Fibroids have been identified as a possible risk factor for preterm birth, however, the magnitude of this risk is unclear. Our objective was to determine the risk of total, spontaneous, and medically indicated preterm birth in women with fibroids.A literature search was performed on 9 June 2021. We selected studies reporting on preterm birth in women with and without fibroids. Fibroids had to be diagnosed by routine ultrasound before or during pregnancy. Main outcomes were total preterm birth <37, <34, <32, and <28 weeks of gestation, and spontaneous and medically indicated preterm birth. Two authors independently performed study selection, data extraction and quality assessment. We performed quality assessment with the Newcastle-Ottawa scale. Meta-analyses were presented as Odds Ratios (ORs) with 95% Confidence Intervals (95%CIs).The search yielded 2078 unique articles of which 11 were included. Meta-analysis for preterm birth <37 weeks of gestation included 256,650 singleton deliveries: 12,309 with fibroids and 244,341 without fibroids. Women with fibroids had a higher rate of preterm birth . Fibroids were also associated with preterm birth <34 , <32  and <28  weeks of gestation. Data on type of preterm birth was limited: one study showed a significant association of fibroids with spontaneous preterm birth and another with indicated preterm birth. The main limitations of the included studies were the lack of correction for confounders, the risk of ascertainment bias due to possible underreporting of fibroids, and the substantial heterogeneity between studies.Our results suggest fibroids are associated with an increased risk of preterm birth, with a stronger risk at earlier gestational ages. We encourage further research to clarify the association between fibroids and preterm birth by systematic myometrial assessment in pregnancy.CRD42020186976].Prospero database [ Worldwide 15 million babies are born preterm each year . ApproxiPrevious reviews have suggested that women with fibroids have an increased risk of preterm birth , 6. BothTo quantify the risk of preterm birth in women with fibroids compared to women without fibroids, we performed a systematic review and meta-analysis. Furthermore, we aimed to differentiate spontaneous from medically indicated preterm birth, and to evaluate how fibroid characteristics  modify the risk of preterm birth.S1 Appendix) [This systematic review was reported according to the PRISMA guidelines for systematics reviews and meta-analyses (ppendix) . No fundS2 Appendix. No language, publication date or other restrictions were applied. All duplicates were excluded using EndNote. A cited-reference search was performed to identify potential additional relevant studies.A systematic literature search was performed by a medical information specialist (JK) and two researchers (GV and AL) on 9 June 2021 in the following databases: PubMed, Embase and Web of Science. The search terms included both keywords as well as free text terms for ‘fibroids’ and ‘preterm birth’, along with their synonyms. The search strategies are presented in Original studies reporting on the risk of preterm birth in women with and without fibroids were eligible for the present systematic review and meta-analysis. To limit the risk of the opportunistic detection  of fibroids, the fibroids had to be diagnosed by routine ultrasound or other imaging before or during pregnancy, indicating we excluded studies that, for example, included women that were admitted to the hospital or selectively referred for ultrasound screening. We also excluded studies including women with multiple gestations due to their increased baseline risk of preterm birth, and studies reporting on preterm birth after surgical or non-surgical treatment of fibroids as this treatment may have influenced obstetric outcome. Furthermore, conference abstracts, case reports, case series, reviews and guidelines were excluded. For the purpose of feasibility, we excluded non-English articles. The main outcomes were preterm birth <37, <34, <32 and <28 weeks of gestation. In addition, we aimed to differentiate between the spontaneous onset of preterm birth following either the onset of contractions or rupture of membranes, and medically indicated preterm birth due to maternal or fetal complications. Other relevant outcomes were preterm prelabour rupture of membranes (PPROM) and mid-trimester fetal loss (between 16 and 22 weeks of gestation).Two authors (GV and AL) independently performed screening of all potential articles using Rayyan . First s The final judgement of quality was summarised in a risk of bias table. No assessment of certainty was planned in the protocol.We used the Newcastle-Ottawa Quality Assessment Scale (NOS) for nonrandomised studies to evaluate the validity of the included studies . We sligTwo authors (GV and AL) independently extracted data from the included articles and performed quality assessment. We collected data on author, year and country of publication, language, publication status, start date and end date of the study, ethical approval, type and source of funding, study design, sample size, population characteristics , diagnostics method used for the identification of uterine fibroids, fibroid characteristics , past treatment of fibroids , the outcome measures as described previously, and key conclusions. Corresponding authors of the included articles were contacted for further information if relevant outcomes or other data were not presented in the original publication. Discrepancies in data extraction and quality assessment were resolved by discussion and consulting a third author (MdB).X2 and I2 statistics and possible publication bias was assessed with a funnel plot. We performed a pre-planned sensitivity analysis of good-quality studies. In addition, we planned to perform subgroup analyses based on the size, number, location and vascularisation of the fibroids; parity, a history of previous miscarriages or preterm birth, and a history of dilation or curettage. Statistical analyses were performed using Review Manager (RevMan 5.3.5) and R Studio .Outcome event rates and crude odds ratios were calculated based on the number of deliveries. If studies included miscarriages in their results, these were excluded from the sample size. If studies were unclear about in- or exclusion of miscarriages in their sample size, we used the reported sample size for our calculations. The meta-analysis included adjusted odds ratios (ORs) of those studies that corrected for confounders and crude ORs of studies that did not. We used a random-effects model with the generic inverse-variance method , 24. As The search provided 2078 unique articles which were assessed for eligibility . One addThe included studies were conducted between 2009 and 2015. Five of the studies were cohort studies , 26, 39 Baseline characteristics of the included study populations are described in According to the Newcastle-Ottawa scale, seven of the included studies were of good quality , 41, 42,2 = 43.99, p<0.01; I2 = 77%). Meta-analyses also showed a significant association of fibroids with preterm birth <34, <32, and <28 weeks of gestation and the strength of this association increased with preterm birth at earlier gestational ages . The medical indications leading to these preterm birth were not reported. There was no difference in spontaneous preterm birth between the fibroid group (5/154 = 3.2%) compared to the control group ; RR 0.77 (95% CI 0.33–1.84) . Convers2 = 14.96, p = 0.04; I2 = 53%). An overview of the crude and adjusted effect sizes per study and outcome can be found in Eight studies reported on PPROM, including 212,348 women: 6,122 in the fibroid group and 206,226 in the control group , 42. MetGood quality studies were included in sensitivity analyses . All the2 = 13.29, p = 0.02; I2 = 62%). Meta-analyses did not show differences in preterm birth <37 weeks of gestation when comparing large (>5 cm) to small (≤5 cm) fibroids , nor when comparing multiple to single fibroids . No subgroup analyses could be performed on fibroid location , vascularisation, FIGO classification or other ultrasound features. Neither could we perform subgroup analyses based on parity, a history of previous mid-trimester fetal losses or preterm birth, or a history of dilation and curettage.The results of the subgroup analyses based on fibroid characteristics are shown in The present meta-analysis, including 11 studies and 256,650 deliveries, suggests uterine fibroids are associated with preterm birth. This association was present for preterm birth <37 weeks of gestation and became stronger with preterm birth at earlier gestational ages <34, <32 and <28 weeks. Moreover, the association with preterm birth <37 and <34 weeks of gestation was also significant in sensitivity analyses including good-quality studies. No association was found between PPROM and the presence of fibroids. No distinction could be made between spontaneous and medically indicated preterm birth in meta-analyses. This distinction is crucial for the interpretation the study results due the disparate underlying aetiologies of these types of preterm birth. Only two included studies made this distinction: one included study showed an association between spontaneous preterm birth and the other showed an association with medically indicated preterm birth. No conclusions can be drawn from these limited data.There is insufficient evidence to conclude whether the size or number of fibroids modifies the risk of preterm birth or not. Other potentially relevant fibroid characteristics have not been reported in the included studies. Fibroid activity, for instance, may be important in the genesis of preterm birth. Fibroid activity could be determined by assessing vascularisation, fibroid growth, signs of degeneration, signs of calcification or other MUSA criteria , 47.Two past reviews also found an association between fibroids and preterm birth. Klatsky et al. found a preterm birth rate of 16.0% in the fibroid group and 10.8% in the control group , and Perez-Roncero et al. of 11.7% versus 9.0%  [We did not identify any studies that reported on mid-trimester fetal loss between 16 and 22 weeks of gestation. These mid-trimester fetal losses are often included in the group of miscarriages defined as loss <20–24 weeks of gestation. A recent systematic review and meta-analysis concluded that the risk of miscarriage, including mid-trimester fetal losses, was not increased in women with fibroids in a general obstetric population . HoweverWe performed an in-depth evaluation of preterm birth in women with fibroids, and a meta-analysis including confounder-adjusted effect sizes. We also performed sensitivity analyses including good-quality studies. Nevertheless, the results of our study should be interpreted in light of the following considerations. Not all studies controlled for or matched for all relevant confounders , and there still might be residual confounding present.We minimised the risk of ascertainment bias by excluding studies with women who were selectively referred for ultrasound screening. However, even when routine prenatal ultrasound screening is performed, there is a risk of underreporting of fibroids in the absence of a prospective protocol for myometrial assessment because the primary focus lies on the fetus rather than the uterine wall. Moreover, ultrasound screening in the second and third trimester also leads to underreporting, as not all fibroids, especially those located in the posterior uterine wall, can be visualised due to the size of the fetus. It seems impossible to quantify the frequency of undiagnosed fibroids in these studies. As the risk of the opportunistic recording of fibroids is likely smaller with larger fibroids, we performed a subgroup analysis including studies that compared fibroids >3 cm and >5 cm to women without fibroids. In this analysis, there was still a significant association present between fibroids and preterm birth. This association was stronger for fibroids >3 cm than for fibroids >5 cm, but uncertainty is large due to the wide confidence interval in the subgroup of fibroids >3 cm. This is probably a consequence of a small number of studies, including one study with an outlying effect size.Finally, there was substantial heterogeneity between studies, which might have been caused by variations in study populations and methodology. There was a wide range in the prevalence of fibroids between studies. This is probably a reflection of differences in ethnicity, as the lowest prevalence of fibroids was found in a French study and the higher prevalence in a Cameroonian study. However, selection bias resulting from opportunistic reporting could also play a role. Furthermore, variations in exposure definitions of fibroids and lower gestational age cut-offs may have caused heterogeneity by differential misclassification.Based on our findings, systematic myometrial assessment before or during the first trimester of pregnancy is warranted. Future studies should have a protocol for prospective fibroid assessment on ultrasound including evaluation of fibroid size, number, FIGO classification, location  growth, and ultrasound features such as vascularisation, degeneration, and calcification , 47. RegThis systematic review and meta-analysis suggests fibroids are associated with total preterm birth and this association is stronger with earlier gestational age of the preterm birth. However, the considerable amount of heterogeneity between studies may indicate biased results. Considering the magnitude of the disease burden of preterm birth, as well as the biological plausibility of an association between preterm birth and fibroids, we encourage further research to clarify this association through prospective and systematic myometrial assessment in early pregnancy. Finally, it is important that these studies distinguish between spontaneous and medically indicated preterm birth.S1 Appendix(PDF)Click here for additional data file.S2 Appendix(PDF)Click here for additional data file.S3 Appendix(PDF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S3 Table(PDF)Click here for additional data file.S1 Fig(TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S3 FigSensitivity analyses of good quality studies for preterm birth (A) <37 and (B) <34 gestational weeks and (C) PPROM. * indicates studies that corrected for potential confounders.(TIF)Click here for additional data file.S4 FigMeta-analysis of (A) fibroids >3 and >5 cm compared to women without fibroids; (B) large versus small fibroids; and (C) multiple versus single fibroids. * indicates studies that corrected for potential confounders.(TIF)Click here for additional data file.


