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  • North Korea’s Kim Jong Un leaves for China by armoured train

    North Korea’s Kim Jong Un leaves for China by armoured train

    Getty Images Kim Jong Un clutching the railing as he walks down train steps - a green train can be seen in the background. Getty Images

    Kim can be seen here making a trip to Russia by train in 2023

    North Korean leader Kim Jong Un has left Pyongyang for China, where he will be attending a military parade in the capital Beijing, media reports say.

    The “Victory Day” parade, which takes place on Wednesday, will see Kim rub shoulders with China’s President Xi Jinping, Russia’s Vladimir Putin and other world leaders – making it his first multilateral international meeting.

    Kim left the North Korean capital on Monday evening onboard his armoured train, which is said to include a restaurant car serving fine French wines and dishes like fresh lobster.

    The train’s heavy protection means it travels slowly, and Kim’s journey is expected to take up to 24 hours, according to South Korea’s Yonhap agency.

    Kim’s attendance marks the first time a North Korean leader has attended a Chinese military parade since 1959. He will be among 26 other heads of states – including leaders from Myanmar, Iran and Cuba – in attendance.

    His attendance is an upgrade from China’s last Victory Day parade in 2015, when Pyongyang sent one of its top officials, Choe Ryong-hae.

    The reclusive leader rarely travels abroad, with his recent contact with world leaders limited to Putin, who he’s met twice since Russia’s invasion of Ukraine.

    He last visited Beijing in 2019 for an event marking the 70th anniversary of diplomatic ties between the countries. That trip also saw him travel by train.

    The tradition of travelling via train was started by Kim’s grandfather Kim Il Sung – who took his own train trips to Vietnam and Eastern Europe.

    Kim’s father, Kim Jong Il, travelled by train as well as he was reportedly afraid of flying.

    According to one South Korean news outlet, the armoured train has around 90 carriages, including conference rooms, audience chambers and bedrooms.

    Tens of thousands of military personnel will march in formation through Beijing’s historic Tiananmen Square on the day of the parade, which will mark the 80th anniversary of Japan’s surrender in World War Two and the end of the conflict.

    The 70-minute parade is likely to feature China’s latest weaponry, including hundreds of aircraft, tanks and anti-drone systems – the first time its military’s new force structure is being fully showcased in a parade.

    Most Western leaders are not expected to attend the parade, due to their opposition to Russia’s invasion of Ukraine, which has driven the sanctions against Putin’s regime.

    But it will see leaders from Indonesia, Malaysia, Myanmar and Vietnam in attendance – further proof of Beijing’s concerted efforts to ramp up ties with neighbouring South East Asia.

    Just one EU leader will be attending – Slovak Prime Minister Robert Fico – while Bulgaria and Hungary will send representatives.

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  • Piastri equals manager Webber’s F1 win total with Dutch Grand Slam

    Piastri equals manager Webber’s F1 win total with Dutch Grand Slam

    The Dutch Grand Prix was non-stop incidents from start to finish, and the man celebrating most at the end of it all was McLaren’s Oscar Piastri. The Australian’s win generated more than its fair share of fascinating F1 trivia, but there were plenty more notable numbers to digest throughout the Zandvoort finishing order…

    • This was Piastri’s ninth career victory, which ties his manager Mark Webber’s career total.

    • It was Piastri’s first career podium finish at Zandvoort.

    • Piastri took pole, victory, fastest lap and led every lap, making it the the first ‘Grand Slam’ win for a McLaren driver since Mika Hakkinen at the 1998 Monaco Grand Prix.

    • Piastri is the first Australian since Jack Brabham to take a Grand Slam (Belgium 1960, Great Britain 1966).

    • Piastri led from start to finish for the first time in his career and now heads the Drivers’ Championship by 34 points.

    • P2 for Max Verstappen ended the Red Bull driver’s longest run without a podium since 2017/2018 (four races).

    • Verstappen has never finished lower than second in his home Grand Prix.

    • Racing Bulls rookie Isack Hadjar took P3 to become the fifth-youngest podium finisher of all-time behind Verstappen, Lance Stroll, Kimi Antonelli and Lando Norris.

    • Hadjar, 20, is the youngest French driver to stand on the F1 podium (the previous record was Pierre Gasly, aged 23, in 2019).

    • It was the sixth podium finish for Racing Bulls in the Faenza team’s history (zero podiums as Minardi, three as Toro Rosso, two as AlphaTauri, one as Racing Bulls).

    • Hadjar tied the best result for a rookie this season (Antonelli was P3 in Canada).

    • George Russell’s P4 was Mercedes’ best finish at Zandvoort since 2022.

    • P5 for Alex Albon was Williams’ first top-five finish at Zandvoort since Keke Rosberg and Derek Daly in 1982.

    • It was Albon’s 10th points finish of the season (his most in a single season since joining Williams).

    • P6 for Oliver Bearman was a career-best finish for the Haas driver, who started from the pit lane.

    • With Esteban Ocon in P10, both Haas cars scored points for the third time this season.

    • Lance Stroll came from 19th on the grid to finish seventh for Aston Martin.

    • Stroll now leads team mate Fernando Alonso 32 points to 30 in the Drivers’ Championship.

    • Alonso took P8 and has scored in six of the last seven Grands Prix.

    • Red Bull’s Yuki Tsunoda finished in P9 to end a seven-race streak without a point.

    • It was Tsunoda’s first-ever points finish at Zandvoort.

    • Franco Colapinto’s P11 was the best finish of the season for this Alpine chassis, by either the Argentine driver or the man he replaced, Jack Doohan.

    • Liam Lawson finished P12 for Racing Bulls and was the only Red Bull-backed car to not score points.

    • Mercedes’ Kimi Antonelli finished sixth on the road but dropped down to P16 after 15 seconds of penalties.

    • In P17 for Alpine, Pierre Gasly was the last classified finisher for the second consecutive race.

    • Lando Norris’ DNF for McLaren was his first mechanical retirement since Brazil 2022.

    • Ferrari had a 100 percent finishing record this season until both cars retired today.

    • Lewis Hamilton has scored no points in last two Grands Prix.

    • Today’s was Hamilton first DNF for Ferrari.

    • Hamilton crashed out – he has had one DNF due to an accident in each of the last five seasons.

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  • Thawing permafrost could tip Earth’s climate balance

    Thawing permafrost could tip Earth’s climate balance

    The air we breathe today carries a story millions of years in the making. Carbon dioxide, a gas central to life and climate, has always risen and fallen with Earth’s rhythm of ice ages and warm interglacial periods.

    A new study from the University of Gothenburg reveals that this story may have an unexpected twist. A large share of carbon dioxide released after the last ice age likely came from thawing permafrost rather than oceans alone.

    Ancient climate patterns


    For centuries, scientists linked carbon dioxide changes mainly to the oceans. During ice ages, CO2 levels dropped, then rose by nearly 100 parts per million as interglacial warmth returned.

    Warmer oceans could not hold as much carbon, so they released it. That was the accepted explanation. But new evidence suggests land north of the Tropic of Cancer also played a huge role when the northern hemisphere warmed.

    “We have concluded that land north of the Tropic of Cancer, 23.5 degrees north, emitted a lot of carbon when the average temperature rose in the northern hemisphere after our last ice age,” said study lead author Amelie Lindgren.

    “We estimate that this carbon exchange may have accounted for almost half of the rising carbon dioxide levels in the atmosphere.”

    Permafrost soils and Earth’s climate

    During the Ice Age, vast landscapes turned into natural vaults of carbon. Grasses and plants froze into the ground and were buried under thick layers of windblown dust called loess. These deposits stretched across Europe, Asia, and North America, sometimes tens of meters thick.

    Permafrost preserved the organic matter within, slowing decomposition and holding more carbon than unfrozen soils could ever store.

