Prolylcarboxypeptidase Is a Risk Factor for Cardiovascular Events

Abstract BACKGROUND: Prolylcarboxypeptidase (PRCP) is a membrane-associated serine protease that regulates biologic peptides bradykinin, angiotensin II, α-melanocyte stimulating hormone, and activates prekallikein. PRCP and its variants have been associated with metabolic syndrome in males, hypertension in preeclampsia, resistance to ACE inhibitors, and embryonic angiogenesis. Recent studies on PRCPgt/gt mice that have 25% normal PRCP levels show that these animals are hypertensive, have higher risk for arterial thrombosis, increased vascular inflammation, and reduced angiogenic repair after ischemia and injury (Blood 117:3929, 2011; Blood 122:1522, 2013). The hypothesis of this investigation is that polymorphisms in PRCP are associated with cardiovascular disease (CVD). METHODS: DNA from 2,243 subjects from the PEACE Trial (NEJM 351:2058, 2004) were genotyped at 2 PRCP SNPs (rs7104980, rs2298668) and 3 KLKB1 (prekallikrein) SNPs (rs4253252, rs3733402, rs3087505). These subjects were 82% female and had a history of (in decreasing frequency) angina (71%), angiographic coronary disease (66%), heart attack (58%), PTCA (44%), hypertension (42%), CABG (36%), diabetes (15%), stroke (4%), and TIA (3%). The association between single SNP alleles and different cardiovascular related phenotypes was assessed using logistic regression models. These models were adjusted for age, weight, gender, history of hypertension, and history of diabetes. RESULTS: When the logistic regression model was adjusted for age, weight, and gender, SNP rs710980 in PRCP had a 21% increased odds [odds ratio=1.211; 95% CI=(1.008, 1.454)] of having a history of PTCA if carrying the G allele (frequency of 66%) as compared to not having the G allele (frequency 34%). Additionally, adjusting the logistic regression model for history of hypertension and diabetes did not alter the odds ratio for PTCA history. However when the logistic regression model included history of hypertension and diabetes, the odds of having a history of a MI if carrying the same allele also is increased by 21% [odds ratio=1.21; 95% CI=(1.001, 1.455)]. In summary, the rs710980 intronic PRCP SNP conferred risk for CVD, while the PRCP exonic SNP rs2298668 showed no relationship in this population. Alternatively, the exonic KLKB1 SNP rs3733402 of Apple Domain 2 where high molecular weight kininogen binds conferred reduced odds of 24% [odds ratio=0.76; 95% CI=(0.622, 0.928)] of having a history of angiographic coronary disease if carrying the G allele (frequency 67%) as compared to not having the G allele (frequency of 33%). The other two KLKB1 SNPs showed no associations. DISCUSSION: These combined data on PRCP suggest that it is a risk factor for CVD. The present genetic data are consistent with biochemical, cell culture, and in vivo investigations showing that PRCP levels influence vascular biology, renal function, and metabolism. The extent of the genetic associations of PRCP polymorphisms with CVD may be resultant of the database interrogated. The PEACE trial consisted of individuals not severely ill with CVD. Its hypothesis to show that administration of ACE inhibitors leads to increased protection from mild CVD was not met. However, the present investigation showing several positive odds ratios with a certain PRCP SNP for CVD suggests that PRCP is a stronger risk factor for CVD than can be demonstrated in the PEACE subject population. PRCP should be interrogated in additional populations of subjects with CVD. Funding Support: NIH HL052779-17, HL112666-2 Disclosures No relevant conflicts of interest to declare.

