SUMMARY: Background Nonacog beta pegol is a recombinant glycoPEGylated factor IX with an extended half-life, developed to improve care for patients with hemophilia B. Objectives To investigate the safety, efficacy and pharmacokinetics of nonacog beta pegol for the prophylaxis and treatment of bleeds in previously treated children with hemophilia B. Patients/Methods This phase 3 trial, paradigm(™) 5, enrolled and treated 25 children (aged ≤ 12 years) with hemophilia B (FIX ≤ 2%). Patients were stratified by age (0-6 years and 7-12 years), and received once-weekly prophylaxis with 40 IU kg(-1) nonacog beta pegol for 50 exposure days. Results No patient developed inhibitors, and no safety concerns were identified. Forty-two bleeds in 15 patients were reported to have been treated; the overall success rate was 92.9%, and most bleeds (85.7%) resolved after one dose. The median annualized bleeding rates (ABRs; bleeds per patient per year) were 1.0 in the total population, 0.0 in the 0-6-year group, and 2.0 in the 7-12-year group; the estimated mean ABRs were 1.44 in the total population, 0.87 in the 0-6-year group, and 1.88 in the 7-12-year group. For 22 patients who had previously been receiving prophylaxis, the estimated mean ABR was 1.38 versus a historical ABR of 2.51. Estimated mean steady-state FIX trough levels were 0.153 IU mL(-1) (0-6 years) and 0.190 IU mL(-1) (7-12 years). Conclusion Nonacog beta pegol was well tolerated in previously treated children with hemophilia B; a 40 IU kg(-1) dose provided effective once-weekly prophylaxis and hemostasis when bleeds were treated.
METHODS: This multicentre, randomised, open-label phase 3 study was done at 26 sites (primarily secondary or tertiary centres) in 12 countries. Men, boys, and young adults aged 12 years or older with severe haemophilia A or haemophilia B with inhibitors previously treated with on-demand bypassing agents were randomly assigned (2:1) to receive once-a-month 80 mg subcutaneous fitusiran prophylaxis (fitusiran prophylaxis group) or to continue with bypassing agents on-demand (bypassing agents on-demand group) for 9 months. The primary endpoint was mean annualised bleeding rate during the efficacy period in the intention-to-treat population estimated by negative binomial model. Safety was assessed as a secondary endpoint in the safety population. This trial is complete and is registered with ClinicalTrials.gov, NCT03417102.
FINDINGS: Between Feb 14, 2018, and June 23, 2021, 85 participants were screened for inclusion, of whom 57 (67%; 57 [100%] men; median age 27·0 years [IQR 19·5-33·5]) were randomly assigned: 19 (33%) participants to the bypassing agent on-demand group and 38 (67%) participants to the fitusiran prophylaxis. Negative binomial model-based mean annualised bleeding rate was significantly lower in the fitusiran prophylaxis group (1·7 [95% CI 1·0-2·7]) than in the bypassing agents on-demand group (18·1 [10·6-30·8]), corresponding to a 90·8% (95% CI 80·8-95·6) reduction in annualised bleeding rate in favour of fitusiran prophylaxis (p<0·0001). 25 (66%) participants had zero treated bleeds in the fitusiran prophylaxis group versus one (5%) in the bypassing agents on-demand group. The most frequent treatment-emergent adverse event in the fitusiran prophylaxis group was increased alanine aminotransferase in 13 (32%) of 41 participants in the safety population; there were no increased alanine aminotransferase treatment-emergent adverse events in the bypassing agents on-demand group. Suspected or confirmed thromboembolic events were reported in two (5%) participants in the fitusiran prophylaxis group. No deaths were reported.
INTERPRETATION: Subcutaneous fitusiran prophylaxis resulted in statistically significant reductions in annualised bleeding rate in participants with haemophilia A or haemophilia B with inhibitors, with two-thirds of participants having zero bleeds. Fitusiran prophylaxis might show haemostatic efficacy in participants with haemophilia A or haemophilia B with inhibitors; therefore, the therapeutic might have the potential to improve the management of people with haemophilia.
FUNDING: Sanofi.
METHODS: Between 2009 and 2012, a kilometre-long walk was completed by trained investigators in 462 communities across 16 countries to collect data on tobacco marketing. We interviewed community members about their exposure to traditional and non-traditional marketing in the previous six months. To examine differences in marketing between urban and rural communities and between high-, middle- and low-income countries, we used multilevel regression models controlling for potential confounders.
