ライフサイエンスコーパス: marital

1 tment; and partner-reported satisfaction and marital adjustment at 28 to 30 weeks and 1 year, predict

2 al Adjustment Questionnaire and to the Locke Marital Adjustment Test before radiotherapy, between wee

3 gnificant effect on sexual satisfaction, and marital adjustment was not significantly improved in par

4 f life, body image, depressive symptoms, and marital adjustment were assessed by use of validated que

5 r; overall sexual function and satisfaction; marital adjustment; and partner-reported satisfaction an

6 Potential confounders (age, sex, income, and marital and immigrant status) and mediators (substance a

7 r after adjustment for maternal age, height, marital and smoking status, and interpregnancy interval.

8 oad, body mass index, education, season, and marital and socioeconomic status, not breastfeeding was

9 A growing share of such non-marital births identify the father, which can create a l

10 (P < 0.001), anxiety disorders (P < 0.001), marital break-up (P = 0.015), and physician visits for m

11 es, were slightly less likely to result in a marital break-up (separation or divorce) and were associ

12 tional off-line venues, but the findings for marital break-up and marital satisfaction remained signi

13 isorders (ARR, 1.41; 95% CI, 1.24-1.60), and marital breakup (ARR, 1.18; 95% CI, 1.13-1.23) in the 2

14 eptibility; and genetic tests as a factor in marital choice.

15 r own and their wife's functioning and their marital communication.

16 IL-1beta) was lower at wound sites following marital conflicts than after social support interactions

17 increased treatment-seeking for depression, marital counseling, or other emotional or psychological

18 uring the second admission, they discussed a marital disagreement.

19 Concern about the negative impact of marital discord and divorce will continue to provide the

20 pidemiological literature has suggested that marital discord is a risk factor for morbidity and morta

21 Marital discord is costly to children, families, and com

22 C experience considerable mental illness and marital disruption.

23 Adverse sentimental relationships that cause marital dissolution may involve a genetic component comp

24 , recent work loss (55.0% versus 35.6%), and marital distress (28.6% versus 13.0%).

25 In children, marital distress, conflict, and disruption are associate

26 interventions for preventing or ameliorating marital distress.

27 e timing, divorce and widow transitions, and marital durations on mortality.

28 t, which was especially important within the marital dyad.

29 at sex differences are related to a nexus of marital experiences and associated health risks.

30 tcomes) and body image, menopausal symptoms, marital functioning, psychological distress, and health-

31 ntercourse frequency, relationship intimacy, marital functioning, psychological distress, or health-r

32 h infection, and only at the STI clinic were marital, genital ulcer disease, and HIV-infection status

33 Variations in the marital histories of parents and children also contribut

34 a range of environmental factors reflecting marital instability, as well as psychopathology and crim

35 ia and Rwanda occurred within serodiscordant marital or cohabiting relationships, depending on the se

36 n certain quality-of-life domains, including marital (P = .002) and sexual functioning (P = .017), as

37 ted with exceptional survival, and lack of a marital partner was associated with mortality before age

38 e if sex and the interaction between sex and marital/partner status were independent prognostic varia

39 variate analyses restricted to men were age, marital/partner status, and income.

40 In response to marital pressures, participant had to reconcile same-sex

41 of major depression), and 5) the last year (marital problems, difficulties, and stressful life event

42 ors, the psychotherapeutic alliance, and the marital relationship.

43 r to determine the dynamic behavior of their marital relationships.

44 ce) and were associated with slightly higher marital satisfaction among those respondents who remaine

45 when they met their husbands and then their marital satisfaction and HC use every 4 mo for up to thr

46 In study 1, wives reported their marital satisfaction every 6 mo for 4 y and then reporte

47 They then reported their marital satisfaction every 6 months for the next 4 years

48 s were less likely to experience declines in marital satisfaction over time.

49 s, but the findings for marital break-up and marital satisfaction remained significant after statisti

50 Decreased marital satisfaction, disturbances in family dynamics, a

51 of osteoporosis, hypothyroidism, employment, marital satisfaction, divorce, or psychological health.