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Prediction of Hospital Mortality Rates by Admission Laboratory Tests

Clinical Chemistry ◽

10.1373/clinchem.2005.059030 ◽

2006 ◽

Vol 52 (2) ◽

pp. 325-328 ◽

Cited By ~ 53

Author(s):

Paul Froom ◽

Zvi Shimoni

Keyword(s):

Internal Medicine ◽

Logistic Regression ◽

Confidence Interval ◽

Regression Model ◽

Odds Ratio ◽

Laboratory Tests ◽

Logistic Regression Model ◽

Complete Blood Count ◽

Laboratory Data ◽

Regional Hospital

Abstract Background: The aim of this study was to explore whether electronically retrieved laboratory data can predict mortality in internal medicine departments in a regional hospital. Methods: All 10 308 patients hospitalized in internal medicine departments over a 1-year period were included in the cohort. Nearly all patients had a complete blood count and basic clinical chemistries on admission. We used logistic regression analysis to predict the 573 deaths (5.6%), including all variables that added significantly to the model. Results: Eight laboratory variables and age significantly and independently contributed to a logistic regression model (area under the ROC curve, 88.7%). The odds ratio for the final model per quartile of risk was 6.44 (95% confidence interval, 5.42–7.64), whereas for age alone, the odds ratio per quartile was 2.01 (95% confidence interval, 1.84–2.19). Conclusions: A logistic regression model including only age and electronically retrieved laboratory data highly predicted mortality in internal medicine departments in a regional hospital, suggesting that age and routine admission laboratory tests might be used to ensure a fair comparison when using mortality monitoring for hospital quality control.

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Developing a Multi-variate Logistic Regression Model to Analyze Accident Scenarios: Case of Electrical Contractors

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17134852 ◽

2020 ◽

Vol 17 (13) ◽

pp. 4852

Author(s):

Pouya Gholizadeh ◽

Behzad Esmaeili

Keyword(s):

Logistic Regression ◽

Regression Model ◽

Odds Ratio ◽

Logistic Regression Model ◽

The Body ◽

Occupational Accidents ◽

Multivariate Logistic Regression Model ◽

Ratio Analysis ◽

Accident Scenarios ◽

Significant Factors

The ability to identify factors that influence serious injuries and fatalities would help construction firms triage hazardous situations and direct their resources towards more effective interventions. Therefore, this study used odds ratio analysis and logistic regression modeling on historical accident data to investigate the contributing factors impacting occupational accidents among small electrical contracting enterprises. After conducting a thorough content analysis to ensure the reliability of reports, the authors adopted a purposeful variable selection approach to determine the most significant factors that can explain the fatality rates in different scenarios. Thereafter, this study performed an odds ratio analysis among significant factors to determine which factors increase the likelihood of fatality. For example, it was found that having a fatal accident is 4.4 times more likely when the source is a “vehicle” than when it is a “tool, instrument, or equipment”. After validating the consistency of the model, 105 accident scenarios were developed and assessed using the model. The findings revealed which severe accident scenarios happen commonly to people in this trade, with nine scenarios having fatality rates of 50% or more. The highest fatality rates occurred in “fencing, installing lights, signs, etc.” tasks in “alteration and rehabilitation” projects where the source of injury was “parts and materials”. The proposed analysis/modeling approach can be applied among all specialty contracting companies to identify and prioritize more hazardous situations within specific trades. The proposed model-development process also contributes to the body of knowledge around accident analysis by providing a framework for analyzing accident reports through a multivariate logistic regression model.

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Dietary Salt-Related Knowledge, Attitude, Behaviors, and Hypertension in a Rural Northern Thailand Population

Current Developments in Nutrition ◽

10.1093/cdn/nzaa053_075 ◽

2020 ◽

Vol 4 (Supplement_2) ◽

pp. 870-870

Author(s):

Celina Morales ◽

Pimbucha Rusmevichientong

Keyword(s):

