本文關(guān)鍵詞：石家莊市孕產(chǎn)婦血清中營養(yǎng)素含量與妊娠并發(fā)癥的患病狀況研究　出處：《河北醫(yī)科大學(xué)》2016年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 孕產(chǎn)婦 營養(yǎng)素 妊娠并發(fā)癥 患病率 影響因素

【摘要】：目的:1了解石家莊市孕產(chǎn)婦常見營養(yǎng)素的總體檢測水平及其缺乏情況。2探討孕產(chǎn)婦在不同觀察因素下血清中各營養(yǎng)素濃度的差異。3了解石家莊市妊娠并發(fā)癥的患病現(xiàn)狀,以及影響妊娠并發(fā)癥發(fā)病的相關(guān)因素,為制定預(yù)防妊娠并發(fā)癥發(fā)生的有效措施提供理論依據(jù)。方法:以2015年6月至9月在石家莊市某醫(yī)院產(chǎn)科住院分娩的孕產(chǎn)婦為研究對象,選擇做孕期妊娠糖尿病篩查以及產(chǎn)前檢查的孕產(chǎn)婦納入本研究,其中產(chǎn)前檢查主要包括一般檢查(身高、體重、血壓等)、血常規(guī)、甲狀腺功能三項(xiàng)、血清中營養(yǎng)素(總蛋白、鈣、鐵、鋅)含量檢測。采用Epidata軟件對上述資料錄入,用SPSS19.0軟件對數(shù)據(jù)進(jìn)行描述和分析。結(jié)果:1研究對象的一般特征:共4431例研究對象納入本次研究,年齡在25~30歲者最多,為2203人,占49.7%;研究對象中無業(yè)組共1892人,占總?cè)藬?shù)的42.7%;居住在市區(qū)的研究對象占66.4%,農(nóng)村的占33.6%;孕前體重正常者共2811人,占63.4%,消瘦和超重者分別占15.5%和16.5%,肥胖者占4.6%;研究對象的孕期增重范圍在≤15kg、15~20kg和≥20kg者,分別為1871人(占42.2%)、1677人(占37.8%)和883人(占19.9%);孕周在37~42周時(shí)分娩的研究對象居多,占總?cè)藬?shù)的96.2%;胎次為1和≥2胎時(shí),分別為2936人(占66.3%)和1495(占33.7%)。2血清中營養(yǎng)素的檢測狀況:3755例孕產(chǎn)婦中,血清中總蛋白濃度為60.53±5.80g/L,缺乏率為36.7%;3594例孕產(chǎn)婦中,血清鈣濃度為2.11±0.31umol/L,缺乏率為69.3%;3616例孕產(chǎn)婦中,血清鐵濃度為11.73±6.45umol/L,缺乏率為40.1%;3590例孕產(chǎn)婦中,血清鋅濃度為8.74±1.89 umol/L,缺乏率為60.4%。3影響血清中總蛋白濃度的單因素分析:孕婦血清中總蛋白濃度隨著年齡增長而降低,差異有統(tǒng)計(jì)學(xué)意義(P0.001)。居住在農(nóng)村地區(qū)的孕婦血清總蛋白濃度略高于市區(qū)(60.80±5.80 g/L vs60.39±5.79 g/L),組間差異有統(tǒng)計(jì)學(xué)意義(P0.05)。隨孕期增重程度的增長,孕婦的血清總蛋白濃度呈降低趨勢,組間差異有統(tǒng)計(jì)學(xué)意義(P0.05)。隨懷孕周數(shù)增長,孕婦的血清總蛋白濃度呈現(xiàn)兩頭高中間低現(xiàn)象,差異有統(tǒng)計(jì)學(xué)意義(P0.001)。4影響血清中鈣濃度的單因素分析結(jié)果顯示:不同年齡、職業(yè)、居住地、孕前BMI、孕期增重、孕周以及胎次對孕產(chǎn)婦血清鈣濃度的影響均無統(tǒng)計(jì)學(xué)意義(P0.05)。5影響血清中鐵濃度的單因素分析結(jié)果顯示:在胎次分別為1組和≥2組,孕產(chǎn)婦的血清鐵濃度分別為10.19±1.64μmol/L和10.72±1.59μmol/L,差異有統(tǒng)計(jì)學(xué)意義(P=0.002)。6影響血清中鋅濃度的單因素分析:孕婦血清鋅濃度在不同職業(yè)和不同居住地間差異顯著,差異有統(tǒng)計(jì)學(xué)意義(P0.05)。胎次為≥2的孕產(chǎn)婦血清鋅濃度高于胎次為1的孕產(chǎn)婦,組間差異有統(tǒng)計(jì)學(xué)意義(P0.05)。7 4431例孕產(chǎn)婦中,妊娠糖尿病的患病率為8.4%,妊娠高血壓的患病率為6.1%,妊娠期貧血的患病率為47.4%,妊娠合并甲減的患病率為5.4%。8妊娠糖尿病的相關(guān)因素分析:單因素結(jié)果顯示,在不同年齡、居住地、孕前BMI、孕期增重、孕周、血清鈣和血清鐵濃度間,孕產(chǎn)婦GD的患病率均不同,組間差異均有統(tǒng)計(jì)學(xué)意義(P0.05)。多因素logistic回歸結(jié)果得出,排除其他混雜因素后,年齡、居住地、孕前BMI、孕期增重、孕周和血清鐵濃度仍是GD的影響因素(P0.05),其中年齡和孕前BMI是GD的危險(xiǎn)因素,孕婦的孕前BMI每增加一個(gè)等級,GD的患病風(fēng)險(xiǎn)增加2.012倍。9妊娠高血壓的相關(guān)因素分析:單因素結(jié)果顯示,在不同年齡、職業(yè)、居住地、孕前BMI、孕期增重、孕周、血清總蛋白以及血清鋅濃度間,孕婦高血壓的患病率均不同,組間差異有統(tǒng)計(jì)學(xué)意義(P0.05)。在排除其他混雜因素后,年齡和血清鋅濃度對孕婦高血壓影響無統(tǒng)計(jì)學(xué)意義,而不同胎次對其影響見統(tǒng)計(jì)學(xué)差異(P0.05)。與無業(yè)組相比較,商管及專技組、個(gè)體及自由職業(yè)組和其他職業(yè)組的孕產(chǎn)婦較無業(yè)組的GH1患病風(fēng)險(xiǎn)均降低(OR1),而科教文衛(wèi)組與無業(yè)組的孕產(chǎn)婦GH1患病率無明顯差異(P0.05)。孕前BMI和孕期增重每增加一個(gè)等級,孕婦高血壓患病風(fēng)險(xiǎn)分別增長2.338倍和1.442倍。孕婦血清總蛋白濃度是GH1患病的保護(hù)因素,即孕婦血清中總蛋白濃度愈高,其患高血壓的可能性愈低(OR=0.442)。10妊娠期貧血的相關(guān)因素分析:單因素結(jié)果顯示,在不同年齡、職業(yè)、居住地、孕前BMI、孕期增重、血清鈣、血清鐵以及血清鋅濃度間,孕婦GA的患病率均不同,組間差異有統(tǒng)計(jì)學(xué)意義(P0.05)。經(jīng)多因素logistic回歸分析得出,居住地、孕前BMI、孕期增重、血清鈣、血清鐵以及血清鋅濃度仍是孕產(chǎn)婦GA的影響因素(P0.05),孕期增重是GA的危險(xiǎn)因素(OR1),孕期增重程度每增加一個(gè)等級,GA患病風(fēng)險(xiǎn)增加1.108倍,95%CI為1.005~1.221。孕婦血清中鈣、鐵以及鋅濃度是GA的保護(hù)因素,即隨三種微量元素濃度的升高,GA患病可能性均降低(OR=0.521、0.625、0.847)。11妊娠合并甲減的相關(guān)因素分析:經(jīng)單因素和多因素分析得出,在不同居住地生活的孕產(chǎn)婦,其GH2的患病率存在差異,且差異有統(tǒng)計(jì)學(xué)意義(P0.05),而且居住在市區(qū)的孕婦患GH2的可能性是農(nóng)村地區(qū)的1.577倍,95%CI=1.059~2.351。結(jié)論:1石家莊市孕產(chǎn)婦常見營養(yǎng)素的缺乏率均較高,有待改善。2年齡較大、孕期增重過多的孕婦血清總蛋白濃度較低;≥2胎次的孕產(chǎn)婦的血清鐵和血清鋅濃度較1胎次的均高;職業(yè)較自由的孕婦血清鋅濃度不易缺乏。3石家莊市孕產(chǎn)婦不同妊娠并發(fā)癥的發(fā)病率在全國均處于較高水平。4控制孕婦懷孕年齡、孕前BMI、孕期增重,并且注重孕期營養(yǎng)素的補(bǔ)充,能有效地控制妊娠并發(fā)癥的發(fā)生。