52 fe, feeling sexually attractive, body image, marital satisfaction, quality of life, medical history,

53 r conscious ones, predicted changes in their marital satisfaction, such that spouses with more positi

54 h, neuroticism, divorce, social support, and marital satisfaction.

55 demonstrated no consistent associations with marital satisfaction.

56 4; 95% confidence interval [CI], 1.17-2.31), marital separation (OR, 2.55; 95% CI, 1.06-6.14), pre-Se

57 efforts remain focused on abstinence and non-marital sex.

58 ssociated with HIV acquisition risk: gender, marital/sexual activity status, geographic location, "ke

59 sibs are expected to be sensitive to cues of marital stability, and these dispositions may be subject

60 e) personal control: alcohol abuse, smoking, marital stability, exercise, body mass index, coping mec

61 -year interval included male gender, lack of marital stability, presence of several of the criteria f

62 k ratio [RR] 1.52, 95% CI 1.48-1.56), single marital status (1.70, 1.66-1.75), age 30-39 years (1.58,

63 e, race, ethnicity, geographic location, and marital status (adjusted hazard ratio, 2.19; 95% CI, 1.8

64 HPV among women in the control arm included marital status (adjusted odds ratio [AOR], 3.2; 95% conf

65 anisms that lead from specific dimensions of marital status (and family structure more broadly) to mo

66 [aOR] 0.5 [95% CI, .3-.9] >/=28 vs 22-23]); marital status (aOR 2.3 [95% CI, 1.5-3.5] single vs marr

67 higher risk for periodontitis, regardless of marital status (odds ratio: 1.5, 95% CI: 1.05 to 2.04, P

68 rder (OR = 1.35), widowed/separated/divorced marital status (OR = 1.28), and arthritis (OR = 1.27) we

69 of receiving chemotherapy included unmarried marital status (OR, 0.59; p = 0.0002) and more comorbidi

70 ikelihood of receiving RT included unmarried marital status (OR, 0.64; p < 0.0001) and more comorbidi

71 ,000 dollars (OR = 5.6, 95% CI, 4.5 to 7.1), marital status (widowed/divorced/separated; OR = 1.3; 95

72 acteristics (age [P = .007], race [P = .05], marital status [P = .04]), personality (extroversion [P

73 were each associated with prevalent RP (for marital status adjusted odds ratio [OR] 2.3, 95% confide

74 d with race/ethnicity, education, income, or marital status after adjusting for age.

75 Medication use, education, and marital status also influenced who underwent biopsy.

76 poverty, low level of education, and single marital status among teenage mothers.

77 vaccination (before and after adjustment for marital status and age) was 0.9 (95% CI, 0.5-1.4; P =.55

78 In women, marital status and alcohol use were each associated with

79 f women of reproductive age defined by their marital status and contraceptive need and use, and the s

80 ationship, adjusted for age and sex, between marital status and dementia.

81 nt for family socioeconomic status, maternal marital status and education, children's nutrition, and

82 age at outcome assessment, prepregnancy BMI, marital status and insurance at delivery, race, smoking

83 ation ratio) and individual-level mediators (marital status and last dental visit).

84 Maternal IQ, education, and marital status and low birth weight predicted IQ at age

85 l measures oversimplify the relation between marital status and mortality and that sex differences ar

86 ibutions to research on the relation between marital status and mortality.

87 iety and depression, IQ, educational status, marital status and pending litigation.

88 investigated one of the SNPs for measures of marital status and quality.

89 analyses, many nonclinical factors, such as marital status and region of the country, had a greater

90 The association between marital status and risk for first registration for alcoh

91 dered personal and life circumstances (e.g., marital status and seniority) when discussing intention

92 Medical conditions as well as ethnic and marital status and smoking habits were considered.

93 We ascertained history of marital status and spouse's death by record linkage to t

94 alysis of studies of the association between marital status and the risk of developing dementia.

95 ing to personal characteristics such as age, marital status and urban or rural residence.

