (3·5–5·8) | −19·7 (−39·2 to 4·8) | |
| Austria | 43 000 (32 400–52 800) | 225·3 (167·4–277·5) | −26·9 (−29·8 to −24·7) | 1140 (930–1310) | 5·0 (4·1–5·7) | −28·8 (−34·0 to −24·3) | |
| Belgium | 68 600 (50 700–84 800) | 279·2 (203·6–346·8) | 1·2 (−1·8 to 4·5) | 1640 (1350–1890) | 5·4 (4·5–6·2) | −2·7 (−8·8 to 4·9) | |
| Cyprus | 4290 (3200–5260) | 233·3 (174·9–285·4) | −45·3 (−52·1 to −39·8) | 97·9 (76·3–120) | 6·6 (4·7–8·0) | −64·1 (−73·4 to −55·6) | |
| Denmark | 21 100 (15 600–25 900) | 176·7 (130·7–216·7) | −43·0 (−46·3 to −40·2) | 540 (431–615) | 4·0 (3·2–4·5) | −55·3 (−58·8 to −52·3) | |
| Finland | 33 900 (24 900–41 900) | 263·8 (191·8–324·8) | −22·3 (−26·4 to −19·2) | 789 (656–913) | 5·1 (4·3–5·9) | −30·0 (−35·1 to −25·0) | |
| France | 371 000 (273 000–463 000) | 242·7 (177·9–303·9) | −25·8 (−30·3 to −22·6) | 10 400 (8100–12 200) | 5·1 (4·0–5·9) | −41·1 (−45·9 to −37·6) | |
| Germany | 427 000 (323 000–523 000) | 206·7 (154·1–253·9) | −15·6 (−18·7 to −13·2) | 12 400 (9910–14 600) | 5·1 (4·1–6·0) | −13·1 (−20·8 to −7·6) | |
| Greece | 36 800 (27 700–45 200) | 156·7 (116·1–192·5) | −30·2 (−32·1 to −28·7) | 909 (757–1020) | 2·9 (2·4–3·2) | −19·1 (−24·7 to −14·7) | |
| Iceland | 1120 (844–1370) | 188·4 (140·1–230·2) | −14·1 (−17·6 to −10·6) | 31·4 (24·7–37·3) | 4·4 (3·5–5·2) | 5·6 (−5·7 to 17·0) | |
| Ireland | 12 400 (8980–15 600) | 162·1 (116·9–203·0) | −24·4 (−28·9 to −21·0) | 217 (176–252) | 2·7 (2·2–3·1) | −45·0 (−49·6 to −40·9) | |
| Israel | 15 900 (11 600–19 700) | 132·3 (96·3–163·3) | −21·9 (−26·3 to −18·9) | 322 (262–371) | 2·4 (1·9–2·7) | −35·4 (−39·8 to −31·5) | |
| Italy | 302 000 (227 000–373 000) | 194·6 (143·7–240·7) | −34·5 (−36·6 to −32·8) | 7960 (6440–9170) | 4·0 (3·2–4·5) | −41·8 (−44·6 to −40·0) | |
| Luxembourg | 2450 (1830–3030) | 224·9 (167·1–277·5) | −21·9 (−25·2 to −18·4) | 63·1 (52·1–71·8) | 5·0 (4·2–5·7) | −17·2 (−24·3 to −9·2) | |
| Malta | 1690 (1230–2110) | 178·6 (128·2–222·0) | −21·5 (−24·7 to −18·6) | 37 (29·8–42·4) | 3·4 (2·8–3·9) | −32·5 (−37·3 to −26·8) | |
| Monaco | 135 (96·1–171) | 141·2 (98·8–175·5) | −8·4 (−14·2 to −2·3) | 2·57 (1·94–3·22) | 2·1 (1·6–2·6) | −14·4 (−30·2 to 17·0) | |
| Netherlands | 87 600 (67 800–106 000) | 236·9 (181·4–288·6) | 24·2 (19·6 to 28·9) | 3170 (2520–3690) | 7·9 (6·3–9·1) | 52·3 (42·0 to 65·1) | |
| Norway | 24 200 (18 300–29 500) | 227·0 (169·8–278·3) | −28·8 (−31·7 to −26·8) | 786 (623–910) | 6·3 (5·1–7·3) | −19·5 (−25·9 to −15·5) | |
| Portugal | 37 800 (28 500–46 400) | 153·1 (114·9–187·6) | −40·7 (−43·3 to −38·0) | 981 (794–1120) | 3·3 (2·7–3·7) | −36·8 (−42·2 to −32·5) | |
| San Marino | 107 (76·2–134) | 160·4 (113·1–201·0) | −10·6 (−17·8 to −3·6) | 2·04 (1·52–2·61) | 2·4 (1·8–3·1) | −14·7 (−31·1 to 8·8) | |
| Spain | 158 000 (114 000–196 000) | 158·1 (113·2–196·4) | −17·3 (−22·8 to −13·3) | 2890 (2350–3340) | 2·3 (1·9–2·6) | −26·8 (−32·0 to −21·7) | |
| Sweden | 44 100 (33 200–54 100) | 191·8 (142·2–237·2) | −17·4 (−19·5 to −15·2) | 1230 (1030–1420) | 4·5 (3·7–5·1) | −8·0 (−13·2 to −3·2) | |
| Switzerland | 48 100 (35 700–60 100) | 247·8 (181·9–308·7) | −32·9 (−35·7 to −30·9) | 1270 (1000–1500) | 5·3 (4·2–6·2) | −41·7 (−47·3 to −37·0) | |
| UK | 224 000 (167 000–278 000) | 169·8 (125·5–211·3) | −1·6 (−3·1 to 0·2) | 5800 (4720–6540) | 3·8 (3·1–4·3) | 25·9 (20·7 to 29·5) | |
| Latin America and Caribbean | 1 070 000 (861 000–1 230 000) | 177·7 (142·6–204·1) | −26·3 (−28·6 to −23·9) | 27 600 (23 100–30 700) | 4·7 (3·9–5·3) | −23·6 (−27·2 to −20·1) | |
| Andean Latin America | 93 300 (75 300–110 000) | 159·2 (128·6–187·8) | −10·8 (−19·4 to −0·7) | 2640 (2170–3170) | 4·7 (3·9–5·6) | −6·0 (−19·9 to 8·6) | |
| Bolivia | 16 300 (12 500–20 400) | 180·3 (139·6–225·7) | −22·2 (−34·4 to −7·0) | 448 (346–577) | 5·6 (4·4–7·2) | −22·7 (−37·8 to −3·3) | |
| Ecuador | 28 700 (22 800–34 200) | 187·1 (148·5–221·8) | −10·6 (−20·3 to 1·1) | 824 (637–1000) | 6·1 (4·7–7·3) | 0·5 (−15·1 to 19·1) | |
| Peru | 48 300 (38 700–57 800) | 142·4 (114·0–170·7) | −6·2 (−17·4 to 9·6) | 1370 (1080–1690) | 4·0 (3·2–5·0) | −0·6 (−19·5 to 22·9) | |
| Caribbean | 93 800 (75 200–109 000) | 176·9 (142·1–206·2) | −4·9 (−11·1 to 0·5) | 3320 (2720–3810) | 6·2 (5·1–7·1) | −5·9 (−13·1 to 0·8) | |
| Antigua and Barbuda | 100 (77–122) | 98·5 (76·8–120·3) | −3·2 (−8·9 to 3·6) | 2·34 (1·98–2·66) | 2·7 (2·3–3·0) | 14·9 (5·1 to 26·9) | |
| The Bahamas | 506 (410–616) | 126·1 (102·5–152·4) | −13·3 (−23·5 to 1·0) | 13·9 (11·5–16·8) | 3·9 (3·2–4·8) | −3·3 (−19·2 to 17·0) | |
| Barbados | 452 (357–551) | 93·5 (73·6–113·8) | −2·0 (−10·6 to 8·5) | 14·5 (11·6–17·7) | 3·0 (2·4–3·6) | 5·8 (−7·6 to 20·5) | |
| Belize | 414 (330–485) | 136·5 (108·8–160·5) | 10·5 (3·1 to 18·1) | 10·0 (8·45–11·5) | 3·7 (3·1–4·3) | 14·1 (1·3 to 24·7) | |
| Bermuda | 115 (88·4–138) | 88·8 (68·6–106·7) | −35·4 (−42·2 to −29·3) | 3·55 (2·99–4·27) | 2·5 (2·0–3·0) | −41·6 (−48·0 to −33·1) | |
| Cuba | 48 200 (39 200–56 100) | 236·9 (192·7–275·0) | 0·3 (−6·3 to 7·8) | 2070 (1710–2400) | 9·5 (7·9–11·0) | 2·6 (−6·9 to 13·5) | |
| Dominica | 98·7 (78·2–117) | 111·2 (88·2–131·7) | −4·0 (−15·7 to 7·2) | 3·13 (2·49–3·81) | 3·5 (2·8–4·2) | 1·6 (−19·9 to 20·7) | |
| Dominican Republic | 13 000 (9770–15 200) | 133·7 (100·8–157·7) | −6·3 (−21·0 to 7·6) | 326 (240–402) | 3·6 (2·7–4·5) | −22·1 (−42·3 to −5·1) | |
| Grenada | 153 (126–180) | 144·1 (118·3–168·8) | 13·4 (5·6 to 20·6) | 4·93 (4·28–5·62) | 5·5 (4·7–6·3) | 39·2 (25·5 to 52·9) | |
| Guyana | 1200 (942–1420) | 196·6 (155·3–229·5) | 1·1 (−10·0 to 16·6) | 35·0 (28·1–42·7) | 7·2 (5·8–8·5) | 5·0 (−12·5 to 24·7) | |
| Haiti | 12 400 (9150–15 900) | 170·2 (127·8–215·2) | −16·8 (−32·6 to 1·4) | 334 (241–428) | 6·0 (4·5–7·7) | −11·5 (−33·4 to 12·0) | |
| Jamaica | 2500 (1910–3070) | 79·9 (61·1–98·4) | 13·8 (4·8 to 24·8) | 69·8 (55·3–84·9) | 2·0 (1·6–2·5) | 37·9 (15·8 to 67·2) | |
| Puerto Rico | 8090 (6170–9690) | 113·1 (86·1–135·8) | −17·2 (−24·4 to −11·6) | 221 (178–254) | 2·6 (2·1–3·0) | −37·2 (−44·6 to −29·1) | |
| Saint Kitts and Nevis | 78·4 (61·5–95·1) | 124·0 (98·9–149·6) | −14·9 (−21·7 to −8·9) | 1·97 (1·64–2·26) | 3·9 (3·3–4·5) | −13·4 (−21·5 to −3·9) | |
| Saint Lucia | 228 (180–272) | 103·3 (81·6–122·9) | −29·2 (−35·9 to −22·0) | 5·92 (4·85–6·89) | 2·9 (2·3–3·3) | −37·7 (−46·5 to −27·8) | |
| Saint Vincent and the Grenadines | 162 (130–191) | 122·8 (99·5–144·4) | 5·4 (−0·7 to 13·3) | 5·09 (4·41–5·73) | 4·4 (3·8–4·9) | 19·3 (10·0 to 31·3) | |
| Suriname | 861 (685–998) | 139·9 (111·0–161·7) | −8·2 (−16·6 to 1·5) | 25·1 (21·1–29·7) | 4·4 (3·6–5·2) | −9·5 (−22·4 to 5·3) | |
| Trinidad and Tobago | 1890 (1490–2270) | 103·0 (81·4–123·7) | −23·6 (−31·3 to −15·1) | 53·7 (42·7–63·9) | 3·0 (2·4–3·6) | −35·1 (−44·3 to −23·6) | |
| Virgin Islands | 211 (171–251) | 125·5 (100·7–150·4) | −11·5 (−21·3 to −0·6) | 5·97 (4·99–7·17) | 3·8 (3·1–4·6) | −25·9 (−38·9 to −11·7) | |
| Central Latin America | 385 000 (298 000–450 000) | 156·7 (121·5–183·1) | −39·9 (−43·1 to −37·1) | 8510 (7390–9550) | 3·6 (3·1–4·0) | −46·4 (−49·9 to −42·4) | |
| Colombia | 66 200 (51 000–78 900) | 120·8 (93·0–144·1) | −40·5 (−44·8 to −36·5) | 1530 (1260–1810) | 2·7 (2·2–3·2) | −44·7 (−51·1 to −38·4) | |
| Costa Rica | 8870 (6870–10 500) | 167·3 (129·9–198·3) | −25·4 (−30·9 to −20·0) | 259 (209–297) | 4·8 (3·9–5·5) | −30·5 (−39·0 to −21·9) | |
| El Salvador | 11 600 (9290–13 600) | 188·1 (151·2–221·5) | −19·8 (−27·4 to −13·3) | 320 (264–376) | 5·0 (4·1–5·7) | −23·2 (−34·3 to −11·4) | |
| Guatemala | 21 000 (16 600–24 700) | 183·1 (145·1–215·1) | −19·2 (−25·2 to −13·5) | 436 (375–493) | 4·4 (3·7–4·9) | −41·4 (−47·9 to −36·3) | |
| Honduras | 11 600 (9190–13 900) | 182·2 (145·3–214·3) | −3·8 (−14·8 to 10·8) | 301 (248–362) | 5·4 (4·6–6·4) | 6·2 (−11·3 to 27·0) | |
| Mexico | 203 000 (158 000–239 000) | 167·7 (130·8–197·5) | −47·0 (−50·1 to −44·5) | 4250 (3530–4830) | 3·8 (3·1–4·3) | −54·8 (−58·1 to −50·6) | |
| Nicaragua | 6310 (4970–7360) | 145·1 (114·3–169·5) | −18·0 (−24·2 to −10·4) | 149 (121–171) | 4·1 (3·4–4·9) | −16·2 (−28·8 to −1·4) | |
| Panama | 4570 (3500–5480) | 105·0 (80·5–126·1) | −38·4 (−43·9 to −33·3) | 96·7 (79·2–111) | 2·2 (1·8–2·5) | −48·4 (−54·4 to −41·5) | |
| Venezuela | 52 000 (39 800–63 700) | 170·2 (130·3–208·1) | −21·2 (−30·2 to −9·6) | 1160 (910–1440) | 4·0 (3·1–4·9) | −26·3 (−39·1 to −9·5) | |
| Tropical Latin America | 503 000 (411 000–582 000) | 202·2 (165·8–234·3) | −19·8 (−22·5 to −17·9) | 13 100 (10 800–14 700) | 5·5 (4·6–6·2) | −6·4 (−12·4 to −2·5) | |
| Brazil | 493 000 (403 000–572 000) | 202·9 (166·2–235·6) | −20·4 (−23·0 to −18·4) | 12 900 (10 600–14 400) | 5·6 (4·6–6·2) | −7·3 (−13·1 to −3·3) | |
