Category: 8. Health

  • Patients face 50-mile trips for routine care available in Goole

    Patients face 50-mile trips for routine care available in Goole

    Anne-Marie Tasker

    Health Correspondent, BBC Look North

    BBC Kelly has tied back dark hair. She is wearing glasses and has nose piercings. She is wearing a coral coloured t-shirt with ruffled sleeves. Her daughter Connie is sitting on her lap and their faces are close together. Connie has her hair tied back and is wearing pink framed glasses. She is holding a blue soft toy.BBC

    Kelly travelled for four hours to take her daughter Connie for eye appointments

    Patients living in and near Goole say they are travelling up to 50 miles (80km) to appointments that could be held in their local hospital.

    For three years, Kelly made four-hour round trips by foot and public transport to take her four-year-old daughter Connie to eye appointments in Beverley every three months.

    She has now had the appointments moved to the ophthalmology department at Goole and District Hospital, just over a mile from her home.

    The Humber Health Partnership, which runs the hospital, said a “large number” of patients go to other sites to receive specialist care and travel was sometimes necessary to “get the patients to the right clinician as quickly as we can.”

    Kelly, a shop worker, said she had to take full days off work to take Connie for her appointments lasting 20 minutes because she relies on public transport.

    “I miss a day of work, have to pay for the train ticket, make sure I have dinner, drinks, snacks, something to keep her occupied on the train and then walk half an hour, have her appointment, then walk half an hour back to the train station, which is quite a lot for a four-year-old,” she said.

    Now the appointments have been moved to Goole, Kelly said it would take just 20 minutes to walk there.

    “I can’t understand why I was having to go through to Beverley so often, when they can do them in Goole,” she said.

    “It’s saved a lot of hassle, a lot of money and a lot of stress.”

    Ivan McConnell, group chief strategy and partnerships officer for Humber Health Partnership said, while there is an ophthalmology department at Goole, some specialist eye services are only provided on other sites.

    “Maybe we should get better at communicating with our patients as to why they are being moved and sent to locations, but it’s really, really important that patient gets the right care from the right clinician,” he said.

    Ivan Mc Connell has close cropped hair, which is receding. He wears round black-framed glasses, a navy jacket, blue shirt and striped tie. He is standing in front of a sign advertising the public consultation about the future of Goole hospital.

    Ivan McConnell from Humber Health Partnership urged patients to ask for local appointments

    Other patients told BBC Look North they fought to move appointments to Goole from other hospitals in Scunthorpe, Grimsby, Hull and Cottingham.

    Shirley Charlesworth said she was sent to Scunthorpe General Hospital last year when she had tonsillitis.

    “All I needed was some IV [intravenous] antibiotics and they could have done that at Goole. It wasn’t that complicated, but they automatically send you out of town,” she said.

    Tracy Hambley said a 93-year-old relative was sent 27 miles (43km) to Scunthorpe for treatment she believed could be safely delivered in her local hospital.

    “We sat in A&E with her for 24 hours, then it was another 48 hours before she got back, just for the sake of having some antibiotics and some fluids,” she said.

    “If she could have just come to Goole, she would have not blocked that bed at the bigger site for all that time.”

    Thirty-two campaigners stand on a pavement outside Goole hospital holding signs and placards reading Hands Off Goole Hospital and Save Goole Hospital. They are all dressed in winter clothing.

    Campaigners have held a series of protests outside Goole and District Hospital

    NHS Humber and North Yorkshire Integrated Care Board (ICB) is currently running a public consultation, to decide which services should be available at Goole and District Hospital in future.

    Within the consultation documents, the ICB says patients living in the Goole area have 15,000 outpatient appointments per year at the hospital, but travel to other hospitals for about 62 appointments a day.

    Campaigners from the Save Goole Hospital Services Action Group have previously said they believe patients are being sent to other sites for appointments as part of a “managed decline” of their local hospital.

    The sign outside the hospital. Goole and District Hospital is in white letters on an NHS blue background.

    A public consultation is looking at future services offered at Goole and District Hospital

    Mr McConnell said: “A number of patients travel for specialist care, or services that are provided where we have centralised a range of things to ensure patients can get tests on a day when they see those specialist medics and see those specialist nurses.”

    He added: “It’s really, really important that patients ask their GPs if there are appointments available within the hospital. That doesn’t always get offered to them.”

    Listen to highlights from Hull and East Yorkshire on BBC Sounds, watch the latest episode of Look North or tell us about a story you think we should be covering here.

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  • Development and validation of a questionnaire to assess women’s hookah smoking: insights from a multi-stage study | BMC Public Health

    Development and validation of a questionnaire to assess women’s hookah smoking: insights from a multi-stage study | BMC Public Health

    This study developed and validated a comprehensive questionnaire (Supplementary Table 3) aimed at identifying factors influencing hookah smoking behavior across personal, interpersonal, and organizational levels. The initial version of the questionnaire was informed by a qualitative study, which provided valuable insights into relevant factors. Through an iterative process, certain items were removed to enhance clarity and relevance, resulting in a refined instrument that was subsequently tested for content validity. The results confirmed the reliability and validity of the questionnaire. The final questionnaire included 81 items aligned with 16 factors. Having tested the face validity, content validity, and construct validity were substantiated. The results offer evidence that this questionnaire is a valid and reliable tool for assessing factors related to hookah smoking among women. To our knowledge, this is the first study to focus specifically on vulnerable populations, such as women who smoke hookah in the Eastern Mediterranean region. Further validation across different sites and cultural contexts would enhance its applicability and provide deeper insights into its broader relevance.

    The need for a questionnaire on women’s hookah smoking in Iran is urgent due to the significant increase in hookah smoking among Iranian women and the adverse effects of consuming this tobacco product on health [24, 25]. Gender differences exist in why men and women start hookah smoking. For example, Iranian men with Turkmen ethnicity often begin smoking due to cultural identity and sense of adulthood [26], while women are more influenced by social approval and emotional needs [14, 27]. These differences suggest that public health strategies should be tailored by gender, and because of this, we need a gender-specific questionnaire. The lack of a questionnaire specifically designed for women shows the need to design one to measure the effective factors in the initiation and continuation of hookah smoking among women. This questionnaire can help develop systematic health promotion initiatives and interventions that specifically address women’s needs and behaviors. There are several questionnaires to evaluate hookah smoking, such as the Hookah Smoking Initiation for Women Questionnaire (HIWQ). This questionnaire was designed using an exploratory sequential mixed methods approach to include six dimensions: drawing the attention of other people, the need to have fun and be relaxed, hookah smoking in the family, availability of hookah, curiosity and having a positive attitude toward hookah. HIWQ aims to assess the initiation of hookah smoking by women. In the questionnaire used in the present study, besides these factors, other issues have also been addressed such as socio-economic deficiencies and role of advertisement and education [13]. Hookah Smoking Obscenity Measurement Scale for Adolescents evaluates the level of obscenity related to hookah smoking among adolescents. This instrument is not specifically designed for women, and considers a specific age group (i.e., adolescents) [12]. The Questionnaire on Smoking Urges for Assessment of Hookah Smoking evaluates the tendency to smoke hookah and, like the previous questionnaire, it is not specifically designed for women [11]. These questionnaires provide a basis for the development of a comprehensive and culturally relevant instrument. It evaluated the beginning and continuation of hookah, which, besides the factors included in these questionnaires, also deals with other factors at the personal, interpersonal and organizational levels.

    These factors include socioeconomic deficiencies, role of advertisement and education, availability, fun and entertainment, hookah smoking in family and relatives, search for peace, attracting others’ attention and approval, physical and mental dependence, color, flavor and sound of hookah, happy environment of coffee shops, pleasant experience of the first puff of hookah smoking, The prevalence of acceptability of hookah smoking in society, false beliefs, Low self-efficacy, Peer pressure, and Family tendencies. These factors showed adequate internal consistency and construct validity and supported their use in evaluating the key factors underlying hookah smoking behavior.

