Background: Public health measures  have significantly reduced the spread of the coronavirus disease-2019 (COVID-19), but the impact of public health measures on other respiratory infectious diseases is unclear.Objective: To assess the correlation between public health measures and the incidence of respiratory infectious diseases in China during the COVID-19 pandemic.Methods: We collected the data from the National Health and Construction Commission in China on the number of patients with six respiratory infectious diseases  from 2017 to 2020 and assessed the correlation between public health measures and the incidence of respiratory infectious diseases. Finally, we used the data of the six respiratory infectious diseases in 2021 to verify our results.Results: We found public health measures significantly reduced the incidence of measles (p = 0.002), tuberculosis (p = 0.002), pertussis (p = 0.004), scarlet fever (p = 0.002), influenza (p = 0.034), and mumps (p = 0.002) in 2020, and prevented seasonal peaks. Moreover, the effects of public health measures were most marked during the peak seasons for these infections. Of the six respiratory infectious diseases considered, tuberculosis was least affected by public health measures.Conclusion: Public health measures were very effective in reducing the incidence of respiratory infectious diseases, especially when the respiratory infectious diseases would normally have been at their peak. The coronavirus disease-2019 (COVID-19) pandemic has severely affected economic development worldwide. To reduce the transmission of COVID-19, various types of public health measures have been implemented worldwide, including wearing masks, physical distancing, strict closed-off management, strict immigration control measures, and isolation . These pA recent report claimed that public health measures reduced the activity of enveloped viruses . This phIt is useful to evaluate the impact of public health measures on respiratory infectious diseases in China. The first case of COVID-19 was reported in China by the Wuhan Municipal Health Commission at the end of 2019. Starting from January 2020, people were asked to wear masks in crowded closed places and public places, reduce participation in non-essential gatherings, and maintain a social distance of more than 1 meter. All provinces in mainland China adopted stringent public health measures from January 2020 . Taking 0) of respiratory infectious diseases, we collected the data on the number of patients with six respiratory infectious diseases  for each month from 2017 to 2021 from the National Health and Construction Commission (http://www.nhc.gov.cn/). The incidence of these respiratory infectious diseases in China was high enough that the relationship between public health measures and the transmission of respiratory infectious diseases could be well-reflected.Taking into account the differences in pathogen types, transmission routes, epidemic cycles, and basic reproduction number  was used for the statistical analyses. The Shapiro–Wilk normality test was used to determine the normality of the data. Continuous variables were compared using the paired p < 0.001), tuberculosis (p < 0.001), pertussis (p < 0.001), scarlet fever (p < 0.001), influenza (p = 0.013), and mumps (p < 0.001). Compared with the projected monthly number of newly confirmed cases that would have occurred in 2020 in the absence of public health measures, the actual monthly number of newly confirmed cases was significantly reduced for measles (p = 0.002), tuberculosis (p = 0.002), pertussis (p = 0.004), scarlet fever (p = 0.002), influenza (p = 0.034), and mumps , pertussis > tuberculosis (p = 0.023), scarlet fever > tuberculosis (p = 0.003), influenza > tuberculosis (p = 0.034), and mumps > tuberculosis (p = 0.009).Moreover, public health measures were most effective against respiratory infectious diseases during the periods when they would normally be at the peak of their incidence. For example , the dec0 of each disease.Furthermore, the actual incidence of measles, tuberculosis, pertussis, scarlet fever, influenza, and mumps throughout the year in 2020 decreased by 74.8, 19.6, 76.5, 78.3, 22.0, and 52.1%, respectively . The impp = 0.176), tuberculosis (p = 0.499), pertussis (p = 0.482), scarlet fever (p = 0.237), influenza (p > 0.999), or mumps (p = 0.819). The monthly number of newly confirmed cases of the six respiratory infectious diseases remained at a low level in 2021. No significant epidemic peaks have been observed in the six respiratory infectious diseases in 2021, to date. Therefore, we speculate that the impact of public health measures during the COVID-19 pandemic on these six respiratory infectious diseases are likely to be maintained until at least the end of 2021, even though many public health measures were gradually eased from April 2020.To verify our results, we collected the data from the National Health and Construction Commission in China on the number of patients with the six respiratory infectious diseases from January to July 2021. In terms of the monthly number of newly confirmed cases from January to July , there wOur results show that public health measures significantly reduced the incidence of measles, tuberculosis, pertussis, scarlet fever, influenza, and mumps. Due to the public health measures, the seasonal peaks in the incidence of the six respiratory infectious diseases disappeared in 2020 and 2021. Public health measures were most effective against respiratory infectious diseases during the months when seasonal incidence normally peaked. Overall, our research provides new evidence for the prevention and control of respiratory infectious diseases. Considering that the COVID-19 pandemic has not yet ended, the impact of public health measures on respiratory infectious diseases still needs further attention.It is worth noting that although public health measures were the main reason for the reduction in the incidence of respiratory infectious diseases, there were still some other confounding factors. First, people actively avoided going to hospitals during the COVID-19 pandemic because they were worried about contracting COVID-19 , which cAmong the six respiratory infectious diseases that we considered, the public health measures had the least impact on tuberculosis. This can be attributed to the following factors: First, as tuberculosis has a long latency period and its diagnosis requires time, diagnosis is often delayed in China due to the technical difficulties in detecting tuberculosis. Therefore, the impact of public health measures on tuberculosis may have been delayed in the reporting system. Second, in addition to transmission through the respiratory tract, tuberculosis may also be transmitted through other routes –18, suchPublic health measures during the COVID-19 pandemic have caused tremendous changes in the incidence of other diseases. In addition to reduce respiratory infectious diseases, public health measures were related to the increase in the incidence of “quarantine dry eye” , 21.Our study had several limitations. First, we could not determine which public health measure might be the most effective in curbing the spread of respiratory infectious diseases. Second, because public health measures may change according to the situation, the degree of impact of public health measures on respiratory infectious diseases would also change accordingly. Third, we could only obtain data from China, and data from more countries need to be included to improve the reliability of the conclusions.In conclusion, public health measures can effectively reduce the spread of respiratory infectious diseases. During an epidemic of these respiratory infectious diseases, it would be necessary to take appropriate public health measures to reduce the incidence. The findings of this study could provide evidence for tailoring control strategies for future epidemics or pandemics of respiratory infectious diseases.The original contributions presented in the study are included in the article/CH and ZZ designed the research study, collected and analyzed the data, and wrote and revised the paper. YZho, XL, QS, ZW, and YT analyzed the data and revised the manuscript. YL, WC, and YZha collected the data and revised the manuscript. All authors contributed to the article and approved the submitted version.This work was supported by the Natural Science Foundation of Guangdong Province (Grant No. 2017A030313860).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Background: Recent studies have reported that homocysteine (Hcy) may play a vital role in the pathogenesis of vascular dementia (VaD) and Alzheimer's disease (AD). Our study explored the relationship between the plasma Hcy and folate levels and the risk of dementia.Methods: We searched Embase, PubMed, and Web of Science for published literature, including case-control studies and prospective cohort studies, and performed a systematic analysis.Results: The results of our meta-analysis, consisting of case-control studies, showed higher levels of Hcy and lower levels of folate in dementia, AD, and VaD patients than those in non-demented controls . AD patients showed significantly lower plasma Hcy levels compared to VaD patients . Subgroup analysis revealed that ethnicity, average age, and dementia type had no significant effect on this association. Furthermore, from the analysis of prospective cohort studies, we identified that elevated plasma Hcy levels were associated with an increased risk of dementia, AD, and VaD . In addition, every 5 μmol/L increase in the plasma Hcy level was associated with a 9% increased risk of dementia and a 12% increased risk of AD.Conclusion: Hcy and folic acid are potential predictors of the occurrence and development of AD. A better understanding of their function in dementia could provide evidence for clinicians to rationalize clinical intervention strategies. Dementia is a severe threat to the health of older people and places a heavy burden on their families and society  Homocysteine OR “Hcy” OR Hyperhomocysteinemia OR Folate OR Folic acid and (2) Dementia OR Cognitive OR Cognition OR Alzheimer OR Vascular dementia. Some articles were identified via manual screening of relevant references from other studies on the subject.The inclusion criteria for the meta-analysis of case-control studies were that the studies must provide the number of dementia patients and controls and clearly present means and standard deviations (SD) of Hcy and/or folic acid levels for both patients and controls. For the meta-analysis of prospective cohort studies, studies must present blood Hcy concentration levels, adjusted relative risk (RR), and 95% confidence intervals (CI) for dementia or AD occurrence.The exclusion criteria were as follows: (1) we selected population-based case-control studies and cohort studies to extract raw data, case report, review, letters were all excluded; (2) we designated two independent reviewers to scrutinize the manuscripts of retrieval, irrelevant titles and abstracts were excluded; and (3) studies with incomplete data were excluded such as undefined included cohorts and imprecise level of Hcy and folic acid.Two reviewers independently assessed the included studies. The extracted data included the name of the first author, publication year, the ethnicity of samples, the number of subjects, gender distribution, mean age, mean follow-up duration, mean and SD of Hcy and folate levels for patients and controls, source and detection method used for Hcy and folate analyses, categories of plasma Hcy, and multivariable-adjusted effects (RR and 95% CI for each exposure category). Different Hcy and folate concentration measurement units were converted to a standard format (μmol/L for Hcy and nmol/L for folate).The Newcastle-Ottawa Scale (NOS) Stang,  was usedAll the included studies were approved by ethics committees and conducted