The physical and chemical factors that can limit or prevent microbial growth in the deep subsurface are not well defined. Brines from an evaporite sequence were sampled in the Boulby Mine, United Kingdom between 800 and 1300 m depth. Ionic, hydrogen and oxygen isotopic composition were used to identify two brine sources, an aquifer situated in strata overlying the mine, and another ambiguous source distinct from the regional groundwater. The ability of the brines to support microbial replication was tested with culturing experiments using a diversity of inocula. The examined brines were found to be permissive for growth, except one. Testing this brine’s physicochemical properties showed it to have low water activity and to be chaotropic, which we attribute to the high concentration of magnesium and chloride ions. Metagenomic sequencing of the brines that supported growth showed their microbial communities to be similar to each other and comparable to those found in other hypersaline environments. These data show that solutions high in dissolved ions can shape the microbial diversity of the continental deep subsurface biosphere. Furthermore, under certain circumstances, complex brines can establish a hard limit to microbial replication in the deep biosphere, highlighting the potential for subsurface uninhabitable aqueous environments at depths far shallower than a geothermally-defined limit to life. Geologically, the mine is situated in the Cleveland Basin at the western margin of the North Sea Basin . The seqFive brine flows were sampled from Boulby between February 2013 and January 2015, found at depths between 800 m and 1.3 km , reducing the pH to prevent cation precipitation . SamplesBrines used for aerobic culturing (both as an inoculum and as a medium) and DNA extraction were collected in sterile 50 mL centrifuge tubes. Those to be used for anaerobic culturing were added to sealed sterile anaerobic serum bottles containing L-cysteine-HCl (as a reducing agent) to a final concentration of 0.8 mM. They were all then placed in a cooler box with ice packs to reduce microbial activity. Once at the surface, all aerobic and anaerobic samples were stored at 4°C and those for DNA extraction at −80°C.18O and δ2H values of water stored in them for at least 1 year . All pH measurements were corrected for temperature and salinity, and were calibrated using standards provided with the instrument. The Ultrameter II has an inbuilt electronic ORP and temperature calibration. All measurements were repeated three times, and the sensor rinsed with distilled water and dried between samples. DO readings were taken from the brine pools using a Spectrum Dissolved Oxygen Meter (model 407510) . Measurements were calibrated and corrected for salinity and temperature on the instrument as described in the instrument manual. The set-up of the taps in the mine meant that brines 29XC and 44XC had to be exposed to the air during sample collection, making it impossible to get an accurate reading of DO without a major redesign of the pumping system. ORP measurements were also limited by this problem, but since they tend to react more slowly to environmental changes, they were recorded with this limitation in mind. Pressure measurements for 29XC and 44XC were provided by the mine from their regular monitoring 2 days before sampling was carried out.Oxidation-reduction potential (ORP), pH and temperature were recorded 2–103 to match the emission intensity of the standards. After dilution, Fe was the only element measured in the brines to fall below detection limits . The wavelengths used to interrogate specific ions were: Na+ 330.237, 588.995, 589.592 nm; K+, 766.490 nm; Mg2+, 279.077, 280.271, 285.213 nm; Ca2+, 315.887 nm, 317.933, 393.366 nm, 396.847 nm; Fe 239.562 nm. When using more than one wavelength per element, the wavelength with the highest r2-value was chosen to calculate the concentration of that ion in the sample.ICP-OES  analyses were carried out on a Perkin Elmer  Optima 5300 DV ICP-OES instrument by the School of Chemistry at University of Edinburgh. Brines had to be diluted with 18.2 M Ω-cm distilled water from a Thermo Fisher Scientific  Barnstead NanoPure system by factors of 10−, and Br− were measured using Ion Exchange Chromatography (IEC). IEC analysis was carried out by the University of Sheffield by the Groundwater Protection and Restoration Group with a Dionex (now Thermo Fisher) ICS-3000. Samples were filtered through a 0.45 μm pore diameter membrane and diluted 103 times with UHQ  water before analysis. This brought them below the detection limits for 2H analyses were performed via manganese reduction at 900°C using a method modified from 18O analyses were performed by the CO2 equilibration method of 2H and δ18O, respectively . Two sets of carbon sources were added to the brines as powders: one media containing just yeast extract (4 g/L), and the other a mixture of sodium pyruvate and casamino acids . The brines were sterilized in an autoclave (121°C for 20 min) and a 50 mL aliquot transferred to sterile glass conical flasks and topped with foam bungs wrapped in tin foil. An artificial media was also used to enrich organisms, prepared with the following recipe: NaCl 250 g/L, KCl 2 g/L and tryptic soy broth 25 g/L or nutrient broth 19 g/L  both balanced to pH 7. The high concentration of NaCl was used to mimic the hypersaline conditions of the NaCl brines, and the KCl to provide an osmoprotectant for extreme halophiles.After being mixed by inversion, unsterilized environmental brine samples were used to inoculate the media . At the time of culturing the brines had been stored in the fridge at 4°C for <2 weeks. All aerobic enrichments were incubated at 37°C , enrichment cultures grown from other environmental brine samples and soil   to mimic 101-P, but with the MgCl2 levels reduced to 2 M , but with lower total ion concentrations, to test whether this parameter accounted for their inability to support growth. This included a MgClSome experiments using environmental brine media and artificial media were carried out under anaerobic conditions see  to broad2PO4, KCl, NaCl, NH4NO3, MgCl2, respectively, as detailed in Water activity was measured in the laboratory using a Rotronic HP23-AW-A water activity meter . This was calibrated using five points of reference with water activities of 0.935, 0.845, 0.755, 0.595, 0.325 composed of saturated calibration solutions KH500) was recorded until it reached room temperature. As in 500 as they cooled to that of a pure 1.5% agar solution. Once the mixture achieved the same increase in A500 as the pure agar at gel point (43.5°C), it was deemed to have undergone gelification.An agar gelation assay was used to measure brine chao/kosmotropicity see . To imprIonic strength has been identified as a potential physicochemical habitability limiter  due to ici = concentration of ion i (in mol liter−1)zi = charge of ion iEscherichia coli and Haloferax volcanii used as positive controls for bacteria and archaea, respectively, and to spike the brines to ensure their chemistry did not impact DNA recovery. Amplification products produced using archaeal primers were consistently more concentrated than those produced using bacterial PCR. Of the three brines able to have DNA extracted, the weakest PCR amplification was observed in 44XC, suggesting it had the lowest concentration of DNA.Ten liters of each brine were filtered using MO BIO 0.22 μm water filters attached to a peristaltic pump. These filters were then placed in a sterile 50 mL Falcon tube with flame sterilized tweezers. DNA extraction was challenging due to the abundance of clay minerals in the brines. A PowerMax Soil DNA Isolation Kit  with clay-proof modifications from DNA was sequenced using Illumina  MiSeq for brine 215 and NextSeq for Billingham and 44XC. This diversity of techniques was related to the methods employed by the different funding bodies involved. MiSeq sequencing was carried out at Edinburgh Genomics, Edinburgh, United Kingdom and the NextSeq at Marine Biological Laboratory, Falmouth, United States. For NextSeq, libraries were constructed with the Nugen Ovation Ultralow Library protocol, targeting an insert size of 225–250 bp to enable read merging. Sequencing was then completed with a 2 × 150 paired-end run using dedicated read indexing. The library was prepared for MiSeq using a standard TruSeq DNA kit, targeting a 400 bp insert library. This was sequenced with a 2 × 250 bp paired end-run. Blanks were also sent for amplicon sequencing, but were failed by the sequencing center due to lack of DNA. Unassembled sequence files were then uploaded to MetaGenome Rapid Annotation with Subsystem Technology (MG-RAST), for taxonomic and functional analysis . SEED SuAll brines collected contained close to saturation levels of several chloride compounds . Sulfate2H and δ18O values. These values were a little higher in Brines 29XC and 44XC. Brine 101-P, however, was the most enriched in 2H and 18O, with δ18O and δ2H values higher than any of the other brines . Similarly, all the brines displayed similar kosmotropic behaviors, except 101-P which was distinctly chaotropic  and four from South Bay Salt Works, Chula Vista, CA, United States .Haloarcula was the most abundant genera in the subsurface metagenomes . Other common taxa included Natronomonas , Halogeometricum , Halomicrobium  and Halobacterium . In the surface brines, Haloquadratum was dominant, although it is worth noting that the metagenomes from Bras del Port were deliberately sampled to include high numbers of Haloquadratum. Despite some differences in relative abundance, the proportions of the most abundant genera between the surface and subsurface brines are comparable within the Halobacteriales order.At the domain level, the three habitable subsurface brines were dominated by archaeal sequences , particuMycobacterium and Bradyrhizobium were highest in 44XC, indicating low levels of contamination (see Discussion).Bacterial populations were compositionally similar between the three subsurface brines, but differed somewhat in relative abundance. The most abundant bacteria phyla included Proteobacteria , Bacteroidetes , Firmicutes , Actinobacteria , and Chloroflexi . Cyanobacteria appear to be present in both surface and subsurface metagenomes, but were more abundant in the surface metagenomes generally. Some of these hits, however, could be incorrectly assigned in our deep subsurface metagenomes as we did not see Cyanobacteria’s distinct 16S in our analysis. In terms of functional genes, the brines were comparable . A totalHaloarcula, Halomicrobium, Halorhabdus, and Halogeometricum. These genes were largely absent from the surface brines.Denitrification is an anaerobic metabolism employed by several halophiles that function at NaCl saturation , 2013. GHalorubrum. Genes coding for key enzymes involved in fermentative arginine degradation (ADI pathway) were found in the three metagenomes. These were attributed to organisms including Salinibacter, Pseudomonas, and Halobacterium. Enzymes involved in arginine production by fermentation and homolactic and ethanol fermentation were also found in the subsurface metagenomes and some of the surface brines.Fumarate reductase, a key enzyme in the reduction of fumarate, is present in the subsurface metagenomes, associated predominantly with Halorhabdus, Halomicrobium, Chromohalobacter, Halomonas, and alanine, arginine, glycine, isoleucine and valine metabolism related to Natronomonas and Haloarcula. These pathways were also present in surface metagenomes.Inferred carbon utilization pathways are also similar between the surface and subsurface brines. Pathways related to the metabolism of many monosaccharides, polysaccharides and amino acids were detected in the subsurface metagenomes, including complete pathways for galactose, fructose, mannose and xylose metabolism, assigned to Pseudomonas. Similarly, small numbers of hits related to alkane hydroxylases, important enzymes in the degradation of alkanes  of MgCl2 was the upper limit for microbial propagation. This limit was raised by −1 in Kryos MgCl2-brine, a significant deviation from previous work on similar brine systems. 