96 atus, tumor size, differentiation, race, and marital status are valuable for prognostication in breas

97 an differences in antisocial behavior across marital status at age 29 years were present even at 17 a

98 Marital status became the second most important factor a

99 Network score and marital status combined explained 27% (95% confidence in

100 evated child problem behaviors, and divorced marital status conveyed elevated risk for psychiatric di

101 Maternal age and marital status did not account for the birth weight tren

102 requently cited "red flag." Age, gender, and marital status did not affect how applicants rated facto

103 igh-income versus low-income, and racial and marital status disparities.

104 3) Marital status has a limited impact on periodontal healt

105 tion between periodontitis risk, gender, and marital status in older adults.

106 ctivity, alcohol consumption, education, and marital status in pooled data from 19 prospective studie

107 lyze the survival difference among different marital status in the United States.

108 er tumor size (OR, 0.37; 95% CI, 0.27-0.51), marital status of being separated at the time of diagnos

109 ers, 50% were single and 20.6% were married (marital status of the remainder was unknown).

110 The influence of marital status on racial/ethnic disparities was stronger

111 factors were not associated with RP in men (marital status OR 1.4, 95% CI 0.6-3.5; alcohol use OR 1.

112 For CD and ND in the EA population, marital status proved to be a significant moderator in t

113 fter adjusting for changes in disability and marital status since baseline (OR, 1.72; 95% CI, 0.99-2.

114 ces of neighborhood socioeconomic status and marital status suggest that social determinants, support

115 atements, white race, older age, and married marital status to be associated with higher adherence (a

116 e than a century of empirical evidence links marital status to mortality.

117 Marital status was found to be an independent prognostic

118 blings, and monozygotic twins discordant for marital status were as strong as that seen in the genera

119 Parent education and marital status were significantly associated with BA and

120 e, sex, race/ethnicity, education level, and marital status) and health factors (OA severity, knee sy

121 ctors (age, education, household income, and marital status) were included in the analysis.

122 ), sociodemographic characteristics (age and marital status), and treatment (surgery and radiation th

123 ce with adjustment for individual (age, sex, marital status), clinical (histologic grade, surgery, ir

124 demographics (age, sex, racial/ethnic group, marital status), comorbid conditions, and economic resou

125 istics (i.e., age, sex, race, education, and marital status), employment status at year of diagnosis,

126 y quintiles, highest level of education, and marital status).

127 , diabetes mellitus, years of education, and marital status).

128 tal health status, maternal IQ, and maternal marital status).

129 ustment for age, sex, education, income, and marital status, acculturation was negatively associated

130 ustment for sex, age, race, education level, marital status, age at first alcohol intoxication, and h

131 Results were similar after adjustment for marital status, age, and education.

132 fects meta-analysis, controlling for region, marital status, age, number of sex partners, and condom

133 to maternal variables (age, race, education, marital status, alcohol during pregnancy) or child varia

134 After adjustment for age, marital status, and antidepressant use, the relative ris

135 ation functional class, depression symptoms, marital status, and baseline beta-blockers, angiotensin-

136 Age, marital status, and comorbidities influenced the probabi

137 ter further adjustment for health behaviors, marital status, and education.

138 sted for height, weight, smoking, education, marital status, and energy intake.

139 erval: 0.09 to 0.72), adjusting for smoking, marital status, and gender.

140 tation correlated with sex, race, ethnicity, marital status, and geographic region (ethnicity, P = .0

141 lower mammography rates based on age, race, marital status, and geographic region.

142 husband's level of education, nested within marital status, and having pets in the home were related

143 r the correlated variables of family income, marital status, and health insurance type.

144 ng for child's age and sex, mother's age and marital status, and household size.

145 r adjusting for insurance, hospitalizations, marital status, and illness severity.

146 ent risk factors for HPV detection were age, marital status, and increasing numbers of lifetime and r

147 ic variables including sex, race, ethnicity, marital status, and insurance status are associated with

148 al surgery, higher disease stage, older age, marital status, and lower comorbidity.