according to the Code of Ethics of the World Medical Association (Declaration of Helsinki). All the participants of the included studies provided written informed consent.Q-test and the I2-test. I2 > 50% represented high heterogeneity. Thus, the random-effects model was applicable. Subgroup analyses—stratified by dementia type (AD and VaD), geographical ethnicity (Caucasian or Asian), average age , and gender distribution —were also conducted. A dose-response meta-analysis was used to assess the potential linear and non-linear dose-response relationships between blood Hcy levels and the risk of dementia. Sensitivity analysis was used to assess the results after removing any of the studies one at a time. The risk of publication bias was assessed using Egger's test and Begg's test. A value of p ≥ 0.05 indicated no publication bias. If publication bias was observed, we applied the trim and fill method to recalculate the results. All meta-analyses were performed using Stata version 15.1.The standard mean differences (SMD) with a 95% confidence interval (CI) were calculated to explore the differences in Hcy and folate levels between the dementia and control groups. The pooled RR with 95% CI was used to evaluate the relationship between the Hcy and folate levels and the risk of dementia. Heterogeneity was evaluated using the We initially identified 1,746 relevant articles from available databases, including Embase, Pubmed, and Web of Science, and 1,078 of the articles were left after removing duplications and reviews. We excluded 927 articles after reading titles or abstracts and selected 151 full-text articles for eligibility. Subsequently, 70 articles were removed on account of failing to data extraction after careful perusal, thus 81 articles were included in this meta-analysis eventually. Thereinto, 55 and 37 articles were retrospective researches relevant to Hcy and folic acid, and 13 articles and 5 articles were prospective aiming at Hcy and folic acid, respectively. A flow diagram of the retrieval process is illustrated in P < 0.05) (p = 0.000) (p = 0.000) . Therefore, we used the trim and fill method to recalculate the pooled effect size, and the results were slightly altered but still similar to our original risk estimate   . Further= 0.000) . Our stu= 0.000) . Begg's  folate) . Sensiti folate) .p < 0.05), and higher Hcy levels in AD patients, with an SMD of 0.689 , than in the controls. This indicated significant differences in plasma Hcy and folate levels between AD patients and controls. Further, we also found that Hcy levels were higher and folate levels were lower in VaD patients than in the controls. Additionally, high Hcy and low folic acid levels in dementia patients were found in the Caucasian and Asian cohorts. Ethnicity also exhibited no significant effect on this association. Further subgroup analysis based on age  showed higher levels of Hcy in dementia patients than in healthy controls. In both male and female subgroups, higher Hcy and lower folic acid levels were observed in dementia patients than in controls. Plasma folate levels were significantly lower in dementia patients with a mean age of 70–80 and 80–90 years than in controls. However, dementia patients with an average age of 60–70 years had marginally lower folic acid levels . The above results are shown in To further explore the effect of geographical ethnicity, average age, gender, and dementia type on plasma Hcy and folate levels in dementia patients and controls, subgroup analyses were performed. The 55 studies for Hcy and 37 studies for folate levels were divided into two subgroups based on the dementia type. Subgroup analysis showed lower folic acid levels in AD patients, with an SMD of −0.503  (p = 0.703).A significant reduction in the plasma Hcy level was observed in AD patients compared to VaD patients  . AdditioIn total, 13 prospective studies on Hcy levels and risk of dementia were included in our study. A summary of these studies is shown in Begg's and Egger's tests indicated no publication bias. For further linear dose–response analysis, eight studies about Hcy with more than two categories were included, with a total of 15,134 participants and 1,627 all-cause dementia cases. There was no significance for non-linear dose-response analysis (p-non-linear = 0.801). The summary RR of dementia was 1.09 (95% CI [1.057–1.131]) per 5 μmol/L of increased Hcy . In otheOur meta-analysis included 81 articles, and 15 of these were prospective cohort studies. Drawing on this, we systematically analyzed the association between the Hcy and folate levels and the risk of dementia. The results of the meta-analysis not only confirmed that dementia patients had higher Hcy and lower folic acid levels than the controls but also suggested that subjects with high Hcy levels and low folic acid levels might be susceptible to AD. We found a linear trend that for every 5 μmol/L increase in Hcy levels, the risk of dementia and AD increased by 9 and 12%, respectively. To our knowledge, the present meta-analysis is the largest and most comprehensive evaluation of the correlation between Hcy and folate levels and the risk of dementia.A recent meta-analysis of retrospective studies by Shen et al. demonstrated that AD was significantly associated with high Hcy levels and low serum folate levels. They also suggested that high Hcy and low folate levels may be associated with an increased risk of occurrence of AD  have reported the beneficial effects of Hcy-lowering interventions  category in the strict sense. Randomized placebo-controlled trials of Hcy-lowering treatment are needed to determine the effect of such treatment on the progression of dementia. In addition, although the RR with fully adjusted models was used in our study, different adjustments for confound risk among the different studies could potentially influence the results. Not all the included studies took account of the adjustment for cardiovascular risk factors, MMSE score, vitamin B, duration of follow-up, and other factors. Lastly, only studies with full texts and published papers were included in our meta-analysis; therefore, publication bias may have affected our findings.In conclusion, our meta-analysis is the first to report that patients with dementia, including AD and VaD, show higher levels of Hcy and lower levels of folic acid compared to non-demented controls. We also revealed a possible influence of elevated plasma Hcy levels and reduced folate levels on the risk of dementia. Moreover, every 5 μmol/L increase in the plasma Hcy level was associated with a 12% increase in the risk of AD. The above findings indicate that Hcy and folic acid may contribute to the incidence of dementia. Our study provides vital evidence for clinicians to rationalize clinical intervention strategies. Moreover, longitudinal studies are needed to further elucidate the relationship between Hcy, folic acid, and dementia.The original contributions presented in the study are included in the article/RZ and XL: designed the experiments. RZ, XL, and JZ: performed the experiments. XL, QW, and HC: analyzed the data. RZ and QW: wrote the paper. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Narcolepsy is characterized by excessive daytime sleepiness (EDS) and cataplexy. Histamine neurons play an important role in enhancing wakefulness. The objective of our study was to evaluate the efficacy of pitolisant, a histamine 3 (H3)-receptor antagonist/inverse agonist, in patients with a high burden of narcolepsy symptoms. We conducted an advanced PubMed search strategy with inclusion and exclusion criteria. The outcome included the Epworth Sleepiness Scale (ESS) and adverse effects frequency. Our primary outcome included the mean ESS score at the endpoint and showed that pitolisant was superior to the placebo, but not non-inferior to modafinil. Adverse effects were less common and shorter in duration in the pitolisant group compared to the modafinil-treated patients. Pitolisant was efficacious in reducing excessive daytime sleepiness and cataplexy compared with placebo, and it was well-tolerated in patients with severe narcolepsy symptoms as compared with modafinil. Narcolepsy is the most common neurological cause of chronic sleepiness . It is cThere are two types of narcolepsy. Narcolepsy with cataplexy (narcolepsy type I), which is caused by the loss of hypocretin or orexin neurons, and narcolepsy without cataplexy (narcolepsy type II) has normal hypocretin and an unknown etiology. Hypocretin is a neuropeptide produced by neurons in the lateral hypothalamus which promotes wakefulness. Genetic, environmental, and possible autoimmune processes are involved in the pathogenesis of narcolepsy -6.The sleep-wake disturbances in narcolepsy cause several symptoms to a patient’s motor, psychiatric, emotional, cognitive, metabolic, and autonomic functions . ExcessiSymptomatic treatment for narcolepsy involves both non-pharmacological and pharmacological approaches. Treatments include counseling, psychosocial guidance, and regular medical follow-up tailored to age, profession, specific lifestyles, and comorbidities . PitolisTable Materials and MethodsProtocolFor this systematic review, we used the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) for clinical trials and the Meta-analysis of Observational Studies in Epidemiology (MOOSE) protocol for observational studies. Eligibility Criteria and Study SelectionWe only included clinical trials (Phase II and above) and observational studies on humans in the last 15 years in the English literature. We excluded all animal studies, studies other than clinical trials and observational studies, and those that did not fulfill the study's outcome. Patients included in the study must have been diagnosed with narcolepsy. After this process, we removed duplicate papers and studies in which the title was not pertinent. After screening the studies, we included papers with the following criteria:1. Patients: Individuals with narcolepsy2. Intervention: Pitolisant in patients with narcolepsy3. Comparator: Placebo or control group4. Outcomes: Epworth Sleepiness ScaleDatabase and Search StrategyA review of the literature using PubMed was performed from May 23 to May 30, 2021. The combination of search terms we used was "narcolepsy" and "pitolisant." We used an advanced search strategy with the following terms: (Pitolisant[Title/Abstract]) AND (narcolepsy[Title/Abstract]).Data Extraction and AnalysisWe collected the following information for each study: author and year of publication, methodology, and functional outcomes. Baseline characteristics of the study methods included the number of participants in the treatment, number of participants in the control group, dose route of the administration of the drugs, duration of treatment, and timing when the drugs were given based on the onset of symptoms. Baseline functional outcomes included the Epworth Sleepiness Scale.Bias AssessmentFor assessing bias, we used the Cochrane Collaboration's tool of risk assessment of the clinical trials (RoB 2) and the ROBINS-I tool for the observational studies -17.ResultsFigure In total, five randomized clinical trials (RCT) and one observational study were considered to be eligible for this systematic review. All of them had a control group. Two studies compared pitolisant, modafinil, and a placebo. One study compared pitolisant vs. placebo, whereas another study compared placebo followed by pitolisant (crossover study). One study compared pitolisant, a placebo, and phentermine, whereas one study compared multiple treatments, including sodium oxybate, mazindol, and methylphenidate.Table The severity of narcolepsy is currently assessed using measures of the ability to stay awake. Because EDS is a frequent complaint in sleep disorders, ESS is often used.Limitations of the Clinical Trials of Pitolisant and NarcolepsyThe study by Davis et al. used statistical analyses that were specified