101-P increased heat capacity by 129.63 kJ kg−1, placing it beyond Hallworth’s hypothetical limit to life but within Steinle’s.The reasons for these apparent differences in habitability can be elucidated by examining the physicochemical characteristics of the brines. The chao/kosmotrocity levels are theoretically permissive to life in all of the brines when factoring in recent work by w,101-P again falls between the previous record for microbial propagation at low water activity of 0.585 aw from w reported by Brines 44XC, 215, 29XC and Billingham Baths all have water activities above the currently debated limits to biological activity in brines. At 0.566 aIt is not possible to isolate either water activity, chaotropicity or any other physicochemical property as the limit to microbial propagation in 101-P. The brine is extreme with regard to several parameters that are well known to powerfully limit microbial growth. The ionic interactions that govern these physicochemical properties are currently not well understood. Additionally, the habitable regimes of water activity and chaotropicity are liable to change as more of the terrestrial biosphere is explored. For these reasons, we consider 101-P’s total ionic composition, which is responsible for its specific physicochemical profile, to be the barrier to microbial propagation, rather than any one individual physicochemical parameter.2+ and Cl− typically induce low water activity and strongly chaotropic behaviors , originated, at least partly, from a separate source. High concentrations of Mgehaviors , suggestIt is worth noting that it would always be possible broaden the range of carbon sources, growth temperatures, inoculants and ionic compositions of the media to increase the chances of a positive enrichment. Additionally, many microorganisms appear not to be culturable with modern enrichment techniques, something that may be especially true when dealing with deep subsurface samples. This was in some way mitigated during these experiments by using communities of organisms from a number of different sources as opposed to isolates to better simulate the complexity of natural environments. Further work could strengthen our hypothesis that 101-P (and other similar brines) is uninhabitable, but realistically this can never be definitive.Halorhabdus, which contains the hypoxic adapted halophile Halorhabdus tiamatea, were over represented in the subsurface samples relative to the surface  and those found in extreme surface NaCl brines, suggests that even in the brines able to support microbial propagation, ionic composition still drastically limits the types of life present. In this way, NaCl at saturation levels appears to be a far stronger influence on community structure than any of the environmental differences between the surface and subsurface experienced by these brine communities .Haloarcula, Halomicrobium, Halorhabdus, and Halogeometricum are found in the subsurface brines, but are absent from the surface metagenomes. Despite generally being scarce in hypersaline environments , and the absence of genes related to many parts of the nitrogen and sulfur cycles  and BN (secondary). JB advised on the metagenomic work and contributed part of the data analysis. BSL advised on and contributed to the isotopic analysis. MF-P advised on the physicochemical analysis and assisted in the field work. SP and TE helped to organize and support the field work.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.


Despite the advent of several antidepressant medications, treatment of Major Depressive Disorder (MDD) is still far from optimal depression frequently is comorbid with many inflammatory illnessesincreased inflammatory biomarkers are associated with major depressive disorder (MDD)exposure to immunomodulating agents may increase the risk of developing depressionstress can activate proinflammatory pathwaysantidepressants can decrease inflammatory responseinhibition of inflammatory pathways can improve mood Growing body of evidence suggests that inflammation is implicated in the pathophysiology of MDD IL-6 is one of the most widely studied cytokines in patients with MDDPrevious studies have already shown that elevated levels of inflammation are associated with poor response to antidepressants. The scientists found that they could pinpoint a threshold and precisely predict which patients would respond to conventional antidepressants. None of the patients with MIF and IL-1β levels above the threshold responded to the antidepressants most often prescribed. Those with inflammation levels below the threshold would likely respond. One reason for the lack of predictive biomarkers in MDD is that little is known with absolute certainty about how antidepressants improve mood. All currently approved medications for depression act in a similar way, increasing the availability of monoamine neurotransmitters like serotonin in the brain. Psychiatrists continue to search for biomarkers to help guide therapy and, potentially, improve chances of discovering new drugs In conclusion, the link between depression and the body's inflammatory response continues getting stronger, with more research showing an ever-tighter correlation.


Uttar Pradesh (UP) is the most populous state in India with historically high levels of fertility rates than the national average. Though fertility levels in UP declined considerably in recent decades, the current level is well above the government’s target of 2.1.Fertility and family planning data obtained from the different rounds of Sample Registration System (SRS) and the National Family Health Survey (NFHS). We analyzed fertility and family planning trends in India and UP, including differences in methods mix, using SRS (1971–2016) and NFHS (1992–2016). Bivariate and multivariate regression analyses were used.From 2000, while the total fertility rate (TFR) declined in UP, it is still well above the national level in 2015–16 . The demand for family planning satisfied increased from 52 to 72% during 1998–99 to 2015–16 in UP, compared to an increase from 75 to 81% in India. Traditional methods play a much greater role in UP than in India (22 and 9% of the demand satisfied respectively), while use of sterilization was relatively low in UP when compared to the national averages .p < .001). Among currently married women, use of traditional methods increased and accounted for almost one-third of users in 2015–16. Use of sterilization declined but remained the primary method (ranging from 33 to 41% of users in high and low fertility districts respectively) while condom use increased from 17 and 16% in 1998–99 to 23 and 25% in 2015–16 in low and high fertility districts respectively.Within UP, district fertility ranged from 1.6 to 4.4, with higher fertility concentrated in districts with low female schooling, predominantly located in north-central UP. Fertility declines were largest in districts with high fertility in the late nineties (B = 7.33, Greater reliance on traditional methods and condoms coupled with relatively low demand for modern contraception suggest inadequate access to modern contraceptives, especially in district with high fertility rates. Family planning activities need to be appropriately scaled according to need and geography to ensure the achievement of state-level improvements in family planning programs and fertility outcomes. There has been a substantial drop in fertility in Uttar Pradesh. The comparative trends between India and Uttar Pradesh show that the Total Fertility Rate (TFR) in the state has always remained above the national average but the fertility trajectory is similar. In fact, the fertility decline in Uttar Pradesh (UP) has accelerated since 2000, and the fertility gap between India and UP has reduced substantially. However, there are substantial variations in the TFR across districts of Uttar Pradesh, ranging from 1.6 to 4.4. When the districts were classified into different clusters based on their fertility levels, this formed a geo-spatial clustering of regions with different levels of fertility. For instance, Tarai belt and its adjacent districts in Central UP formed the cluster with high fertility region and Bundelkhand region was the low fertility cluster.The fertility decline in UP was driven by an increase in use of contraceptive methods among married women. Female sterilization was the predominant method in UP but the percent of married women sterilized was only half as prevalent as in India. Condom use was the second most popular method and has an increasing trend, and is twice as prevalent as in India. The use of traditional methods  of family planning, most notably periodic abstinence, was more than two times higher in UP compared to India. To achieve government TFR target, activities need to be appropriately scaled and targeted according to need and geography to ensure the achievement of state-level improvements in family planning programs and fertility outcomes.India has experienced a dramatic fertility decline over the last 50 years, from 5.2 children per woman in 1971–72 to 2.2 children by 2015–16 –5. ImproIn 2000, Government of India formulated the National Population Policy to achieve a TFR of 2.1 by 2012 and population stabilization by 2045 by addressing family planning unmet needs , 14 and Fertility levels in Uttar Pradesh (UP), the most populous state in India having 199.8 million populations , are welThis paper examines the fertility decline and district differences in UP to understand current progress and identify areas that need to be addressed to sustain or accelerate the fertility decline. We first compared the fertility decline in UP to India as a whole with a focus on changes in the coverage of contraceptive methods and demand met for family planning. We then analyzed fertility and family planning in the administrative districts of UP to identify populations with high fertility and low contraceptive use, which has implications for future efforts to meet the need of all couples in UP through policies and programs.Data from