Sociodemographic Characteristics Of Population Research Articles

Human Papillomavirus (HPV) Infections Among Participants Undergoing Chlamydia trachomatis Testing in Reunion Island (RUN-SurV-HPV Study): Protocol for a Prevalence Study.

Infection by human papillomavirus (HPV) induces various cancers, mainly cervical cancer but also anal and pharyngeal cancers. Reunion Island is a French department in the Indian Ocean. Due to the history of its settlement, the island's population has a wide variety of origins, and the population's sociodemographic characteristics differ from those of the French mainland. These characteristics make the island's population an original French population in its own right, particularly in terms of health. Cervical cancer incidence and mortality in Reunion Island are 10.4 per 100,000 and 4.4 per 100,000, respectively, both of which are much higher than those in mainland France. There is also a disparity in the prevalence of different HPV types, with types 33 and 52 being overrepresented and type 18 being underrepresented. However, vaccination and screening coverage in Reunion Island is low. It is important to understand the burden of infection and its risk factors in members of the young Reunionese population at risk of HPV infection to promote and evaluate the implementation of future vaccination and screening programs on a larger scale. The RUN-SurV-HPV study will have the following four objectives: (1) to describe the prevalence of HPV genotypes in a population at risk of sexually transmitted infections in Reunion Island; (2) to describe the prevalence of HPV genotypes by anatomical site, gender, and sexuality; (3) to describe the correlates and risk factors for HPV detection; and (4) to examine HPV genotypes between different anatomical sites. Cross-sectional analyses of 1200 routine vaginal, anal, pharyngeal, and urinary samples collected between October 2020 to December 2022 from female and male patients aged 16 to 30 years undergoing Chlamydia trachomatis testing at a sexually transmitted infection (STI) testing center at Reunion Island will be performed. The population included 333 women who all had vaginal and pharyngeal swabs, with 80 of them also having had an anal swab. There are 167 men who have sex with men who have had anal and pharyngeal swabs, and 120 men who have sex with women who have had a urine swab only. Results will be correlated with sociodemographic and clinical data collected routinely during the consultations. HPV detection and genotyping will be performed using the Anyplex II HPV28 detection assay (Seegene). The first polymerase chain reactions should begin in November 2023. The first results should be submitted for publication in 2024. The study will determine HPV prevalence by age, sex, male sexual preference, human immunodeficiency virus status, and STI co-infection. Collecting data from young patients not usually routinely screened for HPV infection will be a simple and reproducible way of better understanding local specificities, encouraging vaccination campaigns in the short-term, and evaluating their effectiveness in the future. DERR1-10.2196/47379.

Trends in Diet Quality and Cardiometabolic Risk Factors Among Korean Adults, 2007-2018

Few studies have examined the dietary trends in Korea beyond evaluating selected food groups. To help prevent cardiometabolic disease burdens, a comprehensive investigation of the trends in overall diet quality and identification of possible contributing factors would be useful. To investigate the trends and independent associations of age, period, and birth cohort with diet quality and cardiometabolic risk factors among Korean adults. Serial cross-sectional and age-period-cohort analyses were conducted of nationally representative 24-hour dietary recall data from the Korea National Health and Nutrition Examination Survey 2007-2018. The study population included 65 416 Korean adults aged 19 to 79 years. Data analyses were conducted from March 1, 2020, through April 30, 2021. Age, calendar year, birth cohort, and population sociodemographic characteristics. Korean Healthy Eating Index (KHEI), a validated diet quality score (range, 0-90, with higher scores indicating greater diet quality), and 8 cardiometabolic risk factors (waist circumference and systolic blood pressure, diastolic blood pressure, serum total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglyceride, and fasting blood glucose levels). Among 65 416 participants, mean age (SD) was 44.5 (0.1) years and 36 631 were women (55.8%). In 2007-2018, the age-standardized mean (SE) KHEI score increased from 51.0 (0.4) to 52.1 (0.5), which was associated with reduced sodium intake and increased whole grain, dairy, and protein-rich food intakes. The mean (SE) KHEI score was lowest at age 39 years (50.1 [0.3]) and increased at older ages (58.0 [0.3] at 79 years). Controlling for age and period effects, the highest KHEI score was observed among the birth cohorts of 1960-1964 (53.6 [0.9]) and decreased in subsequent cohorts (45.5 [1.2] in the 1990-1999 birth cohort). Similar cohort effects in cardiometabolic risk factors were observed, showing the lowest waist circumference, blood pressure, and total cholesterol levels among the birth cohorts of the 1960s and 1970s and higher levels among more recent birth cohorts (1990-1999 vs 1960-1964: waist circumference, 83.8 [0.5] vs 81.4 [0.4] cm; systolic blood pressure, 118.7 [0.7] vs 116.4 [0.4] mm Hg; total cholesterol, 200.2 [0.9] vs 198.9 [0.7] mg/dL). At most ages, periods, and birth cohorts, the mean KHEI score was consistently higher in adults living in urban areas (at age 45 years: 50.5 [1.0] vs 49.7 [0.9] rural) and among high-income (at age 45 years: 50.7 [1.1] vs 49.3 [0.9] low income) and educational levels (at age 45 years: 53.1 [0.9] vs 49.1 [1.0] low educational level). The findings of this study suggest that, from 2007 to 2018, the diet quality of Korean adults modestly improved. Despite the improvement, inequalities in diet among age, birth cohort, and socioeconomic subgroups persisted, suggesting that more intense interventions may be needed to target the susceptible groups.