    Our developed and validated questionnaire addresses many dimensions, including low self-efficacy, physical/mental dependence, attracting others’ attention and approval, search for peace, positive attitude towards hookah, false beliefs about personal factors underlying hookah smoking, the color, taste, and sound of hookah, and the pleasant experience of the first puff of hookah. Low self-efficacy, or belief in one’s ability to resist hookah smoking, is a main factor that contributes to hookah smoking. Women with low self-efficacy are more likely to initiate and continue hookah smoking [15]. Self-efficacy assessment helps understand people’s vulnerability to hookah smoking. Moreover, hookah smoking can become addictive and make it hard for women to quit. Assessing the degree of dependence provides insights into the intensity of hookah smoking and the challenges of cessation [15]. Having a positive attitude towards hookah is a major reason for smoking among women. Women who hold more favorable beliefs about hookah are less likely to quit [14, 28]. Assessing attitudes helps identify women at risk of hookah smoking and guides researchers to design interventions to change these attitudes. Meanwhile, the spread of false beliefs about the harmlessness of hookah smoking affects people’s attitudes toward this tobacco product [29]. Some women believe that hookah is less harmful than cigarettes or even has health benefits. The belief that hookah smoking is pleasant and acceptable may add to its popularity among women. It is important to assess these misconceptions to correct them through education. Therefore, individual factors can be effective in women’s hookah smoking, and including relevant questions in questionnaires provides a comprehensive assessment of the risk of hookah smoking in women. This information can guide systematic interventions to prevent hookah initiation, reduce smoking, and promote hookah cessation.

    Interpersonal factors also play a significant role in hookah smoking among women. These factors in the current study include the influence of peers and friends, family preferences, and the role of the family in hookah smoking. These factors are of utmost importance and need to be included in the questionnaire. The role of peers and friends is admittedly an important interpersonal factor involved in hookah smoking among women. Hookah smoking has deep roots in the culture and history of many societies. Climate and cultural norms can affect the prevalence of hookah smoking among women. For example, in some societies like Iran, hookah smoking is considered a social norm and a way to communicate with others as opposed to cigarette which carries stigma for women who smoke [14, 28, 29]. Social norms and peer pressure can initiate, encourage or prohibit the use of hookah. If people closely related to women are hookah smokers, it is more likely that they begin to smoke hookahs too [29]. Friends’ and acquaintances’ smoking can tempt women to smoke hookahs. Including questions about peer pressure in the questionnaire helps recognize the effect of social networks on hookah smoking and informs professionals about interventions that address these relationships. In some cultures, family members may encourage or prohibit hookah smoking, and women may be strongly influenced in their hookah smoking behavior. In this regard, researchers reported that familial habits like having hookah-smoking family members, especially parents or siblings can influence women’s decision to go for hookahs [29, 30]. It can be argued that people can copy hookah smoking by friends and family members and be tempted to smoke due to the availability of hookahs, or the environments that facilitate its use. Including questions about family tendencies in the questionnaire can highlight the role of family in hookah smoking and contribute to interventions that address family dynamics.

    Organizational factors are among the other factors included in this questionnaire as advertisement and education. Advertising can promote hookah smoking by introducing hookah as a social and cultural norm. This could lead to a higher prevalence of hookah smoking among women, as they are more influenced by social norms and cultural expectations [28, 31]. Education can play a significant role in reducing the rate of hookah smoking among women. Educating women on the health risks of hookah smoking can help them make informed decisions about their health.

    In the current study, social factors were also included in the questionnaire. Social factors play a significant role in women’s hookah smoking. These factors included availability, fun and entertainment, socio-economic deficiencies, and happy environment of coffee shops. Easy access to hookah and its low cost are the main factors underlying its prevalence. When hookah is readily available and affordable, women tend more to try it [16]. Moreover, recreational centers where hookah is sold, such as coffee shops and restaurants, can further encourage hookah smoking by providing a pleasant social environment and easy access to hookahs [14, 29]. In addition to the prevalence of hookah smoking in families, the prevalence in public places like coffee shops also familiarizes the young with hookah and gives them easy access to it. The lower cost of hookah compared to other recreational drugs has also attracted many people. The lack of appropriate and large enough social contexts for women, especially recreational facilities, can affect their hookah smoking patterns. This points to the necessity of considering the social and political factors that shape the opportunities and limitations facing women [15]. The political and regulatory system significantly affects the availability of hookahs [27]. Therefore, including questions about social factors in the questionnaire is essential to consider the role of these factors in hookah smoking among women. These factors can provide valuable insights into the social effects of hookah smoking.

    The comprehensive nature of this questionnaire, which includes a wide range of factors, increases its effectiveness in capturing the multidimensional aspects of hookah smoking. Nevertheless, this study has some limitations. First, it was conducted in a single city in Iran, limiting the generalizability of the findings to the wider population of women in Iran or beyond. Further testing in different regions is necessary to enhance the study’s broader applicability. The questionnaire can indeed be applicable to women in other MENA countries as well as in other similar contexts. Second, all data were self-reported, which may introduce recall or reporting biases. Lastly, variations in the use of flavored and non-flavored hookah tobacco, which may influence users’ perceptions and behaviors, were not assessed in this study. Although women in Iran typically smoke mildly flavored hookah tobacco, future studies should account for this important factor.

    Implications of the study

    The present study has major implications for understanding and measuring the complex nature of hookah smoking behavior. Recognition and measurement of these factors give researchers and public health professionals a deeper understanding of the causes and effects of hookah smoking. This knowledge can help with the development of systematic interventions and policies aimed at reducing hookah smoking and its health risks. Future research can use this valid questionnaire to further investigate the factors affecting hookah smoking in different populations and environments. By expanding the scope of research and interventions based on the present findings, stakeholders can attempt to develop goal-oriented strategies to address the complex interplay of personal, interpersonal, and social factors underlying hookah smoking.

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  • Exploring the Impact of Physical Therapy on Patient Outcomes Across the Cancer Care Continuum: A Narrative Review

    Exploring the Impact of Physical Therapy on Patient Outcomes Across the Cancer Care Continuum: A Narrative Review


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  • Food choices during resettlement among immigrants in the US | BMC Public Health

    Food choices during resettlement among immigrants in the US | BMC Public Health

    Table 1 presents differences in characteristics for those who reported losing and adopting foods after migration. Those who reported no longer consuming at least one type of food after migration were different from those who reported that they still ate all of the same items in terms of region of origin, economic standing, age, education, region of residence, years in the US, marital status, school children living at home, English fluency and visa type. Those who reported eating some new foods after migration were different from those who didn’t in terms of region of origin, economic standing, age, education, region of residence, years in the US, marital status, school children living at home, English fluency, and visa type.

    Those who reported losing or adopting foods listed on average 3.5 foods that they no longer consumed and 3.2 foods that they started consuming after migration. Figure 2 lists foods no longer consumed in the US (lost) and foods newly consumed in the US (adopted). The most often reported lost food items were “ethnic foods” (21.9%) and vegetables (16.2%); the most often reported adopted food items were red (18.5%) and processed meats (17.2%).

    Food groups no longer consumed in the US

    PCA scree plots and eigenvalues composed of foods no longer eaten in the US indicated that a three- to six-factor solution was the best fit to the data. PCA for foods no longer eaten in the US stratified by years in the US and gender had excellent to acceptable fit for the three-factor solution (Appendix Table 2). A three-factor solution for foods no longer eaten in the US combined by gender and years in the US was selected as the most meaningful.