However, in Ida-Viru ICS, the ABOs odds are remarkably higher in these characteristics except for the mother’s ethnicity. Furthermore, the ABOs are associated with the residential proximity to ICS. Thus, the Ida-Viru ICS has unequally higher odds of adverse perinatal health across the environmental and sociodemographic factors. In addition to reducing the air pollutants, policy actions on social disparities are vital to address the country’s unjustly higher perinatal health inequalities, especially in the Ida-Viru ICS.Despite the increasing number of studies on industrially contaminated sites (ICS) and their health effects, there are very few studies on perinatal health outcomes in ICSs. In the present study, we examined the perinatal health inequalities by comparing adverse birth outcomes (ABOs) in the oil shale industry region of Ida-Viru County in Estonia with national-level figures and investigated the effects of maternal environmental and sociodemographic factors. Based on the 208,313 birth records from 2004–2018, Ida-Viru ICS has a birth weight 124.5 g lower than the average of 3544 g in Estonia. A higher prevalence of preterm birth (4.3%) and low birth weight (4.8%) in Ida-Viru ICS is found compared to 3.3% on both indicators at the national level. Multiple logistic regression analysis shows the statistically significant association of ABOs with fine particle (PM Health is affected by numerous individual, social, and environmental characteristics ,2. The sSystematic reviews have shown significant socioeconomic disparities in ABOs ,15. ABOs2.5) often emitted in higher concentrations in ICS, has shown associations with low birth weight (LBW) [2.5 is associated with PTB. Similarly, numerous studies on particulate matter (PM10) from industrial sources have shown the effect on LBW [Studies focusing specifically on ICS and ABOs are few; however, a recent systematized review on industrial air pollutants found that birth outcomes are affected by maternal exposure to industrial air pollutants and living closer to industrial areas . Consideht (LBW) ,22,27,28ht (LBW) ,22,27,29ht (LBW)  meta-anat on LBW ,32,33,34t on LBW .A growing body of literature on spatial indicators suggests a strong association between proximity to power plants and LBW ,24,36,37Often, the socioeconomically deprived or marginalized population tends to live in or close to the industrially contaminated sites ,47. StudIn terms of the individual factors, maternal health status also affects birth outcomes, for instance, chronic conditions such as diabetes, hypertension, increased blood sugar during pregnancy, and preeclampsia ,53. AdvaDespite the growing literature on the health impacts of ICS , there aIn this study, we focus on the perinatal health inequalities in an ICS, the oil shale industry region of Ida-Viru County in Estonia. Estonia is one of the highest greenhouse gas emitters per capita in OECD ,58,59 anIn addition to the inequalities in environmental exposures, Ida-Viru also has lower SES, and specific ethnicities  dominate the county . GeneralIn this article, we aim to explore the perinatal health inequalities across the different populations in the Ida-Viru ICS. We adopted Dahlgren and Whitehead’s definition of health inequalities as the socially produced systematic and unjust differences in health across the population . We willHow does maternal exposure to air pollutants affect birth outcomes in Estonia? How does Ida-Viru ICS differ from the nationwide Estonian figure?How does the maternal residential proximity to ICS affect birth outcomes?How are the maternal sociodemographic characteristics associated with ABOs? Moreover, how different is Ida-Viru ICS in these characteristics?In the current study, birth registry data on singleton births were obtained from the Estonian Medical Birth Registry from 1 January 2004 to 31 December 2018. All registered birth in Estonia include data on maternal and neonatal characteristics, including demographics. Neonatal characteristics obtained from the birth registry included personal identification code, date of birth, gender, live or stillbirth, gestation days, and birth weight. In Estonia, gestational age is predominantly determined by ultrasound, and birth weight is measured immediately after the baby is born. The ABO indicators used in the article are preterm birth (PTB: ≤37 weeks of gestation) and low birth weight . LBW and PTB were dichotomously coded and used as the birth outcome indicators. Maternal sociodemographic characteristics and maternal health status that are identified or suspected confounders for ABOs obtained from the birth registry are the level of education, ethnicity, age, preeclampsia, in vitro fertilization, earlier cesarean delivery, preterm birth risk during pregnancy, miscarriage risk during pregnancy, hypertension, chronic diabetes, and gestational diabetes. Data on smoking during pregnancy recorded in the birth registry were excluded due to the self–reported data reliability issue. The county-level income coefficient from 2004–2018 from Statistics Estonia was obtained and used as an indicator of neighborhood SES.10), fine particles (PM2.5), and nitrogen dioxide (NO2) concentrations were calculated for each child according to daily average data in the nearest representative urban background air quality monitoring station ); see the detailed description in the Airviro Documentation [10, PM2.5 and NO2) reported by companies and validated by the Estonian Environmental Board. Same year transport–sector emissions came from the traffic emissions database Traffic2017, domestic heating emissions from the local heating emissions database Localheating2017, both compiled by Estonian Environmental Research Center, and agriculture emissions. The modeled concentrations were validated with measurement data obtained from the monitoring stations all over Estonia and with concentrations measured by passive samplers. For visualization, the model output was generalized and classified into seven classes, using the ArcGIS  scripting environment ArcPy. In ArcGIS, the annual concentrations of modeled pollutants per grid cell were linked with the geocoding of each child’s home address at the moment of birth. During the geocoding, the geographical coordinates of the address points were found according to the textual addresses. The public geocoding service of the Land Board was applied, which is available on the website as Address Data Geocoding [The exposure assessment included two levels of assessment: a combined method using measured and modeled data to catch temporal and spatial differences, and residential proximity to the oil shale industry. For the combined method of measuring and modeling the air pollution, first, the measured particulate matter , proximities to oil shale industrial sites , and maternal sociodemographic characteristics . Logistic regression comprised three models: first, the crude model for the association between exposure and outcome variables; a second adjusted model for the individual-level sociodemographic variables , a third fully-adjusted model adjusting for the individual–level sociodemographic variables including the status of pregnant mother . The third model is also adjusted for neighborhood SES in the analysis with residential proximity and social markers.First, we compared the prevalence of ABOs and their distribution in relation to social markers of Ida-Viru County (newborns whose mother’s place of residence was indicated in the birth register as Ida-Viru County) with the national level. Second, multiple logistic regression analysis was performed to analyze the relationship between birth outcomes and exposure to air pollutants  air quality guideline level (5 µg/m3) [10 remained below the recommended level (15 µg/m3) [2 was below the WHO recommended level of 10 µg/m3 [The annual average concentrations of PM5 µg/m3) , except 5 µg/m3)  since 2010 µg/m3  in Kohtl10, PM2.5, and NO2 can be observed among the newborns in different groups  over the period 2004–2018 during the first and third trimesters  per 10 µg/m3 increase in exposure; however, in the crude model , whereas the association was insignificant at the national level. Exposure to PM10 was not significantly associated with ABOs at both the national and county levels in all models. In the crude model, significant opposite association with LBW with NO2 was shown (3 increase in exposure).de model , the assas shown  but not as shown  exposureThe crude and adjusted model  showed tThe analysis on the effect of mother’s education  shows th2.5 during the first trimester increased the risks of PTB at the national level, while exposure during the third trimester increased the risks of LBW in the Ida-Viru region. Exposure to BaP during whole pregnancy also affected the LBW in Ida-Viru ICS. Living close to the oil shale industries significantly affected the birth outcomes.The current study aimed to investigate perinatal health inequalities in the ICS of Estonia, Ida-Viru oil shale industrial region. The results reported above show a higher prevalence of LBW and PTB in Ida-Viru County than at the national level. Perinatal health inequality is demonstrated through the significantly higher odds ratio in the industrial region of Ida-Viru across most of the studied variables. The results indicate that exposure to PMFurther analysis of the sociodemographic factors revealed that LBW is associated with ethnicity—Russian and other non-Estonian mothers have higher odds of ABOs. A striking contrast for increased risks of ABOs in Ida-Viru County than at the national level is observed with the mother’s education. Mothers with basic and secondary education are more affected by ABOs; however, the chances are even higher in Ida-Viru.2.5 and PTB is consistent with other studies [2.5 exposure during the first trimester increased the PTB risks, while the LBW results were inconclusive. On the other hand, the comprehensive review by Klepac et al. [2.5 exposure. Thus, studies seem to have a heterogenous association with ABOs on the trimester-specific PM2.5 exposure.The identified association between PM studies ,22,27,29 studies  found thc et al.  reportedc et al.  showed a10 exposure and ABOs, which is consistent with the existing evidence on non-significant association [10 and PTB [10 could be that the average annual concentration is on the borderline of the recommended air quality guideline by WHO [2 might explain the no effect of NO2  that is in line with inconsistent results on NO2, including the protective effect identified in a systematic review by Jacobs et al. [The current study showed a positive but statistically non-significant association between prenatal PMociation ,74. Despociation ,74,75, aociation , a numbe and PTB ,27,29,35 and PTB ,33,53. Oe by WHO . SimilarThe effect of BaP is seen only in LBW in Ida-Viru ICS; thus, the observed relations with air pollution may be coming from other unmeasured pollutants or a mixture of multiple pollutants as well, for instance, PAHs has shown even a strong effect on ABOs as suggested by systematized evidence .Our result on the association between ABOs and proximity to ICS is consistent with previous research ,40,41,42The current analysis of the mother’s sociodemographic characteristics showed a higher chance of ABO risk. A possible explanation is that the low SES mothers are more likely to live closer to the ICS, thus exposed to higher amounts of air pollutants . LBW is A review article in the United States identified two pathways for ethnicity and health , which cThe strong positive association with lower education could be attributed to socioeconomic health pathways . Lower SFurthermore, ABOs can also be explained via intergenerational transmission of inequalities, where adverse childhood health leads to increased risks of chronic diseases and lower SES, thus continuing the cycle of adverse child health in offspring . For insOne of the major limitations of our study is that we did not include the important confounding variables such as smoking due to the unreliable self–reported data which often underestimates the smoking prevalence . NeverthAdditionally, the observed