| Paraguay | 9810 (7750–11 900) | 169·4 (134·4–205·4) | 15·0 (0·1 to 35·3) | 255 (189–323) | 4·6 (3·4–5·8) | 43·4 (5·5 to 86·3) | |
| North Africa and Middle East | 792 000 (652 000–913 000) | 168·6 (139·1–193·8) | −24·2 (−28·3 to −20·3) | 18 100 (15 800–20 400) | 4·6 (4·1–5·2) | −26·1 (−31·5 to −19·3) | |
| Afghanistan | 39 900 (31 800–50 200) | 266·7 (212·5–327·1) | 3·0 (−14·6 to 33·6) | 1110 (837–1370) | 10·7 (7·5–13·4) | 4·1 (−13·8 to 33·4) | |
| Algeria | 57 600 (46 200–69 800) | 161·7 (129·8–195·0) | −31·1 (−38·8 to −21·3) | 1290 (1060–1580) | 4·4 (3·6–5·3) | −25·2 (−37·7 to −8·1) | |
| Bahrain | 1240 (964–1470) | 102·8 (82·0–121·3) | −36·8 (−44·2 to −30·2) | 20·3 (16·4–23·5) | 3·4 (2·8–4·0) | −40·8 (−50·3 to −31·5) | |
| Egypt | 74 600 (56 200–87 000) | 110·7 (85·1–130·6) | −22·6 (−28·6 to −16·5) | 1270 (1020–1570) | 2·4 (1·9–3·1) | −24·9 (−38·2 to −13·2) | |
| Iran | 131 000 (109 000–152 000) | 165·5 (136·4–192·5) | −42·2 (−45·8 to −38·6) | 3050 (2670–3500) | 4·3 (3·7–5·0) | −41·8 (−46·7 to −36·6) | |
| Iraq | 43 100 (33 600–52 500) | 158·3 (124·5–188·8) | −24·3 (−36·1 to −10·8) | 869 (683–1110) | 3·8 (3·0–4·6) | −16·4 (−36·1 to 6·6) | |
| Jordan | 7650 (6170–9070) | 103·1 (82·8–122·2) | −40·9 (−49·4 to −32·9) | 154 (124–186) | 2·8 (2·2–3·4) | −46·7 (−57·2 to −35·4) | |
| Kuwait | 4050 (3100–4830) | 123·4 (95·9–145·9) | −33·5 (−39·6 to −27·7) | 88·7 (71·7–104) | 3·8 (3·0–4·4) | −23·1 (−32·4 to −12·9) | |
| Lebanon | 5950 (4800–7020) | 113·1 (91·3–133·3) | −45·5 (−51·9 to −37·6) | 174 (146–206) | 3·4 (2·9–4·0) | −57·6 (−66·2 to −39·0) | |
| Libya | 14 600 (11 700–18 100) | 234·8 (185·7–296·9) | 4·3 (−17·3 to 39·4) | 361 (268–494) | 6·6 (4·9–9·4) | 12·2 (−22·0 to 77·4) | |
| Morocco | 55 900 (41 500–68 900) | 173·8 (130·2–213·3) | −22·3 (−32·1 to −9·5) | 1250 (919–1580) | 4·5 (3·3–5·7) | −17·8 (−33·7 to 5·3) | |
| Oman | 5600 (4560–6530) | 269·5 (220·5–312·0) | −47·3 (−57·3 to −34·5) | 123 (99·8–147) | 9·3 (7·5–10·9) | −40·6 (−52·9 to −20·5) | |
| Palestine | 2700 (2150–3170) | 113·9 (92·0–133·2) | −25·0 (−35·6 to −16·2) | 55·7 (47·9–64·4) | 3·2 (2·7–3·6) | −36·3 (−48·2 to −24·7) | |
| Qatar | 2820 (2130–3530) | 193·8 (148·6–237·5) | −37·1 (−49·7 to −22·9) | 51·2 (38·7–66·5) | 6·8 (5·1–8·5) | −50·8 (−62·4 to −36·3) | |
| Saudi Arabia | 99 800 (78 500–120 000) | 385·4 (304·4–459·4) | −13·2 (−26·3 to 2·1) | 1680 (1300–2100) | 7·8 (6·2–9·3) | −23·9 (−40·0 to −1·5) | |
| Sudan | 37 300 (29 400–45 100) | 184·7 (147·3–221·8) | −28·5 (−38·7 to −14·1) | 972 (765–1220) | 5·7 (4·5–7·1) | −29·0 (−42·0 to −8·9) | |
| Syria | 15 400 (11 900–19 200) | 120·2 (94·6–147·7) | −15·0 (−27·8 to 1·1) | 314 (239–396) | 3·2 (2·5–3·8) | −15·2 (−34·7 to 9·0) | |
| Tunisia | 20 300 (16 400–25 800) | 155·4 (126·4–197·7) | −23·3 (−34·9 to −6·1) | 476 (346–638) | 4·0 (2·9–5·4) | −28·6 (−47·0 to −3·9) | |
| Türkiye | 118 000 (95 800–140 000) | 133·4 (108·1–159·0) | −17·9 (−27·4 to −5·5) | 3630 (2860–4440) | 4·4 (3·4–5·4) | −24·3 (−39·3 to −0·1) | |
| United Arab Emirates | 12 300 (9290–15 200) | 184·3 (143·1–224·4) | −41·1 (−52·5 to −27·9) | 159 (122–209) | 5·3 (4·2–6·6) | −47·3 (−59·6 to −30·5) | |
| Yemen | 40 800 (31 300–51 700) | 261·1 (204·3–324·4) | −26·2 (−43·7 to −6·5) | 1010 (762–1320) | 7·8 (6·0–10·0) | −23·5 (−44·3 to 2·2) | |
| South Asia | 4 120 000 (3 510 000–4 620 000) | 312·3 (266·5–350·2) | 1·9 (−6·5 to 9·7) | 140 000 (119 000–157 000) | 12·5 (10·6–14·1) | 6·3 (−8·6 to 19·9) | |
| Bangladesh | 112 000 (90 400–142 000) | 83·9 (67·2–106·6) | −5·8 (−21·3 to 8·0) | 3110 (2280–4330) | 2·7 (2·0–3·8) | −6·0 (−25·2 to 17·8) | |
| Bhutan | 1430 (1060–1830) | 274·2 (202·6–351·1) | −13·2 (−33·1 to 9·9) | 54·6 (35·1–76·2) | 12·1 (7·6–17·0) | −18·1 (−39·3 to 15·3) | |
| India | 3 780 000 (3 220 000–4 260 000) | 354·6 (302·5–399·4) | 1·0 (−7·3 to 9·5) | 129 000 (110 000–146 000) | 14·2 (12·0–16·2) | 5·8 (−9·2 to 19·9) | |
| Nepal | 46 500 (34 700–61 300) | 229·6 (172·0–305·9) | 2·0 (−12·8 to 18·4) | 1330 (959–2080) | 8·6 (6·2–13·1) | 4·7 (−19·3 to 36·3) | |
| Pakistan | 178 000 (142 000–213 000) | 162·3 (127·6–195·2) | −8·9 (−23·6 to 7·5) | 5810 (4500–7130) | 7·1 (5·3–8·8) | −18·5 (−36·5 to 3·3) | |
| Southeast Asia, east Asia, and Oceania | 4 760 000 (3 960 000–5 700 000) | 178·2 (146·8–214·4) | −8·3 (−21·8 to 4·8) | 131 000 (99 600–160 000) | 5·5 (4·1–6·8) | −2·6 (−28·3 to 19·2) | |
| East Asia | 3 650 000 (3 020 000–4 440 000) | 177·2 (146·0–216·4) | −3·2 (−22·8 to 15·4) | 98 000 (71 700–123 000) | 5·3 (3·8–6·7) | 9·6 (−31·5 to 44·3) | |
| China | 3 540 000 (2 920 000–4 320 000) | 178·8 (146·8–219·1) | −2·0 (−22·4 to 17·4) | 94 900 (68 600–120 000) | 5·3 (3·8–6·8) | 11·3 (−31·5 to 48·0) | |
| North Korea | 55 500 (43 800–69 200) | 168·2 (134·3–209·0) | 6·7 (−13·7 to 28·1) | 1590 (1280–2090) | 5·3 (4·3–6·9) | 20·0 (−8·8 to 55·6) | |
| Taiwan (province of China) | 45 900 (36 500–52 500) | 113·3 (90·1–129·4) | −53·3 (−57·5 to −49·5) | 1520 (1210–1730) | 3·6 (2·9–4·1) | −45·6 (−52·5 to −39·3) | |
| Oceania | 13 100 (10 800–15 800) | 187·2 (152·5–225·0) | −0·8 (−13·1 to 13·2) | 291 (223–376) | 5·3 (4·0–7·0) | −9·7 (−27·8 to 16·6) | |
| American Samoa | 54·7 (43·8–62·9) | 120·5 (96·8–137·9) | −8·3 (−19·0 to 3·9) | 1·56 (1·28–1·88) | 4·1 (3·3–5·0) | −5·5 (−25·5 to 20·4) | |
| Cook Islands | 29·4 (23·5–34·6) | 120·6 (96·3–142·1) | −28·8 (−39·0 to −16·9) | 0·778 (0·619–0·966) | 3·3 (2·6–4·1) | −38·1 (−50·3 to −22·0) | |
| Federated States of Micronesia | 114 (88·9–141) | 176·5 (137·2–214·3) | 3·0 (−14·2 to 29·8) | 3·02 (2·29–3·79) | 6·5 (5·0–8·0) | 11·7 (−11·8 to 49·4) | |
| Fiji | 672 (531–804) | 97·9 (78·5–117·1) | −9·9 (−21·3 to 6·0) | 17·9 (13·9–20·8) | 3·5 (2·8–4·2) | −0·9 (−21·6 to 24·7) | |
| Guam | 189 (151–221) | 98·7 (79·0–115·0) | −23·6 (−31·8 to −16·8) | 5·76 (4·79–6·72) | 3·0 (2·5–3·5) | −33·2 (−47·0 to −19·1) | |
| Kiribati | 57·1 (44·4–69·1) | 84·0 (67·4–99·8) | 5·8 (−9·5 to 24·0) | 1·19 (0·91–1·49) | 2·5 (1·9–3·1) | 28·4 (−0·4 to 63·2) | |
| Marshall Islands | 53·9 (40·9–65·7) | 161·7 (125·4–193·2) | 1·9 (−12·4 to 16·6) | 1·33 (1·03–1·67) | 5·9 (4·5–7·2) | 7·1 (−12·5 to 31·2) | |
| Nauru | 10·5 (7·72–13·4) | 208·6 (158·2–260·2) | −17·7 (−31·9 to 2·0) | 0·220 (0·157–0·294) | 6·4 (4·7–8·9) | −36·3 (−50·0 to −14·9) | |
| Niue | 2·69 (2·09–3·35) | 126·0 (97·8–157·5) | −4·9 (−18·7 to 11·2) | 0·0875 (0·0685–0·112) | 4·2 (3·3–5·3) | −1·9 (−27·2 to 28·4) | |
| Northern Mariana Islands | 77·4 (60·2–93·7) | 161·1 (126·6–192·7) | −12·2 (−25·8 to 2·2) | 1·74 (1·46–2·16) | 5·0 (4·0–6·0) | −14·2 (−31·8 to 7·9) | |
| Palau | 44·5 (36·2–53·3) | 242·4 (204·5–282·6) | −6·3 (−19·3 to 8·7) | 1·21 (0·99–1·48) | 9·7 (8·0–12·0) | −0·3 (−21·2 to 25·5) | |
| Papua New Guinea | 9910 (7970–12 200) | 211·9 (170·1–260·1) | −3·8 (−20·1 to 15·1) | 214 (154–287) | 5·8 (4·0–8·2) | −13·5 (−37·9 to 21·8) | |
| Samoa | 211 (165–250) | 146·7 (116·2–172·9) | 4·5 (−10·4 to 23·0) | 6·19 (4·99–7·53) | 4·9 (3·9–6·0) | 4·2 (−20·4 to 31·3) | |
| Solomon Islands | 758 (589–956) | 242·1 (191·5–298·2) | −4·7 (−20·5 to 16·5) | 13·8 (10·3–18·1) | 5·9 (4·3–7·9) | −15·2 (−35·4 to 15·8) | |
| Tokelau | 1·62 (1·25–2·03) | 123·8 (96·7–153·5) | −24·8 (−35·2 to −9·9) | 0·0498 (0·0374–0·0667) | 4·2 (3·2–5·5) | −37·0 (−50·8 to −16·7) | |
| Tonga | 79·9 (63·0–95·5) | 99·8 (79·1–119·3) | −12·0 (−25·1 to 5·1) | 2·64 (2·06–3·34) | 3·4 (2·7–4·3) | −8·6 (−31·4 to 19·7) | |
| Tuvalu | 15·6 (12·8–18·5) | 162·5 (132·7–192·8) | −13·5 (−23·2 to −0·2) | 0·451 (0·343–0·556) | 5·6 (4·1–6·9) | −16·6 (−32·9 to 4·6) | |
| Vanuatu | 252 (195–301) | 145·8 (113·6–174·2) | −2·9 (−19·0 to 17·5) | 6·72 (5·06–8·15) | 5·0 (3·7–6·0) | 1·2 (−19·8 to 30·9) | |
| Southeast Asia | 1 100 000 (922 000–1 250 000) | 183·8 (151·4–208·5) | −21·0 (−26·9 to −15·1) | 32 800 (26 800–37 800) | 6·4 (5·0–7·5) | −21·2 (−31·7 to −11·0) | |
| Cambodia | 31 900 (25 700–38 200) | 288·8 (234·3–343·1) | 11·1 (−4·9 to 27·8) | 1060 (810–1290) | 11·8 (8·8–14·5) | 16·9 (−6·9 to 41·9) | |
| Indonesia | 351 000 (289 000–411 000) | 173·1 (141·3–204·5) | −25·6 (−35·8 to −17·0) | 10 300 (8270–12 200) | 6·5 (4·9–7·8) | −14·6 (−32·1 to 1·4) | |
| Laos | 7130 (5790–8730) | 161·7 (131·6–196·0) | −19·6 (−34·2 to 2·1) | 202 (161–251) | 5·7 (4·6–7·0) | −15·1 (−32·6 to 16·4) | |
| Malaysia | 48 100 (39 400–56 300) | 176·6 (145·2–206·8) | −10·1 (−20·4 to 3·0) | 1370 (1120–1630) | 5·6 (4·6–6·7) | −8·0 (−22·9 to 8·7) | |
| Maldives | 302 (237–365) | 101·1 (79·7–122·4) | −25·5 (−36·5 to −12·0) | 7·35 (6·05–9·21) | 3·0 (2·3–3·7) | −27·0 (−43·0 to 1·8) | |
| Mauritius | 1750 (1410–2040) | 98·4 (79·1–114·2) | −8·3 (−17·4 to 0·3) | 41·8 (34·6–48·3) | 2·4 (2·0–2·8) | −7·0 (−19·0 to 5·2) | |