after the data were seen, with a short-term (seven to eight-week) study duration, and a relatively small sample size in the cataplexy subgroup . In geneThe study by Dauvilliers et al. had a short duration which prevents the prediction of whether tolerance can develop on continuation. In addition, the flexible dosage and multiple visits could have affected the efficacy, with less responsive patients being more likely to be titrated to the highest dose . The excThe study by Setnik et al. had the primary concern of the generalizability of the results. This study involved single-dose administration of pitolisant in a highly controlled setting to a relatively small population of nondependent stimulant users. However, generalizability to other populations or settings may be limited .The results of the study by Lin et al. need to be confirmed in larger populations and by using an optimized dosage and a double-blind design. The hypothesis that H3-receptor inverse agonists alone, or even more in association with modafinil, improve not only excessive daytime sleepiness but also other symptoms of narcolepsy, such as cataplexy, and remains to be scrutinized in appropriate clinical trials .For analysing the bias in the clinical trials, we used the Cochrane Collaboration's risk tool RoB 2 . For anaThe study by Inocente et al. used a small sample size but the result on ESS was already significant, suggesting a large effect size. The improvement was also visible in the Maintenance of Wakefulness Test (MWT), although it did not reach statistical significance owing to the limited sample size .Table DiscussionFor this systematic review, we used the PRISMA and MOOSE guidelines. The methodology's study included the evaluation of EDS, which was done under the ESS. EDS is the main complaint in sleep disorders and is commonly evaluated using the ESS, which uses eight items to produce a maximal score of 24.For the present study, we analyzed two main narcolepsy symptoms: EDS and cataplexy, meanwhile other symptoms  were not analyzed because they were not well-documented in the trial.Overall, these clinical trials of pitolisant showed good results in reducing sleepiness. In the clinical trials with pitolisant, modafinil, and placebo, they showed improvement for EDS but were non-inferior to modafinil . InteresThe Efficacy and Abuse Potential of Pitolisant Davis et al. showed that the ESS score was significantly reduced from the baseline value in the pitolisant group (-6.1) compared to the placebo  . PitolisThe study of Dauvillier et al. compared the ESS score with modafinil, in addition to pitolisant . ReductiSetnik et al. evaluated the abuse potential of pitolisant at two different doses (35.6 mg and 213.6 mg) compared to phentermine (a substituted amphetamine) and placebo . PitolisThe ESS score in the Lin et al. study showed a reduction of somnolence from a baseline value of 17.6 by 1.0 with the placebo (p = > 0.05) and 5.9 with pitolisant (p = < 0.001), as compared to baseline, appears equivalent to the results obtained after several months of treatment with modafinil . FurtherIn the study of Inocente et al., the ESS score decreased significantly from 14.3 ± 1.1 to 9.5 ± 2.9 (p = 0.03) with pitolisant alone, and even further when combined with mazindol, methylphenidate, or sodium oxybate, plus modafinil (7 ± 3.5) . AdverseThe study by Szakacs et al. improved ESS scores and reduced the weekly cataplexy rate (WCR) in patients with narcolepsy . This waNew Direction in the Treatment of NarcolepsyThe symptomatic treatment of narcolepsy has advanced considerably due to the introduction of new effective drugs approved by the European Medicines Agency (EMA) and the Food and Drug Administration (FDA) .Nowadays, there are several drugs used to treat the two main symptoms of narcolepsy: EDS and cataplexy. Modafinil is the first-line treatment for EDS and may have fewer sympathomimetic effects than amphetamines, but it must be used cautiously in people with a history of arrhythmias or heart disease. Methylphenidate and amphetamines are the second-line treatment for EDS but can generate addiction .Solriamfetol (Sunosi™) was approved by the FDA in 2019. Solriamfetol was studied in a double-blind trial of 236 adults with narcolepsy who were randomly assigned one of the three doses of solriamfetol  or a placebo. The ESS score was significantly reduced from the baseline value, -6.4, -5.4, and -3.8 for the 300 mg, 150 mg, and 75 mg doses of solriamfetol, respectively, and -1.6 with the placebo (p < 0.0001) . SolriamFT218 is a once-nightly formulation of sodium oxybate. In March 2020, a multinational, multicentre, double-blind, placebo-control phase III trial was performed to assess the safety and efficacy of FT218 for the treatment of EDS and cataplexy in patients with narcolepsy. Unfortunately, no safety or tolerability findings have been reported in published abstracts on studies in healthy volunteers. To date, this new drug is under review by the FDA before approval .Study LimitationsThe present study had several limitations. The analysis was based on a systematic review of four RCTs and one observational study that were identified throughout the research and relied upon the availability and accessibility of the publications.Further clinical trials are needed to investigate the effectiveness of the pharmacological treatment for narcolepsy in children, pregnant women, patients with comorbidities, and patients who have narcolepsy with no cataplexy. Also, new severity scales, vigilance tests, and patient-reported outcomes are needed.Pitolisant is the last drug to be introduced in the market to treat narcolepsy. It has shown improvement in reducing sleepiness and fewer adverse effects than the usual medication. After reviewing the studies, we conclude that pitolisant is superior to placebo and non-inferior to modafinil for improving the EDS. Another advantage of pitolisant is the slow abuse potential that it has. Overall, the drug showed significant efficacy of low abuse potential as compared to other drugs. Overall, the drug showed significant efficacy of low abuse potential as compared to other drugs.


Preconception care helps to close the gaps in a continuum of care. It is of paramount importance to reduce maternal and child adverse pregnancy outcomes, increase the utilization of services such as antenatal care, skilled delivery care, and post-natal care, and improve the lives of future generations. Therefore, a validated instrument is required. The purpose of this study was to develop and validate the preconception care improvement scale (PCIS) in a resource-limited setting.A mixed-method study was carried out from 02, March to 10, April 2019 in Manna district, Oromia region, Ethiopia to test the reliability and validity of the scale. Items were generated from literatures review, in-depth interviews with different individuals, and focused group discussions with women of reproductive age groups. A pretested structured questionnaire was used and a survey was conducted among 623 pregnant women in the district. The collected data were entered into EPI-data version 3.1 software and exported to SPSS version 23 software and data were analyzed for internal consistency and validity using reliability analysis and factor analysis.The PCIS has 17 items loaded into six factors: Substance-related behaviors, screening for common non-communicable and infectious diseases, micronutrient supplementation and vaccination, seeking advice, decision and readiness for conception, and screening for sexually transmitted diseases. Factor analysis accounted for 67.51% of the observed variance. The internal consistency  of the scale was 0.776. Diversified participants of the qualitative study and experts’ discussions assured the face and content validity of the scale. Factor loading indicated the convergent validity of the scale. Three of the PCIS subscale scores had a positive and significant association with the practice of preconception care and antenatal care visits, which confirmed the predictive validity of the scale.The PCIS exhibited good reliability, face validity, content validity, convergent validity, and predictive validity. Thus, the scale is valid and helps to improve preconception care, especially in resource-limited settings. During the last four decades, efforts to improve pregnancy outcomes have mainly focused on antenatal care, skilled birth attendants and postnatal care . HoweverPreconception care (PC) is a preventive, promotive or curative health care intervention provided to women of childbearing age before pregnancy and between subsequent pregnancies to improve pregnancy-related health outcomes for women, new-borns and children , 7. It bThe preconception period provides an opportunity to intervene earlier to optimize the health of potential mothers and to prevent risky behaviors. The majority of problems occurring during pregnancy can be addressed before women conceive . EvidencThere are preconception health care tools from high-income countries, particularly from Canada –15. HoweA mixed-methods study was conducted from 02, March to 10, April 2019 in the Manna district, Oromia region, Ethiopia. The qualitative approach used in-depth interviews (IDIs) and focused group discussions (FGDs) with diverse individuals. A total of 623 pregnant women participated in the quantitative study.The scale development process involves complex and systematic procedures that require theoretical and methodological rigor , 22. TheItem development is about coming up with the initial set of questions for an eventual scale. This phase involves identification of the domains and item generation, and consideration of face and content validity.Preconception care is a new concept in Ethiopia and there are no existing validated instruments that can adequately serve the same purpose. We focused on three iterative methods to identify the domains and pool of items that can measure each domain. First, we conducted review of relevant literatures. Accordingly, we identified three domains: behavioural, biomedical and social domains of preconception care. Additionally, the literatures review helped us to identify a pool of 23 potential items that can measure domains. Second, IDIs and FGDs were conducted. A total of 13 IDIs were conducted with women of different age groups, health extension workers, and health care providers of different professions. In addition to IDIs, 4 FGDs were held with women of reproductive age groups. Pregnant women, women who recently gave birth, and women planning to become pregnant participated in each focused group discussion. Semi-structured interview and FGD guides were developed to facilitate in-depth interviews and focused group discussions. The guides were co-designed with the target audience. It was prepared by elicitation with five women and two health care providers. In addition, a detailed discussion was made among the authors considering the research questions during the preparation of the guides. Details about the guides were explained in a separate published article . ParticiA number of individuals participated in IDIs and FGDs, and ideas were gathered from different perspectives. However, the majority of the items elicited from IDIs and FGDs were similar to those obtained from the literatures review. Only 4 new items were obtained from the qualitative study Table . Third, for the sake of becoming pregnant” to each item. Finally, the inputs obtained from different sources enabled researchers to confirm the face validity of the scale.Face validity is established when experts look at the items in the questionnaire and agree that the test is a valid measure of the concept which is being measured just at face value . In the Content validity is the degree to which the sample of items, tasks, or questions on a test is representative of a defined universe or domain of content . ContentThis phase focuses on turning individual