FINDINGS: Compared with high-income countries, the number of tobacco advertisements observed was 81 times higher in low-income countries (incidence rate ratio, IRR: 80.98; 95% confidence interval, CI: 4.15-1578.42) and the number of tobacco outlets was 2.5 times higher in both low- and lower-middle-income countries (IRR: 2.58; 95% CI: 1.17-5.67 and IRR: 2.52; CI: 1.23-5.17, respectively). Of the 11,842 interviewees, 1184 (10%) reported seeing at least five types of tobacco marketing. Self-reported exposure to at least one type of traditional marketing was 10 times higher in low-income countries than in high-income countries (odds ratio, OR: 9.77; 95% CI: 1.24-76.77). For almost all measures, marketing exposure was significantly lower in the rural communities than in the urban communities.
CONCLUSION: Despite global legislation to limit tobacco marketing, it appears ubiquitous. The frequency and type of tobacco marketing varies on the national level by income group and by community type, appearing to be greatest in low-income countries and urban communities.
METHODS: In an international, community-based prospective study, we enrolled individuals from communities in 17 countries between Jan 1, 2005, and Dec 31, 2009 (except for in Karnataka, India, where enrolment began on Jan 1, 2003). Trained local staff obtained data from participants with interview-based questionnaires, measured weight and height, and recorded forced expiratory volume in 1 s (FEV₁) and forced vital capacity (FVC). We analysed data from participants 130-190 cm tall and aged 34-80 years who had a 5 pack-year smoking history or less, who were not affected by specified disorders and were not pregnant, and for whom we had at least two FEV₁ and FVC measurements that did not vary by more than 200 mL. We divided the countries into seven socioeconomic and geographical regions: south Asia (India, Bangladesh, and Pakistan), east Asia (China), southeast Asia (Malaysia), sub-Saharan Africa (South Africa and Zimbabwe), South America (Argentina, Brazil, Colombia, and Chile), the Middle East (Iran, United Arab Emirates, and Turkey), and North America or Europe (Canada, Sweden, and Poland). Data were analysed with non-linear regression to model height, age, sex, and region.
FINDINGS: 153,996 individuals were enrolled from 628 communities. Data from 38,517 asymptomatic, healthy non-smokers (25,614 women; 12,903 men) were analysed. For all regions, lung function increased with height non-linearly, decreased with age, and was proportionately higher in men than women. The quantitative effect of height, age, and sex on lung function differed by region. Compared with North America or Europe, FEV1 adjusted for height, age, and sex was 31·3% (95% CI 30·8-31·8%) lower in south Asia, 24·2% (23·5-24·9%) lower in southeast Asia, 12·8% (12·4-13·4%) lower in east Asia, 20·9% (19·9-22·0%) lower in sub-Saharan Africa, 5·7% (5·1-6·4%) lower in South America, and 11·2% (10·6-11·8%) lower in the Middle East. We recorded similar but larger differences in FVC. The differences were not accounted for by variation in weight, urban versus rural location, and education level between regions.
INTERPRETATION: Lung function differs substantially between regions of the world. These large differences are not explained by factors investigated in this study; the contribution of socioeconomic, genetic, and environmental factors and their interactions with lung function and lung health need further clarification.
FUNDING: Full funding sources listed at end of the paper (see Acknowledgments).
RESEARCH DESIGN AND METHODS: The prevalence of diabetes, defined as self-reported or fasting glycemia ≥7 mmol/L, was documented in 119,666 adults from three high-income (HIC), seven upper-middle-income (UMIC), four lower-middle-income (LMIC), and four low-income (LIC) countries. Relationships between diabetes and its risk factors within these country groupings were assessed using multivariable analyses.