| Myanmar | 87 000 (72 500–107 000) | 194·8 (160·3–233·0) | −23·3 (−35·0 to −8·6) | 2630 (2170–3230) | 7·0 (5·6–8·5) | −24·5 (−41·1 to −3·5) | |
| Philippines | 99 700 (82 200–116 000) | 126·7 (103·8–146·0) | −4·4 (−14·3 to 4·3) | 2580 (2150–2970) | 4·0 (3·2–4·6) | 7·0 (−12·3 to 26·0) | |
| Seychelles | 129 (103–148) | 109·1 (87·1–125·0) | −15·5 (−23·4 to −0·7) | 3·03 (2·51–3·65) | 2·8 (2·4–3·4) | −18·2 (−30·2 to 8·4) | |
| Sri Lanka | 40 600 (32 400–51 200) | 163·8 (130·5–205·6) | −20·6 (−33·7 to −7·1) | 983 (717–1240) | 4·4 (3·3–5·4) | −42·5 (−58·4 to −25·5) | |
| Thailand | 171 000 (140 000–200 000) | 161·4 (131·7–189·4) | −30·4 (−40·1 to −20·1) | 4240 (3290–5300) | 4·1 (3·1–5·1) | −41·6 (−53·5 to −26·5) | |
| Timor-Leste | 1160 (953–1430) | 148·0 (122·5–181·2) | 3·1 (−16·0 to 27·1) | 34·9 (27·2–44·2) | 5·3 (4·1–6·6) | 9·2 (−18·0 to 43·6) | |
| Viet Nam | 264 000 (210 000–318 000) | 292·0 (225·8–351·8) | −2·1 (−17·7 to 14·6) | 9340 (5950–12 300) | 11·8 (7·0–16·1) | −1·8 (−24·4 to 27·5) | |
| Sub-Saharan Africa | 1 040 000 (907 000–1 160 000) | 224·8 (197·9–250·5) | −9·5 (−18·2 to −1·6) | 35 300 (31 300–39 500) | 9·8 (8·6–10·9) | −2·2 (−12·8 to 8·2) | |
| Central sub-Saharan Africa | 151 000 (125 000–181 000) | 260·1 (215·7–311·0) | −3·0 (−19·4 to 15·9) | 4460 (3460–5440) | 10·1 (7·9–12·8) | 3·2 (−17·4 to 24·1) | |
| Angola | 29 400 (23 200–36 400) | 242·7 (199·2–291·9) | −18·3 (−34·9 to 3·7) | 847 (667–1040) | 9·7 (8·0–11·8) | −12·7 (−30·0 to 10·1) | |
| Central African Republic | 8730 (6780–11 300) | 338·6 (266·3–425·1) | −7·3 (−24·6 to 15·0) | 238 (182–309) | 12·5 (9·8–15·7) | −5·1 (−23·1 to 14·2) | |
| Congo (Brazzaville) | 7210 (5410–9050) | 241·2 (187·7–293·6) | −25·6 (−41·7 to −6·6) | 209 (157–264) | 9·4 (7·1–11·9) | −21·8 (−38·2 to −3·1) | |
| DR Congo | 102 000 (80 300–127 000) | 263·7 (208·9–324·8) | 6·0 (−16·9 to 29·0) | 3050 (2230–3830) | 10·1 (7·5–13·5) | 13·1 (−14·5 to 40·4) | |
| Equatorial Guinea | 1080 (791–1430) | 209·0 (155·0–266·9) | −33·1 (−50·9 to −9·0) | 33·1 (23·3–44·2) | 8·2 (5·9–11·0) | −28·4 (−50·0 to 0·7) | |
| Gabon | 2650 (2080–3280) | 240·1 (191·2–293·7) | −12·5 (−28·2 to 10·9) | 83·4 (64·6–105) | 9·3 (7·2–11·9) | −4·5 (−22·8 to 23·1) | |
| Eastern sub-Saharan Africa | 366 000 (318 000–409 000) | 237·7 (207·1–265·6) | −14·6 (−23·5 to −6·1) | 13 600 (12 000–15 200) | 11·4 (10·0–12·7) | −8·4 (−18·8 to 3·3) | |
| Burundi | 10 900 (8860–13 400) | 250·9 (202·4–305·5) | −22·5 (−39·4 to −1·5) | 379 (296–473) | 11·7 (9·2–14·7) | −20·7 (−39·3 to 1·0) | |
| Comoros | 1170 (931–1410) | 243·4 (193·5–295·5) | −23·5 (−37·7 to −4·6) | 47·8 (36·7–57·6) | 11·3 (8·8–14·0) | −24·6 (−40·1 to −4·8) | |
| Djibouti | 1310 (1030–1680) | 226·4 (182·2–282·8) | 4·2 (−20·1 to 30·1) | 42·8 (33·6–55·7) | 10·7 (8·4–13·7) | 13·1 (−15·2 to 46·3) | |
| Eritrea | 7640 (5890–9580) | 287·8 (225·1–348·2) | 3·2 (−13·0 to 23·0) | 243 (182–302) | 13·0 (10·0–15·5) | 2·9 (−16·0 to 21·3) | |
| Ethiopia | 88 900 (76 200–100 000) | 231·1 (200·0–258·9) | −39·2 (−50·1 to −29·2) | 3590 (3120–3970) | 11·7 (9·9–13·1) | −32·1 (−45·0 to −17·6) | |
| Kenya | 48 700 (41 000–55 900) | 243·3 (208·1–281·1) | 11·6 (−5·4 to 33·2) | 1820 (1540–2160) | 12·1 (10·2–14·2) | 15·8 (−6·8 to 45·2) | |
| Madagascar | 18 800 (15 300–23 200) | 177·6 (144·7–215·0) | −7·7 (−23·8 to 14·2) | 602 (488–752) | 8·0 (6·4–9·8) | −3·5 (−23·8 to 22·4) | |
| Malawi | 17 700 (14 800–20 600) | 257·6 (216·2–298·6) | 9·0 (−9·2 to 26·2) | 685 (577–790) | 12·6 (10·2–14·6) | 18·3 (−3·2 to 40·9) | |
| Mozambique | 31 400 (24 000–40 400) | 294·7 (226·0–375·8) | 16·2 (−6·2 to 44·0) | 1110 (837–1480) | 13·4 (9·9–18·1) | 22·0 (−6·4 to 60·4) | |
| Rwanda | 14 200 (11 400–17 300) | 253·3 (206·6–309·6) | −33·3 (−48·0 to −16·7) | 526 (419–657) | 12·2 (9·5–15·7) | −28·9 (−45·4 to −8·7) | |
| Somalia | 21 700 (16 300–27 700) | 318·3 (246·6–389·3) | 21·9 (−2·5 to 48·2) | 687 (505–862) | 14·3 (11·1–18·0) | 36·9 (7·2 to 64·6) | |
| South Sudan | 9760 (7610–12 300) | 251·6 (198·6–312·5) | 14·1 (−11·8 to 40·7) | 352 (273–442) | 11·7 (9·1–14·8) | 18·5 (−8·1 to 47·4) | |
| Tanzania | 46 900 (37 900–57 100) | 201·0 (163·7–242·6) | −15·3 (−26·0 to 1·2) | 1770 (1440–2180) | 9·5 (7·7–11·8) | −14·2 (−26·9 to 4·5) | |
| Uganda | 30 100 (24 000–36 900) | 224·6 (179·5–274·5) | −3·9 (−25·5 to 20·8) | 1100 (876–1380) | 10·5 (8·3–13·0) | −2·4 (−24·9 to 31·5) | |
| Zambia | 17 000 (13 600–21 000) | 262·0 (212·0–319·0) | −5·6 (−23·7 to 14·0) | 597 (467–732) | 12·4 (9·7–15·1) | −4·3 (−21·3 to 16·0) | |
| Southern sub-Saharan Africa | 113 000 (94 200–125 000) | 177·0 (147·9–197·1) | −18·4 (−24·4 to −10·6) | 2790 (2440–3060) | 4·9 (4·3–5·4) | −8·7 (−19·2 to 6·1) | |
| Botswana | 1900 (1590–2330) | 123·3 (104·1–149·3) | −28·4 (−42·8 to −11·1) | 41·9 (34·8–52·9) | 3·4 (2·8–4·1) | −40·6 (−55·7 to −20·8) | |
| Eswatini | 1710 (1280–2220) | 246·9 (191·0–314·9) | 14·9 (−8·9 to 56·7) | 42·4 (31·6–56·4) | 7·2 (5·6–9·5) | 16·1 (−10·4 to 57·3) | |
| Lesotho | 4360 (3450–5550) | 302·4 (243·1–382·0) | 58·1 (24·0 to 100·0) | 112 (88·3–142) | 8·9 (7·1–11·1) | 58·6 (18·8 to 106·9) | |
| Namibia | 2970 (2250–3820) | 185·9 (142·7–234·4) | −7·3 (−26·3 to 11·8) | 78·9 (59·7–105) | 5·6 (4·4–7·2) | −6·6 (−27·2 to 14·9) | |
| South Africa | 87 300 (74 100–97 900) | 174·4 (147·8–195·2) | −24·4 (−30·3 to −17·5) | 2110 (1830–2310) | 4·6 (4·0–5·1) | −13·7 (−23·5 to 1·4) | |
| Zimbabwe | 14 300 (10 900–17 500) | 191·5 (147·6–231·9) | 19·0 (−1·9 to 42·8) | 407 (310–515) | 6·9 (5·2–8·6) | 35·3 (6·2 to 69·8) | |
| Western sub-Saharan Africa | 406 000 (354 000–459 000) | 223·5 (194·7–249·5) | −4·7 (−14·5 to 4·9) | 14 500 (12 700–16 300) | 10·1 (8·8–11·4) | −0·4 (−10·8 to 12·5) | |
| Benin | 10 800 (8650–13 200) | 223·0 (183·0–268·6) | −11·4 (−24·0 to 3·3) | 377 (309–450) | 9·7 (8·1–11·6) | −12·8 (−25·4 to 5·8) | |
| Burkina Faso | 27 300 (23 300–33 700) | 306·0 (259·7–364·6) | −9·8 (−23·8 to 9·0) | 983 (824–1210) | 14·0 (11·6–17·0) | −11·4 (−24·8 to 10·8) | |
| Cabo Verde | 545 (429–652) | 123·3 (97·9–146·9) | 12·1 (−5·6 to 34·1) | 18·4 (14·7–24·5) | 4·3 (3·4–5·7) | 17·2 (−11·9 to 56·4) | |
| Cameroon | 31 700 (25 000–39 100) | 264·9 (212·7–324·7) | −10·3 (−26·3 to 15·6) | 1070 (857–1350) | 11·4 (9·3–14·4) | −12·0 (−30·0 to 15·9) | |
| Chad | 13 300 (10 900–15 900) | 241·7 (202·5–288·4) | 15·8 (−3·3 to 48·0) | 475 (391–578) | 10·8 (8·9–12·9) | 19·0 (−5·9 to 57·6) | |
| Côte d'Ivoire | 24 400 (19 300–30 100) | 233·3 (189·0–281·8) | −8·2 (−22·2 to 13·8) | 808 (677–1000) | 10·2 (8·6–12·4) | −7·8 (−24·8 to 14·4) | |
| The Gambia | 2340 (1880–2850) | 256·1 (207·6–311·3) | 4·7 (−14·8 to 27·7) | 94·2 (74·6–116) | 12·3 (9·7–15·0) | 6·7 (−15·1 to 33·3) | |
| Ghana | 34 500 (27 300–41 700) | 223·8 (179·2–267·4) | 2·8 (−17·5 to 26·5) | 1210 (940–1490) | 10·2 (7·8–12·5) | 8·6 (−16·2 to 40·4) | |
| Guinea | 11 800 (9700–14 200) | 221·6 (183·7–264·7) | 7·5 (−15·5 to 36·4) | 444 (363–537) | 9·7 (8·2–11·8) | 11·0 (−19·9 to 47·8) | |
| Guinea-Bissau | 1990 (1550–2450) | 270·6 (218·2–327·1) | −7·9 (−26·3 to 12·9) | 61·5 (46·9–74·2) | 11·2 (8·7–13·6) | 1·8 (−18·3 to 24·8) | |
| Liberia | 4310 (3460–5370) | 208·5 (170·5–256·0) | 6·2 (−16·4 to 31·9) | 152 (122–194) | 9·4 (7·6–11·8) | 7·0 (−16·5 to 33·2) | |
| Mali | 20 400 (16 500–25 000) | 252·4 (203·7–306·0) | −8·9 (−23·5 to 7·2) | 756 (595–912) | 11·6 (9·0–13·8) | −0·7 (−20·1 to 20·1) | |
| Mauritania | 4680 (3840–5740) | 224·0 (184·3–272·0) | −23·5 (−36·9 to −2·1) | 169 (134–206) | 9·4 (7·4–11·5) | −17·7 (−32·6 to 8·0) | |
| Niger | 16 200 (12 800–20 000) | 226·4 (177·9–281·7) | −2·9 (−20·7 to 20·4) | 543 (414–713) | 10·0 (7·4–13·4) | −0·5 (−24·3 to 31·8) | |
| Nigeria | 169 000 (143 000–201 000) | 205·1 (175·1–239·7) | −7·0 (−20·9 to 9·9) | 6200 (5190–7180) | 9·5 (7·9–11·0) | −0·7 (−15·9 to 18·2) | |
| São Tomé and Príncipe | 213 (181–256) | 208·0 (176·8–244·9) | 14·1 (0·5 to 31·3) | 6·74 (5·54–8·17) | 8·1 (6·5–10·2) | 18·4 (−1·4 to 38·5) | |
| Senegal | 15 800 (12 900–19 500) | 220·9 (180·9–270·9) | −2·6 (−20·7 to 18·0) | 601 (481–747) | 10·0 (8·0–12·5) | −0·2 (−22·2 to 22·4) | |
| Sierra Leone | 7410 (5920–9330) | 210·2 (171·5–257·3) | 2·9 (−14·7 to 25·4) | 265 (209–321) | 9·2 (7·4–11·0) | 2·6 (−15·5 to 24·0) | |
| Togo | 8630 (6930–10 800) | 229·7 (188·8–278·8) | 4·7 (−14·9 to 34·8) | 266 (205–334) | 9·6 (7·4–11·5) | 7·9 (−16·7 to 42·3) | |
Numbers in parentheses are 95% uncertainty intervals. Rates are provided per 100 000 of the population. Values are rounded to three significant figures (absolute numbers) or one decimal place (rates and percentage changes). DALYs=disability-adjusted life-years.