Blood Pressure ◽

Logistic Regression ◽

Family History ◽

Regression Model ◽

Logistic Regression Model ◽

Salt Intake ◽

Dietary Salt ◽

Chiang Mai ◽

Attitudes And Behaviors ◽

History Of

Abstract Objectives The objectives of this study were to examine the dietary salt-related knowledge, attitudes, and behaviors associated with the prevalence of hypertension among adults residing in rural Northern Thailand. Methods A cross-sectional study utilizing convenience sampling was administered in San Pa Tong District, Chiang Mai, Thailand. The one-on-one interview was conducted to assess subject's knowledge, attitudes, and behaviors relating to their dietary salt intake. Various food frequencies for foods high in salt were also measured. Each subject's blood pressure was measured twice before and after the interview. A logistic regression model was used in the analysis to determine potential hypertension risk factors. Results A total of 403 adults participated in the study. A majority of participants were female (73.2%), and the average age was 62.5 years old. Half of participants reported a family history of hypertension and 32% of participants were hypertensive. The major results from the logistic regression model indicated positive attitudes towards decreasing salt intake lead to a lower chance of becoming hypertensive (OR = 0.934). However, a family history of high blood pressure (OR = 1.417), a higher knowledge score about foods high in salt (OR = 1.254), daily use of Monosodium Glutamate (MSG) in food preparation (OR = 1.959) and buying outside food to eat at home (OR = 5.692) lead to a higher chance of becoming hypertensive. Conclusions Our findings suggest higher knowledge does not decrease the chance of becoming hypertensive. However, there is a positive association between hypertension and dietary salt-related behaviors among adults living in rural Thai communities. More specifically, salt-reduction interventions should focus on promoting home-cooked meal preparation with lower salt substitutes to MSG. Funding Sources NIMHD Minority Health and Health Disparities Research Training Program (MHRT), California State University, Fullerton (Department of Public Health) and Chiang Mai University (Department of Community Medicine).

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Validation Study of Logistic Regression in Classifying Primary Vitreoretinal Lymphoma Vs. Uveitis By IL-6 and IL-10 Levels

Blood ◽

10.1182/blood-2018-99-114199 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 2971-2971

Author(s):

David Kuo ◽

Maggie Wei ◽

Jared Knickelbein ◽

Karen Armbrust ◽

Ian Yeung ◽

...

Keyword(s):

Logistic Regression ◽

Regression Model ◽

Logistic Regression Model ◽

Conflicts Of Interest ◽

Training Data ◽

Youden Index ◽

Primary Vitreoretinal Lymphoma ◽

Cytokine Analysis ◽

Vitreoretinal Lymphoma ◽

Sensitivity Specificity

Abstract Background/Aim: The aim of this study was to assess the utility of intraocular IL-10 and IL-6 analysis by logistic regression in classifying primary vitreoretinal lymphoma (PVRL) vs. uveitis using a logistic regression model trained on a single-center retrospective cohort as well as the previously published ISOLD score compared against the IL-10/IL-6 ratio. Methods: Patient diagnoses of PVRL vs. uveitis and associated aqueous and/or vitreous IL-6 and IL-10 levels were retrospectively collected. From this data, cytokine levels were compared between diagnoses with the Mann-Whitney U test and a logistic regression model was developed to classify PVRL vs. uveitis from aqueous and vitreous IL-6 and IL-10 by nested cross-validation. ROC curves were plotted and AUCs were calculated for the IL-10/IL-6 ratio, ISOLD score, and our logistic regression model. Optimal cut-offs for each classifier were determined by the maximal Youden index; and sensitivity, specificity, PPV, and NPV were determined for each cut-off. Results: 79 lymphoma (10 aqueous, 69 vitreous) and 84 uveitis patients (19 aqueous, 65 vitreous) between 10/5/1999 and 9/16/2015 were included in the study. IL-6 was higher in uveitis vs. lymphoma patients while IL-10 was higher in lymphoma vs. uveitis patients (p <0.01 for all comparisons). For vitreous samples, our logistic regression model achieved an AUC of 98.3%, while ISOLD achieved an AUC of 97.8%, and the IL-10/IL-6 ratio achieved an AUC of 96.3%. The optimal cut-offs for our logistic regression model, ISOLD, and the IL-10/IL-6 ratio achieved sensitivity/specificity of 92.7%/100%, 94.2%/96.9%, 94.2%/95.3% respectively, corresponding to PPV/NPV of 100%/92.9%, 97%/94%, and 95.6%/93.9% respectively. For aqueous samples, all three classifiers achieved 100% AUC with 100% sensitivity/specificity. Odds ratios of PVRL vs. uveitis were 0.981 (aqueous) and 0.992 (vitreous) for IL-6 and 1.030 (aqueous) and 1.060 (vitreous) for IL-10 according to our logistic regression model. Conclusion: In this study, logistic regression, as demonstrated by our model and the ISOLD score, showed strong classification performance and generalizability with high sensitivity and specificity. These results, in addition to logistic regression's ability to further improve with more training data suggest a promising step forward in intraocular cytokine analysis for the early diagnosis of primary vitreoretinal lymphoma. Additional validation studies, especially with cohorts that have proven challenging for the IL-10/IL-6 ratio, would further elucidate the strengths and weakness of this approach. Disclosures No relevant conflicts of interest to declare.