RESULTS: Age- and sex-adjusted diabetes prevalences were highest in the poorer countries and lowest in the wealthiest countries (LIC 12.3%, UMIC 11.1%, LMIC 8.7%, and HIC 6.6%; P < 0.0001). In the overall population, diabetes risk was higher with a 5-year increase in age (odds ratio 1.29 [95% CI 1.28-1.31]), male sex (1.19 [1.13-1.25]), urban residency (1.24 [1.11-1.38]), low versus high education level (1.10 [1.02-1.19]), low versus high physical activity (1.28 [1.20-1.38]), family history of diabetes (3.15 [3.00-3.31]), higher waist-to-hip ratio (highest vs. lowest quartile; 3.63 [3.33-3.96]), and BMI (≥35 vs. <25 kg/m(2); 2.76 [2.52-3.03]). The relationship between diabetes prevalence and both BMI and family history of diabetes differed in higher- versus lower-income country groups (P for interaction < 0.0001). After adjustment for all risk factors and ethnicity, diabetes prevalences continued to show a gradient (LIC 14.0%, LMIC 10.1%, UMIC 10.9%, and HIC 5.6%).
CONCLUSIONS: Conventional risk factors do not fully account for the higher prevalence of diabetes in LIC countries. These findings suggest that other factors are responsible for the higher prevalence of diabetes in LIC countries.
METHODS: In this pooled analysis, we studied 133,118 individuals (63,559 with hypertension and 69,559 without hypertension), median age of 55 years (IQR 45-63), from 49 countries in four large prospective studies and estimated 24-h urinary sodium excretion (as group-level measure of intake). We related this to the composite outcome of death and major cardiovascular disease events over a median of 4.2 years (IQR 3.0-5.0) and blood pressure.
FINDINGS: Increased sodium intake was associated with greater increases in systolic blood pressure in individuals with hypertension (2.08 mm Hg change per g sodium increase) compared with individuals without hypertension (1.22 mm Hg change per g; pinteraction<0.0001). In those individuals with hypertension (6835 events), sodium excretion of 7 g/day or more (7060 [11%] of population with hypertension: hazard ratio [HR] 1.23 [95% CI 1.11-1.37]; p<0.0001) and less than 3 g/day (7006 [11%] of population with hypertension: 1.34 [1.23-1.47]; p<0.0001) were both associated with increased risk compared with sodium excretion of 4-5 g/day (reference 25% of the population with hypertension). In those individuals without hypertension (3021 events), compared with 4-5 g/day (18,508 [27%] of the population without hypertension), higher sodium excretion was not associated with risk of the primary composite outcome (≥ 7 g/day in 6271 [9%] of the population without hypertension; HR 0.90 [95% CI 0.76-1.08]; p=0.2547), whereas an excretion of less than 3 g/day was associated with a significantly increased risk (7547 [11%] of the population without hypertension; HR 1.26 [95% CI 1.10-1.45]; p=0.0009).
INTERPRETATION: Compared with moderate sodium intake, high sodium intake is associated with an increased risk of cardiovascular events and death in hypertensive populations (no association in normotensive population), while the association of low sodium intake with increased risk of cardiovascular events and death is observed in those with or without hypertension. These data suggest that lowering sodium intake is best targeted at populations with hypertension who consume high sodium diets.
FUNDING: Full funding sources listed at end of paper (see Acknowledgments).
METHODS: HGS was measured using a Jamar dynamometer in 125,462 healthy adults aged 35-70 years from 21 countries in the Prospective Urban Rural Epidemiology (PURE) study.
RESULTS: HGS values differed among individuals from different geographic regions. HGS values were highest among those from Europe/North America, lowest among those from South Asia, South East Asia and Africa, and intermediate among those from China, South America, and the Middle East. Reference ranges stratified by geographic region, age, and sex are presented. These ranges varied from a median (25th-75th percentile) 50 kg (43-56 kg) in men <40 years from Europe/North America to 18 kg (14-20 kg) in women >60 years from South East Asia. Reference ranges by ethnicity and body-mass index are also reported.
CONCLUSIONS: Individual HGS measurements should be interpreted using region/ethnic-specific reference ranges.
METHODS: The PURE study is a prospective, population-based cohort study of individuals aged 35-70 years who have been enrolled from 21 countries across five continents. The key outcomes were the incidence of fatal and non-fatal cardiovascular diseases, cancers, injuries, respiratory diseases, and hospital admissions, and we calculated the age-standardised and sex-standardised incidence of these events per 1000 person-years.