    To understand this hidden reservoir, the researchers combined pollen records spanning 21,000 years with climate model data. This allowed them to reconstruct vegetation patterns and estimate how much carbon soils stored over time.

    “We have chosen to take a snapshot every thousand years. Once we know what type of vegetation prevailed, we can estimate how much carbon were stored in the soil. In this way, we can model how carbon exchange between the soil and the atmosphere has looked since the last ice age,” said Lindgren.

    As the ice sheets retreated between 17,000 and 11,000 years ago, northern soils thawed. This sudden release of carbon dioxide added to the atmosphere, shifting the balance of Earth’s climate.

    Thawed permafrost and lost carbon

    The new study provides numbers that highlight the scale of change. Loess deposits stored about 363 petagrams of carbon at the peak of the last glaciation. After thaw, only about 57 petagrams remain today.

    Most losses occurred before 10,000 years ago, representing one of the largest carbon shifts of the period.

    At the same time, peatlands spread and became powerful carbon sinks. Over the Holocene, they absorbed about 450 petagrams of carbon – more than any other land system. Their expansion marked the only sustained drawdown of atmospheric carbon in this long timeline.

    Ice retreat and seas

    The retreat of massive ice sheets changed landscapes in several ways. Soils under glaciers lost carbon, but new ground emerged for vegetation to colonize, creating fresh carbon stores. Rising seas also submerged large continental shelves.

    Whether submerged soils released carbon quickly or preserved it as subsea permafrost remains uncertain.

    The study estimates that at least some carbon cycled back into the atmosphere during inundation, but much may have been buried in marine sediments.

    Natural rise in carbon dioxide

    Ice cores confirm the bigger picture. Around 21,000 years ago, carbon dioxide levels hovered at 180 ppm during the peak of the ice age. By 11,000 years ago, they had climbed to 270 ppm, marking the interglacial phase.

    Afterward, increases slowed, thanks to peatlands that absorbed significant amounts of carbon and balanced out permafrost emissions.

    ‘We see that peatlands stored large amounts of carbon during the Holocene. Over time, the uptake in peatlands has actually compensated for the emissions that occurred from the permafrost,” said Lindgren.

    Land as source and sink

    The researchers show that northern lands acted both as sources and sinks of carbon. Deglacial losses were abrupt, linked to thawing loess and permafrost. Later, peatland growth reversed the flow.

    The team’s reconstructions suggest that these land processes were strong enough to shape atmospheric changes, alongside ocean shifts.

    The timing of losses and gains created a complex signal in the atmosphere, sometimes masking the full impact of each process.

    Humans broke the natural cycle

    This natural cycle held steady until humans began altering it. Over the past 250 years, the combustion of coal, oil, and gas has added immense amounts of fossil carbon into the air. Levels have surged from 280 ppm during the Industrial Revolution to 420 ppm today.

    “There are extremely high levels of carbon dioxide in the atmosphere right now, and the permafrost is thawing as temperatures rise. What helped us the last time the permafrost decreased was increased carbon storage in peatlands and new land areas becoming available when the continental ice sheets retreated,” said Lindgren.

    “In the future, we will have less land due to sea level rise, and it is difficult to see where we will store the carbon that will be released.”

    Lessons for tomorrow

    The study highlights how fragile Earth’s carbon balance can be. While natural systems once offset permafrost losses, today’s world faces shrinking land and rising seas.

    Understanding the past may not provide comfort, but it gives clarity. The carbon locked in frozen soils could again shape our climate, only this time against a backdrop of human-driven warming.

    The study is published in the journal Science Advances.

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  • Tell us about a travel experience that benefited the local community | Travel

    Tell us about a travel experience that benefited the local community | Travel

    When tourism genuinely involves local communities it’s a win for all parties – guests enjoy more authentic experiences while the livelihoods of those they are visiting are boosted. We’d love to hear about initiatives you’ve sampled that support grassroots projects and communities – perhaps it was through a homestay programme, a community-run pub or cafe, or an indigenous tour guide keen to provide an insight into local culture. Tell us about where you went and those involved.

    The best tip of the week, chosen by Tom Hall of Lonely Planet wins a £200 voucher to stay at a Coolstays property – the company has more than 3,000 worldwide. The best tips will appear in the Guardian Travel section and website.

    Keep your tip to about 100 words

    If you have a relevant photo, do send it in – but it’s your words we will be judging for the competition.

    We’re sorry, but for legal reasons you must be a UK resident to enter this competition.

    The competition closes on Monday 8 September at 10am GMT/BST

    Have a look at our past winners and other tips

    Read the terms and conditions here

    Send us your tip

    You can send in your best tip by filling in the form below. 

    Your responses, which can be anonymous, are secure as the form is encrypted and only the Guardian has access to your contributions. We will only use the data you provide us for the purpose of the feature and we will delete any personal data when we no longer require it for this purpose. For true anonymity please use our SecureDrop service instead.

    If you’re having trouble using the form click here. Read terms of service here and privacy policy here.

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  • Evaluation of joint effect of frailty and sleep health on Cardiometabo

    Evaluation of joint effect of frailty and sleep health on Cardiometabo

    Introduction

    As the global population ages and chronic diseases grow, there is an urgent need to understand how lifestyle factors and physiological vulnerabilities cumulatively impact health outcomes. Recent projections indicate that by 2050, the prevalence rate of hypertension among the elderly in the United States will exceed 80%, and the prevalence rate of diabetes will be close to 40%.1 Among older adults, cardiometabolic diseases (CMDs), including hypertension, heart disease, type 2 diabetes, and stroke, constitute leading contributors to morbidity and mortality.2–4 Any combination of these diseases is linked to a multiplicative increase in the mortality risk5,6 and further complicates the management of diseases and healthcare services. Cardiometabolic multimorbidity (CMM) has become a major public health challenge. Identifying modifiable risk factors as well as their combined effect with age-associated vulnerabilities is imperative to devise effective preventive and intervention strategies.

    Sleep represents a critical modifiable behavioral factor. Approximately 50% of older adults experience sleep-related complaints,7 such as difficulty in initiating or maintaining sleep.8 The most common sleep issues (such as insomnia, fragmented sleep, and sleep apnea) in the older adults9 are linked to adverse cardiometabolic outcomes.10,11 Inadequate or poor-quality sleep may impair cardiovascular function by increasing systemic inflammation, metabolic dysregulation, and accelerating cellular aging.12,13 Concurrently, frailty, characterized by diminished physiological reserves and increased sensitivity to stress, is a critical marker of vulnerability in aging population.14,15 Frail individuals are particularly vulnerable to adverse health events, including the accelerated progression of CMDs and multimorbidity.16,17 Despite their distinct pathophysiological underpinnings,18,19 sleep problems and frailty often coexist,20,21 potentially interacting to amplify health risks in elderly people.

    Though previous studies have independently examined the association between sleep or frailty with health outcomes, a comprehensive understanding of their combined effects remains limited.22,23 Considering the bidirectional connection between sleep and frailty, this knowledge gap is particularly salient.24 Poor sleep may accelerate the onset of frailty, and frailty may further disrupt sleep architecture, continuously exacerbating health risks. To tackle this issue, our study was designed to achieve the following objectives: (1) investigate associations between sleep health and CMDs/CMM, and (2) explore the joint and mediating effects of sleep and frailty on these outcomes, with emphasis on subgroup disparities.

    Methods

    Data Source and Study Population

    The NHANES is a research initiative from Centers for Disease Control and Prevention (CDC) whose objective is to assess the health and nutritional status among the non-institutionalized demographic. The NHANES provides a nationally representative sample of the US population by using a complex, multi-stage, probability-clustered sampling design. Respondents complete structured home interviews and undergo a series of evaluations, including physical examinations, laboratory tests, and interviews at the Mobile Examination Center (MEC).

