The results of our analysis underscore the importance of frequent STI screening among PWH

Approximately 23% reported using alcohol and drugs prior to sex in the last six months. Participants who had a partner on PrEP reported a higher number of sex partners in the last six months compared to those with only HIV-positive partners and those with HIV-negative partners not on PrEP . However, condomless sex did not statistically differ across the three partner groups, with a prevalence of condomless sex in the last six months of 13% among PWH who had a partner on PrEP, 19% among those with only HIV-positive partners, and 16% among PWH without PrEP partners .This study examined the association of alcohol and drug use and partner use of PrEP with STI risk among PWH with a history of unhealthy drinking. Results indicated that, although PWH in this cohort have reduced HIV transmission risk based on their viral suppression and/or the use of PrEP by partners, the risk of STI transmission remained a concern. We found that participants who had a partner on PrEP had nearly three times the prevalence of STIs compared with those who had HIV-negative partners not taking PrEP. Approximately 8% of the participants in our study had a positive STI test result during the study period. The prevalence we observed was slightly lower compared to recent estimates in the STD Surveillance Network. However, Lucar et al.found similar STI rates in their clinic-based cohort of PWH across multiple sites in the Washington DC metropolitan area. These findings should be interpreted with the context that overall STI incidence among MSM has been steadily increasing over the last two decades. In one study at a community health centre in Boston, incidence of STIs among MSM increased from 4.6 to 26.8 per 100 person-years between 2005 and 2015.This trend is likely multi-factorial and partly due to a decline in condom use, enhanced STI testing, flood tray and broader perception of HIV as a manageable illness.Some have proposed that the roll-out of PrEP has contributed to increases in condomless sex, thus driving incident STIs among MSM.

However, surveillance data have noted increases in STI prevalence in the general MSM population well before the widespread use of PrEP.In our analysis, we found no statistically significant differences in condom use among PWH who had a partner on PrEP and those who did not, suggesting the potential role of other behavioural factors, such as number of partners and alcohol and drug use. Sexual network characteristics may account for the associations we observed. PWH who had a partner on PrEP had four times the median number of sex partners in the last six months compared to others, suggesting a higher probability of STI exposure. Other network characteristics such as background STI prevalence, rate of partner exchange, concurrency of sex partners, and network density or how interconnected individuals are in a sexual network might have also influenced STI risk.w1 As PWH who had a partner on PrEP were more sexually active than others in our cohort, they may also have been screened for STIs more frequently, leading to increased detection of asymptomatic infections. We also found that PWH who used alcohol and drugs prior to sex had a higher STI prevalence, although estimates were not statistically significant. Chemsex, or the use of sex enhancing drugs such as amphetamines during sex, has become increasingly popular among MSM in industrialized countries, and is a well-known driver of sexual risk-taking.The associations we observed were attenuated in adjusted analyses but the direction of each association was consistent with findings from previous reports. For example, alcohol and drug use have been associated with condomless sex, impaired sexual decision-making, and having higher numbers of sexual partners.Our findings also support the need for ongoing discussions around sexual risk behaviours and STI risk reduction during routine clinic visits.

Given the cross-sectional design of our study, we cannot conclude that partner PrEP use is causally associated with STIs in PWH. However, this study has important implications for public health efforts. The prevalence of STIs among PWH who have partners on PrEP suggests that this subgroup may be a high-yield focus for targeted interventions. Along with efforts to increase STI screening, enhanced outreach that integrate HIV and STI care coordination, and novel strategies, such as STI post-exposure prophylaxis, are needed. A key strength of our analysis is the use of a primary care-based cohort in an integrated healthcare system, which allowed us to link interview data with laboratory-confirmed STI test results. However, we acknowledge some important limitations. We were limited in our ability to characterize participants’ sexual networks and assess temporality of exposure and outcome. It is conceivable that participants acquired an STI before any encounter with a partner on PrEP or acquired the infection from others in their sexual network. It is also possible that participants may not have accurately reported their partner’s PrEP use or their condom use behaviours due to recall bias, social desirability, and/or misinformation. Some in our sample may also have received STI testing outside of the KPNC healthcare system, results of which would not be captured in the electronic health record. All participants had a history of unhealthy alcohol use in the prior year, so findings may not be reflective of the experiences of other PWH. However, the prevalence of hazardous alcohol use in our cohort based on AUDIT scores was similar to other studies involving general PWH populations.Lastly, the majority of the participants in our study were MSM and all of them were insured; therefore findings may not be generalizable to the broader population of PWH, particularly cisgender women, transgender people, and those without health insurance coverage.