Figure 2 illustrates the geographical differences in the age-standardised rates of DALYs and deaths attributable to low bone mineral density in 2020. The absolute and age-standardised burden by super-region, region, and country or territory in 2020, and percentage change from 1990 to 2020, are shown in the table. At the region level, for DALYs, south Asia had the highest age-standardised rate in 2020 (312·3 [266·5–350·2] per 100 000 of the population) and central Asia had the lowest rate (123·7 [94·3–148·3] per 100 000). The region with the highest age-standardised mortality in 2020 attributed to low bone mineral density was south Asia (12·5 [10·6–14·1] deaths per 100 000), and the regions with the lowest rate were high-income Asia Pacific (2·2 [1·8–2·5]) per 100 000) and Central Asia (2·2 [1·9–2·5] per 100 000). With respect to YLDs, Australasia had the highest age-standardised rate of YLDs in 2020 (173·8 [121·2–240·6] per 100 000) and southern sub-Saharan Africa had the lowest rate (43·7 [31·7–58·4] per 100 000).
Figure 2.
Map of age-standardised DALY rates (A) and death rates (B) for male and female sexes combined in 2020
Values are rounded to one decimal place. Rates are provided per 100 000 of the population. Intervals start at the lowest estimated rates (Jamaica for DALY rate and Turkmenistan for death rate; table). Areas with several small countries or details are magnified. DALYs=disability-adjusted life-years.
A decomposition analysis by region showed the relative contribution of population growth, population ageing, changes in exposure to low bone mineral density, and changes in risk-deleted injury-related DALY or death rates to the changes in absolute DALYs and deaths attributable to low bone mineral density from 1990 to 2020 (figure 3). Apart from population growth, which was the main driver of increases in DALYs and deaths in central Asia, north Africa and the Middle East, Oceania, and sub-Saharan Africa, population ageing was the main driver of increases in estimates in all other regions that showed an increase in estimates in 2020. In most regions that showed increases in DALYs and deaths, the increases were partially countered by reductions in injury-related DALY and death rates. In high-income North America and Australasia, increased injury-related DALY and deaths rates contributed to increases in absolute DALYs and deaths attributable to low bone mineral density. DALYs and deaths attributable to low bone mineral density showed a slight decrease or remained stable in eastern Europe and central Europe, primarily due to declines in injury-related DALY and death rates.
Figure 3.
Decomposition of change in the number of DALYs (A) and deaths (B) attributable to low bone mineral density from 1990 to 2020 for male and female sexes combined, globally and by region
Note that scales on x-axes differ between plots. DALYs=disability-adjusted life-years. *Injury-related DALY or death rate after removing the effect of low bone mineral density on the rate.
In 2020, falls and road injuries represented the first and second largest contributors, respectively, to the burden from fractures that was attributable to low bone mineral density (figure 4). The proportion of global burden attributable to low bone mineral density resulting from falls in 2020 was 76·2% (95% UI 74·2–78·3) for YLDs, 65·2% (62·9–67·6) for DALYs, and 71·0% (67·4–72·8) for deaths. In comparison, the proportion of global burden attributable to low bone mineral density resulting from road injuries in 2020 was 12·4% (11·1–13·6) for YLDs, 24·6% (22·5–27·1) for DALYs, and 23·1% (21·6–26·2) for deaths. appendix 1 (pp 8–13) presents the proportion of total fall-related burden and road injury-related burden attributable to low bone mineral density in 1990 and 2020, globally and by super-region, region, and country or territory. Globally, as a proportion of all fall-related burden, low bone mineral density accounted for 26·6% (23·2–28·7) of YLDs, 25·6% (22·1–27·4) of DALYs, and 40·6% (35·4–44·0) of deaths in 2020. Of all road injury-related burden, 12·6% (10·8–13·5) of YLDs, 6·3% (5·4–6·9) of DALYs, and 8·9% (7·6–9·6) of deaths were attributable to low bone mineral density. Compared with falls and road injuries, the relative burden from other causes was low and did not vary substantially over time (data not shown).
Figure 4.
DALYs and deaths attributable to low bone mineral density in 2020 by sex, cause of injury, and 5-year age strata
(A) Absolute number by cause of injury. (B) Rate per 100 000 of the population in each age group by cause of injury. Note that scales on y-axes differ between plots. DALYs=disability-adjusted life-years.
Counts of DALYs attributable to low bone mineral density due to falls were highest between age 70 and 84 years for men and women, and counts of fall-related deaths attributable to low bone mineral density were highest between age 80 and 94 years. In men, DALYs and deaths attributable to low bone mineral density due to road injuries were greatest at age 40–49 years and steadily decreased thereafter. In women, road injury-related DALYs were greatest at age 40–59 years and decreased thereafter, whereas road injury-related deaths were greatest at age 65–69 years and 75–79 years (figure 4). In men, road injuries accounted for the largest proportion of DALYs up to age 55–59 years, and deaths until age 60–64 years, after which falls became the primary driver of these outcomes. In women, road injuries were the leading cause of DALYs attributable to low bone mineral density in those aged 40–44 years, with the burden from falls predominating in older age groups. Road injuries were the primary driver of deaths attributable to low bone mineral density in women up to age 50–54 years, after which the burden from falls became the leading cause of attributable deaths.
Discussion
This analysis updates and expands the evidence regarding the global burden attributable to low bone mineral density, an important modifiable risk factor for fractures related to injury. These data show an increase in burden related to low bone mineral density over time, with a nearly two-times increase in DALYs and YLDs and greater than two-times increase in deaths from 1990 to 2020. However, age-standardised rates showed slight decreases over this period, indicating that the numbers will continue to be driven by both population growth and population ageing. To our knowledge, this study highlights for the first time, the part that low bone mineral density plays in the global burden of fractures related to categories of injury other than falls, most notably road injuries.
We found that road injury-related deaths and disabilities constituted a substantial portion of burden associated with low bone mineral density, particularly in men. The data indicated that road injuries in women aged 40–54 years and men aged 40–64 years accounted for the largest proportion of deaths attributable to low bone mineral density, and also accounted for the largest proportion of DALYs attributable to low bone mineral density among women aged 40–44 years and men aged 40–59 years. Taken together, the data underscore the fact that the risk of death and disability attributable to low bone mineral density is not just an isolated problem among older women but also affects younger age groups and men.
South Asia was the region with the greatest burden attributable to low bone mineral density, with high overall rates of morbidity (DALYs) and mortality attributable to low bone mineral density (table). Although age-standardised rates of DALYs and deaths showed little change from 1990 to 2020 in this region, the rising absolute numbers of DALYs and deaths from fractures (figure 3) mean increasing costs to individuals and health systems.44, 45, 46, 47, 48 The Asian Federation of Osteoporosis Societies has projected that direct medical costs for hip fractures alone will escalate from US$9·5 billion in 2018 to $15 billion by 2050.49 Furthermore, infrastructure and capacity to adequately screen, diagnose, and manage low bone mineral density remain underdeveloped in many parts of Asia, with less than one DXA machine per million of the population in several countries or territories, and substantial gaps in health professional training and practice patterns.50 To meet this growing burden, strong collaborative efforts by regional osteoporosis societies have spurred the generation of locally relevant evidence and guidelines, multidisciplinary health professional education and capacity building programmes, including secondary prevention fracture-liaison programmes, and public awareness and advocacy initiatives.48
Sub-Saharan Africa also had increases in absolute DALYs and deaths attributable to low bone mineral density in the context of substantial population growth, including growth in the absolute number of older individuals in some regions. There is a notable lack of access to diagnostics, care, and treatments for osteoporosis across sub-Saharan Africa, and low prioritisation by health-care systems compared with communicable diseases or other non-communicable disease priorities.51, 52 Importantly, the WHO Essential Medicines List does not include any oral formulations of bisphosphonates,53 which are generally considered first-line agents for osteoporosis drug therapy, meaning in many low-income and middle-income countries (LMICs), including those in sub-Saharan Africa, availability might be limited. Intravenous zoledronic acid is on the Essential Medicines List, for the dosage recommended for adjuvant cancer treatment, but not for the formulation recommended for osteoporosis treatment.53 These gaps present an opportunity for advocacy and awareness. In sub-Saharan Africa, where long-standing priorities such as HIV, tuberculosis, and malnutrition continue to dominate the health agenda and international funding, health systems have difficulty managing the concurrent rise of non-communicable diseases and their risk factors.54 In this setting, there remains a paucity of high-quality regional epidemiological and health services data related to osteoporosis to inform evidence-based interventions.52
Although bone mineral density is a well established risk factor for fractures of all types, studies have consistently shown that the proportion of fractures attributable to osteoporosis alone, as defined by bone mineral density, is modest.55 Therefore, fracture prediction tools typically incorporate other clinical risk factors with or without bone mineral density to improve fracture prediction.56, 57 However, unlike risk factors such as age, sex, and family history of fracture, bone mineral density is potentially modifiable through a range of non-pharmacological primary prevention and lifestyle modification approaches (eg, dietary calcium, vitamin D and protein intake, sunlight exposure, weight-bearing physical activity, optimisation of underlying comorbidities, and smoking and alcohol cessation) and pharmacological interventions.58, 59 Furthermore, bone mineral density can be measured by standard techniques that are objective, reproducible, non-invasive, and fast.13 Evidence supports a correlation between change in bone mineral density with osteoporosis treatment and fracture risk reduction, albeit recognising that the full benefit derived from osteoporosis drug therapy goes beyond reductions in bone mineral density alone.60
Despite data supporting the screening, diagnosis, prevention, and management of osteoporosis, notable gaps exist between evidence-based guidelines and clinical practice, even in high-income regions where DXA imaging, osteoporosis treatments, and trained health professionals are available.7, 61 These gaps are compounded in low-income and middle-income regions, where fundamental barriers to accessing such resources exist.62 The critical role of policy and public health messaging in promoting best practices can be seen through key examples around the world. Crisp and colleagues reported a 20% and 13% decrease in age-standardised hip fracture incidence rates among men and women, respectively, in Australia between 1997–98 and 2006–07, a period during which there was active roll-out of public health initiatives focused on osteoporosis.63 Screening and treatment for low bone mineral density is reimbursed by the Australian Government for all men and women aged 50 years and older who have sustained a fracture, and for all individuals aged 70 years and older whether they’ve sustained a fracture or not. By contrast, in the USA, Hayes and colleagues described associations between cuts in Medicare reimbursements for DXA and decreased provision of physician's office-based DXA services and prescriptions for US Food and Drug Administration-approved osteoporosis therapies 2 years later.64 Age-adjusted hip fracture rates also plateaued in the USA from 2012 to 2015, following a decade of steady decreases, in the setting of decreased DXA testing and osteoporosis diagnosis, coupled with a reduction in bisphosphonate prescriptions due to fear of rare side-effects and misperceptions regarding the risk and benefits of treatment.65
The role of secondary prevention in osteoporosis also cannot be understated. Studies have shown that women aged 50 years and older with a history of fracture have as high as a four-times increase in the relative risk of future fractures compared to those without previous fractures.66 Nevertheless, rates of initiation of osteoporosis treatment following a fracture are poor across regions and practice settings.67 Fracture liaison services are coordinated multidisciplinary programmes aimed at identifying patients in the peri-hospitalisation period following a sentinel fracture, and linking patients to osteoporosis care.68, 69 Fracture liaison services have been shown to be effective at reducing both fracture rates and health-care costs compared with usual care or no care, and have been widely promoted by osteoporosis societies worldwide as the single most important step by health systems to prevent fracture-associated burden.67, 70
The promotion of strategies to prevent falls and road traffic injuries is additionally important. Falls prevention strategies include individual-level or practice or hospital-level interventions that might comprise multifactorial components such as falls risk screening, education, exercise, home modifications, medication changes, referral to other health-care services, and recommended use of assistive devices or aids.71, 72 The effectiveness of road traffic injuries prevention strategies across the domains of legislation (eg, seat belt, helmet, and cell phone usage laws and increased penalties), enforcement (eg, specific groups and individuals subject to enforcement and technology for enforcement), public awareness and education (eg, mass media campaigns against drunk driving), speed control (eg, speed bumps and other road designs to reduce speed), and road improvement (eg, repaving damaged roads) have been shown in high-income countries.73 Data from LMICs are comparatively limited. However, given rapid urbanisation and motorisation in these settings, more research and advocacy are needed to guide and strengthen road safety enforcement policies, speed control efforts, and public education campaigns.74, 75
Limitations associated with the comparative risk assessment methodology of the present analyses need to be acknowledged. In these analyses, uncertainty was estimated based on 100 draws where 1000 draws would have been preferable. The TMREL was based on US cohorts, which could lead to overestimation or underestimation of risk factor attribution in some world regions. For example, regions with lower average BMI compared with the USA might have lower age-specific and gender-specific bone mineral density, leading to higher attribution of fractures to low bone mineral density. Furthermore, the choice of a stringent TMREL (99th percentile) could have led to an overall overestimation of the burden of low bone mineral density.