FINDINGS: This analysis assesses the incidence of events in 162 534 participants who were enrolled in the first two phases of the PURE core study, between Jan 6, 2005, and Dec 4, 2016, and who were assessed for a median of 9·5 years (IQR 8·5-10·9). During follow-up, 11 307 (7·0%) participants died, 9329 (5·7%) participants had cardiovascular disease, 5151 (3·2%) participants had a cancer, 4386 (2·7%) participants had injuries requiring hospital admission, 2911 (1·8%) participants had pneumonia, and 1830 (1·1%) participants had chronic obstructive pulmonary disease (COPD). Cardiovascular disease occurred more often in LICs (7·1 cases per 1000 person-years) and in MICs (6·8 cases per 1000 person-years) than in HICs (4·3 cases per 1000 person-years). However, incident cancers, injuries, COPD, and pneumonia were most common in HICs and least common in LICs. Overall mortality rates in LICs (13·3 deaths per 1000 person-years) were double those in MICs (6·9 deaths per 1000 person-years) and four times higher than in HICs (3·4 deaths per 1000 person-years). This pattern of the highest mortality in LICs and the lowest in HICs was observed for all causes of death except cancer, where mortality was similar across country income levels. Cardiovascular disease was the most common cause of deaths overall (40%) but accounted for only 23% of deaths in HICs (vs 41% in MICs and 43% in LICs), despite more cardiovascular disease risk factors (as judged by INTERHEART risk scores) in HICs and the fewest such risk factors in LICs. The ratio of deaths from cardiovascular disease to those from cancer was 0·4 in HICs, 1·3 in MICs, and 3·0 in LICs, and four upper-MICs (Argentina, Chile, Turkey, and Poland) showed ratios similar to the HICs. Rates of first hospital admission and cardiovascular disease medication use were lowest in LICs and highest in HICs.
INTERPRETATION: Among adults aged 35-70 years, cardiovascular disease is the major cause of mortality globally. However, in HICs and some upper-MICs, deaths from cancer are now more common than those from cardiovascular disease, indicating a transition in the predominant causes of deaths in middle-age. As cardiovascular disease decreases in many countries, mortality from cancer will probably become the leading cause of death. The high mortality in poorer countries is not related to risk factors, but it might be related to poorer access to health care.
FUNDING: Full funding sources are listed at the end of the paper (see Acknowledgments).
METHODS: In this international, community-based cohort study, we prospectively enrolled adults aged 35-70 years who had no intention of moving residences for 4 years from rural and urban communities across 17 countries. A portable spirometer was used to assess FEV1. FEV1 values were standardised within countries for height, age, and sex, and expressed as a percentage of the country-specific predicted FEV1 value (FEV1%). FEV1% was categorised as no impairment (FEV1% ≥0 SD from country-specific mean), mild impairment (FEV1% <0 SD to -1 SD), moderate impairment (FEV1%
DESIGN: Prospective cohort study.
SETTING: PURE study in 21 countries.
PARTICIPANTS: 148 858 participants with median follow-up of 9.5 years.
EXPOSURES: Country specific validated food frequency questionnaires were used to assess intakes of refined grains, whole grains, and white rice.
MAIN OUTCOME MEASURE: Composite of mortality or major cardiovascular events (defined as death from cardiovascular causes, non-fatal myocardial infarction, stroke, or heart failure). Hazard ratios were estimated for associations of grain intakes with mortality, major cardiovascular events, and their composite by using multivariable Cox frailty models with random intercepts to account for clustering by centre.
RESULTS: Analyses were based on 137 130 participants after exclusion of those with baseline cardiovascular disease. During follow-up, 9.2% (n=12 668) of these participants had a composite outcome event. The highest category of intake of refined grains (≥350 g/day or about 7 servings/day) was associated with higher risk of total mortality (hazard ratio 1.27, 95% confidence interval 1.11 to 1.46; P for trend=0.004), major cardiovascular disease events (1.33, 1.16 to 1.52; P for trend<0.001), and their composite (1.28, 1.15 to 1.42; P for trend<0.001) compared with the lowest category of intake (<50 g/day). Higher intakes of refined grains were associated with higher systolic blood pressure. No significant associations were found between intakes of whole grains or white rice and health outcomes.
CONCLUSION: High intake of refined grains was associated with higher risk of mortality and major cardiovascular disease events. Globally, lower consumption of refined grains should be considered.