    Table 2 Multi-Variable linear regression models for predicting lost food patterns with individual characteristics before and after migration

    We assigned names to food patterns based on the positive factor loadings that contributed most to each pattern (≥0.20) Component 1: home country foods; Component 2: protein & whole grains; Component 3: meat & vegetables (Fig. 3, Panel A). 21% of the variance was explained with a three-factor solution. The home country foods pattern comprised of “ethnic foods” (includes items such as “bread from my home country, ethiopian bread, etc”), cheese, and refined grains with high negative loadings for fish, fruit and vegetables. A high negative loading for a food group means individuals that had listed food groups like “ethnic foods”, cheese, and refined grains were less likely than the overall sample to report losing foods such as fish, fruits and vegetables. The protein & whole grains pattern comprised of soup, whole grains, eggs, poultry, and beans/nuts/legumes/seeds with high negative loadings for chips/snacks, sweets, ethnic foods, and fruit. The meat & vegetables pattern comprised of fats, fish, eggs, poultry, red meat, and vegetables, with high negative loadings for whole grains and beans/legumes/nuts/seeds.

    Fig. 3

    Lost and Adopted Food Group Factor Loadings derived among Foreign-Born Adults who Achieved Legal Permanent Residency in 2003 in the US. Panel (A) Lost Foods. Panel (B) Adopted Foods- Men. Panel (C) Adopted Foods- Women. Note: Lost: The 3-factor solution resulted in 21% of the variance; Adopted: The 3-factor solution resulted in 36% of the variance explained for both males and females Kaiser-Meyer-Olkin (kmo) statistics: (Lost: 0.50); (Adopted: [male (0.62); female (0.65)]). Lost: Sample Size n = 3,509; Adopted: Sample Size [male (n = 1995); female (n = 2015)]

    Patterns of foods no longer consumed in the US

    Table 2 shows associations of individual covariates with the three lost food patterns described above. Note that in interpretation of estimates from the models of lost food patterns, a positive estimate means higher reporting of a lost food pattern and a negative estimate means lower reporting of a lost food pattern.

    Individuals from East and South Asia and Europe were more likely to report losing foods in the meat & vegetables pattern [β (95% CI)]; [Component 3: Those from East & South Asia (0.19 [0.06,0.33]); Europe (0.28 [0.13,0.43]] and Europe were also more likely to report losing foods within the home country foods pattern [Component 1: (0.29 [0.12,0.47])] compared to those from Latin America. Men were less likely to report losing foods within the protein & whole grains pattern [Comp 2: -0.18 (-0.28,-0.08)] than women. Those with more education were less likely to report losing foods within the protein & whole grains pattern [Component 2: -0.01 (-0.03,-0.0008)]. Those currently living in the Western US were more likely to report losing foods within the home country foods pattern [Component 1: 0.22 (0.07,0.37)] compared to those who were living in the Southeast. Those who had lived in the US for longer were more likely to report losing foods within the home country foods pattern [Component 1: 0.01 (0.002,0.02)]. Those who migrated to the US on an employment visa were more likely to report losing foods within the home country foods pattern [Component 1: 0.17 (0.02,0.33)] compared to those who migrated on a family reunification visa.

    Food groups consumed in the US

    PCA scree plots and eigenvalues composed of foods adopted after coming to the US suggested that a three- to six-factor solution was the best fit to the data. PCA for foods adopted in the US stratified by years in the US revealed excellent to acceptable fit for the three factor solution. However, PCA adopted foods stratified by gender revealed a congruence coefficient below the threshold of 0.50, meaning the patterns for men and women are not similar enough to combine and we kept a 3-factor solution for adopted foods stratified by gender (36% of variance for both men and women) (Appendix Table 2).

    For men, the names assigned based on the 3-factor solution and the factor loadings were: [Component 1: junk food; Component 2: meat (red and processed) and refined grains; Component 3: “ethnic” & refined grains]. (Fig. 3, Panel B). The junk food pattern comprised of pizza and processed meats, with a high negative loading for red meat. The meat & refined grains pattern comprised of processed meats, refined grains, and red meat with high negative loadings for fruits and vegetables. The “ethnic” & refined grains pattern comprised of “ethnic” (including soups) and refined grains with high negative loadings for pizza, processed meats, red meat, and fruits.

    For women, (Fig. 3, Panel C), components explained 36% of the variance with a 3-factor solution [Component 1: fruits & vegetables; Component 2: red meat & poultry/eggs; Component 3: meat (red & processed) & fruits]. The fruits & vegetable pattern was comprised of fruits and vegetables with high negative loadings for pizza and processed meats. The red meat & poultry/eggs pattern was comprised of red meat and poultry/eggs with high negative loadings for processed meats and fruit. The meat & fruit pattern was comprised of processed meats, red meat, and fruit with a high negative loading for vegetables.

    Patterns of foods consumed in the US

    Men from Europe, Central Asia, Canada regions were less likely to report adopting foods within the junk foods pattern and the meat & refined grains [Components 1: -0.10 (-0.17,-0.02); Component 2: -0.18 (-0.25,-0.11)] compared to those from Latin America and the Caribbean (Table 3). Men who lived in rural areas compared to urban areas before migration were less likely to report adopting foods within the junk foods pattern and “ethnic” & refined grains pattern [Components 1 & 3] [Component 1: -0.06,-0.12,-0.003)]; Component 3: -0.07 (-0.11,-0.02)]. Men living in the Midwest, Northeast, and Western regions of the US were more likely to report adopting foods within the junk foods pattern [Component 1] compared to those living in the Southeast region [Midwest: 0.14 (0.06,0.23)]; [Northeast: 0.08 (0.01,0.15)]; [West: 0.11 (0.03,0.18)]. Men living in the Northeast were less likely to report adopting foods within the meat & refined grains pattern [Component 2] [-0.08 (-0.15,-0.02)]. Men who had come to the US on refugee visas were less likely to report adopting foods within the three components compared to men who arrived on a family reunification visas [Component 1: -0.14 (-0.23,-0.04]; [Component 2: -0.09 (-0.17,-0.0009)]; [Component 3: -0.12 (-0.18,-0.06)].

    Table 3 Multi-Variable linear regression models for predicting adopted food patterns for males and females with characteristics before and after migration

    Women from East and South Asia and Europe were more likely to report adopting foods within the fruits & vegetables pattern [Component 1] compared to those from the Latin America and Caribbean region (Table 3) [East and South Asia: 0.11 (0.05,0.18)]; [Europe: 0.25 (0.17,0.32)]. Women from Middle East and North Africa were less likely to report adopting foods within the meat & fruit pattern [Component 3: -0.11 (-0.18,0.01)] compared to those from Latin America and Caribbean region. Women living in the Northeast were less likely to report adopting foods within the red meat & poultry/eggs pattern [Component 2] compared to women living in the Southeast [-0.09 (-0.15,-0.04)]. Women who had lived in the US for longer were less likely to report foods within the meat & fruit pattern [Component 3: -0.003 (-0.0005,-0.002)]. Women who had obtained a legalization visa in 2003 were more likely to report adopting foods in line with fruits & vegetables pattern [Component 1: 0.09 (0.006,0.17)] and red meat & poultry/eggs pattern [Component 2: 0.13 (0.06,0.22)] compared to those with a family reunification visa.