different rounds of Sample Registration System (SRS) and National Family Health Survey (NFHS) were used. The SRS was established in 1964 to provide national and state level estimates of fertility and mortality . We usedThe NFHS is a large-scale multi-round survey which is conducted in a representative sample of households throughout India. Four rounds of the survey have been conducted between 1992 and 93 and 2015–16. The surveys provide national and state information on fertility, infant and child mortality and practice of family planning along with other socio-economic characteristics. UP has undergone several administrative changes over the period of time, including geographical re-organization of district boundaries, formation of new districts and separation of a group of districts to form a separate state. Considering these changes, the NFHS trend analysis is limited to just three rounds of surveys . From the second NFHS (1998–99) survey we excluded districts of Uttarakhand state (formed from select districts of UP in 2000) from the UP district estimates.For the district level fertility analysis within UP, we computed total fertility rates using the birth history data from women 15–49 years in NFHS-2 1999–2000) and NFHS-4 (2015–16), using Bruno Schoumaker’s method (2013) [99–2000 aThe comparison of the fertility trend in UP with India focuses on the average annual rate of decline in fertility and FP methods by time-period. Within UP, we examined clustering of fertility using NFHS data in 2015–16 and assessed the extent to which district characteristics were associated with fertility: level of female education (36% of women did not attend school), proportion of population from poor wealth quintile including poorest, proportion who were Muslim (19%) and proportion of respondents belong to Scheduled Caste (23%). In addition, we assessed the extent to which the relative change in total fertility during 1998–99 and 2015–16 can be explained by district changes in schooling levels and urbanization, baseline levels of total fertility in 1998–99, religious and scheduled caste composition of the districts in 2015–16. Comparable data from the two NFHS surveys were available for 71 of the 75 districts; and for the newly formed four districts namely CSM Nagar, Shamli, Hapur and Sambhal the information was not available in NFHS-4. Bivariate and multivariate linear regression models were used to assess statistical significance.For the analysis of contraceptive use patterns and trends, districts were grouped into three categories, namely, low (<= 2.3), medium (2.4–2.9) and high (> = 3.0) depending on NFHS-4 TFR levels. Similarly, based on rate of decline in TFR, two groups were formed out of total 71 comparable districts in NFHS 2 and 4, 36 districts belong to the faster decline cluster and 35 districts belong to the slower decline cluster. The rate of decline in TFR was calculated by estimating Total Fertility Rate and the percentage change using NFHS rounds 2 and 4 ((NFHS 2-NFHS 4)/NFHS 2 * 100). The criteria for deciding faster and slower rate of fertility decline is to have almost equal number of districts in each group given the small sample size. For each district, change in proportion was calculated between NFHS-3 and NFHS-4 for characteristics associated with fertility such as female education, urbanization, Muslim and Scheduled Caste populations. We examined the differences in coverage with modern and traditional  family planning methods in NFHS 1998–99 and NFHS 2015–16. We used the family planning demand satisfied, which is a better coverage indicator as it measures the use of contraceptive methods among married women 15–49 years who need a contraceptive because they do not want to become pregnant and are exposed to the risk of getting pregnant. The demand for family planning satisfied with modern contraceptive methods is measured as the number of married women who use modern contraceptives divided by the sum of the number of married women whose need for family planning is not met (unmet need) and the number of married women who use modern contraceptives. The extent to which the demand for family planning is met for all methods  is measured in the same way.The fertility decline in UP was slower than India during all decades until 2000 but exceeded the national pace of decline during 2000–2009 and 2010–2016 (0.6% per year faster decline), resulting in a narrowing of the gap between India and UP  and explained more than 60% of the variation in TFR.In 2015–16, the district levels of total fertility ranged from 1.6 in Lucknow and Kanpur Nagar districts; both highly urbanized, in central UP to 4.2 and 4.4 in Shrawasti and Bahraich districts from northern UP bordering Nepal . According to a 2016 survey on family planning practices among currently married women (aged 15–49) conducted in 25 districts of UP, the most preferred method among women who were not using any contraceptive method at the time of survey but intended to use family planning in the future was female sterilization (33%), followed by injectable (22%) and traditional methods (18%) [UP has markedly lower family planning coverage with modern methods among currently married women compared to India (50 and 72% in UP and India respectively), indicating that there is a need for major improvements in access to family planning methods (NFHS-4). The family planning program in UP received a boost by the establishment of an autonomous body in the early nineties and, more recently, of a technical support unit for family planning. During the last two decades, the state government has introduced several interventions such as community-based distributors for contraceptives and clinical outreach camps in low-resource settings. These actions might have contributed to the increase in demand satisfied thereby reducing gap with India in the past two decades, but much more is needed.Within UP there is considerable variation between districts in fertility, ranging from 1.6 to 4.4 in 2015–16, including one-third of districts with fertility levels of 3.0 or higher. Higher fertility districts were more common in the Tarai region and their adjacent districts bordering Nepal, which is considered least developed region in the state. Lower fertility districts were more likely urbanized with better literacy rate.The decline in UP has not been uniform and there are substantial variations in the TFR across districts of UP. The largest declines in TFR were recorded in districts with higher fertility rates, leading to a convergence of fertility between districts. Furthermore, districts that made greater progress in reducing illiteracy had the greatest fertility decline, irrespective of other district economic or sociocultural characteristics. The trends in coverage of family planning and methods mix were dependent on the level of fertility in the districts, but coverage gaps and differential use of sterilization persisted. The increases in demand satisfied and major increases in the share of traditional methods and condoms among married women were observed in the low, middle and high fertility groups of districts (NFHS-4).The increase in traditional methods, mainly the rhythm method, is remarkable. The fact that rhythm method and condoms are among the most popular methods used by couples for contraception in UP and the family planning demand met by any method in all the three clusters is quite high especially in the low fertility districts, indicating that couples might be practicing them correctly and should have contributed for fertility reduction. Moreover, as per NFHS-4, there is a stark difference in UP between rural and urban populations in condom use, which was higher among the urban population with almost 20% condom users compared to their rural counterpart of only 8%. Interestingly, in the early nineties when fertility was high, all the three groups of districts had similar levels of demand satisfied. The recent family planning survey indicates that traditional methods are their preferred method of choice along with injectable [Our study has a number of limitations. We did not analyse the role of sex preference in fertility differentials. Son preference has been identified as an important factor influencing the desire for more children . In 2015The analysis did not consider changes in other determinants of fertility such as age at marriage or the incidence of abortion. The median age at marriage for women increased from 17.1 to 19.0 years in India during 1998–99 to 2015–16, and from 16.3 to 18.5 years in UP. It is unlikely that marriage changes played a major role in limiting fertility, as the median age at marriage is still very low. One of the possible explanations in controlling fertility is rapid increase in induced abortions especially self-administration of medical abortion drugs. A recent study argued that of the estimated 48.1 million pregnancies, 54% resulted in live births, 33% ended in induced abortions and remaining were miscarriages . The autThis analysis provides valuable insights into fertility and family planning within UP. Major declines in fertility have occurred but much remains to be done to achieve fertility targets, reducing inequalities between districts and ensure that couples have universal access to family planning methods. Given UPs large population, activities need to be appropriately scaled and targeted according to need and geography to ensure the achievement of state-level improvements in family planning programs and fertility outcomes.