149 ting for maternal education, race/ethnicity, marital status, and maternal age; separately examining h

150 tment for matching characteristics, smoking, marital status, and race/ethnicity using logistic regres

151 eg, sex, age, education, income, urbanicity, marital status, and regional differences) and mental, ne

152 ifferences in employment, social assistance, marital status, and reproduction were no longer signific

153 Baseline variables of age, sex, marital status, and risk did not modify vaccine efficacy

154 Age group, education, marital status, and sexual behavior were associated with

155 bling group, own socioeconomic position, own marital status, and socioeconomic rank within the siblin

156 ohol use, smoking history, age at menopause, marital status, and the use of hormone replacement thera

157 In men, marital status, and to a lesser extent network score (bu

158 emale sex in Alaska only, whereas education, marital status, and urban residency were associated with

159 ite race, Hispanic ethnicity, education, and marital status, as well as zip code population character

160 lus, crown coverage, age, income, education, marital status, body mass index, diabetes, and vitamin C

161 king and variables to control for education, marital status, body mass, alcohol consumption, occupati

162 Moreover, no association of marital status, body weight, body mass index, blood pres

163 s, by gender, with adjustment for age, race, marital status, branch of service, and type of unit.

164 roups were similar in age, gender ratio, and marital status, but those legally committed for involunt

165 functional independence measure score), age, marital status, chronic conditions, and prestroke ambula

166 ompletion of treatment, including age, race, marital status, comorbidities, and sociodemographic fact

167 d the association of gender, age, education, marital status, current physical activity, body weight,

168 moking, social class, long-standing illness, marital status, diabetes, hypertension)-adjusted hazard

169 weight, height, smoking history, education, marital status, diet, alcohol consumption, and occupatio

170 d with the use of radiation therapy included marital status, disease stage, and type of lymph node su

171 characteristics (age, sex, race, education, marital status, distance to nearest acute care hospital)

172 ion, 197 control), similar across groups for marital status, duration of HIV diagnosis, and distance

173 sociation between self-assessment scores and marital status, education level, performance status, or

174 on and adjusted for maternal race/ethnicity, marital status, education, age, and ozone.

175 ssion, adjusted for maternal race/ethnicity, marital status, education, age, smoking, maximum tempera

176 s are presented by age, sex, race/ethnicity, marital status, education, employment status, and income

177 ing variables of maternal age, parity, race, marital status, education, family income, smoking, alcoh

178 emographic features (age, gender, ethnicity, marital status, education, occupation, poverty, and heal

179 model: study site, maternal age, gravidity, marital status, education, race/ethnicity, smoking, and

180 ty, baseline weight (and their interaction), marital status, education, smoking, calorie intake, and

181 r controlling for age, time since diagnosis, marital status, education, tumor site and stage, comorbi

182 fter adjusting for age, sex, race/ethnicity, marital status, educational attainment, employment, heal

183 were categorized by patient characteristics (marital status, educational level) and tumor characteris

184 er of people in household, country of birth, marital status, educational level, and highest employmen

185 nces in kappa statistics based on age, race, marital status, educational level, and income.

186 fter adjustment for comorbidity score, race, marital status, educational status, clinical stage, and

187 f age, sex, social class, educational level, marital status, employment status, body mass index, phys

188 patient age, race, education, health status, marital status, employment status, distance from the cen

189 h state and trait anxiety were: age, gender, marital status, employment status, level of education, s

190 Marital status, employment, education, geographic locati

191 ogistic regression, adjusting for sex, race, marital status, employment, education, health literacy,

192 -ethnicity, breastfeeding, mode of delivery, marital status, exposure to environmental tobacco smoke,

193 idence after controlling for age, education, marital status, fasting glucose, body mass index, high-d

194 elf-explanatory outcomes such as employment, marital status, financial independence and housing.

195 re consistent with finer-grained analyses by marital status, gender, and age.