result on air pollutants could be over- or underestimated, although we used combined data from monitoring stations and dispersion models. On the one hand, it may not well-capture personal exposure ,90. On tNevertheless, this study has several strengths. First, it contains all the birth records of Estonia in the last 15 years from 2004–2018), extracted from the Estonian birth registry. Thus, the selection bias and uncertainty in estimates are largely minimized, and external validity for the whole region is maximized. We have addressed the potential limitation of spatial measurement and modeling by calculating the buffer zones in the proximity to industrial areas and measuring the association with ABOs, which ultimately compliments the exposure to air pollutants results. Sociodemographic variables are important to identify health inequalities across different populations ,91. Thus004–2018,Future studies could investigate the combined effect of different environmental and social markers as the combined effects are often higher . Exposom2.5 associations with ABOs demonstrate the need to reduce air pollution levels. Furthermore, association with the proximity to the oil shale industry demands rethinking the role of industries because the evidence showing shutting down the industries leading to positive health effects is not new. Policy actions should be comprehensive and multisectoral with a prime focus on addressing the social stressors to break the chain of health inequality. The observed association of ABOs with education and ethnicity requires action to investigate and address the possible institutional and socio–cultural disparities.Given the long-term consequences of ABOs and health inequality, setting up the health monitoring system in the ICS of Ida-Viru is crucial for evidence-based policymaking. Policymakers may strive for equitable policy actions with special emphasis on those differentially exposed to more health-harming characteristics and address the disproportionate distribution of ABOs. PMWe found nationwide significant perinatal health inequalities across chemical, physical, and sociodemographic characteristics. However, the inequalities are even more prevalent in Ida-Viru ICS across air quality, residential proximity to oil shale industries, and maternal education. Though in terms of ethnicity, Russian mothers have equally higher chances of ABOs risks regardless of where they live in Estonia. Considering these health disparities in birth outcomes across environmental, residential, and sociodemographic markers, future public health impact across life course might be higher, potentially widening the social disparities. Thus, in addition to reducing the air pollutant level, policy actions on reducing social disparities are vital to address the unjustly higher perinatal health inequalities in the country and the industrial region of Ida-Viru.


Despite widespread advocacy for exclusive breastfeeding, and the associated benefits of exclusive breastfeeding for both infants and mothers, there is low prevalence in both developed and developing countries. Additionally, although several studies have been conducted on exclusive breastfeeding, very few of such studies have linked birth weight and birth size to exclusive breastfeeding. This study seeks to examine the influence of birth weight and birth size on exclusive breastfeeding.This study adopted a sequential explanatory mixed method approach using both quantitative and qualitative methods. The quantitative approach used cross-sectional data from the 2014 Ghana Demographic and Health Survey (GDHS) and the qualitative data from interviews with exclusive breastfeeding mothers from two health facilities in La Nkwantanang Municipal Assembly in Accra, Ghana. Logistic regression analysis was used to examine whether infants birth weight and mothers perceived birth size are associated with the practice of exclusive breastfeeding while the qualitative data provided further insights into the findings from the quantitative analysis.Majority (85%) of the infants in the study were of normal birth weight while 52% of the infants were perceived by their mothers to be of small birth size. The prevalence of exclusive breastfeeding was found to be 54.8%. The birth weight of infants and mothers’ perceived birth size were found to be significant predictors of exclusive breastfeeding. Infants of normal birth weight  and high birth weight  were more likely to be exclusively breastfed compared to low-birth-weight infants. Similarly, infants perceived to be of normal birth size were more likely  to be exclusively breastfed compared to infants perceived to be of small birth size. The findings from the qualitative analysis show that birth weight rather than birth size influence mothers’ decision to practice exclusive breastfeeding.The findings of the study underscore the relevance of infant birth weight and perceived birth size in the practice of exclusive breastfeeding and highlights the need to incorporate both actual measurement of birth weight, and perception of infant’s birth size into policies targeted at exclusive breastfeeding. There is the need for deliberate targeted efforts at women who deliver infants of low birth weight and women who perceive their children to be of small birth size to practice exclusive breastfeeding. Birth weight and birth size constitute actual and perceived measures of child anthropometrics which are important indicators for assessing the general health of infants at birth . As suchThis notwithstanding, there is empirical evidence that birth weight and birth size have consequences on early optimal feeding practices and standard growth of infants , 2, 8, pEven though several studies have been conducted on exclusive breastfeeding globally –26, onlyThis study adopted a sequential explanatory mixed method approach using both quantitative and qualitative methods . In implThe 2014 GDHS survey used a stratified, two-stage cluster sampling design to select respondents from across the then ten (10) administrative regions of Ghana. The first stage of sampling involved the selection of clusters consisting of enumeration areas stratified by rural and urban residence [The qualitative component of the study employed purposive sampling in selecting respondents. Two health facilities which are polyclinics located in Madina, Accra were purposively selected for the study. These two polyclinics serve the population in the La Nkwantanang Municipal area. The two health facilities are well-organized polyclinics with good child welfare clinics making them ideal for the purpose of this study. Mothers who were attending child welfare clinics with their children in the two polyclinics were selected for interviewing with the help of the health workers who were staff of the polyclinics.The unit of analysis for this study are infants who were the last-born child of their mother, born in the five years preceding the survey, and less than 6 months (0 to 5 months) old with records of both birth weight and birth size. The 2014 Ghana Demographic and Health Survey contained information on a total of 5,884 mothers with children under five years. Out of this number, about 3,239 had no records of birth weight and so were excluded from the sample for this study. The remaining 2,645 children had information about their birth size and birth weight from a child health record book or card. The sample of 2,645 children under five with both recorded actual birth weight and birth size as perceived by the mother was further limited to infants 0 to 5 months old whose total number was 613. This number was further limited to infants whose birth weight records were available from a child health record book or card and who were last born to their mothers. In all, 354 infants who had both birth size and birth weight records from a health record book or card were included in the final analytical sample . To ensuFor the qualitative arm of the study, a total of ten exclusive breastfeeding mothers were interviewed from the two health facilities. Five exclusive breastfeeding mothers were selected from each polyclinic. Exclusive breastfeeding mothers who were selected to participate in the study met the following inclusion criteria; aged 15 to 49 years, has an infant who is less than 6 months old and practicing exclusive breastfeeding. The qualitative interviews were conducted in the preferred language of the participant and the interviews lasted about 30 minutes. The qualitative interviews were audio taped and transcribed using a professional transcriber.The dependent variable for this study is exclusive breastfeeding and this was defined based on the World Health Organization’s infant feeding indicators for assessing breastfeeding practices . ExclusiThe main independent variables considered in this study were birth weight and birth size. During the 2014 GDHS, mothers were asked, “when (NAME) was born, was he/she very large, larger than average, average, smaller than average, or very small?” The responses were very large, larger than average, average, smaller than average and very small. For the purpose of this study, the five responses were recategorised into three  because the count of respondents falling within very large and very small were few. Those who responded that their babies were smaller than average and very small were recoded as “small”, average was maintained as “average”, while those who responded that their babies were larger and larger than average were recoded as “large”.Regarding birth weight, mothers were asked if their infants were weighed at birth and if they were weighed, what was the weight of the infant in kilograms (kg) or grams (g)? Enumerators recorded the birth weight from written records or mother’s recall if such information was available. For the purposes of this study, only birth weight records from written records from the child health card/book was used as this was deemed to be more reliable than recall by the mother. The responses ranged from 1700g to 5000g and this was recategorised into three based on the WHO standard birth weight classification . InfantsThe study controlled for other variables that may have an influence on exclusive breastfeeding. These variables were selected based on the reviewed literature , 33, 34.The study protocol for the GDHS was approved by the Ghana Health Service Ethical Review Committee and the Institutional Review Board of ICF International. Informed consent for voluntary participation was obtained from participants before being interviewed.Ethical clearance for the qualitative study was obtained from the Ethics Review Committee of Ghana Health Service (GHS-ERC #005/08/2017) and the University of Ghana Ethics Committee for the Humanities (ERC #020/17-18). Informed consent was obtained from each participant before they were interviewed. Additionally, the purpose of the study including the general objectives, benefits, and risk of taking part in the study were explained to the participants. The participants were informed about strict confidentiality and anonymity of their responses. They were also informed about their right to stop participating in the study at any point if they desired to do so. Those who agreed to be part of the study signed an informed consent form and, if they could not read or write, they provided a thumb print to participate in the study.The quantitative data were anaylsed using IBM SPSS Statistics for Windows (SPSS) Version 25. The characteristics of the study sample were described using descriptive statistics. Cross tabulations and chi square test were used to test for the associations between the dependent variable and other variables (independent and control variables). Logistic regression analysis was used to examine the influence of birth weight and birth size on exclusive breastfeeding. The qualitative data were analyzed based on emerging themes from the data. Atlas.Ti was used to analyse the data. Deductive coding based on the literature review and inductive coding (data-driven) were employed in analysing the qualitative data. The first author read through all the transcripts to identify