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Tag: Body Mass Index

  • Research identifies optimal body weight to reduce cardiovascular risk in diabetes patients

    Research identifies optimal body weight to reduce cardiovascular risk in diabetes patients

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    New research being presented at this year’s European Congress on Obesity (ECO) in Venice, Italy (12-15 May), identifies the optimum body weight range for adults with type 2 diabetes to minimize their risk of dying from any cardiovascular disease, including heart failure, heart disease, stroke, and chronic kidney disease.

    The findings, based on health data from the UK Biobank, indicate that for adults aged 65 years or younger, maintaining a body mass index (BMI) within the normal range of 23–25 kg/m² was associated with the lowest risk of dying from cardiovascular disease. But for those over 65 years old, being moderately overweight with a BMI of 26–28 kg/m², had the lowest risk.

    Maintaining a healthy weight is crucial for reducing the risk of cardiovascular diseases, particularly for people with type 2 diabetes who are predisposed to cardiovascular disease and death. However, it’s not clear whether the optimal BMI range for people with type 2 diabetes varies by age.

    To plug these knowledge gaps, researchers explored the age differences in the association between BMI and risk of cardiovascular death in 22,874 UK Biobank participants with a previous diagnosis of type 2 diabetes at the time they enrolled between 2006 and 2010. Patients with prior cardiovascular diseases were not excluded.

    The average age of all the participants was 59 years, and around 59% were women. Their cardiovascular health was tracked, using linked health records, for nearly 13 years during which time 891 participants died from cardiovascular diseases.

    Researchers analyzed data in two age groups-;the elderly (over 65 years) and the middle-aged (age 65 years or younger)-;and assessed the relationship between variables such as BMI, waist circumference, and waist-to-height ratio and the risk of cardiovascular death.

    The optimal BMI cut-off point was also calculated in different age groups and the findings were adjusted for traditional cardiometabolic risk factors and other factors associated with adverse cardiovascular outcomes including age, sex, smoking history, alcohol consumption, level of physical exercise, and history of cardiovascular diseases.

    The analyses found that in the middle-aged group, having a BMI in the overweight range range (25 kg/m² to 29.9 kg/m²) was associated with a 13% greater risk of dying from cardiovascular disease than those with a BMI in the normal range (less than 25.0 kg/m²).

    However, in the elderly group, having a BMI in the overweight range (25 kg/m² to 29.9 kg/m²) was associated with an 18% lower risk of dying compared to having a BMI in the normal range (less than 25.0 kg/m²).

    The relationship between BMI and cardiovascular death risk exhibited a U-shaped pattern, even after stratification by age, so the optimal BMI cut-off point was different in the elderly and middle-aged groups. For the middle-aged group, the optimal BMI cut-off was 24 kg/m², whereas for the elderly group, it was 27 kg/m². Consequently, personalized treatment plans can be developed in clinical settings by tailoring recommendations to different age groups.

    The researchers also found a positive relationship between both waist circumference and waist-to-height ratio and the risk of cardiovascular death. As waist circumference increased, the risk of cardiovascular death also showed a corresponding rise. When the study population was divided into older and middle-aged categories, this upward trend remained consistent. Similar patterns were observed for the waist-to-height ratio. However, no significant BMI cut-off point was identified.

    Importantly, we demonstrate that optimal BMI for people with type 2 diabetes varies by age, independent of traditional cardiometabolic risk factors. Our findings suggest that for older individuals who are moderately overweight but not obese, maintaining rather than losing weight may be a more practical way of reducing their risk of dying from cardiovascular disease.”

    Dr Shaoyong Xu, lead author from Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, China

    He adds, “Our findings also indicate that adiposity may offer some protection against fatal diseases to some extent. The possible biological mechanisms that explain this ‘obesity survival paradox’ in elderly people may be associated with a lower rate of bone mass loss, which reduces the effects of fall and trauma episodes, and greater nutritional reserves to accommodate periods of acute stress.”

    The authors say that in the future, measures of central obesity, such as waist circumference, would be used to further refine the risk.

    This is an observational study, and as such, can’t establish cause. And the researchers acknowledge various limitations to their findings, including small numbers of cardiovascular deaths and no information on type of cardiovascular disease or specific treatments. They also note that most of the UK Biobank study participants are White, so the findings might not apply to people of other ethnic backgrounds. Also, the nature of the cohort study may create potential classification errors that could partially affect the conclusions, because anthropometric measurements were only assessed at the start of the study, and body weight may change during the follow-up period.

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  • Study reveals obesity’s link to increased risk of multiple sclerosis and ischemic stroke

    Study reveals obesity’s link to increased risk of multiple sclerosis and ischemic stroke

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    In a recent study published in Scientific Reports, researchers from China used Mendelian randomization (MR) to assess the genetic relationship between body mass index (BMI) and multiple neurological diseases.

    They found that BMI shows a genetic causal relationship with multiple sclerosis (MS) and ischemic stroke (IS), but not with Parkinson’s disease (PD), Alzheimer’s disease (AD), amyotrophic lateral sclerosis (ALS), and epilepsy (EP).

    Study: Genetic causal role of body mass index in multiple neurological diseases. Image Credit: New Africa/Shutterstock.comStudy: Genetic causal role of body mass index in multiple neurological diseases. Image Credit: New Africa/Shutterstock.com

    Background

    BMI is widely used for obesity assessment owing to its simplicity and sensitivity. Economic changes and lifestyle shifts have increased obesity risk globally. Elevated BMI is linked to various diseases and higher mortality rates, including type 2 diabetes, hypertension, coronary heart disease, musculoskeletal disorders, and neoplastic growth.

    Neurological diseases cover a broad spectrum of nervous system conditions, including neurodegenerative, cerebrovascular, infectious, oncological, and hereditary disorders.

    While PD is characterized by dopamine concentration changes and Lewy body presence, AD is linked to β-amyloid deposition and tau protein phosphorylation. ALS affects motor neurons, while MS is a demyelinating disease mediated by the immune system.

    IS is associated with various risk factors like hypertension and diabetes, and EP arises from synchronized neuronal discharges due to genetic or structural abnormalities.

    MR is a method to assess causal relationships between exposures and outcomes using genetic instrumental variables, including single nucleotide polymorphisms (SNPs). The method is robust against the effects of confounders and reverse causation.

    Therefore, researchers in the present study investigated the genetic links between BMI and neurological diseases using MR analysis, aiming to inform disease management strategies.