    This study utilized data from the NHANES (2007–2018) involving 59,842 participants. These specific cycles were chosen due to the consistent and complete measurement of the variables required, particularly the sleep disorders questionnaire (SLQ) and physical functioning questionnaire (PFQ). From an initial sample of 11,910 adults aged ≥60 years, we excluded individuals with incomplete sleep behavior data (n = 1520), undocumented CMD status (n = 186), insufficient frailty index (FI) completion (<80% of items, n = 49), or missing covariates (n = 1211). The final analytical sample comprised 8944 older adults (Figure 1).

    Figure 1 Flowchart of participant selection.

    Sleep Health Assessment

    Referring to previous studies,22,25–27 we developed a composite sleep health score (range: 0–4) based on four dimensions: sleep duration, sleep disorders, subjective sleep continuity, and sleep satisfaction. Sleep duration was categorized as short (<7 hours/night), normal (7–9 hours/night), or long (>9 hours/night).28–30 Sleep disorder was defined as physician diagnosis, or “How often do you snort or stop breathing” answered with “Frequently (5 or more nights a week)”, or “How often feel overly sleepy during day” answered with “Almost always (≥16 days/month)”. Sleep continuity was assessed by the number of nighttime urinations, with ≥2 times per night considered as sleep being easily interrupted. Subjective sleep satisfaction was assessed through self-reported trouble sleeping. Each dimension was scored as optimal (0) or suboptimal (1). Total scores classified participants into three groups: healthy (0), intermediate (1–2), or poor (3–4) sleep health status.

    Definition of CMDs

    CMDs were defined as hypertension, diabetes, heart disease, and stroke. Hypertension was diagnosed based on self-reported physician diagnosis, antihypertensive medication use, or mean systolic/diastolic blood pressure of three measurements ≥140/90 mmHg. Diabetes was confirmed through fasting glucose ≥7.0 mmol/L, hemoglobin A1c ≥6.5%, oral glucose tolerance test 2-hour ≥11.1 mmol/L, or self-reported medical history. Heart disease included physician-confirmed diagnoses of angina pectoris, myocardial infarction (MI), coronary heart disease (CHD), or congestive heart failure (HF). Stroke was defined as self-reported physician diagnosis. Participants were classified into three groups: free CMD (no diagnosis), single CMD (one diagnosis), or cardiometabolic multimorbidity (CMM; ≥ two diagnoses).31,32

    FI

    Frailty was quantified using a 40-item FI based on deficits in physical function, cognition, comorbidities, anthropometric measures, and laboratory biomarkers33,34 (Supplementary Table S1). Each deficit was scored from 0 (absent) to 1 (severe). The FI was computed as the ratio of deficits present to completed items (minimum 80% completion required). Participants were categorized into three groups: robust (FI ≤0.1), pre-frail (0.1< FI <0.25), and frail (FI ≥0.25).

    Multifaceted Health Assessment

    The present analysis evaluated multidimensional health assessments in five key domains: systemic inflammation, metabolic dysfunction, visceral adiposity, cardiometabolic risk, and biological aging. Systemic inflammation was quantified using the Systemic Inflammation Response Index (SIRI). The metabolic status was assessed using the triglyceride-glucose (TyG) index and metabolic score for insulin resistance (METS-IR). Visceral adiposity was characterized using a sex-specific visceral adiposity index (VAI). Cardiometabolic risk profiling was performed using the Cardiometabolic Index (CMI). Detailed computational algorithms for all indices are provided in the Supplementary Materials. Biological aging dynamics were analyzed using five algorithm-based metrics derived from the BioAge R package:35 homeostatic dysregulation (HD), Klemera–Doubal method biological age (KDM), KDM acceleration (KDM-A), phenoage (PA), and PA acceleration (PAA).

    Statistical Analysis

    The analytical procedures rigorously accounted for the NHANES complex sampling design using survey-weighted methods to ensure national representativeness. Baseline characteristics were stratified by CMD status. To investigate the individual and joint effects of sleep health and frailty on CMDs, the number of CMDs, and changes in CMD status, we developed hierarchically adjusted Logistic regression models: Model 1 was adjusted for age, gender, and race as covariates, while Model 2 was further adjusted for socioeconomic factors (education, marital status, and poverty-to-income ratio [PIR]), body mass index (BMI), behavioral covariates (smoking, alcohol consumption, physical activity, and sedentary time). Full covariate specifications are detailed in the Supplementary Materials. Dose-response relationships in existing cumulative counts of CMD were quantified using weighted quasi-Poisson regression and expressed as incidence rate ratios (IRRs) with 95% confidence intervals (CIs). To explore the roles of frailty and sleep status in different populations, we designed three different control comparison groups: Free CMD vs Single CMD, Single CMD vs CMM, and Free CMD vs CMM. The participants were cross-categorized into nine groups based on their combined sleep status (healthy/intermediate/poor) and frailty level (robust/pre-frail/frail). The composite health risk profiles of inflammatory markers, glucose metabolism, visceral adiposity, and aging biomarkers were visualized using radar charts. Mediation analyses implemented using the R mediation package (1000 bootstrap iterations) quantified the proportional mediation of frailty in sleep-CMD associations.

    Stratified analyses were conducted by age, gender, and BMI to evaluate the impact of sleep on CMD. Sleep continuity (the number of nighttime urinations) was removed from the sleep health score to examine the robustness of the results. Sensitivity analyses confirmed the robustness by alternatively modeling frailty as a log-transformed continuous variable and stratified analyses. We used the following methods to examine the robustness of the joint effect: (1) constructed an unordered multinomial logistic regression model; (2) stratified by age and gender. All analyses were conducted using R (version 4.3.1). All tests were two-sided, with a statistical significance level set at α=0.05.

    Results

    Participant Characteristics Stratified by CMD Status

    The final analytical sample included 8944 participants, representing a weighted population of 49,340,699 adults. Table 1 summarized baseline characteristics stratified by CMD status. Participants had an average age of 69.45 ± 6.72 years, with 54.5% female. Sleep health categories were distributed as: healthy (28.2%), intermediate (61.4%), and poor (10.4%). Frailty status included robust (30.6%), pre-frail (50.5%), and frail (18.9%).

    Table 1 Baseline Characteristics According to the CMD Status: NHANES, 2007–2018

    Compared to free-CMD individuals, participants with single-CMD were older, more likely to have obesity, lower socioeconomic status (education and income), reduced physical activity, poor sleep health (eg, abnormal sleep duration, sleep disorders, sleep disruption), and elevated frailty level (p<0.05). These trends intensified in participants with cardiometabolic multimorbidity (CMM), who also exhibited higher proportions of males and non-drinkers (p<0.05).

    The most common CMD combinations among participants were: isolated hypertension, hypertension with diabetes, hypertension with heart disease, and hypertension with diabetes and heart disease. Weighted and unweighted results showed similar patterns (Supplementary Figure S1).

    Associations of Sleep Status, Frailty Levels, and CMD Burden

    In fully adjusted models, poor sleep status was significantly associated with hypertension [odds ratio (OR) (95% CI): 2.33 (1.68, 3.22)], diabetes [OR (95% CI): 1.87 (1.46, 2.40)], heart disease [OR (95% CI): 2.38 (1.75, 3.23)], and stroke [OR (95% CI): 2.51 (1.77, 3.54)]. A graded association was observed between frailty and CMD risk (Figure 2 and Supplementary Tables S2-S3). Sleep status [IRR (95% CI): 1.42 (1.32, 1.52)] and frailty level [IRR (95% CI): 1.84 (1.70, 2.00)] were independently associated with higher cumulative CMD burden (Table 2). Stratified analyses by three CMD status groups revealed that poor sleep status was linked to both single CMD [OR (95% CI): 3.06 (2.08, 4.51)] and CMM [OR (95% CI): 5.63 (3.84, 8.25)] among CMD-free individuals. Among participants with existing CMD, poor sleep status was associated with a 1.89-fold higher odds ratio of CMM [OR (95% CI): 1.89 (1.45, 2.45)]. Significant associations between frailty and CMD status were found in all three control groups (Table 3).