RESEARCH DESIGN AND METHODS: Data on 132,373 individuals aged 35-70 years from 21 countries were analyzed. White rice consumption (cooked) was categorized as <150, ≥150 to <300, ≥300 to <450, and ≥450 g/day, based on one cup of cooked rice = 150 g. The primary outcome was incident diabetes. Hazard ratios (HRs) were calculated using a multivariable Cox frailty model.
RESULTS: During a mean follow-up period of 9.5 years, 6,129 individuals without baseline diabetes developed incident diabetes. In the overall cohort, higher intake of white rice (≥450 g/day compared with <150 g/day) was associated with increased risk of diabetes (HR 1.20; 95% CI 1.02-1.40; P for trend = 0.003). However, the highest risk was seen in South Asia (HR 1.61; 95% CI 1.13-2.30; P for trend = 0.02), followed by other regions of the world (which included South East Asia, Middle East, South America, North America, Europe, and Africa) (HR 1.41; 95% CI 1.08-1.86; P for trend = 0.01), while in China there was no significant association (HR 1.04; 95% CI 0.77-1.40; P for trend = 0.38).
CONCLUSIONS: Higher consumption of white rice is associated with an increased risk of incident diabetes with the strongest association being observed in South Asia, while in other regions, a modest, nonsignificant association was seen.
RESEARCH DESIGN AND METHODS: The Prospective Urban Rural Epidemiology (PURE) study enrolled 143,567 adults aged 35-70 years from 4 high-income countries (HIC), 12 middle-income countries (MIC), and 5 low-income countries (LIC). The mean follow-up was 9.0 ± 3.0 years.
RESULTS: Among those with diabetes, CVD rates (LIC 10.3, MIC 9.2, HIC 8.3 per 1,000 person-years, P < 0.001), all-cause mortality (LIC 13.8, MIC 7.2, HIC 4.2 per 1,000 person-years, P < 0.001), and CV mortality (LIC 5.7, MIC 2.2, HIC 1.0 per 1,000 person-years, P < 0.001) were considerably higher in LIC compared with MIC and HIC. Within LIC, mortality was higher in those in the lowest tertile of wealth index (low 14.7%, middle 10.8%, and high 6.5%). In contrast to HIC and MIC, the increased CV mortality in those with diabetes in LIC remained unchanged even after adjustment for behavioral risk factors and treatments (hazard ratio [95% CI] 1.89 [1.58-2.27] to 1.78 [1.36-2.34]).
CONCLUSIONS: CVD rates, all-cause mortality, and CV mortality were markedly higher among those with diabetes in LIC compared with MIC and HIC with mortality risk remaining unchanged even after adjustment for risk factors and treatments. There is an urgent need to improve access to care to those with diabetes in LIC to reduce the excess mortality rates, particularly among those in the poorer strata of society.
METHODS AND RESULTS: We estimated the durations of total daily sleep and daytime naps based on the amount of time in bed and self-reported napping time and examined the associations between them and the composite outcome of deaths and major cardiovascular events in 116 632 participants from seven regions. After a median follow-up of 7.8 years, we recorded 4381 deaths and 4365 major cardiovascular events. It showed both shorter (≤6 h/day) and longer (>8 h/day) estimated total sleep durations were associated with an increased risk of the composite outcome when adjusted for age and sex. After adjustment for demographic characteristics, lifestyle behaviours and health status, a J-shaped association was observed. Compared with sleeping 6-8 h/day, those who slept ≤6 h/day had a non-significant trend for increased risk of the composite outcome [hazard ratio (HR), 1.09; 95% confidence interval, 0.99-1.20]. As estimated sleep duration increased, we also noticed a significant trend for a greater risk of the composite outcome [HR of 1.05 (0.99-1.12), 1.17 (1.09-1.25), and 1.41 (1.30-1.53) for 8-9 h/day, 9-10 h/day, and >10 h/day, Ptrend < 0.0001, respectively]. The results were similar for each of all-cause mortality and major cardiovascular events. Daytime nap duration was associated with an increased risk of the composite events in those with over 6 h of nocturnal sleep duration, but not in shorter nocturnal sleepers (≤6 h).
CONCLUSION: Estimated total sleep duration of 6-8 h per day is associated with the lowest risk of deaths and major cardiovascular events. Daytime napping is associated with increased risks of major cardiovascular events and deaths in those with >6 h of nighttime sleep but not in those sleeping ≤6 h/night.