the deductive codes. The codes were validated by the other authors after they had read through the transcripts. The initial stage of the analyses involved reading the transcripts repeatedly to gain familiarity with the text as well as noting initial codes. This was followed by assigning codes to the relevant segments of the transcript. At this stage, different codes from the transcripts were sorted into potential themes, as all relevant codes were collated within the identified themes . SimilarAccording to the results presented in The number of times mothers’ made an ANC visit when they were pregnant with the last born child ranged from 0 to 20 times with an average of 6.4 visits. Generally, more than three-quarters of the mothers had their last child delivered at government health facilities and majority of the mothers attended postnatal care within two weeks after delivery. With regards to the mode of delivery, 86.4% of the mothers had normal delivery whilst 13.6% had cesarean delivery. Also, about 88.4% of the mothers did not take maternity leave after delivery. Regarding the infants, almost a quarter (24.6%) were five months old.For the qualitative study, ten (10) exclusive breastfeeding mothers were interviewed. The age range for the participants was 25 to 40 years. About six (6) of the participants had Junior High School education, two (2) had tertiary education and one (1) had primary education. With regards to marital status, eight (8) of the participants were married while two (2) were not married. Also, seven (7) participants were Christians while three (3) were Muslims.The quantitative results further show that birth weight, ethnicity, wealth quintile and age of infants were associated with exclusive breastfeeding . With reThe results of the binary logistic regression in “When I give him other food, he will become plump and not heavy but when you breastfeed, he will gain the normal weight and he won’t fall sick so I considered the birth weight to practice exclusive breastfeeding” .“The birth weight was very important in my decision to practice exclusive breastfeeding” .Another mother was of the view that weight helps her to monitor the growth of the infants and this was very important in her decision to practice exclusive breastfeeding than birth size. She mentioned that;“Because the birth weight helps you to know that the child is growing. It is always important than the size, so I considered the birth weight of the child to practice exclusive breastfeeding” .A few of the mothers who were influenced by birth size to practice exclusive breastfeeding also indicated that birth size helps them to easily know the changes in the size of infants than the birth weight. One woman indicated that;“I don’t know anything about the weight. I was influenced by the birth size to practice exclusive breastfeeding” .Also, another mother indicated that birth size helps to see how large or small the child has grown at any time. She reported that;“The size will help me to see how big he or she is. I would want to maintain it and don’t want her to be falling sick. I won’t introduce any other thing. I will maintain it or increase it” .Other factors that were found to influence exclusive breastfeeding in the quantitative analysis were household wealth quintile, ethnicity, religion and the age of the infant. The results indicate that mothers from the Ewe ethnic group were more likely  to be practicing exclusive breastfeeding compared to mothers from the Akan ethnic group. In terms of religious affiliation, Muslim mothers were 0.384 times as likely to be practicing exclusive breastfeeding compared to mothers from the orthodox faith . Regarding wealth status, mothers from poorer households were less likely  to be practicing exclusive breastfeeding compared to mothers from the poorest household wealth quintile. Similar findings were observed in the qualitative results, where a mother reported that;“If I give him the canned food and I don’t have money to buy more then it means he will starve so I will rather practice exclusive breastfeeding” The results further show that there is an inverse relationship between age of infants and exclusive breastfeeding. Infants who were four months old, had a lower likelihood  of being exclusively breastfed compared to infants who were less than a month old. Also, infants who were five months old, had a lower likelihood  of being exclusively breastfed compared to infants who were less than a month old. The findings from the qualitative analysis complements the findings from the quantitative data. The results revealed that infants are given water and food before the sixth month because mothers expressed that at that age breastmilk alone is not enough for infants when they are growing. Also, mothers are encouraged by their biological mothers and in-laws to give infants water before their sixth month.This study examined the influence of infants’ birth weight and perceived birth size on exclusive breastfeeding in Ghana. The prevalence of exclusive breastfeeding among infants less than six months per the 24-hour recall method was 54.8%. This implies that slightly more than half of the infants were exclusively breastfed during the 24 hours preceding the survey. This prevalence is below the 90% prevalence recommended by the World Health Organization . This, tThe findings also indicate that birth weight is associated with exclusive breastfeeding and is consistent with findings from other studies , 38–40 tAlso, the results show that perceived birth size was associated with exclusive breastfeeding practice. Normal birth size infants were more likely to be exclusively breastfed compared to small birth size infants. Similar findings have been reported in sub-Saharan Africa , 28. ThiThe qualitative findings of the present study also showed that though mothers agreed that they consider both perceived birth size and birth weight in their decision to practice exclusive breastfeeding, most of these mothers mentioned that birth weight influences their decision to practice exclusive breastfeeding. This underscores the relevance of actual measurement rather than perception in decision making. The plausible reason could be that mothers are educated on the weight of infants at both antenatal and postnatal clinics. In addition, infants’ weight is taken at birth and at every child welfare clinic and this emphasizes the relevance of birth weight rather than birth size. The ability to scientifically monitor or objectively weigh infants could have influenced mothers to consider the birth weight of the infant rather than the perceived birth size to practice exclusive breastfeeding. Additionally, the qualitative study was done in an urban environment where most mothers are literate and could read from the birth record book. Their ability to read from the book and understand the relevance of birth weight could also influence their decision to rely on the birth weight rather than the birth size. Furthermore, mothers indicated that breastmilk helps infants to put on weight compared to formula foods. In their view, formula foods make infants large in size but does not allow for an increase in weight. Hence, the interest of mothers to have children with good weight rather than large size motivated them to consider birth weight as an important factor in exclusive breastfeeding.In addition, the results from both the quantitative and qualitative data explain the nuances of wealth being a significant factor in exclusive breastfeeding. The pattern shows that mothers from the poorest household were more likely to practice exclusive breastfeeding. The results from the present study corroborates the observed patterns in other studies , 43. Theet al., [Furthermore, the results of the present study showed that ethnicity is associated with exclusive breastfeeding and women from the Ewe ethnic group, predominantly from the Volta region of Ghana had higher odds of their infants being exclusively breastfed as compared to Akan women. The results is similar to findings from other settings in Ghana , 44, 45.et al.,  found thet al., . The ripet al., [Also, age of the child was found to significantly predict exclusive breastfeeding. The results show that there is an inverse relationship between the age of the child in months and exclusive breastfeeding. Similar findings have been reported in developing countries and Ghana , 49, 50.et al.,  reportedIn addition, practices such as post-partum and maternity leave could influence the practice of exclusive breastfeeding. In Ghana, women are given three months of maternity leave thus creating the opportunity to exclusively breastfeed their children in that period. But exclusive breastfeeding becomes difficult for mothers when they resume work after the three months maternity leave. This could explain why exclusive breastfeeding practice is inversely associated with infants’ age. The qualitative results revealed that maternity leave influences exclusive breastfeeding behavior. Some participants mentioned that they are affected by the three months maternity leave hence they take leave of absence after their maternity leave in order to complete six months exclusive breastfeeding.In spite of these findings, the study has some limitations that are worth mentioning. Firstly, the 24-hour recall method used for computing exclusive breastfeeding was obtained from mothers who were still breastfeeding their 0–5 months old infants. This method measures the “current status” of exclusive breastfeeding but not completed exclusive breastfeeding. Despite these limitations, the 24-hour recalled method is recommended by the World Health Organisation to measure exclusive breastfeeding of infants less than 6 months. Also, the subjective measure of birth size is affected by recall bias. Mothers may forget the size of the infant at birth and may recall incorrectly at the time of the survey. Hence, infants who are the last-born child of their mothers were used in this study to reduce the recall bias of how mothers perceived the birth size of their infants. In spite of these limitations, a mixed method approach provided a more nuanced explanation on the influence of infant birth weight  and mother’s perceived birth size on the practice of exclusive breastfeeding practice in Ghana. This, therefore, serves as a strength for the study as most studies on exclusive breastfeeding in Ghana and SSA are either quantitative or qualitative.The results show that birth weight and birth size were associated with exclusive breastfeeding among infants 0 to 5 months in Ghana. While exclusive breastfeeding is recommended for every newborn baby, women in Ghana tend to base their decision to exclusive breastfeeding on the birth weight of the infant and or their perception of the size of their baby at birth. Advocacy messages should dispel this misconception and restate the place of exclusive breastfeeding as relevant for every baby regardless of their birth weight or perceived size at birth. Furthermore, other factors in addition to birth weight and the perceived size of infants, for example the ethnicity and religion of mothers and the age of the infant as well as household wealth predict the practice of exclusive breastfeeding in Ghana. Policy interventions on exclusive breastfeeding must there consider these other factors in addition to infant birth weight and birth size as perceived by mothers. Also, health workers need to be sensitized to record the birth weight of infants after delivery as well as encourage mothers to keep their health record books. Efforts should also be targeted at women with low-birth-weight infants and mothers who perceive their infants to have small birth size to practice exclusive breastfeeding. In addition, programs aimed at the promotion of exclusive breastfeeding should incorporate ethnic and religious differences as well as targeting women belonging to poor households to encourage them to continue practicing exclusive breastfeeding.S1 Appendix(DOCX)Click here for additional data file.S2 Appendix(XLSX)Click here for additional data file.S3 Appendix(DOCX)Click here for additional data file.