items into a harmonious and measuring construct. It involves the pretesting of questions, sampling and survey administration, item reduction, and extraction of factors.A pre-test was conducted in the Saka district among 15 pregnant women. Saka district is the neighbor of Manna district. Based on the findings obtained from the pre-test, some modifications were made to sequences, grammar, word choice, and how to conduct the interview with the target populations. During pre-testing, participants were invited for an opinion on whether they understand questions as developers intended and that respondents are able to answer in a manner that reflects their experience and assess the appropriateness of the questions to the target populations and the strength of the responses. Accordingly, all respondents suggested that the questions and aim of the instrument are clear. However, they suggested the need for rephrasing some items and word choice. Their feedbacks were incorporated into the final version of the tool.A total of 623 pregnant women  who lived in the Manna district at least six months prior to the study period participated in the main survey. The sample size was proportionally allocated to urban and rural gandas. The sampling frames of rural women were obtained from the family folder of the community health information system. For urban, since the family folder did not exist, a census was conducted to construct the sampling frame. The details were explained in the previously published articles, which were part of the current work , 25.A total of 6 data collectors  and 2 public health officers as supervisors were recruited for the main survey. The recruitment was based on their previous experience in data collection and fluency in the language of the community. Extensive training was provided for both data collectors and supervisors on the objectives of the study, data collection tools and collection processes. The details was explained in the previously published articles, which were part of the current work , 25.Analyses were performed using the Statistical Package for the Social Sciences (SPSS) version 23. Principal component analysis (PCA) was performed for item reduction and extraction of factors. Prior to conducting the PCA, the assumptions were examined to determine whether it was appropriate to continue with the specific analysis. Accordingly, sampling adequacy was determined by Kaiser–Meyer–Olkin (KMO), which lies between 0 and 1 where a value of 1 indicates that each variable is perfectly predicted by the other variables. KMO > 0.5 is acceptable . BartletThe extent to which scores on one item are related to scores on all other items on a scale, and the extent to which items on a scale assess the same content were assessed by inter-item correlation. Accordingly, items with very low correlations (< 0.30) were considered less desirable and deleted from the scale. In addition, items with a factor loading of < 0.4 were suppressed. Indeed, Items loaded on multiple factors with factor loading > 0.4 which were very close (< 0.1 difference) were removed from all the factors. However, items loaded on multiple factors with high factor loading showing significant differences across (≥ 0.1), retained on the factor with higher factor loading , 28.We determined the number of components or factors based on: Kaiser Rule, the percentage of variation that is explained, the pattern of factor loadings, and the scree plot. Based on the Kaiser Rule , we retaReliability: is the degree of consistency exhibited when a measurement is repeated under identical conditions. In this study, it was assessed using Cronbach’s alpha coefficients. The Cronbach’s alpha coefficient ranges from 0 to 1, and values between 0.7–0.9 were regarded as an acceptable threshold for reliability [iability , 32.Validity: is the extent to which instruments measure the latent dimension or construct it was developed to evaluate [face and content validity in phase1, item development. Convergent validity is the extent to which a construct measured in different ways yields similar results (e.g. self-report versus observation) [Predictive validity refers to the ability of the questionnaire to measure events, behavior, attitudes, or outcomes in the future [evaluate . In thisrvation) . It can e future . In thise future , 11.The ethical approval was obtained from the Institutional Review Board (IRB) ethics committee of Jimma University institute of health, approval code IHRPGD/356/19 on 01, March 2019. The permission was also sought from the Manna district health office and Ganda leaders. All the study participants were informed about the purpose of the study, their right to refuse at any time, and assured about the confidentiality of the information they provide. Written informed consent to participate in the study was obtained from all the study participants prior to the interview. For participants under 16 years or illiterate participants, written consent was obtained from their parents. All methods were performed in accordance with the relevant guidelines and regulations.A total of 623 pregnant women participated, with a response rate of 98.0%. More than half, 352(56.5%) and 328(52.6%) of the respondents were in the age range of 25–34 years and had no formal education, respectively. A majority, 553(88.8%) of the respondents were living in rural areas. Nearly three-fourth, 462(74.2%) of the participants were housewives (Table p < 0.001), indicating that the correlation between the items was sufficiently large for factor analysis. The extraction was based on Eigenvalues, in which items with Eigenvalues > 1 were fixed. Varimax rotation was used to simplify the interoperability of the factor solution. Small variances with absolute value < 0.4 were suppressed and the remaining variances were sorted by size to display the coefficients from largest to smallest. Then, a series of three rounds of iterative exploratory factor analysis using PCA was carried out to identify a parsimonious list of factors that enable the improvement of preconception care. Each round involves deleting one or more items at a time and examining the remaining items . During the first round of PCA, 3 items were removed due to low factor loading (< 0.4) and the total variance explained was 57.90%. Then, the second round PCA of 19 items extracted six factors with a total variance of 64.77%, with adequate sample size (KMO = 0.793), significant Bartlett’s test of sphericity (p < 0.001). During this round, 2 items were loaded on multiple factors with a factor loading difference of < 0.1 and thus removed from all the factors. Finally, a third-round PCA of 17 items extracted six factors with a total variance explained (VE = 67.51%), KMO = 0.76 and significant P-value (< 0.05) of Bartlett’s test of sphericity. During the third round of PCA, one item was loaded on multiple factors with factor loading > 0.4 and had significant differences (≥ 0.1). Thus, it was retained on the factor with a higher factor loading.The first round of PCA of 22 items extracted seven factors with KMO = 0.804 and significant Bartlett’s test of sphericity , screening for common non-communicable and infectious diseases (4 items), micro-nutrient supplementation and vaccination (3 items), seeking advice (2 items), decision and readiness for conception (2 items), and screening for sexually transmitted diseases (2 items)  was 0.776. Cronbach’s alpha for sub-scales: Factor 1 (substance-related behaviors), factor 2(screening for common non-communicable and infectious diseases) and factor 3(micro-nutrient supplementation and vaccination) were 0.817, 0.780 and 0.761, respectively. All the calculated Cronbach’s alphas were in the acceptable range (0.7–0.9), indicating good reliability of the sub-scales and the scale. However, Cronbach’s alpha coefficient was not calculated for sub-scales with < 3 items Table .Table 5Sp < 0.001), indicating that the variables correlated with one another. Indeed, the factor loading of almost all items loaded on each factor was > 70%, which helps to assure the convergent validity of the scale .This study assessed the face validity, content validity, convergent validity, and predictive validity of the preconception care improvement scale. The face validity of the scale was assessed by experts and the target populations. Content validity was ensured by experts from different disciplines. In addition, a methodological rigor that included comprehensive literature reviews and involvement of diverse participants in IDIs and FGDs helped to give insight into the content validity of the scale (Details are described in Phase 1: Item development). In this study, the content validity was not quantitatively assessed. Convergent validity was examined by performing PCA with varimax rotation. The overall KMO was 0.76. Bartlett’s test for sphericity was significant . Six components of PCIS were extracted. Namely: substance-related behaviours; screening for common non-communicable and infectious diseases; micronutrient supplementation and vaccination; seeking advice; readiness and decision for conception, and screening for sexually transmitted diseases. The psychometric properties of the tool indicated good reliability, face validity, content validity, convergent validity, and predictive validity.r < 0.3), low factor loading (< 0.4), and double loadings at high factor loading but the insignificant difference (< 0.1) caused the removal of the items of the scales [The process of development and validation of PCIS utilized standard procedures followed by most social, health, and behavioural scaling research or guides , 20, 34.e scales , 37. A se scales .The first factor extracted was substance-related behaviors, indicating the need for advising women about avoiding or cessation of substance use before getting pregnant. This was similar to the preconception health behavior scale, hazardous substance factor . The secp < 0.001) Bartlett’s test for sphericity indicated the variables correlated with one another, which was one evidence for convergent validity [r > 0.4) which indicated the convergent validity of the scale [Finally, a 17 items PCIS with six factors was examined for reliability and validity. Reliability analysis showed that the internal consistency  of the scale was 0.776 and in the acceptable range (0.7–0.9), indicating the scale was reliable . Indeed,validity , 45. Thehe scale , 47This study has several strengths and limitations. A key strength of this study is that the PCIS has been validated in a large sample of participants. In addition, it was a community-based study that makes it a representation of the true population. Indeed, the comprehensive literatures review, the involvement of diverse participants in IDIs and FGDS, and the involvement of experts from different disciplines were the strengths of the scale. Furthermore, to the best of the authors’ knowledge, this was the first preconception improvement scale and it can pave the way for researchers to produce other tools. A study never ends without limitations. The potential limitation of this study was that content validity was not quantitatively assessed. The unavailability of PCIS evidence overtime was another critical limitation of this study. Indeed, this study was conducted among pregnant women and thus there was a chance of recall bias. In addition, interviewer bias may also have occurred. Hence, this study shall be tested again broadly in a diverse population.A 17 items PCIS developed with six components  was found to be a valid and reliable scale. Having a validated tool appropriate for the population is really important to bring the desired behavior change. Therefore, PCIS helps to improve preconception care, especially in resource limed settings. The authors recommend researchers to test the scale again among different women of reproductive age groups such as women planning to become pregnant and currently married women.