P<0.05). Additionally, multivariate Cox regression analysis confirmed pelvic involvement and TSLP overexpression as independent prognostic factors for both overall and disease-free survival. Taken altogether, TSLP overexpression reflects a more malignant phenotype and TSLP may be a novel biomarker for EOC.Thymic stromal lymphopoietin (TSLP) is an IL-7-like cytokine that has been reported to be associated with several malignant tumors. The present study aimed to evaluate its role in epithelial ovarian carcinoma (EOC). The mRNA levels of TSLP in human EOC samples and EOC cell lines were determined. Then, the expression of TSLP was examined in 144 clinical tissue microarray samples and correlated with clinicopathological factors. Finally, the correlation between TSLP overexpression and prognosis of EOC patients was analyzed. Our data show that mRNA levels of TSLP were significantly higher in EOC tissues and cell lines. Chi-square tests revealed that TSLP overexpression in EOC was significantly associated with age, histological type, Federation of Gynecology and Obstetrics (FIGO) stage, histological differentiation, pelvic involvement, and lymphatic metastasis. Kaplan–Meier survival analysis revealed that poor prognosis was significantly correlated with older age, advanced FIGO stage, poor histological differentiation, pelvic involvement, lymphatic involvement, or TSLP overexpression ( Ovarian carcinoma is common amongst women and is one of the most lethal carcinomas of the genital system. Epithelial ovarian cancers (EOC) are the most common serous carcinoma and account for the majority of ovarian malignancies . ApproxiThymic stromal lymphopoietin (TSLP) is an IL-7-like cytokine that had been initially identified by its ability to regulate inflammatory responses at the barrier surfaces . TSLP isn=27) and the adjacent normal counterparts were collected from 2013 to 2015 at Nanjing Maternity and Child Health Care Hospital affiliated of Nanjing Medical University and with the approval of the Nanjing Medical University Ethics Committee. Samples were stored in liquid nitrogen for RNA extraction.Ovarian cancer samples . RNA of EOC cell lines was extracted with TRIzol (Invitrogen) according to the manufacturer’s instruction. PrimeScript Reverse Transcriptase  was used to reverse RNA to cDNA. The relative expression of TSLP was detected with ChamQ SYBR qPCR Master Mix  on the LightCycler 96 . The specific primers were as follows: for TSLP (F: 5′-CCCAGGCTATTCGGAAACTCAG-3′and R: 5′-CGCCACAATCCTTGTAAT TGTG-3′) and GAPDH (F: 5′-GGAAGGTGAAGGTCGGAGTCA-3′ and R: 5′- GTCATTGA TGGCAACAATATCCACT-3′).The ovarian cancer tissue samples were cut into 1 mmTissue microarrays were provided by Nantong University Hospital with approval of the local Ethics Committee. For details, 144 patients with primary EOCs of different histological types, 25 benign diseases, 38 borderline ovarian tumours, 25 normal ovaries, and 29 fallopian tubes were collected from patients who underwent surgery between April 2004 and September 2009 at Nantong University Hospital, Nantong, China. Ovarian carcinomas were defined by a two-tier (negative/low expression and overexpression) system. The record of patients reviewed in the context of clinicopathological information including age, surgical procedure, histological type, tumor stage, histological grade, presence of ascites, pelvic involvement and lymph node involvement, CA199, CA125, CA153, SF, menopause, survival time, and survival status. The overall survival (OS) and disease-free survival (DFS) were employed for survival analysis. OS was defined as the period from initial diagnosis to the date of death or last follow-up visit. DFS was defined as the time interval between the date of surgery and the date of disease recurrence. The records of patients, who were alive at follow-up or who did not die of disease, were censored. None of the patients had received preoperative radiotherapy or chemotherapy. Complete follow-up data until May 2016 were documented in all these cases.To prepare the tissue microarrays, the representative cancer area was labeled in specific paraffin blocks according to hematoxylin and eosin staining results. A tissue array needle was inserted to obtain a 2-mm-diameter tissue sample, with one core for each sample. The tissue was then sequentially aligned into the prepared blank paraffin blocks. The tissue microarrays were cut into 4 μm sections and placed on tissue microarray-specific adhesive-coated glass slides. All tissues were reviewed by two gynecological pathologists to verify the diagnosis, histological grade, and stages. Pathological stage and histological subtype were determined for each surgical specimen according to 2013 International Federation of Gynecology and Obstetrics (FIGO) criteria and WHO classification.After routine deparaffinization, rehydration, blocking with hydrogen peroxide, and tissue antigen retrieval with a microwave, the tissue microarrays were incubated with rabbit polyclonal antibody to TSLP , stained with secondary antibody , counterstained with hematoxylin and then evaluated independently by two pathologists who were unaware of the clinical parameters. Discordant cases were re-evaluated on a double-headed microscope to achieve a consensus. Expression levels of TSLP protein were evaluated by observing the incidence and staining intensity of immunohistochemically positive cells, as described by Abubaker . BrieflyP<0.05, the difference was considered significant. The statistical analyses were performed with the SPSS software package .TSLP mRNA levels of tissue samples and cell lines were evaluated with the Mann–Whitney U test. The Chi-square test was used to analysis expression of TSLP protein in tissue microarrays. To determine their prognostic significance, the Cox proportional hazards model was applied to assess clinicopathological parameters for univariate and multivariate analyses. Survival curves were constructed with the Kaplan–Meier method, and the differences between the curves were compared by the log-rank test. When n=27), (P<0.001)  A, implyiP<0.001) B. Our reP<0.001).TSLP expression patterns were further evaluated in 144 primary EOC tissue microarrays. As shown in In our present study, we also collected the clinical features and clinicopathological factors of the EOC patients. P=0.009), histological type (P=0.022), FIGO stage (P<0.001), histological differentiation (P=0.015), pelvic involvement (P<0.001), and lymphatic metastasis (P=0.034). No other significant associations were observed between TSLP overexpression and other clinicopathological characteristics.As shown in A total of 144 cases were followed until May 2016 for the survival analysis. During the follow-up process, 72 patients had died, with a median overall survival (OS) of 38.4 months and a median disease-free survival (DFS) of 29.1 months. Compared with the low TSLP expression group, the overexpression group had significantly lower OS and DFS values. Ovarian carcinoma is known for its high mortality rate (75%) and difficulty in diagnosis, especially at the early stage. Further, the prognosis of ovarian carcinoma is not properly predicted with usual clinical and pathological parameters, and only limited prognosis markers are presently available. Therefore, the development of novel and more efficient molecular biomarkers will be helpful to improve the diagnosis, prognosis prediction, and targetted therapeutics for ovarian carcinoma. In the present study, we discovered significantly increased mRNA levels of TSLP in EOC cell lines and tissues, and significantly higher TSLP expression in EOC tissues. In addition, the correlation of TSLP overexpression with various clinicopathological factors, such as pathological differentiation, FIGO stage, pelvic, and lymph node metastases, was found. Furthermore, Kaplan–Meier survival curve analysis revealed significantly shorter OS and DFS of patients with TSLP overexpression; this suggested that TSLP overexpression may serve as a marker of poor prognosis in patients with EOC.As a member of the IL-2 cytokine family and a distant paralog of IL-7 , oncogen+ response. Experiments conducted on TSLP receptor-deficient mice indicated that TSLP might play an essential role in protection and metastasis of cancer cells [+T cells. TSLP induces the production of immunosuppressive factors such as IL-10, IL-13, and chemokines, which recruit suppressive immune cells and promote Th2-biased immune responses. This helps malignant cells to escape from immune surveillance and protects them from immune attack [Recent studies have indicated that TSLP overexpression may promote the survival, growth, and metastasis of many solid tumors with a Th2-biased immune response, including cervical, breast and pancreatic cancer, and cutaneous T-cell lymphoma ,14–17. Ter cells  through e attack . MoreoveOvarian carcinoma has also been identified as a Th2-biased micro-environment . FurtherKaplan–Meier analysis revealed worse OS and DFS outcomes amongst patients with TSLP overexpression, compared with patients with negative or low TSLP expression. Multivariate Cox regression analysis confirmed TSLP overexpression and pelvic involvement as independent prognostic factors for both overall and disease-free survival. Notably, the prognostic value of pelvic involvement has been long recognized in most cancers of female genital system. Our statistical analyses showed that TSLP overexpression could be used as a prognostic marker and indicator of poor prognosis in ovarian cancer patients.All our findings suggest that TSLP overexpression could facilitate the growth and metastasis of EOC cells, promote a Th2-biased microenvironment and may subsequently lead to poor prognosis. Nonetheless, more evidences are needed to test these hypotheses. In addition, these results suggest the pathological role of TSLP in the development of other malignant carcinomas, as well as the poor prognosis of patients with TSLP overexpression.In conclusion, this is the first study revealing the correlation of TSLP overexpression in EOC patients with cancer progression and shorter survival time. These data suggest that TSLP might be a useful biomarker to predict the prognosis in EOC patients and the development of anti-TSLP therapy for EOC merits further investigation.


Obstructive sleep apnea-hypopnea syndrome (OSAHS) is prone to being complicated with various cardiovascular, cerebrovascular and metabolic conditions. OSAHS, due to its multifactorial nature, entails individualized and comprehensive treatment. So far, no well-established diagnostic criteria for the disease are available. In recent years, miRNA has been shown to be a sensitive biomarker suggestive of the progression and prognosis of many diseases. In this study, we examined some serum miRNAs in healthy OSAHS (OSAHS patients without complication) and OSAHS with arterial hypertension, with an attempt to understand the potential effects on the disease, improve the diagnosis of OSAHS and find OSAHS-related diagnostic markers.Against various diagnostic criteria, participants were divided into three groups: healthy OSAHS, OSAHS with arterial hypertension and healthy controls. Their serum miRNA profiles were assessed by microarray technology, and then differentially expressed miRNAs were verified by quantitative real-time PCR (qRT-PCR). The receiver operating characteristic (ROC) curves of miRNAs were constructed and the areas under the curve (AUC) were calculated. Meanwhile, the miRNAs were subjected to logistic regression analysis. The target genes were bioinformatically assessed, their functions and signaling pathways further determined and eventually an miRNA-gene network was established.Analysis with the miRNA array exhibited that, compared with the control group, 12 differentially expressed miRNAs were found in healthy OSAHS, and 33 were found in OSAHS with arterial hypertension. The expression of miR-126-3p, let-7d-5p, miR-7641 and miR-1233-5p, miR-320b, miR-145-5p, miR-107, miR-26a-5p were validated by using qRT-PCR. Bioinformatics analysis predicted that the potential target genes of these miRNAs might be involved in metabolism, and the regulation of endothelial cells and nervous system. Moreover, the ROC analysis showed that the using miR-145-5p and let-7d-5p in combination can identify the healthy OSAHS, presence of miR-126-3p, miR-26a-5p and miR-107 was well indicative of OSAHS with arterial hypertension.A cluster of dysregulation miRNAs have been found to be involved in the development of OSAHS patients. Moreover, these miRNAs might be used to be potential diagnostic and early warning markers. OSAHS is a complex, multifactorial disorder known to affect, with varying degrees, millions of people worldwide . The cliAs we