    Table 2 Association Between Sleep Status and Frailty Level with the Number of CMDs

    Table 3 Association Between Sleep Status and Frailty Level with the Distribution of CMD Status

    Figure 2 Associations of sleep status and frailty level with cardiometabolic diseases.

    Note: Forest plots show adjusted ORs with 95% CI for (A) sleep status and (B) frailty level. Models were adjusted for age, gender, race, education, marital status, PIR, BMI, smoking, alcohol consumption, physical activity, and sedentary time. P values were corrected by the Benjamini & Hochberg method: *p <0.05, **p <0.01, ***p <0.001.

    Joint Effects of Sleep Status and Frailty Level on the CMD Burden

    We further explored the joint effect of frailty and sleep status on CMD burden. The results showed that the strength of these associations increased progressively with worsening sleep status or increasing frailty level (Supplementary Figure S2). Poisson regression further quantified the effect of co-exposure on the cumulative number of CMD [IRR (95% CI): 2.01 (1.78, 2.27)] (Figure 3A). The multiplicative interaction between frailty and sleep status had a p-value of 0.006. We modified the subgrouping of sleep (healthy [0–1 scores]/unhealthy [2–4 scores]) and frailty (non-frail [FI<0.21]/frail [FI≥0.21]) to reduce the bias in data distribution caused by an excess of subgroups and evaluate the robustness of the findings. Unhealthy sleep combined with frailty had significant associations with CMDs. In three control comparison groups, participants with both unhealthy sleep and frailty had an OR of 2.06 for single CMD [95% CI: 1.48, 2.88], while the OR for CMM increased to 5.71 [95% CI: 4.16, 7.83]. In the subgroup who had been diagnosed with at least one CMD, poor sleep combined with frailty was significantly associated with the prevalence of CMM [OR (95% CI): 2.98 (2.40, 3.70)] (Figure 3B and Supplementary Table S4).

    Figure 3 Joint effects of sleep status and frailty level on cardiometabolic disease burden.

    Notes: (A) IRR for sleep status and frailty on CMDs cumulative number. (B) IRR and OR for re-grouped sleep status and frailty on CMDs cumulative number and status distribution. Models were adjusted for age, gender, race, education, marital status, PIR, BMI, smoking, alcohol consumption, physical activity, and sedentary time. P values were corrected by the Benjamini & Hochberg method: *p <0.05, **p <0.01, ***p <0.001.

    Mediation Effects of FI on Sleep Health Score and CMDs, the Number of CMDs, and CMD Status Distribution Associations

    To further explore the role of frailty in the association among sleep status, number of CMDs, and changes in CMD status, we conducted a mediation analysis. The correlation between sleep health scores and cumulative number of CMDs was significantly mediated by FI, with a mediation proportion of 57.80%. Compared with the population without CMD, the mediating proportion of FI on the occurrence of CMD was 34.02%, and the mediating proportion of FI on the occurrence of CMM was 46.74%. In the subgroup of patients with at least one type of CMD, significant mediating effect of FI between sleep and CMM was found, but the direct effect was not significant (pADE = 0.160, pACME <0.001, Prop. = 73.16%) (Figure 4 and Supplementary Table S5). Additionally, FI played a significant mediating role in the associations between sleep health scores and hypertension, diabetes, angina pectoris, CHD, and heart failure, with mediation proportions of 43.78%, 52.51%, 37.49%, 51.47%, 59.49%, and 62.45%, respectively. In the mediation analysis of FI in sleep health scores and MI and stroke, no direct effect was found, but the mediation effect was significant, with mediation proportion of 54.38% and 81.26%, respectively (Supplementary Figure S3 and Table S5).

    Figure 4 Mediation analysis of FI on the associations between sleep health and CMDs cumulative number, and status distribution.

    Abbreviations: ADE, Average Direct Effect; ACME, Average Causal Mediation Effect; Prop., Proportion of Mediation.

    Notes: **p <0.01, ***p <0.001. Models were adjusted for age, gender, race, education, marital status, PIR, BMI, smoking, alcohol consumption, physical activity, and sedentary time.

    Radar Chart of Healthy and Aging Risk in Stratified Populations

    Given the results of mediation analysis, we stratified the population to explore whether there were differences in the performance across five dimensions: inflammation level, metabolic function, obesity, cardiometabolic risk, and biological aging. Figure 5 showed a clear upward trend in the weighted mean values of inflammatory (eg, SIRI) and all biological aging indicators with increasing frailty levels. Under different frailty level groups, differences in the performance of health and aging indicators were observed between different sleep statuses. In the robust group, participants with poor sleep exhibited higher weighted means of BMI, SIRI, METS-IR, and CMI than those with healthy sleep (p<0.05). Among the pre-frail participants, those with poor sleep status showed statistically significant differences in SIRI, PA, PAA, and HD compared to those with healthy sleep (p<0.05). In the frail group, individuals with poor sleep status exhibited progressively higher BMI, VAI, PA, and CMI than those with healthy sleep status. However, differences were only statistically significant for BMI, METS-IR, PA, and KDM-A (p<0.05) (Supplementary Table S6–S8).

    Figure 5 Health manifestations and acceleration biological aging profiles stratified by frailty levels.

    Abbreviations: Inflammation level: SIRI, Systemic Inflammation Response Index. Metabolism function: METS-IR, Metabolic Score for Insulin Resistance; TyG, Triglyceride-glucose Index. Obesity: BMI, Body Mass Index (kg/m2); VAI, Visceral Adiposity Index. Cardiometabolic risk: CMI, Cardiometabolic Index. Biological aging: HD, Homeostatic Dysregulation; KDM, Klemera-Doubal Biological Age; KDM-A, KDM Acceleration; PA, Phenoage; PAA, Phenoage Acceleration.

    Note: Weighted mean values of inflammation, metabolism, obesity, cardiometabolic risk, and aging indicators among participants with different levels of frailty.

    Sensitivity Analyses

    When we repeated the analyses of the relationship between sleep and CMD burden stratified by age, gender, and BMI, the results did not change significantly from the original analysis (Supplementary Figures S4 and S5). Sleep continuity was removed from the sleep health score in order to remove the possibility of a reverse confounding effect from frequent nighttime urination. After reclassifying sleep status [healthy (0–1 scores), intermediate (2 scores), poor (3 scores)] and repeating the analysis, the results were consistent with the main analysis (Supplementary Table S9). Similar results were obtained when we replaced the frailty level group with a logarithmic transformation of the FI as a continuous variable (Supplementary Table S10). When we repeated the analyses of the relationship between frailty and CMD burden stratified by age, gender, and BMI, the results were similar to before (Supplementary Figures S6 and S7). The stratified analyses identified several statistically significant interactions; however, the majority appeared to lack clinical significance. We used the CMDs status as the dependent variable and constructed an unordered multinomial logistic regression model with repeated joint effects analyses, obtaining similar results (Supplementary Table S11). When we stratified by age and gender, the joint effects of sleep status and frailty on CMDs were similar to the main analysis results. Notably, in the Free CMD vs Single CMD comparison group, the joint effect was significant in females but not in males (Supplementary Tables S12 and S13).

    Discussion

    The present study provides valuable theoretical insights into the joint effect of poor sleep and frailty on CMDs and multimorbidity in older adults. We used a nationally representative sample in US to show that poor sleep and frailty act both independently and jointly to amplify CMD risk, multimorbidity burden, and the pace of biological aging. These findings will help to enhance our understanding of the multifactorial mechanisms that drive age-related health decline.