Coastal cities in the Southern US floodplains: An evaluation of environmental equity of flood hazards and social vulnerabilities

Few empirical studies have examined environmental equity (EE) within the context of flooding in the United States (US). This paper explores whether lower-income, minority, and vulnerable communities in cities are disproportionately impacted by flooding, as evidenced by Federal Emergency Management Agency (FEMA) designated flood zones. Tampa and Houston, both coastal cities in the US, were investigated to understand flood risk and related equity issues using Geographical Information System (GIS) and statistical analyses. Both approaches allowed us to extract and integrate information from flood hazard maps with census block group-level sociodemographic data. Dasymetric mapping (i.e., binary mapping approach) was performed to calculate population density. Both correlations and logistic regression were used to examine the relationships between sociodemographic characteristics of population and flood risk associated with FEMA flood zones. Our research findings do not suggest any racial and ethnic disparities; however, a measurable inequity is observed in exposure to flood risk across age groups, education level, and income status. Since these vulnerable groups are often unrecognized in hazard-related policy discourses (i.e., preparedness, response, and recovery), the ramifications of these research findings may have significant impacts on EE research relating to flood hazards and related policy formulations.

A comparison of household food insecurity rates in Newfoundland and Labrador in 2011-2012 and 2017-2018.

The prevalence of household food insecurity in Newfoundland and Labrador (NL) fell sharply between 2007 and 2011, but it appears to have risen since then. Our objective was to compare the prevalence of food insecurity between 2011-2012 and 2017-2018 in relation to population socio-demographic characteristics. Our analytic sample comprised all NL households in the Canadian Community Health Survey (CCHS) cycles 2011-2012 and 2017-2018, n = 6800. We stratified the prevalence of household food insecurity for each cycle by socio-demographic characteristics and applied multivariable logistic regression models to determine food insecurity odds in 2017-2018 compared with 2011-2012 after controlling for socio-demographic covariates. Interactions of covariates with survey cycle were tested and models stratified when warranted. The prevalence of food insecurity rose from 12.0% (95% CI 10.5, 13.6) in 2011-2012 to 14.7% (95% CI 13.1, 16.6) in 2017-2018. After adjusting for household socio-demographic variables, the odds of food insecurity was 1.49 (95% CI 1.27, 1.75) in 2017-2018. The prevalence of food insecurity had increased significantly among unattached individuals, renters, households with low educational attainment, and households with income above the Low Income Measure, with concomitant increases in the contribution of these groups to the total provincial prevalence of food insecurity in 2017-2018 compared with that in 2011-2012. The odds of food insecurity among NL households increased significantly from 2011-2012 to 2017-2018. Given the serious negative health implications of household food insecurity, the province should draw on the lessons from its earlier success in food insecurity reduction to reverse the current trend.

Medicaid Expansion and Incidence of Kidney Failure among Nonelderly Adults.