    About the study

    The present study used SNPs from a genome-wide association study (GWAS) dataset as instrumental variables to explore genetic causality between exposure and outcome factors.

    The study followed stringent criteria for MR studies, ensuring robust correlations between instrumental variables and exposure factors while controlling for potential confounders.

    Data on BMI indicators were obtained from the Integrative Epidemiology Unit (IEU) database, comprising nearly one million participants of European ancestry, with measurements for over seven million SNPs.

    Data for various neurological diseases were sourced from the IEU database, including PD, AD, MS, ALS, IS, EP cases, and respective control groups.

    The participants were predominantly of European origin, except for ALS and EP, which comprised individuals of multiple races and regions.

    Quality control procedures were implemented for all disease data. SNPs significantly associated with BMI were subjected to cluster analysis to exclude redundant effects. SNPs causally linked to PD, AD, MS, ALS, IS, EP, and those related to disease confounders were excluded.

    Two-sample MR analysis was employed, with inverse variance weighting (IVW) as the primary analytical approach, supported by weighted median, MR Egger, simple mode, and weighted mode. Further, the sensitivity analysis employed the MR-Egger method, Cochran Q test, and leave-one-out method to assess horizontal pleiotropy, heterogeneity, and robustness of the causal relationship between BMI indicators and neurological diseases.

    Results and discussion

    As per the study, significant genome-wide associations were found between BMI indicators and SNPs for PD (42), AD (42), MS (39), ALS (42), IS (42), and EP (31). The IVW analysis showed no genetic causality between BMI and PD, AD, ALS, and epilepsy (P > 0.05).

    However, a positive genetic causality was found between BMI and MS (P = 0.035) and IS (P = 0.000). The findings suggest that a higher BMI is associated with increased risk for MS and IS.

    Further, the weighted median analysis showed causal relationships between BMI and MS, IS, while the simple mode suggested a relationship with IS alone. Interestingly, MR Egger and weighted mode analyses showed no causal relationship between BMI and the studied diseases.

    Results of the sensitivity analysis corroborated with the main findings. No significant heterogeneity or pleiotropy was found, and the findings were confirmed to be stable and reliable.

    The findings are strengthened with the use of robust instrumental SNPs derived from the most comprehensive GWAS database so far.

    However, the study is limited by its focus on patients of European ancestry, potential incomplete control of all neurological disorder risk factors, and reliance solely on BMI, without considering other body composition metrics.

    Future studies involving waist circumference, waist-to-hip ratio, body fat percentage, and bioelectrical impedance could potentially reduce the bias in the results.

    Conclusion

    In conclusion, the study demonstrates MR analysis’s utility in exploring genetic causal links between BMI and neurological diseases.

    While no causal relationship was found with PD, AD, ALS, or EP, a genetic causal association of BMI was identified with MS and IS, suggesting that an increased BMI may increase the risk of MS and IS.

    These findings highlight obesity’s potential role as a risk factor in neurological disorders, paving the way for prevention and treatment strategies for improved health outcomes.

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  • Study finds genetics influence effectiveness

    Study finds genetics influence effectiveness

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    In a recent study published in the journal JAMA Network Open, researchers investigated the role of genetic risk in physical activity interventions against incident obesity (body mass index [BMI] >30). Their dataset included clinical, genetic, and physical activity data from a large retrospective sample cohort comprising more than 3,000 All of Us Research Program (AoURP) participants. Their findings reveal that daily step count and BMI polygenic risk score (PRS) are both independently associated with incident obesity risk. Notably, engaging in physical activity is shown to mitigate obesity incidence and risk effectively. Importantly, however, the degree of physical activity (measured herein as participants’ mean daily step count) required to reverse incident obesity varied substantially based on the participant’s genetic PRS.

    Study: Physical Activity and Incident Obesity Across the Spectrum of Genetic Risk for Obesity. Image Credit: Amani A / ShutterstockStudy: Physical Activity and Incident Obesity Across the Spectrum of Genetic Risk for Obesity. Image Credit: Amani A / Shutterstock

    This study provides the first evidence that genetic obesity risk is not a deterministic trait but can instead be overcome by altering (generally increasing) physical activity levels. It highlights the need for clinicians to consider genetic history when designing intervention action plans against the condition, suggesting that future treatment against incident obesity may be tailored to the patient under care as opposed to the current “one size fits all” approach.

    The dangers of obesity and the impact of genetics

    Obesity is a medical condition wherein the body accumulates excess fat reserves, usually accompanied by adverse health effects. The global collective impact of obesity is so medically significant that the World Health Organization labeled obesity the ‘greatest threat to the health of the Westernized world’ more than 20 years ago (2000). In the United States of America (US) alone, the condition is reported as being responsible for more than 400,000 deaths per year, with a staggering 40% of the adult population coping with the disease. Alarmingly, despite global efforts aimed at curbing disease prevalence, the global burden of obesity continues to rise unabated annually,

    Encouragingly, obesity represents an entirely modifiable and reversible condition, with diet, physical exercise, and, in extreme cases, pharmacotherapy proving effective in disease management. Physical exercise is the most often recommended intervention against obesity. The recent rise in fitness tracker popularity has seemingly bolstered the effectiveness of this intervention, with these smart devices providing clinicians and policymakers with a relatively accurate and objective means of monitoring activity levels and their impacts on disease progression.

    While current medical recommendations suggest a ballpark of 8,000 daily steps as adequate for mitigating incident obesity (body mass index [BMI] >30), these estimates do not account for dietary (caloric) intake or the patient’s genetics, likely resulting in a step count underestimate based on the interplay between these factors. Genetics, in particular, is assumed to play a significant role in obesity risk and progression, with previous research estimating between 40-70% heritability. While genetic evaluations into obesity outcomes do exist, most use outdated methodology, small sample sizes, or short (<7 days) study durations, thereby confounding results and reducing overall accuracy in obesity intervention estimates.

    A large cohort and long-term study investigating the association between patients’ genetic predisposition to incident obesity and the impacts of varying step counts (physical activity) accounting for this predisposition would allow for the development of novel, patient-specific intervention action plans, hypothesized to substantially improve obesity outcomes and reduce disease burden compared to current traditional interventions.

    About the study

    The present study aims to use a retrospective longitudinal activity monitoring methodology in tandem with genome sequencing data to evaluate and quantify the compounded genetic risk for BMI and physical activity against the risk of incident obesity. The study complies with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline. It comprises participants enrolled in the All of Us Research Program (AoURP), specifically the AoURP Controlled Tier dataset (ver. 7). It includes sociodemographic, medical, and anthropometric data from participants volunteering between May 1, 2018, and July 1, 2022.