    Individuals with either poor sleep status or frailty exhibited more associations with CMDs and greater multimorbidity. This pattern was observed in three controlled comparisons (Free CMD vs Single CMD, Single CMD vs CMM, and Free CMD vs CMM), and was consistent with previous reports.36,37 The complex association between frailty and sleep disorders24,38,39 may lead to the greater risk of CMD and CMM in both poor sleep and frailty. These various pathophysiological interactions create a vicious feedback,40 which eventually leads to adverse cardiometabolic outcomes. Our findings point to a logical correlation between the severity of poor sleep or frailty and CMD prevalence. The prevalence of severe CMDs (eg, HF) or excessive CMM can lead to reduced physical function and disturbed sleep.41,42 Further research is needed to establish causal pathways.

    Frailty was a key mediating factor between poor sleep and CMDs or CMM, similar to previous studies.43 Mediation analysis showed that frailty explained 57.80% of the cumulative burden of poor sleep status on CMDs, especially 81.26% for stroke and 62.45% for HF. In addition, individuals with poor sleep status or frailty showed increased numbers of inflammatory and metabolic markers, along with accelerated biological aging. These findings are highly consistent with the systemic physiological reserve depletion characteristic of frailty:44 poor sleep may accelerate biological aging45 and metabolic dysregulation,46 leading to the premature appearance of frailty phenotypes (eg, sarcopenia and immunosenescence).47 These phenotypes can in turn impair cardiovascular and pancreatic functions through metabolic inflammatory pathways (such as elevated IL-6 and TNF-α).48

    Both poor sleep and frailty were associated with poor health performance, but they showed different health characteristics. Frailty was primarily characterized by inflammation and accelerated aging, while poor sleep more likely to manifest as metabolic imbalance (eg, imbalances in energy intake and expenditure, and increased secretion of appetite hormones),49 which further contributed to obesity. Evidence showed that visceral adiposity significantly increases the risk of cardiovascular disease and type 2 diabetes, while fat deposition in the abdomen and neck can contribute to sleep breathing apnea,50 both of them increase the cardiometabolic burden. Consequently, we propose that non-frail individuals need focus on metabolic parameters (eg, BMI, METS-IR) which can be improved through diet, exercise, psychotherapy, etc. Frail individuals require additional attention to inflammatory and aging markers. Age-related alterations in body composition, metabolism, and pharmacokinetics can induce or exacerbate coexisting conditions.50

    Previous studies found that individuals with both circadian syndrome and frailty were more likely to have new-onset cardiovascular disease.51 However, the joint effect of sleep and frailty in the Free CMD vs Single CMD comparison group was only significant in females in our study. This may be due to the fact that females are more susceptible to long-term wakefulness and circadian rhythm disruption, making them more likely to develop metabolic disorders.52 At the same time, females often experience a heavier frailty burden than males.53 On one hand, the downregulation of estrogen associated with aging reduces the protective effect of immune-regulating genes.54,55 On the other hand, there are gender differences in immune responses and inflammatory signaling pathways. The Y chromosome carried by males encodes some inflammatory pathway genes that have higher innate pro-inflammatory activity and lower adaptive immunity.56 This gap will further increase after the age of 65.53 This condition will significantly increase the risk of frailty in women, while also amplifying the risk of CMD when combined with unhealthy sleep. However, it does not mean that elderly men can ignore sleep and frailty issues. Frailty was related to the prognosis of CMD patients, especially elderly men.57 In our study, unhealthy sleep coexisting with frailty was associated with the development of CMM. Therefore, we recommend that both males and females focus on the prevention and intervention of sleep issues and frailty.

    This study had several limitations. First, although we used a large sample size and complex statistical models, the cross-sectional design was insufficient for concluding causal (eg, whether CMD drives sleep deterioration/frailty).58,59 Second, in large-scale population studies, polysomnography—widely regarded as the gold standard for assessing sleep cycles and sleep disorders, is often difficult to implement due to its high cost. The collection of sleep behavior data mainly relied on subjective reports, which may lead to recall bias or misclassification. Although we have made efforts to conduct a comprehensive assessment of sleep disorders, we have focused only on the more common clinical manifestations such as snoring, apnea, and daytime sleepiness. These symptoms were merely characteristic manifestations of insomnia or sleep apnea, which may lead to an underestimation of the prevalence of sleep disorders. Future research should consider other sleep disorders (eg, parasomnias, circadian rhythm sleep-wake disorders, and restless legs syndrome) and further expand by incorporating low-cost and easily applicable objective measurements (eg, actigraphy). Third, although we selected as many covariates as possible, residual confounding (eg, medications, genetic predisposition) may still exist. Fourth, although previous studies have reported the potential of using Poisson models for estimating IRRs,60–63 the IRRs in this study were based on cross-sectional data considerations. They only reflected the relative ratios of the existing CMD burden (number of diseases) rather than the incidence rates over time. Finally, the applicability of the NHANES data to populations outside the United States requires careful consideration because of potential factors such as genetic and cultural differences.

    Conclusion

    Our findings indicated that sleep health was associated with CMDs and status distribution in older adults. Frailty level and sleep had a joint effect, amplifying the strength of association with the cumulative incidence of CMDs. FI was a key mediating factor in the Sleep-CMM association. These findings will contribute to a better understanding of the relationships and underlying mechanisms among sleep health, frailty, CMD, and CMM. The differences in health risk indicators among populations with different sleep statuses and frailty levels suggested targeted detection for different groups: Elderly individuals with poor sleep should focus on changes on metabolic indicators, while those combined with frailty need pay extra attention to aging and inflammation indicators.

    Abbreviations

    CMD, Cardiometabolic disease; CMM, Cardiometabolic multimorbidity; FI, Frailty index; NHANES, National Health and Nutrition Examination Survey; MI, Myocardial infarction; CHD, Coronary heart disease; HF, Heart failure; BMI, Body mass index; SIRI, Systemic inflammation response index; TyG, Triglyceride-glucose; VAI, Visceral adiposity index; CMI, Cardiometabolic index; METS-IR, Metabolic score for insulin resistance; HD, Homeostatic dysregulation; KDM, Klemera-Doubal method biological age; KDM-A, Klemera-Doubal method biological age acceleration; PA, Phenoage; PAA, Phenoage acceleration; PIR, Poverty index ratio; MVPA, Moderate to vigorous intensity physical activity; OR, Odds ratio; IRR, Incidence rate ratio; CI, Confidence interval.

    Data Sharing Statement

    The NHANES data supporting the results of this study are available online through https://wwwn.cdc.gov/nchs/nhanes/Default.aspx.

    Ethics Approval and Consent to Participate

    NHANES study protocol was reviewed and approved by the National Center for Health Statistics Ethics Review Board, as detailed on their official website (https://www.cdc.gov/nchs/nhanes/about/erb.html?CDC_AAref_Val). According to Article 32, Items 1 and 2 of the “Ethical Review Measures for Life Science and Medical Research Involving Humans” (released on February 18, 2023) in China, this study meets the criteria for exemption from ethical review. Therefore, this study does not require approval from an ethics review committee. This study adhered to the ethical standards of the Declaration of Helsinki.

    Author Contributions

    Conceptualization: QZ; Data curation, Methodology and Visualization: XP and AT; Formal analysis: XP, AT, and JT; Validation: XP, AT, and YM; Project administration and Supervision: QZ, AT, and JT; Funding acquisition: QZ; Writing – original draft: XP; Writing – review and editing: QZ, XP, AT, JT, and YM. All authors drafted, substantially revised, or critically reviewed the article, and agreed on the final version of the manuscript. Furthermore, all authors have agreed on the journal to which the manuscript will be submitted and take responsibility for all aspects of the work.