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  • Interdisciplinary report illuminates demographic, systemic health factors of dry eye disease

    Interdisciplinary report illuminates demographic, systemic health factors of dry eye disease

    Dry eye disease was more prevalent in women than men, and was found to increase with age, investigators reported. Image credit: ©Rido – stock.adobe.com

    The Tear Film and Ocular Surface Society (TFOS) DEWS III Digest Report, published in June 2025 in American Journal of Ophthalmology, has identified key research published since the 2017 TFOS DEWS II Workshop reports in the form of sex, gender and hormones; epidemiology; pathophysiology; tear film; pain and sensation; iatrogenic; and clinical trial design.1 The report was comprised in an effort to support evidence cited in the TFOS DEWS III Diagnostic Methodology and Management and Therapy reports, and included input from 80 experts in 18 countries, according to TFOS.2

    Study authors, led by Fiona Stapleton, PhD, MSc, of the School of Optometry and Vision Science, UNSW Sydney in NSW, Australia, outlined advancements in tear film research, a clarification of pathophysiological distinctions between aqueous deficient dry eye (ADDE) and evaporative dry eye (EDE) and ocular pain perception, among others.1

    For sex, gender and hormones, study authors focused on studies published after July 1, 2017 and cited significant sex-related differences in the lacrimal gland, meibomian gland, cornea, eye lid blinking, corneal thickness, sensitivity, re-epithelisation, pain assessment, hormonal regulation of the ocular surface and adnexa and dry eye disease (DED)-induced damage, among others.1

    “There have been significant research advances linking sex, hormones and gender to DED. Aging, cancer and hormone therapy increasingly broaden the interdisciplinarity in this field over time,” the report authors stated. “Despite the significant impact of gender-affirming hormone therapy on the entire endocrine system and its effects on physical and mental health, there is limited information on its impact on ocular health. Variations in age, health profile, gender-affirming hormone therapy compliance and barriers to accessing regular healthcare limit the documentation of side effects. Clinicians and future research should consider these variations, as recommended in a recent systematic review on the medical aspects of the transgender and gender diverse population.”

    For epidemiology, DED was found to increase with age and was more common in women than men; signs and symptoms were more common in women with higher rates in younger and older adults. Some of the outstanding questions that remain from the research are issues concerning disease severity, geographic considerations, the generalisability of prevalence measures for DED in children and adults under 40 years of age and a need for appropriately powered studies to determine risk factors in patients under 40. Researchers noted that a limited number of studies exist that explore the prevalence, risk factors, or natural history by disease severity.1

    Opportunities for future research concerning tear film were identified in the needed exploration of the relationship between disordered lipids that result in spreading and increased elasticity as compared to ordered lipids that lead to improved resistance to evaporation. Researchers also called for a more detailed understanding of whether tear biomarkers can be used to differentiate subtypes of DED and referenced the society’s recent Diagnostic Methodology report.1

    “Analyses of microbiome changes across individuals of different ethnicities and countries of residence may provide further insights into its potential role in DED pathogenesis or as a marker for the disease,” the study authors noted. “Understanding the potential role of different microRNAs in DED pathogenesis, DED subtype or as biomarkers could be a highly promising area for future investigation.”

    Recommendations for DED management were also suggested by the study authors under iatrogenic, particularly regarding DED implicated in a variety of anti-glaucoma topical drugs, preservatives and excipients, antibiotics and hormone replacement therapy, among others.1

    “The first step is to investigate which medication is causing DED and try to stop its use. This subtraction can be challenging when discontinuing the treatment, which presents a risk to the eye’s health,” the study authors noted. “Sometimes, multiple drugs and components are involved, or adverse effects appear long after treatment initiation, making identification of which is causing DED even more difficult.”

    References:

    1. Stapleton F, Argüeso P, Asbell P, et al. TFOS DEWS III Digest Report. Am Journ of Opthalmol. 2025. https://doi.org/10.1016/j.ajo.2025.05.040
    2. TFOS dry eye workshop (DEWS) III: completed! Tear Film and Ocular Surface Society. News release. June 10, 2025. Accessed June 18, 2025. https://www.tearfilm.org/dettnews-tfos_dry_eye_workshop_dews_iii_completed/7450_16/eng/

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  • Bai W, Chen P, Cai H et al. Worldwide prevalence of mild cognitive impairment among community dwellers aged 50 years and older: a meta-analysis and systematic review of epidemiology studies [J]. Age Ageing, 2022, 51(8).

  • Chen T, Li D. The roles of working memory updating and processing speed in mediating age-related differences in fluid intelligence [J]. Neuropsychology, development, and cognition section B. Aging Neuropsychol Cognition. 2007;14(6):631–46.

    Google Scholar 

  • Wang M, Gamo NJ, Yang Y, et al. Neuronal basis of age-related working memory decline [J]. Nature. 2011;476(7359):210–3.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Elliott EM, Cherry KE, Brown JS, et al. Working memory in the oldest-old: evidence from output serial position curves [J]. Volume 39. Memory & cognition; 2011. pp. 1423–34. 8.

  • D’esposito M, Postle BR. The cognitive neuroscience of working memory [J]. Ann Rev Psychol. 2015;66:115–42.

    Google Scholar 

  • Baddeley A. Working memory [J]. Science. Volume 255. New York, NY); 1992. pp. 556–9. 5044.

  • Fiske ST, Schacter DL, Taylor SE. Working Memory: Theories, Models, and Controversies [J]. 2011.

  • Baddeley AD, Allen RJ, Hitch G, J J E W. M. Binding in visual working memory: The role of the episodic buffer [J]. 2017, 312–331.

  • Farias ST, Harrell E, Neumann C, et al. The relationship between neuropsychological performance and daily functioning in individuals with alzheimer’s disease: ecological validity of neuropsychological tests [J]. Archives Clin Neuropsychology: Official J Natl Acad Neuropsychologists. 2003;18(6):655–72.

    Google Scholar 

  • Jacob L, Smith L, Thoumie P, et al. Association between intelligence quotient and disability: the role of socioeconomic status [J]. Annals Phys Rehabilitation Med. 2020;63(4):296–301.

    Google Scholar 

  • Bahmani Z, Clark K, Merrikhi Y, et al. Prefrontal contributions to attention and working memory [J]. Curr Top Behav Neurosci. 2019;41:129–53.

    PubMed 

    Google Scholar 

  • Kennedy KM, Rodrigue KM, Bischof GN, et al. Age trajectories of functional activation under conditions of low and high processing demands: an adult lifespan fMRI study of the aging brain [J]. NeuroImage. 2015;104:21–34.

    PubMed 

    Google Scholar 

  • Deary IJ, Johnson W, Starr JM. Are processing speed tasks biomarkers of cognitive aging? [J]. Psychol Aging. 2010;25(1):219–28.

    PubMed 

    Google Scholar 

  • Faraza S, Waldenmaier J, Dyrba M et al. Dorsolateral Prefrontal Functional Connectivity Predicts Working Memory Training Gains [J]. Frontiers in aging neuroscience. 2021;13:592261.

  • Talamonti D, Montgomery CA, Clark DPA et al. Age-related prefrontal cortex activation in associative memory: An fNIRS pilot study [J]. NeuroImage. 2020;222(117223).

  • Holtzer R, Mahoney JR, Izzetoglu M, et al. Online fronto-cortical control of simple and attention-demanding locomotion in humans [J]. NeuroImage. 2015;112:152–9.

    PubMed 

    Google Scholar 

  • Guadagni V, Drogos LL, Tyndall AV, et al. Aerobic exercise improves cognition and cerebrovascular regulation in older adults [J]. Neurology. 2020;94(21):e2245–57.

    PubMed 
    PubMed Central 

    Google Scholar 

  • Haeger A, Costa AS, Schulz JB et al. Cerebral changes improved by physical activity during cognitive decline: A systematic review on MRI studies [J]. NeuroImage Clinical. 2019;23(101933).

  • Norevik CS, Huuha AM, Røsbjørgen RN et al. Exercised blood plasma promotes hippocampal neurogenesis in the Alzheimer’s disease rat brain [J]. J Sport Health Sci. 2024;13(2):245–55.

  • Nuzum H, Stickel A, Corona M et al. Potential benefits of physical activity in MCI and dementia [J]. Behav Neurol, 2020;12:7807856.