Finally, the cloning and super-mutation of the clonal selection algorithm (CSA) are introduced into GWO to enhance the ability to jump out of the local optimum. In the experimental part, 15 benchmark functions are selected to perform the function optimization tasks to reveal the performance of pGWO-CSA further. Due to the statistical analysis of the obtained experimental data, the pGWO-CSA is superior to these classical swarm intelligence algorithms, GWO, and related variants. Furthermore, in order to verify the applicability of the algorithm, it was applied to the robot path-planning problem and obtained excellent results.This paper discusses a hybrid grey wolf optimizer utilizing a clone selection algorithm (pGWO-CSA) to overcome the disadvantages of a standard grey wolf optimizer (GWO), such as slow convergence speed, low accuracy in the single-peak function, and easily falling into local optimum in the multi-peak function and complex problems. The modifications of the proposed pGWO-CSA could be classified into the following three aspects. Firstly, a nonlinear function is used instead of a linear function for adjusting the iterative attenuation of the convergence factor to balance exploitation and exploration automatically. Then, an optimal  The metaheuristic algorithm is an improvement of the heuristic algorithm combined with a random algorithm and local search algorithm to implement optimization tasks. In recent years, metaheuristic optimization has made some recent developments. Jiang X et al. proposed optimal pathfinding with a beetle antennae search algorithm using ant colony optimization initialization and different searching strategies . Khan A a. Experimental results proved that the mGWO improves the effectiveness, efficiency, and stability of GWO 30], and In 30 dimensions, the test results of these four algorithms on test function F1–F15 are shown in In terms of the performance of the mean. Sort by the number of optimal values. The pGWO-CSA ranked first with 13 optimal values. PSO and DE tied for second place with one optimal value. FA ranked fourth with zero optimal values. Compared with PSO, pGWO-CSA outperformed PSO in 14 out of 15 test functions, and PSO outperformed pGWO-CSA only in test function F14. Compared with DE, pGWO-CSA outperformed DE in 14 out of 15 test functions, and DE outperformed pGWO-CSA only in test function F6. Compared with FA, pGWO-CSA outperformed FA in all 15 test functions.In terms of the performance of the standard deviation. Sort by the number of optimal values. The pGWO-CSA ranked first with 11 optimal values. PSO ranked second with three optimal values. FA ranked third with one optimal value. DE ranked fourth with zero optimal values. Compared with PSO, pGWO-CSA outperformed PSO in 11 out of 15 test functions, and PSO outperformed pGWO-CSA in test functions F5, F6, F8, and F14. Compared with DE, pGWO-CSA outperformed DE in 13 out of 15 test functions, and DE outperformed pGWO-CSA in test functions F6 and F8. Compared with FA, pGWO-CSA outperformed FA in 14 out of 15 test functions, and FA outperformed pGWO-CSA only in test function F6.In terms of the performance of the minimum. Sort by the number of optimal values. The pGWO-CSA ranked first with 13 optimal values. PSO ranked second with four optimal values. DE and FA tied for third place with zero optimal values. Compared with PSO, pGWO-CSA outperformed PSO in 11 out of 15 test functions, and PSO outperformed pGWO-CSA in test functions F7 and F14. In addition, the minimum values of pGWO-CSA and PSO are the same on the test functions F9 and F12, and both pGWO-CSA and PSO find the minimum values of the functions. Compared with DE and FA, pGWO-CSA outperformed DE and FA in all 15 test functions.In terms of the performance of the maximum. Sort by the number of optimal values. The pGWO-CSA ranked first with 12 optimal values. DE ranked second with two optimal values. PSO ranked third with one optimal value. FA ranked fourth with zero optimal values. Compared with PSO, pGWO-CSA outperformed PSO in 14 out of 15 test functions, and PSO only outperformed pGWO-CSA in test function F14. Compared with DE, pGWO-CSA outperformed DE in 13 out of 15 test functions, and DE outperformed pGWO-CSA in test functions F6 and F8. Compared with FA, pGWO-CSA outperformed FA in 14 out of 15 test functions, and FA outperformed pGWO-CSA only in test function F6.In addition, the pGWO-CSA can find theoretical optimal values on the test functions F9, F11, and F12. In the test functions F1, F2, F3, F4, F10, F11, F13, and F15, pGWO-CSA is superior to PSO, DE, and FA in terms of the mean, standard deviation, and minimum and maximum. Although PSO outperformed pGWO-CSA in the mean, standard deviation, and minimum and maximum on test function F14, pGWO-CSA still outperformed DE and FA on test function F14.In 50 dimensions, the test results of these four algorithms on test function F1–F15 are shown in In terms of the performance of the mean. Sort by the number of optimal values. The pGWO-CSA ranked first with 13 optimal values. PSO and FA tied for second place with one optimal value. DE ranked fourth with zero optimal values. Compared with PSO, pGWO-CSA outperformed PSO in 14 out of 15 test functions, and PSO outperformed pGWO-CSA only in test function F14. Compared with DE, pGWO-CSA outperformed DE in all 15 test functions. Compared with FA, pGWO-CSA outperformed FA in 14 out of 15 test functions, and FA outperformed pGWO-CSA only in test function F6.In terms of the performance of the standard deviation. Sort by the number of optimal values. The pGWO-CSA ranked first with 11 optimal values. PSO ranked second with three optimal values. FA ranked third with one optimal value. DE ranked fourth with zero optimal values. Compared with PSO, pGWO-CSA outperformed PSO in 11 out of 15 test functions, and PSO outperformed pGWO-CSA in test functions F5, F6, F8, and F14. Compared with DE, pGWO-CSA outperformed DE in 14 out of 15 test functions, and DE outperformed pGWO-CSA only in test function F8. Compared with FA, pGWO-CSA outperformed FA in 14 out of 15 test functions, and FA outperformed pGWO-CSA only in test function F6.In terms of the performance of the minimum. Sort by the number of optimal values. The pGWO-CSA ranked first with 11 optimal values. PSO ranked second with four optimal values. FA ranked third with two optimal values. DE ranked fourth with zero optimal values. Compared with PSO, pGWO-CSA outperformed PSO in 11 out of 15 test functions, and PSO outperformed pGWO-CSA in test functions F7 and F14. In addition, the minimum value of pGWO-CSA and PSO are the same on the test functions F9 and F12, and both pGWO-CSA and PSO find the minimum values of the functions. Compared with DE, pGWO-CSA outperformed DE in all 15 test functions. Compared with FA, pGWO-CSA outperformed FA in 13 out of 15 test functions, and FA outperformed pGWO-CSA in test functions F6 and F8.In terms of the performance of the maximum. Sort by the number of optimal values. The pGWO-CSA ranked first with 12 optimal values. PSO, DE, and FA are tied for second place with one optimal value. Compared with PSO, pGWO-CSA outperformed PSO in 14 out of 15 test functions, and PSO only outperformed pGWO-CSA in test function F14. Compared with DE, pGWO-CSA outperformed DE in 14 out of 15 test functions, and DE only outperformed pGWO-CSA in test function F8. Compared with FA, pGWO-CSA outperformed FA in 14 out of 15 test functions, and FA outperformed pGWO-CSA only in test function F6.In addition, pGWO-CSA can find theoretical optimal values on the test functions F9, F11, and F12. In the test functions F1, F2, F3, F4, F9, F10, F13, and F15, pGWO-CSA is superior to PSO, DE, and FA in terms of the mean, standard deviation, and minimum and maximum. Although pGWO-CSA is not as good as FA on test function F6 and as good as PSO on test function F14, pGWO-CSA still outperformed the other two swarm intelligence algorithms on these two functions.Based on the above data and analysis, pGWO-CSA has faster convergence speed, higher accuracy, and better ability to jump out of local optimum compared with other swarm intelligence algorithms in either 30 or 50 dimensions. In order to further verify the performance of pGWO-CSA, we will next compare pGWO-CSA with GWO and its variants.In order to further verify the performance of pGWO-CSA, pGWO-CSA is compared with GWO  and its In 30 dimensions, the test results of these five algorithms on test function F1–F15 are shown in In 50 dimensions, the test results of these five algorithms on test function F1–F15 are shown in In terms of the performance of the mean. Sort by the number of optimal values. The pGWO-CSA ranked first with nine optimal values. DGWO2 ranked second with six optimal values. OGWO ranked third with two optimal values. DGWO1 and GWO tied for fourth place with one optimal value. Compared with GWO, pGWO-CSA outperformed GWO in 14 out of 15 test functions. Compared with OGWO, pGWO-CSA outperformed OGWO in 13 out of 15 test functions, and OGWO outperformed pGWO-CSA only in test function F7. Compared with DGWO1, pGWO-CSA outperformed DGWO1 in 14 out of 15 test functions. Compared with DGWO2, pGWO-CSA outperformed DGWO2 in 9 out of 15 test functions, and DGWO2 outperformed pGWO-CSA only in test functions F1, F2, F3, F4, and F14.In terms of the performance of the standard deviation. Sort by the number of optimal values. The pGWO-CSA and DGWO2 tied for first place with seven