know, OSAHS involves multiple organs and systems, such as cardiovascular systems. About one-third of hypertensive patients have OSAHS, and about half of OSAHS patients have hypertension . A multiIn this study, we examined some diagnostic evidence and identified a set of warning signs for the progression of the disease and compared healthy OSAHS and OSAHS with arterial hypertension, with an attempt to provide diagnostic evidence and early warning indicators for a better diagnosis of OSAHS.This study was approved by the Ethics Committee of the Union Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, and written informed consent was obtained from all participants.The subjects were those who visited the Department of Otorhinolaryngology, the Union Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, due to snoring or apnea from March 2017 to November 2017. Healthy controls were recruited from the Health Screening Center of the same hospital and didn’t have any medical diseases or snoring.All participants received overnight polysomnography (PSG), OSAHS patients and normal subjects were confirmed on the basis of American Academy of Sleep Medicine (AASM) Guidelines. Meanwhile, all participants underwent physical checkups, blood pressure measurement and tests of blood biochemistry.The criteria for exclusion included: (1) presence of other sleep disorders  diagnosis) and history of having received treatment for sleep related breathing disorders; (2) other diseases such as central nervous system diseases, cardiopathy, diabetes, renal disease, thyroid disease, cancer, ongoing infections; (3) old age (> 60 year-old), young age (< 24 year-old), or being pregnant.They were divided into 3 groups, each group having 20 subjects: (1) healthy controls , (2) healthy OSAHS  and (3) OSAHS with arterial hypertension . In each group, 5 subjects were subjected to microarray and the other 15 subjects received qRT-PCR for validation.Blood samples were collected from all the participants at AM 8:00 after receiving full-night in-laboratory polysomnography and an overnight fasting. For miRNA studies, blood was harvested into an inert separation gel vacuum procoagulant tube. Within 60 min of blood collection, the blood was centrifuged at 3000 g for 10 mins to obtain serum. The supernatant was transferred to RNase-free Eppendorf tubes and then stored at − 80 °C until RNA extraction.Total RNA, including miRNA, was extracted from 15 frozen serum by using QIAGEN RNeasy Mini Kit  according to the manufacturer’s instructions. RNA concentration was determined on an ND-2000 spectrophotometer  at 260 nm, 280 nm and RNA integrity was determined by RNA gel electrophoresis. Small isolated RNAs was processed with the FlashTag®Biotin HSR RNA labeling kit  and was subsequently subjected to hybridization in the GeneChip® Hybridization Oven 645 . Washing and scanning were respectively conducted on the GeneChip® Fluidics Station 450  and the GeneChip® Scanner 3000 7G  by following instructions. The data were analyzed against Affymetrix Expression Console-1_4_0 (EC 5.0) by using Robust Multichip Average (RMA) as normalization method.p value < 0.05) as found by the microarray, the miRNAs found in both healthy OSAHS and in OSAHS with arterial hypertension and in those that have been reportedly associated with mental disorder, endothelial dysfunction, oxidative stress or angiogenesis, were selected. Those miRNAs were verified in 45 blood samples by qRT-PCR. Total RNA was extracted according to the instructions of miRNeasy serum kit . Moreover, due to the unavailability of stable internal control in the serum, C. elegans miR-39 miRNA mimic, the miRNeasy serum/plasma spike-in control , was used to monitor miRNA purification and amplification. cDNA was synthesized from total RNA using the miScript II RT kit  and qRT-PCR was performed in a Lightcycle 480 RT-PCR system  using the miScript SYBR Green PCR kit . The thermal cycle profile was as follows: an initial activation of 15 min at 95 °C, and 45 cycles of denaturation (15 s at 94 °C), annealing (30 s at 55 °C) and extension (30 s at 70 °C). The specificity and identity of PCR products were evaluated by melting curve analysis, with cel-miR-39 used as a normalization standard for miRNAs. The relative levels of each miRNAs were determined by 2−[Ct(miRNA)-Ct(cel-miR-39)]. Primer sequences are listed in Table Of the significantly differentially expressed miRNAs  was calculated to calibrate the p value. For the results of qRT-PCR, independent sample Student t-test and Mann-Whitney U tests were performed for statistical analysis. To further determine the prediction values of the selected miRNAs, ROC curves were constructed among the three groups. The AUC was calculated, and the optimum sensitivity and specificity were determined by Youden index. Logistic regression models were generated to assess the value of the differentially expressed miRNAs in combination in the identification of OSAHS patients. Variables were included in the model if they exhibited statistically significant contributions as shown by the likelihood ratio test. The AUC was used to determine the maximum differentiating ability of the model. Variables which had no statistically significant contributions to the model but could increase its AUC were also selected. All analyses were performed using GraphPad Prism  and statistical software package SPSS . All tests were two-sided and a p value < 0.05 was considered to be statistically significant.Normally distributed data were presented as means ± SEM, non-normally distributed data were expressed as medians , and qualitative variables were given as frequencies and percentages. Possible differences in demographic and clinical variables among the groups were evaluated by one-way analysis of variance (ANOVA) and Kruskal-Wallis. For microarray analysis, we adopted the Random variance model modified All participants enrolled were Chinese. Table P < 0.05) in healthy OSAHS. Among them, 6 were up-regulated and 6 were down-regulated (P < 0.05) , compared with the healthy control group. Of them, 20 were up-regulated and 13 down-regulated (P < 0.05)  Fig. . In OSAH05) Fig. . Of note05) Fig. . The resP < 0.05). Moreover, let-7d-5p was down-regulated only in healthy OSAHS . Significant down-regulation of other 4 miRNAs  was also confirmed . The expression levels of miR-7641 and miR-1233-5p were too low to be appreciable in the three groups (data not show).As aforementioned, we chose 6 miRNAs for qRT-PCR validation. Of them, 4 were overlapping miRNAs from healthy OSAHS and OSAHS with arterial hypertension , two were from OSAHS with arterial hypertension . Despite their low fold-change of 1.45 and 1.2, miR-145-5p and miR-320b were also chosen from healthy OSAHS, because, according to the selection criteria, only overlapping miRNAs would be selected in healthy OSAHS. Meanwhile, these two miRNAs had been considered to be potential biomarkers indicative of cardiovascular conditions and hypoxia. Thus, 8 miRNAs were selected for validation by qRT-PCR. Only miR-126-3p was verified to be down-regulated in both OSAHS groups Fig. , b     Fig. . At the 01) Fig. . These G05) Fig. , b. Furt05) Fig. , b.Fig. P = 0.0027), 0.871        . These models were shown to be able to well differentiate OSAHS patients from healthy controls.The sensitivity and specificity of these serum miRNAs as potential diagnostic and early warning markers in OSAHS patients were investigated by ROC analysis. The AUC of miR-126-3p in the two groups was 0.822  = 0.671–0.973; sensitivity: 86.7%; specificity: 66.7%; 01) Fig. . The AUC01) Fig. . The AUC19) Fig. . The AUC11) Fig. . The AUC29) Fig. . The AUC32) Fig. . Logisti01) Fig. . Model 2As a serious poorly-understood clinical condition, OSAHS is associated with many diurnal symptoms and has been a subject of active studies –25. So fIn this study, we analyzed the differences in serum miRNA expression in healthy controls, healthy OSAHS and OSAHS with arterial hypertension using microarray technique, qRT-PCR and statistical analysis. Our data showed six serum miRNAs had significant changes in OSAHS patients as compared to healthy controls. A single cluster of miRNAs appears to be able to specifically identify healthy OSAHS and OSAHS with arterial hypertension. The specificity and sensitivity of the six miRNAs were not good in predicting OSAHS. We used a logistic regression analysis to select those miRNAs that were associated with the two subtypes of OSAHS. The results showed that the combination of miR-145-5p and let-7d-5p and the combination of miR-126-3p, miR-26a-5p and miR-107 was more valuable, in terms of specificity and sensitivity, in differentiating the OSAHS subtypes.Among the dysregulated miRNAs, the miR-126-3p was found to be consistently down-regulated in healthy OSAHS and in OSAHS with arterial hypertension, and in both types of OSAHS, miR-126-3p had good predictive value, indicating that it, as a marker, was involved in the pathogenesis of both healthy OSAHS and OSAHS with arterial hypertension. MiR-126, one of the most abundant miRNAs in endothelial cells , has bee−/− mice with atherosclerosis induced by high-fat diet [Interestingly, among specific miRNAs in the two groups, most of them were hypoxamiRs (hypoxia-associated miRNAs), a specific group of miRNAs that has been proved to be associated with hypoxia . In OSAHfat diet . Moreovefat diet . These sfat diet . Both mifat diet . Indeed,fat diet . In partfat diet , and wasfat diet . A recenfat diet . In addifat diet . PresumaMeanwhile, let-7d-5p, miR-320b and miR-145-5p were validated to be the specific miRNAs in healthy OSAHS. It was reported that let-7 miRNA was one of the highly-expressed miRNA in the human brain . SpecifiAmong the miRNAs investigated in this study, cardiovascular-related miRNAs are of great value in the research of OSAHS. It has been reported that miR-320b was down-regulated during acute myocardial infarction and was intimately related to plaque stability , 57. PreMicroarray tends to yield a long string of target genes. GO and KEGG pathway analyses are generally employed to know their molecular functions and biological processes of these genes , 67, 68.However, several limitations of the present study should be mentioned. First, the sample size of our study was relatively small. We sub-grouped OSAHS patients in terms of freedom of complications and presence of arterial hypertension only, which could substantially limit number of available subjects. Many adult OSAHS patients often had more than one complication, such as diabetes, hypertension, dyslipidemia or cardio-cerebrovascular diseases. On the other hand, absence of complications and the single complication in our series increased the power of our study. Numerous therapeutic studies have shown that early OSAHS damage were reversible . Study oOur study demonstrated that, the miRNA expression was dysregulated in OSAHS patients, and some miRNAs were differentially expressed in healthy OSAHS and OSAHS with arterial hypertension. These miRNAs might be used as biomarkers for stratifying OSAHS patients, achieving early diagnosis and improving diagnostic accuracy.