    Data generation was comprised of activity monitoring (fitness tracker output; daily step count), genetic risk assessments (polygenic risk score [PRS]) obtained from a large-scale, BMI-centric genome-wide association study (GWAS), and obesity evaluations (BMI – weight in kg divided by height in m2). Of these, the former (step count) was obtained from consenting patients who linked their wearable records to the AoURP database, allowing for analyses of data even prior to study initiation.

    “Consistent with our prior data curation approach, days with less than 10 hours of wear time, less than 100 steps, or greater than 45 000 steps or for which the participant was younger than 18 years were removed. For time-varying analyses, mean daily steps were calculated on a monthly basis for each participant. Months with fewer than 15 valid days of monitoring were removed. Because the existing PRS models have limited transferability across ancestry groups and to ensure appropriate power of the subsequent PRS analysis, we limited our analysis to the populations who had a sample size of greater than 500, resulting in 5964 participants of European ancestry with 5 515 802 common SNVs for analysis.”

    Genomic analyses were filtered to only account for biallelic, autosomal single-nucleotide variants (SNVs), following which identified SNVs were further pruned based on their Hardy-Weinberg equilibrium P value (cutoff >1.0 × 10−15). Estimated ancestral populations were then used to assign participants into one of six ethnic groups (Admixed American, African, European, Middle Eastern, East- and South-Asian). PLINK, version 1.9 (Harvard University), was used to generate principle components deriving from generated SNVs and a European ancestry linkage disequilibrium reference panel (1000 Genomes Project phase 3).

    Finally, the clinical differences between identified PRS quartiles were computed using Wilcoxon rank sums and the Kruskal-Wallis test (continuous variables) or the Pearson χ2 test (categorical variables). Associations between daily step count (physical activity), PRS (genetics), and time to event for obesity (outcomes) were computed using Cox proportional hazards regression models. These models were corrected for medical and anthropometric factors, including age, sex, cancer status, cardiovascular health, education levels, and alcohol/drug use/dependency.

    Study findings and conclusions

    Of the 5,964 participants of European ancestry enrolled in the AoURP study, 3,124 were found to be free of obesity at the study baseline and further provided completed activity and genome data, thereby being included in downstream data analyses. An overwhelming majority of participants were found to be White (N = 2958; 95%) and female (N = 2216; 73%). Participants’ mean age was found to be 52.7 years, with participants providing, on average, 5.4 years of follow-up data. When modeling obesity risk stratified by PRS percentile, the association between PRS and obesity was observed to be linear and direct, with PRS and daily steps independently associated with incident obesity risk and progression.

    “Individuals with a PRS at the 75th percentile would need to walk a mean of 2280 (95% CI, 1680-3310) more steps per day (11 020 total) than those at the 50th percentile to reduce the HR for obesity to 1.00 (Figure 1). Conversely, those in the 25th percentile PRS could reach an HR of 1.00 by walking a mean of 3660 (95% CI, 2180-8740) fewer steps than those at the 50th percentile PRS. When assuming a median daily step count of 8740 (cohort median), those in the 75th percentile PRS had an HR for obesity of 1.33 (95% CI, 1.25-1.41), whereas those at the 25th percentile PRS had an obesity HR of 0.74 (95% CI, 0.69-0.79).”

    This study highlights the profound impact of PRS (genetics) on obesity risk and outcomes and establishes the importance of personalized interventions and genetic evaluations in future treatment of this disease. Unlikely previously assumed, not only is 8,000 steps daily too vague an estimate for obesity correction, but the number of required steps generally increases (but may also decrease) given the unique genetic makeup of the patient in question.

    “These results have important clinical and public health implications and may offer a novel strategy for addressing the obesity epidemic by informing activity recommendations that incorporate genetic information.”

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  • Shared eating habits of couples impact pregnancy weight gain, study suggests

    Shared eating habits of couples impact pregnancy weight gain, study suggests

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    In a recent article published in the journal Nutrients, researchers assessed how gestational weight gain (GWG) is associated with the eating behaviors of pregnant people and their non-pregnant partners through a cohort study in the United States.

    Their results indicate that poor cognitive restraint was associated with higher GWG, suggesting that restrained eating by couples could reduce GWG and, therefore, the risk of infant macrosomia, cesarean section, pre-eclampsia, and gestational diabetes mellitus (GDM).

    Study: Healthful Eating Behaviors among Couples Contribute to Lower Gestational Weight Gain. Image Credit: El Nariz / ShutterstockStudy: Healthful Eating Behaviors among Couples Contribute to Lower Gestational Weight Gain. Image Credit: El Nariz / Shutterstock

    Background

    Excess GWG is associated with increased risks of infant macrosomia, pre-eclampsia, cesarean section, and GDM. It is also associated with pre-gravid body mass index (BMI), and diet-centric interventions during pregnancy are effective in reducing GWG.

    Though pregnancy is often associated with eating and snacking more, less is known about what eating behaviors may contribute to excess GWG. The influence of the eating habits of the non-pregnant partner has also not been studied.

    About the study

    In this study, researchers theorized that the non-pregnant partner can influence household food consumption and encourage healthy eating attitudes and food habits during pregnancy.

    They hypothesized that the couple’s behaviors would be most strongly linked with GWG, followed by the pregnant person’s behaviors alone. They expected to see the weakest association between the non-pregnant person’s behaviors and GWG.

    Pregnant people included in the study had a BMI between 18.5 and 35, were over 21 years old, had only one other child, and were either planning their pregnancy or had a gestational age of under 10 weeks.

    People receiving fertility treatments, with existing medical conditions, taking medications such as insulin, which could influence fetal growth, drinking alcohol, or smoking during pregnancy were excluded.

    Demographic factors such as marital status, age, ethnicity and race, individual income, and educational attainment were included. The pregnant person’s weight and GWG were measured during the first and third trimesters, while the partner’s weight was measured once. Weight and height were used to calculate the BMI, while GWG was classified as normal, overweight, or obese.

    An eating inventory was used to assess eating behaviors and attitudes, such as perceived hunger, dietary disinhibition, and cognitive restraint. A higher score for each of these components indicated poorer eating behavior. A couple’s score was calculated as the average of the two individual scores.

    The perceived hunger component scored between 0 and 14, assesses how susceptible an individual is to feelings of hunger, while dietary disinhibition (0-18) evaluates the tendency to overeat palatable foods. The cognitive restraint component (0-21) examines an individual’s ability to restrict their food intake for weight maintenance.