The methodology to account for fracture-related deaths might also be susceptible to error in the estimation of true mortality attributable to low bone mineral density. We used hospital and emergency department data from 35 countries with double coding (ie, ICD codes for cause and nature of injury) to derive the proportion of in-hospital deaths attributable to the fracture event if a more severe life-threatening injury wasn’t listed, an approach subject to variations in coding practices between hospitals and countries. In addition, the excess risk of mortality remains elevated beyond the initial evaluation or hospitalisation period for osteoporotic fractures, not just for hip fractures, but for other types of fragility fractures as well (vertebral, pelvis, distal femur, proximal tibia, proximal humerus, and multiple ribs) and might not be assigned to the fracture as the underlying cause.3, 76, 77
Furthermore, the 12 studies used in the meta-analysis from which we derived the relative risks for hip and non-hip fractures were largely based in high-income countries.25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36 These studies represented diverse regions and showed some variability; however, the relationship between bone mineral density and fracture risk remains to be explored across all populations. More high-quality epidemiological data across racially, ethnically, and socioeconomically diverse populations is needed to better inform future analyses. In addition, variations in modifiable risk factors for low bone mineral density, as well as variations in attributable risk of low bone mineral density related to the social disadvantage index and access to diagnosis and treatment, were beyond the scope of this paper but are important to consider for the future.
In summary, low bone mineral density is a key, modifiable risk factor for fractures related to injury. The present analysis highlights the contribution of low bone mineral density to DALYs and deaths resulting not only from falls in older adults, but also from fractures sustained in road injuries, particularly among middle-aged men. Although age-standardised rates of DALYs and deaths attributable to low bone mineral density decreased in many countries from 1990 to 2020, the increase in absolute numbers due to a growing and ageing global population places a substantial burden on health-care systems. LMICs are less equipped than high-income countries to handle this increasing demand and will thus face greater challenges. We advocate for the addition of oral bisphosphonates to the WHO Essential Medicines List, and for expansion of the eligibility for intravenous bisphosphonates on the Essential Medicines List to include management of low bone mineral density and individuals with high fracture risk aged 50 years and older. We also advocate for support for implementation strategies to improve the uptake of evidence-based injury and fracture prevention approaches, and recommend lifestyle strategies to improve bone health across the life-course.
GBD 2021 Low Bone Mineral Density Collaborators
Affiliations
Contributors
Data sharing
The findings of this study are supported by data available in public online repositories, data publicly available upon request of the data provider, and data not publicly available due to restrictions by the data provider. To download citations and metadata for the input data used in these analyses, please visit the Global Health Data Exchange GBD 2021 website (https://ghdx.healthdata.org/gbd-2021/sources). The data sources used in this analysis are listed in appendix 1 (pp 14–21).
Editorial note: The Lancet Group takes a neutral position with respect to territorial claims in published maps, tables, and institutional affiliations.
Declaration of interests
S Bhaskar reports grants or contracts from the Japan Society for the Promotion of Science (JSPS), Japanese Ministry of Education, Culture, Sports, Science and Technology (for a Grant-in-Aid for Scientific Research, grant ID: 23KF0126) and from JSPS and the Australian Academy of Science for a JSPS International Fellowship (grant ID: P23712); and leadership or fiduciary roles in board, society, committee, or advocacy groups, paid or unpaid, with Rotary District 9675, Sydney, Australia, as the District Chair (Diversity, Equity & Inclusion), with the Global Health & Migration Hub Community, Global Health Hub Germany, Berlin, Germany (Chair, Founding Member and Manager), with PLOS One, BMC Neurology, Frontiers in Neurology, Frontiers in Stroke, Frontiers in Public Health, Journal of Aging Research, Neurology International, Diagnostics, and BMC Medical Research Methodology (Editorial Board Member), with the College of Reviewers, Canadian Institutes of Health Research, Government of Canada (Member), with the World Headache Society, Bengaluru, India (Director of Research), with the Cariplo Foundation, Milan, Italy (Expert Adviser/Reviewer), with the National Cerebral and Cardiovascular Center, Department of Neurology, Division of Cerebrovascular Medicine and Neurology, Suita, Osaka, Japan (Visiting Director), with Cardiff University Biobank, Cardiff, UK (Member, Scientific Review Committee), and with the Rotary Reconciliation Action Plan (Chair); all outside the submitted work. N E Ismail reports unpaid leadership or fiduciary roles in board, society, committee, or advocacy groups with the Malaysian Academy of Pharmacy (Bursar and Council Member) and the Malaysian Pharmacists Society (Committee Member of the Education Chapter), outside the submitted work. K Krishan reports non-financial support from the University Grants Commission Centre of Advanced Study—Phase II, awarded to the Department of Anthropology, Panjab University, Chandigarh, India, outside the submitted work. M Lee reports support for the present manuscript from the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2023S1A3A2A05095298). L M March reports grants or contracts paid to their institution from the Australian National Health and Medical Research Council and the Australian Medical Research Future Fund; royalties from UpToDate for co-authorship of a review titled Epidemiology and Risk Factors for Osteoarthritis; and unpaid leadership or fiduciary roles in board, society, committee, or advocacy groups with the Global Alliance for Musculoskeletal Health as Executive; all outside the submitted work. L Monasta reports support for the present manuscript from the Italian Ministry of Health (Ricerca Corrente 34/2017) via payments made to the Institute for Maternal and Child Health IRCCS Burlo Garofolo. D Prieto-Alhambra reports support paid to their institution from the European Medicines Agency and the Innovative Medicines Initiative; grants or contracts from Amgen, Chiesi-Taylor, Gilead, Lilly, Janssen, Novartis, and UCB; consulting fees paid to their institution from UCB Biopharma; other support from Janssen for training programme's organised by the author's affiliated department; and a position on the Board of the European Health Data & Evidence Network Foundation; all outside the submitted work. Y L Samodra and J H V Ticoalu report leadership or fiduciary roles in board, society, committee, or advocacy groups, paid or unpaid, with Benang Merah Research Center, Indonesia, as Co-founders, outside the submitted work. L M L R Silva reports research contracts with the Sport Physical Activity and Health Research & Innovation Center–Instituto Politécnico da Guarda, Portugal, and RISE-Health, Universidade da Beira Interior, Portugal, outside the submitted work. J A Singh reports consulting fees from ROMTech, Atheneum, Clearview Healthcare Partners, the American College of Rheumatology, Yale University, Hulio, Horizon Pharmaceuticals, DINORA, ANI/Exeltis USA, Frictionless Solutions, Schipher, Crealta/Horizon, Medisys, Fidia, PK Med, Two Labs, Adept Field Solutions, Clinical Care Options, Putnam Associates, Focus Forward, Navigant Consulting, Spherix, MedIQ, Jupiter Life Science, UBM, Trio Health, Medscape, WebMD, Practice Point Communications, and the National Institutes of Health; payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events as a member of the speaker's bureau of Simply Speaking; leadership or fiduciary roles in other board, society, committee, or advocacy groups, paid or unpaid, and support for attending meetings or travel, as a past steering committee member of OMERACT; participation on a data safety monitoring board or advisory board from the US Food and Drug Administration Arthritis Advisory Committee; stock or stock options in Atai Life Sciences, Kintara Therapeutics, Intelligent Biosolutions, Acumen Pharmaceutical, TPT Global Tech, Vaxart Pharmaceuticals, Atyu Biopharma, Adaptimmune Therapeutics, GeoVax Labs, Pieris Pharmaceuticals, Enzolytics, Seres Therapeutics, Tonix Pharmaceuticals, Aebona Pharmaceuticals, and Charlotte's Web Holdings; and previous stock options in Amarin, Viking, and Moderna; all outside the submitted work. M Zielińska reports other financial or non-financial interests from Alexion, AstraZeneca Rare Disease as an employee outside the submitted work. All other authors declare no competing interests.
Acknowledgments
Evelyn Hsieh, Dana Bryazka, Kanyin Liane Ong, Phoebe-Anne Rhinehart, Ewerton Cousin, Hailey Hagins, Cyrus Cooper, Marita Cross, Garland T Culbreth, Karsten E Dreinhoefer, Philippe Halbout, Jacek A Kopec, Sneha Ingle Nicholson, Daniel Prieto-Alhambra, Anthony D Woolf, Theo Vos, Yohannes Habtegiorgis Abate, Sherief Abd-Elsalam, Meriem Abdoun, Mohamed Abouzid, Eman Abu-Gharbieh, Salahdein Aburuz, Abiola Victor Adepoju, Qorinah Estiningtyas Sakilah Adnani, Aqeel Ahmad, Haroon Ahmed, Luai A Ahmed, Syed Mahfuz Al Hasan, Tariq A Alalwan, Rasmieh Mustafa Al-Amer, Hediyeh Alemi, Abid Ali, Yaser Mohammed Al-Worafi, Reza Amani, Abhishek Anil, Jalal Arabloo, Aleksandr Y Aravkin, Demelash Areda, Brhane Berhe Aregawi, Mohammad Asghari-Jafarabadi, Seyyed Shamsadin Athari, Sina Azadnajafabad, Ahmed Y Azzam, Ashish D Badiye, Nasser Bagheri, Sara Bagherieh, Saliu A Balogun, Maciej Banach, Shirin Barati, Pankaj Bhardwaj, Sonu Bhaskar, Gurjit Kaur Bhatti, Yasser Bustanji, Daniela Calina, Vijay Kumar Chattu, Endeshaw Chekol Abebe, Dinh-Toi Chu, Michael H Criqui, Natalia Cruz-Martins, Omid Dadras, Xiaochen Dai, Zhaoli Dai, Reza Darvishi Cheshmeh Soltani, Mohsen Dashti, Tadesse Asmamaw Dejenie, Cristian Del Bo’, Edgar Denova-Gutiérrez, Vinoth Gnana Chellaiyan Devanbu, Syed Masudur Rahman Dewan, Vishal R Dhulipala, Michael Ekholuenetale, Mohamed A Elmonem, Farshid Etaee, Adeniyi Francis Fagbamigbe, Ildar Ravisovich Fakhradiyev, Ali Fatehizadeh, Alireza Feizkhah, Ginenus Fekadu, Bikila Regassa Feyisa, Florian Fischer, Abduzhappar Gaipov, Lucia Galluzzo, Mesfin Gebrehiwot, Fataneh Ghadirian, Tiffany K Gill, Kimiya Gohari, Ali Golchin, Bhawna Gupta, Sapna Gupta, Najah R Hadi, Arvin Haj-Mirzaian, Asif Hanif, Netanja I Harlianto, Ikramul Hasan, Md Saquib Hasnain, Amr Hassan, Simon I Hay, Jiawei He, Golnaz Heidari, Kamal Hezam, Yuta Hiraike, Praveen Hoogar, Chengxi Hu, Segun Emmanuel Ibitoye, Arad Iranmehr, Nahlah Elkudssiah Ismail, Masao Iwagami, Ali Jafari-Khounigh, Mihajlo Jakovljevic, Elham Jamshidi, Sathish Kumar Jayapal, Shubha Jayaram, Digisie Mequanint Jemere, Gwang Hun Jeong, Nitin Joseph, Charity Ehimwenma Joshua, Mikk Jürisson, Vidya Kadashetti, Sanjay Kalra, Morteza Abdullatif Khafaie, Himanshu Khajuria, Moien AB Khan, Javad Khanali, Shaghayegh Khanmohammadi, Moawiah Mohammad Khatatbeh, Sorour Khateri, Min Seo Kim, Oleksii Korzh, Kewal Krishan, Mukhtar Kulimbet, Vishnutheertha Kulkarni, Maria Dyah Kurniasari, Chandrakant Lahariya, Tri Laksono, Iván Landires, Kamaluddin Latief, Thao Thi Thu Le, Munjae Lee, Wei-Chen Lee, Erand Llanaj, Kashish Malhotra, Ahmad Azam Malik, Miquel Martorell, Andrea Maugeri, Hadush Negash Meles, Mohsen Merati, Tuomo J Meretoja, Tomislav Mestrovic, Alireza Mirahmadi, Nouh Saad Mohamed, Abdollah Mohammadian-Hafshejani, Ali H Mokdad, Lorenzo Monasta, Yousef Moradi, Negar Morovatdar, Shane Douglas Morrison, Ebrahim Mostafavi, Parsa Mousavi, Sumaira Mubarik, Christopher J L Murray, Sathish Muthu, Mohsen Naghavi, Pirouz Naghavi, Zuhair S Natto, Biswa Prakash Nayak, Mohammad Hadi Nematollahi, Duc Hoang Nguyen, Hien Quang Nguyen, Van Thanh Nguyen, Robina Khan Niazi, Efaq Ali Noman, Dieta Nurrika, Osaretin Christabel Okonji, Michal Ordak, Wael M S Osman, Yasamin Ostadi, Alicia Padron-Monedero, Shahina Pardhan, Pragyan Paramita Parija, Romil R Parikh, Jay Patel, Fanny Emily Petermann-Rocha, Hoang Tran Pham, Elton Junio Sady Prates, Ibrahim Qattea, Mehran Rahimi, Vafa Rahimi-Movaghar, Mosiur Rahman, Masoud Rahmati, Ivano Raimondo, Shakthi Kumaran Ramasamy, Sina Rashedi, Mohammad-Mahdi Rashidi, Salman Rawaf, Elrashdy M Redwan, Nazila Rezaei, Aly M A Saad, Umar Saeed, Amene Saghazadeh, Fatemeh Saheb Sharif-Askari, Amirhossein Sahebkar, Morteza Saki, Joseph W Sakshaug, Mohamed A Saleh, Yoseph Leonardo Samodra, Abdallah M Samy, Francesco Sanmarchi, Muhammad Arif Nadeem Saqib, Art Schuermans, Yashendra Sethi, Allen Seylani, Moyad Jamal Shahwan, Sunder Sham, Mohammed Shannawaz, Sadaf Sharfaei, Manoj Sharma, Seyed Afshin Shorofi, Emmanuel Edwar Siddig, Luís Manuel Lopes Rodrigues Silva, Jasvinder A Singh, Paramdeep Singh, Hamidreza Soleimani, Chandan Kumar Swain, Shima Tabatabai, Jacques Lukenze Tamuzi, Razieh Tavakoli Oliaee, Seyed Mohammad Tavangar, Masayuki Teramoto, Dufera Rikitu Terefa, Jansje Henny Vera Ticoalu, Asokan Govindaraj Vaithinathan, Tommi Juhani Vasankari, Siavash Vaziri, Fang Wang, Shu Wang, Juan Xia, Naohiro Yonemoto, Chuanhua Yu, Mazyar Zahir, Hanqing Zhao, Magdalena Zielińska, Osama A Zitoun, Lyn M March*, and Lidia Sanchez-Riera*. *Co-senior authors.