[Abstract]:Objective: 1 to understand the general level and lack of common nutrients in pregnant and lying in women in Shijiazhuang. 2 to explore the difference of serum levels of nutrients in pregnant and lying in women under different observation factors. 3 understand the prevalence of pregnancy complications in Shijiazhuang, and the related factors that affect the incidence of pregnancy complications, so as to provide a theoretical basis for developing effective measures to prevent pregnancy complications. Methods: from June 2015 to September in maternal obstetric hospital delivery in a hospital in Shijiazhuang city as the research object, choose to do pregnancy gestational diabetes screening and antenatal examination included in the study, which mainly includes the general inspection of prenatal examination (height, weight, blood pressure, blood, etc.) three thyroid function and serum nutrients (total protein, calcium, iron, zinc) content detection. Epidata software is used to record the above data, and the data are described and analyzed with SPSS19.0 software. Results: the general characteristics of the 1 subjects: the study included a total of 4431 subjects, age at 25~30 years old, 2203 people, accounting for 49.7% of the unemployed group; a total of 1892 people in the study, 42.7% of the total number of living in the city; the research object in rural areas accounted for 66.4%, accounted for 33.6%; pregnancy a total of 2811 people of normal weight, overweight and weight loss accounted for 63.4%, accounted for 15.5% and 16.5%, obesity accounted for 4.6%; the research object's weight gain during pregnancy in the range of less than 15kg, 15~20kg and 20kg, respectively, 1871 (42.2%), 1677 (37.8%) and 883 (19.9%) the object of study; gestational weeks at 37~42 weeks of delivery in the majority, accounting for 96.2% of the total number of 1; and more than 2 parity births, respectively 2936 (66.3%) and 1495 (33.7%). Detection of nutrients in the serum of 2: 3755 cases of pregnant women, serum total protein concentration was 60.53 + 5.80g/L, the lack rate is 36.7%; 3594 cases of pregnant women, serum calcium concentration was 2.11 + 0.31umol/L, the lack rate is 69.3%; 3616 cases of pregnant women, serum iron concentration was 11.73 + 6.45umol/L, the lack rate is 40.1%; 3590 cases of pregnant women, the serum zinc concentration was 8.74 + 1.89 umol/L, the lack rate is 60.4%. 3 the single factor analysis of the total protein concentration in serum: the total protein concentration in pregnant women's serum decreased with age, and the difference was statistically significant (P0.001). The serum total protein concentration of pregnant women living in rural areas was slightly higher than that in urban areas (60.80 + 5.80 g/L vs60.39 + 5.79 g/L), and there was a significant difference between groups (P0.05). The serum total protein concentration of pregnant women decreased with the increase of weight gain during pregnancy, and there was a significant difference between the groups (P0.05). With the increase of the number of pregnant weeks, the serum total protein concentration of pregnant women showed low between two high schools, and the difference was statistically significant (P0.001). 4 the effect of single factor analysis showed calcium concentration in serum showed that the effects of different age, occupation, residence, pre pregnancy BMI, weight gain during pregnancy, gestational age and parity on maternal serum calcium concentrations were not statistically significant (P0.05). 5 Effect of single factor analysis results showed that the serum iron concentration in parity were 1 group and above 2 groups, serum iron concentration of pregnant women were 10.19 + 1.64 and 10.72 + mol/L 1.59 mol/L, the difference was statistically significant (P=0.002). 