    During data analysis, adjusted general linear models were used to examine statistical associations and odds ratios were calculated.

    Findings

    The study included 218 pregnant persons (average age 30.3) and 157 non-pregnant partners (average age 31.4). The average BMI for pregnant persons was 26.1, while the partners had an average BMI of 28.5. Non-pregnant partners were more likely to be obese, earn more than USD 40,000, and be at least college graduates.

    For the entire cohort, the mean GWG was 11.8 kg, and nearly half showed excess GWG. Only one in three pregnant people with normal weight experienced excess GWG compared to 63% of overweight people and 52.2% of obese people.

    Nearly 57%, 86%, and 89% of pregnant participants received low scores on the cognitive restraint, dietary disinhibition, and perceived hunger components, respectively. People with normal weight were more likely to receive low scores. Non-pregnant partners received, on average, lower scores than their partners, indicating healthier eating habits.

    Results from the unadjusted models showed that higher scores for each of the components were associated with higher GWG. The association remained significant for the cognitive restraint score after adjusting for BMI during early pregnancy and demographic factors.

    There were no significant associations between the non-pregnant partner’s scores and GWG. However, there was a significant positive association between a couple’s score for cognitive restraint and GWG. Specifically, if cognitive restraint increased by one unit, GWG increased, on average, by 0.23 kg; this finding persisted after adjusting for BMI and demographic factors.

    Conclusions

    Findings from this study indicate that cohesive partnerships can foster better eating behaviors and lead to optimal GWG. The implication is that involving both partners in dietary interventions could lead to better outcomes than if the pregnant person alone is targeted.

    One limitation of this study is that it did not assess dietary or energy intake, which could be predicted by eating behavior. Sleep and physical activity, which may both contribute to GWG, were also not accounted for in this analysis.

    Journal reference:

    • Healthful eating behaviors among couples contribute to lower gestational weight gain. Sparks, J.R., Redman, L.M., Drews, K.L., Sims, C.R., Krukowski, R.A., Andres, A. Nutrients (2024). DOI: 10.3390/nu16060822, https://www.mdpi.com/2072-6643/16/6/822

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  • Childhood ‘lazy eye’ linked to increased health risks in adulthood

    Childhood ‘lazy eye’ linked to increased health risks in adulthood

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    Adults who had amblyopia (‘lazy eye’) in childhood are more likely to experience hypertension, obesity, and metabolic syndrome in adulthood, as well as an increased risk of heart attack, finds a new study led by UCL researchers.

    In publishing the study in eClinicalMedicine, the authors stress that while they have identified a correlation, their research does not show a causal relationship between amblyopia and ill health in adulthood.

    The researchers analyzed data from more than 126,000 participants aged 40 to 69 years old from the UK Biobank cohort, who had undergone ocular examination.

    Participants had been asked during recruitment whether they were treated for amblyopia in childhood and whether they still had the condition in adulthood. They were also asked if they had a medical diagnosis of diabetes, high blood pressure, or cardio/cerebrovascular disease (ie. angina, heart attack, stroke).

    Meanwhile, their BMI (body mass index), blood glucose, and cholesterol levels were also measured and mortality was tracked.

    The researchers confirmed that from 3,238 participants who reported having a ‘lazy eye’ as a child, 82.2% had persistent reduced vision in one eye as an adult.

    The findings showed that participants with amblyopia as a child had 29% higher odds of developing diabetes, 25% higher odds of having hypertension and 16% higher odds of having obesity. They were also at increased risk of heart attack – even when other risk factors for these conditions (e.g. other disease, ethnicity and social class) were taken into account.

    This increased risk of health problems was found not only among those whose vision problems persisted, but also to some extent in participants who had had amblyopia as a child and 20/20 vision as an adult, although the correlation was not as strong.

    Corresponding author, Professor Jugnoo Rahi (UCL Great Ormond Street Institute for Child Health, UCL Institute of Ophthalmology and Great Ormond Street Hospital), said: “Amblyopia is an eye condition affecting up to four in 100 children. In the UK, all children are supposed to have vision screening before the age of five, to ensure a prompt diagnosis and relevant ophthalmic treatment.

    “It is rare to have a ‘marker’ in childhood that is associated with increased risk of serious disease in adult life, and also one that is measured and known for every child – because of population screening.

    “The large numbers of affected children and their families, may want to think of our findings as an extra incentive for trying to achieve healthy lifestyles from childhood.”

    Amblyopia is when the vision in one eye does not develop properly and can be triggered by a squint or being long-sighted.

    It is a neurodevelopmental condition that develops when there’s a breakdown in how the brain and the eye work together and the brain can’t process properly the visual signal from the affected eye. As it usually causes reduced vision in one eye only, many children don’t notice anything wrong with their sight and are only diagnosed through the vision test done at four to five years of age.

    A recent report from the Academy of Medical Sciences involving some researchers from the UCL Great Ormond Street Institute for Child Health, called on policymakers to address the declining physical and mental health of children under five in the UK and prioritize child health.

    The team hopes that their new research will help reinforce this message and highlight how child health lays the foundations for adult health.

    Vision and the eyes are sentinels for overall health – whether heart disease or metabolic dysfunction, they are intimately linked with other organ systems. This is one of the reasons why we screen for good vision in both eyes.


    We emphasize that our research does not show a causal relationship between amblyopia and ill health in adulthood. Our research means that the ‘average’ adult who had amblyopia as a child is more likely to develop these disorders than the ‘average’ adult who did not have amblyopia. The findings don’t mean that every child with amblyopia will inevitably develop cardiometabolic disorders in adult life.”


    Dr Siegfried Wagner, First Author, UCL Institute of Ophthalmology and Moorfields Eye Hospital

    The research was carried out in collaboration with the University of the Aegean, University of Leicester, King’s College London, the National Institute for Health and Care Research (NIHR) Biomedical Research Centre (BRC) at Moorfields Eye Hospital and UCL Institute of Ophthalmology and the NIHR BRC at UCL Great Ormond Street Institute of Child Health and Great Ormond Street Hospital.

    The work was funded by the Medical Research Council, the NIHR and the Ulverscroft Foundation.

    Source:

    University College London

    Journal reference:

    Wagner, S. K., et al. (2024) Associations between unilateral amblyopia in childhood and cardiometabolic disorders in adult life: a cross-sectional and longitudinal analysis of the UK Biobank. eClinicalMedicine. doi.org/10.1016/j.eclinm.2024.102493.