The goal of this work was to evaluate changes in dietary fiber measured by the traditional enzymatic-gravimetric method (AOAC 991.43) and the more recently accepted modified enzymatic-gravimetric method (AOAC 2011.25), mono- and disaccharides, and starch as a function of assessed ripeness in a controlled study of a single lot of bananas and in bananas at the same assessed stages of ripeness from bananas purchased in retail stores, from different suppliers. Sugars, starch, and dietary fiber were analyzed in bananas from a single lot, at different stages of ripeness, and in retail samples at the same assessed stages of ripeness. Mean fiber measured by the traditional enzymatic-gravimetric method (EG) was ~2 g/100g and not affected by ripeness. Mean fiber assessed with the recently modified method (mEG) was ~18 g/100g in unripe fruit and decreased to 4–5 g/100g in ripe and ~2 g/100g in overripe bananas. Slightly ripe and ripe bananas differed by ~1.1 g/100g in the controlled single-lot study but not among retail samples. There was a large increase in fructose, glucose and total sugar going from unripe to ripe with no differences between ripe and overripe. Aside from stage of ripeness, the carbohydrate composition in retail bananas is likely affected by differences in cultivar and post-harvest handling. Results from this study demonstrate the importance of measuring dietary fiber using the mEG approach, developing more comprehensive and sensitive carbohydrate analytical protocols and food composition data, and recognizing the impact of different stages of maturity and ripeness on carbohydrate intake estimated from food composition data. Musa cultivars characterized by significant genetic diversity, with challenges to banana production from virulent diseases, abiotic stresses, and demands for sustainability, quality, transport, and yield [Musa acuminate, which includes the Cavendish, distinguished by the plant height and familiar features of the fruits [Bananas are one of the most widely consumed fruits according to recent estimates ,2 and rand yield . Accordie fruits .Musa acuminata, “Cavendish”) has been reported to change from approximately 21 g/100g in unripe fruit to approximately 1 g/100g in fully ripe fruit [Carbohydrates are major components of the banana fruit and comprise approximately 20% of the fruit on an as-consumed basis , NDB# 00. Currentpe fruit . During pe fruit  and an ipe fruit .Food composition databases report average nutrient concentrations in foods, primarily for the purpose of estimating dietary intake. When these databases are compiled entries may or may not include the distinction of variables such as ripeness or maturity of fruits and vegetables. For example, the USDA Standard Reference database  reportsThe goal of this work was to evaluate changes in dietary fiber measured by the traditional enzymatic-gravimetric method  and the For the ripening study, the carbohydrate content and composition of bananas (Cavendish) from a single lot of unripe bananas was evaluated at the unripe, slightly ripe, ripe, and overripe stages. Sugars , starch, and dietary fiber were measured by the traditional enzymatic-gravimetric (EG) method (AOAC 991.43) and the newer modified EG (“McCleary”) method (AOAC 2011.25). Medium sized bananas were selected for this comparison. The effect of size was assessed at the unripe and ripe stages by additionally preparing samples of “extra-large” size bananas. Ripeness and size were defined according to specific and consistent criteria. Three samples, each comprising three to five bananas, were prepared for each ripeness/size. The inclusion of multiple bananas was intended to mitigate any variation in the precision of assessed ripeness, and also to provide enough material for analysis of different components. Additionally, samples of medium size ripe bananas were dehydrated and analyzed to gain preliminary data on the effect of dehydration on the dietary fiber content.For the retail study, bananas (Cavendish) were sampled from different local retail markets, without regard to supplier or size, at the slightly ripe, ripe, and overripe stages. Since the goal of this study was to evaluate bananas as purchased and consumed and unripe bananas are not generally presented in retail markets, they were not sampled. Ripeness was assessed according to the same criteria used in the controlled ripening study. These samples were either purchased at the targeted degree of ripeness, or in some cases of slightly ripe or ripe samples some of the bananas were also allowed to ripen and also analyzed at a later stage of ripeness. Thus, the marketplace sampling involved unknown and uncontrolled variables such as producer, country of origin, supply chain, post-harvest handling, ripeness at point of purchase, fruit size. The results from the retail study were then compared to see if the conclusions relating carbohydrate composition and ripeness in the controlled experiment were evident among the marketplace samples.2 (~3.0 m x 0.6 m) countertop with adequate air flow over and around each banana. After removing samples of unripe bananas to be prepared (as described below), the remaining bananas were allowed to ripen at ambient conditions; room temperature was controlled (19–22°C), however, (relative) humidity was uncontrolled (53–77%). At each targeted stage of ripeness, three samples each comprising three (for medium-size samples) or five (for extra-large samples) bananas were prepared for analysis .For the ripening study, three cases of unripe bananas , each containing approximately ~18 kg (40 lb.) and comprising approximately 100 bananas, from the same brand, supplier, and lot were ordered in mid-July 2019 through a local retail outlet . After separating the individual bananas from each hand, they were segregated by size as previously defined and positioned in a single layer over a ~1.8 mOnce the ripeness and sizes of the individual unpeeled bananas had been assessed (as described below), they were peeled, one at a time, and size measurements of the peeled fruits were quickly taken. The fruit was then cut with a stainless steel paring knife into ~1-cm thick slices, immediately frozen in liquid nitrogen, and homogenized in liquid nitrogen using a 6-L Robot Coupe Blixer food processor  as described elsewhere , with suFor the retail study, slightly ripe, ripe, or overripe bananas were sampled directly from local retail outlets , during the first two weeks of December 2019, from multiple brands and countries of origin. A total of six samples at each stage of ripeness were prepared, with ripeness assessed in the same manner as in the ripening study , just before the peeled banana was sliced and homogenized (below), by inserting the 8-mm probe to a depth of 10 mm at each of three places on the fruit .The level of ripeness and size were assessed as summarized in Banana size was defined by length measurement of the unpeeled banana along the outer curve from tip to base of stem, measured with a flexible measuring tape, with “medium” being 21.6–23.5 cm (8.5–9.25 in.) and “extra-large” 28.6–30.5 cm (11.25–12.0 in.). The weight of each banana, unpeeled and peeled, was measured to the nearest 0.1 g, with the “nub” at the base of the banana and any fibrous phloem bundles being removed and included in the peel weight. For ripe bananas, if a peeled fruit had significantly bruised flesh it was excluded and replaced with another banana. Overripe, slightly ripe, and unripe banana flesh was used as is.Quality Control), were shipped on dry ice via overnight delivery to the analytical laboratories , and stored frozen until analyzed. Dietary fiber was determined by two standard enzymatic-gravimetric methods, the traditional EG method (AOAC 991.43) [The sugar, starch, dietary fiber, protein, total fat, and ash assays were performed at certified commercial laboratories using standard methods of analysis. Dietary fiber was determined by two standard enzymatic-gravimetric methods, the traditional EG method (AOAC 991.43)  and the  991.43)  and the  991.43)  (mEG), w 991.43) . Starch  991.43) , with gl 991.43) , ash by  991.43) , and tot 991.43) . Moistur 991.43) .The banana samples were batched with control and/or commercially available certified reference materials for each nutrient analysis. The control materials (CC) had established tolerance limits based on ongoing use in USDA food composition studies . A mixedResults for the CC and RM were evaluated relative to the expected tolerance limits for the CCs and the range from the certificate of analysis as well as the z-score for the assayed mean, calculated according to Engman et al. . AdditioMeans, standard deviations, percent relative standard deviation (RSD) and other calculations were done using Microsoft Excel . Analysis of variance (ANOVA) and Tukey’s test with 95% confidence interval were used for means comparisons  using XLResults for the commercially available reference materials and established in-house control composites support the accuracy of the data . Data foDietary fiber measured by the EG method did not differ by ripeness. However, dietary fiber measured by the mEG method decreased going from unripe to overripe bananas, with a very large difference (14.0 g/100g) between unripe and slightly ripe and smaller changes (1.1–2.3 g/100g) among slightly ripe, ripe, and overripe. Starch followed a similar pattern, with a difference of 9.3 g/100g between unripe and slightly ripe and 1.4–3.0 g/100g among the slightly ripe, ripe, and overripe fruit. Within each ripeness stage, the content of glucose and fructose were similar, and there was no difference in content among slightly ripe, ripe, and overripe bananas, but a 5.0 g/100g difference compared to the unripe fruit. Sucrose was <1 g/100g in unripe fruit, increased to 2.5 g/100g in slightly ripe/ripe bananas, but in overripe fruit dropped to the same level as in unripe. Maltose was <0.5 g/100g in all samples.The composition of the undried and dehydrated ripe bananas were compared on a dry weight basis. Total EG fiber, starch, fructose, glucose, and sucrose contents were unaffected by drying, but mEG total fiber was higher in dehydrated bananas (14.2 g/100g dry weight) compared to the undried bananas (11.6 g/100g dry weight). This analysis was done as an exploratory comparison, but illustrates the possible higher dietary fiber content of dehydrated bananas, presumably from creation of RS3 enzyme-resistant starch . FormatiUnlike in the ripening study, these samples represented different producers, supply chains, lots, post-harvest handling, ripeness at point of purchase, and size. As in the ripening study, there was a small but statistically significant difference (p<0.001) in the moisture content between overripe (78.6 g/100g) and slightly ripe and ripe bananas (75.4 g/100g), but the difference of 3.2 g/100g was not enough to meaningfully impact nutrient concentrations on a fresh weight/as-consumed basis and was similar to the moisture content at each ripeness stage in the ripening study . Table 2For all components except EG fiber, there was wide variability in the concentrations among different samples at the same ripeness. As