Giardia duodenalis , has been widely reported in humans and animals, including rodents. The bamboo rat, a rodent species belonged to the subfamily Rhizomyinae, is farmed in China because of its medicinal and edible values. However, no information of G. duodenalis infection was available in bamboo rats prior to the present study. Here, the prevalence and genetic diversity of G. duodenalis in bamboo rats from Hunan Province of China were investigated.The zoonotic parasite, G. duodenalis infection by using a nested PCR approach targeting the beta giardin (bg) gene. Significant differences (P < 0.01) in prevalence were found among different age groups and geographical localities, and among different farms in Wugang city. Sequence analysis revealed existence of the zoonotic assemblage B and genetic diversity of G. duodenalis in these animals. Multilocus genotyping analysis also indicated broad genetic diversity of assemblage B isolates in these bamboo rats.Of 480 faecal samples collected from six farms located in four cities  of Hunan Province, 52 (10.8%) were positive for G. duodenalis in bamboo rats. These findings will provide basic data for implementing effective strategies to control giardiasis in bamboo rats.This is the first report of the infection and genetic variations of The online version of this article (10.1186/s13071-018-3111-2) contains supplementary material, which is available to authorized users. Giardia duodenalis  is a common zoonotic protozoan that inhabits the gastrointestinal tracts of animals and humans [G. duodenalis, is an important diarrheal disease concerning both public and veterinary health worldwide [G. duodenalis infection has been widely reported in domestic  and wild animals  in Asia, Europe, Australia, North America and Africa [G. duodenalis infection could be observed in young, undernourished, or immunocomprised individuals [d humans –3. Giardorldwide , 5. In rd Africa –19, and d Africa , 21. Altd Africa , 23, watividuals , 25. Furividuals , 27.Rhizomys sinensis), a rodent species belonging to the subfamily Rhizomyinae, is widely distributed in southern Asia, i.e. southern China, India, Myanmar, northern Vietnam and Thailand [Cryptosporidium spp. [Penicilliosis marneffei [Escherichia coli [Trichinella spp.) in these animals should also not be neglected [G. duodenalis in bamboo rats was, until now, unknown, the presence of this parasite in other rodents  has been reported in China, Romania, Laos, America, Germany, Austria, Denmark, Hungary, Finland, France, Italy, Luxembourg, the Netherlands, Norway, Poland, Portugal and Sweden, with a prevalence of 1.9–83.0% [The bamboo rat , triosephosphate isomerase (tpi) and glutamate dehydrogenase (gdh).To reveal the infection status of ene loci –48, nameFrom August to October 2017, 480 fresh faecal samples  following the manufacturer’s protocol. The extracted DNA samples were stored at -20 °C for further analysis.To remove potassium dichromate solution, all faecal specimens of bamboo rats were washed several times using distilled water under centrifugation at 13,000× G. duodenalis in bamboo rats was determined by using a nested PCR targeting the bg gene using primers reported previously [bg gene were further analyzed with nested PCRs of gene loci tpi and gdh, respectively [Ex Taq buffer (Mg2+ free), 2 mM MgCl2, 0.2 mM dNTP mixture, 0.625 U TaKaRa Ex Taq  and 0.4 μM of each primer. Negative and positive controls were included in each PCR reaction and negative samples were spiked with positive material to investigate whether sample material had been associated with inhibition. The secondary PCR amplicons were analyzed by using 1% agarose gels electrophoresis with ethidium bromide. The positive secondary amplicons were sent to Sangon Biotech Co. Ltd.  for direct sequencing using the secondary PCR primers.The prevalence of eviously , 49–51. ectively . A 25 μlG. duodenalis within GenBank by using Basic Local Alignment Search Tool (BLAST) of the National Center for Biotechnology Information (NCBI) to identify the assemblages and subtypes.The nucleotide sequences obtained were aligned and edited by using the software Clustal X 1.83 . Then, tP < 0.05.The differences in prevalence among bamboo rats of different age groups and farms were calculated by using the Chi-square test within the software SPSS 19.0 for Windows , and the difference was considered statistically significant when Giardia duodenalis infection has been reported in humans and a large number of animal hosts worldwide [Apodemus spp., Microtus spp., Myodes spp., house mice, brown rats, Asian house rats, beavers, roof rats and deer mice) [G. duodenalis infection based on the nested PCR amplification targeting the bg gene. The prevalence of G. duodenalis in bamboo rats in this study was well in the range of previous studies in farmed animals and wild rodents. However, significant differences in prevalence  were detected among six farms from four sampling cities, ranging from 0 to 38.2%. The highest prevalence was found on Farm 3 of Wugang city (38.2%), while no infections were detected on Farm 4 of Chenzhou city and Farm 6 of Jishou city  among three farms in Wugang city, with the highest on Farm 3 and lowest on Farm 1  gene was commonly used as a good marker to detect G. duodenalis infection in animals and humans [bg gene was used to investigated G. duodenalis infection in bamboo rats. Theoretically, bg is unique to Giardia and has a high degree of sequence diversity for identifying sub-assemblages [SSU rRNA gene locus, the copy number is lower. In addition, nested PCR may not be used to distinguish between infection (cysts being excreted following encystation) and G. duodenalis DNA being excreted due to dead cysts being ingested. Alternatively, although an under-estimation of prevalence may be associated with traditional microscopy [bg gene to simultaneously evaluate cyst viability and discern zoonotic G. duodenalis assemblages A and B [G. duodenalis in bamboo rats, many methods should be incorporated in future studies.orldwide , 15, 47.er mice) , 53–57. y nature , the smad humans , 58, 59.emblages , 50, 58.croscopy , morpholcroscopy –63. A pr A and B . Therefoχ2 = 28.298, df = 3, P < 0.01) in prevalence was also observed in bamboo rats of the four age groups in the present study  have been detected in rodents [G. duodenalis positive samples from bamboo rats were identified as assemblage B. This finding would indicate the fact of simple G. duodenalis population in bamboo rats. This result may also be due to small sampling numbers from limited areas in this study. To address this point, a large number of epidemiological investigations should be implemented in future studies. However, assemblage B could be transmitted zoonotically [Giardia-infected children in some studies [G. duodenalis in bamboo rats in investigated areas of Hunan Province, the infection status of handlers/farmers in the farms should be determined in future studies.Five  rodents , 66, 69.otically –72 and hotically , 73, 74.otically . Of the  studies , 72, 75. studies . To addrG. duodenalis-positive samples, 52, 12 and 27 were successfully amplified at loci bg, tpi and gdh, respectively, by using nested PCRs  was identified in bamboo rats in the present study, zoonotic potential and genetic diversity were found. To our knowledge, this is the first report on G. duodenalis infection in bamboo rats.Additional file 1:Table S1. Sampling information in the present study. (DOCX 12 kb)Additional file 2:Figure S1. Sampling sites in the present study. (TIF 2527 kb)


World population is growing at about 80 million people each year. Ethiopia is the 12th most populous country in the world. Existing literatures showed that the role of proximate determinants in inhibiting the total fertility has not yet been determined from the DHS data in the country. This study may provide evidence based information regarding the observed changes in total fertility. The objective of this study was assessing proximate determinants of fertility and the role of selected socio-economic variables in influencing fertility in Ethiopia.The EDHS data of 2011 and 2016 were used in our study. A total of 16,515 eligible women included in 2011 and 15,683 in 2016 surveys made up the sample for the study. The roles of each of the four proximate determinants in declining fertility have been determined. The background variables selected for the analysis include: region of residence, educational status, wealth index and place of residence. The Bongaart model is used to explain the observed socio-economic differentials in fertility during the two survey years.In 2011, index of marriage inhibited fertility by 37.8%, however in 2016 it inhibited fertility by 34.4%. In 2011, contraceptive use reduced fertility by 28.5% while in 2016 it reduced fertility by 30.7%. The index of postpartum infecundity decreased fertility by 34.7% in 2011 and by 34.5% in 2016. Foetal wastage inhibited fertility by 9.2% in both survey years. The total fertility rate in 2016 was 4.14 whereas the projected total fertility in 2020 will be 3.2 children per woman.Among the four proximate determinants of fertility, the contribution of index of marriage was the highest in inhibiting fertility in 2011. On the other hand, the contribution of postpartum infecundability was the highest in inhibiting fertility in 2016. The contribution of the index of contraceptive in inhibiting fertility increased from 28.5% in 2011 to 30.7% in 2016. The index of foetal wastage contributed the least in both 2011 and 2016 survey years. Therefore, strategies have to be designed to promote the contraceptive use and breast feeding practices among the reproductive women. World population is growing. The Ethiopia population is also increasing. Fertility rate is an important determinant of population size. In this study the contribution of the proximate determinants of fertility has been determined.A total of 16,515 (2011EDHS) and 15,683 women (2016 EDHS) were the study participants. The extent to which each of the four proximate determinants contributed in declining the total fertility has been determined. The Bongart revised model was used to explain the observed socio-economic differentials in fertility.In 2011, 37.8% of births were inhibited due to the effect of delayed marriage & non marriage, whereas its contribution in declining fertility was 34.4% in 2016. The influence of contraception in fertility inhibition was 28.5 and 30.7% below its biological maximum in 2011 and 2016 respectively. Postpartum infecundability decreased the total fertility by 34.7% in 2011 and 34.5% in 2016. The effects of index of foetal wastage were the same i.e. it inhibited only 9.2% of the total births in both survey years. Based on our projection the future total fertility of Ethiopia in 2020 will be 3.2.In summary, index of marriage and postpartum infecundability were the leading fertility inhibiting factors in 2011 and 2016 respectively. The contribution of the index of contraceptive in inhibiting fertility increased from 28.5% in 2011 to 30.7% in 2016 whereas foetal wastage contributed the least in both survey years. Therefore, contraceptive use and breast feeding practices have to be promoted among the study subjects.In demography, fertility indicates the product or output of reproduction, rather than the ability to have children. The physiological ability to have children that is manifested roughly in the period between menarche and menopause in women is termed fecundity. Demographers define a third, further aspect of