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Association of maternal obesity with fetal and neonatal death: Evidence from South and South-East Asian countries

PLoS ONE ◽

10.1371/journal.pone.0256725 ◽

2021 ◽

Vol 16 (9) ◽

pp. e0256725

Author(s):

Rezwanul Haque ◽

Syed Afroz Keramat ◽

Syed Mahbubur Rahman ◽

Maimun Ur Rashid Mustafa ◽

Khorshed Alam

Keyword(s):

Logistic Regression ◽

Risk Factor ◽

Regression Model ◽

Neonatal Death ◽

Logistic Regression Model ◽

Maternal Obesity ◽

East Asian ◽

Multilevel Logistic Regression ◽

Asian Countries ◽

Neonatal Deaths

Background Obesity prevalence is increasing in many countries in the world, including Asia. Maternal obesity is highly associated with fetal and neonatal deaths. This study investigated whether maternal obesity is a risk factor of fetal death (measured in terms of miscarriage and stillbirth) and neonatal mortality in South and South-East Asian countries. Methods This cross-sectional study pooled the most recent Demographic and Health Surveys (DHS) from eight South and South-East Asian countries (2014–2018). Multivariate logistic regression was deployed to check the relationships between maternal obesity with fetal and neonatal deaths. Finally, multilevel logistic regression model was employed since the DHS data has a hierarchical structure. Results The pooled logistic regression model illustrated that maternal obesity is associated with higher odds of miscarriage (adjusted odds ratio [aOR]: 1.26, 95% CI: 1.20–1.33) and stillbirths (aOR: 1.46, 95% CI: 1.27–1.67) after adjustment of confounders. Children of obese mothers were at 1.18 (aOR: 1.18, 95% CI: 1.08–1.28) times greater risk of dying during the early neonatal period than mothers with a healthy weight. However, whether maternal obesity is statistically a significant risk factor for the offspring’s late neonatal deaths was not confirmed. The significant association between maternal obesity with miscarriage, stillbirth and early neonatal mortality was further confirmed by multilevel logistic regression results. Conclusion Maternal obesity in South and South-East Asian countries is associated with a greater risk of fetal and early neonatal deaths. This finding has substantial public health implications. Strategies to prevent and reduce obesity should be developed before planning pregnancy to reduce the fetal and neonatal death burden. Obese women need to deliver at the institutional facility centre that can offer obstetrics and early neonatal care.

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Association between Attention Deficit Hyperactivity Disorder and Suicide Attempts in Patients with Bipolar Disorder

Iranian Journal of Psychiatry ◽

10.18502/ijps.v14i3.1341 ◽

2019 ◽

Author(s):

Jafar Fili ◽

Marzieh Nojomi ◽

Katayoon Razjouyan ◽

Mojgan Kahdemi ◽

Rozita Davari- Ashtiani

Keyword(s):

Bipolar Disorder ◽

Logistic Regression ◽

Regression Model ◽

Logistic Regression Model ◽

Suicide Attempts ◽

P Value ◽

Hyperactivity Disorder ◽

Significant Difference ◽

Chi Squared ◽

History Of

Objective: The present study aimed to examine the association between ADHD and suicide attempts among adolescents with bipolar disorder. Method: Participants were 168 adolescents who fulfilled DSM-IV-TR criteria for bipolar disorder. They were divided into 2 groups: The first group of patients with bipolar disorder with a history of suicide attempts (n = 84) and the second group without a history of suicide attempts (n = 84). ADHD and other variables were analyzed using a chi-squared test and logistic regression model. Results: No significant difference was observed between the 2 groups in comorbidity of ADHD and other psychiatric disorders (P value > 0/05). In the logistic regression model, and after controlling for other factors, gender (OR = 3.9, CI 95%: 1.5-9.6) and history of sexual abuse (OR = 3.4; CI 95%: 1.06-11.3) were the only 2 factors associated with a history of suicide attempts. Conclusion: No significant association was found between ADHD and suicide attempts in adolescents with bipolar disorder.