Despite these limitations, this study provides important insights that can inform efforts to address the STI epidemic. However, prospective studies are needed to more clearly understand the relationship between partner PrEP use and STI incidence among PWH.Health complications related to preterm birth may impose lifelong sequelae or death.In the United States, 17% to 34% of infant deaths within the first year of life are attributable to prematurity.Children born preterm are more likely to have vision or hearing loss, cerebral palsy, and physical or learning delays.The societal economic burden associated with preterm birth in the United States was estimated to be over $26 billion annually more than a decade ago.Years of study have identified numerous risk factors for preterm birth, including obesity, hypertension, diabetes, smoking, drug or alcohol dependence/abuse during pregnancy and a short interval between pregnancies.Few protective factors against preterm birth have been identified, but include maternal birth outside of the United States and interpregnancy interval of 24 to 60 months.Identification of risk and protective factors has not decreased preterm birth rates in the United States – instead rates have been showing an upward trend. In an effort to improve infant health outcomes, there has been a recent upsurge in efforts to reduce preterm birth rates in the United States.This effort is challenging, due to the complex biology of preterm birth, various clinical presentations,ebb and flow tray and socioeconomic and psychosocial influences.Due to the need for multi-pronged approaches to decrease preterm birth rates, a collaborative place-based approach may be an effective way to decrease rates locally. A place-based approach is designed to take into account the unique local and contextual conditions of specific locations, engage a diverse range of sectors in a collaborative decision making process, and leverage local talent, knowledge, and assets.By addressing drivers of preterm birth that may be more frequent based on location , this method recognizes that one size may not fit all, either in terms of drivers or interventions. California reports a 2016 preterm birth rate of 8.5%, with the highest rate in Fresno County, located in the Central Valley region. Fresno County has just under one million residents, half of whom are Hispanic, and has the highest value of agricultural crops by any county in the United States.Fresno County reports the highest poverty rate in California, with 32.3% of families with children living below the poverty level, and is considered a Primary Care Health Professional Shortage Area.In this study we evaluated the influences of maternal characteristics and obstetric factors on timing of birth in Fresno County to evaluate both risk and prevalence of risk by urban, suburban, and rural residence.

We aimed to identify risk and protective factors for birth before 37 weeks’ gestation that can inform policy and health care priorities designed to reduce preterm birth rates in Fresno County. In this retrospective cohort study, our sample was drawn from California live births between January 1, 2007 and December 31, 2012. The sample was restricted to women with singleton births with best obstetric estimate of gestation at delivery between 20 and 44 weeks, linked to the birth cohort database maintained by the California Office of Statewide Health Planning and Development, with no known chromosomal abnormalities or major structural birth defects, and a Fresno County census tract . The birth cohort database contained linked birth and death certificates, as well as detailed information on maternal and infant characteristics, hospital discharge diagnoses and procedures recorded as early as one year before delivery and as late as one year post-delivery. Data files provided diagnoses and procedure codes based on the International Classification of Diseases, 9th Revision, Clinical Modification .Structural birth defects for the study were considered “major” if determined by clinical review as causing major morbidity and mortality that would likely be identified in the hospital at birth or lead to hospitalization during the first year of life.The sample of Fresno County women was stratified by residence in urban, suburban and rural census tracts as defined by the Medical Service Study Areas . MSSAs “are recognized by the U.S. Health Resources and Services Administration, Bureau of Health Professions’ Office of Shortage Designation as rational service areas for purposes of designating Health Professional Shortage Areas , and Medically Underserved Areas and Medically Underserved Populations ”.Within each of these residence strata, known maternal preterm birth risk factors were compared for women who delivered before 37 weeks’ gestation to those of women who delivered between 37 and 44 completed weeks’ gestation, using Poisson logistic regression to calculate crude relative risks and 95% confidence intervals . Comparisons using data from birth certificate records included race/ethnicity, maternal age, education, payment for delivery, participation in the Women, Infants, and Children program ,parity, maternal birthplace, report of smoking during pregnancy, maternal body mass index , trimester when prenatal care began, and number of prenatal care visits. For multi-parous women, we examined the relationship between preterm birth and previous preterm birth, previous cesarean delivery, and interpregnancy interval. Interpregnancy interval was calculated from previous live birth as reported in linked records and estimated as months to conception of the index pregnancy. Given that the day of previous live birth was not available, the middle of the month was used for calculation purposes.Factors from hospital discharge ICD-9 diagnoses included: Preexisting hypertension without progression to preeclampsia, preexisting hypertension with progression to preeclampsia, gestational hypertension without progression to preeclampsia, gestational hypertension with progression to preeclampsia, preexisting diabetes, and gestational diabetes. We also compared preterm birth with respect to the frequency of coded infection, anemia, drug or alcohol dependence/abuse, and mental disorder . Multivariable models of maternal risk and protective factors for preterm birth were built for each location of residence category using backwards-stepwise Poisson logistic regression wherein initial inclusion was determined by a threshold of p < .20 in crude analyses. Adjusted RRs and their 95% CIs were calculated for each residence stratum. In an effort to visualize overall risk of preterm birth by census tract, cumulative risk scores estimated the overall risk of preterm birth. Scores were calculated for each woman by adding her risks and subtracting her protective factors – 1 remaining in the final multi-variable model. Risk scores were grouped into scores 0.0 or less, 0.1 to 0.9, 1.0 to 1.9, 2.0 to 2.9 and 3.0 or more. Drug dependence/abuse and mental illnesses were further classified based on ICD-9 diagnostic codes, although risks calculations were not computed due to small numbers. Drug dependence/abuse was defined by classification of drug: opioid, cocaine, cannabis, amphetamine, other drug dependence/abuse, and poly substance dependence/abuse. Mental illnesses were further classified as: schizophrenic disorders, bipolar disorder, major depression, depressive disorder, anxiety disorders, personality disorders, and more than one of the previously mentioned categories. Infection was further classified as asymptomatic bacteriuria, urinary tract infection, sexually transmitted infection, and viral infection .

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