  • De La Rosa A, Olaso-Gonzalez G, Arc-Chagnaud C, et al. Physical exercise in the prevention and treatment of alzheimer’s disease [J]. J Sport Health Sci. 2020;9(5):394–404.

    PubMed 
    PubMed Central 

    Google Scholar 

  • Zhidong C, Wang X, Yin J, et al. Effects of physical exercise on working memory in older adults: a systematic and meta-analytic review [J]. Eur Rev Aging Phys Activity: Official J Eur Group Res into Elder Phys Activity. 2021;18(1):18.

    Google Scholar 

  • Xiong J, Ye M, Wang L et al. Effects of physical exercise on executive function in cognitively healthy older adults: A systematic review and meta-analysis of randomized controlled trials: Physical exercise for executive function [J]. International journal of nursing studies. 2021;114(103810).

  • Zhang L, Li B, Yang J, et al. Meta-analysis: resistance training improves cognition in mild cognitive impairment [J]. Int J Sports Med. 2020;41(12):815–23.

    PubMed 

    Google Scholar 

  • Zeng Y, Wang J, Cai X, et al. Effects of physical activity interventions on executive function in older adults with dementia: A meta-analysis of randomized controlled trials [J]. Volume 51. Geriatric nursing (New York, NY); 2023. pp. 369–77.

  • Levin O, Netz Y, Ziv G. The beneficial effects of different types of exercise interventions on motor and cognitive functions in older age: a systematic review [J]. European review of aging and physical activity: official journal of the European Group for Research into Elderly and Physical Activity. 2017;14(20).

  • Venegas-Sanabria LC, Cavero-Redondo I, Martínez-Vizcaino V, et al. Effect of multicomponent exercise in cognitive impairment: a systematic review and meta-analysis [J]. BMC Geriatr. 2022;22(1):617.

    PubMed 
    PubMed Central 

    Google Scholar 

  • Voet NB, Van Der Kooi EL, Van Engelen BG et al. Strength training and aerobic exercise training for muscle disease [J]. The Cochrane database of systematic reviews. 2019;12(12):Cd003907.

  • Beeri MS, Leugrans SE, Delbono O, et al. Sarcopenia is associated with incident alzheimer’s dementia, mild cognitive impairment, and cognitive decline [J]. J Am Geriatr Soc. 2021;69(7):1826–35.

    PubMed 
    PubMed Central 

    Google Scholar 

  • Cui M, Zhang S, Liu Y et al. Grip Strength and the Risk of Cognitive Decline and Dementia: A Systematic Review and Meta-Analysis of Longitudinal Cohort Studies [J]. Front Aging Neurosci. 2021;13:625551.

  • Kunutsor SK, Isiozor NM, Voutilainen A, et al. Handgrip strength and risk of cognitive outcomes: new prospective study and meta-analysis of 16 observational cohort studies [J]. GeroScience. 2022;44(4):2007–24.

    PubMed 
    PubMed Central 

    Google Scholar 

  • Kuo K, Zhang YR, Chen SD, et al. Associations of grip strength, walking pace, and the risk of incident dementia: A prospective cohort study of 340212 participants [J]. Alzheimers Dement. 2023;19(4):1415–27.

    PubMed 

    Google Scholar 

  • Liu SW, Li M, Zhu JT, et al. [Correlation of muscle strength with cognitive function and medial Temporal lobe atrophy in patients with mild to moderate alzheimer’s disease] [J]. Zhonghua Yi Xue Za Zhi. 2022;102(35):2786–92.

    CAS 
    PubMed 

    Google Scholar 

  • Burtscher J, Millet GP, Place N et al. The Muscle-Brain Axis and neurodegenerative diseases: the key role of mitochondria in Exercise-Induced neuroprotection [J]. Int J Mol Sci. 2021, 22(12).

  • Herold F, Labott BK, Grässler B et al. A link between handgrip strength and executive functioning: A Cross-Sectional study in older adults with mild cognitive impairment and healthy controls [J]. Healthcare. 2022;10(2):230.

  • Colcombe SJ, Erickson KI, Raz N et al. Aerobic fitness reduces brain tissue loss in aging humans. J Gerontol A Biol Sci Med Sci. 2003;58(2):176–80.

  • Voelcker-Rehage C, Godde B, Staudinger UM. Physical and motor fitness are both related to cognition in old age [J]. Eur J Neurosci. 2010;31(1):167–76.

    PubMed 

    Google Scholar 

  • Mekari S, Dupuy O, Martins R, et al. The effects of cardiorespiratory fitness on executive function and prefrontal oxygenation in older adults [J]. Geroscience. 2019;41(5):681–90.

    PubMed 
    PubMed Central 

    Google Scholar 

  • Agbangla NF, Audiffren M, Pylouster J et al. Working memory, cognitive load andcardiorespiratory fitness: testing the crunchmodel with Near-Infrared spectroscopy [J]. Brain Sci, 2019, 9(2).

  • First MB. Diagnostic and statistical manual of mental disorders, 5th edition, and clinical utility [J]. J nervous and mental disease. 2013;201(9):727–729.

  • Nasreddine ZS, Phillips NA, Bédirian V, et al. The Montreal cognitive assessment, moca: a brief screening tool for mild cognitive impairment [J]. J Am Geriatr Soc. 2005;53(4):695–9.

    PubMed 

    Google Scholar 

  • Balady GJ, Chaitman B, Driscoll D, et al. Recommendations for cardiovascular screening, staffing, and emergency policies at health/fitness facilities [J]. Circulation. 1998;97(22):2283–93.

    CAS 
    PubMed 

    Google Scholar 

  • Frost A, Moussaoui S, Kaur J et al. Is the n-back task a measure of unstructured working memory capacity? Towards understanding its connection to other working memory tasks [J]. Acta psychologica. 2021;219:103398.

  • Hoshi Y. Functional near-infrared optical imaging: utility and limitations in human brain mapping [J]. Psychophysiology. 2003;40(4):511–20.

    PubMed 

    Google Scholar 

  • Obrig H, Villringer A. Beyond the visible–imaging the human brain with light [J]. J Cereb Blood Flow Metabolism: Official J Int Soc Cereb Blood Flow Metabolism. 2003;23(1):1–18.

    Google Scholar 

  • Laguë-Beauvais M, Brunet J, Gagnon L, et al. A fNIRS investigation of switching and Inhibition during the modified Stroop task in younger and older adults [J]. NeuroImage. 2013;64:485–95.

    PubMed 

    Google Scholar 

  • Mcgrath R, Johnson N, Klawitter L et al. What are the association patterns between handgrip strength and adverse health conditions? A topical review [J]. SAGE open medicine. 2020;8:2050312120910358.

  • Draheim C, Hicks KL, Engle RW. Combining reaction time and accuracy: the relationship between working memory capacity and task switching as a case example [J]. Perspect Psychol Sci. 2016;11(1):133–55.

    PubMed 

    Google Scholar 

  • Cai Z, Wang X, Wang Q. Does muscle strength predict working memory? A cross-sectional fNIRS study in older adults [J]. Frontiers in aging neuroscience. 2023;15(1243283).

  • Gothe NP, Keswani RK, Mcauley E. Yoga practice improves executive function by attenuating stress levels [J]. Biol Psychol. 2016;121(Pt A):109–16.

    PubMed 

    Google Scholar 

  • Korman M, Weiss PL, Hochhauser M, et al. Effect of age on Spatial memory performance in real museum vs. computer simulation [J]. BMC Geriatr. 2019;19(1):165.

    PubMed 
    PubMed Central 

    Google Scholar 

  • Magosso E, Ricci G, Ursino M. Alpha and theta mechanisms operating in internal-external attention competition [J]. J Integr Neurosci. 2021;20(1):1–19.

    PubMed 

    Google Scholar 

  • Cabeza R, Locantore JK, Anderson ND. Lateralization of prefrontal activity during episodic memory retrieval: evidence for the production-monitoring hypothesis [J]. J Cogn Neurosci. 2003;15(2):249–59.