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MO532WHICH UNHEALTHY LIFE-BEHAVIOR IS THE MOST IMPACT FOR THE PRESENCE OF PROTEINURIA?

Nephrology Dialysis Transplantation ◽

10.1093/ndt/gfab087.0052 ◽

2021 ◽

Vol 36 (Supplement_1) ◽

Author(s):

Jun Muratsu ◽

Masahiko Hara ◽

Atsuyuki Morishima ◽

Katsuhiko Sakaguchi ◽

Takashi Fujimoto

Keyword(s):

Logistic Regression ◽

Regression Model ◽

Odds Ratio ◽

Logistic Regression Model ◽

Multivariable Logistic Regression Model ◽

Current Smoking ◽

Exercise Habits ◽

Multivariable Logistic Regression ◽

Skipping Breakfast ◽

Life Behavior

Abstract Background and Aims Unhealthy life-behaviors such as dietary habits, lack of exercise, drinking large amount of alcohol and smoking cause obesity, hypertension, diabetes, dyslipidemia, cardiovascular disease (CVD). These are also closely associated with chronic kidney disease (CKD). CKD is characterized by proteinuria and low glomerular filtration rate (GFR). Independent of GFR, proteinuria is an important predictor of ESKD. Few studies have assessed which is the most clinical impact among the unhealthy life-behaviors: skipping breakfast, snacking, late-night dinner, smoking, heavy alcohol intake and lack of exercise habits for proteinuria in normal renal function patients. Method This cross-sectional study included 29,780 normal renal function patients: eGFR≥60 mL/min/1.73 m2 and no history of kidney diseases who underwent health checkup at the Physical Checkup Center of Sumitomo Hospital. The endpoint of this investigation is defined as dipstick proteinuria of≥ 1+. To assess the association of life-behaviors and the presence of proteinuria, their odds ratios were calculated in adjusted univariable and multivariable logistic regression model. Multivariable logistic regression model was performed by not selected items, the same with univariable model. We would like to investigate the most impact unhealthy life-behavior for the proteinuria. Results Among 29,780 total study subjects (male: 60.3%; mean age: 49±11 years), 1,118 (3.75%) subjects were shown as urinary protein above 1+. The presence of unhealthy dietary life-behaviors: skipping breakfast, snacking and late-night dinner was 5,293 (17.3%), 3,899 (13.1%) and 11,231 (37.7%), respectively. About sleeping duration, the population of <6 hours, 6-8 hours and >8 hours were 12,027 (40.4%), 17,236 (57.9%) and 517 (1.7%). The population of exercise habits: over 3 days/weeks, 1-2 days/weeks and none were 5,138 (17.3%), 9,375 (31.5%) and 15,237 (51.3%), suggesting half of them did not have exercise habits. About smoking habits, the population of current smoking, past smoking and never smoking were shown 6,445 (21.6%), 8,459 (28.4%) and 14,876 (50.0%). In addition, about alcohol amount per day, the population of over 60g, 40-60g, 20-40g and 0-20g were 1,840 (6.18%), 4,504 (15.1%), 6,727 (22.6%) and 16,709 (56.1%). To investigate the impact of life-behavior for proteinuria, we obtained odds ratio of adjusted multivariable logistic regression model. In multivariable regression, among the life-behavior: skipping breakfast, current smoking, alcohol amount (ethanol over 60 g/day), none of exercise habits and snacking were strongly associated with the prevalence of proteinuria (skipping breakfast, adjusted odds ratio 1.45 [1.26, 1.68]; current smoking, 1.35 [1.14, 1.59]; alcohol amount (ethanol over 60 g/day), 1.35 [1.08, 1.69]; none of exercise habits, 1.29 [1.07, 1.57]; snacking, 1.23 [1.04, 1.46]). In addition, among the history of medical history, diabetes mellitus, hypertension and dyslipidemia were significantly associated with the prevalence of proteinuria (diabetes mellitus, adjusted odds ratio 2.39 [1.93, 2.96]; hypertension, 1.83 [1.53, 2.17]; 1.22 [1.03, 1.45]). Conclusion Among the unhealthy life-behaviors, skipping breakfast is the most impact factor for the presence of proteinuria.