Low-income individuals without health insurance have limited access to health care. Medicaid expansions may reduce kidney failure incidence by improving access to chronic disease care. Using a difference-in-differences analysis, we examined the association between Medicaid expansion status under the Affordable Care Act (ACA) and the kidney failure incidence rate among all nonelderly adults, aged 19-64 years, in the United States, from 2012 through 2018. We compared changes in kidney failure incidence in states that implemented Medicaid expansions with concurrent changes in nonexpansion states during pre-expansion, early postexpansion (years 2 and 3 postexpansion), and later postexpansion (years 4 and 5 postexpansion). The unadjusted kidney failure incidence rate increased in the early years of the study period in both expansion and nonexpansion states before stabilizing. After adjustment for population sociodemographic characteristics, Medicaid expansion status was associated with 2.20 fewer incident cases of kidney failure per million adults per quarter in the early postexpansion period (95% CI, -3.89 to -0.51) compared with nonexpansion status, a 3.07% relative reduction (95% CI, -5.43% to -0.72%). In the later postexpansion period, Medicaid expansion status was not associated with a statistically significant change in kidney failure incidence (-0.56 cases per million per quarter; 95% CI, -2.71 to 1.58) compared with nonexpansion status and the pre-expansion time period. The ACA Medicaid expansion was associated with an initial reduction in kidney failure incidence among the entire, nonelderly, adult population in the United States; but the changes did not persist in the later postexpansion period. Further study is needed to determine the long-term association between Medicaid expansion and changes in kidney failure incidence.

Structural Racism and COVID-19 in the USA: a County-Level Empirical Analysis.

Substantial health disparities exist across race/ethnicity in the USA, with Black Americans often most affected. The current COVID-19 pandemic is no different. While there have been ample studies describing racial disparities in COVID-19 outcomes, relatively few have established an empirical link between these disparities and structural racism. Such empirical analyses are critically important to help defuse “victim-blaming” narratives about why minority communities have been badly hit by COVID-19. In this paper, we explore the empirical link between structural racism and disparities in county-level COVID-19 outcomes by county racial composition. Using negative binomial regression models, we examine how five measures of county-level residential segregation and racial disparities in socioeconomic outcomes as well as incarceration rates are associated with county-level COVID-19 outcomes. We find significant associations between higher levels of measured structural racism and higher rates of COVID-19 cases and deaths, even after adjusting for county-level population sociodemographic characteristics, measures of population health, access to healthcare, population density, and duration of the COVID-19 outbreak. One percentage point more Black residents predicted a 1.1% increase in county case rate. This association decreased to 0.4% when structural racism indicators were included in our model. Similarly, one percentage point more Black residents predicted a 1.8% increase in county death rates, which became non-significant after adjustment for structural racism. Our findings lend empirical support to the hypothesis that structural racism is an important driver of racial disparities in COVID-19 outcomes, and reinforce existing calls for action to address structural racism as a fundamental cause of health disparities.Supplementary InformationThe online version contains supplementary material available at 10.1007/s40615-020-00948-8.

Trends in Diet Quality Among Youth in the United States, 1999-2016

Prior studies of dietary trends among US youth have evaluated major macronutrients or only a few foods or have used older data. To characterize trends in diet quality among US youth. Serial cross-sectional investigation using 24-hour dietary recalls from youth aged 2 to 19 years from 9 National Health and Nutrition Examination Survey (NHANES) cycles (1999-2016). Calendar year and population sociodemographic characteristics. The primary outcomes were the survey-weighted, energy-adjusted mean consumption of dietary components and proportion meeting targets of the American Heart Association (AHA) 2020 continuous diet score (range, 0-50; based on total fruits and vegetables, whole grains, fish and shellfish, sugar-sweetened beverages, and sodium). Additional outcomes were the AHA secondary score (range, 0-80; adding nuts, seeds, and legumes; processed meat; and saturated fat) and Healthy Eating Index (HEI) 2015 score (range, 0-100). Poor diet was defined as less than 40% adherence (scores, <20 for primary and <32 for secondary AHA scores); intermediate as 40% to 79.9% adherence (scores, 20-39.9 and 32-63.9, respectively); and ideal, as at least 80% adherence (scores, ≥40 and ≥64, respectively). Higher diet scores indicate better diet quality; a minimal clinically important difference has not been quantified. Of 31 420 youth aged 2 to 19 years included, the mean age was 10.6 years; 49.1% were female. From 1999 to 2016, the estimated AHA primary diet score significantly increased from 14.8 (95% CI, 14.1-15.4) to 18.8 (95% CI, 18.1-19.6) (27.0% improvement), the estimated AHA secondary diet score from 29.2 (95% CI, 28.1-30.4) to 33.0 (95% CI, 32.0-33.9) (13.0% improvement), and the estimated HEI-2015 score from 44.6 (95% CI, 43.5-45.8) to 49.6 (95% CI, 48.5-50.8) (11.2% improvement) (P < .001 for trend for each). Based on the AHA primary diet score, the estimated proportion of youth with poor diets significantly declined from 76.8% (95% CI, 72.9%-80.2%) to 56.1% (95% CI, 51.4%-60.7%) and with intermediate diets significantly increased from 23.2% (95% CI, 19.8%-26.9%) to 43.7% (95% CI, 39.1%-48.3%) (P < .001 for trend for each). The estimated proportion meeting ideal quality significantly increased but remained low, from 0.07% (95% CI, 0.01%-0.49%) to 0.25% (95% CI, 0.10%-0.62%) (P = .03 for trend). Persistent dietary variations were identified across multiple sociodemographic groups. The estimated proportion of youth with a poor diet in 2015-2016 was 39.8% (95% CI, 35.1%-44.5%) for ages 2 to 5 years (unweighted n = 666), 52.5% (95% CI, 46.4%-58.5%) for ages 6 to 11 years (unweighted n = 1040), and 66.6% (95% CI, 61.4%-71.4%) for ages 12 to 19 years (unweighted n = 1195), with persistent differences across levels of parental education, household income, and household food security status. Based on serial NHANES surveys from 1999 to 2016, the estimated overall diet quality of US youth showed modest improvement, but more than half of youth still had poor-quality diets.