optimal values. DGWO1 and OGWO tied for third place with two optimal values. GWO ranked fifth with one optimal value. Compared with GWO, pGWO-CSA outperformed GWO in 11 out of 15 test functions, and GWO only outperformed pGWO-CSA in test functions F7 and F15. Compared with OGWO, pGWO-CSA outperformed OGWO in 13 out of 15 test functions, and OGWO only outperformed pGWO-CSA in test function F7. Compared with DGWO1, pGWO-CSA outperformed DGWO1 in 13 out of 15 test functions, and DGWO1 only outperformed pGWO-CSA in test function F15. Compared with DGWO2, pGWO-CSA outperformed DGWO2 in seven out of fifteen test functions, and DGWO2 outperformed pGWO-CSA in test functions F1, F2, F3, F4, F6, F7, and F14.In terms of the performance of the minimum. Sort by the number of optimal values. The pGWO-CSA and DGWO2 tied for first place with eight optimal values. OGWO ranked third with six optimal values. DGWO1 and GWO tied for fourth place with three optimal values. Compared with GWO, pGWO-CSA outperformed GWO in 12 out of 15 test functions. Compared with OGWO, pGWO-CSA outperformed OGWO in eight out of fifteen test functions, and OGWO outperformed pGWO-CSA only in test functions F4, F7, and F8. Compared with DGWO1, pGWO-CSA outperformed DGWO1 in 12 out of 15 test functions. Compared with DGWO2, pGWO-CSA outperformed DGWO2 in seven out of fifteen test functions, and DGWO2 outperformed pGWO-CSA only in test functions F1, F2, F3, F4, and F13.In terms of the performance of the maximum. Sort by the number of optimal values. The pGWO-CSA and DGWO2 tied for first place with seven optimal values. OGWO ranked third with three optimal values. DGWO1 ranked fourth with two optimal values. GWO ranked fifth with one optimal value. Compared with GWO, pGWO-CSA outperformed GWO in 12 out of 15 test functions, and GWO outperformed pGWO-CSA only in test functions F7 and F15. Compared with OGWO, pGWO-CSA outperformed OGWO in 11 out of 15 test functions, and OGWO outperformed pGWO-CSA only in test functions F6 and F7. Compared with DGWO1, pGWO-CSA outperformed DGWO1 in 12 out of 15 test functions, and DGWO1 outperformed pGWO-CSA only in test functions F6 and F15. Compared with DGWO2, pGWO-CSA outperformed DGWO2 in eight out of fifteen test functions, and DGWO2 outperformed pGWO-CSA only in test functions F1, F2, F3, F4, F6, and F14.In addition, pGWO-CSA can find theoretical optimal values on the test functions F9, F11, and F12. In the test functions F5, F9, F10, F11, and F12, pGWO-CSA is the optimal value among the five algorithms in terms of the mean, standard deviation, and minimum and maximum. Although DGWO2 outperformed pGWO-CSA in the performance of the first four test functions, F1, F2, F3, and F4, pGWO-CSA still outperformed the other three algorithms.In terms of the performance of the mean. Sort by the number of optimal values. The pGWO-CSA ranked first with eight optimal values. DGWO2 ranked second with six optimal values. OGWO ranked third with three optimal values. DGWO1 and GWO tied for fourth place with one optimal value. Compared with GWO, pGWO-CSA outperformed GWO in 14 out of 15 test functions. Compared with OGWO, pGWO-CSA outperformed OGWO in 11 out of 15 test functions, and OGWO outperformed pGWO-CSA only in test functions F3, F7, and F10. Compared with DGWO1, pGWO-CSA outperformed DGWO1 in 14 out of 15 test functions. Compared with DGWO2, pGWO-CSA outperformed DGWO2 in nine out of fifteen test functions, and DGWO2 outperformed pGWO-CSA only in test functions F1, F2, F3, F4, and F14.In terms of the performance of the standard deviation. Sort by the number of optimal values. The pGWO-CSA ranked first with eight optimal values. DGWO2 ranked second with seven optimal values. OGWO ranked third with two optimal values. GWO ranked fourth with one optimal value. DGWO1 ranked fifth with zero optimal values. Compared with GWO, pGWO-CSA outperformed GWO in 13 out of 15 test functions, and GWO only outperformed pGWO-CSA in test function F7. Compared with OGWO, pGWO-CSA outperformed OGWO in 11 out of 15 test functions, and OGWO only outperformed pGWO-CSA in test functions F3, F7, and F14. Compared with DGWO1, pGWO-CSA outperformed DGWO1 in all 15 test functions. Compared with DGWO2, pGWO-CSA outperformed DGWO2 in seven out of fifteen test functions, and DGWO2 outperformed pGWO-CSA in test functions F1, F2, F3, F4, F7, F10, and F14.In terms of the performance of the minimum. Sort by the number of optimal values. DGWO2 ranked first with eight optimal values. The pGWO-CSA and OGWO tied for second place with six optimal values. GWO ranked fourth with two optimal values. DGWO1 ranked fifth with one optimal value. Compared with GWO, pGWO-CSA outperformed GWO in 13 out of 15 test functions. Compared with OGWO, pGWO-CSA outperformed OGWO in six out of fifteen test functions, and OGWO outperformed pGWO-CSA in test functions F1, F3, F4, F7, F10, and F13. Compared with DGWO1, pGWO-CSA outperformed DGWO1 in 14 out of 15 test functions, and DGWO1 outperformed pGWO-CSA only in test function F6. Compared with DGWO2, pGWO-CSA outperformed DGWO2 in six out of fifteen test functions, and DGWO2 outperformed pGWO-CSA in test functions F1, F2, F3, F4, F13, and F14.In terms of the performance of the maximum. Sort by the number of optimal values. DGWO2 ranked first with eight optimal values. The pGWO-CSA ranked second with seven optimal values. OGWO ranked third with three optimal values. GWO ranked fourth with one optimal value. DGWO1 ranked fifth with zero optimal values. Compared with GWO, pGWO-CSA outperformed GWO in 12 out of 15 test functions, and GWO outperformed pGWO-CSA only in test functions F7 and F14. Compared with OGWO, pGWO-CSA outperformed OGWO in 10 out of 15 test functions, and OGWO outperformed pGWO-CSA only in test functions F4, F5, F7, and F14. Compared with DGWO1, pGWO-CSA outperformed DGWO1 in 13 out of 15 test functions, and DGWO1 outperformed pGWO-CSA only in test function F15. Compared with DGWO2, pGWO-CSA outperformed DGWO2 in six out of fifteen test functions, and DGWO2 outperformed pGWO-CSA in test functions F1, F2, F3, F4, F5, F7, F14, and F15.In addition, pGWO-CSA can find theoretical optimal values on the test functions F9, F11, and F12. In the test functions F8, F9, F11, and F12, pGWO-CSA is the optimal value among the five algorithms in terms of the mean, standard deviation, and minimum and maximum. It is not difficult to find from By comparison, it is not difficult to find that pGWO-CSA performs better than the previous seven test functions, F1–F7, in the following eight test functions, F8–F15, whether in the 30 dimensions or the 50 dimensions. It can be seen that pGWO-CSA performs better in more complex functions, which is largely due to the super-mutation operation carried out by pGWO-CSA, which helps pGWO-CSA better jump out of local optimum.Based on the above data and analysis, pGWO-CSA has faster convergence speed, higher accuracy, and better ability to jump out of the local optimum compared with GWO and its variants in either 30 or 50 dimensions. In order to further reveal the performance of pGWO-CSA, the Wilcoxon test is performed in In order to further reveal the performance of pGWO-CSA, according to the experimental data in It can be seen from With the development of artificial intelligence, robots have been widely used in various fields ,34,35. AThe robot path-planning problem mainly includes two aspects: environment modeling and evaluation function. Environment modeling is to transform the environmental information of the robot into a form that can be recognized and expressed by a computer. The evaluation function is used to measure the path quality and is regarded as the objective function to be optimized by the algorithm.a and b represent the center coordinates of the obstacle, and r represents the radius of the circle.The environment model of the robot path-planning problem is shown in w1 and w2 are weight parameters and w1 + w2 = 1.0. n is the total number of path points, and –(16), when the fitness value of In order to verify the applicability and superiority of pGWO-CSA in robot path-planning problems, PSO, DE, FA, GWO, and its variants are compared with pGWO-CSA. The parameters of all algorithms are exactly the same as in According to the experimental data, pGWO-CSA is the optimal value of all algorithms in the performance of the minimum, maximum, and mean. The applicability and superiority of pGWO-CSA are further verified.Aiming at the defects of the GWO, such as low convergence accuracy and easy precocity when dealing with complex problems, this paper proposes pGWO-CSA to settle these drawbacks. Firstly, the pGWO-CSA uses a nonlinear function instead of a linear function to adjust the iterative attenuation of the convergence factor to balance exploitation and exploration. Secondly, pGWO-CSA improves GWO’s position-updating strategy, and finally, pGWO-CSA is mixed with the CSA. The improved pGWO-CSA improves the convergence speed, precision, and ability to jump out of the local optimum. The experimental results show that the pGWO-CSA has obvious accuracy advantages. Compared with GWO and its variants participating in the experiment, the pGWO-CSA shows good stability in both 30 and 50 dimensions and is suitable for the optimization of complex and variable problems. Finally, the proposed algorithm is applied to the robot path-planning problem, which further verifies the applicability and superiority of the proposed algorithm.