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Palifermin In High Dose Chemotherapy and Autologous Stem Cell Transplantation: Reduction of Infections and of Resources Utilization with No Increase in Overall Cost

Blood ◽

10.1182/blood.v118.21.4568.4568 ◽

2011 ◽

Vol 118 (21) ◽

pp. 4568-4568

Author(s):

Giuseppe Milone ◽

Massimo Poidomani ◽

Salvatore Leotta ◽

Valeria Pinto ◽

Andrea Spadaro ◽

...

Keyword(s):

Logistic Regression ◽

Stem Cell ◽

Regression Model ◽

Odds Ratio ◽

Logistic Regression Model ◽

High Dose Chemotherapy ◽

High Dose ◽

Multiple Logistic Regression ◽

Conditioning Therapy ◽

Severe Mucositis

Abstract Abstract 4568 Forty patients affected by various haematological malignancies who underwent high dose chemotherapy and autologous stem cell transplant (ASCT) were treated with Palifermin, this group was compared to 80 control subjects not assuming this drug. Controls were selected on the basis of being matched for length of neutropenia after ASCT and for Diagnosis. Primary end point was occurrence of “infections not CVC-related” (FUO/pneumonia/gram-negative bacteremia) and secondary end point was the “severe oral mucositis”. Patients and controls resulted to be comparable for many pre-transplant and transplant features. Patients treated with Palifermin displayed a lower rate of “infections not CVC-related” when compared to controls (25% versus 50%, P=0.01) and the protective effect of Palifermin on this outcome remained significant also in a multiple logistic regression model [odds ratio: 0.34, 95% CI: 0.12–0.92, P=0.03] adjusting for a series of potential confounders. The odds ratio of severe mucositis was 30% lower in Palifermin treated patients than in controls (odds ratio: 0.70, 95% CI: 0.33–1.51) but this difference did not attain the statistical significance (P=NS). A stratified analysis by conditioning therapy showed that in patients who received Palifermin after BEAM/BU-CY conditioning, the proportion of patients experiencing severe mucositis was significantly lower than that observed in controls (14% versus 56%, P=0.008) while no such difference was found in those who underwent HD-PAM conditioning (65% versus 56%, P=NS). This result indicates that the conditioning therapy modifies the effect of Palifermin on severe mucositis, a finding fully confirmed in a multiple logistic regression model (P for the effect modification=0.018). Palifermin treated patients had also lower severe gastrointestinal toxicity (12% versus 65%, P<0.001), lower morphine utilization (12% versus 40%, P<0.001), lower total parental nutrition (10% versus 71%, P<0.001) and lower PLT and RBC transfusions (P=0.04) when compared to controls. Average economical costs related to the sum of some resources (inpatient stay, TPN, systemic antifungal treatment and blood products transfusions) were lower in Palifermin treated patients than in controls (11.985 EUROs versus 15.717 EUROs, P=0.002) so that the economical saving in Palifermin treated patients (about 3.700 EUROs) fully compensated for the cost of this drug. Remarkably, in patients treated by “BEAM/BU-CY” conditioning therapy and receiving Palifermin, the overall costs (sum of the above mentioned resources and including also cost of the study drug) was lower in Palifermin treated group in respect to group of patients not treated. In fact, in BEAM/BU-CY stratum overall cost in group treated by Palifermin was 15990±2789 EUROs versus 19276±10946 EUROs in group treated by the same conditioning but not receiving Palifermin (P=0.11). In conclusion this controlled study shows that Palifermin, after ASCT using conditioning not containing TBI, significantly reduces rate of “infections not related to CVC” and ameliorates several indicators of resource consumption, without economical overburden. Disclosures: No relevant conflicts of interest to declare.