Mapping the geographic availability of public dental services in Uganda relative to ruralization and poverty of the population

Objectives: Uganda is a low-income country faced with a number of challenges in health service delivery, including oral health services. Despite reports of an increased prevalence of oral diseases, they are afforded less priority, amidst competing priorities of infectious and other non-communicable diseases. Oral health-care services are offered free-of-charge in public health facilities. The majority of the Ugandan population live in rural areas. This would imply that public dental services should be more widely distributed in rural areas to meet the needs of the majority population. This study, therefore, aimed to determine the geographic distribution of public dental services relative to poverty and ruralization of the Ugandan population. Materials and Methods: All 112 districts in Uganda were to be surveyed for this study using an ecological design that incorporated the Ugandan population with socio-demographics obtained from the latest Uganda National Housing and Population Census and poverty data from the national Poverty Status Report 2014. The data from the districts were on the availability of public dental services and the physical location of these dental facilities. Overall, 182 public facilities were included in the study. The geographic location of public dental clinics was established using open-data sources. The data on ruralization were aggregated at the district level and that on poverty at the subregion level. Spatial analysis was done using geographic information science software, Quantum Geographic Information System. Results: The total Ugandan population was 34 million. Overall, 19.7% of the population was poor with the highest proportion located in the North and East of Uganda. Urban-rural characteristics varied across the country. Information on the 182 public dental clinics was collected from 97 of the 112 Ugandan districts. Among the 97 districts, 15% had no public clinic and were located in the poorest Ugandan regions. Among the 40 districts containing over 90% of the rural population, 20% had none, and 55% only had one dental clinic. In general, service availability reduced as the proportion of the rural and poor population increased. Conclusion: The spatial analysis presents an avenue to inform and guide the decision making and planning process by identifying geographic areas with access gaps relative to population socio-demographic characteristics. This study revealed that public dental services were least available for the poorest and rural populations, and yet they are already vulnerable to other access barriers. It is recommended that efforts should be made by health planners and policymakers to avert the health inequalities presented by inequitable access.

Characteristics and Health Care Utilization of Different Segments of a Multiethnic Asian Population in Singapore