reproduction, fecundability, which is the probability of becoming pregnant, or the likelihood of exposure to the possibility, that depends on the pattern of sexual and pregnancy preventive behaviours .Demographically observed fertility or infertility is the result of a well-defined number of both biological and behavioural factors, which serve to mediate the influence of culture, society, economic conditions, living standards, and other similar background determinants on individual reproductive behaviour. Together, these biological and behavioural factors are called the proximate determinants of fertility and they are the factors through which, and only through which, the social and economic environment can influence individual procreation. Together, these factors constrain fertility, and explain why women do not have the maximum possible number of children, which would be about 35 if they reproduced continuously from, say, the age of 18, to about the age of 45, having a birth every 9 months [World population is growing at about 80 million people each year. If current trends keep on, there will be about 9.2 billion people on this planet by the mid of 21st century. Virtually all of the major problems that threaten the world today are connected with rapid population growth. It fuels health risk, hunger or poverty, water scarcity, environmental depletion and political instability  with a rThe TFR of Ethiopia declined from 5.5 children per woman in 2000 to 4.6 children per woman in 2016 . This pu, fertility is differentiated by ethnic group, place of residence, educational attainment, women’s work and age at marriage. Contraceptive use and wealth index also played an important role in explaining the fertility differentials [Studies done in different countries identified various diffentials of fertility. Study conducted in Bangladesh indicated contraceptive practice as a key factor in fertility change . In Zambrentials . The finrentials . Most ofrentials . Study drentials . In Asiarentials .John Bongaarts early framed a model explaining fertility as a function of proximate determinants of fertility through which the background variables affect fertility . RevisedThe source of data for our study was the EDHS conducted in 2011 and 2016. A total of 16,515 eligible women enrolled in 2011 and 15,683 in 2016 surveys made up the sample for this study. The roles of each of the four proximate determinants in fertility decline was determined. One important fertility determinant variable was not captured by these datasets namely abortion due to lack of appropriate data. Instead of abortion data, foetal wastage data was included in the analysis. The selected background variables include: region of residence, educational status, wealth index and place of residence.John Bongaarts framework for analysing proximate determinants of fertility model was used to analyse the data. The four proximate determinants of fertility, total fertility and background variables were calculated by using Microsoft excel software. In the following section we presented detailed analysis of fertility differential model that quantifies the negative and positive effects of each of the socio-economic and cultural factors on fertility through various intermediate fertility variables. For illustration, the model was used to explain the observed socio-economic differentials in fertility during the 2011 and 2016 EDHS.Bongaarts model of estimating the effect of four proximate determinants assumes that the natural reproductive capacity that is total fecundity rates (TF) is nearly the same for all women, but their actual reproductive performance is modified by four major proximate determinants. In his model , Bongaarm is the index of proportion married, Cc is the index of non-contraception, Ca is the index of induced abortion, Ci is the index of lactational infecundability and TF is the total fecundity.Where, CThis revised model replaced only the index of all foetal wastage  instead of the index of abortion. Other three indices have remained the same as proposed by Bongaarts original model .The revised Bongaarts model  is repreTFR is the effect of all four proximate determinants of fertility. It is calculated by multiplying the four indices. Cm, Cc, Cfw, Ci are the indices of marriage, contraception, foetal wastage, and postpartum infecundability respectively. The indices can only take values between 0 and 1. When there is no fertility-inhibiting effect of a given intermediate fertility variable, the corresponding index equals 1, and if its fertility inhibition is complete, the index equals 0. These indices can be estimated from measures of the proximate variables and their estimates are shown below.The index of marriage measures the inhibiting effect of marriage on fertility in the population. It has to be noted that the higher the level of marriage in the population the lower the fertility inhibiting effect and the vice versa. The index equals one when all women are cohabitating, and zero when no women are in a union. The index of marriage is estimated using the formula;Wherem (a) = age specific proportions currently married among females,g (a) = age specific marital fertility rates.m (a) is obtained by dividing the number of married women of a particular age group by the number of women in the same age group whereas; g (a) is calculated by dividing the births of a particular age group by the number of women in the same age group.Cc equals one when no contraception is used, and zero when all fecund women use 100% effective contraception. The index of contraception is estimated using the formulaThe index of contraception in the model measures the inhibiting effect of contraception on fertility in the population. The higher the level of contraception in the population, the higher the inhibiting effect due to contraception and the lower the level of contraception the lower its inhibiting effect on fertility. The Where;u = Proportion using contraception among married women of reproductive age (15–49 years).e = Average use effectiveness of contraception.e (m) = method specific use effectiveness,U (m) = proportion of women using specific method.The coefficient 1.08 represents an adjustment for the fact that women do not use contraception if they know that they are sterile. The indices of use effectiveness proposed for particular contraceptives are; pill = 0.90, IUD = 0.95, sterilization = 1.00, injection = 0.99 and others = 0.70 The index of fetal wastage (Cfw) is defined as the ratio of the observed TFR to the estimated TFR with all fetal wastage which is (TFR + AFW), that is Cfw = TFR/TFR + AFW. Where AFW equals the average number of births averted per woman by the end of the reproductive years for all foetal wastage and which is estimated byWhere, TFW is the total foetal wastage rate and AFW is the average number of all foetal wastages per woman at the end of the reproductive years.i).1.5 months of minimum postpartum anovulation.ii).7.5 months of waiting time to conception.iii).2 months of time added by spontaneous intrauterine mortality.iv).9 months for a full term pregnancy.The index of postpartum infecundability measures the inhibiting effect of breastfeeding or abstinence on fertility in the population. The index of postpartum infecundability in the model is estimated using the effect of breastfeeding (lactation amenorrhea) or postpartum abstinence. The ratio of natural fertility in the presence and absence of postpartum infecundability therefore equals the ratio of the average birth interval without and with postpartum infecundability. If no breastfeeding and postpartum abstinence are practiced, the birth interval averages about 20 months, which is the sum of;Bongaarts Stated that, in the presence of breastfeeding and postpartum abstinence, the average birth interval equals approximately 18.5 months (7.5 + 2 + 9) plus the duration of postpartum infecundability . The indWherei = average duration of postpartum amenorrhea.The index is calculated as the average birth interval in the absence of breastfeeding divided by the average length in the presence of breastfeeding. The index equals one in the absence of lactational amenorrhea or postpartum abstinence and declines in size as the period of postpartum infecundability rises.According to our analysis the value for Cm in 2011 was 0.622, where both delayed marriage and non-marriage inhibited fertility by 37.8%. In 2016 Cm was 0.656, in which case delayed marriage & non marriage inhibited fertility by 34.4%. The value for Cc in 2011 has been estimated to be 0.715, in which case contraceptive use has reduced fertility by 28.5%, while in 2016 the Cc was 0.693, where the use of contraceptives reduced fertility by 30.7% below its biological maximum of 15.3 births. The estimated values were presented in Table Our analysis showed that the index for postpartum infecundity (Ci) in 2011 was 0.653, where lactation amenorrhea decreased fertility by 34.7%, and the index for Ci in 2016 was 0.693, where the effect of lactation amenorrhea reduced fertility by 34.5%. The indices for foetal wastages in both 2011and 2016 survey years were the same, i.e. 0.908. In both years foetal wastages inhibited 9.2% of the observed total births. The estimated values were presented in Table The contribution of each of the four proximate determinants and their variability by these background variables in declining fertility were presented in Tables In our study, in 2011 the highest Cm (0.801) was observed in Afar region whereas in 2016 its highest Cm (0.760) was shown in Somalia region. These showed that delayed marriage and non-marriage reduced fertility by 19.9% in 2011 in Afar and 24% in 2016 in Somalia regions. On the other hand, the lowest Cm (0.316 in 2011 and 0.362 in 2016) were demonstrated in Addis Ababa region, where delayed marriage and non-marriage reduced fertility by 68.4% in 2011 and 63.8% in 2016.Regarding differential in residence, the Cm was highest among rural residents in both survey years where, Cm was 0.665 in 2011 and 0.640 in 2016. These showed that delayed marriage and non-marriage inhibited fertility by 33.5% in 2011 and 36% in 2016 among rural residents. Conversely, the Cm was lowest, 0.352 in 2011 and 0.428 in 2016, among urban residents. These showed that delayed marriage and non-marriage prevented fertility by 64.8% in 2011 and 57.2% in 2016 among urban women.From the participants' education perspective, as per the study results, the Cm was highest, Cm = 0.746, among women with no formal education in 2011 and Cm = 0.608 among women who attended primary education in 2016. These indicated that delayed marriage and non-marriage inhibited fertility by 25.4% in 2011 and 39.2% in 2016 among women with no education and primary education, respectively. On the contrary, the Cm was lowest, 0.371, among women who attended secondary education in 2011 and 0.311 among women with no education in 2016. These showed that delayed marriage and non-marriage decreased fertility by 62.9% in 2011 among those who attended secondary education and 68.9% in 2016 among those who attended no formal education.Differential of marriage indices with respect to differences in wealth quintiles of the women was analysed. Accordingly, the highest Cm, 0.756 in 2011 and 0.783 in 2016 was observed among participants in the lowest wealth quintile. These demonstrated that delayed marriage and non marriage prevented fertility by 24.4% in 2011 and 21.7% in 2016 among women with the lowest wealth quintile. The lowest Cm, on the other hand, 0.512 in 2011 and 0.493 in 2016 were realized amongst participants in the highest wealth quintile where delayed marriage and non-marriage averted fertility by 48.8% in 2011 and 50.7% in 2016.