6 the single factor analysis of the concentration of zinc in serum: the serum zinc concentration in pregnant women was significantly different between different occupations and different places of residence, and the difference was statistically significant (P0.05). The maternal serum zinc concentration is more than 2 higher than the parity parity of 1 pregnant women, there was significant difference between the groups (P0.05). Among 74431 pregnant women, the prevalence of gestational diabetes was 8.4%, the prevalence of pregnancy induced hypertension was 6.1%, the prevalence of anemia in pregnancy was 47.4%, and the incidence of pregnancy with hypothyroidism was 5.4%. 8 factors related to gestational diabetes mellitus: single factor results showed that the prevalence of GD was different among different age, residence, pre pregnancy BMI, gestational weight gain, gestational age, serum calcium and serum iron concentration, and the difference between groups was statistically significant (P0.05). Multivariate logistic regression results, excluding other confounding factors, influencing factors of age, place of residence, pre pregnancy BMI, weight gain during pregnancy, gestational age and serum iron concentration is GD (P0.05), the age and BMI before pregnancy is a risk factor for GD, every increase of pregnant women before pregnancy BMI a grade, the risk for GD an increase of 2.012 times. Analysis of related factors of 9 pregnancy induced hypertension: the results of univariate analysis showed that in different age, occupation, residence, BMI, pre pregnancy weight gain during pregnancy, gestational weeks, serum total protein and serum zinc concentration among pregnant women, the prevalence rate of hypertension was different, there was significant difference between the groups (P0.05). In the exclusion of other confounding factors, age and serum zinc concentration had no significant influence on pregnant women with hypertension, and the effect of Different Parities see statistical difference (P0.05). Compared with the unemployed group, maternal business and technical group, individual freedom and occupation groups and other occupation group with no industry group decreased risk of GH1 (OR1), and the science and education group and non industry group maternal morbidity rate of GH1 had no significant difference (P0.05). The risk of high blood pressure in pregnant women increased by 2.338 times and 1.442 times, respectively, at the level of BMI and weight gain during pregnancy. The concentration of serum total protein in pregnant women is a protective factor for GH1 disease, that is, the higher the total protein concentration in the serum of pregnant women, the lower the possibility of high blood pressure (OR=0.442). 10, the related factors of anemia in pregnancy: single factor results showed that the prevalence of GA was different in different age, occupation, residence, pre pregnancy BMI, gestational weight gain, serum calcium, serum iron and serum zinc concentration, and the difference between groups was statistically significant (P0.05). By multivariate logistic regression analysis, place of residence, BMI before pregnancy, pregnancy weight gain, serum calcium, serum iron and serum zinc concentration is maternal factors of GA (P0.05), weight gain during pregnancy is a risk factor for GA (OR1), every increase in weight gain during pregnancy of a grade, the risk of GA is increased 1.108 times 95%CI, 1.005~1.
【學(xué)位授予單位】：河北醫(yī)科大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：R714.25