    PubMed 

    Google Scholar 

  • Cabeza R. Hemispheric asymmetry reduction in older adults: the HAROLD model [J]. Psychol Aging. 2002;17(1):85–100.

    PubMed 

    Google Scholar 

  • Andrews SC, Hoy KE, Enticott PG, et al. Improving working memory: the effect of combining cognitive activity and anodal transcranial direct current stimulation to the left dorsolateral prefrontal cortex [J]. Brain Stimul. 2011;4(2):84–9.

    PubMed 

    Google Scholar 

  • Li S, Cai Y, Liu J, et al. Dissociated roles of the parietal and frontal cortices in the scope and control of attention during visual working memory [J]. NeuroImage. 2017;149:210–9.

    PubMed 

    Google Scholar 

  • Mattay VS, Fera F, Tessitore A, et al. Neurophysiological correlates of age-related changes in working memory capacity [J]. Neurosci Lett. 2006;392(1–2):32–7.

    CAS 
    PubMed 

    Google Scholar 

  • Yeung MK, Sze SL, Woo J, et al. Reduced frontal activations at high working memory load in mild cognitive impairment: Near-Infrared spectroscopy [J]. Dement Geriatr Cogn Disord. 2016;42(5–6):278–96.

    PubMed 

    Google Scholar 

  • Yang D, Hong KS, Yoo SH et al. Evaluation of Neural Degeneration Biomarkers in the Prefrontal Cortex for Early Identification of Patients With Mild Cognitive Impairment: An fNIRS Study [J]. Front Hum Neurosci. 2019;13(317).

  • Shin J, Von Lühmann A, Kim DW et al. Simultaneous acquisition of EEG and NIRS during cognitive tasks for an open access dataset [J]. Scientific data. 2018;5(180003).

  • Veronese N, Stubbs B, Trevisan C, et al. What physical performance measures predict incident cognitive decline among intact older adults? A 4.4year follow up study [J]. Exp Gerontol. 2016;81:110–8.

    PubMed 

    Google Scholar 

  • Kwon YN, Yoon SS, Sarcopenia. Neurological point of view [J]. J Bone Metabolism. 2017;24(2):83–9.

  • Delbono O, Rodrigues ACZ, Bonilla HJ et al. The emerging role of the sympathetic nervous system in skeletal muscle motor innervation and sarcopenia [J]. Ageing research reviews. 2021;67(101305).

  • Rinne P, Hassan M, Fernandes C, et al. Motor dexterity and strength depend upon integrity of the attention-control system [J]. Proc Natl Acad Sci USA. 2018;115(3):E536–45.

    CAS 
    PubMed 

    Google Scholar 

  • Kilgour AH, Todd OM, Starr JM. A systematic review of the evidence that brain structure is related to muscle structure and their relationship to brain and muscle function in humans over the lifecourse [J]. BMC geriatrics. 2014;14(85).

  • Alfaro-Acha A, Al Snih S, Raji MA et al. Handgrip strength and cognitive decline in older Mexican Americans [J]. The journals of gerontology series A, biological sciences and medical sciences, 2006, 61(8): 859–65.

  • Filardi M, Barone R, Bramato G et al. The Relationship Between Muscle Strength and Cognitive Performance Across Alzheimer’s Disease Clinical Continuum [J]. Frontiers in neurology. 2022;13(833087).

  • Firth J, Stubbs B, Vancampfort D, et al. Grip strength is associated with cognitive performance in schizophrenia and the general population: A UK biobank study of 476559 participants [J]. Schizophr Bull. 2018;44(4):728–36.

    PubMed 
    PubMed Central 

    Google Scholar 

  • Firth J, Firth JA, Stubbs B, et al. Association between muscular strength and cognition in people with major depression or bipolar disorder and healthy controls [J]. JAMA Psychiatry. 2018;75(7):740–6.

    PubMed 
    PubMed Central 

    Google Scholar 

  • Richardson JK, Ellmers TJ. The relationship between clinical measures of cognitive function and grip strength in healthy older adults [J]. BMC Geriatr. 2022;22(1):907.

    PubMed 
    PubMed Central 

    Google Scholar 

  • Tao L, Wang X, Gao S, et al. Longitudinal relationships between grip strength, subjective memory complaints and cognitive function among middle-aged and older adults in China [J]. Aging Clin Exp Res. 2023;35(10):2101–8.

    PubMed 

    Google Scholar 

  • Yang J, Deng Y, Yan H, et al. Association between grip strength and cognitive function in US older adults of NHANES 2011–2014 [J]. J Alzheimer’s Disease: JAD. 2022;89(2):427–36.

    Google Scholar 

  • Makizako H, Shimada H, Doi T, et al. Six-minute walking distance correlated with memory and brain volume in older adults with mild cognitive impairment: a voxel-based morphometry study [J]. Dement Geriatric Cogn Disorders Extra. 2013;3(1):223–32.

    Google Scholar 

  • Giannitsi S, Bougiakli M, Bechlioulis A et al. 6-minute walking test: a useful tool in the management of heart failure patients [J]. Therapeutic advances in cardiovascular disease. 2019;13:1753944719870084.

  • Gabrielle Dupuy E, Besnier F, Gagnon C, et al. Cardiorespiratory fitness moderates the Age-Related association between executive functioning and mobility: evidence from remote assessments [J]. Innov Aging. 2023;7(1):igac077.

    Google Scholar 

  • Dai TH, Liu JZ, Sahgal V, et al. Relationship between muscle output and functional MRI-measured brain activation [J]. Exp Brain Res. 2001;140(3):290–300.

    CAS 
    PubMed 

    Google Scholar 

  • Herold F, Törpel A, Schega L et al. Functional and/or structural brain changes in response to resistance exercises and resistance training lead to cognitive improvements – a systematic review [J]. European review of aging and physical activity: official journal of the European Group for Research into Elderly and Physical Activity. 2019:16:10.

  • Hyodo K, Dan I, Kyutoku Y, et al. The association between aerobic fitness and cognitive function in older men mediated by frontal lateralization [J]. NeuroImage. 2016;125:291–300.

    PubMed 

    Google Scholar 

  • Qi L, Wang GL, Yang YL et al. Positive effects of brisk walking and Tai Chi on cognitive function in older adults: An fNIRS study [J]. Physiology & behavior. 2024;273:114390.

  • Hyodo K, Dan I, Suwabe K, et al. Acute moderate exercise enhances compensatory brain activation in older adults [J]. Neurobiol Aging. 2012;33(11):2621–32.

    PubMed 

    Google Scholar 

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  • Association between the American heart association’s life’s essential 8 score and cognitive function: a cross-sectional NHANES study | BMC Geriatrics

    Association between the American heart association’s life’s essential 8 score and cognitive function: a cross-sectional NHANES study | BMC Geriatrics

    Study population

    This cross-sectional study recruited participants from NHANES 2011–2012 and 2013–2014 (https://www.cdc.gov/nchs/nhanes/index.htm). NHANES is a public health survey program conducted by National Center for Health Statistics (NCHS) in America. The NHANES project recruits participants using a complex, multistage probabilistic sampling design in two-year cycles. NHANES collects information from questionnaires at home, physical and laboratory examinations in mobile examination center (MEC) and telephone interviews. In this study, samples from NHANES 2011–2012 and 2013–2014 were obtained and combined because NHANES project provided the outcome of several cognitive test in these two cycles specifically. There were totally 19,931 participants in these two cycles. Our study implemented a three-stage exclusion protocol: (1) Primary exclusion of 16,530 participants based on age criterion (< 60 years), (2) subsequent removal of 478 cases with incomplete cognitive assessments or missing subjective cognitive questionnaires, followed by (3) elimination of 1,947 individuals lacking essential metrics for LE8 calculation. Finally, we get 976 eligible participants. (Supplement Fig. 5)

    Measurement of LE8 score

    LE8 scoring system is comprised of 8 metrics including 4 behavioral metrics (diet, physical activity frequency and duration, nicotine exposure and sleeping) and 4 biological metrics (blood lipids, blood glucose, blood pressure and BMI score) (Supplement Table 1) [7]. Total LE8 score is the average score of above 8 metrics which range from 0 to 100 with higher score indicate healthier cardiovascular condition. In our study, LE8 score was further classified by quartile into 4 groups named Q1, Q2, Q3 and Q4 with Q1 as reference category.