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  • High BMI affects autologous breast reconstruction outcomes

    High BMI affects autologous breast reconstruction outcomes

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    For women undergoing autologous breast reconstruction – reconstruction using the patient’s own tissues, rather than implants – the risks of overall and specific complications are increased at higher body mass index (BMI) levels, reports the March issue of Plastic and Reconstructive Surgery®, the official medical journal of the American Society of Plastic Surgeons (ASPS). The journal is published in the Lippincott portfolio by Wolters Kluwer. 

    Our study clarifies the impact of high BMI as a risk factor for adverse outcomes of autologous breast reconstruction. It also suggests that, among patients with obesity, losing weight before surgery might lower the risk of complications.” 


    Merisa Piper, MD, senior author of University of California, San Francisco

    How does BMI affect autologous breast reconstruction outcomes? 

    Autologous breast reconstruction, typically using a flap of tissue from the abdomen, is an alternative for reconstruction after mastectomy for breast cancer. Autologous reconstruction offers advantages including stable breast reconstruction with fewer surgical procedures, in less time, and at lower cost, compared to implant-based reconstruction. 

    However, not all patients are optimal candidates for this procedure: risk factors for adverse outcomes include smoking, uncontrolled diabetes, and high BMI. Despite previous studies, the impact of high BMI on outcomes of autologous breast reconstruction remain unclear. 

    Dr. Piper and colleagues analyzed the impact of BMI on outcomes of autologous reconstruction in 365 patients (545 breasts) between 2004 and 2021. All patients underwent microvascular breast reconstruction using an abdominal-based flap. Complications were assessed for patients in different BMI categories, ranging from normal weight (less than 25 kg/m2), to overweight (25 to 29.9 kg/m2), to obese (30 kg/m2 or higher). 

    Complication risks affected at different BMI cutoffs 

    Several types of complications increased at distinct levels of BMI, especially in the obese range. The risk of any complication increased at a BMI of 30 kg/m2 or higher. More severe obesity – BMI 35 kg/m2 or higher – was associated with increased rates of unplanned repeat surgery, including wound breakdown requiring reoperation. 

    Risk of infection requiring oral antibiotics increased at BMI 25 kg/m2 or higher, while infections requiring intravenous antibiotics increased at BMI 30 kg/m2 or higher. Higher BMI levels were also associated with increased rates of complications related to the abdominal donor flap, including infection and wound-healing problems. 

    Further analyses suggested optimal BMI cutoff point of 32.7 kg/m2 to minimize the occurrence of any breast complication and 30.0 kg/m2 for any abdominal complication. With a BMI of 32.7 kg/m2, the risk of breast complications was similar to that associated with current smoking. 

    The study demonstrates “a robust trend” whereby higher BMI levels are associated with increased complication rates for women undergoing autologous breast reconstruction. The findings suggest that targeting specific levels of weight loss before surgery might help to avoid postoperative complications. 

    “By quantifying the change in risk profile associated with a given change in BMI, our results can be used clinically to set evidence-based preoperative weight-loss goals for patients,” Dr. Piper and coauthors conclude. They emphasize that further studies would be needed to specifically evaluate the effects of weight loss before surgery. 

    Source:

    Journal reference:

    Barnes, L., et al. (2024) Relationship between Body Mass Index and Outcomes in Microvascular Abdominally Based Autologous Breast Reconstruction. Plastic and Reconstructive Surgery. doi.org/10.1097/PRS.0000000000010621.

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  • Eating live microbe-rich foods linked to better heart health

    Eating live microbe-rich foods linked to better heart health

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    In a recent study published in Frontiers in Nutrition, researchers explore the relationship between dietary intake of live microorganisms and cardiovascular health (CVH) outcomes among adults in the United States.

    Study: Association between dietary live microbe intake and Life’s Essential 8 in US adults: a cross-sectional study of NHANES 2005-2018. Image Credit: FOTOGRIN / Shutterstock.comStudy: Association between dietary live microbe intake and Life’s Essential 8 in US adults: a cross-sectional study of NHANES 2005-2018. Image Credit: FOTOGRIN / Shutterstock.com

    How diet affects CVH

    Despite advancements in the development of lipid-lowering drugs, cardiovascular disease (CVD) remains a significant cause of death throughout the world, thus impacting economic and social development.

    Dietary patterns are implicated in poor CVH, as gut microbiota convert many nutrients into metabolites. This relationship led to the introduction of Life’s Essential 8 (LE8) by the American Heart Association to improve CVH and reduce CVD. 

    The LE8 covers four health factors, including blood pressure (BP), body mass index (BMI), blood glucose, and blood lipids, as well as four health behaviors of sleep health, nicotine exposure, physical activity (PA), and diet. However, the relationship between live microorganisms in the diet and LE8 is poorly understood.

    About the study

    Data for the current study were obtained from the National Health and Nutrition Examination Survey (NHANES) and included seven survey rounds from 2005 to 2018. All study participants were over 20 years of age and provided information on their dietary live microbial intake, LE8, sample weights, and other relevant covariates.

    Live microbial quantity per gram was quantified from 9,388 food items, and study participants provided detailed dietary intake information during in-person interviews and telephonic follow-up calls. This information was subsequently used to classify study participants with low, medium, and high levels of live microbe content.

    LE8 scores were calculated as an unweighted average of the eight indicators and ranged from zero to 100. Based on this score, individuals in the range of 80-100 points were classified as having high CVH, 50-79 points were considered medium CVH, and zero to 49 points were classified as having low medium.

    Race and ethnicity, gender, age, education, marital status, socioeconomic status, health insurance, alcohol consumption, obesity status, daily nutrient intake, and medical history were included as additional covariates. Chi-square tests, one-way analysis of variance (ANOVA), and linear regression models were used to analyze the dataset.

    Study findings

    After applying exclusion criteria, 10,531 people were included in the final analysis. Females accounted for slightly more than half of the study cohort, with an average age of about 48 years.

    Non-Hispanic White was the predominant ethnicity. Most study participants had at least a college education and health insurance, drank alcohol, and reported being married or in cohabiting relationships.

    Most study participants were obese; nearly 9% had CVD, 14% had diabetes mellitus, about 37% had hypertension, and over 70% had hyperlipidemia. About 66% of the study cohort reported a moderate level of CVH. Across CVH levels, participants were similar in terms of daily intake of carbohydrates, hypertension, and hyperlipidemia but significantly different in other aspects.