in the ripening study, there were no differences among ripeness in the dietary fiber measured by the EG method. In contrast to the controlled ripening study, there was no difference in mEG dietary fiber between slightly ripe and ripe bananas. Also, the difference in mean mEG dietary fiber between slightly ripe/ripe and overripe was ~1 g/100g greater. As in the ripening study, starch decreased going from slightly ripe to ripe and ripe to overripe, but the differences were about 1 g/100g larger. The mean concentrations of glucose and fructose at each ripeness stage (~6 g/100g each) and differences among stages of ripeness were similar to those in the ripening study. The mean sucrose content of the retail banana samples did not differ between slightly ripe and ripe bananas and the content in overripe bananas was lower, as seen the ripening study, but the absolute sucrose contents were higher, by ~ 1–1.5 g/100g.Some differences in composition due to size and other criteria that were controlled in the ripening study, but not in selection of retail samples, may have contributed to overall variability among retail samples. For example, in the ripening study, in which the ripe and unripe medium and extra-large size bananas were analyzed, a small but statistically significant (p<0.05) difference was found between sizes for some components. These components and concentrations in g/100g fresh weight were, for medium and extra-large, respectively: EG total fiber  and moisture  in ripe bananas; mEG fiber , fructose , glucose , and moisture  in unripe bananas. Obviously other variables among samples contribute to the larger variability seen among retail samples at the same assessed ripeness.Carbohydrates comprise approximately 70–80% of the dry mass of the unripe banana, consisting of starch (primarily) and non-starch polysaccharides (NSP) , as well as smaller amounts of fragments of the polysaccharides formed during cell wall breakdown and starch catabolism during ripening ,35. The The most striking finding in this study, which looked at the composition of bananas from a macronutrient perspective, was the higher dietary fiber content in unripe and ripe bananas when measured by the currently accepted modified enzymatic-gravimetric method (AOAC 2011.25)  comparedPerhaps the most touted aspect of the mEG compared to the EG method is that it includes non-digestible low molecular weight oligosaccharides (LMWSDF)  present in some foods such as legumes and some fruits ,41. HoweMoreover, the production of limit dextrins and pectic and hemicellulosic oligosaccharides in ripening bananas, which are likely at levels below the limit of detection for LMWSDF in the mEG assay, should be considered. If all of the difference in fiber quantified by the mEG and EG methods was due to resistant starch, the decrease in starch and mEG fiber would be the same. Among the slightly ripe, ripe, and overripe bananas, there was no detectable difference in the amount by which mEG fiber and starch decreased from slightly ripe to ripe and from ripe to overripe (2 g/100g). However, going from unripe to slightly ripe, the difference between mEG and EG fiber exceeded the decrease in starch by 4 g/100g. Better methods to measure the concentrations, composition, and structure of the carbohydrates comprising “dietary fiber” are important given the contemporary focus on the effects of diet on the gut microbiome and its association with health outcomes –45.In bananas, sucrose is derived from the breakdown of starch into maltose and glucose, which are then converted to sucrose through the action of sucrose synthase, and sucrose is then further broken down into glucose and fructose by invertase as the fruit ripens –48. In tThe results for soluble sugars  in some reported ripening studies differed both from each other and from those obtained in the current study –51. ContMusa spp. , different cultivars are widely distributed in the U.S. retail market, including Dwarf Cavendish, Grade Nain, and Giant Cavendish [Also worth noting is that in the present study, whereas the changes in total mEG fiber and starch were in the same direction between stages of ripeness in particular individual samples that were assayed at more than one ripeness compared to the trend in the overall mean, the same was not true for the sugars, where individual samples in some cases showed a large difference in the direction opposite of the mean differences by ripeness see . Our hypavendish . It has avendish ,56, withavendish . Potassiavendish  and repravendish ,59. Staravendish . Growingavendish ,61. ThusThe impact of analytical methods on values should be considered, not only for fiber, but also for sugars and starch. The carbohydrate components expected in banana fruit include starch, non-starch polysaccharides (NSP) , malto-oligosaccharides, limit dextrins, pectin and hemicellulose fragments, monosaccharides and disaccharides. The maltooligosaccharides, limit dextrins, and pectin and hemicellulose fragments are not accounted for in the routine analysis of sugars (defined as mono- and disaccharides) or by the mEG fiber or starch methods. Larger NSP fragments would precipitate as soluble fiber and be included in fiber recovered in the gravimetric portion of the mEG method. However, smaller limit dextrins and some oligosaccharide fragments of the NSP could be missed in the liquid chromatographic portion of the assay , due to The effect of freezing itself does need to be considered in the fiber analysis. Slow cooling and freezing result in retrogradation and production of RS3 resistant starch in cooked high-starch foods . The effIdeally there would be a more direct and comprehensive method for quantifying all individual non-digestible, prebiotic carbohydrates comprising the totality of carbohydrates in a food, using methods with an adequate limit of detection and in which sample preparation and analysis do not involve conditions that alter the food as consumed. Notably, it is possible that particular components have a prebiotic effect at levels that are too low to detect when analyzed in the LMWSDF fraction left over from the mEG fiber assay, in which sample weights and solvent volumes have been optimized primarily for the gravimetric portion of the assay. Newer, high-throughput mass spectrometric methods that quantify carbohydrates and examine linkages ,69 will The impact of changes in the definition of dietary fiber and analytical methodology on food composition data have been discussed previously, especially for foods containing significant amounts of starch that are consumed uncooked/unprocessed . For banThe physiological effects and health outcomes related to dietary fiber intake and different types of dietary fiber have been the subject of extensive research for more than 50 years ,73. In tIn this study, dietary fiber measured by the mEG method versus the EG method was higher by up to ~3 g per medium banana, which is ~20% of the 14g/1000 kcal DRI. For bananas it is therefore recommended that enzymatic-gravimetric dietary fiber be quantified using the mEG method, which provides a better measure of the total non-digestible carbohydrates to which the gut microbiota is exposed. Attention should also be paid to differences in dietary fiber content of bananas as a function of ripeness, especially in the underripe or slightly ripe fruit. The effect of dehydration on dietary fiber content of bananas also suggests caution in imputing the dietary fiber content of dried fruits from values for fresh fruits. An actual difference in dietary fiber content and composition may be a factor in health claims for dried versus fresh fruits  and shouEnergy  was calculated from assayed proximates  using spMusa genus that are widely consumed throughout the world) and experience less starch degradation during ripening [Proximate components were not measured in the ripening study, and only the ripening study involved unripe bananas. However, given the large difference in mEG fiber between unripe and slightly ripe (16.5 g/118g medium banana) and small differences among subsequent ripeness levels (< 3 g/banana), and the fact that there was a small and statistically significant (p<0.05) decrease in energy calculated with the different energy factors for slightly ripe versus ripe bananas, it is reasonable to assume that there would be an even larger difference in the energy content of unripe bananas calculated using the specific Atwater factors. For example, assuming 16.5 g mEG fiber per medium banana and 30 g total carbohydrate by difference, 0.3 g fat, and 0.8 g protein, the specific and adjusted calculated energy contents are 114 and 61 kcal per medium banana, respectively. Any application using unripe bananas (not further cooked) would likely have the energy contribution from the bananas overestimated significantly if the specific Atwater factors for bananas were used for the calculation, as a result of the high content of non-digestible starch. More importantly than absolute energy values, much of the clinical concern about different foods, in particular those high in carbohydrates, involves the glucose/insulin response and what the microbiota are exposed to in the gut. Other fruits and vegetables that are high in starch or fiber are consumed from the unripe to the very ripe stage, including plantains (another group of cultivars of the ripening .Musa genus that are widely consumed throughout the world), are worthy of more detailed analysis of the carbohydrate content and composition and variability in the food as consumed.From an epidemiological perspective, there is a need for more detailed food composition data, including carbohydrate composition, among fruits and vegetables at different stages of maturity and ripeness. This study demonstrated that the dietary fiber, sugar, and starch content of bananas cannot be generalized across ripeness stages, and food composition databases typically do not distinguish between bananas at different stages of edible ripeness. Some of the carbohydrate differences detected in a single lot of bananas analyzed at the slightly ripe versus ripe stage were non-existent in retail samples. Therefore, caution should be exercised in extrapolating results from controlled studies or field studies to the composition of the food as consumed, given myriad other variables in the supply chain. Large differences in dietary fiber measured by the traditional (EG) and more recently modified (mEG) approaches also suggest that more specific, sensitive, and economical methods are needed to characterize and quantify the actual composition of the non-digestible carbohydrates comprising “fiber” and the changes that occur during ripening. As more and more research demonstrates the role of the gut microbiota in health and disease, epidemiologists, nutritionists, and food analysts must move away from the focus on the “dietary fiber” (i.e. non-digestible residue) of foods and towards considering individual components and their effects on the gut microflora. Other fruits and vegetables that are high in starch or fiber and consumed from the unripe to very ripe stage, including plantains Click here for additional data file.