Descriptive population-level health data are critical components of the evidence base for population health policy. Human populations often display marked heterogeneity in their health status among subgroups of the population. The recent widespread adoption of electronic health records provides opportunities to use routine real-world health care data to examine population health. To report population sociodemographic characteristics, health conditions, health care utilization, and health care costs for different population segments of a multiethnic Asian population divided according to a modified British Columbia Population Segmentation Framework. This population-based cross-sectional study used 2016 data from the Singapore Eastern Regional Health System, the largest Regional Health System in Singapore. Data were obtained from deidentified national-level electronic health records at the Ministry of Health Singapore. Participants included all residents in the Singapore Eastern Regional Health System catchment area in 2016. The descriptive analysis was conducted in August 2018. Socioeconomic profiles, disease prevalence, health care utilization, and cost patterns of population segments. The total size of the study population in 2016 was 1 181 024 residents (576 663 [48.83%] male; median [interquartile range] age, 40 [22-57] years). The population was divided into 8 segments: healthy with no outpatient utilization (493 483 residents), healthy with outpatient utilization (259 909 residents), healthy with inpatient admissions (49 588 residents), low complex (215 134 residents), medium complex (79 350 residents), high complex (44 445 residents), cancer (34 217 residents), and end of life (4898 residents). Overall, the 3 most prevalent conditions were chronic kidney disease (31.89%), hypertension (18.52%), and lipid disorders (18.33%). Distributions of chronic conditions differed across the segments. Different segments had varying health care utilization patterns: the high-complex segment had the highest number of primary care clinic visits (mean [SD], 4.25 [5.46] visits), the cancer segment had the highest number of specialist outpatient clinic visits (mean [SD], 5.55 [8.49] visits), and the end-of-life segment had the highest numbers of accident and emergency department visits (mean [SD], 1.80 [1.88] visits) and inpatient admissions (mean [SD], 1.99 [1.89] admissions) during 2016. For health care costs, specialist outpatient clinic and inpatient care together made up more than 85% of the total cost of nearly 2 billion Singapore dollars. The end-of-life segment contributed approximately 50% of the health care cost per capita of 60 000 Singapore dollars. Different population segments displayed heterogeneity in sociodemographic characteristics, health conditions, health care utilization, and health care cost patterns. This critical health information can be used as baseline data to inform regional and national health priorities for health services research and policy.

Socioeconomic Differences in Cigarette Smoking Among Sociodemographic Groups.

We examined variations in cigarette smoking by socioeconomic status (education and poverty status) in relation to population sociodemographic characteristics (age, race/ethnicity, region and sex). We analyzed data from a nationally representative sample of US adults by using combined data from the National Survey on Drug Use and Health (2011–2014). Low socioeconomic status was generally associated with increased cigarette smoking prevalence by age, race/ethnicity, and region, irrespective of sex. The only exceptions were for Asian and Hispanic women, where low educational attainment was not associated with a high prevalence of cigarette smoking, and among Hispanic men and Asian women, where there was no association between poverty status and smoking. Efforts to reach smokers of low socioeconomic status by using proven tobacco control strategies could reduce disparities in cigarette smoking and smoking-related disease and death.

Rural-Urban Differences in Medicare Quality Scores Persist After Adjusting for Sociodemographic and Environmental Characteristics.

Quality scores are strongly influenced by sociodemographic characteristics and health behaviors, many of which lie outside of the clinician's control. As a result, there is vigorous debate about whether, and how, to risk-adjust quality measures. Yet, rurality has been largely missing from this debate, even though population and environmental characteristics are demonstrably different by rurality. We addressed this gap by examining the influence of county-level population sociodemographic, environmental, and health characteristics on 3 Medicare quality measures. We used a cross-sectional analysis of 2016 County Health Rankings data to estimate differences in 3 Medicare quality scores (preventable hospitalizations, HbA1c monitoring, and mammography screening) by rurality. We then adjusted for county-level sociodemographic and environmental characteristics in multivariable regression models in order to see whether the association between rurality and quality was impacted. Both micropolitan and noncore counties exhibited lower quality scores than metropolitan counties for all 3 measures. After adjustment, noncore counties still had poorer quality on all 3 measures, while micropolitan counties improved on 2 measures. Several county-level sociodemographic and environmental characteristics were associated with quality, although the direction of association depended on the quality measure. Differences in Medicare quality scores by rurality cannot be entirely explained by differences in population or environmental characteristics. Still, to the extent that clinicians are evaluated-and paid-based on measures that are influenced by both population sociodemographic characteristics and geographic location without adequate risk adjustment, the challenges of delivering care in rural areas will only be exacerbated.

Autism spectrum disorder reporting in lower socioeconomic neighborhoods.