    Table 1 Baseline characteristic of covariables according to LE8 score quartile

    Of the 8 metrics, diet score was assessed according to Healthy Eating Index 2015 (HEI-2015). NHANES collects dietary data with two 24-hour recalls interviews, one is conducted in person in MEC while the other is on telephone several days later. Researchers are able to calculate the dietary intake of participants by combining 24-hour food intake files from NHANES and food patterns equivalents data from United States Department of Agriculture (USDA) (https://www.ars.usda.gov/northeast-area/beltsville-md-bhnrc/beltsville-human-nutrition-research-center/food-surveys-research-group/docs/fped-data-tables/). HEI score includes 13 components of 2 classifications: 9 adequacy components and 4 moderation components. Scoring of dietary components is based on energy density which represents the amount of food components per 1000kcal (Supplement Table 2). Self-report questionnaires from NHANES provides information about physical activity intensity, cigarette smoking behaviors, sleeping duration, diabetes history and medication usage. As for the data of BMI, blood pressure, blood lipid and hemoglobin A1c, blood samples are obtained in MEC and then processed, stored, and transported to laboratories for test. The height and weight used to calculate BMI were measured in the MCE. The full test includes three measurements of both systolic and diastolic blood pressure. When data from all three measurements were available, the average systolic and diastolic blood pressure were calculated. If the full set of three measurements was not available, the average was computed using as many measurements as were available.

    Table 2 Weighted coefficients and confidence interval of LE8 score for cognitive test score

    Measurement of cognitive test score and subjective cognitive performance

    NHANES conducted three widely utilized [11,12,13] cognitive tests for participants aged > 60 years in the cycle of 2011–2012 and 2013–2014. First, the word learning and recall modules from the Consortium to Establish a Registry for Alzheimer’s disease (CERAD test) was conducted to assess immediate and delayed learning ability for new verbal information. The test comprises three sequential learning trials followed by delayed recall. During each trial, participants verbally articulate 10 randomly ordered unrelated words presented sequentially, followed by immediate free recall, with word sequence randomization repeated across trials to minimize order effects. A maximum score of 10 per trial is attainable based on correct item retrieval. Second, the Animal Fluency test (AFT) was performed for assessing the executive function where participants are asked to name as many animals as possible in one minute and one point is given for each named animal. Third, Digit Symbol Substitution test (DSST) was conducted which depend on the rapid processing of information, maintaining attention, and retrieving working memory. Participants are provided with a paper which contains 9 numbers with paired symbols, then they are asked to fulfill 133 boxes nearby the numbers with corresponding symbols as much as possible in 2 min. One point is given for one correct match. In this study, we calculated z-score [(individual test score – mean)/standard deviation] of immediate CERAD test, recall CERAD test, AFT test and DSST test respectively. The total cognitive test score refers to the average of above four z-scores [14]. Higher cognitive test score indicates better cognitive function. Participants who reported “being limited in any way because of difficulty remembering or because experience periods of confusion” were defined as having subjective cognitive performance. Participants were defined as having subjective cognitive performance if the participant answered “yes” to the question: “being limited in any way because of difficulty remembering or because experience periods of confusion”.

    Assessment of other covariables

    We included variables of demographic characteristics and health behaviors that are possibly associated with cognitive function [15], including age (continuous variables), sex (male, female), race (non-Hispanic White, non-Hispanic Black, other Hispanic, other race), education level (college graduate or above, some college or associate degree, high school/GED or less ), the ratio of family income to poverty guideline (< 1.3, 1.3–3.5, > 3.5 ) [16] and alcohol consumption (drinker, non-drinker). Alcohol drinker was defined as those who had at least 12 alcohol drinks a year [17].

    Statistical analysis

    NHANES selected participants with a complex multistage probabilistic sampling design thus all analysis in this study were weighted with provided weight variables: WTDRD1, SDMVPSU and SDMVSTRA. Since we combined the 2011–2012 and 2013–2014 cycle, the weights of the combined study population were calculated as 1/2* WTDRD1 (https://wwwn.cdc.gov/nchs/nhanes/tutorials/module3.aspx).

    Initially, we inspected the characteristic of the study population across four quartiles of LE8 score. After examined the normality of variables’ distribution and the homogeneity of variance, continuous variables were described with mean and standard deviation [mean (SD)] and compare with Wilcoxon rank-sum test while categorized variables were described as the case amount and its percentage [n (%)] and compared with chi-squared test. Afterwards univariable regression (linear regression for cognitive test score, logistic regression for subjective cognitive performance) was conducted to select covariables that were significantly associated with cognitive performance.

    Cognitive performance models

    We constructed three regression models to explore the association between LE8 score and cognitive performance, both as continuous variables and categorized variables. Model 1 wasn’t adjusted. Model 2 was adjusted for age, gender, and race. Model 3 was adjusted for age, gender, race, family income, education, and alcohol consumption. We also applied restricted cubic spline (RCS) models to explore the dose-response relationship in the above three models. The 5th, 35th, 65th, and 95th percentiles of the total LE8 score distribution were chosen as the knots of the RCS curves [18]. The R² (coefficient of determination) metrics were derived from our multivariable linear regression Model3 (Supplement Fig. 6). The P– non-linear value of RCS was obtained using a likelihood ratio test (LRT) to assess whether the higher-order coefficients of RCS curve are significantly different from zero. This test was conducted using the rms package in R.

    Subjective cognitive performance models

    We explored the effect of individual LE8 metrics on cognitive performance in a full-adjusted multivariable regression model. In order to validate the reliability of regression model, Receiver Operating Characteristic (ROC) curves of LE8 (both categorized and continuous) were plotted (Supplement Fig. 6). To assess the predictive capacity of LE8 for subjective cognitive performance, we compared the ROC curves of LE8 in relation to cognitive test scores and subjective cognitive performance. For the ROC analysis, cognitive test score was converted into a binary variable according to the lower quartile.

    Subgroup models

    To identify the subpopulation that benefits most from elevating LE8 score, the study population was stratified by all the variables in Model 3. We then calculated the regression coefficients of LE8 score in different subgroups. P values for interaction were calculated using likelihood ratio tests.

    Cross-validation analysis

    We made stratified ten-fold cross-validation with ten independent repetitions (10 × 10 CV) on both the objective cognitive testing and subjective cognitive assessment datasets. Model performance was quantified using R², providing robust measurement of predictive consistency and variance explicability (Supplement Table 6).

    All statistical tests were two-tailed and conducted with R v. 4.2.1 statistical analysis software. Adobe Illustrator v2023 was used for figure preparation. P < 0.05 was considered statistically significant.

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  • Preventing obesity with an immune-altering gut microbe

    Preventing obesity with an immune-altering gut microbe

    The gut bacteria has potential to become a probiotic or postbiotic to treat obesity and metabolic diseases.

    Credit: iStock.com/Artur Plawgo

    The understudied human gut bacteria P. faecium  counteracted weight gain in mice by reducing inflammation, revealing a potential new way to treat obesity.

    The human gut serves as an intersection point for many processes — digesting food, absorbing nutrients, supporting immunity, and regulating metabolism — that all interact with a vital and dynamic ecosystem: the gut microbiome. 