    Funding

    This work was supported by the National Key Research and Development Program of China [Grant No.2023YFC3605200], Major Research Plan of National Natural Science Foundation of China [Grant No.92163213], Major project of Strategic Research and Consulting Project of the Chinese Academy of Engineering [Grant No.2023-DFZD-58], Tianjin science and technology plan project [Grant No.21JCZDJC00940], and Tianjin health science and technology projects [Grant No.TJWJ2022XK001].

    Disclosure

    The authors declare no conflict of interest.

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  • Shingles vaccine found to reduce the risk of dementia

    Shingles vaccine found to reduce the risk of dementia

    Dementia is a progressive neurological syndrome characterised by impairments in memory, cognition, behaviour, and activities of daily living, constituting a leading cause of mortality and morbidity in the UK. The rising prevalence underscores the urgent need for preventive interventions. However, the heterogeneous nature of dementia pathophysiology presents significant challenges to prevention strategies.

    Recent research by Maxine Taquet and colleagues, published in Nature Medicine in June 2024, has unveiled an unexpected connection between the shingles vaccine and reduced dementia risk, offering new hope in the fight against cognitive decline. Varicella-zoster virus (VZV), also known as shingles, causes inflammation and damage to neural pathways, which may contribute to the neurodegeneration seen in dementia, by affecting blood vessels in the brain and triggering inflammatory responses that damage neurons.

    The study by Taquet and colleagues utilised US electronic health records and leveraged a natural experiment opportunity in the US, created by the rapid uptake of the recombinant vaccine and the concurrent disuse of the live vaccine after October 2017. Individuals in the group that predominantly received the recombinant vaccine were at a lower risk of developing dementia over the next six years (restricted mean time lost (RMTL) ratio, 0.83; 95% confidence interval (CI), 0.80–0.87; P < 0.0001) than were those in the group that predominantly received the live vaccine, translating into 17% more time lived diagnosis-free, or 164 (95% CI 124–202) additional diagnosis-free days among those affected. By comparing the incidence of dementia in those who received a shingles vaccine just after versus just before this step change, Taquet and colleagues estimated there is an association between exposure to the recombinant vaccine and subsequent incidence of dementia diagnosis.

    Currently, adults aged 65-80 years are offered the Shingrix recombinant sub-unit vaccine through the National Health Service (NHS), as are those aged 50 and over with a severely weakened immune system. However, as of September 2025, eligibility is being expanded to immunocompromised people ages 18 and over.

    While these findings are encouraging, researchers emphasise that the shingles vaccine should not be viewed as a definitive dementia prevention strategy. However, the potential cognitive protection represents an additional compelling reason for older adults to pursue vaccination as recommended by health authorities. GlobalData epidemiologists currently forecast that there will be 1,674,000 total prevalent cases of dementia among men and women over the age of 60 in the UK in 2025. The total prevalent cases were initially expected to increase to 1,971,000 cases by 2032—but if the uptake of the recombinant shingles vaccine increases, it is likely that over time there will be a reduction in the cases of dementia.



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  • 7 moments you missed off the track

    7 moments you missed off the track

    Max Verstappen’s home charge fell just short of the win after Oscar Piastri dominated the weekend, but the sea of orange still lifted Zandvoort into full party mode, with the off-track action at the Dutch Grand Prix keeping fans buzzing all weekend.

    Zandvoort proved yet again it’s equal parts festival and Formula 1. Here are seven moments you might have missed from the 2025 Dutch Grand Prix.

    A breakthrough podium

    Rookie sensation Isack Hadjar etched his name into the history books with his first-ever F1 podium, finishing third in front of a jubilant Dutch crowd. As the Racing Bulls driver pulled into parc fermé, fellow drivers lined up to congratulate him, with hugs, pats on the back, and plenty of smiles for the young superstar.

    The blooper reel began right after the chequered flag, as Hadjar looked hilariously confused about finding his way to the podium.

    As if the day wasn’t memorable enough, Hadjar accidentally broke his trophy during the celebrations. It seems Hadjar’s rookie year now comes complete with his very own entry in F1’s accidental-trophy-damage hall of fame.

    Marshall madness

    The Zandvoort marshals have become icons in their own right, and 2025 was no exception. Between sessions, cameras caught them waving flags in rhythm, dancing on the barriers, and hyping up the crowd.

    Their enthusiasm mirrored the energy in the stands and proved once again that at the Dutch Grand Prix, everyone, even the officials, are a part of the spectacle of Zandvoort.

    Fur-mula 1

    Qualifying took a turn when an unexpected intruder joined the action, a fox darting across the circuit in front of Charles Leclerc’s Ferrari. Fortunately, the creature made it across safely and Leclerc carried on undisturbed.

    The incident was a reminder that Zandvoort, being nestled in the dunes, is still very much part of nature’s playground, as well as the drivers’!

    Football meets F1

    The Dutch Grand Prix doubled as a football reunion, with Dutch legend Ruud Gullit, the former Chelsea, AC Milan and Netherlands star, soaking up the paddock buzz. On Sunday, World Cup winner Paulo Dybala, currently playing for AS Roma, took centre stage as he waved the chequered flag to close out the race.

    Xavi Simons, who signed for Tottenham on Friday before being officially presented to the team’s crowd on the same day, still couldn’t miss the action in Zandvoort, which he attended on Sunday. He was happy to be in his hometown and eagerly rooted for Verstappen.

    Crowns in the crowd

    Adding to the prestige of the event, members of the Dutch Royal Family were spotted in the paddock, joining tens of thousands of fans in celebrating the nation’s premier sporting weekend.

    Their presence has become something of a tradition, underscoring how the race has grown into a point of national pride since its return to the calendar in 2021.

    The Orange Wave

    Zandvoort once again turned into a sea of orange, with grandstands moving in unison as fans roared Verstappen on. From coordinated chants to choreographed flag waves, the atmosphere felt less like a race and more like a national celebration.

    The Orange Army were the heartbeat of the weekend, showcasing the pride and passion that has made the Dutch Grand Prix one of F1’s most unique stops.

    The festival beyond the track

    For many, the race is just one part of the Dutch Grand Prix experience. Beyond the roar of engines, Zandvoort turned into a full-scale party with DJs, live acts, and beachside stages running long into the night. Fans were treated to sets from Oliver Heldens, Snollebollekes, and Afrojack, alongside Dutch favourites like Yves Berendse and Kraantje Pappie.

    The mix of international names and homegrown stars gave the weekend its signature race-meets-rave energy. With music thumping from the dunes and thousands of supporters dancing in unison, the Dutch Grand Prix once again proved it’s as much a cultural event as a sporting one.

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  • Their Never-Ending War Over ‘Every Breath You Take’

    Their Never-Ending War Over ‘Every Breath You Take’

    Everybody knows “Every Breath You Take.” It’s the biggest hit the Police ever had, one of the most famous tunes of the Eighties. It spent 8 weeks at Number One in the classic pop summer of 1983. In 2019, BMI officially proclaimed it “the Most Played Song in radio history,” breaking the 22-year record set by “You’ve Lost That Lovin’ Feelin.”  It spent another 11 weeks at Number One in the summer of 1997, when Diddy and Faith Evans turned it into a hip-hop tribute to the late Notorious B.I.G., “I’ll Be Missing You.” It’s one of the world’s favorite songs — the most famous hit Sting ever wrote. 

    Or did he? That’s now a legal matter. The music world got a shock this week when his ex-bandmates, Andy Summers and Stewart Copeland, sued him in London High Court, claiming they should be credited — and paid — for writing “Every Breath You Take,” 42 years after it came out. 