    Significant associations were observed between groups of dietary live microbes and LE8 scores, both in crude models and after adjusting for multiple covariates. For all components of LE8, a higher intake of live microorganisms was associated with better health behaviors and health factor scores.

    Those in the high and moderate microorganism groups had lower CVD risk with odds ratios of 0.65 and 0.73, respectively. Notably, in the low-intake group, LE8 score and food intake had a linear negative association, whereas this association was positive in the high-intake group. The moderate microorganism intake group exhibited an inverted ‘U’ shape regarding the relationship between LE8 and food intake.

    Conclusions

    Probiotic supplements can reduce oxidative stress, improve immunity, and reduce blood glucose and blood pressure levels, which could maintain CVH. The current study expanded on previous studies that used self-reported medical history to characterize CVD. Taken together, these findings provide strong evidence supporting the consumption of more foods rich in live microorganisms to improve CVH outcomes.

    Future studies are needed to identify individuals who may respond differently to microbial consumption based on gender and ethnicity. For example, non-Hispanic black individuals did not exhibit a significant association with live microbe consumption and CVH.

    Additional research is also needed to elucidate these associations’ mechanisms and include more diverse cohorts. These types of studies have the potential to overcome the limitations of a cross-sectional study based on dietary recall data to establish causality.

    Journal reference:

    • Wang, L., Wang, S., Wang. Y., et al. (2024). Association between dietary live microbe intake and Life’s Essential 8 in US adults: a cross-sectional study of NHANES 2005-2018. Frontiers in Nutrition (2024). doi:10.3389/fnut.2024.1340028

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  • Healthy lifestyles linked to specific metabolic markers, large study finds

    Healthy lifestyles linked to specific metabolic markers, large study finds

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    In a recent study published in the journal Med, researchers used a collated dataset comprising four American sample cohorts to identify the metabolomic markers of a healthy lifestyle and, potentially, the mechanisms underlying their production. They used a combination of analytical techniques, particularly liquid chromatography-mass spectrometry, on the 13,056 datasets and observed that the healthy lifestyle metabolomic signature was largely reflective of lipid metabolism pathways.

    Shorter and more saturated di—and triacylglycerol metabolite sets were found to be inversely associated with healthy lifestyles, while phosphatidylcholine plasmalogens and cholesteryl esters were directly associated with the condition. Encouragingly, the relative concentrations of these biomarkers accounted for a 17% lower risk of all-cause mortality, a 19% reduced risk of cardiovascular disease-related mortality, a 17% lower risk of cancer-related mortality, and a 25% improved probability of attaining longevity.

    Study: Plasma metabolites of a healthy lifestyle in relation to mortality and longevity: Four prospective US cohort studies

    The relationship between lifestyle choices and metabolic health

    Chronic, non-transmissible disease prevalence is currently higher than it has ever been and has primarily been attributed to the increased adoption of sub-optimal health behavioral choices, including diets (e.g., the Western-style diet) and physical activity levels (e.g., the sedentary lifestyle). Previous research has highlighted the profound benefits of adopting a healthy lifestyle, with research on American cohorts revealing 55-71% reduced all-cause mortality risk in individuals who maintained their body mass index (BMI) between 18.5-24.9 kg/m2, consumed alcohol in moderation, partook in physical activity, and abstained from smoking.

    Unfortunately, the mechanisms underpinning these interactions remain largely unknown. Some studies have suggested that individuals’ health behavior components such as body weight, diet, alcohol consumption, physical activity, and smoking may have associated metabolomic signatures indicative of their current and historical health. Still, these hypotheses have rarely been tested within a scientific framework. The limited information in the field, despite being at times confounding, suggests that polyunsaturated fatty acids (PUFAs), phosphatidylcholines (PCs), and glutamate and similar amino acids (AAs) are associated with improved health outcomes, while triacylglycerols (TAG), sphingomyelins (SMs), and carnitines are associated with suboptimal ones.

    “However, most studies only examined diet and physical activity factors, with small sample sizes and limited sets of metabolites profiled. Thus, a comprehensive understanding of the metabolic pathways underlying healthy lifestyle behaviors remains to be discovered. By studying several modifiable lifestyle factors simultaneously, a better understanding of the common biological mechanisms as well as the key differences may be acquired.”

    About the study

    In the present study, researchers used lifestyle, metabolomic, and clinical information from four American cohorts comprising more than 13,000 individuals to compute a metabolomic-based combined healthy lifestyle score during mid-life and further examine the relationship between this score and mortality and longevity outcomes. Outcome follow-up was extensive and had a mean duration of 28 years. The cohorts included the Nurses’ Health Study (NHS; 1976), the second iteration of the same prospective cohort (NHSII; 1989), the Women’s Health Initiative (WHI; 1993), and the Health Professionals Follow-up Study (HPFS; 1986). They comprised primarily middle-aged (mean 54.3 years) women (85.8%) belonging to the White ethnicity (96.7%).

    Lifestyle information was participant-reported, clinical information was obtained from the prospective cohort database, and metabolomic information was derived from (fasting) blood plasma samples obtained at the time of study initiation and subsequent follow-up. Individuals lacking data on measured outcomes (BMI, alcohol consumption, metabolomic profiling, diets, physical activity levels, smoking status) were excluded. The WHI cohort was used as an external validation cohort for results obtained from the three remaining cohorts.

    Plasma metabolomic profiling was carried out using acetonitrile/methanol/formic acid extraction followed by hydrophilic interaction liquid chromatography (HILIC) and positive ionization mass spectrometry (MS) for polar compounds (e.g., amino acids) and isopropanol extraction followed by octyl high-performance liquid chromatography (HPLC) and positive ionization MS for lipids. The Metabolite Standard Initiative (MSI) database was used to identify obtained metabolites.

    Lifestyle factors (treatments) were of five main categories – diet, alcohol consumption, physical activity, smoking, and BMI, and were assessed using questionnaires and the Alternative Healthy Eating Index (AHEI). Mortality and longevity (outcomes) were obtained from family-member reports (for death), State statistics records, and the National Death Index database. Multivariable linear regressions, logistic regression, and elastic linear regressions were used for statistical data analyses. Cox proportional hazard ratios were computed to translate these results into relative disease risk.

    Study findings

    Results reveal that the metabolomic signature most reflective of healthy lifestyles is the lipid metabolism pathway comprising PC, TAG, CE, and DAG metabolite families. Diet composition and BMI were found to be the best predictors of positive metabolite signatures. Metabolite characterization identified more than 400 metabolites associated with lifestyle choices. Elastic regression analyses identified 187 of these metabolites as descriptive of healthy lifestyle behaviors – 58 were positively associated, while 129 were inversely associated with beneficial mortality and longevity outcomes.