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0970 Longitudinal Study Of Infant Sleep Problems And Influencing Factors

SLEEP ◽

10.1093/sleep/zsaa056.966 ◽

2020 ◽

Vol 43 (Supplement_1) ◽

pp. A368-A368

Author(s):

Z Zhou ◽

N Wang

Keyword(s):

Logistic Regression ◽

Risk Factor ◽

Protective Factors ◽

Regression Model ◽

Body Length ◽

Logistic Regression Model ◽

Sleep Problems ◽

Infant Sleep ◽

Falling Asleep ◽

Bedtime Routine

Abstract Introduction To investigate the sleep problems and influence factors in infants at the age of 1 month and 6 months through longitudinal questionnaire survey. Methods 600 healthy infants aged 1 month were selected from May to August 2014 from Chongqing health center for women and children. A self-made sleep questionnaire was used to investigate the infants’s sleep at the age of 1 month and 6 months respectively. Logistic regression model was used to analyze the correlation between sleep problems and factors. Results The incidence of nigt-waking, difficulty in falling asleep and night crying at 1 month of age were 30%, 17% and 14.1%, respectively, and at 6 months were 7.3%, 9.3% and 13.1%, respectively. Results of the Logistic regression analysis model of sleep problems of infants at 1 month old were: 1. body length grade, baby touch, sleep alone, putting the infants back into bed after being picked up and quiet, night feeding were the protective factors of night-waking, while diaper changing is the risk factor; 2.body length grade, listening to music, orderly bedtime routine, comforting without holding and putting the infants back into bed after being picked up and quiet were protective factors for difficulty in falling asleep, while diaper changing is the risk factor; 3. listening to music, orderly bedtime routine, watching and waiting, holding until sleep were all protective factors of night-crying. Logistic regression model analysis results of sleep problems of infants aged 6 months were: 1. The risk factors of night-waking include putting the infants back into bed after being picked up and quiet, holding the infants until falling asleep, diapers changing, and parent-children interaction before bedtime. 2. Listening to music and sleeping alone in a bed were protective factors for difficulty in falling asleep. 3. Touching, orderly bedtime routine and comforting without holding are protective factors of night-crying. Conclusion Sleep problems in infants are common and decrease with age. The factors of sleep problems at the age of 1 and 6 months are different, Targeted prevention are beneficial to the prevention of infant sleep problems. Support Chinese center for disease control and prevention grant

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Association of dyslipidaemia with osteoporosis in postmenopausal women

Journal of International Medical Research ◽

10.1177/0300060521999555 ◽

2021 ◽

Vol 49 (3) ◽

pp. 030006052199955

Author(s):

Lingnan Zhang ◽

Qilong Liu ◽

Xianshang Zeng ◽

Wenshan Gao ◽

Yanan Niu ◽

...

Keyword(s):

Logistic Regression ◽

Confidence Interval ◽

Regression Model ◽

Postmenopausal Women ◽

Odds Ratio ◽

Logistic Regression Model ◽

Density Lipoprotein ◽

Binary Logistic Regression ◽

Control Group ◽

Binary Logistic Regression Model

Objective To assess the association of dyslipidaemia with osteoporosis in postmenopausal women. Methods Data from 160 postmenopausal women with newly diagnosed osteoporosis (osteoporosis group) and 156 healthy controls (control group) were retrospectively reviewed from 2016 to 2020. The primary outcomes were laboratory values assessed by a multivariate binary logistic regression model. Results Factors that greatly increased the risk of being in the osteoporosis group included high low-density lipoprotein (LDL) and low high-density lipoprotein (HDL) levels. The osteoporosis group had lower HDL and higher LDL levels than the control group. A multivariate binary logistic regression model showed that lower HDL and higher LDL levels were the only variables that were significantly associated with osteoporosis (odds ratio 1.86, 95% confidence interval: 3.66–4.25 and odds ratio 1.47, 95% confidence interval: 1.25–2.74, respectively). Conclusion Low HDL and high LDL levels may be associated with the occurrence of osteoporosis in postmenopausal women.

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