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 郝敏;藺莉;;820例妊娠期糖尿病孕婦的高危因素分析[J];中國婦產(chǎn)科臨床雜志;2015年05期

2 趙海英;劉文慧;張惠欣;;妊娠期糖尿病危險(xiǎn)因素及診療新進(jìn)展[J];中國婦幼保健;2015年26期

3 徐海耿;毛亞飛;顧雷君;花曉艷;黃芳;;孕前BMI及孕期BMI增加對妊娠并發(fā)癥及新生兒出生體重的影響[J];中國現(xiàn)代醫(yī)生;2014年10期

4 何佳南;王玉;;營養(yǎng)元素均衡攝取對孕婦妊娠期營養(yǎng)狀況及生理指標(biāo)的影響研究[J];廣東微量元素科學(xué);2014年02期

5 易小英;程琪梅;;妊高癥相關(guān)危險(xiǎn)因素分析及綜合護(hù)理對妊高癥孕婦的影響[J];河北醫(yī)藥;2013年24期

6 何雁紅;;孕晚期低蛋白血癥的原因及其對妊娠結(jié)局的影響[J];海南醫(yī)學(xué);2013年06期

7 邢改平;;淺析產(chǎn)后大出血120例臨床分析[J];中國醫(yī)藥指南;2013年05期

8 夏芳蓮;蘇宜香;;孕前體質(zhì)指數(shù)對妊娠并發(fā)癥和妊娠結(jié)局的影響[J];中國婦幼保健;2012年27期

9 羅金鳳;李華鳳;;妊娠期高血壓疾病婦女心血管系統(tǒng)病理生理的研究進(jìn)展[J];中華婦幼臨床醫(yī)學(xué)雜志(電子版);2012年03期

10 余燕;侯曉鐘;;妊娠合并甲減30例的臨床護(hù)理[J];中國醫(yī)藥指南;2012年14期

相關(guān)碩士學(xué)位論文 前2條

1 張雪梅;妊娠期糖尿病控制水平對新生兒免疫功能影響的研究[D];大連醫(yī)科大學(xué);2012年

2 葉冬仙;湖南省孕產(chǎn)婦分娩方式影響因素的研究[D];中南大學(xué);2011年

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