= 0.984, in Somalia region and lowest, Cc = 0.437, in Addis Ababa region. These signify that contraceptive use inhibited only 1.6% of births in Somalia region whereas 56.3% in Addis Ababa region. The Cc was also the lowest, Cc = 0.377, in Addis Ababa in 2011 which shows that contraceptive use lowered fertility by 63.8%. Similarly, in 2011, the Cc was the lowest, Cc = 0.960, and contributed 4% in fertility reduction in Somalia region.According to our analysis, in 2016, the Cc was highest, Cc The Cc was analysed in relation to participants’ education level and variability has been observed. Accordingly, the lowest Cc, 0.351, was observed in 2011 among women having higher education and the lowest Cc, 0.481, was shown in 2016 among women with secondary education. These showed that the use of contraceptive lowered fertility by 64.9% in 2011 and 51.9% in 2016 among participants with higher and secondary education, respectively. On the other hand the highest Cc, 0.776 in 2011 and 0.649 in 2016, were observed among women with no formal education, which demonstrated that contraception decreased fertility by 22.4% in 2011 and 35.1% in 2016.In our study, the Cc varied with respect to participants’ place of residence. Consequently, the highest Cc, 0.668 in 2011 and 0.810 in 2016 were observed among rural inhabitants whereas the lowest indices, 0.496 in 2011 and 0.470 in 2016 were demonstrated among their urban counterparts. These showed that contraceptive use in rural setting decreased fertility by 33.2% in 2011 and 19% in 2016 but it decreased fertility by 50.4% in 2011 and 53% in 2016 among the urban women.In both surveys, the lowest Cc, 0.481 in 2011 and 0.518 in 2016, were observed among the participants in the highest wealth quintile. This showed that contraceptive use reduced fertility by 51.9% in 2011 and 48.2% in 2016. On the other hand, the highest Cc values, 0.865 in 2011 and 0.808 in 2016, were observed among participants in the lower wealth quintiles which indicated that contraceptive practices decreased fertility only by 13.5% in 2011 and 20% in 2016.The Cfw was calculated using the data from both surveys to detect any differences across the back ground variables. The Cfw was lowest, 0.750, in Addis Ababa and highest, 0.958, in Afar region in 2011. As a result, fertility declining effect of foetal wastage was 25% in Addis Ababa and 4.2% in Afar region.The lowest Cfw, 0.628 in 2011 and 0.592 in 2016, were observed among participants in the highest wealth quintiles. Therefore, the effect of foetal wastage in reducing fertility was 37.2% in 2011 and 40.8% in 2016. Oppositely, the highest Cfw, 0.907 in 2011 and 0.914 in 2016 were demonstrated among participants in the second wealth quintile. These indicated that the effect of Cfw was 9.3% in 2011 and 8.6% in 2016 in reducing the total fertility.The Cfw was lowest, 0.676 in 2011 and 0.709 in 2016, among women with no education, which showed that the effect of foetal wastage was 32.4% in 2011 and 29.1% in 2016 in fertility reduction. On the other hand, the highest Cfw values, 0.838 in 2011 and 0.860 in 2016 were demonstrated among participants having higher education. This showed that the fertility reducing effect of Cfw was 16.2% in 2011 and 14% in 2016 among women with tertiary education. The lowest values in Cfw, 0.617 in 2011 and 0.575 in 2016, were observed among urban residents, which indicated that the fertility declining effect of foetal wastage among urban women was 38.3% in 2011 and 42.5% in 2016. On the contrary, the highest Cfw, 0.652 in 2011 and 0.659 in 2016, were demonstrated among rural residents. These showed that the effect of foetal wastage in fertility reduction was 34.8% in 2011 and 34.1% in 2016 among rural residents.In our analysis, the Ci varied across the participants’ background variables. Consequently, the highest indices, 0.901 in 2011 and 0.862 in 2016, of postpartum infecundability were observed in Addis Ababa region. This showed that the effect of Ci on total fertility decline was only 9.9% in 2011 and 13.8% in 2016 in the region. On the other hand, the lowest indices, 0.590 in 2011 and 0.590 in 2016 were observed in Tigray region which showed that the indices contributed 46.2% and 41% in fertility decline in 2011 and 2016 respectively, in the region.Differences in Ci were also observed among the wealth quintiles where the lowest Ci values, 0.592 in 2011 and 0.581 in 2016, were observed among the lowest wealth quintiles. These demonstrated that the effect of Ci in fertility decline was 40.8% in 2011 and 41.9% in 2016 among the lowest wealth quintiles. The lowest indices, 0.560 in 2011 and 0.580 in 2016 were demonstrated among study participants with no formal education. These showed that the effect of Ci in declining fertility among participants with no formal education was 44% in 2011 and 42% in 2016. The highest Ci, 0.803, was observed among participants who attended tertiary education in 2011 whereas 0.897 among women who completed secondary education in 2016.Lower indices of postpartum infecundability, 0.687 in 2011 and 0.570 in 2016, were shown among rural inhabitants. These represented that the effects of Ci in lowering fertility were 31.3% in 2011 and 43% in 2016 among rural women.Our analysis was inclusive of the calculation of the total fertility using revised Bongaarts model. As a result, the total fertility rate in 2016 was calculated to be 4.14 children per woman. The findings of our study also showed variability in TFR across the selected background variables. Accordingly, the highest TFR, 8.1 children per woman, and the lowest TFR, 1.5 children per woman, were observed in Somalia and Addis Ababa regions, respectively in 2016. In this year, the highest TFR of 4.9 children per woman was seen in lowest wealth quintile and the lowest TFR of 1.8 children per woman in the highest wealth quintile. In relation to the participants’ education, the highest TFR, 2.6 children per woman, and the lowest TFR, 1.8 children per woman, were observed among participants with primary education and higher education respectively in 2016. The TFR was 2.5 in rural and 1.5 in urban areas in this year.The Bongaarts model of proximate determinants was used to project future fertility of the country. This was analysed by considering the expected contraceptive prevalence rate set by the Ethiopian government to attain a certain fertility level in 2020.We supposed that TFR1 and TFR2 be the total fertility rates, in year 1 (the present year) and year 2 (year in the future), and the corresponding levels of contraceptive prevalence and use effectiveness be u1 and e1, and u2 and e 2, respectively. We calculated the level of total fertility for the changes of contraceptive uses from year 1 to year 2. However, we assumed that the other proximate determinants except for contraception remain constant, that is Cm1 = Cm2, Ci1 = Ci2 and Cfw1 = Cfw2. It is also assumed that contraceptive use-effectiveness remains constant.Then TFR1/TFR2 = C1/C2 orTFR2 = Cc2/Cc1 x TFR1 TFR2 =1–1.08xux e2/1–1.08x u1 x e1 x TFR1In Ethiopia, contraceptive prevalence is 36% in 2016 and the government has planned to increase the contraceptive prevalence rate to 55% in 2020 [The projected total fertility rate becomesTherefore, the projected TFR in 2020 will be 3.2 children per woman.Our study assessed the proximate determinants of fertility and the role of the selected socio-economic variables in influencing the proximate determinants and fertility in Ethiopia. The revised Bongaarts model was used to determine the effects of proximate determinants on total fertility rate and its variability among the selected background variables. Generally, the results in this study showed that the impact of the four proximate determinants of fertility varies considerably among the selected background characteristics. In 2011, the Cm inhibited fertility by 37.8% whereas in 2016 it inhibited by 34.4%. Consequently, the Cm in 2011 contributed more for the reduction of fertility than Cm in 2016. This variation could be due to the fact that the proportion of married women was larger, 65% in 2016, when compared to 58% in 2011. This could be explained by the fact that the more women of child bearing age engage in marriage, the lower is its fertility inhibiting effect.Both in 2011 and 2016, Cm played an important role in inhibiting fertility. This is in line with study done in Zambia, which showed marriage as the largest inhibitor on natural fertility . The finIn current study, contraception practice played a role in influencing fertility. Study conducted in Bangladesh indicated that contraceptive practice played a key role in fertility change . ContracIn 2016 survey year the contraceptive use inhibited only 1.6% of births in Somalia region whereas 56.3% in Addis Ababa region. This huge difference observed between the two regions could be explained by variations in contraceptive prevalence rate between the regions, 55.9% in Addis Ababa and 1.5% in Somalia. Moreover, the variation in education among the study participants between the regions could have brought changes in awareness which in turn might have influenced the contraceptive use. Similarly, the highest and the lowest TFR were observed in Somalia and Addis Ababa region, respectively, in 2016. Study conducted in Ghana showed region of residence as predictor of fertility .In 2016, the highest TFR was seen in lowest wealth quintile. Study done in Ghana and Philippines, showed wealth index as predictor of total fertility , 11.In relation to the participants’ education, the highest TFR and the lowest TFR were observed among participants with primary education and higher education respectively in 2016. This is in line with study conducted in Ghana, which showed higher education levels are consistently associated with lower fertility rates . Study dThe TFR was lower in urban areas than rural. This is in line with Ghanian study, in which urban residence is associated with lower fertility rates . Study dReporting and recall bias particularly for age or other retrospective data relying in memory of the past event is the limitation of the study.Among the four proximate determinants of fertility, index of marriage was the most important inhibiting factor of fertility in 2011. On the other hand, postpartum infecundability was the first important fertility inhibitor in 2016. The contribution of the index of contraceptive in inhibiting fertility increased from 28.5% in 2011 to 30.7% in 2016. The index of foetal wastage contributed the least in both 2011 and 2016 survey years. The study also showed substantial differences in fertility inhibition by background factors in both 2011 and 2016.The contribution of index of contraceptive in inhibiting fertility rate has not been as expected when compared to the contribution of other proximate determinants. The total fertility rate has shown variations across the regions. Therefore, the government and development partners need to design effective strategies and act in a concerted way to increase the prevalence of contraceptive use across the country, with particular emphasis to infrastructure limited regions.The contribution of Ci in inhibiting fertility in 2016 was the highest. This calls for further strengthening of breast feeding as a good behavioural practice to promote natural family planning practices among breast feeding women..