196 aditional measures such as socioeconomic and marital status, health habits, and education may require

197 Age, marital status, health status, stressful life events, an

198 Assessment of marital status, heart failure symptomatology, and percei

199 was associated with excellent health, single marital status, higher education, lower body mass index,

200 rs of better QOL included college education, marital status, higher household income, private health

201 y performance status, stage, sex, age, race, marital status, histology, tumor location, hemoglobin, t

202 rs, after adjustment for smoking, education, marital status, history of heart disease, parity, race/e

203 SV-2 seropositivity were HIV seropositivity, marital status, history of sexually transmitted disease

204 al cancer varies substantially by age, race, marital status, hospital volume, and individual hospital

205 ust, controlling for age, gender, education, marital status, household income and religiosity.

206 Age, gender, marital status, household structure, and occupation did

207 Hazard ratios (HRs) were adjusted for marital status, immigration status, income quartile (sin

208 lic and diastolic blood pressure, education, marital status, income, and occupation.

209 factors including age, ethnicity, education, marital status, income, employment, and drug and alcohol

210 Correlates of depressive symptoms include marital status, income, kidney function, history of affe

211 er adjusting for age, background, education, marital status, income, nativity, smoking, physical acti

212 respect to age, ethnicity, race, education, marital status, income, obstetric history, and language.

213 groups (sex, age, race/ethnicity, education, marital status, income, urban/rural, and region).

214 conomic variables including race, ethnicity, marital status, insurance status, and geographic locatio

215 6) after adjusting for age, smoking, parity, marital status, insurance status, and weight.

216 ex), adjusting for survey year, region, age, marital status, insurance, educational attainment, and i

217 r controlling for age, sex, race, education, marital status, interval between final interview and dea

218 ing status and intensity, educational level, marital status, job status, energy intake, and physical

219 unger age, nonwhite race, male sex, divorced marital status, lack of advance directives, a recent dec

220 physical health status, depressive symptoms, marital status, level of education, and severity of illn

221 s of education, occupational status, income, marital status, life satisfaction, disability, and heigh

222 er controlling for age, sex, race/ethnicity, marital status, living alone or not, education, income,

223 logistic regression models adjusted for age, marital status, living arrangement, family size, and sev

224 health, education level, employment status, marital status, living arrangements, and birth rate were

225 ssociated with lower age, male sex, divorced marital status, living with children, lack of satisfacti

226 adults to investigate the impact of current marital status, marriage timing, divorce and widow trans

227 After adjusting for age, marital status, material deprivation history, smoking, d

228 on, physical activity, body weight, smoking, marital status, medical conditions, and medications.

229 Information regarding income, education, marital status, medical history, and cardiovascular risk

230 alyses revealed that age more than 65 years, marital status, minority populations, and primary tumor

231 ties differed from whites in sex proportion, marital status, number of children, geographic location,

232 e no significant differences with respect to marital status, number of children, or number of hours w

233 and MCS after adjustment for age, education, marital status, number of comorbidities, smoking, cancer

234 ucation, employment, hours of work per week, marital status, or satisfaction with life.

235 ollowing characteristics: gender, age, race, marital status, parental status, additional graduate deg

236 or smoking, body mass index, alcohol intake, marital status, parity, menopausal status, and history o

237 After adjustment for race/ethnicity, marital status, parity, prepregnancy physical activity,

238 f melanoma, institution, histologic subtype, marital status, performance of skin self-examination, nu

239 ing status, alcohol intake, body mass index, marital status, physical activity, and education level.

240 results were controlled for age, education, marital status, physician's health rating, dieting for m

241 ation level, sex, US region, race/ethnicity, marital status, political affiliation, likelihood to vot

242 ation problems, but when maternal education, marital status, poverty level, and race are controlled,

243 Marital status, premorbid functional status, clinical se

244 ance coverage, years of education, literacy, marital status, pretransplantation compliance, and histo

245 Data for age, sex, ethnicity, marital status, psychotic disorder diagnosis, subsequent

246 rate ratio (before and after adjustment for marital status, race, and age) comparing vaccinated with

247 sible modifiers of concordance: patient age, marital status, race, educational level, Eastern Coopera

248 After adjustment for maternal age, marital status, race/ethnicity, and education, the risk

249 After controlling for age, gender, marital status, race/ethnicity, city, and time, the auth

250 ction, race/ethnicity, socioeconomic status, marital status, referral source, and referral year.