Section of Rheumatology, Allergy and Immunology (E Hsieh MD), Department of Internal Medicine (F Etaee MD), Yale School of Medicine, New Haven, CT, USA; Section of Rheumatology (E Hsieh MD), Department of Internal Medicine, VA Connecticut Healthcare System, West Haven, CT, USA; Institute for Health Metrics and Evaluation (D Bryazka MS, K L Ong PhD, P Rhinehart BA, E Cousin PhD, H Hagins MSPH, G T Culbreth PhD, S I Nicholson MSc, Prof T Vos PhD, A Y Aravkin PhD, X Dai PhD, Prof S I Hay FMedSci, J He MSc, T Mestrovic PhD, Prof A H Mokdad PhD, Prof C J L Murray DPhil, Prof M Naghavi PhD), Department of Health Metrics Sciences, School of Medicine (E Cousin PhD, Prof T Vos PhD, A Y Aravkin PhD, X Dai PhD, Prof S I Hay FMedSci, Prof A H Mokdad PhD, Prof C J L Murray DPhil, Prof M Naghavi PhD), Department of Applied Mathematics (A Y Aravkin PhD), University of Washington, Seattle, WA, USA; MRC Lifecourse Epidemiology Unit (Prof C Cooper MD), University of Southampton, Southampton, UK; Institute of Musculoskeletal Sciences (Prof C Cooper MD), University of Oxford, Oxford, UK; Faculty of Medicine and Health (M Cross PhD, Prof L M March PhD), School of Pharmacy and Charles Perkins Centre (Z Dai PhD), School of Chemical and Biomolecular Engineering (E A Noman PhD), Institute of Bone and Joint Research (L Sanchez-Riera PhD), University of Sydney, Sydney, NSW, Australia; Global Alliance for Musculoskeletal Health, Sydney, NSW, Australia (M Cross PhD, Prof K E Dreinhoefer MD); Center of Musculoskeletal Surgery (Prof K E Dreinhoefer MD), Charité Universitätsmedizin Berlin (Charité University Medical Center Berlin), Berlin, Germany; IOF International Osteoporosis Foundation, Nyon, Switzerland (P Halbout PhD); School of Population and Public Health (J A Kopec PhD), University of British Columbia, Vancouver, BC, Canada; Arthritis Research Canada, Richmond, BC, Canada (J A Kopec PhD); Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences (Prof D Prieto-Alhambra PhD), Oxford University, Oxford, UK; Department of Medical Informatics (Prof D Prieto-Alhambra PhD), Erasmus University Medical Center, Rotterdam, Netherlands; Osteoporosis Research Group (Prof A D Woolf FRCP), Lund University, Malmo, Sweden; Global Alliance for Musculoskeletal Health, Truro, UK (Prof A D Woolf FRCP); Department of Clinical Governance and Quality Improvement (Y H Abate MSc), Aleta Wondo General Hospital, Aleta Wondo, Ethiopia; Department of Tropical Medicine and Infectious Diseases (S Abd-Elsalam PhD), Tanta University, Tanta, Egypt; Department of Medicine (Prof M Abdoun PhD), University of Setif Algeria, Sétif, Algeria; Department of Health, Sétif, Algeria (Prof M Abdoun PhD); Department of Physical Pharmacy and Pharmacokinetics (M Abouzid PharmD), Poznan University of Medical Sciences, Poznan, Poland; Department of Clinical Sciences (Prof E Abu-Gharbieh PhD), Department of Basic Biomedical Sciences (Prof Y Bustanji PhD), Sharjah Institute of Medical Sciences (F Saheb Sharif-Askari PhD), College of Medicine (Prof M A Saleh PhD), University of Sharjah, Sharjah, United Arab Emirates; Department of Biopharmaceutics and Clinical Pharmacy (Prof E Abu-Gharbieh PhD), College of Pharmacy (Prof S Aburuz PhD), University of Jordan, Amman, Jordan; Department of Pharmacology and Therapeutics (Prof S Aburuz PhD), Institute of Public Health (Prof L A Ahmed PhD), Family Medicine Department (M A Khan MSc), United Arab Emirates University, Al Ain, United Arab Emirates; Department of HIV and Infectious Diseases (A V Adepoju MD), Jhpiego, Abuja, Nigeria; Department of Adolescent Research and Care (A V Adepoju MD), Adolescent Friendly Research Initiative and Care, Ado Ekiti, Nigeria; Department of Public Health (Q E S Adnani PhD), Universitas Padjadjaran (Padjadjaran University), Bandung, Indonesia; College of Medicine (A Ahmad PhD), Shaqra University, Shaqra, Saudi Arabia; Department of Biosciences (H Ahmed PhD), COMSATS Institute of Information Technology, Islamabad, Pakistan; Division of Public Health Sciences, Department of Surgery (S M Al Hasan PhD), Department of Surgery (S Azadnajafabad MD), Washington University in St. Louis, St. Louis, MO, USA; Department of Biology (T A Alalwan PhD), College of Health and Sport Sciences (A G Vaithinathan MSc), University of Bahrain, Zallaq, Bahrain; School of Nursing (R M Al-Amer PhD), Department of Basic Medical Sciences (Prof M M Khatatbeh PhD), Yarmouk University, Irbid, Jordan; School of Nursing and Midwifery (R M Al-Amer PhD), Western Sydney University, Sydney, NSW, Australia; Hematology, Oncology and Stem Cell Transplantation Research Center (H Alemi MD), Iranian Research Center for HIV/AIDS (O Dadras PhD), Department of Neurosurgery (A Iranmehr MD), Non-Communicable Diseases Research Center (J Khanali MD, P Mousavi MD, M Rashidi MD, N Rezaei MD), School of Medicine (S Khanmohammadi MD, M Merati MD), Sina Trauma and Surgery Research Center (Prof V Rahimi-Movaghar MD), Research Center for Immunodeficiencies (A Saghazadeh MD), Department of Pathology (Prof S Tavangar MD), Tehran University of Medical Sciences, Tehran, Iran; Department of Zoology (A Ali PhD), Abdul Wali Khan University Mardan, Mardan, Pakistan; Department of Medical Sciences (Prof Y M Al-Worafi PhD), Azal University for Human Development, Sana’a, Yemen; Department of Clinical Sciences (Prof Y M Al-Worafi PhD), University of Science and Technology of Fujairah, Fujairah, United Arab Emirates; Interdisciplinary Graduate Program in Human Toxicology (R Amani DVM), University of Iowa, Iowa City, IA, USA; Holden Comprehensive Cancer Center (R Amani DVM), University of Iowa Hospitals and Clinics, Iowa City, IA, USA; Department of Pharmacology (A Anil MD), Department of Community Medicine and Family Medicine (Prof P Bhardwaj MD), School of Public Health (Prof P Bhardwaj MD), All India Institute of Medical Sciences, Jodhpur, India; All India Institute of Medical Sciences, Bhubaneswar, India (A Anil MD); Health Management and Economics Research Center (J Arabloo PhD), Iran University of Medical Sciences, Tehran, Iran; College of Art and Science (D Areda PhD), Ottawa University, Surprise, AZ, USA; School of Life Sciences (D Areda PhD), Arizona State University, Tempe, AZ, USA; College of Medicine and Health Sciences (B B Aregawi PhD), Department of Medical Laboratory Sciences (H N Meles MSc), Adigrat University, Adigrat, Ethiopia; Cabrini Research (Prof M Asghari-Jafarabadi PhD), Cabrini Health, Malvern, VIC, Australia; School of Public Health and Preventive Medicine (Prof M Asghari-Jafarabadi PhD), Monash University, Melbourne, VIC, Australia; Department of Immunology (S S Athari PhD), Zanjan University of Medical Sciences, Zanjan, Iran; Leeds Institute of Rheumatic and Musculoskeletal Medicine (S Azadnajafabad MD), School of Dentistry (J Patel BSc), University of Leeds, Leeds, UK; ASIDE Healthcare, Lewes, DE, USA (A Azzam MD); Faculty of Medicine (A Azzam MD), October 6 University, 6th of October City, Egypt; Department of Forensic Science (A D Badiye PhD), Government Institute of Forensic Science Nagpur, Nagpur, India; Rashtrasant Tukadoji Maharaj Nagpur University, Nagpur, India (A D Badiye PhD); Health Research Institute (Prof N Bagheri PhD), University of Canberra, Canberra, ACT, Australia; School of Medicine (S Bagherieh BSc), Isfahan University of Medical Sciences, Isfahan, Iran; Goldfields University Department of Rural Health (S A Balogun PhD), Curtin University, Kalgoorlie, WA, Australia; Department of Hypertension (Prof M Banach PhD), Medical University of Lodz, Lodz, Poland; Polish Mothers’ Memorial Hospital Research Institute, Lodz, Poland (Prof M Banach PhD); Department of Anatomy (S Barati PhD), Saveh University of Medical Sciences, Saveh, Iran; Global Health Neurology Lab (S Bhaskar MD), NSW Brain Clot Bank, Sydney, NSW, Australia; Division of Cerebrovascular Medicine and Neurology (S Bhaskar MD), National Cerebral and Cardiovascular Center, Suita, Japan; Department of Medical Lab Technology (Prof G K Bhatti PhD), University Centre for Research and Development (S Kalra DM), Chandigarh University, Mohali, India; School of Pharmacy (Prof Y Bustanji PhD), The University of Jordan, Amman, Jordan; Department of Clinical Pharmacy (Prof D Calina PhD), University of Medicine and Pharmacy of Craiova, Romania, Craiova, Romania; Temerty Faculty of Medicine (V K Chattu MD), University of Toronto, Toronto, ON, Canada; Department of Community Medicine (V K Chattu MD), Datta Meghe Institute of Medical Sciences, Sawangi, India; Department of Medical Biochemistry (E Chekol Abebe MSc), Debre Tabor University, Debre Tabor, Ethiopia; The Interdisciplinary Research Group on Biomedicine and Health (D Chu PhD), Faculty of Applied Sciences (D Chu PhD), VNU International School, Hanoi, Viet Nam; Department of Family Medicine and Public Health (Prof M H Criqui MD), University of California San Diego, La Jolla, CA, USA; Life and Health Sciences Research Institute (Prof N Cruz-Martins PhD), University of Minho, Braga, Portugal; Institute for Research and Innovation in Health (Prof N Cruz-Martins PhD), University of Porto, Porto, Portugal; Research Center for Child Psychiatry (O Dadras PhD), University of Turku, Turku, Finland; School of Population Health (Z Dai PhD), University of New South Wales, Sydney, NSW, Australia; Department of Environmental Health (R Darvishi Cheshmeh Soltani PhD), Arak University of Medical Sciences, Arak, Iran; Immunology Research Center (M Dashti MD), Road Traffic Injury Research Center (A Jafari-Khounigh PhD), Cardiovascular Research Center (M Rahimi MD), Tabriz University of Medical Sciences, Tabriz, Iran; Department of Medical Biochemistry (T A Dejenie MSc), University of Gondar, Gondar, Ethiopia; Department of Food, Environmental and Nutritional Sciences (C Del Bo’ PhD), Università degli Studi di Milano (University of Milan), Milan, Italy; Center for Nutrition and Health Research (E Denova-Gutiérrez DSc), National Institute of Public Health, Cuernavaca, Mexico; Chettinad Hospital and Research Institute (Prof V G C Devanbu MD), Chettinad Academy of Research and Education, Chennai, India; Department of Pharmacy (S M R Dewan PhD), United International University, Dhaka, Bangladesh; Pharmacology Division (S M R Dewan PhD), Center for Life Sciences Research Bangladesh, Dhaka, Bangladesh; University of South Carolina, Columbia, SC, USA (V R Dhulipala MD); Faculty of Science and Health (M Ekholuenetale PhD), University of Portsmouth, Hampshire, UK; Department of Clinical and Chemical Pathology (Prof M A Elmonem PhD), Department of Neurology (Prof A Hassan MD), Cairo University, Cairo, Egypt; Department of Epidemiology and Medical Statistics (A F Fagbamigbe PhD), Department of Health Promotion and Education (S E Ibitoye PhD), University of Ibadan, Ibadan, Nigeria; Research Centre for Healthcare and Community (A F Fagbamigbe PhD), Coventry University, Coventry, UK; Director of the Scientific and Technological Park (I R Fakhradiyev PhD), Research and Publication Activity Division (M Kulimbet MSc), Kazakh National Medical University, Almaty, Kazakhstan; Department of Medicine (I R Fakhradiyev PhD), Korea University, Seoul, South Korea; School of Engineering (A Fatehizadeh PhD), Edith Cowan University, Joondalup, WA, Australia; Department of Social Medicine and Epidemiology (A Feizkhah MD), Guilan University of Medical Sciences, Rasht, Iran; Department of Infectious Diseases and Public Health (G Fekadu PhD), City University of Hong Kong, Hong Kong, China; Department of Pharmacy (G Fekadu PhD), Institute of Health Sciences (B R Feyisa MPH), Department of Public Health (D R Terefa MSc), Wollega University, Nekemte, Ethiopia; Jimma University, Jimma, Ethiopia (B R Feyisa MPH); Institute of Public Health (F Fischer PhD), Charité