Utilizing surveillance data from five sites participating in the Autism and Developmental Disabilities Monitoring Network, we investigated contributions of surveillance subject and census tract population sociodemographic characteristics on variation in autism spectrum disorder ascertainment and prevalence estimates from 2000 to 2008 using ordinal hierarchical models for 2489 tracts. Multivariable analyses showed a significant increase in ascertainment of autism spectrum disorder cases through both school and health sources, the optimal ascertainment scenario, for cases with college-educated mothers (adjusted odds ratio = 1.06, 95% confidence interval = 1.02-1.09). Results from our examination of sociodemographic factors of tract populations from which cases were drawn also showed that after controlling for other covariates, statistical significance remained for associations between optimal ascertainment and percentage of Hispanic residents (adjusted odds ratio = 0.93, 95% confidence interval = 0.88-0.99) and percentage of residents with at least a bachelor's degree (adjusted odds ratio = 1.06, 95% confidence interval = 1.01-1.11). We identified sociodemographic factors associated with autism spectrum disorder prevalence estimates including race, ethnicity, education, and income. Determining which specific factors influence disparities is complicated; however, it appears that even in the presence of education, racial and ethnic disparities are still apparent. These results suggest disparities in access to autism spectrum disorder assessments and special education for autism spectrum disorder among ethnic groups may impact subsequent surveillance.

Changes in Visual Function in the Elderly Population in the United States: 1995–2010

ABSTRACTPurpose: To document recent trends in visual function among the United States population aged 70+ years and investigate how the trends can be explained by inter-temporal changes in: (1) population sociodemographic characteristics, and chronic disease prevalence, including eye diseases (compositional changes); and (2) effects of the above factors on visual function (structural changes).Methods: Data from the 1995 Asset and Health Dynamics among the Oldest Old (AHEAD) and the 2010 Health and Retirement Study (HRS) were merged with Medicare Part B claims in the interview years and the 2 previous years. Decomposition analysis was performed. Respondents from both studies were aged 70+ years. The outcome measure was respondent self-reported visual function on a 6-point scale (from 6 = blind to 1 = excellent).Results: Overall, visual function improved from slightly worse than good (3.14) in 1995 to slightly better than good (2.98) in 2010. A decline in adverse effects of aging on vision was found. Among the compositional changes were higher educational attainment leading to improved vision, and higher prevalence of such diseases as diabetes mellitus, which tended to lower visual function. However, compared to compositional changes, structural changes were far more important, including decreased adverse effects of aging, diabetes mellitus (when not controlling for eye diseases), and diagnosed glaucoma.Conclusion: Although the US population has aged and is expected to age further, visual function improved among elderly persons, especially among persons 80+ years, likely reflecting a favorable role of structural changes identified in this study in mitigating the adverse effect of ongoing aging on vision.

The Psychiatry consultation in primary health care setting at an Oporto Area: Sociodemographic and clinical data

IntroductionThe Psychiatry consultation is a collaborative approach between primary health care services and community mental health teams. Our clinic provides support to three Oporto areas (Bonfim/Paranhos, Campanhã and Maia/Valongo) corresponding to a population of 350,000 inhabitants.ObjectivesTo analyze and collect Psychiatry consultation data of the first semester of 2015 in Maia/Valongo region. We aim to describe our population's sociodemographic characteristics, the most common referral motive, diagnosis and therapeutics, and orientation.MethodsPsychiatry consultation data of the first semester of 2015 were collected and analyzed using SPSS software (version 20).ResultsOne hundred and sixty-one patients were evaluated. A total of 26.09% were male and 73.91% were female. The mean age was 51.61 years old. The most frequent referral motives were depressive (47.82%) and anxiety (23.60%) symptoms. The two most common diagnostic groups according to the International Classification of Diseases (version 10) were F30-F39–Mood affective disorders (57.76%) and F40-F48–Neurotic, stress-related and somatoform disorders (18.63%). 22.36% of the patients were referred without medication, but only four were discharged drug-free, corresponding to bereavement situations. 34.16% of our population were previously prescribed two or more psychotropic drugs, increasing to 63.98% after assessment. Only 18.63% met criteria to hospital referral.ConclusionsThe Psychiatry consultation selects the most severe patients and allows a faster evaluation of mentally ill patients awaiting hospital consultation, thus preventing unnecessary access to the emergency room. Authors consider that all the patients referred to a hospital consultation should be previously evaluated by a consultant psychiatrist on a primary health care setting.Disclosure of interestThe authors have not supplied their declaration of competing interest.

Recording of Influenza-Like Illness in UK Primary Care 1995-2013: Cohort Study.