    “…the MSEA revealed CEs, mainly of PUFAs, and PCs as the most enriched metabolite sets positively associated with a healthy lifestyle. CEs serve as a mean for the storage and transportation of cholesterol and other lipids in the blood and were shown to be reflective of dietary fat intake. PCs are naturally found in the body but also in foods such as eggs, fatty fish, and soybeans. They are well known for their essential role in cell membranes and membrane signaling.”

    Animo acids and metabolites involved in purine metabolism were also highlighted as signatures of healthy lifestyles. Vegetarian diets that are rich in circulating glycine, trigonelline, asparagine, hippurate, and glutamine and poor in valine, isoleucine, and leucine were found beneficial over dietary intakes of red meats, chicken, and energy drinks.

    Outcome analyses revealed a surprising fact – the metabolomic signatures identified herein were more accurate predictors of mortality and longevity than patient-reported fitness and health levels.  

    “Indeed, the metabolomic signature explained 38.0% of the association between the self-reported healthy lifestyle score and mortality, pointing to unique biological pathways captured by metabolomics. Consistent with the literature and with our mortality results, we found an association of the healthy lifestyle metabolomic signature with longevity, and the signature explained 48.6% of the association between self-reported healthy lifestyle score and longevity.”

    Conclusion

    The present study uses a large combined American cohort comprising more than 13,000 participants to identify metabolomic signatures associated with positive mortality and longevity outcomes as a consequence of healthy lifestyle and dietary choices. Study findings reveal that more than 100 metabolites are associated with (positive or negative) health lifestyle outcomes, most of which are involved in the lipid metabolism pathways.

    “…our findings suggest that greater adherence to a healthy lifestyle may lead to alterations in the metabolome that are associated with lower premature mortality risk and higher likelihood of longevity. We identified a metabolomic signature associated with a combined healthy lifestyle in US adults that is strongly reflective of lipid metabolism pathways. We found that those with a higher multimetabolite score had a lower risk of total and cause-specific mortality and a greater likelihood of living longer.”

    Journal reference:

    • Tessier, A.-J., Wang, F., Liang, L., Wittenbecher, C., Haslam, D. E., Eliassen, A. H., Tobias, D. K., Li, J., Zeleznik, O. A., Ascherio, A., Sun, Q., Stampfer, M. J., Grodstein, F., Rexrode, K. M., Manson, J. E., Balasubramanian, R., Clish, C. B., Martínez-González, M. A., Chavarro, J. E., … Guasch-Ferré, M. (2024). Plasma metabolites of a healthy lifestyle in relation to mortality and longevity: Four prospective US cohort studies. In Med. Elsevier BV, DOI – 10.1016/j.medj.2024.01.010,  https://www.cell.com/med/fulltext/S2666-6340(24)00040-0

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  • Prenatal Mediterranean diet reduces offspring obesity

    Prenatal Mediterranean diet reduces offspring obesity

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    In a recent study published in Nutrients, researchers determined the relationship between maternal Mediterranean diet (MedDiet) adherence during gestation and overweight or obese offspring risk at four years.

    Study: Close Adherence to a Mediterranean Diet during Pregnancy Decreases Childhood Overweight/Obesity: A Prospective Study. Image Credit: Marian Weyo/Shutterstock.comStudy: Close Adherence to a Mediterranean Diet during Pregnancy Decreases Childhood Overweight/Obesity: A Prospective Study. Image Credit: Marian Weyo/Shutterstock.com

    Background

    The childhood obesity epidemic is a global health concern affecting millions of children under five, causing psychological comorbidities, low self-esteem, behavioral and emotional disorders, and long-term cardiovascular morbidity and cancer.

    In addition, the World Health Organization’s (WHO) report emphasizes the importance of antenatal nutritional balance in preventing childhood obesity. 

    Close maternal adherence to a Mediterranean-style diet during gestation could be a promising strategy for determining potential obesity risks in childhood. Greater adherence to the diet has multiple health benefits for both mother and child.

    However, studies examining the impact of prenatal diet on offspring obesity are scarce and yield varied results, warranting further research.

    About the study

    In the present study, researchers investigated whether maternal MedDiet adherence was associated with offspring obesity at four years and evaluated the impact of maternal factors on the association.

    The team included 272 mother-child dyads from the Ensayo CLInico Para Suplementar con Hierro a EmbarazadaS (ECLIPSES) study for analysis.

    The primary study outcome was offspring overweight or obese based on sex- and age-specific body mass index (BMI) z-scores above the 85th percentile using the WHO child growth standards.

    The researchers obtained baseline maternal data from questionnaires during face-to-face interviews at recruitment, including medical history, age, educational level, socioeconomic status, physical activity, smoking status, and alcohol intake.

    In addition to the gestational age at birth and delivery type, they obtained data on child-related variables, including sex, length, and weight at birth.

    The team assessed prenatal diet using standardized 45-component food-frequency questionnaires (FFQs) at gestational weeks 12, 24, and 36 and calculated relative MedDiet (rMedDiet) scores. They measured offspring height and weight at four years.

    They estimated the total daily calorie intake using the REGAL food table and determined household socioeconomic status using the Catalan classification of occupations (CCO-2011).

    The researchers assessed physical exercise using the International Physical Activity Questionnaire (IPAQ) and categorized gestational weight gain (GWG) using the 2009 Institute of Medicine (IOM) recommendations.

    They performed multivariate logistic regression modeling to determine the odds ratios (OR) for the association between prenatal diet and childhood obesity.

    The ECLIPSES randomized clinical trial was conducted in Tarragona, Spain, from 2013 to 2017 to evaluate the efficacy of maternal iron supplementation in different dosages, adjusting for the initial hemoglobin levels during early gestation, on maternal iron status at the end of gestation.

    Primary care midwives recruited 791 expecting women aged ≥18 years for the study during the initial prenatal visit (before week 12 of gestation).

    Results

    The mean maternal age was 32; 70% were aged ≥30, and 42% were obese or overweight, with body mass index values ≥25 kg m-2.

    Most (86%) mothers were from Spain, 44% received university-level education, 22% had high socioeconomic status, and 17% practiced smoking during pregnancy. Among the mothers, 29% showed low MedDiet adherence, whereas 23% were highly adherent.

    The mean prenatal rMedDiet score was 9.80, and 26% of offspring were overweight or obese at four years, with a higher obesity prevalence among males (63%) than females (37%).