Universitätsmedizin Berlin (Charité Medical University Berlin), Berlin, Germany; Department of Medicine (A Gaipov PhD), Nazarbayev University, Astana, Kazakhstan; Department of Cardiovascular, Endocrine-metabolic Diseases, and Aging (L Galluzzo MA), Italian National Institute of Health, Rome, Italy; Department of Environmental Health (M Gebrehiwot DSc), Wollo University, Dessie, Ethiopia; School of Nursing and Midwifery (F Ghadirian PhD), Obesity Research Center (A Haj-Mirzaian MD), Social Determinants of Health Research Center (J Khanali MD, M Rashidi MD), Department of Orthopedics (A Mirahmadi MD), School of Medicine (Y Ostadi MD), Department of Medical Education (S Tabatabai PhD), Shahid Beheshti University of Medical Sciences, Tehran, Iran; Adelaide Medical School (T K Gill PhD), University of Adelaide, Adelaide, SA, Australia; Department of Biostatistics (K Gohari MS), Tarbiat Modares University, Tehran, Iran; Quantitative Department (K Gohari MS), Department of Epidemiology (S Khanmohammadi MD, S Rashedi MD, H Soleimani MD), Non-Communicable Diseases Research Center, Tehran, Iran; Department of Applied Cell Sciences (A Golchin PhD), Cellular and Molecular Medicine Institute (A Golchin PhD), Urmia University of Medical Sciences, Urmia, Iran; Department of Public Health (B Gupta PhD), Torrens University Australia, Melbourne, VIC, Australia; Department of Toxicology (S Gupta MSc), Shriram Institute for Industrial Research, Delhi, India; Department of Clinical Pharmacology and Medicine (Prof N R Hadi PhD), University of Kufa, Najaf, Iraq; Department of Radiology (A Haj-Mirzaian MD), Massachusetts General Hospital, Boston, MA, USA (M Kim MD); Sakarya University, Turkey, Sakarya, Türkiye (A Hanif PhD); Faculty of Medicine (N I Harlianto MD), Utrecht University, Utrecht, Netherlands; Department of Radiology (N I Harlianto MD), University Medical Center Utrecht, Utrecht, Netherlands; Department of Pharmaceutical Technology (I Hasan MPharm), University of Dhaka, Dhaka, Bangladesh; Department of Pharmacy (Prof M S Hasnain PhD), Marwadi University, Rajkot, India; Independent Consultant, Santa Clara, CA, USA (G Heidari MD); Department of Microbiology (K Hezam PhD), Faculty of Applied Sciences (E A Noman PhD), Taiz University, Taiz, Yemen; School of Medicine (K Hezam PhD), Nankai University, Tianjin, China; Graduate School of Medicine (Y Hiraike PhD), University of Tokyo, Tokyo, Japan; School of Social Sciences (P Hoogar PhD), The Apollo University, Chittoor, India; Department of Psychology (C Hu PhD), Tsinghua University, Beijing, China; Department of Clinical Pharmacy and Pharmacy Practice (Prof N E Ismail PhD), Asian Institute of Medicine, Science and Technology, Bedong, Malaysia; Malaysian Academy of Pharmacy, Puchong, Malaysia (Prof N E Ismail PhD); Department of Health Services Research (M Iwagami PhD), University of Tsukuba, Tsukuba, Japan; Department of Non-Communicable Disease Epidemiology (M Iwagami PhD), London School of Hygiene & Tropical Medicine, London, UK; The World Academy of Sciences UNESCO, Trieste, Italy (Prof M Jakovljevic PhD); Shaanxi University of Technology, Hanzhong, China (Prof M Jakovljevic PhD); Johns Hopkins University, Baltimore, MD, USA (E Jamshidi PharmD); Centre of Studies and Research (S Jayapal PhD), Ministry of Health, Muscat, Oman; Department of Biochemistry (Prof S Jayaram MD), Government Medical College, Mysuru, India; Caring Futures Institute (D M Jemere MBA), Department of Nursing and Health Sciences (S Shorofi PhD), Flinders University, Adelaide, SA, Australia; Geumsan Public Health Center, Geumsan-gun, South Korea (G Jeong MD); College of Medicine (G Jeong MD), Gyeongsang National University, Jinju, South Korea; Department of Community Medicine (N Joseph MD), Manipal Academy of Higher Education, Mangalore, India; Department of Economics (C E Joshua BSc), National Open University, Benin City, Nigeria; Institute of Family Medicine and Public Health (M Jürisson PhD), University of Tartu, Tartu, Estonia; Department of Oral and Maxillofacial Pathology (V Kadashetti MDS), Krishna Vishwa Vidyapeeth (Deemed to be University), Karad, India; Department of Endocrinology (S Kalra DM), Bharti Hospital Karnal, Karnal, India; Department of Public Health (M A Khafaie PhD), Environmental Technologies Research Center, Medical Basic Sciences Research Institute (M A Khafaie PhD), Department of Microbiology (M Saki PhD), Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran; Amity Institute of Forensic Sciences (H Khajuria PhD, B P Nayak PhD), Amity Institute of Public Health (M Shannawaz PhD), Amity University, Noida, India; Primary Care Department (M A Khan MSc), NHS North West London, London, UK; School of Medicine (S Khateri MD), Department of Epidemiology and Biostatistics (Y Moradi PhD), Kurdistan University of Medical Sciences, Sanandaj, Iran; Broad Institute of MIT and Harvard, Cambridge, MA, USA (M Kim MD); Department of General Practice and Family Medicine (Prof O Korzh DSc), Kharkiv National Medical University, Kharkiv, Ukraine; Department of Anthropology (Prof K Krishan PhD), Panjab University, Chandigarh, India; Center of Medicine and Public Health (M Kulimbet MSc), Asfendiyarov Kazakh National Medical University, Almaty, Kazakhstan; Department of Medicine (V Kulkarni MS), Queensland Health, Brisbane, QLD, Australia; Faculty of Medicine and Health Science (M Kurniasari PhD), Universitas Kristen Satya Wacana, Salatiga, Indonesia; School of Nursing (M Kurniasari PhD), Department of Global Health and Health Security (K Latief PhD), Taipei Medical University, Taipei, Taiwan; Division of Evidence Synthesis (C Lahariya MD), Foundation for People-centric Health Systems, New Delhi, India; Division of Lifestyle Medicine (C Lahariya MD), Centre for Health: The Specialty Practice, New Delhi, India; Department of Physiotherapy (T Laksono MS), Universitas Aisyiyah Yogyakarta, Yogyakarta, Indonesia; Institute of Allied Health Sciences (T Laksono MS), National Cheng Kung University, Tainan, Taiwan; Unidad de Genética y Salud Pública (Prof I Landires MD), Instituto de Ciencias Médicas, Las Tablas, Panama; Ministry of Health (Prof I Landires MD), Hospital Joaquín Pablo Franco Sayas, Las Tablas, Panama; Centre for Family Welfare (K Latief PhD), University of Indonesia, Depok, Indonesia; Department of General Medicine (V T Nguyen MD), University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Viet Nam (T T Le MD); Department of Medical Science (M Lee PhD), Ajou University School of Medicine, Suwon, South Korea; Department of Family Medicine (W Lee PhD), University of Texas Medical Branch, Galveston, TX, USA; Department of Molecular Epidemiology (E Llanaj PhD), German Institute of Human Nutrition Potsdam-Rehbrücke, Potsdam, Germany; German Center for Diabetes Research (DZD), München-Neuherberg, Germany (E Llanaj PhD); Rama Medical College Hospital and Research Centre, Uttar Pradesh, India (K Malhotra MBBS); Institute of Applied Health Research (K Malhotra MBBS), University of Birmingham, Birmingham, UK; Rabigh Faculty of Medicine (Prof A Malik PhD), Department of Dental Public Health (Z S Natto DrPH), King Abdulaziz University, Jeddah, Saudi Arabia; Department of Nutrition and Dietetics (M Martorell PhD), Centre for Healthy Living (M Martorell PhD), University of Concepción, Concepción, Chile; Department of Medical and Surgical Sciences and Advanced Technologies “GF Ingrassia” (A Maugeri PhD), University of Catania, Catania, Italy; Comprehensive Cancer Center (T J Meretoja MD), Helsinki University Hospital, Helsinki, Finland; University of Helsinki, Helsinki, Finland (T J Meretoja MD); University Centre Varazdin (T Mestrovic PhD), University North, Varazdin, Croatia; Molecular Biology Unit (N S Mohamed MSc), Bio-Statistical and Molecular Biology Department (N S Mohamed MSc), Sirius Training and Research Centre, Khartoum, Sudan; Modeling in Health Research Center (A Mohammadian-Hafshejani PhD), Shahrekord University of Medical Sciences, Shahrekord, Iran; Clinical Epidemiology and Public Health Research Unit (L Monasta DSc), Burlo Garofolo Institute for Maternal and Child Health, Trieste, Italy; Clinical Research Development Unit (N Morovatdar MD), Biotechnology Research Center (Prof A Sahebkar PhD), Mashhad University of Medical Sciences, Mashhad, Iran; Division of Plastic and Reconstructive Surgery (S D Morrison MD), University of Washington Medical Center, Seattle, WA, USA; Department of Medicine (E Mostafavi PhD), Stanford Cardiovascular Institute (E Mostafavi PhD), Stanford University, Palo Alto, CA, USA; Unit of Pharmacotherapy, Epidemiology and Economics (Prof S Mubarik PhD), Rijksuniversiteit Groningen (University of Groningen), Groningen, Netherlands; Department of Epidemiology and Biostatistics (Prof S Mubarik PhD, Prof C Yu PhD), Wuhan University, Wuhan, China; Department of Research Methods (S Muthu PhD), Orthopaedic Research Group, Coimbatore, India; Department of Biotechnology (S Muthu PhD), Karpagam Academy of Higher Education (Deemed to be University), Coimbatore, India; Department of Computer Science (P Naghavi MS), University of Illinois, Urbana, IL, USA; Department of Health Policy and Oral Epidemiology (Z S Natto DrPH), Beth Israel Deaconess Medical Center (S Sharfaei MD), Harvard University, Boston, MA, USA; Applied Cellular and Molecular Research Center (M H Nematollahi PhD), Kerman University of Medical Sciences, Kerman, Iran; Cardiovascular Laboratory (D H Nguyen MD), Cardiovascular Research Department (H Q Nguyen MD), Methodist Hospital, Merrillville, IN, USA; Department of Allergy, Immunology and Dermatology (D H Nguyen MD), Hanoi Medical University, Hanoi, Viet Nam; Tuberculosis Group (V T Nguyen MD), Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam; International Islamic University Islamabad, Islamabad, Pakistan (R K Niazi PhD); Department of Public Health (D Nurrika PhD), Banten School of Health Science, South Tangerang, Indonesia; Ministry of Research, Technology and Higher Education (D Nurrika PhD), Higher Education Service Institutions (LLDIKTI) Region IV, Bandung, Indonesia; School of Pharmacy (O C Okonji MSc), University of the Western Cape, Cape Town, South Africa; Department of Pharmacotherapy and Pharmaceutical Care (M Ordak PhD), Department of Biochemistry and Pharmacogenomics (M Zielińska MPharm), Medical University of Warsaw, Warsaw, Poland; Department of Biology (W M S Osman PhD), Khalifa University, Abu Dhabi, United Arab Emirates; National School of Public Health (A Padron-Monedero PhD), Institute of Health Carlos III, Madrid, Spain; Vision and Eye Research Institute (Prof S Pardhan PhD), Anglia Ruskin University, Cambridge, UK; Department of Community Medicine (P P Parija MD), All India Institute of Medical Sciences, Jammu, India; Division of Health Policy and Management (R R Parikh MD), University of Minnesota, Minneapolis, MN, USA; Global Health Governance Programme (J Patel BSc), University of Edinburgh, Edinburgh, UK; Faculty of Medicine (F E Petermann-Rocha PhD), Universidad Diego Portales (Diego Portales University), Santiago, Chile; School of Cardiovascular and Metabolic Health (F E Petermann-Rocha PhD), University of Glasgow, Glasgow, UK; Department of Internal Medicine (H T Pham MD), Weiss Memorial Hospital, Chicago, IL, USA; Department of Maternal-Child Nursing and Public Health (E J S Prates BS), Federal University of Minas Gerais, Belo Horizonte, Brazil; Department of Neonatology (I Qattea MD), Case Western Reserve University, Akron, OH, USA; Department of Population Science and Human Resource Development (Prof M Rahman DrPH), University of Rajshahi, Rajshahi, Bangladesh; Health Service Research and Quality of Life Center (Prof M Rahmati PhD), Aix-Marseille University, Marseille, France; Department