    The bottle-blonde British threesome famously hated each other, so this might just seen like the latest of their nonstop battles. They recorded it while regularly punching each other out in the studio. Sting said he spent half the Synchronicity tour with a broken rib, after one of his backstage brawls with Copeland. But this is a unique case. There’s no precedent for a band this famous having a songwriting credit dispute like this, in court, over such a beloved hit. (The Band, they might have complained a lot in bars, but they never took it to court.) Who the hell spends 42 years going to war over a love song?

    It’s also a special case because there’s no argument at all over who did what. Nobody’s ever disputed that Sting wrote the lyrics, chords, and melody, as he almost always did in the Police. “Our current single, ‘Every Breath You Take,’ wrote itself, largely because it was taken from a very old tradition,” Sting told Musician magazine in 1983. “It’s very atavistic and yet it means something now. I woke up in the middle of the night in Jamaica and went straight to the piano and the chords and song just came out within ten minutes. Wrote the song. Went back to bed. It’s a way of saying there’s still something meaningful and useful in the old way of doing a rock & roll ballad. But it’s not entirely derivative, there’s something else I hear in it: a tinge of sadness.”

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    His original demo was a fully formed song, with a Hammond organ part that they dumped after Andy Summers came up with the guitar arpeggios. The demo has the same words and tune as the final version from their 1983 smash Synchronicity. But in recent years, the 82-year-old Summers has been saying his riff earned a writing credit. “’Every Breath You Take’ was going in the trash until I played on it,” Summers said on Jeremy White’s podcast in 2023. “It’s a very contentious [topic] — it’s very much alive at the moment.” He hinted at legal action, saying, “Watch the press; let’s see what happens in the next year. That’s all I can tell you.” 

    The three Police men have made no comment on the case. Sting and his company Magnetic Publishing Limited are listed as co-defendants. In 2022, Sting sold the rights to his songwriting catalog — both solo and with the Police — to Universal Music Group, for an estimated $250 million. 

    It was the biggest hit of 1983, but it’s never left the airwaves, with its seductive sound and sinister emotion. For a few decades, nobody seriously questioned that Sting wrote it, like he wrote all their hits. All three of them play brilliantly: Summer’s guitar, Copeland’s massive snare sound, Sting’s bass throb at the 2:58 point. You can hear what each musician is doing at any given moment, because Hugh Padgham’s expert production and engineering are so beautifully sparse, with so much open space in the sound. The only enigma, sonically, is the weirdly but awesomely clanging piano, played by Sting. He does for one-note piano solos what Neil Young’s “Cinnamon Girl” did for one-note guitar solos. 

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    So it’s not like there’s any mystery about what each one contributed to “Every Breath You Take.” The issue is what counts as “songwriting,” versus what counts as “arranging.” It’s an eternal argument for musicians, but it was different in the old days, when bands made money from album sales. That revenue stream has dried up, which means publishing royalties matter more than ever. The fights get uglier as musicians get older and their grandkids get thirstier. As the New Yorker’s Adam Gopnik wrote, “Every biography or memoir set in the world of popular music turns out to be a book about music publishing.” Spandau Ballet songwriter Gary Kemp once got sued by the rest of the band, except his brother. Did the guy who played the sax solo on “True” write one-fifth of the song? (According to the judge, this much was not true.) 

    As Sting was always fond of saying, “Every Breath You Take” wasn’t the most radically original song in the world. In 1993, when an interviewer told him, “You completely ripped Bob Marley off on ‘So Lonely,’” Sting agreed. “Totally. ‘No Woman, No Cry’ sped up with a slightly different melody. Those chords, classic aren’t they, C, G, A Minor, F. It’s like the chord sequence around ‘Every Breath You Take’ is generic. It’s ‘Stand By Me’ and it’s ‘Slip Slidin’ Away’ by Paul Simon and the lyrics aren’t particularly original either, they’re straight out of a fucking rhyming dictionary. But somehow there’s something quite unique about that song and I don’t know what it is.” 

    It’s no surprise the recording sessions were open warfare, with fistfights in the studio. “Sting wanted Stewart to just play a very straight rhythm with no fills or anything,” Padgham recalled. “And that was the complete antithesis of what Stewart was about. Stewart would say, ‘I want to fucking put my drum part on it!’ and Sting would say, ‘I don’t want you to put your fucking drum part on it! I want you to put what I want you to put on it!’ and it would go on like that. It was really difficult.” As Copeland said, “The times when I came the closest to homicide, the times when it became absolutely critical that I choke the life out of this man, were when he would come over to me and tell me something about the hi-hat.”  

    The combat dragged on until Summers added his arpeggio riff. “I didn’t stand there and crow about it,” he told Guitar World in 2022. “It was more about keeping those other bastards happy.” As he sees it, he rescued the song from oblivion. “That song was going to be thrown out. Sting and Stewart could not agree on how the bass and drums were going to go. We were in the middle of Synchronicity and Sting says, ‘Well, go on then, go in there and make it your own.’ And I did it in one take. They all stood up and clapped. And, of course, the fucking thing went right round the world, straight to Number One in America. And the riff has become a kind of immortal guitar part that all guitar players have to learn.” Sting told the same basic story. As he recalled in 1983, “Musically, I wrote the song and the guitar parts and then turned to Andy and said, ‘Make it your own.’” 

    They argued over songwriting all the time, even in the early days. Copeland and Summers always got a credit or two per album. “The main problem was the songwriting,” Sting said later. “I was giving a portion of my publishing away to the band just to keep it together and everybody wanted to be a songwriter.” Wasn’t it obvious he was the writer in this band? “I can’t really answer that but I was the person writing all the hits. I thought it was beyond argument. But we still had numerous fights about it.” 

    Sumner and Copeland did get to contribute tunes to Synchronicity, so the fact must be faced: these tracks make a real shaky case for their songwriting chops circa 1983. Summers wrote the insultingly awful “Mother,” which was an easy Number One on Rolling Stone’s recent list of Terrible Songs on Great Albums. (It beat “Maxwell’s Silver Hammer.”) The best you can say for Copeland’s “Miss Gradenko” is that it isn’t “Mother.” It was scandalous to stick these piss-poor efforts on the same album as “Every Breath You Take,” “King of Pain,” and “Wrapped Around Your Finger,” and having this evidence on the record is no boost to their cause. Compared to them, “De Doo Doo Doo, De Da Da Da” is a masterpiece on par with any book by Nabokov.

    But in the plus column for Summers, he wrote “Omegaman,” the best song on Ghost in the Machine. He also came up with “Behind My Camel,” which won a Grammy for Best Rock Instrumental of 1980. Sting hated it so much he buried the tape in the yard behind the studio, until Andy dug it up. Copeland penned keepers on 1979’s Reggatta de Blanc, like the gem “Does Everyone Stare.” But he found his outlet composing film soundtracks like Francis Ford Coppola’s Rumble Fish. “My compositions go pretty much to outside projects,” he said. “Because in the band, there’s a kind of unity of sound that we’ve arrived at, on Sting’s material, and I know what to do with it.” 

    The Police broke up soon after “Every Breath You Take,” at the end of their Synchronicity stadium tour, for no reason except mutual loathing. They reconvened very briefly in 1986 for a lousy remake of “Don’t Stand So Close to Me,” then again in 1992 at Sting’s wedding, then finally in 2007 for their long and lucrative reunion tour. They played Al Gore’s Live Earth benefit concert, with John Mayer adding guitar and Kanye West rapping, “Sting, you the only Police good in the hood.” The closest they’ve come to working together since then? This week, actually, when jazzman Christian McBride dropped his new album. It has his version of “Murder by Numbers,” the song Sting and Summers wrote as a Synchronicity B-side. In a comically ironic bit of timing, they both play on the McBride version — hopefully in separate rooms, to avoid killing each other. 