Reduced social functioning in depression has been explained by different factors. Reduced social connectedness and prosocial motivation may contribute to interpersonal difficulties, particularly in chronic depression. In the present study, we tested whether social connectedness and prosocial motivation are reduced in chronic depression. Forty-seven patients with persistent depression and 49 healthy controls matched for age and gender completed the Inclusion of the Other in the Self Scale (IOS), the Compassionate Love Scale (CLS), the Beck Depression Inventory-II, and the Childhood Trauma Questionnaire. A Multivariate analysis of variance (MANOVA) with IOS and CLS as dependent variables revealed a highly significant difference between both groups. The IOS and the CLS-subscale Close Others were lower in persistent depression, whereas there was no difference in the CLS-subscale Strangers/Humanity. IOS and CLS-Close Others showed significant negative correlations with depressive symptoms. Connectedness to family members as measured by the IOS was negatively correlated with childhood trauma in patients with chronic depression. The results indicate that compassion and perceived social connection are reduced in depressed patients toward close others, but not to others in general. Implications for the treatment of depression are discussed. Depression is associated with a low level of social integration and connectedness  and reduAccording to the social identity theory, the impairment of interpersonal relationships and social isolation affects the attachment to close others as well as the belonging to groups, resulting in a loss of social connectedness , 7. A reIn addition, impairment of prosocial motivation may also affect social functioning in depressed individuals. This may be closely related to the reduction of perceived social connectedness. According to Batson et al. , prosociA prominent feature of depression, although not specific to depression alone, is a self-critical attitude . Opposedself-compassion is reduced in depression, research on the role of compassion toward others in depression is sparse. A recent longitudinal study on the relationship between dispositional compassion and depressive symptoms found that among adolescents and young adults, high levels of dispositional compassion predicted lower depression, whereas conversely, depression was not likely to influence compassion  is associated with stronger impairment in life and higher social and economic costs . AlthougMeCBT study  were in the group of chronically depressive patients, and 34 women and 15 men aged 27–69  were in the healthy control sample  developed by Aron et al.  by Sprecher and Fehr , factor two was Gender. The dependent variables were the scores in the Compassionate Love Scale - Close others, the Compassionate Love Scale - Strangers/All of Humanity, and the IOS-Items family, friends, acquaintances and people in general. IOS connectedness to a romantic partner was analyzed in a separate analysis of variance for all participants who filled out the item . The IOS item “romantic partner” was completed less frequently by the chronically depressed patients (N = 30) than by healthy controls (N = 45). We think that the reduced number of romantic partners may be representative for patients with chronic depression. However, due to this difference it is difficult to compare both groups with respect to the “romantic partner” item and results regarding this item should be considered with more caution than the other analyses. Bivariate correlations (Pearson's r) between age, BDI-II, CLS, and IOS scales were exploratively analyzed separately for the two groups. Additionally, among the group of chronically depressed patients, we examined the correlations between the above variables and the CTQ.For the main statistical analysis, we employed a two-factorial MANOVA. Factor 1 was F = 12.05, p < 0.001, F = 3.43, p = 0.004, *Gender  = 2.41, p = 0.034, The MANOVA test using Pillai's Trace showed significant main effects of Group  or interaction effect of Gender by Group on compassion toward strangers/all humanity, as reflected in the CLS scores , healthy individuals  had significantly higher compassion toward close others on the CLS scale, and significantly higher social connectedness on the IOS scale with their romantic partners , family members , friends , acquaintances , and people in general .Univariate analyses  showed nM = 5.85, SD = 1.05) reported significantly more compassion toward close others than men on the CLS scale , and higher connectedness with friends on the IOS scale . With regards to the latter, there was also a significant interaction effect of Group by Gender on social connectedness toward friends, acquaintances, and people in general  compared to a representative sample  = −0.541, p < 0.001, emotional abuse, r(45) = −0.409, p < 0.01, and physical abuse, r(45) = −0.380, p < 0.01 , there was no correlation between severity of depressive symptomatology and connectedness or compassion. However, within the healthy control group , there were a significant negative correlation between depression and connectedness with a romantic partner, and low or non-significant negative correlations between depression and connectedness with the other groups of people  = 0.681, p < 0.05), whereas there were no significant correlations in depressed women. No significant correlations were also found in healthy men, while there was a significant moderate correlation between severity of depression and connectedness with a romantic partner in healthy women (r(29) = 0.413, p < 0.05). However, due to the small number of participants within the subsamples, these results should be interpreted with great caution.The lack of correlations between depression severity and social connectedness encouraged us to explore possible interactions with gender , a differential pattern occurred with respect to compassion. On the one hand, patients with chronic depression also reported significantly reduced compassion to close others. This result is consistent with findings of reduced dispositional compassion  and reduempathic concern ; Ethics Committee of the Faculty of Psychology and Sports Sciences at Goethe University Frankfurt . The patients/participants provided their written informed consent to participate in this study.US conceived the study and obtained ethical approval. AF, IT, SH, and SW contributed to conception and design of the study. IT and AF coordinated recruitment and data collection. AF performed the statistical analysis. AF and US drafted the article. SH and SW contributed to the review of literature and proofread the manuscript. AF edited the final manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.SH was supported by the James S. McDonnell Foundation 21st Century Science Initiative in Understanding Human Cognition - Special Initiative. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Results: The comparison between the two groups did not identify significant differences (p > 0.05) between the flexor hallucis brevis (FHB), flexor digitorum brevis (FDB), quadratus plantae (QP) and abductor hallucis brevis (AHB) variables for the EI and EV. Moreover, excellent intra-rater reliability was reported for the following ultrasound imaging EI variables: ABH (ICC = 0.951), FHB (ICC = 0.949), FDB (ICC = 0.981) and QP (ICC = 0.984). Conclusions: The muscle quality assessment using the EI and EV variables did not identify differences in the FHB, FDB, AHB and QP muscles between individuals with and without PF through USI evaluation. The reliability of all the IFM measurements was reported to be excellent.Objective: The primary aim of the present study was to compare the echo intensity (EI) and echovariation (EV) of the intrinsic foot muscles (IFMs) between individuals with and without plantar fasciitis (PF), using ultrasound imaging. The secondary objective was to study the intra-rater reliability of the echotexture variables. Methods: A case–control study was conducted with 64 participants, who were divided into the following two groups: A, the PF group ( At present, plantar fasciitis (PF) is considered to be one of the main foot disorders, with an estimated prevalence of 7% in the general population , and amoSeveral authors consider PF to have a multifactorial etiology; for example, a systematic review carried out by Rhim et al. reported a broad range of intrinsic and extrinsic risk factors in the context of PF ,11,12. TIntrinsic foot muscles (IFMs) play a key role in providing movement and stability to the ankle and foot; for example, they act as a support for the foot arches . IFMs, sLately, the ultrasound imaging (USI) technique has been employed for the assessment of ankle and foot structures; for example, Wu et al. argued that ultrasonography is a reliable method for the evaluation of the plantar fascia . ArchiteThe study design comprised a cross-sectional investigation carried out from August to September 2021. The present study was a secondary analysis from a prior research about quantitative ultrasonography variables . Informan = 32) and the healthy group (B) (n = 32). Inclusion criteria for the PF group were as follows: heel pain for at least 1 month, tenderness and discomfort in the middle of the plantar fascia or in the medial calcaneal tubercle during palpation and immediate pain upon waking up or after non-weight-bearing activities, such as working in a seated position [A total of 64 volunteers, aged 18 to 55 years old, were enrolled for the present study. The sample was divided into the following two groups: the PF group (A) , with an effect size of 0.86, a one-tailed hypothesis, a power of 0.80 and an α error of 0.05. Thus, a total sample of 64 participants was calculated. G*Power software was employed to develop the sample size calculation.The calculation of the sample size was developed by a prior analysis for the FHB CSA variable in a pilot study  was also calculated.A high-quality Mindray DC-60 with a 6 to 14 MHz linear transducer (L14-6NE) was used to measure all the variables. IFM thickness variables were recorded following the guidelines reported by Mickle et al., with subjects placed in the supine position with the knee slightly flexed . The thip-value < 0.05 to be statistically significant, with a 95% confidence interval (CI). The Kolmogorov–Smirnov test was used to check the normality assumption. The mean and standard deviation (SD) were calculated, and Student’s t-test was performed for parametric data, while the median, interquartile range (IR) and Mann–Whitney U test were employed for non-parametric data. Additionally, Levene’s test was used to check the equality of variances. The intra-class correlation coefficient (ICC) was developed in order to analyze the intra-rater reliability between trials.SPSS v.22  was employed to carry out the statistical analysis, with an alpha error of 0.05, considering a Subsequently, in order to reduce bias for grouping selection, a linear regression model was run for each independent sociodemographic variable and each dependent ultrasonography variable.n = 32) and healthy groups (n = 32), and they showed significant differences (p < 0.05) in age, weight and body mass index (BMI) between the two groups. The comparison between the outcome measurement differences between the groups showed that the differences were not significant (p > 0.05) for the FHB, FDB, QP and AHB variables for the EI and EV . Thus, there was no bias in sociodemographic variables in either group.The linear regression results show non-significant differences for all of the dependent variables checked . In the same context, Almazán-Polo et al. did not observe significant differences in the EV parameter in individuals with lumbopelvic pain, with respect to healthy subjects . At presThe assessment of muscle and soft tissue quality in B-mode USI, whilst studying the pixel intensity, could be useful. Thus, evaluating the IFM echotexture in subjects with PF may provide additional information about the fatty muscle infiltration and soft tissue features which could be related to the contraction capacity and contractile features of the muscle. The present study reported that patients diagnosed with PF did not present higher EI values than the controls, suggesting that the IFMs did not present atrophy or neural disturbances. In addition, the quality assessment, combined with the quantity evaluation by USI and the clinical orthopedic test, should be considered a priority for the diagnosis and management of patients with PF. However, more studies are still necessary in this field of research to expand the knowledge about ultrasonography quality assessment and the neuromusculoskeletal system in individuals with and without PF.Some limitations of the present study should be acknowledged. Firstly, the main limitation was that the USI assessment was not performed by a blinded operator, which could increase the risk of bias. Secondly, there were differences in the BMI between the two groups, and this must be considered in the interpretation of the results, given that the BMI has been associated with hypertrophy of the plantar fascia and intrinsic foot muscles (38). Finally, neural disturbances directly affect the musculoskeletal system, and no neural tests were developed in the present study. Future studies should match age and BMI between both groups. In addition, future research with novel ultrasound systems, such as elastography or M-mode, are needed to assess soft tissue stiffness and mobility.The muscle quality assessment using the EI and EV variables did not report significant differences in the FHB, FDB, AHB and QP muscles between individuals with and without PF, evaluated using USI. Nevertheless, excellent reliability was reported for all the IFM measurements. Evaluation of the muscle quality of the musculoskeletal tissue could aid clinicians and researchers, but more studies are required to provide a deeper understanding, and a solid base to establish USI examination protocols.