In particular, Co-MOF-74 and Fe-MOF-74 show the highest dinitrogen binding energy in the presence of an electric field, twice as high as that of methane. Our work demonstrates that the asymmetric effect of the electric field on different gas molecules can serve as another dimension of design that can be exploited in small gas molecule separation in metal–organic frameworks.In this theoretical study, selective binding of dinitrogen to the coordinatively unsaturated metal site in M-MOF-74  under an external electric field is investigated. Simulation results suggest that an external electric field enhances the π* back-bonding between the transition metal and dinitrogen molecule while weakening the σ bond between the metal and other small gas molecules such as CO 2) while weakening the σ bond . This asymmetric effect enhances N2/CH4 separation performance in MOF-74.External electric field increases the π* back-bonding (metal–N Cryogenic distillation is known to be useful for large-scale N7–9 and thereby can be used as a “switch” to enhance the performance of the material. In particular, electric fields have been gaining traction as of late as their utility has been explored in many different applications such as gas separation of propene/propane10 and electric field-induced assembly of MOF.11 Moreover, there have been many computational studies regarding electric field that have demonstrated its potential utility in CO2 capture,12 methane C–H bond activation,13 graphene hydrogenation14 and controllable molecular gate.15 However, to the best of knowledge there hasn't been anyone who has investigated how electric field can affect the N2/CH4 separation performance.In terms of materials applications, external stimuli and modifications such as pressure, temperature, ligand insertion and electric/magnetic fields provide means to tune the properties of the materials,2 and the CH4 binding energies in M-MOF-74 . We hypothesize that since the donation of electron in π* back-bonding is opposite to that of σ bond, there will be disparate effect on the bonds from the external electric field. And this difference will map into unique effects in the N2 and CH4 binding energies, which can lead to synergetic separation performances.Here, we use density functional theory (DFT) to investigate the mechanisms in which the electric field can asymmetrically modify both the Net al.,16 that cleaves out the cluster by considering metal node as the center and drawing a circle to include linkers , which is deemed to be ground states, experimentally and computationally.17–19When the cluster is cleaved out, functional groups such as carboxylate and oxido are terminated with hydrogen atoms to make the cluster neutral in charge. Then, to investigate the MOF-74 system with transition metals, the Mg atom is substituted with transition metal atoms such as Mn, Fe, Co, Ni, Cu, Zn which to the best of our knowledge are the list of experimentally synthesizable M-MOF-74s. Here we only substitute the central Mg atom to the other transition metals, so that the cluster can precisely simulate the environment of targeted M-MOF-74 while lowering computational cost. Spin state of the central transition metal is set to be a high-spin state (20 (G16), and M06-L21 exchange–correlation functional and def2tzvp22 basis sets, that are well validated as appropriate functional and basis sets for 3d transition metals by Xu et al.,23 are employed. During the geometrical optimization, the central metal atom and the first coordination shell composed of five oxygen atoms are relaxed and other atoms of the cluster are fixed. External electric field is applied to the cluster in the range of −0.010 a.u. to +0.010 a.u. (where 1 a.u. = 5.142 × 1011 V m−1). The positive direction of the electric field corresponds to the vector with direction as follows  within the M-MOF-74 cluster is computed using the below equation.Binding energy of small gas molecules  analysis is performed using the NBO 3.1 program24 (included in the G16). From the NBO analysis, stabilization energy via delocalizing donor NBO (Lewis type) to acceptor NBO (non-Lewis type) is calculated by second order perturbation theory as followingwhere qi is occupancy of the donor NBO, F is the off-diagonal NBO Fock matrix element, and εi, εj are diagonal elements . The stabilization energy less than 0.5 kcal mol−1 is ignored. Visualization of NBO is carried out by GaussView 6.1.25Along with the binding energy, N2 and CH4 under electric field is computed for the M-MOF-74 structures and the results are plotted in 4 shows monotonic increase for all metal types. Since σ bond is the dominant mechanism for CH4 binding in M-MOF-74, positive electric field further induces the electron to move from the CH4 gas molecule towards the coordinatively unsaturated metal site (CUS), thereby strengthening the σ bond. On the contrary, the negative electric field will provide a force that induces electrons away from the metal site and as such weaken the CH4–MOF interactions. On the other hand, N2 binding shows a different trend because of the π* back-bonding via d–π* interaction . For all metal types, positive electric field strengthens the N2 binding energy, similar to the case for CH4. On the other hand, negative electric field weakens N2 binding in Mg, Mn, Ni, and Zn-MOF-74, while it strengthens binding in Fe, Co, and Cu-MOF-74. Similar to CH4, the former can be interpreted as σ bond dominant environment, while for the latter case, π* back-bonding needs to be considered. In the M-MOF-74 systems, the π* back-bonding is formed by donating electrons from the d orbitals of the transition metal to the π* orbital of N2. Therefore, negative electric field induces the electrons to move toward the metal and thereby strengthening the π* back-bonding and increasing the N2 binding energy. 2 binding energy for negative electric fields amongst the investigated systems. Similar analysis for CO2 can be seen in Fig. S12 acts more like CH4 given that it also lacks the π* back-bonding.The DFT binding energy of N2 binding energy is increased when an electric field is applied in the negative direction.To further validate our interpretation, NBO analysis is conducted from the binding energy calculations see . In Fig.2 → metal's antibonding lone pair orbitals (acceptor)) are computed as well  at negative electric field. The exceptions have significant increase of the π* back-bonding in common, and this strong π* back-bonding decreases the distance between N2 and CUS  of N atom in N as well . Accordi2/CH4 separation, the DFT binding energies can serve as good predictors especially when comparing structures with the same topology in materials such as M-MOF-74 structures. As such, the difference between the N2 and CH4 binding energies for three test case M-MOF-74 systems  are plotted in 2 binding energy at negative electric field. In Mg-MOF-74, the binding energy difference between N2 and CH4 remains relatively unchanged for different values of the electric field as both the N2 and the CH4 bind to CUS via σ bond, therefore cancelling out the effect of electric field. For Co-MOF-74 and Fe-MOF-74, similar trends can be found for positive electric field values. However, for negative electric fields, negative electric field increases the N2 binding energy while weakening CH4 binding energy because it strengthens the π* back-bonding and weakens the σ bond. Therefore, the binding energy difference between N2 and CH4 starts to increase as electric field becomes more negative. The increased N2 binding energy for negative electric field is accompanied by a decrease in N2 stretching frequency (see Fig. S3For N2/CH4 separation. However, in real experiments, it is impossible to control the direction of the electric field with respect to the crystal orientation. As such, we explore the effect of the changes in the direction of the electric field while starting with the assumption that the changes in the binding energy will be equivalent to the component of the electric field that are aligned to the optimal direction. To test this assumption, the electric field is applied at the intensity of 0.01 a.u., but in the direction of the field is tilted to around 60 degrees. The resulting data points (In all of the aforementioned analysis, the direction of the electric field was purposefully chosen to optimally enhance the N2 for both positive and negative electric field directions whereas CH4 displays more of a monotonical behavior with respect to electric field. As such, one can theoretically use the electric field to increase the binding energy difference between N2 and CH4 in these systems, and thereby enhance the N2/CH4 separation performances. It remains to be seen how much of this work will be mapped to actual experimental studies given the large magnitudes of the electric field required to see meaningful effects from our computational studies. However, it has been shown in other computational/experimental work10 that electric fields require to see noticeable changes in macroscopic properties can be quite different and as such, it is our opinion that one cannot just dismiss the theoretical studies due to the large magnitude of electric field values.The effect of electric field as external stimuli to control the binding property of small gas molecules in MOF have been investigated computationally at the DFT level. Our computational studies indicate that due to the presence of π* back-bonding, certain M-MOF-74 systems show stronger binding for NThere are no conflicts to declare.RA-012-D2RA04216A-s001