    It’s ironic that such a universally popular wedding ballad has such a fractious origin story — and with this lawsuit, it gets more fractious than ever. But there’s no end of weird details about the saga of “Every Breath You Take.” For one thing, there’s this: “More Than I Can Say,” by the U.K. pop smoothie Leo Sayer, a long-forgotten Top Ten hit from 1981. The first time I heard “Every Breath You Take” on the radio, I wondered, “How can they get away with this?” Spoiler: they got away with it, since nobody noticed or cared, but it’s basically the same song. Sayer was covering a Fifties oldie, but his Eighties version is the one that sounds like “Every Breath You Take,” even though the Police probably never heard it. As for Diddy’s remake, Sting told Rolling Stone, “I put a couple of my kids through college with the proceeds.” Last fall, he said the rap mogul’s trial didn’t “taint” it for him, since “it’s still my song.” 

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    Until now, the most notorious songwriting dispute was The Band. For years, drummer Levon Helm railed against Robbie Robertson over the credits. (Helm’s claims were complicated by the fact that he had a long and prolific solo career, yet did not write songs for his albums.) “I wrote songs before I ever met Levon,” Robertson told Rolling Stone in 2000. “I’m sorry, I just worked harder than anybody else. Somebody has to lead the charge, somebody has to draw the map. The guys were responsible for the arrangements, but that’s what being a band is, that’s your fucking job.” 

    But for Sting, this song was always personal. “It’s ostensibly a love song, a very seductive romantic love song,” Sting told Rolling Stone. “But it’s about controlling somebody to the nth degree and monitoring their movements.” Many fans missed the sinister subtext. “It’s not like ‘Stand by Me,’ which is this wonderful noble song that means just one thing. ‘Every Breath You Take’ is very ambiguous and quite wicked.” Sting later wrote an answer song, his 1985 solo hit “If You Love Someone, Set Them Free.” “I had to write the antidote,” he said, “after I’d poisoned people with this horrible thing.” Maybe that’s why the conflict around this song never ends. It’s a timeless classic with a long, twisted history. But 42 years after it topped the charts, the tale of “Every Breath You Take” just keeps on getting stranger.

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  • First animated video released to raise awareness on cervical cancer, preventive HPV vaccine

    First animated video released to raise awareness on cervical cancer, preventive HPV vaccine

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    PESHAWAR, Sep 01 (APP):First ever animated video message has been prepared and disseminated on social media for public awareness on Cervical Cancer and the introduction of its preventive vaccine, Human Papillomavirus (HPV), to be launched in Pakistan on September 15 next.

    The video message in national Urdu language has been prepared by Jhpeigo Pakistan under the leadership of Expanded Programme for Immunization (EPI) and Federal Directorate of Immunization (FDI).

    “Introduction of animated awareness video on the Human Papillomavirus (HPV) vaccine is a breakthrough effort to spread life-saving information in a way that is simple, visual and impactful,” observed Dr Amina Khan, Country Director Jhpeigo.

    “Cervical cancer is one of the leading causes of cancer-related deaths among women, yet it is largely preventable,” she told APP.

    The HPV virus, which causes cervical cancer, can be tackled through timely vaccination of girls aged 9–14 years. By protecting our daughters today, we can safeguard them from a disease that claims too many lives every year.

    About the awareness video, Dr Amina said it explains in a clear and relatable way how HPV spreads, why vaccination matters, and how the HPV vaccine is a safe, effective solution for protecting future generations.

    The video is released on social media for public awareness and hopefully, it will spread the message about the threats posed by cervical cancer and preventive measures for protection of our female family members from this fatal disease.

    According to video message, cervical cancer is the second most common cancer among women aged 15 to 44 years in Pakistan.

    Free HPV vaccination is going to be introduced in the country in current month of September and by timely use of vaccine we can protect our daughters from this deadly cancer.

    “HPV vaccine is effective, it’s safe and is already protecting millions of girls worldwide,” assures the video message.

    The HPV vaccine provided by government of Pakistan is approved by World Health Organization (WHO), it added.

    It also explains that cervical cancer is a type of cancer in women and is caused by a virus called Human Papillomavirus (HPV).

    It is a silent cancer with no symptoms in the early stages, but with the passage of time, it can develop into a serious, life-threatening disease.

    To diagnose cervical cancer in time, people should look out for some symptoms, including appearance of genital warts, abnormal bleeding and pain in lower abdomen.

    Through regular screening, such as Pap Smear test, abnormal changes can be detected early before they develop into cancer.

    The HPV vaccine is one of the most effective preventive measures protecting girls by stopping the infection before it starts.

    HPV vaccine is very important because its only one dose is effective in protecting females from a deadly and complicated cancer, which may also spread to other parts of the body.

    People are advised to take action and get their daughters vaccinated and protected from cervical cancer.

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  • Softening reinsurance market could drive M&A opportunities: Fitch

    Softening reinsurance market could drive M&A opportunities: Fitch

    According to Fitch Ratings, a softening reinsurance marketplace might well drive the return of merger and acquisition (M&A) activity as organic opportunities diminish and players with accumulated capital mull takeovers of companies less successful in the hard market.

    In a recent report, Fitch noted that in 2025, there was no major and very limited reinsurance market consolidation activity, as trends such as favourable pricing and beneficial terms and conditions kept focus on organic growth and away from M&A activity.

    However, Fitch expects that with organic opportunities subsiding in the softening market, companies with accumulated capital from sizeable profits will consider acquiring insurers and reinsurers that were less successful in taking advantage of the hard market.

    There were a few companies that announced ownership and strategic changes in 2025. One recent strategic transaction is Markel’s sale of the renewal rights for its reinsurance business to Nationwide, representing about $1.2 billion of gross premiums written.

    As noted by Fitch, the transaction is part of Markel’s strategy to focus on its core specialty insurance business, as the reinsurance operations were sub-scale and underperforming.

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    In 2025, IPO activity resumed with Aspen returning to a public company in May after deciding not to proceed with an IPO in 2024. The firm went private in a 2019 deal with Apollo Global Management, Inc., which still owns approximately 82% of Aspen.

    Fitch stated: “The company demonstrated notable improvement following portfolio optimisation efforts to improve profitability and reduce volatility. The improved environment could also present opportunities for newer companies, such as Convex Group Limited and Vantage Group Holdings Ltd., to go public.”

    Recently, there has been only one non-life reinsurance startup, which is Mereo Insurance Limited, as sufficient industry capital diminishes the need for new entrants, explains Fitch.

    Industry veteran Brian Duperreault launched Mereo just after the January 2025 renewals to write property, casualty and specialty reinsurance, raising a modest $650 million from several investors. It also launched an ILS fund with $250 to $300 million of capital.

    The other M&A in 2025 were ownership changes at Enstar Group Limited and SiriusPoint, where Enstar was acquired in July for $5.1 billion by Sixth Street Partners LLC, with Liberty Strategic Capital, J.C. Flowers & Co. LLC and other institutional investors also participating in the transaction. This means that Enstar is no longer a public company.

    Fitch viewed the transaction as neutral to Enstar’s ratings, as the acquisition did not change Enstar’s business profile, financial profile or operating strategy, although the new parent enhances Enstar’s investment capabilities.

    SiriusPoint repurchased all remaining common shares and warrants held by CM Bermuda Limited for $733 million in February 2025, funded with existing capital.

    It will be interesting to see how reinsurance sector M&A develops as the market softens somewhat from the highs of 2023. Although, returns are still attractive for many, as numerous CEOs stressed throughout Q2 earnings season. With returns favourable for many reinsurers and global capital levels hitting new highs, as reported by broking groups, organic growth certainly isn’t off the table for many, but there’s every chance companies turn to M&A to drive growth in the future.

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