Recent literature suggests that sarcopenia, often represented by low lower limbs muscle mass and strength, can be considered a potential risk factor for knee osteoarthritis (OA), but the available literature is still limited. We therefore aimed to investigate whether sarcopenia is associated with a higher risk of radiographic (ROA) and symptomatic knee OA (SxOA) in a large cohort of North American people in the context of the OA initiative. Sarcopenia at baseline was diagnosed in case of low skeletal muscle mass  and poor performance in the chair stands test. The outcomes of interest for this study included ROA  if a knee developed a Kellgren and Lawrence (KL) grade ≥2 at follow-up, and SxOA (symptomatic osteoarthritis) defined as new onset of a combination of painful knee OA. Altogether, 2,492 older participants  were included. At baseline, sarcopenia was present in 6.1% of the population. No significant difference in ROA prevalence was observed between those with and without sarcopenia (p=0.76), whilst people with sarcopenia reported a significant higher prevalence of SxOA (p<0.0001). Using a logistic regression analysis, adjusting for potential confounders at baseline and the diagnosis of sarcopenia during follow-up, sarcopenia was associated with a higher incidence of knee SxOA , but not knee ROA . In conclusion, sarcopenia could be associated with a higher risk of negative knee OA outcomes, in particular symptomatic forms. Osteoarthritis (OA) is the most prevalent type of arthritis  and a veBased on the latest revised European consensus on definition and diagnosis , 10, sarEven though sarcopenia often accompanies OA , the asshttps://nda.nih.gov/oai/). In the OAI, participants were recruited across four clinical sites in the United States of America  between February 2004 and May 2006. In the OAI project, individuals were included if they: (1) had knee OA with knee pain for a 30-day period in the past 12 months or (2) were at high risk of developing knee OA  (Data for this study were obtained from the Osteoarthritis Initiative (OAI) database (knee OA) . For theAll participants provided written informed consent. The OAI study was given full ethics approval by the institutional review board of the OAI Coordinating Center, at the University of California in San Francisco.For the definition of sarcopenia, we used the criteria of the revised European consensus on the definition and diagnosis of sarcopenia . SarcopeSMM was calculated based on the equation proposed by Lee and colleagues : SMM= 0.At baseline and during follow-up examinations, individuals had full knee assessments which included both clinical and radiographic examinations. A fixed flexion posterior–anterior radiograph, which was read centrally for Kellgren and Lawrence (KL) grade, was made for all the participants. In addition, participants were asked regarding knee pain, the following question: ‘During the past 30 days, have you had pain, aching, or stiffness in your right/left knee on most days?’.The outcomes of interest for this study included: (1) ROA  if a knee developed a KL grade ≥2 at follow-up among those without this condition at baseline and (2) SxOA (symptomatic osteoarthritis), defined as the presence of a combination of painful knee OA. The assessment of the knee OA outcomes was made, other than at baseline, at V01 (12 months), V03 (24 months), V05 (36 months), and V06 (48 months).Several covariates at baseline other than age and sex were identified as potential confounding factors based on previous literature . These iData on continuous variables were normally distributed according to the Kolmogorov-Smirnov test. Data were consequently presented as means and standard deviation values (SD) for quantitative measures, and percentages for all categorical variables by the presence or absence of sarcopenia at baseline. P values were calculated using an independent T test for continuous variables and a chi-square test for categorical parameters.To assess the association between sarcopenia and the outcomes of interest during follow-up, a logistic regression analysis was applied, since a survival analysis was not possible due to lack of information on the precise date of event. The basic adjusted model included age and gender. The fully adjusted model included all parameters associated with the outcomes of interest  or significantly different between sarcopenic and non-sarcopenic subjects . Multi-collinearity among covariates was assessed through variance inflation factor (VIF) , taking ® software version 21.0 for Windows .A p<0.05 was deemed statistically significant. All analyses were performed using SPSSThe OAI database initially included a total of 4,796 participants. We excluded 2,211 individuals since they were less than 60 years of age, 52 since no data regarding body composition or chair stands time were available, and 41 for not having data regarding race. Therefore, 2,492 participants were included, as shown in The cohort consisted of 1,529 females (61.4%), with a mean age of 68.4 years . The prevalence of sarcopenia at baseline was 6.1%, affecting 153 subjects. At baseline, 58% were affected by knee ROA and, of them, 24.4% knee SxOA.During the four years of follow-up, the incidence of ROA was 10.7% and that of SxOA 46.9%. As shown in In this research involving 2,492 older people, we found that the presence of sarcopenia at baseline was significantly associated with a higher risk of symptomatic knee OA, over four years of follow-up.The overall prevalence of sarcopenia at baseline in our study was just under 10%, which is in accordance to the latest systematic review and meta-analysis of general population studies . The exiOther works already explored the potential association between sarcopenia and knee OA outcomes in older people. Recently, Andrews et al. reported that sarcopenia could be associated with a higher risk of sarcopenia, in Health, Aging, and Body Composition participants . InteresFor example, physical exercise interventions could be suggested in people with sarcopenia and without symptomatic knee OA since this kind of intervention is able to prevent further muscle mass loss , incidenThe strengths of our study are the long duration of follow-up, the several knee OA outcomes assessed, and the large sample size included. However, our findings should be interpreted within some important limitations. First, the participants of the OAI were at high risk or already had knee OA. Thus, our results cannot be extended to the general population. Second, the observational nature of our findings can introduce another bias in our results, although we tried to correct this limitation using analyses adjusted for potential confounders. Finally, body composition was based on a population equation and not on direct assessment. However, this has been validated against gold standard methods such as magnetic resonance imaging and dual-energy X-ray absorptiometry . At the In conclusion, our study suggests that sarcopenia could be associated with a higher risk of negative knee OA outcomes and in particular symptomatic forms. Our findings further suggest the importance of early detection of sarcopenia, in order to implement appropriate preventive treatment against the progression of knee OA.https://nda.nih.gov/oai/.The dataset supporting the conclusions of this article is freely available in The OAI study was given full ethics approval by the institutional review board of the OAI Coordinating Center, at the University of California in San Francisco. The patients/participants provided their written informed consent to participate in this study.Manuscript preparation, NV, SiS, NA-D, and ShS. Critical revision, SM, LS, CC, RR, and J-YR. Data interpretation, MB, and LD. Statistical analysis, NV. All authors contributed to the article and approved the submitted version.The authors thank the support of the Researchers Supporting Project (RSP-2021/21) King Saud University, Riyadh, Saudi Arabia. The OAI is a public-private partnership comprised of five contracts  funded by the National Institutes of Health, a branch of the Department of Health and Human Services, and conducted by the OAI Study Investigators. Private funding partners include Merck Research Laboratories, Novartis Pharmaceuticals Corporation, GlaxoSmithKline, and Pfizer, Inc. Private sector funding for the OAI is managed by the Foundation for the National Institutes of Health. This manuscript was prepared using an OAI public use data set and does not necessarily reflect the opinions or views of the OAI investigators, the NIH, or the private funding partners.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.