of Medical, Surgical and Experimental Sciences (I Raimondo MD), University of Sassari, Sassari, Italy; Gynecology and Breast Care Center (I Raimondo MD), Mater Olbia Hospital, Olbia, Italy; Department of Radiology (S K Ramasamy MD), Stanford University, Stanford, CA, USA; Brigham and Women's Hospital (S Rashedi MD), Harvard Medical School, Boston, MA, USA; Department of Primary Care and Public Health (Prof S Rawaf MD), Imperial College London, London, UK; Academic Public Health England (Prof S Rawaf MD), Public Health England, London, UK; Department of Biological Sciences (Prof E Redwan PhD), King Abdulaziz University, Jeddah, Egypt; Department of Protein Research (Prof E Redwan PhD), Research and Academic Institution, Alexandria, Egypt; Cardiovascular Department (Prof A M A Saad MD), Zagazig University, Zagazig, Egypt; Operational Research Center in Healthcare (Prof U Saeed PhD), Near East University (NEU), Nicosia Cyprus, Türkiye; International Center of Medical Sciences Research, Islamabad, Pakistan (Prof U Saeed PhD); Center for Global Health Research (Prof A Sahebkar PhD), Saveetha University, Chennai, India; LMU-Munich, Munich, Germany (J W Sakshaug PhD); Institute for Employment Research, Nuremberg, Germany (J W Sakshaug PhD); Faculty of Pharmacy (Prof M A Saleh PhD), Mansoura University, Mansoura, Egypt; Institute of Epidemiology and Preventive Medicine (Y L Samodra PhD), National Taiwan University, Taipei, Taiwan; Benang Merah Research Center (BMRC), Minahasa Utara, Indonesia (Y L Samodra PhD); Department of Entomology (A M Samy PhD), Medical Ain Shams Research Institute (MASRI) (A M Samy PhD), Ain Shams University, Cairo, Egypt; Department of Biomedical and Neuromotor Sciences (F Sanmarchi MD), University of Bologna, Bologna, Italy; Primary Healthcare Department (F Sanmarchi MD), Azienda USL di Bologna, Bologna, Italy; Research Development Coordination Section (M A N Saqib PhD), Pakistan Health Research Council, Islamabad, Pakistan; School of Sciences (M A N Saqib PhD), University of Management and Technology, Lahore, Pakistan; Faculty of Medicine (A Schuermans BSc), Department of Cardiovascular Sciences (A Schuermans BSc), Katholieke Universiteit Leuven, Leuven, Belgium; Department of Medicine (Y Sethi MD), Swami Vivekanand Subharti University, Meerut, India; National Heart, Lung, and Blood Institute (A Seylani MD), National Institutes of Health, Rockville, MD, USA; Center for Medical and Bio-Allied Health Sciences Research (Prof M J Shahwan PhD), Ajman University, Ajman, United Arab Emirates; Department of Pathology and Laboratory Medicine (S Sham MD), Northwell Health, New York, NY, USA; Department of Safety Services (S Sharfaei MD), Baim Institute for Clinical Research, Boston, MA, USA; Department of Social and Behavioral Health (Prof M Sharma PhD), University of Nevada Las Vegas, Las Vegas, NV, USA; Department of Medical-Surgical Nursing (S Shorofi PhD), Mazandaran University of Medical Sciences, Sari, Iran; Unit of Basic Medical Sciences (E E Siddig MD), University of Khartoum, Khartoum, Sudan; Department of Medical Microbiology and Infectious Diseases (E E Siddig MD), Erasmus University, Rotterdam, Netherlands; Sport Physical Activity and Health Research & Innovation Center (Prof L M L R Silva PhD), Polytechnic Institute of Guarda, Guarda, Portugal; CICS-UBI Health Sciences Research Center (Prof L M L R Silva PhD), University of Beira Interior, Covilhã, Portugal; School of Medicine (Prof J A Singh MD), Baylor College of Medicine, Houston, TX, USA; Department of Medicine Service (Prof J A Singh MD), US Department of Veterans Affairs (VA), Houston, TX, USA; Department of Radiodiagnosis (P Singh MD), All India Institute of Medical Sciences, Bathinda, India; Department of Analytical and Applied Economics (C Swain MPhil), Utkal University, Bhubaneswar, India; Department of Epidemiology (J L Tamuzi MSc), Stellenbosch University, Cape Town, South Africa; Department of Medicine (J L Tamuzi MSc), Northlands Medical Group, Omuthiya, Namibia; Basic Sciences in Infectious Diseases Research Center (R Tavakoli Oliaee PhD), Shiraz University of Medical Sciences, Shiraz, Iran; Department of Preventive Medicine (M Teramoto MD), Northwestern University, Chicago, IL, USA; Outpatient Department (D R Terefa MSc), Wollega University, Bedele Town, Ethiopia; Faculty of Public Health (J H V Ticoalu MPH), Universitas Sam Ratulangi (Sam Ratulangi University), Manado, Indonesia; UKK Institute, Tampere, Finland (Prof T J Vasankari PhD); Faculty of Medicine and Health Technology (Prof T J Vasankari PhD), Tampere University, Tampere, Finland; Department of Infectious Disease (Prof S Vaziri MD), Kermanshah University of Medical Sciences, Kermanshah, Iran; School of Public Health (F Wang PhD), Xuzhou Medical University, Xuzhou, China; Department of Neurosurgery (S Wang MD), School of Public Health (J Xia PhD), Capital Medical University, Beijing, China; Department of Neurosurgery (S Wang MD), Beijing Tiantan Hospital, Beijing, China; Department of Biostatistics (Prof N Yonemoto PhD), University of Toyama, Toyama, Japan; Department of Public Health (Prof N Yonemoto PhD), Juntendo University, Tokyo, Japan; Norris Comprehensive Cancer Center, Keck School of Medicine (M Zahir MD), University of Southern California, Los Angeles, CA, USA; College of Traditional Chinese Medicine (H Zhao MD), Hebei University, Baoding, China; School of Public Health Sciences (O A Zitoun MD), University of Waterloo, Waterloo, ON, Canada; College of Medicine (O A Zitoun MD), Sulaiman Alrajhi University, Al Bukairiyah, Saudi Arabia; Department of Rheumatology (Prof L M March PhD), Royal North Shore Hospital, St Leonards, NSW, Australia
Please see appendix 2 (pp 10–12) for more detailed information about individual author contributions to the research, divided into the following categories: providing data or critical feedback on data sources; developing methods or computational machinery; providing critical feedback on methods or results; drafting the manuscript or revising it critically for important intellectual content; and managing the estimation or publications process. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit the manuscript for publication. Members of the core research team for this topic area had full access to the underlying data used to generate estimates presented in this Article. All other authors had access to and reviewed estimates as part of the research evaluation process, which includes additional stages of formal review.
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GBD 2021 Low Bone Mineral Density Collaborators:
Evelyn Hsieh, Dana Bryazka, Kanyin Liane Ong, Phoebe-Anne Rhinehart, Ewerton Cousin, Hailey Hagins, Cyrus Cooper, Marita Cross, Garland T Culbreth, Karsten E Dreinhoefer, Philippe Halbout, Jacek A Kopec, Sneha Ingle Nicholson, Daniel Prieto Alhambra, Anthony D Woolf, Theo Vos, Yohannes Habtegiorgis Abate, Sherief Abd-Elsalam, Meriem Abdoun, Mohamed Abouzid, Eman Abu-Gharbieh, Salahdein Aburuz, Abiola Victor Adepoju, Qorinah Estiningtyas Sakilah Adnani, Aqeel Ahmad, Haroon Ahmed, Luai A Ahmed, Syed Mahfuz Al Hasan, Tariq A Alalwan, Rasmieh Mustafa Al-amer, Hediyeh Alemi, Abid Ali, Yaser Mohammed Al-Worafi, Reza Amani, Abhishek Anil, Jalal Arabloo, Aleksandr Y Aravkin, Demelash Areda, Brhane Berhe Aregawi, Mohammad Asghari-Jafarabadi, Seyyed Shamsadin Athari, Sina Azadnajafabad, Ahmed Y Azzam, Ashish D Badiye, Nasser Bagheri, Sara Bagherieh, Saliu A Balogun, Maciej Banach, Shirin Barati, Pankaj Bhardwaj, Sonu Bhaskar, Gurjit Kaur Bhatti, Yasser Bustanji, Daniela Calina, Vijay Kumar Chattu, Endeshaw Chekol Abebe, Dinh-Toi Chu, Michael H Criqui, Natalia Cruz-Martins, Omid Dadras, Xiaochen Dai, Zhaoli Dai, Reza Darvishi Cheshmeh Soltani, Mohsen Dashti, Tadesse Asmamaw Dejenie, Cristian Del Bo', Edgar Denova-Gutiérrez, Vinoth Gnana Chellaiyan Devanbu, Syed Masudur Rahman Dewan, Vishal R Dhulipala, Michael Ekholuenetale, Mohamed A Elmonem, Farshid Etaee, Adeniyi Francis Fagbamigbe, Ildar Ravisovich Fakhradiyev, Ali Fatehizadeh, Alireza Feizkhah, Ginenus Fekadu, Bikila Regassa Feyisa, Florian Fischer, Abduzhappar Gaipov, Lucia Galluzzo, Mesfin Gebrehiwot, Fataneh Ghadirian, Tiffany K Gill, Kimiya Gohari, Ali Golchin, Bhawna Gupta, Sapna Gupta, Najah R Hadi, Arvin Haj-Mirzaian, Asif Hanif, Netanja I Harlianto, Ikramul Hasan, Md Saquib Hasnain, Amr Hassan, Simon I Hay, Jiawei He, Golnaz Heidari, Kamal Hezam, Yuta Hiraike, Praveen Hoogar, Chengxi Hu, Segun Emmanuel Ibitoye, Arad Iranmehr, Nahlah Elkudssiah Ismail, Masao Iwagami, Ali Jafari-Khounigh, Mihajlo Jakovljevic, Elham Jamshidi, Sathish Kumar Jayapal, Shubha Jayaram, Digisie Mequanint Jemere, Gwang Hun Jeong, Nitin Joseph, Charity Ehimwenma Joshua, Mikk Jürisson, Vidya Kadashetti, Sanjay Kalra, Morteza Abdullatif Khafaie, Himanshu Khajuria, Moien AB Khan, Javad Khanali, Shaghayegh Khanmohammadi, Moawiah Mohammad Khatatbeh, Sorour Khateri, Min Seo Kim, Oleksii Korzh, Kewal Krishan, Mukhtar Kulimbet, Vishnutheertha Kulkarni, Maria Dyah Kurniasari, Chandrakant Lahariya, Tri Laksono, Iván Landires, Kamaluddin Latief, Thao Thi Thu Le, Munjae Lee, Wei-Chen Lee, Erand Llanaj, Kashish Malhotra, Ahmad Azam Malik, Miquel Martorell, Andrea Maugeri, Hadush Negash Meles, Mohsen Merati, Tuomo J Meretoja, Tomislav Mestrovic, Alireza Mirahmadi, Nouh Saad Mohamed, Abdollah Mohammadian-Hafshejani, Ali H Mokdad, Lorenzo Monasta, Yousef Moradi, Negar Morovatdar, Shane Douglas Morrison, Ebrahim Mostafavi, Parsa Mousavi, Sumaira Mubarik, Christopher J L Murray, Sathish Muthu, Mohsen Naghavi, Pirouz Naghavi, Zuhair S Natto, Biswa Prakash Nayak, Mohammad Hadi Nematollahi, Duc Hoang Nguyen, Hien Quang Nguyen, Van Thanh Nguyen, Robina Khan Niazi, Efaq Ali Noman, Dieta Nurrika, Osaretin Christabel Okonji, Michal Ordak, Wael M S Osman, Yasamin Ostadi, Alicia Padron-Monedero, Shahina Pardhan, Pragyan Paramita Parija, Romil R Parikh, Jay Patel, Fanny Emily Petermann-Rocha, Hoang Tran Pham, Elton Junio Sady Prates, Ibrahim Qattea, Mehran Rahimi, Vafa Rahimi-Movaghar, Mosiur Rahman, Masoud Rahmati, Ivano Raimondo, Shakthi Kumaran Ramasamy, Sina Rashedi, Mohammad-Mahdi Rashidi, Salman Rawaf, Elrashdy M Redwan, Nazila Rezaei, Aly M A Saad, Umar Saeed, Amene Saghazadeh, Fatemeh Saheb Sharif-Askari, Amirhossein Sahebkar, Morteza Saki, Joseph W Sakshaug, Mohamed A Saleh, Yoseph Leonardo Samodra, Abdallah M Samy, Francesco Sanmarchi, Muhammad Arif Nadeem Saqib, Art Schuermans, Yashendra Sethi, Allen Seylani, Moyad Jamal Shahwan, Sunder Sham, Mohammed Shannawaz, Sadaf Sharfaei, Manoj Sharma, Seyed Afshin Shorofi, Emmanuel Edwar Siddig, Luís Manuel Lopes Rodrigues Silva, Jasvinder A Singh, Paramdeep Singh, Hamidreza Soleimani, Chandan Kumar Swain, Shima Tabatabai, Jacques Lukenze Tamuzi, Razieh Tavakoli Oliaee, Seyed Mohammad Tavangar, Masayuki Teramoto, Dufera Rikitu Terefa, Jansje Henny Vera Ticoalu, Asokan Govindaraj Vaithinathan, Tommi Juhani Vasankari, Siavash Vaziri, Fang Wang, Shu Wang, Juan Xia, Naohiro Yonemoto, Chuanhua Yu, Mazyar Zahir, Hanqing Zhao, Magdalena Zielińska, Osama A Zitoun, Lyn M March, and Lidia Sanchez-Riera
Supplementary Materials
References
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The findings of this study are supported by data available in public online repositories, data publicly available upon request of the data provider, and data not publicly available due to restrictions by the data provider. To download citations and metadata for the input data used in these analyses, please visit the Global Health Data Exchange GBD 2021 website (https://ghdx.healthdata.org/gbd-2021/sources). The data sources used in this analysis are listed in appendix 1 (pp 14–21).
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