251 ent for a participant's age, sex, education, marital status, religion, and study site.

252 regression that adjusted for age, race, sex, marital status, residence, percent of county below feder

253 When adjusted for age, marital status, residential area, clinical characteristi

254 After adjusting for age, education, race, marital status, self-efficacy, and dental knowledge, mul

255 conomic variables, including age, race, sex, marital status, service connection, prescription copay,

256 ge, surgery weight, surgery body mass index, marital status, sex, educational level, site, Internatio

257 for country, age, race, education duration, marital status, smoking, alcohol, and number of recent s

258 ed to age, state, race/ethnicity, education, marital status, smoking, and alcohol consumption.

259 after adjusting for age, gender, education, marital status, smoking, hypertension, diabetes mellitus

260 Sex, age, ethnicity, marital status, social deprivation, severity of psychopa

261 Covariates were age, sex, education, marital status, social isolation and social support, chr

262 mined the effects of age, gender, education, marital status, social isolation, functional impairment,

263 Three components (marital status, social network size, and religious servi

264 s measured with a 7-item index that included marital status, social network size, frequency of contac

265 s measured with a 7-item index that included marital status, social network size, frequency of contac

266 ciations were not accounted for by sex, age, marital status, socioeconomic position, place of work, s

267 ciocultural factors, such as age, gender and marital status, strongly influence the probability of un

268 e includes 5 domains (employment, education, marital status, substance abuse and income), each with a

269 al radiation, age, sex, race, education, and marital status, survivor hair loss increased risk of anx

270 fter adjustment for age, race/ethnicity, and marital status, the odds of high-risk HPV infection were

271 adults to examine the association of current marital status, timing of first marriage, number and kin

272 ables included individual factors (age, sex, marital status, underlying cause of death) and measures

273 xyvitamin D levels and age, body mass index, marital status, use of hormone therapy, physical activit

274 interaction; and the PFS model also included marital status, weight loss, and p16 x Zubrod interactio

275 adjusted for hormonal contraceptive use and marital status, women reporting multiple male partners o

276 rlson score, residency training program, and marital status, women with early-stage disease were sign

277 tion, knowledge about malaria/ITNs, age, and marital status.

278 breastfeeding, age, education, smoking, and marital status.

279 economic status, rural residence, and single marital status.

280 nformation on educational qualifications and marital status.

281 .9) after adjustment for age, education, and marital status.

282 , poor sleep, health status, employment, and marital status.

283 y, parity, height, body mass index, race, or marital status.

284 conditions were found between spouses or by marital status.

285 ptor (PR) status, differentiation, race, and marital status.

286 ies according to age, race or ethnicity, and marital status.

287 lly by age, residence in Greater London, and marital status.

288 sidered included maternal IQ, education, and marital status.

289 = 0.29), but did not differ by age, sex, or marital status.

290 cts could be explained by differences in: 1) marital status; 2) gender; and 3) ethnicity.

291 mic status; residence area; occupation type; marital status; history of hypertension, diabetes mellit

292 ent, how many children parents have, and the marital statuses of parents and children affect the exte

293 of marriage, and durations spent in various marital statuses with the risk of all-cause mortality.

294 f particular types of stress such as job and marital strain, with recurrent adverse events after AMI.

295 considered: the parent-child subsystem, the marital subsystem, and the sibling subsystem.

296 stics, our best scholars have concluded that marital therapy is at a practical and theoretical impass

297 e hazards of dying associated with long-term marital trajectories and contributing risk factors are l

298 An analysis of the raiding histories, marital trajectories, and reproductive histories of thes

299 essors are discussed in terms of job stress, marital unhappiness, and burden of caregiving.

300 itions - be used to facilitate relational or marital well being?

301 are hormonal contraceptives (HCs) related to marital well-being?