    The team found significant anthropometric differences (height, weight, and body mass index) by sex. The mean body mass index and body weight of offspring at four years were 16 kg m-2 and 18 kg, respectively.

    Males had higher weight (19 versus 17 kg), BMI (16 versus 15.6), weight-for-age z scores (0.5 versus 0.1), and body mass index z-scores (0.7 versus 0.2) than females.

    Overweight/obesity was less prevalent among offspring of mothers with university-level education, higher socioeconomic status, and higher gestational rMedDiet scores.

    After adjusting for potential confounding variables, the team found higher prenatal MedDiet adherence related to a reduced risk of offspring being overweight or obese (OR for the highest versus lowest quartile, 0.3).

    They obtained similar findings, stratifying by maternal age, early gestational BMI, educational attainment, smoking status, socioeconomic status, and GWG.

    After confounder adjustment, the team found that each point increase in the prenatal MedDiet was associated with a 19% lower risk of children being overweight or obese at four years (OR, 0.8).

    Smoking (OR, 2.5), pre-pregnancy overweight (OR, 2.5) or obesity (OR, 2.6), and excessive GWG (OR, 2.9) were considerably associated with offspring overweight or obese at four years.

    The protective effects of MedDiet on offspring weight were higher among expecting women aged below 30 years with overweight or obese during initial gestation, those who did not smoke, and those with low socioeconomic status.

    Conclusion

    Overall, the study findings showed higher prenatal MedDiet adherence associated with lower reduced offspring overweight/obesity at four years, especially among university-educated mothers aged below 30 years from low socioeconomic backgrounds who did not smoke. Future studies could investigate whether the association persists across life stages.

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  • Early onset of menstruation and menopause associated with increased risk of COPD

    Early onset of menstruation and menopause associated with increased risk of COPD

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    In a recent study published in Thorax, a group of researchers evaluated the association between female reproductive factors such as age at menarche, stillbirth, number of children, infertility, miscarriage, and age at natural menopause—and the risk of developing chronic obstructive pulmonary disease (COPD).

    Study: Female reproductive histories and the risk of chronic obstructive pulmonary disease. Image Credit: Image Point Fr/Shutterstock.com

    Background 

    COPD is a significant global health issue, with a prevalence of approximately 3.9% in 2017, showing slight gender differences in rates between men and women. Notably, women are more susceptible to developing severe COPD at younger ages than men, and the majority of non-smokers with COPD are women.

    This suggests that female sex hormones, such as estrogen and progesterone, play crucial roles in lung development and the pathogenesis of COPD. These hormones influence bronchodilation, inflammation, and cellular proliferation, key factors in COPD development.

    The variability in the female hormonal environment throughout different reproductive stages- menarche, pregnancy, menopause, and conditions like infertility or pregnancy loss- highlights the complex relationship between female reproductive health and COPD risk.

    However, research specifically exploring this connection remains limited, indicating a need for further research into how reproductive history impacts COPD risk.

    About the study 

    The present study conducted by the Inter­national Collaboration for a Life Course Approach to Reproductive Health and Chronic Disease Events (InterLACE) consortium utilized data from over 850,000 women across 12 countries.

    It focused on three cohorts with information on reproductive factors and COPD: the Australian Longitudinal Study on Women’s Health, the United Kingdom (UK) Biobank, and the Swedish Women’s Lifestyle and Health Study. 

    To ensure accuracy, the study excluded women who had developed COPD by age 40 from analyses involving infertility, miscarriage, stillbirths, and parity due to the absence of specific ages for these events.

    Only women who had experienced natural menopause were considered for analysis regarding menopause age, and those with COPD before natural menopause were omitted.

    The researchers carefully handled missing data, ensuring participants had complete records on critical factors such as race, education, smoking history, body mass index, and asthma.

    To address potential biases, including the impacts of coronavirus disease 2019 (COVID-19), follow-up adjustments were made across cohorts, and reproductive histories were detailed, including menarche to menopause.

    COPD was identified through diverse data, ensuring accuracy. Statistical analysis, including Cox regression and sensitivity tests, explored reproductive factors’ influence on COPD risk, highlighting their importance in women’s health research.

    Study results 

    In the present comprehensive study encompassing 283,070 women with a median age of 54 years, researchers embarked on an 11-year journey to unravel the intricate relationship between women’s reproductive history and the development of COPD.

    Throughout this period, 3.8% of the participants, equivalent to 10,737 women, were diagnosed with COPD at a median age of 63 years.

    The identification of COPD cases varied, with 7,983 cases recognized through a singular data source—ranging from survey data to hospital records—and 2,754 through multiple sources.

    The initial characteristics of these women highlighted certain risk factors, including advanced age at cohort entry, lower educational attainment, higher body mass indices, significant smoking histories, and pre-existing asthma conditions.

    The researchers excluded 53,205 women due to incomplete data, particularly regarding smoking habits and body mass index, ensuring the robustness of their findings.

    A nuanced pattern emerged, linking the age of menarche with COPD risk; notably, women who experienced menarche at age 11 or younger, as well as those who began menstruating after 13, saw an increased risk, with a particularly sharp rise observed in those who started menstruating at age 14 or beyond.

    Furthermore, the study revealed that motherhood also influenced COPD risk, with women having one or more children facing higher risks compared to childless counterparts. This risk escalated with the number of children borne.

    Additionally, experiences of infertility and miscarriages further intensified COPD risks, painting a complex picture of how reproductive history shapes respiratory health.

    Women who had undergone natural menopause presented an inverse risk relationship with COPD, dependent on the age at menopause. Those entering menopause before age 40 faced the highest risk, whereas the risk diminished for women experiencing menopause at or beyond age 54.

    The study also used rigorous sensitivity analyses, including random effects modeling and competing risk analysis, to validate these findings.

    Notably, the association between infertility and COPD risk diminished in some analyses, yet the overarching trends remained consistent across various subgroups, including smokers and non-smokers, as well as women with and without a history of asthma.

    The analysis extended to explore the impact of bilateral oophorectomy age on COPD risk, finding a heightened risk among women who underwent the procedure at younger ages.

    Further, the study delved into the specific effects of reproductive history facets such as age at menarche, miscarriages, stillbirths, and menopause timing on COPD risk, with findings echoing across individual cohort studies and meta-analyses.

    Despite some variability, especially concerning the age at menarche, most evidence pointed towards a consistent relationship between reproductive factors and the development of COPD.

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