The objective of this study was to evaluate the associations of 92 maternal blood-based proteins with increased infant birth size. The study was performed at the Uppsala University Hospital, Sweden, and included 857 mother and child dyads. The mean age of the women was 30.3 years, and 53.2% were nulliparous. Blood samples were collected at mean 18 + 2 weeks’ gestation, and the Olink cardiovascular II panel was used to measure 92 proteins, either known to be or suspected to be markers of cardiovascular and inflammatory disease in humans. Multiple linear regression models adjusted for maternal age, parity, pre-conception BMI, height, and smoking were performed to evaluate the association of each individual protein with infant birth size. We also performed sex-stratified analyses. Eight proteins , Prostasin (PRSS8), Adrenomedullin (ADM), Pappalysin-1 (PAPP-A), Angiotensin-converting enzyme 2 (ACE2), Sortilin (SORT1), Lectin-like oxidized LDL receptor 1 (LOX-1), and Thrombomodulin (TM)) were associated with infant birth size after false discovery rate adjustment. In the analyses including only female infants, ten proteins , PRSS8, SORT1, ADM, Interleukin-1 receptor antagonist protein (IL-1ra), Leptin (LEP), ACE2, TM, and Tumor necrosis factor receptor superfamily member 11A (TNFRSF11A)) were associated with infant birth size. Two proteins (PAPP-A and PRSS8) were associated with infant birth size among male infants. Our study suggests several proteins as potential biomarkers for increased birth weight, and our findings could act as a base for future research to identify new potential markers that could be added to improve screening for large infants.The online version contains supplementary material available at 10.1007/s43032-022-01093-9. Excessive fetal growth and subsequently high birth weight have significant consequences on the well-being of the individual, and prediction of excessive birth weight is therefore of high clinical importance. A high birth weight (≥ 4000 g or ≥ 4500 g)  is assocBirth weights of female and male infants differ, with males being heavier than females . Since tToday, fundal height measurement is used as a screening tool for abnormal fetal growth, but the method has low sensitivity for detecting excessive growth patterns . UltrasoThere is a growing interest in identifying maternal blood-based biomarkers that could be used as screening tools for pregnancy complications, and some are already applied to predict clinical outcomes in obstetric care. For example, Soluble fms-like tyrosine kinase 1 (sFlt-1) and Placental growth factor (PlGF) are assessed by some centers to evaluate the likelihood of preeclampsia development . In addiThe placenta plays an important role in fetal growth and development, and the placental function is highly dependent on adequate vascularization and regulation of the blood flow . We hypoWe hypothesize that maternal blood-based proteins, either known to be or suspected to be markers of cardiovascular and inflammatory disease, measured in early mid-pregnancy are associated with birth size as a proxy for fetal growth and that there might be sex-specific differences. In this study, we evaluate the associations of 92 blood-based proteins with infant birth weight in a cohort of 857 mother and child dyads. We also perform sex-stratified analyses in order to find possible sex-specific differences between female and male infants.All study participants had donated a blood sample to Uppsala Biobank for Pregnant Women. Blood samples are collected to this population-based biobank in conjunction with the second-trimester anomaly scan (at 16‒20 weeks’ gestation) at Uppsala University Hospital, Uppsala, Sweden, since 2007. Women are invited to donate a blood sample if they are ≥ 18 years, Swedish-speaking, and without blood-borne disease . Invitations to the Biobank are done at random, when a research nurse is available. Approximately 30% of the respondents decline participation, and the Biobank is estimated to cover about half of Uppsala County’s pregnant population [n = 542). Data from the preeclampsia and SGA cases were not included in our study. (2) Data were extracted from pregnant women randomly enrolled from the Biobank to participate in a trial evaluating activity trackers (n = 315). All women included in our study had a singleton pregnancy and available data on self-reported pre-conception weight, height, and smoking habits and gave birth to a term (37 + 0 to 41 + 6 weeks) infant with registered birth weight and sex.In this explorative nested cohort study, we used data from two previous studies that had performed, in the same run, Olink cardiovascular II panel analyses on blood samples donated to the Biobank between 2007 and 2018. (1) Data were extracted from pregnant women without hypertension, diabetes, and renal disease selected as controls in a case–control study evaluating maternal blood-based proteins in relation to preeclampsia and small for gestation age (SGA) .The Olink cardiovascular II panel was used to measure 92 blood-based protein biomarkers either known to be or suspected to be markers of human cardiovascular and inflammatory disease. The Olink analysis is based on a proximity assay technology developed at the Clinical Biomarkers Facility, Science for Life Laboratory, Uppsala, Sweden. Individual protein profiles are measured in the sample using antibody pairs marked with unique DNA tags. When the matched antibodies attach to the protein, their DNA tags hybridize. The hybridized DNA tags are extended to an amplicon generating a unique code for each protein. The protein profile is then read out by qPCR. The protein concentration is calculated based on the number of qPCR cycles, and the relative concentration is reported. The results are presented as Normalized Protein eXpression (NPX) values, which is an arbitrary unit in log2 scale. A high protein value corresponds to a high protein concentration , 22. TheInformation on age, parity, pre-conception weight, height, and smoking habits was obtained from a questionnaire filled in by the woman in conjunction with the blood sampling. Body mass index (BMI) was calculated as the weight in kilograms divided by the square of the height in meters. Data on birth weight, infant sex, and gestational age at birth were extracted from the standardized pediatric electronic medical records. We calculated birth weight standard deviation scores (BWSDS) using Swedish reference standards for birth weight with respect to sex and gestational age at birth .P-value < 0.05 was considered to indicate statistical significance. Kruskal–Wallis test was performed to verify that the distribution of birth weights were the same across the different Olink batches. Multiple linear regression models were performed to evaluate the association of each individual protein with infant birth weight in grams and BWSDS. Covariates included in the model evaluating birth weight were maternal age, parity (nulliparous or parous), pre-conception BMI, height, smoking (yes or no), infant sex, and gestational age at birth. Covariates in the model evaluating BWSDS were maternal age, parity (nulliparous or parous), pre-conception BMI, height, and smoking (yes or no). To adjust for multiple testing, we used false discovery rate (FDR). In order to investigate any sex-specific differences in protein associations between sexes, we also performed the above-described analyses on female and male infants separately. To evaluate possible correlations between the proteins associated with infant birth size, Spearman’s correlations coefficients were calculated. Non-parametric tests were chosen since the proteins were not always normally distributed.The statistical analyses were performed using IBM SPSS Statistics version 28. A nominal two-sided Gene Ontology (GO) analysis was performed to identify any biological processes, besides cardiovascular and inflammatory disease, in which the proteins associated with birth size interact. The GO analysis was performed using geneontology.org on 2022–01-31 with version 10.5281/zenodo.5725227, released 2021–11-16, by using UniprotKB ID for proteins identified to be associated with birth weight in all infants, and stratified by infant sex , 25.The study population consisted of 857 mother and child dyads with complete data. The women were between 18‒47 years of age, 456 (53.2%) were pregnant with their first child, and 322 (37.6%) were either overweight (BMI ≥ 25) or obese (BMI ≥ 30). The characteristics of the study population are presented in Table The distribution of birth weights were the same across the different Olink batches. Since Olink recommends exclusion of assays with a large proportion of samples below the limit of detection, three proteins were excluded from further analysis: Natriuretic peptides B (BNP) (43.8% below limit of detection), Melusin (ITGB1BP2) (42.0% below limit of detection), and Carbonic anhydrase 5A, mitochondrial (CA5A) (41.4% below limit of detection). Hence, 89 protein proteins remained for analysis.The blood sampling was performed at mean 18 + 2 weeks’ gestation. Eight proteins were associated with both infant birth weight and BWSDS following correction for multiple testing  binding proteins (IGFBP), especially IGFBP-4. As IGFBP-4 inhibits IGF, PAPP-A cleavage of IGFBP-4 stimulates growth by increased IGF bioavailability , 73. In Our results showed sex-specific differences; more proteins were associated with increased birth weight among female infants than among males. These dissimilarities are not easily explained since the mechanisms driving sex-specific adaptions to in utero environmental changes are poorly understood. However, previous research indicates altered placental function as well as feto-placental hormonal changes as factors that may contribute to sex-specific differences in adaption to changes in the intrauterine milieu .This study has strengths and limitations. A possible limitation is that the protein concentrations are reported as relative values, which might complicate comparison with other studies using absolute protein concentrations. Nonetheless, a study comparing PlGF measured by the Olink proteomics assay with an immunochemiluminescence assay reports an excellent correlation .Strengths of this study include a large, well-characterized study cohort and a considerable number of proteins analyzed by the Olink cardiovascular II panel. To the best of our knowledge, this is the first study to evaluate these proteins in relation to infant birth weight, including sex-stratified analyses. Future studies are needed to confirm our findings. It might also be of interest to evaluate the predictive value of a combination of protein levels on infant birth weight.Several maternal blood-based proteins measured in early-mid pregnancy were associated with increased infant birth size, with sex-specific differences. More proteins were associated with birth weight among female infants compared with males. Some of the identified proteins’ relation to birth size is unclear, motivating further research to explain possible causal mechanisms. Nonetheless, several of the identified proteins are related to improved vascularization and insulin sensitivity. The performance of prediction models for high birth weight is poor. Our study suggests a number of proteins as potential biomarkers for increased birth weight, and our findings could act as a base for future research to identify new possible markers that could be added to improve screening for large infants.Supplementary file1 (DOCX 34 KB)Below is the link to the electronic supplementary material.