BackgroundThere is a lack of recent studies examining recording of influenza-like illness (ILI) in primary care in the UK over time and according to population characteristics. Our aim was to determine time trends and socio-demographic patterns of ILI recorded consultations in primary care.MethodsWe used The Health Improvement Network (THIN) UK primary care database and extracted data on all ILI consultations between 1995 and 2013. We estimated ILI recorded consultation rates per 100,000 person-weeks (pw) by age, gender, deprivation and winter season. Negative binomial regression models were used to examine time trends and the effect of socio-demographic characteristics. Trends in ILI recorded consultations were compared to trends in consultations with less specific symptoms (cough or fever) recorded.ResultsThe study involved 7,682,908 individuals in 542 general practices. The ILI consultation rate decreased from 32.5/100,000 pw (95% confidence interval (CI) 32.1, 32.9) in 1995–98 to 15.5/100,000 pw (95% CI 15.4, 15.7) by 2010–13. The decrease occurred prior to 2002/3, and rates have remained largely stable since then. Declines were evident in all age groups. In comparison, cough or fever consultation rates increased from 169.4/100,000 pw (95% CI 168.6, 170.3) in 1995–98 to 237.7/100,000 pw (95% CI 237.2, 238.2) in 2010–13. ILI consultation rates were highest among individuals aged 15–44 years, higher in women than men, and in individuals from deprived areas.ConclusionThere is substantial variation in ILI recorded consultations over time and by population socio-demographic characteristics, most likely reflecting changing recording behaviour by GPs. These results highlight the difficulties in using coded information from electronic primary care records to measure the severity of influenza epidemics across time and assess the relative burden of ILI in different population subgroups.

Is demography destiny? Application of machine learning techniques to accurately predict population health outcomes from a minimal demographic dataset.

For years, we have relied on population surveys to keep track of regional public health statistics, including the prevalence of non-communicable diseases. Because of the cost and limitations of such surveys, we often do not have the up-to-date data on health outcomes of a region. In this paper, we examined the feasibility of inferring regional health outcomes from socio-demographic data that are widely available and timely updated through national censuses and community surveys. Using data for 50 American states (excluding Washington DC) from 2007 to 2012, we constructed a machine-learning model to predict the prevalence of six non-communicable disease (NCD) outcomes (four NCDs and two major clinical risk factors), based on population socio-demographic characteristics from the American Community Survey. We found that regional prevalence estimates for non-communicable diseases can be reasonably predicted. The predictions were highly correlated with the observed data, in both the states included in the derivation model (median correlation 0.88) and those excluded from the development for use as a completely separated validation sample (median correlation 0.85), demonstrating that the model had sufficient external validity to make good predictions, based on demographics alone, for areas not included in the model development. This highlights both the utility of this sophisticated approach to model development, and the vital importance of simple socio-demographic characteristics as both indicators and determinants of chronic disease.

Father attendance in nurse home visitation.

Our aim was to examine the rates and predictors of father attendance at nurse home visits in replication sites of the Nurse-Family Partnership (NFP). Early childhood programs can facilitate father involvement in the lives of their children, but program improvements require an understanding of factors that predict father involvement. The sample consisted of 29,109 low-income, first-time mothers who received services from 694 nurses from 80 sites. We conducted mixed-model multiple regression analyses to identify population, implementation, site, and nurse influences on father attendance. Predictors of father attendance included a count of maternal visits (B = 0.12, SE = 0.01, F = 3101.77), frequent contact between parents (B = 0.61, SE = 0.02, F = 708.02), cohabitation (B = 1.41, SE = 0.07, F = 631.51), White maternal race (B = 0.77, SE = 0.06, F = 190.12), and marriage (B = 0.42, SE = 0.08, F = 30.08). Random effects for sites and nurses predicted father-visit participation (2.7 & 6.7% of the variance, respectively), even after controlling for population sociodemographic characteristics. These findings suggest that factors operating at the levels of sites and nurses influence father attendance at home visits, even after controlling for differences in populations served. Further inquiry about these influences on father visit attendance is likely to inform program-improvement efforts.

Where do the rural poor deliver when high coverage of health facility delivery is achieved? Findings from a community and hospital survey in Tanzania.