    What the body absorbs depends on how the intestines — and the microbes living there — break down food, said Nicola Segata, a computational microbiologist at the University of Trento. “There is a clear link between our diet and the composition of our gut microbiome,” he said. 

    Yolanda Sanz first became interested in P. faecium after finding that this bacterium was increased in children with normal weight gain.

    Credit: Yolanda Sanz

    Researchers have found that changes in the gut microbiome are associated with increased risk of obesity. However, “what is still unclear is which are the main biomarkers or microbiome signatures that consistently are linked with obesity,” said Yolanda Sanz, a microbiologist at the Institute of Agrochemistry and Food Technology, Spanish National Research Council (IATA-CSIC).

    In a study published in 2018, Sanz and her colleagues noticed that children who went on to experience excessive weight gain in a four-year period had different microbiomes prior to their weight gain than children who gained a normal amount of weight (1). During this longitudinal study, they found that the bacterial species Phascolarctobacterium faecium  was enriched in children with normal weight gains compared to those who gained excessive weight. This microbe “has long been known to be a regular commensal or inhabitant of our gut microbiome, but we didn’t know much about its role, its function, [or] its significance in our gut,” said Ravinder Nagpal, a microbiologist at Florida State University.

    To dig deeper into the role of this bacterium in obesity, Sanz, Segata, and their labs turned to 7,529 human metagenomic samples to document what microbes are present in the gut of people with and without obesity (2). In a new study, they reported that Pfaecium  is associated with non-obesity and that it acted via an innate immune pathway to counteract metabolic changes associated with obesity (3). This microbe could provide a new path to treating obesity.

    To determine this bacterial species’ potential role in obesity, the researchers fed mice a high fat and sugar diet, while giving control mice a low fat and sugar diet. Without intervention, mice on the high-fat, high-sugar diet gained more weight than control mice. However, when the researchers treated these mice with P. faecium, it limited the mice’s weight and body fat increases and improved glucose clearance.

    Mice on the high-fat, high-sugar diet exhibited an increased amount of pro-inflammatory macrophages in the intestines and had higher levels of intestinal type 1 innate lymphoid cells, which are cells involved in many inflammatory disorders (4). The addition of P. faecium  mitigated these changes by boosting the levels of anti-inflammatory macrophages called M2 macrophages and reducing the increase in type 1 innate lymphoid cells. When the team used a small molecule inhibitor to block macrophages from adopting the M2 phenotype, P. faecium’s positive effects disappeared. These results demonstrate that P. faecium’s anti-obesogenic effect occurs by modulating the immune system.

    In the future, it’s possible that P. faecium  could be developed as a probiotic, said Nagpal, who was not associated with the study. He added that in the mouse model, the microbe “effectively showed promise as a therapeutic or preventative.”

    A group of laboratory researchers stand outside on the grass.

    Yolanda Sanz’s research group studies the role of the microbiome in nutrition and health.

    Credit: Yolanda Sanz

    Beyond probiotics, there’s also potential for this bacterium to act as a postbiotic, which are components released from living or dead microorganisms that have health benefits. The researchers found that both living and pasteurized P. faecium  reduced the pro-inflammatory immune response associated with an obesogenic diet. Sanz explained that they still see this effect for pasteurized bacteria possibly because the immune system could be responding to a structural component of P. faecium’s cell wall. Previous work from another team found that the gut commensal Akkermansia muciniphila  had an effect on metabolism and obesity whether it was alive or not (5). In particular, since P. faecium  is anaerobic, Sanz added that it would be easier to develop it as a postbiotic rather than a probiotic as keeping the bacteria alive during manufacturing is challenging due to oxygen exposure.

    Since the bacteria reduce inflammation, Sanz added that P. faecium  has potential applications beyond metabolic disorders and in other conditions where inflammation has a role.

    “The results are quite promising,” said Sanz. “We hope that, in the end, we can progress towards performing clinical trials and getting evidence from humans.”

    References

    1. Rampelli, S. et al.  Pre-obese children’s dysbiotic gut microbiome and unhealthy diets may predict the development of obesity. Commun Biol  1, 222 (2018).
    2. Pasolli, E. et al.  Accessible, curated metagenomic data through ExperimentHub. Nat Methods  14, 1023–1024 (2017).
    3. Liébana-García, R. et al.  Gut commensal Phascolarctobacterium faecium retunes innate immunity to mitigate obesity and metabolic disease in mice. Nat Microbiol  10, 1310-1322 (2025).
    4. Ebbo, M. et al.  Innate lymphoid cells: major players in inflammatory diseases. Nat Rev Immunol  17, 665–678 (2017).
    5. Plovier, H. et al.  A purified membrane protein from Akkermansia muciniphila or the pasteurized bacterium improves metabolism in obese and diabetic mice. Nat Med  23, 107–113 (2017).

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  • Neurosurgeon explains how ‘brain health is pretty easy to achieve’, reveals foods to eat: Dark chocolate, fish, broccoli | Health

    Neurosurgeon explains how ‘brain health is pretty easy to achieve’, reveals foods to eat: Dark chocolate, fish, broccoli | Health

    Take it from a brain surgeon, brain health is one of the most important things to living a quality life: US-based neurosurgeon Dr Brian Hoeflinger said in a March 23 Instagram post. According to him, food plays a significant role in supporting brain health. In the video he shared, Dr Hoeflinger explained ‘how to maintain a healthy brain’, highlighting some amazing brain-boosting foods. Also read | Want to keep your brain sharp? Add these 6 foods to your diet and know their benefits

    Food plays a significant role in supporting brain health. A balanced diet rich in nutrients can help improve cognitive function, boost memory, and reduce the risk of age-related cognitive decline. (Freepik)

    What’s the secret to achieving a healthy brain?

    According to him, incorporating these foods into your diet can have a positive impact on brain health and overall well-being. From fish that are rich in omega-3 fatty acids, and support brain health and cognitive function, to green vegetables that are packed with vitamins and antioxidants that support cognitive function and may reduce age-related cognitive decline, here’s what Dr Hoeflinger suggested.

    He said, “Brain health is super important and is pretty easy to achieve by knowing this: it starts with food. There are fatty fish, including salmon and tuna. There are also green leafy vegetables, like kale, spinach, and broccoli, and berries like strawberries, raspberries, and blueberries. Then there are nuts and seeds like almonds and walnuts, flaxseeds and chia seeds, eggs, and avocados.”

    A little bit of dark chocolate is good for your brain

    He said that even healthy oils are good, and added that green tea, which contains antioxidants and L-theanine, and may improve focus and reduce stress, as well as dark chocolate, which contains flavonoids, and may improve blood flow and boost cognitive function, are an important part of a brain health-friendly diet.

    Dr Hoeflinger said, “Green tea is healthy for your brain, and lastly, a little bit of dark chocolate can be very beneficial for your brain. The foods you eat are just one aspect of keeping a healthy brain. There are so many other things that you can do.”

    Note to readers: This article is for informational purposes only and not a substitute for professional medical advice. Always seek the advice of your doctor with any questions about a medical condition.

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  • Mpox epidemic is straining African health systems after US aid cuts – Financial Times

    Mpox epidemic is straining African health systems after US aid cuts – Financial Times

    1. Mpox epidemic is straining African health systems after US aid cuts  Financial Times
    2. Multi-country outbreak of mpox, External situation report #54 – 27 June 2025  World Health Organization (WHO)
    3. AHF Urges Vaccine Equity as Mpox Cases Surge in Sierra Leone  AIDS Healthcare Foundation
    4. Health officials encouraged by recent trends in Africa’s mpox outbreaks  CIDRAP
    5. Mpox Surge in Sierra Leone: A Stress Test for National Readiness  Think Global Health

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