IntroductionAs part of maternal mortality reducing strategies, coverage of delivery care among sub-Saharan African rural poor will improve, with a range of facilities providing services. Whether high coverage will benefit all socio-economic groups is unknown. Iringa rural District, Southern Tanzania, with high facility delivery coverage, offers a paradigm to address this question. Delivery services are available in first-line facilities (dispensaries, health centres) and one hospital. We assessed whether all socio-economic groups access the only comprehensive emergency obstetric care facility equally, and surveyed existing delivery services.MethodsDistrict population characteristics were obtained from a household community survey (n = 463). A Hospital survey collected data on women who delivered in this facility (n = 1072). Principal component analysis on household assets was used to assess socio-economic status. Hospital population socio-demographic characteristics were compared to District population using multivariable logistic regression. Deliveries' distribution in District facilities and staffing were analysed using routine data.ResultsWomen from the hospital compared to the District population were more likely to be wealthier. Adjusted odds ratio of hospital delivery increased progressively across socio-economic groups, from 1.73 for the poorer (p = 0.0031) to 4.53 (p<0.0001) for the richest. Remarkable dispersion of deliveries and poor staffing were found. In 2012, 5505/7645 (72%) institutional deliveries took place in 68 first-line facilities, the remaining in the hospital. 56/68 (67.6%) first-line facilities reported ≤100 deliveries/year, attending 33% of deliveries. Insufficient numbers of skilled birth attendants were found in 42.9% of facilities.DiscussionPoorer women remain disadvantaged in high coverage, as they access lower level facilities and are under-represented where life-saving transfusions and caesarean sections are available. Tackling the challenges posed by low caseloads and staffing on first-line rural care requires confronting a dilemma between coverage and quality. Reducing number of delivery sites is recommended to improve quality and equity of care.

Mapping end-stage renal disease (ESRD): spatial variations on small area level in northern France, and association with deprivation.

BackgroundStrong geographic variations in the incidence of end-stage renal disease (ESRD) are observed in developed countries. The reasons for these variations are unknown. They may reflect regional inequalities in the population's sociodemographic characteristics, related diseases, or medical practice patterns. In France, at the district level, the highest incidence rates have been found in the Nord-Pas-de-Calais region. This area, with a high population density and homogeneous healthcare provision, represents a geographic situation which is quite suitable for the study, over small areas, of spatial disparities in the incidence of ESRD, together with their correlation with a deprivation index and other risk factors.MethodsThe Renal Epidemiology and Information Network is a national registry, which lists all ESRD patients in France. All cases included in the Nord-Pas-de-Calais registry between 2005 and 2011 were extracted. Adjusted and smoothed standardized incidence ratio (SIR) was calculated for each of the 170 cantons, thanks to a hierarchical Bayesian model. The correlation between ESRD incidence and deprivation was assessed using the quintiles of Townsend index. Relative risk (RR) and credible intervals (CI) were estimated for each quintile.ResultsSignificant spatial disparities in ESRD incidence were found within the Nord-Pas-de-Calais region. The sex- and age-adjusted, smoothed SIRs varied from 0.66 to 1.64. Although no correlation is found with diabetic or vascular nephropathy, the smoothed SIRs are correlated with the Townsend index (RR: 1.18, 95% CI [1.00–1.34] for Q2; 1.28, 95% CI [1.11–1.47] for Q3; 1.30, 95% CI [1.14–1.51] for Q4; 1.44, 95% CI [1.32–1.74] for Q5).ConclusionFor the first time at this aggregation level in France, this study reveals significant geographic differences in ESRD incidence. Unlike the time of renal replacement care, deprivation is certainly a determinant in this phenomenon. This association is probably independent of the patients' financial ability to gain access to healthcare.

Losing Ground: Mediterranean Shoreline Change from an Environmental Justice Perspective

Loss of land due to coastal erosion is a problem in the Mediterranean region and world-wide. Following a review of environmental justice (EJ) issues among different sectors of activity and contexts, this article describes research that examines the sociodemographic characteristics of populations destined to be effected by erosion in the city of Netanya, Israel. It also examines the availability of open space serving as an alternative to that expected to erode. Results provide a basis for which to explore the EJ implications of coastal erosion. The study finds that seashore dwellers in the case study area are generally mixed populations, not particularly strong or weak as defined herein. Also, planners and city managers have increasingly provided residents in close proximity to the shore with alternative open space. This work highlights the complexities of considering coastal erosion from a justice perspective. Although coastal erosion does not fit the typical EJ paradigm, the use of this analytical approach in the future at appropriate temporal and spatial intervals is recommended.